IF 2 3区物理与天体物理

Entropy Pub Date : 2025-07-01 DOI: 10.3390/e27070715

Rongshang Chen, Zhiyong Chen

{"title":"Modeling Spatial Data with Heteroscedasticity Using PLVCSAR Model: A Bayesian Quantile Regression Approach.","authors":"Rongshang Chen, Zhiyong Chen","doi":"10.3390/e27070715","DOIUrl":"10.3390/e27070715","url":null,"abstract":"Spatial data not only enables smart cities to visualize, analyze, and interpret data related to location and space, but also helps departments make more informed decisions. We apply a Bayesian quantile regression (BQR) of the partially linear varying coefficient spatial autoregressive (PLVCSAR) model for spatial data to improve the prediction of performance. It can be used to capture the response of covariates to linear and nonlinear effects at different quantile points. Through an approximation of the nonparametric functions with free-knot splines, we develop a Bayesian sampling approach that can be applied by the Markov chain Monte Carlo (MCMC) approach and design an efficient Metropolis-Hastings within the Gibbs sampling algorithm to explore the joint posterior distributions. Computational efficiency is achieved through a modified reversible-jump MCMC algorithm incorporating adaptive movement steps to accelerate chain convergence. The simulation results demonstrate that our estimator exhibits robustness to alternative spatial weight matrices and outperforms both quantile regression (QR) and instrumental variable quantile regression (IVQR) in a finite sample at different quantiles. The effectiveness of the proposed model and estimation method is demonstrated by the use of real data from the Boston median house price.","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 7","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12294695/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144728889","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

Advancements in Information-Theoretic Methods for Data Analytics. 数据分析的信息论方法进展。

IF 2 3区物理与天体物理

Entropy Pub Date : 2025-06-30 DOI: 10.3390/e27070708

Kichun Lee

引用次数: 0

Compressed Adaptive-Sampling-Rate Image Sensing Based on Overcomplete Dictionary. 基于过完备字典的压缩自适应采样率图像感知。

IF 2 3区物理与天体物理

Entropy Pub Date : 2025-06-30 DOI: 10.3390/e27070709

Jianming Wang, Dingpeng Li, Qingqing Yang, Yi Peng

{"title":"Compressed Adaptive-Sampling-Rate Image Sensing Based on Overcomplete Dictionary.","authors":"Jianming Wang, Dingpeng Li, Qingqing Yang, Yi Peng","doi":"10.3390/e27070709","DOIUrl":"10.3390/e27070709","url":null,"abstract":"In this paper, a compressed adaptive image-sensing method based on an overcomplete ridgelet dictionary is proposed. Some low-complexity operations are designed to distinguish between smooth blocks and texture blocks in the compressed domain, and adaptive sampling is performed by assigning different sampling rates to different types of blocks. The efficient, sparse representation of images is achieved by using an overcomplete ridgelet dictionary; at the same time, a reasonable dictionary-partitioning method is designed, which effectively reduces the number of candidate dictionary atoms and greatly improves the speed of classification. Unlike existing methods, the proposed method does not rely on the original signal, and computation is simple, making it particularly suitable for scenarios where a device's computing power is limited. At the same time, the proposed method can accurately identify smooth image blocks and more reasonably allocate sampling rates to obtain a reconstructed image with better quality. The experimental results show that our method's image reconstruction quality is superior to that of existing ARCS methods and still maintains low computational complexity.","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 7","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12295657/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144728839","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

Onsager's Non-Equilibrium Thermodynamics as Gradient Flow in Information Geometry. 信息几何中梯度流的Onsager非平衡热力学。

IF 2 3区物理与天体物理

Entropy Pub Date : 2025-06-30 DOI: 10.3390/e27070710

Tatsuaki Wada, Antonio Maria Scarfone

引用次数: 0

Application of Shannon Entropy to Reaction-Diffusion Problems Using the Stochastic Finite Difference Method. 随机有限差分法在反应扩散问题中的应用。

IF 2 3区物理与天体物理

Entropy Pub Date : 2025-06-30 DOI: 10.3390/e27070705

Marcin Kamiński, Rafał Leszek Ossowski

引用次数: 0

Fine-Grained Semantics-Enhanced Graph Neural Network Model for Person-Job Fit. 人-工作匹配的细粒度语义增强图神经网络模型。

IF 2 3区物理与天体物理

Entropy Pub Date : 2025-06-30 DOI: 10.3390/e27070703

Xia Xue, Jingwen Wang, Bo Ma, Jing Ren, Wujie Zhang, Shuling Gao, Miao Tian, Yue Chang, Chunhong Wang, Hongyu Wang

