INDICATORS AND REGIONAL PLANNING: PROMULGATE A COHERENCE by Iuli Nascimento

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Low-cycle fatigue life prediction method for stud connectors based on interpretable machine learning by Jianan Pan, Xiaoling Liu, Bing Wang, Ying Liu

“…However, traditional theoretical formulas and experimental methods suffer from limitations such as low accuracy and individual variability. This study aims to develop a high-precision prediction model for low-cycle fatigue life using machine learning methods, providing a new approach for material performance evaluation. …”
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The Impact of Students' Motivational Drive and Attitude toward Online Learning on Their Academic Engagement during the Emergency Situation by Audi Yundayani, Yatha Yuni, Fiki Alghadari

“…In addition, the Confirmatory Factor Analysis (CFA) method was employed to assess the reflective measurement models. This included the internal consistency (Cronbach's alpha, composite reliability), the convergent validity encompassed indicator reliability and average variance extracted (AVE), and the discriminant validity conducted using the cross-loadings approach and the Fornell-Larcker criterion. …”
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A MATHEMATICAL APPROACH TO INVESTMENT WITH CHARGE ON BALANCE AND VOLUNTARY CONTRIBUTIONS UNDER WEIBULL MORTALITY FORCE FUNCTION by Edikan Edem Akpanibah, Peter Benneth, Ase Matthias Esabai

“…To achieve this, there is need to develop an optimal portfolio which considers the volatility of the stock market price consisting of one risk-free asset and a risky asset which follows the Heston volatility model (HVM). Also, the portfolio considers additional voluntary contributions (AVC) by members, tax on the stock market price, charge on balance (CB), and the mortality risk of the pension scheme members (PSM) modeled by the Weibull mortality force function.  …”
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Critical Factors Governing the Frictional Coefficient in Mg Alloys—Learn From Machine Learning by Negar Bagherieh, Moslem Noori, Dongyang Li, Meisam Nouri

“…The collected data is then used to train models for the following two scenarios: (i) COF prediction using composition, processing parameters, and tribological variables; (ii) COF prediction using mechanical properties (hardness, yield strength, ultimate tensile strength, ductility, and elastic modulus), and tribological variables. …”
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Prediction of the digestibility and digestible energy content of hay for horses using an enzymatic degradability method by D. Andueza, W. Martin-Rosset

“…The incorporation of chemical composition variables as independent variables into the prediction models did not result in a meaningful improvement in the model results obtained from dCS and dCO. …”
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Experimental study on DEM parameters calibration for organic fertilizer by the particle swarm optimization − backpropagation neural networks by Fandi Zeng, Limin Liu, Yinzeng Liu, Hongbin Bai, Chunxiao Li, Zhihuan Zhao

“…The previously identified important variables were optimized by the Central Composite Design test. …”
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Biomod2 for evaluating the changes in the spatiotemporal distribution of Locusta migratoria tibetensis Chen in the Qinghai-Tibet Plateau under climate change by Rulin Wang, Nier Wu, Zhaopeng Shi, Chao Li, Na Jiang, Chun Fu, Mingtian Wang

“…[Method] Utilizing 68 geographical distribution points of L. migratoria tibetensis, in conjunction with 6 environmental variables, a composite model was developed employing the Biomod2 software package to simulate potential shifts in the spatial distribution of L. migratoria tibetensis under future climate scenarios. …”
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Assessing Digital Performance of Public Services in the EU: E-Governance and Technology Integration by Oana Ramona Lobonț, Cristina Criste, Alexandra Ioana Vintilă, Andreea Florentina Crăciun, Nicoleta Claudia Moldovan

“…To evaluate the digital performance of the European Union regions, the analysis employs the following methods: (i) Principal Component Analysis to construct a composite Institutional Quality Index based on governance indicators, (ii) Gaussian graphical models to assess the relationships between digital intensity, institutional quality, and e-government highlighting the interconnections between variables, (iii) Data Envelopment Analysis to measure the relative efficiency of public service delivery, and (iv) cluster dendrograms to identify the clusters of countries with similar performance levels and challenges. …”
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Spatial distribution and habitat preference of sarcosaprophagus Calliphoridae (Diptera) in the Brazilian Northeast, with notes on the utilization of different animal baits by ANA BEATRIZ L. DE ASSIS, TACIANO M. BARBOSA, RICARDO JOSÉ P. SOUZA E GUIMARÃES, RENATA A. GAMA

