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The main objective of this deliverable is to provide resources that can assist life sciences researchers and data stewards in creating reference Data Management Plans (DMPs) for their research projects. The resources provided in this deliverable are intended to promote good research data management practices across the EU research landscape. To achieve this objective, a range of activities were undertaken, with a particular focus on the needs of the different domains covered by the demonstrator use-cases. In order to create these resources, the RDMkit pages were extended to include domain-specific information, which can be used as a reference when developing DMPs for different research projects. These pages fall under the "Your Domain" category and provide specific information on the data management needs and considerations for each domain. They also highlight challenges that are specific to each domain, such as data types, species, or areas, and offer solutions and considerations to overcome these challenges. In this deliverable, the RDMkit page for the Toxicology data demonstrator use-case was completed and added to the existing RDMkit pages for the other demonstrator use-cases. Additionally, a new Tool Assembly was added to the RDMkit corresponding to the Plant Sciences demonstrator use-case, covering the entire life cycle of experimental plant phenotyping data. In addition, the general Knowledge Models (KMs) of the Data Stewardship Wizard (DSW) were adapted to address the specific DMP questions needed for each demonstrator use-case. The DSW is a collaborative tool that enables data stewards and researchers to efficiently create DMPs for their research projects and it is designed with a hierarchical KM that guides users through the creation of DMPs. Since the relevant information for DMPs can vary across different domains, these KMs can be modified to contain the information relevant for each demonstrator use-case. For this deliverable, special focus was put on two of the demonstrator use-cases, namely Toxicology and Epitranscriptomics data. Additionally, related to the Human Data use-case, separate efforts are underway to enhance the sensitive data section of the KM system to ensure the proper management of such data. The improvements and new question suggestions that were found during these sessions were incorporated into the DSW KM by the DSW team. Furthermore, DMP templates were created in DSW for the demonstrator use-case using two standard approaches: creating a KM or a project template (PT). When creating a PT, a set of answers is saved and can be used to generate a partially pre-filled questionnaire for a new project. In the ideal case scenario, the two methods can be used together to provide domain-specific recommendations by answering questions that better reflect a scientific domain, such as metadata standards. In conclusion, this deliverable provides several valuable resources for life sciences researchers and data stewards, including extended RDMkit pages, customised DSW KMs, domain-specific DMP templates, and a new KM for creating DPIAs. These resources are designed to encourage good research data management practices across the EU research landscape, ensuring that valuable research data is effectively managed before, during, and after a project.

The overall goal of ELIXIR-CONVERGE’s WP5 was, based on the analysis of a set of very diverse use cases, to contribute to the development of a set of resources supporting the development and implementation of Data Management Plans (DMPs) in national and transnational projects. Six use cases were considered to co-develop and test a method to address domain specific data management planning associated to a set of resources in collaboration with WP1, WP2 and WP3. In this context, another objective of WP5 was to develop, implement and refine key performance indicators (KPIs) in order to monitor the demonstrator projects’ implementation of data management plans and possibly assess their adoption by the relevant community. WP5 developed two sets KPIs in collaboration with WP4, in charge of developing KPIs across the entire ELIXIR-CONVERGE project and for assessing the impact of the project : a first set aiming at monitoring the development of guidance, resources for the development of DMP and for training in the context of the use cases a second set aiming at addressing the adoption of these resources by relevant communities of users as a way to assess the impact of the work achieved In parallel, in order to ensure long term maintenance/update of the developed resources and to increase their impact, WP5 started to engage with ELIXIR communities that could be natural owners of these resources. The KPI developed and collected by WP5 during the ELIXIR-CONVERGE project were useful to follow the partner’s progress in the development and test of a sort of starter kit for domain specific data management support. Success stories could be collected showing adoption by communities and new projects and were mapped on ELIXIR’s categories of impacts showing already “hits” on several of these.

