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

“…Further analyses examined immune infiltration patterns and functional pathways. Importantly, we analyzed the relationship between prognostic-related genes and ubiquitination, and further characterized the characteristics of ubiquitination-related prognostic genes. …”
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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

“…Accurate offset measurement is crucial for recovering the size of past earthquakes and understanding the recurrence patterns of strike-slip faults. Traditional methods, which rely on manual delineation of displaced geomorphic markers from satellite images, often introduce significant uncertainties. …”
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MODELING OF DEEP CURRENTS IN THE JAPAN SEA: RELATIONSHIP WITH THE CURRENTS IN THE THERMOCLINE LAYER by O. O. Trusenkova

“…The main simulated patterns are the cyclonic gyres along the sea margins and in the deep basins and the anticyclonic circulation above underwater rises, that generally corresponds with the schemes based on deep floats tracking. …”
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Characterization of full-length long noncoding RNAs and identification of virus-responsive lncRNAs in Sogatella furcifera by Yawen Ban, Yawen Ban, Ting Cui, Ting Cui, Lifei Zhao, Lifei Zhao, Xue Li, Xue Li, Qing Bai, Qing Bai, Qingfa Wu, Qingfa Wu

“…Long non-coding RNAs (lncRNAs) are crucial regulators of development and stress responses in eukaryotes, but their roles in non-model insects, particularly rice planthoppers, remain poorly characterized. …”
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StructureNet: Physics-Informed Hybridized Deep Learning Framework for Protein–Ligand Binding Affinity Prediction by Arjun Kaneriya, Madhav Samudrala, Harrish Ganesh, James Moran, Somanath Dandibhotla, Sivanesan Dakshanamurthy

“…Overall, the results show that structural data alone are sufficient for binding affinity predictions and can address pattern recognition challenges introduced by sequence and interaction features. …”
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Estimation of soil thickness in karst landforms using a quantile regression forests approach by Fayong Fang, Ruyi Zi, Zhen Han, Qian Fang, Rui Hou, Longshan Zhao

“…The prediction results reveal the distribution pattern of soil thickness at both regional and local scales within karst landforms. …”
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Hip Involvement in Pediatric Scurvy: Early Magnetic Imaging Signs by Lisa Gamalero, Anna Perrone, Chiara Macucci, Alessandra Meneghel, Marta Balzarin, Sandra Trapani, Giuseppe Indolfi, Giorgia Martini, Teresa Giani

“…In all patients, pelvic MRI showed a bilateral, patchy, abnormal, water-like signal intensity pattern in the sacroiliac area. Sacroiliitis was detected in three children and hip effusion in another child. …”
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Rainfall-induced Landslide Susceptibility Prediction Considering Spatial Heterogeneity by ZHANG Xingfu, JIANG Yuanjun, ABI Erdi

“…Inputs such as terrain features, soil characteristics, vegetation indices, and rainfall patterns were utilized to train and evaluate the models. …”
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High-temperature dolomite in the Lower Cretaceous Cupido Formation, Bustamante Canyon, northeast Mexico: petrologic, geochemical and microthermometric constraints by Gabriela Sara Guzzy-Arredondo, Gustavo Murillo-Muñetón, Dante Jaime Morán-Zenteno, José Manuel Grajales-Nishimura, Ricardo Martínez-Ibarra, Peter Schaaf

“…Dolomite distribution was apparently not controlled by major tectonic features (e.g., faults or fractures); the dolomitizing fluid seems to have followed subhorizontal or lateral flowing circulating patterns controlled by the former porosity and permeability of the calcareous facies.   …”
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Identification and Interpretation of Cultural Landscape Field from the Integral Conservation Perspective by Zhitong LIANG, Yan DU, Haiyan XIA

“…Through synthesizing theoretical postulates from multidisciplinary scholarship on spatial interpretation, this research establishes the application logic of field paradigm in spatial cognition and mechanistic explanation: Conceptual demarcation of the spatial field entity coupled with identification of its core driving forces; abstraction of operational logic encompassing participatory actor typologies and their interaction patterns; elucidation of the mechanistic relationships between constituent elements and the integral system through nodal field effects. …”
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Dynamic monitoring of fine-grained ecological vulnerability in dryland urban agglomeration integrating novel remote sensing index and explainable machine learning by Chunqiang Li, Shanchuan Guo, Qin Huang, Haowei Mu, Bo Yuan, Zilong Xia, Hong Fang, Wei Zhang, Pengfei Tang, Peijun Du

“…However, persistent technological gaps in large-scale, fine-grained and long-term monitoring hinder a comprehensive understanding of vulnerability patterns in these fragile regions. To address this, a novel Dryland Ecological Vulnerability Index (DEVI) is proposed by integrating six key indicators and combining remote sensing and machine learning to simplify the complex vulnerability scoping diagram (VSD). …”
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Machine learning based differential diagnosis of SAPHO syndrome and secondary bone tumors using whole body bone scintigraphy by Hongyang Jiang, Aihui Liu, Yihan Cao, Zhimin Lin, Haixu Jiang, Shengyan Liu, Qiuwei Peng, Xia Wu, Yuchen Liu, Xinbo Yu, Maming Wei, Yalin Pan, Chen Li, Zhenhua Ying

“…The WBBS findings of SAPHO syndromes and secondary bone tumors (SBT) have overlapping features, posing diagnostic challenges. In this multicenter study, we aim to identify different bone and joint involvement patterns between the two disease entities through multiple methods to build machine-learning models and explore interpretable variables. …”
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Numerical Investigations of Convective Initiation in Barbados by Kim Whitehall, Sen Chiao, Margarette Mayers-Als

“…Localized convection in Barbados accounts for hazardous conditions and a significant percentage of the island’s annual rainfall. The feature results in rainfall accumulations exceeding 50 mm in 3 hours or less, over isolated locations. …”
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A hybrid Bi-LSTM and RBM approach for advanced underwater object detection. by Manimurugan S, Karthikeyan P, Narmatha C, Majed M Aborokbah, Anand Paul, Subramaniam Ganesan, Rajendran T, Mohammad Ammad-Uddin

“…The model benefits from effective feature learning, aided by RBMs that enable the extraction of hierarchical and abstract representations. …”
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Deep learning enabled integration of tumor microenvironment microbial profiles and host gene expressions for interpretable survival subtyping in diverse types of cancers by Haohong Zhang, Xinghao Xiong, Mingyue Cheng, Lei Ji, Kang Ning

“…In this study, we aimed to decode this complex relationship by developing ASD-cancer (autoencoder-based subtypes detector for cancer), a semi-supervised deep learning framework that could extract survival-related features from tumor microbiome and transcriptome data, and identify patients’ survival subtypes. …”
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