Publications

Graphs of order n with fault-tolerant metric dimension n have recently been character-ized.This paper points out an error in the proof of this characterization. We show that the complete multipartite graphs also have the fault-tolerant metric dimension n, which provides an infinite family of counterexamples to the characterization. Furthermore, we find exact values of the metric, edge metric, mixed-metric dimensions, the domination number, locating-dominating number, and metric-locating-dominating number for the complete multipartite graphs. These results generalize various results in the literature from complete bipartite to complete multipartite graphs.

We study the evolution of some simple cosmological black holes in the framework of the generalized Lemaitre-Tolman-Bondi (LTB) model developed by Lasky and Lun, which includes the effects of nonzero pressure. A small Gaussian overdensity is introduced into the LTB solutions, and an equation of state is assumed in order to fix the relation between the pressure and the density. Numerical solutions are calculated, which simulate the dynamical effects of the pressure field on the formation of a black hole as the end state of the collapse. The influence of the pressure effects on the behavior of the solutions is measured by comparing the development of the generalized LTB model with that of the corresponding pressure-free LTB model. Finally, we plot the location of the apparent horizon on each shell and examine the differences in the locations between the cases with and without pressure. The evidence indicates that the apparent horizon forms later in the presence of pressure.

The aim of this research was the analysis of the effect of a dam height raise on the water quality of a tropical reservoir used for drinking water purposes in South East Asia. Analyses of iron, manganese, pH and ammonia were performed over a 5-year period from daily water sampling at the reservoir. In addition, high-frequency monitoring data of nitrate, ammonium, pH and blue-green algae were obtained using a monitoring probe. The results showed that due to the raising of the reservoir water level, previously oxic sediments became submerged, triggering an increase in iron and manganese in particular due to the establishment of reducing conditions. Manganese concentrations with values up to 4 mg L−1 are now exceeding guideline values. The analysis strongly indicated that both iron and manganese have a seasonal component with higher iron and manganese concentrations during the wet season. Over a three-year period afterwards, concentrations did not go back to pre-raise levels. The change in water quality was accompanied by a change in pH from previous values of around 5 to pH values of around 6.5. Geochemical simulations confirmed the theory that the increasing concentrations of iron and manganese are due to the dissolution of MnO2 and ferric oxyhydroxides oxidising organic matter in the process. This study showed that changes in reservoir water levels with the establishment of reducing conditions can have long-term effects on the water quality of a reservoir.

An irregularity index I R(Γ) of a graph Γ is a nonnegative numeric quantity (i.e., I R(Γ) ≥ 0) such that I R(Γ) = 0 iff Γ is a regular graph. In this paper, we show that I RC closely correlates with the normal boiling point Tbp and the standard heat of formation ∆Hof of lower benzenoid hydrocarbons. The correlation models that fit the data efficiently for both Tbp and ∆Hof are linear. We develop further mathematical properties of I RC by calculating its exact expressions for the recently introduced transformation graphs as well as certain derived graphs, such as the total graph, semi-total point graph, subdivision graph, semi-total line graph, double, strong double, and extended double cover graphs. Some open problems are proposed for further research on the I RC index of graphs.

Purpose: Information sharing is one of essential collaboration methods for building effective system-level disruption responses and communication for supply chain resilience. However, supply chain members are often reluctant to share the members’ business information for fear of losing competitiveness. To facilitate the cooperation among these members, the supply chain members’ should be made aware of the value of information. As a result, the purpose of this paper is to quantify the benefit of information sharing and evaluate its magnitude under various factors. Design/methodology/approach: In this paper, information sharing is measured in a two-stage supply chain containing a manufacturer and a retailer. A demand function is constructed as a linear combination of a first-order autoregressive [AR(1)] process, the retail and reference prices. The values of information sharing are quantified for four scenarios: (1) no information sharing, (2) full information sharing, (3) limited information sharing and (4) partial information sharing. Based on the four scenarios, the conditions for valuable information sharing are determined. In addition, the impact of several demand parameters on the usefulness of information sharing is analyzed. Findings: When the demand function is a pure AR(1) process (i.e. there is no impact from the retail and reference prices), information sharing is always valuable regardless of the autoregressive coefficient. Under the influence of the retail price and consumer behavior via the reference price, information sharing is not always beneficial. The boundaries for useful information sharing are analytically constructed. In addition to full information sharing, this study also quantifies the value of information under a partial sharing scheme. The results indicate that the information is more valuable as long as the information is inducible. Originality/value: This study highlights several specific conditions for a beneficial information sharing agreement in consideration of consumer behaviors. These conditions enable supply chain members to design a sustainable partnership.

Methods for the treatment of item non-response in attitudinal scales and in large-scale assessments under the pairwise likelihood (PL) estimation framework and under a missing at random (MAR) mechanism are proposed. Under a full information likelihood estimation framework and MAR, ignorability of the missing data mechanism does not lead to biased estimates. However, this is not the case for pseudo-likelihood approaches such as the PL. We develop and study the performance of three strategies for incorporating missing values into confirmatory factor analysis under the PL framework, the complete-pairs (CP), the available-cases (AC) and the doubly robust (DR) approaches. The CP and AC require only a model for the observed data and standard errors are easy to compute. Doubly-robust versions of the PL estimation require a predictive model for the missing responses given the observed ones and are computationally more demanding than the AC and CP. A simulation study is used to compare the proposed methods. The proposed methods are employed to analyze the UK data on numeracy and literacy collected as part of the OECD Survey of Adult Skills.

In this article, the efficiency of all the well-known valency-based molecular descriptors has been measured using certain comparative testing. Importantly, we use a computational technique for hexagonal systems to generate regression models to determine the correlation of valency-based molecular descriptors with the π-electronic energies for polycyclic aromatic hydrocarbons. The study implicates some favorable outcomes as the sum-connectivity index and certain Randić index have correlation coefficient of 0.9999. To ensure the applicability of our proposed study, we compute analytically explicit expressions for efficient valency-based molecular descriptors for certain infinite families of carbon nanotubes and carbon nanocones. Our results assist in correlating the π-electronic energies of underlying chemical structures of these nanotubes and nanocones.

Alicyclic hydrocarbons and their derivatives have been studied extensively by researchers in recent years. Actually, they are a subclass of the toroidal networks. The kind of networks can be characterized as the toroidal networks obtained from associating lots of identical basic sub-networks into a cycle. In this paper, we study topological indices correlated with the toroidal networks, such as resistance distance, the Kirchhoff index, and the degree-Kirchhoff index by creating n-separations which can compute resistance distance simply. Furthermore, we also derive and analyze lots of topological indices based on degree of the toroidal networks. For instance, the Zagreb index, the general Randić index, the Forgotten index, and so on. These characteristic quantities can be utilized to evaluate the properties of alicyclic hydrocarbons as well as can be extensively applied to many fields, like mathematics, physics, chemistry, biology, or other fields.

Background: In estimating the global burden of cancer, adolescents and young adults with cancer are often overlooked, despite being a distinct subgroup with unique epidemiology, clinical care needs, and societal impact. Comprehensive estimates of the global cancer burden in adolescents and young adults (aged 15–39 years) are lacking. To address this gap, we analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, with a focus on the outcome of disability-adjusted life-years (DALYs), to inform global cancer control measures in adolescents and young adults. Methods: Using the GBD 2019 methodology, international mortality data were collected from vital registration systems, verbal autopsies, and population-based cancer registry inputs modelled with mortality-to-incidence ratios (MIRs). Incidence was computed with mortality estimates and corresponding MIRs. Prevalence estimates were calculated using modelled survival and multiplied by disability weights to obtain years lived with disability (YLDs). Years of life lost (YLLs) were calculated as age-specific cancer deaths multiplied by the standard life expectancy at the age of death. The main outcome was DALYs (the sum of YLLs and YLDs). Estimates were presented globally and by Socio-demographic Index (SDI) quintiles (countries ranked and divided into five equal SDI groups), and all estimates were presented with corresponding 95% uncertainty intervals (UIs). For this analysis, we used the age range of 15–39 years to define adolescents and young adults. Findings: There were 1·19 million (95% UI 1·11–1·28) incident cancer cases and 396 000 (370 000–425 000) deaths due to cancer among people aged 15–39 years worldwide in 2019. The highest age-standardised incidence rates occurred in high SDI (59·6 [54·5–65·7] per 100 000 person-years) and high-middle SDI countries (53·2 [48·8–57·9] per 100 000 person-years), while the highest age-standardised mortality rates were in low-middle SDI (14·2 [12·9–15·6] per 100 000 person-years) and middle SDI (13·6 [12·6–14·8] per 100 000 person-years) countries. In 2019, adolescent and young adult cancers contributed 23·5 million (21·9–25·2) DALYs to the global burden of disease, of which 2·7% (1·9–3·6) came from YLDs and 97·3% (96·4–98·1) from YLLs. Cancer was the fourth leading cause of death and tenth leading cause of DALYs in adolescents and young adults globally. Interpretation: Adolescent and young adult cancers contributed substantially to the overall adolescent and young adult disease burden globally in 2019. These results provide new insights into the distribution and magnitude of the adolescent and young adult cancer burden around the world. With notable differences observed across SDI settings, these estimates can inform global and country-level cancer control efforts. Funding: Bill & Melinda Gates Foundation, American Lebanese Syrian Associated Charities, St Baldrick’s Foundation, and the National Cancer Institute.

Since the first case of novel coronavirus (COVID-19) which was detected on March 9, 2020 in Brunei Darussalam, higher learning institutions and schools have shifted to online based learning instead of face to face (F2F) for teaching and learning (TL). On March 12, 2020, Universiti Brunei Darussalam (UBD) has announced that all TL will be using available online and electronic learning platforms such as CANVAS, Skype, Zoom meetings, Microsoft Team (MS Team) and Teleconferencing. This study discusses the implementation of CANVAS as one of learning management system (LMS) to teach first year discrete mathematics to assess the students’ performance by giving them online assessments via assignments or quizzes, using built-in features on CANVAS. Based on the feedback from students, it is found that the use of CANVAS has significantly made students’ learning more systematic and also improved the understanding of the students on the mathematics course.

As a crucial tool for exploring and characterizing the structure properties of the molecular graphs, spectrum analysis and computation are flourishing in recent year. Let Ln be obtained from the transformation of the graph (Formula presented.) which obtained by attaching crossed four-membered rings to the terminal of crossed phenylenes. In this article, we first determine the (normalized) Laplacian spectra of Ln, then obtain its (multiplicative degree) Kirchhoff index and complexity corresponding to Ln. Finally, by comparing with its Wiener index and Gutman index, we are pleased to find that the (multiplicative degree) Kirchhoff index of Ln is nearly one quarter of its (Gutman) Wiener index.

Background: This study provides population-based study of cancer incidence, mortality and survival rates for women diagnosed with epithelial ovarian cancer (EOC), and evaluate the prognostic factors of EOC patients survival in Brunei Darussalam. Methods: This is a retrospective study of patients diagnosed with EOC between 1st January 2007 and 31st December 2017 in Brunei Darussalam. Crude, age-specific, age-standardized incidence and mortality rates per 100,000 women were calculated. Kaplan-Meier method was used to determine the overall 5-years survival rate. Log-rank test was used to examine the differences in survival between groups. The multivariable Cox Proportional Hazard regression models were used to estimate the hazard ratio for overall survival and to identify the prognostic factors. Results: A total of 207 patients were included in the study. The crude incidence and mortality rates were 9.7 and 3.6 per 100,000 respectively while the age-standardized incidence and mortality rates were 11.3 (95% CI: 9.7,12.9) and 4.5 (95% CI: 3.4,5.6) per 100,000 respectively in the period 2007-2017. The overall mean age at diagnosis was 48.4 (standard deviation=15.3) years. The overall survival rates at 1, 3, and 5 years for EOC patients were 79.7%, 69.7%, and 61.4% respectively. Age at diagnosis, cancer stage, and histology were significant prognostic factors for patients’ survival. Older age at diagnosis (≥70 years vs <40 years), regional or advanced stage (vs localized stage) and having undifferentiated or other epithelial ovarian (vs serous carcinoma) were associated with having higher hazard of death. Conclusion: Early detection of disease should be emphasized through public education and raising awareness to improve survival rates of patients with EOC.

The objective of this study is to examine the sociodemographic factors contributing to the readmission to a drug rehabilitation center among drug addicts in Brunei Darussalam. This retrospective study used de-identified data obtained from the Al-Islah Rehabilitation Center for the period 1 January 2010 to 31 December 2017. Univariate and multiple logistic regression analyses with a stepwise variable selection method were used to estimate and determine significant factors associated with readmission to the center. A total of 92 out of 705 subjects (13%) were readmitted to the rehabilitation center within the study period, with ages ranging from 20 to 59 years (M = 36.1, SD = 8.6 years). Multiple logistic regression found that subjects who were in the age group of 40 to 49 (OR = 2.24, 95% CI [1.16, 4.37]) resided in the Belait district (OR = 1.94, 95% CI [1.00, 3.63]), divorced or widowed (OR = 2.14, 95% CI [1.19, 3.82]), had committed other criminal offenses (OR = 1.91, 95% CI [1.16, 3.11]), and voluntarily admitted (OR = 2.33, 95% CI [1.34, 4.01]), were found to be significantly more likely to get readmitted to the rehabilitation center. This study provides evidence of sociodemographic factors in relation to readmission to the rehabilitation center in Brunei Darussalam.

The aim of this research study is to determine suitable creative and innovative teaching methods for secondary school level mathematics during Covid-19 pandemic, based on the findings of interview sessions conducted at nine randomly chosen secondary schools in Brunei Darussalam. The interview sessions were conducted to at least one Mathematics teacher from each school to find out various teaching methods and IT tools that the teachers used in their teachings. In addition, questionnaires on teaching methodology were also distributed to the participants. The participants were selected based on their teaching experiences of more than 10 years and they must have accurate knowledge of the subject, ability to bring the subject matter to the level of student understanding, self-confidence, ability of expression, knowledge of evolution techniques, ability in questioning and respect for students’ opinion (Vijayabarathi et al. in International Journal of Computing Algorithm 2:229–304, 2013). Based on the interview sessions and questionnaires, suitable creative & innovative online teaching methods to help improve the understanding of students in secondary school level mathematics during this Covid-19 pandemic will be determined.

IMPORTANCE The Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019) provided systematic estimates of incidence, morbidity, and mortality to inform local and international efforts toward reducing cancer burden. OBJECTIVE To estimate cancer burden and trends globally for 204 countries and territories and by Sociodemographic Index (SDI) quintiles from 2010 to 2019. EVIDENCE REVIEW The GBD 2019 estimation methods were used to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) in 2019 and over the past decade. Estimates are also provided by quintiles of the SDI, a composite measure of educational attainment, income per capita, and total fertility rate for those younger than 25 years. Estimates include 95% uncertainty intervals (UIs). FINDINGS In 2019, there were an estimated 23.6 million (95% UI, 22.2-24.9 million) new cancer cases (17.2 million when excluding nonmelanoma skin cancer) and 10.0 million (95% UI, 9.36-10.6 million) cancer deaths globally, with an estimated 250 million (235-264 million) DALYs due to cancer. Since 2010, these represented a 26.3% (95% UI, 20.3%-32.3%) increase in new cases, a 20.9% (95% UI, 14.2%-27.6%) increase in deaths, and a 16.0% (95% UI, 9.3%-22.8%) increase in DALYs. Among 22 groups of diseases and injuries in the GBD 2019 study, cancer was second only to cardiovascular diseases for the number of deaths, years of life lost, and DALYs globally in 2019. Cancer burden differed across SDI quintiles. The proportion of years lived with disability that contributed to DALYs increased with SDI, ranging from 1.4% (1.1%-1.8%) in the low SDI quintile to 5.7% (4.2%-7.1%) in the high SDI quintile. While the high SDI quintile had the highest number of new cases in 2019, the middle SDI quintile had the highest number of cancer deaths and DALYs. From 2010 to 2019, the largest percentage increase in the numbers of cases and deaths occurred in the low and low-middle SDI quintiles. CONCLUSIONS AND RELEVANCE The results of this systematic analysis suggest that the global burden of cancer is substantial and growing, with burden differing by SDI. These results provide comprehensive and comparable estimates that can potentially inform efforts toward equitable cancer control around the world.

