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        <title>Frontiers in Physics | New and Recent Articles</title>
        <link>https://www.frontiersin.org/journals/physics</link>
        <description>RSS Feed for Frontiers in Physics | New and Recent Articles</description>
        <language>en-us</language>
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        <pubDate>2026-08-04T18:18:33.740+00:00</pubDate>
        <ttl>60</ttl>
        <item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1895766</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1895766</link>
        <title><![CDATA[Fokker-Planck analysis of non-monotonic freeze-out and a proton anomaly in Au-Au collisions (7.7–200 GeV): clues to a QCD phase transition]]></title>
        <pubdate>2026-07-30T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Muhammad Waqas</author><author>Hassan Ali Khan</author><author>Murad Badshah</author><author>Ouazir Salem</author><author>Muhammad Yousaf Khattak</author><author>Atef Abdelkader</author><author>Muhammad Ajaz</author><author>Eman Aldosari</author><author>Abd Haj Ismail</author>
        <description><![CDATA[We analyze the transverse momentum spectra of pions, kaons, and protons in Au-Au collisions from sNN=7.7 to 200 GeV using the Generalized Fokker-Planck Solution. This framework treats the collision fireball as a stochastic medium where particles gain or lose momentum through a combination of drag and diffusion. The fit parameters have clear physical meanings: T is the effective temperature, b sets the transition scale from exponential to power-law behavior, c controls the steepness of the high-pT tail, and d determines how sharp that transition is. Looking at how these parameters change with collision energy, we find several things worth noting. The temperature T rises steadily up to 19.6 GeV, then flattens until 39 GeV, and starts rising again above 62.4 GeV. That plateau is consistent with what one would expect if the equation of state softens during the transition from hadronic matter to quark-gluon plasma. For pions, the parameter c peaks at 19.6 GeV, right where the plateau begins, suggesting a relative increase in the importance of drift compared to diffusion in the transition region. The most surprising result comes from d. For protons at 62.4 GeV, d jumps to about 4, while for pions and kaons it never exceeds 2 at any energy. Nothing like this happens for the lighter particles. This proton-specific spike sits at the same energy where T leaves its plateau and where c for protons reaches its lowest value. This may indicate that baryons start interacting with the medium differently once the system enters the quark-gluon plasma phase. When considered together, the non-monotonic behaviors in T, c, and d are qualitatively consistent with a softening of the equation of state in the energy range of the RHIC beam, suggesting that protons could be a sensitive probe of changes in the underlying freeze-out dynamics. We emphasize, however, that these findings are based on a phenomenological fit model and that additional data and theoretical input are required for a complementary measurements of a QCD phase transition.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1809931</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1809931</link>
        <title><![CDATA[Assessing pegmatite compositional evolution through analysis of muscovite from historic North Carolina mining districts by handheld laser-induced breakdown spectroscopy (hLIBS)]]></title>
        <pubdate>2026-07-29T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Russell S. Harmon</author><author>Michael A. Wise</author><author>Robert M. Ramos</author><author>Adam C. Curry</author>
        <description><![CDATA[Mineral exploration provides the commodities society requires, but continuing discovery and development of new critical mineral deposits is necessary to realize a sustainable, low-carbon future. Pegmatites in historic mining districts across North Carolina have been sites of mineral production for over a century, initially for mica and subsequently for spodumene. Most granitic pegmatites here are mineralogically simple feldspar, quartz, and muscovite pegmatites, with beryl, spodumene, and columbite-group minerals present in some chemically complex pegmatites. Analysis for Li, K, Zn, Ga, Rb, Sn and Cs content and K/Rb ratio by handheld LIBS has been undertaken for suites of muscovite samples from pegmatites in five historic mining districts across North Carolina—the Spruce Pine, Franklin-Sylva, and Cashiers districts in the Blue Ridge province and the Shelby district and Carolina Tin-Spodumene Belt (CTSB) in the Piedmont province, to assess their petrological character, degree of compositional evolution, and potential for rare element mineralization. Most pegmatites have only undergone moderate degrees of melt differentiation and compositional fractionation, and only rarely has melt evolution reached the extreme extent required for beryl or spodumene formation. The quartz-feldspar pegmatites of the Franklin-Sylva, Cashiers, and Shelby districts are poorly to moderately fractionated, whereas moderately to highly fractionated spodumene-bearing pegmatites are present in both the Spruce Pine district and Carolina Tin-Spodumene Belt. Muscovite from spodumene-bearing pegmatites is not unusually enriched in Li, but can be distinguished from its counterpart in common quartz-feldspar pegmatites by characteristically low K/Rb ratios of <40 and Li contents exceeding 0.05 wt. %.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1877199</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1877199</link>
