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Introduction: Respiratory exchange ratio (RER) is the ratio between produced CO2 and used O2 for body metabolism. It indicates the type of fuel that is metabolized in the body. This study aimed to measure and compare the RER in non-obese and obese sedentary young adults in rest, moderate-intensity, and vigorous-intensity exercise. Methods: This cross-sectional study was conducted with 23 non-obese and 24 obese sedentary young adults. Resting RER was measured with 12-h fasting after 15-min rest with an automated gas analyzer. Then, RER was measured during steady moderate-intensity and vigorous-intensity exercise on a cycle ergometer. RER was compared between males and females, non-obese and obese in resting, moderate-intensity, and vigorous-intensity exercise by t-test. Results: The Mean age of the non-obese and obese groups was 19.35±1.11 and 19.79±0.78 years, respectively. Males showed higher RER (in resting and moderate-intensity exercise) than females. In comparison to non-obese group, the obese group showed higher RER in resting (0.802±0.018 versus 0.821±0.022, P=0.001), moderate-intensity exercise (0.812±0.013 versus 0.83±0.02, P<0.001), and vigorous-intensity exercise (0.853±0.43 versus 0.914±0.032, P<0.001). Concerning resting value, RER significantly increased during moderate- and vigorous-intensity exercise in both the non-obese and obese groups. Conclusion: Obese young adults use relatively more carbohydrates as fuel than non-obese in both resting conditions and during exercise. When the intensity of exercise increased, both obese and non-obese showed higher RER which indicates that sedentary young adults use relatively more carbohydrates as fuel in the higher grade of exercise. [ABSTRACT FROM AUTHOR]

The process parameters involved in electron beam welding have major influences on spiking and penetration efficiency of the joint. In addition to this, the input–output relationships of electron beam welding are nonlinear and complex in nature. Therefore, adaptive neuro-fuzzy inference system (ANFIS)-based input–output modeling had been attempted to predict the spiking severity in electron beam welded joints. Swarm-based optimization algorithms, like grey wolf optimizer, particle swarm optimization, and bonobo optimizer (BO), were used for optimizing the ANFIS architecture and predicting the response precisely. Multi-objective bonobo optimization (MOBO), Multi-objective grey wolf optimization, and Multi-objective particle swarm optimization algorithms had been used for solving the conflicting multi-objective criteria problems associated with the study. The input process parameters were accelerating voltage, beam current, scan speed, focusing distance, and beam oscillation parameters, whereas mean weld-bead penetration and its standard deviation were considered as the responses of the system. The irregular penetration, that is, spiking was expressed in terms of the standard deviation of weld penetration. The accuracy level of optimization and modeling had been tested with some test cases obtained through the real experiments. MOBO had shown the better accuracy in predicting the optimized set of input parameters, which could satisfy both the spiking and penetration criteria, while BO-ANFIS had shown the superior efficiency in predicting the response with minimum error. [ABSTRACT FROM AUTHOR]

The resistive switching phenomenon is attributed to local formation and rupture of conductive filaments (CF), however some aspects of the switching mechanism still need wider consensus. The origin of resistance contribution to low resistance state (LRS) and high resistance state (HRS) is although well known, the origin of capacitive contribution to the memory state of resistive random access memory device (RRAM) is ambiguous. Here we report impedance spectroscopic studies carried on Cu/TiO 2 /Pt devices to address the origin of resistive and capacitive contribution, where the effect of DC bias voltage, reset stop voltage and set compliance current on the impedance of RRAM memory states were investigated in detail. The studies revealed that the capacitive contribution was dominated by the surrounding TiO 2 bulk and contrary to existing knowledge, gap formed owing to ruptured CF has negligible role. These studies also reaffirmed the origin of the resistive contribution to the HRS and LRS state, which was dictated by the ruptured gap and connected CF, respectively. Results of this study may be significant towards improving the switching time and operating frequency performance of futuristic memory, RF switch and neuromorphic computing applications of RRAM devices. [ABSTRACT FROM AUTHOR]

We have synthesised tungsten metal encapsulated WO3 nanoparticles by a straightforward sol–gel method and current–voltage (I-V) characteristics have been analysed to show the benefits of the metal–metal oxide. The I-V characteristic of these nanoparticles displays two discrete negative resistance (NR) areas together with the production of metal (W) filaments following the current-controlled negative differential resistance (CC-NDR) model. These materials have an extraordinary high-output ac power supplying capacity with a peak-to-voltage ratio (PVR) of 9.65 in the voltage range of 0.45–0.7 V. Their special characteristics render them ideal materials for new-generation oscillating devices. On the other hand, in order to tune charge-storing capacity, increase energy density and customise the electronic circuital space, we have attempted to adjust interfacial-dipolar polarisation and electron trapping by modulating grain-grain boundary interfaces through the voltage-dependent electrical study. Here we have also investigated the effects of temperature and voltage fluctuations on the I-V characteristics, impedance spectroscopy or phase angle and assessed how the relaxation dynamics and charge transportation changed under various environmental conditions. Additionally, the orientation of the polar PVA and the flexible composite films' luminance spectra are amended by adding hydrophilic W-WO3 nanoparticles and modifying the excitation wavelength (280–320 nm). The linear relationship between the luminance spectra and excitation wavelength (280–320 nm) of the composite films suggests their usefulness as UV-B detectors. Therefore, this foundational research highlighted multifunctional nanoparticles and flexible organic materials paving towards commercialization. [ABSTRACT FROM AUTHOR]

High dimensionality of input dataset is an important issue in machine learning. Though there are a few effective ways of dimensionality reduction, none of them, other than feature selection, preserve the original features of the input dataset. Feature selection assesses relevance of features along with their potential redundancy for dimensionality reduction. This paper proposes a first of its kind fuzzy graph based technique for measuring feature relevance and redundancy. The proposed technique addresses the uncertainty in interpretation of feature relevance and redundancy by defining a fuzzy set based formulation of feature relevance and redundancy. Superior performance of the proposed algorithm is illustrated by simulation experiments with 20 benchmark datasets. The proposed algorithm has demonstrated an average feature reduction of 86% along with a 10% improvement in average classification accuracy compared to the state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]

The transcription factors, such as activators and repressors, can interact with the promoter of gene either in a competitive or non-competitive way. In this paper, we construct a stochastic model with non-competitive transcriptional regulatory architecture and develop an analytical theory that re-establishes the experimental results with an improved data fitting. The analytical expressions in the theory allow us to study the nature of the system corresponding to any of its parameters and hence, enable us to find out the factors that govern the regulation of gene expression for that architecture. We notice that, along with transcriptional reinitiation and repressors, there are other parameters that can control the noisiness of this network. We also observe that, the Fano factor (at mRNA level) varies from sub-Poissonian regime to super-Poissonian regime. In addition to the aforementioned properties, we observe some anomalous characteristics of the Fano factor (at mRNA level) and that of the variance of protein at lower activator concentrations in the presence of repressor molecules. This model is useful to understand the architecture of interactions which may buffer the stochasticity inherent to gene transcription. [ABSTRACT FROM AUTHOR]

