Entropy最新文献

{"title":"Explicit Future Pattern-Enhanced Multivariate Time Series Forecasting.","authors":"Yaokang Li, Yunan Wei, Jing Cai, Wenbin Cheng, Yiting Lin","doi":"10.3390/e28091031","DOIUrl":"10.3390/e28091031","url":null,"abstract":"<p><p>Multivariate time series forecasting requires models to infer future values and how the temporal structure evolves beyond the observation boundary. A central challenge is to define this evolution as an intermediate prediction and connect it to value forecasting. We propose explicit future pattern (EFP)-enhanced forecasting, which represents evolution as a multiscale change from the last observed pattern. A separately supervised predictor estimates this change from history, and a decoder combines the predicted pattern with historical behavior and variable relations. A mixed training strategy exposes the decoder to supervised, predicted, and perturbed patterns; inference requires only historical input. Experiments on nine public datasets and four forecasting horizons evaluate the forecasting accuracy and the contribution of explicit future patterns. Predicted patterns outperform shuffled patterns on all nine datasets, and the error increases in aggregate as sample alignment is weakened. Ablations support the roles of dynamic multiscale evolution, frequency information, and mixed training. These results indicate that explicit future patterns can provide useful, inspectable guidance for multivariate forecasting when their estimates remain aligned with the current sample.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"28 9","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13605277/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149059393","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":"Computational Methods for Molecular Dynamics of Supercooled Water Between 200 and 273 K.","authors":"Francisco Carrascoza, Konrad Gorzelanczyk, Jacek Blazewicz","doi":"10.3390/e28091029","DOIUrl":"10.3390/e28091029","url":null,"abstract":"<p><p>Water exhibits anomalous thermodynamic and structural behaviour as it approaches and crosses below its melting point. Modelling this behaviour computationally remains challenging: as temperature decreases, nuclear quantum effects (NQEs) become increasingly significant, sampling efficiency deteriorates, and the choice of computational method critically impacts the accuracy of predicted structural and dynamical properties. This review aims to provide practitioners with a practical guide to performing reliable molecular dynamics simulations of water at low temperatures, with emphasis on the supercooled regime (200-273 K). We examine commonly used <i>ab initio</i> molecular dynamics (AIMD) methods and critically evaluate strategies for incorporating nuclear quantum effects through path-integral molecular dynamics (PIMD), ring-polymer MD (RPMD), and centroid MD (CMD). On cooling through the supercooled regime, the relative importance of nuclear quantum effects increases steadily, so that the error incurred by treating the nuclei classically grows and affects the structural and dynamical properties of interest. The known limitations of density functional approximations for water's structure are assessed in the context of their interplay with NQE treatment, rather than in isolation. By discussing practical considerations, including sampling efficiency and the temperature scaling of path-integral bead counts, alongside the methods themselves, this review is intended to serve as a reference for reliable AIMD studies of supercooled water.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"28 9","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13604963/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149059308","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":"On a Grover-Based Quantum Signature Scheme and a Teleportation-Based Design.","authors":"Guoliang Xu, Songyao Xue, Xiangfu Zou, Yumei Zhang","doi":"10.3390/e28091030","DOIUrl":"10.3390/e28091030","url":null,"abstract":"<p><p>Quantum computation, with tools including Grover's algorithm, quantum walks, and quantum teleportation, plays an important role in quantum signature designs. Although such designs offer signature functionality, they sometimes come at the cost of security. This paper first reviews a Grover-based scheme and shows how man-in-the-middle attacks enable complete key recovery, Alice's disavowal, and Bob's forgery. We then propose an arbitrated quantum signature scheme based on quantum teleportation and a strengthened quantum one-time pad. The scheme is designed for quantum messages with known classical descriptions, not for arbitrary unknown quantum states. The security of the proposed scheme is analyzed through a formal adversarial model for unforgeability and non-repudiation, and its resilience against replay, intercept-and-resend, man-in-the-middle, entanglement, and collective or coherent attacks is examined. Numerical simulations and an asymptotic resource analysis further illustrate the practicality of the scheme.