Integrated Machine Learning Algorithms-Enhanced Predication for Cervical Cancer from Mass Spectrometry-Based Proteomics Data by Da Zhang, Lihong Zhao, Bo Guo, Aihong Guo, Jiangbo Ding, Dongdong Tong, Bingju Wang, Zhangjian Zhou

“…Early diagnosis is critical for improving outcomes in cancer patients; however, the application of diagnostic markers derived from serum proteomic screening remains challenging. …”
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High-Accuracy HLA Type Inference from Whole-Genome Sequencing Data Using Population Reference Graphs. by Alexander T Dilthey, Pierre-Antoine Gourraud, Alexander J Mentzer, Nezih Cereb, Zamin Iqbal, Gil McVean

“…We also identify and re-type two erroneous alleles in the original validation data. We conclude that HLA*PRG for the first time achieves accuracies comparable to gold-standard reference methods from standard whole-genome sequencing data, though high computational demands (currently ~30-250 CPU hours per sample) remain a significant challenge to practical application.…”
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Comparison of Multiple Surface Ocean Wind Products with Buoy Data over Blue Amazon (Brazilian Continental Margin) by Vitor Paiva, Milton Kampel, Rosio Camayo

“…Orbital sensors, such as radar scatterometers, provide data on ocean surface wind speed and direction with spatial and temporal resolutions suitable for multiple applications and air-sea studies. …”
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Semantic-Driven Approach for Validation of IoT Streaming Data in Trustable Smart City Decision-Making and Monitoring Systems by Oluwaseun Bamgboye, Xiaodong Liu, Peter Cruickshank, Qi Liu

“…The approach provides an enhancement to data quality and credibility, capable of providing near-real-time decision support mechanisms for critical smart city applications, and facilitates accurate situational awareness across both the application and operational levels of the smart city.…”
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A Kriging Interpolation-Enhanced MART for Nonuniform Observational Data in Geosynchronous SAR-Based Computerized Ionospheric Tomography by Yi Sui, Xichao Dong, Yuanhao Li, Zhiyang Chen, Cheng Hu

“…This proposed method embeds Kriging interpolation into the conventional MART iteration, utilizing the spatial correlation of electron density to compensate for voxels with sparse TEC data, while still incorporating the voxel's own TEC data. …”
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Multichannel Deep Attention Neural Networks for the Classification of Autism Spectrum Disorder Using Neuroimaging and Personal Characteristic Data by Ke Niu, Jiayang Guo, Yijie Pan, Xin Gao, Xueping Peng, Ning Li, Hailong Li

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Electrical resistivity imaging data for hydrological and soil investigations of virgin Rospuda River peatland (north-eastern Poland) by G. Sinicyn, Ł. Kaczmarek, R. Mieszkowski, S. Mieszkowski, B. Bednarz, K. Kochanek, M. Grygoruk, M. Grodzka-Łukaszewska

“…The study delivers geophysical measurement data performed in the Rospuda wetlands located in north-eastern Poland. …”
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Coconut Testa Flour Sub-Fractions: Correlation Between FTIR Spectral Data and α-Glucosidase Inhibitory Activities by Rasika Gunarathne, Savani Ulpathakumbura, Nazrim Marikkar, Lalith Jayasinghe, Jun Lu

“…This study suggests that the application of multivariate regression analysis of FTIR spectral data on coconut-based products could help to detect Alpha-glu inhibitory activities.…”
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An Improved Processing Method for Low-Frequency Spaceborne Full-Polarimetric SAR Data Affected by Ionospheric Faraday Rotation by Xun Wang, Yunhua Zhang, Dong Li

“…Spaceborne full-polarimetric (FP) synthetic aperture radar (SAR) system operating at low frequency (such as L- or P-band) is a powerful microwave sensor used to capture the Earth’s surface information. However, the application effectiveness of the data acquired by such a sensor depends on the processing for the effects of ionospheric Faraday rotation (FR) and possibly-existing certain system errors. …”
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DETEC-ADHD: A Data-Driven Web App for Early ADHD Detection Using Machine Learning and Electroencephalography by Ismael Santarrosa-López, Giner Alor-Hernández, Maritza Bustos-López, Jonathan Hernández-Capistrán, Laura Nely Sánchez-Morales, José Luis Sánchez-Cervantes, Humberto Marín-Vega

“…To address these limitations, this study introduces DETEC-ADHD, a web-based application that combines machine learning (ML) techniques with multi-source data to enhance diagnostic accuracy. …”
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Assessment of plant diversity index in degraded desert grassland using UAV hyperspectral multimodal data and Encoder-CNN by Zhaohui Tang, Chuanzhong Xuan, Tao Zhang, Xinyu Gao, Suhui Liu, Mengqin Zhang

