Identifying key factors influencing maize stalk lodging resistance through wind tunnel simulations with machine learning algorithms by Guanmin Huang, Ying Zhang, Shenghao Gu, Weiliang Wen, Xianju Lu, Xinyu Guo

“…Climate change has intensified maize stalk lodging, severely impacting global maize production. While numerous traits influence stalk lodging resistance, their relative importance remains unclear, hindering breeding efforts. …”
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Preliminary study on objective evaluation algorithm of human infrared thermogram seriality and its clinical application in population with metabolic syndrome by Yu Chen, Jia-Yang Guo, Yan-Hong An, Xian-Hui Zhang, Jia-Min Niu, Xiao-Ran Li, Hui-Zhong Xue, Yi-Meng Yang, Lu-Qi Cai, Yu-Chen Xia, Quan-Yi Chen, Bing-Yang Cai, Wen-Zheng Zhang, Yong-Hua Xiao

“…Objectives To develop an objective evaluation algorithm for assessing the seriality of infrared thermograms for the auxiliary diagnosis of diseases, and to internally validate the algorithm using metabolic syndrome (MS) as a case example.Methods A total of 266 healthy participants (133 of each sex) and 180 patients with MS (133 males and 47 females) were retrospectively enrolled. …”
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An Automatic Algorithm for Mapping Algal Blooms and Aquatic Vegetation Using Sentinel-1 SAR and Sentinel-2 MSI Data by Yihao Xin, Juhua Luo, Jinlong Zhai, Kang Wang, Ying Xu, Haitao Qin, Chao Chen, Bensheng You, Qing Cao

“…There are still limited algorithms that comprehensively reflect the dynamic changes of aquatic vegetation and AB. …”
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Screening potential diagnostic biomarkers for PLA2R‑associated idiopathic membranous nephropathy by WGCNA analysis and LASSO algorithm by Jinxu Huang, Yaqing Huang, Xiaoling Zeng, Yuhong Zhang, Junneng Zhang, Qingchu Hong, Yongtiao Peng

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Classification of FAMACHA© Scores with Support Vector Machine Algorithm from Body Condition Score and Hematological Parameters in Pelibuey Sheep by Oswaldo Margarito Torres-Chable, Cem Tırınk, Rosa Inés Parra-Cortés, Miguel Ángel Gastelum Delgado, Ignacio Vázquez Martínez, Armando Gomez-Vazquez, Aldenamar Cruz-Hernandez, Enrique Camacho-Pérez, Dany Alejandro Dzib-Cauich, Uğur Şen, Hacer Tüfekci, Lütfi Bayyurt, Hilal Tozlu Çelik, Ömer Faruk Yılmaz, Alfonso J. Chay-Canul

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Screening and validation of long non-coding RNAs associated with colorectal cancer based on random forest and LASSO regression algorithm by Yujia Zhao, Qian Li, Xintong Cui, Zhiyu Zhang, Yong You, Xiaowen Hou, Yan Wang, Xu Feng

“…Random forest (RF) and LASSO (Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithms were constructed to screen lncRNAs closely related to CRC, and their screening efficiency was verified. …”
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Supervised machine learning algorithms for the classification of obesity levels using anthropometric indices derived from bioelectrical impedance analysis by Rodrigo Yáñez-Sepúlveda, Aldo Vásquez-Bonilla, Rodrigo Olivares, Pablo Olivares, Juan Pablo Zavala-Crichton, Claudio Hinojosa-Torres, Catalina Muñoz-Strale, Frano Giakoni-Ramírez, Josivaldo de Souza-Lima, Jacqueline Páez-Herrera, Jorge Olivares-Arancibia, Tomás Reyes-Amigo, Guillermo Cortés-Roco, Juan Hurtado-Almonacid, Eduardo Guzmán-Muñoz, Nicole Aguilera-Martínez, José Francisco López-Gil, Boryi A. Becerra-Patiño, Juan David Paucar-Uribe, Exal Garcia-Carrillo, Vicente Javier Clemente-Suárez

“…SHapley Additive exPlanations analysis revealed that FMI, FFMI, and BMI were the most influential features, while sex had minimal predictive impact. Machine learning models, particularly tree-based algorithms like random forest, show great potential in classifying obesity levels from anthropometric data with high accuracy and interpretability. …”
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Using Optimization Algorithms for Effective Missing-Data Imputation: A Case Study of Tabular Data Derived from Video Surveillance by Mahmoud M. Eid, Kamal ElDahshan, Abdelatif H. Abouali, Alaa Tharwat

