A systematic review on evidences supporting quality indicators of bilingual, plurilingual and multilingual programs in higher education

This systematic review intends to report on the strength of evidences supporting the quality indicators (predictors) attributed to higher education bilingual, plurilingual or multilingual practices and programs across four key dependent variables (outcomes) analyzed (i.e., student performance, second language proficiency, employment, and motivation and attitudes). The rapid growth of both offer and demand of this type of higher education and learning worldwide requires the implementation of high-quality evaluation strategies and techniques to measure potential causal links between interventions and results. To do so, a pre-specified systematic review protocol following the Campbell Collaboration (2015) recommendations is designed and implemented. The results suggest the urgent need to increase the primary research quality standards in this sub-discipline by reducing bias in the processes of designing, implementing and reporting research. Despite the scarcity of results sustained on statistical conclusions with the higher statistical power found in this review, specific results of the dependent variables indicate that this type of education benefits students’ performance and second language proficiency, with a higher impact on receptive skills. Although no results were obtained concerning student employment, other results point out that there is general satisfaction of participation with the programs. Finally, several recommendations on how to scale up those quality research standards in this sub-discipline are provided

Robust Resolution-Enhanced Prostate Segmentation in Magnetic Resonance and Ultrasound Images through Convolutional Neural Networks

[EN] Prostate segmentations are required for an ever-increasing number of medical applications, such as image-based lesion detection, fusion-guided biopsy and focal therapies. However, obtaining accurate segmentations is laborious, requires expertise and, even then, the inter-observer variability remains high. In this paper, a robust, accurate and generalizable model for Magnetic Resonance (MR) and three-dimensional (3D) Ultrasound (US) prostate image segmentation is proposed. It uses a densenet-resnet-based Convolutional Neural Network (CNN) combined with techniques such as deep supervision, checkpoint ensembling and Neural Resolution Enhancement. The MR prostate segmentation model was trained with five challenging and heterogeneous MR prostate datasets (and two US datasets), with segmentations from many different experts with varying segmentation criteria. The model achieves a consistently strong performance in all datasets independently (mean Dice Similarity Coefficient -DSC- above 0.91 for all datasets except for one), outperforming the inter-expert variability significantly in MR (mean DSC of 0.9099 vs. 0.8794). When evaluated on the publicly available Promise12 challenge dataset, it attains a similar performance to the best entries. In summary, the model has the potential of having a significant impact on current prostate procedures, undercutting, and even eliminating, the need of manual segmentations through improvements in terms of robustness, generalizability and output resolutionThis work has been partially supported by a doctoral grant of the Spanish Ministry of Innovation and Science, with reference FPU17/01993Pellicer-Valero, OJ.; González-Pérez, V.; Casanova Ramón-Borja, JL.; Martín García, I.; Barrios Benito, M.; Pelechano Gómez, P.; Rubio-Briones, J.... (2021). 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Differential Segmentation of the Prostate in MR Images Using Combined 3D Shape Modelling and Voxel Classification. 3rd IEEE International Symposium on Biomedical Imaging: Macro to Nano, 2006. doi:10.1109/isbi.2006.1624940Freedman, D., Radke, R. J., Tao Zhang, Yongwon Jeong, Lovelock, D. M., & Chen, G. T. Y. (2005). Model-based segmentation of medical imagery by matching distributions. IEEE Transactions on Medical Imaging, 24(3), 281-292. doi:10.1109/tmi.2004.841228Klein, S., van der Heide, U. A., Lips, I. M., van Vulpen, M., Staring, M., & Pluim, J. P. W. (2008). Automatic segmentation of the prostate in 3D MR images by atlas matching using localized mutual information. Medical Physics, 35(4), 1407-1417. doi:10.1118/1.2842076Ronneberger, O., Fischer, P., & Brox, T. (2015). U-Net: Convolutional Networks for Biomedical Image Segmentation. