Evidence-based strategies for optimizing long-term temperature monitoring in offices by Peixian Li, Xiangjun Zhao, Siyan Wang, Thomas Parkinson, Richard de Dear, Xing Shi

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MACHINE LEARNING TECHNIQUES FOR RETINOPATHY DETECTION IN DIABETIC PATIENTS by Ajay Kushwaha, Ahankari Sachin Suresh, Chennoju Phanindra, Anil Kumar Sahu, Devanand Bhonsle, Yamini Chouhan

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Local clinical informatics investments are required for in silico biomarker generation across the globe: lessons learned from a secondary analysis of the PROP trial by Juliet Torres, Satya D. Malla, Valentina Silveira, Luis Mainero, Catherine Czeisler, José L. Díaz-Rossello, Alejandro Maccarrone, Alexandria Medoro, Pablo Sanchez, Fernanda Blasina, Jose J. Otero

“…However, over long-term predictions, models trained on PROP clinical trial patients showed significantly more error in the Uruguayan patients. # Conclusions Although these prediction models built upon PROP data were not generalizable to Uruguayan patients, our data suggest that prediction models using simple anthropomorphic measurements, if trained on local patients, may be able to provide value as a low-cost in silico biomarker. …”
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Spatial autocorrelation with environmental factors related to tuberculosis prevalence in Nepal, 2020–2023 by Roshan Kumar Mahato, Kyaw Min Htike, Alex Bagas Koro, Rajesh Kumar Yadav, Vijay Sharma, Alok Kafle, Suvash Chandra Ojha

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Aligning Evapotranspiration from MOD16A2.061 Product to Ground Estimates in Piemonte (NW Italy): an analysis of temporal and spatial biases by E. Ronco, E. C. Borgogno Mondino

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New Parameters Based on Ground Reaction Forces for Monitoring Rehabilitation Following Tibial Fractures and Assessment of Heavily Altered Gait by Christian Wolff, Elke Warmerdam, Tim Dahmen, Tim Pohlemann, Philipp Slusallek, Bergita Ganse

“…Parametrized curves were fitted and regression analyses conducted to determine the best fit, reflected in the highest R²-value and lowest fitting error. A Wald Test with t-distribution was employed for statistical analysis. …”
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A Method for Temporally Resolved Continuous Inline Measurement of Multiple Solute Concentrations With Microfluidic Spectroscopy by Andrea Lorenzo Henri Sergio Detry, Vinny Chandran Suja, Nathaniel Merriman Sims, Robert A. Peterfreund, David E. Arney

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Leveraging expression from multiple tissues using sparse canonical correlation analysis and aggregate tests improves the power of transcriptome-wide association studies. by Helian Feng, Nicholas Mancuso, Alexander Gusev, Arunabha Majumdar, Megan Major, Bogdan Pasaniuc, Peter Kraft

“…Consequently, TWAS power can be low when expression quantitative trait locus (eQTL) data used to train the genetic predictors have small sample sizes, or when data from causally relevant tissues are not available. …”
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Estimating Near-Surface Air Temperature From Satellite-Derived Land Surface Temperature Using Temporal Deep Learning: A Comparative Analysis by Jangho Lee

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Mapping football tactical behavior and collective dynamics with artificial intelligence: a systematic review by José E. Teixeira, José E. Teixeira, José E. Teixeira, José E. Teixeira, José E. Teixeira, José E. Teixeira, Eduardo Maio, Eduardo Maio, Eduardo Maio, Pedro Afonso, Pedro Afonso, Samuel Encarnação, Samuel Encarnação, Samuel Encarnação, Guilherme F. Machado, Guilherme F. Machado, Ryland Morgans, Tiago M. Barbosa, Tiago M. Barbosa, António M. Monteiro, António M. Monteiro, Pedro Forte, Pedro Forte, Pedro Forte, Ricardo Ferraz, Ricardo Ferraz, Luís Branquinho, Luís Branquinho, Luís Branquinho, Luís Branquinho

“…Concretely, the tactical behavior was expressed by spatiotemporal tracking data using convolutional neural networks, recurrent neural networks, variational recurrent neural networks, and variational autoencoders, Delaunay method, player rank, hierarchical clustering, logistic regression, XGBoost, random forest classifier, repeated incremental pruning produce error reduction, principal component analysis, and T-distributed stochastic neighbor embedding. …”
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Context-Aware Embedding Techniques for Addressing Meaning Conflation Deficiency in Morphologically Rich Languages Word Embedding: A Systematic Review and Meta Analysis by Mosima Anna Masethe, Hlaudi Daniel Masethe, Sunday O. Ojo