Institutional mathematics education has long been traditional in its ways of being teacher-centric, a tradition which perhaps dates back to the Ancient Greece. Much like the society in those days, where there was a wary public feeling about the rigidness of the mathematical instruction in Pythagoras’ school, mathematics educators find themselves in a similar position in the common era of 2020. Unlike the Ancient Greece however, the battle is for the sustained delivery of a comprehensive mathematics education in the midst of the Covid-19 pandemic. It would be fair to say that mathematics departments across all levels of the education sector have been affected drastically; more so on instructors who favour the traditional “chalk and talk” method of instruction. In this article, we share several lessons learned in the delivery of mathematical instruction at undergraduate university level during the Covid-19 pandemic, drawing on our experience at Universiti Brunei Darussalam. These include specific methods for implementing online learning effectively, the pros and cons of such methods, and how we can use computer based tools to make learning more conducive. We highly think that these implementations are beneficial to be adapted by mathematics departments anywhere as a means of adapting to the new realities post Covid-19.

Solar energy is one of the most environmentally friendly renewable energy. There are several solar energy systems that have been studied and one of the studies made is to combine solar energy systems, which aims to optimize the energy efficiency. Photovoltaic/thermal solar collector; also known as hybrid solar collector, combines photovoltaic solar cells which convert sunlight into electricity with a solar thermal collector which transfer the wasted heat from the photovoltaic module to a heat transfer fluid. The hybrid technology has shown higher overall energy efficiency than solar photovoltaic or solar thermal alone. The target of this book is to review and present the use of important key properties of mathematical models that describe the PV/T solar collector system. A review on the current development of new mathematical models to achieve higher energy efficiency as well as challenges and limitations of photovoltaic/thermal solar collector system will also be presented.

Background: Colorectal cancer (CRC) is a major cause of cancer-related mortality worldwide. It is the second leading cause of cancer death in men and women in Brunei Darussalam in 2017, posing a major burden on society. Methods: This retrospective cohort study (n = 1035 patients diagnosed with CRC in Brunei Darussalam from 1st January 2002 until 31st December 2017) aims to compare the overall survival rates of CRC patients (2002–2017), to compare survival rates between two study periods (2002–2009 and 2010–2017) and to identify prognostic factors of CRC. Kaplan-Meier estimator and log-rank tests were performed to analyse the overall survival rates of CRC patients. Multiple Cox regression was performed to determine the prognostic factors of CRC with adjusted hazard ratios (Adj. HRs) reported. Results: The 1-, 3- and 5-year survival rates of CRC patients are 78.6, 62.5, and 56.0% respectively from 2002 to 2017. The 1-, 3-, and 5-year survival rates of CRC patients for 2002–2009 are 82.2, 69.6, and 64.7%; 77.0, 59.1, and 51.3% for 2010–2017 respectively. A significant difference in CRC patients’ survival rate was observed between the two study periods, age groups, ethnic groups, cancer stages, and sites of cancer (p < 0.05). The Adjusted Hazard Ratios (Adj. HRs) were significantly higher in the 2010–17 period (Adj. HR = 1.78, p < 0.001), older age group (≥ 60 years) (Adj. HR = 1.93, p = 0.005), distant cancer (Adj. HR = 4.69, p < 0.010), tumor at transverse colon and splenic flexure of colon (Adj. HR = 2.44, p = 0.009), and lower in the Chinese(Adj. HR = 0.63, p = 0.003). Conclusion: This study highlights the lower survival rates of CRC patients in 2010–2017, Malays, older patients, distant cancer, and tumors located at the latter half of the proximal colon (transverse colon), and predominantly LCRC (splenic flexure, descending colon, sigmoid colon, overlapping lesion colon and colon (NOS), as well as the rectosigmoid junction and rectum (NOS)). Age, ethnicity, cancer stage, and tumor location are significant prognostic factors for CRC. These findings underscore the importance of public health policies and programmes to enhance awareness on CRC from screening to developing strategies for early detection and management, to reduce CRC-associated mortality.

In this paper, we propose a family of nested weighted n-polygon networks, which is a kind of promotion of infinite fractal dimension networks. We study the coherence of the networks with recursive features that contain the initial states dominated by a weighted parameter. The network coherence is a consensus problem with additive noises, and it is known that coherence is defined by the eigenvalues of the Laplacian matrix. According to the structure of recursive nested model, we get the recursive expressions of Laplacian eigenvalues and further derive the exact results of first- A nd second-order coherence. Finally, we investigate the influential impacts on the coherence for different large parameters and discuss the relationship between Laplacian energy and network coherence. Furthermore, we obtain the expressions of Kirchhoff index, mean first-passage time and average path length of the networks.

We present a construction of C1 piecewise quadratic hierarchical bases of Lagrange type on arbitrary polygonal domains Ω⊂R2. Properly normalized, these bases are Riesz bases for Sobolev spaces Hs(Ω), with [Formula presented]. The method is applicable to arbitrary initial triangulations of polygonal domains, and does not require a checkerboard quadrangulation needed for earlier C1 cubic hierarchical Lagrange bases. Homogeneous boundary conditions can be taken into account in a natural way, and lead to Riesz bases for Sobolev spaces H0s(Ω), s∈(1,5/2)∖3/2, and H003/2(Ω).

The efficiency of convolutional neural networks (CNNs) facilitates 3D face reconstruction, which takes a single image as an input and demonstrates significant performance in generating a detailed face geometry. The dependence of the extensive scale of labelled data works as a key to making CNN-based techniques significantly successful. However, no such datasets are publicly available that provide an across-the-board quantity of face images with correspondingly explained 3D face geometry. State-of-the-art learning-based 3D face reconstruction methods synthesize the training data by using a coarse morphable model of a face having non-photo-realistic synthesized face images. In this article, by using a learning-based inverse face rendering, we propose a novel data-generation technique by rendering a large number of face images that are photo-realistic and possess distinct properties. Based on the real-time fine-scale textured 3D face reconstruction comprising decently constructed datasets, we can train two cascaded CNNs in a coarse-to-fine manner. The networks are trained for actual detailed 3D face reconstruction from a single image. Experimental results demonstrate that the reconstruction of 3D face shapes with geometry details from only one input image can efficiently be performed by our method. Furthermore, the results demonstrate the efficiency of our technique to pose, expression and lighting dynamics.

When the drivers approaching signalized intersections (onset of yellow signal), the drivers would enter into a zone, where they will be in uncertain mode assessing their capabilities to stop or cross the intersection. Therefore, any improper decision might lead to a right-angle or back-end crash. To avoid a right-angle collision, drivers apply the harsh brakes to stop just before the signalized intersection. But this may lead to a back-end crash when the following driver encounters the former’s sudden stopping decision. This situation gets multifaceted when the traffic is heterogeneous, containing various types of vehicles. In order to reduce this issue, this study’s primary objective is to identify the driving behaviour at signalized intersections based on the driving features (parameters). The secondary objective is to classify the outcome of driving behaviour (safe stopping and unsafe stopping) at the signalized intersection using a support vector machine (SVM) technique. Turning moments are used to identify the zones and label them accordingly for further classification. The classification of 50 instances is identified for training and testing using a 70%–30% rule resulted in an accuracy of 85% and 86%, respectively. Classification performance is further verified by random sampling using five cross-validation and 30 iterations, which gave an accuracy of 97% and 100% for training and testing. These results demonstrate that the proposed approach can help develop a pre-warning system to alert the drivers approaching signalized intersections, thus reducing back-end crash and accidents.

Road accidents occur at traffic signals, even though traffic patrolling and awareness are increased. Accidents occurred at traffic signal junctions are a significant proportion in the overall reported road accidents. Usually, when the drivers approaching the traffic signals, at the onset of yellow, the drivers would enter into a dilemma zone, where they will be in confusion mode assessing their capabilities to cross the intersection or stop. So, any improper decision might lead to a collision. To avoid right-angle crash, drivers apply harsh brake to stop before the traffic signals. But this may lead to back-end crash, when the following driver encounters the former’s sudden stopping decision. This situation gets multifaceted when the traffic is heterogeneous containing various types of vehicles. So, the main objective of this study is to assess the performance using machine learning techniques. In this study, support vector machine (SVM) and K-nearest neighbors’ (KNN) techniques are implemented to validate the classification of the driving behaviour in terms of safe stopping/unsafe stopping at the signalized junctions at the onset of the yellow signal.

In this paper, we investigate the prediction potential of commonly occurring eigenvalues-based descriptors which are related to chemical matrices corresponding to valency of vertices. The normal boiling point has been chosen to be representative of van-der-Waals and intermolecular type interactions, whereas, the standard enthalpy/heat of formation is selected to represent thermal properties, for our comparative testing. First, we propose a unified computational method to calculate commonly occurring eigenvalues-based valency descriptors. Experimental results show that our proposed method possesses less algorithmic and computational complexities and is more computationally diverse. The proposed method is used to calculate commonly occurring eigenvalues-based descriptors to investigate their correlation ability with the experimental data for the two chosen physicochemical properties. The Randić energy shows the best correlation among all the commonly occurring eigenvalues-based descriptors. Experimental results show some unexpected outcomes as the correlation ability of the well-known adjacency energy and the Laplacian & signless Laplacian Estrada indices is weak. Unlike their reputation among researchers, the harmonic energy and Estrada index outperformed all the well-known eigenvalues-based descriptors. The results warrant further usage of the harmonic energy and Estrada index in the structure-activity and structure-property models. Our study contributes towards putting forward the best spectrum-based topological descriptors while mentioning the ones which do not deserve further attention of researchers. Applications to certain families of titania nanotubes are presented.

In this paper, we investigate the predictive potential of commonly occurring spectrum-based distance descriptors which are based on eigenvalues of distance-related chemical matrices. For our comparative testing, the normal boiling point has been chosen to be representative of van-der-Waals and intermolecular type interactions, whereas, the standard enthalpy/heat of formation is selected to represent thermal properties. We introduce three new chemical matrices and results show that the spectral descriptors based on these new matrices outperform the existing well-studied spectral descriptors. A computational method is used to calculate commonly occurring spectrum-based distance descriptors to investigate their correlation ability with the experimental data for the two chosen physicochemical properties for lower polycyclic aromatic hydrocarbons. By providing the list of the five best spectrum-based distance descriptors, our study contributes towards putting forward the best spectrum-based topological descriptors while mentioning the ones which do not deserve further attention of researchers. Applications of our results to certain families of carbon polyhex nanotubes and one-hexagonal nanocones have been presented. The results can potentially be used to determine certain physicochemical of these nanotubes and nanocones theoretically with higher accuracy and negligible error.

Various global health initiatives are currently advocating the elimination of schistosomiasis within the next decade. Schistosomiasis is a highly debilitating tropical infectious disease with severe burden of morbidity and thus operational research accurately evaluating diagnostics that quantify the epidemic status for guiding effective strategies is essential. Latent class models (LCMs) have been generally considered in epidemiology and in particular in recent schistosomiasis diagnostic studies as a flexible tool for evaluating diagnostics because assessing the true infection status (via a gold standard) is not possible. However, within the biostatistics literature, classical LCM have already been criticised for real-life prob-lems under violation of the conditional independence (CI) assumption and when applied to a small number of diagnostics (i.e. most often 3-5 diagnostic tests). Solutions of relaxing the CI assumption and accounting for zero-inflation, as well as collecting partial gold standard information, have been proposed, offering the potential for more robust model estimates. In the current article, we examined such approaches in the context of schistosomiasis via analysis of two real datasets and extensive simulation studies. Our main conclusions highlighted poor model fit in low prevalence settings and the necessity of collecting partial gold standard information in such settings in order to improve the accuracy and reduce bias of sensitivity and specificity estimates.

The normalized Laplacian plays an indispensable role in exploring the structural properties of irregular graphs. Let Ln8,4 represent a linear octagonal-quadrilateral network. Then, by identifying the opposite lateral edges of Ln8,4, we get the corresponding Möbius graph MQn8,4. In this paper, starting from the decomposition theorem of polynomials, we infer that the normalized Laplacian spectrum of MQn8,4 can be determined by the eigenvalues of two symmetric quasi-triangular matrices ℒA and ℒS of order 4n. Next, owing to the relationship between the two matrix roots and the coefficients mentioned above, we derive the explicit expressions of the degree-Kirchhoff indices and the complexity of MQn8,4.

It is one of the core problems in the study of chemical graph theory to study the topological index of molecular graph and the internal relationship between its structural properties and some invariants. In recent years, topological index has been gradually applied to the models of QSAR and QSPR. In this work, using the definition of the ABC index, AZI index, GA index, the multiplicative version of ordinary first Zagreb index, the second multiplicative Zagreb index, and Zagreb index, we calculate the degree-based topological indices of some networks. Then, the above indices’ formulas are obtained.

This paper discusses scattered data interpolation using cubic trigonometric Bézier triangular patches with C1 continuity everywhere. We derive the C1 condition on each adjacent triangle. On each triangular patch, we employ convex combination method between three local schemes. The final interpolant with the rational corrected scheme is suitable for regular and irregular scattered data sets. We tested the proposed scheme with 36,65, and 100 data points for some well-known test functions. The scheme is also applied to interpolate the data for the electric potential. We compared the performance between our proposed method and existing scattered data interpolation schemes such as Powell–Sabin (PS) and Clough–Tocher (CT) by measuring the maximum error, root mean square error (RMSE) and coefficient of determination (R2). From the results obtained, our proposed method is competent with cubic Bézier, cubic Ball, PS and CT triangles splitting schemes to interpolate scattered data surface. This is very significant since PS and CT requires that each triangle be splitting into several micro triangles.

Scattered data interpolation refers to the problems of constructing a smooth surface through non-uniform and uniform set of data points. Besides that, this subject is very vital in various fields such as medical, sciences, engineering and others. There are many researchers who have done their studies in interpolation methods with different approaches and has been reported in many papers. There are two different approaches to the interpolation of scattered data where it can be clarified as global and local methods. The global method is influenced by all data while the local method is not influenced all the data where it effected at nearby points. This chapter discusses the rainfall distributions in several areas in Malaysia by using the rational quartic triangular patches.

In this paper, we determine the efficiency of all commonly occurring eigenvalues-based topological descriptors for measuring the π-electronic energy of lower polycyclic aromatic hydrocarbons. Results show some favorable outcomes as the spectrum-based descriptors such as the adjacency energy, the arithmetic-geometric energy, the geometric-arithmetic energy, and the adjacency Estrada index have the best correlation coefficients greater than 0.999 among all others. However, certain well-known spectrum-based descriptors such as the adjacency, Laplacian & signless Laplacian spectral radii, and the first & second Zagreb Estrada indices show considerably weak performance. Poor performances of the first & second Zagreb Estrada indices are, in general, unexpected. The arithmetic-geometric and geometric-arithmetic energies with correlation coefficients 0.99997 and 0.99996, respectively, are warranted for further use in quantitative structure activity/property relationship (QSAR/QSPR) models. Based on our comparative testing, we generate a priority list of the top five spectrum-based topological descriptors for measuring the π-electronic energy. These best preforming descriptors are then studied for certain infinite families of boron triangular and boron α-nanotubes. The results help in determining the π-electronic energy of these families of boron nanotubes. Combining our results with similar results studied in literature, we conclude that among all the classes of topological descriptors, spectrum-based descriptors are the best in correlating the π-electronic energy.

