Search Results (2,226)

This article reconceptualizes entropy not as a metaphysical substance but as a structural constraint that shapes the formation, energetic cost, and durability of records. It links the coarse-grained—and typically irreversible—flow of time to questions of moral responsibility and divine justice. Drawing on the second law of thermodynamics, information theory, and contemporary cosmology, it advances an analogical and operational framework in which actions are accountable in an analogical sense insofar as they leave energetically costly traces that resist erasure. Within a Qur’ānic metaphysical horizon, concepts such as kitāb (Book), ṣaḥīfa (Record), and tawba (Repentance) function as structural counterparts to informational inscription and revision, without reducing theological meaning to physical process. In contrast to Kantian ethics, which grounds moral law in rational autonomy, the Qurʾān situates responsibility within the irreversible structure of time. Understood in this way, entropy is not a threat to coherence but a condition for accountability. By placing the Qurʾānic vision in dialog with modern science and theology, the article contributes to broader discussions on justice, agency, and the metaphysics of time within the science–religion discourse. Full article

We propose a unified theoretical framework grounded in a Primordial Quantum Field (PQF)—a continuous, non-local informational substrate that precedes space-time and matter. The PQF is represented by a wave functional evolving in an abstract configuration space, where physical properties emerge through the self-organization of complexity. We introduce a novel physical quantity—complexity entropy Sc[ϕ]—which quantifies the structural organization of the PQF. Unlike traditional entropy measures (Shannon, von Neumann, Kolmogorov), Sc[ϕ] captures non-trivial coherence and functional correlations. We demonstrate how complexity gradients induce an emergent geometry, from which spacetime curvature, physical constants, and the arrow of time arise. The model predicts measurable phenomena such as entanglement waves and reinterprets dark energy as informational coherence pressure, suggesting empirical pathways for testing via highly correlated quantum systems. Full article

This study focuses on a bulb tubular pump to clarify the flow characteristics and energy loss laws of low-lift tubular pumps under variable speed regulation and addresses deviations from optimal operating conditions in complex scenarios. For two typical rotational speeds, a full-flow passage model was established; the SST k-ω turbulence model was used to solve 3D incompressible viscous flow, energy loss was analyzed via entropy production theory, and simulations were experimentally validated. The results showed the following: pump efficiency exhibited a “first rise then fall” trend, head decreased monotonically with flow rate, and the optimal operating point shifted to lower flow rates at slower speeds. Meanwhile, local entropy production rate effectively characterized loss location and intensity, with aggravated off-design loss concentrated near the hub and rim along the spanwise direction and within 30 mm of the near-wall region. This study clarifies core energy loss mechanisms, providing a quantitative basis for operation optimization and structural improvement to support the safe, economical operation of low-lift pump stations. Full article

This paper introduces an Improved Red-Billed Blue Magpie Optimizer (IRBMO) to enhance the Maximum Second-Order Cyclostationary Blind Deconvolution (CYCBD) method, which traditionally depends on manual, experience-based setting of its key parameters (filter length $L$ and cyclic frequency $\mathsf{\alpha }$). By adopting an Improved Envelope Spectrum Entropy (EK) as the fitness function, the IRBMO autonomously optimizes these parameters, eliminating the need for prior knowledge and improving its applicability in industrial settings. The Improved Red-Billed Blue Magpie algorithm is employed to adaptively optimize the penalty parameter and kernel function parameter of the support vector machine, thereby obtaining an optimal support vector machine model. By introducing fuzzy entropy theory, the feature vectors of filtered signals—processed by the Cyclostationary Blind Deconvolution method with optimal parameters—are extracted and used as input for the optimally parameterized support vector machine, achieving multi-fault classification for bogie bearings. The results show that the IRBMO-CYCBD method significantly enhances the periodic weak fault impulse components and improves the signal-to-noise ratio of the processed signal. Envelope spectrum analysis of the filtered signal allows for clear observation of shaft frequency components, as evidenced by the accurate identification of the 110 Hz fundamental frequency and its harmonic components at 220 Hz, 330 Hz, and 440 Hz in the spectrum. Simulation tests verify the efficacy of the IRBMO-CYCBD method in processing rolling bearing vibration signals under strong noise interference. Under laboratory conditions, simulation experiments were conducted by collecting vibration acceleration signals from rolling bearings in various states. The aforementioned method was applied for fault diagnosis, achieving a maximum diagnostic accuracy of 100%. Through repeated experiments, it was verified that this method meets the fault diagnosis requirements for rolling bearings in metro train bogies. Full article

