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Este debate ocorreu na data de 30 de outubro do ano de 2021 como um lançamento em chamada pública para o dossiê temático de mesmo título. Ele está hospedado na plataforma YouTube no canal Luz Laboratório UDESC, pertencente ao Laboratório de iluminação da Universidade do Estado de Santa Catarina. O debate integrou a programação da décima edição do Evento A Luz em Cena. Teve como debatedores os integrantes da comissão editorial do Quarto Dossiê entre eles Flora Holderbaum, Thais Oliveira, Morgana Martins, Ernani Maleta e José Claudio Castanheira. A abertura e encerramento ficou sobre a coordenação de Marcelo Araújo como um representante do evento.

Modern manufacturing and assembly environments are characterized by a high variability in the built process which challenges human–robot cooperation. To reduce the cognitive workload of the operator, the robot should not only be able to learn from experience but also to plan and decide autonomously. Here, we present an approach based on Dynamic Neural Fields that apply brain-like computations to endow a robot with these cognitive functions. A neural integrator is used to model the gradual accumulation of sensory and other evidence as time-varying persistent activity of neural populations. The decision to act is modeled by a competitive dynamics between neural populations linked to different motor behaviors. They receive the persistent activation pattern of the integrators as input. In the first experiment, a robot learns rapidly by observation the sequential order of object transfers between an assistant and an operator to subsequently substitute the assistant in the joint task. The results show that the robot is able to proactively plan the series of handovers in the correct order. In the second experiment, a mobile robot searches at two different workbenches for a specific object to deliver it to an operator. The object may appear at the two locations in a certain time period with independent probabilities unknown to the robot. The trial-by-trial decision under uncertainty is biased by the accumulated evidence of past successes and choices. The choice behavior over a longer period reveals that the robot achieves a high search efficiency in stationary as well as dynamic environments., The work received financial support from FCT through the PhD fellowships PD/BD/128183/2016 and SFRH/BD/124912/2016, the project “Neurofield” (PTDC/MAT-APL/31393/2017) and the research centre CMAT within the project UID/MAT/00013/2013.

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Na sociedade contemporânea, há um número crescente de textos multimodais e de recursos tecnológicos que constroem representações sociais e estabelecem relações interpessoais, que, por sua vez, influenciam a maneira como entendemos nossas experiências cotidianas nos mais diversos contextos. Neste artigo, investigamos representações de masculinidades presentes em capas de revistas produzidas para o público LGBT+. Com base nos estudos de Kress e van Leeuwen (2006) em sua gramática do design visual, bem como em conceitos propostos pela Análise Crítica do Discurso (ACD) de Fairclough (1989), além de estudos de gênero social (LOPES, 2006; CONNELL, 2005), foram analisadas seis capas da revista MaisJR, com circulação nacional, tendo sido escolhida por ter a maior tiragem entre revistas do gênero no Brasil. Nessas capas, buscamos encontrar aspectos que nos ajudassem a entender se tais representações contribuem para a manutenção de uma visão hegemônica de masculinidade, ou se, ao contrário, ajudam a desconstruir padrões conhecidos na sociedade e propagados em outros meios. Após a seleção das capas, fizemos a análise multimodal e discutimos os resultados textuais encontrados com base em conceitos da ACD. Resultados gerais indicam que a revista trabalha com uma política editorial que favorece a propagação de valores hegemônicos no que diz respeito a masculinidades, valorizando o homem forte, musculoso, que possui pelos no corpo e que transmite a ideia de poder por meio do vestuário e/ou de como se comporta no meio social.

The skin is the most extensive and outermost organ in the body and can be greatly exploited both from the point of view of alternative routes of systemic drug delivery and treatment of dermatological diseases. Because of its main function as a barrier against harmful external agents, it also becomes a barrier to drug administration, but there are strategies to reduce this limitation of this promising route of administration. The development of polymer-based film-forming formulations is extensively studied for this purpose, since the formation of a film on the skin increases the contact time of the drug, for this being characterized as a controlled release reservoir system. There are a multitude of possible polymers to compose these formulations and their choice must be made according to the purpose of each application. This work, therefore, aims to study the state of the art of film forming systems for topical application of pharmaceutical formulations.

Na sociedade contemporânea, são inúmeras as demandas criadas cotidianamente decorrentes das relações interseccionais que compõem as experiências identitárias de indivíduos e de grupos sociais diversos, com base em marcadores sociais da diferença como gênero, sexualidade, raça, classe, etnia, afiliação religiosa e deficiência, que frequentemente se tornam catalizadoras de preconceitos e de discriminação. Diante desse contexto, investigamos, neste artigo, a construção do imaginário sociodiscursivo sobre o Catimbó-Jurema por meio da análise de quadros de cenas selecionadas do filme O Auto da Compadecida (2000), com suporte teórico-metodológico e crítico da gramática sistêmico-funcional (HALLIDAY; MATTHIESSEN, 2014), mais especificamente do sistema de transitividade da metafunção experiencial, da gramática do design visual (KRESS; VAN LEEUWEN, 2021), com foco nas metafunções representacional e composicional, e da análise crítica do discurso (FAIRCLOUGH, 1995, 2015; RESENDE; RAMALHO, 2006), com base no modelo tridimensional de Fairclough, em relação transdisciplinar com estudos em antropologia, ciências da religião, sociologia e filosofia. Resultados gerais das análises críticas e sistêmico-funcionais do discurso multimodal sobre o Catimbó-Jurema no filme O Auto da Compadecida apontam que a construção desse imaginário social ocorre por meio da mobilização de recursos verbais e imagéticos que buscam associar religiões afro-indígenas ao demoníaco na intersecção de discursos e práticas sociais que se (re)articulam de formas complexas, históricas e situadas. Por fim, compreendemos que as análises empreendidas nos possibilitaram uma visão crítica não apenas quanto à utilização dos recursos multimodais neste filme, mas também no que diz respeito às inter-relações entre os processos de construção de sentido por meio da linguagem e as inteligibilidades que também são parte do imaginário sociocultural.

