Multiple kernel learning captures a systems-level functional connectivity biomarker signature in amyotrophic lateral sclerosis. by Tomer Fekete, Neta Zach, Lilianne R Mujica-Parodi, Martin R Turner

“…Complex network analysis showed that functional networks in ALS differ markedly in their topology, reflecting the underlying altered functional connectivity pattern seen in patients: 1) reduced connectivity of both the cortical and sub-cortical motor areas with non motor areas 2)reduced subcortical-cortical motor connectivity and 3) increased connectivity observed within sub-cortical motor networks. …”
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Effect and Mechanism of Yisui Fuyongtang (YSFYT) Decoction on Cognitive Function and Synaptic Plasticity in Rats with Vascular Cognitive Impairment by Tingliang Gong, Zhaoliang Luo, Li Huang, Caixian Xiao, Junlu Yi, Junfeng Yan, Qian Chen, Weihong Li, Wenqiang Tao

“…Clinical medications have found that Yisui Fuyongtang (YSFYT) Decoction is effective in improving neurological signs and learning-memory functions in patients who develop white matter lesions and whole brain atrophy. …”
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RE-YOLO: An apple picking detection algorithm fusing receptive-field attention convolution and efficient multi-scale attention. by Jinxue Sui, Li Liu, Zuoxun Wang, Li Yang

“…Finally, the loss function of YOLOv8 is improved using the Wise Intersection over Union (WIOU) function, which not only simplifies the gradient gain assignment mechanism and improves the ability to detect targets of different sizes, but also accelerates the model optimization. …”
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Spatial Division Multiplexing-Based Reflective Intensity-Modulated Fiber Optics Displacement Sensor by Tianye Lan, Cong Zhang, Songnian Fu, Benpeng Zhu, Ming Tang, Weijun Tong

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SILVERRUSH. XIV. Lyα Luminosity Functions and Angular Correlation Functions from 20,000 Lyα Emitters at z ∼ 2.2–7.3 from up to 24 deg2 HSC-SSP and CHORUS Surveys: Linking the Postr... by Hiroya Umeda, Masami Ouchi, Satoshi Kikuta, Yuichi Harikane, Yoshiaki Ono, Takatoshi Shibuya, Akio K. Inoue, Kazuhiro Shimasaku, Yongming Liang, Akinori Matsumoto, Shun Saito, Haruka Kusakabe, Yuta Kageura, Minami Nakane

“…Confirming the large sample with 241 spectroscopically identified LAEs, we determine Ly α LFs and ACFs in the brighter luminosity range down to 0.5 L _⋆ , and confirm that our measurements are consistent with previous studies but offer significantly reduced statistical uncertainties. The improved precision of our ACFs allows us to clearly detect one-halo terms at some redshifts, and provides large-scale bias measurements that indicate host halo masses of ∼10 ^11 M _⊙ over z  ≃ 2−7. …”
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Prevalence and functional impact of flexible flatfoot in school-aged children: a cross-sectional clinical and postural assessment by Saleh M. Kardm, Ziad Ahmed Alanazi, Tariq Abdullah S. Aldugman, Ravi Shankar Reddy, Ajay Prashad Gautam

“…However, persistent cases may contribute to discomfort, functional limitations, and reduced physical activity levels. …”
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Survey on 3D Anomaly Detection Regarding Defect Size: Tradeoff Between Accuracy and Efficiency With Future Research Direction by A-Seong Moon, Kunho Lee, Jaesung Lee

“…Recent advancements in neural networks has enhanced image anomaly detection in different industries such as manufacturing, reduced human intervention, and boosted productivity and quality. …”
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Intrusion Detection-Data Security Protection Scheme Based on Particle Swarm-BP Network Algorithm in Cloud Computing Environment by Zhun Wang, Xue Chen

“…First, based on the four modules of data collection, data preprocessing, feature selection, and intrusion detection, the overall framework of the intrusion detection model is constructed by designing corresponding functions. …”
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A Real-Time Restraint Method for Range Walk Error in 3-D Imaging Lidar Via Dual Detection by Ling Ye, Guohua Gu, Weiji He, Huidong Dai, Qian Chen

“…Geiger-mode avalanche photodiode (Gm-APD) offers 3D imaging lidar much better capability in terms of detection sensitivity. However, a range walk error (RWE) exists in Gm-APDs which refers to the fluctuation of the measured distance as a function of the intensity of echo pulses. …”
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A Method for Service Function Chain Migration Based on Server Failure Prediction in Mobile Edge Computing Environment by Joelle Kabdjou, Norihiko Shinomiya

“…However, traditional hardware-based middleboxes limit flexibility and scalability, leading to the adoption of Network Function Virtualization (NFV). NFV enables the deployment of network functions as software, optimizing resource allocation and reducing costs. …”
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MSPB-YOLO: High-Precision Detection Algorithm of Multi-Site Pepper Blight Disease Based on Improved YOLOv8 by Xiaodong Zheng, Zichun Shao, Yile Chen, Hui Zeng, Junming Chen

