Expose flexible conformations for intrinsically disordered protein by Jiaan Yang, Wenxin Ji, Wen Xiang Cheng, Gang Wu, Si Tong Sheng, Peng Zhang, Jun Lin, Xiaojia Chen, Qiong Shi

“…Although many methods and databases provide information for intrinsically disordered protein (IDP), they are mainly limited to determining the intrinsically disordered regions (IDR) lacking knowledge of possible folding patterns. To overcome the barrier, the protein structure fingerprint technology has been developed, which includes PFSC (Protein Folding Shape Code) (Yang, 2008) and PFVM (Protein Folding Variation Matrix) (Yang et al., 2022) algorithms as well as FiveFold (Yang et al., 2025) approach for protein structure prediction, which are able explicitly to expose the possible conformational structures for intrinsically disordered protein. …”
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Transfer learning drives automatic HER2 scoring on HE-stained WSIs for breast cancer: a multi-cohort study by Xiaoping Li, Zhiquan Lin, Chaoran Qiu, Yiwen Zhang, Chuqian Lei, Shaofei Shen, Weibin Zhang, Chan Lai, Weiwen Li, Hui Huang, Tian Qiu

“…Patch analysis revealed a core-to-peritumoral probability decrease pattern as malignancy spread outward from the lesion's core. …”
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TECTONOPHYSICAL SIGNS OF THE FORMATION OF STRONG EARTHQUAKE FOCI IN SEISMIC ZONES OF CENTRAL ASIA by S. I. Sherman

“…Such movements take place in a stepwise pattern with high or reduced friction, depending on the presence of fluids, hitches on the fault planes and other factors. …”
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A Vision-Based Method for Detecting the Position of Stacked Goods in Automated Storage and Retrieval Systems by Chuanjun Chen, Junjie Liu, Haonan Yin, Biqing Huang

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Stress State of Modular Blocks with Large Door Openings by Ilia Teshev, Aliy Bespayev, Murat Tamov, Zauresh Zhambakina, Ulan Altigenov, Timur Zhussupov, Aigerim Tolegenova

“…Experimental results revealed that crack opening characteristics, main load-bearing wall deformations, horizontal deflections, and failure patterns under vertical loads are directly influenced by the small thickness and increased flexibility of the blocks. …”
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RF-PSignal: The Smart Home Gesture Recognition System Based on Channel-Wise Topology and Self-Adaptive Attention by Xiaohang Zhang, Chunhong Yue, Yajun Zhang, Kun Liang, Yanxiang Li

“…Unlike most existing studies that rely on time-series signals for feature extraction and pattern recognition, the system achieves outstanding performance and computational efficiency through a time-series-to-image transformation algorithm and lightweight model design. …”
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An algorithm for annotation and classification of T. cruzi MASP sequences: towards a better understanding of the parasite genetic variability by Aldana Alexandra Cepeda Dean, Luisa Berná, Carlos Robello, Carlos Andrés Buscaglia, Virginia Balouz

“…On the contrary, structural features of canonical MASPs, MASP-related sequences, and MASP-chimeras were largely conserved across parasite genomes. …”
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Advanced artificial intelligence with federated learning framework for privacy-preserving cyberthreat detection in IoT-assisted sustainable smart cities by Mahmoud Ragab, Ehab Bahaudien Ashary, Bandar M. Alghamdi, Rania Aboalela, Naif Alsaadi, Louai A. Maghrabi, Khalid H. Allehaibi

“…Deep learning (DL) focused cyberthreat detection has developed as a powerful and effective approach to identifying abnormal patterns or behaviours in the data field. …”
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Unobtrusive Sleep Posture Detection Using a Smart Bed Mattress with Optimally Distributed Triaxial Accelerometer Array and Parallel Convolutional Spatiotemporal Network by Zhuofu Liu, Gaohan Li, Chuanyi Wang, Vincenzo Cascioli, Peter W. McCarthy

“…Accurate identification of sleep postures can offer valuable insights into an individual’s sleep patterns, comfort levels, and potential health risks. …”
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Exploring the potential of deep learning models integrating transformer and LSTM in predicting blood glucose levels for T1D patients by Xin Xiong, XinLiang Yang, Yunying Cai, Yuxin Xue, JianFeng He, Heng Su

