The refractive index of silver nanowire networks: a heuristic approach to the foundations of the optical constants, from experiment to theory by Amaury Baret, Julia Baumgarten, François Balty, Frédéric Rabecki, Jérémy Brisbois, Buyun Zheng, Daniel Bellet, Ngoc Duy Nguyen

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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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East Asian aerosol cleanup has likely contributed to the recent acceleration in global warming by Bjørn H. Samset, Laura J. Wilcox, Robert J. Allen, Camilla W. Stjern, Marianne T. Lund, Sharar Ahmadi, Annica Ekman, Maxwell T. Elling, Luke Fraser-Leach, Paul Griffiths, James Keeble, Tsuyoshi Koshiro, Paul Kushner, Anna Lewinschal, Risto Makkonen, Joonas Merikanto, Pierre Nabat, Larissa Narazenko, Declan O’Donnell, Naga Oshima, Steven T. Rumbold, Toshihiko Takemura, Kostas Tsigaridis, Daniel M. Westervelt

“…Here we show, using a large set of simulations from eight Earth System Models, how a time-evolving 75% reduction in East Asian sulfate emissions partially unmasks greenhouse gas-driven warming and influences the spatial pattern of surface temperature change. …”
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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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Quantifying the sources and health risks of groundwater nitrate via dual NO isotopes and Monte Carlo simulations in a developed planting-breeding area by Jianwei Liu, Shuo Qiao, Shilong Zhao, Hui Chen, Yong Wu, Donghao Li, Ping Liu, Ling Li

“…The analysis results revealed that the NO3− concentration ranged from 0.02 to 44.6 mg/L, with a mean value of 7.54 mg/L, along with a significant spatial variability. Analysis by combining stable isotopes (δ15N-NO3− and δ18O-NO3−) with the Bayesian isotope mixing model (MixSIAR) revealed that soil N (60.3 %) and manure and sewage (35.9 %) contributed the most NO3− in groundwater, followed by chemical N fertilizer (2.9 %) and atmospheric N deposition (0.8 %). …”
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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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Enhanced thyroid nodule detection and diagnosis: a mobile-optimized DeepLabV3+ approach for clinical deployments by Changan Yang, Muhammad Awais Ashraf, Mudassar Riaz, Pascal Umwanzavugaye, Kavimbi Chipusu, Hongyuan Huang, Yueqin Xu

“…Preprocessing steps, including noise reduction and contrast optimization, were applied to enhance image clarity. …”
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Exploring the Benefits of 3D Smart MRI in Resident Training and Surgical Planning for Transcervical Radiofrequency Ablation by Sepehr Janghorbani, Victoria Weprinsky, Alexandre Caprio, Tamatha Fenster, Bobak Mosadegh

“…Residents using Smart MRI reported higher confidence in identifying and treating all fibroids (83% vs. 43%) and rated their spatial understanding significantly higher on Likert-scale assessments (4.6 vs. 3.25). …”
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Investigating the Dynamic Change and Driving Force of Vegetation Carbon Sink in Taihang Mountain, China by Qiushi Qu, Sihui Jian, Anguo Chen, Chiwei Xiao

“…The results of this study can not only provide a reference for carbon reduction and sink increase and ecological restoration projects in the Taihang Mountains but also benefit the research paradigm of vegetation carbon sequestration in other regions.…”
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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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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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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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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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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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Changes in habitat suitability for wintering dabbling ducks during dry conditions in the Central Valley of California by Erin E. Conlisk, Kristin B. Byrd, Elliott Matchett, Austen A. Lorenz, Michael Casazza, Gregory H. Golet, Mark D. Reynolds, Kristin A. Sesser, Matthew E. Reiter

“…Overall, species distribution models created using data on the environmental conditions present at the time of bird observations can aid conservation efforts under extreme conditions over large spatial scales.…”
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Increased Phosphorus Losses in the Food System in China and Region‐Specific Mitigation Strategies to Ensure Losses Below Safe Limits by Jichen Zhou, Wim deVries, Lin Ma, Xiaoqiang Jiao, Kai Zhang, Yang Lyu, Zed Rengel, Fusuo Zhang, Jianbo Shen

“…Here, we examined the trends and driving factors of (a) P losses from the food chain in 31 provinces in China over the period 1980–2016 and (b) predicted 2030 losses under different scenarios using the NUFER model and the Geographical Detector model. …”
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Prognostic Value of Deep Learning‐Extracted Tumor‐Infiltrating Lymphocytes in Esophageal Cancer: A Multicenter Retrospective Cohort Study by Peishen Li, Shujie Huang, Haijie Xu, Zijie Li, Sichao Wang, Zhen Gao, Yuejiao Dong, Zhuofeng Chen, Guibin Qiao, Hansheng Wu, Liangli Hong

“…Further studies should focus on the lymphocyte subgroups and make better use of the spatial information to improve the predictive efficacy of TILs.…”
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