Zero forcing is a process of coloring in a graph in time steps known as propagation time. These graph-theoretic parameters have diverse applications in computer science, electrical engineering and mathematics itself. The problem of evaluating these parameters for a network is known to be NP-hard. Therefore, it is interesting to study these parameters for special families of networks. Perila et al. (2017) studied properties of these parameters for some basic oriented graph families such as cycles, stars and caterpillar networks. In this paper, we extend their study to more non-trivial structures such as oriented wheel graphs, fan graphs, friendship graphs, helm graphs and generalized comb graphs. We also investigate the change in propagation time when the orientation of one edge is flipped.

Let Hn be the molecular graph of a linear polyacene chain. In this paper, we introduce a kind of linear polyacene cylinder graph (Formula presented.) which is the strong product of two automorphism polyacene graphs Hn and (Formula presented.) Next, we obtain that the Laplacian spectrum of (Formula presented.) consists of the eigenvalues of symmetric matrices LA and LS of order (Formula presented.) according to the decomposition theorem of Laplacian characteristic polynomial. Furthermore, by applying the relationship between the roots and coefficients of the characteristic polynomials of the above two matrices, we study the Kirchhoff index and the number of spanning trees, and derive their explicit expressions in terms of n for the graph (Formula presented.).

A convex polytope is the convex hull of a finite set of points in the Euclidean space ℝn. By preserving the adjacency-incidence relation between vertices of a polytope, its structural graph is constructed. A graph is called Hamilton-connected if there exists at least one Hamiltonian path between any of its two vertices. The detour index is defined to be the sum of the lengths of longest distances, i.e., detours between vertices in a graph. Hamiltonian and Hamilton-connected graphs have diverse applications in computer science and electrical engineering, whereas the detour index has important applications in chemistry. Checking whether a graph is Hamilton-connected and computing the detour index of an arbitrary graph are both NP-complete problems. In this paper, we study these problems simultaneously for certain families of convex polytopes. We construct two infinite families of Hamilton-connected convex polytopes. Hamilton-connectivity is shown by constructing Hamiltonian paths between any pair of vertices. We then use the Hamilton-connectivity to compute the detour index of these families. A family of non-Hamilton-connected convex polytopes has also been constructed to show that not all convex polytope families are Hamilton-connected.

In this paper, we have used two different proof techniques to show the Hamilton-connectedness of graphs. By using the vertex connectivity and Hamiltoniancity of graphs, we construct an infinite family of Hamilton-connected convex polytope line graphs whose underlying family of convex polytopes is not Hamilton-connected. By definition, we constructed two more infinite families of Hamilton-connected convex polytopes. As a by-product of our results, we compute exact values of the detour index of the families of Hamilton-connected convex polytopes. Finally, we classify the Platonic solids according to their Hamilton-connectedness and Hamilton-laceability properties.

A connected graph is called Hamilton-connected if there exists a Hamiltonian path between any pair of its vertices. Determining whether a graph is Hamilton-connected is an NP-complete problem. Hamiltonian and Hamilton-connected graphs have diverse applications in computer science and electrical engineering. The detour index of a graph is defined to be the sum of lengths of detours between all the unordered pairs of vertices. The detour index has diverse applications in chemistry. Computing the detour index for a graph is also an NP-complete problem. In this paper, we study the Hamilton-connectivity of convex polytopes. We construct three infinite families of convex polytopes and show that they are Hamilton-connected. An infinite family of non-Hamilton-connected convex polytopes is also constructed, which, in turn, shows that not all convex polytopes are Hamilton-connected. By using Hamilton connectivity of these families of graphs, we compute exact analytical formulas of their detour index.

Background Prevention, control, and treatment of respiratory tract cancers are important steps towards achieving target 3.4 of the UN Sustainable Development Goals (SDGs)—a one-third reduction in premature mortality due to non-communicable diseases by 2030. We aimed to provide global, regional, and national estimates of the burden of tracheal, bronchus, and lung cancer and larynx cancer and their attributable risks from 1990 to 2019. Methods Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 methodology, we evaluated the incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life-years (DALYs) of respiratory tract cancers (ie, tracheal, bronchus, and lung cancer and larynx cancer). Deaths from tracheal, bronchus, and lung cancer and larynx cancer attributable to each risk factor were estimated on the basis of risk exposure, relative risks, and the theoretical minimum risk exposure level input from 204 countries and territories, stratified by sex and Socio-demographic Index (SDI). Trends were estimated from 1990 to 2019, with an emphasis on the 2010-19 period. Findings Globally, there were 2·26 million (95% uncertainty interval 2·07 to 2·45) new cases of tracheal, bronchus, and lung cancer, and 2·04 million (1·88 to 2·19) deaths and 45·9 million (42·3 to 49·3) DALYs due to tracheal, bronchus, and lung cancer in 2019. There were 209 000 (194 000 to 225 000) new cases of larynx cancer, and 123 000 (115 000 to 133 000) deaths and 3·26 million (3·03 to 3·51) DALYs due to larynx cancer globally in 2019. From 2010 to 2019, the number of new tracheal, bronchus, and lung cancer cases increased by 23·3% (12·9 to 33·6) globally and the number of larynx cancer cases increased by 24·7% (16·0 to 34·1) globally. Global age-standardised incidence rates of tracheal, bronchus, and lung cancer decreased by 7·4% (−16·8 to 1·6) and age-standardised incidence rates of larynx cancer decreased by 3 ·0% (−10·5 to 5·0) in males over the past decade; however, during the same period, age-standardised incidence rates in females increased by 0·9% (−8·2 to 10·2) for tracheal, bronchus, and lung cancer and decreased by 0·5% (−8·4 to 8·1) for larynx cancer. Furthermore, although age-standardised incidence and death rates declined in both sexes combined from 2010 to 2019 at the global level for tracheal, bronchus, lung and larynx cancers, some locations had rising rates, particularly those on the lower end of the SDI range. Smoking contributed to an estimated 64·2% (61·9–66·4) of all deaths from tracheal, bronchus, and lung cancer and 63·4% (56·3–69·3) of all deaths from larynx cancer in 2019. For males and for both sexes combined, smoking was the leading specific risk factor for age-standardised deaths from tracheal, bronchus, and lung cancer per 100 000 in all SDI quintiles and GBD regions in 2019. However, among females, household air pollution from solid fuels was the leading specific risk factor in the low SDI quintile and in three GBD regions (central, eastern, and western sub-Saharan Africa) in 2019. Interpretation The numbers of incident cases and deaths from tracheal, bronchus, and lung cancer and larynx cancer increased globally during the past decade. Even more concerning, age-standardised incidence and death rates due to tracheal, bronchus, lung cancer and larynx cancer increased in some populations—namely, in the lower SDI quintiles and among females. Preventive measures such as smoking control interventions, air quality management programmes focused on major air pollution sources, and widespread access to clean energy should be prioritised in these settings.

The Water Evaluation and Planning (WEAP) model was invented by the Stockholm Environment Institute (SEI) to assist planning and management issues related with the development of water resources. The WEAP model can be applied to agricultural site and other sectors; and it can also tackle a large scope of problems encompassing water demand analyses, water saving, optimizing available water distribution and cost-profit analyses [1]. In this study, the WEAP model is introduced to look at the performance of the effect of different agricultural irrigation scenarios on special type of rice variety, i.e. MRQ76, planted in Wasan padi field, situated at Brunei-Muara District, Brunei Darussalam. Specifically, we apply the WEAP-MABIA model (based on soil-water balance approach) to perform evaluation of irrigation scheduling for three different rice growing seasons. We found that the WEAP model is a good model for providing the best irrigation scheduling strategy for optimum rice yield and efficient water management.

Several chemical and medical experimentation reveals a dependence of physicochemical and biological properties of a compound on its molecular structure. Molecular/topological descriptors/indices retrieve this dependence by employing mathematical/statistical tools to generate quantitative structure property/activity relationship (QSAR/QSPR) models. QSAR/QSPR models are regression models which theoretically relate a physicochemical/biological property to a molecular descriptor. By converting a compound to a chemical graph, graph-theoretic topological indices use algorithmic graph theory to generate QSAR/QSPR models. Degree-related molecular indices have been well-known for correlating better with certain physicochemical characteristics of compounds. In this paper, we conduct a comparative analysis to put forward the best degree-based index for correlating with physicochemical characteristics of polycyclic aromatic hydrocarbons. Two different computational techniques have been put forward and then used to conduct our comparative analysis. Our comparative testing generates several favorable and unexpected conclusions as the well-known indices such as the augmented Zagreb index, the atom-bond connectivity index, the geometric arithmetic index deliver relatively poor performance. Moreover, exceptional performance of the generalized variants of Randić and sum-connectivity indices is somehow unexpected as they significantly outperform the well-studied and well-researched degree-based indices. This warrants to study further the general Randić and sum-connectivity indices for QSAR/QSPR models. Applications to certain families of carbon polyhex aromatic nanotubes are reported.

The Bayesian approach to modelling differs from the frequentist approach primarily in the supplementation of additional information about the parameters to the data. If we specify a “good” prior, in the sense that the prior nudges the likelihood in the right direction, then the estimates will also be good. This is what we aim to do in the case of variable selection problems, whereby the Bayesian method reduces the selection problem to one of estimation from a true search of the variable space for the model which optimises a certain criterion. We contribute to the vastly available literature of variable selection methods by using I-priors [5]—a class of Gaussian distributions which has the distinguishing property of having covariance proportional to the Fisher information (of the model parameters). The original motivation behind the I-prior methodology was to develop a novel unifying approach to various regression models. In this work, we detail the I-prior model used, and showcase some simulation results and several real-world applications in which the I-prior performs favourably compared to other prior distributions and/or variable selection techniques in terms of model size, predictive ability, and so on.

Graph signal processing deals with signals whose domain, defined by a graph, is irregular. The total π -electron energy or simply the π -electronic energy, as calculated within the Hückel tight-binding molecular orbital approximation, is one of the important quantum-theoretical characteristic of conjugated molecules. In this paper, we propose an efficient computer-assisted computational method to determine eigenvalues-based distance descriptors for chemical compounds which are then used to learn to quantitative relationship between the activity/property and the structure (QSAR/QSPR) of compound. Comparisons with other similar methods show that our proposed method possesses less algorithmic and computational complexities and is more computationally diverse. The proposed method is used to determine predictive potential of eigenvalues-based distance descriptors for measuring the π -electronic energy of benzenoid hydrocarbons. Importantly, we propose three new chemical matrices and, unexpectedly, results show that the spectral descriptors defined based on new chemical matrices outperform all the well-known descriptors in the literature. Specifically, our proposed second atom-bond connectivity Estrada index show the best correlation coefficient of 0.9997. Applications of our computational method to certain infinite families of carbon nanotubes and carbon nanocones are presented. The obtained results can potentially be used to determine the π -electronic energy of these nanotubes and nanocones theoretically with higher accuracy and negligible error.

In this paper, we investigate the prediction power of all the well-known distance-based molecular structure descriptors in the literature for 22 lower polycyclic aromatic hydrocarbons (PAHs). The standard enthalpy/heat of formation is chosen to be the representative of thermal properties, whereas, the normal boiling point is selected to represent intermolecular and van-der-Waals type interactions. First, we present a computational technique to compute distance-based, eccentricity-based, degree-distance-based and degree based topological descriptors. The proposed method extends certain existing techniques in the literature. The proposed method is used to compute various distance-based descriptors for the 22 PAHs and then we develop the regression models with their normal boiling point and standard enthalpy of formation. Experimental results reveal some unexpected outcomes as the correlation ability of some well-known distance-based descriptors such as the Wiener and the Szeged indices is rather weak. Unlike their reputation among researchers, the second atomic-bond connectivity index and the fourth geometric-arithmetic index yield the best performance with correlation coefficients greater than 0.95. The results warrant further usage of the second atom-bond connectivity index in the structure-activity and structure-property models. Our study contributes towards slowing down the proliferation of distance-based topological descriptors.

Colorectal cancers (CRC) continues to increase worldwide and is associated with significant morbidity and mortality. CRC can be prevented through early detection using several modalities. However, like any screening program participation remains suboptimal. This study assessed the factors associated with participation in a stool based CRC screening that was carried out as part of an Integrated Health Screening Survey for civil servants. Materials and Methods: Civil servants who participated in a health survey (N=10,756, mean age 48.08 ± 5.26 years old) were studied. Demographic factors (gender, age groups, marital status, employment status, body mass index [BMI] categories, smoking status, personal and family history of cancers) were analyzed to assess for features associated with willingness to participate in this fecal immunohistochemistry test (FIT) screening for CRC. Comorbid conditions studied were cardiac disease, diabetes mellitus, dyslipidemia, hypertension and stroke. Multivariate analysis was performed to evaluate variables associated with participation in CRC screening programme. Results: Of the invited 10,756 participants, 7,360 returned a stool specimen giving a participation rate of 68.4%. Those who participated were significantly older (<40 [41.3%], 40-44 [64.6%], 45-49 [68.8%], 50-54 years [70.6%], 55-59 years [72.4%] and >60 years [77.8%], p<0.001 for trend), being of professional employment (p=0.010) and presence of comorbid conditions (p=0.003). There were no significant differences between gender, race, marital status, BMI categories, personal history of cancer, family history of cancer, and smoking status (all p values >0.05). Multivariate analyses showed that older age (45-49, 50-54, 55-59 and >60) and employment status (professional) remained significant factors associated with participation in a stool based CRC screening. Conclusions: Our study showed that older age and professional employment status were significantly associated with willingness to participate in a stool based CRC screening.

Resistance distance is a novel distance function, also a new intrinsic graph metric, which makes some extensions of ordinary distance. Let On be a linear crossed octagonal graph. Recently, Pan and Li (Int J Quantum Chem 118(24):e25787, 2018) derived the closed formulas for the Kirchhoff index, multiplicative degree-Kirchhoff index and the number of spanning trees of Hn. They pointed that it is interesting to give the explicit formulas for the Kirchhoff and multiplicative degree-Kirchhoff indices of On. Inspired by these, in this paper, two resistance distance-based graph invariants, namely, Kirchhoff and multiplicative degree-Kirchhoff indices are studied. We firstly determine formulas for the Laplacian (normalized Laplacian, resp.) spectrum of On. Further, the formulas for those two resistance distance-based graph invariants and spanning trees are given. More surprising, we find that the Kirchhoff (multiplicative degree-Kirchhoff, resp.) index is almost one quarter to Wiener (Gutman, resp.) index of a linear crossed octagonal graph.

We explore deeper and analyse in more detail Fermat’s and Hamilton’s principles. We try to address some questions: Is it possible to have S negative? Is Hamilton’s principle always valid for entire path of the system? Is there a relation between Fermat’s principle and Hamilton’s principle? We assume analogy with Hamilton’s principle, is Fermat’s principle always valid for entire path of the system? Does a least action take a least time for happening?.

This study is to solve the problem of low accuracy and slow processing speed for real-time face detection and tracking systems. A margin-based region of interest approach with fixed and dynamic margin concepts is proposed to speed up the processing time. In addition, a hybrid system is developed to boost the accuracy and overcome the deficiency of the main detection algorithm. This approach consists of two routines, i.e., main and escape routines. Three algorithms are used independently as the main routine to evaluate the effectiveness of the proposed hybrid approach. These algorithms are Haar cascade, Joint cascade, and multitask convolutional neural networks. The escape routine based on template matching algorithm is designed to evaluate the effectiveness of the proposed hybrid approach and improve detection accuracy. Two RGB video datasets with diversity and variations in face poses, video backgrounds, illuminations, video resolutions, expressions, over exposed faces, and occlusions of people within various unseen environments have been used for experiments and evaluation. The experiment results confirm that the hybrid approach is capable of detecting and tracking faces in non-frontal orientation with better accuracy and faster processing speed, i.e., four times faster than the conventional full frame scanning techniques.

