Development of the Ward Nurses' Perspective-taking of the Staff Receiving Discharged Patients Scale: An observational study of ward nurses. by Shingo Tanaka, Masatoshi Saiki, Yukie Takemura

“…The goodness-of-fit indices were as follows: comparative fit index, 0.95; root mean square error of approximation, 0.08; and standardized root mean squared residual, 0.06. …”
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RMIS-Net: a fast medical image segmentation network based on multilayer perceptron by Binbin Zhang, Guoliang Xu, Yiying Xing, Nanjie Li, Deguang Li

“…The network incorporates layer normalization and dropout regularization to ensure training stability, complemented by Gaussian error linear unit (GELU) activation functions for improved non-linear modeling. …”
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Tri-manual interaction in hybrid BCI-VR systems: integrating gaze, EEG control for enhanced 3D object manipulation by Jian Teng, Jian Teng, Sukyoung Cho, Shaw-mung Lee

“…Experimental validation with eight participants across 160 trials demonstrated 87.5% virtual hand success rate and 41% spatial error reduction (σ = 0.23 mm vs. 0.39 mm) compared to traditional dual-hand control. …”
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Predictive modeling of hydrogen production and methane conversion from biomass-derived methane using machine learning and optimisation techniques by Adegboyega Bolu Ehinmowo, Bright Ikechukwu Nwaneri, Joseph Oluwatobi Olaide

“…The key process parameters studied include calcination temperature (450–600°C), time of calcination (3–8 h), specific surface area (5.4–249 m²/g), and pore volume (0.03–0.48 cm³/g); reduction temperature (500–700°C), time of reduction (1–5 h), and catalyst weight (0.05–1.00 g). …”
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Centralized Measurement Level Fusion of GNSS and Inertial Sensors for Robust Positioning and Navigation by Mohamed F. Elkhalea, Hossam Hendy, Ahmed Kamel, Ashraf Abosekeen, Aboelmagd Noureldin

“…Specifically, the TC algorithm demonstrated a remarkable reduction of over 90% in 2D position root mean square error (RMSE) and a 75% reduction in 3D position RMSE when compared to solutions utilizing the weighting matrix provided by Google with all visible satellites. …”
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A Convolutional Neural Network-Weighted Cellular Automaton Model for the Fast Prediction of Urban Pluvial Flooding Processes by Jiarui Yang, Kai Liu, Ming Wang, Gang Zhao, Wei Wu, Qingrui Yue

“…The predicted inundation spatial distribution and depth by CNN-WCA closely aligned with those of LISFLOOD-FP, with the mean absolute error concentrated within 5 mm, and the prediction time of CNN-WCA was only 0.8% that of LISFLOOD-FP. …”
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Case report: refractory atelectasis after infection of adenovirus and Mycoplasma Pneumoniae in an immunocompetent patient by Xuehua Xu, Hui Xu, Xiaoyun Jia, Huifeng Fan, Diyuan Yang, Dongwei Zhang, Gen Lu

“…The cellular analysis of the atrophic lung tissue showed a selective reduction in type I alveolar epithelial cells.…”
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Classifcation of events in information security systems based on neural networks by A. A. Mikryukov, A. V. Babash, V. A. Sizov

“…In such cases, it seems reasonable to build compositions of algorithms, mutually compensating errors of individual algorithms. The study also gives an insight into the application of neural network ensemble to address security issues in the corporate information system and provides a brief review of existing approaches to the construction of neural network ensembles and methods to shape problem solving with neural networks classifiers. …”
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A Combination of Classification Robust Adaptive Kalman Filter with PPP-RTK to Improve Fault Detection for Integrity Monitoring of Autonomous Vehicles by Hassan Elsayed, Ahmed El-Mowafy, Amir Allahvirdi-Zadeh, Kan Wang, Xiaolong Mi

“…Epoch-wise weighting adjustments in the robustness test create a more accurate stochastic model, aided by an adaptive unit weight variance (UWV) calculated with a sliding window, achieving a 7–28% UWV reduction. Three test scenarios with up to four simultaneous faults in code and phase observations, ranging from 1 to 200 m and 0.4 to 20 m, respectively, demonstrated successful identification and de-weighting of faults, resulting in maximum positioning errors of 6 mm (horizontal) and 11 mm (vertical). …”
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Physics-Informed Neural Networks for Enhanced State Estimation in Unbalanced Distribution Power Systems by Petros Iliadis, Stefanos Petridis, Angelos Skembris, Dimitrios Rakopoulos, Elias Kosmatopoulos

