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Next generation wireless communication (WC) needs high-performance which assist high-speed data transmission while meeting the requirements for low profile, weight and cost. Several researchers introduce graphene-based circular, triangular, square and hexagonal antenna for WC in the terahertz (THz) resonant frequency (RF). This research work introduces a deep graphene based reconfigurable circularly polarized star-shaped microstrip antenna at 2.98 THz frequency for biomedical application. Graphene has been applied in the structure of star-shaped microstrip antenna. This reconfigurable circularly polarized graphene-based antenna is obtained on a SiO2 substrate. The introduced circularly polarized antenna has a single feed and an easy design. The major objective of this research work is to propose graphene material as an efficient solution in designing antenna for organizing and adjusting its polarization. Because of the complexity of the structure of graphene antenna, enhanced scalable graph random improved Fick's law neural networks is applied for predicting the antenna parameters. This proposed method is a combination of enhanced scalable graph random neural network (ESGRNN) and an improved Fick's law optimization which is used to optimize the prediction error of the proposed ESGRNN. To prevent premature incomplete convergence in the traditional Fick's law algorithm, a dynamic lens-imaging learning strategy is incorporated. Finally, the achieved prediction accuracy is 98%, the mean square error is 2%, minimal return loss (S11) is − 55.98 dB, impedance bandwidth is 800 GHz, gain is 9.8 dB, and voltage standing wave ratio is 1.011 at 2.98 THz RF. As a result, the designed antenna is well-suitable for biomedical applications like riboflavin detection. [ABSTRACT FROM AUTHOR]

Brain tumor segmentation (BTS) from magnetic resonance imaging (MRI) scans is crucial for the diagnosis, treatment planning, and monitoring of therapeutic results. Thus, this research work proposes a novel graph momentum fully convolutional network with a modified Elman spike neural network (MESNN) for BTS and overall survival prediction (OSP). Initially, the introduced graph momentum fully convolutional network segments the brain tumor as enhanced tumor, the tumor core, and the whole tumor from the pre‐processed MRI scans. Second, the texture, intensity, shape, and wavelet features were extracted from the segmented tumors. Then, the horse herd optimization algorithm is utilized to minimize the feature's dimensionality. Finally, the OSP is performed by the MESNN which classifies the survival prediction of a patient as long‐term, mid‐term, and short‐term. The achieved segmentation accuracy of proposed method is 97% and the survival prediction's average RMSE is 215.5. [ABSTRACT FROM AUTHOR]

Abstract Recently, human beings have been affected mainly by dreadful cancer diseases. Predicting cancer risk levels is a major challenge in biomedical research for feature selection and classification at the margins. To resolve this problem, we propose a Subset Clustering-Based Feature Selection using a Multi-Layer Perception Neural Network (SCFS-MLPNN). Initially, pre-processing is carried out with Intensive Mutual Disease Influence Rate (IMDIR) to identify the relational features. In addition, the Successive Disease Pattern Stimulus Rate (SDPSR) is carried out to create relative feature patterns. Based on the patterns, the features are selected and grouped into clustering. Inter-Class Sub-Space Clustering (ICSSC) is applied to split the features by class labels depending on the marginal rate. From the class labels, marginal features are obtained using spectral subset feature selection (SSFS). The selected features are then trained in a Multi-Layer Perception Neural Network (MLPNN) classifier to classify the patient features by risk. Its contribution is to exploit subset features to improve classification accuracy by clustering relational features. The proposed classifier yields higher classification accuracy than previous methods and observes cancer detection for early detection. Therefore, the proposed method achieved a risk analysis accuracy of 91.8% and an F-measure of 91.3% for early detection, which is recommended for early diagnosis. [ABSTRACT FROM AUTHOR]

To combat drought stress in rice, a major threat to global food security, three major quantitative trait loci for 'yield under drought stress' (qDTYs) were successfully exploited in the last decade. However, their molecular basis still remains unknown. To understand the role of secondary regulation by miRNA in drought stress response and their relation, if any, with the three qDTYs, the miRNA dynamics under drought stress was studied at booting stage in two drought tolerant (Sahbaghi Dhan and Vandana) and one drought sensitive (IR 20) cultivars. In total, 53 known and 40 novel differentially expressed (DE) miRNAs were identified. The primary drought responsive miRNAs were Osa-MIR2919, Osa-MIR3979, Osa-MIR159f, Osa-MIR156k, Osa-MIR528, Osa-MIR530, Osa-MIR2091, Osa-MIR531a, Osa-MIR531b as well as three novel ones. Sixty-one target genes that corresponded to 11 known and 4 novel DE miRNAs were found to be co-localized with the three qDTYs, out of the 1746 target genes identified. We could validate miRNA-mRNA expression under drought for nine known and three novel miRNAs in eight different rice genotypes showing varying degree of tolerance. From our study, Osa-MIR2919, Osa-MIR3979, Osa-MIR528, Osa-MIR2091-5p and Chr01_11911S14Astr and their target genes LOC_Os01g72000, LOC_Os01g66890, LOC_Os01g57990, LOC_Os01g56780, LOC_Os01g72834, LOC_Os01g61880 and LOC_Os01g72780 were identified as the most promising candidates for drought tolerance at booting stage. Of these, Osa-MIR2919 with 19 target genes in the qDTYs is being reported for the first time. It acts as a negative regulator of drought stress tolerance by modulating the cytokinin and brassinosteroid signalling pathway. [ABSTRACT FROM AUTHOR]

