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Germ cell development in teleost gonads

Aquaculture and Fisheries 2024年第3期9卷 422-436页

作者： Partigya sharma Shriya Purohit Sachin kothiyal Indrashis Bhattacharya Department of Zoology HNB Garhwal UniversitySrinagar CampusPauri Garhwal246174India

Among vertebrate species,fishes are considered to be the most developmentally diverse taxa exhibiting remarkable gonadal plasticity with capacity of sex *** determination in teleost fishes is governed via a complex regulatory network involving multiple genetic,environmental(temperature,population density,pH),social interaction/stress *** germ-line originates as Primordial germ cells(PGC)from cleavage blastomeres/endoderm and gets specified by maternal inheritance of Vasa,N anos,Tdrds,Dnd,Dazl etc and subsequently migrates to reach the embryonic gonadal ***-hatching,mitotically active germ cells(Gc)continue to proliferate via two distinct pathways-firstly,stem cell-like mode followed by meiosis-committed cystic *** Japanese rice fish medaka,Oryzias latipes sex gets determined on the chromosomal basis,where XY becomes a male because of testicular Dmy transcription and XX develops as female owing to Gc restricted Foxl 3 *** specific germ-line stem cell systems also have been found in adult *** in teleost fishes,the developmental fate of transplanted Gc do not depend on the sex of the donor rather solely relies upon the sex of the ***,sexually mature piscine gonads remain developmentally plastic showing extensive responsiveness towards sex *** critical regulation of gonadal differentiation is directed by female specific 17β-estradiol(E2)and bio-active male androgen 11-keto-testosretone(11-kT).Various transcription factors(TFs)e.g.-Dmrt1,DAX1,Ad4BP/SF-1,Foxl 2 regulate the bio-conversion rate of testosterone(T)to either E2 or ***,multiple endocrine factors(EFs)e.g.-LH,FSH,E2,11-kT and growth factors(GFs)e.g-AMH,GSDF,IGF-1/3,GDF-9/BMP-15 critically induce Gc differentiation to regulate the gametogenic *** this article we have precisely discussed the endocrine regulation of Gc development during gonadal maturation of teleosts.

关键词： Testis Spermatogenesis Sperm Ovary Oogenesis Egg Gonads

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Effectiveness of hybrid ensemble machine learning models for landslide susceptibility analysis:Evidence from Shimla district of North-west Indian Himalayan region

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Journal of Mountain Science 2024年第7期21卷 2368-2393页

作者： sharma Aastha SAJJAD Haroon RAHAMAN Md Hibjur SAHA Tamal kanti BHUYAN Nirsobha Department of Geography Faculty of SciencesJamia Millia IslamiaNew Delhi-110025India

The Indian Himalayan region is frequently experiencing climate change-induced ***,landslide susceptibility assessment assumes greater significance for lessening the impact of a landslide *** paper makes an attempt to assess landslide susceptibility in Shimla district of the northwest Indian Himalayan *** examined the effectiveness of random forest(RF),multilayer perceptron(MLP),sequential minimal optimization regression(SMOreg)and bagging ensemble(B-RF,BSMOreg,B-MLP)models.A landslide inventory map comprising 1052 locations of past landslide occurrences was classified into training(70%)and testing(30%)*** site-specific influencing factors were selected by employing a multicollinearity *** relationship between past landslide occurrences and influencing factors was established using the frequency ratio *** effectiveness of machine learning models was verified through performance *** landslide susceptibility maps were validated by the area under the receiver operating characteristic curves(ROC-AUC),accuracy,precision,recall and *** key performance metrics and map validation demonstrated that the BRF model(correlation coefficient:0.988,mean absolute error:0.010,root mean square error:0.058,relative absolute error:2.964,ROC-AUC:0.947,accuracy:0.778,precision:0.819,recall:0.917 and F-1 score:0.865)outperformed the single classifiers and other bagging ensemble models for landslide *** results show that the largest area was found under the very high susceptibility zone(33.87%),followed by the low(27.30%),high(20.68%)and moderate(18.16%)susceptibility *** factors,namely average annual rainfall,slope,lithology,soil texture and earthquake magnitude have been identified as the influencing factors for very high landslide *** texture,lineament density and elevation have been attributed to high and moderate ***,the study calls for devising suitable landslide mitig

