Entropy最新文献

{"title":"Maximizing Free Energy Gain.","authors":"Artemy Kolchinsky, Iman Marvian, Can Gokler, Zi-Wen Liu, Peter Shor, Oles Shtanko, Kevin Thompson, David Wolpert, Seth Lloyd","doi":"10.3390/e27010091","DOIUrl":"10.3390/e27010091","url":null,"abstract":"<p><p>Maximizing the amount of work harvested from an environment is important for a wide variety of biological and technological processes, from energy-harvesting processes such as photosynthesis to energy storage systems such as fuels and batteries. Here, we consider the maximization of free energy-and by extension, the maximum extractable work-that can be gained by a classical or quantum system that undergoes driving by its environment. We consider how the free energy gain depends on the initial state of the system while also accounting for the cost of preparing the system. We provide simple necessary and sufficient conditions for increasing the gain of free energy by varying the initial state. We also derive simple formulae that relate the free energy gained using the optimal initial state rather than another suboptimal initial state. Finally, we demonstrate that the problem of finding the optimal initial state may have two distinct regimes, one easy and one difficult, depending on the temperatures used for preparation and work extraction. We illustrate our results on a simple model of an information engine.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11765171/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143032756","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}

{"title":"Nonadditive Entropies and Nonextensive Statistical Mechanics.","authors":"Ugur Tirnakli","doi":"10.3390/e27010093","DOIUrl":"10.3390/e27010093","url":null,"abstract":"<p><p>The centennial Boltzmann-Gibbs statistical mechanics [...].</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11764646/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143032812","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}

{"title":"A Resource-Efficient Multi-Entropy Fusion Method and Its Application for EEG-Based Emotion Recognition.","authors":"Jiawen Li, Guanyuan Feng, Chen Ling, Ximing Ren, Xin Liu, Shuang Zhang, Leijun Wang, Yanmei Chen, Xianxian Zeng, Rongjun Chen","doi":"10.3390/e27010096","DOIUrl":"10.3390/e27010096","url":null,"abstract":"<p><p>Emotion recognition is an advanced technology for understanding human behavior and psychological states, with extensive applications for mental health monitoring, human-computer interaction, and affective computing. Based on electroencephalography (EEG), the biomedical signals naturally generated by the brain, this work proposes a resource-efficient multi-entropy fusion method for classifying emotional states. First, Discrete Wavelet Transform (DWT) is applied to extract five brain rhythms, i.e., delta, theta, alpha, beta, and gamma, from EEG signals, followed by the acquisition of multi-entropy features, including Spectral Entropy (PSDE), Singular Spectrum Entropy (SSE), Sample Entropy (SE), Fuzzy Entropy (FE), Approximation Entropy (AE), and Permutation Entropy (PE). Then, such entropies are fused into a matrix to represent complex and dynamic characteristics of EEG, denoted as the Brain Rhythm Entropy Matrix (BREM). Next, Dynamic Time Warping (DTW), Mutual Information (MI), the Spearman Correlation Coefficient (SCC), and the Jaccard Similarity Coefficient (JSC) are applied to measure the similarity between the unknown testing BREM data and positive/negative emotional samples for classification. Experiments were conducted using the DEAP dataset, aiming to find a suitable scheme regarding similarity measures, time windows, and input numbers of channel data. The results reveal that DTW yields the best performance in similarity measures with a 5 s window. In addition, the single-channel input mode outperforms the single-region mode. The proposed method achieves 84.62% and 82.48% accuracy in arousal and valence classification tasks, respectively, indicating its effectiveness in reducing data dimensionality and computational complexity while maintaining an accuracy of over 80%. Such performances are remarkable when considering limited data resources as a concern, which opens possibilities for an innovative entropy fusion method that can help to design portable EEG-based emotion-aware devices for daily usage.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11764894/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143032633","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}

