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

“…We improved YOLOv8n through dataset expansion, algorithm lightweighting, attention mechanism integration, and loss function optimization. Our improved model achieved the highest detection accuracy of 98.11% compared to other state-of-the-art (SOTA) target detection algorithms. …”
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A New Hybrid Machine Learning Method for Stellar Parameter Inference by Sujay Shankar, Michael A. Gully-Santiago, Caroline V. Morley

“…Gaussian process minimization is used to infer stellar parameters by minimizing a rms loss function. Testing 210 noise-free models ( T _eff : [3000, 11,000] K, ${\mathrm{log}}\,(g)$ : [2, 6], [Fe/H]: [−0.5, 0]), we find inference errors: T _eff : 93 K, ${\mathrm{log}}\,(g)$ : 0.24, and [Fe/H]: 0.056 for T _eff  <  7000 K, and T _eff : 347 K, ${\mathrm{log}}\,(g)$ : 0.26, and [Fe/H]: 0.16 for T _eff ≥ 7000 K. …”
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Knowledge- and Model-Driven Deep Reinforcement Learning for Efficient Federated Edge Learning: Single- and Multi-Agent Frameworks by Yangchen Li, Lingzhi Zhao, Tianle Wang, Lianghui Ding, Feng Yang

“…We formulate a joint optimization problem for FL worker selection and algorithm parameter configuration to minimize the final test loss subject to time and energy constraints. …”
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High-Throughput 3D Rice Chalkiness Detection Based on Micro-CT and VSE-UNet by Zhiqi Cai, Yangjun Deng, Xinghui Zhu, Bo Li, Chenglin Xu, Donghui Li

“…Through comprehensive training optimization strategies, including the Dice focal loss function and dropout technique, the model achieves robust and accurate segmentation of both kernels and chalky regions in continuous CT slices. …”
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Comparative analysis of different methods of retraction of the left lobe of the liver during laparoscopic sleeve gastrectomy by O. O. Kalashnikov, O. Yu. Usenko, I. M. Todurov, S. V. Kosiukhno

“…Retracting of the left liver lobe during laparoscopic sleeve gastrectomy is important for achieving an optimal surgical field. Aim. The aim of our study was to evaluate the results of using different methods of retraction of the left liver lobe during laparoscopic sleeve gastrectomy in patients with morbid obesity. …”
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Dupilumab, a Potential Novel Treatment for Hailey–Hailey Disease by Liliana Gabriela Popa, Calin Giurcaneanu, Florentina Zaharia, Andreea Grigoras, Alexandra Denisa Oprea, Cristina Beiu

“…<b>Background/Objectives:</b> Hailey–Hailey disease (HHD) is an uncommon genodermatosis with autosomal dominant inheritance caused by loss-of-function mutations in the ATP2C1 gene, which lead to disruption in keratinocyte adhesion and intraepidermal acantholysis. …”
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DMF-YOLO: Dynamic Multi-Scale Feature Fusion Network-Driven Small Target Detection in UAV Aerial Images by Xiaojia Yan, Shiyan Sun, Huimin Zhu, Qingping Hu, Wenjian Ying, Yinglei Li

“…Finally, we propose an Expanded Window-based Bounding Box Regression Loss Function (EW-BBRLF), which optimizes localization accuracy through dynamic auxiliary bounding boxes, effectively reducing missed detections of small targets. …”
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Synergetic effect of fungal pretreatment and lignin modification on delignification and saccharification: a case study of a natural lignin mutant in mulberry by James Paul T. Madigal, Masami Terasaki, Masatsugu Takada, Shinya Kajita

“…Results Mulberry wood prepared from homozygotes or heterozygotes with a loss-of-function in the cinnamyl alcohol dehydrogenase gene (CAD) was pretreated with three fungal species. …”
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Identification of potential drug targets for achalasia from genetic insights: a Mendelian randomization study by Kai Xiong, Hao Fang, Caihong Song, Dilihumaer Tuerxun, Peng Zhang

“…Abstract Background Achalasia (AC) is an esophageal dyskinetic disorder characterized by loss of function of ganglion cells of the intermuscular plexus of the distal esophagus and lower esophageal sphincter. …”
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Transient stability improvement of a transmission system through the application of an artificial neural network-based high-voltage direct current system by Chibuike Peter Ohanu, Uche C Ogbuefi, Emenike Ejiogu