Electrocardiogram (ECG) is a non-invasive medical tool that divulges the rhythm and function of the human heart. This is broadly employed in heart disease detection including arrhythmia. Arrhythmia is a general term for abnormal heart rhythms that can be identified and classified into many categories. Automatic ECG analysis is provided by arrhythmia categorization in cardiac patient monitoring systems. It aids cardiologists to diagnose the ECG signal. In this work, an Ensemble classifier is proposed for accurate arrhythmia detection using ECG Signal. Input data are taken from the MIT-BIH arrhythmia dataset. Then the input data was pre-processed using Python in Jupyter Notebook which run the code in an isolated manner and was able to keep code, formula, comments, and images. Then, Residual Exemplars Local Binary Pattern is applied for extracting statistical features. The extracted features are given to ensemble classifiers, like Support vector machines (SVM), Naive Bayes (NB), and random forest (RF) for classifying the arrhythmia as normal (N), supraventricular ectopic beat (S), ventricular ectopic beat (V), fusion beat (F), and unknown beat (Q). The proposed AD-Ensemble SVM-NB-RF method is implemented in Python. The proposed AD-Ensemble SVM-NB-RF method is 44.57%, 52.41%, and 29.49% higher accuracy; 2.01%, 3.33%, and 3.19% higher area under the curve (AUC); and 21.52%, 23.05%, and 12.68% better F-Measure compared with existing models, like multi-model depending on the ensemble of deep learning for ECG heartbeats arrhythmia categorization (AD-Ensemble CNN-LSTM-RRHOS), ECG signal categorization utilizing VGGNet: a neural network based classification method (AD-Ensemble CNN-LSTM) and higher performance arrhythmic heartbeat categorization utilizing ensemble learning along PSD based feature extraction method (AD-Ensemble MLP-NB-RF). [ABSTRACT FROM AUTHOR]

Switched reluctance generator (SRG) has become the key focus of research for its usage in wind power generation. The sizing and performance of SRG depend on the core material used for the stator and rotor. This paper analyses the impact of the magnetic loading of different core materials on the performance of SRG in terms of self-inductance, torque, iron losses, ohmic losses, and generated voltage. 1 kW SRG with different pole configuration 8/6 SRG and 12/8 SRG for the wind speed of 3 m/s to 6 m/s has been designed. Static and dynamic analyses using the finite element analysis (FEA) were carried out for analytically designed 1 kW SRG with different core materials with the same lamination thickness. Prototypes of 8/6 SRG and 12/8 SRG are fabricated. The output of simulation results has been validated by experimental measurements. [ABSTRACT FROM AUTHOR]

The contemporary concern in worldwide power scenario and consumption rate is frightening significantly at a marvelous amount of population, and it originates a very high augment in the electrical energy area. The all-embracing attraction and manufacture of fossil energy is the chief reason in the ecological issues. Due to these relic fuels, the ecological resources get exhausted, and it results in climatic change. Due to these negative aspects, every country puts effort to bring the energy efficiency high with the help of renewable energy. Presently, the solar energy donation worldwide decreases. Contrarily, solar energy contribution to the global energy is highly contrary to nonconventional energy resources. But there is a progress in power generation, and it plays a vital role in solar photovoltaic generation. Gallium nitride and silicon carbide power semiconductors will emerge to bring the efficiency high in the photovoltaic technology. In this work, we will converse about how to increase the efficiency by using gallium nitride. [ABSTRACT FROM AUTHOR]

