Extended Kalman filter on sparse identification of nonlinear systems: application to the SoC estimation of a phase change material-based energy storage by Mustapha Habib, Youssef Elomari, Felix Hochwallner, Adam Buruzs, Tilman Barz, Qian Wang

“…Since SoC is not a direct measurement, there is a need for highly accurate prediction models. In this article, we propose solving this challenge by employing sparse identification of nonlinear dynamics (SINDy) to unlock the nonlinear dynamic complexity of PCM-TES. …”
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Individualizing glioma radiotherapy planning by optimization of a data and physics-informed discrete loss by Michal Balcerak, Jonas Weidner, Petr Karnakov, Ivan Ezhov, Sergey Litvinov, Petros Koumoutsakos, Tamaz Amiranashvili, Ray Zirui Zhang, John S. Lowengrub, Igor Yakushev, Benedikt Wiestler, Bjoern Menze

“…We present the Glioma Optimizing the Discrete Loss (GliODIL) framework, which infers the full spatial distribution of tumor cell concentration from available multi-modal imaging, leveraging a Fisher-Kolmogorov type physics model to describe tumor growth. …”
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The techniques and applications of patient-derived head and neck cancer organoids: a systematic review by Yangyang Xia, Shang Xie, Zhigang Cai, Xiaofeng Shan

“…Lowering the construction cost, improving the predictive accuracy of models, and exploring the mechanisms of tumor development and metastasis may be directions for further research in the future.…”
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Hybrid neural network method for damage localization in structural health monitoring by Fatahlla Moreh, Yusuf Hasan, Zarghaam Haider Rizvi, Sven Tomforde, Frank Wuttke

“…Our proposed model incorporates a single RNN layer, complemented by essential supporting layers, which contributes to a reduction in complexity and a decrease in the number of parameters. …”
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Evaluation of Near‐Surface Specific Humidity and Air Temperature From Atmospheric Infrared Sounder (AIRS) Over Oceans by Weikang Qian, Yixin Wen, Shang Gao, Zhi Li, Jesse Kisembe, Haotong Jing

“…The Atmospheric Infrared Sounder (AIRS) provides global estimates of near‐surface AT and SH estimates, with continuous improvements in accuracy leading to significant reductions in error rates. However, existing studies have not systematically validated AIRS near‐surface products in both temporal and spatial perspectives, especially over oceans. …”
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Seismic Facies Classification of Salt Structures and Sediments in the Northern Gulf of Mexico Using Self-Organizing Maps by Silas Adeoluwa Samuel, Camelia C. Knapp, James H. Knapp

“…While conventional techniques like core analysis and well logs provide limited spatial reservoir information, seismic data can offer valuable 3D insights into fluid and rock properties away from the well. …”
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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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Spatiotemporal dataset of dengue influencing factors in Brazil based on geospatial big data cloud computing by Qixu Zhu, Zhichao Li, Jinwei Dong, Ping Fu, Qu Cheng, Jun Cai, Helen Gurgel, Linsheng Yang

“…Addressing this challenge necessitates the efficient data integration methods and the assembly of multi-factorial datasets to aid public health authorities in understanding dengue transmission mechanisms and improving risk prediction models. In response, we developed a population-weighted dataset of 12 dengue risk factors, covering 558 microregions in Brazil over 1252 epidemiological weeks from 2001 to 2024. …”
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The impact of information disclosure and smart technology integration on e-retailing performance: A production delivery policy framework by Muhammad Tayyab, Hira Tahir, Muhammad Salman Habib

“…This research presents a sustainable multi-item integrated model for manufacturer–retailer collaboration in e-retailing by incorporating multiple delivery policies and investments in technology aimed at information disclosure and environmental footprint reduction. …”
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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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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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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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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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Rate-induced transitions and noise-driven resilience in vegetation pattern dynamics by L. Vanderveken, M. Crucifix

“…<p>Understanding the resilience and stability of vegetation patterns under changing environmental conditions is crucial for predicting ecosystem responses to climate change. This study investigates the dynamics of vegetation patterns in response to a spatially homogeneous decrease in rainfall across the entire domain. …”
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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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