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In Serbia, modern pork production systems with implemented control measures, including the detection of Trichinella larvae in meat (ISO18743), have eliminated farmed pork from pigs slaughtered at abattoirs as a source of trichinellosis. Epidemiological data from 2011 to 2020 indicate that the number of human cases and the number of infected domestic pigs has decreased significantly. Over the years, pork was the most frequent source of human infection. Cases generally occurred in small family outbreaks, and the infection was linked to consumption of raw or undercooked pork from backyard pigs. In most of the outbreaks, T. spiralis was the aetiological agent of infection, but in 2016, a large outbreak was caused by consumption of uninspected wild boar meat containing T. britovi larvae. To achieve safe pork, it is important that consumers of pork from animals raised in backyard smallholdings and of wild game meat are properly educated about the risks associated with consumption of untested meat. Laboratories conducting Trichinella testing should have a functional quality assurance system to ensure competency of analysts and that accurate and repeatable results are achieved. Regular participation in proficiency testing is needed.
Despite the COVID-19 pandemic, influenza remains an important issue. Especially in community settings, influenza outbreaks can be difficult to control and can result in high attack rates. In April 2022, a large A(H3N2) influenza outbreak spread in the largest Italian drug-rehabilitation community. One hundred eighty-four individuals presented influenza-like symptoms (attack rate of 26.2%); 56% previously received the influenza vaccine. Sequence analyses highlighted a genetic drift from the vaccine strain, which may have caused the observed lack of protection.
In this work, we establish a connection between the cumulative residual entropy and the Gini mean difference (GMD). Some relationships between the extropy and the GMD, and the truncated GMD and dynamic versions of the cumulative past extropy are also established. We then show that several entropy and extropy measures discussed here can be brought into the framework of probability weighted moments, which would facilitate finding estimators of these measures.
We consider the critical Galton–Watson process with overlapping generations stemming from a single founder. Assuming that both the variance of the offspring number and the average generation length are finite, we establish the convergence of the finite-dimensional distributions, conditioned on non-extinction at a remote time of observation. The limiting process is identified as a pure death process coming down from infinity.
This result brings a new perspective on Vatutin’s dichotomy, claiming that in the critical regime of age-dependent reproduction, an extant population either contains a large number of short-living individuals or consists of few long-living individuals.
SARS-CoV-2 has severely affected capacity in the National Health Service (NHS), and waiting lists are markedly increasing due to downtime of up to 50 min between patient consultations/procedures, to reduce the risk of infection. Ventilation accelerates this air cleaning, but retroactively installing built-in mechanical ventilation is often cost-prohibitive. We investigated the effect of using portable air cleaners (PAC), a low-energy and low-cost alternative, to reduce the concentration of aerosols in typical patient consultation/procedure environments. The experimental setup consisted of an aerosol generator, which mimicked the subject affected by SARS-CoV-19, and an aerosol detector, representing a subject who could potentially contract SARS-CoV-19. Experiments of aerosol dispersion and clearing were undertaken in situ in a variety of rooms with two different types of PAC in various combinations and positions. Correct use of PAC can reduce the clearance half-life of aerosols by 82% compared to the same indoor-environment without any ventilation, and at a broadly equivalent rate to built-in mechanical ventilation. In addition, the highest level of aerosol concentration measured when using PAC remains at least 46% lower than that when no mitigation is used, even if the PAC's operation is impeded due to placement under a table. The use of PAC leads to significant reductions in the level of aerosol concentration, associated with transmission of droplet-based airborne diseases. This could enable NHS departments to reduce the downtime between consultations/procedures
Suppose that m drivers each choose a preferred parking space in a linear car park with n spots. In order, each driver goes to their chosen spot and parks there if possible, and otherwise takes the next available spot if it exists. If all drivers park successfully, the sequence of choices is called a parking function. Classical parking functions correspond to the case $m=n$.
We investigate various probabilistic properties of a uniform parking function. Through a combinatorial construction termed a parking function multi-shuffle, we give a formula for the law of multiple coordinates in the generic situation $m \lesssim n$. We further deduce all possible covariances: between two coordinates, between a coordinate and an unattempted spot, and between two unattempted spots. This asymptotic scenario in the generic situation $m \lesssim n$ is in sharp contrast with that of the special situation $m=n$.
A generalization of parking functions called interval parking functions is also studied, in which each driver is willing to park only in a fixed interval of spots. We construct a family of bijections between interval parking functions with n cars and n spots and edge-labeled spanning trees with $n+1$ vertices and a specified root.
