Maglev Derived Systems: An Interoperable Freight Vehicle Application Focused on Minimal Modifications to the Rail Infrastructure and Vehicles by Jesus Felez, Miguel A. Vaquero-Serrano, William Z. Liu, Carlos Casanueva, Michael Schultz-Wildelau, Gerard Coquery, Pietro Proietti

“…Target speed profiles were precomputed using dynamic programming, while a model predictive control algorithm determined the optimal train state and control trajectories. …”
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Uncertainty quantification with graph neural networks for efficient molecular design by Lung-Yi Chen, Yi-Pei Li

“…Using benchmarks from the Tartarus and GuacaMol platforms, our results show that UQ integration via probabilistic improvement optimization (PIO) enhances optimization success in most cases, supporting more reliable exploration of chemically diverse regions. …”
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On the academic ideology of “Sorting the gangue is sorting the images” by Hongwei MA, Ye ZHANG, Peng WANG, Xiangang CAO, Zhen NIE, Xiaorong WEI, Wenjian ZHOU, Mingzhen ZHANG

“…Coal gangue sorting is the most basic, effective, and important technical measure to improve coal quality. …”
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Maximum likelihood self-calibration for direction-dependent gain-phase errors with carry-on instrumental sensors:case of deterministic signal model by WANG Ding1, PAN Miao2, WU Ying1

“…Aim at the self-calibration of direction-dependent gain-phase errors in case of deterministic signal model,the maximum likelihood method（MLM） for calibrating the direction-dependent gain-phase errors with carry-on instrumental sensors was presented.In order to maximize the high-dimensional nonlinear cost function appearing in the MLM,an improved alternative projection iteration algorithm,which could optimize the azimuths and direction-dependent gain-phase errors was proposed.The closed-form expressions of the Cramér-Rao bound（CRB） for azimuths and gain-phase errors were derived.Simulation experiments show the effectiveness and advantage of the novel method.…”
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Research on Behavior Recognition and Online Monitoring System for Liaoning Cashmere Goats Based on Deep Learning by Geng Chen, Zhiyu Yuan, Xinhui Luo, Jinxin Liang, Chunxin Wang

“…YOLOv8n demonstrated superior performance, converging within 50 epochs with an average accuracy of 95.31%, making it a baseline for further improvements. We improved YOLOv8n through dataset expansion, algorithm lightweighting, attention mechanism integration, and loss function optimization. …”
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Low power IoT device communication through hybrid AES-RSA encryption in MRA mode by Qiang Chang, Tianqi Ma, Wenzhong Yang

“…This modification optimizes computational efficiency and strengthens security.Furthermore, we investigate the feasibility of integrating the RSA and AES algorithms and propose a novel RSA-AES hybrid algorithm MRA. …”
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Student employment forecasting model based on random forest and multi-features fusion by Zhenguo Xing, Xiao Wu, Jiangjiang Li

“…Secondly, in order to improve the accuracy of the prediction model, a feature selection model combining principal component analysis and random forest algorithm is used to select the optimal subset from the original features. …”
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Modeling Worldwide Tree Biodiversity Using Canopy Structure Metrics from Global Ecosystem Dynamics Investigation Data by Jin Xu, Kjirsten Coleman, Volker C. Radeloff, Melissa Songer, Qiongyu Huang

“…With the launch of NASA’s Global Ecosystem Dynamics Investigation (GEDI), we evaluated the efficacy of space-borne lidar metrics in predicting tree species richness globally and explored whether integrating spectral vegetation metrics with space-borne lidar data could improve model performances. Using Forest Global Earth Observatory (ForestGEO) data, we developed three models using the random forest algorithm to predict global tree species richness across climate zones, including a dynamic habitat index (DHI)-only model, a GEDI-only model, and a combined GEDI-DHI model. …”
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Promoting mental health in the age of new digital tools: balancing challenges and opportunities of social media, chatbots, and wearables by Julien Coelho, Julien Coelho, Florian Pécune, Jean-Arthur Micoulaud-Franchi, Jean-Arthur Micoulaud-Franchi, Bernard Bioulac, Pierre Philip, Pierre Philip

