Meteorological Anomalies During Earthquake Preparation: A Case Study for the 1995 Kobe Earthquake (M = 7.3) Based on Statistical and Machine Learning-Based Analyses by Masashi Hayakawa, Shinji Hirooka, Koichiro Michimoto, Stelios M. Potirakis, Yasuhide Hobara

“…We have utilized a combinational use of NARX (Nonlinear Autoregressive model with eXogenous inputs) and Long Short-Term Memory (LSTM) models, which was successful in objectively re-confirming the anomalies in both parameters on the same day prior to the EQ. …”
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The Impact of Land Circulation on Common Prosperity in the Digital Economy Context by Cong Xu, Feng Wu, Jingran Lin, Yie-Ru Chiu

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An annual 30 m cultivated-pasture dataset of the Tibetan Plateau from 1988 to 2021 by B. Han, J. Bi, S. Tao, T. Yang, Y. Tang, M. Ge, H. Wang, Z. Jin, J. Dong, Z. Nan, J.-S. He, J.-S. He

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How does academic self-efficacy influence learning anxiety and academic burnout in Chinese characters learning among international students in China? by Yang Lin

“…BackgroundThe interplay between learning self-efficacy, anxiety, and burnout has been extensively documented in English as a Second Language (ESL) education. However, Chinese character learning—a uniquely complex task involving visual–spatial processing, stroke order mastery, and radical decomposition—presents distinct cognitive and affective challenges. …”
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Rhetoric of allegorical formation in Maqamat Ayed Al-Qarni by Salih Mala Aziz  ,  Yahya Mahmoud Ahmed

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Integrating Temporal Vegetation and Inundation Dynamics for Elevation Mapping Across the Entire Turbid Estuarine Intertidal Zones Using ICESat-2 and Sentinel-2 Data by Siqi Yao, Jianrong Zhu, Wanying Zhang, Bo Tian, Weiwei Sun, Weiguo Zhang, Weiming Xie, Pengjie Tao, Chunpeng Chen, Kai Tan

“…These two features effectively utilize the variations observed in different regions and land covers within the Sentinel-2 image series caused by the unique tide periodic fluctuation phenomenon and elevation trend law in intertidal zones, thereby rendering the method applicable to elevation prediction across the entire spatial range of intertidal zones, rather than being limited to nonvegetated regions. …”
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Toward 6G: Deep GRU and RNN Empowered MVDR and LCMV Adaptive Beamformers for IRS-Aided Wireless Environments by D. L. Sharini, Ravilla Dilli, M. Kanthi, G. D. Goutham Simha

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Unraveling nonlinear effects of environment features on green view index using multiple data sources and explainable machine learning by Cai Chen, Jian Wang, Dong Li, Xiaohu Sun, Jiyong Zhang, Changjiang Yang, Bo Zhang

“…Our research results show that: (1) Within the Sixth Ring Road of Beijing, GVI shows significant spatial clustering phenomenon and positive correlation linkage, and at the same time exhibits significant spatial differences; (2) Among many environmental variables, the increase of green coverage rate has the most significant positive effect on GVI, while the increase of building density shows a strong negative correlation with GVI; (3) The performance of the GWRF model in predicting GVI is excellent and far exceeds that of comparison models.; (4) Whether it is the green coverage rate, urban built environment or socioeconomic factors, their influence on GVI shows non-linear characteristics and a certain threshold effect. …”
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A Shared Control Method of Multiobjective Motion Fusion for Surgical Robot by Xilin Xiao, Xiaojian Li, Hangjie Mo, Yudong Shi, Jing Fang, Ling Li, Bo Ouyang, Shanlin Yang

“…In addition, a state feedback mechanism with prediction and evaluation model is developed to balance the control inputs of different control objectives. …”
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Bayesian approach for localizing cardiac sources in Magnetocardiography using Vectorcardiography based total variational priors by Vikas R. Bhat, Karunakar Kotegar, H. Anitha

