Evidence for preferred propagating terrestrial heatwave pathways due to Rossby wave activity by Mingzhao Wang, Yu Huang, Christian L. E. Franzke, Naiming Yuan, Zuntao Fu, Niklas Boers

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Identification and Mechanistic Studies of Key Genes in Thalamic Hemorrhage Pain by Multi-omics by Chen Yang, Ju Gao, Yaqun Li, Yinggang Xiao, Tianfeng Huang

“…Methods: A mouse model of THP was established and mice were divided into THP and control groups. …”
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Cocoa Farmers’ Perceptions of Drought and Adaptive Strategies in the Ghana–Togo Transboundary Cocoa Belt by Afi Amen Christèle Attiogbé, Udo Nehren, Emmanuel Quansah, Enoch Bessah, Seyni Salack, Jean Mianikpo Sogbedji, Sampson K. Agodzo

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Interpretation of Cultural Landscape Layering and Assessment of Heritage Value of Urban Historical Parks: A Case Study of Xiamen Zhongshan Park by Xufang LI, Xiangpin ZHOU, Feifan WENG

“…It constructs a cultural landscape heritage layering model of Xiamen Zhongshan Park by combining ancient literature and the spatial interpretation of ancient maps, and employing the historic urban landscape (HUL) method. …”
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Cover crop impacts on soil organic matter dynamics and its quantification using UAV and proximal sensing by Nikolaos-Christos Vavlas, Rima Porre, Liang Meng, Ali Elhakeem, Fenny van Egmond, Lammert Kooistra, Gerlinde B. De Deyn

“…With proximal sensing (MIR) the best SOM prediction was achieved using SVR (R2= 0.84, RMSE= 1.55 g/kg SOM). …”
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Extraction of typical oyster pile columns in the Maowei Sea, Beibu Gulf, based on unmanned aerial vehicle laser point cloud orthophotos by Jinze Du, Jinze Du, Meiqin Huang, Zhenjun Kang, Zhenjun Kang, Zhenjun Kang, Yichao Tian, Yichao Tian, Yichao Tian, Jin Tao, Jin Tao, Qiang Zhang, Qiang Zhang, Yutong Xie, Yutong Xie, Yutong Xie, Jinying Mo, Jinying Mo, LiYan Huang, LiYan Huang, Yusheng Feng, Yusheng Feng

“…By employing band features and texture indices extracted from UAV’s multi-spectral images as data sources and combining them with a classification and prediction model based on deep learning convolutional neural networks (CNN), we successfully extract the desired oyster pile columns. …”
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Multi-omics analysis constructs a novel neuroendocrine prostate cancer classifier and classification system by Junxiao Shen, Luyuan Lu, Zujie Chen, Wei Guo, Shuwen Wang, Ziqiao Liu, Xuke Gong, Yiming Qi, Ruyi Jin, Cheng Zhang

“…In clinical settings, the use of the NEP100 model can greatly improve the diagnostic and prognostic prediction of NEPC. …”
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FMO2+ cancer-associated fibroblasts sensitize anti-PD-1 therapy in patients with hepatocellular carcinoma by Hui Li, Wenxin Xu, Qinghai Ye, Qiang Yu, Jialei Weng, Shaoqing Liu, Minghao Xu, Yinghao Shen, Hui-Chuan Sun, Yufei Zhao, Peiyi Xie, Mincheng Yu, Bugang Liang, Junbo Chen

“…CCL19 treatment potentiated the therapeutic efficacy of anti-PD-1 therapy in mouse orthotopic HCC models. A favorable immunotherapy response was observed in patients with HCC with high serum levels of CCL19.Conclusions We identified a novel FMO2+ CAF subset that serves as a critical regulator of microenvironmental immune properties and a predictive biomarker of the immunotherapy response in patients with HCC. …”
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Solving geocryology problems based on generalized Fourier theory for temperature waves in half-space by Anatoliy M. Afanasyev, Yulia S. Bakhracheva

“…Currently, in geocryology, to predict seasonal changes in the state of frozen rocks and soils, Fourier formulas obtained earlier are widely used, modeling temperature fluctuations in the surface layer of the earth’s crust caused by annual fluctuations in its surface temperature. …”
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Deciphering cholangiocarcinoma heterogeneity and specific progenitor cell niche of extrahepatic cholangiocarcinoma at single-cell resolution by Chunliang Liu, Xiang Wang, Erdong Liu, Yali Zong, Wenlong Yu, Youhai Jiang, Jianan Chen, Mingye Gu, Zhengyuan Meng, Jingfeng Li, Yang Liu, Yongjie Zhang, Jing Tang, Hongyang Wang, Jing Fu

