MODELI NG CLINICAL AND ECONOMIC OUTCOMES OF TESTING FOR LTBI WITH T-SPOT.TB IN IMMUNOCOMPROMISED CHILDREN by V. I. Ignatyeva, M. V. Avxentyeva, V. V. Omelyanovsky, G. R. Khachatryan

“…The aim of the study was to evaluate the cl inical and economic outcomes of testingfor LTBI with T-SPOT.TB in immunocompromised children. Methods: we develope d a model, forecasting the testing results, probable cases of tuberculosis activation and related costs for scenarios with alternative use of T-SPOT.TB and TST for diagnosing LTBI in immunocompromised children. …”
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Over-activation and dysfunction of platelet-NK cell aggregates in HIV-infected individuals by Meiju Deng, Ruojia Biao, Meiqing Jiang, Jiantao Fu, Hongxin Zhao, Juan Du

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An advanced approach to tomato apex head thickness measurement using lightweight YOLO variants, faster RCNN, and RGB-depth sensor by Amora Amir, Suraj Giri, Surya Giri, Marya Butt

“…This study presents an automated method for detecting and measuring the apex head thickness of tomato plants, a critical phenotypic trait associated with plant health, fruit development, and yield forecasting. …”
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Refining Rainfall Derived from Satellite Radar for Estimating Inflows at Lam Pao Dam, Thailand by Nathaporn Areerachakul, Jaya Kandasamy, Saravanamuthu Vigneswaran, Kittitanapat Bandhonopparat

“…To improve accuracy, satellite-derived rainfall estimates were adjusted using ground-based rainfall measurements from stations located near and within the catchment area, applying the 1-DVAR method. The Kriging method was employed to estimate the spatial distribution of rainfall over the catchment area. …”
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Machine learning and artificial intelligence in type 2 diabetes prediction: a comprehensive 33-year bibliometric and literature analysis by Mahreen Kiran, Ying Xie, Nasreen Anjum, Graham Ball, Barbara Pierscionek, Duncan Russell

“…Key thematic clusters include foundational ML techniques, epidemiological forecasting, predictive modelling, and clinical applications. …”
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The microbial landscape action on development destructive erysipelas forms by L. A. Vasilevskaya

“…Of our studies indicate that the microflora of the primary cells in destructive forms of the erysipelas changed both quantitatively and qualitatively. Detected microbial pathogens in bacteriological studies of soft tissue exudates allowed installing criteria for forecasting the development of purulent complications. …”
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Adaptive spatial-channel feature fusion and self-calibrated convolution for early maize seedlings counting in UAV images by Zhenyuan Sun, Zhenyuan Sun, Zhenyuan Sun, Zhi Yang, Zhi Yang, Yimin Ding, Yimin Ding, Boyan Sun, Boyan Sun, Saiju Li, Saiju Li, Zhen Guo, Zhen Guo, Lei Zhu, Lei Zhu

“…By integrating RSCconv and ASCFF into other detection frameworks such as Faster R-CNN, RetinaNet, and Deformable DETR, we observed enhanced detection and counting accuracy, further validating the effectiveness of our proposed method. …”
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Meteorological factors and normalized difference vegetation index drivers of scrub typhus incidence in Shandong Province based on a 16-year time-frequency analysis by Zhisong Ni, Shufen Li, Rui Xi, Kemeng Liang, Sihao Song, Chuanlong Cheng, Hui Zuo, Liang Lu, Xiujun Li

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A novel mitochondrial quality regulation gene signature for anticipating prognosis, TME, and therapeutic response in LUAD by multi-omics analysis and experimental verification by Lijun Zeng, Sixuan Wu, Zhimin Li, Yuanbin Tang, Yeru Tan, Renji Liang, Yuehua Li

“…Methods We extensively examined transcriptome and clinical data from TCGA and GEO databases to discover differentially expressed MQRGs. …”
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Solar Flare Prediction Using Long Short-term Memory (LSTM) and Decomposition-LSTM with Sliding Window Pattern Recognition by Zeinab Hassani, Davud Mohammadpur, Hossein Safari

“…A sliding window technique is employed to detect temporal quasi-patterns in both irregular and regularized flare time series. …”
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Bacterial Infections Transmitted by Ticks in Barnaul: Epidemiological and Epizootological Situation, Diagnostic Problems by T. A. Chekanova, A V. Rakov, K. Petremgvdlishvili, A. V. Timonin, N. V. Lukyanenko, T. V. Safyanova, S. V. Shirokostup, N. Ya. Lukyanenko, U. V. Kalinina, I. G. Pashchenko