关键词： Landslide susceptibility Site-specific factors Machine learning models Hybrid ensemble learning Geospatial techniques Himalayan region

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Variation in the Flaring Potential of Different Sunspot Groups During Different Phases of Solar Cycles 23 and 24

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Research in Astronomy and Astrophysics 2024年第2期24卷 144-153页

作者： Abha Singh Anurag Chaudhari Gyaneshwar sharma A.k.Singh Department of Physics T.D.P.G.College Jaunpur-222002India Department of Physics Banaras Hindu UniversityVaranasi-221005India

In this present study,we have analyzed different types of X-ray solar flares(C,M,and X classes)coming out from different classes of sunspot groups(SSGs).The data which we have taken under this study cover the duration of 24 yr from 1996 to *** this,we observed a total of 15015 flares(8417 in SC-23 and 6598 in SC-24)emitted from a total of 33780 active regions(21746 in SC-23 and 12034 in SC-24)with sunspot *** defined the flaring potential or flare-production potential as the ratio of the total number of flares produced from a particular type of SSG to the total number of the same-class SSGs observed on the solar *** we studied yearly changes in the flaring potential of different McIntosh class groups of sunspots in different phases of SC-23 and *** addition,we investigated yearly variations in the potential of producing flares by different SSGs(A,B,C,D,E,F,and H)during different phases(ascending,maximum,descending,and minimum)of SC-23 and *** are our findings:(1)D,E,and F SSGs have the potential of producing flares≥8 times greater than A,B,C and H SSGs;(2)The larger and more complex D,E,and F SSGs produced nearly 80%of flares in SC-23 and 24;(3)The A,B,C and H SSGs,which are smaller and simpler,produced only 20%of flares in SC-23 and 24;(4)The biggest and most complex SSGs of F-class have flaring potential 1.996 and 3.443 per SSG in SC-23 and 24,respectively.(5)The potential for producing flares in each SSG is higher in SC-24 than in SC-23,although SC-24 is a weaker cycle than SC-23.(6)The alterations in the number of flares(C+M+X)show different time profiles than the alterations in sunspot numbers during SC-23 and 24,with several peaks.(7)The SSGs of C,D,E,and H-class have the highest flaring potential in the descending phase of both SC-23 and 24.(8)F-class SSGs have the highest flaring potential in the descending phase of SC-23 but also in the maximum phase of SC-24.

关键词： (Sun:)sunspots-Sun flares-Sun activity-Sun magnetic fields-Sun filaments-prominences

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Energy-growth nexus for‘Renewable Energy Country Attractiveness Index’countries:Evidence from new econometric methods

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Geoscience Frontiers 2024年第3期15卷 298-311页

作者： Mandeep Mahendru Aviral kumar Tiwari Gagan Deep sharma Solomon Nathaniel Mansi Gupta Szechenyi Istvan University GyorHungary Indian Institute of Management BodhgayaIndia University School of Management Studies Guru Gobind Singh Indraprastha UniversitySector 16 CDwarkaNew DelhiIndia Department of Economics University of LagosAkokaNigeria Centre for Financial Innovation S P Jain Institute of Management and ResearchMumbaiIndia