{"title":"Fine-Grained Semantics-Enhanced Graph Neural Network Model for Person-Job Fit.","authors":"Xia Xue, Jingwen Wang, Bo Ma, Jing Ren, Wujie Zhang, Shuling Gao, Miao Tian, Yue Chang, Chunhong Wang, Hongyu Wang","doi":"10.3390/e27070703","DOIUrl":"10.3390/e27070703","url":null,"abstract":"Online recruitment platforms are transforming talent acquisition paradigms, where a precise person-job fit plays a pivotal role in intelligent recruitment systems. However, current methodologies predominantly rely on coarse-grained semantic analysis, failing to address the textual structural dependencies and noise inherent in resumes and job descriptions. To bridge this gap, the novel fine-grained semantics-enhanced graph neural network for person-job fit (FSEGNN-PJF) framework is proposed. First, graph topologies are constructed by modeling word co-occurrence relationships through pointwise mutual information and sliding windows, followed by graph attention networks to learn graph structural semantics. Second, to mitigate textual noise and focus on critical features, a differential transformer and self-attention mechanism are introduced to semantically encode resumes and job requirements. Then, a novel fine-grained semantic matching strategy is designed, using the enhanced feature fusion strategy to fuse the semantic features of resumes and job positions. Extensive experiments on real-world recruitment datasets demonstrate the effectiveness and robustness of FSEGNN-PJF.","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 7","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12294162/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144728851","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

Research on the Tail Risk Spillover Effect of Cryptocurrencies and Energy Market Based on Complex Network. 基于复杂网络的加密货币与能源市场尾部风险溢出效应研究。

IF 2 3区物理与天体物理

Entropy Pub Date : 2025-06-30 DOI: 10.3390/e27070704

Xiao-Li Gong, Xue-Ting Wang

{"title":"Research on the Tail Risk Spillover Effect of Cryptocurrencies and Energy Market Based on Complex Network.","authors":"Xiao-Li Gong, Xue-Ting Wang","doi":"10.3390/e27070704","DOIUrl":"10.3390/e27070704","url":null,"abstract":"As the relationship between cryptocurrency mining activities and electricity consumption becomes increasingly close, the risk spillover effect is steadily drawing a lot of attention to the energy and cryptocurrency markets. For the purpose of studying the risk contagion between the cryptocurrency and energy market, this paper constructs a risk contagion network between cryptocurrency and China's energy market using complex network methods. The tail risk spillover effects under various time and frequency domains were captured by the spillover index, which was assessed by the leptokurtic quantile vector autoregression (QVAR) model. Considering the spatial heterogeneity of energy companies, the spatial Durbin model was used to explore the impact mechanism of risk spillovers. The research showed that the framework of this paper more accurately reflects the tail risk spillover effect between China's energy market and cryptocurrency market under various shock scales, with the extreme state experiencing a much higher spillover effect than the normal state. Furthermore, this study found that the tail risk contagion between cryptocurrency and China's energy market exhibits notable dynamic variation and cyclical features, and the long-term risk spillover effect is primarily responsible for the total spillover. At the same time, the study found that the company with the most significant spillover effect does not necessarily have the largest company size, and other factors, such as geographical location and business composition, need to be considered. Moreover, there are spatial spillover effects among listed energy companies, and the connectedness between cryptocurrency and the energy market network generates an obvious impact on risk spillover effects. The research conclusions have an important role in preventing cross-contagion of risks between cryptocurrency and the energy market.","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 7","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12294015/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144728916","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

Two-Level Regular Designs for Baseline Parameterization. 基线参数化的两级规则设计。

IF 2 3区物理与天体物理

Entropy Pub Date : 2025-06-30 DOI: 10.3390/e27070706

Shengli Zhao, Mengru Qin

引用次数: 0

Including Quantum Effects in Molecular Simulations Using the Feynman-Kleinert Linearized Path Integral Method. 包括费曼-克莱纳线性路径积分法在分子模拟中的量子效应。

IF 2 3区物理与天体物理

Entropy Pub Date : 2025-06-30 DOI: 10.3390/e27070702

Jens Aage Poulsen, Gunnar Nyman

引用次数: 0

Inferring Cinematic Aesthetic Biases from the Statistics of Early Movies. 从早期电影的统计数据推断电影审美偏见。

IF 2 3区物理与天体物理

Entropy Pub Date : 2025-06-30 DOI: 10.3390/e27070707

Daniel M Grzywacz, Norberto M Grzywacz

{"title":"Inferring Cinematic Aesthetic Biases from the Statistics of Early Movies.","authors":"Daniel M Grzywacz, Norberto M Grzywacz","doi":"10.3390/e27070707","DOIUrl":"10.3390/e27070707","url":null,"abstract":"Cinematic aesthetic values have not been studied as thoroughly as those in music and the visual arts. Three hypotheses for these values are that they are like those of artistic paintings, that they emphasize the spatial coherence of the optical flow, and that they are temporally smooth. Here, we test these hypotheses and investigate other candidate aesthetic values by comparing the statistics of narrative movies and those obtained spontaneously. We perform these tests by using narrative movies from the early stages of cinematic history because these films are simple. We statistically compare these films with spontaneous movies of scenes from daily life. These statistical comparisons do not support the first hypothesis for early movies. The comparisons show that symmetry, balance, and image complexity (normalized Shannon entropy) are not different in early and spontaneous movies. For similar reasons, our data do not support the spatial coherence of early-movie optical flows as having cinematic aesthetic functions. However, in support of the third hypothesis, the temporal smoothness of luminance, but not of motions, appears to have cinematic aesthetic value. The data also uncovered two other cinematic aesthetic value candidates in both statistical surprise and spatial and temporal complexities. We discuss these candidates, pointing out similarities to music and the importance of film editing.","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 7","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12295773/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144728865","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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