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Effects of Nonmonotonic Functional Responses on a Disease Transmission Model:Modeling and Simulation

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Communications in Mathematics and Statistics 2022年第2期10卷 195-214页

作者： abhishek kumar Nilam Department of Applied Mathematics Delhi Technological UniversityDelhi 110042India

In this article,a novel susceptible-infected-recovered epidemic model with nonmonotonic incidence and treatment rates is proposed and analyzed *** Monod-Haldane functional response is considered for nonmonotonic behavior of both incidence rate and treatment *** model analysis shows that the model has two equilibria which are named as disease-free equilibrium(DFE)and endemic equilibrium(EE).The stability analysis has been performed for the local and global behavior of the DFE and *** the help of the basic reproduction number(R_(0)),we investigate that DFE is locally asymptotically stable when R_(0)*** local stability of DFE at R_(0)=1 has been analyzed,and it is obtained that DFE exhibits a forward transcritical ***,we identify conditions for the existence of EE and show the local stability of EE under certain ***,the global stability behavior of DFE and EE has been ***,numerical simulations have been done in the support of our theoretical findings.

关键词： Monod-Haldane functional Basic reproduction number Local and global stability Bifurcation

Deep Neural Network and Pseudo Relevance Feedback Based Query Expansion

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Computers, Materials & Continua 2022年第5期71卷 3557-3570页

作者： abhishek kumar Shukla Sujoy Das Department of Mathematics Bio-Informatics and Computer ApplicationsMaulana Azad National Institute of Technology BhopalBhopalMadhya Pradesh462003India

The neural network has attracted researchers immensely in the last couple of years due to its wide applications in various areas such as Data mining,Natural language processing,Image processing,and Information retrieval *** embedding has been applied by many researchers for Information retrieval *** this paper word embedding-based skip-gram model has been developed for the query expansion *** terms are obtained from the top“k”initially retrieved documents using the Pseudo relevance feedback model and then they are trained using the skip-gram model to find the expansion terms for the user *** performance of the model based on mean average precision is *** proposed model compares with other existing *** improvement of 6.61%,6.93%,and 9.07%on MAP value is observed compare to the Original query,BM25 model,and query expansion with the Chi-Square model *** proposed model also retrieves 84,25,and 81 additional relevant documents compare to the original query,query expansion with Chi-Square model,and BM25 model respectively and thus improves the recall value *** per query analysis reveals that the proposed model performs well in 30,36,and 30 queries compare to the original query,query expansion with Chi-square model,and BM25 model respectively.

关键词： Information retrieval query expansion word embedding neural network deep neural network

Three-phase AC-DC Converter for Direct-drive PMSG-based Wind Energy Conversion System

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Journal of Modern Power Systems and Clean Energy 2023年第2期11卷 589-598页

作者： kumar abhishek Singh Ayushi Chaudhary Kalpana Chaudhary Department of Electrical Engineering Indian Institute TechnologyVaranasiIndia Department of Electrical Engineering Indian Institute TechnologyKanpurIndia

In this paper,a wind energy conversion system(WECS)is presented for the electrification of rural areas with wind energy availability.A three-phase AC-DC converter based on a bridgeless Cuk converter is used for power extraction from the permanent magnet synchronous generator(PMSG).The bridgeless topology enables the elimination of the front-end diode bridge rectifier(DBR).Moreover,the converter has fewer components,simple control,and high efficiency,making it suitable for a small-scale WECS.A squirrel cage induction motor(SCIM)is used to emulate a MOD-2 wind turbine to implement the PMSG-based WECS.A direct-drive eight-pole PMSG is used in this study;thus,a low-input-voltage system is *** converter is designed to operate in the discontinuous inductor current mode(DICM)for inherent power factor correction(PFC)and the maximum power point tracking(MPPT)is achieved through the tip-speed ratio(TSR)*** performance of the developed system is analyzed through simulation,and a 500 W hardware prototype is developed and tested in different wind speed conditions.

关键词： Permanent magnet synchronous generator(PMSG) three-phase AC-DC converter wind energy conversion system(WECS) wind turbine emulator

Inhibitory Interaction and Pharmacological Analyses of Berries Phenolics Against Listeria monocytogenes Virulent Protein Internalin B

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World Journal of Traditional Chinese Medicine 2023年第1期9卷 71-80页

作者： abhishek kumar Archana Vimal Awanish kumar School of Agriculture Indira Gandhi National Open UniversityNew DelhiIndia Department of Bioengineering Integral University LucknowUttar PradeshIndia Department of Biotechnology National Institute of TechnologyRaipurChhattisgarhIndia

