TomaFDNet: A multiscale focused diffusion-based model for tomato disease detection by Rijun Wang, Rijun Wang, Yesheng Chen, Fulong Liang, Xiangwei Mou, Xiangwei Mou, Guanghao Zhang, Hao Jin

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Optimizing DD-SIMCA modeling for accurate classification of rice varieties via raman spectroscopy by Somaye Vali Zade, Hamed Sahebi, Adel Mirza Alizadeh, Behrooz Jannat, Hossein Rastegar, Solmaz Abedinzadeh, Fataneh Hashempour-Baltork, Amin Mousavi Khaneghah

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A Comprehensive Review of Unimodal and Multimodal Fingerprint Biometric Authentication Systems: Fusion, Attacks, and Template Protection by U. Sumalatha, K. Krishna Prakasha, Srikanth Prabhu, Vinod C. Nayak

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New Approach to Drug Delivery in Ophthalmological Practice: Development of Composite Ophthalmological Solution for Drug Loading of Soft Contact Lenses by D. K. Naplekov, E. T. Zhilyakova, A. Yu. Malyutina, A. V. Bondarev, N. B. Demina, O. O. Novikov, R. A. Abramovich

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Multi-crop plant counting and geolocation using a YOLO-Powered GUI System by Renato Herrig Furlanetto, Nathan Schawn Boyd, Ana Claudia Buzanini

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Design and Evaluation of ACAFiB-APP, a clinical decision support system for anticoagulant considerations in patients with atrial fibrillation by Ramin Ansari, Sorayya Rezayi, Ali Asghar Safaei, Reza Mollazadeh, Eisa Rezaei, Mahboobeh Khabaz Mafinejad, Soha Namazi, Keyhan Mohammadi

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A global daily mesoscale front dataset from satellite observations: in situ validation and cross-dataset comparison by Q. Xing, H. Yu, W. Yu, W. Yu, W. Yu, W. Yu, X. Chen, X. Chen, X. Chen, X. Chen, H. Wang, H. Wang, H. Wang

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Providing a Framework for Assessing and Evaluating Network Data Studies in the Fight Against Social Anomalies by Mohammad Khalili, Hamzehali Nourmohammadi, Nader Naghshineh

“…Additionally, clustering techniques, such as k-means, were employed to identify different forms of theft crimes. Classification algorithms, including neural networks, Bayesian rules, Bayesian navigation, and support vector machines, were used to predict theft crimes. …”
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In-depth insight into structure-reactivity/regioselectivity relationship of Lewis acid catalyzed cascade 4πe-cyclization/dicycloexpansion reaction by Ka Lu, Pan-Pan Zhou, Yong-Qiang Tu, Fu-Min Zhang, Xiao-Ming Zhang, Kai Li, Kun Fang, Yun-Peng Wang, Zi-Hao Li, Jia-Qi Li

“…Then, DFT calculations combined with machine learning algorithms establish a prediction model for first cycloexpansion (i e. regioselectivity). …”
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Performance analysis of advanced deep learning technics: Application to solar energy forecasting and management in several cities in Chad by Osée Mounkang, Claude Vidal Aloyem Kaze, Nzoko Tayo Dieudonné, Ghislain Junior Bangoup Ntegmi, Duclair Paul Edouard Pountounynyi, Hervice Roméo Fogno Fotso, Armel Zambou Kenfack, Germaine Kenmoe Djuidje, René Tchinda

“…This study proposes a hybrid artificial intelligence model that combines LLM and LSTM methods, utilizing the Adam optimization algorithm to make hourly solar radiation predictions over a seven-day period. …”
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Exploring Mechanisms of Lang Qing Ata in Non-Alcoholic Steatohepatitis Based on Metabolomics, Network Pharmacological Analysis, and Experimental Validation by Li S, Zhu H, Zhai Q, Hou Y, Yang Y, Lan H, Jiang M, Xuan J

“…By integrating known databases and target prediction algorithms, which encompassed database-based target prediction, protein-protein interaction networks, as well as Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, we unveiled the potential key targets and signaling pathways that these bioactive components might engage with. …”
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Exploration of crucial stromal risk genes associated with prognostic significance and chemotherapeutic opportunities in invasive ductal breast carcinoma by Guohua Tang, Zhi Wang, Wei Geng, Yang Yu, Yang Zhang

