Abstract
The demand for cost-effective broadband wireless underwater communications has increased in the past few years, motivated by the video collection performed by Autonomous Underwater Vehicles (AUVs) in areas such as environmental monitoring and oil and gas industries. However, the current technological limitations make it hard to implement a viable broadband wireless communications system for transferring the large amounts of data collected. Existing underwater communications solutions, using wireless optical or Radio Frequency (RF), limit high definition wireless video transfer to distances up to tens of meters. In case of underwater acoustic communications, long ranges can be achieved, but the low bandwidth makes them unsuitable for video streaming, even for standard definition video.In this paper we propose a solution, named Underwater Adaptive and Reliable Video Streaming (UARVS), that offers a video streaming service built upon the GROW data muling approach. UARVS exploits the use of data mules - small and agile AUVs - that travel between two physical nodes, bringing the data from an underwater survey unit to a central station at the surface. To validate the solution, an experimental testbed was built using airtight PVC cylinders, on a freshwater tank. The experimental results obtained show that UARVS enables an adaptive and continuous flow of video, avoids butter underruns, and reacts to data mule losses and delays.

Abstract
Background: Multimorbidity is the co-occurrence of two or more chronic diseases. Objective: This study, based on self-reported medical diagnosis, aims to investigate the dynamic distribution of multimorbidity across sociodemographic levels and its impacts on health-related issues over 15 years in Brazil using national data. Methods: Data were analyzed using descriptive statistics, hypothesis tests, and logistic regression. The study sample comprised 679,572 adults (18-59 years of age) and 115,699 elderly people (=60 years of age) from the two latest cross-sectional, multiple-cohort, national-based studies: The National Sample Household Survey (PNAD) of 1998, 2003, and 2008, and the Brazilian National Health Survey (PNS) of 2013. Results: Overall, the risk of multimorbidity in adults was 1.7 times higher in women (odds ratio [OR] 1.73, 95% CI 1.67-1.79) and 1.3 times higher among people without education (OR 1.34, 95% CI 1.28-1.41). Multiple chronic diseases considerably increased with age in Brazil, and people between 50 and 59 years old were about 12 times more likely to have multimorbidity than adults between 18 and 29 years of age (OR 11.89, 95% CI 11.27-12.55). Seniors with multimorbidity had more than twice the likelihood of receiving health assistance in community services or clinics (OR 2.16, 95% CI 2.02-2.31) and of being hospitalized (OR 2.37, 95% CI 2.21-2.56). The subjective well-being of adults with multimorbidity was often worse than people without multiple chronic diseases (OR=12.85, 95% CI: 12.07-13.68). These patterns were similar across all 4 cohorts analyzed and were relatively stable over 15 years. Conclusions: Our study shows little variation in the prevalence of the multimorbidity of chronic diseases in Brazil over time, but there are differences in the prevalence of multimorbidity across different social groups. It is hoped that the analysis of multimorbidity from the two latest Brazil national surveys will support policy making on epidemic prevention and management.

Abstract
In this paper we enhance the EasyCrypt proof assistant to reason about computational complexity of adversaries. The key technical tool is a Hoare logic for reasoning about computational complexity (execution time and oracle calls) of adversarial computations. Our Hoare logic is built on top of the module system used by EasyCrypt for modeling adversaries. We prove that our logic is sound w.r.t. the semantics of EasyCrypt programs - we also provide full semantics for the EasyCrypt module system, which was previously lacking. We showcase (for the first time in EasyCrypt and in other computer-aided cryptographic tools) how our approach can express precise relationships between the probability of adversarial success and their execution time. In particular, we can quantify existentially over adversaries in a complexity class, and express general composition statements in simulation-based frameworks. Moreover, such statements can be composed to derive standard concrete security bounds for cryptographic constructions whose security is proved in a modular way. As a main benefit of our approach, we revisit security proofs of some well-known cryptographic constructions and we present a new formalization of Universal Composability (UC).

Abstract
To stimulate research in the area of automotive electronics and electric vehicles, the IEEE Vehicular Technology Society (VTS) initiated the Motor Vehicles Challenge. The objective of the 2021 edition of this challenge is to provide a benchmark problem for the energy management of a dual-motor electric vehicle. To solve this, we propose a pragmatic optimization-based energy management system (EMS) that minimizes the instantaneous power consumption of the vehicle through manipulation of torque distribution ratios among the electric motors. Numerical results obtained with the VTS benchmark simulation model demonstrate that the proposed EMS can extend the vehicle range up to 3% when compared to baseline solutions.

Abstract
The main objective of the present research is to identify the knowledge flows responsible for promoting the innovation capacity of Portuguese companies. Specifically, we intend to identify which variables influence Portuguese innovation capacity from a macro and micro perspective, so that we can establish possible ways to promote open innovation (OI) in Portugal since Portuguese companies have little maturity in terms of open innovation when compared to companies in other countries of the European Union. To achieve this goal, the methodological design used consisted of two phases. In the first phase, a literature review was conducted to identify the main variables associated with innovation performance. After identifying the most influential variables in the literature, in a second phase, data were collected through three distinct databases, namely Pordata, the Portuguese Tax and Customs Authority, and SABI. To identify the most influential variables in the Portuguese innovation capacity, the multivariate multiple regression technique based on the ordinary least square (OLS) method was applied. The results of the present research bring empirical evidence that researchers dedicated to R&D from non-profit institutions (i.e., inbound OI) and researchers from firms (i.e., outbound OI) exert a significant influence on innovation capacity so the development of an optimal strategy for the strengthening of open innovation by Portuguese firms should take into account the use and combination of these two specific knowledge flows. In this sense, the originality of this research lies in the fact that it is the first attempt to understand the possible implications of the determinants of innovation capacity on open innovation, from an exploratory study concerning the flows of knowledge.

Abstract
Over the last decades clinical research has been driven by informatics changes nourished by distinct research endeavors. Inherent to this evolution, several issues have been the focus of a variety of studies: multi-location patient data access, interoperability between terminological and classification systems and clinical practice and records harmonization. Having these problems in mind, the Data Safe Haven paradigm emerged to promote a newborn architecture, better reasoning and safe and easy access to distinct Clinical Data Repositories. This study aim is to present a novel solution for clinical search harmonization within a safe environment, making use of a hybrid coding taxonomy that enables researchers to collect information from multiple repositories based on a clinical domain query definition. Results show that is possible to query multiple repositories using a single query definition based on clinical domains and the capabilities of the Unified Medical Language System, although it leads to deterioration of the framework response times. Participants of a Focus Group and a System Usability Scale questionnaire rated the framework with a median value of 72.5, indicating the hybrid coding taxonomy could be enriched with additional metadata to further improve the refinement of the results and enable the possibility of using this system as data quality tagging mechanism.