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Effects of Initial and Boundary Conditions on Heavy Rainfall Simulation over the Yellow Sea and the Korean Peninsula:Comparison of ECMWF and NCEP Analysis Data Effects and Verification with Dropsonde Observation

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Advances in Atmospheric Sciences 2024年第9期41卷 1787-1803页

作者： Jiwon HWANG dong-hyun cha donghyuck YOON Tae-Young GOO Sueng-Pil JUNG Department of Civil Urban Earth and Environmental Engineering Ulsan National Institute of Science and TechnologyUlsan 44919South Korea Program in Atmospheric and Oceanic Sciences Princeton UniversityPrincetonNew Jersey 08544USA National Institute of Meteorological Sciences NIMSJeju 63568South Korea

This study evaluated the simulation performance of mesoscale convective system(MCS)-induced precipitation,focusing on three selected cases that originated from the Yellow Sea and propagated toward the Korean *** evaluation was conducted for the European Centre for Medium-Range Weather Forecasts(ECMWF)and National Centers for Environmental Prediction(NCEP)analysis data,as well as the simulation result using them as initial and lateral boundary conditions for the Weather Research and Forecasting ***,temperature and humidity profiles from 3D dropsonde observations from the National Center for Meteorological Science of the Korea Meteorological Administration served as validation *** showed that the ECMWF analysis consistently had smaller errors compared to the NCEP analysis,which exhibited a cold and dry bias in the lower levels below 850 *** model,in terms of the precipitation simulations,particularly for high-intensity precipitation over the Yellow Sea,demonstrated higher accuracy when applying ECMWF analysis data as the initial *** advantage also positively influenced the simulation of rainfall events on the Korean Peninsula by reasonably inducing convective-favorable thermodynamic features(i.e.,warm and humid lower-level atmosphere)over the Yellow *** conclusion,this study provides specific information about two global analysis datasets and their impacts on MCS-induced heavy rainfall simulation by employing dropsonde observation ***,it suggests the need to enhance the initial field for MCS-induced heavy rainfall simulation and the applicability of assimilating dropsonde data for this purpose in the future.

关键词： initial conditions dropsonde heavy rainfall forecast global model analysis evaluation

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Intracellular zinc signaling via Kruppel-like transcription factor 6 promotes HuD expression in pancreatic β cell

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Genes & Diseases 2024年第4期11卷 24-27页

作者： Seongho cha Chongtae Kim Myeongwoo Jung Seungyeon Ryu Sukyoung Han Wook Kim Eun Kyung Lee Department of Biochemistry Department of Biomedicine&Health SciencesCollege of MedicineThe Catholic University of KoreaSeoul 06591South Korea Catholic Institute for Visual Science College of MedicineThe Catholic University of KoreaSeoul 06591South Korea Department of Molecular Science&Technology Ajou UniversitySuwon 16499South Korea

Dysfunction of pancreaticβcells caused by zinc deficiency is related to the pathogenesis of diabetes.1 Impaired zinc homeostasis in diabetes is associated with reduced zinc transporters.2 Down-regulation of HuD,an es... 详细信息

关键词： βcell homeostasis zinc

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Deep Convolutional Neural Networks for Accurate Classification of Gastrointestinal Tract Syndromes

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Computers, Materials & Continua 2024年第1期78卷 1207-1225页

作者： Zahid Farooq Khan Muhammad Ramzan Mudassar Raza Muhammad Attique Khan Khalid Iqbal Taerang Kim Jae-Hyuk cha Department of Computer Science COMSATS University IslamabadWah CampusWah47040Pakistan Department of Computer Science and Mathematics Lebanese American UniversityBeirut13-5053Lebanon Department of Computer Science HITEC UniversityTaxila47080Pakistan Department of Computer Science COMSATS University IslamabadAttock CampusAttock43600Pakistan Department of Computer Science Hanyang UniversitySeoul04763Korea

