Determinação do coeficiente convectivo de transferência de calor de figos submetidos ao resfriamento rápido Determination of the convective heat transfer coefficient of fig fruits... by Mariangela Amendola, Saul Dussán-Sarria, Anderson A. Rabello

“…For the prediction of the temperature, near to the center of fruits, the Fourier law model was considered. Algorithms employing the finite differences and finite elements methods were implemented for the one-dimensional and three-dimensional models. …”
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Artificial Intelligence Control Methodologies for Shape Memory Alloy Actuators: A Systematic Review and Performance Analysis by Stefano Rodinò, Giuseppe Rota, Matteo Chiodo, Antonio Corigliano, Carmine Maletta

“…Future research should prioritize adaptive algorithms for fatigue compensation, lightweight AI models for embedded deployment, and standardized benchmarking to bridge material-specific performance gaps. …”
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Realización computacional en tres dimensiones del Método de los Elementos de Contorno en la teoría de la Elasticidad // Three dimension computational realization of the Method of t... by I. L. Alemán Romero

“…<br />In the present work triangular elements are considered, lineal interpolation is employed, the transformation to homogeneal<br />coordinates is used and it is shown the algorithms that guide to the assembling of the equations system that contributes to the<br />solution on the boundary.…”
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A Physically Constrained Downscaling Framework for Hourly, All-Sky Land Surface Temperature in Mountainous Regions by Yongkang Li, Qing He, Yongqiang Liu, Yang Yan, Hailiang Zhang, Jiao Tan

“…The DADF incorporates data assimilation algorithms for LST downscaling, enabling accurate capture of actual LST under cloudy conditions. …”
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Self-Organizing Wireless Sensor Networks Solving the Coverage Problem: Game-Theoretic Learning Automata and Cellular Automata-Based Approaches by Franciszek Seredynski, Miroslaw Szaban, Jaroslaw Skaruz, Piotr Switalski, Michal Seredynski

“…In this paper, we focus on developing self-organizing algorithms aimed at solving, in a distributed way, the coverage problem in Wireless Sensor Networks (WSNs). …”
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Diagnosis and Management of Alzheimer’s Disease in Primary Care: A Real-World Study in Ontario, Canada by Zahinoor Ismail, Melanie Wilson, Hany Khalifa, Daniela Belovich, Eileen Shaw, Tram Pham, Suzanne McMullen, Yuhao Chen, Nafiz Sadman, Jackson Cai, Farhana Zulkernine, David Barber

“…Individuals ≥50 years old with dementia or AD were identified using AD and dementia-related diagnostic codes, medications, and keywords searched using natural language processing (NLP) and Artificial Intelligence (AI) algorithms from EMR chart notes. Diagnostic and screening tools included scales, neuroimaging, and laboratory tests. …”
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Dataset of apples for grading by sweetness, ripeness and varietyMendeley Data by Shilpa Gaikwad, Sonali Kothari, Ignisha Rajathi G

“…This dataset of ours can be used by researchers to develop and test algorithms to classify apples and estimate their ripeness and the presence of diseases. …”
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Machine learning-driven development of a stratified CES-D screening system: optimizing depression assessment through adaptive item selection by Ruo-Fei Xu, Zhen-Jing Liu, Shunan Ouyang, Qin Dong, Wen-Jing Yan, Dong-Wu Xu

“…Model performance was systematically evaluated through discrimination (ROC analysis), calibration (Brier score), and clinical utility analyses (decision curve analysis), with additional validation using random forest and support vector machine algorithms across independent samples. Results The resulting stratified screening system consists of an initial four-item rapid screening layer (encompassing emotional, cognitive, and interpersonal dimensions) for detecting probable depression (AUC = 0.982, sensitivity = 0.945, specificity = 0.926), followed by an enhanced assessment layer with five additional items. …”
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Research on rock fracture evolution prediction model based on Adam-ConvLSTM and transfer learning by Runze Liu, Ziwei Wang, Yanbo Zhang, Xulong Yao, Shaohong Yan, Zhiyuan Chen, Shuai Wang, Hua Li, Qi Wang

“…Comparative validation indicates that this comprehensive model outperforms traditional methods and basic deep learning algorithms in both prediction efficiency and accuracy. …”
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The application of super-resolution ultrasound radiomics models in predicting the failure of conservative treatment for ectopic pregnancy by Mingyan Zhang, Junfa Sheng

