Assessing motor control and movement quality in patients with non-specific low back pain: a scoping review and development of an ICF-based conceptual framework by Kerstin Luedtke, Agnes Sturma, Georg Pfluegler, Meike Klinger, Clemens Ley, Beate Schüßler

“…A conceptual framework was constructed, consisting of five International Classification of Functioning, Disability and Health-based broad motor control functions and 10 movement quality domains, namely flexibility, stability, accuracy, symmetry, speed, smoothness, adaptability, variability, efficiency and coordination.Conclusion The provided conceptual framework for motor control functions and movement quality domains can serve as a structural foundation for future research on the content validity of assessment approaches in the context of LBP.…”
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Field Testing of a Smart Geomat Based on Fiber Optic Sensors and Sensor Fusion for Levee Monitoring by Manuel Bertulessi, Francesca Ceccato, Francesco Ioli, Federico Barbieri, Livio Pinto, Paolo Simonini, Giovanni Menduni

“…ABSTRACT Real‐time monitoring of the functionality of river embankments, especially during flood events, is an increasingly important topic in the new scenario outlined by climate change. …”
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Cumulative Distribution-Based Method for Pavement Performance Modeling by Chenhao Tu, Wenya Ye, Rui Zhang, Xudong Qian, Qun Yang

“…Predicting future pavement conditions accurately and efficiently helps determine the optimal maintenance time, select appropriate measures, and allocate rehabilitation funds effectively. …”
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Changes in AXL and/or MITF melanoma subpopulations in patients receiving immunotherapy by M. Willemsen, J. Bulgarelli, S.K. Chauhan, R.R. Lereim, D. Angeli, G. Grisendi, G. Krebbers, I. Davidson, J.A. Kyte, M. Guidoboni, R.M. Luiten, W.J. Bakker

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Exploring Machine Learning Models for Vault Safety in ICL Implantation: A Comparative Analysis of Regression and Classification Models by Qing Zhang, Qi Li, Zhilong Yu, Ruibo Yang, Emmanuel Eric Pazo, Yue Huang, Hui Liu, Chen Zhang, Salissou Moutari, Shaozhen Zhao

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Bottom-up Biomaterial strategies for creating tailored stem cells in regenerative medicine by Brenda Cruz-Gonzalez, Ellie Johandes, Dominique Gramm, Donny Hanjaya-Putra, Donny Hanjaya-Putra, Donny Hanjaya-Putra, Donny Hanjaya-Putra

“…By replicating lineage-specific mechanical, chemical, and spatial cues, these tailored biomaterials enhance differentiation fidelity, reprogramming efficiency, and functional integration. This paradigm shift from passive scaffolds to dynamic, cell-instructive platforms bridges critical gaps between laboratory success and clinical translation, offering a transformative roadmap for regenerative medicine and tissue engineering.…”
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Elucidating the role of mind–body connection profiles in emotional reactivity and regulation amongst typically developed adults by Kristen Van Bael, Jessica Scarfo, Emra Suleyman, Michelle Ball

“…Abstract Background Adaptive emotional functioning necessitates a strong mind–body connection. …”
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Toward generalizable prediction of antibody thermostability using machine learning on sequence and structure features by Ameya Harmalkar, Roshan Rao, Yuxuan Richard Xie, Jonas Honer, Wibke Deisting, Jonas Anlahr, Anja Hoenig, Julia Czwikla, Eva Sienz-Widmann, Doris Rau, Austin J. Rice, Timothy P. Riley, Danqing Li, Hannah B. Catterall, Christine E. Tinberg, Jeffrey J. Gray, Kathy Y. Wei

“…In this work, we show two machine learning approaches – one with pre-trained language models (PTLM) capturing functional effects of sequence variation, and second, a supervised convolutional neural network (CNN) trained with Rosetta energetic features – to better classify thermostable scFv variants from sequence. …”
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Importance Analysis of Vegetation Change Factors in East Africa Based on Machine Learning by Zhang Xiumei, Ma Bo, Zhang Yijie

“…The independent treatment variables were two climatic factors and five human activity factors affecting vegetation changes in East Africa. …”
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Optimized Temporal Interference Stimulation Based on Convex Optimization: A Computational Study by Chao Geng, Yang Li, Long Li, Xiaoqi Zhu, Xiaohan Hou, Tian Liu

