Precursors of interactional value formation through digital banking interactions [version 1; peer review: 2 approved] by Ramya Tauh, Savitha Basri

“…A quantitative approach was adopted through a survey questionnaire to gather the responses. The data gathered was analyzed using SmartPLS 4.0 software. …”
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Birthing parent and companion verbal reactions following interactions with inpatient postpartum health care team members: an observational study using naturalistic filming by Maggie Mangas, Neha Simran Saggi, Marisue Peralta Macias, Alison M. Stuebe, Kristin P. Tully

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LiMMCov: An interactive research tool for efficiently selecting covariance structures in linear mixed models using insights from time series analysis. by Perseverence Savieri, Lara Stas, Kurt Barbé

“…The correct specification of covariance structures in linear mixed models (LMMs) is critical for accurate longitudinal data analysis. These data, characterised by repeated measurements on subjects over time, demand careful handling of inherent correlations to avoid biased estimates and invalid inferences. …”
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Analysis on hydrodynamic interaction of two floating bodies with different dimensions using a hybrid two-way coupled field-domain decomposition method by Fujian LI, Xueqin LIU, Dan LI, Wei MENG, Zhuang KANG

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Study of the interaction of the GSB-106 BDNF neurotrophin dipeptide mimetic with the TrkB tyrosine kinase receptor using surface plasmon resonance technology by A. V. Tarasiuk, Y. V. Mezentsev, O. V. Gnedenko, P. Yu. Povarnina, A. S. Ivanov

“…The interaction of the neurotrophin BDNF dipeptide mimetic, compound GSB-106, with the tyrosine kinase TrkB receptor specific for the fullsized neurotrophin was studied using surface plasmon resonance. …”
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Meso-Alpha Scale Tropospheric Interactions within the Western Mediterranean Basin: Statistical Results Using 15-Year NCEP/NCAR Reanalysis Dataset by J. L. Palau, F. Rovira

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Elucidating Interpersonal Cardiac Synchrony During a Naturalistic Social Interaction Using Dyadic Poincaré Plot Analysis by Karly S. Franz, Sanaz Rezaei, Tom Chau

“…While a variety of physiological signals are used to investigate synchrony, heartrate variability (HRV) has emerged as a valuable indicator of autonomic coordination between interacting participants. …”
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Capturing the complexity of child behavior and caregiver-child interactions in the HEALthy Brain and Child Development (HBCD) Study using a rigorous and equitable approach by Renee C. Edwards, Elizabeth M. Planalp, Michelle Bosquet Enlow, Natacha Akshoomoff, Stefanie C. Bodison, Marianne B. Brennan, Lucia Ciciolla, Rina D. Eiden, Courtney A. Fillipi, Hanna C. Gustafsson, Lorraine M. McKelvey, Amanda S. Morris, Myriam Peralta-Carcelén, Julie Poehlmann, Lauren S. Wakschlag, Sylia Wilson

“…Multi-level-observational and caregiver-report measures were deemed necessary for capturing the desired constructs across multiple contexts while balancing the nuance of observational data with pragmatic considerations. WG-BEH prioritized developmentally sensitive, validated assessments with psychometrics supporting use in diverse populations and focused on mechanistic linkages and prediction of desired constructs. …”
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Examining the association between maternal prenatal psychiatric disorders and behavioural problems among offspring in early childhood: population-based study by Amy Braddon, Rosa Alati, Kim S. Betts

“…Aims To assess whether there is an association between prenatal maternal psychiatric disorders and offspring behavioural problems in early childhood, using linked health administrative data and the Australian Early Development Census from New South Wales, Australia. …”
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Numerical Study of Air Cushion Effect in Notched Disk Water Entry Process Using Structured Arbitrary Lagrangian–Eulerian Method by Zhe Zhang, Nana Yang, Jinlong Ju, Xingzhi Bai, Houcun Zhou, Wenhua Wu

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Evaluation of changes in prediction modelling in biomedicine using systematic reviews by Lara Lusa, Franziska Kappenberg, Gary S. Collins, Matthias Schmid, Willi Sauerbrei, Jörg Rahnenführer, on behalf of the Topic Group for High-dimensional data of the STRATOS initiative