Monitoring and controlling the power grid is extremely important to prevent power outages and blackouts. Traditionally, the most common methods for inspecting high-voltage towers and power lines include visual inspections by qualified personnel, inspections by helicopters, and, in some cases, the use of specialized robots, among others. These inspections aim to detect anomalies near the infrastructure, anomalies due to hotspots in the insulation or visual defects in the various structural elements. One of the main problems of these techniques is the high economic cost and the lack of accuracy. As an alternative, unmanned aerial vehicles (UAVs) are becoming more popular in the market, and the trend is gradually moving towards this technology, as it offers significant cost reduction, better mobility and flexibility, and great potential for obtaining high-quality images. This thesis (TFG) studies the feasibility of developing a system capable of autonomously detecting high-voltage towers using an unmanned aerial vehicle and conducting power line inspections. This system consists of a desktop application that allows the user to program legs of a flight plan, and a drone that executes them and detects the high-voltage towers using an artificial intelligence model. The system developed in this study is part of a contribution to the Drone Engineering Ecosystem (DEE), a platform for controlling and monitoring unmanned aerial vehicles using desktop and/or web applications. The main goal of this platform is the improvement and continuity of its development by future students. Objectius de Desenvolupament Sostenible::9 - Indústria, Innovació i Infraestructura

In silico predictive models for toxicology include quantitative structure-activity relationship (QSAR) and physiologically based kinetic (PBK) approaches to predict physico-chemical and ADME properties, toxicological effects and internal exposure. Such models are used to fill data gaps as part of chemical risk assessment. There is a growing need to ensure in silico predictive models for toxicology are available for use and that they are reproducible. This paper describes how the FAIR (Findable, Accessible, Interoperable, Reusable) principles, developed for data sharing, have been applied to in silico predictive models. In particular, this investigation has focussed on how the FAIR principles could be applied to improved regulatory acceptance of predictions from such models. Eighteen principles have been developed that cover all aspects of FAIR. It is intended that FAIRification of in silico predictive models for toxicology will increase their use and acceptance. This research received funding from the Innovative Medicines Initiative 2 Joint Undertaking (IMI2 JU) under grant agreement eTRANSAFE (777365), the European Union’s Horizon 2020 ELIXIR-CONVERGE Project (871075) and research and innovation programme under grant agreement No 964537 (RISK-HUNT3R).

En aquest treball, s'estudiarà el comportament de dispositius piezoelèctrics davant esdeveniments d'impacte, amb la finalitat d'utilitzar-los com a sensors per preveure el dany ocasionat en un substrat determinat per única causa de l'impacte. Per fer-ho, es dissenyarà el pertinent circuit elèctric capaç de generar un senyal a partir de la resposta piezoelèctrica, i s'establirà un procediment de lectura d'aquest mitjançant un dispositiu, en aquest cas, un microcontrolador. A més es dissenyarà una configuració d'assaig i una matriu d'assajos, on sotmetent els sensors a impactes en un substrat determinat, es buscarà esclarir el comportament dels sensors envers diverses condicions d'impacte tenint en compte diferents variables com l'energia d'impacte o la velocitat d'impacte entre d'altres. Amb la informació provinent dels resultats dels assajos, i mitjançant raonaments científics es faran afirmacions i hipòtesis sobre el comportament dels sensors i es raonarà la viabilitat d'aplicar-los com a sensors per a la previsió del dany en impacte. Finalment i si escau, es proposaran noves vies per continuar la investigació amb la finalitat de confirmar o desmentir les afirmacions i hipòtesis mencionades en aquest treball. This project will study the behavior of piezoelectric devices against impact events, with the purpose of using them as sensors to foresee the damage caused in a certain substrate by only cause of the impact on itself. To do that, the corresponding electric circuit will be designed to generate an electric signal based on the piezoelectric response. After that, a procedure for reading this measurement through an external device will be established, concretely for the case of this project we will use a microcontroller. Besides that, the corresponding test method and test matrix will be designed, in which the sensors will be submitted to impact events placed in a specific substrate. We will try to clarify the behavior of piezoelectric sensors by exposing the substrate to different impact conditions, using diverse variables such as impact energy or impact speed among others. Using the information provided by the testing results, and through scientific reasoning, statements and hypothesis will be made related to sensor's behavior, and we will discuss the viability of applying them as impact damage sensors. Finally, and if applicable, new investigation lines will be purposed to continue the investigation with the intention of confirming or denying the already mentioned statements and hypothesis.

