Search Results (6,306)

This study introduces a Caputo fractional-order version of the SEIRS-V model to investigate the spreading dynamics of worms within wireless sensor networks. Traditional integer-order worm propagation models describe the instantaneous evolution of network states; however, they do not adequately account for memory and hereditary characteristics that may influence the transmission dynamics. Consequently, their ability to represent realistic network behavior can be limited in systems where past states affect current propagation patterns. The framework divides sensor nodes into susceptible, exposed, infectious, recovered, and vaccinated classes, while explicitly incorporating worm transmission rates, temporary loss of immunity, and the impact of preventive security measures under limited resource conditions. A detailed theoretical examination is performed, covering the existence, boundedness, and uniqueness of solutions of the fractional-order system. The coupled nonlinear fractional system is solved semi-analytically by means of the Fractional Reduced Differential Transform (FRDT) technique. To confirm accuracy and robustness, the identical system is also discretized and solved using the finite difference scheme (FDS). Unlike previous studies on worm propagation models in wireless sensor networks, which are mainly limited to equilibrium point analysis and qualitative investigations without deriving explicit solutions, the present work develops an approximate semi-analytical solution for the fractional-order SEIRS-V system using the FRDTM. Comparisons between the two solution sets demonstrate excellent agreement and high precision. Numerical outcomes are presented through a series of 2D graphical profiles that illustrate the time-dependent behavior of each compartment and reveal the sensitivity of worm propagation and suppression to variations in the fractional order and key model parameters. The integrated theoretical and computational findings underscore the strong protective role of vaccination in mitigating worm outbreaks and offer valuable guidelines for strengthening cybersecurity measures in wireless sensor networks. Full article

Distant Retrograde Orbits (DROs) and Near-Rectilinear Halo Orbits (NRHOs), as categories of Lagrange orbits, have been selected for the construction of future deep-space navigation constellations in the Earth-Moon space due to their unique orbital trajectories and dynamical characteristics. To obtain high-precision orbit and clock solutions, the orbit determination (OD) and time synchronization (TS) performance of DRO and NRHO based on Beidou Navigation Satellite System (BDS) L-band and Ka-band signals were analyzed. Considering the constraints of onboard resources and cost, it may be infeasible to establish Ka-band links with all BDS satellites. Therefore, multiple experiments with different link configuration schemes were designed. The results show that an orbit determination accuracy of about 500 m and the time synchronization accuracy of 50 ns can be achieved using only L-band observations. In contrast, much higher accuracy can be obtained with full Ka-band links, with orbit and clock accuracy reaching 80 m and 7 ns, respectively. Moreover, higher orbit and clock accuracies can be obtained with more Ka-band links based on L-band observations. Furthermore, with the addition of the DRO-NRHO links, the orbit determination and time synchronization performance of each scheme was further improved by 15%. And the orbit determination accuracy can be better than 65 m, while the time synchronization accuracy can be better than 5 ns. Although the analysis is based on BDS signals, the proposed framework is general in nature and can be extended to other GNSS-based or future space navigation systems, providing a reference for the design of high-precision cislunar navigation and timing architectures. Full article

This paper establishes the global-in-time existence and uniqueness of mild solutions to the relativistic Vlasov–Maxwell–Fokker–Planck (VMFP) system near a global Maxwellian equilibrium. We adopt a low-regularity functional framework, namely the mixed-norm space $L_k^1{L}_T^{\infty }{L}_p^2$ introduced for kinetic equations, which requires only integrability in the Fourier frequency variable and avoids high-order spatial differentiability. By employing a macro–micro decomposition, we derive macroscopic estimates for the hydrodynamic density and electric field, complemented by coercive estimates for the microscopic dissipation. Under a smallness assumption on the initial perturbation measured in this low-regularity norm, we derive a uniform a priori bound for the associated energy functional. This work provides the global existence result for the relativistic VMFP system in such low-regularity spaces, significantly relaxing the regularity requirements of previous classical Sobolev approaches. Full article

