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The mathematical modeling of a combination of non-thermal technologies for E. coli inactivation is of great interest for describing the dynamic behavior of microorganisms in food, with the goal of process control, optimization, and prediction. This research focused on the design and implementation of a mathematical model to predict the effect of power ultrasound (US), high-pressure processing (HPP), and the combination of both non-thermal technologies on the inactivation kinetics of E. coli (DSM682) inoculated in orange juice. Samples were processed by US, HPP, and a combination of both technologies at varying process parameters, and a mathematical model for microbial inactivation was developed using a System Dynamics approach. The results showed that the combination of these technologies exhibited a synergistic effect, resulting in no detectable colony-forming units per mL of juice. The developed model accurately predicted the inactivation of E. coli following the combination of these technologies (R2 = 0.82) and can be used to predict microbial load reduction or optimize it based on process parameters. Additionally, combining both techniques offers a promising approach for extending the shelf life of fresh juices using non-thermal stabilization technology. [ABSTRACT FROM AUTHOR]

Biological–mathematical models of trees can be exploited for a wide range of agronomic applications including crop management, visualization of ecosystem changes over time, in-field phenotyping, crop load effects, testing of plant functions, biomechanics, and many others. Some models propose a 3D output of tree that, in addition to having functionality to visualize the result, offers an additional tool for the evaluation of some parameters of the model itself (interception and amount of light, temperature, obstacles, physical competition between multiple trees). The present study introduces a biological–mathematical model of tree growth with a 3D output of its structure in a realtime 3D rendering environment (Unity©). Thanks to the virtual environment created in Unity©, it was possible to obtain variable environmental parameters (amount of light, temperature) used as inputs to the mathematical simulation of growth. The model is based on ordinary differential equations (ODEs) that compute the growth of each single internode in length (primary growth) and width (secondary growth) and the accumulation of growth inhibitors regulating the seasonal cyclicity of the tree. Virtual experiments were conducted varying environmental conditions (amount of light and temperature), and the species-specific characteristics of the simulated tree (number of buds, branching angle). The results have been analyzed showing also how the model can be adapted for the creation of different tree species and discussing the potential agronomic applications of model. [ABSTRACT FROM AUTHOR]

Computer-Generated Imagery (CGI) has received increasing interest in both research and the entertainment industry. Recent advancements in computer graphics allowed researchers and companies to create large-scale virtual environments with growing resolution and complexity. Among the different applications, the generation of biological assets is a relevant task that implies challenges due to the extreme complexity associated with natural structures. An example is represented by trees, whose composition made by thousands of leaves, branches, branchlets, and stems with oriented directions is hard to be modeled. Realistic 3D models of trees can be exploited for a wide range of applications including decision-making support, visualization of ecosystem changes over time, and for simple visualization purposes. In this review, we give an overview of the most common approaches used to generate 3D tree models, discussing both methodologies and available commercial software. We focus on strategies for modeling and rendering of plants, highlighting their accordance or not with botanical knowledge and biological models. We also present a proof of concept to link biological models and 3D rendering engines through Ordinary Differential Equations. [ABSTRACT FROM AUTHOR]

Large scale wildfire events that occurred around the world involved a massive loss of animal lives, with a consequent economic impact on agricultural holdings and damages to ecosystems. Preparing animals for a wildfire evacuation requires an extra level of planning, preparedness and coordination, which is missing in the current practice. This paper describes a conceptual framework of an ICT system implemented to support the activities of the Regional Veterinary referral Center for non-epidemic emergencies (CeRVEnE) in the Campania Region for the twofold objectives. On the one hand, it realizes the monitoring of the wooded areas under risk of fire in the so-called "Mount Vesuvius' red zone". On the other hand, it determines the OPtimal Evacuation Route for Animals (OPERA) in case of fire, for each of the reported animal species living in the mentioned red zone. The main innovation of the proposed system lies in its software architecture that aims at integrating a Distributed Sensor Network (DSN), an ad-hoc software to generate timely simulations for fire risk modeling, and a GIS (Geographic Information System) for both the activities of web mapping and OPERA definition. This paper shows some effective preliminary results of the system implementation. The importance of the system mainly lies in its accordance with the so-called "Foresight approach" perspective, that provides models and tools to guarantee the prevention of systematic failure in disaster risk management, and becomes moreover critical in the case of Mount Vesuvius, which hosts a unique combination of both animal and anthropic elements within a delicate natural ecosystem. [ABSTRACT FROM AUTHOR]