The effects of explicit chiral symmetry breaking multiquark interactions on the spin 0 and 1 meson nonets: the ruling of the vector mesons

We have recently extended the scalar-pseudoscalar sector of a generalized NJL Lagrangian that includes all NLO non derivative interactions in Nc counting (including explicit symmetry breaking ones) in order to incorporate the spin 1 mesons in the low-lying ground state of QCD [1]. Upon bosonization, the well known mixing of the scalar-vector and of the pseudoscalar- axial-vector fields occurs in the quadratic part of the Lagrangian. We show that a linearized diagonalization of these terms can be effected in a completely general way without compromising the underlying symmetries of the Lagrangian [2]. The resulting spin 1 mass spectra evidence a relation involving only the vector and axial-vector meson masses and the constituent quark masses. We discuss the dominant role of this relation in the fits and we show that the model may be fitted to accommodate to a very good accuracy the 4 low-lying meson spectra.Comment: 5 pages, 3 tables; based on a talk given at Hadron 2017, Salamanc

A general framework to diagonalize vector--scalar and axial-vector--pseudoscalar transitions in the effective meson Lagrangian

A new mathematical framework for the diagonalization of the nondiagonal vector--scalar and axial-vector--pseudoscalar mixing in the effective meson Lagrangian is described. This procedure has unexpected connections with the Hadamard product of $n\times n$ matrices describing the couplings, masses, and fields involved. The approach is shown to be much more efficient as compared with the standard methods employed previously. The difference is especially noticeable if the chiral symmetry is broken explicitly. The paper ends with an illustrative application to the chiral model with broken $SU(3)_L\times SU(3)_R$ symmetry.Comment: 16 page

Sistema de recomendação Web usando agentes

O crescimento da Web trouxe vários problemas aos utilizadores. A grande quantidade de informação existente hoje em dia em alguns sítios Web torna a procura de informação útil muito difícil. Os objetivos dos proprietários dos sítios Web e dos utilizadores nem sempre coincidem. O conhecimento dos padrões de visitas dos utilizadores é crucial para que os proprietários possam transformar e adaptar o sítio Web. Este é o princípio do sítio Web adaptativo: o sítio Web adapta-se de forma a melhorar a experiência do utilizador. Alguns algoritmos foram propostos para adaptar um sítio da Web. Neste artigo, descrevemos uma proposta de um sistema de recomendação Web baseado em agentes que combina dois algoritmos: regras de associação e filtragem colaborativa. Ambos os algoritmos são incrementais e funcionam com dados binários. Os resultados mostram que, em algumas situações, a abordagem multiagente melhora a capacidade preditiva quando comparada com os agentes individuais.The growth of the Web has brought several problems for users. Today the vast amount of information on some web sites makes useful information finding very difficult. The objectives of the owners of the web sites and users do not always coincide. The knowledge of patterns of user visits is crucial to the owners to transform and adapt their web site. This is the adaptive website principle: the website adapts to improve the user experience. Some algorithms have been proposed to tailor a website. In this paper, we describe a proposal for a web recommendation system based on agents that combines two algorithms: association rules and collaborative filtering. Both algorithms are incremental and work with binary data. The results show that, in some situations, the multi-agent approach overcomes the predictive capacity of individual agents

Intelligent monitoring and management platform for the prevention of olive pests and diseases, including IoT with sensing, georeferencing and image acquisition capabilities through computer vision

Climate change affects global temperature and precipitation patterns. These effects, in turn, influence the intensity and, in some cases, the frequency of extreme environmental events, such as forest fires, hurricanes, heat waves, floods, droughts, and storms. In general, these events can be particularly conducive to the appearance of plant pests and diseases. The availability of models and a data collection system is crucial to manage pests and diseases in sustainable agricul-tural ecosystems. Agricultural ecosystems are known to be complex, multivariable, and unpredict-able. It is important to anticipate crop pests and diseases in order to improve its control in a more ecological and economical way (e.g., precision in the use of pesticides). The development of an intel-ligent monitoring and management platform for the prevention of pests and diseases in olive groves at Trás-os- Montes region will be very beneficial. This platform must: a) integrate data from multi-ple data sources such as sensory data (e.g., temperature), biological observations (e.g., insect counts), georeferenced data (e.g., altitude) or digital images (e.g., plant images); b) systematize these data into a regional repository; c) provide relevant forecasts for pest and diseases. Convolutional Neural Networks (CNNs) can be a valuable tool for the identification and classi-fication of images acquired by Internet of Things (IoT).info:eu-repo/semantics/publishedVersio