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"28 9","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13605562/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149059286","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":"Hulls of Non-Separable Constacyclic Codes over FqR and Their Applications in Constructing New QECCs.","authors":"Xiying Zheng, Bo Kong, Enbin Zhang","doi":"10.3390/e28091028","DOIUrl":"10.3390/e28091028","url":null,"abstract":"<p><p>Let R=Fq[u1,u2,u3]/⟨ui2=ui,uiuj=ujui=0⟩ and FqR={(a,d)|a∈Fq,d∈R}, where q=pm, <i>p</i> is a prime, and m∈N+. We investigate the algebraic structure of the non-separable constacyclic codes over the mixed-alphabet ring FqR and then determine the generator polynomials and the dimensions of their hulls. As an application, using the construction X, we obtain some new quantum error-correcting codes that are not listed in the online quantum codes database.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"28 9","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13604992/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149059433","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":"Unsupervised Feature Selection via Self-Supervised HSIC and Elastic Net Regularization.","authors":"Yuhong Chen, Tinghua Wang, Long Zou","doi":"10.3390/e28091027","DOIUrl":"10.3390/e28091027","url":null,"abstract":"<p><p>Unsupervised feature selection is essential for high-dimensional data analysis, where irrelevant and redundant variables may obscure the intrinsic data structure, reduce interpretability, and degrade downstream learning performance. The key challenge is to identify informative features without label supervision while suppressing redundant selections under nonlinear dependencies. To address this issue, this paper proposes an unsupervised Hilbert-Schmidt Independence Criterion (HSIC)-Elastic Net (ENet) feature selection framework, termed U-HSIC-ENet. The proposed method reformulates unlabeled feature weighting as a self-supervised kernel alignment problem. Specifically, a target kernel is constructed directly from unlabeled data to encode global sample relationships, while each feature is represented by a centered and Frobenius-normalized feature-induced kernel. Feature relevance is then measured by centered kernel alignment (CKA) in a reproducing kernel Hilbert space (RKHS). The main novelty of U-HSIC-ENet lies in a unified relevance-redundancy-stability formulation. Feature-target alignment is used to estimate nonlinear relevance, whereas pairwise similarities between feature-induced kernels are used to characterize inter-feature redundancy in the same kernel alignment space. On this basis, an explicit off-diagonal redundancy penalty is incorporated into a nonnegative Elastic Net-type objective, which strengthens the suppression of co-selected similar features while preserving sparse and stable feature weighting. The resulting quadratic formulation clarifies how relevance promotion, redundancy control, sparsity, and numerical stabilization are coupled within a single optimization framework. Experiments on eight benchmark datasets under a fixed-budget evaluation protocol show that U-HSIC-ENet achieves the strongest average performance on Normalized Mutual Information (NMI), the Adjusted Rand Index (ARI), and clustering accuracy (ACC) compared with representative graph-, spectral-, and HSIC-based baselines. The advantage is the most pronounced on NMI, suggesting that the self-supervised target kernel and CKA-based relevance modeling are effective in preserving the clustering-relevant nonlinear structure. Friedman tests and Wilcoxon signed-rank tests with Holm correction provide statistical support for the observed improvements. Subsampling-based stability evaluation reveals a trade-off between clustering effectiveness and selection reproducibility: several baselines achieve higher stability scores despite the stronger average clustering performance of U-HSIC-ENet. These results indicate that the proposed framework is effective for unsupervised nonlinear feature weighting when relevance estimation, redundancy control, and stability are considered jointly.