Dual-Channel Dynamic Gated Spatio-Temporal Graph for Traffic Flow Forecasting by Chao Wang, Jun-Feng Hao, He Huang, Wang Zou, Xia Sun, Ting Peng

“…Additionally, the predefined static graph structure fails to adequately capture the dynamic spatial features of traffic flow. To address the these challenges, this paper proposes a Dual-Channel Dynamic Gated Spatio-Temporal graph network (DC-DGST) for traffic flow prediction. …”
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Water pollution and water quality assessment and application of criterion impact loss (CILOS), geographical information system (GIS), artificial neural network (ANN) and decision-l... by Abhijeet Das

“…Based on the results, the strongest association between the best qualities and the WQI was shown by the ANN, which proved to be the most accurate prediction model. The 13 characteristics found in the model were quite significant and demonstrated good performance in predicting the WQI with a respectable level of accuracy. …”
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Multiscale Two-Stream Fusion Network for Benggang Classification in Multi-Source Images by Xuli Rao, Chen Feng, Jinshi Lin, Zhide Chen, Xiang Ji, Yanhe Huang, Renguang Chen

“…Experimental comparisons of different data inputs and network models revealed that the proposed method outperformed current state-of-the-art approaches in extracting spatial features and textures of Benggangs. …”
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AI-augmented pathology: the experience of transfer learning and intra-domain data diversity in breast cancer metastasis detection by Manuel Cossio, Nina Wiedemann, Esther Sanfeliu Torres, Esther Barnadas Sole, Laura Igual

“…To enhance interpretability, we developed a visualization tool that employs color-coded probability maps to highlight tumor regions alongside their prediction confidence. Our experiments demonstrated that integrating an external dataset (Camelyon16) during training significantly improved model performance, surpassing the benefits of data augmentation alone. …”
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Attention residual network for medical ultrasound image segmentation by Honghua Liu, Peiqin Zhang, Jiamin Hu, Yini Huang, Shanshan Zuo, Lu Li, Mailan Liu, Chang She

“…Finally, the predictive efficacy of the model was evaluated using publicly accessible breast ultrasound and thyroid ultrasound data. …”
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Hippocampal vascularization pattern and cerebral blood flow cooperatively modulate hippocampal tolerable amount of Aβ deposition in the occurrence of MCI by Yuhao Xu, Hong Wei, Rui Du, Ranchao Wang, Yan Zhu, Tian Zhao, Xiaolan Zhu, Yuefeng Li

“…We explored the relationships between hippocampal blood supply (VP and CBF), hippocampal PiB uptake, and the occurrence of mild cognitive impairment (MCI) using a generalized nonlinear model. Results We demonstrated the synergistic effect of hippocampal VP and CBF on predicting the occurrence of MCI. …”
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Building the foundation for international conservation planning for breeding ducks across the U.S. and Canadian border. by Kevin E Doherty, Jeffrey S Evans, Johann Walker, James H Devries, David W Howerter

“…Our spatial population models were able to identify key areas for duck conservation across the PPR and predict between 62.1-79.1% (68.4% avg.) of the variation in duck counts by year from 2002-2010. …”
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Spatio-Temporal Coupling and Forecasting of Construction Industry High-Quality Development and Human Settlements Environmental Suitability in Southern China: Evidence from 15 Provi... by Keliang Chen, Bo Chen, Wanqing Chen

“…Using panel data for 15 southern provinces (2013–2022), we applied the entropy method, coupling coordination model, Dagum Gini coefficient, spatial trend surface analysis, gravity model, and grey forecasting to evaluate current conditions and predict future trends. …”
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Study on the influence of complex fault geometry on earthquake risk assessment based on physical simulation: a case study of the Zhujiangkou Fault in the Guangdong–Hong Kong–Macao... by Houyun Yu, Yilong Li, Xiuwei Ye, Wenqiang Wang, Chunjing Wang, Zhenguo Zhang, Wei Zhang, Xiaofei Chen

“…Dynamic rupture simulations offer a physics-based approach to model earthquake processes and assess seismic hazards. …”
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Detection of Apple Proliferation Disease Using Hyperspectral Imaging and Machine Learning Techniques by Uwe Knauer, Sebastian Warnemünde, Patrick Menz, Bonito Thielert, Lauritz Klein, Katharina Holstein, Miriam Runne, Wolfgang Jarausch

“…Prediction of qPCR results by regression based on spectral data achieved RMSE of 14.491 phytoplasma per plant cell.…”
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Assessment of relationship between sea surface temperature (SST) changes and precipitation types in Nigeria from 2000 to 2022 by Tertsea Igbawua, Fanan Ujoh, Solomon Kwaghfan Mkighirga, Grace Adagba

“…The analysis of NIF values indicates a varied but generally stronger relationship between WAf SST anomalies and precipitation types compared to nino3.4 SST versus precipitation types. As a signal for prediction of seasonal and spatial distribution of precipitation across Nigeria’s different climatic zones, this outcome can support planning for food security, water and biodiversity conservation, and climate change adaptation and mitigation.…”
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Mesoscale Numerical Simulation and Cloud Microphysical Characteristics of the Warm Zone Blizzard in Northern Xinjiang by Anbei LI, Chenxiang JU, Yaman ZHOU, Man LI, Ruqi LI

