Digital technology in managing Erasmus+ mobilities: efficiency gains and impact analysis from Spanish, Italian, and Turkish universities

The European Union is investing in the areas of digital skills, digital infrastructures, digitisation of businesses, and public services to speed up numerous administrative processes and to facilitate access to citizens from member countries and neighbouring ones as well. This study provides a quantitative assessment of the efficiency gains that can be attained by the ongoing digital transformation in the realm of Erasmus+, the European Commission’s programme for education, training, youth, and sport for the period 2021–2027. This programme manages a sizable budget allocated to education and training opportunities abroad for millions of students, teachers, and other staff of Higher Education Institutions within the EU and beyond. The management of such experiences has significantly grown in complexity over the last decades, entailing notable expenses that the EC aims to reduce through the end-to-end digitalisation of administrative procedures. Our analysis of the savings attained by the so-called Erasmus Without Paper project (EWP) was conducted by taking a close look at the workload, resources, and money invested in Erasmus+ proceedings by four universities from Spain, Italy, and Turkey. The analysis revealed significant savings in terms of paper wastage (a reduction of more than 13.5 million prints every year for the whole Erasmus+ programme) and administrative time, which may translate into lower staff effort and increased productivity, to the point of managing up to 80% more mobilities with the same resources and staff currently available.European University Foundation | Ref. 2020-1-TR-KA203-09384

Eliciting requirements and scenarios using the SCTL-MUS methodology. The shuttle system case study

ABSTRACT The development of complex systems demands methodologies that conveniently support the stakeholders in the creative tasks. In this paper, we present a methodology for the incremental elicitation of requirements and scenarios, driven by the integration checks performed over a state machine that represents the global behavior of the desired system

Evaluation of an expert system for the generation of speech and language therapy plans

Background: Speech and language pathologists (SLPs) deal with a wide spectrum of disorders, arising from many different conditions, that affect voice, speech, language, and swallowing capabilities in different ways. Therefore, the outcomes of Speech and Language Therapy (SLT) are highly dependent on the accurate, consistent, and complete design of personalized therapy plans. However, SLPs often have very limited time to work with their patients and to browse the large (and growing) catalogue of activities and specific exercises that can be put into therapy plans. As a consequence, many plans are suboptimal and fail to address the specific needs of each patient. Objective: We aimed to evaluate an expert system that automatically generates plans for speech and language therapy, containing semiannual activities in the five areas of hearing, oral structure and function, linguistic formulation, expressive language and articulation, and receptive language. The goal was to assess whether the expert system speeds up the SLPs’ work and leads to more accurate, consistent, and complete therapy plans for their patients. Methods: We examined the evaluation results of the SPELTA expert system in supporting the decision making of 4 SLPs treating children in three special education institutions in Ecuador. The expert system was first trained with data from 117 cases, including medical data; diagnosis for voice, speech, language and swallowing capabilities; and therapy plans created manually by the SLPs. It was then used to automatically generate new therapy plans for 13 new patients. The SLPs were finally asked to evaluate the accuracy, consistency, and completeness of those plans. A four-fold cross-validation experiment was also run on the original corpus of 117 cases in order to assess the significance of the results. Results: The evaluation showed that 87% of the outputs provided by the SPELTA expert system were considered valid therapy plans for the different areas. The SLPs rated the overall accuracy, consistency, and completeness of the proposed activities with 4.65, 4.6, and 4.6 points (to a maximum of 5), respectively. The ratings for the subplans generated for the areas of hearing, oral structure and function, and linguistic formulation were nearly perfect, whereas the subplans for expressive language and articulation and for receptive language failed to deal properly with some of the subject cases. Overall, the SLPs indicated that over 90% of the subplans generated automatically were “better than” or “as good as” what the SLPs would have created manually if given the average time they can devote to the task. The cross-validation experiment yielded very similar results. Conclusions: The results show that the SPELTA expert system provides valuable input for SLPs to design proper therapy plans for their patients, in a shorter time and considering a larger set of activities than proceeding manually. The algorithms worked well even in the presence of a sparse corpus, and the evidence suggests that the system will become more reliable as it is trained with more subjects.Fondo Europeo de Desarrollo RegionalXunta de GaliciaMinisterio de Economía y Competitividad | Ref. TIN2013-42774-

A crowdsourcing recommendation model for image annotations in cultural heritage platforms

