Federated Learning for Fall Detection With Multimodal Residual Fusion and Pareto-Optimized Client Selection by Bao-Quan Wang, Fan Yang, Yi Wang, Fan Zhao, Yun-Fei Han, Yu-Peng Ma

“…Finally, a Pareto-optimized client selection method is introduced to efficiently select reliable clients for global aggregation, ensuring both the stability and robustness of the global model. …”
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Using Differential Scanning Calorimetry to Measure the Energetic Properties of Residual Sludge and Catalysts from the Textile, Tannery, and Galvanic Industries by Ghem Carvajal-Chávez, Josselyn Cazar, Gilda Gordillo, Andrés De-La-Rosa, Gonzalo Chiriboga, Carolina Montero-Calderón

“…The data gathered were the input for constructing specific heat models through polynomial regression employing the least squares method. These models were subsequently used to estimate variations in the enthalpy and entropy for both the sludge and catalysts through integration. …”
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Voice as a sensitive biomarker for predicting exercise intensity: a modelling study by Shuyi Zhou, Ruisi Ma, Wangjing Hu, Dandan Zhang, Rui Hu, Shengwei Zou, Dingyi Cai, Zikang Jiang, Hexiao Ding, Ting Liu

“…These features were analyzed using statistical models, including support vector machine (SVM), to classify exercise intensity.ResultsSignificant variations in speech characteristics, such as speech duration, fundamental frequency (F0), and pause times, were observed across different exercise intensities, with the models achieving high accuracy in distinguishing between exercise states.ConclusionThese findings suggest that speech analysis can provide a non-invasive, real-time method for monitoring exercise intensity. …”
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Optimizing Photovoltaic Grid‐Connected Power Systems Through Artificial Intelligence and Robust Nonlinear Control by Collins Ngong Sang, Harrison Ambe, Arnaud flanclair Tchouani Njomo, Zeric Tabekoueng Njitacke, Wulfran Fendzi Mbasso, Pradeep Jangir, Aseel Smerat

“…ABSTRACT Photovoltaic (PV) systems are highly sensitive to stochastic environmental variations, particularly irradiance and temperature, which complicate the task of consistently operating at the maximum power point (MPP). …”
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Feature Enhancement Network for Infrared Small Target Detection in Complex Backgrounds Based on Multi-Scale Attention Mechanism by Sen Zhang, Weilin Du, Yuan Liu, Ni Zhou, Zheng Li

“…For assessing our technique’s efficiency, we present a novel benchmark dataset, IRMT-UAV, noted for its considerable discrepancies in target size, intricate backdrops, and substantial variations in the signal-to-noise ratio. The outcomes of our experiments using the public IRSTD-1k dataset and the internally developed IRMT-UAV dataset reveal that our technique surpasses cutting-edge (SOTA) methods, with mAP50 enhancements of 1.4% and 4.9%, respectively, thus proving our method’s efficiency and sturdiness.…”
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Identifying climate and environmental determinants of spatial disparities in wheat production using a geospatial machine learning model by Kai Ren, Yongze Song, Linchao Li, Francesco Mancini, Zhuoyao Xiao, Xueyuan Zhang, Rui Qu, Qiang Yu

“…First, a spatial autocorrelation method is employed to identify the hotspot area of wheat production in Australia. …”
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Advances of Hydroxyapatite Nanoparticles in Dental Implant Applications by Md. Aminul Islam, Nayem Hossain, Sumaya Hossain, Fardin Khan, Saniya Hossain, Md. Mostafizur Rahman Arup, Mohammad Asaduzzaman Chowdhury, Md. Majibur Rahman

“…The green synthesis method illustrated a new door to synthesize HAp for maintaining biocompatibilityand increasing antibacterial properties. …”
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Dynamic Synergy Network Analysis Reveals Stage-Specific Regional Dysfunction in Alzheimer’s Disease by Xiaoyan Zhang, Chao Han, Jingbo Xia, Lingli Deng, Jiyang Dong

“…<b>Method:</b> This study pioneered the application of an Integrated Information Decomposition (ΦID) framework in AD brain network analysis, constructing single-sample network models based on ΦID-derived synergy metrics to systematically compare their differences with mutual information-based methods in pathological sensitivity, computational robustness, and network representation capability, while detecting brain regions with declining dynamic synergy during AD progression through intergroup <i>t</i>-tests. …”
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Seasonally Robust Offshore Wind Turbine Detection in Sentinel-2 Imagery Using Imaging Geometry-Aware Deep Learning by Xike Song, Ziyang Li

“…To address these limitations, We propose a novel deep learning approach to capture the variability in OWT appearance and shadows caused by changes in solar illumination and satellite viewing geometry. Our method learns intrinsic, imaging geometry-invariant features of OWTs, enabling robust detection across multi-seasonal Sentinel-2 imagery. …”
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Improving prenatal diagnosis with combined karyotyping, CNV-seq and QF-PCR: a comprehensive analysis of chromosomal abnormalities in high-risk pregnancies by Jia-pei Liu, Shan-Bing Wang, Li Luo, Ya-mei Guo

“…ObjectiveThis study aims to assess the diagnostic efficacy of a combined approach integrating chromosomal karyotyping, copy number variation sequencing (CNV-seq), and quantitative fluorescence polymerase chain reaction (QF-PCR) in detecting chromosomal abnormalities in high-risk pregnancies.MethodsThis retrospective study analyzed 617 high-risk pregnancies undergoing prenatal diagnosis from February 2023 to August 2024, with amniotic fluid samples concurrently analyzed using karyotyping, CNV-seq, and QF-PCR. …”
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Perceptions and attitudes of nurse practitioners toward artificial intelligence adoption in health care by Moustaq Karim Khan Rony, Sharker Md. Numan, Fateha tuj Johra, Khadiza Akter, Fazila Akter, Mitun Debnath, Sujit Mondal, Md. Wahiduzzaman, Mousumi Das, Mohammad Ullah, Mohammad Habibur Rahman, Shuvashish Das Bala, Mst. Rina Parvin