{"title":"Spatiotemporal Evolution of the Water System's Structure and Its Relationship with Urban System Based on Fractal Dimension: A Case Study of the Huaihe River Basin, China.","authors":"Hailong Yu, Bin Yu, Xiangmin Zhang, Yong Fan, Sai Wen, Shanshan Jiao","doi":"10.3390/e27010092","DOIUrl":"10.3390/e27010092","url":null,"abstract":"<p><p>The formation and development of cities are inseparable from a certain scale of water resources. The information contained in the morphological structures of cities and water systems is often overlooked. Exploring the spatiotemporal evolution of water system structures (WSS) and urban system structures (USS) can reveal the \"urban-water\" relationship from a new perspective. The Huaihe River Basin (HRB) was selected as the case area, based on the theory of fractal dimensions, grid dimension and multifractal spectrum methods were used to depict the structural evolutionary characteristics of water systems and urban systems from different dimensions. Then, through a comparative analysis of fractal parameters and spectral lines, the characteristics and changing patterns of the \"urban-water\" relationship in the HRB from 1980 to 2019 were revealed. The results indicate the following: (1) The water system structure in the HRB is complex and exhibits distinct scale characteristics, showing improvement overall and at larger scales while continuously degrading at smaller scales. (2) Both the water system and urban system exhibit increasingly complex spatial development characteristics; however, the USS continues to optimize over time, while the WSS experiences degradation. (3) The development patterns of the water system and urban system are significant differences in the HRB. Urban development mainly relies on outward expansion, whereas the water system is primarily characterized by intensive enhancement. (4) Because of the rapid development of urban areas, water scarcity may occur in densely populated urban areas or larger cities in the future. The research results can serve as a scientific reference for urban planning and water resource management in the HRB.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11765358/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143032914","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}

{"title":"Discontinuous Structural Transitions in Fluids with Competing Interactions.","authors":"Ana M Montero, Santos B Yuste, Andrés Santos, Mariano López de Haro","doi":"10.3390/e27010095","DOIUrl":"10.3390/e27010095","url":null,"abstract":"<p><p>This paper explores how competing interactions in the intermolecular potential of fluids affect their structural transitions. This study employs a versatile potential model with a hard core followed by two constant steps, representing wells or shoulders, analyzed in both one-dimensional (1D) and three-dimensional (3D) systems. Comparing these dimensionalities highlights the effect of confinement on structural transitions. Exact results are derived for 1D systems, while the rational function approximation is used for unconfined 3D fluids. Both scenarios confirm that when the steps are repulsive, the wavelength of the oscillatory decay of the total correlation function evolves with temperature either continuously or discontinuously. In the latter case, a discontinuous oscillation crossover line emerges in the temperature-density plane. For an attractive first step and a repulsive second step, a Fisher-Widom line appears. Although the 1D and 3D results share common features, dimensionality introduces differences: these behaviors occur in distinct temperature ranges, require deeper wells, or become attenuated in 3D. Certain features observed in 1D may vanish in 3D. We conclude that fluids with competing interactions exhibit a rich and intricate pattern of structural transitions, demonstrating the significant influence of dimensionality and interaction features.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11765121/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143032661","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}

{"title":"Novel Ensemble Approach with Incremental Information Level and Improved Evidence Theory for Attribute Reduction.","authors":"Peng Yu, Yifeng Zheng, Ziwen Liu, Baoya Wei, Wenjie Zhang, Ziqiong Lin, Zhehan Li","doi":"10.3390/e27010094","DOIUrl":"10.3390/e27010094","url":null,"abstract":"<p><p>With the development of intelligent technology, data in practical applications show exponential growth in quantity and scale. Extracting the most distinguished attributes from complex datasets becomes a crucial problem. The existing attribute reduction approaches focus on the correlation between attributes and labels without considering the redundancy. To address the above problem, we propose an ensemble approach based on an incremental information level and improved evidence theory for attribute reduction (IILE). Firstly, the incremental information level reduction measure comprehensively assesses attributes based on reduction capability and redundancy level. Then, an improved evidence theory and approximate reduction methods are employed to fuse multiple reduction results, thereby obtaining an approximately globally optimal and a most representative subset of attributes. Eventually, using different metrics, experimental comparisons are performed on eight datasets to confirm that our proposal achieved better than other methods. The results show that our proposal can obtain more relevant attribute sets by using the incremental information level and improved evidence theory.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11764816/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143032821","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}