The uncitedness of twelve Indian physics and astronomy journals over twelve years (2009-2020) time span is analysed here. Besides Uncitedness Factor (UF), three other indicators are discussed, viz., Time-normalized Citation per paper (CY), H-core Density (HD) and Time-normalised H-index (TH). The journal-wise variational patterns of these four indicators, i.e., UF, CY, HD and TH and the relationships of UF with the other three indicators are analysed. The calculated numerical values of these indicators are observed to formulate seven hypotheses, which are tested by the F-Test method. The average annual rate of change of uncited paper is found to be 67% of the total number of papers. The indicator CY is found temporally constant. The indicator HD is found to be nearly constant journal-wise over the entire time span, while the indicator TH is found to be nearly constant for all the journals. The UF inversely varies with CY and TH for the journals and directly varies with TH over the years. Except for a few Indian journals in physics and astronomy, the majority of the other journals face the situation of uncitedness. The uncitedness of Indian journals in this field is higher by 12% as compared to foreign journals in the same field, which indicates a possible poor circulation of the journals. [ABSTRACT FROM AUTHOR]

Summary: Present work successfully demonstrates the synthesis of ion diffused ant colony‐like porous carbon structure (PSWC) with high surface roughness from seaweed using a facile pre‐carbonization NaCl treatment, followed by carbonization at 800°C. X‐ray photoelectron spectroscopy and energy‐dispersive X‐ray spectroscopy studies confirm the retention of natural redox groups such as pyrrolic N, pyridinic N, oxidized sulfur, carboxyl, Fe3+, and Zn2+ and the diffusion of Na+ and Cl− ions in the PSWC. The electrochemical analysis of PSWC reveals that NaCl treatment further enhances the performance, and the redox groups and transition metal ions facilitate the faradic battery‐type energy storage with an excellent specific capacitance of 904.44 F g−1 at 1 A g−1 of current density in a classic three‐electrode system. The fabricated polyvinyl alcohol‐potassium hydroxide gel electrolyte‐based quasi‐solid‐state asymmetric supercapacitor device exhibits good energy density and power density of 52.15 Wh kg−1 and 362.14 W Kg−1, respectively with a superior cyclic life (98.94% capacitance retention after 10 000 cycles). The overall eco‐friendliness, low cost, availability, facile synthesis process, sustainability, facile upscale synthesis, and excellent electrochemical properties provide a potential application of PSWC in advanced energy storage systems. [ABSTRACT FROM AUTHOR]

Staphylococcus aureus infection is a leading cause of mortality and morbidity in community, hospital and live-stock sectors, especially with the widespread emergence of methicillin-resistant S. aureus (MRSA) strains. To identify new drug molecules to treat MRSA patients, we have undertaken to search essential proteins that are indispensable for their survival but non-homologous to human host proteins. The current study utilizes a subtractive genome and proteome approach to screen the possible therapeutic targets against S. aureus USA300. Bacterial essential genes are obtained from the DEG database and are compared to avoid cross-reactivity with human host genes. In silico analysis shows 198 proteins that may be considered as therapeutic candidates. Depending on their sub-cellular localization, proteins are grouped as either vaccine or drug targets or both. Extracellular proteins such as cell division proteins (Q2FZ91, Q2FZ95), penicillin-binding proteins (Q2FZ94, Q2FYI0) of the bacterial cell wall, phosphoglucomutase (Q2FE11) and lipoteichoic acid synthase (Q2FIS2) are considered as vaccine targets, and their epitopes have been mapped. Altogether, 53 drug targets are identified, which have shown similarity with the drug targets available in the DrugBank database. Predicted drug targets belong to the common metabolic pathways of MRSA, such as fatty acid biosynthesis, folate biosynthesis, peptidoglycan biosynthesis, ribosome, etc. Protein–protein interaction analysis emphasizing peptidoglycan biosynthesis reveals the connection between penicillin-binding proteins, mur-family proteins and FemXAB proteins. In this study, staphylococcal FemA protein (P0A0A5) is subjected to structure-based virtual screening for the drug repurposing approach. There are 20 residues missing in the crystal structure of FemA, and 12 of these residues are located at the catalytic site. The missing residues are modelled, and stereochemistry is checked. FDA approved drugs available in the DrugBank database have been used in virtual screening with FemA in search of potential repurposed molecules. This approach provides us with 10 drugs that may be used in the treatment of methicillin-resistant staphylococcal mediated diseases. AutoDock 4.2 is used for in silico screening and shows a comparable inhibition constant (Ki) for all 10 FDA-approved drugs towards FemA. Most of these drugs are used in the treatment of various cancers, migraines and leukaemia. Protein–drug interaction analysis shows that the drugs mostly interact with hydrophobic residues of FemA. Moreover, Tyr328 and Lys383 contribute largely to hydrogen bondings during interactions. All interacting amino acids that bind to the drugs are part of the active site cavity of FemA. [ABSTRACT FROM AUTHOR]

Purpose – The study found on the University of Burdwan physics department faculties and research scholars’ information needs and information seeking behaviour. The purpose is to find out the information needs, source use, satisfaction level, and improvement needs for library infrastructure, sources and services. Methodology – In this information needs and seeking behaviour study, two sets online questionnaire has been developed to achieve the objective. Only physics faculties and regular registered research scholars (session 2011 – 2020) in the University of Burdwan have been selected as main respondents. Data has been collected using Google form. Online questionnaire have been served through email to all the physics faculty members and one hundred five registered research scholars in the University of Burdwan. The response rates from respondents are 47.62% (faculty) and 64.86% (scholars). The ratio of male – female respondents’ of physics faculty members and scholars are 9:1 and 38:10 respectively. Findings – The study depicted the physics department faculty members and research scholars’ information needs and information seeking behaviour at the University of Burdwan. Information need and information seeking behaviour of physics department faculty members and regular research scholars was in-depth understanding of the major roles on overall university library development in the angle from the students; purview on Burdwan university library. Originality/value – The current finding are original and reflected latest observation on the physics department faculties and research scholars’ information-seeking behaviour in the University of Burdwan. The study benefits information Seekers and as well as library policy makers who provide the library collection development and services to the users of the University. [ABSTRACT FROM AUTHOR]