Background/Objectives: Artificial intelligence (AI) offers a promising approach for detecting and classifying symptom severity in patients with Parkinson’s disease (PD). The objective was to provide an overview of AI methods performance used for this classification through a systematic review and meta-analysis conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Methods: The Google Scholar, IEEE Xplore, PubMed/MedLine, and ScienceDirect databases were searched for the period 2015–2025. The studies included were original, peer-reviewed studies written in English that addressed an AI method based on machine learning (ML) or deep learning (DL) for the classification of PD patients. The dataset used had to be “Gait in Parkinson’s Disease,” in which the severity of disease symptoms was assessed using the Hoehn and Yahr (H&Y) scale. Studies had to report at least one of the five performance metrics: accuracy, sensitivity, specificity, precision, and F1 score. Two reviewers independently selected articles, assessed the risk of bias using PROBAST (Prediction Model Study Risk of Bias Assessment Tool), and extracted data. The logit-transformed values were pooled separately by performance metrics and by severity level using a random-effects model. Cochran’s Q test, the I² statistic, and inter-study variability (τ²), computed using the generalized inverse variance method with the restricted maximum likelihood model, were used to assess heterogeneity. Forest plots with 95% confidence intervals were used to present the results. Possible causes of heterogeneity were explored using a subgroup analysis (ML vs. DL) and a sensitivity analysis. Finally, publication bias (Egger’s test) and the certainty of the evidence (using GRADE—Grading of Recommendations Assessment, Development, and Evaluation) were assessed to verify the generalizability of the results. Results: Among the 257 unique records, 12 studies were included. The methods demonstrated very high overall performance (>92%): accuracy (96.4%, 95% CI: 95.9–96.9%), specificity (97.7%, 95% CI: 97.3–98.1%), sensitivity (94.0%, 95% CI: 92.7–95.2%), precision (93.4%, 95% CI: 92.0–94.6%), F1 score (92.1%, 95% CI: 90.6–93.4%). Accuracy, specificity, and precision were high for all H&Y levels. However, the more advanced the symptoms, the lower the sensitivity (97.3% for H&Y0 vs. 92.1% for H&Y3). ML models achieved the best results for classifying healthy patients (H&Y0: 95.7% to 98.2%), while DL approaches performed better for classifying higher severity levels (>92%). Heterogeneity and inter-study variability were moderate (I²: 40–50% and τ²: 0.3–0.4) for precision and F1 score, and high (I² > 90% and τ² > 0.6) for accuracy, specificity, and sensitivity. The GRADE analysis revealed low-quality evidence for precision and F1 score and very-low quality for accuracy, specificity, and sensitivity. Conclusions: Thus, AI-based wearable gait assessment devices show great promise in terms of aiding clinical decision-making and treatment personalization. However, further research using a rigorous methodology (PROBAST) is needed to ensure the generalizability of the results and the clinical viability of the proposed solutions. Full article

In this paper, based on the Schauder fixed point theorem, the (generalized) Darbo fixed point theorem, and the (generalized) Banach contraction mapping principle, we study the mixed-type fractional impulse evolution equation with non-local and delay terms, and obtain the existence and uniqueness theorems under whether the operator is compact or not. The order of the derivative in this paper is $0<\alpha <1$, this fractional order introduces a series of problems concerning compactness, continuity, and convergence. We overcome these problems using methods such as H$\ddot{o}$lder inequality and Minkowski inequality. Moreover, under the condition of the non-compact measure, the non-negative constant is extended to an unbounded Lebesgue-integrable function. In addition, when obtaining the uniqueness of the solution through the (generalized) Banach contraction mapping principle, the non-negative constant L in the Lipschitz condition is extended to an unbounded Lebesgue integrable function. Finally, a case study is conducted to demonstrate the validity of the theoretical results. Full article

