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Analysing the relationship between drought and soil erosion using vegetation health index and RUSLE models in Godavari middle sub-basin,India

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Geoscience Frontiers 2022年第2期13卷 21-33页

作者： md masroor Haroon Sajjad Sufia Rehman Roshani Singh md Hibjur Rahaman Mehebub Sahana Raihan Ahmed Ram Avtar Department of Geography Faculty of Natural SciencesJamia Millia IslamiaNew DelhiIndia School of Environment Education and Development(SEED)University of ManchesterUnited Kingdom Graduate School of Environment Earth Science Hokkaido UniversityJapan

Drought is a natural phenomenon posing severe implications for soil,groundwater and agricultural *** has been recognized as one of the most pervasive global change drivers to affect the *** being a weakly renewable resource takes a long time to form,but it takes no time to ***,the response of soil to drought conditions as soil loss is not manifested in the existing ***,this study makes a concerted effort to analyze the relationship between drought conditions and soil erosion in the middle sub-basin of the Godavari River in *** remote sensing data was utilized for driving drought indices during ***,we constricted Temperature condition index(TCI)and Vegetation Condition Index(VCI)from Land Surface Temperature(LST)and Enhanced Vegetation Index(EVI)derived from MODIS *** and VCI were then integrated to determine the Vegetation Health Index(VHI).Revised Universal Soil Loss Equation(RUSLE)was utilized for estimating soil *** relationship between drought condition and vegetation was ascertained using the Pearson *** of the northern and southern watersheds experienced severe drought condition in the sub-basin *** mean frequency of the drought occurrence was 7.95 *** average soil erosion in the sub-basin was estimated to be 9.88 t ha^(-1)year^(-1).A positive relationship was observed between drought indices and soil erosion values(r value being 0.35).However,wide variations were observed in the distribution of spatial *** various factors,the slope length and steepness were found to be the main drivers of soil erosion in the ***,the study calls for policy measures to lessen the impact of drought and soil erosion.

关键词： Drought vulnerability Soil erosion RUSLE Vegetation Health Index(VHI) Godavari middle sub-basin

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Ensemble machine learning models based on Reduced Error Pruning Tree for prediction of rainfall-induced landslides

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International Journal of Digital Earth 2021年第5期14卷 575-596页

作者： Binh Thai Pham Abolfazl Jaafari Trung Nguyen-Thoi Tran Van Phong Huu Duy Nguyen Neelima Satyam md masroor Sufia Rehman Haroon Sajjad Mehebub Sahana Hiep Van Le Indra Prakash Division of Computational Mathematics and Engineering Institute for Computational ScienceTon Duc Thang UniversityHo Chi Minh CityViet Nam Faculty of Civil Engineering Ton Duc Thang UniversityHo Chi Minh CityViet Nam Research Institute of Forests and Rangelands Agricultural ResearchEducationand Extension Organization(AREEO)TehranIran Institute of Geological Sciences Vietnam Academy of Sciences and TechnologyHanoiViet Nam Faculty of Geography V.N.U.University of ScienceVietnam National UniversityHanoiViet Nam Discipline of Civil Engineering Indian Institute of Technology IndoreMadhya PradheshIndia Department of Geography Jamia Millia IslamiaNew DelhiIndia School of Environment Education and DevelopmentUniversity of ManchesterManchesterUK Institute of Research and Development Duy Tan UniversityDa NangViet Nam DDG(R)Geological Survey of India GujaratIndia

In this paper,we developed highly accurate ensemble machine learning models integrating Reduced Error Pruning Tree(REPT)as a base classifier with the Bagging(B),Decorate(D),and Random Subspace(RSS)ensemble learning techniques for spatial prediction of rainfallinduced landslides in the Uttarkashi district,located in the Himalayan range,*** do so,a total of 103 historical landslide events were linked to twelve conditioning factors for generating training and validation *** Mean Square Error(RMSE)and Area Under the receiver operating characteristic Curve(AUC)were used to evaluate the training and validation performances of the *** results showed that the single REPT model and its derived ensembles provided a satisfactory accuracy for the prediction of *** D-REPT model with RMSE=0.351 and AUC=0.907 was identified as the most accurate model,followed by RSS-REPT(RMSE=0.353 and AUC=0.898),B-REPT(RMSE=0.396 and AUC=0.876),and the single REPT model(RMSE=0.398 and AUC=0.836),*** prominent ensemble models proposed and verified in this study provide engineers and modelers with insights for development of more advanced predictive models for different landslide-susceptible areas around the world.