Accurate detection and classification of artifacts within the gastrointestinal(GI)tract frames remain a significant challenge in medical image *** science combined with artificial intelligence is advancing to automate the diagnosis and treatment of numerous *** to this is the development of robust algorithms for image classification and detection,crucial in designing sophisticated systems for diagnosis and *** study makes a small contribution to endoscopic image *** proposed approach involves multiple operations,including extracting deep features from endoscopy images using pre-trained neural networks such as Darknet-53 and ***,feature optimization utilizes the binary dragonfly algorithm(BDA),with the fusion of the obtained feature *** fused feature set is input into the ensemble subspace k nearest neighbors(ESKNN)*** Kvasir-V2 benchmark dataset,and the COMSATS University Islamabad(CUI)Wah private dataset,featuring three classes of endoscopic stomach images were *** assessments considered various feature selection techniques,including genetic algorithm(GA),particle swarm optimization(PSO),salp swarm algorithm(SSA),sine cosine algorithm(SCA),and grey wolf optimizer(GWO).The proposed model excels,achieving an overall classification accuracy of 98.25% on the Kvasir-V2 benchmark and 99.90% on the CUI Wah private *** approach holds promise for developing an automated computer-aided system for classifying GI tract syndromes through endoscopy images.

关键词： Feature fusion Darknet-53 Xception binary dragonfly algorithm ensemble

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Human Gait Recognition for Biometrics Application Based on Deep Learning Fusion Assisted Framework

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Computers, Materials & Continua 2024年第1期78卷 357-374页

作者： Ch Avais Hanif Muhammad Ali Mughal Muhammad Attique Khan Nouf Abdullah Almujally Taerang Kim Jae-Hyuk cha Department of Electrical Engineering HITEC UniversityTaxila47080Pakistan Department of Computer Science and Mathematics Lebanese American UniversityBeirutLebanon Department of Computer Science HITEC UniversityTaxila47080Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Hanyang UniversitySeoul04763Korea

The demand for a non-contact biometric approach for candidate identification has grown over the past ten *** on the most important biometric application,human gait analysis is a significant research topic in computer *** have paid a lot of attention to gait recognition,specifically the identification of people based on their walking patterns,due to its potential to correctly identify people far *** recognition systems have been used in a variety of applications,including security,medical examinations,identity management,and access *** systems require a complex combination of technical,operational,and definitional *** employment of gait recognition techniques and technologies has produced a number of beneficial and well-liked *** proposes a novel deep learning-based framework for human gait classification in video *** framework’smain challenge is improving the accuracy of accuracy gait classification under varying conditions,such as carrying a bag and changing *** proposed method’s first step is selecting two pre-trained deep learningmodels and training fromscratch using deep transfer ***,deepmodels have been trained using static hyperparameters;however,the learning rate is calculated using the particle swarmoptimization(PSO)***,the best features are selected from both trained models using the Harris Hawks controlled Sine-Cosine optimization *** algorithm chooses the best features,combined in a novel correlation-based fusion ***,the fused best features are categorized using medium,bi-layer,and tri-layered neural *** the publicly accessible dataset known as the CASIA-B dataset,the experimental process of the suggested technique was carried out,and an improved accuracy of 94.14% was *** achieved accuracy of the proposed method is improved by the recent state-of-the-art techniques that show the significance of this wor

关键词： Gait recognition covariant factors biometric deep learning fusion feature selection

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Enhancement of vertical phase separation in sequentially deposited organic photovoltaics through the independent processing of additives

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Journal of Energy Chemistry 2024年第7期94卷 768-777页

作者： Damin Lee changwoo Park Gayoung Ham Young Yong Kim Sung-Nam Kwon Junyeong Lee Sungjin Jo Seok-In Na Hyojung cha Department of Hydrogen and Renewable Energy Kyungpook National UniversityDaegu 41566Republic of Korea Department of Energy Convergence and Climate change Kyungpook National UniversityDaegu 41566Republic of Korea Pohang Accelerator Laboratory(PAL) Pohang University of Science and Technology(POSTECH)PohangGyeongbuk 37673Republic of Korea Department of Flexible and Printable Electronics Jeonbuk National UniversityJeonju-siJeollabuk-do 54896Republic of Korea School of Energy Engineering Kyungpook National UniversityDaegu 41566Republic of Korea