This study explores the connections between renewable energy consumption(REC),non-renewable energy consumption(NREC),gross fixed capital formation(GFCF),the labor force(LF),and economic growth(GDP)in Renewable Energy Country Attractiveness Index(RECAI)countries for *** quantify the nexus between REC,NREC,and GDP while utilizing a production model framework and including the measures of labor and capital,for suggesting a phase-wise strategy to attain the sustainable development *** use robust methodologies including Lagrange Multiplier(LM)panel unit root tests with trend shifts,Westerlund cointegration test,LM bootstrap technique for cointegration with breaks,continuously updated fully modified(CUP-FM)and continuously updated bias-corrected(CUPBC)estimators,Augmented Mean Group(AMG)approach,fully modified ordinary least squares,dynamic ordinary least squares,Canonical Cointegrating Regression(CCR),and panel causality test proposed by Canning&*** compute non-parametric time-varying coefficients with fixed effects for seeing the impact of GFCF,LF,REC,and NREC on *** results press upon policymakers to shift toward clean energy and REC for attaining the environmental goals(SDGs 6,7,13,and 15)and the economic goals(SDGs 1,2,8,and 10).While this shift would help developed economies,which have already attained the economic goals,to progress on the front of environmental goals,it would enable developing countries to progress on both fronts in a balanced manner.

关键词： Renewable energy consumption Economic growth Non-renewable energy consumption CUP-BC CUP-FM Time-varying coefficients with fixed effects

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Do natural resources impact economic growth:An investigation of P5+1 countries under sustainable management

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Geoscience Frontiers 2024年第3期15卷 192-208页

作者： Sanjeet Singh Gagan Deep sharma Magdalena Radulescu Daniel Balsalobre-Lorente Pooja Bansal University Centre for Research and Development Chandigarh UniversityGharuanMohaliPunjabIndia University School of Management Studies Guru Gobind Singh Indraprastha UniversityDwarkaDelhiIndia Department of Finance Accounting and EconomicsUniversity of PitestiPitesti 110040Romania Institute for Doctoral and Post-Doctoral Studies University“Lucian Blaga”SibiuSibiu 550024Romania Department of Applied Economics I University of Castilla-La ManchaSpain Department of Management Faculty of Economics and ManagementCzech University of Life Sciences PraguePrague 16500Czech Republic

Natural resources represent the base of our living and the entire economic *** depletion is a major challenge for the economic development of both developed and developing *** effi-cient use is an indispensable requirement and must be the aim of the public policies designed by the authorities *** this research,we have investigated the impact of the natural resources rent on the economic growth in some major wealthy economies of the world(P5+1 countries namely:US,Uk,France,China,Russia,and Germany).We have applied a quantile-on-quantile regression to analyse this impact on different quantiles and a cross-sectional autoregressive distributed lag(CS-ARDL)approach for the panel of these six *** Dumitrescu-Hurlin panel causality test was also used to check the causality between natural resource rents and economic growth in these *** show a negative relationship between natural resources rent and economic growth for the panel but a different impact on quantiles in each *** for China and the US,a positive effect can be noticed for both lower and higher quantiles of natural resources and economic *** Dumitrescu-Hurlin causality test shows that natural resources can predict economic growth only in China,the U.S.,and the *** contrast,no causality was found for the other four countries included in the *** suggest that nations invest in wind and solar projects,use biofuels and nuclear energy,introduce a temporary profit tax to protect consumers from escalating energy prices,and increase energy efficiency in buildings and *** would benefit from a regulatory framework that is uniform and exhaustive,as well as easier to traverse and more receptive to innovation and ***-private partnership investments in innovation,innovation incentives,and environmental sector opportunities may foster long-term economic growth。

关键词： Natural resources rent Economic growth Quantile-on-quantile regression Cross-sectional ARDL P5+1 countries

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A review of torsional vibration mitigation techniques using active control and machine learning strategies

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Petroleum 2024年第3期10卷 411-426页

作者： Aditya sharma khizar Abid Saket Srivastava Andres Felipe Baena Velasquez Catalin Teodoriu The University of Oklahoma NormanOKUSA

Drilling is one of the most challenging and expensive processes in hydrocarbon extraction and geothermal well *** faced during drilling can increase the non-productive time(NPT)greatly,resulting in inflating the drilling cost and also pose a safety *** of the main problems faced during drilling that limits the life of drilling equipment and tools and decreases the overall productivity of the system is drilling *** vibrations can be categorized into three modes:axial,lateral,and ***-slip vibrations are a type of torsional vibration in which the bottom hole assembly(BHA)periodically stops to rotate followed by a spike in the bottom hole *** paper provides a comprehensive review of techniques used to control and mitigate torsional vibration with an emphasis on stick-slip.A brief introduction to drillstring and friction modeling is presented followed by a concise summary of passive control techniques to control *** the focus is shifted to an up-to-date review of active control and machine learning for stick-slip control and *** paper ultimately highlights the importance of adapting novel control and mitigation concepts to improve stick slip detection and improve the overall drilling process.A unique solution is insufficient to control a complex process such as drilling,but integration of various techniques has been found promising.