        <title><![CDATA[An enhanced cellular automaton model incorporating power-law deceleration behavior for accurate reproduction of traffic flow dynamics]]></title>
        <pubdate>2026-07-29T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Yanguo Cong</author><author>Sixuan Li</author><author>Si Peng</author><author>Mengzhou Li</author><author>Chaohang Yan</author>
        <description><![CDATA[IntroductionThis paper proposes a new cellular automaton traffic flow model capable of reproducing the concave growth pattern of traffic oscillations.MethodsThe randomization process is implemented through a power-law deceleration function to capture the diverse responses of drivers to disturbances. Using traffic stability as the performance metric, the model was calibrated with trajectory data from a 25-vehicle platoon.ResultsSimulation results indicate that the model can reproduce three typical traffic phases: free flow, synchronized flow, and congested flow. Meanwhile, the simulated maximum traffic flow is consistent with the empirical observations.DiscussionThese findings provide preliminary support for the effectiveness of the proposed stochastic deceleration mechanism in reproducing realistic traffic flow dynamics.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1875295</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1875295</link>
        <title><![CDATA[Information saturation and the structural origin of low-entropy spacetime]]></title>
        <pubdate>2026-07-29T00:00:00Z</pubdate>
        <category>Hypothesis and Theory</category>
        <author>Wan Zheng</author>
        <description><![CDATA[The origin of the Universe’s extremely low initial gravitational entropy remains an open problem, commonly addressed by imposing the Penrose Weyl curvature condition as an additional assumption. In this work, we propose a structural explanation based on an information saturation interface, formulated through a saturation functional governing relational information organization. The saturation regime is a limit in which information channels are maximally utilized and admissible local operations no longer generate additional independently distinguishable relational organization. We argue that approaching this limit favors a near-uniform relational background and assigns a positive quadratic cost to non-uniform or locally extensible deviations, thereby suppressing the robust amplification of symmetry-breaking relational modes. Accordingly, if a classical geometric description emerges from such a structure, its effective background metric is constrained to inherit, at the macroscopic level, the corresponding symmetry content, restricting admissible geometries toward the Friedmann–Lemaître–Robertson–Walker class. Within an effective general-relativistic interpretation, such geometries correspond to vanishing or strongly suppressed Weyl curvature and hence very low gravitational entropy. The framework therefore does not derive a continuum Lorentzian metric or compute the Weyl tensor directly from the saturation functional, but instead proposes a structural admissibility criterion for low-gravitational-entropy emergent backgrounds.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1855044</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1855044</link>
        <title><![CDATA[Security prediction and reliability analysis method of smart grid based on edge computing]]></title>
        <pubdate>2026-07-27T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Qiang Li</author><author>Shizeng Liu</author><author>Jinyun Yu</author><author>Tongbo He</author><author>Chunhai Guo</author><author>Yunhai Song</author><author>Shihong Zhang</author><author>Yi Luo</author>
        <description><![CDATA[In order to solve the problem of high latency and low precision collaborative optimization in smart grid security prediction, this paper proposes a smart grid security prediction and reliability analysis method (EA-LSTM-GraphAgg, EALG) based on edge computing. In the initial prediction stage, EA-LSTM is deployed on edge servers in various regions. Through collaborative optimization of attention mechanism and competitive random search, the temporal traffic data of smart grid collection nodes is locally processed to generate local initial prediction results. In the aggregation stage, to address the local limitations of initial predictions, a GraphAgg aggregation network is designed. The EA-LSTM prediction results are transmitted through lightweight collaborative directional transmission between edge nodes, rather than the original data. At the edge, a graph structure is constructed with smart grid devices as nodes and communication connections as edges. Through localized information aggregation, node traffic associations are mined to improve prediction accuracy. Experiments and analysis show that EALG can output high-precision smart grid security prediction results. It can provide reliable support for smart grid reliability analysis and traffic anomaly warning in smart grid operation and maintenance.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1819239</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1819239</link>
