The case study of Setúbal, Portugal

Green infrastructure is a strategically planned network of natural and semi-natural areas that are designed and managed to deliver a wide range of ecosystem services. It incorporates green and blue spaces and other physical features in terrestrial and marine areas. Despite the increase of green infrastructure planning in several regions of the world, such as Europe and North America, there is still a complexity and diversity associated with the concept of green infrastructure that influences the variance in approaches of green infrastructure planning. This research proposed a multi-criteria method that was organized in four steps for designing a green infrastructure for the municipality of Setúbal (Portugal) that efficiently integrated the ecological and social components in the planning and policymaking processes, as well as green infrastructure planning principles. The results show a green infrastructure that comprised around 91% of the territory of the case study, organized into two systems: the fundamental green infrastructure, which was related to the areas whose ecological interests were more favorable, and the urban green infrastructure, which aimed to enhance and intensify ecological processes in built-up areas. This approach focused on the protection of ecological functions, the preservation of the cultural and natural heritage, and the prevention of risks at a local level; it also followed several green infrastructure planning principles, namely, connectivity, multifunctionality, diversity, integration, and applicability.publishersversionpublishe

hybridModels: An R Package for the Stochastic Simulation of Disease Spreading in Dynamic Networks

Disease spreading simulations are traditionally performed using coupled differential equations. However, in the setting of metapopulations, most of the solutions provided by this method do not account for the dynamic topography of subpopulations. Conversely, the alternative approach of individual-based modeling (IBM) may add computational cost and complexity. Hybrid models allow for the study of disease spreading because they combine both aforementioned approaches by separating them across different scales: a local scale that addresses subpopulation dynamics using coupled differential equations and a global scale that addresses the contact between these subpopulations using IBM. We present a simple way of simulating the spread of disease in dynamic networks using the high-level statistical computational language R and the hybridModels package. We built four examples using disease spread models at the local scale in several different networks: an animal movement network; a three-node network, whose model solution using a stochastic simulation algorithm is compared with the ordinary differential equations approach; the commuting of individuals between patches, which we compare with the permanent migration of individuals; and the commuting of individuals within the metropolitan area of São Paulo

Model-based user interface testing with Spec Explorer and ConcurTaskTrees

Analytic usability analysis methods have been proposed as an alternative to user testing in early phases of development due to the cost of the latter approach. By working with models of the systems, analytic models are not capable of identifying implementation related problems that might have an impact on usability. Model-based testing enables the testing of an implemented software artefact against a model of what it should be (the oracle). In the case of model-based user interface testing, the models should be expressed at an adequate level of abstraction, adequately modelling the interaction process. This paper describes an effort to develop tool support enabling the use of task models as oracles for model-based testing of user interfaces.FCT -Fuel Cell Technologies Program(POSC/EIA/56646/2004

A bibliometric review and analysis of traffic lights optimization

The significant increase in the number of vehicles in urban areas emerges the challenge of urban mobility. Researchers in this area suggest that most daily delays in urban travel times are caused by intersections, which could be reduced if the traffic lights at these intersections were more efficient. The use of simulation for real intersections can be effective in optimizing the cycle times and improving the traffic light timing to coordinate vehicles passing through intersections. From these themes emerge the research questions: How are the existing approaches (optimization techniques and simulation) to managing traffic lights smartly? What kind of data (offline and online) are used for traffic lights optimization? How beneficial is it to propose an optimization approach to the traffic system? This paper aims to answer these questions, carried out through a bibliometric literature review. In total, 93 articles were analyzed. The main findings revealed that the United States and China are the countries with the most studies published in the last ten years. Moreover, Particle Swarm Optimization is a frequently used approach, and there is a tendency for studies to perform optimization of real cases by real-time data, showing that the praxis of smart cities has resorted to smart traffic lights.This work has been supported by FCT— Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020 and the project “Integrated and Innovative Solutions for the well-being of people in complex urban centers” within the Project Scope NORTE-01-0145-FEDER-000086