关键词： Machine learning ensemble modeling Bagging Decorate Random Subspace

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Status and prospects for symmetric organic redox flow batteries

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Journal of Energy Chemistry 2025年第1期100卷 125-143页

作者： md Al Raihan C.Adam Dyker Department of Chemistry University of New Brunswick

As environmental concerns from fossil fuel consumption intensify, large-scale energy storage becomes imperative for the integration of renewable sources like wind, hydro, and solar with the electrical *** flow batteries, particularly those employing organic molecules, are positioned as a key technology for this purpose. This review explores the growing field of symmetric organic redox flow batteries(ORFBs) within this context. Unlike traditional asymmetric designs based on unique active materials for each electrode, symmetric ORFBs involve a single bipolar species for both electrodes. This review highlights the benefits of a symmetric design, and categorizes five distinct classes of organic bipolar molecules used in both aqueous and non-aqueous solvents. By providing a comprehensive overview of their cell cycling and performance characteristics, the strengths and weaknesses of the diverse categories of bipolar molecules are highlighted for both solvent systems, as are opportunities for future development. This should guide new research directions and advance the development of practical symmetric ORFBs.

关键词： Redox flow battery Symmetric battery Organic battery Aqueous electrolyte Non-aqueous electrolyte

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Regeneration mechanisms and therapeutic strategies for neuromuscular junctions in aging and diseases

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Neural Regeneration Research 2025年第1期20卷 193-194页

作者： Masashi Fujitani Abu md Mamun Tarif Yoshinori Otani Department of Anatomy and Neuroscience Faculty of MedicineShimane UniversityShimaneJapan

The neuromuscular junction(NMJ)is an essential synaptic structure composed of motor neurons,skeletal muscles,and glial cells that orchestrate the critical process of muscle contraction(Li et al.,2018).The typical NMJ structure is classically described as having a“pretzel-like”shape in mice(Figure 1),whereas human NMJs have a smaller,fragmented structure throughout *** NMJs exhibit smaller or fragmented endplates,partial denervation,reduced numbers of synaptic vesicles,abnormal presynaptic mitochondria,and dysfunctional perisynaptic Schwann cells(Alhindi et al.,2022).

关键词： aging structure Figure

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Steel Surface Defect Detection Using Learnable Memory Vision Transformer

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Computers, Materials & Continua 2025年第1期82卷 499-520页

作者： Syed Tasnimul Karim Ayon Farhan md.Siraj Jia Uddin Department of Computer Science and Engineering BRAC UniversityDhaka1212Bangladesh Department of AI and Big Data Endicott CollegeWoosong UniversityDaejeon34606Republic of Korea

This study investigates the application of Learnable Memory Vision Transformers(LMViT)for detecting metal surface flaws,comparing their performance with traditional CNNs,specifically ResNet18 and ResNet50,as well as other transformer-based models including Token to Token ViT,ViT withoutmemory,and Parallel *** awidely-used steel surface defect dataset,the research applies data augmentation and t-distributed stochastic neighbor embedding(t-SNE)to enhance feature extraction and *** techniques mitigated overfitting,stabilized training,and improved generalization *** LMViT model achieved a test accuracy of 97.22%,significantly outperforming ResNet18(88.89%)and ResNet50(88.90%),aswell as the Token to TokenViT(88.46%),ViT without memory(87.18),and Parallel ViT(91.03%).Furthermore,LMViT exhibited superior training and validation performance,attaining a validation accuracy of 98.2%compared to 91.0%for ResNet 18,96.0%for ResNet50,and 89.12%,87.51%,and 91.21%for Token to Token ViT,ViT without memory,and Parallel ViT,*** findings highlight the LMViT’s ability to capture long-range dependencies in images,an areawhere CNNs struggle due to their reliance on local receptive fields and hierarchical feature *** additional transformer-based models also demonstrate improved performance in capturing complex features over CNNs,with LMViT excelling particularly at detecting subtle and complex defects,which is critical for maintaining product quality and operational efficiency in industrial *** instance,the LMViT model successfully identified fine scratches and minor surface irregularities that CNNs often *** study not only demonstrates LMViT’s potential for real-world defect detection but also underscores the promise of other transformer-based architectures like Token to Token ViT,ViT without memory,and Parallel ViT in industrial scenarios where complex spatial relationships are *** research m