“…The use of multimodal data combining spatial spectral features with index features, combined with the Encode-CNN model, can provide the most accurate information on community composition. …”
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Link-State-Aware Proactive Data Delivery in Integrated Satellite–Terrestrial Networks for Multi-Modal Remote Sensing by Ranshu Peng, Chunjiang Bian, Shi Chen, Min Wu

“…By integrating satellite cache states, user cache states, and multi-modal data attributes (including imagery, metadata, and temporal request patterns) into a unified Markov decision process (MDP), our approach pioneers the application of the multi-actor-attention-critic with parameter sharing (MAPPO) algorithm to ISTNs push tasks. …”
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A framework for tracing the sources of nitrate in surface water through remote sensing data coupled with machine learning by Di Tian, Xinfeng Zhao, Lei Gao, Tao Jiang, Zuobing Liang, Zaizhi Yang, Pengcheng Zhang, Qirui Wu, Kun Ren, Chenchen Yang, Rui Li, Shaoheng Li, Yingjie Cao, Yingxue Xuan, Jianyao Chen, Aiping Zhu

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Linear and nonlinear multidimensional functional connectivity methods reveal similar networks for semantic processing in EEG/MEG data by Setareh Rahimi, Rebecca L. Jackson, Rebecca L. Jackson, Olaf Hauk

“…However, TL-MDPC remains linear and may therefore miss nonlinear interactions among brain areas.MethodsThus, we introduce Nonlinear TL-MDPC (nTL-MDPC), a novel bivariate functional connectivity method for event-related EEG/MEG applications, and compare its performance to the original linear TL-MDPC. nTL-MDPC describes how well patterns in ROI X at a time point tx can predict patterns of ROI Y at a time point ty using artificial neural networks.ResultsApplying this method and its linear counterpart to simulated data demonstrates that both can identify nonlinear dependencies, with nTL-MDPC achieving up to ~0.75 explained variance under optimal conditions (e.g., high SNR), compared to ~0.65 with TL-MDPC. …”
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Novel machine learning paradigms-enabled methods for smart building operations in data-challenging contexts: Progress and perspectives by Fan Cheng, Lei Yutian, Mo Jinhan, Wang Huilong, Wu Qiuting, Cai Jiena

“…Recent advances in data science have provided novel machine learning paradigms to tackle such data challenges for practical applications, such as transfer learning, semi-supervised learning, and generative learning. …”
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Assessing Public Transit Network Efficiency and Accessibility in Johor Bahru and Penang, Malaysia: A Data-Driven Approach by Mahbub Hassan, Hridoy Deb Mahin, Ferdoushi Ahmed, Md. Maruf Hassan, Atikur Rahaman, Masuk Abdullah

“…This study conducts a comprehensive analysis of public bus transit networks in Johor Bahru and Penang, Malaysia, using General Transit Feed Specification (GTFS) data. It focuses on evaluating network efficiency, spatial equity, and accessibility within the myBAS Johor and Rapid Bus Penang systems. …”
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Integration of In Situ and Sentinel-2 Data to Assess Soil Quality in Forest Monitoring: The Case Study of the Vesuvius Fires by Lucia Santorufo, Massimiliano Gargiulo, Valeria Memoli, Giulia Maisto, Rossella Barile, Giuseppe Ruello

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Catchment-scale assessment of groundwater discharge using ecological, thermal, and hydrochemical surveillance data in the Halton Region, Ontario by Nathan Beckner-Stetson, Virginie Gaye, Mason Marchildon, Andrea D. Dunn, Behnam Doulatyari, Kim Funk, Steve Holysh, Kim Barrett, Bas Vriens

“…This study explores the application of readily available surface water monitoring data to identify potential groundwater discharge locations in 15 catchments within Conservation Halton's jurisdiction within the Halton Region, Ontario, Canada. …”
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Using the aeromagnetic data for mapping the basement depth and contact locations, at southern part of Tihamah region, western Yemen by Marwan A. Al-Badani, Yahia M. Al-Wathaf

“…The present study aims to produce an excellent picture for the basement depth and contact locations, deduced from the available aeromagnetic data. The total intensity aeromagnetic map was first corrected by the application of the reduction to the magnetic pole (for low latitude areas) technique. …”
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Construction and Analysis of Slope Plane Deformation of High CFRD Based on Statistical Analysis of Multi‐Points Monitoring Data by Xiongxiong Zhou, Wenjun Cai, Qiujiang He, Jing Zhou, Bingqian Zhou

“…Compared with the traditional single point monitoring method, the proposed method provides more accurate prediction results on the basis of multi‐point data collaborative analysis, provides a new idea for dam displacement monitoring and settlement prediction, and has high engineering application and popularization value.…”
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