“…CVXTI leverages the distribution characteristics of the TI envelope electric field to optimize electrode configurations, enhancing the optimization efficiency.…”
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Multi-Scale Multi-Domain Hybrid Finite Element Modeling of Light Propagation by Jingwei Wang, Zhanwen Wang, Lida Liu, Yuntian Chen

“…We revisit finite element method of modeling multi-scale photonic/electromagnetic devices via the proposed beam basis function, in combination with domain decompositions. …”
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HEE-SegGAN: A holistically-nested edge enhanced GAN for pulmonary nodule segmentation. by Yong Wang, Seri Mastura Mustaza, Mohammad Syuhaimi Ab-Rahman, Siti Salasiah Mokri

“…Compared to traditional 3D methods, our approach extracted features more efficiently while preserving spatial information and reducing computational requirements. …”
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Forecasting water quality indices using generalized ridge model, regularized weighted kernel ridge model, and optimized multivariate variational mode decomposition by Marjan Kordani, Mohsen Bagheritabar, Iman Ahmadianfar, Arvin Samadi-Koucheksaraee

“…Statistical metrics confirmed that the proposed OMVMD-GRKR model, concerning the best efficiency in the Ahvaz (R = 0.987, RMSE = 0.761, and U95% = 2.108) and Molasani (R = 0.963, RMSE = 1.379, and U95% = 3.828) stations, outperformed the OMVMD and simple-based methods such as ridge regression (Ridge), least squares support vector machine (LSSVM), deep random vector functional link (DRVFL), and deep extreme learning machine (DELM). …”
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Smart Fermentation Technologies: Microbial Process Control in Traditional Fermented Foods by Chong Shin Yee, Nur Asyiqin Zahia-Azizan, Muhamad Hafiz Abd Rahim, Nurul Aqilah Mohd Zaini, Raja Balqis Raja-Razali, Muhammad Ameer Ushidee-Radzi, Zul Ilham, Wan Abd Al Qadr Imad Wan-Mohtar

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Study on a Quantitative Evaluation Method of Goaf Instability Risk of Phosphate Deposits in Layered Rock Mass by Dongfang CHEN, Mengke WANG, Dingping XU, Haiwang YE, Qizhou WANG, Jian LIU, Bin XIANG

“…The Hermite random polynomial coefficients between the input field of c and <italic>ϕ</italic>_j and the output field of the FAI are solved by the probability collocation method, establishing an explicit function expression between the probability collocation point and the FAI. …”
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The operational municipal solid waste management policy focuses on identifying waste generation behavior across multiple levels in mega cities, a case study by Hamed Alimoradiyan, Ahmad Hajinezhad, Hossein Yousefi, Mario Giampietro

“…Abstract The results of an effort to create a thorough framework that efficiently arranges and combines quantitative data characterizing the performance of Urban Waste Management Systems (UWMS) across a range of scales and dimensions are presented in this study. …”
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Structural Parameter Identification Using Multi-Objective Modified Directional Bat Algorithm by LIU Li-jun, LIN Ying-hai, SU Yong-hui, LEI Ying

“…This approach improved the accuracy and robustness of structural parameter identification while maintaining computational efficiency.MethodsMOMDBA is an enhanced version of the Directional Bat Algorithm （DBA）， a swarm intelligence optimization technique inspired by the echolocation behavior of bats. …”
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Cross-sectional associations between physical activity and sedentary time with cardiovascular health in children from the ALSPAC study using compositional data analysis by K. M. Sansum, B. Bond, R. M. Pulsford, A. McManus, A. O. Agbaje, A. M. Skinner, A. R. Barker

“…Abstract This study adopted a compositional framework to cross-sectionally examine the associations between physical activity (PA) and sedentary time (ST) with vascular structure and function and clustered cardiovascular disease (CVD) risk factors in 4277 children (2,226 girls), aged 10.6±0.2 years. …”
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Strong Amplitude Modulation of Hard-band X-Ray Quasiperiodic Oscillation with Soft-band Flux in RE J1034+396 by Ruisong Xia, Hao Liu, Yongquan Xue

“…They are highly correlated, with an average cross-correlation function (CCF) peak coefficient of 0.61 and a lag of approximately 3 ks. …”
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Long-term evolution of the calibration constant on a mobile water vapour Raman lidar by P. Chazette, J. Totems, F. Laly

“…We note that the use of ground-based measurements does not introduce any more uncertainty in the lidar calibration coefficient than vertical profiles obtained by radiosondes or airborne means. …”
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