“…Additionally, the introduction of the RepGFPN network structure enhances the model’s capability for multi-scale feature fusion, resulting in a marked improvement in multi-target detection accuracy. Furthermore, we optimized CIOU to DIOU by integrating the center distance of bounding boxes into the loss function; as a result, the model achieved an impressive mAP@0.5 score of 96.4%. …”
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DSCONV-GAN: a UAV-BASED model for Verticillium Wilt disease detection in Chinese cabbage in complex growing environments by Jun Zhang, Dongfang Zhang, Jingyan Liu, Yuhong Zhou, Xiaoshuo Cui, Xiaofei Fan

“…Here, we propose a detection model, DSConv-GAN, which is based on images acquired by an unmanned aerial vehicle (UAV). …”
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LWSARDet: A Lightweight SAR Small Ship Target Detection Network Based on a Position–Morphology Matching Mechanism by Yuliang Zhao, Yang Du, Qiutong Wang, Changhe Li, Yan Miao, Tengfei Wang, Xiangyu Song

“…To address these challenges, we propose a lightweight SAR small ship detection network, LWSARDet, which mitigates feature redundancy and reduces computational complexity in existing models. …”
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A Lightweight Method for Road Defect Detection in UAV Remote Sensing Images with Complex Backgrounds and Cross-Scale Fusion by Wenya Zhang, Xiang Li, Lina Wang, Danfei Zhang, Pengfei Lu, Lei Wang, Chuanxiang Cheng

“…Moreover, the CAA attention mechanism is employed to strengthen the model’s global feature extraction abilities; (2) a cross-scale feature fusion strategy known as GFPN is developed to tackle the problem of diverse target scales in road damage detection; (3) to reduce computational resource consumption, a lightweight detection head called EP-Detect has been specifically designed to decrease the model’s computational complexity and the number of parameters; and (4) the model’s localization capability for road damage targets is enhanced by integrating an optimized regression loss function called WiseIoUv3. …”
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Detailed Morphological Changes of Foveoschisis in Patient with X-Linked Retinoschisis Detected by SD-OCT and Adaptive Optics Fundus Camera by Keiichiro Akeo, Shuhei Kameya, Kiyoko Gocho, Daiki Kubota, Kunihiko Yamaki, Hiroshi Takahashi

“…During the follow-up period, the foveal thickness in the SD-OCT images and the number of retinal folds in the AO images were reduced. Conclusions. We have presented the detailed morphological changes of foveoschisis in a patient with XLRS detected by SD-OCT and AO fundus camera. …”
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DT-YOLO: An Improved Object Detection Algorithm for Key Components of Aircraft and Staff in Airport Scenes Based on YOLOv5 by Zhige He, Yuanqing He, Yang Lv

“…In addition, we utilized deformable convolutions in CNNs to extract features from multi-scale and deformed objects, further enhancing the model’s adaptability and detection accuracy. In terms of loss function design, we modified GIoULoss to address its discontinuities and instability in certain scenes, which effectively mitigated gradient explosion and improved the stability of the model. …”
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Surface defect detection model of laser cutting polycrystalline cubic boron nitride tool based on asymptotic fusion strategy by Anfu Zhu, Jiaxiao Xie, Heng Guo, Jie Wang, Zilong Guo, Lei Xu, SiXin Zhu, Zhanping Yang, Bin Wang

“…In the backbone network, the C3SE module is constructed by modeling the correlation between feature channels to improve the model’s focus on key features in order to enhance the feature extraction and processing capability of the backbone network; In the neck network, adaptive spatial fusion operation and direct interaction of non-adjacent layers are utilized for multi-scale information fusion, and the asymptotic feature pyramid network for object detection (AFPN) is used instead of the FPN structure to improve the detection performance; In the head network, a soft suppression mechanism is introduced to reduce the overlapping frame score using a decay function, thus improving the detection accuracy. …”
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Software with artificial intelligence-derived algorithms for detecting and analysing lung nodules in CT scans: systematic review and economic evaluation by Julia Geppert, Peter Auguste, Asra Asgharzadeh, Hesam Ghiasvand, Mubarak Patel, Anna Brown, Surangi Jayakody, Emma Helm, Dan Todkill, Jason Madan, Chris Stinton, Daniel Gallacher, Sian Taylor-Phillips, Yen-Fu Chen

“…Models estimated incremental cost-effectiveness ratios, cost per correct detection of an actionable nodule, and cost per cancer detected and treated. …”
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An Improved YOLOv8 Model for Detecting Four Stages of Tomato Ripening and Its Application Deployment in a Greenhouse Environment by Haoran Sun, Qi Zheng, Weixiang Yao, Junyong Wang, Changliang Liu, Huiduo Yu, Chunling Chen

“…Further, Shape_IoU replaced CIoU as the loss function, prioritizing bounding box shape and size for improved detection accuracy. …”
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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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