Experimental Investigation of Mechanical Properties and Pore Characteristics of Hipparion Laterite Under Freeze–Thaw Cycles by Tengfei Pan, Zhou Zhao, Jianquan Ma, Fei Liu

“…We innovatively integrated F-T cycling tests with ring-shear experiments to establish a hydro-thermal–mechanical coupled multi-scale evaluation framework for assessing F-T damage in the slip zone material. …”
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The role of mitochondria-related genes and immune infiltration in carotid atherosclerosis: identification of hub targets through bioinformatics and machine learning approaches by Dan Liu, Kun Guo, Min Li, Xiaochen Yu, Xue Guan, Xiuru Guan

“…These findings may provide new insights into therapeutic monitoring and prognosis evaluation.…”
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EEG–fNIRS signal integration for motor imagery classification using deep learning and evidence theory by Mohammed E. Seno, Niladri Maiti, Maulik Patel, Mihirkumar M. Patel, Kalpesh B. Chaudhary, Ashish Pasaya, Babacar Toure

“…For EEG signals, spatiotemporal features are extracted using dual-scale temporal convolution and depthwise separable convolution, and a hybrid attention module is introduced to enhance the network's sensitivity to salient neural patterns. …”
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Comparative Analysis of AlexNet, ResNet-50, and VGG-19 Performance for Automated Feature Recognition in Pedestrian Crash Diagrams by Baraah Qawasmeh, Jun-Seok Oh, Valerian Kwigizile

“…By employing cutting-edge technological methods, the research aims to uncover and extract hidden features from pedestrian crash data in Michigan, thereby enhancing the understanding and prevention of such incidents. This study evaluates the effectiveness of three Convolutional Neural Network (CNN) architectures—VGG-19, AlexNet, and ResNet-50—in classifying multiple hidden features in pedestrian crash diagrams. …”
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Transfer learning for securing electric vehicle charging infrastructure from cyber-physical attacks by Ahmad Almadhor, Shtwai Alsubai, Imen Bouazzi, Vincent Karovic, Monika Davidekova, Abdullah Al Hejaili, Gabriel Avelino Sampedro

“…The CICEVSE2024 (EVSE-A and EVSE-B) datasets are used to assess the framework, where one dataset is used to train and store weights, and the second is used to evaluate the learned patterns using transfer learning. …”
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An Enhanced Approach for Remaining Useful Life Prediction of Bearings Using Incomplete Lifecycle Data by Xunmeng An, Chao Zhang, Caiye Liu, Wentao Zhao

“…To address these challenges, we propose the Incomplete Lifecycle Data Enhanced Network (ILDENet), a self-supervised learning network incorporating contrastive learning to improve feature discrimination. …”
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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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Smart medical report: efficient detection of common and rare diseases on common blood tests by Ákos Németh, Ákos Németh, Gábor Tóth, Péter Fülöp, György Paragh, Bíborka Nádró, Zsolt Karányi, György Paragh, Zsolt Horváth, Zsolt Csernák, Zsolt Csernák, Erzsébet Pintér, Erzsébet Pintér, Dániel Sándor, Dániel Sándor, Gábor Bagyó, István Édes, János Kappelmayer, Mariann Harangi, Bálint Daróczy, Bálint Daróczy

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Advanced cloud intrusion detection framework using graph based features transformers and contrastive learning by Vijay Govindarajan, Junaid Hussain Muzamal

“…Abstract This paper presents a modular and scalable intrusion detection framework that combines graph-based feature extraction, Transformer-based autoencoding, and contrastive learning to improve detection accuracy in cloud environments. Network flows are modeled as graphs to capture relational patterns among IP addresses and services, and a Graph Neural Network (GNN) is used to extract structured embeddings. …”
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Research on deep learning model for stock prediction by integrating frequency domain and time series features by Wenjie Sun, Jianhua Mei, Shengrui Liu, Chunhong Yuan, Jiaxuan Zhao

“…By fusing information from both domains, the deep neural network significantly improves prediction accuracy and reliability. …”
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A novel transformer-based dual attention architecture for the prediction of financial time series by Anita Hadizadeh, Mohammad Jafar Tarokh, Majid Mirzaee Ghazani