“…Although stigma and discrimination hinder progress, these conditions are often preventable or manageable at minimal cost. The adoption of digital tools in mental health promotion, including telemedicine, online therapy, social media, and wearables, offers promising new avenues to address these issues. …”
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Multi-Level Spectral Attention Network for Hyperspectral BRDF Reconstruction from Multi-Angle Multi-Spectral Images by Liyao Song, Haiwei Li

“…For the multi-level Transformer spectral dimension enhancement algorithm, we added spectral response loss constraints to improve BRDF accuracy. …”
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An Evolutionary Deep Reinforcement Learning-Based Framework for Efficient Anomaly Detection in Smart Power Distribution Grids by Mohammad Mehdi Sharifi Nevisi, Mehrdad Shoeibi, Francisco Hernando-Gallego, Diego Martín, Sarvenaz Sadat Khatami

“…This optimization ensures improved accuracy, faster convergence, and better generalization to unseen data. …”
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Global Feature Focusing and Information Enhancement Network for Occluded Pedestrian Detection by ZHENG Kaikui, JI Kangyou, LI Jun, LI Qiming

“…Existing methods, including post-processing optimization, specific model based improvements, and body part feature based methods, have limitations such as inaccurate handling of heavily occluded positive samples, high computational complexity, and susceptible to background noise. …”
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Strategies and Challenges in Detecting XSS Vulnerabilities Using an Innovative Cookie Collector by Germán Rodríguez-Galán, Eduardo Benavides-Astudillo, Daniel Nuñez-Agurto, Pablo Puente-Ponce, Sonia Cárdenas-Delgado, Mauricio Loachamín-Valencia

“…Additionally, clustering algorithms enabled user segmentation based on cookie data, identification of behavioral patterns, enhanced personalized web recommendations, and browsing experience optimization. …”
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PATH PLANNING AND OBSTACLE AVOIDANCE METHODS FOR AUTONOMOUS MOBILE ROBOTS by Ihor Berizka

“…Research at the time of writing focuses on optimizing existing algorithms and hybridization to improve efficiency. …”
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Combined unstable damage to the pelvis and abdominal organs. Justification of treatment tactics by O.A. Burianov, V.Р. Kvasha, V.M. Diomin, V.M. Lianskorunskyi, D.V. Miasnikov

“…The mortality rate for pelvic fractures and abdominal trauma is approximately 5–10 %, which is attributed to hemodynamic instabi­lity in this cohort. The purpose was to improve treatment outcomes in patients with combined pelvic and abdominal organ injuries by optimizing treatment strategy. …”
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Sonar-Based Simultaneous Localization and Mapping Using the Semi-Direct Method by Xu Han, Jinghao Sun, Shu Zhang, Junyu Dong, Hui Yu

“…To obtain better feature extraction results in specific directions, we propose a method that accelerates the computation of the two-dimensional SO-CFAR algorithm, with the time cost being only a very slight increase compared to the one-dimensional SO-CFAR. …”
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Electrophysiological changes in the acute phase after deep brain stimulation surgery by Lucia K. Feldmann, Diogo Coutinho Soriano, Jeroen Habets, Valentina D'Onofrio, Jonathan Kaplan, Varvara Mathiopoulou, Katharina Faust, Gerd-Helge Schneider, Doreen Gruber, Georg Ebersbach, Hayriye Cagnan, Andrea A. Kühn

“…Background: With the introduction of sensing-enabled deep brain stimulation devices, characterization of long-term biomarker dynamics is of growing importance for treatment optimization. The microlesion effect is a well-known phenomenon of transient clinical improvement in the acute post-operative phase. …”
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Energy-efficient power control for two-tier femtocell networks with block-fading channels by Zhixin Liu, Jieshuai Wu, Yang Liu, Hongjiu Yang, Jianfeng Guan, Yu Wang

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Building Up a Robust Risk Mathematical Platform to Predict Colorectal Cancer by Le Zhang, Chunqiu Zheng, Tian Li, Lei Xing, Han Zeng, Tingting Li, Huan Yang, Jia Cao, Badong Chen, Ziyuan Zhou

“…Colorectal cancer (CRC), as a result of a multistep process and under multiple factors, is one of the most common life-threatening cancers worldwide. To identify the “high risk” populations is critical for early diagnosis and improvement of overall survival rate. …”
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DAG-based swarm learning: A secure asynchronous learning framework for Internet of Vehicles by Xiaoge Huang, Hongbo Yin, Qianbin Chen, Yu Zeng, Jianfeng Yao

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