Coverage and invariance for the biological control of pests in mediterranean greenhouses

A major problem related to the treatment of ecosystems is that they have no available mathematical formalization. This implies that many of their properties are not presented as short, rigorous modalities, but rather as long expressions which, from a biological standpoint, totally capture the significance of the property, but which have the disadvantage of not being sufficiently manageable, from a mathematical standpoint. The interpretation of ecosystems through networks allows us to employ the concepts of coverage and invariance alongside other related concepts. The latter will allow us to present the two most important relations in an ecosystem – predator–prey and competition – in a different way. Biological control, defined as “the use of living organisms, their resources or their products to prevent or reduce loss or damage caused by pests”, is now considered the environmentally safest and most economically advantageous method of pest control (van Lenteren, 2011). A guild includes all those organisms that share a common food resource (Polis et al., 1989), which in the context of biological control means all the natural enemies of a given pest. There are several types of intraguild interactions, but the one that has received most research attention is intraguild predation, which occurs when two organisms share the same prey while at the same time participating in some kind of trophic interaction. However, this is not the only intraguild relationship possible, and studies are now being conducted on others, such as oviposition deterrence. In this article, we apply the developed concepts of structural functions, coverage, invariant sets, etc. (Lloret et al., 1998, Esteve and Lloret, 2006a, Esteve and Lloret, 2006b and Esteve and Lloret, 2007) to a tritrophic system that includes aphids, one of the most damaging pests and a current bottleneck for the success of biological control in Mediterranean greenhouses

A Sociocybernetics Data Analysis Using Causality in Tourism Networks

The aim of this paper is to propose a mathematical model to determine invariant sets, set covering, orbits and, in particular, attractors in the set of tourism variables. Analysis was carried out based on a pre-designed algorithm and applying our interpretation of chaos theory developed in the context of General Systems Theory. This article sets out the causal relationships associated with tourist flows in order to enable the formulation of appropriate strategies. Our results can be applied to numerous cases. For example, in the analysis of tourist flows, these findings can be used to determine whether the behaviour of certain groups affects that of other groups and to analyse tourist behaviour in terms of the most relevant variables. Unlike statistical analyses that merely provide information on current data, our method uses orbit analysis to forecast, if attractors are found, the behaviour of tourist variables in the immediate future

Design of Products Through the Search for the Attractor

The development of Internet technologies and their application to commerce environments has favored new business strategies for industries. These allow including in the design phase the experience of use that the clients have of the product. However, this new element has not been considered in formal terms. A fundamental problem in product design is that it has not been modeled in mathematical terms, which means that their characteristics do not appear in rigorous and short properties, but in long developments that from an economic point of view maintain their meaning but that from a mathematical point of view are not sufficiently manageable. Therefore, since these properties have not been axiomatically formalized, we cannot work with them mathematically. For this reason, we propose analyzing the design of products through a network and discrete chaos theory perspective, which will allow us to use important mathematical tools such as graph theory and concepts, such as coverage, invariability, orbits, attractors, and the structural function. This paper also draws attention to the importance of circular flow in the general systems theory and its application to the design phase of products. Finally, the Intel case study is analyzed, locating the current attractor and its relationship with the success of the company’s products.This work was supported in part by the Spanish Research Agency (AEI) and the European Regional Development Fund (FEDER) through project CloudDriver4Industry under Grant TIN2017-89266-R, and in part by the Valencian Government under Grant GV/2018/061

Causal Analysis of Databases Concerning Electromagnetism and Health

In this article, we conducted a causal analysis of a system extracted from a database of current data in the telecommunications domain, namely the Eurobarometer 73.3 database arose from a survey of 26,602 citizens EU on the potential health effects that electromagnetic fields can produce. To determine the cause-effect relationships between variables, we represented these data by a directed graph that can be applied to a qualitative version of the theory of discrete chaos to highlight causal circuits and attractors, as these are basic elements of system behavior

Exploring the potential of nanofluids to enhance the productivity of solar stills

