Deep Learning Model for Precipitation Nowcasting Based on Residual and Attention Mechanisms by Zhan Zhang, Qingping Song, Minzheng Duan, Hailei Liu, Juan Huo, Congzheng Han

“…The model introduces the residual neural network (ResNet) and the convolutional block attention module (CBAM) to integrate multi-scale features into the U-Net encoder–decoder architecture, enhancing its ability to capture the spatiotemporal evolution of precipitation systems. …”
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Fully automated MRI‐based analysis of the locus coeruleus in aging and Alzheimer's disease dementia using ELSI‐Net by Max Dünnwald, Friedrich Krohn, Alessandro Sciarra, Mousumi Sarkar, Anja Schneider, Klaus Fliessbach, Okka Kimmich, Frank Jessen, Ayda Rostamzadeh, Wenzel Glanz, Enise I. Incesoy, Stefan Teipel, Ingo Kilimann, Doreen Goerss, Annika Spottke, Johanna Brustkern, Michael T. Heneka, Frederic Brosseron, Falk Lüsebrink, Dorothea Hämmerer, Emrah Düzel, Klaus Tönnies, Steffen Oeltze‐Jafra, Matthew J. Betts

“…METHODS We present a deep learning–based LC segmentation and feature extraction method called Ensemble‐based Locus Coeruleus Segmentation Network (ELSI‐Net) and apply it to healthy aging and AD dementia datasets. …”
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In-vitro immune-modulation of triple-negative breast cancer through targeting miR-30a-5p/MALAT1 axis using nano-PDT combinational approach by Asmaa Ramzy, Mohammad Abdel-Halim, Tamer Manie, Noha M. Elemam, Samar Mansour, Rana A. Youness, Aya Sebak

“…Special focus is directed towards evaluation of the role of the selected treatment agents on the non-coding RNAs (ncRNAs) involved in tuning the immuno-oncogenic profile of TNBC, for instance, the miR-30a-5p/MALAT1 network. …”
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Permeability selection of biologically relevant membranes matches the stereochemistry of life on Earth. by Olivia Goode, Urszula Łapińska, Juliano Morimoto, Georgina Glover, David S Milner, Alyson E Santoro, Stefano Pagliara, Thomas A Richards

“…Early in the evolution of life, a proto-metabolic network was encapsulated within a membrane compartment. …”
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Advanced Point Cloud Techniques for Improved 3D Object Detection: A Study on DBSCAN, Attention, and Downsampling by Wenqiang Zhang, Xiang Dong, Jingjing Cheng, Shuo Wang

“…Finally, we incorporated a CSPNet downsampling module, which substantially boosts the network’s overall performance and processing speed while reducing computational costs through advanced feature map segmentation and fusion techniques. …”
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Achievements and prospects of applying high-throughput sequencing techniques to potato genetics and breeding by I. V. Bykova, N. A. Shmakov, D. A. Afonnikov, A. V. Kochetov, E. K. Khlestkina

“…The Potato Genome Sequencing Consortium activities included not only constructing genome libraries, sequencing, assembling and annotation of the genome, but also genome sequence-based investigations uncovering features of potato genome evolution, SNP identification, analysis of genes and gene networks regulating resistance to phytopathogens and technological characteristics. …”
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Theoretical Study and Application of Rate Transient Analysis on Complex Fractured-Caved Carbonate Reservoirs by Qingyan Yu, Qi Wang, Pengcheng Liu, Jing Zhang, Qi Zhang, Xiaojuan Deng, Kai Feng

“…Large-scale dissolved caves are mostly discrete and isolated, while the fractures are complex and various. The fracture features are observed either as a single large fractures or as a local fracture network. …”
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Multimodal EEG-fNIRS Seizure Pattern Decoding Using Vision Transformer by Rafat Damseh, Abdelhadi Hireche, Parikshat Sirpal, Abdelkader Nasreddine Belkacem

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Analysis of the Customer Churn Prediction Project in the Hotel Industry Based on Text Mining and the Random Forest Algorithm by Leila Taherkhani, Amir Daneshvar, Hossein Amoozad Khalili, Mohamad Reza Sanaei

“…In this model, to increase the efficiency of the proposed method in compare with existing works, the gravitational search algorithm was used to select the useful features, and the differential evolution algorithm was used to adjust the parameters of the classification method. …”
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Interface-aware molecular generative framework for protein–protein interaction modulators by Jianmin Wang, Jiashun Mao, Chunyan Li, Hongxin Xiang, Xun Wang, Shuang Wang, Zixu Wang, Yangyang Chen, Yuquan Li, Kyoung Tai No, Tao Song, Xiangxiang Zeng