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Novel post-translational modification learning signature reveals B4GALT2 as an immune exclusion regulator in lung adenocarcinoma by Ge Zhang, Zhenfa Zhang, Lianmin Zhang, Guangyao Zhou, Pengpeng Zhang, Dingli Wang, Shuai Jiang

“…The signature’s efficacy in predicting immunotherapy response was evaluated using 12 immunotherapy cohorts spanning multiple cancer types (n=1201). …”
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Local Diversity-Guided Weakly Supervised Fine-Grained Image Classification Method by Yuebo Meng, Xianglong Luo, Hua Zhan, Bo Wang, Shilong Su, Guanghui Liu

“…To address this problem, we propose a weakly supervised fine-grained classification network model with Local Diversity Guidance (LDGNet). We designed a Multi-Attention Semantic Fusion Module (MASF) to build multi-layer attention maps and channel–spatial interaction, which can effectively enhance the semantic representation of the attention maps. …”
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The dynamic theoretical analysis of performance characteristics for open-cycle absorption energy storage system using HCOOK-H2O as the working fluid under full and partial mode by Yaqi Ding, Qingpu Li, Bicui Ye, Muhammad Kashif Shahzad, Neng Gao, Guangming Chen

“…Open absorption energy storage systems can efficiently address the temporal and spatial mismatches between the solar energy driving heat source and the user. …”
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Spectral purification improves monitoring accuracy of the comprehensive growth evaluation index for film-mulched winter wheat by Zhikai Cheng, Xiaobo Gu, Yadan Du, Zhihui Zhou, Wenlong Li, Xiaobo Zheng, Wenjing Cai, Tian Chang

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A Novel Dense-Swish-CNN With Bi-LSTM Framework for Image Deepfake Detection by B. C. Soundarya, H. L. Gururaj

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MFGC-Net: Bridging and Fusing Multiscale Features and Global Contexts for Multitask Sea Ice Fine Segmentation by Tianen Ma, Xinwei Chen, Linlin Xu, Pengfei Ma, Peilin Yu

“…Subsequently, a context transformer block based on efficient multihead self-attention was developed to model remote dependencies across spatial and channel dimensions, thereby enhancing the extraction of multiscale global contextual information. …”
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Data Mining Between Classical and Modern Applications: A Review by Ammar Yaseen Abd Alazeez

“…It includes four sub-groups: a) Classification, Prediction and Regression, b) Clustering, c) Association Rule and Sequence Pattern Mining, and d) Outliers and Anomaly Detection. …”
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An Autism Spectrum Disorder Identification Method Based on 3D-CNN and Segmented Temporal Decision Network by Zhiling Liu, Ye Chen, Xinrui Dong, Jing Liu

“…The concatenated spatiotemporal features are classified using Gradient Boosting Decision Trees (GBDTs), and finally, a voting mechanism is applied to determine whether the subject belongs to the ASD group based on the prediction results. This approach not only enhances the efficiency of spatiotemporal feature extraction but also improves the model’s ability to learn complex brain activity patterns. (3) Results: The proposed method was evaluated on the ABIDE dataset, which includes 1035 subjects from 17 different brain imaging centers. …”
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Application of Ensemble Kalman Filter With Covariance Localization in Data Assimilation of Radiation Belt Electrons by Yuan Lei, Xing Cao, Binbin Ni, Taorong Luo, Xiaoyu Wang

“…As a result, EnKF has emerged as an increasingly important tool for the reanalysis and prediction of highly dynamic variations of energetic electrons in Earth's radiation belt. …”
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Infra-3DRC-FusionNet: Deep Fusion of Roadside Mounted RGB Mono Camera and Three-Dimensional Automotive Radar for Traffic User Detection by Shiva Agrawal, Savankumar Bhanderi, Gordon Elger

“…These anchors guide the prediction of 2D bounding boxes, object categories, and confidence scores. …”
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