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Modern educational technology systems allow learners to access large amounts of learning materials such as educational videos, learning notes, and teaching books. Automated summarization techniques simplify the access and exploration of complex data collections by producing synthetic versions of the original content. This paper addresses the problem of video lecture summarization by means of abstractive techniques. To enhance the accessibility of the video lecture content in challenging contexts or while coping with learners with special needs it produces a synthetic textual summary condensing the key concepts mentioned in the lecture's speech. Unlike prior works based on extractive methods, the proposed method can produce more readable and actionable summaries, not necessarily composed of existing portions of speech content. To compensate the lack of annotated data, it also opportunistically reuses the pretrained models available for meeting summarization. The experimental results achieved on a benchmark dataset show that the proposed method generates more fluent and actionable summaries than prior approaches simply relying on content extraction. Finally, we also envision further applications of summarization techniques to learning content. The future prospects of use of summarization techniques in education have shown to go well beyond video summarization.

The advent of Version Control Systems (VCS) in computer science education has significantly improved the learning experience. The Learning Analytics community has started to analyze the interactions between students and VCSs to evaluate the behavioral and cognitive aspects of the learning process. Within the aforesaid scope, a promising research direction is the use of Artificial Intelligence (AI) to predict students’ exam outcomes early based on VCS usage data. Previous AI-based solutions have two main drawbacks: (i) They rely on static models, which disregard temporal changes in the student–VCS interactions. (ii) AI reasoning is not transparent to end-users. This paper proposes a time-dependent approach to early predict student performance from VCS data. It applies and compares different classification models trained at various course stages. To gain insights into exam performance predictions it combines classification with explainable AI techniques. It visualizes the explanations of the time-varying performance predictors. The results of a real case study show that the effect of VCS-based features on the exam success rate is relevant much earlier than the end of the course, whereas the timely submission of the first lab assignment is a reliable predictor of the exam grade.

Computer laboratories are learning environments where students learn programming languages by practicing under teaching assistants’ supervision. This paper presents the outcomes of a real case study carried out in our university in the context of a database course, where learning SQL is one of the main topics. The aim of the study is to analyze the level of engagement of the laboratory participants by tracing and correlating the accesses of the students to each laboratory exercise, the successful/failed attempts to solve the exercises, the students’ requests for help, and the interventions of teaching assistants. The acquired data are analyzed by means of a sequence pattern mining approach, which automatically discovers recurrent temporal patterns. The mined patterns are mapped to behavioral, cognitive engagement, and affective key indicators, thus allowing students to be profiled according to their level of engagement in all the identified dimensions. To efficiently extract the desired indicators, the mining algorithm enforces ad hoc constraints on the pattern categories of interest. The student profiles and the correlations among different engagement dimensions extracted from the experimental data have been shown to be helpful for the planning of future learning experiences.

Anna Vittoria Mattioli,1 Francesca Coppi,2 Antonio Manenti,1 Alberto Farinetti3 1Surgical, Medical and Dental Department of Morphological Sciences Related to Transplant, Oncology and Regenerative Medicine, University of Modena and Reggio Emilia, Modena, Italy; 2Cardiology Division, Policlinico di Modena, Modena, Italy; 3Department of Medical and Surgical Sciences for Children and Adults, University of Modena and Reggio Emilia, Modena, ItalyCorrespondence: Anna Vittoria MattioliSurgical, Medical and Dental Department of Morphological Sciences Related to Transplant, Oncology and Regenerative Medicine University of Modena and Reggio Emilia, Via del pozzo, 71, Modena, 41100, ItalyEmail annavittoria.mattioli@unimore.itAbstract: The cardiovascular risk assessment must be carried out during all the different phases of life because the cardiovascular risk and the related prevention actions are dynamic and constantly evolving. As patients age, they change their exposure to various risk factors and accumulate comorbidities by changing their subjective cardiovascular risk, so it is necessary to undertake personalized early and preventive diagnostic actions. The main approach to asymptomatic vascular disease is based on primary prevention with the adoption of a healthy lifestyle. Indeed, lifestyle influences most of the traditional risk factors. In recent years, important differences between the sexes regarding cardiovascular risk factors have emerged and in particular, risk factors specific for female sex have been identified. Women are more likely to be categorized into lower risk categories for cardiovascular disease and, as a result, receive less lifestyle counseling than men, as well as less intensive prevention. This narrative review aims to analyze CVD risk prevention in asymptomatic atherosclerosis with a look at new emerging factors. In the end, we quickly analyzed the effects of the recent pandemic on lifestyle and cardiovascular risk and the potential negative effects in the long term.Keywords: prevention, risk factors, women, lifestyle, microbiota, pandemic

The present letter to editor comments the manuscript “Energy Drink-Associated Cardiomyopathy after Excessive Consumption: A Case Report. J Teh Univ Heart Ctr 2021;16(3):119-122” presenting some comments on consumption of energy drinks and cardiac damages.

