Mejora del dimensionamiento de una red de calidad del aire mediante el empleo de métodos estadísticos multivariantes

Two multivariate statistical methods (principal component analysis and cluster analysis) have been used in this work to assess potential redundancies in stations and measurements of the air quality monitoring network of the Región de Murcia (Spain). The results show that there are no redundancies, not even in areas with more stations than required by the legislation. This highlights that current criteria for assigning stations to a particular area (based on population numbers) must be complemented with criteria that consider, among others, its industrial or touristic activity. The described methodology is applicable to other existing networks

Modelos matemáticos para la descripción del crecimiento de microorganismos patógenos en alimentos

[ESP] Los requerimientos actuales de calidad y seguridad microbiana en los alimentos sólo pueden ser satisfechos a través de una descripción detallada del comportamiento de los microorganismos patógenos durante el ciclo de vida del producto. La microbiología predictiva es clave en este aspecto, ya que describe por medio de modelos matemáticos la evolución de la población microbiana bajo diferentes condiciones ambientales. En esta contribución se presentan los modelos matemáticos más utilizados actualmente para la descripción de crecimiento microbiano. [ENG] Current standards on food quality and microbial safety can only be fulfilled through a detailed description of the behaviour of the pathogen microorganism during the life cycle of the product. Predictive microbiology serves a key role in this aspect. This science describes through mathematical models the evolution of a microbial population under different environmental conditions. This contribution presents the mathematical models most commonly used for the description of microbial growth.Escuela Técnica Superior de Ingeniería de Telecomunicación (ETSIT), Escuela Técnica Superior de Ingeniería Agronómica (ETSIA), Escuela Técnica Superior de Ingeniería Industrial (ETSII), Escuela Técnica Superior de Arquitectura y Edificación (ETSAE), Escuela Técnica Superior de Ingeniería de Caminos, Canales y Puertos y de Ingeniería de Minas (ETSICCPIM), Facultad de Ciencias de la Empresa (FCCE), Parque Tecnológico de Fuente Álamo (PTFA), Vicerrectorado de Estudiantes y Extensión de la UPCT, Vicerrectorado de Investigación e Innovación de la UPCT, y Vicerrectorado de Internacionalización y Cooperación al Desarrollo de la UPCT

Dynamics of microbial Inactivation and acrylamide production in high-temperature heat treatments

In food processes, optimizing processing parameters is crucial to ensure food safety, maximize food quality, and minimize the formation of potentially toxigenic compounds. This research focuses on the simultaneous impacts that severe heat treatments applied to food may have on the formation of harmful chemicals and on microbiological safety. The case studies analysed consider the appearance/synthesis of acrylamide after a sterilization heat treatment for two different foods: pureed potato and prune juice, using Geobacillus stearothermophilus as an indicator. It presents two contradictory situations: on the one hand, the application of a high-temperature treatment to a low acid food with G. stearothermophilus spores causes their inactivation, reaching food safety and stability from a microbiological point of view. On the other hand, high temperatures favour the appearance of acrylamide. In this way, the two objectives (microbiological safety and acrylamide production) are opposed. In this work, we analyse the effects of high-temperature thermal treatments (isothermal conditions between 120 and 135 _C) in food from two perspectives: microbiological safety/stability and acrylamide production. After analysing both objectives simultaneously, it is concluded that, contrary to what is expected, heat treatments at higher temperatures result in lower acrylamide production for the same level of microbial inactivation. This is due to the different dynamics and sensitivities of the processes at high temperatures. These results, as well as the presented methodology, can be a basis of analysis for decision makers to design heat treatments that ensure food safety while minimizing the amount of acrylamide (or other harmful substances) produced.The financial support of this research work was provided by the Ministry of Science, Innovation and Universities of the Spanish Government and European Regional Development Fund (ERDF) through project AGL2017-86840-C2-1-R. J.L.P.-S. is grateful to the JAE-INTRO program from CSIC (Grant no JAEINT19_EX_0797). A.G. was supported by a postdoctoral grant from the Fundación Séneca (20900/PD/18)

A multi-pollutant methodology to locate a single air quality monitoring station in small and medium-size urban areas

Air quality management is underpinned by continuous measurements of concentrations of target air pollutants in monitoring stations. Although many approaches for optimizing the number and location of air quality monitoring stations are described in the literature, these are usually focused on dense networks. However, there are small and medium-size urban areas that only require one monitoring station but also suffer from severe air pollution. Given that target pollutants are usually measured at the same sampling points; it is necessary to develop a methodology to determine the optimal location of the single station. In this paper, such a methodology is proposed based on maximizing an objective function, that balances between different pollutants measured in the network. The methodology is applied to a set of data available for the city of Cartagena, in southeast Spain. A sensitivity analysis reveals that 2 small areas of the studied city account for 80% of the optimal potential locations, which makes them ideal candidates for setting up the monitoring station. The methodology is easy to implement, robust and supports the decision-making process regarding the siting of fixed sampling sites.The sampling campaigns used to test the methodology were funded by the Consejería de Agricultura y Agua of the Comunidad Autónoma de la Región de Murcia

Multiplicity of solutions in model‑based multi objective optimization of wastewater treatment plants

Wastewater treatment process design involves the optimization of multiple conflicting objectives. The detection of different equivalent solutions in terms of objective values is crucial for designers in order to efficiently switch to the new optimal operation policies if changes in the process conditions or new constraints occur. In this work, the dynamic multi-objective optimization of a municipal wastewater treatment plant model is carried out. The aim is to simultaneously optimize an economic cost term and an effluent quality index. The selected process variables for the optimization are (1) an aeration factor in the aerated tank previous to the clarifier, and (2) an internal recycle flow rate. Their time profiles are approximated using the control vector parameterization technique. To solve the multi-objective problem and find the Pareto front, the NSGA-II algorithm has been used. The simulation of different realistic scenarios which impose operational constraints (e.g., maintenance operations) reveals that, indeed, multiple solutions exist at least in some areas of the Pareto front. It is observed that different control profiles can produce nearly identical results in terms of Pareto solutions. The a priori knowledge of these equivalent solutions for different scenarios provides the decision makers with alternative choices to be adapted to their organizations policies when events altering decision variables bounds or adding new constraints to the process model occur.The authors are grateful to Ministry of Science, Innovation and Universities (MICINN) and FEDER for their fnancial support (Projects DPI2016-77538-R and RTI2018-099139-B-C21

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press