This paper traces one hundred and twenty years journey of Indian physics and astronomy journals. Of the 122 journals that have been published since 1902, 36 journals have ceased publication. The oldest physics related article was published in 1788 in Asiatick Researches, the first Indian research periodical. The oldest Indian astronomy journal Publications of the Maharaja Takhtasingji Observatory came into being in 1902 from Pune and ceased in 1912. The oldest Indian physics journal Bhoutika Kalanidhi or The Treasury of the Physical Sciences started in the year 1911 from Madras (present-day Chennai) and ceased in 1919. In all, 53% of journals belong to broad science discipline but publish articles on physics and astronomy regularly along with other major science disciplines followed by 35% and 12% journals strictly belong to the subject areas, physics, and astronomy respectively. It is observed that nearly 50% of journals are indexed by the Indian Citation Index, while 20% of journals are indexed by the Indian Citation Index, Scopus, and Web of Science. Also, 30% of journals are not indexed by any citation database. In the 120 year period, the highest number of seven journals came into being in the year 2012. [ABSTRACT FROM AUTHOR]

COVID-19 continues to have catastrophic effects on the lives of human beings throughout the world. To combat this disease it is necessary to screen the affected patients in a fast and inexpensive way. One of the most viable steps towards achieving this goal is through radiological examination, Chest X-Ray being the most easily available and least expensive option. In this paper, we have proposed a Deep Convolutional Neural Network-based solution which can detect the COVID-19 +ve patients using chest X-Ray images. Multiple state-of-the-art CNN models—DenseNet201, Resnet50V2 and Inceptionv3, have been adopted in the proposed work. They have been trained individually to make independent predictions. Then the models are combined, using a new method of weighted average ensembling technique, to predict a class value. To test the efficacy of the solution we have used publicly available chest X-ray images of COVID +ve and –ve cases. 538 images of COVID +ve patients and 468 images of COVID –ve patients have been divided into training, test and validation sets. The proposed approach gave a classification accuracy of 91.62% which is higher than the state-of-the-art CNN models as well the compared benchmark algorithm. We have developed a GUI-based application for public use. This application can be used on any computer by any medical personnel to detect COVID +ve patients using Chest X-Ray images within a few seconds. [ABSTRACT FROM AUTHOR]

This paper presents a review of 159 bibliometric studies on Indian physics and astronomy research output. The distribution of the 159 papers from1964 to 2020, contributing authors and specific subject domains are analysed. It is found that current research topics of physics and astronomy are hardly selected for the bibliometric study. A few papers incorporate currently relevant aspects of bibliometric analysis to carry out the studies. Both facets, i.e., bibliometrics and physics & astronomy as tool and subject respectively, need to be focussed upon as per the requirement and relevance of time. [ABSTRACT FROM AUTHOR]

Bloom’s taxonomy has been utilized in many brunches of disciplines and several user and nonuser study has been conducted by researchers to find out the reasons of degradation of library usage. But the application of Bloom’s taxonomy in elementary education in order to flourish the reading habit and library usage has not been done much. This paper outlines the lacunas of elementary education systems in India to indicate the primary deficiency of ability to make a library-oriented community and listing the antecedents of learning to read as well as draws a relationship model between education and library system and a symbiosis model among elementary education, library usage and Bloom’s Taxonomy have been given. [ABSTRACT FROM AUTHOR]

Purpose - The study examines the aspects of information needs and information seeking behaviour of faculties and research scholar of the mathematics departments including methods applied for finding data. The academic status and research field of users with their information seeking behaviour was investigated. Methodology - Data has been collected usingonline questionnaire survey from faculties and regular research scholars of the Department of Mathematics under the University of Burdwan faculties (80 per cent response rate) and research scholars (response rate 61.29%) participated in the online Google form survey. Findings - The study reveals the comparisonamong regular faculties and Regular Research scholars of mathematics departments under the university of Burdwan in terms of information needs and information seeking behaviour, enlightened the need for reinvestigating the quality of library infrastructure and services within the disciplinespecific for a deeper understanding of the information behaviour of faculties and research scholars in mathematics departments under the university of Burdwan. Originality/value - The study is the first study to deeply investigate the similarities of information-seeking behaviour of faculties and research scholar in mathematics departments under the University of Burdwan. It is also an up-to-date account of information needs and information seeking behaviour of faculties and research scholarsin mathematics department of the University of Burdwan. [ABSTRACT FROM AUTHOR]

SS 201 had been reported as a good substitute for SS304 without any significant compromise in performance. However, modeling EBW process using an efficient tool like adaptive neuro-fuzzy inference system (ANFIS) and use of multi-objective optimization to optimize its performance are not reported yet. Thus, the present study employed ANFIS models tuned by genetic algorithm, particle swarm optimization, gray wolf optimizer, and bonobo optimizer (BO) to predict weld attributes during EBW of SS201 as a function of input process parameters. Among the developed models, ANFIS tuned by BO was seen to yield the best prediction accuracy. In multi-objective optimization (MOO), the two conflicting goals were to minimize secondary dendritic arm spacing and maximize Vicker's hardness number simultaneously. In MOO, some interesting facts were observed, such as the fixed input parameter of power (P) as 3200-W and squeezed experimental range for the welding speed (S). [ABSTRACT FROM AUTHOR]

Genetic algorithm (GA) is used to solve a variety of optimization problems. Mutation operator also is responsible in GA for maintaining a desired level of diversity in the population. Here, a directional mutation operator is proposed for real-coded genetic algorithm (RGA) along with a directional crossover (DX) operator to improve its performance. These evolutionary operators use directional information to guide the search process in the most promising area of the variable space. The performance of an RGA with the proposed mutation operator and directional crossover (DX) is tested on six benchmark optimization problems of different complexities, and the results are compared to that of the RGAs with five other mutation schemes. The proposed IRGA is found to outperform other RGAs in terms of accuracy in the solutions, convergence rate, and computational time, which is established firmly through statistical analysis. Furthermore, the performance of the proposed IRGA is compared to that of a few recently proposed optimization algorithms. The proposed IRGA is seen to yield the superior results compared to that of the said techniques. It is also applied to solve five constrained engineering optimization problems, where again, it has proved its supremacy. The proposed mutation scheme using directional information leads to an efficient search, and consequently, a superior performance is obtained. [ABSTRACT FROM AUTHOR]

Herein, diode characteristics of n‐MgxZn1−xO/p‐Si heterojunctions grown by pulsed laser deposition at different oxygen ambient pressures are investigated. It is found that the heterojunctions grown at lower oxygen growth pressure of 1.0 × 10−2 mbar and below do not show rectifying diode‐like behavior, whereas those grown at higher oxygen pressures at and above 2.5 × 10−2 mbar exhibit perfect diode‐like rectifying characteristics. The diode characteristics are found to improve significantly with increasing oxygen ambient pressure during the growth of MgxZn1−xO film. The current–voltage measurements show that the n‐MgxZn1−xO/p‐Si heterojunction diode grown at a higher oxygen ambient pressure of ≈1.0 × 10−1 mbar has the lowest reverse saturation current of ≈19 nA and highest rectification ratio of ≈1.4 × 104. The capacitance–voltage measurements reveal that the depletion layer width of heterojunction diodes increases manifold with increasing oxygen ambient pressure during the growth of MgxZn1−xO, which is understood in terms of decrease in carrier concentrations in the MgxZn1−xO thin films grown at higher oxygen ambient pressures. The n‐MgxZn1−xO/p‐Si heterojunction diodes, grown at high oxygen ambient pressures, with low reverse saturation current, high rectification ratio, and large depletion width may have potential application in wide‐bandgap nanoelectronic devices and UV enhanced photodetectors. [ABSTRACT FROM AUTHOR]

