Comparison of Elemental Carbon (EC) and Black Carbon (BC) measurements derived by Thermo-Optical and filter-based light transmission techniques at North Atlantic.

7th International Aerosol Conference. St. Paul, Minnesota, 10-15 September 2006.Terceira Island (38.691º; 27.354º; 50 m altitude) in the Azores Archipelago, developed to provide a base for remote marine boundary layer measurements at a location near the PICO-NARE (Honrath & Fialho, 2002) (Figure 1). In order to determine a long term carbonaceous component of atmospheric aerosols in North Atlantic, measurements of aerosol BC and EC were begun in 2002. EC and BC define similar fraction of the carbonaceous component of atmospheric aerosols and are supposed to be comparable, but have a delicate different thermal, optical and chemical behaviour in most cases (Lavanchy et al., 1999)

Assessment of air quality on basis of particle matter (PM) measurement in the North Atlantic.

7th International Aerosol Conference. St. Paul, Minnesota, 10-15 September 2006.The European thematic strategy on air pollution and the accompanying proposal to revise the ambient air quality directive (1999/30/EC) would, for the first time, introduce controls on human expose to PM2.5 to complement the existing limits on coarse particulate matter (PM10) (EC, 2005)

Seasonal variability of ozone dry deposition under southern European climate conditions, in Portugal

Ozone dry deposition measurements were carried out during approximately one year over a flat grass field in Portugal. The results show prominent diurnal and seasonal patterns in deposition flux, dry deposition velocity and surface resistance, especially for the daytime period. Dry deposition velocities vary diurnally from a minimum of 0.1 cm s-1, during the night to a maximum of 0.2-0.5 cm s-1 during the day. The observed canopy resistance (Rc) varies from values higher than 500 s m-1, at night, to a minimum of 200 s m-1, around noon. Seasonal variation is characterised by daytime Rc values much larger in summer than in winter and spring, while nighttime values do not show any evident seasonal pattern. This behaviour can be ascribed to the stomatal intake, which represents the most important controlling factor on ozone dry deposition. The Wesely parameterisation scheme of surface resistance predicts Rc diurnal cycles reasonably well. However, the observed canopy resistance seasonal cycle is completely different from Wesely predictions, since season parameters in Wesely's parameterisation were defined for a vegetation growing cycle different from that prevailing in our conditions.We gratefully acknowledge the European Commission and the Junta Nacional de Investigac7a8o Cienti"ca, for "nancial support through the projects EV5V-CT93-316 and PRAXIS/3/3.2/AMB/38/94, respectively. We also wish to thank the Instituto de Estruturas Agra& rias e Desenvolvimento Rural who permitted the measurements at the `Polder Pilotoa of Sarrazola and all research groups who participated in the SREMP Project

Automatic Spanish translation of SQuAD dataset for multi-lingual question answering

Recently, multilingual question answering became a crucial research topic, and it is receiving increased interest in the NLP community.However, the unavailability of large-scale datasets makes it challenging to train multilingual QA systems with performance comparableto the English ones. In this work, we develop the Translate Align Retrieve (TAR) method to automatically translate the Stanford QuestionAnswering Dataset (SQuAD) v1.1 to Spanish. We then used this dataset to train Spanish QA systems by fine-tuning a Multilingual-BERTmodel. Finally, we evaluated our QA models with the recently proposed MLQA and XQuAD benchmarks for cross-lingual ExtractiveQA. Experimental results show that our models outperform the previous Multilingual-BERT baselines achieving the new state-of-the-artvalues of 68.1 F1 on the Spanish MLQA corpus and 77.6 F1 on the Spanish XQuAD corpus. The resulting, synthetically generatedSQuAD-es v1.1 corpora, with almost 100% of data contained in the original English version, to the best of our knowledge, is the firstlarge-scale QA training resource for Spanish.This work is supported in part by the Spanish Ministe-rio de Econom ́ıa y Competitividad, the European RegionalDevelopment Fund and the Agencia Estatal de Investi-gaci ́on, through the postdoctoral senior grant Ram ́on y Ca-jal (FEDER/MINECO) amd the project PCIN-2017-079(AEI/MINECO).Peer ReviewedPostprint (published version

