Electrospun Polycaprolactone–Gelatin Fibrils Enabled 3D Hydrogel Microcapsules for Biomedical Applications by Felix Tettey-Engmann, Thakur Sapkota, Sita Shrestha, Narayan Bhattarai, Salil Desai

“…The average diameters of the PG nanofibers ranged between 0.2 and 2 μm, with an average porosity between 58 and 73%. …”
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Advancement of Artificial Intelligence in Cost Estimation for Project Management Success: A Systematic Review of Machine Learning, Deep Learning, Regression, and Hybrid Models by Md. Mahfuzul Islam Shamim, Abu Bakar bin Abdul Hamid, Tadiwa Elisha Nyamasvisva, Najmus Saqib Bin Rafi

“…The results show that AI-powered approaches, particularly artificial neural networks (ANNs)—which constitute 26.33% of the studies—, enhance predictive accuracy and adaptability to complex, dynamic project environments. …”
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Outcome measurement instruments in neurodegenerative diseases: Comprehensive analysis and platform construction by Hui Zong, Jiaxue Cha, Liang Tao, Muyun Shi, Yan Zhao, Ru Zhang, Bairong Shen

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Instance segmentation and automated pig posture recognition for smart health management by Md Nasim Reza, Md Sazzadul Kabir, Md Asrakul Haque, Hongbin Jin, Hyunjin Kyoung, Young Kyoung Choi, Gookhwan Kim, Sun-Ok Chung

“…The model effectively identified standard postures, achieving a mean average precision of 0.937 for piglets and 0.935 for adults. …”
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Epidemiological Situation of Schigеllosis in the Republic of Dagestan and Directions for Improving Epidemiological Surveillance by Z. G. Tagirovа, N. M-G. Zulpukarova, Z. M. Daniyalbekova

“…The main causes of epidemiological well-being for schigеllosis in Dagestan are determined by: poor state of the water supply system and sanitary and communal improvement of populated areas; the use of food products stored, transported and sold in the distribution network in violation of sanitary and hygienic requirements. …”
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Effects of <i>Lactobacillus plantarum</i>-81-Fermented Feed on Growth and Intestinal Health of Muscovy Ducks by Zhaolong Li, Song Peng, Mengshi Zhao, Xiaodong Zhuang, Huini Wu, Tiecheng Sun, Fengqiang Lin

“…These multi-omics insights establish that LP81-FF enhances growth performance through coordinated modulation of gut–liver axis homeostasis, mucosal immunity activation, and microbial-metabolic network optimization. Our results position LP81-FF as a sustainable alternative to antibiotic growth promoters in waterfowl production systems.…”
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HP-YOLO: A Lightweight Real-Time Human Pose Estimation Method by Haiyan Tu, Zhengkun Qiu, Kang Yang, Xiaoyue Tan, Xiujuan Zheng

“…Additionally, the Reparameterized Network with Cross-Stage Partial Connections and Efficient Layer Aggregation Network (RepNCSPELAN4) module was incorporated into the detection head, boosting accuracy in detecting small-sized targets through multi-scale convolution and reparameterization techniques while accelerating inference speed. …”
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Impact of Safety Signage Placement on Evacuation Behavior in Virtual Fire Scenarios Based on EDA Data by Wenqi Song, Xu Feng, Yu Song

“…Experimental results yield average classification accuracies of 93.36%, 97.71%, and 95.99% across the three scenarios, demonstrating the neuro-engineering value of combining VR-based simulations with EDA monitoring to optimize safety-sign placement.…”
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Improved printed circuit board defect detection scheme by Lufeng Bai, Wen Hao Xu

“…First, we incorporate the Efficient Channel Attention Network (ECANet) attention mechanism into the backbone network of YOLOv8, which improves the performance of small-target detection by adaptively enhancing the expressiveness of key features, so that the network possesses higher sensitivity and focus on tiny details in PCB images. …”
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Enhanced Driver Posture Feature Extraction Method Based on the Spatial Prior Probabilistic Model by WANG Han; SUN Yu; YIN Jie

