arXiv subjects

Abdallah Alsammani

Publications and source records attributed to Abdallah Alsammani.

10 recordsLinked to original sources

arXiv2026

Threshold Dynamics and Integrated Control of Cholera Transmission with Sanitation and Vaccination

Cholera transmission is sustained by interacting human and environmental pathways, making integrated control essential in settings with inadequate water, sanitation, and hygiene infrastructure. We develop and analyze a Susceptible--Infected--Recovered--Water (SIWR) model with Monod-type environmental transmission and three interventions: human sanitation, environmental sanitation, and vaccination. The control reproduction number decomposes as $\mathcal{R}_0=\mathcal{R}_0^{(h)}+\mathcal{R}_0^{(e)}$, separating direct and environmental transmission and yielding closed-form elasticity measures of pathway-specific contributions. We further quantify interactions between sanitation measures through an explicit Bliss independence synergy index. We establish local and global stability of the disease-free equilibrium and prove that the model undergoes a forward transcritical bifurcation at $\mathcal{R}_0=1$, excluding backward bifurcation. Global sensitivity analysis identifies direct transmission, the half-saturation constant, pathogen shedding, and human sanitation as major determinants of epidemic burden. Numerical simulations demonstrate that coordinated sanitation interventions can produce synergistic reductions in epidemic burden, providing a quantitative framework for evaluating integrated cholera control strategies.

math.DS↗

arXiv2026

Stochastic Dynamics of Hepatitis B Virus Infection: Extinction, Persistence, and Ergodicity

We develop and analyze a three-compartment stochastic model of within-host hepatitis B virus infection with multiplicative Itô noise. We establish global well-posedness, strict positivity, and uniform moment bounds, and derive an explicit sufficient criterion for almost sure exponential clearance. Standard extinction arguments based on $\ln(y+z)$ are conservative and fail to recover the deterministic spectral threshold. To overcome this limitation, we optimize over the weighted family $\ln(αy+z)$ and control hepatocyte fluctuations through exact occupation identities for $x+y$, avoiding both equilibrium substitution and an invalid pathwise comparison. The resulting general extinction bound admits a reduced optimized form under an explicit admissibility condition. This reduced bound lies no more than $\tfrac12\max\{σ_2^2,σ_3^2\}$ below the spectral abscissa $λ_{\max}(J)$ of the deterministic infected subsystem and converges to $λ_{\max}(J)$ when $σ_2,σ_3\to0$ with $σ_1^2/(σ_2^2+σ_3^2)\to0$. We further show that a noise-corrected reproduction number above unity guarantees the existence of a unique ergodic invariant measure in the positive orthant, and that the sufficient extinction and persistence regimes are mutually exclusive. Numerical experiments illustrate the theoretical results and quantify the effects of stochastic fluctuations on within-host viral dynamics.

math.DS↗

arXiv2026

Long-term Coexistence of Epidemics and Risk Awareness: Impacts of Adaptive Human Response and Fatigue

Human behavior shapes epidemic dynamics, yet most models represent it by rescaling the transmission rate, which conflates behavior with biology and fails to capture the memory associated with sustained protective behavior. We develop and analyze a susceptible-infected-recovered-aware model in which awareness is generated by prevalence and eroded by fatigue. Rather than modifying transmission probabilities, awareness moves susceptible and infectious individuals between accessible and inaccessible compartments. The basic reproduction number is independent of all behavioral parameters, showing that awareness cannot directly alter invasion. A unique endemic equilibrium exists exactly when the basic reproduction number is greater than one, thereby excluding backward bifurcation. Infection and awareness are uniformly persistent, ensuring robust coexistence. We derive an exact decomposition of the reduction in endemic burden into contributions from susceptible withdrawal and infectious sequestration, determine the effect of each behavioral parameter, and show that the endemic state depends on awareness response and fatigue only through their ratio. In addition, prevalence vanishes linearly as fatigue approaches zero. In the limit of instantaneous behavioral relaxation, the model reduces to the classical transmission-modulating formulation, whose endemic equilibrium is always stable. At finite relaxation rates, however, accessibility can destabilize the endemic equilibrium through a Hopf bifurcation, generating self-sustained epidemic cycles without any imposed delay.

physics.soc-ph↗

arXiv2026

A Tutorial on Symbolic Structural Identifiability Analysis of ODE Models in Julia