“…In the first experiment, using only synthetic data, the results indicate that the WOA-based approach outperforms PSO, GWO, and SCA optimization algorithms. The second experiment used real datasets, while the third used tabular data extracted from a video-surveillance system. …”
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Software with artificial intelligence-derived algorithms for detecting and analysing lung nodules in CT scans: systematic review and economic evaluation by Julia Geppert, Peter Auguste, Asra Asgharzadeh, Hesam Ghiasvand, Mubarak Patel, Anna Brown, Surangi Jayakody, Emma Helm, Dan Todkill, Jason Madan, Chris Stinton, Daniel Gallacher, Sian Taylor-Phillips, Yen-Fu Chen

“…Average specificity decreased slightly in two studies while it improved slightly in one study (0.77–1.00 without and 0.81–0.97 with AI assistance). …”
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A new stochastic multi-objective model for the optimal management of a PV/wind integrated energy system with demand response, P2G, and energy storage devices by Hossein Faramarzi, Navid Ghaffarzadeh, Farhad Shahnia

“…Non-dominated sorting genetic algorithm III (NSGA-III) is employed to efficiently search for the optimal solutions. …”
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A Comprehensive Review and Benchmarking of Fairness-Aware Variants of Machine Learning Models by George Raftopoulos, Nikos Fazakis, Gregory Davrazos, Sotiris Kotsiantis

“…Beyond these, an increasingly explored avenue is the direct modification of existing algorithms, aiming to embed fairness constraints into their design while preserving or even enhancing predictive performance. …”
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Paradigmatic Relations of the Metalanguage of Metalinguistics by Sergey V. Lesnikov

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Modification of preoperative preparation as a guarantee of improvement of perioperative treatment in elderly and senile patients by M. B. Danylyuk, S. M. Zavgorodniy, A. I. Rylov, M. A. Кubrak, N. O. Yareshko, A. V. Bachurin

“…Into the control group 89 (58.2 %) patients were included, who were treated in accordance to the standards and clinical protocols, while into the main one - 64 (41.8%) patients, in whom preoperative preparation was modified in accordance to algorithm. …”
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Development of a PYTHON library for a mathematical model of nuclear reactor kinetics by Aleksei G. Goryunov, Danil D. Kachanov, Kirill D. Kachanov

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Optimized and Routed Wiring Harness Based on Zonal Clustering Concept Using AI in the Automotive Industry by Md Sanowar Hossain, Hafiz Abdul Quddus, Ziya Cevahir, Alexander Jesser

“…A methodology integrating K-means clustering with dynamic grid-based routing algorithms (A* and Bresenham’s line algorithm) is applied to optimize the wiring harness layout across the vehicle’s zones, covering six key domains (comfort, chassis, drive assist, infotainment, system, and powertrain). …”
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Solving Three-Stage Operating Room Scheduling Problems with Uncertain Surgery Durations by Yang-Kuei Lin, Chin Soon Chong

“…The results from different problem sizes and uncertainty levels show that GARS and GARS_SA consistently perform better than the other algorithms. In large-scale tests with moderate uncertainty (30 surgeries, α = 0.5), GARS achieves an average makespan of 633.85, a standard deviation of 40.81, and a worst-case performance ratio (WPR) of 1.00, while GAD reaches 673.75, 54.21, and 1.11, respectively. …”
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Research and application of new method based on MDT intelligent analysis of LTE radio interference by Qizhu ZHONG, Xiuquan WU, Yaoman LUO

“…Aiming at the traditional LTE (long term evolution) wireless interference judgment analysis method has insufficient user dimension data,insufficient correlation of quality reasons,and too much dependence on manual analysis.A new method based on MDT (minimized drive test) technology for intelligent analysis of LTE radio interference was proposed.Firstly,the user’s wireless quality data and latitude and longitude information were collected by using MDT and MR (measurement report),and then DBSCAN (density-based spatial clustering of applications with noise) and adaptive clustering algorithm were used to collect the wireless coverage indicators and the latitude and longitude and other data were used for cluster analysis.Finally,the clustered data was imported into the self-built wireless interference judgment model,and the interference type was analyzed to realize the intelligent analysis of LTE wireless interference.Compared with the traditional interference analysis method,the proposed method can avoid the complicated road test process and improve the accuracy of the analysis.Data acquisition clustering and model analysis experiments show that the new method improves the efficiency and location accuracy of data collection,and effectively reduces the time of manual investment while the results are more accurate.…”
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Lightweight Implicit Approximation of the Minkowski Sum of an N-Dimensional Ellipsoid and Hyperrectangle by Martijn Courteaux, Bert Ramlot, Peter Lambert, Glenn Van Wallendael

“…To this end, we propose a fast, computationally lightweight, non-iterative algorithm that approximates the Minkowski sum through the intersection of two carefully constructed bounding boxes. …”
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Crops Disease Detection, from Leaves to Field: What We Can Expect from Artificial Intelligence by Youssef Lebrini, Alicia Ayerdi Gotor

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Utilizing LSTM-GRU for IOT-Based Water Level Prediction Using Multi-Variable Rainfall Time Series Data by Indrastanti Ratna Widiasari, Rissal Efendi

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