Framework for extracting multi-objective operation rules for cascade reservoirs based on causal features and physical mechanisms by Donglin Gu, Baowei Yan, Jianbo Chang, Yixuan Zou, Dongxu Yang, Mingbo Sun, Xiaoyu Diao

“…Moreover, embedding physical constraints into the model’s loss function further enhances interpretability. …”
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State Identification of Charging Module Based on SN‐EMD‐SSEE and DBO‐HKELM by Bingyu Li, Xianhai Pang, Xuhao Du, Ziwen Cai

“…The charging module is usually composed of power electronic devices, but failures may occur in power electronic devicesdue to device aging and mechanical vibration in the complex environment; it will result in huge economic losses. However, the protection function of the charging module covers short fault, over‐voltage fault, and over‐current at system level rather than the open‐circuit fault of MOSFETs and diodes at component level, which leads to hidden fire danger or accident risks. …”
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Functional Dehydrated Foods for Health Preservation by R. M. S. C. Morais, A. M. M. B. Morais, I. Dammak, J. Bonilla, P. J. A. Sobral, J.-C. Laguerre, M. J. Afonso, E. C. D. Ramalhosa

“…The market of functional foods has experienced a huge growth in the last decades due to the increased consumers’ awareness in a healthy lifestyle. …”
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Applying machine learning algorithms to explore the impact of combined noise and dust on hearing loss in occupationally exposed populations by Yong Li, Xin Sun, Yongtao Qu, Shuling Yang, Yueyi Zhai, Yan Qu

“…Abstract This study aimed to explore the combined impacts of occupational noise and dust on hearing and extra-auditory functions and identify associated risk factors via machine learning techniques. …”
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Multi-period and multi-objective stock portfolio modeling considering cone constraints by Masoomeh Zeinalnezhad, Zohreh Ebrahimi, Towhid Pourrostam

“…Another result obtained in this study is calculating the percentage of optimal amounts assigned to each asset, providing a base for investors to avert investing in unsuitable assets and incurring losses. …”
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Improvement of the Voltage Profile and Loss Reduction in Distribution Network Using Moth Flame Algorithm: Wolaita Sodo, Ethiopia by S. Balakumar, Akililu Getahun, Samuel Kefale, K. Ramash Kumar

“…The objective function is defined to minimize voltage deviation and power loss. …”
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Pipe Resistance Loss Calculation in Industry 4.0: An Innovative Framework Based on TransKAN and Generative AI by Qinyu Zhang, Huiying Liu, Zhike Liu, Yongkang Liu, Yuhan Gong, Chonghao Wang

“…The rapid development of Industry 4.0 provides intelligent and data-driven optimization ideas for this challenge. This study introduces a novel pipeline resistance loss prediction framework integrating generative artificial intelligence with a TransKAN model. …”
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Improvement in Pavement Defect Scenarios Using an Improved YOLOv10 with ECA Attention, RefConv and WIoU by Xiaolin Zhang, Lei Lu, Hanyun Luo, Lei Wang

“…This study addresses challenges such as multi-scale defects, varying lighting, and irregular shapes by proposing an improved YOLOv10 model that integrates the ECA attention mechanism, RefConv feature enhancement module, and WIoU loss function for complex pavement defect detection. …”
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A Multi-Objective Gray Consistency Correction Method for Mosaicking Regional SAR Intensity Images with Brightness Anomalies by Jiaying Wang, Xin Shen, Deren Li, Litao Li, Yonghua Jiang, Jun Pan, Zezhong Lu, Wei Yao

“…We constructed a two-objective optimization model to ensure regional image gray consistency and mitigate brightness information loss. …”
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An Automated Decision Support System for Portfolio Allocation Based on Mutual Information and Financial Criteria by Massimiliano Kaucic, Renato Pelessoni, Filippo Piccotto

“…In the second stage, this work considers a portfolio optimization model where the objective function is a modified version of the Sharpe ratio, consistent with the choices of a rational agent even when faced with negative risk premiums. …”
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Interactive behaviour between currency speculators, monetary and fiscal actors to minimise social loss: A game theoretic analysis by Shahbazi Bita, Pesyan Vahid Nikpey, Salimi Zahra

