Abstract

Abstract
Due to the competitiveness in the job shop nature of the metalworking industry, project management plays an important role in improving performance, efficiently and effectively managing its performance. Many of the generic problems observed in project management in metalworking industries were in the domain of document management, communication, multiple projects simultaneously, organizational structure, and poorly time estimation of project activities. The aim of this study was to improve the planning and time control in the project management of a metalworking industry in order to reduce the delivery delays. Using the existing data, an analysis of the project management process was carried out with the view to optimize the production system. In order to meet the established objectives, some of the project management tools were used, such as the Ishikawa diagram, PERT (three points estimating times), Monte Carlo simulation, as well as the involvement of people in the estimation and sequencing of activities, and holding weekly meetings to ensure the alignment of professionals. After the implementation of the actions proposed for the production process, there were gains of 50% and 38% in the average of deviations of times for two different projects of the case study and the Monte Carlo gave the best approximation.

Abstract
Visible Light Communication (VLC) has been emerging as a promising technology to address the increasingly high data-rate and time-critical demands that the Internet of Things (IoT) and 5G paradigms impose on the underlying Wireless Sensor Actuator Networking (WSAN) technologies. In this line, the IEEE 802.15.7 standard proposes several physical layers and Medium Access Control (MAC) sub-layer mechanisms that support a variety of VLC applications. Particularly, at the MAC sub-layer, it can support contention-free communications using Guaranteed Timeslots (GTS), introducing support for time-critical applications. However, to effectively guarantee accurate usage of such functionalities, it is vital to derive the worst-case bounds of the network. In this paper, we use network calculus to carry out the worst-case bounds analysis for GTS utilization of IEEE 802.15.7 and complement our model with an in-depth performance analysis. We also propose the inclusion of an additional mechanism to improve the overall scalability and effective bandwidth utilization of the network.

Abstract
Traditional explicit authentication mechanisms, in which the device remains unlocked after the introduction of some kind of password, are slowly being complemented with the so-called implicit or continuous authentication mechanisms. In the latter, the user is constantly monitored in one or more ways, in search for signs of unauthorized access, which may happen if a third party has access to the phone after it has been unlocked. There are some different forms of continuous authentication, some of which based on Machine Learning. These are generally black box models, that provide a decision but not an explanation. In this paper we propose an approach for continuous authentication based on behavioral biometrics, machine learning, and that includes domain-dependent aspects for the user to interpret the actions and decisions of the system. It is non-intrusive, does not require any additional hardware, and can be used continuously to monitor user identity.

Abstract
Indomethacin is a potent non-steroidal anti-inflammatory drug (NSAID) with a strong selective inhibitor activity towards cyclooxygenase-2 (COX-2), an enzyme that is highly overexpressed in various tumour cells, being involved in tumourigenesis. Concomitantly, porphyrins have gained much attention as promising photosensitizers (PSs) for the non-invasive photodynamic therapy (PDT) of cancer. Herein, we report the design, and determine the singlet oxygen generation capacity and in vitro cellular toxicity of porphyrin.- and chlorin-indomethacin conjugates (P2-Ind and C2-Ind). Both the conjugates were obtained in high yields and were characterized by H-1, F-19 and C-13 NMR as well as by high resolution mass spectrometry. The singlet oxygen generation properties were assessed by the 1,3-diphenylisobenzofuran singlet oxygen trap method, which showed that C2 and C2-Ind are the best singlet oxygen photosensitizers. in addition, it was found that the presence of indomethacin did not influence the singlet oxygen generation of porphyrin or chlorin. Cytotoxicity studies of the conjugate in human HEp2 cells revealed that the porphyrin ... and chlorin- indomethacin conjugates have similar dark cytotoxicities, while chlorin C2 was shown to be the most phototoxic. Despite having lower cellular uptake than C2-Ind after 24 hours, chlorin C2 had a broad localization in HEp2 cells while the chlorin-indomethacin conjugate C2-Ind could be detected in the form of small aggregates. DFT calculations were performed to shed light on the reaction energy involved in the formation of the indomethacin conjugates and to compare the relative stability of selected isomers in solution. Moreover, the calculated energy of their first excited triplet state structures confirmed their use as suitable photosensitizers to generate singlet oxygen for PDT.

Abstract
Geographically distributed wind turbines, photovoltaic panels and sensors (e.g., pyranometers) produce large volumes of data that can be used to improve renewable energy sources (RES) forecasting skill. However, data owners may be unwilling to share their data, even if privacy is ensured, due to a form of prisoner's dilemma: all could benefit from data sharing, but in practice no one is willing to do do. Our proposal hence consists of a data marketplace, to incentivize collaboration between different data owners through the monetization of data. We adapt here an existing auction mechanism to the case of RES forecasting data. It accommodates the temporal nature of the data, i.e., lagged time-series act as covariates and models are updated continuously using a sliding window. A test case with wind energy data is presented to illustrate and assess the effectiveness of such data markets. All agents (or data owners) are shown to benefit in terms of higher revenue resulting from the combination of electricity and data markets. The results support the idea that data markets can be a viable solution to promote data exchange between RES agents and contribute to reducing system imbalance costs.