Feature selection is a critical research problem in data science. The need for feature selection has become more critical with the advent of high-dimensional data sets especially related to text, image and micro-array data. In this paper, a graph-theoretic approach with step-by-step visualization is proposed in the context of supervised feature selection. Mutual information criterion is used to evaluate the relevance of the features with respect to the class. A graph-based representation of the input data set, named as feature information map (FIM) is created, highlighting the vertices representing the less informative features. Amongst the more informative features, the inter-feature similarity is measured to draw edges between features having high similarity. At the end, minimal vertex cover is applied on the connected vertices to identify a subset of features potentially having less similarity among each other. Results of the experiments conducted with standard data sets show that the proposed method gives better results than the competing algorithms for most of the data sets. The proposed algorithm also has a novel contribution of rendering a visualization of features in terms of relevance and redundancy. [ABSTRACT FROM AUTHOR]

In this work, a graph-based approach has been adopted for feature selection in case of high-dimensional data. Feature selection intends to identify an optimal feature subset to solve the given learning problem. In an optimal feature subset, only relevant features are selected as “members” and features that have redundancy are considered as “non-members”. This concept of “membership” and “non-membership” of a feature to an optimal feature subset has been represented by a strong intuitionistic fuzzy graph. The algorithm proposed in this work at first maps the feature set of the data as the vertex set of a strong intuitionistic fuzzy graph. Then the association between features represented as an edge-set is decided by the degree of hesitation between the features. Based on the feature association, the Strong Intuitionistic Fuzzy Feature Association Map (SIFFAM) is developed for the datasets. Then a sub-graph of SIFFAM is derived to identify features with maximal non-redundancy and relevance. Finally, the SIFFAM based feature selection algorithm is applied on very high dimensional datasets having features of the order of thousand. Empirically, the proposed approach SIFFAM based feature selection algorithm is found to be competitive with several benchmark feature selection algorithms in the context of high-dimensional data. [ABSTRACT FROM AUTHOR]

Introduction: Neonatal sepsis is a clinical syndrome characterised by signs and symptoms of infection with or without accompanying bacteraemia in the first month of life. It is responsible for about 30-50% of the total neonatal deaths in developing countries. Neonatal sepsis can be divided into two sub-types depending upon whether the onset of symptoms is within the first 72 hours of life (Early Onset Neonatal Sepsis) or after 72 hours of life (Late Onset Neonatal Sepsis). Meningitis is an important complication of late onset neonatal sepsis. Method: This was hospital based prospective observational study conducted among the neonates admitted with diagnosis of late onset neonatal sepsis in Neonatal Intermediate Care Unit (NIMCU) and Neonatal Intensive Care Unit (NICU) of a tertiary care referral centre in Kathmandu, Nepal from July 2016 to June 2017. The objective of this study was to evaluate the importance of performing lumbar puncture in neonates with LONS. Results: 16.8% neonates with late onset neonatal sepsis were found to have meningitis. Among the neonates with meningitis C reactive protein was positive in 57.2% and negative in 42.8%. Among the cases with abnormal CSF findings, blood culture was sterile in 85% cases and organism was isolated 15% cases. In 88.8% cases with positive blood culture, no meningitis was detected. Lumbar puncture was traumatic in one neonate (0.8%) in first attempt. Apart from this no other complication of performing lumbar puncture was noted. Conclusion: Lumbar puncture and CSF examination is mandatory in all cases with late-onset sepsis. [ABSTRACT FROM AUTHOR]

This study is intended to define the Free Flow Speed (FFS) ranges of urban street classes and speed ranges of Level of Service (LOS) categories. In order to accomplish the study FFS data and average travel speed data were collected on five urban road corridors in the city of Mumbai, India. Mid-sized vehicle (car) mounted with Global Positioning System (GPS) device was used for the collection of large number of speed data. Self-Organizing Tree Algorithm (SOTA) clustering method and five cluster validation measures were used to classify the urban streets and LOS categories. The above study divulges that the speed ranges for different LOS categories are lower than that suggested by Highway Capacity Manual (HCM) 2000. Also it has been observed that average travel speed of LOS categories expressed in percentage of free flow speeds closely resembles the percentages mentioned in HCM 2010. [ABSTRACT FROM AUTHOR]

This paper aims to develop a simulation model for heterogeneous traffic using cellular automata (CA). A detailed description of the developed CA model used to simulate heterogeneous traffic is presented. Heterogeneous traffic comprises of vehicles of different static and dynamic characteristics. Therefore, the developed model should be capable enough to include the characteristics of different types of vehicles. The results of simulation depict that not only the model includes heterogeneous traffic characteristics but real traffic behavior is also taken care of. The developed model is calibrated and validated using distance headway–speed relationship obtained from field data. [ABSTRACT FROM AUTHOR]

We deal with multi-objective optimization problems in various fields and in some of them, the objectives are found to be conflicting in nature. We obtain multiple optimal or near-optimal solutions of the problem using a multi-objective evolutionary algorithm (MOEA). In this study, an approach is proposed for enhancing the use of MOEA to establish important input–output relationships of some manufacturing processes. In the proposed approach, after getting an initial set of Pareto-front data points through MOEA, the trade-off solutions are used to train a neuro-fuzzy system (NFS) utilizing an EOA. This trained NFS is then used to get a modified Pareto-front and the modified trade-off solutions are clustered using different clustering algorithms. These clustered solutions are then analyzed to establish the relationships among decision variables and objectives. These principles will surely enrich the knowledge of designers and inspire them to apply this approach for a broad range of practical problems. The data related to two different engineering problems are used to show the applicability of the proposed approach. • A novel approach for capturing fuzziness of the data related to manufacturing process. • Fuzziness of the experimental data has been modeled using neuro-fuzzy system (NFS). • Input–output relationships are determined through NFS-based multi-objective optimization. • Performance of the developed approach has been tested on two problems. [ABSTRACT FROM AUTHOR]