Size distribution of atmospheric particulate ionic species at a coastal site in Portugal

A Berner impactor was used to collect size-differentiated aerosol samples from March to August 2003 in the city of Aveiro, on the Portuguese west coast. The samples were analysed for the main water-soluble ion species. The average concentration of sulphate, nitrate, chloride and ammonium was 6.38, 3.09, 1.67 and 1.27 µg m-3, respectively. The results show that SO4(2-) and NH4+ were consistently present in the fine fraction 2), possibly due to greater availability of ammonia coming from agricultural activities or from the neighbouring chemical industrial complex. During the remaining periods, the aerosol was found to be somewhat acidic and predominantly in the form of ammonium bisulphate (NH4+/SO4(2-) molar ratios = 0.5-1.25). Samples collected under a major or exclusive influence of maritime air masses were essentially constituted by coarse particles with enrichment in sea salt, while for air masses of continental origin the contribution of water-soluble ionic species in the fine mode was more pronounced

Comparison of methodologies for assessing desert dust contribution to regional PM10 and PM2.5 levels: a one-year study over Portugal

Desert dust outbreaks may affect air quality. This study estimates the importance of African dust contribution to the PM10 and PM2.5 concentrations observed in rural regional background sites in Portugal. Desert dust contribution is evaluated by two different approaches: A measurement-approach methodology based on the monthly moving 40th percentile, and a model-approach methodology based on WRF-CHIMERE simulations, whose performance is also assessed within this work. Several desert dust episodes affected atmospheric aerosols in the planetary boundary layer over Portugal during 2016. Their intensity was variable, with at least two events (21–22 February and 27–28 October) contributing to exceedances to the PM10 daily limit value defined in the European Air Quality Directive. African dust contributions obtained for the year 2016 with the measurement-approach methodology are higher than the ones simulated by WRF-CHIMERE. Contributions to PM10 and to PM2.5 concentrations range from 0 to 90 µg m-3 and from 0 to 30 µg m-3, respectively, in most of the regions and days. Caution must be employed when using measurement-approach methodologies to quantify dust contributions to PM levels when forest fires occur simultaneously with the long-range transport of desert dust, as happened in August 2016.This research was funded by FCT – Portuguese Foundation for Science and Technology and FEDER (within the PT2020 Partnership Agreement and Compete 2020), grant numbers UID/AMB/50017 - POCI- 01-0145-FEDER-007638 (CESAM associated laboratory), MIT-EXPL/IRA/0023/2017 (ISY-AIR research project) and POCI-01-0145-FEDER-029374 (ARTUR research project).Peer ReviewedPostprint (published version

Vickybot, a Chatbot for Anxiety-Depressive Symptoms and Work-Related Burnout in Primary Care and Health Care Professionals: Development, Feasibility, and Potential Effectiveness Studies