“…Feature selection involved statistical testing and Least Absolute Shrinkage and Selection Operator (LASSO) regression. Random forest algorithms were used to construct NR and SR models. …”
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Linking online activity to offline behavior: A meta-review of three decades of online-to-offline scholarship with future implications for AI by Scott Leo Renshaw, Kathleen M. Carley

“…As society grapples with the emerging significance and implications of Large Language Models (LLMs), such as OpenAI’s ChatGPT, or Google’s Gemini, as well as other advancements in modern generative Artificial Intelligence (AI), it is crucial to recognize the existing role that data, algorithms, and online social networks have already played in shaping our contemporary society. …”
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Date delivery scheme of delay-tolerant mobile sensor networks for high-voltage power transmission line inspection robot by FAN Fei, WU Gong-ping, WANG Man, XU Qing-shan, CAO Qi, YANG Song

“…Multiple simulation scenarios were performed, and the influences of different parameters with four routing algorithms were discussed. The results indicate that compared with the commonly used DTMSN data transmission methods, the proposed method can provide a higher delivery ratio and lower transport delay under appropriate transmission energy consumption.…”
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Secondary exposure and risk assessment of biocides as disinfectant sprays for COVID-19 prevention by Gihong Min, Jihun Shin, Youngtae Choe, Dongjun Kim, Jaemin Woo, Byunglyul Woo, Jangwoo Lee, Mansu Cho, Kilyong Choi, Wonho Yang

“…The inhalation and dermal exposure algorithms in ConsExpo 4.0, a software developed by the Dutch National Institute for Public Health and the Environment (RIVM), were used to assess the risk of active substances in biocidal products. …”
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Activation of thermal states by coherently controlled thermalization processes by Kyrylo Simonov, Saptarshi Roy, Tamal Guha, Zoltán Zimborás, Giulio Chiribella

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Integrated transcriptome analysis and combinatorial machine learning to construct a homeostatic model of acetylation for ccRCC and validate the key gene GCNT4 by Baohua Zhu, Ziyang Mo, Yi Bao, Xinxin Gan, Linhui Wang

“…Ten machine learning algorithms and their 101 combinations were used to analyze the prognostic significance of acetylation-related differentially expressed genes (DEGs) and to construct a prognostic risk model. …”
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Assessing the comparative effects of interventions in COPD: a tutorial on network meta-analysis for clinicians by Katrin Haeussler, Afisi S. Ismaila, Mia Malmenäs, Stephen G. Noorduyn, Nathan Green, Chris Compton, Lehana Thabane, Claus F. Vogelmeier, David M. G. Halpin

“…Randomized controlled trials (RCTs) are vital for demonstrating the efficacy of interventions; however, information on how an intervention compares to already available treatments and/or fits into treatment algorithms is sometimes limited. Although different therapeutic classes are available for the treatment of chronic obstructive pulmonary disease (COPD), assessing the relative efficacy of these treatments is challenging. …”
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Multi-Omics Identification of <i>Fos</i> as a Central Regulator in Skeletal Muscle Adaptation to Long-Term Aerobic Exercise by Chaoyang Li, Xinyuan Zhu, Yi Yan

“…Key feature genes were screened using Lasso regression, SVM-RFE, and Random Forest machine learning algorithms, validated by RT-qPCR, and refined through PPI network analysis. …”
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A Risk Warning Model for Anemia Based on Facial Visible Light Reflectance Spectroscopy: Cross-Sectional Study by Yahan Zhang, Yi Chun, Hongyuan Fu, Wen Jiao, Jizhang Bao, Tao Jiang, Longtao Cui, Xiaojuan Hu, Ji Cui, Xipeng Qiu, Liping Tu, Jiatuo Xu

“…Then, we used 10 different machine learning algorithms to create a predictive model for anemia. …”
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Unveiling new insights into migraine risk stratification using machine learning models of adjustable risk factors by Yu-Chen Liu, Ye-Hai Liu, Hai-Feng Pan, Wei Wang

“…Second, we trained ensemble machine learning (ML) algorithms that incorporated these factors, with Shapley Additive exPlanations (SHAP) value analysis quantifying predictor importance. …”
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Construction and validation of risk prediction models for renal replacement therapy in patients with acute pancreatitis by Fei Zuo, Lei Zhong, Jie Min, Jinyu Zhang, Longping Yao

“…Using these features, four machine learning (ML) algorithms were developed. The optimal model was visualized and clarified using SHapley Additive exPlanations (SHAP) and presented as a nomogram. …”
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