Exploring factors for antibiotic over-prescription in children with acute upper respiratory tract infections in Assiut, Egypt: a qualitative study.

BACKGROUND: Over-prescription of antibiotics contributes to antibiotic resistance, which is a global health threat. Egypt has alarmingly high rates of antibiotic over-prescription for acute upper respiratory tract infections (URIs) in children. To effectively address this issue, it is important to understand the various factors that influence prescription behaviors. The Teixeira antibiotic prescription behavioral model (TAPBM) offers a comprehensive framework through which these factors can be explored. This qualitative study sought to investigate the perspectives of key stakeholders involved in pediatric healthcare in Egypt, with the primary goal of identifying the underlying determinants that contributed to this problem. METHODS: This qualitative study was conducted in Assiut City, Egypt, between January and March 2023. Purposive sampling was used to select participants, including consultant pediatricians, supervisors of pediatric training programs, and specialists in infection prevention and control. Thirteen semi-structured in-depth interviews (IDIs) were conducted, audio-recorded, and transcribed. Thematic analysis was performed using MAXQDA 2020 software. RESULTS: Two main themes emerged from the analysis: intrinsic factors related to physicians, extrinsic factors related to patients, and nonphysician factors. Intrinsic factors encompass personal characteristics and attitudes. Prescribing decisions were influenced by factors such as fear of complications, limited follow-up visits, and competition. Knowledge and education also played a significant role. Moreover, diagnostic uncertainty in distinguishing between bacterial and viral infections posed a challenge. Extrinsic factors included patient and caregiver factors, such as parental expectations and demands for antibiotics, driven by the belief that they produced rapid results. Moreover, patients' demographic factors, including socioeconomic status and living conditions, affected their prescribing behavior. Health system-related factors, such as the type of healthcare institution and the absence of formal national guidelines, were identified as influential factors. Additionally, this study highlighted the influence of the pharmaceutical industry. The potential impact of the COVID-19 pandemic on antibiotic prescriptions was addressed. CONCLUSIONS: The study highlights the intricate interplay between intrinsic and extrinsic factors that shape antibiotic prescription decisions, underscoring the significance of addressing these factors in mitigating overprescribing.

Cluster Synchronization of Finite-Field Networks.

This technical paper investigates the cluster synchronization of finite-field networks (FFNs) based on the algebraic state space representation. By resorting to the semi-tensor product of matrices, the cluster synchronization of an FFN can be completely converted into the set stability of state trajectory. Then, a necessary and sufficient condition for the cluster synchronization of FFNs is obtained based on the invariant subset and one-step transition matrix. In particular, the obtained results are applicable to check the leader-follower synchronization and group consensus of FFNs. Finally, a numerical example is given to illustrate the feasibility of the obtained results.

Intermittent Event-Triggered Optimal Leader-Following Consensus for Nonlinear Multi-Agent Systems Via Actor-Critic Algorithm.

This article investigates the intermittent event-triggered optimal leader-following consensus for nonlinear multi-agent systems (MASs) utilizing the actor-critic algorithm. First, we propose a novel distributed intermittent event-triggered control strategy, and a sufficient criterion is obtained to guarantee the leader-following consensus of MASs by establishing a novel piecewise differential inequality. Next, the intermittent event-triggered optimal control strategy is delicately given. Remarkably, the optimality of MASs is proven based on policy iteration and the convergence of the closed-loop system is also proved based on the Lyapunov stability theory. Then, the intermittent event-triggered approximate optimal control strategy is designed via an actor-critic network whose weights are only updated at the trigger instants. Furthermore, the Zeno behavior can be excluded in this article. Finally, two simulation examples further verify the effectiveness of the proposed scheme.

Quasisynchronization of Heterogeneous Dynamical Networks via Event-Triggered Impulsive Controls.

The time-triggered impulsive control of complex homogeneous dynamical networks has received wide attention due to its occasional occupation of the communication channels. This article is devoted to quasisynchronization of heterogeneous dynamical networks via event-triggered impulsive controls with less channel occupation. Two kinds of triggered mechanisms, that is, the centralized event-triggered mechanism in which the control is updated based upon the state information of all nodes, and the distributed event-triggered mechanism where the control is updated according to the state information of each node and its neighboring node, are proposed, respectively, such that the synchronization error between the heterogeneous dynamical networks and a virtual target is not more than a nonzero bound. What is more, the Zeno behavior is shown to be excluded. It is found that the combination method of the event-triggered control and the impulsive control, that is, the distributed event-triggered impulsive control has the advantage of low-energy consumption and takes up many fewer communication channels over the time-triggered impulsive control. Two numerical examples are conducted to illustrate the effectiveness of the proposed event-triggered impulsive controls.

Entropic Uncertainty for Two Coupled Dipole Spins Using Quantum Memory under the Dzyaloshinskii-Moriya Interaction.