“…The framework first employs Graph Attention Networks to capture atomic-level interaction features at the protein complex interface. …”
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Semi-Supervised Deep Subspace Embedding for Binary Classification of Sella Turcica by Kaushlesh Singh Shakya, Azadeh Alavi, Julie Porteous, Priti Khatri, Amit Laddi, Manojkumar Jaiswal, Vinay Kumar

“…Additionally, fine-tuning the Inception-ResNet-v2 network on these enriched features reduces retraining costs when new unlabeled data becomes available. t-distributed stochastic neighbor embedding (t-SNE) is employed for effective feature representation through manifold learning, capturing complex patterns that previous methods might miss. …”
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DeepGenMon: A Novel Framework for Monkeypox Classification Integrating Lightweight Attention-Based Deep Learning and a Genetic Algorithm by Abdulqader M. Almars

“…This suggested framework leverages an attention-based convolutional neural network (CNN) and a genetic algorithm (GA) to enhance detection accuracy while optimizing the hyperparameters of the proposed model. …”
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Using machine learning to develop a stacking ensemble learning model for the CT radiomics classification of brain metastases by Huai-wen Zhang, Yi-ren Wang, Bo Hu, Bo Song, Zhong-jian Wen, Lei Su, Xiao-man Chen, Xi Wang, Ping Zhou, Xiao-ming Zhong, Hao-wen Pang, You-hua Wang

“…By using various machine-learning algorithms, including random forest, support vector machine, gradient boosting machine, XGBoost, decision tree, artificial neural network, k-nearest neighbors, LightGBM, and CatBoost algorithms, a stacking ensemble model was developed to classify gross tumor volume (GTV), brainstem, and normal brain tissue based on radiomic features. …”
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Extraction of <i>Suaeda salsa</i> from UAV Imagery Assisted by Adaptive Capture of Contextual Information by Ning Gao, Xinyuan Du, Min Yang, Xingtao Zhao, Erding Gao, Yixin Yang

“…This paper achieves the following research results: (1) An Adaptive Context Information Extraction module based on large kernel convolution and an attention mechanism is designed; this module functions as a multi-scale feature extractor without altering the spatial resolution, enabling a seamless integration into diverse network architectures to enhance the context-aware feature representation. (2) The proposed ACI-Unet (Adaptive Context Information U-Net) model achieves a high-precision identification of <i>Suaeda salsa</i> in UAV imagery, demonstrating a robust performance across heterogeneous morphologies, densities, and scales of <i>Suaeda salsa</i> populations. …”
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Optical flow estimation based on global cross information and dynamic encoder–dynamic decoder by Haoxin Guo, Yifan Wang, Xiaobo Guo

“…The experimental results show that compared with the RAFT benchmark network, the model in this paper preserves the global features and edge detail information of large-scale motion without significantly increasing the number of model parameters.…”
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Development of Cyber Security Platform for Experiential Learning by Abhishek Vaish, Ravindra Kumar, Samo Bobek, Simona Sternad

“…The present research proposes a comprehensive web-based platform that can be used to communicate, collaborate and practice various use cases in the domain of network intrusion detection tools using machine learning algorithms and to evaluate user experience. …”
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Computer-Aided Grading of Gliomas Combining Automatic Segmentation and Radiomics by Wei Chen, Boqiang Liu, Suting Peng, Jiawei Sun, Xu Qiao

“…The MRI data containing 220 high-grade gliomas and 54 low-grade gliomas are used to evaluate our system. A multiscale 3D convolutional neural network is trained to segment whole tumor regions. …”
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DeepCatra: Learning flow‐ and graph‐based behaviours for Android malware detection by Yafei Wu, Jian Shi, Peicheng Wang, Dongrui Zeng, Cong Sun

“…This study proposes DeepCatra, a multi‐view learning approach for Android malware detection, whose model consists of a bidirectional LSTM (BiLSTM) and a graph neural network (GNN) as subnets. The two subnets rely on features extracted from statically computed call traces leading to critical APIs derived from public vulnerabilities. …”
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An Analysis of the Similarities and Differences between Chinese and Western Modernization by Xinhua Jian

“…The common features of Chinese and Western modernization can be summarized briefly as the basic realization of industrialization, urbanization, agricultural modernization, service provision, mechanization, electrification, chemicalization, socialization, large-scale and intensive operation, marketization, democratization and the rule of law, as well as ongoing evolution toward informatization, networking, digitization, and intelligentization. …”
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A Hybrid LSTM-GRU Model for Stock Price Prediction by Amirfarhad Farhadi, Azadeh Zamanifar, Amir Alipour, Alireza Taheri, Mohammad Asadolahi

“…Initially, we use machine learning to extract appropriate features for making predictions. Subsequently, the impact of each feature is adjusted proportionally to the weight matrix extracted from the neural network. …”
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