Background: Colorectal cancer (CRC) is the third most common cancer in both men and women. In most Asian countries, both the incidence and mortality rates of CRC are gradually increasing. In Brunei Darussalam, CRC ranks first and second in lifetime risk among men and women respectively. This study aims to report the overall survival rates and associated factors of CRC in Brunei Darussalam. Methods: This is a retrospective study examining CRC data for the period 2007 to 2017 retrieved from a population based cancer registry in Brunei Darussalam. A total of 728 patients were included in the analysis. Kaplan Meier method was used to estimate survival rates. Univariate analysis using log-rank test was used to examine the differences in survival between groups. Multivariate analysis using Cox PH regression was used to estimate hazard of death and obtain significant predictors that influence CRC patients’ survival. Results: The median survival time for colorectal, colon and rectal cancer patients were 57.0, 85.8 and 40.0 months respectively. The overall 1-, 3- and 5- year survival rates for CRC patients were 78.0%, 57.7% and 49.6% respectively. In univariate analysis, age at diagnosis, ethnicity, cancer stage, tumour location and histology were found to have significant difference in CRC patients’ survival. In the Cox PH analysis, older age (=70 years), cancer stage, ethnicity and other histological type were determined as associated factors of CRC patients’ survival. Conclusion: This study found the overall 5-year survival rate of CRC in Brunei Darussalam is similar to that in some Asian countries such as Singapore and Malaysia. However, more efforts need to be carried out in order to raise awareness of CRC and improve the survival of CRC patients.

Road traffic accidents are among the major concerns that are leading for deaths and injuries in the world. Many predictive models use data mining technique to provide semi optimal solutions. Pattern identification and recognition have been used to for road accident predictions based on the critical features extracted depending on the dangerous locations and frequency of occurrences prone for accidents. The aim of this research is to propose a novel predictive model based on the pattern mining predictor which improves the accuracy of accident prediction in frequent accident locations. The proposed system consists of association rules mining technique, which identifies the correlation, frequent pattern and association among the various attributes of the road accident. Clustering technique that discriminates the data based on different patterns and classification technique that classify and predicts the severity of accident. Novel system built leads to an improvement in the accuracy of the accident prediction from 92% to 94%. Furthermore, using selective subset of features decreased the processing time and precision of classification is improved using boosting technique.

A topological index is a numerical quantity correlating an important physicochemical property of a chemical compound. Study of such indices has found important and vital applications in QSAR/QSPR study, drug design, and pharmacology. In this paper, we use a novel mathematical method of edge partition to compute the Wiener polarity index and a special cases of generalized Wiener polarity index of boron-triangular and boron-α nanotubes. Furthermore, we compute certain distance-based indices of boron triangular nanotubes by using the edge partition technology. A computational analysis and graphical comparison of computed indices is also given to confirm the validity of obtained results.

A fixed interconnection parallel architecture is characterized by a graph, with vertices corresponding to processing nodes and edges representing communication links. An ordered set R of nodes in a graph G is said to be a resolving set of G if every node in G is uniquely determined by its vector of distances to the nodes in R. Each node in R can be thought of as the site for a sonar or loran station, and each node location must be uniquely determined by its distances to the sites in R. A fault-tolerant resolving set R for which the failure of any single station at node location v in R leaves us with a set that still is a resolving set. The metric dimension (resp. fault-tolerant metric dimension) is the minimum cardinality of a resolving set (resp. fault-tolerant resolving set). In this article, we study the metric and fault-tolerant dimension of certain families of interconnection networks. In particular, we focus on the fault-tolerant metric dimension of the butterfly, the Benes and a family of honeycomb derived networks called the silicate networks. Our main results assert that three aforementioned families of interconnection have an unbounded fault-tolerant resolvability structures. We achieve that by determining certain maximal and minimal results on their fault-tolerant metric dimension.

In this paper, we provide efficient regression models for correlating the π-electronic energies of carbon nanotubes and nanocones. First, a computational technique for determining distance-based, eccentricity-based, degree-distance-based, and degree-based molecular descriptors is proposed. Then, the application of our technique has been explained for the family of fibonacenes. Importantly, we use the proposed computational technique to determine commonly occurring distance-based molecular descriptors and generate regression models to determine their correlation with the π-electronic energies of lower polycyclic aromatic hydrocarbons (PAHs). Unlike its reputation among chemical graph theorists and reticular chemists, the fourth version of the geometric–arithmetic index outperforms all the distance-based descriptors having the correlation coefficient 0.999. This warrants further usage of the fourth geometric–arithmetic index in quantitative structure-activity relationship models. To ensure the applicability of our proposed study, we use the proposed computational technique to compute analytically explicit expressions for certain distance-based molecular descriptors for certain infinite families of carbon nanotubes and carbon nanocones. Our results assist in correlating the π-electronic energies of underlying chemical structures of these nanotubes and nanocones.

Background: This study aims to determine the survival rates for children and adolescents aged 0–19 years diagnosed with childhood cancer and to evaluate the associated factors for childhood cancer survival in Brunei Darussalam. Methods: The analysis was based on de-identified data of 263 childhood cancer for the period 2002 to 2017 retrieved from a population-based cancer registry. Overall survival was estimated using the Kaplan-Meier method. Univariate analysis, using the log-rank test, was used to examine the differences in survival between groups. Multivariate analysis, using the Cox Proportional Hazard (PH) regression model, was used to estimate the hazard ratios (HRs) and select the significant associated factors for childhood cancer patients’ survival. Results: The overall 1-, 5- and 10-year survival rates for all childhood cancers combined were 79.4%, 70.0% and 68.8% respectively. The most common types of cancer were leukemias, malignant epithelial neoplasms, lymphomas and tumours of the central nervous system (CNS). The 5-year survival estimates were highest for malignant epithelial neoplasms (84.2%) while the lowest was tumours of the CNS (44.1%). Log rank tests showed significant differences in childhood cancer patients’ survival between tumour types and period of diagnosis. In the Cox PH analysis, the presence of lymphomas, gonodal and germ cell neoplasms, and malignant epithelial neoplasms compared to leukemia; children aged 1–4 and 5–9 years compared to adolescents aged 15–19 years; and periods of diagnosis in 2002–2006 and 2007–2011 compared to 2012–2017 were significantly associated with lower hazard of death in this study. Conclusion: This study provides a baseline measurement of childhood cancer survival for monitoring and evaluation of cancer control programmes, to allow planning of cancer control program strategies such as surveillance, screening, and treatment to improve childhood survival rates in Brunei Darussalam.

We report on the activities of the 2015 edition of the BioHackathon, an annual event that brings together researchers and developers from around the world to develop tools and technologies that promote the reusability of biological data. We discuss issues surrounding the representation, publication, integration, mining and reuse of biological data and metadata across a wide range of biomedical data types of relevance for the life sciences, including chemistry, genotypes and phenotypes, orthology and phylogeny, proteomics, genomics, glycomics, and metabolomics. We describe our progress to address ongoing challenges to the reusability and reproducibility of research results, and identify outstanding issues that continue to impede the progress of bioinformatics research. We share our perspective on the state of the art, continued challenges, and goals for future research and development for the life sciences Semantic Web.

In this paper, we study resolvability and fault-tolerant resolvability of convex polytopes and related geometric graphs. Imran et al. (2010) [18] raised an open problem asserting that whether or not every family of convex polytope has a constant metric dimension. Raza et al. (2018) [28] studied the fault-tolerant metric dimension of certain families of convex polytopes. They also concluded their study with an open problem asking whether or not every family of convex polytope has a constant fault-tolerant metric dimension. In this paper, we provide negative answers to both of the aforementioned open problems. We answer the first question by constructing a family of convex polytopes with an unbounded metric dimension. By proving a result between resolvability and fault-tolerant resolvability structures of a graph, we show that the family of convex polytope with an unbounded metric dimension also possesses an unbounded fault-tolerant resolvability structure. Moreover, we construct three more infinite families of graphs which are closely related to convex polytopes, having an unbounded metric dimension.

In this article, we present an efficient computer-based computational technique to compute the energy and Estrada index of graphs. It is shown that our computational method is more efficient and bears less computational and algorithmic complexity. We use our method to show the main result of this article, which asserts that the Estrada index correlates with the π-electronic energies of lower benzenoid hydrocarbons with correlation coefficient 0.9993. This enhances the practical applicability of the Estrada index and warrants its further usage in quantitative structure activity relationships. We further apply our computational technique in computing the energy and Estrada index of two infinite families of boron triangular nanotubes. We perform simulation based on certain computer software packages to study the graph-theoretic behavior of the obtained results. Our results help to correlate certain physicochemical properties of underlying chemical structures of these nanotubes.

The anti-Kekulé number of a graph G with a perfect matching, is defined to be the minimum number of edges that should be deleted such that the remaining graph is connected and contains no perfect matchings. This graph parameter finds potential applications in chemistry, especially in the stability and resonance energy of chemical compounds. For a graph G and a fixed positive integer γ, the problem of finding whether the anti-Kekulé number of G is less than γ, is NP-complete. The anti-Kekulé number of parallelograms, catacondensed benzenoids, fullerenes, triangular, rectangular and hexagonal grids has been investigated in a number of papers. In this paper, we propose the concepts of permitted induced subgraph and matching-based edge partitions in chemical graphs which help us to compute lower and upper bounds respectively on the anti-Kekuté number. We further use these concepts to investigate the anti-Kekulé number of k-polyomino system which is a finite 2-connected plane graph such that each interior face (also called cell) is surrounded by a regular 4k-cycle of length one. First, we calculate the exact value of the anti-Kekué number of k-polyomino system for k = 1,2. Finally, we prove the result for general k-polyomino system by induction on k.

Metric dimension and fault-tolerant metric dimension have potential applications in telecommunication, robot navigation and geographical routing protocols, among others. The computational complexity of these problems is known to be NP-complete. In this paper, we study the fault-tolerant metric dimension of various interconnection networks. By using the resolving sets in these networks, we locate fault-tolerant resolving sets in them. As a result, certain lower and upper bounds on the fault-tolerant metric dimension of those networks are obtained. We conclude the paper with some open problems.

In this paper we show that for integers [Formula presented], [Formula presented], any co-edge-regular graph which is cospectral with the [Formula presented]-clique extension of the [Formula presented]-grid is the [Formula presented]-clique extension of the [Formula presented]-grid, if [Formula presented] is large enough. Gavrilyuk and Koolen used a weaker version of this result to show that the Grassmann graph [Formula presented] is characterized by its intersection array as a distance-regular graph, if [Formula presented] is large enough.

Introduction: Cervical cancer is the third most prevalent cancer among women in Bru-nei Darussalam. This study aims to report the overall survival rates and associated factors of pa-tients diagnosed with malignant cervical cancer in Brunei Darussalam. Methods: A retrospective study of patients diagnosed with cervical cancer from 2007 to 2017 in Brunei Darussalam. The data were obtained from the population-based cancer registry in Brunei Darussalam. Kaplan-Meier survival analysis was used to estimate the overall survival rates at 1-, 3- and 5-year inter-vals while the log-rank test was used to assess differences in survival between groups. Cox Pro-portional Hazard (PH) regression analysis was used to examine the association of demographic and clinical factors on the survival of cervical cancer patients. Results: A total of 329 registered malignant cervical cancer cases were analyzed. The mean age at diagnosis of patients with cervi-cal cancer was 46.7 ± 12.2 years. There were 28.6% deaths and the overall survival rates at 1, 3 and 5 years were 85.4%, 72.6% and 68.6% respectively. Age at diagnosis, cancer stage and his-tology types were significant predictive factors for overall survival of the patients diagnosed with cervical cancers when analysed on both log rank tests and Cox PH model. Conclusion: Age at di-agnosis, cancer stage and histology types were significantly associated with the overall survival rates of cervical cancer patients in Brunei Darussalam. Early detection and management of cervi-cal cancer at early stages should be prioritized to improve the survival rate and quality of cancer care.

Introduction: Breast cancer is the most common cancer and leading cause of cancer deaths among women worldwide. In Brunei Darussalam, breast cancer has the highest incidence rate among women. This study presents the survival rate of women diagnosed with breast cancer in Brunei Darussalam and explores the association between survival and demographic or clinical characteristics. Methods: This is a retrospective study of breast cancer diagnosed from 2007 to 2017 among women in Brunei Darussalam. Cancer data was retrieved from population based cancer registry. Kaplan-Meier survival analysis and Log rank test were applied to estimate the survival rates and the association between survival and important patients’ characteristics. Haz-ard ratios were derived using Cox Proportional Hazard model. Results: The survival rates of breast cancer patients at 1, 3 and 5 years were 89.5%, 79.2% and 72.0% respectively. The 5-year survival rates for cancer stages were 92.2% for localized, 76.9% for regional, and 21.4% for distant metastasis. Ethnicity, cancer stages and cancer stages-morphology interaction were sig-nificant independent predictors for breast cancer survival in Brunei Darussalam. Conclusion: The survival rate of women diagnosed with breast cancer in Brunei Darussalam and its significant pre-dictors are similar to those reported from other developed countries. Further studies on predic-tors such as health seeking behaviours and impact of different cancer treatment will provide fur-ther insight in improving survival rates of breast cancer through early cancer detection pro-grammes and strengthening of the healthcare service delivery.

In this paper, we consider fault-tolerant resolving sets in graphs. We characterize n-vertex graphs with fault-tolerant metric dimension n, n - 1, and 2, which are the lower and upper extremal cases. Furthermore, in the first part of the paper, a method is presented to locate fault-tolerant resolving sets by using classical resolving sets in graphs. The second part of the paper applies the proposed method to three infinite families of regular graphs and locates certain fault-tolerant resolving sets. By accumulating the obtained results with some known results in the literature, we present certain lower and upper bounds on the fault-tolerant metric dimension of these families of graphs. As a byproduct, it is shown that these families of graphs preserve a constant fault-tolerant resolvability structure.

© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.Road fatality is one of the leading causes of death in Brunei with 79 deaths in 1993, the highest ever recorded. The Brunei government has been trying to reduce this by implementing new traffic measures and successfully reduced fatalities to 24 fatalities in 2014. Yearly road fatality has been fluctuating, but there has been a declining tendency overall. The aim of this study is to investigate road fatality in Brunei by extending the research. We developed a multiple regression model and carried out an analysis on road fatality in Brunei. Our analysis indicates that the road fatality appears to rise depending on the increase in the number of young drivers between 15 to 24 years and the number of unemployed people. Comparisons of Brunei road fatality rate per 10,000 vehicles are made with some other countries and we conclude that Brunei has approximately the same rate as Australia in 2014.

Publishing databases in the Resource Description Framework (RDF) model is becoming widely accepted to maximize the syntactic and semantic interoperability of open data in life sciences. Here we report advancements made in the 6th and 7th annual BioHackathons which were held in Tokyo and Miyagi respectively. This review consists of two major sections covering: 1) improvement and utilization of RDF data in various domains of the life sciences and 2) meta-data about these RDF data, the resources that store them, and the service quality of SPARQL Protocol and RDF Query Language (SPARQL) endpoints. The first section describes how we developed RDF data, ontologies and tools in genomics, proteomics, metabolomics, glycomics and by literature text mining. The second section describes how we defined descriptions of datasets, the provenance of data, and quality assessment of services and service discovery. By enhancing the harmonization of these two layers of machine-readable data and knowledge, we improve the way community wide resources are developed and published. Moreover, we outline best practices for the future, and prepare ourselves for an exciting and unanticipatable variety of real world applications in coming years.

Quantitative structure-activity and structure-property associations of natural systems require terminologies for their topological properties. Structure-based topological descriptors/indices of these systems allow these chemical possessions and the bioactivities of these compounds through reckonable structure-activity and structure-property associations’ procedures. In this paper, we propose a computational technique to compute analytically exact expressions for certain degree and distance-based topological indices for general graphs. A comparative analysis is conducted with the known techniques where certain experiments are performed to show that our technique is more efficient and possesses less algorithmic and computational complexity. We apply our method to compute explicit expressions of certain degree and distance topological indices for certain infinite families of fullerenes, carbon nanotubes, and carbon nanocones. The obtained results in this paper generalize certain known results in the literature.

