Responses to European policies: The impact of the Erasmus programme on national policy-making

Session 1: Governance in the European Unio

Mapping the scattered field of research on higher education. A correlated topic model of 17,000 articles, 1991–2018

Parallel to the increasing level of maturity of the field of research on higher education, an increasing number of scholarly works aims at synthesising and presenting overviews of the field. We identify three important pitfalls these previous studies struggle with, i.e. a limited scope, a lack of a content-related analysis, and/or a lack of an inductive approach. We take these limitations into account by analysing the abstracts of 16,928 articles on higher education between 1991 and 2018. To investigate this huge collection of texts, we apply topic models, which are a collection of automatic content analysis methods that allow to map the structure of large text data. After an in-depth discussion of the topics differentiated by our model, we study how these topics have evolved over time. In addition, we analyse which topics tend to co-occur in articles. This reveals remarkable gaps in the literature which provides interesting opportunities for future research. Furthermore, our analysis corroborates the claim that the field of research on higher education consists of isolated ‘islands’. Importantly, we find that these islands drift further apart because of a trend of specialisation. This is a bleak finding, suggesting the (further) disintegration of our field

Symbolic Reachability Analysis of B through ProB and LTSmin

We present a symbolic reachability analysis approach for B that can provide a significant speedup over traditional explicit state model checking. The symbolic analysis is implemented by linking ProB to LTSmin, a high-performance language independent model checker. The link is achieved via LTSmin's PINS interface, allowing ProB to benefit from LTSmin's analysis algorithms, while only writing a few hundred lines of glue-code, along with a bridge between ProB and C using ZeroMQ. ProB supports model checking of several formal specification languages such as B, Event-B, Z and TLA. Our experiments are based on a wide variety of B-Method and Event-B models to demonstrate the efficiency of the new link. Among the tested categories are state space generation and deadlock detection; but action detection and invariant checking are also feasible in principle. In many cases we observe speedups of several orders of magnitude. We also compare the results with other approaches for improving model checking, such as partial order reduction or symmetry reduction. We thus provide a new scalable, symbolic analysis algorithm for the B-Method and Event-B, along with a platform to integrate other model checking improvements via LTSmin in the future

Twenty-Four Hour Tonometry in Patients Suspected of Chronic Gastrointestinal Ischemia

Background and aims: Gastrointestinal tonometry is currently the only clinical diagnostic test that enables identification of symptomatic chronic gastrointestinal ischemia. Gastric exercise tonometry has proven its value for detection of ischemia in this patients group, but has its disadvantages. Earlier studies with postprandial tonometry gave unreliable results. In this study we challenged (again) the use of postprandial tonometry in patients suspected of gastrointestinal ischemia. Methods: Patients suspected for chronic gastrointestinal ischemia had standard diagnostic work up, including gastric exercise tonometry and 24-h tonometry using standard meals. Results: Thirty-three patients were enrolled in the study. Chronic gastrointestinal ischemia was diagnosed in 17 (52%) patients. The 24-h tonometry correctly predicted the presence of ischemia in 13/17 patients, and absence of ischemia in 15/16 patients. Conclusions: The use of 24-h tonometry after meals in patients suspected of gastrointestinal ischemia seems feasible, with promising accuracy for the detection of ischemia

Single-center versus multi-center biparametric MRI radiomics approach for clinically significant peripheral zone prostate cancer

Contains fulltext : 239809.pdf (Publisher’s version ) (Open Access

A deep learning masked segmentation alternative to manual segmentation in biparametric MRI prostate cancer radiomics

