Abstract
Objectives High-quality data are crucial for guiding decision-making and practising evidence-based healthcare, especially if previous knowledge is lacking. Nevertheless, data quality frailties have been exposed worldwide during the current COVID-19 pandemic. Focusing on a major Portuguese epidemiological surveillance dataset, our study aims to assess COVID-19 data quality issues and suggest possible solutions. Settings On 27 April 2020, the Portuguese Directorate-General of Health (DGS) made available a dataset (DGSApril) for researchers, upon request. On 4 August, an updated dataset (DGSAugust) was also obtained. Participants All COVID-19-confirmed cases notified through the medical component of National System for Epidemiological Surveillance until end of June. Primary and secondary outcome measures Data completeness and consistency. Results DGSAugust has not followed the data format and variables as DGSApril and a significant number of missing data and inconsistencies were found (eg, 4075 cases from the DGSApril were apparently not included in DGSAugust). Several variables also showed a low degree of completeness and/or changed their values from one dataset to another (eg, the variable 'underlying conditions' had more than half of cases showing different information between datasets). There were also significant inconsistencies between the number of cases and deaths due to COVID-19 shown in DGSAugust and by the DGS reports publicly provided daily. Conclusions Important quality issues of the Portuguese COVID-19 surveillance datasets were described. These issues can limit surveillance data usability to inform good decisions and perform useful research. Major improvements in surveillance datasets are therefore urgently needed-for example, simplification of data entry processes, constant monitoring of data, and increased training and awareness of healthcare providers-as low data quality may lead to a deficient pandemic control.

Abstract
This paper presents a nine-leg (9L) multilevel inverter to drive a six-phase induction machine in an open-end winding (OEW) configuration. The system is based on three conventional two-level three-phase voltage source inverters (VSIs) and three, two, or one isolated dc links. A machine with two sets of 30 degrees shifted three-phase stator windings is considered. The inverter operating principles are discussed and a simple space-vector pulse-width modulation (SV-PWM) is proposed. The 9L-OEW system is compared with two conventional drives: the six-leg two-level (6L), and the 12-leg OEW (12L-OEW) systems. The number of components, the required dc-link voltage, voltage and current harmonic distortions, torque ripple, and semiconductor losses are considered as figures of merit. Simulations and experiments were also performed, showing steady-state results for a 1 HP machine operating at constant torque.

Abstract
Background: Ovar was the first Portuguese municipality to declare active community transmission of SARS-CoV-2, with total lockdown decreed on March 17, 2020. This context provided conditions for a large-scale testing strategy, allowing a referral system considering other symptoms besides the ones that were part of the case definition (fever, cough, and dyspnea). This study aims to identify other symptoms associated with COVID-19 since it may clarify the pre-test probability of the occurrence of the disease. Methods: This case-control study uses primary care registers between March 29 and May 10, 2020 in Ovar municipality. Pre-test clinical and exposure-risk characteristics, reported by physicians, were collected through a form, and linked with their laboratory result. Results: The study population included a total of 919 patients, of whom 226 (24.6%) were COVID-19 cases and 693 were negative for SARS-CoV-2. Only 27.1% of the patients reporting contact with a confirmed or suspected case tested positive. In the multivariate analysis, statistical significance was obtained for headaches (OR 0.558), odynophagia (OR 0.273), anosmia (OR 2.360), and other symptoms (OR 2.157). The interaction of anosmia and odynophagia appeared as possibly relevant with a borderline statistically significant OR of 3.375. Conclusion: COVID-19 has a wide range of symptoms. Of the myriad described, the present study highlights anosmia itself and calls for additional studies on the interaction between anosmia and odynophagia. Headaches and odynophagia by themselves are not associated with an increased risk for the disease. These findings may help clinicians in deciding when to test, especially when other diseases with similar symptoms are more prevalent, namely in winter.

Abstract
With the increasing use of smartphones in people's daily lives, mobile accessibility has become a key factor for them. Tourism is one of the sectors that has benefited the most from this growth but has not yet reached its full potential as accessibility has not yet been fully exploited. The main goal of this study is to assess accessibility in mobile applications for the tourism sector. Thus, 14 mobile applications were analyzed, using a manual and automatic methodology through the proposal of an evaluation model divided by quantitative and qualitative requirements, as well as the use of features such as VoiceOver and TalkBack. The results show a high overall number of errors in most quantitative requirements as well as non-compliance with most qualitative requirements. On iPhone 4, "Viseu - Guia da Cidade" was the application with the highest rating, while on Wiko GOA, it was the "JiTT.Travel Funchal" application. In turn, on iPhone 6 Plus, iPhone XR, Nokia 5.1 and OnePlus 6 devices, the best results were achieved by the "Viseu - Guia da Cidade," "JiTT.Travel Funchal" and "TUR4all" applications. Regarding the accessibility of mobile applications on different versions of the same mobile operating system, it was concluded that there are no differences in their accessibility on both operating systems (iOS and Android). Finally, regarding the accessibility of applications on smartphones with different screen sizes, there are also no differences in their accessibility.

Abstract
Cooperation between different data owners may lead to an improvement in forecast quality-for instance, by benefiting from spatiotemporal dependencies in geographically distributed time series. Due to business competitive factors and personal data protection concerns, however, said data owners might be unwilling to share their data. Interest in collaborative privacy-preserving forecasting is thus increasing. This paper analyzes the state-of-the-art and unveils several shortcomings of existing methods in guaranteeing data privacy when employing vector autoregressive models. The methods are divided into three groups: data transformation, secure multi-party computations, and decomposition methods. The analysis shows that state-of-the-art techniques have limitations in preserving data privacy, such as (i) the necessary trade-off between privacy and forecasting accuracy, empirically evaluated through simulations and real-world experiments based on solar data; and (ii) iterative model fitting processes, which reveal data after a number of iterations.

Abstract
Hexapods are very common in astronomy as a mechanism to provide a stiff mount or a precision alignment tool. Here, we present a lumped model for a general symmetric hexapod that allows us to compute the load distribution under external forces, the hexapod's resolution, and the identification of singularity loci within the workspace. We also developed a script to analyze this parametric model, which is publicly available. We use this model to develop and design a hexapod for mid-infrared ELT imager and spectrograph, one of the extremely large telescope's first light instruments. The designed hexapod solution can survive strict earthquake conditions that can go up to 5g, and position and align the 11 ton instrument with submillimetric and arcsecond precisions. Although the model presented is not as precise or as realistic as a finite element WO analysis, it provides, in a fraction of a second, a very good first approximation. Therefore, unlike Eh methods, the model is able to study many geometries in a short time. (C) 2021 Society of Photo-Optical Instrumentation Engineers (SPIE)