Abstract
Context. The dust- and gas-rich protoplanetary disks around young stellar systems play a key role in star and planet formation. While considerable progress has recently been made in probing these disks on large scales of a few tens of astronomical units (au), the central au requires further investigation. Aims.We aim to unveil the physical processes at play in the innermost regions of the strongly accreting T Tauri Star S CrA N by means of near-infrared interferometric observations. As recent spectropolarimetric observations suggest that S CrA N might undergo intense ejection processes, we focus on the accretion-ejection phenomena and on the star-disk interaction region. Methods. We obtained interferometric observations with VLTI/GRAVITY in the K-band during two consecutive nights in August 2022. The analysis of the continuum emission, coupled with the differential analysis across the Br gamma line, allows us to constrain the morphology of the dust and the gas distribution in the innermost regions of S CrA N and to investigate their temporal variability. These observations are compared to magnetospheric accretion-ejection models of T Tauri stars and to previous observations in order to elucidate the physical processes operating in these regions. Results. The K-band continuum emission is well reproduced with an azimuthally modulated dusty ring with a half-light radius of 0.24 au (similar to 20 R*), an inclination of similar to 30 degrees, and a position angle of similar to 150 degrees. As the star alone cannot explain such a large sublimation front, we propose that magnetospheric accretion is an important dust-heating mechanism leading to this continuum emission. The Br gamma-emitting region (0.05-0.06 au; 5-7 R*) is found to be more compact than the continuum, to be similar in size or larger than the magnetospheric truncation radius. The on-sky displacements across the Br gamma spectral channels are aligned along a position angle offset by 45 degrees from the disk, and extend up to 2 R*. This is in agreement with radiative transfer models combining magnetospheric accretion and disk winds. These on-sky displacements remain unchanged from one night to another, while the line flux decreases by 13%, suggesting a dominant contribution of wind to the origin of the Br gamma line. Conclusions. Our observations support the scenario where the Br gamma line originates from a combination of (variable) accretion-ejection processes in the inner disk region.

Abstract
Left ventricle (LV) segmentation of 2-D echocardiography images is an essential step in the analysis of cardiac morphology and function and-more generally-diagnosis of cardiovascular diseases (CVD). Several deep learning (DL) algorithms have recently been proposed for the automatic segmentation of the LV, showing significant performance improvement over the traditional segmentation algorithms. However, unlike the traditional methods, prior information about the segmentation problem, e.g., anatomical shape information, is not usually incorporated for training the DL algorithms. This can degrade the generalization performance of the DL models on unseen images if their characteristics are somewhat different from those of the training images, e.g., low-quality testing images. In this study, a new shape-constrained deep convolutional neural network (CNN)-called B-spline explicit active surface (BEAS)-Net-is introduced for automatic LV segmentation. The BEAS-Net learns how to associate the image features, encoded by its convolutional layers, with anatomical shape-prior information derived by the BEAS algorithm to generate physiologically meaningful segmentation contours when dealing with artifactual or low-quality images. The performance of the proposed network was evaluated using three different in vivo datasets and was compared with a deep segmentation algorithm based on the U-Net model. Both the networks yielded comparable results when tested on images of acceptable quality, but the BEAS-Net outperformed the benchmark DL model on artifactual and low-quality images.

Abstract

Abstract

Abstract
Dropout from Higher Education (HE), that is, the number of students that totally leave a given HE institution is concerningly high, especially in times of crisis. Institutions struggle to minimize dropout, but limited data is available likely because gathering data from learners who dropped out is sensitive, likely involving private information. This paper presents a case study research on student dropout from a very large Portuguese engineering faculty. The main objectives of this research include to gain a better understanding about the reasons for dropout, from the former student’s point of view, and to build a profile for the dropout-at-risk student. The collected data was retrieved from institutional records and from 134 telephonic interviews with former students. The resulting data is analysed in both quantitative and qualitative ways. Results of all gathered dropout data are clustered into three profiles of students who dropout: those that “pull out”, those who were “pushed out” and those who “fall out”. Findings include that students do not decide to dropout by a simple single reason but rather a set of reasons. This research article includes 5 concrete improvement suggestions that are likely to reduce dropout. The two main suggestions are to better prepare the transition to HE and to make policies more flexible in times of crisis, example more flexible schedule. © 2024, Author. All rights reserved.

Abstract
Although the concept of Circular Economy (CE) has become popular in recent years, the transition towards a CE system requires a change in consumers' behaviour. However, there is still limited knowledge of consumers' efforts in CE initiatives. The present paper aims to analyse and compare consumers' behaviour towards circular approaches and compare the results on items like generation and demographics. 495 answers were collected through a questionnaire from 3 countries (Albania, Poland, and Portugal). Data collected was analysed mainly through a Crosstabs analysis to identify associations or different behaviours regarding nationality, gender, generation, education, and place of residence. From the paper's findings, we can emphasise that residents of EU countries seem to be more aware of the concept of circular economy. However, price is still a very important factor for EU residents when it comes to deciding on a greener purchase. Albanians (non-EU residents) tend to take a more linear approach when it comes to purchasing a new product regardless of its cost. Regarding the Digital Product Passport, a tool proposed by the European Commission through its Circular Economy Action Plan, non-EU residents have a better understanding of the concept. This tool seems to be more relevant for Millennials and Generation X. Generation Z, i.e., the tech generation, does not show an overwhelming propensity for technological options, such as online buying and digital technologies for a greener society.