Advances in the automotive industry are changing the relationship between cars and drivers. Advanced driver assistant systems, such as navigation systems, advanced cruise control, collision avoidance systems, and other safety systems, are now common and assist the driver in controlling the car. Smart key fobs have made getting in and starting the car almost effortless: the fob can be left in the pocket and the doors will unlock when a driver/user approaches the car and simply touches the door handle. This is a level of personalization and convenience that is almost standard today. The research presented here brings a new perspective on personalization and driver assistance systems. An online survey was conducted, which aimed to gather public opinion on the usefulness of endowing future (semi-)autonomous cars with social and cognitive behavior, such as the ability to learn drivers' routines and preferences in order to make decisions and perform actions in preparation for the next trip and to manage comfort within the cockpit without being commanded to do so. After filtering, the study included 657 respondents from 93 nations. The results demonstrate a favorable opinion towards such human-centered cognitive vehicles and could be helpful for designers in the automotive industry and other related stakeholders in the development of future cognitive vehicles.

Shunt surgery (SS) remains the most effective treatment for idiopathic Normal pressure hydrocephalus (iNPH), but the selection of the patients with the greatest potential benefit remains elusive.Identify gait features predictive of best response to SS in iNPH.Eight patients with iNPH were assessed at baseline, after Cerebrospinal fluid tap-test (CSF-TT) and SS, with clinical scales (Clinical/Patient Global Clinical Impression, EuroQol-5D, Clinical Dementia Rating Scale(CDR), MoCA test, Hoehn-Yahr Scale) and gait analysis with inertial sensors.The 8 included iNPH patients had a mean age of 73 years(59-81), moderate cognitive (CDR-1.5 (0.5-2); MoCA-9.5 (3-21)) and motor impairment (Hoehn-Yahr-2.75(2-3)). After SS, patients had a significant improvement in cognition (MoCA, p = 0.001) and quality of life. At baseline, patients with lower improvement (no change/ minimally improved) (n = 2), in comparison to patient with higher improvement (much/very much improved) (n = 6), already had higher cognitive impairment (MoCa-3(3-3) vs. 11(7-21)). Patients with lower improvement had a lower % of change in gait performance at LP (mean 10.2 %) and were absent of additional benefit after SS(mean -0.8 %). In contrast, gait performance in patients with higher improvement consistently got better from baseline to LP (mean 23.1 %) and from baseline to SS (mean 82.9 %). A significant negative correlation was observed between CDR score and several gait variables: speed (rThe magnitude of gait improvement after CSF-TT, quantified by gait analysis, can be used as an integral variable in the multimodal clinical approach to the prediction of improvement after SS.

Water loss is one of the factors that most affect a concessionaire’s financial sustainability. Early detection of any anomaly in water consumption is very valuable. This article aims to carry out a preliminary study to detect change points in consumption associated with water meter malfunction. The dataset is composed of water consumption measurements of two different companies (a hotel and a hospital) located in the north of Portugal, obtained during a complete year. Different methods were implemented in order to study its effectiveness in the detection of change points in the time series related to a sharp decrease in water consumption. Results suggest that the Seasonal Decomposition of Time Series by Loess method (STL) and the combination of several breakpoint detection methods is a suitable approach to be implemented in a software system, in order to help the company in anomaly detection and in the decision-making process of substituting the water meters.

As partículas poliméricas são estruturas complexas, que podem ser produzidas a partir de diversos tipos de polímeros, e as suas propriedades físico-químicas podem ser modificadas a fim de alterar o perfil de liberação de ativos. Neste estudo foram obtidas partículas poliméricas de poli(ácido lático) (PLA), pela técnica de emulsão/difusão, com a utilização de poloxamer (PF68) como tensoativo do sistema. Depois de preparadas as partículas, a suspensão resultante foi seca por dois métodos: Spray Dryer ou secagem por aspersão e Liofilização, e caracterizados por Espalhamento Dinâmico de Luz (DLS) Análise Termogravimétrica (TGA), Calorimetria Diferencial de Varredura (DSC). No TGA, observou-se dois eventos de degradação, os quais podem ser relacionados aos componentes da formulação (PLA e PF68). Quando as amostras foram analisadas por DLS, a amostra seca por spray dryer teve menor tamanho de partícula do que a amostra liofilizada. Na análise de TGA, ambas as amostras mostraram que a temperatura de degradação inicial foi menor do que as dos polímeros puros (PLA e PF68) e esse resultado está correlacionado com o tamanho da partícula. A amostra liofilizada apresentou a maior temperatura (Tonset), devido a um colapso das partículas oriundo da falta de crioprotetor. Por meio da técnica de calorimetria diferencial de varredura (DSC) tem-se que, a amostra obtida por spray dryer possui 2 populações de cristais, que são apresentados por um pico alargado, em temperaturas mais baixas, resultante de cristais menores ou mais imperfeitos e um pico de cristais mais perfeitos ou maiores, em temperaturas mais elevadas. Já a amostra liofilizada há apenas uma população de cristais. O grau de cristalinidade das partículas obtidas por liofilização e por spray dryer foi de 28% e 61%, respectivamente. Dessa forma, as partículas desenvolvidas por spray dryer apresentaram uma maior organização. A utilização de diferentes técnicas de secagem de partículas representa uma estratégia para produzir sistemas poliméricos com diferentes características.