“…Three strategies for each player (government, central bank, and currency market participants) were defined by their objectives, and through optimisation, the reaction function for each player was determined. This approach helped to identify the optimal interactive strategy among these players to minimise social loss. …”
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Loss of correlated proteasomal subunit expression selectively promotes the 20SHigh state which underlies luminal breast tumorigenicity by Rangapriya Sundararajan, Shubhada R. Hegde, Ashish Kumar Panda, Joel Christie, Nikhil Gadewal, Prasanna Venkatraman

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Impact of Pathological Grades of Metabolic Dysfunction-Associated Steatotic Liver Disease on Weight Loss Following Laparoscopic Sleeve Gastrectomy by Qu YF, Wang K, Li Y, Cheng YG, Hu SY, Zhong MW

“…General linear models confirmed the significant dynamic effects of MASLD severity on weight loss over time (P < 0.05).Conclusion: MASLD severity significantly affects postoperative weight loss and delays the achievement of optimal outcomes, especially in the early postoperative period. …”
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Economic and environmental power dispatch for energy management systems applied to microgrids with wind energy resources and battery energy storage systems by Jhon Montano, John E. Candelo-Becerra, Cristian Escudero-Quintero, Juan Pablo Guzmán

“…To solve this problem, four metaheuristic optimization algorithms were implemented: Enhanced Prairie Dog Optimization (EPDO), Salp Swarm Algorithm (SSA), Generalized Normal Distribution Optimization (GNDO), and Crow Search Algorithm (CSA). …”
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Advancing Seaweed Cultivation: Integrating Physics Constraint in Machine Learning for Enhanced Biomass Forecasting in IMTA Systems by Alisa Kunapinun, William Fairman, Paul S. Wills, Dennis Hanisak, Bing Ouyang

“…Compared with the LSTM models with MSE loss function alone, the results showed that the model with a loss function under physics constraint achieved a significantly lower error in predicting seaweed growth. …”
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Solar-thermoelectric mobile storage system integrated with electric vehicles for reducing postharvest and microbial losses in agro produce transportation by Lalith Pankaj Raj Nadimuthu, Kirubakaran Victor, Mohit Bajaj, Vojtech Blazek, Lukas Prokop

“…These losses are predominantly attributed to the lack of accessible and decentralized cold storage infrastructure. …”
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SDES-YOLO: A high-precision and lightweight model for fall detection in complex environments by Xiangqian Huang, Xiaoming Li, Limengzi Yuan, Zhao Jiang, Hongwei Jin, Wanghao Wu, Ru Cai, Meilian Zheng, Hongpeng Bai

“…By incorporating a multi-scale feature extraction pyramid (SDFP), occlusion-aware attention mechanism (SEAM), an edge and spatial information fusion module (ES3), and a WIoU-Shape loss function, the SDES-YOLO model significantly enhances fall detection performance in complex scenarios. …”
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Improving the Accuracy of Neural Network Pattern Recognition by Fractional Gradient Descent by Ruslan I. Abdulkadirov, Pavel A. Lyakhov, Valentina A. Baboshina, Nikolay N. Nagornov

“…In this paper we propose the fractional gradient descent for increasing the training and work of modern neural networks. This optimizer searches the global minimum of the loss function considering the fractional gradient directions achieved by Riemann-Liouville, Caputo, and Grunwald-Letnikov derivatives. …”
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VariGAN: Enhancing Image Style Transfer via UNet Generator, Depthwise Discriminator, and LPIPS Loss in Adversarial Learning Framework by Dawei Guan, Xinping Lin, Haoyi Zhang, Hang Zhou

“…The purpose of this research is to present <i>VariGAN</i>, a novel approach that incorporates three additional strategies to optimize GAN-based image style transfer: (1) Improving the quality of transferred images by utilizing an effective UNet generator network in conjunction with a context-related feature extraction module. (2) Optimizing the training process while reducing dependency on the generator through the use of a depthwise discriminator. (3) Introducing LPIPS loss to further refine the loss function and enhance the overall generation quality of the framework. …”
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A Distributed Multi-Robot Collaborative SLAM Method Based on Air–Ground Cross-Domain Cooperation by Peng Liu, Yuxuan Bi, Caixia Wang, Xiaojiao Jiang

“…Then, it uses the minimization substitution function of non-trivial loss kernel optimization to gradually converge the distributed pose graph optimization problem to a first-order critical point, thereby significantly improving global pose estimation accuracy. …”
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