Aims Longitudinal data on the mental health impact of the coronavirus disease 2019 (Covid-19) pandemic in healthcare workers is limited. We estimated prevalence, incidence and persistence of probable mental disorders in a cohort of Spanish healthcare workers (Covid-19 waves 1 and 2) -and identified associated risk factors. Methods 8996 healthcare workers evaluated on 5 May–7 September 2020 (baseline) were invited to a second web-based survey (October–December 2020). Major depressive disorder (PHQ-8 ≥ 10), generalised anxiety disorder (GAD-7 ≥ 10), panic attacks, post-traumatic stress disorder (PCL-5 ≥ 7), and alcohol use disorder (CAGE-AID ≥ 2) were assessed. Distal (pre-pandemic) and proximal (pandemic) risk factors were included. We estimated the incidence of probable mental disorders (among those without disorders at baseline) and persistence (among those with disorders at baseline). Logistic regression of individual-level [odds ratios (OR)] and population-level (population attributable risk proportions) associations were estimated, adjusting by all distal risk factors, health care centre and time of baseline interview. Results 4809 healthcare workers participated at four months follow-up (cooperation rate = 65.7%; mean = 120 days s.d. = 22 days from baseline assessment). Follow-up prevalence of any disorder was 41.5%, (v. 45.4% at baseline, p < 0.001); incidence, 19.7% (s.e. = 1.6) and persistence, 67.7% (s.e. = 2.3). Proximal factors showing significant bivariate-adjusted associations with incidence included: work-related factors [prioritising Covid-19 patients (OR = 1.62)], stress factors [personal health-related stress (OR = 1.61)], interpersonal stress (OR = 1.53) and financial factors [significant income loss (OR = 1.37)]. Risk factors associated with persistence were largely similar. Conclusions Our study indicates that the prevalence of probable mental disorders among Spanish healthcare workers during the second wave of the Covid-19 pandemic was similarly high to that after the first wave. This was in good part due to the persistence of mental disorders detected at the baseline, but with a relevant incidence of about 1 in 5 of HCWs without mental disorders during the first wave of the Covid-19 pandemic. Health-related factors, work-related factors and interpersonal stress are important risks of persistence of mental disorders and of incidence of mental disorders. Adequately addressing these factors might have prevented a considerable amount of mental health impact of the pandemic among this vulnerable population. Addressing health-related stress, work-related factors and interpersonal stress might reduce the prevalence of these disorders substantially. Study registration number: NCT04556565

International audience; Encountered-Type Haptic Displays (ETHDs) enable users to touch virtual surfaces by using robotic actuators capable of co-locating real and virtual surfaces without encumbering users with actuators. One of the main challenges of ETHDs is to ensure that the robotic actuators do not interfere with the VR experience by avoiding unexpected collisions with users. This paper presents a design space for safety techniques using visual feedback to make users aware of the robot’s state and thus reduce unintended potential collisions. The blocks that compose this design space focus on what and when the feedback is displayed and how it protects the user. Using this design space, a set of 18 techniques was developed exploring variations of the three dimensions. An evaluation questionnaire focusing on immersion and perceived safety was designed and evaluated by a group of experts, which was used to provide a first assessment of the proposed techniques.

Background: Healthcare workers are a key occupational group at risk for suicidal thoughts and behaviors (STB). We investigated the prevalence and correlates of STB among hospital workers during the first wave of the Spain COVID-19 outbreak (March-July 2020). Methods: Data come from the baseline assessment of a cohort of Spanish hospital workers (n = 5450), recruited from 10 hospitals just after the height of the coronavirus disease 2019 (COVID-19) outbreak (May 5-July 23, 2020). Web-based self-report surveys assessed 30-day STB, individual characteristics, and potentially modifiable contextual factors related to hospital workers' work and financial situation. Results: Thirty-day STB prevalence was estimated at 8.4% (4.9% passive ideation only, 3.5% active ideation with or without a plan or attempt). A total of n = 6 professionals attempted suicide in the past 30 days. In adjusted models, 30-day STB remained significantly associated with pre-pandemic lifetime mood (odds ratio [OR] = 2.92) and anxiety disorder (OR = 1.90). Significant modifiable factors included a perceived lack of coordination, communication, personnel, or supervision at work (population-attributable risk proportion [PARP] = 50.5%), and financial stress (PARP = 44.1%). Conclusions and Relevance: Thirty-day STB among hospital workers during the first wave of the Spain COVID-19 outbreak was high. Hospital preparedness for virus outbreaks should be increased, and strong governmental policy response is needed to increase financial security among hospital workers. Fondo de Investigación Sanitaria, Instituto de Salud Carlos III (Ministerio de Ciencia e Innovación) /FEDER, Grant/Award Number: COV20/00711; ISCIII, Grant/Award Number: Sara Borrell, CD18/00049, PFIS, FI18/00012; FPU, Grant/Award Number: FPU15/05728; Generalitat de Catalunya, Grant/Award Number: 2017SGR452 Sí