“…The difficulty of diagnostic of tick-borne rickettsiosis without rash is aggravated by the shortage of reagent kits, primarily for the detection of specific antibodies. The landscape confinement of Dermacentor and Ixodes ticks should take into account when organizing long-term stationary observation sites for monitoring and forecasting the epidemiological and epizootological situation. …”
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Automated Eddy Identification and Tracking in the Northwest Pacific Based on Conventional Altimeter and SWOT Data by Lan Zhang, Cheinway Hwang, Han-Yang Liu, Emmy T. Y. Chang, Daocheng Yu

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Chemometric and computational modeling of polysaccharide coated drugs for colonic drug delivery by Ahmad Khaleel AlOmari, Khaled Almansour

“…For ML modeling, we examined the predictive accuracy of three machine learning models—Elastic Net (EN), Group Ridge Regression (GRR), and Multilayer Perceptron (MLP)—for forecasting the release behavior of samples. The dataset, consisting of 155 data points with over 1500 spectral features, underwent preprocessing involving normalization, Principal Component Analysis (PCA) for dimensionality reduction, and outlier detection using Cook’s Distance. …”
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Evolution of wind field in the atmospheric boundary layer using multiple-source observations during the passage of Super Typhoon Doksuri (2305) by X. Wang, X. Wang, J. Xu, J. Xu, S. Wu, S. Wu, S. Wu, Q. Wang, G. Dai, G. Dai, P. Zhu, Z. Su, S. Chen, X. Shi, M. Fan

“…The CDL provides high-temporal- and high-spatial-resolution wind speed profiles from tens of meters to its highest detection height. The wind speeds above the highest detection height of the CDL are supplemented with the RWP measurements. …”
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Study on soil moisture estimation using a three-frequency combination of observations integrated with robust estimation and machine learning by Yintao Liu, Chao Ren, Hongjuan Shao

“…The new methods eliminate the impact of geometrical factors and atmospheric delays. …”
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Hybridisation of artificial neural network with particle swarm optimisation for water level prediction by Sarah J. Mohammed, Salah L. Zubaidi

“…This study applies an artificial neural network (ANN) integrated with the particle swarm optimisation algorithm (PSO-ANN) for simulating monthly WL of the Tigris River in Alkut City, Iraq. Data pre-treatment methods are utilised for improving raw data quality and detect the optimal predictors. …”
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The impact of land use/land cover change on ecosystem services in Golestan province by Hamidreza Kamyab, Nasim Shabani

“…In this paper, we assessed LU/LC dynamics in Golestan Province using change detection and Markov chain as inputs for ESV of different land use types to estimate the amount of services. …”
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Application of deep learning in cloud cover prediction using geostationary satellite images by Yeonjin Lee, Seyun Min, Jihyun Yoon, Jongsung Ha, Seungtaek Jeong, Seonghyun Ryu, Myoung-Hwan Ahn

“…Predicting cloud cover is essential in fields, such as agriculture, climatology, and meteorology, where accurate weather forecasting can significantly impact decision-making. …”
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Hyperion Image Analysis Depicts a Preliminary Landscape of Tumor Immune Microenvironment in OSCC with Lymph Node Metastasis by Shang Xie, Xin-Yuan Zhang, Xiao-Feng Shan, Vicky Yau, Jian-Yun Zhang, Wei Wang, Yong-Pan Yan, Zhi-Gang Cai

“…This study is aimed at utilizing the Hyperion imaging system to depict a preliminary landscape of the tumor immune microenvironment in OSCC with lymph node metastasis. Methods. We collected neoplasm samples from OSCC patients. …”
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Trends and advances in Leptospira, a bibliometric analysis by Wei Wang, Wei Wang, Wei Wang, Yamin Gao, Yamin Gao, Yamin Gao, Jianyu Ji, Jianyu Ji, Jianyu Ji, Zhai Huang, Zhai Huang, Bin Xiong, Bin Xiong, Shulin Xiang, Shulin Xiang

“…This study applies bibliometric analysis to generate a visual knowledge map, identifying research hotspots and forecasting future trends in leptospirosis investigations.MethodsData were extracted from the Web of Science Core Collection (WOSCC), encompassing all publications up to May 1, 2024. …”
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