Abstract This paper presents the work carried out by the Centro di Sonologia Computazionale (CSC) of the University of Padua, regarding the reactivation and preservation of time-based media artworks, including computer music, live electronics, performances, and multimedia art installations. During the last few years, the CSC has been developing a specific approach for archiving, documenting, and reactivating time-based media artworks, which led to the definition of the Multilevel Dynamic Preservation (MDP) model. Through in-depth analysis, various approaches are examined in the reactivation of several case studies, including digitisation, restoration, migration, and virtualisation of the artworks. The selected case studies involve various forms of art expression, such as video art, computer music, expanded cinema, and interactive performance. This contribution offers a comprehensive overview of the challenges encountered in the process of reactivating and preserving multimedia art, investigating the possible solutions offered by new technologies in preserving, digitising and virtualizing some of its forms, such as multimedia installations, expanded cinema, and video art performances.

We report on the development of two video games with educational intent and entertainment ambitions. The first game – “Cash or Card?” – is a cashier simulation to raise awareness of the issues surrounding cash vs electronic payments, a hotly debated topic shrouded in false information and conspiracy theories. The second game – “Untitled Journalist Game” – is an investigative reporting simulation focusing on the analysis and evaluation of information sources, and on how information is presented in the media. We present the design and development process of the two games, and some preliminary usage data of “Cash or Card?” We found that the synergy of game designers, educators, and game researchers is critical in developing and evaluating games to educate and entertain so that all the actors can contribute confidently according to their expertise, and produce games that communicate important content while challenging and entertaining the players.

Digital games aimed at improving cognitive and/or motor-sensory skills need to be carefully designed to take into account the characteristics and needs of particular categories of users. Several novel mini-games explicitly aimed at children with visual impairment (VI) were co-designed by a multidisciplinary team which involved computer engineers and a therapy team from the Robert Hollman Foundation (Padova, Italy). These games are played by children moving within a large-scale interactive environment - i.e., a floor portion placed under a motion capture system capable of tracking one or more people - with the game linking the players movements to the audio and visual output to produce meaningful interactions. We report on a pilot study of the usability of the system involving 11 children with VI. The results allowed us to improve the system and to define a set of guidelines useful for designers and developers of similar systems. Supplementary Information: The online version contains supplementary material available at 10.1007/s11042-022-13665-7.

Online learning in STEM subjects requires an easy way to enter and automatically mark mathematical equations. Existing solutions did not meet our requirements, and therefore we developed Inequality, a new open-source system which works across all major browsers, supports both mouse and touch-based entry, and is usable by high school children and teachers. Inequality has been in use for over 2 years by about 20000 students and nearly 900 teachers as part of the Isaac online learning platform. In this paper we evaluate Inequality as an entry method, assess the flexibility of our approach, and the effect the system has on student behaviour. We prepared 343 questions which could be answered using either Inequality or a traditional method. Looking across over 472000 question attempts, we found that students were equally proficient at answering questions correctly with both entry methods. Moreover, students using Inequality required fewer attempts to arrive at the correct answer 73% of the time. In a detailed analysis of equation construction, we found that Inequality provides significant flexibility in the construction of mathematical expressions, accommodating different working styles. We expected students who first worked on paper before entering their answers would require fewer attempts than those who did not, however this was not the case (p = 0.0109). While our system is clearly usable, a user survey highlighted a number of issues which we have addressed in a subsequent update.

UNLABELLED: A successful approach for predicting functional associations between non-homologous genes is to compare their phylogenetic distributions. We have devised a phylogenetic profiling algorithm, SVD-Phy, which uses truncated singular value decomposition to address the problem of uninformative profiles giving rise to false positive predictions. Benchmarking the algorithm against the KEGG pathway database, we found that it has substantially improved performance over existing phylogenetic profiling methods. AVAILABILITY AND IMPLEMENTATION: The software is available under the open-source BSD license at https://bitbucket.org/andrea/svd-phy CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

BACKGROUND: The increasing protein family and domain based annotations constitute important information to understand protein functions and gain insight into relations among their codifying genes. To allow analyzing of gene proteomic annotations, we implemented novel modules within GFINDer, a Web system we previously developed that dynamically aggregates functional and phenotypic annotations of user-uploaded gene lists and allows performing their statistical analysis and mining. RESULTS: Exploiting protein information in Pfam and InterPro databanks, we developed and added in GFINDer original modules specifically devoted to the exploration and analysis of functional signatures of gene protein products. They allow annotating numerous user-classified nucleotide sequence identifiers with controlled information on related protein families, domains and functional sites, classifying them according to such protein annotation categories, and statistically analyzing the obtained classifications. In particular, when uploaded nucleotide sequence identifiers are subdivided in classes, the Statistics Protein Families&Domains module allows estimating relevance of Pfam or InterPro controlled annotations for the uploaded genes by highlighting protein signatures significantly more represented within user-defined classes of genes. In addition, the Logistic Regression module allows identifying protein functional signatures that better explain the considered gene classification. CONCLUSION: Novel GFINDer modules provide genomic protein family and domain analyses supporting better functional interpretation of gene classes, for instance defined through statistical and clustering analyses of gene expression results from microarray experiments. They can hence help understanding fundamental biological processes and complex cellular mechanisms influenced by protein domain composition, and contribute to unveil new biomedical knowledge about the codifying genes.