Accepted Manuscript, The literature on gait analysis in Vascular Parkinsonism (VaP), addressing issues such as variability, foot clearance patterns, and the effect of levodopa, is scarce. This study investigates whether spatiotemporal, foot clearance and stride-to-stride variability analysis can discriminate VaP, and responsiveness to levodopa. Fifteen healthy subjects, 15 Idiopathic Parkinson's Disease (IPD) patients and 15 VaP patients, were assessed in two phases: before (Off-state), and one hour after (On-state) the acute administration of a suprathreshold (1.5 times the usual) levodopa dose. Participants were asked to walk a 30-meter continuous course at a self-selected walking speed while wearing foot-worn inertial sensors. For each gait variable, mean, coefficient of variation (CV), and standard deviations SD1 and SD2 obtained by Poincaré analysis were calculated. General linear models (GLMs) were used to identify group differences. Patients were subject to neuropsychological evaluation (MoCA test) and Brain MRI. VaP patients presented lower mean stride velocity, stride length, lift-off and strike angle, and height of maximum toe (later swing) (p, projects NORTE-01-0145-FEDER-000016 (NanoSTIMA) and NORTE-01-0145-FEDER-000026 (DeM), financed by the Regional Operational Program of the North (NORTE2020), under PORTUGAL2020 and FEDER.

The identification of stop locations in GPS trajectories is an essential preliminary step for obtaining trip information. We propose a neural network approach, based on the theoretical framework of dynamic neural fields (DNF), to identify automatically stop locations from GPS trajectories using their spatial and temporal characteristics. Experiments with real-world GPS trajectories were performed to show the feasibility of the proposed approach. The outcomes are compared with results obtained from more conventional clustering algorithms (K-means, hierarchical clustering, and HDBSCAN) which usually limit the use of the available temporal information to the definition of a threshold for the duration of stay. The experimental results show that the DNF approach not only robustly identifies places visited for a longer time but also stop locations that are visited for shorter periods but with higher frequency. Moreover, the self-stabilized activation patterns that the network dynamics develop and continuously update in response to GPS input encode simultaneously the spatial information and the time spent in each location. The impact of the obtained results on systems that automatically detect drivers’ daily routines from GPS trajectories is discussed.

Idiopathic Parkinson's disease (IPD) and vascular parkinsonism (VaP) present highly overlapping phenotypes, making it challenging to distinguish between these two parkinsonian syndromes. Recent evidence suggests that gait assessment and response to levodopa medication may assist in the objective evaluation of clinical differences. In this paper, we propose a new approach for gait pattern differentiation that uses convolutional neural networks (CNNs) based on gait time series with and without the influence of levodopa medication. Wearable sensors positioned on both feet were used to acquire gait data from 14 VaP patients, 15 IPD patients, and 34 healthy subjects. An individual's gait features are affected by physical characteristics, including age, height, weight, sex, and walking speed or stride length. Therefore, to reduce bias due to intersubject variations, a multiple regression normalization approach was used to obtain gait data. Recursive feature elimination using the linear support vector machine, lasso, and random forest were applied to infer the optimal feature subset that led to the best results. CNNs were implemented by means of various hyperparameters and feature subsets. The best CNN classifiers achieved accuracies of 79.33%±6.46, 82.33%±10.62, and 86.00%±7.12 without (off state), with (on state), and with the simultaneous consideration of the effect of levodopa medication (off/on state), respectively. The response to levodopa medication improved classification performance. Based on gait time series and response to medication, the proposed approach differentiates between IPD and VaP gait patterns and reveals a high accuracy rate, which might prove useful when distinguishing other diseases related to movement disorders., This research was partially financed by NORTE2020 and FEDER within the project NORTE-01–0145-FEDER- 000026 (DeM-Deus Ex Machina) and by Portuguese Funds through FCT (Fundação para a Ciência e a Tecnologia) within the Projects UIDB/00013/2020, UIDP/00013/2020 and UIDB/00319/2020.

Nowadays an increasing number of vehicles are being equipped with powerful cockpit systems capable of collecting drivers’ footprints over time. The collection of this valuable data opens effective opportunities for routine prediction. With the growing ability of vehicles to collect spatial and temporal information solving the routine prediction problem becomes crucial and feasible. It is then extremely important to advance and take advantage of the capabilities of these cockpit systems. A vehicle that is capable of predicting the next destination of the driver and when the driver intends to leave to that destination can prepare the journey in advance. Previous studies tackling the next location prediction problem have made use of Traditional Markov models, Neural Networks, Dynamic models, among others. In this work, a framework based on the hierarchical density-based clustering algorithm followed by a Long Short-Term Memory (LSTM) recurrent neural network is proposed for spatial-temporal prediction of drivers’ routines. Based on real-life driving scenarios of three different users, the proposed approach achieved a test set accuracy of 96.20%, 90.23%, and 86.40% when predicting the next destination and a R2 Score of 93.69, 79.21, and 28.81 when predicting the departure time, respectively. The results indicate that the proposed architecture can be implemented on the vehicle cockpit for the assistance of the management of future trips., Programme (COMPETE 2020) and national funds, through the ADI Project Bosch & UMinho “Easy Ride: Experience is everything” , ref POCI-01-0247 FEDER-039334, FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020 and UIDB/00013/2020.