In the thermodynamic equilibrium of dipolar-coupled spin systems under the influence of a Dzyaloshinskii-Moriya (D-M) interaction along the z-axis, the current study explores the quantum-memory-assisted entropic uncertainty relation (QMA-EUR), entropy mixedness and the concurrence two-spin entanglement. Quantum entanglement is reduced at increased temperature values, but inflation uncertainty and mixedness are enhanced. The considered quantum effects are stabilized to their stationary values at high temperatures. The two-spin entanglement is entirely repressed if the D-M interaction is disregarded, and the entropic uncertainty and entropy mixedness reach their maximum values for equal coupling rates. Rather than the concurrence, the entropy mixedness can be a proper indicator of the nature of the entropic uncertainty. The effect of model parameters (D-M coupling and dipole-dipole spin) on the quantum dynamic effects in thermal environment temperature is explored. The results reveal that the model parameters cause significant variations in the predicted QMA-EUR.

Optimizing quantum cloning circuit parameters based on adaptive guided differential evolution algorithm.

Introduction: Quantum cloning operation, started with no-go theorem which proved that there is no capability to perform a cloning operation on an unknown quantum state, however, a number of trials proved that we can make approximate quantum state cloning that is still with some errors. Objectives: To the best of our knowledge, this paper is the first of its kind to attempt using meta-heuristic algorithm such as Adaptive Guided Differential Evolution (AGDE), to tackle the problem of quantum cloning circuit parameters to enhance the cloning fidelity. Methods: To investigate the effectiveness of the AGDE, the extensive experiments have demonstrated that the AGDE can achieve outstanding performance compared to other well-known meta-heuristics including; Enhanced LSHADE-SPACMA Algorithm (ELSHADE-SPACMA), Enhanced Differential Evolution algorithm with novel control parameter adaptation (PaDE), Improved Multi-operator Differential Evolution Algorithm (IMODE), Parameters with adaptive learning mechanism (PALM), QUasi-Affine TRansformation Evolutionary algorithm (QUATRE), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Cuckoo Search (CS), Bat-inspired Algorithm (BA), Grey Wolf Optimizer (GWO), and Whale Optimization Algorithm (WOA). Results: In the present study, AGDE is applied to improve the fidelity of quantum cloning problem and the obtained parameter values minimize the cloning difference error value down to 10-8 . Conclusion: Accordingly, the qualitative and quantitative measurements including average, standard deviation, convergence curves of the competitive algorithms over 30 independent runs, proved the superiority of AGDE to enhance the cloning fidelity.

Synchronization Analysis for Complex Dynamical Networks With Coupling Delay via Event-Triggered Delayed Impulsive Control.

This article deals with the exponential synchronization problem for complex dynamical networks (CDNs) with coupling delay by means of the event-triggered delayed impulsive control (ETDIC) strategy. This novel ETDIC strategy combining delayed impulsive control with the event-triggering mechanism is formulated based on the quadratic Lyapunov function. Among them, the event-triggering instants are generated whenever the ETDIC strategy is violated and delayed impulsive control is implemented only at event-triggering instants, which allows the existence of some network problems, such as packet loss, misordering, and retransmission. By employing the Lyapunov-Razumikhin (L-R) technique and impulsive control theory, some sufficient conditions with less conservatism are proposed in terms of linear matrix inequalities (LMIs), which indicates that the ETDIC strategy can guarantee the achievement of the exponential synchronization and eliminate the Zeno phenomenon. Finally, a numerical example and its simulations are presented to verify the effectiveness of the proposed ETDIC strategy.

A novel mathematical approach of COVID-19 with non-singular fractional derivative.

We analyze a proposition which considers new mathematical model of COVID-19 based on fractional ordinary differential equation. A non-singular fractional derivative with Mittag-Leffler kernel has been used and the numerical approximation formula of fractional derivative of function ( t - a ) n is obtained. A new operational matrix of fractional differentiation on domain [0, a], a ≥ 1, a ∈ N by using the extended Legendre polynomial on larger domain has been developed. It is shown that the new mathematical model of COVID-19 can be solved using Legendre collocation method. Also, the accuracy and validity of our developed operational matrix have been tested. Finally, we provide numerical evidence and theoretical arguments that our new model can estimate the output of the exposed, infected and asymptotic carrier with higher fidelity than the previous models, thereby motivating the use of the presented model as a standard tool for examining the effect of contact rate and transmissibility multiple on number of infected cases are depicted with graphs.

A novel Lyapunov theorem on finite/fixed-time stability of discontinuous impulsive systems.