Background: Traditional plants, their parts, and phytochemicals obtained from them are beneficial for human beings. They are used as potent antimicrobials, but very little research is conducted on the use of traditional medicine against food-borne infection. Different berry plants are rich in phenolic compounds and conventionally known to have many properties such as antioxidants, anti-carcinogenic, anti-inflammatory, anti-bacterial, and anti-diabetics. However, only limited polyphenols are known for their antilisterial effect. The present study aimed to explore the antimicrobial efficacy of phenolic compounds of berries for the treatment of food-borne infection caused by the bacteria Listeria monocytogenes. Materials and Methods: Molecular docking studies employing the Swiss DOCK server were performed to evaluate the antimicrobial activity of phenolic compounds obtained from different varieties of berries. Internalin B(Inl B), a virulence protein of L. monocytogenes was selected as a target. The absorption, distribution, metabolism, excretion, and toxicity profiling of each test ligand was done through the Swiss ADME tool. Results: Among all the test ligands, p-coumaric acid, epicatechins, chlorogenic acid, and quercetin showed better binding efficiency with the target protein Inl B. The binding energy obtained for quercetin, p-coumaric acid, chlorogenic acid, and epicatechins was-8.93,-8.23,-8.18,-7.58, kcal/mol, respectively. Quercetin and p-coumaric acid were forming 4 H-bonds, whereas chlorogenic acid and epicatechins were forming 3-H bonds inside the binding pocket. Conclusion: In a nutshell, analyses indicated that identified ligands have the potential to block the virulent protein Inl B of L. monocytogenes and help combat Listeria infection. These phenolic compounds could be a substitute for synthetic antimicrobials and can be used in food preservation and combat food-borne diseases. However, future in-depth in vitro and in vivo analysis is needed to get mor

关键词： Berry plant internalin B Listeria monocytogenes pharmacological analyses phenolics potent inhibitor traditional medicine

Human Verification over Activity Analysis via Deep Data Mining

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Computers, Materials & Continua 2023年第4期75卷 1391-1409页

作者： kumar abhishek Sheikh Badar ud din Tahir Senior Member IEEESeattle98103USA Department of Software Engineering Capital University of Science and Technology(CUST)Islamabad44000Pakistan

Human verification and activity analysis(HVAA)are primarily employed to observe,track,and monitor human motion patterns using redgreen-blue(RGB)images and *** human interaction using RGB images is one of the most complex machine learning tasks in recent *** models rely on various parameters,such as the detection rate,position,and direction of human body components in RGB *** paper presents robust human activity analysis for event recognition via the extraction of contextual intelligence-based *** use human interaction image sequences as input data,we first perform a few denoising ***,human-to-human analyses are employed to deliver more precise *** phase follows feature engineering techniques,including diverse feature ***,we used the graph mining method for feature optimization and AdaBoost for *** tested our proposed HVAA model on two benchmark *** testing of the proposed HVAA system exhibited a mean accuracy of 92.15%for the Sport Videos in theWild(SVW)*** second benchmark dataset,UT-interaction,had a mean accuracy of 92.83%.Therefore,these results demonstrated a better recognition rate and outperformed other novel techniques in body part tracking and event *** proposed HVAA system can be utilized in numerous real-world applications including,healthcare,surveillance,task monitoring,atomic actions,gesture and posture analysis.

关键词： AdaBoost classification deep features mining graph mining human detection human verification

Circulating and non-circulating proteins and nucleic acids as biomarkers and therapeutic molecules in ovarian cancer

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Genes & Diseases 2023年第3期10卷 1005-1018页

作者： kumar Utkarsh abhishek kumar Aditi Azhar Khan Ashima Nayyar Shabirul Haque Shams Iqbal Department of Microbiology and Biotechnology Shoolini UniversitySolanHimachal Pradesh 173229India Faculty of Applied Science and Biotechnology Shoolini UniversitySolanHimachal Pradesh 173229India Tisch Cancer Institute Icahn School of MedicineMt.SinaiNY 10029USA Department of Autoimmune Diseases Feinstein Institute for Medical ResearchNorthwell HealthManhassetNY 11030USA Vascular Interventional Radiology Department of RadiologyMassachusetts General HospitalHarvard Medical SchoolBostonMA 02115USA

Ovarian cancer is the second most fatal gynecological cancer. For the last decade or so significant use of non-circulating and circulating biomarkers has been highlighted. However, the study of such biomarkers at nanovesicle technology such as exosomes, proteomic and genomics studies could further contribute to better identification of anomalous protein and networks which could act as potential targets for biomarker and immunotherapy development. This review provides an overview of the circulating and non-circulating biomarkers with the aim of addressing the current challenges and potential biomarkers that could lead to early ovarian cancer diagnosis and better management. By means of this review we also lay a hypothesis that characterization of exosomal protein, nucleic acid content from body fluids (serum, plasma, urine, etc.) can decode the secret of disease and potentially improve diagnostic sensitivity which could further lead to more effective screening and early detection of the disease.

