Abstract
In Portugal, labour availability has been revealed as a key factor for the activity, particularly in mountain viticulture. The latest statistics present worrying values that could undermine the production of quality wine and the attractive set of wine landscapes considered as a potential resource for tourism development. The Douro Region is one of the main Portuguese wine regions, characterized by a prominent and accentuated mountain viticulture. This paper aims to simulate the behaviour of its farms about the changes in the price of labour, through Agent-Based Models (ABM). The MATLAB software was used to obtain periodic functions adjusted to the data that characterize the relevant variables, obtained from face-to-face surveys of 110 farms, and taking into account the data provided by PTFADN. Subsequently, the ABM software (NETLOGO) was selected to simulate the next 100 years, familiarizing the real dynamics based on the previously considered data. Depending on the price of labour at the end of the simulation horizon, with a grape price of 0,77 €/kg, from the 300 initially existing farms survive between 127 and 231 (42,3 - 77%). In a more optimistic scenario, with a grape price of 1,17 €/kg, the survival rate ranges between 72.1 and 93.2%. © 2021

Abstract
Hereditary Transthyretin Amyloidosis (vATTR-V30M) is a rare and highly incapacitating sensorimotor neuropathy caused by an inherited mutation (Val30Met), which typically affects gait, among other symptoms. In this context, we investigated the possibility of using machine learning (ML) techniques to build a model(s) that can be used to support the detection of the Val30Met mutation (possibility of developing the disease), as well as symptom onset detection for the disease, given the gait characteristics of a person. These characteristics correspond to 24 gait parameters computed from 3-D body data, provided by a Kinect v2 camera, acquired from a person while walking towards the camera. To build the model(s), different ML algorithms were explored: k-nearest neighbors, decision tree, random forest, support vector machines (SVM), and multilayer perceptron. For a dataset corresponding to 66 subjects (25 healthy controls, 14 asymptomatic mutation carriers, and 27 patients) and several gait cycles per subject, we were able to obtain a model that distinguishes between controls and vATTR-V30M mutation carriers (with or without symptoms) with a mean accuracy of 92% (SVM). We also obtained a model that distinguishes between asymptomatic and symptomatic carriers with a mean accuracy of 98% (SVM). These results are very relevant, since this is the first study that proposes a ML approach to support vATTR-V30M patient assessment based on gait, being a promising foundation for the development of a computer-aided diagnosis tool to help clinicians in the identification and follow-up of this disease. Furthermore, the proposed method may also be used for other neuropathies.

Abstract
Vulnerability detection and repair is a demanding and expensive part of the software development process. As such, there has been an effort to develop new and better ways to automatically detect and repair vulnerabilities. DifFuzz is a state-of-the-art tool for automatic detection of timing side-channel vulnerabilities, a type of vulnerability that is particularly difficult to detect and correct. Despite recent progress made with tools such as DifFuzz, work on tools capable of automatically repairing timing side-channel vulnerabilities is scarce. In this paper, we propose DifFuzzAR, a new tool for automatic repair of timing side-channel vulnerabilities in Java code. The tool works in conjunction with DifFuzz and it is able to repair 56% of the vulnerabilities identified in DifFuzz's dataset. The results show that the tool can indeed automatically correct timing side-channel vulnerabilities, being more effective with those that are controlflow based.

Abstract
Reliable detection of gait events is important to ensure accurate assessment of gait. While it is usually performed resorting to force platforms, methods based uniquely on kinematic analysis have also been proposed. These methods place no restrictions on the number of steps that can be analysed, simplifying setup and complexity of assessments. They also replace the need of annotating events manually when force platforms are not available. Although few methods have been proposed in literature, validation studies are relatively scarce. In this study we present multiple methods for the detection of heel strike (HS) and toe off (TO) in normal walking, and validate the detection against annotated events using three different datasets. The best performing candidates are based on the evaluation of heel vertical velocity (for HS) and toe vertical acceleration (for TO), resulting in relative errors of -12.4 +/- 32.9 ms for HS and of -15.5 +/- 24.9 ms for TO. The method is compatible with barefoot and shod walking, constituting a convenient, fast and reliable alternative to automatic gait event detection using kinematic data.

Abstract
At a local scale, kaolin particle-film technology is considered a short-term adaptation strategy to mitigate the adverse effects of global warming on viticulture. This study aims to evaluate kaolin application effects on photochemistry and related defence responses of Touriga Franca (TF) and Touriga Nacional (TN) grapevines planted at two Portuguese winegrowing regions (Douro and Alentejo) over two summer seasons (2017 and 2018). For this purpose, chlorophyll a fluorescence transient analysis, leaf temperature, foliar metabolites, and the expression of genes related to heat stress (VvHSP70) and stress tolerance (VvWRKY18) were analysed. Kaolin application had an inhibitory effect on VvHSP70 expression, reinforcing its protective role against heat stress. However, VvWRKY18 gene expression and foliar metabolites accumulation revealed lower gene expression in TN-treated leaves and higher in TF at Alentejo, while lipid peroxidation levels decreased in both treated varieties and regions. The positive kaolin effect on the performance index parameter (PIABS) increased at ripening, mainly in TN, suggesting that stress responses can differ among varieties, depending on the initial acclimation to kaolin treatment. Moreover, changes on chlorophyll fluorescence transient analysis were more pronounced at the Douro site in 2017, indicating higher stress severity and impacts at this site, which boosted kaolin efficiency in alleviating summer stress. Under applied contexts, kaolin application can be considered a promising practice to minimise summer stress impacts in grapevines grown in Mediterranean-like climate regions.

Abstract
Textile electrodes are an alternative to conventional silver-chloride electrodes in wearable systems. Their easy integration in garments and comfort provided to the user make them an interesting development of textile engineering. The potential of such electrodes to allow more unobtrusive data collection in health and sports context may enable the development of biosensing garments to be used in biomechanics. However, proper validation of the recorded signals is paramount, and few studies have yet presented consistent methodologies for textile-based electromyographic recordings. This study presents the validation of the electrical and morphological properties of electromyographic signals recorded with textile electrode, in comparison to conventional silver-chloride electrodes. Results indicate that both sets of electrodes have identical signal-to-noise ratios, but with distinct impedance frequency responses. Electromyographic envelope morphologies are also identical, although textile electrodes usually have lower amplitudes.