Phosphatidyl-myo-inositol mannosides (PIMs), Lipomannan (LM), and Lipoarabinomannan (LAM) are essential components of the cell envelopes of mycobacteria. At the beginning of the biosynthesis of these compounds, phosphatidylinositol (PI) is mannosylated and acylated by various enzymes to produce Ac1/2PIM4, which is used to synthesize either Ac1/2PIM6 or LM/LAM. The protein PimE, a membrane-bound glycosyltransferase (GT-C), catalyzes the addition of a mannose group to Ac1PIM4 to produce Ac1PIM5, using polyprenolphosphate mannose (PPM) as the mannose donor. PimE-deleted Mycobacterium smegmatis (Msmeg) showed structural deformity and increased antibiotic and copper sensitivity. Despite knowing that the mutation D58A caused inactivity in Msmeg, how PimE catalyzes the transfer of mannose from PPM to Ac1/2PIM4 remains unknown. In this study, analyzing the AlphaFold structure of PimE revealed the presence of a tunnel through the D58 residue with two differently charged gates. Molecular docking suggested PPM binds to the hydrophobic tunnel gate, whereas Ac1PIM4 binds to the positively charged tunnel gate. Molecular dynamics (MD) simulations further demonstrated the critical roles of the residues N55, F87, L89, Y163, Q165, K197, L198, R251, F277, W324, H326, and I375 in binding PPM and Ac1PIM4. The mutation D58A caused a faster release of PPM from the catalytic tunnel, explaining the loss of PimE activity. Along with a hypothetical mechanism of mannose transfer by PimE, we also observe the presence of tunnels through a negatively charged aspartate or glutamate with two differently-charged gates among most GT-C enzymes. Common hydrophobic gates of GT-C enzymes probably harbor sugar donors, whereas, differently-charged tunnel gates accommodate various sugar-acceptors. [ABSTRACT FROM AUTHOR]

AbstractIn this study, a very recently developed intelligent algorithm called the self-adaptive bonomo optimizer (SABO) algorithm is implemented for the size and shape optimizations of the truss structures with the multiple frequency constraints. The bonomo optimizer (BO) algorithm is a recently developed metaheuristic optimization algorithm that imitates the social behavior and reproductive schemes of the bonobos and this algorithm is successfully applied to solve some challenging and highly nonlinear optimization problems. On the other hand, the BO algorithm suffers from the poor exploration and prematurely converges to the non-optimal solutions, especially when dealing with the multi-dimensional optimization problems. In order to overcome these shortcomings, an improved version of this algorithm, the so-called self-adaptive bonomo optimizer (SABO) algorithm, is utilized to optimize the truss structures subjected to the design constraints. The objective of this study is to minimize the weight of the truss structures with the multiple frequency constraints. Five well-known benchmark problems are considered to verify the robustness and reliability of the SABO algorithm. The design results obtained by the SABO algorithm are compared with those previously reported in the literature. [ABSTRACT FROM AUTHOR]

Search-based methods that use matrix- or vector-based representations of the dataset are commonly employed to solve the problem of feature selection. These methods are more generalized and easy to apply. Recently, a set of algorithms have started using graph-based representation of the dataset instead of the traditional representations. These methods require additional modelling as the dataset needs to be represented as a graph. However, graph-based methods help in visualizing inter-feature relationship based on which graph-theoretic principles can be applied to identify good-quality feature subsets. A combination of the graph-based representation with traditional search techniques has the potential to increase model performance as well as interpretability. As per literature study, there is hardly any method which combines these approaches. In this paper, we have proposed a feature selection algorithm, which represents the dataset as a graph and then uses maximal independent sets and minimal vertex covers to improve traditional hill climbing search. The proposed method produces statistically significant improvement over (i) hill climbing, (ii) standard search-based methods and (iii) pure graph-based methods. [ABSTRACT FROM AUTHOR]

Genetic algorithm (GA) is one of the most widely used meta-heuristic optimization tools to solve a variety of problems. It is a powerful tool for global optimization. However, like other heuristic optimization techniques, it has a probabilistic guarantee to reach the globally optimum solution in a finite number of generations. In addition, a GA suffers from the poor local search capability and hence, it is slow in convergence. To overcome these disadvantages of a GA, there had been a lot of attempts made by several researchers using different techniques. One of such techniques is the restart strategy for a GA. This strategy is nothing but to start with a new population of solutions of the GA, whenever it is unable to find any better quality of solution or it satisfies some conditions pre-specified by the user. There are a few restart strategies available in the literature with their own merits and demerits. In this paper, a novel restart strategy with elitism has been proposed. It consists of mainly three different conditions, and if any of these conditions is fulfilled, the algorithm gets restarted. The proposed restart strategy has been designed in such a way that a proper balance between the exploration and exploitation can be maintained during the search. In addition, the proposed restart scheme is able to detect the premature convergence situation of a GA and it triggers out a restart of the algorithm to avoid such situation. To measure the performance of a real-coded genetic algorithm (RCGA) with the proposed restart strategy, two sets of experiments have been done on different test functions, and the results are compared with that of the RCGAs with other restart strategies available in the literature. From the experiments, it is clear that the RCGA with the proposed restart strategy is able to yield the better results compared to others. [ABSTRACT FROM AUTHOR]

Extensive research is being conducted worldwide to design and develop novel high-performance electrodes for supercapacitors (SCs) being a viable alternative to fossil fuels, dealing with the challenges of looming energy crisis and environmental issues globally. Herein, the design and synthesis of novel binder-free Cu x Fe 3-x Se 4 @carbon cloth (CFS@CC) nanoheterostructure array electrode materials with tunable copper (Cu)/iron (Fe) stoichiometric ratios are demonstrated via a one-step room-temperature chronoamperometric (potentiostatic) electrodeposition process and their electrochemical characteristics as a promising faradaic negative electrode for SCs are explored systematically. The effect of Cu/Fe stoichiometric ratios on the morphological property and electrochemical performance of different CFS@CC array electrodes is thoroughly investigated to realize the sufficiently reaping synergistic benefits of Cu and Fe ions. Moreover, following a kinetic matching strategy, the optimized CFS@CC arrays as a negative electrode are assembled with the faradaic Ni 3 Se 2 /NiSe 2 @CC nanosheet arrays as a positive electrode to fabricate a novel asymmetric supercapacitor (ASC) device (Ni 3 Se 2 /NiSe 2 @CC//CFS-1.5@CC) which is operable in a large and stable potential window of 1.6 V and exhibits a high energy density of 84.8 Wh kg−1 at a power density of 664 W kg−1 with an excellent long-term electrochemical cycling stability. Some real-life applications of the as-fabricated ASC device are displayed to ensure its practicality. [Display omitted] • Faradaic Cu x Fe 3-x Se 4 nanoheterostructure arrays are explored as a negative electrode. • The optimized Cu x Fe 3-x Se 4 electrode exhibits a specific capacity of 317 mAh g−1. • An ASC device is fabricated with Ni 3 Se 2 /NiSe 2 @CC nanosheet arrays as a positive electrode. • The ASC device shows a high energy density of 84.8 Wh kg−1 at 664 W kg−1 of power density. • The practicality of the ASC device is demonstrated by powering electronic components. [ABSTRACT FROM AUTHOR]