        <title><![CDATA[Comparison of PET photon attenuation for human tissue compositions, tissue-equivalent material compositions, and CT-phantom measurements]]></title>
        <pubdate>2026-07-24T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Heba Alrakh</author><author>Lutz Tellmann</author><author>Omid Nikoubashman</author><author>Maike Zimmermann</author><author>Sadaf Shokrgozar</author><author>Oliver H. Winz</author><author>Sebastian Faby</author><author>Ali Abu arra</author><author>Martin Wiesmann</author><author>N. Jon Shah</author><author>Christoph Lerche</author>
        <description><![CDATA[IntroductionIn this study, the accuracy of linear attenuation coefficients for annihilation photons (511 keV) and additional cascade gammas (603, 1,077, and 1,157 keV) derived from two commercially available phantoms, i.e., the Sun Nuclear electron density and DIAGNOMATIC Pro-RT ED phantoms, was evaluated.MethodsLACs obtained from computations using the NIST XCOM database and literature values of real tissue compositions were compared to LACs obtained from computations using the NIST XCOM database and tissue-equivalent inserts (when available) and to LACs obtained from transmission measurements. Also, LACs obtained from computations using the NIST XCOM database and tissue-equivalent inserts were compared to LACs obtained from transmission measurements (when possible). In addition, transmission scans were performed using the ECAT EXACT HR + positron emission tomography scanner.ResultsTwelve out of 23 tissue-equivalent inserts showed a deviation in the LACs of less than 5% when the values obtained from transmission measurements were compared to those computed using the NIST XCOM database with literature values of real tissue compositions. The highest relative errors were observed in lung-equivalent tissues (up to 37.45) and solid dense bone inserts (26.10%).DiscussionCombining the breast and solid trabecular bone inserts of the Diagnomatic Pro-RT ED phantom with the liver, brain, adipose, lung-450, inner bone, cortical bone, HE Blood 40, HE Blood 70 and HE Blood 100 inserts from the Sun Nuclear phantom provides a relatively complete set of tissue-equivalent inserts from CT phantoms that reproduce the attenuation with systematic errors below 5%.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1876070</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1876070</link>
        <title><![CDATA[A novel semi-quantum private comparison protocol of size relation based on d-dimensional Bell states]]></title>
        <pubdate>2026-07-24T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Yuke Tong</author><author>Tao Chen</author><author>Hao Cao</author>
        <description><![CDATA[Many semi-quantum private comparison (SQPC) protocols have been proposed to compare the equality of participants, but they suffer from low qubit efficiency and require classical participants to perform quantum state measurement and preparation operations. We here propose a novel SQPC protocol based on d-dimensional Bell states. With the assistance of a semi-honest third party, classical participants can compare the sizes of their privacies merely through particle reflection and simple unitary operations, but they do not need to prepare and measure quantum states. Furthermore, participants can compare two bits of privacy just once with one qubit. By combining decoy state eavesdropping detection with pre-shared key encryption as dual security strategies, analysis shows that the proposed protocol is secure against internal and external attack in theory. The qubit efficiency of the protocol reaches 66.7%, which is significantly superior to existing schemes.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1863258</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1863258</link>
        <title><![CDATA[Physical representation and cross scale dynamics modeling of digital trade network structure]]></title>
        <pubdate>2026-07-23T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Huihong Liu</author><author>Jin Huang</author><author>Lixi Zhao</author><author>Shuoguo Zhao</author>
        <description><![CDATA[IntroductionThis study introduces an innovative framework for modeling the physical representation and cross scale dynamics of digital trade network structures, addressing limitations in traditional approaches that often fail to capture the hierarchical and semantic complexities inherent in such systems.MethodsThe proposed methodology is organized into three core components: preliminaries, the HierarchicalSemanticOptimal model, and a modular structure learning strategy. The preliminaries establish the theoretical foundation by formalizing the problem and defining key mathematical constructs necessary for subsequent analysis. The HierarchicalSemanticOptimal model is designed to encapsulate the multifaceted dynamics of digital trade networks through a hierarchical composition mapper, a semantic transition checker, and an optimal transport matcher, enabling a nuanced understanding of trade flows and resource distribution. The modular structure learning strategy further enhances the model’s adaptability and scalability by employing rule guided inference mechanisms to dynamically adjust both parameters and structural configurations in response to evolving network conditions.Results and DiscussionExperimental evaluations demonstrate the efficacy of the proposed framework, revealing significant improvements in modeling accuracy and computational efficiency compared to existing methods. These findings underscore the potential of the framework to provide deeper insights into the optimization of digital trade networks, facilitating more efficient trade operations and resource allocation across diverse scales and contexts.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1816587</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1816587</link>
