ANNA Tool: A Way to Connect Future and Past Students in STEM

The 'Increasing Gender Diversity in STEM' project involved six different partner universities around Europe. The scope of the project was to investigate the gender difference in self-perception of students in relation to their career choice. This was done through a web-based app, ANNA tool, that allows high school students to match their own personality, views, and expectations to those of engineering students and professional engineers. In the meantime, the data collection gave the opportunity to take a look at how students perceive their university and undergraduate program. This pilot application is then been further studied in order to analyse its scalability in other countries with broader STEM content

How Online Solutions Help Beat the Lockdown in Higher Education: A Central Asia Case Study

This chapter is aimed at summarizing the recent initiatives put in action for solving the problems in delivering the educational services in the Turin Polytechnic University in Tashkent, TTPU, after the lockdown, and the stringent measures taken by the Uzbek government in March 2020, for the pandemic explosion of the COVID-19 virus. The long-lasting connection between Politecnico di Torino, a European University, and this Central Asia Institution has been proven to be extremely effective, maximizing the benefits of TTPU in promptly offering online solutions for remote lectures, and the preparation of the technical substrate for both the exams and admission test which will be delivered after the completion of the second semester lectures. A summary of the IT tools adopted, with compact highlights of their features, as well as the qualitative feedback collected from the first courses offered with a reshaped structure suitable for online classes are thoroughly discussed in this work

Diagnostic performance of the Strength and Pain Assessment (SPA) score for non-contact muscle injury screening in male soccer players

Objectives: The aims of this study were to develop a clinical-feature based scoring system for muscle injury screening and to assess its diagnostic accuracy when large number of injuries are suspected. Methods: A prospective diagnostic accuracy study was performed according to the Standards for Reporting of Diagnostic Accuracy (STARD) criteria. The diagnostic accuracy of the Strength and Pain Assessment (SPA) score (index test) was assessed in relation to muscle ultrasonography (reference standard). A large (n = 175) number of male soccer players met the inclusion/exclusion criteria: clinical assessment (i.e., evaluation of pain onset modality, location, distribution, impact on performance, and manual muscle strength testing) and ultrasonography were performed in all players after 48 hours from the sudden or progressive onset of muscle pain during or after a soccer competition. Results: 91 of 175 cases (52%) were classified as functional muscle disorders, while signs of muscle tear were observed in the remaining 84 of 175 (48%) cases that were classified as structural muscle injuries. The median (1st–3rd quartile) value of the SPA score was significantly (P < 0.001) lower in the functional disorder group [9 (9–10)] compared to the structural injury group [12 (12–13)]. The area under the Receiver Operating Characteristic curve for different cutoff points of the SPA score was 0.977 (95% confidence intervals: 0.957–0.998) and the optimal cutoff value of the SPA score providing the greatest sensitivity and specificity (respectively, 99% and 89%) was 11. Conclusion: This study found that the SPA score has high diagnostic accuracy for structural muscle injuries and could be used as a valid screening tool in soccer players presenting with sudden or progressive onset of muscle pain during or after a competition

DXA-Based Detection of Low Muscle Mass Using the Total Body Muscularity Assessment Index (TB-MAXI): A New Index with Cutoff Values from the NHANES 1999–2004

The aims of this study were to investigate age-related changes in total body skeletal muscle mass (TBSMM) and the between-limb asymmetry in lean mass in a large sample of adults. Demographic, anthropometric, and DXA-derived data of National Health and Nutrition Examination Survey participants were considered. The sample included 10,014 participants of two ethnic groups (Caucasians and African Americans). The age-related decline of TBSMM absolute values was between 5% and 6% per decade in males and between 4.5% and 5.0% per decade in females. The adjustment of TBSMM for body surface area (TB-MAXI) showed that muscle mass peaked in the second decade and decreased progressively during the subsequent decades. The following thresholds were identified to distinguish between low and normal TB-MAXI: (i) 10.0 kg/m2 and 11.0 kg/m2 in Caucasian and African American females; and (ii) 12.5 kg/m2 and 14.5 kg/m2 in Caucasian and African American males. The lean asymmetry indices were higher for the lower limbs compared with the upper limbs and were higher for males compared with females. In conclusion, the present study proposes the TB-MAXI and lean asymmetry index, which can be used (and included in DXA reports) as clinically relevant markers for muscle amount and lean distribution

An evaluative baseline for geo-semantic relatedness and similarity

In geographic information science and semantics, the computation of semantic similarity is widely recognised as key to supporting a vast number of tasks in information integration and retrieval. By contrast, the role of geo-semantic relatedness has been largely ignored. In natural language processing, semantic relatedness is often confused with the more specific semantic similarity. In this article, we discuss a notion of geo-semantic relatedness based on Lehrer’s semantic fields, and we compare it with geo-semantic similarity. We then describe and validate the Geo Relatedness and Similarity Dataset (GeReSiD), a new open dataset designed to evaluate computational measures of geo-semantic relatedness and similarity. This dataset is larger than existing datasets of this kind, and includes 97 geographic terms combined into 50 term pairs rated by 203 human subjects. GeReSiD is available online and can be used as an evaluation baseline to determine empirically to what degree a given computational model approximates geo-semantic relatedness and similarity