IF 2 3区物理与天体物理

Entropy Pub Date : 2025-09-16 DOI: 10.3390/e27090960

Carlos Carrizales-Velazquez, Jennifer Perez-Oregon, Israel Reyes-Ramírez, Lev Guzmán-Vargas, Fernando Angulo-Brown

{"title":"Detection of Significant Seismic Quiescence Patterns in the Mexican Subduction Zone Using Extended Schreider Algorithms.","authors":"Carlos Carrizales-Velazquez, Jennifer Perez-Oregon, Israel Reyes-Ramírez, Lev Guzmán-Vargas, Fernando Angulo-Brown","doi":"10.3390/e27090960","DOIUrl":"10.3390/e27090960","url":null,"abstract":"This study investigates the implementation of Schreider's quiescence algorithm and two variants that utilize spatiotemporal data to identify patterns of seismic quiescence. These patterns are of particular interest as they may serve as precursors to major seismic events, specifically large earthquakes (M>7), within the Mexican subduction zone associated with the Cocos Plate. We identify two characteristic stages: the α-stage, where a notable deviation is observed in the Schreider convolutions, and the β-stage, where the convolutions return to their background levels. In addition, we identify that the Schreider algorithm cannot discern quiescence patterns when earthquakes M>7 are too close in space and time. Consequently, we explore the behavior of the convolutions in three cases where the algorithm is restarted after the mainshocks, and we find apparent advantages for the spatiotemporal variants of the convolutions. The findings contribute to a more profound understanding of the stages preceding large subduction earthquakes and aid in the identification of precursor patterns in this region.","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 9","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12468736/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145174197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Statistical Inference for High-Dimensional Heteroscedastic Partially Single-Index Models. 高维异方差部分单指标模型的统计推断。

IF 2 3区物理与天体物理

Entropy Pub Date : 2025-09-16 DOI: 10.3390/e27090964

Jianglin Fang, Zhikun Tian

引用次数: 0

Fundamental Solutions to Fractional Heat Conduction in Two Joint Half-Lines Under Conditions of Nonperfect Thermal Contact. 非完全热接触条件下两关节半线上分式热传导的基本解。

IF 2 3区物理与天体物理

Entropy Pub Date : 2025-09-16 DOI: 10.3390/e27090965

Yuriy Povstenko, Tamara Kyrylych, Viktor Dashkiiev, Andrzej Yatsko

引用次数: 0

Reconstructing Hyperspectral Images from RGB Images by Multi-Scale Spectral-Spatial Sequence Learning. 基于多尺度光谱空间序列学习的RGB高光谱图像重建。

IF 2 3区物理与天体物理

Entropy Pub Date : 2025-09-15 DOI: 10.3390/e27090959

Wenjing Chen, Lang Liu, Rong Gao

{"title":"Reconstructing Hyperspectral Images from RGB Images by Multi-Scale Spectral-Spatial Sequence Learning.","authors":"Wenjing Chen, Lang Liu, Rong Gao","doi":"10.3390/e27090959","DOIUrl":"10.3390/e27090959","url":null,"abstract":"With rapid advancements in transformers, the reconstruction of hyperspectral images from RGB images, also known as spectral super-resolution (SSR), has made significant breakthroughs. However, existing transformer-based methods often struggle to balance computational efficiency with long-range receptive fields. Recently, Mamba has demonstrated linear complexity in modeling long-range dependencies and shown broad applicability in vision tasks. This paper proposes a multi-scale spectral-spatial sequence learning method, named MSS-Mamba, for reconstructing hyperspectral images from RGB images. First, we introduce a continuous spectral-spatial scan (CS3) mechanism to improve cross-dimensional feature extraction of the foundational Mamba model. Second, we propose a sequence tokenization strategy that generates multi-scale-aware sequences to overcome Mamba's limitations in hierarchically learning multi-scale information. Specifically, we design the multi-scale information fusion (MIF) module, which tokenizes input sequences before feeding them into Mamba. The MIF employs a dual-branch architecture to process global and local information separately, dynamically fusing features through an adaptive router that generates weighting coefficients. This produces feature maps that contain both global contextual information and local details, ultimately reconstructing a high-fidelity hyperspectral image. Experimental results on the ARAD_1k, CAVE and grss_dfc_2018 dataset demonstrate the performance of MSS-Mamba.","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 9","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12468563/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145174364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

b-Value Evaluation and Applications to Seismic Hazard Assessment. b值评价及其在地震危险性评价中的应用。