Structural identifiability analysis determines whether the parameters of a mechanistic ordinary differential equation (ODE) model can be uniquely recovered from ideal observations and is therefore a fundamental prerequisite for reliable parameter estimation. This tutorial presents a modern, reproducible computational framework for symbolic structural identifiability analysis using the Julia package StructuralIdentifiability.jl. We provide a rigorous yet accessible introduction to local and global identifiability, observability, parameter-to-output mappings, and identifiable parameter combinations, together with a unified workflow based on the core functions @ODEmodel, assess_local_identifiability, assess_identifiability, and find_identifiable_functions. The framework is demonstrated through seven case studies from epidemiology, pharmacokinetics, and systems biology, illustrating globally identifiable systems, local-only identifiability, structural non-identifiability, and recovery of identifiability through additional measurements and reparameterization. Beyond the theoretical foundations, the tutorial emphasizes practical model reformulation, experimental design, and reproducible scientific workflows within the Julia SciML ecosystem, providing a comprehensive reference for researchers and graduate students working with mechanistic ODE models.

stat.ME↗

arXiv2026

Adaptive Control and Mittag-Leffler Stability of Caputo Fractional Systems with State-Dependent Delays

This paper establishes new sufficient conditions for Mittag-Leffler stability of Caputo fractional-order nonlinear systems with state-dependent delays. The central analytical tool is a class of Lyapunov-Krasovskii functionals that incorporate singular kernels of the form $ξ^{α-1}$ for $α\in (0,1)$, coupling fractional memory effects with delay-induced dynamics in a unified framework. We prove that the resulting stability conditions reduce to computationally tractable linear matrix inequalities and derive explicit formulas for the maximum tolerable delay perturbation. Building on this stability foundation, we design an adaptive controller governed by fractional-order parameter update laws with $σ$-modification and a filter-based delay estimation mechanism that circumvents the need for classical state derivatives, which may not exist for fractional-order trajectories. The convergence analysis establishes ultimate boundedness of the closed-loop system with a computable bound that vanishes as the regularization parameters approach zero. Numerical validation on a three-neuron fractional Hopfield network with state-dependent transmission delays demonstrates that the proposed adaptive scheme reduces cumulative control energy by 99.3\% and achieves an asymptotic state error two orders of magnitude smaller than a comparable fractional sliding mode controller.

math.DS↗

arXiv2026

A Scalable Transaction Management Framework for Consistent Document-Oriented NoSQL Databases

NoSQL databases are widely used in modern applications due to their scalability and schema flexibility, yet they often rely on eventual consistency models that limit reliable transaction processing. This study proposes a four-stage transaction management framework for document-oriented NoSQL databases, with MongoDB as the reference platform. The framework combines transaction lifecycle management, operation classification, pre-execution conflict detection, and an adaptive locking strategy with timeout-based deadlock prevention. Formal correctness analysis shows that the proposed approach guarantees conflict serializability under defined conditions. An experimental evaluation using the Yahoo Cloud Serving Benchmark (YCSB) workloads A, B, and F, with concurrency levels ranging from 1 to 100 clients, demonstrates a reduction in transaction abort rates from 8.3% to 4.7%, the elimination of observed deadlocks, and a 34.2% decrease in latency variance. Throughput improvements ranging from 6.3% to 18.4% are observed under high concurrency, particularly for read-modify-write workloads. Distributed experiments on clusters of up to 9 nodes confirm scalability, achieving 15.2% higher throughput and 53% lower abort rates than baseline systems. Comparisons with MongoDB's native transactions, CockroachDB, and TiDB indicate that the proposed framework strikes a good balance between consistency guarantees and performance overhead. Sensitivity analysis identifies optimal parameter settings, including a lock timeout of 100 ms, an initial backoff of 10 ms, and a maximum backoff of 500 ms. These results show that carefully designed consistency mechanisms can significantly improve data integrity in NoSQL systems without undermining scalability.

cs.DB↗

arXiv2024

Coexistence via trophic cascade in plant-herbivore-carnivore systems under intense predation pressure