This paper presents a wearable electrotactile feedback system to enhance contact information for mid-air interactions with virtual objects. In particular, we propose the use of electrotactile feedback to render the interpenetration distance between the user's finger and the virtual content is touched. Our approach consists of modulating the perceived intensity (frequency and pulse width modulation) of the electrotactile stimuli according to the registered interpenetration distance. In a user study (N=21), we assessed the performance of four different interpenetration feedback approaches: electrotactile-only, visual-only, electrotactile and visual, and no interpenetration feedback. First, the results showed that contact precision and accuracy were significantly improved when using interpenetration feedback. Second, and more interestingly, there were no significant differences between visual and electrotactile feedback when the calibration was optimized and the user was familiarized with electrotactile feedback. Taken together, these results suggest that electrotactile feedback could be an efficient replacement of visual feedback for enhancing contact information in virtual reality avoiding the need of active visual focus and the rendering of additional visual artefacts., ICAT-EGVE 2021 - International Conference on Artificial Reality and Telexistence and Eurographics Symposium on Virtual Environments, Feedback and Registration, 83, 92, Sebastian Vizcay, Panagiotis Kourtesis, Ferran Argelaguet, Claudio Pacchierotti, and Maud Marchal, CCS Concepts: Human-centered computing --> Haptic devices; Virtual reality; User studies

Additional file 2. Large figure showing the aspect of the model documentation GUI in Flame.

Introduction: Healthcare workers are vulnerable to adverse mental health impacts of the COVID-19 pandemic. We assessed prevalence of mental disorders and associated factors during the first wave of the pandemic among healthcare professionals in Spain. Methods: All workers in 18 healthcare institutions (6 AACC) in Spain were invited to web-based surveys assessing individual characteristics, COVID-19 infection status and exposure, and mental health status (May 5 - September 7, 2020). We report: probable current mental disorders (Major Depressive Disorder-MDD- [PHQ-8≥10], Generalized Anxiety Disorder-GAD- [GAD-7≥10], Panic attacks, Posttraumatic Stress Disorder -PTSD- [PCL-5≥7]; and Substance Use Disorder -SUD-[CAGE-AID≥2]. Severe disability assessed by the Sheehan Disability Scale was used to identify probable "disabling" current mental disorders. Results: 9,138 healthcare workers participated. Prevalence of screen-positive disorder: 28.1% MDD; 22.5% GAD, 24.0% Panic; 22.2% PTSD; and 6.2% SUD. Overall 45.7% presented any current and 14.5% any disabling current mental disorder. Workers with pre-pandemic lifetime mental disorders had almost twice the prevalence than those without. Adjusting for all other variables, odds of any disabling mental disorder were: prior lifetime disorders (TUS: OR=5.74; 95%CI 2.53-13.03; Mood: OR=3.23; 95%CI:2.27-4.60; Anxiety: OR=3.03; 95%CI:2.53-3.62); age category 18-29 years (OR=1.36; 95%CI:1.02-1.82), caring "all of the time" for COVID-19 patients (OR=5.19; 95%CI: 3.61-7.46), female gender (OR=1.58; 95%CI: 1.27-1.96) and having being in quarantine or isolated (OR= 1.60; 95CI:1.31-1.95). Conclusions: One in seven Spanish healthcare workers screened positive for a disabling mental disorder during the first wave of the COVID-19 pandemic. Workers reporting pre-pandemic lifetime mental disorders, those frequently exposed to COVID-19 patients, infected or quarantined/isolated, female workers, and auxiliary nurses should be considered groups in need of mental health monitoring and support. Introducción: Los profesionales sanitarios son vulnerables al impacto negativo en salud mental de la pandemia COVID-19. Evaluamos la prevalencia de trastornos mentales y factores asociados durante la primera oleada de la pandemia en sanitarios españoles. Métodos: Se invitó a todos los trabajadores de 18 instituciones sanitarias españolas (6 CCAA) a encuestas en línea evaluando características individuales, estado de infección y exposición a COVID-19 y salud mental (5 Mayo – 7 Septiembre, 2020). Reportamos: probables trastornos mentales actuales (Trastorno depresivo mayor TDD [PHQ-8≥10], Trastorno de ansiedad generalizada TAG [GAD-7≥10], Ataques de pánico, Trastorno de estrés postraumático TEP [PCL-5≥7]; y Trastorno por uso de sustancias TUS [CAGE-AID≥2]. La interferencia funcional grave (Escala de Discapacidad de Sheehan) identificó los probables trastornos “discapacitantes”. Resultados: Participaron 9.138 sanitarios. Prevalencia de cribado positivo: 28,1% TDD; 22,5% TAG, 24,0% Pánico; 22,2% PTE; y 6,2% TUS. En general, el 45,7% presentó algún trastorno mental actual y el 14,5% algún trastorno discapacitante. Los sanitarios con trastornos mentales previos tuvieron el doble de prevalencia que aquellos sin patología mental previa. Ajustando por todas las variables, el trastorno mental incapacitante se asoció positivamente con: trastornos previos (TUS: OR=5.74; 95%CI 2.53-13.03; Ánimo: OR=3.23; 95%CI:2.27-4.60; Ansiedad: OR=3,03; IC 95%: 2,53-3,62); edad 18-29 años (OR=1,36; IC 95%: 1,02-1,82); atender “siempre” a pacientes COVID-19 (OR=5,19; IC 95%: 3,61-7,46), género femenino (OR=1,58; IC 95%: 1,27-1,96) y haber estado en cuarentena o aislado (OR=1,60; IC 95%: 1,31-1,95). Conclusiones: Uno de cada 7 sanitarios españoles presentaron un probable trastorno mental discapacitante durante la primera oleada de COVID-19. Aquéllos con trastornos mentales alguna vez antes de la pandemia, los que están expuestos con frecuencia a pacientes con COVID-19, los infectados o en cuarentena / aislados, las mujeres y las enfermeras auxiliares deben considerarse grupos que necesitan seguimiento y apoyo de su salud mental.