“…We employed a variety of algorithms, such as the log-rank test, the LASSO-cox model, the univariate regression model, and the multivariate regression model, to predict prognostic-risk genes and the prognostic-risk model. …”
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Detection of litchi fruit maturity states based on unmanned aerial vehicle remote sensing and improved YOLOv8 model by Changjiang Liang, Changjiang Liang, Dandan Liu, Dandan Liu, Weiyi Ge, Weiyi Ge, Wenzhong Huang, Wenzhong Huang, Yubin Lan, Yubin Lan, Yubin Lan, Yongbing Long, Yongbing Long, Yongbing Long, Yongbing Long

“…In addition, YOLOv8-FPDW was more competitive than mainstream object detection algorithms. The study predicted the optimal harvest period for litchis, providing scientific support for orchard batch harvesting and fine management.…”
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Segmentation versus detection: Development and evaluation of deep learning models for prostate imaging reporting and data system lesions localisation on Bi‐parametric prostate magn... by Zhe Min, Fernando J. Bianco, Qianye Yang, Wen Yan, Ziyi Shen, David Cohen, Rachael Rodell, Dean C. Barratt, Yipeng Hu

“…The ground‐truth (GT) perspective lesion‐level sensitivity and prediction‐perspective lesion‐level precision are reported, to quantify the ratios of true positive voxels being detected by algorithms over the number of voxels in the GT labelled regions and predicted regions. …”
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Identification of m6 A-regulated ferroptosis biomarkers for prognosis in laryngeal cancer by Xin Wang, Wen Zhang, Kun Liang, Yujuan Wang, Jin Zhang, Jinping Wang, An Li, Yonggang Yun, Hiu Liu, Yanan Sun

“…Furthermore, drug sensitivity prediction found that 19 chemotherapy drugs were strongly correlated with a risk score. …”
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Prospects of artificial intelligence for the sustainability of sugarcane production in the modern era of climate change: An overview of related global findings by Rajan Bhatt, Akbar Hossain, Debjyoti Majumder, Mandapelli Sharath Chandra, Rajiv Ghimire, Muhammad Faisal Shahzad, Krishan K. Verma, Amarinder Singh Riar, Vishnu D. Rajput, Mauro Wagner Oliveira, Adel Nisi, Riyadh S. Almalki, Viliam Bárek, Marian Brestic, Sagar Maitra

“…This study discusses the latest research on artificial intelligence (AI) in sugarcane farming, with particular attention given to soil biochemistry, disease detection, climate-smart technology for greenhouse gas emissions, yield and water productivity prediction, and cane juice biochemistry. Artificial intelligence (AI) tools, such as machine learning algorithms, can optimize irrigation, increase yields, save water, and properly estimate sugarcane production. …”
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Combined endodontic treatment: microbiological aspects by using scanning electronical microscopy by V. N. Tsarev, A. V. Mitronin, M. S. Podporin, D. A. Ostanina, E. V. Ippolitov, V. A. Mitronin

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Research of the state of the stress-realizing systems in pregnant women with miscarriage by V. A. Plotnik

“…The aim of the work was to investigate some stress-realizing systems by adopting an integrated approach in women with threatened abortion for further development of the algorithm of the evaluation and prediction of risk of the miscarriage, which will contribute to the reduction of perinatal losses and improve the reproductive health of women. …”
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Machine-Learning-Assisted Identification of Steam Channeling after Cyclic Steam Stimulation in Heavy-Oil Reservoirs by Yu Li, Huiqing Liu, Peng Jiao, Qing Wang, Dong Liu, Liangyu Ma, Zhipeng Wang, Hao Peng

“…In this work, a machine-learning-assisted identification model, based on a random-forest ensemble algorithm, is developed to predict the occurrence of steam channeling during steam huff-and-puff processes. …”
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A Comprehensive Monte Carlo-Simulated Dataset of WAXD Patterns of Wood Cellulose Microfibrils by Ricardo Baettig, Ben Ingram

“…It enables the development, validation, and benchmarking of novel algorithms and machine learning models for MFA prediction from diffraction patterns. …”
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