In the era of industrial revolution 4.0, an automotive industry flourished in a way that was never before. As different features added in the driver assistance systems time-to-time, hence, nowadays the driving process is not so much tedious as it seems before. This ensures the operation of hassle-free driving, which leads towards autonomous vehicles. Overall, it opens up many opportunities for researchers and business communities, but at the same time, raises concerns and issues for discussion that need to be analyzed before put the final product (here, in the sense of fully automated vehicle) on the road. We conducted an online-survey (N = 3139) with participants from 146 nations was participated and assembled their valuable feedback on the automated driving and human presence in the autonomous vehicles considering all the levels of driving automation. This paper explores the results in terms of useful implications, which highlights and implied us to re-examine the present regulations and policies in automated driving and autonomous vehicles.

The goal of this study was grouping patients with parkinsonism that share similar gait characteristics based on principal component analysis (PCA). Spatiotemporal gait data during self-selected walking were obtained from 15 patients with Vascular Parkinsonism, 15 patients with Idiopathic Parkinson's Disease and 15 Controls. PCA was used to reduce the dimensionality of 12 gait characteristics for the 45 subjects. Fuzzy C-mean cluster analysis was performed plotting the first two principal components, which accounted for 84.1% of the total variability. Results indicates that it is possible to quantitatively differentiate different gait types in patients with parkinsonism using PCA. Objective graphical classification of gait patterns could assist in clinical evaluation as well as aid treatment planning., POCI-01-0145-FEDER-006961, National Funds through the FCT as part of project UID/EEA/50014/2013

Este trabalho tem como foco a obra teórico-técnica intitulada “Pequena Arte da Expressão do Violino ou Nuanças que fazem a Beleza da Execução”, de Adolpho Ferreira de Mello, compositor, intérprete e maestro natural de São José (SC) que atuou naquela cidade e em Desterro* (atual Florianópolis), nos fins do século XIX e início do XX. Traçaremos um breve perfil histórico das duas cidades vizinhas, situando o contexto musical local frente ao cenário nacional da Música de Salão e, através de artigos em revistas e jornais da época, resgataremos informações sobre a atuação musical de Adolpho Mello, a fim de lançar um olhar mais amplo sobre sua figura histórica. A seguir, faremos uma análise de seu anual de violino, analisando os conceitos ali apresentados à luz da literatura pedagógica do violino. Verificaremos assim, a relação entre a obra pesquisada e o referencial teórico–tecnico violinístico encontrado em Galamian e Flesch.

This paper presents a novel analytic method to uniquely solve inverse kinematics of 7 degrees-of-freedom manipulators while avoiding joint limits and singularities. Two auxiliary parameters are introduced to deal with the self-motion manifolds: the global configuration (GC), which specifies the branch of inverse kinematics solutions; and the arm angle (ψ) that parametrizes the elbow redundancy within the specified branch. The relations between the joint angles and the arm angle are derived, in order to map the joint limits and singularities to arm angle values. Then, intervals of feasible arm angles for the specified target pose and global configuration are determined, taking joint limits and singularities into account. A simple metric is proposed to compute the elbow position according to the feasible intervals. When the arm angle is determined, the joint angles can be uniquely calculated from the position-based inverse kinematics algorithm. The presented method does not exhibit the disadvantages inherent to the use of the Jacobian matrix and can be implemented in real-time control systems. This novel algorithm is the first position-based inverse kinematics algorithm to solve both global and local manifolds, using a redundancy resolution strategy to avoid singularities and joint limits., This work was partially supported by the NETT Project [FP7-PEOPLE-2011-ITN-289146]; and Foundation for Science and Technology, Portugal [grant number SFRH/BD/86499/2012]., info:eu-repo/semantics/publishedVersion

Diagnosis of Fabry disease (FD) remains a challenge mostly due to its rare occurrence and phenotipical variability, with considerable delay between onset and clinical diagnosis. It is then of extreme importance to explore biomarkers capable of assisting the earlier diagnosis of FD. There is growing evidence supporting the use of gait assessment in the diagnosis and management of several neurological diseases. In fact, gait abnormalities have previously been observed in FD, justifying further investigation. The aim of this study is to evaluate the effectiveness of different machine learning strategies when distinguishing patients with FD from healthy controls based on normalized gait features. Gait features of an individual are affected by physical characteristics including age, height, weight, and gender, as well as walking speed or stride length. Therefore, in order to reduce bias due to inter-subject variations a multiple regression (MR) normalization approach for gait data was performed. Four different machine learning strategies - Support Vector Machines (SVM), Random Forest (RF), Multiple Layer Perceptrons (MLPs), and Deep Belief Networks (DBNs) - were employed on raw and normalized gait data. Wearable sensors positioned on both feet were used to acquire the gait data from 36 patients with FD and 34 healthy subjects. Gait normalization using MR revealed significant differences in percentage of stance phase spent in foot flat and pushing ( $p ), with FD presenting lower percentages in foot flat and higher in pushing. No significant differences were observed before gait normalization. Support Vector Machine was the superior classifier achieving an FD classification accuracy of 78.21% after gait normalization, compared to 71.96% using raw gait data. Gait normalization improved the performance of all classifiers. To the best of our knowledge, this is the first study on gait classification that includes patients with FD, and our results support the use of gait assessment on the clinical assessment of FD.