IF 2 3区物理与天体物理

Entropy Pub Date : 2025-09-15 DOI: 10.3390/e27090958

Ying Chang, Rui Wang, Peng Han, Jinhong Wang, Miao Miao, Zhiyi Zeng, Weiwei Wu, Changsheng Jiang, Lingyuan Meng, Haixia Shi, Katsumi Hattori

{"title":"b-Value Evaluation and Applications to Seismic Hazard Assessment.","authors":"Ying Chang, Rui Wang, Peng Han, Jinhong Wang, Miao Miao, Zhiyi Zeng, Weiwei Wu, Changsheng Jiang, Lingyuan Meng, Haixia Shi, Katsumi Hattori","doi":"10.3390/e27090958","DOIUrl":"10.3390/e27090958","url":null,"abstract":"Earthquake forecast and risk assessment are of key importance in reducing casualties and property losses. However, they have not been fully achieved due to the complexity of earthquakes. Numerous studies have explored the correspondence of the b-value with changes in effective stress, leveraging temporal and spatial variations to identify precursor characteristics of destructive events in both natural and induced seismic activities. However, robust interpretation of predictive b-values hinges on rigorous estimation, as biased results can mislead conclusions. This paper provides a comprehensive review of spatiotemporal b-value estimation methods alongside statistical significance tests. A pilot b-value analysis of natural earthquakes and induced seismicity manifested the valid impression. The expansion of monitoring datasets with the development of acquisition technology or dense array and advanced estimation methodology will augment the utility of b-value analysis in seismic research and hazard assessment.","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 9","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12468554/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145174373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Lightweight Quantum Authentication and Key Agreement Scheme in the Smart Grid Environment. 智能电网环境下轻量级量子认证与密钥协议方案。

IF 2 3区物理与天体物理

Entropy Pub Date : 2025-09-14 DOI: 10.3390/e27090957

Zehui Jiang, Run-Hua Shi

{"title":"Lightweight Quantum Authentication and Key Agreement Scheme in the Smart Grid Environment.","authors":"Zehui Jiang, Run-Hua Shi","doi":"10.3390/e27090957","DOIUrl":"10.3390/e27090957","url":null,"abstract":"Smart grids leverage smart terminal devices to collect information from the user side, achieving accurate load forecasting and optimized dispatching of power systems, effectively improving power supply efficiency and reliability while reducing energy consumption. However, the development of quantum technology poses severe challenges to the communication security of smart grids that rely on traditional cryptography. To address this security risk in the quantum era, this paper draws on the core idea of quantum private comparison and proposes a quantum-secure identity authentication and key agreement scheme suitable for smart grids. This scheme uses Bell states as quantum resources, combines hash functions and XOR operations, and can adapt to resource-constrained terminal devices. Through a security proof, it verifies the scheme's ability to resist various attacks; the experimental results further show that the scheme still has good robustness in different noise environments, providing a feasible technical path for the secure communication of smart grids in the quantum environment and having clear practical engineering value.","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 9","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12469892/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145174462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Entropy and Chaos-Based Modeling of Nonlinear Dependencies in Commodity Markets. 基于熵和混沌的商品市场非线性依赖建模。

IF 2 3区物理与天体物理

Entropy Pub Date : 2025-09-14 DOI: 10.3390/e27090955

Irina Georgescu, Jani Kinnunen

引用次数: 0

Fault Diagnosis of Planetary Gearboxes Based on LSTM Improved via Feature Extraction Using VMD, Fusion Entropy, and Random Forest. 基于VMD、融合熵和随机森林特征提取改进LSTM的行星齿轮箱故障诊断。

