Expanding a Health Technology Solution to Address Therapist Challenges in Implementing Homework With Adult Clients: Mixed Methods Study by Brian E Bunnell, Kaitlyn R Schuler, Julia Ivanova, Lea Flynn, Janelle F Barrera, Jasmine Niazi, Dylan Turner, Brandon M Welch

“… BackgroundHomework is implemented with variable effectiveness in real-world therapy settings, indicating a need for innovative solutions to homework challenges. …”
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Impact of IgG subclass on monoclonal antibody developability by Paul Cain, Lihua Huang, Yu Tang, Victor Anguiano, Yiqing Feng

“…We thus conducted a systematic study of 12 mAbs derived from three sets of unrelated variable regions, each cloned into IgG1, an IgG1 variant with diminished effector functions, IgG2, and a stabilized IgG4 variant with further reduced FcγR interaction, to evaluate the impact of IgG subclass on manufacturability and high concentration stability in a common formulation buffer matrix. …”
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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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Application of machine learning and neural network models based on experimental evaluation of dissimilar resistance spot-welded joints between grade 2 titanium alloy and AISI 304 s... by Marwan T. Mezher, Alejandro Pereira, Rusul Ahmed Shakir, Tomasz Trzepieciński

“…The best prediction model was found to be the ANN model when training the conjugate gradient with the Polak-Ribiere updates (Traincgp) training function with the hyperbolic tangent sigmoid transfer function (Tansig) with the mean squared error (MSE) and correlation coefficient (R2) values recorded as 0.01886 and 0.94973, respectively. …”
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Research on the Inversion of Key Growth Parameters of Rice Based on Multisource Remote Sensing Data and Deep Learning by Jian Li, Jian Lu, Hongkun Fu, Wenlong Zou, Weijian Zhang, Weilin Yu, Yuxuan Feng

“…Dehui City in Jilin Province, China, was selected as the case study area, where multidimensional data including vegetation indices, ecological function parameters, and environmental variables were collected, covering seven key growth stages of rice. …”
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Spatiotemporal Analysis and Anomalous Trends of Asia AOD (2001–2024): Insights from a Deep Learning Fusion Model and EOF Decomposition by Yu Ding, Wenjia Ni, Jiaxin Dong, Jie Yang, Shiyao Meng, Siwei Li

“…To overcome these challenges, this study employs the deep learning model TabNet, incorporating Digital Elevation Model (DEM) data and ERA5 meteorological variables, to fuse MERRA-2 AOD with MODIS MAIAC AOD observations. …”
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Fokker-Planck Central Moment Lattice Boltzmann Method for Effective Simulations of Fluid Dynamics by William Schupbach, Kannan Premnath

“…This can be interpreted as a new path for the collision process in terms of the relaxation of the various central moments to “equilibria”, which we term as the Markovian central moment attractors that depend on the products of the adjacent lower order moments and a diffusion coefficient tensor, thereby involving of a chain of attractors; effectively, the latter are nonlinear functions of not only the hydrodynamic variables, but also the non-conserved moments; the relaxation rates are based on scaling the drift coefficient by the order of the moment involved. …”
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Effect of Pre-Trip Information in a Traffic Network with Stochastic Travel Conditions: Role of Risk Attitude by Yun Yu, Shiteng Zheng, Yuankai Li, Huaqing Liu, Jianan Cao

“…User equilibrium states of the two regimes have been analyzed, based on the canonical BPR travel time function with power coefficient <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>p</mi></mrow></semantics></math></inline-formula>. …”
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Serum Interleukin-6, Interleukin-17A, and transforming growth factor beta are raised in systemic sclerosis with interstitial lung disease by Anupam Wakhlu, Rasmi Ranjan Sahoo, Jyoti Ranjan Parida, Mohit K Rai, Durga P Misra, Vinita Agrawal, Vikas Agarwal

“…Serum IL-6, IL-17A and TGF β1 levels were assayed using ELISA kit and compared among disease subtypes and clinical parameters. Spearman coefficient was used to test correlation between continuous variables. …”
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PGTransNet: a physics-guided transformer network for 3D ocean temperature and salinity predicting in tropical Pacific by Song Wu, Senliang Bao, Wei Dong, Senzhang Wang, Xiaojiang Zhang, Chengcheng Shao, Junxing Zhu, Xiaoyong Li

“…Firstly, we design a loss function that deliveries the physical relationship among temperature, salinity and density by fusing the Thermodynamic Equation. …”
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Evaluation of ChatGPT-4 as an Online Outpatient Assistant in Puerperal Mastitis Management: Content Analysis of an Observational Study by Fatih Dolu, Oğuzhan Fatih Ay, Aydın Hakan Kupeli, Enes Karademir, Muhammed Huseyin Büyükavcı

