A Comprehensive Review of Safety Monitoring Technologies for Concrete Face Rockfill Dams Addressing the Challenges of "Three Highs, One Deep, and One Narrow" by XIAO Sheng, YANG Jie, LU Xi, ZHOU Heng, CHENG Lin, MA Chunhui, TONG Fei

“…In the future, the predictive technology for the safety performance of CFRDs needs significant improvement. …”
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An edge sensitivity based gradient attack on graph isomorphic networks for graph classification problems by Srinitish Srinivasan, Chandraumakantham OmKumar

“…We experimentally validate this model on 4 benchmark datasets in the molecular property prediction literature where our model outperformed over 75% of all LLM-based architectures. …”
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Assessing climate risks from satellite imagery with machine learning: A case study of flood risks in Jakarta by Jeasurk Yang, Donghyun Ahn, Junbeom Bahk, Sungwon Park, Nurrokhmah Rizqihandari, Meeyoung Cha

“…Our research demonstrates that disaster-related risk measurement becomes more comprehensive and multi-faceted by including the following components: hazards, exposure, and vulnerability. Our model first maps hazard-related risks with geo-spatial data, then extends the model to incorporate exposure and vulnerability. …”
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Measurement of Suspended Sediment Concentration at the Outlet of the Yellow River Canyon: Using Sentinel-2 Images and Machine Learning by Genxin Song, Youjing Jiang, Xinyu Lei, Shiyan Zhai

“…Overall, the random forest model outperformed traditional methods in SSC prediction for sediment-laden rivers.…”
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Gaze Estimation Based on a Multi-Stream Adaptive Feature Fusion Network by Changli Li, Enrui Tong, Kao Zhang, Nenglun Cheng, Zhongyuan Lai, Zhigeng Pan

“…A parallel channel and spatial attention mechanism is employed to fuse low-dimensional eye and facial features, while an adaptive weight adjustment mechanism (AWAM) dynamically determines the contribution ratio of eye and facial features. …”
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Explainable artificial intelligence with temporal convolutional networks for adverse weather condition detection in driverless vehicles by Samah Alzanin

“…The CapsNet model is employed for feature extraction to recognize spatial hierarchies and capture intricate patterns from complex visual data. …”
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Depression detection based on dual path DCGAN data generation and classification-regression network by LU Jingxue, LI Hongyan, ZHENG Ruichao, QIN Ruizhen

“…Later, the addition of LPCC and Jitter features also improved the accuracy of model prediction to a certain extent. In the data enhancement part, when the original data set was used to predict depression scores, Acc, RMSE and MAE were 80.51%, 8.47 and 3.94, respectively. …”
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Applications and Advancements of Spaceborne InSAR in Landslide Monitoring and Susceptibility Mapping: A Systematic Review by Yusen Cheng, Hongli Pang, Yangyang Li, Lei Fan, Shengjie Wei, Ziwen Yuan, Yinqing Fang

“…We highlight advancements in key areas, including atmospheric delay correction, 3D landslide monitoring, failure time prediction, enhancements in spatial and temporal resolution, and integration with other technologies like the Global Navigation Satellite System (GNSS) and physical models. …”
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Investigation of the dynamic charge transport behaviours under electron beam irradiation of advanced insulation materials for aerospace applications by Guangyu Sun, Xiong Yang, Wentong An, Kun Huang, Xiaogang Qin, Baipeng Song, Guanjun Zhang

“…The model reveals the spatial–temporal evolutions of the current, charge density, and electric field distribution. …”
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Estimates of Effective Number of Breeders Identify Drivers of Decline in Mid‐Atlantic Brook Trout Populations by Zachary L. Robinson, Jason A. Coombs, Mark Hudy, Keith H. Nislow, Andrew R. Whiteley

“…The existence of numerous, spatially distinct populations poses substantial challenges for monitoring population status (e.g., abundance, recruitment, or occupancy). …”
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A Regionalization of Downscaled GCM Data Considering Geographical Features in a Mountainous Area by Soojun Kim, Jaewon Kwak, Hung Soo Kim, Yonsoo Kim, Narae Kang, Seung Jin Hong, Jongso Lee

“…Future rainfall levels have been predicted by downscaling the data from CNRM-CM3 climate model, which was simulated under the A1B scenario. …”
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Evolution Law of Longitudinal Deformation Curve and Release Coefficient of Viscoelastic Rock by WANG Jiachen, MENG Lingzan, ZHANG Dingli, LU Song, WEN Ming

“…Empirical formulas are fitted for the longitudinal deformation curve, including time, spatial, and spatiotemporal factors. The research conclusion can provide a more convenient method for predicting the deformation of soft rock tunnels.…”
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Network control energy reductions under DMT relate to serotonin receptors, signal diversity, and subjective experience by S. Parker Singleton, Christopher Timmermann, Andrea I. Luppi, Emma Eckernäs, Leor Roseman, Robin L. Carhart-Harris, Amy Kuceyeski

“…Using receptor distribution and pharmacokinetic information, we recapitulate DMT’s effects on global control energy trajectories, demonstrating control models can predict pharmacological effects on brain dynamics.…”
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Adjusting ITE’s Trip Generation Handbook for urban context by Kelly J. Clifton, Kristina M. Currans, Christopher D. Muhs

“…A number of policy-relevant built environment measures were used to estimate a set of nine models predicting an adjustment to ITE trip rates. …”
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Predator occupancy rates in a thinned ponderosa pine forest, Arizona: A pilot study by Kevin J. Barrett, Elizabeth L. Kalies, Carol L. Chambers

“…However, our inability to develop strong models that predicted predator occupancy indicates that higher sample sizes and more habitat covariates are needed. …”
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Investigation on the early pressure load characteristics of bubbles in near-field underwater explosion with condensed-phase CL-20 explosive detonation by Yi Hao, Zhenxin Sheng, Bo Yan, Teng Xie, Lunping Zhang, Haibin Mao, Jun Yu

“…Validation against 1D detonation wave tests confirms the accuracy of our burn model. Numerical simulations of cylindrical and spherical CL-20 charges under near-field conditions show good agreement with the experimental data, highlighting the model’s precision in predicting shock wave propagation and interface motion. …”
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Study on the Risk of Urban Population Exposure to Waterlogging in Huang-Huai Area Based on Machine Learning Simulation Analysis—A Case Study of Xuzhou Urban Area by Shuai Tong, Jiuxin Wang, Jiahui Qin, Xiang Ji, Zihan Wu

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Enhanced Blood Loss Quantification Using a Novel Multi-Wavelength Imaging Approach by Ara Abigail E. Ambita, Laura T. David, Catherine Sim Co, Prospero C. Naval

“…Lastly, an individualized interpretation for each surgical test gauze is provided, a useful tool to understand how the machine learning model predicts the absorbed blood volume.…”
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Enhancing Clear Radiance Generation for Geostationary Hyperspectral Infrared Sounder Using High Temporal Resolution Information by Di Di, Jun Li, Zhenglong Li, Jing Zheng, Xinya Gong

“…Abstract With high spatio‐temporal resolution geostationary hyperspectral infrared sounder (GeoHIS) observations, monitoring, and predicting rapidly changing weather events are expected to be improved with continuous information of 3D weather cube. …”
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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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