“…Second, the Nonprice Attention Network (NAN) is proposed as a parallel network that processes related financial features. …”
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Investigation of the HLA locus in autopsy-confirmed progressive supranuclear palsy by Jinguo Wang, Shelley L. Forrest, Sathish Dasari, Hidetomo Tanaka, Ekaterina Rogaeva, M. Carmela Tartaglia, Susan Fox, Anthony E. Lang, Subha Kalyaanamoorthy, Gabor G. Kovacs

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Exploring the benefits and prescribing informations of combining East Asian herbal medicine with conventional medicine in the treatment of rheumatoid arthritis: A systematic review... by Hee-Geun Jo, Jihye Seo, Eunhye Baek, Donghun Lee

“…These herbs and synergistic herbal combinations were anticipated to be the most pharmacologically influential in contributing to the meta-analysis outcomes, as substantiated by analytical metrics including network topology and intricate association pattern evaluations. …”
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Unveiling the dynamic effects of major depressive disorder and its rTMS interventions through energy landscape analysis by Chun-Wang Su, Chun-Wang Su, Yurui Tang, Nai-Long Tang, Nai-Long Tang, Nian Liu, Nian Liu, Jing-Wen Li, Shun Qi, Hua-Ning Wang, Zi-Gang Huang, Zi-Gang Huang

“…The effects of rTMS intervention on these networks were also evaluated.ResultsOur findings revealed notable dynamical alterations in the pDMN, the vDMN, and the aSN, suggesting their potential as diagnostic and therapeutic markers. …”
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High Throughput 512Mbps True Random Number Generation Using Uncertainty in Mobile Communication Bands by Farid Alidoust Aghdam, Mohammad Erfanimehr, Hodjat Ahmadi, Armin Zarghami, Seyed Ahmad Madani, Ali Rostami

“…We have evaluated this through numerical calculations and antenna pattern measurements in the laboratory, and the results and their comparison show a promising performance. …”
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Thermodynamic Modeling of Hashtag Dynamics for Social Media Clustering: A Maxwell-Boltzmann Approach by Krishnan Batri, Rajermani Thinakaran, Bhuvana Jayabalan, L. Karthikeyan, S. Lakshmi, R. Sowrirajan, Sivaram Murugan

“…The approach enables more accurate identification of topic clusters, revealing distinct discourse patterns that conventional methods fail to capture.…”
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Novel, Reproducible, Consortia Factors Derived from Adipose Stem Cells for Burn Wound Treatment by Talavera-Adame D, Palomares M, Plaza MR, Rogowski N, Lee BS, Zemach A, Newman N

“…Finally, pro-angiogenesis was evaluated by the induction of tube-like structures and capillary networks in HMEC-1 cells promoted by CFx-δ 2.Results: Our technology enabled the production of CFx-δ 2 with enhanced efficiency and quality. …”
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Respiratory bacterial and viral pathogen spectrum among influenza-positive and influenza-negative patients by Jing Shi, Shi Han, Yating Zhang, Xiaohua Lu, Yunxia Gan, Narenqimuge Tong, Lu Ma, Hang Zhuan, Ying Dai, Yaqi Ji, Guoming Li, Dan Chen, Lu Yang

“…The most common co-infection pattern was H. influenzae and influenza virus, accounting for 133 cases (29.95% of mixed infections). …”
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Variation in Feed Point within Differed L-Slot Multi-frequency Microstrip Patch by Sandeep Arya, Ramni Gupta, Saleem Khan, Parveen Lehana

“…It is designed successfully for mobile communication systems and Wireless Local Area Networks (WLAN) applications. The results obtained had showed better improvement in the return loss and radiation pattern in comparison to the other existing antennas.…”
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Integration of Machine Learning and Wavelet Algorithms for Processing Probing Signals: An Example of Oil Wells by Zukhra Abdiakhmetova, Zhanerke Temirbekova

“…Furthermore, machine learning models, including standard regression algorithms and neural networks, are leveraged to enhance signal interpretation and predictive capabilities. …”
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