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015, 234-241. doi:10.1007/978-3-319-24574-4_28He, K., Gkioxari, G., Dollar, P., & Girshick, R. (2017). Mask R-CNN. 2017 IEEE International Conference on Computer Vision (ICCV). doi:10.1109/iccv.2017.322Shelhamer, E., Long, J., & Darrell, T. (2017). Fully Convolutional Networks for Semantic Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(4), 640-651. doi:10.1109/tpami.2016.2572683He, K., Zhang, X., Ren, S., & Sun, J. (2016). Deep Residual Learning for Image Recognition. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). doi:10.1109/cvpr.2016.90Milletari, F., Navab, N., & Ahmadi, S.-A. (2016). V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation. 2016 Fourth International Conference on 3D Vision (3DV). doi:10.1109/3dv.2016.79Zhu, Q., Du, B., Turkbey, B., Choyke, P. L., & Yan, P. (2017). Deeply-supervised CNN for prostate segmentation. 2017 International Joint Conference on Neural Networks (IJCNN). doi:10.1109/ijcnn.2017.7965852To, M. N. N., Vu, D. Q., Turkbey, B., Choyke, P. L., & Kwak, J. T. (2018). Deep dense multi-path neural network for prostate segmentation in magnetic resonance imaging. International Journal of Computer Assisted Radiology and Surgery, 13(11), 1687-1696. doi:10.1007/s11548-018-1841-4Huang, G., Liu, Z., Van Der Maaten, L., & Weinberger, K. Q. (2017). Densely Connected Convolutional Networks. 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). doi:10.1109/cvpr.2017.243Zhu, Y., Wei, R., Gao, G., Ding, L., Zhang, X., Wang, X., & Zhang, J. (2018). Fully automatic segmentation on prostate MR images based on cascaded fully convolution network. Journal of Magnetic Resonance Imaging, 49(4), 1149-1156. doi:10.1002/jmri.26337Wang, Y., Ni, D., Dou, H., Hu, X., Zhu, L., Yang, X., … Wang, T. (2019). Deep Attentive Features for Prostate Segmentation in 3D Transrectal Ultrasound. IEEE Transactions on Medical Imaging, 38(12), 2768-2778. doi:10.1109/tmi.2019.2913184Lemaître, G., Martí, R., Freixenet, J., Vilanova, J. C., Walker, P. M., & Meriaudeau, F. (2015). Computer-Aided Detection and diagnosis for prostate cancer based on mono and multi-parametric MRI: A review. Computers in Biology and Medicine, 60, 8-31. doi:10.1016/j.compbiomed.2015.02.009Litjens, G., Toth, R., van de Ven, W., Hoeks, C., Kerkstra, S., van Ginneken, B., … Madabhushi, A. (2014). Evaluation of prostate segmentation algorithms for MRI: The PROMISE12 challenge. Medical Image Analysis, 18(2), 359-373. doi:10.1016/j.media.2013.12.002Zhu, Q., Du, B., & Yan, P. (2020). Boundary-Weighted Domain Adaptive Neural Network for Prostate MR Image Segmentation. IEEE Transactions on Medical Imaging, 39(3), 753-763. doi:10.1109/tmi.2019.2935018He, K., Zhang, X., Ren, S., & Sun, J. (2015). Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification. 2015 IEEE International Conference on Computer Vision (ICCV). doi:10.1109/iccv.2015.123Pan, S. J., & Yang, Q. (2010). A Survey on Transfer Learning. IEEE Transactions on Knowledge and Data Engineering, 22(10), 1345-1359. doi:10.1109/tkde.2009.191Smith, L. N. (2017). Cyclical Learning Rates for Training Neural Networks. 2017 IEEE Winter Conference on Applications of Computer Vision (WACV). doi:10.1109/wacv.2017.58Abraham, N., & Khan, N. M. (2019). A Novel Focal Tversky Loss Function With Improved Attention U-Net for Lesion Segmentation. 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019). doi:10.1109/isbi.2019.8759329Lei, Y., Tian, S., He, X., Wang, T., Wang, B., Patel, P., … Yang, X. (2019). Ultrasound prostate segmentation based on multidirectional deeply supervised V‐Net. Medical Physics, 46(7), 3194-3206. doi:10.1002/mp.13577Orlando, N., Gillies, D. J., Gyacskov, I., Romagnoli, C., D’Souza, D., & Fenster, A. (2020). Automatic prostate segmentation using deep learning on clinically diverse 3D transrectal ultrasound images. Medical Physics, 47(6), 2413-2426. doi:10.1002/mp.14134Karimi, D., Zeng, Q., Mathur, P., Avinash, A., Mahdavi, S., Spadinger, I., … Salcudean, S. E. (2019). Accurate and robust deep learning-based segmentation of the prostate clinical target volume in ultrasound images. Medical Image Analysis, 57, 186-196. doi:10.1016/j.media.2019.07.005PROMISE12 Resultshttps://promise12.grand-challenge.org/Isensee, F., Jaeger, P. F., Kohl, S. A. A., Petersen, J., & Maier-Hein, K. H. (2020). nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nature Methods, 18(2), 203-211. doi:10.1038/s41592-020-01008-