IF 2 3区物理与天体物理

Entropy Pub Date : 2025-09-14 DOI: 10.3390/e27090956

Xin Xia, Haoyu Sun, Aiguo Wang

{"title":"Fault Diagnosis of Planetary Gearboxes Based on LSTM Improved via Feature Extraction Using VMD, Fusion Entropy, and Random Forest.","authors":"Xin Xia, Haoyu Sun, Aiguo Wang","doi":"10.3390/e27090956","DOIUrl":"10.3390/e27090956","url":null,"abstract":"Extracting effective fault features from the complex vibration signals of planetary gearboxes is the key to conducting efficient fault diagnosis, and it involves signal processing, feature extraction, and feature selection. In this paper, a novel feature extraction method is proposed using variational mode decomposition (VMD), fusion entropy, and random forest (RF). Firstly, VMD is employed to process the nonlinear and non-stationary signals of planetary gearboxes, which can effectively address the issues of signal modulation and mode mixing. Additionally, a fusion entropy that incorporates various refined composite multi-scale entropies is proposed; it fully utilizes the signal characteristics reflected by various entropies as features for fault diagnosis. Then, RF is adopted to calculate the importance of each feature, and appropriate features are selected to form a fault diagnosis vector, aiming to solve the problems of feature redundancy and interference in fusion entropy. Finally, long short-term memory (LSTM) is used for fault classification. The experimental results demonstrate that the proposed fusion entropy achieves higher accuracy compared with a single entropy value. The RF-based feature selection can also reduce interference and improve diagnostic efficiency. The proposed fault diagnosis method exhibits high fault diagnosis accuracy under different rotational speeds and environmental noise conditions.","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 9","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12468993/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145174427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

On the Monotonicity of Relative Entropy: A Comparative Study of Petz's and Uhlmann's Approaches. 相对熵的单调性：Petz和Uhlmann方法的比较研究。

IF 2 3区物理与天体物理

Entropy Pub Date : 2025-09-14 DOI: 10.3390/e27090954

Santiago Matheus, Francesco Bottacin, Edoardo Provenzi

{"title":"On the Monotonicity of Relative Entropy: A Comparative Study of Petz's and Uhlmann's Approaches.","authors":"Santiago Matheus, Francesco Bottacin, Edoardo Provenzi","doi":"10.3390/e27090954","DOIUrl":"10.3390/e27090954","url":null,"abstract":"We revisit the monotonicity of relative entropy under the action of quantum channels, a foundational result in quantum information theory. Among the several available proofs, we focus on those by Petz and Uhlmann, which we reformulate within a unified, finite-dimensional operator-theoretic framework. In the first part, we examine Petz's strategy, identify a subtle flaw in his original use of Jensen's contractive operator inequality, and point out how it was corrected to restore the validity of his line of reasoning. In the second part, we develop Uhlmann's approach, which is based on interpolations of positive sesquilinear forms and applies automatically to non-invertible density operators. By comparing these two approaches, we highlight their complementary strengths: Petz's method is more direct and clear; Uhlmann's method is more abstract and general. Our treatment aims to clarify the mathematical structure underlying the monotonicity of relative entropy and to make these proofs more accessible to a broader audience interested in both the foundations and applications of quantum information theory.","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 9","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12469047/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145174268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Quasi-Monte Carlo Method Based on Neural Autoregressive Flow. 一种基于神经自回归流的拟蒙特卡罗方法。

IF 2 3区物理与天体物理

Entropy Pub Date : 2025-09-13 DOI: 10.3390/e27090952

Yunfan Wei, Wei Xi

{"title":"A Quasi-Monte Carlo Method Based on Neural Autoregressive Flow.","authors":"Yunfan Wei, Wei Xi","doi":"10.3390/e27090952","DOIUrl":"10.3390/e27090952","url":null,"abstract":"This paper proposes a novel transport quasi-Monte Carlo framework that combines randomized quasi-Monte Carlo sampling with a neural autoregressive flow architecture for efficient sampling and integration over complex, high-dimensional distributions. The method constructs a sequence of invertible transport maps to approximate the target density by decomposing it into a series of lower-dimensional marginals. Each sub-model leverages normalizing flows parameterized via monotonic beta-averaging transformations and is optimized using forward Kullback-Leibler (KL) divergence. To enhance computational efficiency, a hidden-variable mechanism that transfers optimized parameters between sub-models is adopted. Numerical experiments on a banana-shaped distribution demonstrate that this new approach outperforms standard Monte Carlo-based normalizing flows in both sampling accuracy and integral estimation. Further, the model is applied to A-share stock return data and shows reliable predictive performance in semiannual return forecasts, while accurately capturing covariance structures across assets. The results highlight the potential of transport quasi-Monte Carlo (TQMC) in financial modeling and other high-dimensional inference tasks.","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 9","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12468320/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145174140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

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