On tuning the particle swarm optimization for solving the traffic light problem

In everyday routines, there are multiple situations of high traffic congestion, especially in large cities. Traffic light timed regulated intersections are one of the solutions used to improve traffic flow without the need for large-scale and costly infrastructure changes. A specific situation where traffic lights are used is on single-lane roads, often found on roads under maintenance, narrow roads or bridges where it is impossible to have two lanes. In this paper, a simulation-optimization strategy is tested for this scenario. A Particle Swarm Optimization algorithm is used to find the optimal solution to the traffic light timing problem in order to reduce the waiting times for crossing the lane in a simulated vehicle system. To assess vehicle waiting times, a network is implemented using the Simulation of Urban MObility software. The performance of the PSO is analyzed by testing different parameters of the algorithm in solving the optimization problem. The results of the traffic light time optimization show that the proposed methodology is able to obtain a decrease of almost 26% in the average waiting times.This work has been supported by FCT-Fundação para a Ciência e Tecnologia within the R &D Units Project Scope: UIDB/00319/2020 and the project “Integrated and Innovative Solutions for the well-being of people in complex urban centers” within the Project Scope NORTE-01-0145-FEDER-000086

Production of Natural Pigments by Penicillium brevicompactum Using Agro-Industrial Byproducts

The demand for natural pigments for industrial applications has significantly increased. Penicillium brevicompactum was recently reported as a promising pigments producer using submerged fermentation and a synthetic culture medium containing lactose. In this work, pigment production by P. brevicompactum was studied under different fermentation conditions, namely, submerged fermentation with free (SmF) and immobilized mycelium (SmFi), and solid-state fermentation (SSF). The potential of culture media composed of agro-industrial byproducts (cheese-whey (CW) and corn steep liquor (CSL)) was investigated for the first time as low-cost alternatives to pigment production by P. brevicompactum. The fungus showed great adaptability to the different culture media and types of fermentation, being able to synthesize pigments under all the tested conditions. A culture medium composed of 34.6 g/L of CW and 8 g/L of CSL proved to be the most suitable alternative to the synthetic medium, especially under SmF and SmFi. Our data also show that different mixtures of pigments (yellow, orange, and red) can be produced depending on the medium composition and the type of fermentation. Additionally, the immobilization and reuse of biomass to produce pigments by P. brevicompactum were demonstrated for the first time, suggesting the possibility of operating under repeated batch mode at an industrial scale

Bipolar current power supply for the steering beam of the main line of the CV-28 Cyclotron

The objective of the beam transport system is to make the accelerated particles reach the targets with specific characteristics and with the desired quality optics, so it is necessary to use remotely commanded devices, such as collimators, quadrupoles lenses and steering magnets

ESTIMATIVAS DE ÁREA BASAL E USO DO RELASCÓPIO DE BITTERLICH EM AMOSTRAGEM DE FLORESTA ESTACIONAL DECIDUAL

A Floresta Estacional Decidual da região nordeste de Goiás é um tipo de vegetação florestal do grande bioma Cerrado, que pode ocorrer em áreas de afloramento de calcário e, geralmente, apresenta maior biomassa de espécies arbóreas que a vegetação de cerrado adjacente. Este estudo foi desenvolvido em uma área de floresta intacta (Fazenda Flor Ermo) e em quatro áreas de floresta perturbada (Fazendas Formosa, Traçadal, Manguinha e Conçeição Mocambo). O objetivo foi estimar a área basal e a intensidade amostral utilizando o relascópio de Bitterlich em florestas deciduais. A área basal foi de 29,3 m²/ha na floresta intacta e de 23 a 24 m²/ha nas perturbadas. As florestas com perturbação acentuada apresentaram curvas de distribuição do desvio padrão dos pontos de amostragem com pequena variação comparada com a curvas das áreas com baixo nível de perturbação. Para um limite de confiança de 95 % de probabilidade de confiança para a estimativa da média, 20 unidades amostrais com o relascópio podem ser suficientes para amostrar satisfatoriamente a área basal nesse tipo de vegetação

Forensic Human Identification for Cutaneous Microbiome, a Brief Review

Forensic Science compounds many study areas in context of solving crimes, one of which is the forensic microbiology. Combined with genomic approaches, microbiology has shown strong performance in studies regarding the relationship between microorganisms present on human skin and environment. The Human Microbiome Project (HMP) has contributed significantly to characterization of microbial complexity and their connection to human being. The purpose of this work consists of a historical overview of scientific articles, demonstrating the growth and possibility of using skin microbiome in forensic identification. Studies about use of cutaneous microbiome in human identification, as well its forensic approaches, were looked into for writing of this review. Comparisons among cutaneous microbial communities and manipulated objects have been tested using 16S rRNA, as well as a thorough sequencing of the bacterial genome. From use of ecological measures of distance to genetic markers with nucleotide variants and predictive algorithms, research has shown promising results for advances in field of forensic identification. The development of metagenomic microbial panel markers, named hidSkinPlax for targeted sequencing has been designed and tested with great results. Research results show satisfactory potential in human identification by cutaneous microbiome and the possibility for contributive use in elucidating crimes