Abstract
This paper presents a new stochastic mixed-integer second-order cone programming model to solve the problem of optimal operation of distribution systems considering network reconfiguration, voltage control devices, dispatchable and nondispatchable distributed generators (DGs), and the possibility of closed-loop topology operation. The decision variables are the active and reactive power generation of DGs, the tap position of substations' (SS) on-load tap changers and voltage regulators, the number of switchable capacitor banks in operation, and the operational statuses of sectionalizing and tie switches. The proposed formulation considers the minimization of (i) the cost of the energy purchased from the distribution SSs and dispatchable DGs, (ii) greenhouse gas emissions, (iii) technical energy losses, and (iv) the number of basic loops formed in the network. Tests are carried out using the 33-node system and the results demonstrate the effectiveness of the proposed formulation. The benefits provided by the presented approach include reduced operational costs and greenhouse gas emissions mitigation.

Abstract
With the rising popularity of the cloud, companies lose control of both the hardware and the operating system responsible for hosting their software and data. This means that companies are at risk of losing confidential data when these are utilized in components controlled by a third-party cloud vendor. Secure enclaves can help solve this problem by creating a secure environment where code can be executed securely, guaranteeing that no unwanted parties read or modify the data inside this secure environment. While the use of secure enclaves has been focused on small footprints software, such as the implementation of trusted computing base for distributed protocols, we analyze the strengths and shortcoming of current tools in an effort to further expand the applicability of their use. Given the importance of web servers and their inherent greater exposure to attacks, we explore the hardening of Apache web server through the use of secure enclaves. This was accomplished by making the necessary modifications to further protect its private key from both the operating system and hypervisor. We also provide a performance assessment to quantify the overhead associated with the use of secure enclaves, namely, Intel SGX.

Abstract
Transactional isolation is a challenge for polystores, as along with the limited capabilities of each datastore, we have to contend with their sheer diversity. However, transactional isolation is increasingly desirable as a variety of datastores are being sought after for roles that go beyond data lakes. Transactional guarantees are also relevant for reliability at scale. In this paper, we propose that transactional isolation in polystores can be achieved by leveraging the query engine, i.e., basing some of the responsibilities of a traditional transactional storage manager (TSM) on the query language itself. This has the key advantage of greatly simplifying design and implementation, as it doesn’t need to be re-invented for each datastore, and should increase performance, by taking advantage of dynamic query optimization where available. We demonstrate the feasibility of the proposal with a simple proof-of-concept and experiment.

Abstract
This study aims at assessing the accuracy of estimating daily reference evapotranspiration (ETo) computed with NASA POWER reanalysis products. Daily ETo estimated from local observations of weather variables in 14 weather stations distributed across Alentejo Region, Southern Portugal were compared with ETo derived from NASA POWER weather data, using raw and bias-corrected datasets. Three different methods were used to compute ETo: (a) FAO Penman-Monteith (PM); (b) Hargreaves-Samani (HS); and (c) MaxTET. Results show that, when using raw NASA POWER datasets, a good accuracy between the observed ETo and reanalysis ETo was observed in most locations (R-2 > 0.70). PM shows a tendency to over-estimating ETo with an RMSE as high as 1.41 mm d(-1), while using a temperature-based ET estimation method, an RMSE lower than 0.92 mm d(-1) is obtained. If a local bias correction is adopted, the temperature-based methods show a small over or underestimation of ETo (-0.40 mm d(-1) & LE; MBE < 0.40 mm d(-1)). As for PM, ETo is still underestimated for 13 locations (MBE < 0 mm d(-1)) but with an RMSE never higher than 0.77 mm d(-1). When NASA POWER raw data is used to estimate ETo, HS_Rs proved the most accurate method, providing the lowest RMSE for half the locations. However, if a data regional bias correction is used, PM leads to the most accurate ETo estimation for half the locations; also, when a local bias correction is performed, PM proved the be the most accurate ETo estimation method for most locations. Nonetheless, MaxTET proved to be an accurate method; its simplicity may prove to be successful not only when only maximum temperature data is available but also due to the low data required for ETo estimation.

Abstract
Open innovation is a hot topic which currently facilitates the establishment of links between Universities and Industry. Thus, the primary goal of this research is to synthetize the existing literature by establishing a University-Industry relationship with Open Innovation. In this scenario, we also identify the extent to which open innovation is improving innovation ecosystems in terms of promoting smart and responsible innovation. To do so, we have used a systematic literature review, which is considered an adequate method to study the state of the art of a given topic. In light of the above, we performed 1) a quantitative assessment of 50 articles by using bibliometric tools and 2) a qualitative analysis of the literature to identify meaningful relationships between articles. As a result, the literature evidenced a trinomial relationship between Universities, Society and Industries, which are interestingly far more exploited than the Education and Research. Given the noticeable importance of producing knowledge and dissemination of that information, we believe Universities will continue to have a prominent centrality in society in that regard; however, current data leads us to believe that the Universities success of producing knowledge highly depends on the efficiency of each countries to establish effective political actions. (C) 2021 The Authors. Published by Elsevier B.V.

Abstract
Cork stoppers were shown to have unique characteristics that allow their use for authentication purposes in an anti-counterfeiting effort. This authentication process relies on the comparison between a user's cork image and all registered cork images in the database of genuine items. With the growth of the database, this one-to-many comparison method becomes lengthier and therefore usefulness decreases. To tackle this problem, the present work designs and compares hashing-assisted image matching methods that can be used in cork stopper authentication. The analyzed approaches are the discrete cosine transform, wavelet transform, Radon transform, and other methods such as difference hash and average hash. The most successful approach uses a 1024-bit hash length and difference hash method providing a 98% accuracy rate. By transforming the image matching into a hash matching problem, the approach presented becomes almost 40 times faster when compared to the literature.