Herein,the impact of the independent control of processing additives on vertical phase separation in sequentially deposited (SD) organic photovoltaics (OPVs) and its subsequent effects on charge carrier kinetics at the electron donor-acceptor interface are *** film morphology exhibits notable variations,significantly depending on the layer to which 1,8-diiodooctane (DIO) was *** incidence wide-angle X-ray scattering analysis reveals distinctly separated donor/acceptor phases and vertical crystallinity details in SD ***-of-flight secondary ion mass spectrometry analysis is employed to obtain component distributions in diverse vertical phase structures of SD films depending on additive *** addition,nanosecond transient absorption spectroscopy shows that DIO control significantly affects the dynamics of separated charges in SD *** SD OPVs,DIO appears to act through distinct mechanisms with minimal restriction,depending on the applied *** study emphasizes the significance of morphological optimization in improving device performance and underscores the importance of independent additive control in the advancement of OPV technology.

关键词： Sequential deposition Vertical phase separation charge dynamics Organic photovoltaics Nonfullerene acceptors

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An Artificial Intelligence-Based Framework for Fruits Disease Recognition Using Deep Learning

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Computer Systems Science & Engineering 2024年第2期48卷 529-554页

作者： Irfan Haider Muhammad Attique Khan Muhammad Nazir Taerang Kim Jae-Hyuk cha Department of Computer Science HITEC UniversityTaxila47080Pakistan Department of Computer Science Hanyang UniversitySeoulKorea

Fruit infections have an impact on both the yield and the quality of the *** a result,an automated recognition system for fruit leaf diseases is *** artificial intelligence(AI)applications,especially in agriculture,deep learning shows promising disease detection and classification *** recent AI-based techniques have a few challenges for fruit disease recognition,such as low-resolution images,small datasets for learning models,and irrelevant feature *** work proposed a new fruit leaf leaf leaf disease recognition framework using deep learning features and improved pathfinder *** fruit types have been employed in this work for the validation process,such as apple,grape,and *** the first step,a noisy dataset is prepared by employing the original images to learn the designed framework *** EfficientNet-B0 deep model is fine-tuned on the next step and trained separately on the original and noisy *** that,features are fused using a serial concatenation approach that is later optimized in the next step using an improved Path Finder Algorithm(PFA).This algorithm aims to select the best features based on the fitness score and ignore redundant *** selected features are finally classified using machine learning classifiers such as Medium Neural Network,Wide Neural Network,and Support Vector *** experimental process was conducted on each fruit dataset separately and obtained an accuracy of 100%,99.7%,99.7%,and 93.4%for apple,grape,Citrus fruit,and citrus plant leaves,respectively.A detailed analysis is conducted and also compared with the recent techniques,and the proposed framework shows improved accuracy.

关键词： Fruit disease contrast enhancement augmentation deep learning fusion feature selection classification

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TRAIL and Celastrol Combinational Treatment Suppresses Proliferation, Migration, and Invasion of Human Glioblastoma Cells via Targeting Wnt/β-catenin Signaling Pathway

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Chinese Journal of Integrative Medicine 2024年第4期30卷 322-329页

作者： QIN Jing-jing NIU Meng-da cha Zhe GENG Qing-hua LI Yu-lin REN Chun-guang David P.Molloy YU Hua-rong Research Center of Neuroscience School of Basic Medical SciencesChongqing Medical UniversityChongqing(400016)China Laboratory of Developmental Biology Department of Cell Biology and GeneticsSchool of Basic Medical SciencesChongqing Medical UniversityChongqing(400016)China Department of Biochemistry and Molecular Biology School of Basic Medical SciencesChongqing Medical UniversityChongqing(400016)China