“…The Transformer Encoder captures long-range dependencies, while the LSTM models short-term patterns. To improve feature extraction, we integrate Bidirectional LSTM and Transformer Encoder layers at multiple stages. …”
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Fine-Tuning Retrieval-Augmented Generation with an Auto-Regressive Language Model for Sentiment Analysis in Financial Reviews by Miehleketo Mathebula, Abiodun Modupe, Vukosi Marivate

“…Additionally, the pre-training of a larger language model (PTLM) struggles to capture bidirectional contextual knowledge learnt through word dependency because the sentence-level representation fails to take broad features into account. We develop a novel structure called language feature extraction and adaptation for reviews (LFEAR), an advanced natural language model that amalgamates retrieval-augmented generation (RAG) with a conversation format for an auto-regressive fine-tuning model (ARFT). …”
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Event-based landslide inventory through very high-resolution optical images and field surveys by P. Confuorto, R. Franceschini, L. Scarpitta, N. Casagli, S. Morelli, F. Raspini, V. Tofani, S. Moretti

“…Objectives This study aims to develop a detailed post-event landslide inventory of the Misa basin and to analyze the spatial distribution, the main morphological features, and the environmental context of the triggered landslides. …”
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Efficient Anomaly Detection for Edge Clouds: Mitigating Data and Resource Constraints by Javad Forough, Hamed Haddadi, Monowar Bhuyan, Erik Elmroth

“…This enables the model to benefit from the learned features and patterns from related tasks such as network intrusion detection, resulting in improved detection accuracy. …”
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Hyper IgE Syndromes: Understanding, Management, and Future Perspectives: A Narrative Review by Mohammad Salehi, Zeinab Neshati, Hamid Ahanchian, Rana Tafrishi, Alireza Pasdar, Mojtaba Safi, Ehsan Ghayoor Karimiani

“…In this review we aim to provide a comprehensive understanding of the condition and also discuss latest updates on pathological features, clinical spectrum and its variability, immunological abnormalities, inheritance patterns, new candidate genes, challenges, management strategies, epidemiology and future directions of HIES. …”
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Explainability of Network Intrusion Detection Using Transformers: A Packet-Level Approach by Pahavalan Rajkumardheivanayahi, Ryan Berry, Nicholas U. Costagliola, Lance Fiondella, Nathaniel D. Bastian, Gokhan Kul

“…Machine learning based NIDS models leverage algorithms that learn from historical network traffic data to identify patterns and anomalies to capture complex relationships. …”
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Surgical management and outcomes of corrosive esophageal injuries: a prospective study from Sana’a, Yemen by Mohammed Mohammed Al-Shehari, Yasser Abdurabo Obadiel, Ahmed Hamood Al-Helali, Haitham Mohammed Jowah

“…This study evaluated the demographic patterns, clinical presentations, management strategies, and outcomes of patients with corrosive esophageal injuries at a tertiary hospital in Sana’a, Yemen. …”
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Deciphering transcriptomic signatures in schizophrenia, bipolar disorder, and major depressive disorder by Priyanka, Rajesh Kumar, Vinod Kumar, Ashwani Kumar, Sandeep Singh Rana

“…At the same time, each disorder also demonstrated unique transcriptional patterns, supporting the existence of disorder-specific mechanisms. …”
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Roadblocks to ride: Unraveling barriers to access shared micromobility systems in the United States by Farzana Mehzabin Tuli, Suman Kumar Mitra

“…To elucidate the specific barriers faced by users, we employed the K-Prototype clustering methodology, an unsupervised machine learning technique capable of handling datasets with both numerical and categorical features. This approach enabled us to uncover distinct patterns and groupings among shared micromobility services based on these barriers. …”
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A simulation-based network analysis of intervention targets for comorbid symptoms of depression and anxiety in Chinese healthcare workers in the post-dynamic zero-COVID policy era by Chao Zhang, Ruyong Li, Wei Zhang, Yanqiang Tao, Xiangping Liu, Yichao Lv

“…In this new phase, concerns related to work and family, rather than infection, may have become new sources of psychological issues such as depression and anxiety among healthcare workers, leading to new patterns of comorbidity. However, few studies have addressed these issues. …”
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AMCL: supervised contrastive learning with hard sample mining for multi-functional therapeutic peptide prediction by Jiwei Fang, Henghui Fan, Jintao Zhao, Jianping Zhao, Junfeng Xia

“…The field faces challenges such as long-tail distribution problems, data sparsity, and complex label co-occurrence patterns due to peptides’ multi-functional nature. …”
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