关键词： Biomarker Circulating protein Exosomes Extracellular vesicles Ovarian cancer Proteonnics

Aflatoxin contamination in food crops:causes,detection,and management:a review

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Food Production, Processing and Nutrition 2021年第1期3卷 228-236页

作者： abhishek kumar Hardik Pathak Seema Bhadauria Jebi Sudan Department of Plant Biotechnology JECRC UniversityJaipurRajasthanIndia Department of Botany Dr.Bhimrao Ambedkar UniversityAgraUttar PradeshIndia

Mycotoxins are secondary metabolites produced by several fungal species and *** favorable conditions like high temperature and moisture,they contaminate a large number of food commodities and regional crops during pre and *** is the main mycotoxin that harm animal and human health due to its carcinogenic *** are mainly released by Aspergillus flavus and Aspergillus ***1 constitutes the most harmful type of aflatoxins and is a potent hepato-carcinogenic,mutagenic,teratogenic and it suppresses the immune *** maintain food safety and to prevent aflatoxin contamination in food crops,combined approaches of using resistant varieties along with recommended farming practices should be *** review concentrates on various aspects of mycotoxin contamination in crops and recent methods to prevent or minimize the contamination.

关键词： Mycotoxin Aflatoxin contamination Aspergillus flavus Aspergillus parasiticus Food crops

A perspective on biochar for repairing damages in the soil-plant system caused by climate change-driven extreme weather events

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Biochar 2022年第1期4卷 817-839页

作者： abhishek kumar Tanushree Bhattacharya Santanu Mukherjee Binoy Sarkar Department of Civil and Environmental Engineering Birla Institute of TechnologyMesraRanchi 835215JharkhandIndia School of Agriculture Shoolini University of Biotechnology and Management SciencesSolan 173229India Lancaster Environment Centre Lancaster UniversityLancaster LA14YQUK

There has been more than 75%rise in the number of extreme weather events such as drought and flood during 2000-2019 compared to 1980-1999 due to the adverse effects of climate change,causing significant deterioration of the soil and water ***,the growing human population has been exerting pressure on available water and soil resources due to overuse or unplanned *** greenhouse gas emissions have intensified,the fertility of agricultural soils has declined globally due to the exposure of soils to frequent flooding,desertification,and salinization(resulting from extreme weather events).The current review aims to give an overview of damages caused to the soil-plant system by extreme weather events and provide a perspective on how biochar can repair the damaged *** is known to improve soil fertility,increase crop productivity and mitigate greenhouse gas emissions via sustainable recycling of *** properties of biochar such as alkaline pH,high cation exchange capacity,abundant surface functional groups,remarkable surface area,adequate porosity,excellent water holding capacity,and sufficient nutrient retention capacity can help repair the adverse effects of extreme weather events in the soil-plant *** paper recommends some cautious future approaches that can propel biochar’s use in improving the soil-plant systems and promoting sustainable functioning of extreme weather-affected areas via mitigation of the adverse effects.

关键词： Biochar Climate change Drought Flood Salinization Temperature rise

Performance Estimation of Machine Learning Algorithms in the Factor Analysis of COVID-19 Dataset

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Computers, Materials & Continua 2021年第2期66卷 1921-1936页

作者： Ashutosh kumar Dubey Sushil Narang abhishek kumar Satya Murthy Sasubilli Vicente García-Díaz Chitkara University Institute of Engineering and Technology Chitkara UniversityPunjabIndia Workday Integration Architect Huntington ColumbusOHUSA Department of Computer Science University of OviedoOviedoSpain

Novel Coronavirus Disease(COVID-19)is a communicable disease that originated during December 2019,when China officially informed the World Health Organization(WHO)regarding the constellation of cases of the disease in the city of ***,the disease started spreading to the rest of the *** this point in time,no specific vaccine or medicine is available for the prevention and cure of the *** research works are being carried out in the fields of medicinal and pharmaceutical sciences aided by data analytics and machine learning in the direction of treatment and early detection of this viral *** present report describes the use of machine learning algorithms[Linear and Logistic Regression,Decision Tree(DT),K-Nearest Neighbor(KNN),Support Vector Machine(SVM),and SVM with Grid Search]for the prediction and classification in relation to *** data used for experimentation was the COVID-19 dataset acquired from the Center for Systems Science and Engineering(CSSE),Johns Hopkins University(JHU).The assimilated results indicated that the risk period for the patients is 12–14 days,beyond which the probability of survival of the patient may *** addition,it was also indicated that the probability of death in COVID cases increases with *** death probability was found to be higher in males as compared to *** with Grid search methods demonstrated the highest accuracy of approximately 95%,followed by the decision tree algorithm with an accuracy of approximately 94%.The present study and analysis pave a way in the direction of attribute correlation,estimation of survival days,and the prediction of death *** findings of the present study clearly indicate that machine learning algorithms have strong capabilities of prediction and classification in relation to COVID-19 as well.

关键词： COVID-19 linear and logistic regression DT KNN SVM SVMwith grid search