Abstract
Many service jobs are carried out in modern offices, with individual offices being increasingly replaced by open-plan settings. The high number of adult people working in office buildings, in most situations sharing the work-place with many others during a considerable part of their daily time, highlights the importance of providing adequate guidance to ensure the quality of office environments. This paper aims to summarize existing data on modern offices' indoor environmental quality (IEQ) conditions in terms of air pollution (volatile organic compounds (VOC), particulate matter and inorganic pollutants), thermal comfort, lighting and acoustics and the respective associations with health and productivity-related outcomes in workers. Evidence shows that al-though many offices present acceptable IEQ, some office settings can have levels of air pollutants, hygrothermal conditions/thermal comfort and illuminance that do not comply with the existing international standards and recommendations. In addition, findings suggest the existence of significant associations between the assessed IEQ indicators and the risk of detrimental effects on health and productivity of office workers. In particular, airborne particles, CO2, O 3 and thermal comfort were linked with the prevalence of sick building syndrome symptoms. Poor lighting and acoustical quality have also been associated with malaise and physiological stress among office workers. Similarly, better productivity levels have been registered for good indoor air quality conditions, in terms of VOC, airborne particles and CO2. Overall, the evidence revised in this work suggests that for promoting health and productivity recommendations for office building managers include actions to ensure that: i) all relevant IEQ indicators are periodically controlled to ensure that levels comply with recommended limit values; ii) declared in-door pollution sources are avoided; iii) adequate ventilation and acclimatization strategies are implemented; and iv) there is the possibility of conduct personalized adjustments to environmental conditions (following workers' preferences).

Abstract
The growing number of battery electric vehicles (BEV) and plug-in hybrid electric vehicles (PHEV) brings the need of more fast charging stations across cities and highway stops. This charging stations toned to be connected to the electrical grid via existent facilities, causing constraints such as power availability. This study brings an approach for the planning and operation of such energy hubs by coping with this challenge by deploying a Battery-based Energy Storage System (BESS). With the BESS integration, it is expected to minimize utilization and overall energy costs, preventing infrastructure upgrades, and enhancing the integration of renewable energy resources. This approach sizes a stationary energy storage system with lithium-ion technology batteries through a co-optimization of the planning and operation stages, integrated in an electrical installation that will implement fast charging stations. This sizing is a result of an optimization based on the interior point algorithm, where the objective is to minimize the costs of maintenance, operation, and installation of a BESS, while properly modelling the different resources such as the BESS, the charging station and EV charging and PV generation. © 2023, Universidade do Porto - Faculdade de Engenharia. All rights reserved.

Abstract
Despite its worldwide relevance as an invasive plant, there are few studies on Ulex europaeus (gorse) and its allelopathic activity is almost unexplored. The allelochemical profile of gorse was analysed through methanolic extract of pods and roots, and its phytotoxic effects on Lactuca sativa germination. The methanolic extract of pods had no effect in germination, while extract of roots resulted in a U-shaped dose-response curve: reducing the germination at concentration 0.5 mg mL-1. GC-MS analysis detected compounds with proven antimicrobial and antioxidant activities in the pods and cytotoxic compounds in the roots, which could explain the bioassay results. The quinolizidine alkaloids (QAs) composition was evaluated to predict possible biological functions. It showed the presence of QAs in gorse that are absent in their native range, indicating broad defense strategies against bacteria, fungi, plants, and insects in the Chilean ecosystem. This could explain the superiority of gorse in the invaded areas.

Abstract
Technologies related to the transportation electrification have been gaining attention in recent years. One technology that stands out is wireless charging, which still presents numerous challenges in terms of design and optimization of parameters. This article proposes a design methodology for optimizing the performance of an inductive power transfer (IPT) for wireless charging of electric vehicles, taking into account operating limits. The proposed methodology uses a PSO (Particle Swarm Optimization) algorithm to find the design variables that maximize the eficiency. The methodology and the development of a 3.6 kW experimental setup are presented, resulting in a power transfer efficiency of 89.4 %. © 2023 IEEE.

Abstract
In this paper we explain how to compute gradients of functions of the form G = 1/2 Sigma(m)(i=1) (Ey(i) - C-i )(2), which often appear in the calibration of stochastic models, using automatic adjoint differentiation and parallelization. We expand on the work of Goloubentsev and Lakshtanov and give approaches that are faster and easier to implement. We also provide an implementation of our methods and apply the technique to calibrate European options.

Abstract
The application of machine learning (ML) algorithms to electronic health records (EHR) data allows the achievement of data-driven insights on various clinical problems and the development of clinical decision support (CDS) systems to improve patient care. However, data governance and privacy barriers hinder the use of data from multiple sources, especially in the medical field due to the sensitivity of data. Federated learning (FL) is an attractive data privacy-preserving solution in this context by enabling the training of ML models with data from multiple sources without any data sharing, using distributed remotely hosted datasets. The Secur-e-Health project aims at developing a solution in terms of CDS tools encompassing FL predictive models and recommendation systems. This tool may be especially useful in Pediatrics due to the increasing demands on Pediatric services, and the current scarcity of ML applications in this field compared to adult care. Herein we provide a description of the technical solution proposed in this project for three specific pediatric clinical problems: childhood obesity management, pilonidal cyst post-surgical care and retinography imaging analysis.