A convex polytopes is a polytope that is also a convex set of points in the n-dimensional Euclidean space Rn. By preserving the same adjacency relation between vertices of a convex polytope, its graph is constructed. The metric dimension problem has been extensively studied for convex polytopes and other families of graphs. In this paper, we study the fault-tolerant metric dimension problem for convex polytopes. By using a relation between resolving sets and fault-tolerant resolving sets of graphs, we prove that certain infinite families of convex polytopes are the families of graphs with constant fault-tolerant metric dimension. We conclude the paper with some open problems.

A convex polytope or simply polytope is the convex hull of a finite set of points in Euclidean space ℝd. Graphs of convex polytopes emerge from geometric structures of convex polytopes by preserving the adjacency-incidence relation between vertices. In this paper, we study the problem of binary locating-dominating number for the graphs of convex polytopes which are symmetric rotationally. We provide an integer linear programming (ILP) formulation for the binary locating-dominating problem of graphs. We have determined the exact values of the binary locating-dominating number for two infinite families of convex polytopes. The exact values of the binary locating-dominating number are obtained for two rotationally-symmetric convex polytopes families. Moreover, certain upper bounds are determined for other three infinite families of convex polytopes. By using the ILP formulation, we show tightness in the obtained upper bounds.

A topological descriptor/index (or molecular structure descriptor) is a numerical value associated with chemical constitution for correlation of chemical structure/network with various physical properties, chemical reactivity or biological activity. Quantitative structure–activity and structure–property relationships of chemical networks require expressions for the topological properties of these networks. Topological indices provide these expressions of topological properties. Valency-based topological descriptors are the oldest and most successful class of descriptors so far. A chemical graph/network is a representation of the structural formula of a chemical compound whose vertices correspond to the atoms of the compound and edges correspond to chemical bonds. In this paper, we study valency-based topological indices of chemical networks. By using some real world data, we performed certain comparative testings to investigate the performance of almost all well-known valency-based indices. Dependence on the molecular structure is studied for topological indices which are best in performance. We calculated explicit formulas for well-performed indices of some infinite families of carbon nanotubes, carbon nanocones and a newly proposed family of organic networks called tetrahedral diamond networks. Tetrahedral diamond networks arises by recurrently joining graphene layers in a diamond cluster. Significance and applicability of the obtained results are reported.

Real-time face detection and tracking systems suffer from low accuracy and slow processing speed that lead to poor robustness. This problem is vital in real-time setups including human robot interactions (HRI) and video analysis systems. This paper presents margin-based region of interest (MROI) approach to speed up the processing time. Further a hybrid approach is also presented that combines Multi-task Convolutional Neural Networks (MTCNN) with template matching to improve face detection accuracy. The MROI approach which is responsible to speed up the processing time is presented in two variants with fixed and dynamic margin concepts. Dataset used in this work comprises of twenty RGB video files. Each video file is fifteen seconds long and been created from real-life videos containing a person in lecture delivering environment. Each video file contains a person in which the person moves, turns head and the camera also moves. The highest face detection and tracking accuracy achieved in this paper is 99.31% with a processing time of 14.93 milliseconds per frame. The proposed hybrid algorithm significantly improves the ability to detect and track faces in sideway orientation apart from frontal face. The proposed algorithm has the ability to process above 65 frames per second (FPS). The system presented has increased FPS processing ability by more than 400% as well as given boost to the accuracy if compared to the conventional MTCNN full frame scanning techniques.

The purpose of this paper is to show that short-ranged dependence prevailed for Singapore-Malaysia exchange. Although, it is perceived that there is some evidence of long-ranged dependence [1,2], it is still unclear whether Singapore-Malaysia exchange indeed exhibits long-ranged dependence. For this paper, we focus on the currency rate for a sixteen-year period ranging from September 2002 to September 2017. We estimate the Hurst parameter using the famous rescaled R/S statistics technique. From our analysis, we showed that the Hurst parameter is approximately 0.5 which indicates short-ranged dependence. This short memory property is further validated by performing a one-tailed z-test whose alternative hypothesis is that the Hurst parameter is not 0.5 at 1% significance level. We conclude that the alternative hypothesis is rejected. The existence of short memory proves that the behaviour of the exchange rate is unpredictable, supporting the efficient market hypothesis, which states that not only is price movement completely random but also tomorrow’s prices are predicted by all the information in today’s prices.

In the protein sequence space, natural proteins form clusters of families which are characterized by their unique native folds whereas the great majority of random polypeptides are neither clustered nor foldable to unique structures. Since a given polypeptide can be either foldable or unfoldable, a kind of “folding transition” is expected at the boundary of a protein family in the sequence space. By Monte Carlo simulations of a statistical mechanical model of protein sequence alignment that coherently incorporates both short-range and long-range interactions as well as variable-length insertions to reproduce the statistics of the multiple sequence alignment of a given protein family, we demonstrate the existence of such transition between natural-like sequences and random sequences in the sequence subspaces for 15 domain families of various folds. The transition was found to be highly cooperative and two-state-like. Furthermore, enforcing or suppressing consensus residues on a few of the well-conserved sites enhanced or diminished, respectively, the natural-like pattern formation over the entire sequence. In most families, the key sites included ligand binding sites. These results suggest some selective pressure on the key residues, such as ligand binding activity, may cooperatively facilitate the emergence of a protein family during evolution. From a more practical aspect, the present results highlight an essential role of long-range effects in precisely defining protein families, which are absent in conventional sequence models.

For this study, Zollman’s four corners-and-a-diamond mathematics graphic organiser embedded with Polya’s Problem Solving Model was used to investigate secondary school students’ performance in arithmetic word problems. This instructional learning tool was used to help students break down the given information into smaller units for better strategic planning. The participants were Year 7 students, comprised of 21 male and 20 female students, aged between 11-13 years old, from a co-ed secondary school in Brunei Darussalam. This study mainly adopted a quantitative approach to investigate the types of differences found in the arithmetic word problem pre- and post-tests results from the use of the learning tool. Although the findings revealed slight improvements in the overall comparisons of the students’ test results, the in-depth analysis of the students’ responses in their activity worksheets shows a different outcome. Some students were able to make good attempts in breaking down the key points into smaller information in order to solve the word problems.

We re-examine a site-binding approach independently proposed by Schellman (Schellman, J.A. (1958) Compt. rend. Lab. Carlsberg Ser. Chim. 30, 439–449) and Aune and Tanford (Aune, K.C. and Tanford, D. (1969) Biochemistry, 8, 4586–4590) for explicitly including the denaturant concentration within the protein unfolding equilibrium. We extend and formalize the approach through development of a multi-dimensional analytical model in which the folding reaction coordinate is defined by the number of denaturant molecules bound to sites located on either the initially folded, or unfolded, states of the protein. We use the developed method to re-examine the mechanistic determinants underlying the sigmoidal shape of the unfolding transition. A natural feature of our method is that it presents a landscape picture of the denaturant induced protein unfolding reaction.

The Protein Data Bank Japan (PDBj), a member of the worldwide Protein Data Bank (wwPDB), accepts and processes the deposited data of experimentally determined biological macromolecular structures. In addition to archiving the PDB data in collaboration with the other wwPDB partners, PDBj also provides a wide range of original and unique services and tools, which are continuously improved and updated. Here, we report the new RDB PDBj Mine 2, the WebGL molecular viewer Molmil, the ProMode-Elastic server for normal mode analysis, a virtual reality system for the eF-site protein electrostatic molecular surfaces, the extensions of the Omokage search for molecular shape similarity, and the integration of PDBj and BMRB searches.

The recent global financial crisis has highlighted the need for financial institutions to find and implement of appropriate models for risk measurement. There was a particular interest of investors to increase their positions in the gold market as the risk in equity and bond markets was increasing. This study evaluates the effectiveness of various volatility models with respect to modeling and forecasting market risk in the gold future market. For this study, last trading price of gold futures are considered from January 1990 to June 2014 with 6,373 observations. The gold futures volatility is modeled and forecasted using GARCH-class models with long memory and fat-tail distributions, by considering ARMA model as the conditional returns. The results reveal that ARMA(1,1) model provides best results for the conditional returns. Among the linear and non-linear GARCH-class models, EGARCH and FIEGARCH models are provided best results for in-sampling forecasting. Moreover, EGARCH model gives bit of higher performance than FIEGARCH model under model diagnostic tests. After that, futures price volatilities of gold are forecasted using EGARCH and FIEGARCH models. Furthermore, it was found that long memory effect is significant. Forecasting accuracy of GARCH-class models are compared with different distributions of innovations. The results indicate that GARCH model with skew t-distribution outperform those with normal distribution. For speculations and noise traders in futures market, both linear and nonlinear models should be taken into account.

We have developed a rigorous computational technique to compute exact analytic expressions for a number of distance-based topological indices of chemical graphs. There are two main advantages of our technique over existing techniques of similar nature: first, our technique is significantly diverse as it also covers the Wiener index and eccentricity-based topological indices besides Szeged-like indices, and secondly we have considerably reduced the algorithmic and computational complexity in comparison to previous techniques. Our proposed technique generates certain vertex and edge partitions of a graph which are essential in computing the exact analytical formulas of distance-based and eccentricity-based indices. To ensure the applicability of our technique, we have computed various distance-based and eccentricity-based topological indices for certain infinite families of polyomino chain system. Moreover, we _find analytical exact expressions of certain degree-based topological indices for these polyomino chains. These topological indices can be obtained as a by-product of our technique.

To estimate the areas of the fields to be discovered in a mature play, we use a model that conceptually divides the play (or a portion of it) into hexagons of "unit area," loosely defined as the minimum area that an oil field should have to be commercial. The individual hexagons may contain oil, and they are supposed to be spatially independent. The distribution of field sizes is defined by just one parameter (the quotient cells with oil in the area of study/total number of cells in the area of study). Samples taken from this discrete distribution look as if they had been drawn from continuous log-normal distributions. The paper considers the hypothesis that all samples drawn from a distribution of field sizes are biased, overestimating the true areas of the fields existing in the play.

This study examined 86 high school (Year 11) students’ basic proficiencies in Mathematics were examined, and the connections between language proficiency, gender, family socio-economic background and family factors to their performances were also identified. A ‘proficiency test’ paper was developed to investigate students’ proficiency in Mathematics, and semi-structured interviews were utilized to gather data regarding parental involvement in students’ academic activities. Several different statistical tests were employed for the data analyse. Although the findings revealed a positive correlation between students’ proficiency test score and their yearly Mathematics achievements, the relationship between students’ basic proficiency in Mathematics and their gender were not found to be significant. The students’ English language literacy was significantly related to their achievements in Mathematics. And the students’ basic proficiency in Mathematics and parents’ income was significantly correlated, but the students’ proficiency and parents’ education was not significantly correlated. Students’ English language proficiency and parental involvement in terms of emotional or financial support (such as attending private tuition class) were also determined to be the contributing factors in the students’ achievement in Mathematics.

There are various topological indices such as degree based topological indices, distance based topological indices and counting related topological indices etc. These topological indices correlate certain physicochemical properties such as boiling point, stability of chemical compounds. In this study, the authors compute the sum-connectivity index and multiplicative Zagreb indices for certain networks of chemical importance such as silicate networks, hexagonal networks, oxide networks, and honeycomb networks. Moreover, a comparative study using computer-based graphs has been made to clarify their nature for these families of networks.

The problem of shear dispersion in the atmospheric boundary layer (ABL) is revisited. The aim is to improve understanding of how and why the behaviour of state-of-the-art ‘random flight’ Lagrangian particle dispersion models (RFMs) can differ from that of simpler ‘random displacement’ models (RDMs or eddy diffusivity models). First an asymptotic analysis is used to obtain a formula, valid for quite general profiles of turbulent statistics and the mean wind, for the effective horizontal diffusivity of a tracer in the ABL. Second, with ‘poison gas release’ problems in mind, a large-deviation approach is used to understand in greater detail the behaviour of the concentration in the tails of the distribution. Results are verified by solving the RFM equations numerically for a large ensemble of particles. Turbulent statistics relevant to stable and neutral boundary-layer conditions are considered, as is the effect of non-uniqueness in the RFM equations. The importance of three-dimensional effects such as the effect of an Ekman spiral in the mean wind are then considered, and criteria determining whether plume widths are controlled by direct horizontal diffusion or by secondary shear dispersion effects are obtained. Finally, a quantitative account of ‘plume bending’ in the stable ABL is presented.

We study nonlinear sigma model, especially Skyrme model with twist: twisted Skyrmion string where twist term, mkz, is indicated in vortex solution. To add gravity, we replace gμv in Lagrangian system with a space-time metric tensor, gμv which in view of the time-independence and cylindrical symmetry of the assumed vortex solution is taken to be a function of r alone. We use ode45 for numerical calculation, i.e. a tool box in Matlab to solve coupled Einstein field equations which have ordinary differential equations (ODE) form.

Most existing publications regarding the supply chain (SC) have concentrated on two-tier models that include the vendor and the buyer. In reality, SC systems are more multifaceted and consist of at least three parties: supplier, manufacturer, and retailer. This study presents a manufacturer managed consignment policy (CP) model for a three-tier supply chain involving a single supplier, a single manufacturer, and multiple retailers. We also present a traditional policy (TP) model considering similar circumstances for a comparative study. In these models, we consider that retailers’ demands are random variables following generic probability density functions. The manufacturer collects raw materials from the supplier to produce finished goods, and then delivers the finished items to the retailers depending upon the retailers’ demand. These are profit maximizing models. We present techniques for solving these problems. We demonstrate the potential significance of the proposed models using comparative studies based on three numerical example problems. We found that all SC members earned increased profits under CP when compared with TP, and that the three-tier consignment is better than the two-tier consignment. We also analyzed the retail price markdown.

Globalisation is an important world phenomenon whose impact can be increasingly felt at the higher education arena. In this paper, we looked at how a local university in Brunei Darussalam has embraced globalisation in three broad areas; teaching and learning, research and internationalisation. Conventionally, a university primarily prepares students on an academic level with the aim of aiding them in establishing a successful career in the future. Today, globalisation is transforming the job market tremendously. Increasing human migration and population has made jobs more competitive. The local university’s traditional curriculum has transformed into a hybrid program incorporating both an academic environment of the highest quality as well as unconventional means of intellectual enrichment. In addition, the university interacts directly with efforts of globalisation by maintaining a prominent presence in the realm of maintaining active exchanges with international collaborators. Moving forward, we propose how we can better deal with globalisation without threatening its fundamental mission in imparting knowledge to students.

This study investigated the use of interdisciplinary learning activity task to construct students‟ knowledge in Mathematics, specifically on the topic of scale drawing application. The learning activity task involved more than one academic discipline, which is Mathematics, English Language, Art, Geography and integrating the Brunei Darussalam national philosophy of the Malay Islamic Monarchy. A quantitative method using a pre-experimental design focusing on one-group pre-and post-test design was used for this study. The participants were selected from a convenient sample of 43 Year 9 students in one of the secondary schools in Brunei. The findings were also triangulated with the students‟ collected reflective journal artifact documents. Each student journal was analyzed using the identified learning activity stages within the RBC-model, where the R denotes Recognizing, B is Building with and C means Constructing. The results showed an improvement in the students‟ achievement, and they were able to construct the mathematics knowledge by means of collaboration among group members. Based on the findings, it is recommended that Mathematics teachers be encouraged and supported to design authentic and interdisciplinary learning activity that are learner centered catering to the different needs of our students and also to meet the 21st century skills demand.