This paper does not aim to prove new mathematical theorems or claim a fundamental unification of physics and information, but rather to provide a new pedagogical framework for interpreting foundational results in algorithmic information theory. Our focus is on understanding the profound connection between entropy and Kolmogorov complexity. We achieve this by applying these concepts to a physical model. Our work is centered on the distinction, first articulated by Boltzmann, between observable low-complexity macrostates and unobservable high-complexity microstates. We re-examine the known relationships linking complexity and probability, as detailed in works like Li and Vitányi’s An Introduction to Kolmogorov Complexity and Its Applications. Our contribution is to explicitly identify the abstract complexity of a probability distribution $\mathrm{K}\left(\rho \right)$ with the concrete physical complexity of a macrostate $\mathrm{K}\left(M\right)$. Using this framework, we explore the “Not Alone” principle, which states that a high-complexity microstate must belong to a large cluster of peers sharing the same simple properties. We show how this result is a natural consequence of our physical framework, thus providing a clear intuitive model for understanding how algorithmic information imposes structural constraints on physical systems. We end by exploring concrete properties in physics, resolving a few apparent paradoxes, and revealing how these laws are the statistical consequences of simple rules. Full article

This state-of-the-art review provides a comprehensive, critical synthesis of the rapidly expanding field of HECCs, emphasizing the unique scientific challenges that distinguish these materials from conventional ceramics and high-entropy alloys. Key challenges of HECCs include accurately predicting stable phases and quantifying resultant material properties, optimizing complex fabrication and processing techniques, and establishing a robust correlation between the intricate microstructural characteristics and macroscopic performance. Unlike previous reviews that focus on individual ceramic families, this article integrates the novel features, diverse applications, and recent developmental breakthroughs across carbides, nitrides, borides, and oxides to reveal the unifying principles governing configurational disorder, phase stability, and microstructure property relationships in HECCs. A key novelty of this review work is the systematic mapping of fabrication pathways, including CTR, PAS, SPS, and reactive sintering, against the underlying thermodynamic and kinetic constraints specific to multicomponent ceramic systems. The review introduces emerging ideas such as HEDFT, machine-learning-assisted phase prediction, and entropy–enthalpy competition as foundational tools for next-generation HECC design and performance analysis. Additionally, it uniquely presents densification behavior, diffusion barriers, defect chemistry, and residual stress evolution with mechanical, thermal, and tribological performance across the coating classes. By consolidating theoretical intuitions with experimental developments, this article provides a novel roadmap for predictive compositional design, development, microstructural engineering, and targeted application of HECCs in extreme environments. This work aims to support researchers and coating industries toward the rational development of high-performance HECCs and establish a unified framework for future research in high-entropy ceramic technologies. Full article

The Yangtze River Economic Belt is a crucial driver of China’s economy, and its shoreline is a strategic, finite resource vital for ecological security, flood control, navigation, and socioeconomic development. However, intensive development has resulted in functional conflicts and ecological degradation, underscoring the need for accurate identification and suitability assessment of shoreline functions. Conventional methods, which predominantly rely on land use data and remote sensing imagery, are often limited in their ability to capture dynamic changes in large river systems. This study introduces an integrated framework combining macro-level “Three-Zone Space” (urban, agricultural, ecological) theory with micro-level Point of Interest (POI) data to rapidly identify shoreline functions along the Yichang section of the Yangtze River. We further developed a multi-criteria evaluation system incorporating ecological, production, developmental, and risk constraints, utilizing a combined AHP-Entropy weight method to assess suitability. The results reveal a clear upstream-downstream gradient: ecological functions dominate upstream, while agricultural and urban functions increase downstream. POI data enabled refined classification into five functional types, revealing that ecological conservation shorelines are extensively distributed upstream, port and urban development shorelines concentrate in downstream nodal zones, and agricultural production shorelines are widespread yet exhibit a spatial mismatch with suitability scores. The comprehensive evaluation identified high-suitability units, primarily in downstream urban cores with superior development conditions and lower risks, whereas low-suitability units are constrained by high geological hazards and poor infrastructure. These findings provide a scientific basis for differentiated shoreline management strategies. The proposed framework offers a transferable approach for the sustainable planning of major river corridors, offering insights applicable to similar contexts. Full article

We review aspects of entanglement entropy in the quantum mechanics of $N\times N$ matrices, i.e., matrix quantum mechanics (MQM), at large N. In doing so, we review standard models of MQM and their relation to string theory, D-brane physics, and emergent non-commutative geometries. We overview, in generality, definitions of subsystems and entanglement entropies in theories with gauge redundancy and discuss the additional structure required for definining subsystems in MQMs possessing a $U\left(N\right)$ gauge redundancy. In connecting these subsystems to non-commutative geometry, we review several works on ‘target space entanglement,’ and entanglement in non-commutative field theories, highlighting the conditions in which target space entanglement entropy displays an ‘area law’ at large N. We summarize several example calculations of entanglement entropy in non-commutative geometries and MQMs. We review recent work in connecting the area law entanglement of MQM to the Ryu–Takayanagi formula, highlighting the conditions in which $U\left(N\right)$ invariance implies a minimal area formula for the entanglement entropy at large N. Finally, we make comments on open questions and research directions. Full article

