Responses of CYP450 dependent system to aliphatic and aromatic hydrocarbons body burden in transplanted mussels from South coast of Portugal

Mussels Mytilus galloprovincialis were cross-transplanted at South Portugal from a reference site (site 1) to a site more contaminated with hydrocarbon compounds (site 2), and vice versa, in an active biomonitoring (ABM) concept, to assess the biotransformation capacity catalyzed by the mixed function oxygenase (MFO) system. Total alkanes (TAlk), the unresolved complex mixture (UCM), and total polycyclic aromatic hydrocarbons (TPAHs) concentration increased respectively 6, 4.4 and 4.2 fold relatively to control, in mussels transplanted from site 1 to 2. In the cross-transplant, a 48, 57 and 62% depuration of TAlk, UCM and TPAHs concentrations occurred by the end of the 3-4th week. Petrogenic and biogenic (marine and terrigenous) sources of AHs, and petrogenic and pyrolitic (biomass and oil/fuel incomplete combustion) sources of PAHs were detected at both sites. CYP450, CYT b (5) and NADPH-RED in mussels transplanted from site 1 to 2 were induced from day 0 to 28, with a total increase of 35, 32 and 35%, respectively, while biochemical equilibrium to lesser environmental contamination occurs in mussels transplanted from site 2 to 1. A significant relationship between CYP450 and NADPH-RED was found with TPAH, with distinctive behavior at the two sites. MFO system components increase with exposure time at one site and decreases in the other, reflecting an adaptation to distinct environmental hydrocarbon loads. The ABM strategy proved to be useful to understand the environment real impact on the biochemical responses in mussels' local populations. In this study, CYP450 and NADPH-RED are a useful biomarker for hydrocarbon exposure.FCT: PRAXIS XXI/BD/3740/94info:eu-repo/semantics/publishedVersio

East African cichlid fishes

Cichlid fishes are a very diverse and species-rich family of teleost fishes that inhabit lakes and rivers of India, Africa, and South and Central America. Research has largely focused on East African cichlids of the Rift Lakes Tanganyika, Malawi, and Victoria that constitute the biodiversity hotspots of cichlid fishes. Here, we give an overview of the study system, research questions, and methodologies. Research on cichlid fishes spans many disciplines including ecology, evolution, physiology, genetics, development, and behavioral biology. In this review, we focus on a range of organismal traits, including coloration phenotypes, trophic adaptations, appendages like fins and scales, sensory systems, sex, brains, and behaviors. Moreover, we discuss studies on cichlid phylogenies, plasticity, and general evolutionary patterns, ranging from convergence to speciation rates and the proximate and ultimate mechanisms underlying these processes. From a methodological viewpoint, the last decade has brought great advances in cichlid fish research, particularly through the advent of affordable deep sequencing and advances in genetic manipulations. The ability to integrate across traits and research disciplines, ranging from developmental biology to ecology and evolution, makes cichlid fishes a fascinating research system.Peer reviewe

Hyperbolicity through stable shadowing for generic geodesic flows

We prove that the closure of the closed orbits of a generic geodesic flow on a closed Riemannian n >= 2 dimensional manifold is a uniformly hyperbolic set if the shadowing property holds C2-robustly on the metric. We obtain analogous results using weak specification and the shadowing property allowing bounded time reparametrization.The authors were partially supported by the Project ‘New trends in Lyapunov exponents’ (PTDC/MAT-PUR/29126/2017). MB was partially supported by FCT - ‘Fundação para a Ciência e a Tecnologia’, through Centro de Matemática e Aplicações (CMA-UBI), Universidade da Beira Interior, project UID/MAT/00212/2013. JLD was partially supported by the Project CEMAPRE - UID/MULTI/00491/2019 financed by FCT/MCTES through national funds. MJT was partially supported by the Research Centre of Mathematics of the University of Minho with the Portuguese Funds from the Fundação para a Ciência e a Tecnologia, through the Project UID/MAT/00013/2013

