Reveal genomic insights into cotton domestication and improvement using gene level functional haplotype-based GWAS by Guoan Qi, Yiqian Li, Wanying Zhang, Zegang Han, Jinwen Chen, Ziqian Zhang, Lisha Xuan, Rui Chen, Lei Fang, Yan Hu, Tianzhen Zhang

“…Abstract Genome-wide association studies (GWAS) are widely used to detect associations between genetic variants and phenotypes. …”
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Toward Adaptive Unsupervised and Blind Image Forgery Localization with ViT-VAE and a Gaussian Mixture Model by Haichang Yin, KinTak U, Jing Wang, Wuyue Ma

“…Experimental results on benchmark datasets demonstrate that DVVG not only enhances VAE performance but also improves efficiency in modeling complex latent distributions. …”
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Adaptively evolved human oral actinomyces‐sourced defensins show therapeutic potential by Shunyi Zhu, Bin Gao, Yoshitaka Umetsu, Steve Peigneur, Ping Li, Shinya Ohki, Jan Tytgat

“…Signatures of natural selection were detected in defensins from the actinomyces colonized in human oral cavity and ruminant rumen and dental plaque, highlighting their role in adaptation to complex multispecies bacterial communities. …”
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Beyond the nuclear border: single-cell analysis of in situ sequenced human brain tissue using cellular features by Janssen M. Kotah, Thomas Rust, Hilmar R. J. van Weering, Janneke Bosma, Amber L. Woudstra, Susanne M. Kooistra, Bart J. L. Eggen

“…A key challenge in ISS data analysis is optimizing transcript allocation while minimizing misallocation, particularly in the morphologically complex central nervous system (CNS). We compared geospatial methods using nuclear and expanded nuclear boundaries for segmentation and transcript allocation. …”
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Bone scintigraphy based on deep learning model and modified growth optimizer by Omnia Magdy, Mohamed Abd Elaziz, Abdelghani Dahou, Ahmed A. Ewees, Ahmed Elgarayhi, Mohammed Sallah

“…To address the aforementioned issues, this work proposed a machine-learning technique that uses phases to detect Bone scintigraphy. The first phase in the proposed model is the feature extraction and it was conducted based on integrating the Mobile Vision Transformer (MobileViT) model in our framework to capture highly complex representations from raw medical imagery using two primary components including ViT and lightweight CNN featuring a limited number of parameters. …”
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Parcel Segmentation Method Combined YOLOV5s and Segment Anything Model Using Remote Sensing Image by Xiaoqin Wu, Dacheng Wang, Caihong Ma, Yi Zeng, Yongze Lv, Xianmiao Huang, Jiandong Wang

“…The improved YOLOv5s module integrates Efficient Channel Attention (ECA) and BiFPN to boost feature extraction and small-object recognition, while Soft-NMS is used to reduce missed detections. …”
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Analyzing customer churn behavior using datamining approach: hybrid support vector machine and logistic regression in retail chain by Mohammad Barzegar, Aliakbar Hasani

“…Customer churn is one of the challenges of business management in today's complex competitive environment. For this purpose, the organization must have an efficient system to detect and analyze the factors influencing customer churn. …”
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BTCP: Binary Temporal Convolutional Network-Based Data Prefetcher for Low Inference Latency and Storage Overhead by Chang Ho Ryu, Tae Hee Han

“…Machine learning (ML)-based data prefetchers have demonstrated superior address prediction performance compared with traditional rule-based prefetchers by learning complex patterns to hide long-latency memory access. …”
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Connotation and practice of the integration of academic field based on Bourdieu’s theory——taking the cultivation of cyberspace security talents as an example by Qian ZHOU, Haiping HUANG, Le WANG, Yanchun ZHANG, Fu XIAO

“…The deployment of network security has become a crucial strategy for the development of modern nations, with skilled professionals serving as the core driving force behind cybersecurity efforts.Cultivating cybersecurity talents and fostering team building are essential for China's talent reserves and strategic capital accumulation.With economic globalization, 0-day vulnerabilities have constantly emerged in information systems, attack chains have become increasingly complex, threat targets were difficult to detect, and hidden viruses varied over time.Talents trained by traditional universities for network security were unable to adapt to innovative production and practical activities in the new fields, as it was confined to their training structure system.In order to break through the shackles of the internal administrative structure and traditional curriculum system of universities, and ease the contradiction between the uncertainty of cyberspace security situation and the standardization of talent cultivation, the talent cultivation models based on Bourdieu's theory were studied, the fusion meaning of cultural capital in the academic field was analyzed and three practical standards were put forward in terms of teaching content, cultivation model and teaching opportunity of cyberspace security talents in combination with the actual cases of the “Fang class”.In terms of education content, standards and open knowledge systems were established to meet the differentiated needs of students.The mentorship approach was employed to construct habitus, fostering students’ ability to adapt flexibly to problems by adopting different cognitive thinking modes.Favorable teaching opportunities were utilized by tutors in various roles to promote efficient integration of individuals and fields, helping students establish a valuable and stable mindset.By leveraging Bourdieu's theory to explore the integration path of academic fields, it has leveraged the advantages of independently cultivating high-quality talents, vigorously promoting technological innovation and the healthy ecological development of the industry.…”
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A Review of Optimization Methods for Pipeline Monitoring Systems: Applications and Challenges for CO₂ Transport by Teke Xu, Sergey Martynov, Haroun Mahgerefteh

