A joint three-plane physics-constrained deep learning based polynomial fitting approach for MR electrical properties tomography by Kyu-Jin Jung, Thierry G. Meerbothe, Chuanjiang Cui, Mina Park, Cornelis A.T. van den Berg, Stefano Mandija, Dong-Hyun Kim

“…Deep learning-based approaches are robust to these artifacts but need extensive training datasets and suffer from generalization to unseen data. …”
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A Secure and Robust Machine Learning Model for Intrusion Detection in Internet of Vehicles by Pradeep Kumar Tiwari, Shiv Prakash, Animesh Tripathi, Tiansheng Yang, Rajkumar Singh Rathore, Manish Aggarwal, Narendra Kumar Shukla

“…The proposed fine tree-based model can be validated by conducting extensive experiments with benchmark real-world datasets which can simulate emerging IoV scenarios. …”
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Decoding Gestures in Electromyography: Spatiotemporal Graph Neural Networks for Generalizable and Interpretable Classification by Hunmin Lee, Ming Jiang, Jinhui Yang, Zhi Yang, Qi Zhao

“…Our methodology exhibits remarkable efficacy, achieving state-of-the-art performance across five publicly available datasets, thus underscoring its prowess in gesture recognition tasks. …”
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Measuring above-ground carbon stock using spatial analysis and the InVEST model: application in the Thoria Watershed, India by Zhe Guo, Himani Sharma, Mahesh Jadav, Upeksha Hettiarachchi, Chiranjit Guha, Wei Zhang, Pratiti Priyadarshini, Ruth S Meinzen-Dick

“…This study introduces a novel methodology for evaluating above-ground carbon storage and sequestration in the Thoria watershed, India, using time-series open-access remotely sensed datasets and the InVEST (Integrated Valuation of Environmental Services and Tradeoffs) carbon model. …”
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RNA Virus Discovery Sheds Light on the Virome of a Major Vineyard Pest, the European Grapevine Moth (<i>Lobesia botrana</i>) by Humberto Debat, Sebastian Gomez-Talquenca, Nicolas Bejerman

“…We further explored viral sequences in several publicly available transcriptomic datasets of the moth, indicating potential prevalence across distinct conditions. …”
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Unified Visual-Aware Representations for Data Analytics by Ladislav Peska, Ivana Sixtova, David Hoksza, David Bernhauer, Jakub Lokoc, Tomas Skopal

“…One of the characteristics of big data is its internal complexity and variety manifested in many types of datasets that are to be managed, searched, or analyzed. …”
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SNP rs9364554 Modulates Androgen Receptor Binding and Drug Response in Prostate Cancer by Yuqian Yan, Lei Shi, Tao Ma, Liguo Wang, Haojie Huang

“…SLC22A3, a membrane transporter, has been linked to SNP rs9364554 risk loci for drug efficacy in prostate cancer. (2) Methods: We examined the location of SNP rs9364554 in the genome and utilized TCGA and other publicly available datasets to analyze the association of this SNP with <i>SLC22A3</i> transcription levels. …”
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GPX3-Mediated Oxidative Stress Affects Pyrimidine Metabolism Levels in Stomach Adenocarcinoma via the AMPK/mTOR Pathway by Yaowen Zhang, Yixin Yang, Shanshan Kuang, Yang Zhang, Hancheng Qin, Jisheng Xie

“…RNA sequencing transcriptome data in the TCGA-STAD (training set) and GTEx datasets (validation set) were used. The LIMMA R program enabled the differentially expressed amino acid metabolism-related genes (AAMRGs) to be found. …”
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Frequency anomalies and characteristics of extratropical cyclones during extremely wet, dry, windy, and calm seasons in the extratropics by H. Binder, H. Wernli

“…However, a global statistical characterisation of observed extreme seasons is challenging because at any specific location, very few such seasons occurred during the limited period with available reanalysis datasets. This study therefore uses 1050 years of present-day (1990–1999) climate simulations of the Community Earth System Model Large Ensemble (CESM-LE) and 71 years (1950–2020) of ERA5 reanalyses to systematically identify extremely wet, dry, windy, and calm seasons in the extratropics during winter and summer and to quantify the role of extratropical cyclones in their occurrence. …”
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Integrative bioinformatics and machine learning approach unveils potential biomarkers linking coronary atherosclerosis and fatty acid metabolism-associated gene by Hong Li, Yongyun Xu, Aiting Wang, Chuanxin Zhao, Man Zheng, Chunyan Xiang