Neural field models, formalized by integro-differential equations, describe the large-scale spatio-temporal dynamics of neuronal populations [1]. They have been used in the past as a framework for modeling a wide range of brain functions, including multi-item working memory [2]. Neural field equations support spatially localized regions of high activity (or bumps) that are initially triggered by brief sensory inputs and subsequently become self-sustained by recurrent interactions within the neural population. We apply a special class of oscillatory coupling functions and analyze how the shape and spatial extension of multi-bump solutions change as the spatial ranges of excitation and inhibition within the field are varied [3]. More precisely, we use numerical continuation to find and follow solutions of neural field equations as the parameter controlling the distance between consecutive zeros of the coupling function is varied [4]. Important for a working memory application (e.g. [5]), we investigate how changes in this parameter affect the shape of bump solutions and therefore the maximum number of bumps that may exist in a given finite interval., The work received financial support from FCT through the PhD fellowship PD/BD/128183/2016.

Differential diagnosis between Idiopathic Parkin-son's disease (IPD) and Vascular Parkinsonism (VaP) is a difficult task, especially early in the disease. There is growing evidence to support the use of gait assessment in diagnosis and management of movement disorder diseases. The aim of this study is to evaluate the effectiveness of some machine learning strategies in distinguishing IPD and VaP gait. Wearable sensors positioned on both feet were used to acquire the gait data from 15 IPD, 15 VaP, and 15 healthy subjects. A comparative classification analysis was performed by applying two supervised machine learning algorithms: Multiple Layer Perceptrons (MLPs) and Deep Belief Networks (DBNs). The decisional space was composed of the gait variables, with or without neuropsychological evaluation (Montreal cognitive assessment (MoCA) score), top-ranked in an error incremental analysis. In the classification task of characterizing parkinsonian gait by distinguishing between patients (IPD+VaP) and healthy control, from the all strides classification of the gait performed by the person, high accuracy (93% with or without MoCA) was obtained for both algorithms. In the classification task of the two groups of patients (VaP vs. IPD), DBN classifier achieved higher performance (73% with MoCA). To the best of our knowledge, this is the first study on gait classification that includes a VaP group. DBN classifiers are not frequently applied in literature to similar studies, but the results here obtained demonstrate that the use of DBN classifiers based on gait analysis is promising to be a good support to the neurologist in distinguishing VaP and IPD.

Fires are an important land use tool, a growing global hazard, and a factor involved in landscape processes with feedbacks on land degradation, especially in the Southwestern Mediterranean Europe, where the importance of fires in shaping ecological processes has long been recognized. As fires become recurrent, their intensity and dimension have increased and they have taken on catastrophic proportions, losing their role as catalysts of ecosystem renewal. Fires, and especially large forest fires (LFF), are the main drivers of land degradation in forest areas in Mediterranean sub-humid regions and are likely to increase as a result of climate and other global changes. The study area consists of the whole of mainland Portugal, which for the purpose of civil protection, is divided into 18 districts. The data used, including physical and demographic characteristics, change in land use and land cover, and economic structures are provided mainly by the Institute for the Conservation of Nature and Forests in statistical format and in shapefile format. Throughout the years, LFF in Portugal have become increasingly important. Although LFF in mainland Portugal represent a small fraction of the total occurrences (0.8 %), in accordance with the trends of the Mediterranean Basin, they are responsible for a large percentage of burned areas (>70 %). With the use of the GIS software, we were able to use the available information to generate a map of forest fire recurrences and, with the purpose of detecting homogeneous groups between the districts of mainland Portugal, a cluster analysis was applied. Using a multiple regression analysis, we present the LFF and their recurrence in mainland Portugal at the district level, demonstrating their regional incidence and the similarity between districts.

"Available online 3 March 2016", We study the conditions for the formation of multiple regions of high activity or “bumps” in a one-dimensional, homogeneous neural field with localized inputs. Stable multi-bump solutions of the integro-differential equation have been proposed as a model of a neural population representation of remembered external stimuli. We apply a class of oscillatory coupling functions and first derive criteria to the input width and distance, which relate to the synaptic couplings that guarantee the existence and stability of one and two regions of high activity. These input-induced patterns are attracted by the corresponding stable one-bump and two-bump solutions when the input is removed. We then extend our analytical and numerical investigation to NN-bump solutions showing that the constraints on the input shape derived for the two-bump case can be exploited to generate a memory of N>2N>2 localized inputs. We discuss the pattern formation process when either the conditions on the input shape are violated or when the spatial ranges of the excitatory and inhibitory connections are changed. An important aspect for applications is that the theoretical findings allow us to determine for a given coupling function the maximum number of localized inputs that can be stored in a given finite interval., The work received financial support from FCT through a PhD grant (SFRH/BD/41179/2007) and from the EU-FP7 ITN project NETT: Neural Engineering Transformative Technologies (nr. 289146).

Visando a obtencao de sistemas para aplicacao em tratamento de lesoes por HPV foram obtidos sistemas a base de PVA, PVP e da blenda destas matrizes na proporcao (75:25 PVA:PVP) carregados com 2,5% de oleo de Melaleuca. Os sistemas foram obtidos via solucao em solucao hidroalcoolica de agua com etanol na proporcao (70:30 v/v) e investigados pelas tecnicas de DRX e RMN-DT. As analises dos sistemas evidenciam uma miscibilidade mesmo que parcial entre as matrizes e indica uma acao de reducao da mobilidade molecular do oleo de Melaleuca nos sistemas propostos. Os resultados de DRX evidenciam que a presenca do oleo nas matrizes obtidas gera uma reducao da cristalinidade dos sistemas.

