Muscle Strengthening Exercises for the Foot and Ankle: A Scoping Review Exploring Adherence to Best Practice for Optimizing Musculoskeletal Health by John W. A. Osborne, Hylton B. Menz, Glen A. Whittaker, Matthew Cotchett, Karl B. Landorf

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Edge-centric optimization: a novel strategy for minimizing information loss in graph-to-text generation by Yao Zheng, Jingyuan Li, Jianhe Cen, Shiqi Sun, Dahu Yin, Yuanzhuo Wang

“…TriELMR adopts three main strategies to reduce information loss during learning: (1) Knowledge Sequence Optimization; (2) EMLR Framework; and (3) Graph Activation Function. …”
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Transformer Fault Diagnosis Based on Multi-Strategy Enhanced Dung Beetle Algorithm and Optimized SVM by Shuming Zhang, Hong Zhou

“…Subsequently, the IDBO optimizes the SVM’s penalty factor <i>C</i> and kernel function parameter <i>g</i>, which are then input into the SVM for training, yielding an efficient fault diagnosis model. …”
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Optimization Strategy for Underwater Target Recognition Based on Multi-Domain Feature Fusion and Deep Learning by Yanyang Lu, Lichao Ding, Ming Chen, Danping Shi, Guohao Xie, Yuxin Zhang, Hongyan Jiang, Zhe Chen

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Optimal treatment strategy and prognostic analysis for patients with locally advanced Upper Tract Urothelial Carcinoma by Fan Jiang, Ruijie Dai, Mingguo Zhou, Xuefei Cao, Jun Lu, Xinyu Zheng, Xinyu Zheng

“…ObjectiveThis study aims to identify the optimal treatment strategy and conduct a prognostic analysis for patients with locally advanced Upper Tract Urothelial Carcinoma (UTUC).Methods and materialsThe study included 3,829 patients diagnosed with pT3-4N0/+M0 UTUC from 2004 to 2015, with data obtained from the Surveillance, Epidemiology, and End Results (SEER) database. …”
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Research on operation optimization of heavy-haul combined trains in long and steep downhill sections based on reinforcement learning by WANG Jianhua, WANG Chunyi, ZENG Zhou, WANG Cong, WANG Qingyuan, YANG Hang

“…This algorithm incorporated constraints including train traction/electric braking characteristics, braking application and release times of train pipes, speed limits, and operational smoothness, to optimize the operation strategy for heavy-haul combined trains in long and steep downhill sections by reinforcement learning. …”
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Joint Optimization Method for Preventive Maintenance and Train Scheduling of Subway Vehicles Based on a Spatiotemporal Network Graph by Chuanzhen Liu, Zhongwei Xu, Meng Mei, Wenqing Li

“…Finally, an improved genetic algorithm is employed to solve the model and determine the optimal scheduling and maintenance strategy. The experimental results demonstrate that the proposed method effectively addresses the challenges in modeling and solving the joint optimization problem, enabling efficient coordination between maintenance and scheduling while enhancing the overall operational efficiency in subway vehicle management.…”
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One-point Method for Speed Strategy Optimization Based on Slope Simplification and Speed Limit Prediction by XING Jian, HAN Bing

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Optimization of the Network Control Strategy for ATP Auto-passing Neutral Section in the CRH2 EMU by HUANG Keqing, XIONG Yan, LIN Lei, BIN Huajia

“…Through the combination optimization strategy, the proposed scheme solves the applicability of different operating conditions, improves the stability and reliability of the network control system, and guarantees the safety of train operation. …”
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Optimizing the Pairs-Trading Strategy Using Deep Reinforcement Learning with Trading and Stop-Loss Boundaries by Taewook Kim, Ha Young Kim

“…We find that our proposed model is trained well and outperforms traditional pairs-trading strategies.…”
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Dynamic Collaborative Optimization Strategy for Multiple Area Clusters in Distribution Networks Considering Topology Change by Weichen Liang, Xinsheng Ma, Shuxian Yi, Yi Zhang, Xiaobo Dou

“…To tackle the challenges arising from missing real-time measurement data and dynamic changes in network topology in optimizing and controlling distribution networks, this study proposes a data-driven collaborative optimization strategy tailored for multi-area clusters. …”
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OPTIMIZATION STRATEGIES AND COMPUTATIONAL MODELING IN THE DESIGN AND PERFORMANCE EVALUATION OF GREEN POROUS OIL ADSORBENT MATERIALS by Haoran Zhang, Sagdat Mederbekovna Tazhibayeva

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OPTIMIZATION STRATEGIES AND COMPUTATIONAL MODELING IN THE DESIGN AND PERFORMANCE EVALUATION OF GREEN POROUS OIL ADSORBENT MATERIALS by Haoran Zhang, Sagdat Mederbekovna Tazhibayeva

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Using the proximal policy optimization and prospect theory to train a decision-making model for managing personal finances by Vladyslav Didkivskyi, Dmytro Antoniuk, Tetiana Vakaliuk, Yevhen Ohinskyi

“…The tasks can be formulated as follows: 1) design a reinforcement learning environment featuring different investment options with varying average returns and volatility levels; 2) train the reinforcement learning agent using the Proximal Policy Optimization algorithm to learn recommended investment allocations; 3) implement a reward function based on Prospect Theory, incorporating parameters that reflect different investor risk profiles, such as loss aversion and diminishing sensitivity to gains and losses. …”
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VILLAGE WEBSITE DEVELOPMENT TRAINING AS A DIGITAL-BASED SERVICE OPTIMIZATION IN ALANG-ALANG VILLAGE, TRAGAH, BANGKALAN by Erna Setijaningrum, Muhammad Ghofiqi, Luqman Purwanto, Rendy Billiyanto, Faried Effendy

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Neutrosophic Analysis of Strategies to Improve Productivity in an Restaurant Chain by Efrén Gonzalo Montenegro Cueva, Milena Alejandra Napa Alcívar

“…The research focused on identifying effective strategies to optimize processes and addressing specific challenges such as staff turnover and compensation management. …”
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Strategi Bimbingan Kelompok dengan Teknik Permainan untuk Meningkatkan Optimisme by Mualwi Widiatmoko, Fadhila Malasari Ardini

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Multicomponent Exercise and Functional Fitness: Strategies for Fall Prevention in Aging Women by André Schneider, Luciano Bernardes Leite, José Teixeira, Pedro Forte, Tiago M. Barbosa, António M. Monteiro

“…Multicomponent exercise training has emerged as an effective strategy for mitigating these risks by enhancing strength, balance, flexibility, and aerobic capacity. …”
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Research on LSTM-PPO Obstacle Avoidance Algorithm and Training Environment for Unmanned Surface Vehicles by Wangbin Luo, Xiang Wang, Fang Han, Zhiguo Zhou, Junyu Cai, Lin Zeng, Hong Chen, Jiawei Chen, Xuehua Zhou

“…In response to the above problems, this paper proposes a long and short memory network-proximal strategy optimization (LSTM-PPO) intelligent obstacle avoidance algorithm for non-particle models in non-ideal environments, and designs a corresponding deep reinforcement learning training environment. …”
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Research on adaptive parking planning of heavy-haul trains on Shenmu-Shuozhou railway by HE Jia, YUAN Peng

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