OBJECTIVES: To determine the value of a deep learning masked (DLM) auto-fixed volume of interest (VOI) segmentation method as an alternative to manual segmentation for radiomics-based diagnosis of clinically significant (CS) prostate cancer (PCa) on biparametric magnetic resonance imaging (bpMRI). MATERIALS AND METHODS: This study included a retrospective multi-center dataset of 524 PCa lesions (of which 204 are CS PCa) on bpMRI. All lesions were both semi-automatically segmented with a DLM auto-fixed VOI method (averaging < 10 s per lesion) and manually segmented by an expert uroradiologist (averaging 5 min per lesion). The DLM auto-fixed VOI method uses a spherical VOI (with its center at the location of the lowest apparent diffusion coefficient of the prostate lesion as indicated with a single mouse click) from which non-prostate voxels are removed using a deep learning-based prostate segmentation algorithm. Thirteen different DLM auto-fixed VOI diameters (ranging from 6 to 30 mm) were explored. Extracted radiomics data were split into training and test sets (4:1 ratio). Performance was assessed with receiver operating characteristic (ROC) analysis. RESULTS: In the test set, the area under the ROC curve (AUCs) of the DLM auto-fixed VOI method with a VOI diameter of 18 mm (0.76 [95% CI: 0.66-0.85]) was significantly higher (p = 0.0198) than that of the manual segmentation method (0.62 [95% CI: 0.52-0.73]). CONCLUSIONS: A DLM auto-fixed VOI segmentation can provide a potentially more accurate radiomics diagnosis of CS PCa than expert manual segmentation while also reducing expert time investment by more than 97%. KEY POINTS: * Compared to traditional expert-based segmentation, a deep learning mask (DLM) auto-fixed VOI placement is more accurate at detecting CS PCa. * Compared to traditional expert-based segmentation, a DLM auto-fixed VOI placement is faster and can result in a 97% time reduction. * Applying deep learning to an auto-fixed VOI radiomics approach can be valuable

Preparing children with a mock scanner training protocol results in high quality structural and functional MRI scans

We evaluated the use of a mock scanner training protocol as an alternative for sedation and for preparing young children for (functional) magnetic resonance imaging (MRI). Children with severe mental retardation or developmental disorders were excluded. A group of 90 children (median age 6.5 years, range 3.65–14.5 years) participated in this study. Children were referred to the actual MRI investigation only when they passed the training. We assessed the pass rate of the mock scanner training sessions. In addition, the quality of both structural and functional MRI (fMRI) scans was rated on a semi-quantitative scale. The overall pass rate of the mock scanner training sessions was 85/90. Structural scans of diagnostic quality were obtained in 81/90 children, and fMRI scans with sufficient quality for further analysis were obtained in 30/43 of the children. Even in children under 7 years of age, who are generally sedated, the success rate of structural scans with diagnostic quality was 53/60. FMRI scans with sufficient quality were obtained in 23/36 of the children in this younger age group. The association between age and proportion of children with fMRI scans of sufficient quality was not statistically significant. We conclude that a mock MRI scanner training protocol can be useful to prepare children for a diagnostic MRI scan. It may reduce the need for sedation in young children undergoing MRI. Our protocol is also effective in preparing young children to participate in fMRI investigations

Six-Minute Walk Test in Patients With Down Syndrome:Validity and Reproducibility

Contains fulltext : 81543.pdf (publisher's version ) (Closed access)OBJECTIVES: To examine the validity of the six-minute walk test (6MWT) as a tool to evaluate functional exercise performance in patients with Down syndrome (DS). DESIGN: Comparison of the six-minute walk distance (6MWD) in 2 distinct groups of DS patients: with and without severe cardiac disease. To test reproducibility, a group of patients with DS performed the 6MWT twice. SETTING: Tertiary referral centers for patients with congenital heart defects and outpatient clinics for people with intellectual disabilities. PARTICIPANTS: Adult patients with DS with (n=29) and without (n=52) severe cardiac disease categorized by cardiac echocardiography. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURE: Distance walked on the 6MWT. RESULTS: The mean 6MWD in the group with severe cardiac disease was 289+/-104 m and in the group without severe cardiac disease 280+/-104 m (P=.70). Older age, female sex, and severe level of intellectual disability were all found to be independently and significantly correlated with a lower 6MWD (r=.67, P<.001). The paired 6MWD was not significantly different (310+/-88 m vs 317+/-85 m; P=.40) in patients who performed the 6MWT twice. The coefficient of variation was 11%. CONCLUSIONS: The 6MWD between the 2 groups was not significantly different. However, the walking distance inversely correlated with the level of intellectual disability. Therefore, the 6MWT is not a valid test to examine cardiac restriction in adult patients with DS

The limitation of genetic testing in diagnosing patients suspected for congenital platelet defects

Thrombosis and Hemostasi