“…On the other hand, native taxa have a more restricted distribution, except for the species Cochliomyia macellaria (Fabricius, 1775). The variables that most influenced the models were precipitation and wind. …”
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Prediction cardiovascular deterioration in a paediatric intensive care unit (PicEWS): a machine learning modelling study of routinely collected health-care dataResearch in context by Dan Fredman Stein, Michael J. Carter, John Booth, Mark J. Peters, Samiran Ray, Neil J. Sebire, Payam Barnaghi, Mario Cortina-Borja

“…We compared model compositions, including without trend, variability, and frequency of input to smaller models. …”
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Evaluating the impacts of xylo-oligosaccharides on growth performance of broiler chickens: A meta-analytical study by M. Naeem, Dianna Bourassa, Samuel Rochell, Mike Bedford

“…These findings underscore the potential of XOS to optimize broiler productivity and sustainability. However, the variability in efficacy due to dietary composition, XOS purity, and environmental conditions warrants further investigation.…”
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Influence of the moisture and ash content in flue gases on the performance of adsorption processes using activated carbons to capture the CO2 for reuse in greenhouses by R. López Pastor, M.G. Pinna-Hernández, J.A. Sánchez Molina, F.G. Acién Fernández

“…This model was used to optimize the combustion gas variables and thus their influence on the final CO2 adsorption/desorption capacity. …”
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Longitudinal Reciprocal Effects of Physical Exercise, Executive Function, and Subjective Well-Being: A Three-Wave Random-Intercept Cross-Lagged Panel Model in Chinese Minority Coll... by Xueyan Bai, Lin Yang

“…Data were analyzed using a random-intercept cross-lagged panel model (RI-CLPM), and multigroup analysis (MGA) was used to examine the moderating effects of gender, family ethnic composition, and residential area. …”
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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

“…Various transfer and training functions were applied with the multilayer perceptron employing the feed-forward-back propagation approach when building the ANN models. Also, for the first time in the RSW field, an estimation of the relative importance of the RSW variables regarding the predicted shear force is presented in the current study. …”
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The Characteristics and Driving Factors of Soil Salinisation in the Irrigated Area on the Southern Bank of the Yellow River in Inner Mongolia: A Assessment of the Donghaixin Irriga... by Ziyuan Qin, Tangzhe Nie, Ying Wang, Hexiang Zheng, Changfu Tong, Jun Wang, Rongyang Wang, Hongfei Hou

“…This study examines the spatial distribution and determinants of soil salinisation through macro-environmental variables and micro-ion composition, integrating regression models and groundwater ion characteristics to elucidate the patterns and causes of soil salinisation systematically. …”
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Comparison of the Methods for Predicting the Critical Temperature and Critical Pressure of Petroleum Fractions and Individual Hydrocarbons by Evdokia Sotirova, Svetlin Vasilev, Dicho Stratiev, Ivelina Shishkova, Sotir Sotirov, Radoslava Nikolova, Anife Veli, Veselina Bureva, Krassimir Atanassov, Vanya Georgieva, Denis Stratiev, Svetoslav Nenov

“…Our study aims to provide robust predictive models that can accurately estimate critical properties across diverse petroleum fractions and compositions.…”
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Cardiometabolic index and mortality risks: elevated cancer and reduced cardiovascular mortality risk in a large cohort by Junjie Wang, Li Xiao, Zhou Li

“…The Cox frailty model and average marginal effects were employed to evaluate the contribution of CMI to all-cause and specific mortality collectively. …”
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Behavioral determinants of dental and facial esthetic self-perception among an academic population: a cross-sectional study by Ana Cristina Mafla, Mauricio Herrera-López, Juliana Estefanía Salas-Burbano, Camilo Andrés Guerrero-Dávila, Diana Paola Insuasty-Fuertes, Juan Sebastián Bustos-López, Falk Schwendicke

“…Structural Equation Modeling (SEM) was performed with robust unweighted least squares estimation method to assess the mediating effects of the behavioral variables on dental and facial esthetics. …”
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Clinical differential factors in patients with hereditary transthyretin amyloidosis with Val142Ile and Ser43Asn mutations by Sandra Milena Castellar-Leones, Edicson Ruiz-Ospina, Jorge Diaz-Ruiz, Cristian Correa-Arrieta, Xiomara Ruiz-Cortés, Diana Luzuriaga-Carpio, Dario Zambrano-Vera, Jeanneth Cedeño-Quincha, Luis Guerrero-Cepeda, Daniel César-Chávez, Fernando Ortiz-Corredor

“…The final random forest model identified the NHP test, Norfolk QOL-DN score, and CSA of the median and ulnar nerves as key discriminating variables. …”
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