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Action Recognition with 3D Residual Attention and Cross Entropy by Yuhao Ouyang, Xiangqian Li

“…Additionally, the integration of Fast Fourier Convolution (FFC) enhances the network’s capability to effectively capture temporal and spatial features. Simultaneously, we used the cross-entropy loss function to describe the difference between the predicted value and GT to guide the model’s backpropagation. …”
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Three-dimensional characteristics of T cells and vasculature in the development of mouse esophageal cancer by Shanshan Bi, Yueguang Wu, Ning Ding, Yan Zhou, Huijuan Liu, Yongjia Weng, Qiqin Song, Li Zhang, Matthew Yibo Cheng, Heyang Cui, Weimin Zhang, Yongping Cui

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Spatio-Temporal Joint Planning for Integrated Energy Systems with Internet Data Center Considering Privacy Preservation by WU Chengbang, CHENG Zhijiang, LU Haifeng, YANG Handi

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Meta-Learning Approach for Adaptive Anomaly Detection from Multi-Scenario Video Surveillance by Deepak Kumar Singh, Dibakar Raj Pant, Ganesh Gautam, Bhanu Shrestha

“…Leveraging the swin transformer as a spatial feature extractor, the model captures rich hierarchical representations from surveillance videos. …”
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Analysis of The State of The Tourism Industry in Russia аnd The Direction of Its Development by P. G. Nikolenko, A. M. Terekhov

“…Based on the Box–Jenkins methodology, predictive models were created and medium-term forecasts were calculated for variables characterizing the number of tourist firms and the number of sanatorium-resort organizations and recreation organizations. …”
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Future Precipitation Projection Based on Multiple Statistical Downscaling Methods — A Case Study of Tibetan Plateau by DONG Qianjin, YUAN Xin

“…Although the Coupled Model Intercomparison Project 6 (CMIP6) can well predict large-scale climatic factors,its effect on projecting watershed scales is still different from the measured data.The error of climate models is even bigger over the Tibetan Plateau,which is a high-altitude region with complicated terrain.Based on the historical scenario of the latest generation of high-resolution CMIP6 model and a variety of future climate emission scenarios such as SSP126,SSP245,SSP370,and SSP585,this paper conducts downscaling analysis and evaluates the projection performance of various statistical downscaling methods such as bias correction,KNN,and SDSM.On this basis,the best statistical downscaling method is used to project future precipitation over the Tibetan Plateau, and the spatial-temporal evolution characteristics of the projected precipitation are analyzed and compared with the historical precipitation over the Tibetan Plateau.The results reveal that the applicability amongst the three statistical downscaling methods in the Tibetan Plateau is large,with the linear regression downscaling method performing the best,followed by the bias correction method and the KNN analogy method.According to the analysis of future precipitation projections,the average precipitation and extreme precipitation over the Tibetan Plateau in the next 80 years will exhibit an overall upward trend,although the rise will be slight,and the spatial distribution will not change much.The results can provide a scientific foundation for the evaluation,planning,and management of water resources on the Tibetan Plateau.…”
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Pancreas segmentation using AI developed on the largest CT dataset with multi-institutional validation and implications for early cancer detection by Sovanlal Mukherjee, Ajith Antony, Nandakumar G. Patnam, Kamaxi H. Trivedi, Aashna Karbhari, Madhu Nagaraj, Murlidhar Murlidhar, Ajit H. Goenka

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How Long Until Agricultural Carbon Peaks in the Three Gorges Reservoir? Insights from 18 Districts and Counties by Danqing Li, Yunqi Wang, Huifang Liu, Cheng Li, Jinhua Cheng, Xiaoming Zhang, Peng Li, Lintao Wang, Renfang Chang

“…Pathway scenario prediction: We construct three developmental scenarios (low-carbon transition, business-as-usual, and high-resource dependency) integrated with regional planning parameters. …”
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Physical activity in the relationship between multiple air pollutants exposure and risk of hypertension: a prospective cohort study in China by Yuquan Chen, Yanwei You, Jiarong He, Yuechuan Zhang, Qi Zhang, Fan Yang, Mingming Zhang

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The risk of a mosquito-borne infection in a heterogeneous environment. by David L Smith, Jonathan Dushoff, F Ellis McKenzie

“…These models predict that the human biting rate is highest shortly after the mosquito densities peak, near breeding sites where adult mosquitoes emerge, and around the edges of areas where humans are aggregated. …”
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