“…The warm zone blizzard are both infrequent and highly destructive， making their accurate prediction a challenging and crucial focus.This study utilized four distinct cloud microphysics schemes （Lin， Thompson， WDM6， and WSM6） within the WRF mesoscale model to conduct a numerical simulation of a typical warm zone blizzard process in the northern Xinjiang in the middle of November 2016.The research objectives encompassed the evaluation of the model's capacity to simulate the warm zone blizzard， the selection of an optimal parameterization scheme， an analysis of the vertical distribution and evolution of hydrometeors during the snowstorm， and an exploration of the developmental patterns of related mesoscale systems contributing to the snowstorm.The analysis yielded the following key findings： （1） Among the diverse cloud microphysics parameterization schemes tested， the Lin scheme demonstrated the most favorable performance， effectively simulating snowfall magnitudes， spatial distributions， and trends.（2） In the cloud， all kinds of water condensate particles are active in the lower and middle troposphere， with graupel and snow being the most.Ice crystals， snow， cloud water and graupel particles are distributed from the upper layer to the lower layer.Near the windward slope of Altai Mountain is the center of the large concentration of each water condensate particle.The vertical alignment of the high value center of the four kinds of cloud water condensate particles in the strong snowfall area is conducive to the transformation of each particle.（3） High-humidity systems upstream moved westward， with the intensification of low-level southward jet streams resulting in pronounced moisture convergence.The western foothills of the Altai Mountains acted as a barrier， promoting moisture convergence by blocking the windward side； The low-level southerly jet also provides a continuous updraft and unstable condition for the generation of the blizzard.Strong snowfall is located in a wide updraft area between two groups of secondary circulations.The explosive growth of vertical movement is conducive to triggering the release of unstable energy， providing strong dynamic lifting conditions for the development and maintenance of the blizzard.…”
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On the Universality of the Split Monopole Black Hole Magnetosphere by S. Selvi, O. Porth, B. Ripperda, L. Sironi

“…Our results enable a quantitative prediction of the timescales and spatial structure of these evolving magnetospheres, essential for understanding electromagnetic counterparts to gravitational wave events and reconnection-powered flares from accreting BHs.…”
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Quality Assessment of MRI-Radiomics-Based Machine Learning Methods in Classification of Brain Tumors: Systematic Review by Shailesh S. Nayak, Saikiran Pendem, Girish R. Menon, Niranjana Sampathila, Prakashini Koteshwar

“…Machine learning algorithms such as deep learning networks, support vector machines, random forests, and logistic regression were applied to develop predictive models. Conclusions: The present study indicates high accuracies in glioma classification, outperforming traditional imaging methods and inexperienced radiologists in some cases. …”
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Epigenetic-modification associated hnRNPA3 acts as a prognostic biomarker and promotes malignant progression of HCC by Xufan Cai, Weihui Guo, Fang Wu, Weilang Xu, Tao Ding, Yizhe Diao, Lei Wang, Zhenyuan Qian, Guangyuan Song

“…Logistic regression, receiver operating characteristic curve (ROC), Kaplan–Meier analysis, and nomogram modeling were used to evaluate prognostic values of hnRNPA3 in HCC. hnRNPA3 level in cell subtypes in HCC tumor microenvironment was analysed through spatial transcriptomic. …”
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Vision transformer embedded video anomaly detection using attention driven recurrence by Ummay Maria Muna, Shanta Biswas, Syed Abu Ammar Muhammad Zarif, Philip Jefferson Deori, Tauseef Tajwar, Swakkhar Shatabda

“…To further enhance the multiclass prediction performance, we develop a cluster-based weighting mechanism that assigns weights to classification scores based on feature similarity. …”
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Temperature field study of LSAM-50 flexible base asphalt pavement by Yufeng Bi, Minghao Mu, Mengyu Guo, Wanyu Wu, Tingting Ding, Chengduo Qian, Deshui Yu, Yingjun Jiang, Hongjian Su

“…Although numerous studies on pavement temperature distribution and prediction models have been conducted both domestically and internationally, significant differences still exist in the temperature distribution of pavements with varying structures and materials, as well as in different regions and terrains.…”
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Enhanced YOLOv10 Framework Featuring DPAM and DALSM for Real-Time Underwater Object Detection by Suthir Sriram, Aburvan P., Arun Kaarthic T. P., Nivethitha Vijayaraj, Thangavel Murugan

“…The marine fusion loss (MFL) provides an object detection prediction that combines both binary cross-entropy loss and complete intersection over union (CIoU) loss to enhance bounding box localization while also including spatial context to incorporate important underwater features. …”
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Progressive Guided Fusion Network With Multi-Modal and Multi-Scale Attention for RGB-D Salient Object Detection by Jiajia Wu, Guangliang Han, Haining Wang, Hang Yang, Qingqing Li, Dongxu Liu, Fangjian Ye, Peixun Liu

“…The depth map contains abundant spatial structure cues, which makes it extensively introduced into saliency detection tasks for improving the detection accuracy. …”
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Enhanced simulation of gross and net carbon fluxes in a managed Mediterranean forest by the use of multi-sensor data by Marta Chiesi, Nicola Arriga, Luca Fibbi, Lorenzo Bottai, Luigi D'Acqui, Alessandro Dell’Acqua, Sara Di Lonardo, Lorenzo Gardin, Maurizio Pieri, Fabio Maselli

“…The proposed advancements are aimed at improving the model performance in managed Mediterranean forests and concern: i) the calibration of C-Fix GPP sensitivity to water stress; ii) the quantification of the green, woody and soil C pools which regulate the prediction of NPP and NEP. …”
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