Desalination technologies are being used to augment access to safe drinking water around the world. Nonetheless, most of these technologies are energy-intensive and driven by fossil fuels which emit greenhouse gases into the atmosphere, thereby contributing to climate change. Additionally, fossil fuels are non-renewable sources of energy and the exhaustion of such reserves can cause a threat to energy security. Consequently, exploitation of sustainable sources of energy for the desalination process has attracted a lot of attention. One such strategy is the use of a solar still which utilises solar energy to produce fresh water from saline or brackish water. However, the major drawback of a solar still lies in its low productivity. Many studies have investigated means of increasing the productivity of a solar still. One such technique which has recently been studied is to disperse nanoparticles into the impure water inside the basin of a solar still in order to obtain a nanofluid with enhanced optical and heat transfer characteristics. Since this is a relatively new topic, very few numerical studies on solar stills with nanofluids are available. Moreover, based on a literature review, no study examining the effect of nanoparticle size on the productivity of solar stills, and on the economic and environmental performance of solar stills was found. Additionally, the few available numerical studies on solar stills with nanofluids have not taken into account the view factor in the computation of the internal radiative heat transfer coefficient. Therefore, the aim of this study was to investigate both numerically and experimentally the effect of nanoparticle size on the performance of solar stills. Mathematical models with the view factor (Model 1) and without the view factor (Model 2) were developed for single slope solar stills, and a code was written in MATLAB software to solve a system of equations iteratively. Calculations were performed using climatic data from Stellenbosch (latitude 33.93°S, longitude 18.86°E) and University of Cape Town (latitude 33.96°S, longitude 18.46°E), South Africa, in order to evaluate the performance of solar stills with varying nanoparticle sizes. For the experimental phase, four identical solar stills were designed and built, and they were first tested with water only (base fluid) in all of them to test their performance and for calibration purposes. An Analysis of Variance (ANOVA) test was conducted on the experimental data collected from this first test. Subsequently, nanofluids containing aluminium oxide (Al2O3) nanoparticles of size 10 nm, 50 nm and 100 nm were used in three of the solar stills, with the other solar still containing the base fluid only. All the experiments were conducted at the University of Cape Town. The mathematical models were then validated using experimental data. Simulations in MATLAB based on Stellenbosch climatic data showed that for the month of January, which is a summer month in South Africa, the productivity of the solar still with the 10 nm, 50 nm and 100 nm Al2O3 nanoparticles was 9.01%, 8.94% and 8.89%, respectively higher than the productivity of the solar still with the base fluid only. On the other hand, for the month of July, which is a winter month in South Africa, the average productivity of the solar still with the 10 nm, 50 nm and 100 nm Al2O3 nanoparticles was 1.31%, 1.23% and 1.19%, respectively higher than the productivity of the solar still with base fluid only. In terms of the economic analysis, the simulations in MATLAB based on annual climatic data from Stellenbosch revealed that the cost of distilled water obtained from the solar still with the 10 nm, 50 nm and 100 nm Al2O3 nanoparticles was 10.42%, 6.21% and 3.51%, respectively higher than the cost of water obtained from the solar still with the base fluid only. Additionally, the payback period for the solar still with the 10 nm, 50 nm and 100 nm Al2O3 nanoparticles was 13.32%, 7.86% and 4.37%, respectively higher than the payback period for the solar still with the base fluid only. In terms of the environmental performance, the amount of carbon dioxide equivalent (CO2 equivalent) mitigated by the solar still with the 10 nm, 50 nm and 100 nm Al2O3 nanoparticles was 6.18%, 6.11% and 6.06%, respectively higher than the amount of CO2 equivalent mitigated by the solar still with the base fluid only. For the experimental phase, the ANOVA test based on the first set of experimental data (with base fluid only in all four solar stills) gave a probability-value (P-value) of 1.00. Moreover, experimental data collected from solar stills with base fluid and nanofluids revealed that the productivity of the solar still with nanoparticles of size 10 nm and 50 nm was 26.46% and 1.46%, respectively higher than the productivity of the solar still with base fluid only. On the other hand, the productivity of the solar still with nanoparticles of size 100 nm was 9.38% lower than that of the solar still with base fluid only. Furthermore, the root mean square error (RMSE) for the solar stills with nanofluids for Model 1 and Model 2 was 22.02% and 36.03%, respectively. It was confirmed that the performance of the calibrated solar stills was not significantly different. Moreover, the enhancement in the productivity of a solar still with nanofluids is much more distinct in summer than in winter. It was also demonstrated that the productivity of a solar still decreases with increasing nanoparticle size. Additionally, it was established that the cost of distilled water, the payback period and the amount of mitigated CO2 equivalent decrease with increasing nanoparticle size. Theoretically, the distillate yield and environmental performance of a solar still with nanofluids were marginally sensitive to the nanoparticle size while the cost of distilled water and payback period were significantly affected by the nanoparticle size. The effect of nanoparticle size on distillate yield was experimentally significant. Finally, it was demonstrated that the inclusion of the view factor improves the accuracy of modelling of solar stills with nanofluids