• The input data is pre-processed using Morphological filtering. • Extended Empirical wavelet transformation for removing the baseline. • The pre-processed data are given to Ternary pattern and discrete wavelet transform. • The proposed BiGRU-AE-AD-ECG method is implemented in python. • It is examined under sensitivity, precision, recall, f-measure, specificity and accuracy. Heartbeat irregularity or arrhythmia of a patient with serious congestive cardiovascular breakdown is distinguished in this article, and the class not really settled utilizing long haul ECG information. Several existing methods on arrhythmia detection are utilized, which does not accurately classify the Arrhythmia and it takes higher computational time. Morphological filtering and Extended Empirical wavelet transformation preprocess the input data to remove noises and base line. Then these pre-processed data is fed to Ternary Pattern and Discrete Wavelet Transform (TP-DWT) related feature extracting to take relevant feature. Then, the extracted features are given to Bidirectional Gated Recurrent Unit with Auto Encoder (BiGRU-AE) to classify Arrhythmia into Normal, Atrial Fibrillation (AF), First-degree atrioventricular block (1-AVB), Left Bundle Branch (LBBB), Right Bundle Branch Block (RBBB), Premature Atrial Contraction (PAC), Premature Ventricular Contraction (PVC), ST-segment depression (STD) and ST-segment elevation (STE). The proposed BiGRU-AE-AD-ECG is activated in Python and its efficiency is measured under certain metrics, like sensitivity, precision, f-measure, specificity, accuracy, error rate, ROC and computational time. Here, CPSC 2018 dataset is used to validate the efficiency of the BiGRU-AE-AD-ECG method. The performance of BiGRU-AE-AD-ECG method provides 23.40 %, 18.78 % and 28.05 % higher accuracy, 20.41 %, 27.07 % and 18.80 % higher precision, 32.01 %, 27.40 % and 28.95 % higher sensitivity and 28.05 %, 23.41 % and 31.34 % higher specificity analyzed with existing models, like automatic cardiac arrhythmias categorization based on CNN and attention-based RNN network (CNN-RNN-AD-ECG), a multiple lead-branch fusion network under 12-Lead ECG for multiple class arrhythmia categorization (MLBFNet-AD-ECG), analysis of ECG-based arrhythmia identification scheme using machine learning (SVM-AD-ECG)respectively. [ABSTRACT FROM AUTHOR]

The synchronous reluctance motor (Sync-RM) is known for its higher reliability, faster dynamic response, higher efficiency, higher speed range, higher power density, and higher torque per ampere. Consequently, the scope of research into emerging Sync-RMs drive system has been extended. For different kinds of mechanical and electrical applications, motors are important components of any machine or tool. There are several types of motors available for various kinds of industrial applications, but the benefits of Sync-RM in medium- and low-power applications have eventually been very efficient compared to other motor types, regarding the factors such as high flux density per unit volume, high efficiency, requirements of low maintenance, and low electromagnetic obstruction. This research proposed a Sync-RM drive fed by a bridgeless LUO converter (BLLC) using the Glowworm Swarm Optimization (GSO) tuned proportional integral (PI) controller. High competence, higher power density, and a small structure of the motor drive are delivered by the PI-tuned converter. The output voltages are related to the Sync-RM motor of the proposed converter. Due to its minimum effort and modest development, the Sync-RM here is chosen for the drive. The proposed Sync-RM drive framework based on the LUO converter was evaluated by simulation using the Matlab/Simulink tool. [ABSTRACT FROM AUTHOR]

A wealth of microarray and RNA-seq data for studying abiotic stress tolerance in rice exists but only limited studies have been carried out on multiple stress-tolerance responses and mechanisms. In this study, we identified 6657 abiotic stress-responsive genes pertaining to drought, salinity and heat stresses from the seedling stage microarray data of 83 samples and used them to perform unweighted network analysis and to identify key hub genes or master regulators for multiple abiotic stress tolerance. Of the total 55 modules identified from the analysis, the top 10 modules with 8–61 nodes comprised 239 genes. From these 10 modules, 10 genes common to all the three stresses were selected. Further, based on the centrality properties and highly dense interactions, we identified 7 intra-modular hub genes leading to a total of 17 potential candidate genes. Out of these 17 genes, 15 were validated by expression analysis using a panel of 4 test genotypes and a pair of standard check genotypes for each abiotic stress response. Interestingly, all the 15 genes showed upregulation under all stresses and in all the genotypes, suggesting that they could be representing some of the core abiotic stress-responsive genes. More pertinently, eight of the genes were found to be co-localized with the stress-tolerance QTL regions. Thus, in conclusion, our study not only provided an effective approach for studying abiotic stress tolerance in rice, but also identified major candidate genes which could be further validated by functional genomics for abiotic stress tolerance. [ABSTRACT FROM AUTHOR]

There is no reservation that semiconductor equipment distorted the world despite the fact of doing the practical experiments and also in research field. Researchers will communicate the process of semiconductor statistics with nearby pupils. In this work, diverse brand of semiconductor equipment was thrashed out with elementary properties and their distinctiveness. One type of semiconductor is differentiated based on energy band gap with an added type of semiconductor equipment. Semiconductor resources are the edifice block for the electrical and electronics component. This work makes an available apt generic argument of materials with the latest discussion and its impact of temperature on different materials, and it also reveals dissimilar parameters such as modern density, porch voltage value, transmission rate, and drain resistance value. Exceptional applications were discussed for divergent semiconductor materials. [ABSTRACT FROM AUTHOR]

