On the accuracy of schedule-based GTFS for measuring accessibility by Nate Wessel, Steven Farber

“…Origins with lower scheduled access tend to produce less reliable estimates with more variability from hour to hour in real accessibility, while higher access zones seem to converge on an estimate 5-15 percent lower than the schedule predicts. Such over- and under-predictions exhibit strong spatial patterns which should be of concern to those using accessibility metrics in statistical models. …”
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Light-driven phenotypic plasticity in the depth-generalist coral, Pavona varians. by Claire J Lewis, Shayle B Matsuda, Tayler L Sale, Caitlyn Genovese, Chelsea S Wolke, Norton Chan, Stephen Ranson, Jake M Ferguson, Amy L Moran, David A Gulko, Peter B Marko

“…This additively negative relationship in the model is consistent with the hypothesis that reductions in bleaching at depth could be the product of reduced light stress at depth rather than reduced temperature stress. …”
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Awe is characterized as an ambivalent affect in the human behavior and cortex by Jinwoo Lee, Danny Dongyeop Han, Seung-Yeop Oh, Jiook Cha

“…Notably, this variability significantly predicted subjective awe ratings. Lastly, hidden Markov modeling revealed that the multiple band powers, particularly in the frontoparietal channels, were significantly associated with differentiation of valent states during awe-inducing VR watching. …”
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Temporal resolution of spike coding in feedforward networks with signal convergence and divergence. by Zach Mobille, Usama Bin Sikandar, Simon Sponberg, Hannah Choi

“…Additionally, we found that a simple network model based on convergence and divergence ratios of a hawkmoth (Manduca sexta) nervous system can reproduce the relative contribution of spike timing information in its motor output, providing testable predictions on optimal temporal resolutions of spike coding across the moth sensory-motor pathway at both the single-neuron and population levels.…”
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RGB to hyperspectral: Spectral reconstruction for enhanced surgical imaging by Tobias Czempiel, Alfie Roddan, Maria Leiloglou, Zepeng Hu, Kevin O'Neill, Giulio Anichini, Danail Stoyanov, Daniel Elson

“…Transformer models exhibit superior performance in terms of RMSE, SAM, PSNR and SSIM by effectively integrating spatial information to predict accurate spectral profiles, encompassing both visible and extended spectral ranges. …”
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Enhancing urban resilience through machine learning-supported flood risk assessment: integrating flood susceptibility with building function vulnerability by Xiaoling Qin, Shifu Wang, Meng Meng, Haiyan Long, Huilan Zhang, Haochen Shi

“…Using a Random Forest (RF) model, it predicts flood susceptibility based on flood records, hydrological, topographical, and anthropogenic features. …”
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Research on the employment mobility patterns and driving factors of graduates from double first-class universities in the central China by Zilong Jiang, Zongyu Shao, Qiang Wang

“…Additionally, the study predicts the evolutionary trend of the network using the TERGM model. …”
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Enhanced simulation of gross and net carbon fluxes in a managed Mediterranean forest by the use of multi-sensor data by Marta Chiesi, Nicola Arriga, Luca Fibbi, Lorenzo Bottai, Luigi D'Acqui, Alessandro Dell’Acqua, Sara Di Lonardo, Lorenzo Gardin, Maurizio Pieri, Fabio Maselli

“…The proposed advancements are aimed at improving the model performance in managed Mediterranean forests and concern: i) the calibration of C-Fix GPP sensitivity to water stress; ii) the quantification of the green, woody and soil C pools which regulate the prediction of NPP and NEP. …”
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Pharmacological potential of 6,11-dihydro[1,2,4]triazolo[4’,3’:1,6]-pyrido[3,4-b]-5-carboxylic acid and its esters by S. O. Fedotov, A. S. Hotsulia

“…Molecular docking was performed using Vina software, which provides modelling and evaluation of interactions between ligand and three-dimensional protein structure, considering their energy and spatial compatibility. …”
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Global high-resolution fire-sourced PM_2.5 concentrations for 2000–2023 by Y. Hu, C. Tian, X. Yue, Y. Lei, Y. Cao, R. Xu, Y. Guo