“…It is suggested that machine learning techniques are becoming more popular to develop prediction models to exploit complex data structures, higher-dimensional predictor spaces, very large number of participants, heterogeneous subgroups, with the ability to capture higher-order interactions. …”
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“Let me hear what you’re needing”: exploring how HIV providers conceptualize patient-provider interactions with people with HIV who use drugs using a harm reduction framework by Stephanie L. Creasy, James E. Egan, Sarah Krier, Jessica Townsend, Jessica Ward, Mary Hawk, Emma Sophia Kay

“…Design: We used a qualitative descriptive design to characterize HCWs’ descriptions of their interactions with PWH who use drugs. …”
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Lessons Learned From European Health Data Projects With Cancer Use Cases: Implementation of Health Standards and Internet of Things Semantic Interoperability by Amelie Gyrard, Somayeh Abedian, Philip Gribbon, George Manias, Rick van Nuland, Kurt Zatloukal, Irina Emilia Nicolae, Gabriel Danciu, Septimiu Nechifor, Luis Marti-Bonmati, Pedro Mallol, Stefano Dalmiani, Serge Autexier, Mario Jendrossek, Ioannis Avramidis, Eva Garcia Alvarez, Petr Holub, Ignacio Blanquer, Anna Boden, Rada Hussein

“…These initiatives aim to enhance the analysis of heterogeneous health data while aligning with EHDS implementation, specifically for the EHDS for the secondary use of data (EHDS2). …”
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Multi-Index Assessment and Machine Learning Integration for Drought Monitoring Using Google Earth Engine by Xulong Duan, Rana Waqar Aslam, Syed Ali Asad Naqvi, Dmitry E. Kucher, Zohaib Afzal, Danish Raza, Rana Muhammad Zulqarnain, Yahia Said

“…This study advances multisensor remote sensing data fusion integrating optical (Sentinel-2, MODIS), thermal (LST), and hydrological (SMAP) sensors with climate datasets to evaluate soil moisture dynamics at five depths (0–50 cm) across nine agricultural zones (October 2021–September 2023), leveraging AI and machine learning to address data quality challenges in heterogeneous sensor inputs. …”
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Identifying Ring Galaxies in DESI Legacy Imaging Surveys Using Machine Learning Methods by Aina Zhang, Xiaoming Kong, Bowen Liu, Nan Li, Yude Bu, Zhenping Yi, Meng Liu

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Reinforcement Learning-Driven Path Generation for Ankle Rehabilitation Robot Using Musculoskeletal-Informed Energy Optimization by Naveed Ahmad Khan, Prashant K. Jamwal, Fahad Hussain, Mergen H. Ghayesh, Shahid Hussain

“…The methodology is validated using data from ten stroke patients, demonstrating its potential to enhance rehabilitation effectiveness by promoting more natural, efficient, and physiologically accurate movement trajectories.…”
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Comparative Analysis of the Impact of Built Environment and Land Use on Monthly and Annual Mean PM_2.5 Levels by Anjian Song, Zhenbao Wang, Shihao Li, Xinyi Chen

“…It utilizes gridded monthly and annual mean PM_2.5 data from 2019 as the dependent variable. The research selects 33 independent variables from the perspectives of the built environment and land use. …”
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Finger tracking for wearable VR glove using flexible rack mechanism by Roshan Thilakarathna, Maroay Phlernjai

“…We employed the Gage Repeatability and Reproducibility to analyze and interpret the repeatable data. Furthermore, we integrated the gloves into a SteamVR home environment using the OpenGlove auto-calibration tool. …”
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Spatiotemporal Characterization of Solar Radiation in a Green Dwarf Coconut Intercropping System Using Tower and Remote Sensing Data by Gabriel Siqueira Tavares Fernandes, Breno Rodrigues de Miranda, Luis Roberto da Trindade Ribeiro, Matheus Lima Rua, Maryelle Kleyce Machado Nery, Leandro Monteiro Navarro, Joshuan Bessa da Conceição, João Vitor de Nóvoa Pinto, Vandeilson Belfort Moura, Alexandre Maniçoba da Rosa Ferraz Jardim, Samuel Ortega-Farias, Paulo Jorge de Oliveira Ponte de Souza

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GCN-Transformer: Graph Convolutional Network and Transformer for Multi-Person Pose Forecasting Using Sensor-Based Motion Data by Romeo Šajina, Goran Oreški, Marina Ivašić-Kos

“…Multi-person pose forecasting involves predicting the future body poses of multiple individuals over time, involving complex movement dynamics and interaction dependencies. Its relevance spans various fields, including computer vision, robotics, human–computer interaction, and surveillance. …”
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