关键词： Drilling vibrations Controllers Mitigations strategies Stick slip Torsional vibrations Machine Learning

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Lighting up plants with near-infrared fluorescence probes

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Science China Chemistry 2024年第3期67卷 774-787页

作者： Yida Pang Mengjiao Lu Hyeonji Rha Wenchao Yang Amit sharma Yao Sun Jong Seung kim National key Laboratory of Green Pesticide Key Laboratory of Green Pesticide and Agricultural BioengineeringMinistry of EducationCenter for R&D of Fine Chemicals of Guizhou UniversityGuiyang 550025China National key Laboratory of Green Pesticide College of ChemistryCentral China Normal UniversityWuhan 430079China Department of Chemistry Korea UniversitySeoul 02841Korea CSIR-Central Scientific Instruments Organisation Sector-30CChandigarh160030India TheranoChem Incorporation Seongbuk-guSeoul02856Korea

Fluorescence imaging is a non-invasive and highly sensitive bioimaging technique that has shown remarkable strides in plant science. It enables real-time monitoring and analysis of biological and pathological processes in plants by labeling specific molecular or cellular structures with fluorescent probes. However, tissue scattering and phytochrome interference have been obstacles for conventional fluorescence imaging of plants in the ultraviolet and visible spectrum, resulting in unsatisfactory imaging quality. Fortunately, advances in near-infrared(NIR) fluorescence imaging technology(650-900 nm) offer superior spatial-temporal resolution and reduced tissue scattering, which is sure to improve plant imaging quality. In this review, we summarize recent progress in the development of NIR fluorescence imaging probes and their applications for in vivo plant imaging and the identification of plant-related biomolecules. We hope this review provides a new perspective for plant science research and highlights NIR fluorescence imaging as a powerful tool for analyzing plant physiology, adaptive mechanisms, and coping with environmental stress in the near future.

关键词： NIR fluorescent probe plant imaging biologic application

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Machine Learning Techniques Using Deep Instinctive Encoder-Based Feature Extraction for Optimized Breast Cancer Detection

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Computers, Materials & Continua 2024年第2期78卷 2441-2468页

作者： Vaishnawi Priyadarshni Sanjay kumar sharma Mohammad khalid Imam Rahmani Baijnath kaushik Rania Almajalid Department of Computer Science Gautam Buddha UniversityGreater NoidaUttar PradeshIndia College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia School of Computer Science Shri Vaishno Devi UniversityKatraIndia

Breast cancer(BC)is one of the leading causes of death among women worldwide,as it has emerged as the most commonly diagnosed malignancy in *** detection and effective treatment of BC can help save women’s *** an efficient technology-based detection system can lead to non-destructive and preliminary cancer detection *** paper proposes a comprehensive framework that can effectively diagnose cancerous cells from benign cells using the Curated Breast Imaging Subset of the Digital Database for Screening Mammography(CBIS-DDSM)data *** novelty of the proposed framework lies in the integration of various techniques,where the fusion of deep learning(DL),traditional machine learning(ML)techniques,and enhanced classification models have been deployed using the curated *** analysis outcome proves that the proposed enhanced RF(ERF),enhanced DT(EDT)and enhanced LR(ELR)models for BC detection outperformed most of the existing models with impressive results.