        <title><![CDATA[Patient-specific quality assurance and plan complexity: from photon standardisation to the unique characteristics of particle therapy]]></title>
        <pubdate>2026-07-23T00:00:00Z</pubdate>
        <category>Mini Review</category>
        <author>Maxence Rayer</author><author>Daniel Maneval</author><author>Cyril Moignier</author><author>Thomas Tessonnier</author><author>Dorothée Lebhertz</author><author>Anthony Vela</author><author>Gary Delattre</author><author>Laetitia Lechippey</author><author>Alain Batalla</author><author>Aurélien Corroyer-Dulmont</author>
        <description><![CDATA[Patient-specific quality assurance (PSQA) is a safety barrier ensuring that treatment plans calculated by the Treatment Planning System (TPS) are accurately delivered by the machine. With the widespread adoption of highly modulated techniques, such as Intensity Modulated Radiation Therapy (IMRT), Volumetric Modulated Arc Therapy (VMAT) and Intensity Modulated Proton Therapy (IMPT) delivered via Pencil Beam Scanning (PBS), the sensitivity of delivery to plan complexity has increased drastically. Currently, the “gold standard” remains experimental PSQA, relying on pre-treatment measurements evaluated through dose comparison metrics, most commonly gamma index analysis. However, this approach is resource-intensive, its correlation with clinically relevant dose errors has been questioned, and applying spatial criteria (Distance-To-Agreement) loses its traditional experimental rationale when comparing purely computational dose distributions (e.g., TPS vs. Monte Carlo). In photon therapy, the field is shifting toward predictive quality assurance based on complexity indices, but this predictive framework is largely absent in particle therapy. Although Monte Carlo simulations and log-file analysis provide detailed data, translating this raw data into standardised complexity indices remains challenging and limits the use of artificial intelligence to predict delivery accuracy for proton and heavy ion therapy despite attempts. This narrative mini-review focuses primarily on research published between 2020 and 2025. We examine: (1) photon therapy as the benchmark for complexity-based prediction; (2) computational proton PSQA, which offers robust verification but currently lacks the complexity indices required for prediction; and (3) the extension to Ion Beam Therapy, arguing for the need to couple physical modulation with radiobiological effectiveness.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1875639</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1875639</link>
        <title><![CDATA[Structural evolution and product-level heterogeneity in global digital product trade networks]]></title>
        <pubdate>2026-07-22T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Yin-Ting Zhang</author><author>Mo-Lei Chen</author><author>Hao Wang</author>
        <description><![CDATA[Digital technologies have increasingly reshaped the organization of international trade, yet limited attention has been paid so far to the structural characteristics of global digital trade networks. This study constructs an international digital product trade network based on bilateral trade flows in six categories of digital products from 2007 to 2023 and examines its evolution using network analysis. The results show that the global digital product trade network has undergone a process of structural deepening, characterized by a relatively stable number of participating economies but substantial growth in trade links, network density, and trade value. The network also exhibits a persistent but multidimensional core structure, with the United States maintaining the strongest embedded position, while China dominates in trade scale and intermediary roles. At the product level, significant structural heterogeneity is observed. Electronic components and equipment form the most commercially intensive network, whereas other digital manufacturing products are more structurally connected and diversified. By contrast, computer manufacturing displays weaker cohesion and higher concentration, indicating a more hierarchical and potentially vulnerable structure. These findings highlight the importance of network structure, product heterogeneity, and diversification for understanding the resilience and governance of digital trade.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1773784</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1773784</link>