Effect of a Pulmonary Embolism Diagnostic Strategy on Clinical Outcomes in Patients Hospitalized for COPD Exacerbation. A Randomized Clinical Trial

SLICE Trial Group.[Importance] Active search for pulmonary embolism (PE) may improve outcomes in patients hospitalized for exacerbations of chronic obstructive pulmonary disease (COPD).[Objective] To compare usual care plus an active strategy for diagnosing PE with usual care alone in patients hospitalized for COPD exacerbation.[Design, Setting, and Participants] Randomized clinical trial conducted across 18 hospitals in Spain. A total of 746 patients were randomized from September 2014 to July 2020 (final follow-up was November 2020).[Interventions] Usual care plus an active strategy for diagnosing PE (D-dimer testing and, if positive, computed tomography pulmonary angiogram) (n = 370) vs usual care (n = 367).[Main Outcomes and Measures] The primary outcome was a composite of nonfatal symptomatic venous thromboembolism (VTE), readmission for COPD, or death within 90 days after randomization. There were 4 secondary outcomes, including nonfatal new or recurrent VTE, readmission for COPD, and death from any cause within 90 days. Adverse events were also collected.[Results] Among the 746 patients who were randomized, 737 (98.8%) completed the trial (mean age, 70 years; 195 [26%] women). The primary outcome occurred in 110 patients (29.7%) in the intervention group and 107 patients (29.2%) in the control group (absolute risk difference, 0.5% [95% CI, −6.2% to 7.3%]; relative risk, 1.02 [95% CI, 0.82-1.28]; P = .86). Nonfatal new or recurrent VTE was not significantly different in the 2 groups (0.5% vs 2.5%; risk difference, −2.0% [95% CI, −4.3% to 0.1%]). By day 90, a total of 94 patients (25.4%) in the intervention group and 84 (22.9%) in the control group had been readmitted for exacerbation of COPD (risk difference, 2.5% [95% CI, −3.9% to 8.9%]). Death from any cause occurred in 23 patients (6.2%) in the intervention group and 29 (7.9%) in the control group (risk difference, −1.7% [95% CI, −5.7% to 2.3%]). Major bleeding occurred in 3 patients (0.8%) in the intervention group and 3 patients (0.8%) in the control group (risk difference, 0% [95% CI, −1.9% to 1.8%]; P = .99).[Conclusions and Relevance] Among patients hospitalized for an exacerbation of COPD, the addition of an active strategy for the diagnosis of PE to usual care, compared with usual care alone, did not significantly improve a composite health outcome. The study may not have had adequate power to assess individual components of the composite outcome.[Trial Registration] ClinicalTrials.gov Identifier: NCT02238639.Peer reviewe

