The greener, the richer, the happier?——Spatial distribution and coupling analysis of urban green space and residents’ emotion based on social media data by Zexun Li, Lihui Hu, Alin Lin, Jiarui Chen, Yue Xu

“…It has also discovered that enhancing the quality and functionality of green spaces can boost urban well-being, offering valuable guidance to planners in the context of park city.…”
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Deep Learning-Based Remote Sensing Image Analysis for Wildfire Risk Evaluation and Monitoring by Shiying Yu, Minerva Singh

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A systematic review as type of review-analytical products by O. L. Lavrik, T. A. Kalyuzhnaya, M. A. Pleshakova

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Generation of Spatial Structure of Urban Parks Based on Spatial Analysis of Agent-Based Models by Huizi KONG, Tianming LIU, Jiajie LIAO, Liu CUI

“…This research employs agent-based models (ABM) to simulate spatial information and explore the spatial function distribution of planned sites under urban spatial function penetration, thereby guiding the structural morphology of scheduled sites.MethodsThis research adopts a spatial network analysis design method using slime mold intelligence based on mapping point of interest (POI) data. …”
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Unveiling Key Biomarkers and Mechanisms in Septic Cardiomyopathy: A Comprehensive Transcriptome Analysis by Zhao D, Zhuang J, Wang L, Wu L, Xu W, Zhao L, Hong J, Jin W, Miao C

“…These findings enhanced our understanding of SCM’s underlying mechanisms and might pave the way for novel therapeutic strategies to improve clinical outcomes.Keywords: septic cardiomyopathy, integrated bioinformatics analysis, hub biomarkers, single-cell data analysis, immunity…”
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La réflexivité algorythmique by Noé Latreille de Fozières

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Time series generation model based on multi-discriminator generative adversarial network by Yanhui LU, Han LIU, Hang LI, Guangxu ZHU

“…Aiming at the problems of expensive collection cost and missing data due to the privacy and continuity of time series data set, a multi-discriminator generative adversarial network model based on recurrent neural network was proposed, which could synthesize time series dataset that were approximately distributed with real data of a small scale dataset.Multi-discriminator included four discriminators in time domain, frequency domain, time-frequency domain and autocorrelation.Different discriminators could effectively recognize the features of the time series in different domains.In the experiment, the convergence of loss function, principal component analysis and error analysis were performed to evaluate the performance of the model from qualitative and quantitative perspectives.The experimental results show that the proposed model has better performance than other reference models.…”
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Flexible Adaptive Marine Predator Algorithm and Its Application in Fault Detection for Wind Turbines by WANG Wen, YI Jiabiao

“…With the increasing dimensions of operational data for wind turbines, traditional expert empirical methods, such as fuzzy logic systems and fault tree analysis, struggle to provide accurate fault diagnosis amid high-dimensional complex data. …”
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Approximate Bayesian Computation for a Dual-Failure-Modes Models and Its Application to Failure Times Data by Mustapha Muhammad, Badamasi Abba, Jinsen Xiao

“…We practically demonstrate approximate Bayesian computation (ABC)-Gibbs scheme using Kolmogorov-Smirnov as distance function; this method is a simulation-based scheme, which the explicit formulation of the likelihood function is not required, hence, suitable for a complex model or big data, where the “accept-reject” mechanism is required for the posterior computation. …”
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The Effects of Social Spending on Income Inequality in 30 OECD Countries by Can Verberi, Sema Yaşar

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Comparison of Univariate and Multivariate Applications of GBLUP and Artificial Neural Network for Genomic Prediction of Growth and Carcass Traits in the Brangus Heifer Population by Sunday O. Peters, Kadir Kızılkaya, Mahmut Sinecen, Milt G. Thomas

“…Univariate and multivariate genomic best linear unbiased prediction models based on the genomic relationship matrix and univariate and multivariate artificial neural networks models with 1 to 10 neurons, as well as the learning algorithms of Bayesian Regularization, Levenberg–Marquardt and Scaled Conjugate Gradient and transfer function combinations of tangent sigmoid–linear and linear–linear in the hidden-output layers, including the inputs from genomic relationship matrix, were created and applied for the analysis of growth and carcass data. …”
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A novel method for simulating dynamic facades to analysing, and optimizing daylight and visual comfort in office buildings by Mehran Shahmoradi, Mansour Yeganeh

“…Mathematica software gets these results of sample hours data as inputs and operates the data fitting process on them. …”
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Identification of comorbid genes between type 2 diabetes and migraine through peripheral blood single-cell and Mendelian randomization analysis by Bobo Yuan, Jianrui Li, Qing Shu, Xiaoye Wang, Guogang Luo, Ranran Ma

“…Methods Single-cell datasets from T2DM and migraine were analyzed to identify differentially expressed genes (DEGs). MR analysis was employed to prioritize key causal genes, followed by network-based functional characterization, disease-drug association analysis, cell annotation, and pseudo-time trajectory modeling. …”
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Improved Electrochemical–Mechanical Parameter Estimation Technique for Lithium-Ion Battery Models by Salvatore Scalzo, Davide Clerici, Francesca Pistorio, Aurelio Somà

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Retraction notice to “Immunomodulatory effects of β-defensin 2 on tumor associated macrophages induced antitumor function in breast cancer” [Adv. Cancer Biol. – Metastasis 7 (2023)... by Sonam Agarwal, Anita Chauhan, Pramod Kumar Gautam

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MAS-YOLO: A Lightweight Detection Algorithm for PCB Defect Detection Based on Improved YOLOv12 by Xupeng Yin, Zikai Zhao, Liguo Weng

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Extensions and Applications of Locally Solid Convergence Structures by Saeed Hashemi Sababe

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Robust phylogenetic profile clustering for Saccharomyces cerevisiae proteins by Paul M. Harrison

“…Conclusions For individual proteins, the profile cluster data generated here are useful for investigating experimental hypotheses, since they provide evidence for functional linkages that have yet to be discerned.…”
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WIND ENERGY EVALUATION AND TURBINE IDENTIFICATION FOR POWER GENERATION IN SOME SELECTED AREAS IN NIGERIA by MUSEDIQ ADEDOYIN SULAIMAN, IGNATIUS KEMA OKAKWU, AKINTUNDE SAMSON ALAYANDE, OLAKUNLE ELIJAH OLABODE, AUGUSTUS EHIREMEN IBHAZE

“…The analysis of the data is carried out using a two-parameter Weibull Distribution Function (WDF). …”
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DETERMINANTS OF DEMAND FOR FRESH VEGETABLES IN THE SLOVAK REPUBLIC by Elena Hoskova, Iveta Zentková

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