In this paper, functions of BMS in elections vehicles are explained. The BMS consists of number of electronics components for monitoring and controlling the functions of batteries in electrical vehicles (EVs). Nowadays, the EV has more concentrations because it has number of merits like compact in size, does not require fossil fuel so it is environment friendly, and cost-saving. The main components in EV are batteries because batteries decide the performance and efficiency of EV. So, we should give more importance to batteries. Battery is controlled and monitored with the help of BMS. The BMS protects the battery and increases life time and efficiency due to charging discharging process. [ABSTRACT FROM AUTHOR]

A wealth of microarray and RNA-seq data for studying abiotic stress tolerance in rice exists but only limited studies have been carried out on multiple stress-tolerance responses and mechanisms. In this study, we identified 6657 abiotic stress-responsive genes pertaining to drought, salinity and heat stresses from the seedling stage microarray data of 83 samples and used them to perform unweighted network analysis and to identify key hub genes or master regulators for multiple abiotic stress tolerance. Of the total 55 modules identified from the analysis, the top 10 modules with 8–61 nodes comprised 239 genes. From these 10 modules, 10 genes common to all the three stresses were selected. Further, based on the centrality properties and highly dense interactions, we identified 7 intra-modular hub genes leading to a total of 17 potential candidate genes. Out of these 17 genes, 15 were validated by expression analysis using a panel of 4 test genotypes and a pair of standard check genotypes for each abiotic stress response. Interestingly, all the 15 genes showed upregulation under all stresses and in all the genotypes, suggesting that they could be representing some of the core abiotic stress-responsive genes. More pertinently, eight of the genes were found to be co-localized with the stress-tolerance QTL regions. Thus, in conclusion, our study not only provided an effective approach for studying abiotic stress tolerance in rice, but also identified major candidate genes which could be further validated by functional genomics for abiotic stress tolerance. [ABSTRACT FROM AUTHOR]

In this paper, we develop a healthcare biclustering model in the field of healthcare to reduce the inconveniences linked to the data clustering on gene expression. The present study uses two separate healthcare biclustering approaches to identify specific gene activity in certain environments and remove the duplication of broad gene information components. Moreover, because of its adequacy in the problem where populations of potential solutions allow exploration of a greater portion of the research area, machine learning or heuristic algorithm has become extensively used for healthcare biclustering in the field of healthcare. The study is evaluated in terms of average match score for nonoverlapping modules, overlapping modules through the influence of noise for constant bicluster and additive bicluster, and the run time. The results show that proposed FCM blustering method has higher average match score, and reduced run time proposed FCM than the existing PSO-SA and fuzzy logic healthcare biclustering methods. [ABSTRACT FROM AUTHOR]

In this paper, we develop a healthcare biclustering model in the field of healthcare to reduce the inconveniences linked to the data clustering on gene expression. The present study uses two separate healthcare biclustering approaches to identify specific gene activity in certain environments and remove the duplication of broad gene information components. Moreover, because of its adequacy in the problem where populations of potential solutions allow exploration of a greater portion of the research area, machine learning or heuristic algorithm has become extensively used for healthcare biclustering in the field of healthcare. The study is evaluated in terms of average match score for nonoverlapping modules, overlapping modules through the influence of noise for constant bicluster and additive bicluster, and the run time. The results show that proposed FCM blustering method has higher average match score, and reduced run time proposed FCM than the existing PSO-SA and fuzzy logic healthcare biclustering methods. [ABSTRACT FROM AUTHOR]

In this paper, we develop a healthcare biclustering model in the field of healthcare to reduce the inconveniences linked to the data clustering on gene expression. The present study uses two separate healthcare biclustering approaches to identify specific gene activity in certain environments and remove the duplication of broad gene information components. Moreover, because of its adequacy in the problem where populations of potential solutions allow exploration of a greater portion of the research area, machine learning or heuristic algorithm has become extensively used for healthcare biclustering in the field of healthcare. The study is evaluated in terms of average match score for nonoverlapping modules, overlapping modules through the influence of noise for constant bicluster and additive bicluster, and the run time. The results show that proposed FCM blustering method has higher average match score, and reduced run time proposed FCM than the existing PSO-SA and fuzzy logic healthcare biclustering methods. [ABSTRACT FROM AUTHOR]

Since 1990s, the world has seen a lot of advances in providing humanitarian aid through sophisticated logistics operations. The current consensus seems to be that humanitarian relief organizations (HROs) can improve their relief operations by collaborating with logistics service providers (CLSPs) in the commercial sector. The question remains: how can HROs select the most appropriate CLSP for disaster preparation? Despite its practical significance, no explicit effort has been done to identify the criteria/factors in prioritizing and selecting a CLSP for disaster relief. The present study aims to address this gap by consolidating the list of criteria from a socio-technical systems (STS) perspective. Then, to handle the interdependence among the criteria derived from the STS, we develop a hybrid multi-criteria decision making model for CLSP selection in the disaster preparedness stage. The proposed model is then evaluated by a real-life case study, providing insights into the decision-makers in both HROs and CLSPs. [ABSTRACT FROM AUTHOR]