[EN] Introduction: Healthcare workers are vulnerable to adverse mental health impacts of the COVID-19 pandemic. We assessed prevalence of mental disorders and associated factors during the first wave of the pandemic among healthcare professionals in Spain. Methods: All workers in 18 healthcare institutions (6 AACC) in Spain were invited to web-based surveys assessing individual characteristics, COVID-19 infection status and exposure, and mental health status (May 5 - September 7, 2020). We report: probable current mental disorders (Major Depressive Disorder-MDD- [PHQ-8≥10], Generalized Anxiety Disorder-GAD- [GAD-7≥10], Panic attacks, Posttraumatic Stress Disorder -PTSD- [PCL-5≥7]; and Substance Use Disorder -SUD-[CAGE-AID≥2]. Severe disability assessed by the Sheehan Disability Scale was used to identify probable "disabling" current mental disorders. Results: 9,138 healthcare workers participated. Prevalence of screen-positive disorder: 28.1% MDD; 22.5% GAD, 24.0% Panic; 22.2% PTSD; and 6.2% SUD. Overall 45.7% presented any current and 14.5% any disabling current mental disorder. Workers with pre-pandemic lifetime mental disorders had almost twice the prevalence than those without. Adjusting for all other variables, odds of any disabling mental disorder were: prior lifetime disorders (TUS: OR=5.74; 95%CI 2.53-13.03; Mood: OR=3.23; 95%CI:2.27-4.60; Anxiety: OR=3.03; 95%CI:2.53-3.62); age category 18-29 years (OR=1.36; 95%CI:1.02-1.82), caring "all of the time" for COVID-19 patients (OR=5.19; 95%CI: 3.61-7.46), female gender (OR=1.58; 95%CI: 1.27-1.96) and having being in quarantine or isolated (OR= 1.60; 95CI:1.31-1.95). Conclusions: One in seven Spanish healthcare workers screened positive for a disabling mental disorder during the first wave of the COVID-19 pandemic. Workers reporting pre-pandemic lifetime mental disorders, those frequently exposed to COVID-19 patients, infected or quarantined/isolated, female workers, and auxiliary nurses should be considered groups in need of mental health monitoring and support. [ES] Introducción: Los profesionales sanitarios son vulnerables al impacto negativo en salud mental de la pandemia COVID-19. Evaluamos la prevalencia de trastornos mentales y factores asociados durante la primera oleada de la pandemia en sanitarios españoles. Métodos: Se invitó a todos los trabajadores de 18 instituciones sanitarias españolas (6 CCAA) a encuestas en línea evaluando características individuales, estado de infección y exposición a COVID-19 y salud mental (5 Mayo – 7 Septiembre, 2020). Reportamos: probables trastornos mentales actuales (Trastorno depresivo mayor TDD [PHQ-8≥10], Trastorno de ansiedad generalizada TAG [GAD-7≥10], Ataques de pánico, Trastorno de estrés postraumático TEP [PCL-5≥7]; y Trastorno por uso de sustancias TUS [CAGE-AID≥2]. La interferencia funcional grave (Escala de Discapacidad de Sheehan) identificó los probables trastornos “discapacitantes”. Resultados: Participaron 9.138 sanitarios. Prevalencia de cribado positivo: 28,1% TDD; 22,5% TAG, 24,0% Pánico; 22,2% PTE; y 6,2% TUS. En general, el 45,7% presentó algún trastorno mental actual y el 14,5% algún trastorno discapacitante. Los sanitarios con trastornos mentales previos tuvieron el doble de prevalencia que aquellos sin patología mental previa. Ajustando por todas las variables, el trastorno mental incapacitante se asoció positivamente con: trastornos previos (TUS: OR=5.74; 95%CI 2.53-13.03; Ánimo: OR=3.23; 95%CI:2.27-4.60; Ansiedad: OR=3,03; IC 95%: 2,53-3,62); edad 18-29 años (OR=1,36; IC 95%: 1,02-1,82); atender “siempre” a pacientes COVID-19 (OR=5,19; IC 95%: 3,61-7,46), género femenino (OR=1,58; IC 95%: 1,27-1,96) y haber estado en cuarentena o aislado (OR=1,60; IC 95%: 1,31-1,95). Conclusiones: Uno de cada 7 sanitarios españoles presentaron un probable trastorno mental discapacitante durante la primera oleada de COVID-19. Aquéllos con trastornos mentales alguna vez antes de la pandemia, los que están expuestos con frecuencia a pacientes con COVID-19, los infectados o en cuarentena / aislados, las mujeres y las enfermeras auxiliares deben considerarse grupos que necesitan seguimiento y apoyo de su salud mental. This work was supported by Instituto de Salud Carlos III (Ministerio de Ciencia e Innovación)/FEDER (COV20/00711); ISCIII (Sara Borrell, CD18/00049) (PM); FPU (FPU15/05728)); ISCIII (PFIS, FI18/00012); Generalitat de Catalunya (2017SGR452). Sí

