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

“…Thereto, we used Random Forest (RF), Support Vector Regression (SVR), and Partial Least Squares (PLS) models and found that the best fitting model depended on the type of spectral sensor. …”
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Deep reinforced cognitive analytics algorithm (DRCAM): An advanced method to early detection of cognitive skill impairment using deep learning and reinforcement learning by Sunita Patil, Dr. Swetta Kukreja

“…This study proposes a novel approach combing Multimodal Transformers (MMT) for fusion features, namely, neuroimaging data, wearable sensors, neuropsychological test scores, and text pro-appraisals. A CNN-LSTM hybrid model is used for mapping spatial and temporal dependencies, and, on the other hand, a Deep Q-Network (DQN) improves while instructing how to perform proper cognitive training. …”
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Effective human–object interaction recognition for edge devices in intelligent space by Haruhiro Ozaki, Dinh Tuan Tran, Joo-Ho Lee

“…Given the need for advanced machine-learning systems that provide spatial analysis and services, the recognition model should be robust to various changes, have high extensibility, and provide sufficient recognition speed even with minimal computational overhead. …”
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How Do Particles with Complex Interactions Self-Assemble? by Lara Koehler, Pierre Ronceray, Martin Lenz

“…However, current self-assembly models typically ignore this aspect, and the principles by which it determines the large-scale structure of protein assemblies are largely unknown. …”
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Land cover as a driver of fish community changes in New York's Oswego River Watershed. by Kate M Henderson, Megan Hazlett, Joshua A Drew

“…Land cover exerts a powerful influence on aquatic communities at multiple spatial scales, and alterations to systems can persist even after restoration actions are taken. …”
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Selection Theory of Dendritic Growth with Anisotropic Diffusion by Martin von Kurnatowski, Klaus Kassner

“…Any physical solution should include this feature. A simple spatial rescaling is used to reduce the bulk equation in 2D to the case of isotropic diffusion. …”
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PROGRAMA INNOVADOR PARA EVALUAR USO Y PREFERENCIA DE HÁBITAT by Javier Montenegro, Alberto Acosta

“…This topic is high priority due to the rapid climatic changesthat, according to model predictions, will directly or indirectly affect the resources, conditions and therefore itshabitat, modifying its abundance, spatial distribution, and local probability of extinction. …”
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Information support for chub mackerel Scomber japonicus fishery in the Pacific waters of the Russian Federation by E. P. Chernienko, I. S. Chernienko

“…The model was trained on the data for 2016–2019 and verified on the data for 2020. …”
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Rain‐Induced Surface Sensible Heat Flux Reduces Monsoonal Rainfall Over India by Xin Zhou, Pallav Ray, Haochen Tan, Jimy Dudhia, R. S. Ajayamohan, Helber Gomes, Yipeng Pan

“…This reduction was primarily due to a reduction in vertical advection of moisture. …”
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Epidemiological Characteristics of Human Rabies in Urban and Suburban Districts in Shanghai, 2006–2021 by Zhi Li, Jiayu Hu, Zhuoying Huang, Xiang Guo, Jia Ren, Jing Qiu, Xiaoying Ma, Han Yan, Fang Huang, Xiaodong Sun

“…Infection risk was predicted with a Bayesian aggression model. A total of 43 human rabies cases were registered in Shanghai in 2006–2021; the annual average incidence rate was 0.01/100000. …”
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MGNN: Moment Graph Neural Network for Universal Molecular Potentials by Jian Chang, Shuze Zhu

“…Abstract The quest for efficient and robust deep learning models for molecular systems representation is increasingly critical in scientific exploration. …”
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Covid-19 pandemic data analysis using tensor methods by Dipak Dulal, Ramin Goudarzi Karim, Carmeliza Navasca

“…Second, we implement a tensor completion algorithm using canonical polyadic tensor decomposition to predict spatiotemporal data from multiple spatial sources and to identifyCovid-19 hotspots. …”
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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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Research on status monitoring and positioning compensation system for digital twin of parallel robots by Yuting Zhang, Pei Gao, Zongyan Wang, Quanling He

“…Initially, the digital twin framework is constructed. Establishing a spatial kinematics model that serves as the foundation for the twin model, the kinematics model facilitates basic synchronized interaction. …”
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Clustering of Floating Tracer Due to Mesoscale Vortex and Submesoscale Fields by Dmitry V. Stepanov, Eugene A. Ryzhov, Alexei A. Zagumennov, Pavel Berloff, Konstantin V. Koshel

“…We found that the mesoscale vortices do not prevent clustering but significantly modify its rate and spatial pattern. We also demonstrated that even weak surface‐velocity divergence has to be taken into account to avoid significant errors in model predictions of the floating tracer patterns. …”
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All is not loss: plant biodiversity in the anthropocene. by Erle C Ellis, Erica C Antill, Holger Kreft

“…Here we explore contemporary anthropogenic global patterns in vascular plant species richness at regional landscape scales by combining spatially explicit models and estimates for native species loss together with gains in exotics caused by species invasions and the introduction of agricultural domesticates and ornamental exotic plants. …”
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Tropical precipitation extremes: Response to SST‐induced warming in aquaplanet simulations by Ritthik Bhattacharya, Simona Bordoni, João Teixeira

“…Abstract Scaling of tropical precipitation extremes in response to warming is studied in aquaplanet experiments using the global Weather Research and Forecasting (WRF) model. We show how the scaling of precipitation extremes is highly sensitive to spatial and temporal averaging: while instantaneous grid point extreme precipitation scales more strongly than the percentage increase (∼7% K−1) predicted by the Clausius‐Clapeyron (CC) relationship, extremes for zonally and temporally averaged precipitation follow a slight sub‐CC scaling, in agreement with results from Climate Model Intercomparison Project (CMIP) models. …”
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“Sunshade World”: A fully coupled GCM evaluation of the climatic impacts of geoengineering by D. J. Lunt, A. Ridgwell, P. J. Valdes, A. Seale

“…We investigate the magnitude and nature of this climate change for the first time within a fully coupled General Circulation Model. We find significant cooling of the tropics, warming of high latitudes and related sea ice reduction, a reduction in intensity of the hydrological cycle, reduced ENSO variability, and an increase in Atlantic overturning. …”
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A New Climate vulnerability Index Sistan and Baluchistan province by esmaeail ahmadi, zahra hejazizadeh, bohlol alijani, Mohammad saligheh, Hassan danaie fard

“…Area with very high vulnerability label expanded from 57.5% to 100%, which reflects the spatial expansion of vulnerability over SB. The overall result is that vulnerability reduction needs for accurate and continuous measurement, on the increase adaptation capacity and mitigate climate sensitivity.…”
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Lessons learned from the co-development of operational climate forecast services for vineyards management by N. Pérez-Zanón, V. Agudetse, E. Baulenas, P.A. Bretonnière, C. Delgado-Torres, N. González-Reviriego, A. Manrique-Suñén, A. Nicodemou, M. Olid, Ll. Palma, M. Terrado, B. Basile, F. Carteni, A. Dente, C. Ezquerra, F. Oldani, M. Otero, F. Santos-Alves, M. Torres, J. Valente, A. Soret

“…The workflow includes the downscaling of model outputs to increase their spatial resolution, the storage of sub-seasonal climate forecasts at daily frequencies to feed phenological impact models, the provision of past climate simulations to train the impact models, the bias-adjust of climate forecasts to reduce systematic model errors, the assessment of the climate forecasts to aware users on their quality and the deployment of a server to allow access to impact modellers.The variables provided are mean, minimum and maximum temperature, accumulated precipitation and solar radiation. …”
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