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Size Effect on Energy Characteristics of Axial Flow Pump Based on Entropy Production Theory by Hongliang Wang, Xiaofeng Wu, Xiao Xu, Suhao Bian, Fan Meng

“…By solving the unsteady Reynolds-averaged Navier–Stokes (URANS) equations with the Shear Stress Transport (SST) k-omega turbulence model, the external characteristic parameters and internal flow field structures were predicted. …”
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Mineral prospectivity mapping using geological map semantic knowledge graph embedding: a case study of gold prospecting in Ankang, Shaanxi Province, China by Qun Yan, Linfu Xue, Yongsheng Li, Rui Wang, Ke Ding, Zhenglin Xu

“…To improve the model’s ability to learn the complex variations in geospatial features, we employ the Conformer deep learning model for gold prospectivity prediction. …”
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A condition diagnosis method for subway track structures employing distributed optical fiber sensing by Hong Han, Xiaopei Cai, Liang Gao

“…Through spatial correlation analysis of the strain of symmetric measuring points, the Mahalanobis distance of the predicted residual is used as the diagnostic factor to realize accurate identification of the orbital structure state. …”
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The annual dynamic dataset of high-resolution crop water use in China from 1991 to 2019 by Minglei Wang, Wenjiao Shi

“…Firstly, we estimated the yearly crop blue and green water use at the site scale by incorporating more localized input parameters using a dynamic water balance model. Then, the random forest model was combined with site-scale simulation results to generate spatial predictions of blue and green water for each crop from 1991 to 2019. …”
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Analysis of the spatio-temporal variability of spawning mackerel in the Northeast Atlantic by Gersom Costas

“…To achieve this objective, a Random Forest model was used to predict the presence of mackerel eggs based on temporal, geographical, and environmental variables. …”
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Environment-assisted quantum transport of excitons in perovskite nanocrystal superlattices by Daria D. Blach, Victoria A. Lumsargis-Roth, Chern Chuang, Daniel E. Clark, Shibin Deng, Olivia F. Williams, Christina W. Li, Jianshu Cao, Libai Huang

“…Our results connect theoretical predictions and experiments using a stochastic Anderson localization model, highlighting perovskite nanocrystals as promising building blocks for quantum materials.…”
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Pedestrian Mobility Behaviors of Older People in the Face of Heat Waves in Madrid City by Diego Sánchez-González, Joaquín Osorio-Arjona

“…Multiple linear regression models and Moran’s I spatial autocorrelation were applied. …”
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Specificity, propagation, and memory of pericentric heterochromatin by Katharina Müller‐Ott, Fabian Erdel, Anna Matveeva, Jan‐Philipp Mallm, Anne Rademacher, Matthias Hahn, Caroline Bauer, Qin Zhang, Sabine Kaltofen, Gunnar Schotta, Thomas Höfer, Karsten Rippe

“…From the experimental data, we developed a predictive mathematical model that explains how chromatin‐bound SUV39H1/2 complexes act as nucleation sites and propagate a spatially confined PCH domain with elevated histone H3 lysine 9 trimethylation levels via chromatin dynamics. …”
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Observed Tightening of Tropical Ascent in Recent Decades and Linkage to Regional Precipitation Changes by Hui Su, Longtao Wu, Chengxing Zhai, Jonathan H. Jiang, J. David Neelin, Yuk L. Yung

“…Abstract Climate models predict that the tropical ascending region should tighten under global warming, but observational quantification of the tightening rate is limited. …”
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The potential spatiotemporal distribution patterns of Avena nuda and Avena sativa from global perspective provide new insights for the cultivation of commonly cultivated oats by Huanhuan Lu, Yuying Zheng, Ting Zhao, Liuban Tang, Fan Zhang, Wengang Xie

“…This study comprehensively collected the geographic distribution and environmental data of A. nuda and A. sativa from global regions, the ensembled niche and Marxan model were used to predict the potential spatiotemporal distribution and planting pattern of commonly cultivated oats, and further explore the environmental factors that affected the spatial distribution and genetic diversity pattern. …”
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