Over the years, neurons undergo functional changes initially linked to the maturation of the brain and then are progressively linked to normal aging. The curious relationship between brain decay, aging, and neuronal diseases has aroused the interest of numerous studies to better understand and contrast the evolution of these pathologies. The objective of this research is to apply the non-equilibrium thermodynamic theory with the internal variables of the study of the rheological properties of the brain, focusing on the study of viscoelastic properties. After a thermodynamic introduction of the principal rheological phenomena, this paper discusses the results by the application of our mathematical technique, which revealed a prevalence of anelastic properties in the old central nervous system compared to the young one. Furthermore, the entropy production trend tested identifies a greater disorder in the young brain in respect to the old one. The results obtained highlight that a lower stiffness in the old central nervous system may be interpreted with dendritic regression associated with neuronal death, both being potential consequences of an increased production of free radicals due to reduced antioxidant defenses and/or an altered mitochondrial dysfunction in aging. Full article

The cosmological constant (CC, $\Lambda$) problem stands as one of the most profound puzzles in the theory of gravity, representing a remarkable discrepancy of about 120 orders of magnitude between the observed value of dark energy and its natural expectation from quantum field theory. This paper synthesizes two innovative paradigms—holographic naturalness (HN) and pre-geometric gravity (PGG)—to propose a unified and natural resolution to the problem. The HN framework posits that the stability of the CC is not a matter of radiative corrections but rather of quantum information and entropy. The large entropy $S_{\mathrm{dS}}\sim M_{\mathrm{P}}^2/\Lambda$ of the de Sitter (dS) vacuum (with $M_{\mathrm{P}}$ being the Planck mass) acts as an entropic barrier, exponentially suppressing any quantum transitions that would otherwise destabilize the vacuum. This explains why the universe remains in a state with high entropy and relatively low CC. We then embed this principle within a pre-geometric theory of gravity, where the spacetime geometry and the Einstein–Hilbert action are not fundamental, but emerge dynamically from the spontaneous symmetry breaking of a larger gauge group, SO($1,4$)→SO($1,3$), driven by a Higgs-like field ${\varphi }^A$. In this mechanism, both $M_{\mathrm{P}}$ and $\Lambda$ are generated from more fundamental parameters. Crucially, we establish a direct correspondence between the vacuum expectation value (VEV) v of the pre-geometric Higgs field and the de Sitter entropy: $S_{\mathrm{dS}}\sim v$ (or $v^3$). Thus, the field responsible for generating spacetime itself also encodes its information content. The smallness of $\Lambda$ is therefore a direct consequence of the largeness of the entropy $S_{\mathrm{dS}}$, which is itself a manifestation of a large Higgs VEV v. The CC is stable for the same reason a large-entropy state is stable: the decay of such state is exponentially suppressed. Our study shows that new semi-classical quantum gravity effects dynamically generate particles we call “hairons”, whose mass is tied to the CC. These particles interact with Standard Model matter and can form a cold condensate. The instability of the dS space, driven by the time evolution of a quantum condensate, points at a dynamical origin for dark energy. This paper provides a comprehensive framework where the emergence of geometry, the hierarchy of scales and the quantum-information structure of spacetime are inextricably linked, thereby providing a novel and compelling path toward solving the CC problem. Full article

The link between information and energy introduces the observer and their knowledge into the understanding of a fundamental quantity in physics. Two approaches compete to account for this link—Brillouin’s negentropy law of information and Landauer’s law on data erasure—which are often confused. The first, based on Clausius’ inequality and Shannon’s mathematical results, is very robust, whereas the second, based on the simple idea that information requires a material embodiment (data bits), is now perceived as more physical and therefore prevails. In this paper, we show that Landauer’s idea results from a confusion between information (a global emergent concept) and data (a local material object). This confusion leads to many inconsistencies and is incompatible with thermodynamics and information theory. The reason it prevails is interpreted as being due to a frequent tendency of materialism towards reductionism, neglecting emergence and seeking to eliminate the role of the observer. A paradoxical trend, considering that it is often accompanied by the materialist idea that all scientific knowledge, nevertheless, originates from observation. Information and entropy are actually emergent quantities introduced in the theory by convention. Full article