Implantées dans des régions agricoles de cultures intensives et drainées, les zones tampons humides artificielles ont démontré leur efficacité pour restaurer la qualité de l’eau et recréer des îlots de biodiversité. Dans le cadre du programme de recherche Brie’Eau, les chercheurs se sont intéressés au cadre légal applicable à la protection de ces zones artificialisées, et ont analysé comment les outils juridiques disponibles pouvaient être mobilisés pour que leur statut évolue vers un statut de zone humide et qu'elles bénéficient d'une protection renforcée.

Author(s): Anna Vittoria Mattioli [sup.1], Matteo Ballerini Puviani [sup.2], Milena Nasi [sup.1], Alberto Farinetti [sup.1] Author Affiliations: (1) Surgical, Medical and Dental Department of Morphological Sciences related to Transplant, Oncology [...], COVID-19 is causing a global pandemic with a high number of deaths and infected people. To contain the diffusion of COVID-19 virus, Governments have enforced restrictions on outdoor activities or even collective quarantine on the population. One important consequence of quarantine is a change in lifestyle: reduced physical activity and unhealthy diet. 2019 guidelines for primary prevention of cardiovascular disease indicate that 'Adults should engage in at least 150 minute per week of accumulated moderate-intensity or 75 minute per week of vigorous-intensity aerobic physical activity (or an equivalent combination of moderate and vigorous activity) to reduce ASCVD risk.' During quarantine, strategies to further increase home-based physical activity and to follow a healthy diet should be implemented. Quarantine carries some long-term effects on cardiovascular disease, mainly related to unhealthy lifestyle and anxiety. Following quarantine a global action supporting healthy diet and physical activity is mandatory to encourage people to return to good lifestyle.

The advent of Version Control Systems (VCS) in computer science education has significantly improved the learning experience. The Learning Analytics community has started to analyze the interactions between students and VCSs to evaluate the behavioral and cognitive aspects of the learning process. Within the aforesaid scope, a promising research direction is the use of Artificial Intelligence (AI) to predict students' exam outcomes early based on VCS usage data. Previous AI-based solutions have two main drawbacks: (i) They rely on static models, which disregard temporal changes in the student–VCS interactions. (ii) AI reasoning is not transparent to end-users. This paper proposes a time-dependent approach to early predict student performance from VCS data. It applies and compares different classification models trained at various course stages. To gain insights into exam performance predictions it combines classification with explainable AI techniques. It visualizes the explanations of the time-varying performance predictors. The results of a real case study show that the effect of VCS-based features on the exam success rate is relevant much earlier than the end of the course, whereas the timely submission of the first lab assignment is a reliable predictor of the exam grade. [ABSTRACT FROM AUTHOR]

In this contribution, we present an attempt to approach the past landscape of the Lavrion area, considering inscriptions dated to the 4th cent. BCE, recording the leases of the mines by the Athenian polity to individuals (the poletae record), as mental maps. The research aim is threefold: first, to reconstruct a flexible set of abstract mental maps, beyond a defined geometric space, in order to explore the network of spatial relationships defined in the epigraphical record and the social and economic meanings involved; second, to develop a methodology for the production of an “intermediate” map, spatially and geometrically correct, which transforms the mental map into an intra-referential map; third, final goal is to proceed to a reconstruction (insofar it is possible) of the landscape and the topographical layout of the area as in the 4th cent. BCE.

Implantées dans des régions agricoles de cultures intensives et drainées, les zones tampons humides artificielles ont démontré leur efficacité pour restaurer la qualité de l'eau et recréer des îlots de biodiversité. Dans le cadre du programme de recherche Brie'Eau, les chercheurs se sont intéressés au cadre légal applicable à la protection de ces zones artificialisées, et ont analysé comment les outils juridiques disponibles pouvaient être mobilisés pour que leur statut évolue vers un statut de zone humide et qu'elles bénéficient d'une protection renforcée.

The heterotopic mesenteric ossification, also known as myositis ossificans, is a rare form of heterotopic ossification, a metaplastic phenomenon where new bone is formed in the mesenteric base, generally after abdominal trauma (surgical or other). The pathophysiology of heterotopic mesenteric ossification is unknown; clinical presentation is not specific, with vague abdominal symptoms, uncertain radiological findings, and often regular laboratory exams. No consensus exists on the best possible approach, although it might well be both medical and surgical. We reviewed the clinical history of a 28-year-old man with a recent motor vehicle accident who was admitted to our surgical unit with symptoms consistent with a small bowel obstruction; after surgery, a diagnosis of myositis ossificans was surprisingly made.