“…Objectives This study aimed to gain insights into nurse practitioners' perceptions and attitudes toward AI adoption in health care. Methods This qualitative research employed a descriptive and phenomenological approach using in‐depth interviews. …”
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Canonical correlation analysis for multi-omics: Application to cross-cohort analysis. by Min-Zhi Jiang, François Aguet, Kristin Ardlie, Jiawen Chen, Elaine Cornell, Dan Cruz, Peter Durda, Stacey B Gabriel, Robert E Gerszten, Xiuqing Guo, Craig W Johnson, Silva Kasela, Leslie A Lange, Tuuli Lappalainen, Yongmei Liu, Alex P Reiner, Josh Smith, Tamar Sofer, Kent D Taylor, Russell P Tracy, David J VanDenBerg, James G Wilson, Stephen S Rich, Jerome I Rotter, Michael I Love, Laura M Raffield, Yun Li, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Analysis Working Group

“…Canonical correlation analysis (CCA) is a correlation-based integrative method designed to extract latent features shared between multiple assays by finding the linear combinations of features-referred to as canonical variables (CVs)-within each assay that achieve maximal across-assay correlation. …”
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Pore evolution in tight sandstone and its impact on oil saturation: a case study of Chang 6 to Chang 8 reservoirs in Triassic Yanchang Formation, Ganquan area, Ordos Basin by Hongli ZHONG, Lihua CHEN, Fengqi ZHANG, Yongqi LIANG

“…The movable fluid saturation during the main hydrocarbon accumulation period was then calculated using integration methods. The results showed that the Chang 6 to Chang 8 tight sandstone reservoirs experienced strong compaction during the early and middle diagenetic stages, with an average porosity reduction of 81.85% due to compaction. …”
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A Tumor Volume Segmentation Algorithm Based on Radiomics Features in FDG-PET in Lung Cancer Patients, Validated Using Surgical Specimens by Lena Bundschuh, Jens Buermann, Marieta Toma, Joachim Schmidt, Glen Kristiansen, Markus Essler, Ralph Alexander Bundschuh, Vesna Prokic

“…Background: Although the integration of positron emission tomography into radiation therapy treatment planning has become part of clinical routine, the best method for tumor delineation is still a matter of debate. …”
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Hardware assurance with silicon photonic physical unclonable functions by Mohammad Amin Mahdian, Ebadollah Taheri, Kaveh Rahbardar Mojaver, Mahdi Nikdast

“…These findings underscore the potential of silicon photonic PUFs in enhancing security for optical communication systems of different scales. The integration of such photonic PUFs offers robust and reliable security solutions for applications where traditional electronic methods introduce additional attack surfaces and fail to provide adequate protection.…”
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A proof-of-concept study of personalized dosimetry for targeted radioligand therapy using pre-treatment diagnostic dynamic PET/CT and Monte Carlo simulation by Thanh Tai Duong, Danny De Sarno, Hatim Fakir, Glenn Bauman, Martin Martinov, Rowan M. Thomson, Ting-Yim Lee, Ting-Yim Lee, Ting-Yim Lee

“…Our voxel-based approach demonstrates significant dose variations in prostate cancer patients under standard TRT with a one-size-fits-all radioligand dose, enabling pre-treatment dose personalization—a critical step toward precision radiotheranostics.MethodsDynamic PET/CT scans obtained with 18F-DCFPyL over 22 min from six prostate cancer patients were used in this study. …”
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JiuZhou: open foundation language models and effective pre-training framework for geoscience by Zhou Chen, Ming Lin, Mingrun Zang, Zimeng Wang, Juanzi Li, Yuqi Bai

“…We introduce a two-stage pre-adaptation pre-training method to enhance the efficiency of knowledge learning and transfer in the model and demonstrated its effectiveness. …”
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Reinforcement learning-based assimilation of the WOFOST crop model by Haochong Chen, Xiangning Yuan, Jian Kang, Danni Yang, Tianyi Yang, Xiang Ao, Sien Li

“…Crop model assimilation is a crucial technique for improving the accuracy and precision of crop models by integrating observational data and crop models. Although conventional data assimilation methods such as Kalman filtering and variational methods have been widely applied, these methods often face limitations in data quality, model bias, and high computational complexity. …”
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Snow depth inversion and mapping at 500 m resolution from 1980 to 2020 in Northeast China using radiative transfer model and machine learning by Yanlin Wei, Xiaofeng Li, Lingjia Gu, Zhaojun Zheng, Xingming Zheng, Tao Jiang

“…Passive microwave (PMW) remote sensing is among the most effective methods for snow depth (SD) retrieval. However, significant uncertainties persist in SD retrieval and mapping due to snow characteristic variations, forest canopy interference, and low spatial resolution of PMW. …”
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Modified Model-Free Predictive Control for Reliable Operation of Multiple Parallel Grid-Forming Inverters by Mohamed Islam Grairia, Riad Toufouti, Z. M. S. Elbarbary, Mamadou-Bailo Camara, Abderahmane Abid, Shaik Mohammad Irshad, Hafiz Ahmed

“…Algebraic identification methods are typically used to estimate this unknown function. …”
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