Abstract
<p>Gamma radiation measured over the ocean is mainly due to airborne radionuclides, as gamma emission by radon degassing from the ocean is negligible. Airborne gamma-emitting elements include radon progeny (Pb-2114, Bi-214, Pb-210) and cosmogenic radionuclides such as Be-7. Radon progeny attaches readily to aerosols, thus the fate of gamma-emitting radon progeny, after its formation by radioactive decay from radon, is expected to be closely linked to that of aerosols.</p> <p>Gamma radiation measurements over the Atlantic Ocean were made on board the ship-rigged sailing ship NRP Sagres in the framework of project SAIL (Space-Atmosphere-Ocean Interactions in the marine boundary Layer). The measurements were performed continuously with a NaI(Tl) scintillator counting all gamma rays from 475 keV to 3 MeV.  </p> <p>The counts from the sensor were recorded every 1 second into a computer system which had his time reference corrected by a GNSS pulse per second (PPS) signal. The GNSS was also used to precisely position the ship. The measurements were performed over the Atlantic ocean from January to May 2020, along the ship’s round trip from Lisboa - Cape Verde – Rio de Janeiro – Buenos Aires – Cape Town – Cape Verde - Lisboa.</p> <p>The results show that the gamma radiation time series displays considerable higher counts and larger variability in January compared to the remaining period. Reanalysis data also indicate higher aerosol concentration. This work investigates in detail the association between the temporal evolution of the gamma radiation measurements obtained from the SAIL campaign over the Atlantic Ocean and co-located total aerosol concentration at 550 nm obtained every 3 hours from EAC4(ECMWF Atmospheric Composition Reanalysis 4) data.</p>

Abstract
Textual health records of cancer patients are usually protracted and highly unstructured, making it very time-consuming for health professionals to get a complete overview of the patient's therapeutic course. As such limitations can lead to suboptimal and/or inefficient treatment procedures, healthcare providers would greatly benefit from a system that effectively summarizes the information of those records. With the advent of deep neural models, this objective has been partially attained for English clinical texts, however, the research community still lacks an effective solution for languages with limited resources. In this paper, we present the approach we developed to extract procedures, drugs, and diseases from oncology health records written in European Portuguese. This project was conducted in collaboration with the Portuguese Institute for Oncology which, besides holding over 10 years of duly protected medical records, also provided oncologist expertise throughout the development of the project. Since there is no annotated corpus for biomedical entity extraction in Portuguese, we also present the strategy we followed in annotating the corpus for the development of the models. The final models, which combined a neural architecture with entity linking, achieved..1 scores of 88.6, 95.0, and 55.8 per cent in the mention extraction of procedures, drugs, and diseases, respectively.

Abstract
In this paper, we consider three Relaxation Adaptive Memory Programming (RAMP) approaches for solving the Uncapacitated Facility Location Problem (UFLP), whose objective is to locate a set of facilities and allocate these facilities to all clients at minimum cost. Different levels of sophistication were implemented to measure the performance of the RAMP approach. In the simpler level, (Dual-) RAMP explores more intensively the dual side of the problem, incorporating a Lagrangean Relaxation and Subgradient Optimization with a simple Improvement Method on the primal side. In the most sophisticated level, RAMP combines a Dual-Ascent procedure on the dual side with a Scatter Search (SS) procedure on primal side, forming the Primal-Dual RAMP (PD-RAMP). The Dual-RAMP algorithm starts with (dual side) the dualization of the initial problem, and then a projection method projects the dual solutions into the primal solutions space. Next, (primal side) the projected solutions are improved through an improvement method. In the PD-RAMP algorithm, the SS procedure is incorporated in the primal side to carry out a more intensive exploration. The algorithm alternates between the dual and the primal side until a fixed number of iterations is achieved. Computational experiments on a standard testbed for the UFLP were conducted to assess the performance of all the RAMP algorithms.

Abstract

Abstract
Given the new requirements of Machine Learning problems in the last years, especially in what concerns the volume, diversity and speed of data, new approaches are needed to deal with the associated challenges. In this paper we describe CEDEs - a distributed learning system that runs on top of an Hadoop cluster and takes advantage of blocks, replication and balancing. CEDEs trains models in a distributed manner following the principle of data locality, and is able to change parts of the model through an optimization module, thus allowing a model to evolve over time as the data changes. This paper describes its generic architecture, details the implementation of the first modules, and provides a first validation.

Abstract
Objectives:Angiotensin-converting enzymes' (ACEs) relationship with blood pressure (BP) during childhood has not been clearly established. We aimed to compare ACE and ACE2 activities between BMI groups in a sample of prepubertal children, and to characterize the association between these enzymes' activities and BP.Methods:Cross-sectional study of 313 children aged 8-9 years old, included in the birth cohort Generation XXI (Portugal). Anthropometric measurements and 24-h ambulatory BP monitoring were performed. ACE and ACE2 activities were quantified by fluorometric methods.Results:Overweight/obese children demonstrated significantly higher ACE and ACE2 activities, when compared to their normal weight counterparts [median (P25-P75), ACE: 39.48 (30.52-48.97) vs. 42.90 (35.62-47.18) vs. 43.38 (33.49-49.89) mU/ml, P for trend = 0.009; ACE2: 10.41 (7.58-15.47) vs. 21.56 (13.34-29.09) vs. 29.00 (22.91-34.32) pM/min per ml, P for trend < 0.001, in normal weight, overweight and obese children, respectively]. In girls, night-time systolic BP (SBP) and diastolic BP (DBP) increased across tertiles of ACE activity (P < 0.001 and P = 0.002, respectively). ACE2 activity was associated with higher night-time SBP and DBP in overweight/obese girls (P = 0.037 and P = 0.048, respectively) and night-time DBP in the BMI z-score girl adjusted model (P = 0.018). Median ACE2 levels were significantly higher among nondipper girls (16.7 vs. 11.6 pM/min per ml, P = 0.009).Conclusions:Our work shows that obesity is associated with activation of the renin-angiotensin-aldosterone system, with significant increase of ACE and ACE2 activities already in childhood. Also, we report sex differences in the association of ACE and ACE2 activities with BP.