Objective To investigate the mechanistic basis for the anti-proliferation and anti-invasion effect of tumor necrosis factor-related apoptosis-induced ligand(TRAIL)and celastrol combination treatment(TCCT)in glioblastoma *** Cell counting kit-8 was used to detect the effects of different concentrations of celastrol(0-16µmol/L)and TRAIL(0-500 ng/mL)on the cell viability of glioblastoma cells.U87 cells were randomly divided into 4 groups,namely control,TRAIL(TRAIL 100 ng/mL),Cel(celastrol 0.5µmol/L)and TCCT(TRAIL 100 ng/mL+celastrol 0.5µmol/L).Cell proliferation,migration,and invasion were detected by colony formation,wound healing,and Transwell assays,*** reverse transcription polymerase chain reaction and Western blotting were performed to assess the levels of epithelial-mesenchymal transition(EMT)markers(zona occludens,N-cadherin,vimentin,zinc finger E-box-binding homeobox,Slug,and β-catenin).Wnt pathway was activated by lithium chloride(LiCl,20 mol/L)and the mechanism for action of TCCT was *** Celastrol and TRAIL synergistically inhibited the proliferation,migration,invasion,and EMT of U87 cells(Pchanism of action for TCCT as an effective therapy for glioblastoma.

关键词： celastrol Chinese medicine tumor necrosis factor-related apoptosis-induced ligand glioblastoma β-catenin Tripterygium wilfordii

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Des-Arg(9)bradykinin as a causal metabolite for autism spectrum disorder

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World Journal of Psychiatry 2024年第1期14卷 88-101页

作者： Zhong-Yu Huang Zi-Pan Lyu Hong-Gui Li Hua-Zhi You Xiang-Na Yang Cai-Hui cha Center for Medical Research on Innovation and Translation Institute of Clinical MedicineGuangzhou First People’s HospitalSchool of MedicineSouth China University of TechnologyGuangzhou 510000Guangdong ProvinceChina School of Biological Sciences Nanyang Technological UniversityNanyang Ave 639798Singapore Department of Pediatrics First Affiliated Hospital of Guangzhou University of Chinese MedicineGuangzhou 510405Guangdong ProvinceChina Department of Nutrition First Affiliated Hospital of Guangzhou University of Chinese MedicineGuangzhou 510405Guangdong ProvinceChina Department of Pediatric Traditional Chinese Medicine Clinic Guangzhou Women and Children's Medical CenterGuangzhou 510632Guangdong ProvinceChina Department of Psychology Guangzhou Women and Children's Medical CenterGuangzhou 510632Guangdong ProvinceChina

BACKGROUND Early diagnosis and therapeutic interventions can greatly enhance the developmental trajectory of children with autism spectrum disorder(ASD).However,the etiology of ASD is not completely *** presence of confounding factors from environment and genetics has increased the difficulty of the identification of diagnostic biomarkers for *** To estimate and interpret the causal relationship between ASD and metabolite profile,taking into consideration both genetic and environmental *** A two-sample Mendelian randomization(MR)analysis was conducted using summarized data from large-scale genome-wide association studies(GWAS)including a metabolite GWAS dataset covering 453 metabolites from 7824 European and an ASD GWAS dataset comprising 18381 ASD cases and 27969 healthy *** in plasma were set as exposures with ASD as the main *** causal relationships were estimated using the inverse variant weight(IVW)*** also performed leave-one-out sensitivity tests to validate the robustness of the *** on the drafted metabolites,enrichment analysis was conducted to interpret the association via constructing a protein-protein interaction network with multi-scale evidence from databases including Infinome,SwissTargetPrediction,STRING,and *** Des-Arg(9)-bradykinin was identified as a causal metabolite that increases the risk of ASD(β=0.262,SE=0.064,P_(IVW)=4.64×10^(-5)).The association was robust,with no significant heterogeneity among instrument variables(P_(MR Egger)=0.663,P_(IVW)=0.906)and no evidence of pleiotropy(P=0.949).Neuroinflammation and the response to stimulus were suggested as potential biological processes mediating the association between Des-Arg(9)bradykinin and *** Through the application of MR,this study provides practical insights into the potential causal association between plasma metabolites and *** findings offer perspectives for the discovery of diagnos