“…This intelligent control mechanism enhances transient stability by optimizing power system responses based on real-time operational data. …”
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Risk prediction model of physical frailty for a rural older population: a cross-sectional study in Hunan Province, China by Xiuyan Guo, Chunhong Shi

“…IntroductionPhysical frailty is a common medical syndrome characterized by low muscle strength, low endurance, and reduced physiological function that leads to significantly negative health outcomes in older adults. …”
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Course of symptoms and health-related quality of life during specialized pre-dialysis care. by Moniek C M de Goeij, Gurbey Ocak, Joris I Rotmans, Jan-Willem Eijgenraam, Friedo W Dekker, Nynke Halbesma

“…<h4>Background</h4>Concerns are present on the limited value of renal function alone in defining the optimal moment to start dialysis. …”
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Right-sided hemicolectomy in 90-year-old patient with cecum cancer by A. M. Sidorenko, T. A. Semenova, V. V. Varvarov

“…Liver mass decreases by 40%, therefore hepatic blood flow is changed. Number of functioning glomeruli is reduced by 50% compared with young age. …”
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DualHet-YOLO: A Dual-Backbone Heterogeneous YOLO Network for Inspection Robots to Recognize Yellow-Feathered Chicken Behavior in Floor-Raised House by Yaobo Zhang, Linwei Chen, Hongfei Chen, Tao Liu, Jinlin Liu, Qiuhong Zhang, Mingduo Yan, Kaiyue Zhao, Shixiu Zhang, Xiuguo Zou

“…Secondly, a Proportional Scale IoU loss function is introduced that improves regression accuracy. …”
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Colossal permittivity in high-entropy CaTiO3 ceramics by chemical bonding engineering by Jinghan Cai, Shun Lan, Bin Wei, Junlei Qi, Ce-Wen Nan, Yuan-Hua Lin

“…However, challenges remain in further optimizing dielectric properties due to the correlation between these parameters. …”
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In-situ tensile analysis of microstructure evolution in Ni, Ni5W, and Ni9W using EBSD by Yaotang Ji, Hongli Suo, Zhen Ma, Baoxu Huang, Jianhua Liu, Zili Zhang, Qiuliang Wang

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The Simulation of Mode Control for a Photonic Lantern Adaptive Amplifier by Yuxuan Ze, Pengfei Liu, Hanwei Zhang, Yanyang Hu, Lianchuang Ding, Baozhu Yan, Jiangbin Zhang, Qiong Zhou, Wenguang Liu

“…In this work, we combined the gains and losses of individual modes within the fiber amplifier and introduced a mode content parameter at the amplifier’s output as an evaluation function to simulate mode control effects. …”
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Laser-based 3D printing and optical characterization of optical micro-nanostructures inspired by nocturnal insects compound eyes by Bogdan Stefanita Calin, Roxana Cristina Popescu, Eugenia Tanasa, Irina Alexandra Paun

“…For example, the development of 3D micro-nanostructures that mimic nocturnal insect eyes (optimized for night vision), emerges as promising technology for detection in IR spectral region. …”
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Design and efficiency improvement of eco-conscious Sr3PBr3 and Sr3NCl3 double perovskite solar cells with IGZO and Cu2O as ETL and HTL by Md．Shamim Reza, Avijit Ghosh, Md．Selim Reza, Shafaiet Newaz Wornob, Sabina Sultana

“…The study provides an in-depth theoretical examination of the energy band structure, defect properties, and quantum efficiency of the DPSC, focusing on the optimized photovoltaic (PV) specifications. Remarkably, the optimized DPSC achieves a power conversion efficiency (PCE), an open-circuit voltage (VOC), a short-circuit current density (JSC), and a fill factor (FF) of 32.46 %, 1.40 V, 26.51 mA/cm2, 87.26 %. …”
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A novel lightweight YOLOv8-PSS model for obstacle detection on the path of unmanned agricultural vehicles by Zhijian Chen, Yijun Fang, Jianjun Yin, Shiyu Lv, Farhan Sheikh Muhammad, Lu Liu

“…This adjustment preserves accuracy while reducing the complexity of the model. After optimization, the bounding box loss function is finally upgraded to Shape-IoU (Shape Intersection over Union), which improves both model accuracy and generalization.ResultsThe experimental results demonstrate that the improved YOLOv8_PSS model achieves a precision of 85.3%, a recall of 88.4%, and an average accuracy of 90.6%. …”
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