A Task Offloading and Resource Allocation Strategy Based on Multi-Agent Reinforcement Learning in Mobile Edge Computing by Guiwen Jiang, Rongxi Huang, Zhiming Bao, Gaocai Wang

“…Finally, an offloading decision algorithm TOMAC-PPO is proposed. The algorithm applies the proximal policy optimization to the multi-agent system and combines the Transformer neural network model to realize the memory and prediction of network state information. …”
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Characterizing and mapping the spatial variability of HIV risk among adolescent girls and young women: A cross-county analysis of population-based surveys in Eswatini, Haiti, and M... by Kristen N Brugh, Quinn Lewis, Cameron Haddad, Jon Kumaresan, Timothy Essam, Michelle S Li

“…Using geolocated survey data at enumeration clusters and high-resolution satellite imagery, we applied algorithms to predict the number and proportion of at-risk AGYW at hyperlocal levels.…”
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Innovative approach for gauge-based QPE in arid climates: comparing neural networks and traditional methods by Bayan Banimfreg, Ernesto Damiani, Vesta Afzali Gorooh, Duncan Axisa, Luca Delle Monache, Youssef Wehbe

“…Conclusion By effectively merging advanced neural network algorithms with conventional rainfall estimation methods, this study provides a robust framework for understanding and estimating precipitation in arid regions like the UAE. …”
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Feasibility and case studies on converting small hydropower stations to pumped storage by Yangqing Dan, Qingyue Chen, Daren Li, Wenhuan Bai, Weiming Zhou, Anyu Yang, Jia Yang

“…The proposed conversion scheme has been assessed, and predictions regarding annual operating hours, power generation, and energy consumption have been formulated. …”
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Investigation of granuloma-targeted host-pathogen interactions identify vaccine correlates of immune protection associated with control of M. tuberculosis replication by David Forrest Ackart, Dr. Faye Lanni, Victoria Mitcham, Dr. G. Brooke Anderson, Dr. Michael Lyons, Dr. Marcela Henao-Tamayo, Dr Brendan Podell

“…While a number of blood transcriptomic signatures have been shown to predict clinical states of TB in human subjects, no correlates exist to indicate immune signatures that control bacterial growth, which would inform improved vaccine design. …”
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Machine-Learning-Driven Approaches for Assessment, Delegation, and Optimization of Multi-Floor Building by Abtin Baghdadi, Harald Kloft

“…The significance of this research lies in its ability to automate and accelerate complex structural analysis using Adaptive Neuro-Fuzzy Inference Systems (ANFISs), achieving an average error of less than 2% in multi-variable prediction scenarios. The results were compared against reference calculations and ETABS simulations to validate its effectiveness, demonstrating deviations of less than 3%. …”
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Trends in Russia’s GDP Growth under Environmental Constraints by Z. V. Bragina, A. R. Denisov, N. N. Masyuk, N. V. Steblyanskii

“…Methods used: empirical and statistical analysis, building regression models, algorithmic and predictions, building time trends, etc. …”
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Novel estrogen-related gene variants identified by whole-exome sequencing in pregnancy-associated intrahepatic cholestasis by Hua Lai, Siming Xin, Jinliang Zhang, Yang Hu, Wenjuan Fan, Hong Wan, Bowen Chen, Yang Zou, Xiaoming Zeng, Xianxian Liu

“…These variants exhibited the following characteristics: (1) complete absence in 1,237 controls and all public genomic databases (1000 Genomes, ExAC, and dbSNP); (2) evolutionary conservation of the affected residues, with unanimous pathogenic predictions from all algorithms (PolyPhen-2: damaging; SIFT: deleterious; MutationTaster: disease-causing); (3) molecular modeling demonstrating structural perturbations in critical functional domains, including steroid-binding and redox partner interaction sites. …”
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Federated Learning Based on an Internet of Medical Things Framework for a Secure Brain Tumor Diagnostic System: A Capsule Networks Application by Roman Rodriguez-Aguilar, Jose-Antonio Marmolejo-Saucedo, Utku Köse

