Advancing plant biomass measurements: Integrating smartphone‐based 3D scanning techniques for enhanced ecosystem monitoring by Peter Dietrich, Melanie Elias, Peter Dietrich, Stanley Harpole, Christiane Roscher, Jan Bumberger

“…Additionally, results indicate significant effects of plant species richness and fertilization on biomass production and volume estimates, underscoring the potential for high‐resolution temporal and spatial analyses of vegetation dynamics. This method's innovation extends beyond traditional practices with implications for future integration of AI to automate species segmentation, ecological trait extraction and predictive modelling. …”
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Root growth and branching are enabled by brassinosteroid-regulated growth anisotropy and carbon allocation by Hitaishi Khandal, Guy Horev, Bas van den Herik, Yoram Soroka, Tamar Lahav, Tamar Avin-Wittenberg, Kirsten ten Tusscher, Sigal Savaldi-Goldstein

“…A newly developed “grow and branch” simulation model demonstrates that these shoot- and root-derived BR effects are sufficient to explain and predict root growth dynamics and branching phenotype in wild-type, BR-deficient mutants, and micro-graft combinations. …”
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Assessing climate change impacts on extreme hydrological characteristics of reservoir inflow in Tianshan Mountain Range, China by Xiaobo Yun, Jianwen Wang, Hongjun Bao

“…These insights help to deepen the comprehension of the changing characteristics of hydrological extremes induced by climate change in Tianshan Mountain Range reservoirs, and provide support for predicting hydrological extremes in other arid inland mountain regions.…”
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Geoinformatics-based prioritisation of natural resources rich regions at disaggregated levels for sustainable management by T. V. Ramachandra, Paras Negi

“…Modeling likely land uses through the simulation of long-term spatial variations of complex patterns has been done through the CA–Markov model. …”
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Dynamic interpretation of hedgehog signaling in the Drosophila wing disc. by Marcos Nahmad, Angelike Stathopoulos

“…Here, we provide evidence that the interpretation of Hh signaling depends on the history of exposure to Hh and propose that a single concentration threshold is sufficient to support multiple outputs. Using mathematical modeling, we predict that at steady state, only two domains can be defined in response to Hh, suggesting that the boundaries of two or more gene expression patterns cannot be specified by a static Hh gradient. …”
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Morphometric analysis for understanding river basin hydrology: a case of gelda watershed, Tana Sub-Basin, Ethiopia by Dessie Wubetu Melsse, Moges Animut Tegegne, Yitbarek Andualem Mekonnen, Yilak Taye Bihon

“…The research utilized ASTER Digital Elevation Model (DEM) data with a resolution of 12.5 m and ArcGIS 10.5 for spatial analysis. …”
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Frame topology fusion-based hierarchical graph convolution for automatic assessment of physical rehabilitation exercises by Shaohui Zhang, Qiuying Han, Peng Wang, Junjie Li

“…This method aims to provide a more precise assessment of rehabilitation movement quality by effectively modeling both spatial and temporal features. First, this method combines nearby and distant keypoints to construct a fused topology structure for obtaining the enhanced motion representation. …”
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GeoDGP: One‐Hour Ahead Global Probabilistic Geomagnetic Perturbation Forecasting Using Deep Gaussian Process by Hongfan Chen, Gabor Toth, Yang Chen, Shasha Zou, Zhenguang Huang, Xun Huan

“…The model takes solar wind measurements, the Dst index, and the prediction location in solar magnetic coordinate system as inputs, and is trained on 28 years of data from SuperMAG global magnetometer stations. …”
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IMPLEMENTATION OF MAPPING-BASED MACHINE LEARNING ALGORITHM AS NON-STRUCTURAL DISASTER MITIGATION TO DETECT LANDSLIDE SUSCEPTIBILITY IN TAKARI DISTRICT by Sefri Imanuel Fallo, Lidia Paskalia Nipu

“…Furthermore, further research could conduct spatial validation of the model predictions using additional datasets or remote sensing data to validate the accuracy of the landslide susceptibility map and ensure its applicability across different geographical regions.…”
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An ensemble machine learning bioavailable strontium isoscape for Eastern Canada by Mael Le Corre, Felipe Dargent, Vaughan Grimes, Joshua Wright, Steeve D. Côté, Megan S. Reich, Jean-Noël Candau, Marrissa Miller, Brent Holmes, Clement P. Bataille, Kate Britton