        <title><![CDATA[Dual-driven physics–data and signal perception synergy: a layered fault diagnosis framework for hybrid islanded power supply systems]]></title>
        <pubdate>2026-07-22T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Qiang Bian</author><author>Weibo Li</author><author>Yi Wang</author><author>Yi Zhou</author><author>Hualiang Fang</author>
        <description><![CDATA[In an isolated island environment, a hybrid power supply system of fuel, biomass, wind, solar, and storage faces multiple challenges, such as multi-source heterogeneity, strong coupling of AC and DC, and resource constraints. Its fault characteristics show cross-domain propagation concealment and multi-scale dynamic complexity. Traditional single diagnostic paradigms have difficulty balancing real-time performance, accuracy, and interpretability. Therefore, this article proposes a physics- and data-driven hierarchical fault diagnosis framework that is coordinated by signal perception. This framework builds a three-level collaborative mechanism of “end-edge-cloud:” at the device perception layer, it uses signal processing techniques such as wavelet packet transform combined with lightweight mechanism rules to achieve millisecond-level locking of hard faults in power electronic devices and transient protection. At the regional decoupling layer, it integrates the data mining capabilities of graph neural networks (GNNs) with the power grid topology model to accurately analyze the cross-domain propagation paths of faults in AC and DC hybrid systems. At the system decision-making layer, it establishes a “physics–data dual-drive” closed loop, using long short-term memory networks (LSTMs) to capture nonlinear dynamic residuals to correct physical models, and at the same time introduces physics-informed neural networks (PINNs) to constrain the training boundaries of data-driven models, ensuring that decisions comply with physical laws such as energy conservation. In addition, for the fluctuation of wind and solar power and computing power constraints in isolated island scenarios, a feature adaptive strategy driven by transfer learning and a model pruning algorithm are designed. Verification of typical cases, such as gas turbine surge warning and energy storage converter cascading fault analysis, shows that this framework can effectively break through the weak fault detection bottleneck in a strong noise background, significantly reducing the false alarm rate while ensuring a high detection rate. This framework provides a new paradigm for improving the overall resilience and intelligent operation and maintenance level of isolated island hybrid power supply systems.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1878336</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1878336</link>
        <title><![CDATA[Network-position heterogeneity and nonlinear risk propagation in supply chain networks under external shocks]]></title>
        <pubdate>2026-07-20T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Qiaoming Hou</author><author>Jinrong Ma</author>
        <description><![CDATA[Amid the increasing complexity and uncertainty of global supply chains, external shocks have become a major source of systemic risk in supply chain networks. Existing studies are largely based on homogeneous assumptions and single-system frameworks, making it difficult to reveal the coupling interactions among firms with different network positions and their effects on the dynamic evolution of risk propagation. To address this gap, this study is positioned as a theoretical modeling and numerical simulation study. From the perspective of network-position heterogeneity among supply chain firms, it integrates propagation dynamics with discrete dynamics to construct a heterogeneous, dual-population coupled spatiotemporal model of risk propagation. The model is used to investigate the nonlinear evolution mechanisms of shock-driven risk propagation in supply chains. The results show that: (1) The basic reproduction capacity of systemic risk is jointly determined by the risk propagation reproduction capacities of high-network-position firms and ordinary firms. In addition, the stronger the business coupling with high-network-position firms, the more pronounced the network risk propagation effect.(2) When the number of core firms is relatively large and the business dependence between core firms and ordinary firms is strong, local risks are more likely to spread through supply chain relationships and evolve into systemic risks. The more concentrated the initially infected firms are, the more likely risks are to form spatial clusters in local areas and further diffuse to surrounding firms.(3) The timing of intervention plays a decisive role in risk control effectiveness. The optimal control strategy constructed in this study can suppress risk propagation in the network at the early stage and exhibits stronger risk suppression capability in high-risk network structures characterized by core-firm agglomeration and close business connections. However, when the initial risk sources are highly concentrated, risks possess stronger initial diffusion potential, which substantially increases the difficulty of risk control. This study reveals the spatiotemporal evolution mechanism of supply chain risk propagation driven by network-position heterogeneity and coupling effects, enriches the dynamical theory of systemic risk propagation in complex networks, and provides a new theoretical perspective for studying risk propagation and system stability in heterogeneous complex systems.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1868373</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1868373</link>
