Interactive relationship between carbon flow and economic growth and influencing factors based on land use transition by ZHANG Changren, HAN Zenglin, ZHAO Yuqing, YAN Xiaolu

Get full text

PBC-Transformer: Interpreting Poultry Behavior Classification Using Image Caption Generation Techniques by Jun Li, Bing Yang, Jiaxin Liu, Felix Kwame Amevor, Yating Guo, Yuheng Zhou, Qinwen Deng, Xiaoling Zhao

“…The model employs a multi-head concentrated attention mechanism, Head Spatial Position Coding (HSPC), to enhance spatial information; a learnable sparse mechanism (LSM) and RNorm function to reduce noise and strengthen feature correlation; and a depth-wise separable convolutional network for improved local feature extraction. …”
Get full text

The characteristics and functional significance of disulfidptosis-related genes in head and neck squamous cell carcinoma by Haiqian Zhu, Chifeng Zhao, Haoran Zhu, Xuhui Xu, Conglin Hu, Zhenxing Zhang

“…The relative compositions of cells in the tumor microenvironment (TME), mutant landscape, lasso regression analysis, and predicted clinical outcome were performed by analyzing bulk RNA-sequencing data. …”
Get full text

Small scale, elevation- and environmental-related differences in life history strategies in a temperate resident songbird by Benjamin R. Sonnenberg, Carrie L. Branch, Angela M. Pitera, Virginia K. Heinen, Lauren E. Whitenack, Joseph F. Welklin, Vladimir V. Pravosudov

“…Due to the harsher and less predictable environmental conditions at higher elevations, this investment strategy in this resident species likely leads to the production of offspring with greater chances of survival. …”
Get full text

Study of the dynamics of herbs productivity based on long-term monitoring data by D. A. Ivanov, O. V. Karaseva, M. V. Rublyuk

“…It has been determined that different groups of observation years differ in productivity and in the nature of its spatio-temporal variability, as well as in the factors that determine them and in the conditions that affect these factors. This makes, when predicting the yield of grasses of different ages, to create mathematical models of its dependence on landscape conditions for different time clusters.…”
Get full text

Machine learning-guided integration of fixed and mobile sensors for high resolution urban PM2.5 mapping by Tianshuai Li, Xin Huang, Qingzhu Zhang, Xinfeng Wang, Xianfeng Wang, Anbao Zhu, Zhaolin Wei, Xinyan Wang, Haolin Wang, Jiaqi Chen, Min Li, Qiao Wang, Wenxing Wang

Get full text

Structural Connectivity Shaped by Cryospheric Degradation Modulates Sediment Transport Dynamics in High Mountain Asia by Jinlong Li, Genxu Wang, Jiapei Ma, Peng Huang, Chunlin Song, Shouqin Sun, Linmao Guo, Kai Li, Haoyu Wang, Dongfeng Li, Admin Husic

Get full text

A Near-Real-Time Operational Live Fuel Moisture Content (LFMC) Product to Support Decision-Making at the National Level by Akli Benali, Giuseppe Baldassarre, Carlos Loureiro, Florian Briquemont, Paulo M. Fernandes, Carlos Rossa, Rui Figueira

“…Live fuel moisture content (LFMC) significantly influences fire activity and behavior over different spatial and temporal scales. The ability to estimate LFMC is important to improve our capability to predict when and where large wildfires may occur. …”
Get full text

Regulation of MAP2, GFAP, and calcium in the CA3 Region Following Kainic Acid Exposure to  organotypic hippocampal slice culture [version 3; peer review: 2 approved] by Aulanni'am Aulanni'am, Kusworini Handono, Ettie Rukmigarsari, Hidayat Sujuti, Machlusil Husna

Get full text

Metabolomics and network analysis reveal the mechanism of Salvia miltiorrhiza bunge extract in ameliorating cognitive dysfunction in sleep-deprived rats by Meiya Zhang, Xirui Huang, Mengxiang Dai, Shunbo Zhang, Chao Yin, Qiuyun You

Get full text

Recognition of Maize Tassels Based on Improved YOLOv8 and Unmanned Aerial Vehicles RGB Images by Jiahao Wei, Ruirui Wang, Shi Wei, Xiaoyan Wang, Shicheng Xu

“…The tasseling stage of maize, as a critical period of maize cultivation, is essential for predicting maize yield and understanding the normal condition of maize growth. …”
Get full text

Impact of Subjective and Objective Green Space Characteristics on Mental Health Benefits: An Explainable Machine Learning Approach by Ke LI, Yipei MAO, Yongjun LI

