Effects of the lavage through fistula in treatment of spontaneous esophageal rupture by combined thoracoscopic and gastroscopic management by Zhao Huang, Penglong Zhao, Bingmei Qiu, Chuan Gao, Zhao Chen, Nan Yang, Yang Xu, Zhiqiang Zou, Yi Shen, Liwen Hu

“…Conclusions The Lavage-Drainage approach enhanced the drainage efficiency, reduced the inflammation level, and improved the prognosis of SER. However, this study has some limitations, and further multi-center prospective studies are needed to optimize the treatment and reduce costs.…”
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Electric Submersible Pump Fault Diagnosis Based on Laplacian Eigenmaps and Weighted Extreme Learning Machine by XU Zekun, FU Jun, GAO Xiaoyong, ZHANG Yu, LI Qiang, TAN Chaodong

“…In response to the serious imbalance in the data collected by ESP, firstly, a fault diagnosis model is established using a weighted extreme learning machine; Then, to solve the problems of insufficient algorithm learning, high computational costs caused by weighted strategies, and poor performance in applying to high-dimensional feature spaces, the Laplacian eigenmaps method is introduced to further optimize the model; finally, the effectiveness of the proposed method was validated on the TE chemical process dataset, and the practicality of the algorithm was experimentally validated on the real-time fault dataset of electric submersible pump. …”
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AC-YOLO: A lightweight ship detection model for SAR images based on YOLO11. by Rui He, Dezhi Han, Xiang Shen, Bing Han, Zhongdai Wu, Xiaohu Huang

“…However, existing SAR ship detection algorithms encounter two major challenges: limited detection accuracy and high computational cost, primarily due to the wide range of target scales, indistinct contour features, and complex background interference. …”
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Deep learning-based identification of patients at increased risk of cancer using routine laboratory markers by Vivek Singh, Shikha Chaganti, Matthias Siebert, Sowmya Rajesh, Andrei Puiu, Raj Gopalan, Jamie Gramz, Dorin Comaniciu, Ali Kamen

“…Abstract Early screening for cancer has proven to improve the survival rate and spare patients from intensive and costly treatments due to late diagnosis. …”
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Adaptive Multi-Robot Exploration for Unknown Environments Using Edge-Weighted Path Planning by Farhad Baghyari, Tyler Parsons, Jaho Seo, Byeongjin Kim, Mingeuk Kim, Hanmin Lee

“…Existing centralized approaches struggle with scalability, while decentralized methods often incur high computational costs and inefficient task coordination. This study presents a scalable and adaptive multi-robot exploration algorithm that adaptively updates edge weights based on visit counts, reservations, and obstacles to optimize path allocation and minimize redundant scanning. …”
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Integrated export instream coefficient model for accurate nonpoint source pollution estimation and management in the Yellow River Basin by Xueting Wang, Lei Wu, Yongkun Luo, Yimu Liu, Ruowen Wang

“…Empirical EC values were derived using genetic algorithm (GA) and Latin hypercube sampling, then improved EC and corrected EC were employed to estimate pollutant discharge and water inflow across land uses. …”
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The Mode of Constructing Safe Trajectories of Motion of the Unmanned Aerial Vehicle while Monitoring Power Lines Considering the Influence of their Electromagnetic Fields by Shabanova A.R., Tolstoy I.M., Lebedev I.V.

“…Consequently, maintenance costs of overhead power line service can be optimized.…”
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Machine Learning Approach to Quantity Management for Long-Term Sustainable Development of Dockless Public Bike: Case of Shenzhen in China by Qingfeng Zhou, Chun Janice Wong, Xian Su

“…It is feasible to use these factors to predict area type to optimize the number of available bicycles, reduce operating costs, and improve utilization efficiency. …”
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Distribution Ratio Prediction of Major Components in 30%TBP/kerosene-HNO3 System Based on Machine Learning by YU Ting1, ZHANG Yinyin2, ZHANG Ruizhi3, JIN Wenlei2, LUO Yingting2, ZHU Shengfeng3, HE Hui1, YE Guoan1, GONG Helin4

“…These models were trained based on different datasets, and their hyper-parameters were optimized using algorithms such as grid search, Bayesian optimization, and K-fold cross-validation. …”

Presenting a Multi-Start Hybrid Heuristic for Solving the Problem of Two-Echelon Location-Routing Problem with Simultaneous Pickup and Delivery (2E-LRPSPD) by Houming Fan, Jiaxin Wu, Xin Li, Xiaodan Jiang

“…Results indicate that MHH-PR can reduce the gap between the near optimal and global optimal solutions by 1%-2%. The proposed algorithm significantly improves computational efficiency by reducing the computational time of more than 10 min for existing cases involving 20 nodes to less than 10 s.…”
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The use of artificial intelligence in the HR processes of logistics companies by Adam Panek