关键词： Des-Arg(9)bradykinin Autism spectrum disorder Mendelian randomization Metabolite Enrichment analysis

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清肝宁胃方辅助莫沙必利治疗对胃镜下胆汁反流情况与胃肠激素表达影响的前瞻性研究

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中华中医药学刊 2024年第6期42卷 232-235页

作者：高华查旋董巍安庆市第一人民医院安徽安庆246000

目的探讨清肝宁胃方辅助莫沙必利治疗对胆汁反流性胃炎(Bile reflux gastritis, BGR)患者胃镜下胆汁反流情况与胃肠激素表达的影响,以期为临床治疗提供一定参考。方法应用前瞻性随机对照研究方法选取2020年1月—2023年1月我院BGR患者... 详细信息

目的探讨清肝宁胃方辅助莫沙必利治疗对胆汁反流性胃炎(Bile reflux gastritis, BGR)患者胃镜下胆汁反流情况与胃肠激素表达的影响,以期为临床治疗提供一定参考。方法应用前瞻性随机对照研究方法选取2020年1月—2023年1月我院BGR患者118例,以计算机生成的随机数字表分为中西医结合组(59例)、西医组(59例)。西医组给予莫沙必利,中西医结合组给予清肝宁胃方辅助莫沙必利,均治疗1个月。比较两组疗效、不良反应与治疗前、治疗1个月后中医证候积分、胃镜下胆汁反流情况、血清炎症因子[白细胞介素-8(Interleukin 8,IL-8)、肿瘤坏死因子-α(Tumor Necrosis Factor-α,TNF-α)、C反应蛋白(C-reactive protein, CRP)]、胃肠激素[胃泌素(Gastrin, GAS)、胃动素(Motilin, MTL)]水平。结果 (1)疗效:经治疗,中西医结合组总有效率为93.22%,高于西医组的79.66%(P0.05)。结论应用清肝宁胃方辅助莫沙必利治疗BGR患者可改善胃镜下胆汁反流情况与胃肠激素表达,减轻机体炎症反应与临床症状,增强疗效,且安全性好。

关键词：清肝宁胃方莫沙必利胆汁反流性胃炎胃镜下胆汁反流情况胃肠激素

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Obstructive sleep apnea:Overlooked comorbidity in patients with diabetes

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World Journal of Diabetes 2024年第7期15卷 1448-1460页

作者： Eric D Tenda Joshua Henrina Jin H cha Muhammad R Triono Ersananda A Putri Dahliana J Aristy Dicky L Tahapary Division of Respirology and Critical Care Department of Internal MedicineFaculty of Medicine Universitas Indonesia-Cipto Mangunkusumo HospitalDKI JakartaJakarta Pusat 10430Indonesia Head of Research Group Artificial Intelligence and Digital Health Indonesian Medical Education and Research InstituteFaculty of Medicine University of IndonesiaDKI JakartaJakarta Pusat 10430Indonesia Division of Endocrinology Metabolism and DiabetesDepartment of Internal MedicineFaculty of Medicine Universitas Indonesia-Cipto Mangunkusumo HospitalDKI JakartaJakarta Pusat 10430Indonesia

In this review article,we explore the interplay between obstructive sleep apnea(OSA)and type 2 diabetes mellitus(T2DM),highlighting a significant yet often overlooked *** delve into the pathophysiological links between OSA and diabetes,specifically how OSA exacerbates insulin resistance and disrupts glucose *** research examines the prevalence of OSA in diabetic patients and its role in worsening diabetes-related *** the importance of comprehensive management,including weight control and positive airway pressure therapy,the study advocates integrated approaches to improve outcomes for patients with T2DM and *** review underscores the necessity of recognizing and addressing OSA in diabetes care to ensure more effective treatment and better patient outcomes.

关键词： Obstructive sleep apnea Type 2 diabetes mellitus Macrovascular Microvascular Weight loss Positive airway pressure

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