“…Based on the SHAP values, the non-linear relationships between them are further clarified.ResultsThrough the analysis of 3 types of mental health benefits and 5 models, the LightGBM model outperforms other algorithms (such as Random Forest and XGBoost) in terms of prediction accuracy (R 2: 0.523 – 0.642), with its robustness in capturing complex feature interactions being verified. …”
Get full text

Deep Learning Approach for Estimating Workability of Self-Compacting Concrete from Mixing Image Sequences by Zhongcong Ding, Xuehui An

“…We propose a deep learning approach to better utilize the spatial and temporal information obtained from image sequences of the self-compacting concrete- (SCC-) mixing process to recover SCC characteristics in terms of the predicted slump flow value (SF) and V-funnel flow time (VF). …”
Get full text

High-resolution mapping of on-road vehicle emissions with real-time traffic datasets based on big data by Y. Wang, H. Wang, B. Zhang, P. Liu, X. Wang, S. Si, L. Xue, Q. Zhang, Q. Wang

“…Based on the established emission model, we predicted that the benefits of vehicle electrification in reducing vehicle emissions could reach 40 %–80 %. …”
Get full text

HMGB1 Inhibition Alleviates Chronic Nonbacterial Prostatitis by Suppressing M1 Polarization of Macrophages by Zhou J, Ding L, Chen J, Chen C, Jiang P, Mei Z, Jiang Q, Hua X

“…Co-immunofluorescence was used to analyze the functional phenotype of macrophages and spatial localization of HMGB1 in prostate of EAP mice. …”
Get full text

Getting NBA Shots in Context: Analysing Basketball Shots with Graph Embeddings by Schmid Marc, Schöpf Moritz, Kolbinger Otto

“…We introduce a graph neural network to process a graph based on player and ball tracking data to compute expected shot quality. We evaluate this model against other models focusing on calibration. …”
Get full text

Freeze–Thaw-Induced Degradation Mechanisms and Slope Stability of Filled Fractured Rock Masses in Cold Region Open-Pit Mines by Jun Hou, Penghai Zhang, Ning Gao, Wanni Yan, Qinglei Yu

“…Based on regression fitting using 0–25 FT cycles, regression model predictions indicate that when the number of <i>FT</i> cycles exceeds 42, the slope safety factor drops below 1.0, entering a critical instability state. …”
Get full text

Defending Data Poisoning Attack Through Watermarked Friendly Noise Luminosity Activated Dense Layered UNet for Classification of Lung Disease by M. Shyamala Devi, S. Priya

Get full text

cogsworth: A Gala of COSMIC Proportions Combining Binary Stellar Evolution and Galactic Dynamics by Tom Wagg, Katelyn Breivik, Mathieu Renzo, Adrian M. Price-Whelan

“…We provide a detailed explanation of the functionality of cogsworth and demonstrate its capabilities through a series of use cases: (1) we predict the spatial distribution of compact objects and runaways in both dwarf and Milky Way–like galaxies; (2) using a star cluster from a hydrodynamical simulation, we show how supernovae can change the orbits of stars in several ways; and (3) we predict the separation of disrupted binary stellar companions on the sky and create a synthetic Gaia color–magnitude diagram. …”
Get full text

WetCH₄: a machine-learning-based upscaling of methane fluxes of northern wetlands during 2016–2022 by Q. Ying, Q. Ying, B. Poulter, J. D. Watts, K. A. Arndt, A.-M. Virkkala, L. Bruhwiler, Y. Oh, Y. Oh, B. M. Rogers, S. M. Natali, H. Sullivan, A. Armstrong, A. Armstrong, E. J. Ward, E. J. Ward, L. D. Schiferl, C. D. Elder, C. D. Elder, O. Peltola, A. Bartsch, A. R. Desai, E. Euskirchen, M. Göckede, B. Lehner, M. B. Nilsson, M. Peichl, O. Sonnentag, E.-S. Tuittila, T. Sachs, T. Sachs, A. Kalhori, M. Ueyama, Z. Zhang, Z. Zhang

“…The most important predictor<span id="page2508"/> variables included near-surface soil temperatures (top 40 cm), vegetation spectral reflectance, and soil moisture. Our results, modeled from 138 site years across 26 sites, had relatively strong predictive skill, with a mean <span class="inline-formula"><i>R</i>²</span> of 0.51 and 0.70 and a mean absolute error (MAE) of 30 and 27 nmol m<span class="inline-formula">⁻²</span> s<span class="inline-formula">⁻¹</span> for daily and monthly fluxes, respectively. …”
Get full text