Abstract
Change point detection methods try to find any sudden changes in the patterns and features of a given time series. In this paper a new change point detection method is presented, where the window width is automatically calculated. The proposed algorithm, AutoSW, is based on a Sliding Window search method of the Python ruptures package and uses a subset of statistical concepts to compute a possibly optimal window width. The proposed algorithm is compared with some other popular methods such as PELT using different real-world and synthetic time series. Results show that AutoSW can perform better than PELT producing a better set of change points in the time series tested. © 2022 IEEE.

Abstract
Since its first introduction in late 90s, the use of marketplaces has continued to grow, today virtually everything from physical assets to services can be purchased on digital marketplaces, real estate is not an exception. Some marketplaces allow acclaimed asset owners to advertise their products, to which the services gets commission/percentage from proceeds of sale/lease. Despite the success recorded in the use of the marketplaces, they are not without limitations which include identity and property fraud, impersonation and the use of centralised technology with trusted parties that are prone to single point of failures (SPOF). Being one of the most valuable assets, real estate has been a target for marketplace fraud as impersonators take pictures of properties they do not own, upload them on marketplace with promising prices that lures innocent or naive buyers. This paper addresses these issues by proposing a self sovereign identity (SSI) and smart contract based framework for identity verification and verified transaction management on secure digital marketplaces. First, the use of SSI technology enable methods for acquiring verified credential (VC) that are verifiable on a decentralised blockchain registry to identify both real estate owner(s) and real estate property. Second, the smart contracts are used to negotiate the secure transfer of real estate property deeds on the marketplace. To assess the viability of our proposal we define an application scenario and compare our work with other approaches.

Abstract
The aim of this paper is to analyse the relationship between academic inbreeding in Portugal and research collaboration, using co-authored publications as proxies. As previous research has shown that inbreeding is detrimental for research collaborations, it is hypothesised that academic inbreeding will lead to smaller research networks and, consequently, to fewer co-authored publications outside the institution of affiliation. Relying on a large data set which merged information on academics, their inbreeding status and their publications, binomial negative and fractional models were estimated to test the hypothesis. Findings show that inbred academics have smaller research networks; while they publish most co-authored papers, the relative weight of publications written in collaboration with institutional colleagues is the highest. In contrast, non-inbred academics with foreign PhDs have larger co-authorship networks. However, they publish most single-authored papers and the weight of their international co-authorships is heaviest.

Abstract
Analysis of intra- and inter-population diversity has become important for defining the genetic status and distribution patterns of a species and a powerful tool for conservation programs, as high levels of inbreeding could lead into whole population extinction in few generations. Microsatellites (SSR) are commonly used in population studies but discovering highly variable regions across species' genomes requires demanding computation and laboratorial optimization. In this work, we combine next generation sequencing (NGS) with automatic computing to develop a genomic-oriented tool for characterizing SSRs at the population level. Herein, we describe a new Python pipeline, named Micro-Primers, designed to identify, and design PCR primers for amplification of SSR loci from a multi-individual microsatellite library. By combining commonly used programs for data cleaning and microsatellite mining, this pipeline easily generates, from a fastq file produced by high-throughput sequencing, standard information about the selected microsatellite loci, including the number of alleles in the population subset, and the melting temperature and respective PCR product of each primer set. Additionally, potential polymorphic loci can be identified based on the allele ranges observed in the population, to easily guide the selection of optimal markers for the species. Experimental results show that Micro-Primers significantly reduces processing time in comparison to manual analysis while keeping the same quality of the results. The elapsed times at each step can be longer depending on the number of sequences to analyze and, if not assisted, the selection of polymorphic loci from multiple individuals can represent a major bottleneck in population studies.

Abstract
Computer science education has always been a challenging topic for both sides of the trench: educators and learners. Nowadays, with the pandemic state that we are facing, these challenges are even greater, leading educators to look for strategies that promote effective virtual learning. One of such strategies includes the use of game mechanics to improve student engagement and motivation. This design strategy is typically called gamification. Nowadays, gamification is being seen as the solution to solve most of the issues related to demotivation, complexity, or tedious tasks. In the latest years, we saw thousands of educational applications being created with gamification in mind. Nevertheless, this has been an unsustainable growth with ad hoc designs and implementations of educational gamified applications, hampering interoperability and the reuse of good practices. This chapter presents a systematic study on gamification standardization aiming to characterize the status of the field, namely describing existing frameworks, languages, services, and platforms.

Abstract
This chapter will be focused on contributing to the increase of universal design competencies of future engineers, educators, and designers through the use of mixed reality technologies, closing the gap between theory and field application of principles, towards a more inclusive world and promoting health and wellbeing for all. The experience of a situation where limitations arise in relation to what is taken for granted is an important experience that leads to a personal knowledge of the difficulties. By the use of simulators, especially virtual (VR) and mixed reality (MR) technologies, it is possible to create such experiences. Training based on MR can prepare future and current professionals for up-to-date requirements of the labor market. In addition, it can ensure that the standards such as barrier-free concepts, broader accessibility, adaptive and assistive technology will be familiar to trainees.