In this research, we investigate the interaction between the redox mediator ferrocene carboxylic acid (Fc-COOH) and glucose oxidase (GOD) in order to determine the thermodynamics parameters K_int, ΔG_int, ΔH_int, and ΔS_int using simple UV–visible experiments at different temperatures. Positive values of ΔH_int, ΔS_int, together with a negative value of ΔG_int indicate an entropy-driven hydrophobic interaction typical of spontaneous association processes. The homogeneous electron transfer rate constants between the oxidized organometallic mediator and the reduced enzyme (k_s), along with their activation parameters (ΔG_ET^≠, ΔH_ET^≠ and ΔS_ET^≠), were calculated using data obtained from foot of the wave analysis (FOWA) of cyclic voltammetry experiments performed at variable temperature. According to transition state theory, the obtained parameters indicate a low activation enthalpy that reflects minimal energetic requirements for electron transfer, while the large negative activation entropy suggests the formation of an ordered transition state. The positive activation free energy falls within the expected range for biological electron transfer processes. Variable temperature cyclic voltammetry experiments of ferrocene carboxylic acid (Fc-COOH) were also performed. The obtained ΔG°, ΔH°, and ΔS° parameters indicate strong stabilization of the redox pair, consistent with a small difference in solvation energy. Circular dichroism, UV–vis spectroscopy, and combined CD and UV–Vis Spectroelectrochemistry measurements performed during redox mediation demonstrate that no significant structural alterations occur in either the enzyme or the redox mediator before or during the electron transfer processes. Full article

The substantial domain discrepancy inherent in multi-source and multi-view imagery presents formidable challenges to achieving precise drone-based multi-view geo-localization. Existing methodologies primarily focus on designing sophisticated backbone architectures to extract view-invariant representations within abstract feature spaces, yet they often overlook the rich and discriminative frequency-domain cues embedded in multi-view data. Inspired by the principles of $\pi$-Noise theory, this paper proposes a frequency-domain Positive-Incentive Information Screening (PIIS) mechanism that adaptively identifies and preserves task-relevant frequency components based on entropy-guided information metrics. This principled approach selectively enhances discriminative spectral signatures while suppressing redundant or noisy components, thereby improving multi-view feature alignment under substantial appearance and geometric variations. The proposed PIIS strategy demonstrates strong architectural generality, as it can be seamlessly integrated into various backbone networks including convolutional-based and Transformer-based architectures while maintaining consistent performance improvements across different models. Extensive evaluations on the University-1652 and SUES-200 datasets have validated the great potential of the proposed method. Specifically, the PIIS-N model achieves a Recall@1 of 94.56% and a mean Average Precision (mAP) of 95.44% on the University-1652 dataset, exhibiting competitive accuracy among contemporary approaches. These findings underscore the considerable promise of frequency-domain analysis in advancing multi-view geo-localization. Full article

A virtual power plant (VPP) faces multiple uncertainties and temporal coupled decisions when participating as an independent entity in electricity and green markets. A multi-level electricity–green coupled market framework is constructed for a VPP participating as an independent market entity. To address uncertainties in renewable energy outputs and market prices, a risk management method based on conditional value at risk entropy weight method information gap decision theory (CVaR-EIGDT) is proposed. To address the temporal coupled challenges in VPP participation across multi-level electricity–green coupled markets, a multi-stage rolling decision-making method coordinating annual, monthly, and daily scales is proposed, achieving deep coupling in the decision-making sequence of multi-level electricity–green coupled markets. Results show that the proposed model enables adaptive decision-making under varying risk preferences, with decisions exhibiting strong practical adaptability while balancing real-time adjustments and long-term planning. The multi-level electricity–green coupled market framework enhances VPP profitability and resilience, while the CVaR-EIGDT method effectively improves decision-making efficiency across multi-level electricity–green coupled markets. Full article

The Lorentz invariance violation (LIV) predicted by some quantum gravity theories would manifest as an energy-dependent speed of light, which may potentially distort the observed temporal profile of photons from astrophysical sources at cosmological distances. The dispersion cancellation (DisCan) algorithm offers a powerful methodology for investigating such effects by employing quantities such as Shannon entropy, which reflects the initial temporal characteristics. In this study, we apply the DisCan algorithm to search for LIV effects in the LHAASO observations of GRB 221009A, combining data from both the Water Cherenkov Detector Array (WCDA) and Kilometer Squared Array (KM2A) detectors that collectively span an energy range of ∼0.2–13 TeV. Our analysis accounts for the uncertainties from both energy resolution and temporal binning. We derive $95\%$ confidence level lower limits on the LIV energy scale of $E_{\mathrm{QG},1}/{10}^{19}\mathrm{GeV}>14.6$ (11.2) for the first-order subluminal (superluminal) scenario, and $E_{\mathrm{QG},2}/{10}^{11}\mathrm{GeV}>13.7$ (12.5) for the second-order subluminal (superluminal) scenario. Full article