“…Validation of the expression levels of the seven FAMGs was performed using datasets GSE43292 and GSE9820. Results The study pinpointed seven FAMGs with a close association to AS: ACSBG2, ELOVL4, ACSL3, CPT2, ALDH2, HSD17B10, and CPT1B. …”
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Downregulation of FXYD2 Is Associated with Poor Prognosis and Increased Regulatory T Cell Infiltration in Clear Cell Renal Cell Carcinoma by Zedan Zhang, Yanlin Tang, Lei Li, Wuping Yang, Yawei Xu, Jingcheng Zhou, Kaifang Ma, Kenan Zhang, Hongkai Zhuang, Yanqing Gong, Kan Gong

“…The data from TCGA-KIRC, ICGC, GEO, Oncomine, ArrayExpress, TIMER, HPA datasets, and our clinical samples were used to determine and validate the expression level, prognostic roles, and potentially immune-related mechanisms in ccRCC. …”
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Causal Associations Between Sarcopenia and Gestational Diabetes Mellitus by Huang Y, Zhao S, Hong J, Shen L, Wang Z, Wang D

“…In this study, we used a bi-directional Mendelian randomization (MR) approach to explore this intricate relationship.Methods: This study utilized data from FinnGen datasets and genome-wide association studies. A bi-directional MR study was conducted. …”
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Socioeconomic and health-related inequalities in major depressive symptoms among older adults: a Wagstaff’s decomposition analysis of data from the LASI baseline survey, 2017–2018... by Manish Kumar, Shobhit Srivastava, T. Muhammad, Anjali Elsa Skariah

“…Objectives To find out the association between socioeconomic and health status and depression among older adults and explore the contributing factors in the socioeconomic and health-related inequalities in late-life depression.Design A cross-sectional study was conducted using large representative survey data.Setting and participants Data for this study were derived from the baseline wave of the Longitudinal Ageing Study in India conducted during 2017–2018. …”
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Bioinformatics and System Biological Approaches for the Identification of Genetic Risk Factors in the Progression of Cardiovascular Disease by Joy Dip Barua, Shudeb Babu Sen Omit, Humayan Kabir Rana, Nitun Kumar Podder, Utpala Nanda Chowdhury, Md Habibur Rahman

“…We used GEO microarray datasets for the CVD and other risk factors in this study. …”
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Mapping groundwater potential zone by robust machine learning algorithms &amp; remote sensing techniques in agriculture dominated area, Bangladesh by M. M. Shah Porun Rana, Muhammad Tauhidur Rahman, Md Fuad Hassan

“…This is randomly divided into two datasets: training (80 %) and testing (20 %). The resultant groundwater potential zone map is divided into five categories: extremely poor, very poor, moderate, good, and excellent. …”
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Pathway Analysis of Metabolic Syndrome Using a Genome-Wide Association Study of Korea Associated Resource (KARE) Cohorts by Unjin Shim, Han-Na Kim, Yeon-Ah Sung, Hyung-Lae Kim

“…To overcome this limitation, pathway analyses are being applied to GWAS datasets. The aim of this study is to elucidate the biological pathways involved in the pathogenesis of MetS through pathway analysis. …”
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Identification of hub genes, non-coding RNAs and pathways in Renal cell carcinoma (RCC): A comprehensive in silico study by Ahmad Golestanifar, Hengameh Khedri, Parisa Noorabadi, Mohammadreza Saberiyan

“…Using high-throughput sequencing datasets from the Gene Expression Omnibus (GEO), we identified differentially expressed mRNAs (DEMs), miRNAs (DEMIs), and circRNAs (DECs) in KIRC samples compared to normal kidney tissues. …”
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Improving Crack Detection Precision of Concrete Structures Using U-Net Architecture and Novel DBCE Loss Function by Andrew Prasetyo, I Ketut Eddy Purnama, Eko Mulyanto Yuniarno, Priyo Suprobo

“…The performance of our method is rigorously evaluated by combining DeepCrack, GAPS, Crack500, and CrackForest datasets to illustrate that the model can detect cracks in various material conditions. …”
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SSMM: Semi-supervised manifold method with spatial-spectral self-training and regularized metric constraints for hyperspectral image dimensionality reduction by Bei Zhu, Yao Jin, Xuehua Guan, Yanni Dong

“…SSMM conducts various forms of experiments on the Houston 2013, Indian Pines, and Washington DC datasets. In the dimensionality reduction experiments, the overall accuracy of SSMM in any dimension is higher than that of other algorithms. …”
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The Golden Afromontane ecosystems at cross-road: Wetland-based upstream-downstream linkage in Genale Dawa River Basin by Habtamu Temesgen, Haile Ketema, Gezahegn Kebede, Fikadu Woldemariyam, Gebremedihin Tesfaye

“…Landsat images between 2005 and 2020, along with documents review, were utilized to generate datasets. A stakeholders’ consultation forum and expert judgment were employed to understand the historical ecology of WESs in the GDRB. …”
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