Abstract
Higher Education Institutions (HEI) design and implement globalisation and internationalisation policies to promote the image, expand influence and increase both the number and quality of staff and students. This is especially important for engineering schools competing for the reduced cohort of motivated Science, Technology, Engineering and Mathematics (STEM) applicants available yearly. Moreover, to train future engineers, engineering education needs to depart from the traditional teacher-centred paradigm. Student-centred learning is central to maintain high student motivation and to drive the development of hard (scientific and technological) and soft (inter-personal) skills. For students to develop these 21st-century engineering skills, today’s curriculums must embed student-centred pedagogical methods, address the design and implementation of solutions guided by ethics and sustainability, and expose undergraduates to multicultural multidisciplinary teamwork, under strong efficiency constraints.The European Project Semester (EPS) is a project-based, international teamwork initiative, that replaces the design capstone semester of undergraduate engineering degrees. It is offered by a network of 19 HEI located in 12 different European countries. The network develops transnational projects together and exchanges students, staff, ideas, and best practices, expanding the influence of the providers. EPS at the Instituto Superior de Engenharia do Porto (EPS@ISEP) runs during the spring semester. It provides 30 European Credit Transfer System Units (ECTU), with 20?ECTU assigned to the project module and 10?ECTU equally divided by five support modules: Energy and Sustainable Development, Ethics and Deontology, Foreign Language and Culture, Marketing and Communication, and Project Management and Teamwork. The programme is offered to international and local students, but during its 12-year existence most students were international. The students are placed in teams considering psychological profiles. The multiculturalism and the diversity of skills within teams also foster a more inclusive and enriching learning experience. The sustainability and ethics objectives are requirements to be considered in the solution design and in the choice of technologies and components for the project implementation. The weekly project meetings between the teams and the coaching panel (7 teachers from 6 different departments), are not only pivotal to the project-based learning process, but promote the internal dialogue between departments and scientific areas. The reduced project budget provides a strong creative stimulus, while reinforcing the sustainability criteria, since turnkey solutions and waste are incompatible with a constrained bill of materials. Besides the positive effect of the programme on student training/education, as shown by the grades and the projects' documentation, EPS@ISEP has strongly influenced the teacher's skills and performance, as attested by the number of programme-related publications and its influence on other courses and modules offered by ISEP. EPS@ISEP is an effective low-cost programme that acts as a testbed and catalyst in the process of bringing engineering education into the 21st century, following sound ethical and sustainability criteria. EPS@ISEP contributes to the globalisation and internationalisation of ISEP as well as to the dissemination and adoption of best practices in engineering education.

Abstract
CloudAnchor is a multi-agent brokerage platform for the negotiation of Infrastructure as a Service cloud resources between Small and Medium Sized Enterprises, acting either as providers or consumers. This project entails the research, design, and implementation of a smart contract solution to permanently record and manage contractual and behavioural stakeholder data on a blockchain network. Smart contracts enable safe contract code execution, increasing trust between parties and ensuring the integrity and traceability of the chained contents. The defined smart contracts represent the inter-business trustworthiness and Service Level Agreements established within the platform. CloudAnchor interacts with the blockchain network through a dedicated Application Programming Interface, which coordinates and optimises the submission of transactions. The performed tests indicate the success of this integration: (i) the number and value of negotiated resources remain identical; and (ii) the run-time increases due to the inherent latency of the blockchain operation. Nonetheless, the introduced latency does not affect the brokerage performance, proving to be an appropriate solution for reliable partner selection and contractual enforcement between untrusted parties. This novel approach stores all brokerage strategic knowledge in a distributed, decentralised, and immutable database.

Abstract
Motivation is the key to academic success. In the case of engineering, autonomous project teamwork guided by ethics and sustainability concerns acts as a major student motivator. Moreover, it empowers students to become lifelong learners and agents of sustainable development. Engineering schools can thus address simultaneously these two essential education goals – learning and academic success – by challenging students to find innovative, sustainable solutions in a learner-centred set-up.This paper describes how the European Project Semester (EPS), a capstone engineering programme offered by the Instituto Superior de Engenharia do Porto (ISEP), combines challenge-based learning, ethics and sustainability-driven problem-solving, and international multidisciplinary teamwork to achieve both goals.

Abstract
Extreme summer temperatures in the Iberia Peninsula are analyzed from ERA5-Land reanalysis data based on an extreme value mixture model combining a Normal distribution for the bulk distribution (i.e. for the non-extreme values) and a Generalized Pareto Distribution for the extremes in the upper tail. This approach allows to treat the threshold of temperature exceedances as being one of model parameters rather than fixed a priori, enabling to take into account its corresponding uncertainty. Extreme value mixture models are estimated individually for each location, and the analysis is performed separately for two distinct periods, namely from 1981 to 2000 and from 2000 to 2019, respectively. The results show significant differences in the extreme value mixture models for the two periods, and in their corresponding 20-year return levels. The mean of the bulk distribution of summer maximum temperature increases significantly, particularly in Eastern Iberia. The largest differences in the tails of the data distribution between the two periods occur in the eastern Mediterranean area, and are characterized by a significant increase in the threshold for temperature exceedances and in their corresponding return levels.

Abstract

Abstract
<p><br>The automatic classification of peaks in gamma radiation time series is relevant for both scientific and practical applications. From the practical perspective, the classification of  peaks is fundamental for  early-warning systems for radiation protection and detection of radioactive material. From the scientific point of view, peaks in gamma radiation are often driven by precipitation  and consequent  scavenging of airborne radon progeny radionuclides to the ground (mainly Pb-214 and Bi-214). Thus measurements of gamma radiation at the earth's surface have the potential to provide information on micro-physical processes occurring high above in the clouds, as the dominant source of radon progeny is thought to be associated with in-cloud processes – nucleation scavenging and interstitial aerosol collection by cloud or rain droplets. </p><p>The present study addresses the classification of peaks in high-resolution (1-minute) gamma radiation time series from the GRM (Gamma Radiation Monitoring) campaign, which is being carried out since 2015 at the Eastern North Atlantic (ENA) station of the ARM (Atmospheric Radiation Measurements) programme. In addition to the gamma time series, precipitation information from laser disdrometer measurements is considered, including rain rate, liquid water content, median drop diameter and droplet concentration. Diverse machine learning algorithms are examined with the goal to identify and classify gamma peaks driven by precipitation events, and further examine the association between precipitation characteristics and the resulting gamma radiation peak on the ground.</p><p> </p>