Estimating the Growing Degree Days in the Northwest of Iran based on Climate Change Models by Hasan Zolfaghari, Jafar Masoompourv Samakosh, Shabnam Chahvari

“…For the little power of temporal and spatial distinction of this model, its outputs were downscaled using LARS-WG software and presented under Emission Scenarios including A1B (moderate scenario), A2 (maximum or pessimistic scenario), and B1 (minimum or optimistic scenario). …”
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Strengthening mycology research through coordinated access to microbial culture collection strains by D. Smith, A. Kermode, G. Cafà, A. G. Buddie, T. S. Caine, M. J. Ryan

“…This review provides an overview of the uses and outputs of collections that support work in mycology, agriculture and the environment. …”
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Toward GIC Forecasting: Statistical Downscaling of the Geomagnetic Field to Improve Geoelectric Field Forecasts by C. Haines, M. J. Owens, L. Barnard, M. Lockwood, C. D. Beggan, A. W. P. Thomson, N. C. Rogers

“…One solution that is widely used in climate science is “downscaling,” wherein sub‐grid variations are added to model outputs on a statistical basis. We present proof‐of‐concept results for a method that temporally downscales low‐resolution magnetic field data on a 1‐hr timescale to 1‐min resolution, with the hope of improving subsequent geoelectric field magnitude estimates. …”
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Waste Foundry Sand as Permeable and Low Permeable Barrier for Restriction of the Propagation of Lead and Nickel Ions in Groundwater by Ayad A. H. Faisal, Zaid Abed Al-Ridah, Laith A. Naji, Mu. Naushad, Hamed A. El-Serehy

“…This work aims to investigate the ability of using waste foundry sand (WFS) resulting as inexpensive by-product from steel industry in the low permeability barrier (LPB) and permeable reactive barrier (PRB) technologies for restriction of the movement of lead and nickel ions in the groundwater. Outputs of flask and tank tests certified that this material could capture these ions with sorption efficiency greater than 95% at time, pH, sorbent dosage, and speed equal to 60 min, 4 for lead and 6 for nickel, 2.5 g/100 mL, and 250 rpm, respectively. …”
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A Free-Space-Based Model for Predicting Peanut Moisture Content during Natural Drying by Xin Xu, Ying Sun, Yuanyuan Yin, Yiwei Xue, Fangyan Ma, Chao Song, Hang Yin, Liqing Zhao

“…The peanut dielectric constant, porosity, and bulk density were used as inputs and peanut kernel moisture as outputs. Support vector regression (SVR), extreme learning machine (ELM), sparrow search algorithm-support vector regression (SSA-SVR), and sparrow search algorithm-extreme learning machine (SSA-ELM) were used to create a prediction model of peanut kernel moisture content. …”
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A Workload Indicators of Staffing Need (WISN) based framework and implementation tool for dietitians at South African central and tertiary public hospitals by Vertharani Nolene Naicker, Jane W. Muchiri, Keshan Naidoo, Modiehi Heather Legodi

“…The tool’s calculated outputs were compared against the WISN software. Results Central and tertiary public hospitals were identified as the target facilities. …”
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A Novel Optimization Method Using the Box–Behnken Design Integrated with a Back Propagation Neural Network–Genetic Algorithm for Hydrogen Purification by Nannan Zhang, Sumeng Hu, Qianqian Xin

“…To explore a better optimization solution, a novel optimization method using machine learning with a back propagation neural network (BPNN) was then proposed, and a kind of heuristic algorithm–genetic algorithm (GA) was introduced to enhance the architecture of the BPNN. The predicted outputs of hydrogen production using two kinds of models based on the BPNN–GA and the BBD method integrated with the BPNN–GA (BBD–BPNN–GA). …”
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Simulation-based validation of a method to detect changes in SARS-CoV-2 reinfection risk. by Belinda Lombard, Harry Moultrie, Juliet R C Pulliam, Cari van Schalkwyk

“…The model parameters converged in most scenarios leading to model outputs aligning with anticipated outcomes. The model successfully detected changes in the risk of reinfection when such a change was introduced to the data. …”
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Towards global elimination of lymphatic filariasis: a systematic review of the application of spatial epidemiological methods to enhance surveillance and support elimination progra... by Angela Cadavid Restrepo, Colleen L Lau, Beatris Mario Martin, Helen J Mayfield

“…The most frequent model outputs were prevalence maps (17 studies, 27.9%), followed by risk maps based on environmental suitability (7 studies, 11.5%) and maps of the odds of seroprevalence being above a predetermined threshold (7 studies, 11.5%).Interpretation By demonstrating the applicability of spatial methods for investigating transmission drivers, identifying clusters and predicting hotspots, we highlight innovative ways in which spatial epidemiology has provided valuable evidence to support LF elimination. …”
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Toward a physics-guided machine learning approach for predicting chaotic systems dynamics by Liu Feng, Yang Liu, Benyun Shi, Jiming Liu