        <title><![CDATA[Multi-parameter extraction and estimation method based on time-frequency contour for flapping-wing vehicle by laser micro-Doppler detection]]></title>
        <pubdate>2026-07-17T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Yufei Wei</author><author>Rui Yao</author><author>Xuehe Zheng</author><author>Yong Zhang</author><author>Xinlei Qu</author><author>Dan Jiao</author><author>Yufan Yang</author>
        <description><![CDATA[Addressing the challenge of insufficient accuracy in extracting kinematic parameters of flapping-wing targets using current laser micro-Doppler detection methods, this paper proposes a parameter extraction and estimation method based on time-frequency contour analysis. The method first establishes an analytical micro-Doppler model of flapping-wing motion and reveals the mapping relationship between time-frequency spectral features and target parameters through numerical simulations. Then, by employing time-frequency contour analysis combined with a hybrid filtering approach using top-hat transform and singular value decomposition (SVD), the method accurately extracts key contour features such as peak frequency shift and crossing frequency shift from the time-frequency representation. Subsequently, parameters including flapping angle and wing length are retrieved. Compared with existing methods, the proposed approach achieves high-precision extraction of flapping frequency, flapping angle, and wing length. Under simulation conditions, the average relative errors for flapping angle and wing length are 2.19% and 3.43%, respectively; under 5 m experimental conditions, they are 6.30% and 6.75% (8.20% and 8.65% for 300 m condition). Compared with the previous error of 11%, the proposed method achieves a maximum improvement of 9% in flapping angle extraction accuracy. This study significantly enhances the estimation accuracy of micro-motion parameters of flapping-wing targets, providing a reliable theoretical and algorithmic foundation for laser micro-Doppler based recognition of flapping-wing targets.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1795926</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1795926</link>
        <title><![CDATA[The Omega metric: a Hessian geometry for finite-depth structural variation]]></title>
        <pubdate>2026-07-17T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Patrick Bini</author>
        <description><![CDATA[Complex systems exhibit not only increasing disorder but also the emergence of structured organization across space, time, and scale. The finite–depth Intropy framework formalized this interplay through a discrete structural potential profile Ω(k) and adjacent–scale increments Ik=ΔΩk=Ωk+1−Ωk, which quantify organized change across admissible scales in a multiscale representation. What remained open was a principled extension of this finite–depth local description to a global geometric framework able to define distances between states, propagate uncertainty, and support falsifiable stability and contraction statements. This study addresses that gap by endowing the state space with the Omega metric ω=∇2Ω, a Hessian Riemannian structure linking local structural variation to global geometric properties such as geodesics, curvature, and coarse–graining behavior. The study establishes conditions under which the metric ω is well defined and uniformly elliptic on validated compact domains, derives curvature–based operational stability indicators, and proves a contractive geometric data–processing inequality under explicit metric–domination assumptions in the genuinely many–to–one regime, while more general observation maps satisfy Lipschitz comparison bounds on structural distance. A robustness protocol based on block bootstrap, anisotropy tests, and mask–aware normalization provides operational uncertainty quantification. Controlled benchmarks on networks, the two–dimensional Ising transition, and finite–depth fractal signals illustrate the synthetic operating regime of the framework. A complementary raw–data benchmark on real micro–CT sandstone patches, including both a self–supervised and a fully unsupervised variant, shows that the resulting Omega geometry can also be estimated from real observations and assessed against an independently held–out physical descriptor. Taken together, these results place finite–depth Intropy diagnostics within a continuous geometric framework for structural variation.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1884614</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1884614</link>
        <title><![CDATA[The form factor expansion in the precision β decay era]]></title>
        <pubdate>2026-07-15T00:00:00Z</pubdate>
        <category>Mini Review</category>
        <author>Leendert Hayen</author>