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"28 9","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13605230/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149059459","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":"Detecting Unseen IoT Attacks with Calibrated Dual Evidence Under Low False-Positive Budget.","authors":"Jiahui Yue, Yuliang Lu, Yi Xie","doi":"10.3390/e28091026","DOIUrl":"10.3390/e28091026","url":null,"abstract":"<p><p>Internet of Things (IoT) traffic anomaly detection is essential for limiting device compromise and large-scale attacks. Existing detectors may miss attack families absent from model development, while heterogeneous benign traffic makes it difficult to maintain a low false-positive rate (FPR). To address these two practical limitations, we propose the Mode-Calibrated Dual-Evidence Detector (MCDE). Its supervised branch estimates the probability that a sample is malicious from labeled benign and known-attack traffic, while its benign-deviation branch measures distance from multiple learned benign traffic modes, providing a complementary route for unseen attacks. MCDE maps the heterogeneous probability and distance scores to comparable empirical benign-tail evidence, normalizes each branch by its allocated share of the target FPR, and fuses them into an anomaly score. A disjoint held-out benign set determines the decision threshold. Equivalently, the fusion compares budget-adjusted benign-tail surprisal, linking the decision rule to empirical self-information. We further establish the conditions under which the budgeted fusion controls the nominal overall FPR. Family-hold-out experiments on IoT-23 and N-BaIoT validate MCDE. At a 1% target benign FPR, MCDE improves IoT-23 unseen recall over histogram-based gradient boosting from 85.77% to 90.85% and harmonic known-unseen recall from 91.82% to 95.07%, while maintaining a 0.96% benign-test FPR. It also achieves 99.87% unseen recall on N-BaIoT.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"28 9","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13605448/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149059354","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 Long-Range Distributed Antenna Method Based on Microwave-Photonics Frequency Synchronization.","authors":"Haotian Teng, Mingtuan Lin, Hui Han, Hao Gao, Xinglin Qin, Baichi Chen, Yuanmei Xie, Juntao He, Bo Liu","doi":"10.3390/e28091024","DOIUrl":"10.3390/e28091024","url":null,"abstract":"<p><p>Coherent signal synthesis among multiple remote apertures is a fundamental challenge for next-generation distributed radar and communication systems, and its performance hinges on the precision of the frequency and time references shared by the distributed nodes. In this work, we report a system-level study of a microwave-photonics-based frequency synchronization system that phase-locks two independent signal sources over a 40 km fiber link, and we validate the resulting coherent beamforming and power combining capabilities of the synchronized pair. The synchronization link, built on an adaptive phase-locked loop with dispersion compensation, delivers a frequency stability of 8.0×10-15 at 1 s and 2.0×10-16 at 1000 s. Using the synchronized pair, we perform beam-scanning and beamforming experiments in a microwave anechoic chamber at 1-7 GHz. The measured beam-pointing angles agree with theoretical predictions, and a coherent gain enhancement of 5.9 dB is obtained with a gain loss below 0.1 dB. Furthermore, field tests with a 150 m free-space separation between the two transmitting antennas confirm stable coherent signal synthesis, with the combined amplitude maintained within 1 dB over extended periods. Beyond the specific experimental results, we apply the known gain-loss relation to derive an engineering guideline relating the frequency stability of the synchronization link to the achievable coherent gain loss. These results show that an established microwave-photonics synchronization technology, when integrated with standard signal sources, provides a practical route toward distributed coherent arrays for long-range detection and wideband communication.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"28 9","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13605182/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149059274","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":"Certified Elimination of Source Candidates Under Capacity, Transit-Time, and Deadline Constraints.","authors":"Zimeng Wang, Chao Zhao, Chung Chan","doi":"10.3390/e28091022","DOIUrl":"10.3390/e28091022","url":null,"abstract":"<p><p>Source identification is constrained not only by network connectivity but also by whether a finite message can reach observed nodes before a deadline. We study deterministic source-candidate elimination in directed networks with arc capacities and transit times. A time-expanded construction gives an exact causal network-coding characterization in which a candidate is retained if and only if its temporal min-cut to every required recipient is at least the message size. Rejection is therefore conservative for any weaker compliant routing or replication protocol. We derive an equivalent minimum-cost circulation computation, monotone certificates under parameter uncertainty, and closed-form formulas for bidirected trees, including linear-time evaluation for uniform capacities and an O(|V|log2|V|) centroid decomposition algorithm for heterogeneous capacities. Protocol-generated experiments show zero true-source eliminations and substantial refinement in routing regimes. Held-out calibration supports transfer to unseen networks. On benchmark representations of 40 real backbone topology families with 50 to 197 nodes, mean candidate retention falls from 99.3% under static screening to 25.3% under exact temporal screening, without true-source elimination. A focused RLNC diagnostic attributes weak refinement in coding-rich regimes to the static screen retaining all candidates and to broad temporal feasibility, while decode-before-forward restrictions create a substantially larger protocol gap.