关键词： Learnable Memory Vision Transformer(LMViT) Convolutional Neural Networks(CNN) metal surface defect detection deep learning,computer vision image classification learnable memory gradient clipping label smoothing t-SNE visualization

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Ru/NiMnB spherical cluster pillar for highly proficient green hydrogen electrocatalyst at high current density

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Journal of Energy Chemistry 2025年第1期100卷 397-408页

作者： md Ahasan Habib Shusen Lin Mehedi Hasan Joni Sumiya Akter Dristy Rutuja Mandavkar Jae-Hun Jeong Jihoon Lee Department of Electronic Engineering College of Electronics and Information Kwangwoon University

Advanced OER/HER electrocatalytic alternatives are crucial for the wide adaptation of green hydrogen ***,Ru/NiMnB spherical cluster pillar （SCP）,denoted as Ru/NiMnB,is synthesized using a combination of electro-deposition and hydrothermal *** investigation of Ru doping in the NiMnB matrix revealed significant improvements in electrocatalytic *** Ru/NiMnB SCPs demonstrate superior OER/HER activity with low overpotentials of 150 and 103 mV at 50mA/cm2in 1 M KOH,making them highly competitive with state-of-the-art ***,the Ru/NiMnB SCPs exhibit a low 2-E cell voltage of 2.80 V at ultra-high current density of 2,000 m A/cm2in 1 M KOH,outperforming the standard benchmark electrodes of RuO2||Pt/C,thereby positioning Ru/NiMnB as one of the best bifunctional *** SCPs exhibit exceptional high-current characteristics,stability and corrosion resistance,as evidenced by continuous operation at 1,000 mA/cm2high-current density for over 150 h in 6 M KOH at elevated temperatures under harsh industrial *** a small amount of Ru incorporation significantly enhances the electrocatalytic performances of NiMnB,attributed to increased active sites and improved intrinsic properties such as conductivity,adsorption/desorption capability and reaction ***,Ru/NiMnB SCPs present a promising bi-functional electrode concept for efficient green H2production.

关键词： Potassium hydroxide

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Rhabdomyolysis-related acute kidney injury in COVID-19:A critical concern

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World Journal of Virology 2025年第1期14卷 127-129页

作者： md Safiullah Sarker Virology Laboratory Infectious Diseases DivisionDhaka 1212Bangladesh

Rhabdomyolysis is a severe condition characterized by the breakdown of muscle tissue leading to the release of intracellular components into the *** condition,when associated with acute kidney injury(AKI),can result in significant morbidity and mortality,particularly in the context of coronavirus disease 2019(COVID-19).This editorial discusses a retrospective study on patients with COVID-19 who developed rhabdomyolysis-related *** study highlights that patients with rhabdomyolysis exhibited higher inflammatory markers,such as Creactive protein,ferritin,and procalcitonin,and experienced worse clinical outcomes compared to those with other causes of *** findings underscore the importance of early recognition and management of rhabdomyolysis in COVID-19 patients to improve prognosis and reduce mortality rates.