        <description><![CDATA[Precision tests of the Standard Model using β decay have always relied on a careful choice of transition to minimize residual nuclear structure uncertainties. Following breakthroughs in nucleon-level radiative corrections in the last decade, however, corrections due to nuclear structure are once more a limiting factor in several scenarios. Progress in ab initio nuclear theory provides a path forward, but common recoil-order approximations in traditional formalisms often go unnoticed. Here, we critically examine their origin and address recently resolved issues as well as identify open questions.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1797094</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1797094</link>
        <title><![CDATA[Japanese Traditional Kampo Medicine as a holistic countermeasure for spaceflight-induced physiological and psychological health challenges: a comprehensive review]]></title>
        <pubdate>2026-07-10T00:00:00Z</pubdate>
        <category>Hypothesis and Theory</category>
        <author>Shin Takayama</author><author>Silke Cameron</author><author>Kenny Kuchta</author><author>Tadashi Ishii</author><author>Masahiro Terada</author>
        <description><![CDATA[Spaceflight introduces a complex array of health challenges that affect nearly every physiological system, primarily owing to microgravity, cosmic radiation, isolation, altered environments, and logistical supply constraints. Astronauts commonly experience musculoskeletal degradation, including bone density and muscle mass loss; cardiovascular deconditioning; and fluid redistribution. These lead to orthostatic intolerance; immune suppression; increased infection risk; exposure to ionizing radiation, which poses elevated risks of malignancy and neurodegenerative diseases; gastrointestinal dysfunction; gut dysbiosis; and cognitive, psychological, and sleep disturbances. These multifaceted stressors necessitate holistic and multitarget countermeasures, particularly as extended missions have become a reality. Japanese Traditional (Kampo) medicines, composed of multiple herbal ingredients, offer a promising supportive strategy because of their efficacy in simultaneously managing diverse physical and psychological symptoms. Kampo formulas exert diverse benefits. For example, Ninjin’yoeito, Juzentaihoto, Hochuekkito, and Goshajinkigan promote musculoskeletal strength and prevent frailty. Goreisan regulates fluid and cardiovascular homeostasis; Hochuekkito supports immune modulation and infection prevention; Rikkunshito address gastrointestinal symptoms via appetite and digestive regulation; and Yokukansan and Kamikihito mitigate neurological and psychological disturbances. Another benefit is the regulation of the gut microbiota, mitochondrial function, and gene expression, which are relevant to space-induced metabolic and inflammatory alterations. The holistic, preventive, and safe profile of Kampo medicines make them well suited for integrated health management in space, facilitating the maintenance of performance and quality of life during long-duration missions. Ongoing research and advances in personalized medicine will help clarify and optimize the application of Kampo in space medicine.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1828648</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1828648</link>
        <title><![CDATA[A security monitoring and warning method for economic growth and unemployment in financial social networks]]></title>
        <pubdate>2026-07-10T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Lei Liu</author><author>Yuanyuan Wen</author>
        <description><![CDATA[Accurately predicting economic growth and unemployment rate is an important prerequisite for macroeconomic regulation in financial social networks. Traditional security monitoring and warning methods often rely on lagging official statistical data, making it difficult to capture nonlinear correlations and sudden signals in economic dynamics in real time. Therefore, this paper proposes a Boruta-SHAP and Transformer-XL (BST-XL) security monitoring and warning model based on Transformer-XL. The framework first constructs a Boruta-SHAP (BS) two-stage feature selection method based on ensemble learning framework and Shapley Additive Explanations (SHAP) interpretability analysis. By identifying important features related to economic time series task from a given feature set, focusing on economic growth and unemployment rate, the problem of feature redundancy in economic time series data is effectively solved. Secondly, by using Transformer-XL to measure the impact of historical economic sequences on recent economic dynamics, the latest state characteristics of economic dynamics can be obtained. This is beneficial for accurately predicting the dynamic changes of economic growth and unemployment rates. Experimental analysis shows that BST-XL performs well in predicting economic growth and unemployment rate, with higher security monitoring accuracy. It is suitable as a predictive model for economic growth and unemployment rate in financial social networks.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1884610</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1884610</link>
        <title><![CDATA[300 GHz digital holography imaging based on a silver/polypropylene hollow terahertz waveguide]]></title>