“…The significant degree of heterogeneity was further emphasized by the H² score of 8.10 and the I² value of 87.65%. A trim and fill analysis with a beta value of 5.95, a standard error of 4.767, a Z-value (or Z-score) of 1.25 which is a statistical term used to express the number of standard deviations a data point deviates from the established mean, and a <i>p</i>-value (probability value) of 0.2 was performed to account for publication bias which is one statistical tool that can be used to assess the importance of hypothesis test results. …”
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An explainable GeoAI approach for the multimodal analysis of urban human dynamics: a case study for the COVID-19 pandemic in Rio de Janeiro by David Hanny, Dorian Arifi, Steffen Knoblauch, Bernd Resch, Sven Lautenbach, Alexander Zipf, Antonio Augusto de Aragão Rocha

“…Understanding the spatiotemporal dynamics of urban human behaviour is essential for such responses. Crowd-sourced geo-data can be a valuable data source for this understanding. …”
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Implementation of a Real-Time Analysis Simulation System for Traffic Signal Control Algorithms to Reduce Vehicle Exhaust Emissions and Improve Traffic Flow by Hyeokgyu Kwon, Jinhwan Jang, Jongsik Kim, Dongmahn Seo, Soobin Jeon

“…To validate RTASS, we experiment using actual intersection data. As a result of comparing the traffic volume of the actual intersection data and the simulation, we confirmed that the error rate was maintained within 2% on average. …”
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Fast Analysis of Multi-Layered Anisotropic Electromagnetic Propagation Based on Z-Transform Finite-Difference Time-Domain Method with Scale-Compressed Technique by Yuxian Zhang, Yilin Kang, Xiaoli Feng, Lixia Yang, Zhixiang Huang

“…Compared with the popular commercial software COMSOL, those data from multi-layered computation are quite consistent with the approximate trend the 2nd-order error convergence.…”
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Spatiotemporal Land Use Change Detection Through Automated Sampling and Multi-Feature Composite Analysis: A Case Study of the Ebinur Lake Basin by Yi Yang, Liang Zhao, Ya Guo, Shihua Liu, Xiang Qin, Yixiao Li, Xiaoqiong Jiang

“…This study proposes an innovative technical framework that integrates automated sample generation, multi-feature optimization, and classification model refinement to enhance the accuracy of land use classification and enable detailed spatiotemporal analysis in the Ebinur Lake Basin. By integrating Landsat data with multi-temporal European Space Agency (ESA) products, we acquired 14,000 pixels of 2021 land use samples, with multi-temporal spectral features enabling robust sample transfer to 12028 pixels in 2011 and 10,997 pixels in 2001. …”
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Analysis of the Accuracy of a Body-Force Propeller Model and a Discretized Propeller Model in RANS Simulations of the Flow Around a Maneuvering Ship by Long Jiang, Jianxi Yao, Zuyuan Liu

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Relationship between Tai Chi and clinical outcomes in elderly patients with COVID-19: a protocol for systematic review and dose–response meta-analysis by Yang Wang, Na Li, Xiao Peng, Chun Wang, Sheng He, Jinfeng Yang, Yuanpeng Liao

“…Risk of bias, subgroup analysis and sensitivity analysis will also be performed. …”
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New Emerging and Comprehensive Land Mapping Unit at Detailed Scale: Integrating Random Forest Analysis and Remote Sensing Techniques for Sustainable Land Management by Aditya Nugraha Putra, Reni Ustiatik, Novandi Rizky Prasetya, Erza Aulia Adara, Istika Nita, Syamsu Ridzal Indra Hadi, Soemarno Soemarno, Sudarto Sudarto, Sri Rahayu Utami, Mochammad Munir, Mochtar Lutfi Rayes

“…This study aims to present an innovative framework for the development of Land Mapping Units (LMUs) at a detailed scale (1:20,000), through the integration of Random Forest (RF) analysis and high-resolution remote sensing data. This study was conducted in the South Malang Plateau, Indonesia (the area characterized by karst, tectonic, volcanic, and alluvial landforms) from June to December 2024. …”
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Wealth-related inequalities of women’s cervical cancer screening in 11 Sub-Saharan African countries: evidence from a pooled decomposition analysis by Beminate Lemma Seifu, Yohannes Mekuria Negussie, Angwach Abrham Asnake, Hiwot Atlaye Asebe, Bezawit Melak Fente, Zufan Alamrie Asmare, Mamaru Melkam, Meklit Melaku Bezie, Alemayehu Kasu Gebrehana, Sintayehu Simie Tsega

“…The study analyzed 138,605 weighted samples of reproductive-aged women from DHS data spanning 2015 to 2023 across SSA countries. …”
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Hierarchical clustering methods in a task to find abnormal observations based on groups with broken symmetry by A. N. Kislyakov, S. V. Polyakov

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