“…The impacts of the physical properties of CO₂ and complex designs and operation scenarios of CO₂ transport on the pipeline monitoring systems design are discussed. …”
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Implementation of SLAM-Based Online Mapping and Autonomous Trajectory Execution in Software and Hardware on the Research Platform Nimbulus-e by Thomas Schmitz, Marcel Mayer, Theo Nonnenmacher, Matthias Schmitz

“…The implementation is validated through both full vehicle simulations using an ADAMS Car—MATLAB co-simulation and a scaled physical prototype, demonstrating the effectiveness of the system in navigating complex environments. This work contributes to the field of autonomous systems by demonstrating the potential of combining advanced sensor technologies with innovative control algorithms to achieve reliable and efficient navigation. …”
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A Sleep Sensor Made with Electret Condenser Microphones by Teru Kamogashira, Tatsuya Yamasoba, Shu Kikuta, Kenji Kondo

“…This customized configuration allows the ECM to detect subtle changes in airflow associated with breathing patterns, enabling the monitoring of respiratory activity with minimal invasiveness and complexity. …”
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Clinical validation of AI assisted animal ultrasound models for diagnosis of early liver trauma by Qing Song, Xuelei He, Yanjie Wang, Hanjing Gao, Li Tan, Jun Ma, Linli Kang, Peng Han, Yukun Luo, Kun Wang

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TMN-Net: A Hybrid 2.5D Multi-Branch Transformer Network for Coronary Artery Segmentation in Cardiac Diagnosis by Bo Zhao, Jianjun Peng, Kai Zhang, Yongyan Fan, Ce Chen, Yang Zhang

“…Coronary artery disease (CAD) continues to be a leading cause of global mortality, necessitating accurate and efficient diagnostic tools for early detection and treatment planning. …”
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A deep neural network model with spectral correlation function for electrocardiogram classification and diagnosis of atrial fibrillation by Sara Mihandoost

“…The obtained results demonstrate that the proposed approach efficiently represents ECG signals through SCF coefficients, leading to the accurate detection of AF with an average accuracy of 92.76% and an average F1-score of 89.1%.…”
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An Over-the-Air Multi-User Convolutional Code for URLLC by Rafael Santos, Daniel Castanheira, Adao Silva, Atilio Gameiro

“…This scheme can be viewed as a non-orthogonal multiple access scheme, whose structure enables ML joint detection and decoding with the complexity of standard Viterbi algorithm.…”
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Research on Underwater Acoustic Target Recognition Based on a 3D Fusion Feature Joint Neural Network by Weiting Xu, Xingcheng Han, Yingliang Zhao, Liming Wang, Caiqin Jia, Siqi Feng, Junxuan Han, Li Zhang

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AASNet: A Novel Image Instance Segmentation Framework for Fine-Grained Fish Recognition via Linear Correlation Attention and Dynamic Adaptive Focal Loss by Jianlei Kong, Shunong Tang, Jiameng Feng, Lipo Mo, Xuebo Jin

“…However, underwater fish recognition faces challenges in complex aquatic environments, which hinder accurate detection and behavioral analysis. …”
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Research on fault location algorithm of hybrid line based on distributed traveling wave by HU Shuncai, LI Jing, CHEN Ping, LIU Yang, ZHOU Futao, CHEN Haohao

“…When the cable hybrid transmission line fails, more complex traveling wave refraction and reflection will appear, which brings great difficulty to fault location. …”
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Evaluating Skin Tone Fairness in Convolutional Neural Networks for the Classification of Diabetic Foot Ulcers by Sara Seabra Reis, Luis Pinto-Coelho, Maria Carolina Sousa, Mariana Neto, Marta Silva, Miguela Sequeira

“…VGG19 achieved the highest accuracy at 97%, demonstrating superior ability to focus activations on relevant lesion areas in complex images. MobileNetV2, while slightly less accurate, excelled in computational efficiency, making it a suitable choice for mobile devices and environments with hardware constraints. …”
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