“…Moreover, the average recognition rate under the combination of neural network and proposed method is 12% higher than other traditional methods.…”
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A fast and efficient green apple object detection model based on Foveabox by Weikuan Jia, Zhifen Wang, Zhonghua Zhang, Xinbo Yang, Sujuan Hou, Yuanjie Zheng

“…Specifically, the EfficientNetV2-S with fast training and small size is used as the backbone network, a weighted bi-directional feature pyramid network (BiFPN) is employed as the feature extraction network to fuse multi-scale features easily and fast, and then the fused features are fed to the fovea head prediction network for the classification and bounding box prediction. …”
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Edge Server Placement and Task Allocation for Maximum Delay Reduction by Koki Shibata, Sumiko Miyata

“…If a user is extremely far from the edge server, the network delay for that user will also increase. Conventional edge computing methods focus on reducing the average propagation delay of user-processing requests (tasks). …”
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Nondestructive freshness recognition of chicken breast meat based on deep learning by Rui Jian, Guangbo Li, Xie Jun, Guolong Shi

“…Experimental results show that in the improved algorithm, YOLOv8n_CA_DSC3 achieves suboptimal recall rate but optimal precision, average precision at IoU = 0.5, and average precision at IoU = 0.5:0.95. …”
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Human Action Recognition Method Based on Multi-channel Fusion by Zhiyong TAO, Xijun GUO, Xiaokui REN, Ying LIU, Zemin WANG

“…A temporal convolutional network processes the extracted action features. This network performs convolution operations on features at different instances, enabling the model to capture changes over time and identify long-term dependencies between action features. …”
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Rough-and-Refine Model for Scene Graph Generation by Li Junliang, Lv Shirong, Li Wei

“…The TQG and EPR modules also provide a degree of improvement, with average decreases of 4.7% and 5.2% when removed. The model represented in the first row of the table, which excludes all four modules, is equivalent to the Rough Part, showing an average decrease of 24.9%.ConclusionsTo address the issue of insufficient predicate representation, a scene graph generation method based on a Rough-and-Refine network is proposed. …”
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HU to RGB transformation with automatic windows selection for intracranial hemorrhage classification using ncCT. by Dittapong Songsaeng, Akara Supratak, Pantid Chantangphol, Saowapot Sarumpakul, Natsuda Kaothanthong

“…HRT dynamically selects optimal WW and WL values from predefined settings to accentuate hemorrhage visibility. …”
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The Integration of a Medium-Resolution Underwater Radioactivity System in the COSYNA Observing System at Helgoland Island, Germany by Christos Tsabaris, Stylianos Alexakis, Miriam Lienkämper, Max Schwanitz, Markus Brand, Manolis Ntoumas, Dionisis L. Patiris, Effrosyni G. Androulakaki, Philipp Fischer

“…The continuous monitoring of radioactivity in a cabled subsea network in the North Sea Observatory was performed to test the performance of a medium-resolution underwater spectrometer, as well as to identify and to assess potential anthropogenic and/or natural hazards. …”
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Preparation for Entering a Higher Educational Institution as an Investment Project by V. A. Kataeva, V. R. Masalkina, A. A. Ponomareva

“…As a result of creating a neural network model, a mathematical model is designed to determine the most optimal training method. …”
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Design of Command and Dispatch System for Automatic Reading of Meter Images in Substations by UAV Inspection Photos by Guanghong Deng, Liangpei Lin, Baihao Lin, Wenlong Jing, Xiaodan Zhao, Yong Li, Rui Yang, Shidun Xie, Pengfeng Wei

“…The post-processing part uses numba to optimize the inference speed. The experimental results show that in two datasets, The mean average precision of 50 (mAP50) accuracy of the YOLOv6n model using this method reached 99.71% and 98.60%, respectively, and the inference speed of a single image was 17.1[Formula: see text]ms and 13.2[Formula: see text]ms, respectively. …”
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Investigating the Effects of Spectroscopic Method in Estimating Soluble Solid Content Values and Firmness of Cherries from an Environmental Point of View: Prediction of Environment... by Shirzad Naim, Shahgholi Gholamhossein, Ardabili Sina, Szymanek Mariusz

“…It was found that the radial basis function neural network could estimate the environmental effects of the experimental process with an acceptable accuracy (over 95% on average).…”
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