Emotional intelligence profile of tourists and its impact on tourism

The study aims to characterize, for the first time, the emotional intelligence profile of the tourists visiting the city of Porto as well as to observe its influence on the intention to return and activities perfomed during the stay, along with other sociodemographic factors,To achieve these purposes, we used a sample of 886 responses with the following purposes: on the one hand, to get the emotional intelligence constructs by applying the confirmatory factorial analysis, and on the other hand, to apply a logit model to describe the intention to return. Four constructs of tourists’ emotional intelligence emerged: emotion regulation, emotion use, evaluation of their own emotions, and evaluation of others’ emotions. . The first construct was indicated as the most important leading us to conclude that tourists have the ability to control their own emotions, presenting a strong emotional control. The four constructs and different variables of the tourists’ socio-demographic profile show a positive effect on the intention to return. This type of information is highly useful for the sector since it allows the definition of communication strategies and guides businesses to adapt to the profile of tourists.B913-0565-0908 | Elvira VieiraN/

Deep learning-based energy expenditure estimation in assisted and non-assisted gait using inertial, EMG, and heart rate wearable sensors

Energy expenditure is a key rehabilitation outcome and is starting to be used in robotics-based rehabilitation through human-in-the-loop control to tailor robot assistance towards reducing patients’ energy effort. However, it is usually assessed by indirect calorimetry which entails a certain degree of invasiveness and provides delayed data, which is not suitable for controlling robotic devices. This work proposes a deep learning-based tool for steady-state energy expenditure estimation based on more ergonomic sensors than indirect calorimetry. The study innovates by estimating the energy expenditure in assisted and non-assisted conditions and in slow gait speeds similarly to impaired subjects. This work explores and benchmarks the long short-term memory (LSTM) and convolutional neural network (CNN) as deep learning regressors. As inputs, we fused inertial data, electromyography, and heart rate signals measured by on-body sensors from eight healthy volunteers walking with and without assistance from an ankle-foot exoskeleton at 0.22, 0.33, and 0.44 m/s. LSTM and CNN were compared against indirect calorimetry using a leave-one-subject-out cross-validation technique. Results showed the suitability of this tool, especially CNN, that demonstrated root-mean-squared errors of 0.36 W/kg and high correlation (ρ > 0.85) between target and estimation (R¯2 = 0.79). CNN was able to discriminate the energy expenditure between assisted and non-assisted gait, basal, and walking energy expenditure, throughout three slow gait speeds. CNN regressor driven by kinematic and physiological data was shown to be a more ergonomic technique for estimating the energy expenditure, contributing to the clinical assessment in slow and robotic-assisted gait and future research concerning human-in-the-loop control.This work has been supported in part by the FEDER Funds through the COMPETE 2020-Programa Operacional Competitividade e Internacionalizacao (POCI) and P2020 with the Reference Project SmartOs Grant POCI-01-0247-FEDER-039868, and by FCT national funds, under the national support to R&D units grant, through the reference project UIDB/04436/2020 and UIDP/04436/2020, under the FCT scholarship with reference 2020.05708.BD, and under the Stimulus of Scientific Employment with the grant 2020.03393.CEECIND

Graphical simulation of numerical algorithms : an approach based on code instrumentation and Java technologies

We want to create a working tool for mathematics teachers and a corresponding learning tool for students, namely a graphical simulator of mathematical algorithms (GraSMa). To achieve it we try two different strategies. We started by annotate manually the original algorithm with inspector functions. Now we are testing a new approach that aims to automatically annotate the original code with inspector functions. To achieve this we are developing a language translator module that enables to comment automatically any code written in Octave language. The run of the annotated code gated by one of these two ways, records in a XML (eXtensible Markup Language) file everything that happened during the execution. Subsequently, the XML file is parsed by a Java application that graphically represents the mathematic objects and their behaviour during execution. The final application will be accessed on-line through a website (WebGraSMa) which is currently under development. In this paper we report and discuss about the procedures followed and present some intermediate results