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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Extreme high temperatures and heatwave events across Europe in 2023 by Yuqing Sun, Gensuo Jia, Xiyan Xu

“…However, there is a lack of quantitative analysis of spatial and temporal features of such record high heatwaves. Here, we investigated the spatial patterns and seasonal evolution of heatwaves over Europe in 2023. …”
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Application of Concentration-Area fractal modeling and artificial neural network to identify Cu, Zn±Pb geochemical anomalies in Hashtjin area, NW of Iran by Ali Imamalipour, Hamed Ebrahimi, Amir reza Abdollahpur

“…This neural network automatically and through unsupervised learning identifies patterns, complex structures, and high-level features of the input data. …”
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Management and utilization of the Fund for Innovative Medicines: a multistakeholder qualitative survey on regional and local practices by Andrea Vitagliano, Marzia Bonfanti, Chiara Lucchetti, Andrea Marcellusi

“…A survey administered through interviews to 18 KOLs (clinicians, hospital pharmacists, top hospital managers, and regional pharmaceutical service directors) from 9 Italian regions provided evidence of FFI utilization patterns. The content analysis identified FFI management features, challenges, and best practices. …”
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Multimodal Deep Learning in Early Autism Detection—Recent Advances and Challenges by Sheril Sophia Dcouto, Jawahar Pradeepkandhasamy

“…Deep learning models, with their ability to analyze complex patterns and extract meaningful features from large datasets, offer great promise in addressing the challenge of early ASD detection. …”
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Learning deep forest for face anti-spoofing: An alternative to the neural network against adversarial attacks by Rizhao Cai, Liepiao Zhang, Changsheng Chen, Yongjian Hu, Alex Kot

“…Our approach introduces a multi-scale texture representation based on local binary patterns (LBP) as the model input, replacing the grained-scanning mechanism (GSM) used in the traditional deep forest model. …”
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Neuropathic Pain Detection: An EEG-Based Brain Functional Network Approach by Abdulyekeen T. Adebisi, Ho-Won Lee, Kalyana C. Veluvolu

“…By extracting persistent homology features from these networks, we developed a support vector machine (SVM)-based classifier that distinguishes control subjects from those experiencing varying degrees of NP. …”
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Molecular and Clinical Overview of Type 1 Neurofibromatosis: Single Center Study and Mini Review on NF1-Associated Vasculopathy and Juvenile Myelomonocytic Leukemia by Şule Altıner, Alper Han Çebi

“…Molecular diagnosis is important in patients with an atypical presentation, as well as in children who have not yet developed sufficient characteristic features or for providing prenatal diagnosis. …”
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REVIEW OF: GOLUBKOVA O.N. FUNDAMENTALS OF SCIENTIFIC RESEARCH IN THE PROFESSIONAL FIELD: TEXTBOOK by A.A. Bilyalova, A.N. Utekhina

“…Patterns in the use of methodological concepts based on their functions in a study are highlighted. …”
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Leveraging machine learning for data-driven building energy rate prediction by Nasim Eslamirad, Mehdi Golamnia, Payam Sajadi, Francesco Pilla

“…Focusing on Dublin, we integrate diverse geospatial datasets with building-specific and neighbourhood-scale features to classify BER. Our approach leverages cutting-edge ML techniques, including Decision Trees (DT), Random Forest (RF), K-Nearest Neighbours (KNN), and Support Vector Machines (SVM), to develop highly accurate predictive models. …”
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The Reliability of Diagnosing Schizophrenia Using the GRU Layer in Conjunction with EEG Rhythms by Pankaj Kumar Sahu, Karan Jain

“…Deep learning methods and patterns found in EEG of brain activity are helpful features for verifying schizophrenia. …”
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Analysis of consumer purchase intentions using functional near-infrared spectroscopy(fNIRS): A neuromarketing study on the aesthetic packaging of Korean red ginseng products. by SuJin Bak, Jaeyoung Shin, Daeun Kim, Sungkean Kim

“…By measuring brain activities, we aim to develop neuromarketing techniques and provide insights into consumer purchasing decisions influenced by the aesthetic features of product packaging.…”
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Single-cell sequencing combined with machine learning to identify glioma biomarkers and therapeutic targets by Yu Yan, Zhengmin Chu, Qi Zhong, Genghuan Wang

“…A 16-gene DRG signature was developed for predicting the survival of glioma patients. …”
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Individualized spatial network predictions using Siamese convolutional neural networks: A resting-state fMRI study of over 11,000 unaffected individuals. by Reihaneh Hassanzadeh, Rogers F Silva, Anees Abrol, Mustafa Salman, Anna Bonkhoff, Yuhui Du, Zening Fu, Thomas DeRamus, Eswar Damaraju, Bradley Baker, Vince D Calhoun

“…Many neuroimaging studies have demonstrated the potential of functional network connectivity patterns estimated from resting functional magnetic resonance imaging (fMRI) to discriminate groups and predict information about individual subjects. …”
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A conceptual root zone model to calculate the application amount and frequency of water available for recharge by Francisco Flores-López, David Arrate, Mehrdad Bastani

“…The method is based on soil-land use combination, and crop saturation tolerance considering seasonal patterns during a long-term application of water available for recharge. …”
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Evaluation of K-Means Algorithm for Faulted Landforms Extraction and Offset Measurement With an Example From the Eastern Kunlun Fault by Shengchao Zhou, Zhou Lin

“…This study aims to develop a more objective and accurate method for identifying faulted landforms and measuring offsets. …”
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MODELING OF DEEP CURRENTS IN THE JAPAN SEA: RELATIONSHIP WITH THE CURRENTS IN THE THERMOCLINE LAYER by O. O. Trusenkova

“…Geostrophic deep circulation in the Japan Sea is modeled using the primitive equation multilayer model developed by N.B. Shapiro and E.M. Mikhaylova (Marine Hydrophysical Istitute, RAS). …”
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Epidemiological trends and clinical characteristics of measles in Iraq (2023–2024): a retrospective cross-sectional study by Mohammed A. Jalal, Kamil M. Halboot, Sundus A. Lami, Entidhar A. Gumar, Mortada H. Kreeb al-Delphi, Faris Lami, Taqi Mohammed Jwad Taher

“…This study aims to analyze the epidemiological patterns and clinical features of measles in Iraq to develop effective public health interventions. …”
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CH-RUN: a deep-learning-based spatially contiguous runoff reconstruction for Switzerland by B. Kraft, M. Schirmer, W. H. Aeberhard, M. Zappa, S. I. Seneviratne, L. Gudmundsson

“…</p> <p>The developed data-driven model demonstrates not only competitive performance, but also notable improvements over traditional hydrological modeling in replicating daily runoff patterns, capturing interannual variability, and discerning long-term trends. …”
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Research on Creep Constitutive Model for High Temperature Reactor Based on Neural Network by ZHANG Fan, DAI Shoutong

“…This research aims to develop a novel creep constitutive model, leveraging neural networks to precisely predict long-term creep behavior from short-term data. …”
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