“…Notably, the PINN achieves up to a 97% reduction in current estimation errors while maintaining high voltage prediction accuracy. …”
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Achieving National Food Security in Sub‐Saharan African Countries: The Role of Foreign Agricultural Aid by Mehmet Balcilar, Godwin Olasehinde‐Williams, Berkan Tokar

“…Coefficients from the fixed effects and random effects with Driscoll–Kraay standard errors are also reported. Additionally, causal linkages between foreign agricultural aid and food security are examined through panel causality testing with bootstrapping. …”
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Surface Quality Monitoring and Improvement for Dimensional Metrology in Inline CT by Denoising with Neural Networks and Fast Surface Quality Metric by Faizan Ahmad, Ahmed Baraka, César Cardona-Marin, Steffen Kieß, Dominik Wolfschläger, Robert H. Schmitt, Sven Simon

“…This metric demonstrates a strong correlation with measurement errors associated with surface quality degradation due to noise. …”
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Atmospheric horizontal gradients measured with eight co-located GNSS stations and a microwave radiometer by T. Ning, G. Elgered

“…Using a weak constraint enhances the GNSS estimates to track large gradients of short duration at the cost of increased formal errors. To mitigate random noise in the GNSS gradients, we adopted a fusion approach, averaging estimates from the GNSS stations. …”
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Energy Management and Edge-Driven Trading in Fractal-Structured Microgrids: A Machine Learning Approach by Mostafa Pasandideh, Jason Kurz, Mark Apperley

“…Leveraging incremental learning capabilities, the proposed model continuously updates, achieving robust predictive performance with mean absolute errors (MAE) across individual households and the community of less than 10% of typical hourly consumption values. …”
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Coupling a high-Q resonator to a spin qubit with all-electrical control by Rafael S. Eggli, Taras Patlatiuk, Eoin G. Kelly, Alexei Orekhov, Gian Salis, Richard J. Warburton, Dominik M. Zumbühl, Andreas V. Kuhlmann

“…Our experiments show that qubit control pulses with their broad range of higher harmonics ring up the tank when the control pulse spectrum overlaps with the tank resonance. This can cause a reduction of the readout visibility if the tank ringing amplitude exceeds the excited state splitting of the quantum dot, lifting Pauli spin blockade and thus leading to state preparation and measurement errors. …”
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Forecasting monthly residential natural gas demand in two cities of Turkey using just-in-time-learning modeling. by Burak Alakent, Erkan Isikli, Cigdem Kadaifci, Tonguc S Taspinar

“…The JITL-GPR method is easy to use and optimize, and offers a reduction in forecast errors compared to traditional time series methods and a state-of-the-art combination model; therefore, it is a promising tool for NGD forecasting in similar settings.…”
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Study of a face stepped milling cutter for finishing flat surfaces by H.M. Vyhovskyi, M.M. Plysak, Y.O. Koval

“…The proposed cutter design, with a finishing insert operating in the axial direction and maintaining elastic contact with a stationary profile follower, allows for compensation of elastic deformations, stabilization of the insert position, and reduction of machining errors. The obtained results can be used to optimize face milling cutter designs and machining parameters in order to improve machining accuracy and surface quality during milling operations.…”
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Estimating the Within-Person Change in Dental Service Access Measures during the COVID-19 Pandemic in the United States by Jason Semprini

“…By constructing a probability-weighted linear regression model with fixed-effects, we estimated the average within-person change from 2019 to 2020. Robust standard errors were clustered within each respondent. Results. …”
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RATIONING OF FUEL CONSUMPTION WITH THE USE OF INFORMATION TECHNOLOGY by V. M. Kurganov, A. N. Dorofeev, M. V. Gryaznov

“…However, the normalization of fuel consumption is difficult due to the high probability of errors by the manual calculation. Currently, there is no methodology for determining the correction factors for taking into account the existing operating conditions for the stock of vehicles.Materials and methods. …”
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The tug of war: will regulatory quality and green innovation outpace carbon emissions? by Raphael Ampedu, Xiongyuan Wang, Kihumuro Jotham, Richmond Mensah

“…The factors influencing emissions reduction in the region are investigated using PMG, GEE, Quantile regression, Panel Corrected Standard Errors (PCSE), and Two Step System Generalized Method of Moments (GMM) for robustness. …”
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