We propose a fractional-order cancer virotherapy model based on Caputo derivatives to investigate the temporal interactions among tumor cells, viruses, and immune response components. The existence and uniqueness of the solutions for the proposed model are rigorously studied. The proposed model is capable of tracking the temporal dynamics of uninfected and infected cancer cells, free oncolytic virus, and several components of the immune response. To determine the analytical solutions of the resulting nonlinear fractional-order system, we utilize the Temimi–Ansari method (TAM). The convergence and accuracy of the method are confirmed via error analysis and numerical simulation carried out in MATHEMATICA. It is observed that the fractional order plays a prominent role in controlling the temporal dynamics of the cancer–virus–immune system, leading to a reduction in the number of infected cancer cells due to virotherapy. On the other hand, the immune response is vital for controlling cancer growth. Full article

Two-dimensional black phosphorus (2D BP) has emerged as one of the most promising two-dimensional semiconductors for next-generation micro and nanoelectronics beyond Moore’s Law. It is distinguished by its unique combination of a layer dependent direct bandgap, broadband photoresponse, and pronounced in-plane anisotropy, addressing key intrinsic limitations that have hindered the widespread application of graphene and conventional transition metal dichalcogenides (TMDCs). This review provides a systematic and comprehensive overview of recent advances in the controllable fabrication of 2D BP and its applications in transistors and photodetectors. We first elucidate its crystal lattice structure and fundamental physical properties, then categorize and summarize synthesis strategies based on production scale ranging from small scale methods (e.g., mechanical exfoliation and solution based exfoliation) to large scale methods (e.g., Chemical Vapor Deposition (CVD) and Pulsed Laser Deposition (PLD)), with a particular focus on recent advances in high-speed field-effect transistors and broadband photodetectors. In summary, the key to achieving large-scale controllable synthesis lies in addressing the challenges of high-temperature oxidation of black phosphorus and the uncontrollable diffusion of phosphorus sources. In the future, industrial applications are expected to be realized through CVD based regulation of phosphorus sources, low-temperature growth by PLD, and deep integration with silicon-based processes. Full article

Network latency remains a fundamental bottleneck in vehicle teleoperation, inducing instability and performance degradation in conventional control methods, while predictive techniques like the Smith Predictor offer a theoretical solution, their efficacy is often compromised by unmodelled dynamics and real-world disturbances. This paper presents the first experimental validation of the Successive Reference-Pose Tracking (SRPT) architecture. By streaming future reference poses rather than direct steering commands, SRPT leverages an onboard Nonlinear Model Predictive Controller to compute optimal vehicle actions while inherently accounting for dynamic constraints and network delays. Real-world human-in-the-loop experiments were conducted with four drivers on a test track featuring cornering, double lane-change, and slalom manoeuvres. Quantitative comparisons at 10 km/h across four modes—manual driving, direct teleoperation, a Smith Predictor, and SRPT—demonstrate that SRPT significantly outperforms other teleoperation methods, reducing cross-track error by up to 66% and yielding smoother, more stable control inputs. Furthermore, SRPT uniquely maintained stability during a proof-of-concept trial at 13 km/h, where it proactively moderated vehicle speed to respect actuator limits—a critical safety behavior absent in other modes. This work provides the first tangible evidence that SRPT is a robust and superior framework for delay-resilient vehicle teleoperation in real-world conditions. Full article

In this article, we construct a framework for analyzing the equilibrium and stability of networked multi-sector economic systems via fixed-point analysis. We represent directional intersectoral dependencies, nonlinear feedback effects, and heterogeneous adjustment dynamics in the model by the coupled and tripled fixed-point theory in the graphically extended suprametric spaces. The graphical structure encodes supply-chain and influence networks, whereas asymmetric and nonuniform interaction strengths are encoded in the suprametric setting. Furthermore, we prove the existence, uniqueness, and convergence of equilibrium solutions under new generalized contraction conditions. We apply the theoretical findings in nonlinear state systems in which prices in interdependent markets are adjusted using integral equations. The results of numerical simulations show consistent convergence, and the sensitivity parameter of the network structure significantly influences the determination of economic stability and speed of adjustment. Full article

