The public health risk posed by Listeria monocytogenes in frozen fruit and vegetables including herbs, blanched during processing

A multi-country outbreak ofListeria monocytogenesST6 linked to blanched frozen vegetables (bfV)took place in the EU (2015–2018). Evidence of food-borne outbreaks shows thatL. monocytogenesisthe most relevant pathogen associated with bfV. The probability of illness per serving of uncooked bfV,for the elderly (65–74 years old) population, is up to 3,600 times greater than cooked bfV and verylikely lower than any of the evaluated ready-to-eat food categories. The main factors affectingcontamination and growth ofL. monocytogenesin bfV during processing are the hygiene of the rawmaterials and process water; the hygienic conditions of the food processing environment (FPE); andthe time/Temperature (t/T) combinations used for storage and processing (e.g. blanching, cooling).Relevant factors after processing are the intrinsic characteristics of the bfV, the t/T combinations usedfor thawing and storage and subsequent cooking conditions, unless eaten uncooked. Analysis of thepossible control options suggests that application of a complete HACCP plan is either not possible orwould not further enhance food safety. Instead, specific prerequisite programmes (PRP) andoperational PRP activities should be applied such as cleaning and disinfection of the FPE, water control,t/T control and product information and consumer awareness. The occurrence of low levels ofL. monocytogenesat the end of the production process (e.g.<10 CFU/g) would be compatible with thelimit of 100 CFU/g at the moment of consumption if any labelling recommendations are strictly followed(i.e. 24 h at 5°C). Under reasonably foreseeable conditions of use (i.e. 48 h at 12°C),L. monocytogeneslevels need to be considerably lower (not detected in 25 g). Routine monitoring programmes forL. monocytogenesshould be designed following a risk-based approach and regularly revised based ontrend analysis, being FPE monitoring a key activity in the frozen vegetable industry

Toward the development of iteration procedures for the interval-based simulation of fractional-order systems

In many fields of engineering as well as computational physics, it is necessary to describe dynamic phenomena which are characterized by an infinitely long horizon of past state values. This infinite horizon of past data then influences the evolution of future state trajectories. Such phenomena can be characterized effectively by means of fractional-order differential equations. In contrast to classical linear ordinary differential equations, linear fractional-order models have frequency domain characteristics with amplitude responses that deviate from the classical integer multiples of ±20 dB per frequency decade and, respectively, deviate from integer multiples of ± 2 in the limit values of their corresponding phase response. Although numerous simulation approaches have been developed in recent years for the numerical evaluation of fractional-order models with point-valued initial conditions and parameters, the robustness analysis of such system representations is still a widely open area of research. This statement is especially true if interval uncertainty is considered with respect to initial states and parameters. Therefore, this paper summarizes the current state-of-the-art concerning the simulation-based analysis of fractional-order dynamics with a restriction to those approaches that can be extended to set-valued (interval) evaluations for models with bounded uncertainty. Especially, it is shown how verified simulation techniques for integer-order models with uncertain parameters can be extended toward fractional counterparts. Selected linear as well as nonlinear illustrating examples conclude this paper to visualize algorithmic properties of the suggested interval-based simulation methodology and point out directions of ongoing research

On the computation of solution spaces in high dimensions

A stochastic algorithm that computes box-shaped solution spaces for nonlinear, high-dimensional and noisy problems with uncertain input parameters has been proposed in Zimmermann and von Hoessle (Int J Numer Methods Eng 94(3):290–307, 2013). This paper studies in detail the quality of the results and the efficiency of the algorithm. Appropriate benchmark problems are specified and compared with exact solutions that were derived analytically. The speed of convergence decreases as the number of dimensions increases. Relevant mechanisms are identified that explain how the number of dimensions affects the performance. The optimal number of sample points per iteration is determined in dependence of the preference for fast convergence or a large volume

Combined parametric and worst case circuit analysis via Taylor models

This paper proposes a novel paradigm to generate a parameterized model of the response of linear circuits with the inclusion of worst case bounds. The methodology leverages the so-called Taylor models and represents parameter-dependent responses in terms of a multivariate Taylor polynomial, in conjunction with an interval remainder accounting for the approximation error. The Taylor model representation is propagated from input parameters to circuit responses through a suitable redefinition of the basic operations, such as addition, multiplication or matrix inversion, that are involved in the circuit solution. Specifically, the remainder is propagated in a conservative way based on the theory of interval analysis. While the polynomial part provides an accurate, analytical and parametric representation of the response as a function of the selected design parameters, the complementary information on the remainder error yields a conservative, yet tight, estimation of the worst case bounds. Specific and novel solutions are proposed to implement complex-valued matrix operations and to overcome well-known issues in the state-of-the-art Taylor model theory, like the determination of the upper and lower bound of the multivariate polynomial part. The proposed framework is applied to the frequency-domain analysis of linear circuits. An in-depth discussion of the fundamental theory is complemented by a selection of relevant examples aimed at illustrating the technique and demonstrating its feasibility and strength