Abstract
In this paper, we consider a permutation flowshop problem, with a weighted squared tardiness objective function, which addresses an important criterion for many customers. Our objective is to find metaheuristics that can, within acceptable computational times, provide sizeable improvements in solution quality over the best existing procedure (a dispatching rule followed by an improvement method). We consider four metaheuristics, namely iterated local search (ILS), iterated greedy (IG), variable greedy (VG) and steady-state genetic algorithms (SSGA). These are known for performing well on permutation flowshops and/or on tardiness criteria. For each metaheuristic, four versions are developed, differing on the choice of initial sequence and/or local search. Additionally, four different time limits are considered. Therefore, a total of 64 sets of results are obtained. The results show that all procedures greatly outperform the best existing method. The IG procedures provide the best results, followed by the SSGA procedures. The VG methods are usually inferior to SSGA, while the ILS metaheuristics tend to be the worst performers. The four metaheuristics prove to be robust in what regards initial solution and local search method, since both have little effect on the performance of the metaheuristics. Increasing the time limit does improve the performance of all procedures. Still, a sizeable improvement is obtained even for the lowest time limit. Therefore, even under restrictive time limits, the metaheuristics greatly outperform the best existing procedure.

Abstract
There are lot of interactive environments that encourage the practice of computer programming. Despite their usefulness, these systems are naturally disconnected from the schools' educational environments, forcing teachers and students to alternate between tools. This work integrates Agni - a computer programming learning playground - with Moodle Learning Management System (LMS). Unlike the plugins' strategy to link applications to specific LMS, this integration uses a broader approach, through the IMS LTI standard which defines a set of specifications that allows the connection of any LTI-compliant LMS to external tools. © 2022 Owner/Author.

Abstract
Optimizing research on the developmental origins of health and disease (DOHaD) involves implementing initiatives maximizing the use of the available cohort study data; achieving sufficient statistical power to support subgroup analysis; and using participant data presenting adequate follow-up and exposure heterogeneity. It also involves being able to undertake comparison, cross-validation, or replication across data sets. To answer these requirements, cohort study data need to be findable, accessible, interoperable, and reusable (FAIR), and more particularly, it often needs to be harmonized. Harmonization is required to achieve or improve comparability of the putatively equivalent measures collected by different studies on different individuals. Although the characteristics of the research initiatives generating and using harmonized data vary extensively, all are confronted by similar issues. Having to collate, understand, process, host, and co-analyze data from individual cohort studies is particularly challenging. The scientific success and timely management of projects can be facilitated by an ensemble of factors. The current document provides an overview of the 'life course' of research projects requiring harmonization of existing data and highlights key elements to be considered from the inception to the end of the project.

Abstract
Objectives Research into the effectiveness of mindfulness-based programs (MBPs) in school settings has grown substantially. However, studies in the field are still scarce, present methodological limitations, and fail to examine how children's characteristics influence MBPs' effects. The twofold aim of this study was to analyze the effectiveness of an MBP on children's attention and emotional regulation, writing performance, and school grades, and to evaluate the moderating role of baseline scores, age, gender, and socioeconomic status. Methods Fifty-seven third graders received the MBP (n = 28) or a health-based program (n = 29), which is the active control group, for 8 weeks. In each week, both programs were composed of two 30-min sessions delivered by psychologists and three 5-min sessions delivered by teachers. Before and after the implementation of the programs, we assessed teacher-rated children's attention and emotional regulation, performance-based attention networks (alerting, orienting, and conflict monitoring), writing performance (handwriting fluency, spelling, and text quality), and school grades in Portuguese, Mathematics, and Social Studies. Results Compared to the control group, after the program, the mindfulness group displayed higher teacher-rated attention and emotional regulation, as well as better Portuguese, Mathematics, and Social Studies grades. Emotional regulation and alerting baseline scores as well as age were found to moderate the MBP's effects. Conclusions These findings provide preliminary evidence on the effectiveness of a MBP on children's behavior and school grades. This means that students may benefit from the integration of mindfulness practices into the educational setting as a complement to the school curriculum.

Abstract
Practical programming competencies are critical to the success in computer science (CS) education and goto-market of fresh graduates. Acquiring the required level of skills is a long journey of discovery, trial and error, and optimization seeking through a broad range of programming activities that learners must perform themselves. It is not reasonable to consider that teachers could evaluate all attempts that the average learner should develop multiplied by the number of students enrolled in a course, much less in a timely, deep, and fair fashion. Unsurprisingly, exploring the formal structure of programs to automate the assessment of certain features has long been a hot topic among CS education practitioners. Assessing a program is considerably more complex than asserting its functional correctness, as the proliferation of tools and techniques in the literature over the past decades indicates. Program efficiency, behavior, and readability, among many other features, assessed either statically or dynamically, are now also relevant for automatic evaluation. The outcome of an evaluation evolved from the primordial Boolean values to information about errors and tips on how to advance, possibly taking into account similar solutions. This work surveys the state of the art in the automated assessment of CS assignments, focusing on the supported types of exercises, security measures adopted, testing techniques used, type of feedback produced, and the information they offer the teacher to understand and optimize learning. A new era of automated assessment, capitalizing on static analysis techniques and containerization, has been identified. Furthermore, this review presents several other findings from the conducted review, discusses the current challenges of the field, and proposes some future research directions.

Abstract