Dynamics of metro coach is complex with frequent acceleration, braking, sharp turns and gradients. Due to sharp turns and twists in track, metro coaches are more prone to the derailment, frictional energy loss and wear. Since contact parameters are difficult to obtain experimentally and are time consuming to determine even computationally through multibody dynamics simulations, in this work, artificial neural network (ANN) and recurrent neural network (RNN) models are used to predict rail-wheel contact parameters. The determined parameters include contact forces, derailment ratio, frictional power, contact location and contact area. These models can be used for reducing derailment tendency, wheel wear and energy consumption. To tackle local extreme values, four meta-heuristic techniques namely Improved Real-coded Genetic Algorithm (IRGA), Success History based Adaptive Differential Evolution (SHADE), Bonobo Optimizer (BO) and Grey Wolf Optimizer (GWO) algorithms are used to optimize the ANN and RNN models. During training, inputs and outputs to the machine learning techniques are generated from a multibody dynamics model built in commercial software Simpack. The multibody dynamics model used is validated using instrumented field trials. Mean absolute percentage error (MAPE) is used for evaluating the performance of the machine learning techniques. Results demonstrate that SHADE is the best optimizer among the four meta-heuristic techniques considered. MAPE in tests, for SHADE-ANN and SHADE-RNN are found to be less than 7%. The developed machine learning models, particularly SHADE-RNN, can be used for onboard monitoring and can help the pilots in running the trains safely and efficiently. • Rail-wheel contact parameters are predicted using ANN and RNN models. • Four meta-heuristic algorithms are used as optimizers for neural networks. • A multibody dynamics model is used for generating training and test data. • Instrumented field trail is used to validate multibody dynamics model. • SHADE algorithm is found to be the best optimizer. [ABSTRACT FROM AUTHOR]

This study examines the effect of Nwd cycles on unconfined compressive strength (UCS), pH, electrical conductivity (EC), mass loss (ML) of treated sapric, fibric and hemic peat. The two types of rice husk ash (RHA) based geopolymers are formed by adding two different sources of extra aluminium as pure Al2O3, referred to as G1, and bauxite referred to as G2. For comparison, ordinary Portland cement was selected as a control sample. From the results, the UCS of geopolymer treated peats show more strength than cement treated peats because the hydrotalcite phases of geopolymer fill the voids more efficiently. However, the rate of decrement of UCS in both geopolymer treated peats is more than cement treated peats because the increased number of micropores in geopolymer treated peats. The field emission scanning electron microscope (FESEM) micrographs show dense and smooth cementitious products before Nwd cycles consistent with X-ray diffraction (XRD) results and show the existence of micropores after Nwd cycles for geopolymer treated peats. Fourier transform infrared spectroscopy (FTIR) confirms the results of XRD as it shows the adsorption bands of aluminosilicates, which form the basis of geopolymerization, and further confirms the existence of cavities and cracks in samples after Nwd cycles. [ABSTRACT FROM AUTHOR]

A study of a 60-storey reinforced concrete residential building was undertaken to evaluate the propping schemes supporting the flat slabs. Relevant data necessary for evaluation were acquired from the construction site. Based on the obtained data, a simple methodology to formulate the alternative propping schemes is presented in this paper. The propping scheme designed at the construction site for a 10 d slab cycle is analysed and possible alternative schemes are proposed. The primary objectives of the alternative schemes are to ensure safety and economy, and to minimise the number of construction activities on each level. A comparison of the propping schemes suitable for different slab cycle durations was also performed. It is shown that specific slab cycle durations are comparatively more cost-effective. [ABSTRACT FROM AUTHOR]

Feature selection, both for supervised as well as for unsupervised classification is a relevant problem pursued by researchers for decades. There are multiple benchmark algorithms based on filter, wrapper and hybrid methods. These algorithms adopt different techniques which vary from traditional search-based techniques to more advanced nature inspired algorithm based techniques. In this paper, a hybrid feature selection algorithm using graph-based technique has been proposed. The proposed algorithm has used the concept of Feature Association Map (FAM) as an underlying foundation. It has used graph-theoretic principles of minimal vertex cover and maximal independent set to derive feature subset. This algorithm applies to both supervised and unsupervised classification. The performance of the proposed algorithm has been compared with several benchmark supervised and unsupervised feature selection algorithms and found to be better than them. Also, the proposed algorithm is less computationally expensive and hence has taken less execution time for the publicly available datasets used in the experiments, which include high-dimensional datasets. [ABSTRACT FROM AUTHOR]

This study describes the preparation of porous poly(vinylidene fluoride) (PVDF)/(ferrosoferric oxide (Fe 3 O 4 ) decorated polyaniline/single wall carbon nanohorn (SWCNH)) PFC composite through a simple solution blending process using pre-synthesized PFC composite prepared by the in-situ oxidative polymerization of aniline in the presence of SWCNH with FeCl 3 as oxidant (also used as the Fe source in the synthesis of Fe 3 O 4 ) for highly efficient electromagnetic shielding application with high absorption capability. PFC was homogeneously dispersed in the PVDF matrix as conductive nanofiller to develop the conducting network and the porous morphology in the composite was achieved by leaching out of the salt (NaCl) added during solution blending process. The composite shows an excellent EMI shielding effectiveness (EMI SE) due to its porous structure and presence of continuous conductive network (polyaniline-SWCNH) and ferromagnetic Fe 3 O 4 nanoparticles. Moreover, the highly conductive (∼2.5 × 10 −2 S cm −1 ) PVDF-PFC composite (2 mm thickness) has greater dielectric loss and permeability property with a high EMI SE value (≈−29.7 dB) at very low loading (10 wt %) of PFC and SWCNH (1 wt%) in extended Ku-band region. The microwave absorption value also exceeds the reflection as the incident microwaves reflected and scattered multiple times internally and dissipated by the conductive 3D network of SWCNH and polyaniline throughout the composite pore wall. [ABSTRACT FROM AUTHOR]

Feature subset selection is basically an optimization problem for choosing the most important features from various alternatives in order to facilitate classification or mining problems. Though lots of algorithms have been developed so far, none is considered to be the best for all situations and researchers are still trying to come up with better solutions. In this work, a flexible and user-guided feature subset selection algorithm, named as FCTFS (Feature Cluster Taxonomy based Feature Selection) has been proposed for selecting suitable feature subset from a large feature set. The proposed algorithm falls under the genre of clustering based feature selection techniques in which features are initially clustered according to their intrinsic characteristics following the filter approach. In the second step the most suitable feature is selected from each cluster to form the final subset following a wrapper approach. The two stage hybrid process lowers the computational cost of subset selection, especially for large feature data sets. One of the main novelty of the proposed approach lies in the process of determining optimal number of feature clusters. Unlike currently available methods, which mostly employ a trial and error approach, the proposed method characterises and quantifies the feature clusters according to the quality of the features inside the clusters and defines a taxonomy of the feature clusters. The selection of individual features from a feature cluster can be done judiciously considering both the relevancy and redundancy according to user’s intention and requirement. The algorithm has been verified by simulation experiments with different bench mark data set containing features ranging from 10 to more than 800 and compared with other currently used feature selection algorithms. The simulation results prove the superiority of our proposal in terms of model performance, flexibility of use in practical problems and extendibility to large feature sets. Though the current proposal is verified in the domain of unsupervised classification, it can be easily used in case of supervised classification. [ABSTRACT FROM AUTHOR]