The increasing adoption of renewable energy sources introduces significant variability in power generation, requiring effective strategies to ensure maintain grid stability. Incentive-based demand response programs provide a practical solution for balancing supply and demand, however disputes may arise over energy data integrity. The existing solutions frequently rely on centralized authorities, exposing a single point of failure, or high costs and privacy limitation of recording granular data on-chain. To address this challenge, we propose a decentralized framework that separates cloud storage from integrity certification. This system employs a community aggregator to collect high-frequency energy measurements, store the raw data in the cloud, while anchors unique cryptographic hashes for batch of raw data to a public blockchain. This process creates an auditable and tamper-evident record of data. By recording only hashes on chain, our approach achieves privacy and scalability. Evaluation using a real-world Australian dataset confirms that the system enables transparent dispute resolution, with blockchain transaction costs consistently representing less than 0.10% of the total incentives awarded to participants. Full article

The problem of bilevel decision-making under multi-expert uncertain information is addressed in this paper. Traditional fuzzy bilevel models are unable to accurately quantify expert consensus and capture evaluation hesitation. To overcome these limitations, a fully hesitant fuzzy bilevel linear programming model is proposed, in which all coefficients and decision variables are characterized by hesitant fuzzy numbers. By virtue of $(\alpha ,k)$-cuts, the original model is equivalently transformed into an interval-valued bilevel programming problem and further decomposed into best–best and worst–worst sub-models to derive the upper and lower bounds of optimal solutions. Under the Slater constraint qualification, Karush–Kuhn–Tucker (KKT) conditions are adopted to convert the two sub-models into single-level mathematical programs with complementarity constraints (MPCCs), thereby enabling efficient model solving. The proposed method is applied to the resource allocation problem in quantum communication networks. The numerical results demonstrate that the optimal solution interval converges to a unique core value as the membership-level $\alpha$ increases, while a larger consensus parameter k reduces the fuzzy support set without altering the core solution. Full article

Waterlogged archaeological wood represents a unique cultural heritage but is highly susceptible to physical and chemical degradation, which complicates conservation and restoration. This study aimed to prepare artificial archaeological Cunninghamia lanceolata wood using NaOH vacuum impregnation and systematically evaluate the effects of NaOH concentration and treatment cycles as two treatment variables on wood degradation. Untreated heartwood specimens were treated with 5%, 10%, 20%, and 30% NaOH solutions for 2, 4, and 6 cycles. The NaOH treatment first induced chemical and structural deterioration, including selective degradation of hemicelluloses, changes in cellulose crystallinity, and progressive damage to the wood cell-wall structure. XRD analysis revealed a significant reduction in cellulose crystallinity from 35.96% to 10.11%, while FTIR confirmed the degradation of hemicelluloses and the relative enrichment of lignin-related structures. SEM observations further showed severe cell-wall erosion, lumen deformation, and local collapse, indicating that alkali treatment effectively reproduced typical microstructural features of degraded waterlogged wood. These chemical and microstructural changes subsequently led to marked changes in physical and mechanical properties. Mass loss increased with NaOH concentration and cycle number, while basic density decreased and maximum water content increased, indicating enhanced deterioration and water-holding capacity. Treated specimens also exhibited increased swelling and shrinkage rates and a substantial reduction in longitudinal compressive strength, with the most pronounced deterioration occurring under higher NaOH concentrations and repeated cycles. The study demonstrates that NaOH treatment can reproducibly simulate the physical, chemical, and microstructural characteristics of waterlogged archaeological wood, providing a reliable experimental model for studying wood degradation mechanisms and supporting conservation strategies. Full article

