Deep Learning-Based Imagery Style Evaluation for Cross-Category Industrial Product Forms by Jianmin Zhang, Yuliang Li, Mingxing Zhou, Sixuan Chu

“…Validation on 40 product types confirms strong cross-category generalization with a root mean square error (RMSE) of 0.26. Visualization through feature maps and Gradient-weighted Class Activation Mapping (Grad-CAM) further verifies the accuracy and interpretability of the ISE model. …”
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Bootstrapping the Quantum Hall Problem by Qiang Gao, Ryan A. Lanzetta, Patrick Ledwith, Jie Wang, Eslam Khalaf

“…We also show that, by combining the bootstrap lower bounds with variational Monte Carlo calculations for various quantum Hall states, we can obtain two-sided bounds on the ground state energy that rigorously bounds the error to below a few percentage for large system sizes where exact diagonalization is not accessible. …”
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Optical Correction of Keratoconus with a Scleral Gas-Permeable Lenses by A. V. Myagkov, Yu. B. Slonimskiy, E. V. Belousova, T. S. Mitichkina, L. R. Bunyatova

“…Contact lens vision correction is the main way to correct the refractive error resulting from keratoconus. However, the use of corneal gas permeable or soft contact lenses cannot provide high quality vision, additionally causing discomfort associated with their excessive mobility. …”
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A Novel Dynamical Framework for Crop Phenology Estimation With Remote Sensing by Lucio Mascolo, Tomas Martinez-Marin, Juan M. Lopez-Sanchez

“…Accordingly, the nonstationary transition matrix is defined to characterize the transitions between discrete phenological stages in numerical scale. …”
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DEMOGRAPHY OF ALPINE SHORT-LIVED PLANTS, LONGEVITY AND ONTOGENY STAGE DURATIONS by E. S. Kazantseva, V. G. Medvedev, V. G. Onipchenko

“…We found out that the lifespan of Anthyllis vulneraria is 2.6±0.3 years (hereinafter “±” is Standard error), Draba hispida – 4.5±0.3, Murbeckiella huetii – 4.6±1.1, Carum meifolium – 7.8±1.4, Eritrichium caucasicum – 9.1±1.4, Trifolium badium – 10.3±2.6, Sedum tenellum – 11±2.05, Androsace albana – 12.1±2.5, Minuartia recurva – 22.9±4.5. …”
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Features of Measuring the Hardness of a Metal Surface Modified with Ultrafine Particles of Minerals by A. V. Skazochkin, G. G. Bondarenko, P. Żukowski

“…By the method of instrumental hardness, standard measurements were performed without preliminary selection of the indentation site (at a load of 1.05 N) and measurements during indentation into even sections (at low loads of 10 mN).It is noted that the high precision of measurements implemented by instrumental indentation, due to the large roughness of the samples, leads to large values of the error in calculating the measurement results. An additional difference in the results of measurements performed by two methods at shallow indentation depths may be due to the fact that the object under study has a complex structure consisting of a metal matrix and particles distributed over the depth of the sample. …”
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A model of anaerobic tissue perfusion during trauma-Lactate trajectory curvature can determine recovery. by Austin Baird, Steven A White, Erika K Bisgaard, Rachel K Wentz, Edward M Sims, David Hananel

“…Finally, we fit a logistic curve to the resulting data for a quick patient severity tool and denote the standard error of parameterization based on the delta method.…”
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Evaluation of nurses’ perspectives on the design and use of assistant nurse robots in obstetrics and neonatal care: a mixed-method study by Özen İnam, Samet Okay

“…Qualitative analysis findings reveal positive perceptions regarding the robots’ potential to reduce error rates, enhance patient safety, and alleviate workload. …”
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Development of Production-Forecasting Model Based on the Characteristics of Production Decline Analysis Using the Reservoir and Hydraulic Fracture Parameters in Montney Shale Gas R... by Hyeonsu Shin, Viet Nguyen-Le, Min Kim, Hyundon Shin, Edward Little

“…The mean absolute percentage error on history matching was 5.28% and 6.23% for the forecasting model and numerical simulator, respectively. …”
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Anti-Jamming RIS Communications Using DQN-Based Algorithm by Pham Duy Thanh, Hoang Thi Huong Giang, Ic-Pyo Hong

“…As a result, the optimal resource allocation is achieved through trial-and-error interactions with environment by observing the predefined rewards and the network state transition. …”
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Analysis of installed photovoltaic capacity in Mexico: A systems dynamics and conformable fractional calculus approach by Jorge Manuel Barrios-Sánchez, Roberto Baeza-Serrato, Leonardo Martínez-Jiménez