A comparative study of current-voltage characteristics and ferroelectric properties of polyvinylidene fluoride (PVDF) based nanocomposite films with pure multiwall carbon nanotubes (MWCNTs) and surface functionalized MWCNTs by different type of functionalize groups (-COOH, -OH, -NH2) as filler, was reported. The flexible nanocomposite films based on PVDF and surface modified MWCNTs were fabricated via solution casting method. The current voltage characteristics suggests that -COOH and -OH functionalize MWCNT loading PVDF films are semiconducting in nature whereas raw MWCNT and -NH2 functionalize MWNCT loading PVDF films are comparatively conducting in nature. Experimental data of current density-electric field were fitted with different existing theoretical models. It is observed that just by changing the functionalization group the electrical conductivity of the composite films significantly changes which is discernible from the current-voltage characteristic. From ferroelectric study the energy density of -COOH, -OH loaded PVDF films are doubled and tripled compare to the pure PVDF film. This work may provide a rout for using different functionalize MWCNTs into polymer matrix to enhance either the energy density or conducting nature of polymer nanocomposite. [ABSTRACT FROM AUTHOR]

Mycobacterium tuberculosis has distinctive ability to detoxify various microbicidal superoxides and hydroperoxides via a redox catalytic cycle involving thiol reductants of peroxiredoxin (Prx) and thioredoxin (Trx) systems which has conferred on it resistance against oxidative killing and survivability within host. We have used computational approach to disrupt catalytic functions of Prx-Trx complex which can possibly render the pathogen vulnerable to oxidative killing in the host. Using protein–protein docking method, we have successfully constructed the Prx-Trx complex. Statistics of interface region revealed contact area of each monomer less than 1500 Å 2 and enriched in polar amino acids indicating transient interaction between Prx and Trx. We have identified ZINC40139449 as a potent interface binding molecule through virtual screening of drug-like compounds from ZINC database. Molecular dynamics (MD) simulation studies showed differences in structural properties of Prx-Trx complex both in apo and ligand bound states with regard to root mean square deviation (RMSD), radius of gyration (Rg), root mean square fluctuations (RMSF), solvent accessible surface area (SASA) and number of hydrogen bonds (NHBs). Interestingly, we found stability of two conserved catalytic residues Cys61 and Cys174 of Prx and conserved catalytic motif, WCXXC of Trx upon binding of ZINC40139449. The time dependent displacement study reveals that the compound is quite stable in the interface binding region till 30 ns of MD simulation. The structural properties were further validated by principal component analysis (PCA). We report ZINC40139449 as promising lead which can be further evaluated by in vitro or in vivo enzyme inhibition assays. [ABSTRACT FROM AUTHOR]

Here, we demonstrate synthesis of grass-like cobalt vanadium oxide hydrate (CVO) nanocanes arrays followed by decoration of CVO by iron oxide nanospheres (FeO@CVO) using iron nitrate and CVO through a cost-effective hydrothermal method. Finally, a high-performance robust mesoporous hybrid composite electrode (PPy/FeO@CVO) was fabricated through wrapping up of polypyrrole (PPy) over FeO@CVO using low-temperature in-situ oxidative polymerization of pyrrole. Electrochemical studies of PPy/FeO@CVO with 1 M KOH reveals highest specific capacitance of ~1202 F/g with exceptionally high cyclic stability at 1 A/g in a three-electrode configuration. Furthermore, a two-electrode based asymmetric supercapacitor using PPy/FeO@CVO as positive and graphene nanoplates (GNP) as negative electrodes and KOH-soaked paper as a separator reveals an outstanding energy density of 38.2 Wh/kg (power density 700 W/kg at 1 A/g) with amazing cyclic stability (95% capacitance retention after 5000 cycles), suggesting great prospective of the ASC for high-power device applications in modern electronic industries. [ABSTRACT FROM AUTHOR]

In the present paper, the response of cylindrical storage tank foundation resting on stone column-reinforced ground has been studied considering the separation between the bottomraft and ground under liftoff condition. The bottomraft of the tank is idealized by a circular plate. The stone column-reinforced ground ismodeled as a tensionless foundation. Soft foundation soil and granular fill are idealized as a spring-dashpot element and Pasternak shear layer, respectively. Stone columns are modeled as stiff nonlinear springs. The stone columns are converted into equivalent concentric rings with one stone column at the center to simulate the axisymmetric condition for the analysis. The governing differential equations are derived fromthe classical theory of thin plate and solved using the finite-difference technique. A parametric study is performed to investigate the differences between the response of tensionless and conventional elastic foundation systems. It is observed that tensionless foundation idealization is essential to analyze the liftoff and avoid erroneous design of the raft for the cylindrical storage tank. Recommendations are also suggested to avoid possible liftoff. [ABSTRACT FROM AUTHOR]

Listeria monocytogenes is the causative agent of listeriosis, which is dangerous for pregnant women, the elderly or individuals with a weakened immune system. Individuals with leukaemia, cancer, HIV/AIDS, kidney transplant and steroid therapy suffer from immunological damage are menaced. World Health Organization (WHO) reports that human listeriosis has a high mortality rate of 20–30% every year. To date, no vaccine is available to treat listeriosis. Thereby, it is high time to design novel vaccines against L. monocytogenes. Here, we present computational approaches to design an antigenic, stable and safe vaccine against the L. monocytogenes that could help to control the infections associated with the pathogen. Three vital pathogenic proteins of L. monocytogenes , such as Listeriolysin O (LLO), Phosphatidylinositol-specific phospholipase C (PI-PLC), and Actin polymerization protein (ActA), were selected using a subtractive proteomics approach to design the multi-epitope vaccine (MEV). A total of 5 Cytotoxic T-lymphocyte (CTL) and 9 Helper T-lymphocyte (HTL) epitopes were predicted from these selected proteins. To design the multi-epitope vaccine (MEV) from the selected proteins, CTL epitopes were joined with the AAY linker, and HTL epitopes were joined with the GPGPG linker. Additionally, a human β-defensin-3 (hBD-3) adjuvant was added to the N-terminal side of the final MEV construct to increase the immune response to the vaccine. The final MEV was predicted to be antigenic, non-allergen and non-toxic in nature. Physicochemical property analysis suggested that the MEV construct is stable and could be easily purified through the E. coli expression system. This in-silico study showed that MEV has a robust binding interaction with Toll-like receptor 2 (TLR2), a key player in the innate immune system. Current subtractive proteomics and immunoinformatics study provides a background for designing a suitable, safe and effective vaccine against pathogenic L. monocytogenes. • Three pathogenic proteins, such as Listeriolysin O (LLO), Phosphatidylinositol-specific phospholipase C (PI-PLC), and Actin polymerization protein (ActA), were chosen through a subtractive proteomics pipeline. • A total of 5 Cytotoxic T-lymphocyte (CTL) and 9 Helper T-lymphocyte (HTL) epitopes were predicted from the 3 selected proteins. • The designed multiepitope vaccine (MEV) was found to be stable, highly antigenic, non-allergenic and non-toxic. • Codon optimization and in-silico cloning verified the translation efficiency and successful expression of the designed MEV in E. coli. • Additionally, the in-silico immune simulation study exhibited a significant immunogenic response due to the MEV administration. [ABSTRACT FROM AUTHOR]

