Abstract
The electricity field is facing major challenges in the implementation of Renewable Energy Sources (RES) at a large scale. End users are taking on the role of electricity producers and consumers simultaneously (prosumers), acting like Distributed Energy Resources (DER), injecting their excess electricity into the grid. This challenges the management of grid load balance, increases running costs, and is later reflected in the tariffs paid by consumers, thus threatening the widespread of RES. The Flexigy project explores a solution to this topic by proposing a smart-grid architecture for day-ahead flexibility scheduling of individual and Renewable Energy Community (REC) resources. Our solution is prepared to allow Transmission System Operators (TSO) to request Demand Response (DR) services in emergency situations. This paper overviews the grid balance problematic, introduces the main concepts of energy flexibility and DR, and focuses its content on explaining the Flexigy architecture.

Abstract
The experimental investigation of building-integrated photovoltaic thermal (BIPVT) solar systems is essential to characterise the operation of these elements under real conditions of use according to the climate and building type they pertain. BIPVT systems can increase and ensure energy performance and readiness without jeopardising the occupant comfort if correctly operated. The present work presents a case study's experimental analysis composed of a BIPVT system for heat recovery located in a controlled test room. This work contribution focuses on the presentation of the obtained measured value results that correspond to the BIPVT main boundary conditions (weather and room characteristics) and the thermal behaviour and performance of the BIPVT system, located in the Solar XXI Building, a nZEB exposed to the mild Mediterranean climate conditions of Portugal.

Abstract
Up to one third of the global food production depends on the pollination of honey bees, making them vital. This study defines a methodology to create a bee hive health monitoring system through image processing techniques. The approach consists of two models, where one performs the detection of bees in an image and the other classifies the detected bee's health. The main contribution of the defined methodology is the increased efficacy of the models, whilst maintaining the same efficiency found in the state of the art. Two databases were used to create models based on Convolutional Neural Network (CNN). The best results consist of 95% accuracy for health classification of a bee and 82% accuracy in detecting the presence of bees in an image, higher than those found in the state-of-the-art.

Abstract

Abstract
The continuous characterization of genome-wide diversity in population and case-cohort samples, allied to the development of new algorithms, are shedding light on host ancestry impact and selection events on various infectious diseases. Especially interesting are the long-standing associations between humans and certain bacteria, such as the case of Helicobacter pylori, which could have been strong drivers of adaptation leading to coevolution. Some evidence on admixed gastric cancer cohorts have been suggested as supporting Homo-Helicobacter coevolution, but reliable experimental data that control both the bacterium and the host ancestries are lacking. Here, we conducted the first in vitro coinfection assays with dual human- and bacterium-matched and -mismatched ancestries, in African and European backgrounds, to evaluate the genome wide gene expression host response to H. pylori. Our results showed that: (1) the host response to H. pylori infection was greatly shaped by the human ancestry, with variability on innate immune system and metabolism; (2) African human ancestry showed signs of coevolution with H. pylori while European ancestry appeared to be maladapted; and (3) mismatched ancestry did not seem to be an important differentiator of gene expression at the initial stages of infection as assayed here.

Abstract
Liquid biopsy is an emerging technology with a potential role in the screening and early detection of lung cancer. Several liquid biopsy-derived biomarkers have been identified and are currently under ongoing investigation. In this article, we review the available data on the use of circulating biomarkers for the early detection of lung cancer, focusing on the circulating tumor cells, circulating cell-free DNA, circulating micro-RNAs, tumor-derived exosomes, and tumor-educated platelets, providing an overview of future potential applicability in the clinical practice. While several biomarkers have shown exciting results, diagnostic performance and clinical applicability is still limited. The combination of different biomarkers, as well as their combination with other diagnostic tools show great promise, although further research is still required to define and validate the role of liquid biopsies in clinical practice.