The key objective of this study is to develop a tool (hybridization or integration of different techniques) for locating the temporary blood banks during and post-disaster conditions that could serve the hospitals with minimum response time. We have used temporary blood centers, which must be located in such a way that it is able to serve the demand of hospitals in nearby region within a shorter duration. We are locating the temporary blood centres for which we are minimizing the maximum distance with hospitals. We have used Tabu search heuristic method to calculate the optimal number of temporary blood centres considering cost components. In addition, we employ Bayesian belief network to prioritize the factors for locating the temporary blood facilities. Workability of our model and methodology is illustrated using a case study including blood centres and hospitals surrounding Jamshedpur city. Our results shows that atleast six temporary blood facilities are required to satisfy the demand of blood during and post-disaster periods in Jamshedpur. The results also show that that past disaster conditions, response time and convenience for access are the most important factors for locating the temporary blood facilities during and post-disaster periods. [ABSTRACT FROM AUTHOR]

Voltage multiplier factor circuits area unit wide employed in several high-voltage/low-current applications this paper proposes a hybrid SVM (HSVM) for dc high-voltage applications. The multiplier factor is made by cascading a diode-bridge rectifier associated an (symmetrical voltage multiplier factor) SVM with diode-bridge rectifier because the initial stage of multiplier. The planned topology saves 2 high-voltage capacitors and needs just one secondary of HVT. Besides, it's lesser free fall and quicker transient response at start-up, compared with typical SVM. [ABSTRACT FROM AUTHOR]

during this paper a completely unique topology for top increase DCDC convertor is introduced. The convertor makes use of coupled electrical device and voltage multiplier factor cell to achieve the specified high increase voltage gain. the most benefits of the projected convertor square measure easy topology, high increase voltage gain, continuous input current, exercise the energy of the run inductance of the coupled electrical device, and utilizing only 1 active switch with reduced voltage stress. Reduced switch voltage stress leads to choice of switch with low on-resistance that improves the potency. Operational principles of the convertor in steady state square measure studied Associate in Nursingd an analytical approach is employed to realize voltage gain and switch voltage stress. [ABSTRACT FROM AUTHOR]

This paper presents a very distinctive boost device with twin coupled-inductors and a voltage variety module. On the one hand, the primary windings of two coupled-inductors unit of measurement connected in parallel to share the input current and deate this ripple at the input. On the other hand, the projected device inherits the deserves of interleaved series-connected output capacitors for prime voltage gain, low output voltage ripple and low switch voltage stress. Moreover, the secondary sides of two coupled-inductors unit of measurement connected asynchronous to a regenerative device by a diode for extending the voltage gain and leveling the primary-parallel currents. In addition, the active switches unit of measurement turned on at zero-current and conjointly the reverse recovery disadvantage of diodes is relieved by low cost leak inductances of the coupled inductors. Besides, the energy of leak inductances is recycled. [ABSTRACT FROM AUTHOR]

Series Z-Source network, Associate in Nursing enlargement of the favored conception of Z-source dc link, was initially projected for enhancing the output voltage of power electronic inverters. Throughout this paper, that concept is extended on a three-phase indirect matrix converter. The converter depends on the ultra-sparse matrix topology characterized by the minimum vary of semiconductor switches. The series Z-source network is placed between the three-switch input rectifier stage and additionally the six-switch output electrical converter stage, in either the positive or negative rail. A short shoot-through state produces the voltage boost. Associate in Nursing optimum pulse breadth modulation technique is developed for higher boosting capability of the converter and reduce of switch losses. A comparison is made between the matrix converters mistreatment series and customary cascade Z-source networks. The inpouring current and Z-source capacitor's voltage are reduced inside the series Z-source matrix converter. [ABSTRACT FROM AUTHOR]

This work proposes a DTC-SVM management rule supported computer coordinate transformation to manage associate induction machine fed by a three-level Neutral purpose clamped matrix converter. The rule is simulated on Matlab Simulink to verify its performance. It provides reasonable performance usually. The results are mentioned, and a study of the results of the variation of computer resistance is projected jointly. [ABSTRACT FROM AUTHOR]

This research proposes a change of magnitude dc-dc device supporting the Cockcroft-Walton (CW) voltage number while not a transformer, providing continuous input current, with low ripple, high voltage, quantitative relation and low voltage stress on the switches, diodes, and capacitors. The projected device should be appropriate for applying to low-input-level dc generation systems. In this study, the projected management strategy employs 2 freelance frequencies, one that operates at high frequency to attenuate the scale of the inductance and an opposite one that operates at the comparatively low frequency in keeping with the required output voltage ripple. [ABSTRACT FROM AUTHOR]

This project presents a replacement three-phase converter supported the Cuk converter. The principal feature of the planned topology is that the energy storage parts, like inductors and capacitors, is reduced therefore on boost the trustworthiness, and reduce the size and total value. The buck-boost inherent characteristic of the Cuk device, reckoning on the time-varying duty magnitude relation, provides flexibility for stand alone and grid-connected applications once the required output ac voltage is lower or larger than the dc aspect voltage. Average large and little signal models are accustomed to studying the Cuk converter's nonlinear operation. The essential structure, management vogue, and MATLAB/SIMULINK results are given. [ABSTRACT FROM AUTHOR]