“…Adding local bioavailable 87Sr/86Sr to a global dataset significantly improved the model prediction with a drastic increase of predicted 87Sr/86Sr and increased spatial uncertainty in the northern Canadian craton. …”
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The glycolytic characteristics of hepatocellular carcinoma and its interaction with the microenvironment: a comprehensive omics study by Dan Chen, Dandan Lin, Huling Li, Jiandong Yang, Lei Liu, Hanyuan Zhang, Dandan Tang, Kai Wang

“…Through public data integration, 17 glycolysis-related DEGs were identified and 101 predictive models were constructed using machine learning. …”
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Hypoperfusion regions linked to National Institutes of Health Stroke Scale scores in acute stroke by Hana Kim, Alex Teghipco, Chris Rorden, Julius Fridriksson, Mathew Chaves, Argye E. Hillis

“…Additionally, we used stability selection to identify the most consistent features across subsets, reducing overfitting and ensuring robust predictive models. We verified the consistency of results through nested cross-validation. …”
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Fast and Accurate Plane Wave and Color Doppler Imaging with the FOCUS Software Package by Jacob S. Honer, Robert J. McGough

“…Simulation results demonstrate rapid convergence and lower error rates compared to conventional spatial impulse response methods and Field II, resulting in substantial reductions in computation time. …”
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A Framework for High-Spatiotemporal-Resolution Soil Moisture Retrieval in China Using Multi-Source Remote Sensing Data by Zhuangzhuang Feng, Xingming Zheng, Xiaofeng Li, Chunmei Wang, Jinfeng Song, Lei Li, Tianhao Guo, Jia Zheng

“…This indicates that multi-source data can provide complementary information for SM monitoring. (2) Compared to XGBoost and LSTM, RFR and EL demonstrate superior overall performance and are the preferred models for SM prediction. Their R² for the training and test sets exceed 0.969 and 0.743, respectively, and their ubRMSE are below 0.022 and 0.063 m³/m³, respectively. (3) The SM prediction accuracy is highest for the scenario of optical + SAR + auxiliary data, followed by SAR + auxiliary data, and finally optical + auxiliary data. (4) With an increasing Normalized Difference Vegetation Index (NDVI) and SM values, the trained models exhibit a general decrease in prediction performance and accuracy. (5) In 2021 and 2022, without considering cloud cover, the IF theoretically achieved an SM revisit time of 1–3 days across 95.01% and 96.53% of China’s area, respectively. …”
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An MCMC Approach to Bayesian Image Analysis in Fourier Space by Konstantinos Bakas, John Kornak, Hernando Ombao

“…Bayesian image analysis methods are commonly applied to solve image analysis problems such as noise reduction, feature enhancement, and object detection. …”
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SkelETT—Skeleton-to-Emotion Transfer Transformer by Pedro Victor Vieira Paiva, Josue Junior Guimaraes Ramos, Marina Gavrilova, Marco Antonio Garcia de Carvalho

“…By exposing the model to an extensive corpus of unlabeled human skeleton data, we can effectively learn to represent complex spatial and temporal dependencies inherent in body movements. …”
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Research on the Evaluation of the Node Cities of China Railway Express Based on Machine Learning by Chenglin Ma, Mengwei Zhou, Wenchao Kang, Haolong Wang, Jiajia Feng

“…The Random Forest model outperformed comparative algorithms with 99.5% prediction accuracy (8.33% higher than conventional classification models), particularly in handling multi-dimensional interactions between urban development factors. …”
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High Resolution Sea Ice Concentration Using a Sentinel-1 U-Net Ice-Water Classifier by Jozef Rusin, Anthony P. Doulgeris, K. Andrea Scott, Thomas Lavergne, Catherine Taelman

“…We trained the U-Net across multilooking levels to balance resolution, noise reduction, and computational efficiency, allowing the model to handle noise artefacts effectively. …”
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Research on step-by-step visual servo control system of anchor drilling robot by Mengyu LEI, Xuhui ZHANG, Wenjuan YANG, Jicheng WAN, Yuyang DU, Henghan YU, Chenhui TIAN

“…Secondly, through displacement and angular sensors deployed on manipulator joints, this study constructed an enhanced kinematic model using the modified Denavit-Hartenberg (MDH) method, enabling accurate spatial position resolution of the end-effector and determination of its initial and target positions. …”
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Weapon detection with FMR-CNN and YOLOv8 for enhanced crime prevention and security by Shanthi P, Manjula V

“…Such a combination enables the concurrent utilization of high-resolution spatial context information and rapid frame-wise predictions, thus making it well-suited for continuous video surveillance tasks. …”
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