Ripening Study Based on Multi-Structural Inversion of Cherry Tomato qMRI by Yanan Li, Jingfa Yao, Wenhui Yang, Zhao Wei, Peng Luan, Guifa Teng

“…This study introduces a non-destructive, quantitative method using low-field MRI to assess moisture mobility and content distribution in cherry tomatoes. This study developed an advanced 3D non-local mean denoising model to enhance tissue feature analysis and applied an optimized TransUNet model for structural segmentation, obtaining multi-echo data from six tissue types. …”
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Ангари як архітектурний елемент авіаційних музейних комплексів by Yuriy Doroshenko, Alexander Khlyupin, Bohdana Nikolchuk

“…Aim: to determine the design features of hangars in museum complexes, their practical significance and functional purpose. …”
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Early signs of strong El Niño–Southern Oscillation episodes by Wenxiu Zhong, Arnold Sullivan, Gian Luca Eusebi Borzelli, Ziguang Li

“…Additionally, we find that the spatial standard deviations of the sea surface temperature anomaly in Niño-3 and Niño-4 region, rapidly decrease in the first half of ENSO developing year. This feature is fundamentally distinct from that in neutral years, suggesting that the cycle of ENSO persistence goes beyond the SPB and sea surface temperature anomalies in those two Niño regions are the most predictable.…”
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Flash Flood Regionalization for the Hengduan Mountains Region, China, Combining GNN and SHAP Methods by Yifan Li, Chendi Zhang, Peng Cui, Marwan Hassan, Zhongjie Duan, Suman Bhattacharyya, Shunyu Yao, Yang Zhao

“…The SHAP model was then applied to quantify the impact of all the inducing factors on the regionalization results by Dink-Net. The newly developed framework captured the spatial interactions of the inducing factors and characterized the spatial distribution patterns of the factors. …”
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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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Révision de l’espèce Homo erectus (Dubois, 1893) by Valéry Zeitoun

“…The reconstruction of this evolutionary pattern should be matched with other data (dating, biogeography) to allow to reconstruct a real evolutionary synopsis.According to several authors (Stringer, 1984; Hublin, 1986; Kennedy, 1991; Brauer and Mbua, 1992) the existence of autapomorphic features for Homo erectus is not proved. …”
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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

“…The present study aims to investigate the features of the stressed state of modular blocks with large door openings and the effect of size and place of the doors on the openings on the overall structural behavior of the building. …”
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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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Microbiological and Clinicoepidemiological Profile of a Series of Patients with Infective Endocarditis at a Center in Eastern Nepal by Sohani Bajracharya, Basudha Khanal, Shraddha Siwakoti, Rupa Rajbhandari Singh, Sanjib Kumar Sharma

“…Majority of patients developed acute kidney injury (35.3%) and congestive cardiac failure (23.5%). …”
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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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Deep learning model using continuous skin temperature data predicts labor onset by Chinmai Basavaraj, Azure D. Grant, Shravan G. Aras, Elise N. Erickson

“…We investigated if continuous body temperature exhibits similar changes in women and whether these changes may be linked to hormonal status. Finally, we developed a deep learning model using temperature patterning to provide a daily forecast of time to labor onset. …”
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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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