• The role of operations and SCM in managing epidemics and pandemics is reviewed. • Five research areas are identified, providing an integrative view of the field. • Ten future research directions are developed. • A starting point for researchers to investigate this domain is provided. Epidemics have been posing significant challenges to health, existence, and continuity. From the emergence of an outbreak to its elimination, managing an epidemic/pandemic entails many operations and supply chain management decisions that can contribute to a lessening of its impact. With these decisions, epidemic-/pandemic-imposed challenges related to forecasting, planning, supply, manufacturing, storage, and transportation can be addressed in an effort to curtail and end the epidemic/pandemic. We have witnessed these disruptions first-hand during the COVID-19 pandemic, which has had a destructive effect on many well-established supply chains, threatening the existence of firms. The role of operations and supply chain management is thus pivotal for navigating epidemics/pandemics. Against this background, we present a systematic literature review on the role of operations and supply chain management during epidemics and pandemics, illustrating its potential and calling for future research. Leveraging bibliographic coupling analysis, we identify major research areas and contributions that serve as a foundation to propel these domains forward. We further critically review these research areas, identifying multiple themes of which many have been perennially relevant, while others have come to the fore only recently due to the COVID-19 pandemic. Our review provides an integrative view of the field, concurrently advancing theory, and offering ten distinct future research directions. Overall, this paper is meant to serve as a starting point for researchers in operations and supply chain management aiming to investigate this increasingly important domain. [ABSTRACT FROM AUTHOR]

The Internet of Vehicles (IoV) ability to monitor the surrounding environment promotes autonomous activities like determining a trajectory and responding accordingly. Security and transportation are vital components of today's technology-driven society. In addition to search and rescue, it may also be used for planetary exploration and material management. So, the Internet of Vehicles must drive independently in various dynamic situations. Unlocking the potential of the IoV navigation process, a dynamic access control architecture-based autonomous navigation system is proposed. It can perform assigned tasks while also reacting quickly to unexpected situations. The efficiency of AI-based IoV navigation is compared and studied using autonomous decision control systems. [Display omitted] [ABSTRACT FROM AUTHOR]

Among the various climate change causing agents, transportation alone is responsible for 19.2% of the carbon emissions. By proper implementation of various preventive measures, the impact of transportation on climate change can be drastically reduced. It is also necessary to determine the relationship between the transportation factors responsible for creating environmental degradation and causing climate change and to rank them based on the preventive measures impact to deal with them. In this paper, we have identified the transportation factors that affect climate change and the factors related to its preventive measures based on the 'environment', 'sociology' and 'modernity' elements of Ecological Modernization Theory (EMT). Given the context, this study focusses on development of an assessment framework that combines three techniques: Simple Additive Weighting (SAW), Interpretive Structural Modelling (ISM) and Interpretive Ranking Process (IRP). • We integrate SAW-ISM-IRP approach to understand the impact of transportation on climate change. • We have identified the factors based on Ecological Modernization Theory. • First, SAW has been used to reduce the number of factors in order to apply ISM and IRP easily. • We have collected data from 10 experts. [ABSTRACT FROM AUTHOR]

Hypertriglyceridemia induced pancreatitis is the third most common cause of acute pancreatitis after gall stones and alcohol. Most of the patients with Hypertriglyceridemia (HTG) has primary or genetic defect in lipoprotein metabolism. Groove pancreatitis is a rare form of Pancreatitis with most patients being male and history of alcohol consumption. Here we report a case of 33 year old female who is a known diabetic, presented with diabetic ketoacidosis. Her serum lipase was 3133 U/l (<40U/l). Here we report a case of familial dyslipidemia with severe hypertriglyceridemia causing pancreatitis involving the Groove presenting with Diabetic Ketoacidosis. [ABSTRACT FROM AUTHOR]

