Enhancing building roof insulation: A comparative examination of PCM layers integrated with and without nanoparticles by Hayder M. Abbas, Abd Alsatar Hussein

“…The primary goal is to investigate the effectiveness of these materials in reducing indoor heat transfer, thereby enhancing energy efficiency, using a numerical model based on finite volume and enthalpy methods in a three-dimensional spatial domain. …”
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Evolutionary Algorithms for the Optimal Design of Robotic Cells: A Dual Approximation for Space and Time by Raúl-Alberto Sánchez-Sosa, Ernesto Chavero-Navarrete

“…Through simulations and a digital model of the cell, key metrics such as total space reduction, operational time improvement, and productivity increase are evaluated. …”
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Estimation of Aboveground Biomass of Chinese Milk Vetch Based on UAV Multi-Source Map Fusion by Chaoyang Zhang, Qiang Zhu, Zhenghuan Fu, Chu Yuan, Mingjian Geng, Ran Meng

“…Estimation based exclusively on structural features resulted in R² values of 0.65 and 0.52 for model cross-validation and spatial transferability validation, respectively. …”
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Data-driven support for smart renewal of urban neighbourhoods by Spela VEROVSEK, Matevz JUVANCIC, Tadeja ZUPANCIC

“…The research develops structured evaluation model, this is, neighbourhood sustainability performance index which provides the foundation for targeted actions. …”
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A spatiotemporal recurrent neural network for missing data imputation in tunnel monitoring by Junchen Ye, Yuhao Mao, Ke Cheng, Xuyan Tan, Bowen Du, Weizhong Chen

“…ST-RNN consists of two moduli: a temporal module employing recurrent neural network (RNN) to capture temporal dependencies, and a spatial module employing multilayer perceptron (MLP) to capture spatial correlations. …”
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The theoretical cognition and research paradigm of land system science by LONG Hualou, CHEN Kunqiu, ZHENG Yuhan, ZHANG Yingnan

“…The research paradigm of land system science has gradually transformed from knowledge and phenomenon description to the simulation and prediction of complex land systems, which emphasizes the integration of multidisciplinary theories and methods as well as understanding the local-distant coupled interactions of land systems based on the integrated multiscale analysis of expanding boundaries, and focuses on the construction of large-scale quantitative land system models to provide comprehensive and dynamic integrated analysis, prediction and simulation of its dynamic mechanisms, integrated effects and future scenarios and risks, and appeals for an opening scientific collaboration in the era of big data.…”
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Long time-series and high-frequency ecological evaluation of Henan section of the Yellow River by Jianzhong Guo, Daozhu Xu, Jian Xu, Ruoxin Zhu, Ning Li

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Spatiotemporal, environmental, and behavioral predictors of Varroa mite intensity in managed honey bee apiaries. by Laura Boehm Vock, Lauren M Mossman, Zoi Rapti, Adam G Dolezal, Sara M Clifton

“…We examine risk factors for Varroa infestation using apiary inspection data collected across the state of Illinois over 2018-2019, and we test the models using inspection data from 2020-2021. After accounting for spatial and temporal trends, we find that most environmental factors (e.g., floral quality, insecticide load) are not predictive of Varroa intensity, while lower numbers of nearby apiaries and several beekeeper behaviors (e.g., supplemental feeding and mite monitoring/treatment) are protective against Varroa. …”
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iMESc – an interactive machine learning app for environmental sciences by Danilo Cândido Vieira, Danilo Cândido Vieira, Fabiana S. Paula, Luciana Erika Yaginuma, Gustavo Fonseca

“…Finally, a hybrid model combining an unsupervised SOM and followed by the supervised Random Forest model returned an accuracy of 83.47% for the training and 80.77% for the test, with Bathymetry, Chlorophyll, and Coarse Sand as key predictive variables. …”
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Total flavonoids of Dracocephalum moldavica L. alleviate cognitive impairment via TNF-α/NF-κB p65 signaling pathway in vascular dementia rats by Shangjia Ma, Jianxin Jia, Jianxin Jia, Lie Wu, Kai Tian, Lu Wang, Hua Li, Jiayu Lv, Dewang Gao, Zhanjun Yang, Zhanjun Yang, Xia Guo

“…The Morris water maze test assessed spatial learning and memory capacities. Nissl staining was used to examine the neuronal damage. …”
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Identifying monthly rainfall erosivity patterns using hourly rainfall data across India by Subhankar Das, Manoj Kumar Jain, Karl Auerswald, Carlos Rogerio de Mello, Peter Molnar