In this paper, the Tricomi problem for a second-kind mixed-type equation with a lower-order term is studied in an unbounded domain. The elliptic part of the domain is a vertical half-strip, while the hyperbolic part is bounded by characteristics. Homogeneous Dirichlet conditions are imposed on the walls of the half-strip, gluing conditions are given on the parabolic degeneracy line, and the trace of the desired solution is prescribed on one of the characteristics. The uniqueness of the solution is proved using the extremum principle and the Zaremba–Giraud principle. The existence of the solution is established by Green’s function method: in the elliptic part, Green’s function of the mixed problem is constructed in the form of a rapidly convergent series; in the hyperbolic part, a generalized solution of the Cauchy problem of a special class is used. The functional relations on the degeneracy line lead to a singular integral equation, which is regularized by the Carleman–Vekua method into a Fredholm integral equation of the second kind with a weak singularity. Explicit formulas for the trace of the solution and its normal derivative are obtained. For a specific set of parameters, a numerical visualization of the solution is performed, the gluing conditions are verified, and a physical interpretation of the obtained graphs is given in the context of transonic gas dynamics. The results can be useful for mathematical modeling of flows in Laval nozzles and other problems of mechanics. Full article

In this paper, we introduce a new class of contractions, called dual connected-image contractions, for a pair of self-mappings on a metric space endowed with a directed graph. This concept extends the notion of connected-image contractions by incorporating the interaction between two mappings through the graph structure. By employing a class of auxiliary functions, we establish existence and uniqueness results for common fixed points under this generalized contractive framework. The proposed approach not only unifies and extends several known results in the literature but also provides greater flexibility in handling nonlinear problems. As an application, the theoretical results are applied to a class of nonlinear fractional differential equations with nonlocal integral boundary conditions, where the existence of solutions is established by reformulating the problems as equivalent integral equations and applying the developed common fixed point framework. Full article

Corporate balance sheets report aggregate equity and liability totals but conceal the internal allocation of financing sources across asset categories—an identification problem that conventional econometric methods cannot resolve without additional parametric assumptions. This paper develops a maximum entropy (ME) panel estimator to recover two latent scalar parameters: x ∈ (0,1), the share of equity capital directed toward long-term asset financing, and y ∈ (0,1), the corresponding debt allocation share. Grounded in maximum entropy principle, the estimator selects the unique parameter vector that satisfies the mean-level balance-sheet constraint while maximising joint Shannon entropy—the least-biassed solution consistent with observable data. The closed-form logistic representation yields a scalar Lagrange multiplier λ*, interpreted as a financing pressure index, recoverable via bisection in at most 21 iterations at tolerance ε = 10⁻⁵. Building on the ME estimates, we introduce a continuous matching alignment index M* = x* − y* that measures the degree of compliance with the financial matching principle along a continuous spectrum rather than as a binary categorisation. Applied to a ten-firm, cross-sectoral panel spanning Technology, Finance, Energy, and Automotive sectors over an observation window spanning 2001 to 2025 (with firm-specific subperiods reflecting differences in IPO dates and data availability), the framework reveals substantial heterogeneity in latent financing flows: equity allocation shares range from 30.1% (NVIDIA) to 75.1% (ExxonMobil), while debt allocation shares span 37.1% to 77.5%. Across the panel, only Meta exhibits substantial positive matching alignment, while Microsoft, ExxonMobil, Apple, and Tesla show only very slight differences that fall within the neutral band, and the remaining firms show varying degrees of structural departure from the matching benchmark; the thresholds used to summarise these descriptive labels are interpretive aids rather than re-imposed binary criteria, and the substantive ranking of firms along M* does not depend on the specific threshold values adopted. The ME solution’s entropy H(x*, y*) and the normalised diversification index D(x*, y*) describe allocation balance under the estimator’s information–theoretic criterion rather than independently observed firm complexity; in the present sample, the cross-firm ordering of these values is not recovered by firm size, leverage, or sector classification alone. These findings, based on a ten-firm case-study panel with time-invariant allocation parameters, should be interpreted as descriptive patterns of the present sample rather than statistically validated regularities. They provide a theoretically rigorous and computationally tractable identification of unobservable corporate financing flows, with potential implications for capital structure theory, financial risk assessment, and balance sheet analysis that would benefit from validation on larger and more representative samples in future work. Full article