It has been hypothesized that the metabolism of alcohol is altered following bariatric surgery. However, few studies have evaluated preoperative and postoperative alcohol use. The aims of the study were to characterize alcohol use in the preoperative period and 2 years postoperatively as well as to identify factors associated. A study was conducted using data from the electronic charts of patients submitted to laparoscopic adjustable gastric banding (LAGB) and Roux-en-Y gastric bypass (RYGB) surgery in the city of Porto, Portugal. Associations with the following variables were analyzed: age, marital status, schooling, alcohol use, body mass index, binge eating disorder, and lifestyle habits. Among the 659 patients, 42.0 % completed the 2 years of follow-up. A total of 90.2 % were women; 67.4 % underwent LAGB, and 32.6 % underwent RYGB. The frequency of alcohol use was 24.2 % in the preoperative period and 9.4 % in the postoperative period (p = 0.000). Daily alcohol intake was two drinks in the preoperative period and 1.8 drinks in the postoperative period. Significant associations were found between postoperative alcohol use and the male gender (p = 0.001), age a parts per thousand yen45 years (p = 0.018), and preoperative BMI < 40 kg/m(2) (p = 0.028). No significant associations were found with the surgical technique. No previous nondrinkers became drinkers, and no patients increased the quantity or frequency of alcohol intake in the postoperative period. The prevalence of alcohol use in the sample was low. Moreover, a lower prevalence rate was found in the postoperative period, independently of surgical technique, clinical factors, and percentage of weight loss.

O presente artigo objetivou mostrar a utilização da etnoecologia, etnobotânica e o etnoconhecimento em comunidades locais do Estado de Mato Grosso, com foco no saber popular sobre plantas do bioma Cerrado. Goal of this study was to demonstrate the utilization of ethnoecology, ethnobotanic and ethno-knowledge at local communities in Mato Grosso State, focusing popular knowledge about plants of the Cerrado biome. Le but de cette étude était de démontrer l’utilisation de l’ethnoécologie, ethnobotanique e l’ethno-connaissance dans communautés locales en Mato Grosso Province mettant l’accent sur les savoirs populaires sur les plantes du biome Cerrado. El presente artículo tiene como objetivo mostrar el uso de etnoecología, etnobotánica y el etnoconocimiento en cumunidades locales del Estado de Mato Grosso, con el foco (centrándose) en el saber popular sobre las plantas del bioma Cerrado.

If we want robots to engage effectively with humans in service applications or in collaborative work scenarios they have be endowed with the capacity to perceive the passage of time and control the timing of their actions. Here we report result of a robotics experiment in which we test a computational model of action timing based on processing principles of neurodynamics. A key assumption is that elapsed time is encoded in the consistent buildup of persistent population activity representing the memory of sensory or motor events. The stored information can be recalled using a ramp-to-threshold dynamics to guide actions in time. For the experiment we adopt an assembly paradigm from our previous work on natural human-robot interactions. The robot first watches a human executing a sequence of assembly steps. Subsequently, it has to execute the steps from memory in the correct order and in synchrony with an external timing signal. We show that the robot is able to efficiently adapt its motor timing and to store this information in memory using the temporal mismatch between the neural processing of the sensory feedback about executed actions and the external cue., FCT - Fundació Catalana de Trasplantament(PD/BD/128183/2016)This research was supported by the Marie Curie Network for Initial Training NETT, FCT through the PhD fellowship PD/BD/128183/2016, the FCT-Research Center CMAT (PEstOE/MAT/UI0013/2014), and FCT - Algoritmi research Centre (COMPETE: POCI-01-0145-FEDER-007043 and FCT - Fundação para a Ciência e Tecnologia within the Project ˆ Scope: UID/CEC/00319/2013)

We consider feed-forward and auto-regulation feed-forward neural (weighted) coupled cell networks. In feed-forward neural networks, cells are arranged in layers such that the cells of the first layer have empty input set and cells of each other layer receive only inputs from cells of the previous layer. An auto-regulation feed-forward neural coupled cell network is a feed-forward neural network where additionally some cells of the first layer have auto-regulation, that is, they have a self-loop. Given a network structure, a robust pattern of synchrony is a space defined in terms of equalities of cell coordinates that is flow-invariant for any coupled cell system (with additive input structure) associated with the network. In this paper, we describe the robust patterns of synchrony for feed-forward and auto-regulation feed-forward neural networks. Regarding feed-forward neural networks, we show that only cells in the same layer can synchronize. On the other hand, in the presence of auto-regulation, we prove that cells in different layers can synchronize in a robust way and we give a characterization of the possible patterns of synchrony that can occur for auto-regulation feed-forward neural networks.

Throughout the years we have seen a new reality in Portugal regarding large forest fires, since they have become increasingly important. Although large forest fires (LFFs) in Portugal represent a small fraction of the total of occurrences, in keeping with the trends of the Mediterranean Basin, they are responsible for a large percentage of burned area. In the last ten years, the largest forest fires in the Portuguese territory (mega-fires) have been recorded, and although they do not cover a larger percentage of LFFs there is more burned area, which means that, on average, each LFF burned more area when compared to the previous decades. On the one hand, this resulted in the reduction of the number of LFFs throughout the years ; on the other hand, there is an increase in the individual area of the larger “large fires”.