“…However, evaluator variability and the subjective nature of assessments highlight the need for further optimization of AI tools. …”
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Distinctive Gait Variations and Neuroimaging Correlates in Alzheimer's Disease and Cerebral Small Vessel Disease by Xia Zhou, Wen‐Wen Yin, Chao‐Juan Huang, Si‐Lu Sun, Zhi‐Wei Li, Ming‐Xu Li, Meng‐Meng Ren, Ya‐Ting Tang, Jia‐Bin Yin, Wen‐Hui Zheng, Chao Zhang, Yu Song, Ke Wan, Yue Sun, Xiao‐Qun Zhu, Zhong‐Wu Sun

“…Gait metrics included the timed up and go (TUG) test, dual‐task TUG (DTUG) test, Berg balance scale (BBS), dual‐task cost (DTC), step length, gait speed, cadence and coefficient of variation of gait. The relationships among structural and perfusion variations, gait metrics and cognitive function were examined. …”
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IrrigApp: An Online Tool for Determining Crop Water Use and Evaluating Irrigation Scheduling Options by José O. Payero

“…., county, crop, soil type, start date, end date, irrigation applications, and irrigation efficiency). IrrigApp calculates daily crop evapotranspiration (ETc) and conducts a daily soil water balance to estimate several daily and seasonal variables, such as ETc under dryland and irrigated conditions, soil water content in the crop root zone, and water losses by runoff and deep percolation. …”
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Optimizing Load Frequency Control of Multi-Area Power Renewable and Thermal Systems Using Advanced Proportional–Integral–Derivative Controllers and Catch Fish Algorithm by Saleh A. Alnefaie, Abdulaziz Alkuhayli, Abdullah M. Al-Shaalan

“…Additionally, by contrasting the performance of the PID, PI, cascaded PI(PDN), and FOPID, PI(1+DD) controllers, the efficiency of the CFA is confirmed. Additionally, a sensitivity analysis that considers simultaneous modifications of the frequency bias coefficient (B) and speed regulation (R) within a range of ±25% validates the efficacy and dependability of the suggested CFA-tuned PI(1+DD). …”
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Bayesian inference for peak feature extraction and prediction of material property in X-ray diffraction data by Ryo Murakami, Taisuke T. Sasaki, Hideki Yoshikawa, Yoshitaka Matsushita, Keitaro Sodeyama, Tadakatsu Ohkubo, Hiroshi Shinotsuka, Kenji Nagata

“…We challenge peak feature extraction in the situation where only the peak function profile is known a priori, without knowledge of the measurement material or crystal structure factor. …”
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Fast 3D localization of nano-objects in wide-field interferometric scattering microscopy via vectorial diffraction model-derived analytical fitting by Liaoliao Wei, Caroline Livan Anyi, Huakun Li, Haitao Nie, Bihan Wen, Tong Ling

“…The simplified analytic function includes a quadratically scaling amplitude term and a linearly scaling phase term, both of which change with the nano-object’s axial position. …”
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Thermoelastic damping in piezothermoelastic nanobeam resonators under the strain gradient theory with micro-inertia and non-fourier heat conduction by Olha Hrytsyna, Maryan Hrytsyna

“…To account for small-scale effects, the Helmholtz free energy density is defined as a function of the strain tensor, strain gradient tensor, electric field vector, and temperature field, considering these parameters as independent state variables. …”
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Sensitivity Analysis of the Thermal Structure Within Subduction Zones Using Reduced‐Order Modeling by Gabrielle M. Hobson, Dave A. May

“…Our analysis highlights the strong effect of variability in the apparent coefficient of friction, with previously published ranges resulting in pronounced variability in estimated rupture limit depths.…”
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Commercial Vehicle Ride Comfort Optimization Based on Intelligent Algorithms and Nonlinear Damping by Shuilong He, Keren Chen, Enyong Xu, Wei Wang, Zhansi Jiang

“…The sum of the frequency-weighted RMS of the driver seat acceleration, the RMS of dynamic tyre load, and suspension working space is taken as the objective function in this article, using nonlinear damping coefficients and stiffness of suspension as design variables. …”
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Deep Learning Approaches for Morphological Classification of Intestinal Organoids by Giovanni Cicceri, Sebastiano Di Bella, Simone Di Franco, Giorgio Stassi, Matilde Todaro, Salvatore Vitabile

“…The use of deep learning (DL) in organoid image analysis becomes crucial to handle complexity, variability, and large amounts of data efficiently and accurately, overcoming the limitations of traditional image processing approaches. …”
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