“…It enables machine learning or deep learning algorithms to establish a client–server relationship, whereby specific parameters are securely shared between models while maintaining the integrity of the learning tasks being executed. …”
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Exploration of Biomarkers of Psoriasis through Combined Multiomics Analysis by Lu Xing, Tao Wu, Li Yu, Nian Zhou, Zhao Zhang, Yunjing Pu, Jinnan Wu, Hong Shu

“…This study aims to screen potential diagnostic indicators affected by DNA methylation for psoriasis based on bioinformatics using multiple machine learning algorithms and to preliminarily explore its molecular mechanisms. …”
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Streaming LiDAR Scene Flow Estimation by Mazen Abdelfattah, Z. Jane Wang, Rabab Ward

“…Scene flow estimation models this dynamic environment by predicting point motion between sequential point cloud scans, and is crucial for safe navigation. …”
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Outpatient diagnosis of endogenous intoxication in surgery by A. A. Solomakha, A. P. Vlasov, V. I. Gorbachenko

“…The problems of diagnosis, treatment, prevention and prediction of purulent diseases in surgery can be solved thanks to advanced digital technologies.Aim of the study. …”
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Machine learning−derived multivariable predictors of postcardiotomy cardiogenic shock in high-risk cardiac surgery patientsCentral MessagePerspective by Edward G. Soltesz, MD, MPH, Randi J. Parks, PhD, Elise M. Jortberg, MS, Eugene H. Blackstone, MD

“…Objective: To develop a model for preoperatively predicting postcardiotomy cardiogenic shock (PCCS) in patients with poor left ventricular (LV) function undergoing cardiac surgery. …”
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Molecular insights into ulcerative colitis and orbital inflammation by Kang Tan, Pei Liu, Zixuan Wu, Xi Long, Yunfeng Yu, Pengfei Jiang, Qinghua Peng

“…GO enrichment, PPI networks, and transcription factor prediction were performed using Cytoscape plugins (cytoHubba and iRegulon). …”
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Machine learning developed LKB1-AMPK signaling related signature for prognosis and drug sensitivity in hepatocellular carcinoma by Wang Li, Xiaoyi Zhu, Jieying Fang

“…The optimal LRS developed using the Lasso algorithm served as a significant risk factor for HCC patients. …”
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Performance evaluation and multi-objective optimization of EDM parameters for Ti6Al4V using different tool electrodes by Manoj Jagdale, Masuk Abdullah, Nitin Ambhore, Atul Kulkarni, Rakesh Chaudhari, Jay Vora, József Menyhárt

“…A minor adequate deviance was observed between the TLBO algorithm’s predicted and actual findings. Scanning electron microscopy (SEM) analysis was conducted to evaluate surface morphology. …”
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Computational Intelligence-Based Structural Health Monitoring of Corroded and Eccentrically Loaded Reinforced Concrete Columns by Somain Sharma, Harish Chandra Arora, Aman Kumar, Denise-Penelope N. Kontoni, Nishant Raj Kapoor, Krishna Kumar, Arshdeep Singh

“…Machine learning (ML)-based prediction models are beneficial in dealing with such complex databases. …”
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Supervised machine learning and genotype by trait biplot as promising approaches for selection of phytochemically enriched Rhus coriaria genotypes by Hamid Hatami Maleki, Reza Darvishzadeh, Ahmad Alijanpour, Yousef Seyfari

“…By using 13 feature selection algorithms, ISSR loci (U823) L1, (U835) L1, (U801) L1, (U816) L2, (U816) L4, (U835) L4, (U854) L1, and (U835) L9 were identified as functional markers which could predict phytochemical response of sumac germplasm. …”
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Design and Development of Diabetes Management System Using Machine Learning by Robert A. Sowah, Adelaide A. Bampoe-Addo, Stephen K. Armoo, Firibu K. Saalia, Francis Gatsi, Baffour Sarkodie-Mensah

“…The model achieved specified goals by predicting with high accuracy, labels of new images. …”
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Machine learning unveils key Redox signatures for enhanced breast Cancer therapy by Tao Wang, Shu Wang, Zhuolin Li, Jie Xie, Kuiying Du, Jing Hou

“…We employed a comprehensive approach by combining ten distinct machine learning algorithms across 108 different combinations to scrutinize 88 pre-existing signatures of breast cancer. …”
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