Cultural heritage is one of many fields that has seen a significant digital transformation in the form of digitization and asset annotations for heritage preservation, inheritance, and dissemination. However, a lack of accurate and descriptive metadata in this field has an impact on the usability and discoverability of digital content, affecting cultural heritage platform visitors and resulting in an unsatisfactory user experience as well as limiting processing capabilities to add new functionalities. Over time, cultural heritage institutions were responsible for providing metadata for their collection items with the help of professionals, which is expensive and requires significant effort and time. In this sense, crowdsourcing can play a significant role in digital transformation or massive data processing, which can be useful for leveraging the crowd and enriching the metadata quality of digital cultural content. This paper focuses on a very important challenge faced by cultural heritage crowdsourcing platforms, which is how to attract users and make such activities enjoyable for them in order to achieve higher-quality annotations. One way to address this is to offer personalized interesting items based on each user preference, rather than making the user experience random and demanding. Thus, we present an image annotation recommendation system for users of cultural heritage platforms. The recommendation system design incorporates various technologies intending to help users in selecting the best matching images for annotations based on their interests and characteristics. Different classification methods were implemented to validate the accuracy of our work on Egyptian heritage.Agencia Estatal de Investigación | Ref. TIN2017-87604-RXunta de Galicia | Ref. ED431B 2020/3

Machine learning algorithms to predict breast cancer recurrence using structured and unstructured sources from electronic health records

Recurrence is a critical aspect of breast cancer (BC) that is inexorably tied to mortality. Reuse of healthcare data through Machine Learning (ML) algorithms offers great opportunities to improve the stratification of patients at risk of cancer recurrence. We hypothesized that combining features from structured and unstructured sources would provide better prediction results for 5-year cancer recurrence than either source alone. We collected and preprocessed clinical data from a cohort of BC patients, resulting in 823 valid subjects for analysis. We derived three sets of features: structured information, features from free text, and a combination of both. We evaluated the performance of five ML algorithms to predict 5-year cancer recurrence and selected the best-performing to test our hypothesis. The XGB (eXtreme Gradient Boosting) model yielded the best performance among the five evaluated algorithms, with precision = 0.900, recall = 0.907, F1-score = 0.897, and area under the receiver operating characteristic AUROC = 0.807. The best prediction results were achieved with the structured dataset, followed by the unstructured dataset, while the combined dataset achieved the poorest performance. ML algorithms for BC recurrence prediction are valuable tools to improve patient risk stratification, help with post-cancer monitoring, and plan more effective follow-up. Structured data provides the best results when fed to ML algorithms. However, an approach based on natural language processing offers comparable results while potentially requiring less mapping effort.European Union | Ref. 875406Fondo Europeo de Desarrollo Regional (FEDER)Xunta de Galici

On how technology-powered storytelling can contribute to cultural heritage sustainability across multiple venues-Evidence from the crosscult H2020 project

Sustainability in Cultural Heritage (CH) is a complex question that needs to be addressed by a group of experts tackling the different issues. In this light, the present work wishes to provide a multi-level analysis of the sustainability in CH, using as an example a recent European H2020 project (CrossCult) and the lessons learnt from its design, implementation and evaluation. The sustainability of CH has qualitatively changed over the last few years, under the developments in digital technology that seems to affect the very nature of the cultural experience. We discuss sustainability in venues using digital technologies, covering a span of needs of small/unknown and large/popular venues, which try to enhance the visitor experience, attract visitors, form venue networks, etc. Moreover, we explore issues of sustainability of digital content and its re usability through holistic design. Aspects of technology, human networks and data sustainability are also presented, and we conclude with the arguments concerning the sustainability of visitor reflection, the interpretation of social and historical phenomena and the creation of meaning.This research was funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 693150. The authors from the University of Vigo got further support from the European Regional Development Fund (ERDF) and the Galician Regional Government under agreement for funding the AtlantTIC Research Center for Information and Communication Technologies, as well as the Ministerio de Educación y Ciencia (Gobierno de España) research project TIN2017-87604-R

Sporadic cloud-based mobile augmentation on the top of a virtualization layer: a case study of collaborative downloads in VANETs

Current approaches to Cloud-based Mobile Augmentation (CMA) leverage (cloud-based) resources to meet the requirements of rich mobile applications, so that a terminal (the so-called application node or AppN) can borrow resources lent by a set of collaborator nodes (CNs). In the most sophisticated approaches proposed for vehicular scenarios, the collaborators are nearby vehicles that must remain together near the application node because the augmentation service is interrupted when they move apart. This leads to disruption in the execution of the applications and consequently impoverishes the mobile users’ experience. This paper describes a CMA approach that is able to restore the augmentation service transparently when AppNs and CNs separate. The functioning is illustrated by a NaaS model where the AppNs access web contents that are collaboratively downloaded by a set of CNs, exploiting both roadside units and opportunistic networking. The performance of the resulting approach has been evaluated via simulations, achieving promising results in terms of number of downloads, average download times, and network overheadMinisterio de Educación y Ciencia | Ref. TIN2017-87604-

Urgent urinary diversion by intrinsic or extrinsic obstructive disease of the urinary tract. Percutaneous nephrostomy versus ureteral stent