[Display omitted] • Co 2 FeSe 4 ultrathin nanosheet arrays were synthesized via a facile electrodeposition. • The effect of Co and Fe concentrations on electrochemical performance was investigated. • Co 2 FeSe 4 electrode exhibited the areal capacitance of 3393 mF cm−2 at 3 mA cm−2. • Co 2 FeSe 4 and activated carbon were employed as electrodes for the hybrid device. • A quasi-solid-state supercapacitor was fabricated using PVA-KOH gel electrolyte. In this report, binder-free ultrathin nanosheet arrays of Co 2 FeSe 4 (CFS) are prepared for the first time via the potentiostatic electrodeposition method for three minutes. Various physiochemical characterizations are performed to study the effect of Co and Fe in Co x Fe 3-x Se 4. Ultrathin porous nanosheet arrays of the optimized CFS-2 (using 2 mmol CoCl 2 ·6H 2 O) facilitate the electrolytic diffusion to the core electroactive sites, resulting in enhanced capacitive property of the electrode. As per the obtained results, the as-prepared CFS-2 delivers the maximum areal capacitance of 3393 mF cm−2 at a current density of 3 mA cm−2 in 1 M KOH with excellent capacitance retention of 96.4% even after 10,000 charge-discharge cycles. Furthermore, the CFS-2 is employed to fabricate poly(vinyl alcohol)-KOH gel electrolyte-based quasi-solid-state asymmetric supercapacitor device. The fabricated supercapacitor exhibits outstanding energy and power densities of 157.3 mWh cm−2 and 2250 mW cm−2, respectively and demonstrates excellent long cycling stability (85.8% capacitance retention) and columbic efficiency (101.8%) after 10,000 charge-discharge cycles. The overall three-minute electrodeposition synthesis enabling facile upscale route and excellent electrochemical properties suggests the potential of CFS-2 to be applicable in advanced energy storage systems and portable electronics. [ABSTRACT FROM AUTHOR]

Here we propose a simple and facile route to synthesize a high-performance composite electrode material (PMG composite) for next-generation supercapacitor through in-situ polymerization of aniline in the presence of molybdenum trioxide (MoO 3 ) and graphene nanoplatelets (GNP). Its structure and bonding were studied with Fourier transform infrared (FTIR) spectroscopy, wide angle X-ray diffraction (WAXD) and Raman spectroscopy. Morphological analysis (Field emission scanning electron microscopy (FESEM) and high resolution transmission electron microscopy (HRTEM)) revealed the coating of fibrillar PANI on MoO 3 /GNP composite. The prepared composite electrode material is semiconducting in nature as indicated from its non-linear current (I)-voltage (V) characteristics. Most importantly, this PMG composite showed significantly large specific capacitance of ≈593 F/g at the current density of 1 A/g with outstanding cyclic stability (with 92.4% retention of the original specific capacitance even after 1000 cycles) and 734 F/g at 10 mV/s scan rate indicating the highly availability of the electrode-electrolyte interfacial area for the redox processes by synergistic contributions of the components through mutual interactions facilitating the ionic conduction through the constituents. Moreover, applicability of the PMG composite as the high-power energy resource in acidic electrolyte is accomplished as it shows excellent energy density along with high power density. [ABSTRACT FROM AUTHOR]

This study discusses a simple and feasible method that involves in-situ polymerization of aniline in the presence of zinc acetate dihydrate [Zn(CH 3 COO) 2· 2H 2 O] and graphene nanoplatelets (GNP) for the preparation of high performance electrode material (PZG composite) for supercapacitor application. In the presence of metal salt [Zn(CH 3 COO) 2· 2H 2 O], the capacitance value is changed and increased enormously compared to the capacitance value of PANI/GNP (PG) composite. Thus, the proposed method gives specific capacitance value for the PZG composite is ∼688 F/g at a 10 mV/s scan rate which is very high compared to the specific capacitance value (∼340 F/g) of PG composite at the same scan rate. In the PZG composite, zinc acetate and GNP are successfully coated by PANI, which provides more active sites for nucleation and electron transfer path. In addition, the inter- and intra-molecular interactions among them facilitate the electron transfer path which plays an important role to enhance the capacitance value of the composite. Moreover, the prepared composite is electrically conducting in nature and shows electrical conductivity in the order of ≈4.67 × 10 −2 S cm −1 . In addition, PZG composite shows semi-conducting behavior. Field Emission Scanning Electron Microscopy (FESEM) and high resolution transmission electron microscopy (HRTEM) have been studied for the morphological analysis of the PZG composite. [ABSTRACT FROM AUTHOR]

Here, we report the morphology and properties of melt-blended poly(acrylonitrile-butadiene-styrene) (ABS) toughened polyoxymethylene (POM)/clay nanocomposites at different clay loadings (2.5 and 5 phr). The number average domain diameter (Dn) of the ABS droplets in the (75/25 w/w) POM/ABS blend was gradually decreased with increase in clay loading. The X-ray diffraction (XRD) study and transmission electron microscopic (TEM) analysis of the (75/25 w/w) POM/ABS/clay nanocomposites revealed that, the major amount of clay silicates was dispersed selectively in the POM phase of the blend with an exfoliated morphology. The thermal stability of the (75/25 w/w) POM/ABS blend was increased with the increase in clay loadings. Differential scanning calorimetry (DSC) study suggested the enhancement in the non-isothermal crystallization temperature of the matrix polymer in the blend/clay nanocomposites. The rheological study revealed a shear thinning behavior in the nanocomposites indicating good processability of the nanocomposites. The solvent uptake property of the blend was decreased in the presence of small amount of the clay in the nanocomposites. The tensile strength and Young modulus of the (75/25 w/w) POM/ABS blend were increased, whereas, percent elongation of the blend was decreased with increasing the clay content. The toughening effect of the ABS was prominent in the POM/ABS/clay nanocomposites compared to the pristine polymer. POLYM. COMPOS., 35:273-282, 2014. © 2013 Society of Plastics Engineers [ABSTRACT FROM AUTHOR]