“…Specifically, our method consists of three key elements: a data-driven component (DDC) that captures dynamic patterns and mapping functions from historical data; a physics-guided component (PGC) that leverages the governing principles of the system to inform and constrain the learning process; and a nonlinear learning component (NLC) that effectively synthesizes the outputs of both the data-driven and physics-guided components. …”
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Improvement of Propeller Hydrodynamic Prediction Model Based on Multitask ANN and Its Application in Optimization Design by Liang Li, Yihong Chen, Lu Huang, Qing Hai, Denghai Tang, Chao Wang

“…The propeller’s comprehensive geometric features are used as inputs, and the coefficients of quadratic polynomials for the thrust coefficient (<i>K_T</i>) and torque coefficient (10<i>K_Q</i>) curves are predicted as outputs. The loss function is customized through a positive gradient penalty of the curves to accelerate training. …”
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Monitoring Urban Expansion and Loss of Agriculture on the North Coast of West Java Province, Indonesia, Using Google Earth Engine and Intensity Analysis by Laju Gandharum, Djoko Mulyo Hartono, Asep Karsidi, Mubariq Ahmad

“…The overall accuracy of Landsat image classification results for 2003, 2013, and 2020 were 88%, 87%, and 88%, respectively. IA outputs at interval levels for all categories showed that the annual change-of-area rate was higher during 2013–2020 than during 2003–2013. …”
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Exploring the development, evaluation and implementation of complex health interventions to prevent early childhood caries in preschool children: A scoping review protocol. by Peggy C J M van Spreuwel, Milou L C Munk-Overkamp, Linda C Smit, Kirsten A Ziesemer, Cor van Loveren, Geert J M G van der Heijden, Josef J M Bruers, Katarina Jerković-Ćosić

“…The results will be presented in tables, visual outputs, and a narrative summary in response to the review questions.…”
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Rapid Emulation of Spatially Resolved Temperature Response to Effective Radiative Forcing by Christopher B. Womack, Paolo Giani, Sebastian D. Eastham, Noelle E. Selin

“…We evaluate emulator performance across 5 CMIP6 experiments including the SSPs, demonstrating accurate emulation of global mean and spatially resolved temperature change with respect to CMIP6 ensemble outputs. Global mean relative error in emulated temperature averages 1.49% in mid‐century and 1.25% by end‐of‐century. …”
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Application of the Lasso regularisation technique in mitigating overfitting in air quality prediction models by Abbas Pak, Abdullah Kaviani Rad, Mohammad Javad Nematollahi, Mohammadreza Mahmoudi

“…The present investigation, using an extensive collection of data from 16 sensors in Tehran, Iran, from 2013 to 2023, focuses on applying the Least Absolute Shrinkage and Selection Operator (Lasso) regularisation technique to enhance the forecasting precision of ambient air pollutants concentration models, including particulate matter (PM2.5 and PM10), CO, NO2, SO2, and O3 while decreasing overfitting. The outputs were compared using the R-squared (R2), mean absolute error (MAE), mean square error (MSE), root mean square error (RMSE), and normalised mean square error (NMSE) indices. …”
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Creative-Motivated Citizen Science After-School STEAM Programme for Motivating Actions Related to the Oceanic Microplastics Problem by Tomomi Sayuda, Haruyuki Kinoshita, Fumitoshi Kato, Miles Pennington

“…Three creative project outputs were produced, and four MP data sampling sessions were conducted. …”
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A grey wolf optimization approach for evaluating the engine responses of various biodiesel blends in an internal combustion engine by Chukwuka Prosper Ozule, Adeyinka Oluwo, Nehemiah Sabinus Alozie, John Rajan, Swaminathan Jose, Sunday Ayoola Oke, Ugochukwu Sixtus Nwankiti

“…The results show that load demand and turbocharge boast air pressure have the least and highest values of engine outputs, respectively. The blend ratio had its highest values when optimized alongside the main injection duration. …”
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Dynamic transmission modeling of COVID-19 to support decision-making in Brazil: A scoping review in the pre-vaccine era. by Gabriel Berg de Almeida, Lorena Mendes Simon, Ângela Maria Bagattini, Michelle Quarti Machado da Rosa, Marcelo Eduardo Borges, José Alexandre Felizola Diniz Filho, Ricardo de Souza Kuchenbecker, Roberto André Kraenkel, Cláudia Pio Ferreira, Suzi Alves Camey, Carlos Magno Castelo Branco Fortaleza, Cristiana Maria Toscano

“…However, several other outputs were forecasted, such as the isolation/quarantine effect on transmission, hospital facilities required, secondary cases caused by infected children, and the economic effects of the pandemic. …”
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Drivers of success in global health outcomes: A content analysis of Exemplar studies. by Nadia Akseer, David E Phillips, Exemplars in Global Health Partner Network

“…Exemplars in Global Health (EGH) is a program that studies positive outlier countries that have made extraordinary progress in health outcomes (despite limited resources) and disseminates their successes through multiple types of outputs. To date, EGH has studied, or is studying, 14 global health topics in 28 countries. …”
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Human Posture Recognition and Estimation Method Based on 3D Multiview Basketball Sports Dataset by Xuhui Song, Linyuan Fan

“…The input is a randomly sampled point set, and after a layer of perceptron, it outputs a feature set of n × 16. Then, the feature set is sent to two network branches, one is to continue to use the perceptron method to generate the feature set of n × 1024, and the other network is used to extract the local features of points. …”
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