This paper proposes a robust moment selection method aiming to pick the best model even if this is a moment condition model with mixed identification strength, that is, moment conditions including moment functions that are local to zero uniformly over the parameter set. We show that the relevant moment selection procedure of Hall et al. (2007, Journal of Econometrics 138, 488–512) is inconsistent in this setting as it does not explicitly account for the rate of convergence of parameter estimation of the candidate models which may vary. We introduce a new moment selection procedure based on a criterion that automatically accounts for both the convergence rate of the candidate model’s parameter estimate and the entropy of the estimator’s asymptotic distribution. The benchmark estimator that we consider is the two-step efficient generalized method of moments estimator, which is known to be efficient in this framework as well. A family of penalization functions is introduced that guarantees the consistency of the selection procedure. The finite-sample performance of the proposed method is assessed through Monte Carlo simulations.
Given a spectrally negative Lévy process, we predict, in an $L_1$ sense, the last passage time of the process below zero before an independent exponential time. This optimal prediction problem generalises [2], where the infinite-horizon problem is solved. Using a similar argument as that in [24], we show that this optimal prediction problem is equivalent to solving an optimal prediction problem in a finite-horizon setting. Surprisingly (unlike the infinite-horizon problem), an optimal stopping time is based on a curve that is killed at the moment the mean of the exponential time is reached. That is, an optimal stopping time is the first time the process crosses above a non-negative, continuous, and non-increasing curve depending on time. This curve and the value function are characterised as a solution of a system of nonlinear integral equations which can be understood as a generalisation of the free boundary equations (see e.g. [21, Chapter IV.14.1]) in the presence of jumps. As an example, we numerically calculate this curve in the Brownian motion case and for a compound Poisson process with exponential-sized jumps perturbed by a Brownian motion.
The COVID-19 pandemic remains a public health problem threatening national and global health security. The socio-economic impact of COVID-19 was more severe on developing countries including Lebanon, especially due to the fragile healthcare system, weak surveillance infrastructure and lack of comprehensive emergency preparedness and response plans. Lebanon has been struggling with plethora of challenges at the social, economic, financial, political and healthcare levels prior to the COVID-19 pandemic. The COVID-19 pandemic in Lebanon revealed gaps and challenges across the spectrum of preparedness and response to emergencies. Despite these challenges, the Lebanese response was successful in delaying the steep surge of COVID-19 cases and hospitalisations through imposing strict public health and social measures. The deployment of the national vaccination plan in Lebanon in February 2021 coincided with the reduction in the number of cases and hospitalisation rates. The aim of this manuscript is to advance the epidemiologic evolution of COVID-19 in Lebanon pre- and post-vaccination, the challenges affecting the response and recovery, and the lessons learned.
From the Poisson–Dirichlet diffusions to the Z-measure diffusions, they all have explicit transition densities. We show that the transition densities of the Z-measure diffusions can also be expressed as a mixture of a sequence of probability measures on the Thoma simplex. The coefficients are the same as the coefficients in the Poisson–Dirichlet diffusions. This fact will be uncovered by a dual process method in a special case where the Z-measure diffusions are established through an up–down chain in the Young graph.
The axioms of quantum physics imply that in general it makes no sense to speak of the long-term behaviour of a quantum walk. In this chapter we introduce a process that allows us to develop a meaningful substitute for a simple average.
To specify a discrete quantum walk on a graph, we need more than just the graph. In general we need some kind of ordering on the edges on each vertex, and this extra structure is closely related to machinery used to describe embeddings of graph in surfaces. in this chapter we explain this connection.
We present applications of the machinery developed in the previous chapter. The applications include examples of perfect state transfer, and a second treatment of Grover’s algorithm.
We consider solutions of Lévy-driven stochastic differential equations of the form $\textrm{d} X_t=\sigma(X_{t-})\textrm{d} L_t$, $X_0=x$, where the function $\sigma$ is twice continuously differentiable and the driving Lévy process $L=(L_t)_{t\geq0}$ is either vector or matrix valued. While the almost sure short-time behavior of Lévy processes is well known and can be characterized in terms of the characteristic triplet, there is no complete characterization of the behavior of the solution X. Using methods from stochastic calculus, we derive limiting results for stochastic integrals of the form $t^{-p}\int_{0+}^t\sigma(X_{t-})\,\textrm{d} L_t$ to show that the behavior of the quantity $t^{-p}(X_t-X_0)$ for $t\downarrow0$ almost surely reflects the behavior of $t^{-p}L_t$. Generalizing $t^{{\kern1pt}p}$ to a suitable function $f\colon[0,\infty)\rightarrow\mathbb{R}$ then yields a tool to derive explicit law of the iterated logarithm type results for the solution from the behavior of the driving Lévy process.
The invariant Galton–Watson (IGW) tree measures are a one-parameter family of critical Galton–Watson measures invariant with respect to a large class of tree reduction operations. Such operations include the generalized dynamical pruning (also known as hereditary reduction in a real tree setting) that eliminates descendant subtrees according to the value of an arbitrary subtree function that is monotone nondecreasing with respect to an isometry-induced partial tree order. We show that, under a mild regularity condition, the IGW measures are attractors of arbitrary critical Galton–Watson measures with respect to the generalized dynamical pruning. We also derive the distributions of height, length, and size of the IGW trees.