Abstract: Between September 2002 and February 2004, 40 kidney transplant (27 from deceased and 13 from living donors) recipients (25 male and 15 female, aged 50.3 ± 15.1 years) were treated with Campath 1H (C 1H; 30 mg/dose IV) for biopsy-proven steroid-resistant rejection (SRR) or rejections equal to or worse than Banff 1B. All transplantations occurred between August 2001 and May 2003. All patients had received antibody preconditioning (RATG 5 mg/kg, n = 34; C 1H 60 mg, n = 4; C 1H 30 mg, n = 2) preoperatively and were treated with Tacrolimus monotherapy (target level 10 ng/ml) postoperatively and subsequent spaced weaning. Elevated creatinine levels at follow-up were evaluated by renal transplant biopsy. Rejection was treated with steroids, reversal of weaning, addition of sirolimus, and/or antibody treatment, depending on grade of rejection. The mean duration of follow-up was 453 ± 163 days after C 1H administration. Twenty-nine patients received C 1H for SRR and 11 patients for Banff 1B or worse rejections; 26 patients received more than 1 dose of C 1H. Graft survival was 62.5% (25 patients); 6 of the 15 allografts (40%) that failed had presented with rejections because of noncompliance. Graft survival in compliant patients with SRR or rejections equal to or worse than Banff 1B was 73.5% (25 of 34). Fourteen patients (35%) had infectious complications, of whom 2 patients (5%) died. C 1H is an effective agent for SRR and Banff 1B or worse rejections, with 95% patient survival and 73.5% graft survival (in compliant patients). The number of doses of 30 mg C 1H should be restricted to two, as there is a high incidence of potentially fatal infectious complications. [Copyright &y& Elsevier]

In recent years, municipal authorities especially in the developing nations are battling to select the best health care waste (HCW) disposal technique for the effective treatment of the medical wastes during and post COVID-19 era. As evaluation of various disposal alternatives of HCW and selection of the best technique requires considering various tangible and intangible criteria, this can be framed as multi-criteria decision-making (MCDM) problem. In this paper, we propose an assessment framework for the selection of the best HCW disposal technique based on socio-technical and triple bottom line perspectives. We have identified 10 criteria on which the best HCW disposal techniques to be selected based on extant literature review. Next, we use Fuzzy VIKOR method to evaluate 9 HCW disposal alternatives. The effectiveness of the proposed framework has been demonstrated with a real-life case study in Indian context. To check the robustness of the proposed methodology, we have compared the results obtained with Fuzzy TOPSIS (Technique of Order Preference Similarity to the Ideal Solution). The results help the municipal authorities to establish a methodical approach to choose the best HCW disposal techniques. Our findings indicate that incineration is the best waste disposal technique among the available alternatives. Even if the dataset indicates 'incineration' is the best method, we must not forget about the environmental concerns arising from this method. In COVID time, incineration may be the best method as indicated by the data analysis, but "COVID" should not be an excuse for causing "Environmental Pollution". • Health care waste disposal technique selection is a serious concern during COVID-19. • We propose Fuzzy VIKOR based method for selecting the best disposal technique. • This work has been grounded on Triple Bottom Line and Socio-Technical perspectives. • The proposed framework has been validated with a real-life case study. • The effectiveness of the proposed method has been compared with Fuzzy TOPSIS. [ABSTRACT FROM AUTHOR]

This paper aims to understand the impact of big data analytics on the retail supply chain. For doing so, we set our context to select the best big data practices amongst the available alternatives based on retail supply chain performance. We have applied TODIM (an acronym in Portuguese for Interactive Multi-criteria Decision Making) for the selection of the best big data analytics tools among the identified nine practices (data science, neural networks, enterprise resource planning, cloud computing, machine learning, data mining, RFID, Blockchain and IoT and Business intelligence) based on seven supply chain performance criteria (supplier integration, customer integration, cost, capacity utilization, flexibility, demand management, and time and value). One of the intriguing understandings from this paper is that most of the retail firms are in a dilemma between customer loyalty and cost while implementing the big data practices in their organization. This study analyses the dominance of the big data practices at the retail supply chain level. This helps the newly emerging retail firms in evaluating the best big data practice based on the importance and dominance of supply chain performance measures. [ABSTRACT FROM AUTHOR]

To improve the efficiency of the circuit and to minimize the THD to the negligible level voltage doubler circuit is interleaved with the single stage ZVS PFC converter circuits. The voltage doubler circuit is used to obtain UPF with low THD and increased performance efficiency of the converter by imposing the control over the current. The voltage doubler is charged by the converter operation at both negative and positive cycle. The converter circuit without voltage doubler was used in low power rating applications. But with the voltage doubler circuits high power ratings applications are possible. In this circuit the reduced switching loss of 6.7% is obtained with the THD 2.95[12]. The improvised performance efficiency with the input condition of 529.65W/31.21 A is 93.28%. [ABSTRACT FROM AUTHOR]

This investigation pertains to the bitumen production using component blending. During the manufacture of blended bitumen, the proportion of the constituents, the temperature during blending, and the duration of blending are selected to meet the penetration at 25°C and the absolute viscosity at 60°C as per the Indian specifications. The choices of the blend parameters become challenging when the constituents from multiple crudes are blended to produce different paving grades. Two constituent and three constituent blends for four different grades of bitumen were prepared in a laboratory blending facility from four different crude sources. A design of experiments framework was used to develop prediction models for penetration and viscosity. Simulations were carried out to suggest blending schemes to manufacture all the viscosity grades from different crude sources. Correspondence between the viscosity grade and high-temperature performance grade was observed for blend parameters for the crude sources investigated in this study. [ABSTRACT FROM AUTHOR]