        <pubdate>2026-07-10T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Yaya Zhang</author><author>Binzhen Zhang</author><author>Junping Duan</author><author>Lei Cheng</author>
        <description><![CDATA[The major challenge limiting the application of terahertz (THz) imaging quality lies in the significant attenuation of THz waves during free-space transmission. This attenuation arises primarily from water vapor absorption and gas molecule scattering. Compared with free space propagation, low-loss and stable transmission of THz wave can be achieved through the waveguide. Waveguide transmission at low THz frequencies has attracted considerable attention, particularly at around 300 GHz (0.3 THz). Among the various types of THz waveguides, hollow waveguides offer a simple structure, ease of fabrication, low cost, and excellent transmission performance in the THz regime. Here we present a low-loss THz metal dielectric hollow waveguide based on polypropylene (PP) tubing, where an external silver film coated on the PP tube forms a leaky-type hollow waveguide structure. The linear transmission loss is measured to be 1.35 dB/m at 300 GHz. By optimizing this low-loss THz hollow waveguide, we achieve a far-field THz digital holographic (TDH) imaging recording configuration for the first time. To evaluate the imaging performance, different types of samples are measured. Experimental results for a plastic plate with aluminum strips validate a lateral resolution of ∼2.5 mm. The proposed method holds potential as a powerful tool for investigating spontaneous phenomena in the THz band.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1870382</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1870382</link>
        <title><![CDATA[Network properties and information entropy of fractal Koch network via degree-based topological indices]]></title>
        <pubdate>2026-07-10T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Xiu-Jian Wang</author><author>Xiaohong Dong</author><author>Jiadong Si</author>
        <description><![CDATA[The Koch network, as a typical fractal network, exhibits unique topological characteristics and serves as an important model in complex network studies. This study aims to systematically analyze degree-based topological indices in the Koch network to uncover the deeper connections between its structure and informational properties. The analytical expressions for these indices in the Koch network are derived through theoretical analysis and numerical simulations, and the trends of each index with varying network iterations are thoroughly examined. To further explore structural properties, entropy calculations are incorporated to analyze the changes in entropy with vertex degree and network iterations, illustrating entropy trends at different stages. Results indicate that, under the same iteration count t, various entropy values exhibit notable differences, though the overall trends remain consistent. As the iteration count t increases, the topological complexity of the Koch network decreases, with entropy gradually diminishing and reaching its maximum at t=1. With increased iterations, the relative differences among entropy values also progressively narrow. This study provides a theoretical basis for research on Koch network topological indices in chemical graph theory and supports studies on entropy in fractal-based complex networks.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1839225</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1839225</link>
        <title><![CDATA[Machine learning analysis of cross-industry innovation efficiency: evidence from Chinese listed companies (2006–2023)]]></title>
        <pubdate>2026-07-09T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Tan Yang</author><author>Haiqing Hu</author><author>Pufeng Wu</author><author>Huanqing Liu</author>
        <description><![CDATA[BackgroundHow listed firms convert R&D spending into patent outputs is central to innovation management and applied econometrics. We treat InnoEff1 as a reduced-form innovation-conversion indicator—not a DEA/SFA frontier-efficiency score.MethodsUsing 40,706 Chinese listed firm-years (2006–2023) across 20 industry segments, we prioritize a restricted-variable Gradient Boosting specification that excludes contemporaneous patent stocks overlapping the outcome numerator. Validation combines five-fold GroupKFold blocking by firm, a strict 2019–2023 time hold-out, DEA/SFA-style benchmarks, and industry-balanced subsample checks.ResultsUnder GroupKFold, the restricted model attains R2 ≈ 0.414 (time hold-out ≈0.144), versus ≈0.989 (hold-out ≈0.978) when patent overlaps are retained—quantifying mechanical fit inflation. Tabulated cross-industry mean InnoEff1 spans 0.088 (Table 1); Kruskal–Wallis rejects equal distributions (H ≈ 2133, P < 10−10), and 28 of 45 Table-1 pairwise contrasts remain significant after Holm–Bonferroni adjustment. Lagged R&D intensity and financial covariates dominate SHAP attributions in the restricted model.ConclusionThe contribution lies in validated machine-learning practice—leakage control, interpretability, and transparent benchmarking—not in near-unity R2 diagnostics. Predictive patterns are associative; they do not justify causal claims that broad-based policies dominate sector-specific innovation support.]]></description>
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