Carnivores interact with herbivores to indirectly impact plant populations, creating trophic cascades within plant-herbivore-carnivore systems. We developed and analyzed a food chain model to gain a mechanistic understanding of the critical roles carnivores play in ecosystems where plants face intense herbivory. Our model incorporates key factors such as seed production rates, seed germination probabilities, local plant interactions, herbivory rates, and carnivore predation rates. In the absence of carnivores, herbivores significantly reduce plant densities, often driving plants to extinction under high herbivory rates. However, the presence of carnivores suppresses herbivore populations, allowing plants to recover from herbivore pressure. We found that plant densities increase with carnivore predation rates, highlighting top-down effects and underscoring the importance of conserving carnivores in ecosystems where plants are at high risk of extinction from herbivory. Our results also show that carnivore density increases with seed-production rates, while herbivore density remains constant, indicating that plants benefit carnivores more than herbivores. This increase in carnivore density driven by high seed-production rates reflects bottom-up effects in the system. Overall, our study demonstrates that plants, herbivores, and carnivores can coexist even under intense predation stress. It suggests that carnivores play a crucial role in regulating plant and herbivore populations, with significant potential for maintaining biodiversity within ecosystems.

q-bio.PE↗

arXiv2023

Enhancement of database access performance by improving data consistency in a non-relational database system (NoSQL)

This study aims to enhance data consistency in NoSQL databases, traditionally designed with BASE properties, as opposed to the strong consistency guaranteed by ACID principles in RDBMS. We introduce a comprehensive four-stage server-side model engineered explicitly for MongoDB. This model covers transaction management, bifurcation of read and write transactions, assessment of transaction readiness, and transaction execution via a specialized locking algorithm. Utilizing the Yahoo Cloud Services Benchmark (YCSB), particularly for update-heavy workloads (A, B, and F), our model exhibited significant improvements. Specifically, the average throughput, read, and update latencies improved to 2864.726 ms, 32806.275 ms, and 51845.629 ms, respectively, from the baseline metrics of 2914.110 ms, 26510.930 ms, and 32457.662 ms. These results demonstrate the efficacy of our proposed model in enhancing consistency not only in document-based NoSQL databases like MongoDB but also in other NoSQL database variants, including key-value, graph, and wide-column stores.

cs.DB↗

arXiv2023

Mathematical Analysis of Autonomous and Nonautonomous Hepatitis B Virus Transmission Models

This study presents an improved mathematical model for Hepatitis B Virus (HBV) transmission dynamics by investigating autonomous and nonautonomous cases. The novel model incorporates the effects of medical treatment, allowing for a more comprehensive understanding of HBV transmission and potential control measures. Our analysis involves verifying unique solutions' existence, ensuring solutions' positivity over time, and conducting a stability analysis at the equilibrium points. Both local and global stability are discussed; for local stability, we use the Jacobian matrix and the basic reproduction number, $R_0$. For global stability, we construct a Lyapunov function and derive necessary and sufficient conditions for stability in our models, establishing a connection between these conditions and $R_0$. Numerical simulations substantiate our analytical findings, offering valuable insights into HBV transmission dynamics and the effectiveness of different interventions. This study advances our understanding of Hepatitis B Virus (HBV) transmission dynamics by presenting an enhanced mathematical model that considers both autonomous and nonautonomous cases.

math.DS↗

arXiv2022

Estimation of circular statistics in the presence of measurement bias

Background and objective. Circular statistics and Rayleigh tests are important tools for analyzing the occurrence of cyclic events. However, current methods fail in the presence of measurement bias, such as incomplete or otherwise non-uniform sampling. Consider, for example, studying 24-cyclicity but having data not recorded uniformly over the full 24-hour cycle. The objective of this paper is to present a method to estimate circular statistics and their statistical significance even in this circumstance. Methods. We present our objective as a special case of a more general problem: estimating probability distributions in the context of imperfect measurements, a highly studied problem in high energy physics. Our solution combines 1) existing approaches that estimate the measurement process via numeric simulation and 2) innovative use of linear parametrizations of the underlying distributions. We compute the estimation error for several toy examples as well as a real-world example: analyzing the 24-hour cyclicity of an electrographic biomarker of epileptic tissue controlled for state of vigilance. Results. Our method shows low estimation error. In a real-world example, we observed the corrected moments had a root mean square residual less than 0.007. We additionally found that, even with unfolding, Rayleigh test statistics still often underestimate the p-values (and thus overestimate statistical significance) in the presence of non-uniform sampling. Numerical estimation of statistical significance, as described herein, is thus preferable. Conclusions. The presented methods provide a robust solution to addressing incomplete or otherwise non-uniform sampling. The general method presented is also applicable to a wider set of analyses involving estimation of the true probability distribution adjusted for imperfect measurement processes.

q-bio.QM↗