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"28 9","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13605446/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149059182","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":"Uncertainty-Calibrated Collaborative Filtering via Heteroscedastic Bayesian Neural Networks.","authors":"Xiaowei Wang","doi":"10.3390/e28091025","DOIUrl":"10.3390/e28091025","url":null,"abstract":"<p><p>Although recommendation systems based on neural collaborative filtering (NCF) can achieve high rating accuracy, the point estimates they generate do not express prediction confidence. Existing variants that account for uncertainty, such as Monte Carlo dropout, deep ensemble models, and single-head Bayesian networks, can only capture epistemic uncertainty. We propose BayesNCF-v2, a single-model Bayesian neural collaborative filtering framework that combines a Bayes-by-Backprop output layer with a heteroscedastic head trained under the Gaussian NLL, thereby jointly learning aleatoric and epistemic uncertainty. Across five seeds and three datasets, compared to standard NCF, it reduces ECE by 25-73% and NLL by 7-20%, while its calibration performance shows no statistically significant difference from heteroscedastic MC dropout and approaches that of a heteroscedastic deep ensemble consisting of five models, despite having significantly fewer parameters. For cold-start users, the learned aleatoric variance increases, thereby reducing the ECE for cold-start users on three datasets. These results hold consistently across both random and temporal partitions, demonstrating that heteroscedastic aleatoric modeling is the main driver of calibration in these experiments.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"28 9","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13605793/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149059401","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":"Decision-Theoretic Ecological Optimization of the Curzon-Ahlborn Heat Engine.","authors":"Karen K Huruntz, Lilit E Ghukasyan, Ashok Vaseashta, Artak V Gevorgyan","doi":"10.3390/e28091023","DOIUrl":"10.3390/e28091023","url":null,"abstract":"<p><p>Finite-time heat engines must balance useful power output against irreversibility. We develop a decision-theoretic framework for ecological optimization of the endoreversible Curzon-Ahlborn engine based on its normalized power-loss Pareto frontier. We first examine bargaining-based selection rules. For Newtonian heat transfer, a symmetric Nash compromise between retained power and reduced exergy destruction selects a unique interior operating point with efficiency ηN=1-τ3/4, where τ=Tc/Th is the cold-to-hot reservoir temperature ratio. The same Newtonian state is recovered by the Arias-Hernández-Angulo-Brown prescription, which fixes the ecological weight from the maximum-power reference. Our contribution is therefore not a new efficiency law but a decision-theoretic interpretation of the established 3/4 law as a distinguished compromise between maximum-power operation and the reversible Carnot limit. Under the same normalization, the Kalai-Smorodinsky and egalitarian selectors also identify the same balance point. We then extend the bargaining analysis beyond Newton's law of cooling and compare the Nash continuation with the Arias-Hernández-Angulo-Brown Eϵ - Cϵ prescription. Although coinciding in the Newtonian limit, the two approaches separate at first order when the heat-transfer law is perturbed, thereby distinguishing their underlying selection principles. This comparison raises a further question: how should an operating state be chosen when the relative priority assigned to power and irreversibility reduction is itself uncertain? We address this question through minimax-regret optimization, which selects the operating point that minimizes the largest loss relative to the optimum that would have been chosen had the priority been known. Under complete normalized uncertainty in the ecological priority, the regret-robust selector again yields η=1-τ3/4, giving the same operating state a complementary interpretation in terms of robustness to priority uncertainty.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"28 9","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13605922/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149059266","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}