All is not loss: plant biodiversity in the anthropocene. by Erle C Ellis, Erica C Antill, Holger Kreft

“…While global observing systems and models that integrate anthropogenic species loss, introduction and invasion at regional landscape scales remain at an early stage of development, integrating predictions from existing models within a single assessment confirms their vast global extent and significance while revealing novel patterns and their potential drivers. …”
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Improved leaf area index reconstruction in heavily cloudy areas: A novel deep learning approach for SAR-Optical fusion integrating spatiotemporal features by Mingqi Li, Pengxin Wang, Kevin Tansey, Fengwei Guo, Ji Zhou

“…Secondly, the 2D CNN-Transformer predicted LAI and the Sentinel-2 LAI are input into the Enhanced Deep Convolutional Model for Spatiotemporal Image Fusion (EDCSTFN) model to further improve the accuracy. …”
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Building occupancy type classification and uncertainty estimation using machine learning and open data by Tom Narock, J. Michael Johnson, Justin Singh-Mohudpur, Arash Modaresi Rad

“…We demonstrate how existing open-source datasets can be spatially integrated and subsequently used as training for machine learning (ML) models to predict building occupancy type, a major component needed for disaster preparedness and decision -making. …”
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Modular Mobile Charging Facility Layout Optimization Method and Deployment Strategy by Jiajun ZHENG, Xiaoyu DUAN, Zechun HU, Xiaorui HU, Bin ZHU

“…Firstly, an electric vehicle user travel mechanism model is established to predict the spatial and temporal distribution of charging demand at the node level. …”
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The BIRDIES Experiment: Measuring Beryllium Isotopes to Resolve Dynamics in the Stratosphere by Sonia Wharton, Alan J. Hidy, Thomas S. Ehrmann, Wenbo Zhu, Shaun N. Skinner, Hassan Beydoun, Philip J. Cameron-Smith, Marisa Repasch, Nipun Gunawardena, Jungmin M. Lee, Ate Visser, Matthew Griffin, Samuel Maddren, Erik Oerter

“…While the spatial patterns in rainfall suggested some evidence for overshooting convection, inter-event temporal variability was clearly observed and predicted with good agreement using the 3D chemical transport model GEOS-CHEM.…”
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Storm water runoff studies in built-up watershed areas using curve number and remote sensing techniques by Arati Reddy Nilap, H. N. Rajakumara, Ali Aldrees, Hasan Sh. Majdi, Wahaj Ahmad Khan

“…The model satisfactorily predicted runoff from the simulated data analysis with evaluation criteria NSE = 0.9945, MAE = 5.4121, r = 0.9975, R2 = 0.9949, RMSE = 6.8117 and PBias = 1.1436. …”
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Energy-efficient human-like trajectory planning for wheeled robots in unstructured environments based on the RCSM-PL network by Hao Xu, Guanyu Zhang, Huanyu Zhao

“…Experimental results show that, compared with traditional and state-of-the-art methods, the proposed approach significantly reduces cumulative power consumption and improves accuracy in predicting future trajectories. The model effectively learns human manipulation behaviors and demonstrates superior energy-saving performance in complex driving scenarios.…”
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Transverse dynamics of charmed hadrons in ultra-relativistic nuclear collisions by Anton Andronic, Peter Braun-Munzinger, Hjalmar Brunßen, Jana Crkovská, Johanna Stachel, Vytautas Vislavicius, Martin Völkl

“…The investigations are performed within the framework of the Statistical Hadronization Model with the transverse dynamics evaluated using predictions from relativistic viscous hydrodynamics as implemented in the computer codes MUSIC and FluiduM. …”
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Spatiotemporal dynamics of future hydrology in the Pearl River Basin: Controls of climate change and land surface by Ying Zhang, Jianping Gan

“…Driven by an optimized subset of General Circulation Models through a comprehensive framework of multi-level calibrations, we employed a well-validated Soil and Water Assessment Tool to predict streamflow and investigate the underlying dynamics in the basin. …”
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How Do Particles with Complex Interactions Self-Assemble? by Lara Koehler, Pierre Ronceray, Martin Lenz

“…We then successfully identify the most relevant aspect of the interaction complexity in predicting these outcomes, namely, the particles’ ability to form periodic structures. …”
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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

“…The length scale is predicted and a quantitative description of the inverted growth phenomenon is given. …”
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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

“…Approximately 75 % of the annual catch of chub mackerel was caught at the predicted sites in 2020; this portion reached 84 % in the period of the highest catches.…”
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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

“…Therefore, we propose a novel method that combines the skeletal method with object detection to accurately predict a set of $ \langle $ human, verb, object $ \rangle $ triplets in a video frame considering the robustness, extensibility, and lightweight of the model. …”
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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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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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A GAN Guided NCCT to CECT Synthesis With an Advanced CNN-Transformer Aggregated Generator by Haozhe Wang, Dawei Gong, Rongzhen Zhou, Junbo Liang, Ruili Zhang, Wenbin Ji, Sailing He

“…MSPHAB consists of spatial self-attention and channel self-attention in parallel. …”
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Adaptive mechanisms of social and asocial learning in immersive collective foraging by Charley M. Wu, Dominik Deffner, Benjamin Kahl, Björn Meder, Mark K. Ho, Ralf H.J.M. Kurvers

“…Here, we use a collective foraging task in a virtual Minecraft environment to integrate these two fields, by leveraging automated transcriptions of visual field data combined with high-resolution spatial trajectories. Our behavioral analyses capture both the structure and temporal dynamics of social interactions, which are then directly tested using computational models sequentially predicting each foraging decision. …”
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