Introducción: La obstrucción de la vía urinaria es una patología urgente que se presenta con relativa frecuencia y que en determinados casos requiere de derivación urinaria inminente. El objetivo de este estudio es analizar los resultados y complicaciones en pacientes con obstrucción de la vía urinaria superior tras derivación urinaria con stent ureteral versus nefrostomía percutánea. Métodos: Estudio retrospectivo desde 1 Enero de 2011 a 31 Diciembre de 2012 incluyendo 134 pacientes (65 hombres, 69 mujeres) de edad media 61.2 ± 17.4 años procedentes de Urgencias y requirieron derivación urinaria urgente. Se analiza según el tipo de derivación urinaria diferentes parámetros etiológicos, estancia hospitalaria, evolución clínica y analítica y complicaciones. Resultados: De los 134 pacientes, en 89 casos se optó por colocación de stent ureteral y en 45 casos de nefrostomía percutánea. Los pacientes en los que se colocó nefrostomía percutánea eran más añosos y presentaban unos niveles más elevados de creatinina respecto al grupo de stent ureteral de forma significativa. No se encontraron diferencias estadísticamente significativas en la evolución clínica o analítica entre una u otra derivación, únicamente en la estancia hospitalaria que fue mayor para los pacientes con nefrostomía debido a la mayor edad, mayores cifras de creatinina al ingreso y mayor comorbilidad. Conclusión: No existen diferencias en los resultados y complicaciones entre stent ureteral y nefrostomía, si bien consideramos el stent ureteral como primera opción ante una obstrucción aguda de la vía, reservando la nefrostomía para casos de obstrucción maligna, sepsis con alteración de parámetros inflamatorios y mayor comorbilidad.Introduction: Obstruction of the urinary tract is a relatively frequent disease and sometimes requires urgent urinary derivation. The objective of this study was to compare outcomes and complications in patients with upper urinary tract obstruction after urinary derivation with ureteral stent or percutaneous nephrostomy. Material and Methods: A retrospective study was conducted from 1 January 2011 to 31 December 2012 in 134 patients (65 males, 69 females) with a mean age of 61.2 ± 17.4 yrs who came to our emergency department requiring urgent urinary derivation. Data were gathered on the type of urinary derivation, aetiology, length of hospital stay, clinical and analytical results and complications. Results: A ureteral stent was placed in 89 of the 134 patients and percutaneous nephrostomy in the remaining 45. Creatinine levels and age were significantly higher in the percutaneous nephrostomy versus ureteral stent group. No inter-group differences were found in clinical or analytical outcomes. The hospital stay was longer for the percutaneous nephrostomy patients, attributable to their higher mean age, admission creatinine level, and comorbidities. Conclusions: No differences in outcomes or complications were found between ureteral stent and percutaneous nephrostomy placement. Ureteral stents may be preferable in patients with acute tract obstruction and nephrostomy preferable in patients with malignant obstruction or sepsis with altered inflammatory parameters and a greater comorbidity burden

Revista de Vertebrados de la Estación Biológica de Doñana

Catálogo descriptivo de los anfibios y reptiles de CubaEvolución estacional de la comunidad de aves en un robledal de Sierra NevadaComposición de la comunidad de aves en pinares del Parque Nacional de Doñana (suroeste de España).Alimentación de la pagaza piconegra (Gelochelidon nilotica) en las marismas del GuadalquivirContaminación xenobiótica del Parque Nacional de Doñana. III. Residuos de insecticidas organoclorados, bifenilos policlorados y metales pesados en ciconiformesAlimentación de la lechuza común Tyto alba en la cuenca del Duero, EspañaEstudio de una población rural de (Mus musculus L.) I. La probabilidad de captura y la estima numéricLa reproducción en Gazella dorcasIncidencia del Nemátodo parásito Skrjabingylus Leuckart, 1842 sobre el Mustela en España.Desplazamientos de ungulados silvestres a través de una zona de ecotono en Doñana.Etograma de la cabra montés (Capra pyrenaica) y comparación con otras especies.Sobre comportamiento agresivo de Triturus marmoratus en época de celoEmbarrancamiento masivo de ejemplares de tortuga lad (Dermochelys coriacea L.) en las costas de Ceuta (España, norte de África)Sobre un ejemplar melánico de Podarcis hispanica (Steindachner, 1870)Nuevos datos sobre la distribución de cuatro especies de reptiles en la provincia de Cádiz.Algunos datos sobre la nidificación de Ciconia nigra L. en sierra Morena (S. España)Observación del halcón de Eleonor (Falco eleonorae) en el centro de EspañaNueva localidad de cría del pájaro moscón (Remiz pendulinus) en la Península IbéricaRegistro de aves en el sur de BoliviaNidificación del paiño de Madeira Oceanodroma castro (Harcourt, 1851) en las Islas Canarias.Observación primaveral de Phalaropus fulicarius L. en el SO de EspañaNuevos datos sobre la presencia del nóctulo gigante Nyctalus lasiopterus (Chiroptera, vespertilionidae) en EspañaNote sur l'alimentation de Martes martes a Menorca (Baleares).Peer reviewe

La "app" Google Lens en la didáctica universitaria de códigos verbales y artísticos

Memoria ID-113. Ayudas de la Universidad de Salamanca para la innovación docente, curso 2019-2020