Abstract
The European Structural and Investment Funds (ESIF) are the main instrument of the European Union (EU) Cohesion Policy to promote convergence, economic growth and reduce imbalances between EU members. The objectives of the 2014-2020 programming period follow the agenda of the Europe 2020 Strategy to promote smart, sustainable and inclusive growth of EU members. Since before joining the EU, in 1986, until the end of the Portugal 2020 Partnership Agreement (PT2020), Portugal will have received more than EUR 130 billion. Have the subsidies that Portugal has received been well applied? Our study fills a gap in the literature by portraying citizens' perceptions about the effectiveness of EU funds for the development of the country and its regions. The study is quantitative in nature, and a non-probabilistic sample of 1119 participants answered our survey. A high proportion (76%) of the respondents considered that EU funds contributed to the development of the region where they live, although a significant percentage of the respondents (more than half) considered that there may be corruption in Portugal. The Portuguese also mentioned the existence of practices such as favouritism and lobbying regarding the approval of projects. Our findings are supported by the literature, which refers to "lost opportunities" in the inefficient application of ESIF, while recognising that EU funds have played a significant role in Portugal's development over the last three decades.

Abstract

Abstract
A non-parametric identification algorithm is proposed to identify Linear Time Periodic (LTP) systems. The period is unknown and can be any real positive number. The system is modelled as an ARX Linear Parameter Varying (LPV) system with a virtual scheduling signal consisting of two orthogonal sinusoids (a sine and a cosine) with a period equal to the system period. Hence, the system parameters are polynomial functions of the scheduling vector. As these polynomials may have infinite degree, a non-parametric model is adopted to describe the LPV system. This model is identified by a Gaussian Process Regression (GPR) algorithm where the system period is a hyperparameter. The performance of the proposed identification algorithm is illustrated through the identification of a simulated LTP continuous system described by a state-space model. The ARX-LTP discrete-time model estimated in the noiseless case was taken as the true model. Copyright (C) 2021 The Authors.

Abstract
As software becomes more complex and assumes an even greater role in our lives, formal verification is set to become the gold standard in securing software systems into the future, since it can guarantee the absence of errors and entire classes of attack. Recent advances in formal verification are being used to secure everything from unmanned drones to the internet. At the same time, the usable security research community has made huge progress in improving the usability of security products and end-users comprehension of security issues. However, there have been no human-centered studies focused on the impact of formal verification on the use and adoption of formally verified software products. We propose a research agenda to fill this gap and to contribute with the first collection of studies on people's mental models on formal verification and associated security and privacy guarantees and threats. The proposed research has the potential to increase the adoption of more secure products and it can be directly used by the security and formal methods communities to create more effective and secure software tools.

Abstract
This work addresses the use of hyperspectral imaging systems for remote detection of marine litter concentrations in oceanic environments. The work consisted on mounting an off-the-shelf hyperspectral imaging system (400-2500 nm) in two aerial platforms: manned and unmanned, and performing data acquisition to develop AI methods capable of detecting marine litter concentrations at the water surface. We performed the campaigns at Porto Pim Bay, Fail Island, Azores, resorting to artificial targets built using marine litter samples. During this work, we also developed a Convolutional Neural Network (CNN-3D), using spatial and spectral information to evaluate deep learning methods to detect marine litter in an automated manner. Results show over 84% overall accuracy (OA) in the detection and classification of the different types of marine litter samples present in the artificial targets.

Abstract
This study seeks to answer the following research question: "What factors can explain the number of patent filing requests made by residents in Brazil at patent offices in Brazil, the United States, Europe, and triadic patent families?". The methods used in this research are quantitative, using big data from private and public investments in Science and Technology, and about patent deposit numbers in Brazil from 2000 to 2017. A model of linear regression was performed and explains how these investments in Science and Technology influence patent deposit numbers. The results of this research study point towards the importance of universities, up and beyond the traditional training and education aspect of university activity. The importance of public and private innovation investments is also shown to be important. This study shows that the patent registrations in the different regions under analysis are affected by different factors. There is thus no single formula towards the creation of innovation output and governments would do well to continue to invest in higher education while also investing in public research and development activities. Additionally, and not least important, private entities should be continually encouraged to make innovation investments and favourable government policies need to thus exist for this to happen. Finally, the low numbers regarding patent filings in Brazil may be linked to institutional deficiencies in the country. Patent breaches may be difficult to punish, and the judicial system may be slow and untrustworthy, compared to the United States and to Europe-leading to diminished patent registrations in Brazil. A set of implications and recommendations for policy derived from this study and will be strategic for policymakers.