Abstract
This paper presents a mathematical problem formulation for energy management systems for smart homes. The flexibility can be provided by a home energy management system (HEMS) in a local energy community. The main concept is to model the flexibility provision and flexibility procurement within the energy community that can be provided to the aggregator from active consumers. The integrated energy management model is coded as a standard mixed-integer linear programming (MILP) model which can be solved by open-source tools like the PuLP package developed in Python. The simulation results confirm the performance of the proposed model in terms of flexibility provided by the centralized integrated energy system introduced in this paper.

Abstract
Almost two years have passed since COVID-19 was officially declared a pandemic by the World Health Organization. However, it still holds a tight grasp on the entire human population. Several variants of concern, one after another, have spread throughout the world. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) omicron variant may become the fastest spreading virus in history. Therefore, it is more than evident that the use of personal protective equipment (PPE) will continue to play a pivotal role during the current pandemic. This work depicts an integrative approach attesting to the effectiveness of ultra-violet-C (UV-C) energy density for the sterilization of personal protective equipment, in particular FFP2 respirators used by the health care staff in intensive care units. It is increasingly clear that this approach should not be limited to health care units. Due to the record-breaking spreading rates of SARS-CoV-2, it is apparent that the use of PPE, in particular masks and respirators, will remain a critical tool to mitigate future pandemics. Therefore, similar UV-C disinfecting rooms should be considered for use within institutions and companies and even incorporated within household devices to avoid PPE shortages and, most importantly, to reduce environmental burdens.

Abstract
The COVID-19 pandemic places unique challenges to medical rescuers’ occupational health. Thus, it is crucial to assess its direct and indirect impacts on key psychological outcomes and adaptation strategies. This study aims to analyse the impact of this pandemic on medical rescuers’ coping and emotion regulation strategies, and their levels of work-related psychological outcomes, such as burnout, trauma and post-traumatic growth. Additionally, it aims to analyse the contribution of coping and emotion regulation strategies, employed to manage the COVID-19 pandemic, on burnout, trauma and post-traumatic growth. A sample of 111 medical rescuers answered the Brief Cope, Emotion Regulation Questionnaire, Oldenburg Burnout Inventory, Impact of Event Scale-Revised and Post-Traumatic Growth Inventory. Medical rescuers resorted moderately to coping and emotion regulation strategies, since the beginning of COVID-19. They presented moderate burnout and post-traumatic growth and low trauma. Coping presented a higher weight on burnout, trauma and post-traumatic growth, than emotion regulation. Expressive suppression and dysfunctional coping predicted burnout and trauma, and problem and emotion-focused coping predicted post-traumatic growth. Dysfunctional coping mediated and, thus, exacerbated the effect of expressive suppression on burnout and on trauma. Practitioners should pay closer attention to professionals with higher burnout and trauma. Occupational practices should focus on reducing dysfunctional coping and expressive suppression and promoting problem-focused coping. © 2022, Instituto Superior de Psicologia Aplicada. All rights reserved.

Abstract
Lessons from a pandemic.

Abstract
Literature posits that most data and research on E-Government dominantly focuses on large economies where social, political, organizational and economic aspects of these local contexts significantly differ from other parts of the world. One such part is the group of island states specifically referred to as Small Islands Developing States (SIDS), sharing common challenges of reduced size, diseconomies of scale, impact of climate changes and other challenges. E-Government models should be adapted to local context, and for SIDS this entails understanding the local context so as to formulate a sustainable model. Even though we find studies and models for SIDS, significant differences exists among SIDS that warrant individual approaches. An example of a SIDS is Sao Tome and Principe, where the government is involved in E-Government initiatives. This is visible at the Ministry of Finance where different interacting Departments have developed systems and software tools to manage business processes. These systems and tools are used for interactions internally and with public and private sectors. However, for implementation, there is a lack of a centralized, interoperable vision or directive. Consequences are high total cost of ownership, subsequent costs with interoperability and maintenance, and, in the end, deficient long-term sustainability. Considering the impact of costs of information technology initiatives to the public budget, financed in its majority by development and bilateral assistance, there is a need for an E-Government model that prescribes directives for a sound, interoperable and sustainable E-Government implementation. We propose the development of E-GovSTP, a framework/model that intends to combine technical considerations and aspects of the local context to formulate guidelines for E-Government implementations in the Ministry of Finance. This artifact shall be developed through sound theoretical foundation, application of established standards and guidelines to areas of privacy and security, interoperability and system and communications. Additionally, the fundamental aspects of the local context (political, social and organizational) shall be factored into the model in order to guarantee the sustainability having in mind existing technical, material and financial constrains the country faces.

Abstract
The Internet of Things (IoT) envisions a smart environment powered by connectivity and heterogeneity where ensuring reliable services and communications across multiple industries, from financial fields to healthcare and fault detection systems, is a top priority. In such fields, data is being collected and broadcast at high speed on a continuous and real-time scale, including IoT in the streaming processing paradigm. Intrusion Detection Systems (IDS) rely on manually defined security policies and signatures that fail to design a real-time solution or prevent zero-day attacks. Therefore, anomaly detection appears as a prominent solution capable of recognizing patterns, learning from experience, and detecting abnormal behavior. However, most approaches do not fit the urged requirements, often evaluated on deprecated datasets not representative of the working environment. As a result, our contributions address an overview of cybersecurity threats in IoT, important recommendations for a real-time IDS, and a real-time dataset setting to evaluate a security system covering multiple cyber threats. The dataset used to evaluate current host-based IDS approaches is publicly available and can be used as a benchmark by the community.