This paper deals with the Finite/Fixed-Time Stability (FTS) problem of the discontinuous impulsive differential equation. Under the framework on differential inclusion, this problem can be transformed into the FTS problem of impulsive differential inclusion. A uniform criterion on FTS of nonlinear discontinuous impulsive differential systems with pre-given finite impulse instances is established, which is effective for both stabilizing impulses and destabilizing impulses. During this process, we propose an improved Lyapunov method, where the derivative of the Lyapunov Function (LF) may not exist in some instances. Moreover, the upper-bound estimation for the derivative of LF is allowed to be a time-varying function and takes both positive and negative values. Finally, the proposed criterion is supported by two numerical examples.

Event-Triggered Synchronization for Neutral-Type Semi-Markovian Neural Networks With Partial Mode-Dependent Time-Varying Delays.

This article studies the event-triggered stochastic synchronization problem for neutral-type semi-Markovian jump (SMJ) neural networks with partial mode-dependent additive time-varying delays (ATDs), where the SMJ parameters in two ATDs are considered to be not completely the same as the one in the connection weight matrices of the systems. Different from the weak infinitesimal operator of multi-Markov processes, a new one for the double semi-Markovian processes (SMPs) is first proposed. To reduce the conservative of the stability criteria, a generalized reciprocally convex combination inequality (RCCI) is established by the virtue of an interesting technique. Then, based on an eligible stochastic Lyapunov-Krasovski functional, three novel stability criteria for the studied systems are derived by employing the new RCCI and combining with a well-designed event-triggered control scheme. Finally, three numerical examples and one practical engineering example are presented to show the validity of our methods.

Incidence of HCV induced-Esophageal varices in Egypt: Valuable knowledge using data mining analysis.

Esophageal varices is one of the most important comorbidity related liver cirrhosis, patients usually presented with hematemesis, melena, or both, ultimately 20% is the mortality during the first attack, hence we aimed to investigate the incidence of such esophageal varices related chronic Hepatitis C virus (HCV) in randomized Egyptian population.One thousand eighteen Egyptian patients, aged between 17 and 58 years, positive for Hepatitis C virus genotype 4 (HCV-4) by enzyme linked immunosorbent assay Ab and HCV RNA-polymerase chain reaction were screened for the presence of esophageal varices.Incidence of esophageal varices was 62.3%; 635 patients, those with large Esophageal varices (LEVs) was 47.4%; 301 patients. Model for end-stage liver disease (MELD) score has not been significantly improved post variceal band ligation (VBL). Using 2D U/S was useful for EVs prediction.Incidence of esophageal varices in HCV Egyptian patients still high, valuable knowledge would be helpful in clinical field have been discovered by data mining computational intelligent analysis using in practical medicine to improve overall health care.

Collapsing a perfect superposition to a chosen quantum state without measurement.

Given a perfect superposition of [Formula: see text] states on a quantum system of [Formula: see text] qubits. We propose a fast quantum algorithm for collapsing the perfect superposition to a chosen quantum state [Formula: see text] without applying any measurements. The basic idea is to use a phase destruction mechanism. Two operators are used, the first operator applies a phase shift and a temporary entanglement to mark [Formula: see text] in the superposition, and the second operator applies selective phase shifts on the states in the superposition according to their Hamming distance with [Formula: see text]. The generated state can be used as an excellent input state for testing quantum memories and linear optics quantum computers. We make no assumptions about the used operators and applied quantum gates, but our result implies that for this purpose the number of qubits in the quantum register offers no advantage, in principle, over the obvious measurement-based feedback protocol.

Prevalence of skin diseases in rural areas of Assiut Governorate, Upper Egypt.

BACKGROUND: Few epidemiological surveys have been carried out to determine the prevalence of skin diseases in the population of Egypt, particularly "Upper Egypt". So it is a pressing necessity to conduct such a study in rural Assiut. OBJECTIVES: To determine the prevalence of various skin diseases in rural Assiut. SUBJECTS AND METHODS: A cross-sectional community-based survey was followed. The survey included 8008 rural inhabitants of all ages and both sexes from a representative of three villages of Assiut Governorate, Upper Egypt. The data were collected through personal interview and examination at homes from December 1994 to December 1996. RESULTS: They showed that 6961 (86.93%) of the studied population had one or more skin diseases. The group with parasitic skin infestations had the highest prevalence rate (27.40%) of the total sample, of which pediculosis capitis (19.37%) was the commonest. Eczema/dermatitis group had a rate of 19.82%, with pityriasis alba forming the majority (13.49%). Pigmentary disorders were 17.68%, followed by fungal skin infections (16.17%), then naevoid disorders (16.10%), hair and scalp disorders (12.07%), bacterial skin infections (10.10%), sweat gland disorders (6.16%), acne vulgaris (5.37%). Leprosy constituted 1.6/10,000. Other various skin disorders were recorded. CONCLUSIONS: Infective-parasitic diseases were a major problem particularly among the younger age-group and those of low socio-economic status.