O fogo é um elemento presente nas paisagens dos países do Sul da Europa, tendo acompanhado o pastoreio e os desbastes da floresta, através do tempo, e condicionado o desenvolvimento ou regressão dos ecossistemas florestais (Alves et al., 2006).As mudanças socioeconómicas em curso nos países do Sul da Europa, na segunda metade do seculo XX, refletiram-se no uso tradicional da terra e estilo de vida das populações e traduziram-se no aumento de grandes áreas de terras agrícolas abandonadas, muitas das quais se tornaram paisagens propensas à ocorrência de incêndios de grande intensidade, devido aos elevados níveis de biomassa, acumulados ao longo dos anos e prontos para alimentar fogos catastróficos durante o Verão.Com os grandes incêndios a aumentar em frequência e extensão, tomando, por vezes, dimensões catastróficas, perdeu-se o seu importante papel de renovadores dos ecossistemas (Noss et al., 2006).

The recurrence of forest fires is degrading an important part of the Portuguese natural heritage namely its forest and soils. In this paper we present the case study of Cabeço da Vaca (Cabreira Mountain—northwest Portugal), where in recent decades, particularly in the 70s, there was a significant increase in the number of forest fires and in the areas scorched annually. There is thus a turning point between a period when fire was an integral part of the ecosystems and when fire has become a serious threat to woodland management and development (Bento Gonçalves, 2006). Starting with a thorough characterization of forest fires and based on the mapping of scorched areas between 1990 and 2006, we have proceeded to identify the annual pattern of maximum recurrence and the definition of the return interval in Cabeço da Vaca, producing thus a valuable document to support management and forestry development in general.

Este artigo constitui um primeiro ensaio metodológico que visa realçar a importância da recorrência como indicador de situações de risco. Trata-se de uma metodologia expedita que permite obter a distribuição espacial das áreas de risco de incêndio.

As Interfaces Urbano-Rurais apresentam características que, em Portugal, são diversas das de outros países, dificultando a sua definição e identificação, bem como a das estratégias adequadas à prevenção, protecção e combate aos incêndios florestais. Tomando como área de estudo a região do Ave, no período de 2001 a 2007, procedemos à análise e identificação das freguesias correspondentes a áreas de Interface Urbano-Rural, utilizando a tipologia do INE., Au Portugal, les interfaces habitat urbain-forêt ont des caractéristiques différentes d’autres pays, ce qui rend difficile leur définition et l’identification des stratégies appropriées en matière de prévention, protection et lutte contre les incendies de forêt. Prenant la région d’Ave comme l’aire d’étude, on a procédé, pour la période de 2001 à 2007, à l’analyse et à l’identification de municipalités correspondantes aux interfaces habitat urbain-forêt, en utilisant la typologie de l’INE (Institut National de Statistique)., Wildland-Urban Interface (WUI) show different characteristics in Portugal, making it difficult to define and identify, as well as accurate strategies of prevention, protection and forest fire fighting. Considering Ave region as case study, between the years of 2001 and 2007, we have proceeded to the analysis and identification of territories corresponding to the WUI areas, using INE (National Statistic Institute) typology.

Em 1957 Freeman Tilden, em sua obra publicada e intitulada “Interpreting our Heritage” definiu interpretação como sendo Uma atividade educacional que objetiva revelar significados e relações através da utilização de objetos originais, de experiência de primeira mão, bem como de mídia ilustrativa, ao invés de simplesmente comunicar informações factuais. O propósito da mensagem interpretativa é inspirar e provocar os visitantes para que amplie seus horizontes. Estas são dicas, pistas chaves ou elementos de juízo, entre outros, que produzidas mediante o emprego de técnicas de comunicação efetivas e precisas, visam permitir mensagens impactantes e significativas. Para o produto turístico a interpretação é um componente essencial, sobretudo quando se apóia na cultura e em paisagens essenciais, ela possibilita aos visitantes conhecer e apreciar mais os lugares, podendo levá-los a prolongar sua permanência e estimular novas visitas. Desta forma, nosso trabalho visou avaliar o entendimento a respeito do conceito, princípios e práticas da interpretação da natureza por agentes envolvidos na cadeia do ecoturismo no estado do Mato Grosso. Para isso, formatou-se um questionário estruturado online (Google Docs), contendo nove questões, com quatro alternativas de resposta, onde formulou-se apontamentos coerentes e afirmações negativas pautadas nos princípios da interpretação da natureza. A amostragem deste trabalho envolveu 30 guias com registro no Cadastur como profissionais atuantes no segmento de ecoturismo no estado do Mato Grosso. Os resultados apontaram que a interpretação da natureza não é aplicada em sua totalidade pelos agentes da cadeia de ecoturismo, porque não há conhecimento e/ou entendimento do conceito em estudo, bem como sua fundamentação teórica e experiências de capacitação para o desenvolvimento nas atividades práticas. E quando aplicada não há clareza da fundamental importância de um programa interpretativo. O estudo apontou ainda a necessidade de expansão da aplicação metodológica a outros ambientes com prática do ecoturismo. The interpretation of nature and your application by ecotourism agents in Mato Grosso (Brazil) ABSTRACT In 1957 Freeman Tilden, in their published work and entitled "Interpreting our Heritage" defined interpretation as being an educational activity which aims to reveal meanings and relationships through the use of original objects, by firsthand experience, as well as illustrative media, rather than simply to communicate factual information. The purpose of the interpretative message is to inspire and lead visitors to widen your horizons. These are tips, hints or key elements of judgment, among others, which produced through the use of effective and precise communication techniques, designed to enable significant and impactful messages. For the tourist product interpretation is an essential component, especially when it relies on culture and in critical landscapes, It allows visitors to learn about and enjoy more seats, and may cause them to prolong their stay and encourage new visitors. In this way, our work aimed to evaluate the understanding regarding the concept, principles and practices of interpretation of nature for actors involved in the chain of ecotourism in the State of Mato Grosso, Brazil. For this purpose, a questionnaire formatted structured online (Google Docs), containing nine questions with four answer alternatives, where he formulated himself coherent and negative statements notes based on the principles of interpretation of nature. The sampling of this work involved 30 guides with the record as “Cadastur” working professionals in the ecotourism segment in the State of Mato Grosso. The results showed that the interpretation of nature is not applied in its entirety by the agents of ecotourism, because there is no knowledge and/or understanding of the concept under study, as well as its theoretical foundation and training experiences to development in practical activities. And when applied there is no clarity on the fundamental importance of an interpretive program. The study pointed out the necessity of expanding the methodological application to other environments with practice of ecotourism. KEYWORDS: Protect Areas; Planning; Awareness Activities; Guides