IntroductionHealthcare workers are vulnerable to adverse mental health impacts of COVID-19. We assessed prevalence of mental disorders and associated factors during the first wave of the pandemic among healthcare professionals in Spain.MethodsAll workers in 18 healthcare institutions (6 AACC) in Spain were invited to a series of online surveys assessing a wide range of individual characteristics, COVID-19 infection status and exposure, and mental health status. Here we report: current mental disorders (Major Depressive Disorder-MDD- [PHQ-8≥10], Generalized Anxiety Disorder-GAD- [GAD-7≥10], Panic attacks, Posttraumatic Stress Disorder –PTSD- [PCL-5≥7]; and Substance Use Disorder –SUD-[CAGE-AID≥2]. Severe disability assessed by the Sheehan Disability Scale was used to identify “disabling” current mental disorders.Results9,138 healthcare workers participated. Prevalence of screen-positive disorder: 28.1% MDD; 22.5% GAD, 24.0% Panic; 22.2% PTSD; and 6.2% SUD. Overall 45.7% presented any current and 14.5% any disabling current mental disorder. Healthcare workers with prior lifetime mental disorders had almost twice the prevalence of current disorders than those without. Adjusting for all other variables, odds of any disabling mental disorder were: prior lifetime disorders (TUS: OR=5.74; 95%CI 2.53-13.03; Mood: OR=3.23; 95%CI:2.27-4.60; Anxiety: OR=3.03; 95%CI:2.53-3.62); age category 18-29 years (OR=1.36; 95%CI:1.02-1.82), caring “all of the time” for COVID-19 patients (OR=5.19; 95%CI: 3.61-7.46), female gender (OR=1.58; 95%CI: 1.27-1.96) and having being in quarantine or isolated (OR= 1.60; 95CI:1.31-1.95).ConclusionsCurrent mental disorders were very frequent among Spanish healthcare workers during the first wave of COVID-19. As the pandemic enters its second wave, careful monitoring and support is needed for healthcare workers, especially those with previous mental disorders and those caring COVID-19 very often.