“…The primary goal is to address the need to model energy transitions accurately and realistically, considering Mexico's advantages in renewable energy, particularly solar power. …”
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Enhancing phase change thermal energy storage material properties prediction with digital technologies by Minghao Yu, Jing Liu, Cheng Chen, Mingyue Li

“…Traditional experimental approaches, while effective, are resource-intensive and time-consuming, often requiring extensive trial-and-error methods. To address these limitations, the integration of digital technologies, such as computational modeling and machine learning (ML), has become increasingly important.MethodsThis paper proposes a hybrid multiscale modeling framework that integrates molecular dynamics (MD) simulations, finite element methods (FEM) from continuum mechanics, and supervised ML algorithms—including deep neural networks and gradient boosting regressors—to enable accurate and efficient prediction of material properties across scales. …”
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AI-Based Forecasting in Renewable-Rich Microgrids: Challenges and Comparative Insights by Martins Osifeko, Josiah Lange Munda

“…Our results show that Bidirectional-Long Short-term Memory (Bi-LSTM) achieved the best demand and PV forecasting performance with a Root Mean Square Error (RMSE) / R2 of 303.95, Megawatt MW/ 0.9877 and 48.04 MW / 0.996, while XGBoost delivered a competitive accuracy for PV (RMSE: 49.74 MW, R2: 0.996) and Wind (RMSE: 119.77 MW, R2: 0.964). …”
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A latent Markov modelling approach to the evaluation of circulating cathodic antigen strips for schistosomiasis diagnosis pre- and post-praziquantel treatment in Uganda. by Artemis Koukounari, Christl A Donnelly, Irini Moustaki, Edridah M Tukahebwa, Narcis B Kabatereine, Shona Wilson, Joanne P Webster, André M Deelder, Birgitte J Vennervald, Govert J van Dam

“…We present a discrete Markov chains modelling framework that deals with the longitudinal study design and the measurement error in the diagnostic methods under study. A longitudinal detailed dataset from Uganda, in which one or two doses of PZQ treatment were provided, was analyzed through Latent Markov Models (LMMs). …”
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Application of the generalized point source method for solving boundary value problems of mathematical physics by Sergey Yu. Knyazev, Elena E. Shcherbakova

“…The dependences of the numerical solution error on the number of linear equations in the resulting system are obtained. …”
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Impact of a USMLE Step 2 Prediction Model on Medical Student Motivations by Anthony Shanks, Ben Steckler, Sarah Smith, Debra Rusk, Emily Walvoord, Erin Dafoe, Paul Wallach

“…PURPOSE With the transition of USMLE Step 1 to Pass/Fail, Step 2 CK carries added weight in the residency selection process. …”
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Multi-heat keypoint incorporation in deep learning model to tropical cyclone centering and intensity classifying from geostationary satellite images by Thanh-Ha Do, Son-The Phan, Duc-Tien Du, Dinh-Quan Dang, Khanh-Hung Mai, Lars R. Hole

“…The proposed MHKD can help reduce the over-estimate rate for the TD grade and under-estimate rates for TS and STS grades, and most notably, the TC center localization yielded an average error of approximately 34 km with a single keypoint or one head attention network (One ATTN) and around 27 km when using three head attention network (Three ATTN).…”
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Technological Advancements and Economic Growth as Key Drivers of Renewable Energy Production in Saudi Arabia: An ARDL and VECM Analysis by Faten Derouez

“…This study examines the short- and long-term effects of various economic, environmental, and policy factors on renewable energy production (REP) in Saudi Arabia from 1990 to 2024, using the Autoregressive Distributed Lag (ARDL) approach and Vector Error Correction Model (VECM) techniques. The analysis focuses on fossil fuel consumption (FFC), renewable energy investment (REI), carbon emissions (CEs), energy prices (EPs), government policies (GPs), technological advancements (TAs), socioeconomic factors (SEFs), and economic growth (EG) as determinants of REP, measured as electricity generated from solar power sources in kilowatt-hours (kWh). …”
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Food Security–Renewable Energy Nexus: Innovations and Shocks in Saudi Arabia by Nourah A. Althani, Raga M. Elzaki, Fahad Alzahrani

“…We use the time series annual data covering the period (2000–2022) analyzed by applying the Vector Autoregressive (VAR) model system and its environment, Granger causality, the forecast-error variance decompositions (FEVD), and the impulse response functions (IRFs). …”
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Digital twin manifesto for the pathology laboratory by Albino Eccher, Fabio Pagni, Massimo Dominici, Luca Reggiani Bonetti, Stefano Marletta, Enrico Munari, Giorgio Cazzaniga, Anil V Parwani, Vincenzo L’Imperio, Angelo Paolo Dei Tos

“…The framework highlights measurable gains such as up to 90% reduction in labeling errors, 20–30% improvements in slide quality, and 30–50% reductions in diagnostic turnaround time. …”
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