Many of our everyday tasks require the control of the serial order and the timing of component actions. Using the dynamic neural field (DNF) framework, we address the learning of representations that support the performance of precisely time action sequences. In continuation of previous modeling work and robotics implementations, we ask specifically the question how feedback about executed actions might be used by the learning system to fine tune a joint memory representation of the ordinal and the temporal structure which has been initially acquired by observation. The perceptual memory is represented by a self-stabilized, multi-bump activity pattern of neurons encoding instances of a sensory event (e.g., color, position or pitch) which guides sequence learning. The strength of the population representation of each event is a function of elapsed time since sequence onset. We propose and test in simulations a simple learning rule that detects a mismatch between the expected and realized timing of events and adapts the activation strengths in order to compensate for the movement time needed to achieve the desired effect. The simulation results show that the effector-specific memory representation can be robustly recalled. We discuss the impact of the fast, activation-based learning that the DNF framework provides for robotics applications.

We tested in a robotics experiment a dynamic neural field model for learning a precisely timed musical sequence. Based on neuro-plausible processing mechanisms, the model implements the idea that order and relative timing of events are stored in an integrated representation whereas the onset of sequence production is controlled by a separate process. Dynamic neural fields provide a rigorous theoretical framework to analyze and implement the necessary neural computations that bridge gaps between sensation and action in order to mediate working memory, action planing, and decision making. The robot first memorizes a short musical sequence performed by a human teacher by watching color coded keys on a screen, and then tries to execute the piece of music on a keyboard from memory without any external cues. The experimental results show that the robot is able to correct in very few demonstration-execution cycles initial sequencing and timing errors., The work received financial support from FCT - Fundação para a Ciência e Tecnologia within the Project Scope: PEst- OE/EEI/UI0319/2014, the Research Centers for Mathematics and Algoritmi through the FCT Pluriannual Funding Program, PhD and Post-doctoral Grants (SFRH/BD/41179/2007, SFRH/BD/48529/2008 and SFRH/BPD/71874/2010, financed by POPH-QREN-Type 4.1-Advanced Training, co-funded by the European Social Fund and national funds from MEC), and Project NETT: Neural Engineering Transformative Technologies, EU-FP7 ITN (nr.289146).

The aim of this study is to evaluate different features, extracted from a Poincaré plot of gait signals, in their ability to classify the gait of patients with neurodegenerative diseases: Parkinson’s disease (PD) and Huntington’s disease (HD). Five different features that describe gait variability were extracted from the Poincaré plots of two gait signals: stride time and percentage of stride time spent in swing phase. Among the set of extracted features, those that displayed significant differences between the two groups and were not correlated with each other, were used as input to the support vector machine classifier. It was found that all extracted features (with exception of one feature in PD vs healthy group comparison) are significantly different between healthy and pathological subjects and are suitable to discriminate them (with accuracies greater than 80%). When comparing PD vs HD, just three features were significantly different, however, a relatively good classification accuracy (around 72%) was achieved using two of them. The results demonstrate that it is feasible to apply variability measures extracted from Poincaré plots of gait data signals in gait classification problems.

Em Portugal, por razões meramente estatísticas, a Autoridade Florestal Nacional – AFN (atual Instituto de Conservação da Natureza e da Florestal - ICNF) definiu como ‘grandes incêndios florestais’ (GIF), aqueles cuja área ardida fosse superior a 100ha. Nos últimos 10 anos, de 2003 a 2012, foram contabilizados, no território continental português, 31 GIF com dimensão superior a 5000ha (12 deles com área superior a 10000ha), tendo estes ocorrido sempre nos meses de julho a setembro. Muito embora a relação existente entre determinadas situações sinópticas e a ocorrência de GIF ser já conhecida em Portugal, tendo vários autores tentado identificar as mais favoráveis (REBELO, 1980; LOURENÇO, 1988; CUNHA e BENTO-GONÇALVES, 1994), na nova realidade dendrocaustológica, que poderá mesmo configurar a existência de um novo regime de fogo em Portugal, é fundamental identificar padrões sinópticos associados aos GIF (superiores a 5000ha), o que poderá constituir uma importante ferramenta meteorológica na gestão dos incêndios florestais.

A desestruturação do mundo rural, em particular em áreas de montanha, levou a um forte incremento do número de deflagrações de incêndios florestais, bem como da respectiva área ardida, constituindo a serra da Cabreira um excelente exemplo dessa realidade., La déstructuration des zones rurales, en particulier dans les montagnes, a conduit à une forte augmentation du nombre d’incendies de forêt ainsi que des aires brûlées, et la montagne de Cabreira est un excellent exemple de cette réalité., The destructuring of rural areas, particularly in mountain areas, led to a sharp increase in the number of forest fires as well of the areas burned, and Cabreira mountain is an excellent example of this reality.