ECOS-LINCE : a high-intensity heavy-ion facility for nuclear structure and reactions

Presented at the XXXIV Mazurian Lakes Conference on Physics, Piaski, Poland, September 6–13, 2015During the last years, the ECOS working group has been considering the construction of a new high-intensity accelerator of stable ion beams for the next Long-Range Plan of the nuclear physics community in Europe. The new facility (LINCE) will be a multi-user facility dedicated to ECOS science: fundamental physics, astrophysics, nuclear structure and reaction dynamics. In this paper, we summarize preliminary design studies of the low-energy part of this facility based on the use of a multi-ion supercon- ducting linac.Work partially supported by the Spanish Government under the grant Feder-Interconnecta “Aceltec” ITC-20111070. The authors are also grateful to the companies Alter Technology-Tüv, Avs, Cibernos, Elitt Energy, Faysol, Idom, and Tti Norte for partial funding of this work and active participation in the design and prototyping carried-out in this study

Monitorización y seguimiento del esfuerzo realizado por los estudiantes y de su asistencia a actividades presenciales

Este artículo documenta el planteamiento, la metodología y los primeros resultados de un plan de monitorización detallada del esfuerzo y de asistencia a actividades presenciales por parte de los estudiantes de las titulaciones ofertadas por la Escuela Técnica Superior de Ingenieros Navales de la Universidad Politécnica de Madrid durante el segundo cuatrimestre del curso 2011-2012. Se ha establecido un sistema mecánico de recogida de datos de esfuerzo por parte de los estudiantes utilizando una hoja tipo test especialmente configurada al efecto. Se pasa una hoja en todas y cada una de las actividades presenciales realizadas y en la hoja se solicita información sobre el trabajo "fuera de clase". Se documenta en este artículo cómo se ha estructurado esa hoja, qué tipo de datos se recogen, cómo se tratan mediante una base de datos creada al efecto, qué tipo de análisis se puede realizar y qué resultados preliminares obtenemos de dichos análisis

Antibody conversion rates to SARS-CoV-2 in saliva from children attending summer schools in Barcelona, Spain.

Background: Surveillance tools to estimate viral transmission dynamics in young populations are essential to guide recommendations for school opening and management during viral epidemics. Ideally, sensitive techniques are required to detect low viral load exposures among asymptomatic children. We aimed to estimate SARS-CoV-2 infection rates in children and adult populations in a school-like environment during the initial COVID-19 pandemic waves using an antibody-based field-deployable and non-invasive approach. Methods: Saliva antibody conversion defined as ≥ 4-fold increase in IgM, IgA, and/or IgG levels to five SARS-CoV-2 antigens including spike and nucleocapsid constructs was evaluated in 1509 children and 396 adults by high-throughput Luminex assays in samples collected weekly in 22 summer schools and 2 pre-schools in 27 venues in Barcelona, Spain, from June 29th to July 31st, 2020. Results: Saliva antibody conversion between two visits over a 5-week period was 3.22% (49/1518) or 2.36% if accounting for potentially cross-reactive antibodies, six times higher than the cumulative infection rate (0.53%) assessed by weekly saliva RT-PCR screening. IgG conversion was higher in adults (2.94%, 11/374) than children (1.31%, 15/1144) (p=0.035), IgG and IgA levels moderately increased with age, and antibodies were higher in females. Most antibody converters increased both IgG and IgA antibodies but some augmented either IgG or IgA, with a faster decay over time for IgA than IgG. Nucleocapsid rather than spike was the main antigen target. Anti-spike antibodies were significantly higher in individuals not reporting symptoms than symptomatic individuals, suggesting a protective role against COVID-19. Conclusion: Saliva antibody profiling including three isotypes and multiplexing antigens is a useful and user-friendlier tool for screening pediatric populations to detect low viral load exposures among children, particularly while they are not vaccinated and vulnerable to highly contagious variants, and to recommend public health policies during pandemics