Lack of resources established in the present world is initiating everyone towards energy efficient technologies. Among all these resources, power is one which needs to be monitored and controlled as per the need since electricity consumption is increasing day-by day. In this project, we have described an effective implementation of an intelligent remote monitoring system for solar Photovoltaic (PV), Wind Energy Conversion System (WECS) and battery which are used in a greenhouse environment. The proposed system design can be installed in solar PV, WECS and battery in order to solve management problems, maintenance and shortens the mean time to repair. We have designed a smart remote monitoring system based on internet of thing for monitoring Solar PV, WECS and Battery. This system had incorporated remote monitoring for solar PV, WECS and battery through internet using host, network GPRS (Global Positioning Radio Service), embedded system gateway and Arduino. The result of our demonstration shows that the system can monitor store and manipulate data from solar PV, WECS and battery. Thus, the remote monitoring functions are realized in real-time. [ABSTRACT FROM AUTHOR]

The year 2020 can be earmarked as the year of global supply chain disruption owing to the outbreak of the coronavirus (COVID-19). It is however not only because of the pandemic that supply chain risk assessment (SCRA) has become more critical today than it has ever been. With the number of supply chain risks having increased significantly over the last decade, particularly during the last 5 years, there has been a flurry of literature on supply chain risk management (SCRM), illustrating the need for further classification so as to guide researchers to the most promising avenues and opportunities. We therefore conduct a bibliometric and network analysis of SCRA publications to identify research areas and underlying themes, leading to the identification of three major research clusters for which we provide interpretation and guidance for future work. In doing so we focus in particular on the variety of parameters, analytical approaches, and characteristics of multi-criteria decision-making techniques for assessing supply chain risks. This offers an invaluable synthesis of the SCRA literature, providing recommendations for future research opportunities. As such, this paper is a formidable starting point for operations researchers delving into this domain, which is expected to increase significantly also due to the current pandemic. [ABSTRACT FROM AUTHOR]

Background: India is termed as the diabetic capital of the world and modifiable risk factors such as unhealthy dietary behaviors and inadequate physical activity play an important role in the control of diabetes. Objectives: To describe the pattern of diet consumption among Type II diabetic patients who were treated in a Tertiary care Hospital in South India. To describe the nature and extent of sweet consumption and to assess the relationship between nature of diet and sweet consumption among them. Materials and methods: A hospital based cross-sectional analytical study done among 368 adult Type II diabetic patients treated in a tertiary care hospital in South India during May 2020 to Dec 2021. Participants were recruited through consecutive sampling and data were collected using a pretested semi-structured questionnaire. Chi-square test was done to find out association between categorical variables and P value <0.05 was considered to be statistically significant. Results: Out of 368 participants, 227 (61.7%) belong to 50 to 69 years followed by 83 (22.6%) in 30 to 49 years age group, 187 (50.8%) were females and 181 (49.2%) were males, 90 (24.5%) were vegetarians, and 278 (75.5%) were non-vegetarians. Sweet consumption in the past 1 month was observed more (54%) among non-vegetarians. Mean ± SD of FBS level among vegetarians versus non-vegetarians was 123 ± 25.6 and 135 ± 34.5. Mean ± SD of PPBS level among vegetarians versus non-vegetarians was 189.4 ± 48.3 versus 208.6 ± 57.4. Conclusion: Participants following vegetarian diet with less sweet consumption and with more involvement in physical activity were observed to have a better diabetic control. [ABSTRACT FROM AUTHOR]

The choice of the optimal orientation of the solar panels is by far one of the most important issues in the practical application of solar installations. The use of phase changing materials (PCMs) is an efficient approach of storing solar thermal energy. Because PCMs are isothermal in nature, they provide better density energy storage and the capacity to function across a wide temperature range. Unfortunately, this feature is very rare on various solar power panels; however, ignoring it can reduce the performance of the panels to unacceptable levels. The fact is that the angle of incidence of rays on the surface greatly affects the reflection coefficient and, consequently, the role of unacceptable solar energy. In this paper, a smart energy harvesting model was proposed. In the case of glass, when the angle of incidence varies vertically from its surface to 30, the reflection coefficient is practically unchanged and slightly less than 5%, i.e., more than 95% of the radiation goes inwards. Furthermore, the reflection increase is noticeable, and the area of the reflected radiation by 60 doubles to almost 10%. At an angle of incidence of 70, it reflects 20% of the radiation, and at 80, 40%. For most other objects, the dependence of the reflection magnitude on the angle of incidence is approximately the same. [ABSTRACT FROM AUTHOR]

Currently, electric cars are receiving a lot of attention because of their low fuel consumption and pollution-free nature. The efficiency of electric vehicles is constantly being improved via a variety of studies and applications. The battery is a significant portion of an electric vehicle's overall component count. Because the electric vehicle's battery acts like the vehicle's heart, battery performance and efficiency in electric vehicles (EVs) are examined in this research. [ABSTRACT FROM AUTHOR]