Face detection and tracking algorithms mainly suffer from low accuracy, slow processing speed, and poor robustness when meet with real-time setup. The problem becomes crucial in real-time situations such as in human robot interactions (HRI) or video analysis. A margin-based region of interest (ROI) hybrid approach that combines Haar cascade and template matching for face detection and tracking is proposed in this paper to improve the detection accuracy and processing speed. To speed up the processing time, region of interests (ROIs) with fixed and dynamic margin concepts are used. A dataset comprising of ten RGB video streams of fifteen seconds have been created from real-life videos containing a person in lecture delivering environment. In each video, there exists person’s movement, face turning and camera movements. An accuracy of 97.96% with processing time of 10.76 ms per frame has been achieved. The proposed algorithm can detect and track faces in sideway orientation apart from frontal face. The proposed approach can process the video streams at the speed above 90 frames per second (FPS). The proposed approach reduces processing time by ten times and with a boost to accuracy in comparison to the conventional full frame scanning techniques.

In this note, we study graphs with two main and two plain eigenvalues. Besides some other characterization results, we characterize the disconnected graphs with two main and two plain eigenvalues. Moreover, we provide several families of examples of such graphs.

This small-scale action research study examines the students’ ability in using their mathematical skills when performing order of operations in numerical expressions. In this study, the ‘hierarchy-of-operators triangle’ by Ameis (2011) was introduced as an alternative BODMAS approach to help students in gaining a better understanding behind the concept of the order of operations. The study involved 21 students from Year 9 (or equivalent to 8th Grade in American schooling) in one of the government secondary schools in Brunei Darussalam. Mixed method research design was adopted for this study. Data were collected and analyzed from the students’ pre and post-test scores as well as from the interviews. Comparisons of the scores showed positive progress and greater improvement in the students’ performance. The interviews were necessary in order to gain the students’ feedback in the implementation of the alternative approach. Most of the students who were interviewed responded that it was easier for them to remember the triangle rather than using the mnemonic as a tool to remember the order of operations.

Structure-based topological descriptors/indices of complex chemical networks enable prediction of physico-chemical properties and the bioactivities of these compounds through QSAR/QSPR methods. In this paper, we have developed a rigorous computational and theoretical technique to compute various distance-based topological indices of complex chemical networks. A fullerene is called the IPR (Isolated-Pentagon-Rule) fullerene, if every pentagon in it is surrounded by hexagons only. To ensure the applicability of our technique, we compute certain distance-based indices of an infinite family of IPR fullerenes. Our results show that the proposed technique is more diverse and bears less algorithmic and combinatorial complexity.

Teaching mathematical topics through problem solving is becoming an important aspect of teaching and learning. Undoubtedly, students’ conceptual understanding and procedural knowledge play an important role in problem solving process predominantly in solving non-routine problems. In this investigation, students’ level of conceptual understanding and procedural knowledge were assessed according to the Oregon Mathematics Problem Solving Rubrics. The students’ solutions allow them to be classified as proficient, apprentice or novice problem solvers.

We develop a Hermite interpolation scheme and prove error bounds for C1 bivariate piecewise polynomial spaces of Argyris type vanishing on the boundary of curved domains enclosed by piecewise conics.

In this note, we consider connected graphs with exactly two main eigenvalues. We will give several constructions for them, and as a consequence we show the existence of a family of such graphs with an unbounded number of distinct valencies.

Across the Internet where massive amounts of data are being created every second. Widely known as the big data, this tool can be signified as the techniques to capture, store and analyse data of resources. It enables us to provide instrumental means in formulating data such as for communication, sending information and online activities purpose. Moreover, it can also offer innovative teaching and learning for higher learning institution. This study aims to discuss the teaching based on big data application and practices to enhance innovation in teaching, learning, sociality, and technology for students. In this study, we deploy thematic analysis to construct a model for higher institutions to regulate their scenario on big data application. The findings reveal that it can be used to improve decision-makings, provide insights, knowledge discoveries, and optimise learning processes. Higher learning institution can adopt big data analytics-based teaching and learning strategy to sustain in providing innovative teaching and learning experience to the students with opportunities to improve learning experiences to them with big data analytics. In fact, students nowadays rely on online resources and at the same time they produce data for sharing purposes.

Over the years various innovative teaching approaches were developed, notably Problem-Based Learning (PBL) help students develop flexible understanding and lifelong learning skills. The present research study used a structured PBL approach adapted from the four step model (Wong & Day, 2009). A convergent mixed-method design was used to determine if administering a structured PBL approach would improve students’ ability to solve college-level Mechanics problems and students’ attitudes towards mathematics and their learning environment. From the pre- and post-test results, there were no significant changes in students’ academic performance. However, teacher reflective statements indicated increase in the use of higher-order thinking skills and overall engagement. From the observations, interviews and questionnaire results, students showed a positive change in their attitudes towards mathematics.

We show that the d-cube is determined by the spectrum of its distance matrix.

A rigorous methodology for the evaluation of integration schemes for Lagrangian particle dispersion models (LPDMs) is presented. A series of one-dimensional test problems are introduced, for which the Fokker-Planck equation is solved numerically using a finite-difference discretisation in physical space and a Hermite function expansion in velocity space. Numerical convergence errors in the Fokker-Planck equation solutions are shown to be much less than the statistical error associated with a practical-sized ensemble ( Combining double low line 106) of LPDM solutions; hence, the former can be used to validate the latter. The test problems are then used to evaluate commonly used LPDM integration schemes. The results allow for optimal time-step selection for each scheme, given a required level of accuracy. The following recommendations are made for use in operational models. First, if computational constraints require the use of moderate to long time steps, it is more accurate to solve the random displacement model approximation to the LPDM rather than use existing schemes designed for long time steps. Second, useful gains in numerical accuracy can be obtained, at moderate additional computational cost, by using the relatively simple "small-noise" scheme of Honeycutt.

Teaching by telling and teaching for the sake of examination may lead to students experiencing misconceptions in their mathematics lessons. The present study explored how the topic ‘solving simultaneous linear equations’ were taught to two groups of Year 9 students in two government secondary schools in Brunei Darussalam, and the misconceptions that these students have experienced. The instruments used for this study were pen-and paper test items, the ‘Learning solving simultaneous questionnaire’ and interviews. A total of four teachers and 41 Year 9 students participated in the study. Results from the qualitative analyses revealed that teaching by telling still exists in some of the teachers’ instructions and that students lack the conceptual understanding of the procedures. Another qualitative finding is that students’ incompetency in their pre-requisite knowledge of addition and subtraction of integers also deterred them from solving the simultaneous linear equations successfully. Formative assessment and a learner-centred approach are recommended to minimise such misconceptions.

Background: The nuclear magnetic resonance (NMR) spectroscopic data for biological macromolecules archived at the BioMagResBank (BMRB) provide a rich resource of biophysical information at atomic resolution. The NMR data archived in NMR-STAR ASCII format have been implemented in a relational database. However, it is still fairly difficult for users to retrieve data from the NMR-STAR files or the relational database in association with data from other biological databases. Findings: To enhance the interoperability of the BMRB database, we present a full conversion of BMRB entries to two standard structured data formats, XML and RDF, as common open representations of the NMR-STAR data. Moreover, a SPARQL endpoint has been deployed. The described case study demonstrates that a simple query of the SPARQL endpoints of the BMRB, UniProt, and Online Mendelian Inheritance in Man (OMIM), can be used in NMR and structure-based analysis of proteins combined with information of single nucleotide polymorphisms (SNPs) and their phenotypes. Conclusions: We have developed BMRB/XML and BMRB/RDF and demonstrate their use in performing a federated SPARQL query linking the BMRB to other databases through standard semantic web technologies. This will facilitate data exchange across diverse information resources.

In our relentless effort to achieve global excellence, we have identified internationalisation as one of the key strategic thrusts. One of our key priorities is to recruit international students from our partner universities to undertake study abroad in our university. These students are important to us, as they will be our future unofficial ambassadors. Thus, enhancing their experience during short stints in Brunei is our main priority. In this paper, we not only discuss the support and services we put in place to attract these international students but also how we enhanced the international student’s experience. We also identified common problems faced by the international students so that we can continually improve our services offered to them. It should be noted that enhancing international students’ experience is an all-encompassing effort from the pre-arrival to post-departure. To address some of these common problems, we have put in place several notable support system such as ‘1-stop’ student central, student-buddy system, 24-hour hotline, ‘crash’ courses in local customs and traditions and many more. To conclude, we discuss possible future initiatives to further enhance the international students’ experience.

Algebra is a fundamental concept in Mathematics at the secondary level. The focus of this study is on the four different main subtopics in algebra namely, factorisation, expansion, inequalities and algebraic application word problems. This study aims to investigate and identify misconceptions and common errors occurring among secondary school students as well as to suggest solutions to counter each respective common error found according to each subtopic. For the purpose of this study, a test paper was designed containing five questions. Each question consisted of one of the four main algebra subtopics and an additional fifth question on inequality. The test was disseminated to a mixed ability Year 10 class in Brunei Darussalam chosen by convenient sampling. The findings reported were from the qualitative analyses of the collected students’ work. Constant patterns of misconceptions and common errors emerging among the students were discerned and its findings were reported in this paper. According to the findings, generally, the students developed misconceptions that prevented them from achieving the required solutions. As a consequence, these misconceptions had strongly led the students towards the action of performing common errors in their workings. Hence, to overcome these consistently incorrect habits among students from arising in the future, the suggested solutions should be included in the teaching strategies as a guide for future educators of Mathematics.

In this action research study on junior college level (the equivalent of 11th and 12th grades in American schooling) students, an investigation was conducted to determine the effectiveness in implementing a cooperative learning strategy known as the Students Team Achievement Division (STAD). Data were collected quantitatively and qualitatively from two groups of 95 first year students in one of the junior colleges in Brunei Darussalam. In the first cycle, an achievement test was administered to Group 1 without STAD (N = 49) and Group 2 with STAD (N = 46). An independent sample t-test was later conducted to compare the two groups and the results showed that there was a significant difference in their mathematics scores; for Group 1 without STAD (M = 35.8%, SD = 19.9) and Group 2 with STAD (M = 45.6%, SD = 20.8) on conditions; t(93) = 2.347, p = 0.0211. The p-value indicated that this difference in mean was statistically significant. In addition, qualitative data was collected in the form of an unstructured interview in each of the two cycles. The findings revealed that the students were positive and satisfied with the STAD approach. Implementing the cooperative learning strategy STAD may be useful as an alternative teaching method for junior college level mathematics.

A finite element solution has been performed in this work to solve unsteady governing equations of natural convection in a carbon nanotube-water-filled cavity with inclined heater. The temperature of ceiling and left vertical walls is lower than that of the heater while the other walls are adiabatic. The main governing parameters are nanofluid volume fraction and Rayleigh number (Ra). It is found that the heat transfer rate shows different trends based on Rayleigh number and it increases with increase in nanoparticle volume fraction. It has been estimated that average Nusselt number (Nu) is dependent onRa through power regression models with strong positive linear correlation between ln (Nu) and ln (Ra). In particular, for the maximum time, when the solid volume fraction is varied from 0 to 0.1 the dependence between average Nu and linear Ra, on a logarithmic scale, is very high.

We study numerical solution, especially using 4th order Runge-Kutta method, for solving a twisted Skyrme string equation. We find numerically that the value of minimum energy per unit length of vortex solution for a twisted Skyrmion string is 20.37 × 1060 eV/m.

Topological descriptors are the most important numerical quantities in the fields of mathematical chemistry and nanotechnology. These numerical descriptors are based on the topology of the atoms and their bonds (chemical conformation, quaternary structure). Local-valency/degree based topological descriptors/indices are of vital importance due to their specific chemical significance. These numerical invariants are the most successful molecular descriptors in structure-property and structure-activity relationships studies. A nanostructure is an object of intermediate size between molecular and microscopic structures. It is a product derived through engineering at the molecular scale. The most important of these new materials are carbon nanotubes. They have remarkable electronic properties and many other unique characteristics. Carbon nanosheets are 2-dimensional lattices of carbon nanotubes. To compute and study topological indices of nanostructures is a respected problem in nanotechnology. In this paper, degree based topological indices of certain carbon nanosheets are strong-minded. We formulate an important conjecture at the end of this article.

In theoretical and computational chemistry, a molecular descriptor is a numerical representation of a chemical structure while a topological descriptor correlates certain physico-chemical characteristics of underlying chemical compounds besides its numerical representation. Valency based topological descriptors like atom-bond connectivity index and geometric-arithmetic index play an important role in the stability analysis of linear alkanes. The prediction power of frustration indices for stability of various chemical and nanostructures like fullerenes is better then some valency based topological descriptors. In this paper, certain valency based and frustration related topological descriptors for titania nanotubes are studied.

The measure of bipartivity is one of the important topological and structural property which describes the chemical stability of underlying chemical structures. Bipartite edge frustration is one of the topological descriptors which calculate measure of bipartivity of a chemical structure. Carbon hexagonal nanotubes, boron triangular nanotubes and boron α -nanotubes are important nanostructures, which have been studied extensively by both of the theoretical and computational chemists. In this article, we consider carbon hexagonal nanotubes, boron triangular nanotubes and boron α -nanotubes for the study of bipartite edge frustration.

In the last decade, the emergence of diverse students in a streamed class based on the mathematical ability brought upon challenges for the teacher to find an approach which could accommodate all students. This study aims to investigate the connection of students’ ability with their learning preferences in mathematics by applying differentiated instruction using tiered assignments and parallel tasks. This qualitative approach was used for this study from a sample of year 7 mathematics students within Pengukuhan Kemahiran Asas programme (PEKA) (the Basic Skills Strengthening programme), which revolved upon low ability for students with very weak numeracy skills. The findings in general revealed that there is an improvement in their performance.

Let G(V,E)be a connected graph. A set M ⊆ E is called a matching if no two edges in M have a common end-vertex. A matching M in G is perfect if every vertex of G is incident with an edge in M. The perfect matchings correspond to Kekulé structures which play an important role in the analysis of resonance energy and stability of hydrocarbons. The anti-Kekulé number of a graph G, denoted as akG, is the smallest number of edges which must be removed from a connected graph G with a perfect matching, such that the remaining graph stay connected and contains no perfect matching. The anti-Kekulé numbers of silicate, oxide and honeycomb networks were calculated in [Xavier, Shanthi, and Raja, International Journal of Pure and Applied Mathematics 6, 1019 (2013)]. In this paper, we calculate the anti-Kekulé number of HAC5C7/2p(q), TUC4(C8)R,2p(q), ∀ pq nanotubes and CNC2kn, ∀ k(n) nanocones. We set the infinite cases of all nanotubes as conjecture.

A numeric quantity which characterise the whole structure of a graph is called a topological index. The concept of atom-bond connectivity (ABC) and geometric-arithmetic (GA) topological indices were established in chemical graph theory based on vertex degrees. Later on, other versions of these indices were introduced and some of the versions of these indices are recently designed. Let H be a graph, then the general definitions of these indices are as follows: ABC(H) = ∑ab∈E(H) √(Qa + Qb - 2)/(QaQb), and GA(H) = ∑ab∈E(H)2√QaQb/(Qa + Qb/), where Qa is the quantity which is uniquely related to the vertex a. Carbon nanotubes which are actually carbon allotropes, have applications in the fields such as electronics, materials science, optics, nanotechnology, and architecture. To study and compute topological indices of nanostructures is a respected problem in nanotechnology. In this article, we compute atom-bond connectivity (ABC), geometric-arithmetic (GA), and Randić indices of H-Naphtalenic nanotubes and TUC4[mo, n] nanotube. We also compute fourth version of atom-bond connectivity (ABC4) index and fifth version of geometric-arithmetic (GA5) index for these families of nanotubes.