People use language to express their thoughts and feelings, unveiling important aspects of their psychological traits and social interactions. Although there are several studies describing methodologies to create a collection of words in English related to depression and other conditions, in most of them the selection of words is not clinical or expert based. The objective of this study is twofold: firstly, to introduce a comprehensive collection of Spanish words commonly used by patients suffering from depression, which will be available as a free open source for research purposes (GitHub), and secondly, to study the usefulness of this collection of words in identifying social media posts that could be indicative of patients suffering from depression. The level of agreement among medical doctors to determine the best words that should be used to select tweets related to depression was low. This finding may be due to the complexity of depression and the extraordinary diversity in the way people express themselves when describing their illness. It is critical to perform a thorough analysis of the specific language used in each condition, before deciding the best words to be used for filtering the tweets in each disease. As our study shows, the words supposedly more linked to depression are very common words used in other contexts, and consequently less specific for detecting depressive users. In addition, grammatical gender forms should be considered when analysing some languages such as Spanish.

International audience; The role of haptic feedback on virtual embodiment is investigated in this paper in a context of active and fine manipulation.In particular, we explore which haptic cue, with varying ecological validity, has more influence on virtual embodiment.We conducted a within-subject experiment with 24 participants and compared self-reported embodiment over a humanoid avatar during a coloring task under three conditions: force-feedback, vibrotactile feedback, no haptic feedback.In the experiment, force-feedback was more ecological as it matched reality more closely, while vibrotactile feedback was more symbolic.Taken together, our results show significant superiority of force-feedback over no haptic feedback regarding embodiment, and significant superiority of force-feedback over the other two conditions regarding subjective performance.Those results suggest that a more ecological feedback is better suited to elicit embodiment during fine manipulation tasks.

Creating selection criteria and guidelines, to aid identification of IMI datasets with the potential to generate high societal impact upon FAIRification, is an important goal of FAIRplus. This deliverable report describes the process put in place to identify, evaluate and select projects. Two thirds of projects to be addressed by FAIRplus will cover societal priorities of H2020, namely; 1) promoting healthy ageing[1]; 2) addressing chronic diseases; 3) neurodegenerative diseases and 4) emergence of antibiotic resistance. In addition, we have identified cross-cutting projects “Cross” which provide toolssuch as cell lines, biomarkers and animal models, which enable research progression in the primary priority areas. In the first period, some 25 projects have been identified based on the application of the criteria and discussions are ongoing with these consortia representativesin order to provide a steady flow of datasets into FAIRplus. [1]seehttp://ec.europa.eu/programmes/horizon2020/en/h2020-section/health-demographic-change-and-wellbeing

Candidate Pilot IMI projects (eTOX, ND4BB-TRANSLOCATION, ReSOLUTE, Aetionomy, OncoTrack and OPENPhacts) were initially identified based upon a long list highlighted in the DoA and through the FAIRplus partner network. Summaries of the activities and data sets available within these candidate Pilot IMI projects were collected via a survey tool, and further information was presented at the FAIRplus kick-off event by project owners. Following review, WP1 prioritized 4 IMI projects as Pilots, (eTOX, ND4BB-TRANSLOCATION, ReSOLUTE and OncoTrack). The prioritized Pilots were ratified by the General Assembly and formally selected. Each project was then assigned a key FAIRplus contact person, who worked with the data owners to identify, prioritise and release suitable data sets to the FAIRplus consortium, Squads and WP2 / 3 members. As of 30.06.2019, data sets have been released from eTOX, ND4BB-TRANSLOCATION and ReSOLUTE. OncoTrack is on course to release data in July 2019.