“…Monthly erosivity estimates derived from hourly data were linked with monthly rainfall, enabling a simplified and efficient estimation approach. To predict monthly erosivity based on rainfall, temperature, and topographic variables, we developed and evaluated three modeling approaches: linear regression, a machine learning-based XGBoost model, and an ensemble model. …”
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Mode use in long-distance travel by Alexander Reichert, Christian Holz-Rau

“…The aim of this paper is to analyze the mode use in long-distance travel in different spatial settings by using multivariate regression models. …”
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Nonlinear and synergistic effects of demographic characteristics on urban polycentric structure using SHAP by Yichen Ruan, Xiaoyi Zhang, Mingyu Zhang, Feiyang Sun, Qiuxiao Chen

“…Spatial heterogeneity is observed in the demographic profiles of urban centers; for instance, primary central cores are predominantly young, single females, whereas peripheral and secondary centers have stronger presence of highly educated residents.…”
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Government environmental governance, fiscal decentralization, and carbon intensity of the construction industry by Yuhao Sun, Minghui Liu, Yong Lv

“…This paper, utilizing provincial panel data from 2007 to 2021, empirically analyzes the impact of government environmental governance (EG) on the carbon intensity of the construction industry (CCEI) through the panel regression, spatial econometric and dynamic threshold models. …”
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Bankruptcy rules and sustainable water management: A MODSIM-NSGAII simulation multi-objective optimization framework for equitable transboundary water allocation by Bentolhoda Asl-Rousta, S. Jamshid Mousavi

“…Classical bankruptcy game methods assume homogenous resource accessibility, but water resource systems vary widely in both spatial and temporal dimensions. This study addresses these challenges by introducing a new optimal bankruptcy rule (OpPro rule) through a simulation-optimization model (MODSIM-NSGAII), where MODSIM simulates the spatial and temporal variability of water resources, and the NSGA-II optimization algorithm includes two objective functions of maximizing basin-wide ecological sustainability and maximizing economic efficiency reflecting ''equitable and reasonable utilization'' of water. …”
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Emerging carbon dioxide hotspots in East Asia identified by a top-down inventory by Lei Xia, Rui Liu, Wenxuan Fan, Changxu Ren

“…This study used a top-down spatial proxy model to develop a high-resolution (1 km) carbon dioxide emission inventory for East Asia from 2012 to 2021. …”
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Simulation of the Vibratory Behavior of Slender Shafts Subject to Transverse Loads Moving in the Axial Direction by F. Bucchi, P. Forte

“…The effect of a load moving axially at a given speed followed by similar loads after given spatial intervals was simulated investigating the influence of speed and load interval on shaft vibrations and resonance. …”
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Estimation of Relative Sea Level Change in Locations Without Tide Gauges Using Artificial Neural Networks by Heeryun Kim, Young Il Park, Wansik Ko, Taehyun Yoon, Jeong-Hwan Kim

“…Unlike conventional forecasting approaches focused on future time series prediction, the proposed model is designed to learn spatial distribution patterns and temporal rates of sea level change from a fusion of satellite altimetry and tide gauge data. …”
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Physical forcing mechanisms controlling the variability of chlorophyll-a over the Royal-Charlotte and Abrolhos Banks-Eastern Brazilian Shelf. by Renato David Ghisolfi, Meyre Pereira da Silva, Felipe Thomaz dos Santos, Ricardo Nogueira Servino, Mauro Cirano, Fabiano Lopes Thompson

“…The present study investigates the seasonal and spatial distributions of chlorophyll-a (Chl-a) and water conditions by analyzing nine years (2003-2011) of level-3 Moderate-resolution Imaging Spectroradiometer (MODIS) derived Chl-a, National Centers for Environmental Prediction (NCEP)/ETA model-derived winds, NCEP model-derived heat fluxes, thermohaline and velocity results from the Hybrid Circulation Ocean Model (HYCOM) 1/12o assimilated simulation. …”
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Radar Echo Extrapolation Based on Translator Coding and Decoding Conditional Generation Adversarial Network by Xingang Mou, Yuan He, Wenfeng Li, Xiao Zhou

“…In response to the shortcomings of current spatiotemporal prediction models, which frequently encounter difficulties in temporal feature extraction and the forecasting of medium to high echo intensity regions over extended sequences, this study presents a novel model for radar echo extrapolation that combines a translator encoder-decoder architecture with a spatiotemporal dual-discriminator conditional generative adversarial network (STD-TranslatorNet). …”
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