“…Personalization of AI-based training improves employee engagement and productivity, while optimization of work schedules and accurate forecasting of staffing needs allow for better human resource management. …”
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Machine learning allows robust classification of lung neoplasm tissue using an electronic biopsy through minimally-invasive electrical impedance spectroscopy by Georgina Company-Se, Virginia Pajares, Albert Rafecas-Codern, Pere J. Riu, Javier Rosell-Ferrer, Ramon Bragós, Lexa Nescolarde

“…This study aims to use classification algorithms with minimally invasive electrical impedance spectroscopy to improve neoplastic lung tissue identification during biopsies. …”
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Performance and emission analysis of CI engine fueled with Dunaliella salina biodiesel and TiO₂ nanoparticle additives: Experimental and ANN-based Predictive Approach by V Hariram, S Balamurugan, R Mohan, R Karthick, Nandagopal Kaliappan, K Barathiraja, J Godwin John, K Kamakshi Priya

“…Experimental results identified the D80DuBD20TiO₂ blend at a compression ratio of 18 (CR18) as optimal, demonstrating improved combustion efficiency and reduced emissions. …”
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Recent technical advancements and clinical applications of MR-guided radiotherapy in lung cancer treatment by Chi Ma, Xiao Wang, Ke Nie, Zhenyu Xiong, Keying Xu, Ning Yue, Yin Zhang

“…Additionally, MRgRT could potentially allow multileaf collimator (MLC) tracking to further improve the treatment efficiency. Recent technological innovations, including AI-powered auto-contouring algorithms, deep-learning (DL) based prediction models, and adaptive treatment strategies, further optimize MRgRT by improving workflow efficiency and reducing treatment time. …”
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Impact of occupancy behavior on building energy efficiency: What’s next in detection and monitoring technologies? by Wenjie Song, John Calautit

“…Finally, economic feasibility considerations such as installation costs and associated energy savings achieved through occupancy-driven heating, ventilation and air-conditioning (HVAC ) optimization are crucial for large-scale implementation. …”
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Harnessing AI forward and backward chaining with telemetry data for enhanced diagnostics and prognostics of smart devices by Muhammad Shoaib Farooq, Rizwan Pervez Mir, Atif Alvi, Kilian Tutusaus, Eduardo Garcia Villena, Fadwa Alrowais, Hanen Karamti, Imran Ashraf

“…Accurate early diagnosis and prediction of potential failures have the capability to greatly improve maintenance efficiency, minimize downtime, and optimize cost.…”
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Energy-Efficient Trajectory Planning With Joint Device Selection and Power Splitting for mmWaves-Enabled UAV-NOMA Networks by Ahmad Gendia, Osamu Muta, Sherief Hashima, Kohei Hatano

“…Dynamic selection of suitable hovering spots within the target zone where the battery-constrained UAV needs to be positioned as well as calibrated NOMA power control with proper device pairing are critical for optimized performance. We propose cost-subsidized multiarmed bandit (CS-MAB) and double deep Q-network (DDQN)-based solutions to jointly address the problems of dynamic UAV path design, device pairing, and power splitting for downlink data transmission in NOMA-based systems. …”
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Performance Evaluation of Robotic Harvester with Integrated Real-Time Perception and Path Planning for Dwarf Hedge-Planted Apple Orchard by Tantan Jin, Xiongzhe Han, Pingan Wang, Yang Lyu, Eunha Chang, Haetnim Jeong, Lirong Xiang

“…For motion planning, a Dynamic Temperature Simplified Transition Adaptive Cost Bidirectional Transition-Based Rapidly Exploring Random Tree (DSA-BiTRRT) algorithm was developed, demonstrating significant improvements in the path planning performance. …”
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Automated classification of oral potentially malignant disorders and oral squamous cell carcinoma using a convolutional neural network framework: a cross-sectional studyResearch in... by Cristina Saldivia-Siracusa, Eduardo Santos Carlos de Souza, Arnaldo Vitor Barros da Silva, Anna Luíza Damaceno Araújo, Caíque Mariano Pedroso, Tarcília Aparecida da Silva, Maria Sissa Pereira Sant'Ana, Felipe Paiva Fonseca, Hélder Antônio Rebelo Pontes, Marcos G. Quiles, Marcio Ajudarte Lopes, Pablo Agustin Vargas, Syed Ali Khurram, Alexander T. Pearson, Mark W. Lingen, Luiz Paulo Kowalski, Keith D. Hunter, André Carlos Ponce de Leon Ferreira de Carvalho, Alan Roger Santos-Silva

“…MobileNet displayed the lowest computational cost. Grad-CAM analysis demonstrated discrepancies between the best-performing model and the highest explainability model. …”
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The Role of Artificial Intelligence (AI) in the Future of Forestry Sector Logistics by Leonel J. R. Nunes

“…Results: The results demonstrated that optimization algorithms reduced transportation costs and carbon emissions. …”
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