关键词： Rhabdomyolysis Acute kidney injury COVID-19 SARS-CoV-2 Creatine kinase Inflammation Prognosis Mortality

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Capturing transition and non-transition flows with a new shear stress transport model

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Chinese Journal of Aeronautics 2023年第3期36卷 121-136页

作者： md Mizanur RAHMAN School of Mechanical Engineering Hangzhou Dianzi UniversityHangzhou 310018China

A new Shear Stress Transport(SST)k-ω model is devised to integrate salient features of both the non-transitional SST k-ω model and correlation-based γ-Re_(θ) transition *** exceptionally simplified approach is applied to extend the New SST(NSST)model capabilities toward transition/non-transition ***’s stress-intensity factor R_(b)=|-uv|/k can be parameterized with the wall-distance dependent Reynolds number Re_(y)=√ky/v;however,as the Re_(y)is replaced by a“flow-structure-adaptive”parameter R_(μ)=v_(T)/v,the resulting R_(b)is capable of capturing various transition phenomena *** prospective stress-intensity parameter R_(b)=R_(b)(Re_(y),R_(μ))is incorporated in the constitutive relations for eddy-viscosity v_(T) and production term P_(k).The proposed formulation is intrinsically plausible,having a dramatic impact on the prediction of bypass,separation-induced and natural transitions together with non-transitional *** extra viscous-production term P_(k)^(lim) is added with the k-equation to ensure proper generation of k at the viscous sublayer when computing separation-induced transition over a Low-Reynolds Number(LRN)*** demonstrate that the NSST k-ω model maintains an excellent consistency with both SST k-ω and γ-Re_(θ) models.

关键词： γ-Re_(θ)model Non-transition Stress-intensity parameter SST model Transition

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Pressure-dependent physical properties of cubic SrΒO3(Β=Cr,Fe)perovskites investigated by density functional theory

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Chinese Physics B 2020年第12期29卷 212-220页

作者： md Zahid Hasan md Rasheduzzaman Khandaker Monower Hossain Department of Electrical and Electronic Engineering International Islamic University ChittagongKumiraChittagong-4318Bangladesh Department of Materials Science and Engineering University of RajshahiRajshahi-6205Bangladesh

We perform the first-principles investigations of the structural,elastic,electronic,and optical properties of SrBO3(B=Cr,Fe)perovskites under pressure based on density functional theory(DFT).This is the first detailed pressure-dependent study of the physical properties for these *** calculated structural parameters are consistent with the existing experimental results and slightly decrease with the application of *** mechanical properties are discussed in detail and reveal that the SrCrO3 is harder than *** pressure,these compounds behave like half-metals,confirmed by their band structure and density of *** the SrCrO3 retains its half-metallic nature under pressure,SrFeO3 becomes metallic for both up-spin and down-spin *** charge density and bond overlap population reveal the covalent nature of Cr–O bond and Fe–O bond in the studied *** optical properties of SrBO3,also discussed for the first time,reveal some interesting results.

关键词： density functional theory(DFT) effects of pressure electronic band structure optical properties

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Active Cell Balancing Control Strategy for Parallelly Connected LiFePO_(4) Batteries

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CSEE Journal of Power and Energy Systems 2021年第1期7卷 86-92页

作者： md Ohirul Qays Yonis Buswig md Liton Hossain md Momtazur Rahman Ahmed Abu-Siada Department of Electrical and Electrical Engineering Faculty of EngineeringUniversity Malaysia SarawakKota SamarahanSarawakMalaysia Department of Electrical and Computer Engineering Curtin UniversityKent StreetBentleyPerth 6102WAAustralia Electron Science Research Institute Edith Cowan University270 Joondalup DriveJoondalupWA6027Australia

While several recent studies have focused on elimi-nating the imbalance of energy stored in series-connected battery cells,very little attention has been given to balancing the energy stored in parallel-connected battery *** such,this paper aims at presenting a new balancing approach for parallel LiFePO_(4) battery *** this regard,a Backpropagation Neural Network(BPNN)based technique is employed to develop a Battery Management System(BMS)that can assess the charging status of all cells and control its operations through a DC/DC Buck-Boost *** results demonstrate the effectiveness of the proposed approach in balancing the energy stored in parallel-connected battery cells in which the state of charge(SoC)estimation error is found to be only 1.15%.

关键词： Active cell balancing battery management system DC/DC buck-boost converter state of charge estimation

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