{"title":"Structured Dynamics in the Algorithmic Agent.","authors":"Giulio Ruffini, Francesca Castaldo, Jakub Vohryzek","doi":"10.3390/e27010090","DOIUrl":"10.3390/e27010090","url":null,"abstract":"<p><p>In the Kolmogorov Theory of Consciousness, algorithmic agents utilize inferred compressive models to track coarse-grained data produced by simplified world models, capturing regularities that structure subjective experience and guide action planning. Here, we study the dynamical aspects of this framework by examining how the requirement of tracking natural data drives the structural and dynamical properties of the agent. We first formalize the notion of a <i>generative model</i> using the language of symmetry from group theory, specifically employing Lie pseudogroups to describe the continuous transformations that characterize invariance in natural data. Then, adopting a generic neural network as a proxy for the agent dynamical system and drawing parallels to Noether's theorem in physics, we demonstrate that data tracking forces the agent to mirror the symmetry properties of the generative world model. This dual constraint on the agent's constitutive parameters and dynamical repertoire enforces a hierarchical organization consistent with the manifold hypothesis in the neural network. Our findings bridge perspectives from algorithmic information theory (Kolmogorov complexity, compressive modeling), symmetry (group theory), and dynamics (conservation laws, reduced manifolds), offering insights into the neural correlates of agenthood and structured experience in natural systems, as well as the design of artificial intelligence and computational models of the brain.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11765005/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143032920","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}

{"title":"Fitting Copulas with Maximal Entropy.","authors":"Milan Bubák, Mirko Navara","doi":"10.3390/e27010087","DOIUrl":"10.3390/e27010087","url":null,"abstract":"<p><p>We deal with two-dimensional copulas from the perspective of their differential entropy. We formulate a problem of finding a copula with maximum differential entropy when some copula values are given. As expected, the solution is a copula with a piecewise constant density (a checkerboard copula). This allows us to simplify the optimization of the continuous objective function, the differential entropy, to an optimization of finitely many density values. We present several ideas to simplify this problem. It has a feasible numerical solution. We also present several instances that admit closed-form solutions.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11765149/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143032723","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}

{"title":"Some New Constructions of <i>q</i>-ary Codes for Correcting a Burst of at Most <i>t</i> Deletions.","authors":"Wentu Song, Kui Cai, Tony Q S Quek","doi":"10.3390/e27010085","DOIUrl":"10.3390/e27010085","url":null,"abstract":"<p><p>In this paper, we construct <i>q</i>-ary codes for correcting a burst of at most <i>t</i> deletions, where t,q≥2 are arbitrarily fixed positive integers. We consider two scenarios of error correction: the classical error correcting codes, which recover each codeword from one read (channel output), and the reconstruction codes, which allow to recover each codeword from multiple channel reads. For the first scenario, our construction has redundancy logn+8loglogn+o(loglogn) bits, encoding complexity O(q7tn(logn)3) and decoding complexity O(nlogn). For the reconstruction scenario, our construction can recover the codewords with two reads and has redundancy 8loglogn+o(loglogn) bits. The encoding complexity of this construction is Oq7tn(logn)3, and decoding complexity is Oq9t(nlogn)3. Both of our constructions have lower redundancy than the best known existing works. We also give explicit encoding functions for both constructions that are simpler than previous works.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11765203/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143032912","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}

{"title":"Environmental Performance, Financial Constraints, and Tax Avoidance Practices: Insights from FTSE All-Share Companies.","authors":"Probowo Erawan Sastroredjo, Marcel Ausloos, Polina Khrennikova","doi":"10.3390/e27010089","DOIUrl":"10.3390/e27010089","url":null,"abstract":"<p><p>Through its initiative known as the Climate Change Act (2008), the Government of the United Kingdom encourages corporations to enhance their environmental performance with the significant aim of reducing targeted greenhouse gas emissions by the year 2050. Previous research has predominantly assessed this encouragement favourably, suggesting that improved environmental performance bolsters governmental efforts to protect the environment and fosters commendable corporate governance practices among companies. Studies indicate that organisations exhibiting strong corporate social responsibility (CSR), environmental, social, and governance (ESG) criteria, or high levels of environmental performance often engage in lower occurrences of tax avoidance. However, our findings suggest that an increase in environmental performance may paradoxically lead to a rise in tax avoidance activities. Using a sample of 567 firms listed on the FTSE All Share from 2014 to 2022, our study finds that firms associated with higher environmental performance are more likely to avoid taxation. The study further documents that the effect is more pronounced for firms facing financial constraints. Entropy balancing, propensity score matching analysis, the instrumental variable method, and the Heckman test are employed in our study to address potential endogeneity concerns. Collectively, the findings of our study suggest that better environmental performance helps explain the variation in firms' tax avoidance practices.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11764494/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143032718","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}