Impact of interstitial lung disease on the survival of systemic sclerosis with pulmonary arterial hypertension

To assess severity markers and outcomes of patients with systemic sclerosis (SSc) with or without pulmonary arterial hypertension (PAH-SSc/non-PAH-SSc), and the impact of interstitial lung disease (ILD) on PAH-SSc. Non-PAH-SSc patients from the Spanish SSc registry and PAH-SSc patients from the Spanish PAH registry were included. A total of 364 PAH-SSc and 1589 non-PAH-SSc patients were included. PAH-SSc patients had worse NYHA-functional class (NYHA-FC), worse forced vital capacity (FVC) (81.2 +/- 20.6% vs 93.6 +/- 20.6%, P < 0.001), worse tricuspid annular plane systolic excursion (TAPSE) (17.4 +/- 5.2 mm vs 19.9 +/- 6.7 mm, P < 0.001), higher incidence of pericardial effusion (30% vs 5.2%, P < 0.001) and similar prevalence of ILD (41.8% vs. 44.9%). In individuals with PAH-SSc, ILD was associated with worse hemodynamics and pulmonary function tests (PFT). Up-front combination therapy was used in 59.8% and 61.7% of patients with and without ILD, respectively. Five-year transplant-free survival rate was 41.1% in PAH-SSc patients and 93.9% in non-PAH-SSc patients (P < 0.001). Global survival of PAH-SSc patients was not affected by ILD regardless its severity. The multivariate survival analysis in PAH-SSc patients confirmed age at diagnosis, worse NYHA-FC, increased PVR, reduced DLCO, and lower management with up-front combination therapy as major risk factors. In conclusion, in PAH-SSc cohort risk of death was greatly increased by clinical, PFT, and hemodynamic factors, whereas it was decreased by up-front combination therapy. Concomitant ILD worsened hemodynamics and PFT in PAH-SSc but not survival regardless of FVC impairment

Impact of interstitial lung disease on the survival of systemic sclerosis with pulmonary arterial hypertension

To assess severity markers and outcomes of patients with systemic sclerosis (SSc) with or without pulmonary arterial hypertension (PAH-SSc/non-PAH-SSc), and the impact of interstitial lung disease (ILD) on PAH-SSc. Non-PAH-SSc patients from the Spanish SSc registry and PAH-SSc patients from the Spanish PAH registry were included. A total of 364 PAH-SSc and 1589 non-PAH-SSc patients were included. PAH-SSc patients had worse NYHA-functional class (NYHA-FC), worse forced vital capacity (FVC) (81.2 ± 20.6% vs 93.6 ± 20.6%, P &lt; 0.001), worse tricuspid annular plane systolic excursion (TAPSE) (17.4 ± 5.2 mm vs 19.9 ± 6.7 mm, P &lt; 0.001), higher incidence of pericardial effusion (30% vs 5.2%, P &lt; 0.001) and similar prevalence of ILD (41.8% vs. 44.9%). In individuals with PAH-SSc, ILD was associated with worse hemodynamics and pulmonary function tests (PFT). Up-front combination therapy was used in 59.8% and 61.7% of patients with and without ILD, respectively. Five-year transplant-free survival rate was 41.1% in PAH-SSc patients and 93.9% in non-PAH-SSc patients (P &lt; 0.001). Global survival of PAH-SSc patients was not affected by ILD regardless its severity. The multivariate survival analysis in PAH-SSc patients confirmed age at diagnosis, worse NYHA-FC, increased PVR, reduced DLCO, and lower management with up-front combination therapy as major risk factors. In conclusion, in PAH-SSc cohort risk of death was greatly increased by clinical, PFT, and hemodynamic factors, whereas it was decreased by up-front combination therapy. Concomitant ILD worsened hemodynamics and PFT in PAH-SSc but not survival regardless of FVC impairment