The purpose of this paper is to implement a random death process into a persistent random walk model which produces sub-ballistic superdiffusion (Lévy walk). We develop a stochastic two-velocity jump model of cell motility for which the switching rate depends upon the time which the cell has spent moving in one direction. It is assumed that the switching rate is a decreasing function of residence (running) time. This assumption leads to the power law for the velocity switching time distribution. This describes the anomalous persistence of cell motility: the longer the cell moves in one direction, the smaller the switching probability to another direction becomes. We derive master equations for the cell densities with the generalized switching terms involving the tempered fractional material derivatives. We show that the random death of cells has an important implication for the transport process through tempering of the superdiffusive process. In the long-time limit we write stationary master equations in terms of exponentially truncated fractional derivatives in which the rate of death plays the role of tempering of a Lévy jump distribution. We find the upper and lower bounds for the stationary profiles corresponding to the ballistic transport and diffusion with the death-rate-dependent diffusion coefficient. Monte Carlo simulations confirm these bounds.

The question of which two-qubit states are steerable [i.e., permit a demonstration of Einstein - Podolsky - Rosen (EPR) steering] remains open. Here, a strong necessary condition is obtained for the steerability of two-qubit states having maximally mixed reduced states, via the construction of local hidden state models. It is conjectured that this condition is in fact sufficient. Two provably sufficient conditions are also obtained, via asymmetric EPR-steering inequalities. Our work uses ideas from the quantum steering ellipsoid formalism, and explicitly evaluates the integral of n/(nTAn) over arbitrary unit hemispheres for any positive matrix A.

A topological index is a numeric quantity which represents the structure of a graph. A molecular/chemical graph is hydrogen depleted chemical structure in which vertices denote atoms and edges denote the bonds. There are certain types of topological indices like distance based, degree based and counting related topological indices. Among them degree based topological indices are of much importance due to their chemical significance. Carbon nanotubes, a type of fullerene, have potential in fields such as nanotechnology, electronics, optics, materials science and architecture. In this article, we compute atom-bond connectivity (ABC), geometric-arithmetic (GA), Randi c′ and zagreb indices of VC5C7[p,q], HC5C7[p,q] and SC5C7[p,q] nanotubes. We also compute ABC4 and GA5 indices for these nanotubes.

‘Middle censoring’ is a very general censoring scheme where the actual value of an observation in the data becomes unobservable if it falls inside a random interval (L, R) and includes both left and right censoring. In this paper, we consider discrete lifetime data that follow a geometric distribution that is subject to middle censoring. Two major innovations in this paper, compared to the earlier work of Davarzani and Parsian [3], include (i) an extension and generalization to the case where covariates are present along with the data and (ii) an alternate approach and proofs which exploit the simple relationship between the geometric and the exponential distributions, so that the theory is more in line with the work of Iyer et al. [6]. It is also demonstrated that this kind of discretization of life times gives results that are close to the original data involving exponential life times. Maximum likelihood estimation of the parameters is studied for this middle-censoring scheme with covariates and their large sample distributions discussed. Simulation results indicate how well the proposed estimation methods work and an illustrative example using time-to-pregnancy data from Baird and Wilcox [1] is included.

Topological indices are the global parameters defined for the simple graphs such that they give the same numerical value if the graphs are isomorphic. These numbers are of much importance because of their chemical importance, they correlate certain physico-chemical properties of certain organic compounds such hydrocarbons etc. A chemical graph is a graph which is created from some molecular structure by applying some graphical operations. Valency is a local graph parameter, which is defined for every vertex as the number of connections with other vertices in a graph, just like for an atom in a molecule. Dendrimers are recognized as one of the major commercially available nanoscale building blocks, large and complex molecules with well defined chemical structure. Cactus chains are simple linear polymers which were first known as Husimi trees. A cactus graph is a connected graph in which no edge lies in more than one cycle. In this article, we study general Randić, harmonic, atom-bond connectivity (ABC), and geometric arithmetic (GA) indices for organosilicon dendrimers and cactus chains of three types.

This book is a comprehensive survey of the current state of knowledge about the dynamics and gravitational properties of cosmic strings treated in the idealized classical approximation as line singularities described by the Nambu-Goto action. The author’s purpose is to provide a standard reference to all work that has been published since the mid-1970s and to link this work together in a single conceptual framework and a single notational formalism. A working knowledge of basic general relativity is assumed. The book will be essential reading for researchers and postgraduate students in mathematics, theoretical physics, and astronomy interested in cosmic strings.

Topological descriptors are the numerical indices based on the topology of the atoms and their bonds (chemical conformation, quaternary structure). Valency/degree based topological descriptors are of vital importance due to their specific chemical significance. They correlate certain physico-chemical properties like boiling point, stability, enthalpy of vaporization, Kovat’s constant etc. of chemical compounds especially carbon-containing structures. Carbon nanotubes, a type of fullerene, have potential in fields such as nanotechnology, electronics, optics, materials science and architecture. Carbon nanosheets are 2-dimensional lattices of carbon nanotubes. To compute and study topological descriptors of nanostructures is a respected problem in nanotechnology. Graph theory has found significant use in this field of research. In this paper, valency based topological descriptors of various nanosheets are strong-minded. We quote an important observation at the end of this article.

The study of spectrum (i.e. multiset of eigenvalues) of graphs especially molecular graphs has found a considerable use in theoretical chemistry and computational nanoscience. There are various kinds of spectrum related topological indices such as, energy, Estrada index, Laplacian Estrada index, positive and negative inertia indices, nullity, signature etc., which play a key role in QSAR/QSPR studies. Energy and Estrada indices relate energies associated to the π -electron orbitals with the conjugated hydrocarbons and the degree of folding of proteins and some other long-chain biomolecules respectively. Whereas, inertia indices and nullity have found a significant use in the study of stability of chemical compounds. In this paper, inertia indices, nullity and signature of CNC3[n] and CNC5[n] nanocones are studied. Furthermore, we formulate a conjecture on these numerical parameters for general CNC2k+1[n] nanocones

In 2009, the Universiti Brunei Darussalam (UBD) made extensive changes to its curriculum from a majorcentric to a liberal arts style broad-based degree with emphasis on the soft-skill development. One of the important components of the new curriculum is the mandatory year out also known as the ‘Discovery Year’. The objectives of the discovery year is to promote real-world experiential and design-centric learning, and students are given the opportunity to gain community-based or international experience outside of the UBD campus. During the discovery year, students have a choice of four activities namely study abroad, internship, incubation and community outreach programme. Since the inception of the discovery year, study abroad has always been the first choice for most of our students. In 2011, the ratio of UBD students who did the study abroad programme was 4 out of 10. This proportion increased to 7 out of 10 in 2014. More importantly, around 90% of students who left Brunei chose the study abroad option. In this paper, we investigated the reasons behind why study abroad is and has always been the first choice, and also the reasons behind the increasing proportion. We also explored the benefits of study abroad from the perspectives of both the home and host universities. Furthermore, we examined the issues and challenges that hindered the students from taking other activities during discovery year. To conclude, the benefits of study abroad are an all encompassing one from raising the quality of education, improving the university’s ranking to fostering global citizens.

Our university was first established in 1985. One of its main goals then is to produce local workforce for the nation. Fast-forward 30 years later, the university has evolved to become a research-intensive university with internationalisation at the forefront of its strategic thrust. The transformational journey was timely in order to cater to the ever-changing needs of local and international society and the global market, and to respond to the rapidly changing expectations of higher education. This paper looks at how we evolved on the internationalisation front focusing particularly on outward student mobility. On the outbound front, our innovative curriculum, known as GenNEXT, allows students to leave the university for one year in their third year of studies also known as the discovery year. Various supports and services have been put ranging from academic, financial to welfare support in order to facilitate this outbound mobility.

A topological index can be considered as a transformation of a chemical structure into a real number. The degree based topological indices such as Randic index, geometric-arithmetic (GA) index and atom-bond connectivity (ABC) index are of vital importance among all topological indices. These topological descriptors significantly correlate certain physico-chemical properties of the corresponding chemical compounds. Graph theory has been found to be very useful in this area of research. The topological indices of certain interconnection and mesh derived networks are recently studied by Imran et al. [17]. In this paper, we define some new classes of networks from honeycomb networks by using basic graph operations like stellation, medial and dual of a graph. We derive analytical close formulas of general Randic index Rα(G) (for different values of α) for hexagonal and honeycomb derived networks. We also compute first Zagreb, ABC, and GA indices for these important classes of networks.

A molecular/chemical graph is hydrogen depleted chemical structure in which vertices denote atoms and edges denote the bonds. Topological descriptors are the numerical indices based on the topology of the atoms and their bonds (chemical conformation, quaternary structure). They correlate various physico-chemical properties like boiling point, enthalpy of formation, enthalpy of vaporization, Kovat’s constant etc., of various chemical compounds. Carbon nanotubes, a type of fullerene, have potential in fields such as nanotechnology, electronics, optics, materials science and architecture. The numerical parameters like inertia indices, signature and nullity attract much attention due to their diverse application in chemistry e.g., nullity of a molecular graph is related to the stability of saturated hydrocarbons.In this paper, inertia indices, signature and nullity of TUC4 C8(R) [2m-1,2n-1] nanotube are strong-minded. We conclude that the positive and negative inertia indices are equal for this nanotube and signature and nullity for this nanotube remain zero.

Among topological connectivity indices, the atom-bond connectivity (ABC) index and geometric-arithmetic (GA) index are of vital importance. The ABC index is defined as: ABC(G) = Σ uvεE(G) √ (dG(u)+dG(v)-2)/(dG(u)dG(v)), while GA(G) index also defined as follows: GA(G) = Σ uvεE(G)((2 √ dG(u)dG(v))/(dG(u)+dG(v))), where dG(u) denotes the degree of vertex u ε V (G). Recently, the fourth version of ABC index is proposed by Ghorbani et al. defined as follows: ABC4(G) = Σ uvεE(G) √ (δG(u)+δG(v)-2)/(δG(u)δG(v)). The fifth version of GA index is introduced by Graovac et al. defined as follows: GA5(G) = Σ uvεE(G)((2 √ δG(u)δG(v))/(δG(u)+δG(v))), where δu = Σ uvεE(G) dG(v). In this paper, we study the fourth atom-bond connectivity index ABC4 and fifth geometric-arithmetic index GA5 and give close formulae of these indices for HAC5C7[p,q], HAC5C6C7[p,q] and TUC4C8(R)[p,q] nanotubes and their corresponding nanotori. We also give a characterization of k-regular graphs with respect to their fifth geometric-arithmetic index.

A molecular graph is a graphical representation of a chemical structure which is constructed by using certain graph operation. Topological indices are global graph-theoretic parameters which are studied for molecular graphs and provide significant information related to physico-chemical properties of underlying chemical substances. Bipartite edge frustration is defined as the minimum number of edges whose deletion from the graph gives the bipartite spanning subgraph of given graph. Bipartite edge frustration is a topological index which is related to the chemical stability of various nanostructures such as Fullerenes. In this paper, the bipartite edge frustration of cactus chains are studied. We give an important conjecture generalizing this concept for whole family of cacti graphs at the end of the article.

In this paper, we compute fourth atom-bond connectivity indices and fifth geometric-arithmetic indices for conical graphite. We also compute atom-bond conncetivity (ABC) and geometric-arithmetic (GA) indices for these conical graphite.

In QSAR/QSPR study, physico-chemical properties and topological indices such as Randić, atom-bond connectivity (ABC) and geometric-arithmetic (GA) index are used to predict the bioactivity of chemical compounds. A topological index is actually designed by transforming a chemical structure into a numeric number. These topological indices correlate certain physico-chemical properties like boiling point, stability, strain energy etc of chemical compounds. Graph theory has found a considerable use in this area of research. The topological properties of certain networks are studied recently in [13] by Hayat and Imran (2014). In this paper, we extend this study to interconnection networks and derive analytical closed results of general Randić index Rα(G) for different values of "α" for butterfly and Benes networks. We also compute first Zagreb, ABC, and GA indices for these important classes of networks. Moreover, we construct two new classes of mesh derived networks by using some basic operations of graphs on m×n mesh networks, and then study certain topological indices for these classes of networks.

There are certain types of topological indices such as degree based topological indices, distance based topological indices and counting related topological indices etc. Among degree based topological indices, the so-called atom-bond connectivity (ABC), geometric-arithmetic (GA) are of vital importance. These topological indices correlate certain physico-chemical properties such as boiling point, stability and strain energy etc. of chemical compounds. In this paper, we compute ABC4 and GA5 indices for certain networks like silicate, chain silicate, hexagonal, oxide and honeycomb networks. The atom-bond connectivity index (ABC index) and geometric-arithmetic index (GA index) for oxide and chain silicate networks are also computed in this paper.

The elastic network model (ENM) is a widely used method to study native protein dynamics by normal mode analysis (NMA). In ENM we need information about all pairwise distances, and the distance between contacting atoms is restrained to the native value. Therefore ENM requires O(N2) information to realize its dynamics for a protein consisting of N amino acid residues. To see if (or to what extent) such a large amount of specific structural information is required to realize native protein dynamics, here we introduce a novel model based on only O(N ) restraints. This model, named the ‘contact number diffusion’ model (CND), includes specific distance restraints for only local (along the amino acid sequence) atom pairs, and semi-specific non-local restraints imposed on each atom, rather than atom pairs. The semi-specific non-local restraints are defined in terms of the non-local contact numbers of atoms. The CND model exhibits the dynamic characteristics comparable to ENM and more correlated with the explicit-solvent molecular dynamics simulation than ENM. Moreover, unrealistic surface fluctuations often observed in ENM were suppressed in CND. On the other hand, in some ligand-bound structures CND showed larger fluctuations of buried protein atoms interacting with the ligand compared to ENM. In addition, fluctuations from CND and ENM show comparable correlations with the experimental B-factor. Although there are some indications of the importance of some specific non-local interactions, the semi-specific non-local interactions are mostly sufficient for reproducing the native protein dynamics.

We study nonlinear sigma model, especially Skyrme model without twist and Skyrme model with twist: twisted Skyrmion string. Twist term, mkz, is indicated in vortex solution. Necessary condition for stability of vortex solution has consequence that energy of vortex is minimum and scale-free (vortex solution is neutrally stable to changes in scale). We find numerically that the value of vortex minimum energy per unit length for twisted Skyrmion string is 20.37 × 1060 eV/m.

A significant amount of energy is wasted by electrical appliances when they operate inefficiently either due to anomalies and/or incorrect usage. To address this problem, we present SocketWatch - an autonomous appliance monitoring system. SocketWatch is positioned between a wall socket and an appliance. SocketWatch learns the behavioral model of the appliance by analyzing its active and reactive power consumption patterns. It detects appliance malfunctions by observing any marked deviations from these patterns. SocketWatch is inexpensive and is easy to use: it neither requires any enhancement to the appliances nor to the power sockets nor any communication infrastructure. Moreover, the decentralized approach avoids communication latency and costs, and preserves data privacy. Real world experiments with multiple appliances indicate that SocketWatch can be an effective and inexpensive solution for reducing electricity wastage. © 2014 IEEE.

To understand the dynamic aspects of multispecificity of ubiquitin, we studied nine ubiquitin-ligand (partner protein) complexes by normal mode analysis based on an elastic network model. The coupling between ubiquitin and ligand motions was analyzed by decomposing it into rigid-body (external) and vibrational (internal) motions of each subunit. We observed that in total the external motions in one of the subunits largely dominated the coupling. The combination of external motions of ubiquitin and the ligands showed general trends of rotations and translations. Moreover, we observed that the rotational motions of ubiquitin were correlated to the ligand orientations. We also identified ubiquitin atomic vibrations that differentiated the orientation of the ligand molecule. We observed that the extents of coupling were correlated to the shapes of the ligands, and this trend was more pronounced when the coupling involved vibrational motions of the ligand. In conclusion, an intricate interplay between internal and external motions of ubiquitin and the ligands help understand the dynamics of multispecificity, which is mostly guided by the shapes of the ligands and the complex.