Ecophysiology of Penicillium expansum and patulin production in synthetic and olive-based media

Olives and their derivatives, in particular olive oil, represent one of the most significant agricultural products in the Mediterranean basin. Storage under inadequate conditions poses serious problems concerning fungal contamination, with consequent defects and potential mycotoxin production in olives and olive oils. Penicillium expansum represents one of the most significant postharvest pathogens in several fruits, including olives. Not only it causes blue mold but also is one of the most relevant patulin producing species of the genus Penicillium. The aim of this research was to evaluate the ecophysiological conditions governing growth and PAT production by P. expansum strains previously isolated from Tunisian olives. For this purpose, four P. expansum isolates were tested in a synthetic medium (Czapek Yeast Autolysate, CYA) and in olive-based medium (OM) for their ability to grow and produce PAT under different temperatures (4 °C, 15 °C and 25 °C) for 10 and 20 d. The mycotoxin was analysed by HPLC-UV. Results showed that all isolates were able to grow on tested media at different temperatures. Different PAT production profiles were found, showing that at 25 °C P. expansum isolates were able to produce PAT on CYA and OM medium. At 15 °C the production of PAT was only detected on CYA medium, while no PAT production was detected at 4 °C for the two media.The authors are grateful to the Foundation for Science and Technology (FCT, Portugal) and FEDER under Programme PT2020 for financial support to CIMO (UID/AGR/00690/2019).info:eu-repo/semantics/publishedVersio

Context-based multi-agent recommender system, supported on IoT, for guiding the occupants of a building in case of a fire

The evacuation of buildings in case of fire is a sensitive issue for civil society that also motivates the academic community to develop and study solutions to improve the efficiency of evacuating these spaces. The study of human behavior in fire emergencies has been one of the areas that have deserved the attention of researchers. However, this modeling of human behavior is difficult and complex because it depends on factors that are difficult to know and that vary from country to country. In this paper, a paradigm shift is proposed which, instead of focusing on modeling the behavior of occupants, focuses on conditioning this behavior by providing real-time information on the most efficient evacuation routes. Making this information available to occupants is possible with a solution that takes advantage of the growing use of the IoT (Internet of Things) in buildings to help occupants adapt to the environment. Supported by the IoT, multi-agent recommender systems can help users to adapt to the environment and provide the occupants with the most efficient evacuation routes. This paradigm shift is achieved through a context-based multi-agent recommender system based on contextual data obtained from IoT devices, which recommends the most efficient evacuation routes at any given time. The obtained results suggest that the proposed solution can improve the efficiency of evacuating buildings in the event of a fire; for a scenario with two hundred people following the system recommendations, the time they take to reach a safe place decreases by 17.7%.info:eu-repo/semantics/publishedVersio

An ontology for fire building evacuation

Guiding the building occupants under fire emergency to a safe place is an open research problem, and finding solutions to address the problem requires a perfect knowledge of the fire building evacuation domain. The use of ontologies to model knowledge of a domain allows a common and shared understanding of that domain, between people and heterogeneous systems. This paper presents an ontology that aims to build a knowledge model to understand the referred domain better and help develop more capable building evacuation solutions and systems. The herein proposed ontology considers the different variables and actors involved in the fire building evacuation process. We followed the Methontology methodology for its developing, and we present all the development steps, from the specification to its implementation with the Protégé tool.info:eu-repo/semantics/publishedVersio

An ontological model for fire evacuation route recommendation in buildings

Guiding the occupants of a building to a safe place is an area of research that deserves the attention of researchers. Finding solutions for the problem of guiding the building occupants requires a perfect knowledge of the fire building evacuation domain. The use of ontologies to model the knowledge of a domain allows a common and shared understanding of that domain. This paper presents an ontology that has the purpose to deepen the understanding of that domain and help develop building evacuation solutions and systems capable of guiding the occupants during a building evacuation process. The proposed ontology considers the different variables and actors involved in the fire building evacuation process. The ontology development followed the Methontology methodology, and for implementation, the Protégé tool was used. The ontological model was successfully submitted to a thorough evaluation process and is publicly available on the Web.info:eu-repo/semantics/publishedVersio