关键词： Autoencoder breast cancer deep neural network convolutional neural network image processing machine learning deep learning

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An Insight Survey on Sensor Errors and Fault Detection Techniques in Smart Spaces

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Computer Modeling in Engineering & Sciences 2024年第3期138卷 2029-2059页

作者： Sheetal sharma kamali Gupta DeepaliGupta Shalli Rani Gaurav Dhiman Chitkara University Institute of Engineering and Technology Chitkara UniversityPunjab140401India PG Department of Information Technology Goswami Ganesh Dutta Sanatan Dharma CollegeChandigarh160030India Department of Computer Science Government Bikram College of CommercePatialaIndia Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon University Centre for Research and Development Department of Computer Science and EngineeringChandigarh UniversityMohali140413India Department of Computer Science and Engineering Graphic Era Deemed to be UniversityDehradun248002India Division of Research and Development Lovely Professional UniversityPunjab144001India

The widespread adoption of the Internet of Things (IoT) has transformed various sectors globally, making themmore intelligent and connected. However, this advancement comes with challenges related to the effectiveness ofIoT devices. These devices, present in offices, homes, industries, and more, need constant monitoring to ensuretheir proper functionality. The success of smart systems relies on their seamless operation and ability to handlefaults. Sensors, crucial components of these systems, gather data and contribute to their functionality. Therefore,sensor faults can compromise the system’s reliability and undermine the trustworthiness of smart *** address these concerns, various techniques and algorithms can be employed to enhance the performance ofIoT devices through effective fault detection. This paper conducted a thorough review of the existing literature andconducted a detailed *** analysis effectively links sensor errors with a prominent fault detection techniquecapable of addressing them. This study is innovative because it paves theway for future researchers to explore errorsthat have not yet been tackled by existing fault detection methods. Significant, the paper, also highlights essentialfactors for selecting and adopting fault detection techniques, as well as the characteristics of datasets and theircorresponding recommended techniques. Additionally, the paper presents amethodical overview of fault detectiontechniques employed in smart devices, including themetrics used for evaluation. Furthermore, the paper examinesthe body of academic work related to sensor faults and fault detection techniques within the domain. This reflectsthe growing inclination and scholarly attention of researchers and academicians toward strategies for fault detectionwithin the realm of the Internet of Things.

关键词： Error fault detection techniques sensor faults outliers Internet of Things

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Exploring the Potential of Syzygium cumini(L.)Skeels(Jamun)Seed Powder as an Eco-Friendly Agent for Developing Friction Ridges on Porous and Nonporous Surfaces

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Journal of Forensic Science and Medicine 2024年第2期10卷 75-83页

作者： Vaibhav sharma Abhishek R.Rai Divyansh Jain Poonam kumari Varad Nagar Anubhav Singh kumud kant Awasthi Archana Gautam Tina sharma Mahipal Singh Sankhla Anuj sharma Department of Forensic Science Vivekananda Global UniversityJaipurRajasthanIndia School of Forensics Risk Management and National SecurityRashtriya Raksha UniversityLavadGujaratIndia Department of Life Sciences Vivekananda Global UniversityJaipurRajasthanIndia Department of Forensic Science UIAHSChandigarh UniversityMohaliPunjabIndia University Centre for Research and Development Chandigarh UniversityMohaliPunjabIndia Department of Forensic Science ITM UniversityGwaliorM.P.India

Background:Development of obscured fingerprints on a diverse range of surfaces is a crucial aspect of forensic *** and Objectives:In this particular study,the utilization of Syzygium cumini(L.)Skeels(Jamun)seed powder was examined for the purpose of revealing hidden fingerprints on a variety of surfaces,including both permeable and impermeable *** and Methods:The seed powder was extracted using a simple process and was analysed using multiple analytical *** efficacy of the jamun seed powder in developing latent fingerprints was ***:The findings of this investigation demonstrate that the jamun seed powder was capable of producing fingerprint patterns of exceptional quality and clarity on numerous ***:This research highlights the potential use of jamun seed powder as a practical and effective alternative for the development of hidden fingerprints in forensic investigations,while also providing cost-effectiveness.

关键词： Forensic investigation jamun seed latent fingerprints medicinal value

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