A numeric quantity which characterizes the whole structure of a graph is called a topological index. The concept of Randić X(H), atom-bond connectivity (ABC) and geometric-arithmetic (GA) topological indices were established in chemical graph theory based on vertex degrees. Later on, other versions of ABC and GA indices were introduced and some of the versions of these indices are recently designed. Dendrimers are recognized as one of the major commercially available nanoscale building blocks, large and complex molecules with well defined chemical structure. The nanostar dendrimer is a part of a new group of macroparticles that appear to be photon funnels just like artificial antennas. A k -polyomino system is a finite 2 -connected plane graph such that each interior face (also called cell) is surrounded by a regular 4k -cycle of length one. In this article, we compute ABC, GA, and Randić indices of two important families of nanostar dendrimers. We also compute fourth version of atom-bond connectivity (ABC4) index and fifth version of geometric-arithmetic (GA5) index for graphs of 1 and 2 -polyomino chains of 8 -cycles.

A new method has been developed to discriminate sand from shale, from P-wave velocity, S-wave velocity, and density values obtained from elastic seismic inversion without well control. The method, based on empirical or semiempirical principles, has been tested with well data in thick Tertiary clastic columns in the Gulf of Mexico, where the input data (compressional and shear sonic logs and bulk density) are of good quality and where there is a lithology log to verify results. The method cannot be applied to gas-bearing sands. Gas sands should be separated prior to application of the method using, for instance, the Vp/Vs values as a criterion. A preliminary discrimination of sand from shale in areas without well control is indeed a useful exploration tool. It is also very useful in pore-pressure calculations in which, ideally, only shale points should be used to determine the normal compaction trend.

In this paper, we present multi-almost periodicity of a general class of discrete-time neural networks derived from a well-known semi-discretization technique, that is, coexistence and exponential stability of 2N almost periodic sequence solutions of discrete-time neural networks subjected to external almost periodic stimuli. By using monotonicity and boundedness of activation functions, we construct 2N close regions to attain the existence of almost periodic sequence solutions. Meanwhile, some new and simple criteria are derived for the networks to converge exponentially toward 2 N almost periodic sequence solutions. As special cases, our results can extend to discrete-time analogues of periodic or autonomous neural networks and hence complement or improve corresponding existing ones. Finally, computer numerical simulations are performed to illustrate multi-almost periodicity of semi-discretizations of neural networks.

We show that a nested sequence of Cr macro-element spline spaces on quasi-uniform triangulations gives rise to hierarchical Riesz bases of Sobolev spaces Hs(Ω), 1 < s < r + 3/2, and H 0s(Ω), 1 < s < σ+ 3/2, s ∉ ℤ + 1/2, as soon as there is a nested sequence of Lagrange interpolation sets with uniformly local and bounded basis functions, and, in case of H0 s(Ω), the nodal interpolation operators associated with the macroelement spaces are boundary conforming of order σ. In addition, we provide a brief review of the existing constructions of C1 Largange type hierarchical bases. © Springer-Verlag 2014.

Counting polynomials are those polynomials having at exponent the extent of a property partition and coefficients the multiplicity/occurrence of the corresponding partition. In this paper, omega and Sadhana polynomials are computed for nanotubes. These polynomials were proposed on the ground of quasi-orthogonal cuts edge strips in polycyclic graphs. These counting polynomials are useful in the topological description of bipartite structures as well as in counting some single number descriptors, i.e. topological indices. These polynomials count equidistant and non-equidistant edges in graphs. In this paper, analytical closed formulas of these polynomials for H-Naphtalenic, TUC4C8(R)[m,n] and TUC4[m,n], nanotubes are derived.

Many proteins function by interacting with other small molecules (ligands). Identification of ligand-binding sites (LBS) in proteins can therefore help to infer their molecular functions. A comprehensive comparison among local structures of LBSs was previously performed, in order to understand their relationships and to classify their structural motifs. However, similar exhaustive comparison among local surfaces of LBSs (patches) has never been performed, due to computational complexity. To enhance our understanding of LBSs, it is worth performing such comparisons among patches and classifying them based on similarities of their surface configurations and electrostatic potentials. In this study, we first developed a rapid method to compare two patches. We then clustered patches corresponding to the same PDB chemical component identifier for a ligand, and selected a representative patch from each cluster. We subsequently exhaustively as compared the representative patches and clustered them using similarity score, PatSim. Finally, the resultant PatSim scores were compared with similarities of atomic structures of the LBSs and those of the ligand-binding protein sequences and functions. Consequently, we classified the patches into 2000 well-characterized clusters. We found that about 63% of these clusters are used in identical protein folds, although about 25% of the clusters are conserved in distantly related proteins and even in proteins with cross-fold similarity. Furthermore, we showed that patches with higher PatSim score have potential to be involved in similar biological processes.

We analyse the steady-state operation of a continuous flow bioreactor in which the biochemical reaction is governed by noncompetitive substrate inhibition (Andrews kinetics). A generalized reactor model is used in which the well-stirred bioreactor and the idealized membrane bioreactor are special cases. As generic properties of systems subject to substrate inhibition have been obtained by other authors, we discuss reaction engineering features specific to Andrews kinetics.

We present a construction of nested spaces of C 2 macro-elements of degree 5 on triangulations of a polygonal domain obtained by uniform refinements of an initial triangulation and a Powell-Sabin-12 split. © 2012 Elsevier B.V. All rights reserved.

Date hub proteins are a type of proteins that show multispecificity in a time-dependent manner. To understand dynamic aspects of such multispecificity we studied Ubiquitin as a typical example of a date hub protein. Here we analyzed 9 biologically relevant Ubiquitin-protein (ligand) heterodimer structures by using normal mode analysis based on an elastic network model. Our result showed that the self-coupled motion of Ubiquitin in the complex, rather than its ligandcoupled motion, is similar to the motion of Ubiquitin in the unbound condition. The ligand-coupled motions are correlated to the conformational change between the unbound and bound conditions of Ubiquitin. Moreover, ligand-coupled motions favor the formation of the bound states, due to its in-phase movements of the contacting atoms at the interface. The self-coupled motions at the interface indicated loss of conformational entropy due to binding. Therefore, such motions disfavor the formation of the bound state. We observed that the ligand-coupled motions are embedded in the motions of unbound Ubiquitin. In conclusion, multispecificity of Ubiquitin can be characterized by an intricate balance of the ligand-and self-coupled motions, both of which are embedded in the motions of the unbound form.

The Indian electricity sector, despite having the world’s fifth largest installed capacity, suffers from a 12.9% peaking shortage. This shortage could be alleviated, if a large number of deferrable loads, particularly the high powered ones, could be moved from on-peak to off-peak times. However, conventional Demand Side Management (DSM) strategies may not be suitable for India as the local conditions usually favor inexpensive solutions with minimal dependence on the pre-existing infrastructure. In this work, we present a completely autonomous DSM controller called the nPlug. nPlug is positioned between the wall socket and deferrable load(s) such as water heaters, washing machines, and electric vehicles. nPlugs combine local sensing and analytics to infer peak periods as well as supply-demand imbalance conditions. They schedule attached appliances in a decentralized manner to alleviate peaks whenever possible without violating the requirements of consumers. nPlugs do not require any manual intervention by the end consumer nor any communication infrastructure nor any enhancements to the appliances or the power grids. Some of nPlug’s capabilities are demonstrated using experiments on a combination of synthetic and real data collected from plug-level energy monitors. Our results indicate that nPlug can be an effective and inexpensive technology to address the peaking shortage. This technology could potentially be integrated into millions of future deferrable loads: appliances, electric vehicle (EV) chargers, heat pumps, water heaters, etc. © 1983-2012 IEEE.

Protein functions are mediated by interactions between proteins and other molecules. One useful approach to analyze protein functions is to compare and classify the structures of interaction interfaces of proteins. Here, we describe the procedures for compiling a database of interface structures and ef fi ciently comparing the interface structures. To do so requires a good understanding of the data structures of the Protein Data Bank (PDB). Therefore, we also provide a detailed account of the PDB exchange dictionary necessary for extracting data that are relevant for analyzing interaction interfaces and secondary structures. We identify recurring structural motifs by classifying similar interface structures, and we de fi ne a coarse-grained representation of supersecondary structures (SSS) which represents a sequence of two or three secondary structure elements including their relative orientations as a string of four to seven letters. By examining the correspondence between structural motifs and SSS strings, we show that no SSS string has particularly high propensity to be found interaction interfaces in general, indicating any SSS can be used as a binding interface. When individual structural motifs are examined, there are some SSS strings that have high propensity for particular groups of structural motifs. In addition, it is shown that while the SSS strings found in particular structural motifs for nonpolymer and protein interfaces are as abundant as in other structural motifs that belong to the same subunit, structural motifs for nucleic acid interfaces exhibit somewhat stronger preference for SSS strings. In regard to protein folds, many motif-speci fi c SSS strings were found across many folds, suggesting that SSS may be a useful description to investigate the universality of ligand binding modes.

Energy storage technologies that are connected to medium- or low-voltage distribution systems are referred to as Distributed Energy Storage (DES). DES are becoming more common as the storage technologies are becoming cheaper. Energy stored on the distribution system, whether it is generated by Distributed Generation (DG) or central generation units, could provide crucial services (such as load leveling, automatic generation control, smoothing fluctuations in intermittent sources, etc) to electricity suppliers. The need of the hour is to effectively utilize these distributed storage devices so as to lower operating costs while offering aforementioned services. In contemporary literature, while DES have been considered, they could only be charged/discharged from/to the grid. The current work marks a significant departure with the goal of allowing storage devices to charge each other. Such battery-to-battery energy transfer is useful for instance in scenarios when generators cannot be run for certain reasons, or that it might cause too much load on the network, if the storage devices were to be charged directly from the power grid. Simulation results on a 30-bus IEEE benchmark system validate the benefits of inter-storage charge transfers.

As the output from the solar PV systems varies significantly with technologies, designs and prevailing weather parameters, their evaluation under actual field conditions is important in identifying their real performance characteristics. In this paper, comparative performances of six different PV systems connected to a 1.2 MWp grid integrated solar farm are presented. The solar technologies considered are the single crystalline (sc-Si), poly crystalline (mc-Si), micro crystalline (nc-Si/a-Si), amorphous silicon (a-Si), Copper Indium Selenium (CIS) and Heterojunction with Intrinsic Thin Layer (HIT). Following the IEA guidelines, the array yield, capture losses, array efficiency ratio, and performance ratio were taken as the criteria for the performance comparison. Among the six different module types, the systems based on amorphous silicon and HIT offer the best performance under the tropical environment considered.

Remote sensing is a technique which demands a large amount of analysis on data which may have been captured from a variety of sources. Common sources range from aerial vehicles equipped with scanning devices to sensors attached to satellites in space missions. The data acquisition, however, is commonly subject to the interference of external factors, such as particles in the atmosphere and clouds, which may lead to noise in the data. This paper presents a technique to detect the presence of such artifacts, as observed in some digital elevation model data, and an algorithm to patch them. A case study on the second version of the ASTER GDEM shows that the proposed algorithm is effective in the detection and patching of vertical artifacts and that it can be applied to different data sets in the realm of digital elevation models.

Using the Coulomb gas method and standard methods of statistical physics, we compute analytically the joint cumulative probability distribution of the extreme eigenvalues of the Jacobi-MANOVA ensemble of random matrices in the limit of large matrices. This allows us to derive the rate functions for the large fluctuations to the left and the right of the expected values of the smallest and largest eigenvalues analytically. Our findings are compared with some available known exact results as well as with numerical simulations finding good agreement.

In this paper, by discussing parameter conditions based on properties of activation functions, we decompose state space into positively invariant sets and establish sufficient conditions for the existence of locally stable equilibria for delayed Cohen-Grossberg neural networks (CGNNs) through Cauchy convergence principle. Some new criteria are derived for ensuring equilibria (periodic orbits) to be locally or globally exponentially stable in any designated region. Finally, our results are demonstrated by four numerical simulations.

Most biological processes are described as a series of interactions between proteins and other molecules, and interactions are in turn described in terms of atomic structures. To annotate protein functions as sets of interaction states at atomic resolution, and thereby to better understand the relation between protein interactions and biological functions, we conducted exhaustive all-against-all atomic structure comparisons of all known binding sites for ligands including small molecules, proteins and nucleic acids, and identified recurring elementary motifs. By integrating the elementary motifs associated with each subunit, we defined composite motifs that represent context-dependent combinations of elementary motifs. It is demonstrated that function similarity can be better inferred from composite motif similarity compared to the similarity of protein sequences or of individual binding sites. By integrating the composite motifs associated with each protein function, we define meta-composite motifs each of which is regarded as a time-independent diagrammatic representation of a biological process. It is shown that meta-composite motifs provide richer annotations of biological processes than sequence clusters. The present results serve as a basis for bridging atomic structures to higher-order biological phenomena by classification and integration of binding site structures.

Weather models with high spatial and temporal resolutions are required for accurate prediction of meso-micro scale weather phenomena. Using these models for operational purposes requires forecasts with sufficient lead time, which in turn calls for large computational power. There exists a lot of prior studies on the performance of weather models on single domain simulations with a uniform horizontal resolution. However, there has not been much work on high resolution nested domains that are essential for high-fidelity weather forecasts. In this paper, we focus on improving and analyzing the performance of nested domain simulations using WRF on IBM Blue Gene/P. We demonstrate a significant reduction (up to 29%) in runtime via a combination of compiler optimizations, mapping of process topology to the physical torus topology, overlapping communication with computation, and parallel communications along torus dimensions. We also conduct a detailed performance evaluation using four nested domain configurations to assess the benefits of the different optimizations as well as the scalability of different WRF operations. Our analysis indicates that the choice of nesting configuration is critical for good performance. To aid WRF practitioners in making this choice, we describe a performance modeling approach that can predict the total simulation time in terms of the domain and processor configurations with a very high accuracy (< 8%) using a regression-based model learned from empirical timing data.

The Indian electricity sector, despite having the world’s fifth largest installed capacity, suffers from a 12.9% peaking shortage. This shortage could be alleviated, if a large number of deferrable loads, particularly the high powered ones, could be moved from on-peak to off-peak times. However, conventional DSM strategies may not be suitable for India as the local conditions usually favor only inexpensive solutions with minimal dependence on the pre-existing infrastructure. In this work, we present nPlug, a smart plug that sits between the wall socket and deferrable loads such as water heaters, washing machines, and electric vehicles. nPlugs combine real-time sensing and analytics to infer peak periods as well as supply-demand imbalance and reschedule attached appliances in a decentralized manner to alleviate peaks whenever possible. They do not require any manual intervention by the end consumer nor any enhancements to the appliances or existing infrastructure. Some of nPlug’s capabilities are demonstrated using experiments on a combination of synthetic and real data collected from plug-level energy monitors. Our results indicate that nPlug can be an effective and inexpensive technology to address the peaking shortage. © 2012 ACM.

Comparison and classification of protein structures are fundamental means to understand protein functions. Due to the computational difficulty and the ever-increasing amount of structural data, however, it is in general not feasible to perform exhaustive all-against-all structure comparisons necessary for comprehensive classifications. To efficiently handle such situations, we have previously proposed a method, now called GIRAF. We herein describe further improvements in the GIRAF protein structure search and alignment method. The GIRAF method achieves extremely efficient search of similar structures of ligand binding sites of proteins by exploiting database indexing of structural features of local coordinate frames. In addition, it produces refined atom-wise alignments by iterative applications of the Hungarian method to the bipartite graph defined for a pair of superimposed structures. By combining the refined alignments based on different local coordinate frames, it is made possible to align structures involving domain movements. We provide detailed accounts for the database design, the search and alignment algorithms as well as some benchmark results.