Background: Many people attending primary care (PC) have anxiety-depressive symptoms and work-related burnout compounded by a lack of resources to meet their needs. The COVID-19 pandemic has exacerbated this problem, and digital tools have been proposed as a solution. Objective: We aimed to present the development, feasibility, and potential effectiveness of Vickybot, a chatbot aimed at screening, monitoring, and reducing anxiety-depressive symptoms and work-related burnout, and detecting suicide risk in patients from PC and health care workers. Methods: Healthy controls (HCs) tested Vickybot for reliability. For the simulation study, HCs used Vickybot for 2 weeks to simulate different clinical situations. For feasibility and effectiveness study, people consulting PC or health care workers with mental health problems used Vickybot for 1 month. Self-assessments for anxiety (Generalized Anxiety Disorder 7-item) and depression (Patient Health Questionnaire-9) symptoms and work-related burnout (based on the Maslach Burnout Inventory) were administered at baseline and every 2 weeks. Feasibility was determined from both subjective and objective user-engagement indicators (UEIs). Potential effectiveness was measured using paired 2-tailed t tests or Wilcoxon signed-rank test for changes in self-assessment scores. Results: Overall, 40 HCs tested Vickybot simultaneously, and the data were reliably transmitted and registered. For simulation, 17 HCs (n=13, 76{\%} female; mean age 36.5, SD 9.7 years) received 98.8{\%} of the expected modules. Suicidal alerts were received correctly. For the feasibility and potential effectiveness study, 34 patients (15 from PC and 19 health care workers; 76{\%} [26/34] female; mean age 35.3, SD 10.1 years) completed the first self-assessments, with 100{\%} (34/34) presenting anxiety symptoms, 94{\%} (32/34) depressive symptoms, and 65{\%} (22/34) work-related burnout. In addition, 27{\%} (9/34) of patients completed the second self-assessment after 2 weeks of use. No significant differences were found between the first and second self-assessments for anxiety (t8=1.000; P=.34) or depressive (t8=0.40; P=.70) symptoms. However, work-related burnout scores were moderately reduced (z=−2.07, P=.04, r=0.32). There was a nonsignificant trend toward a greater reduction in anxiety-depressive symptoms and work-related burnout with greater use of the chatbot. Furthermore, 9{\%} (3/34) of patients activated the suicide alert, and the research team promptly intervened with successful outcomes. Vickybot showed high subjective UEI (acceptability, usability, and satisfaction), but low objective UEI (completion, adherence, compliance, and engagement). Vickybot was moderately feasible. Conclusions: The chatbot was useful in screening for the presence and severity of anxiety and depressive symptoms, and for detecting suicidal risk. Potential effectiveness was shown to reduce work-related burnout but not anxiety or depressive symptoms. Subjective perceptions of use contrasted with low objective-use metrics. Our results are promising but suggest the need to adapt and enhance the smartphone-based solution to improve engagement. A consensus on how to report UEIs and validate digital solutions, particularly for chatbots, is required.We are grateful to all participants. GA is supported by a Rio Hortega 2021 grant (CM21/00017) from the Spanish Ministry of Health financed by the Instituto de Salud Carlos III (ISCIII) and cofinanced by Fondo Social Europe Plus. MS was supported by a grant from the Baszucki Brain Research Fund. AM is supported by the Agència de Gestió d’Ajudes Universitàries I de Investigació—PANDÈMIES 2020 grant (PI047003) from the Generalitat de Catalunya. IG thanks the support of the Spanish Ministry of Science and Innovation (PI19/00954) integrated into the Plan Nacional de I+D+I and cofinanced by the ISCIII-Subdirección General de Evaluación y el Fondos Europeos de la Unión Europea (FEDER, Fondo Social Europe, Next Generation European Union or Plan de Recuperación Transformación y Resiliencia_PRTR); the Instituto de Salud Carlos III; the CIBER of Mental Health (CIBERSAM); and the Secretaria d’Universitats i Recerca del Departament d’Economia i Coneixement (2017 SGR 1365), CERCA Programme or Generalitat de Catalunya as well as the Fundació Clínic per la Recerca Biomèdica (Pons Bartran 2022-FRCB_PB1_2022). AHY’s independent research was funded by the National Institute for Health Research Biomedical Research Centre in South London and Maudsley National Health Service Foundation Trust and King’s College London. The views expressed are those of the authors and not necessarily those of the National Health Service, National Institute for Health and Care Research, or Department of Health. JR is supported by a Miguel Servet II contract (CPII19/00009), funded by ISCIII and cofunded by the European Social Fund “Investing in your future.” CT has been supported through a “Miguel Servet” postdoctoral contract (CPI14/00175) and a Miguel Servet II contract (CPII19/00018) and thanks the support of the Spanish Ministry of Innovation and Science (PI17/01066 and PI20/00344), funded by the Instituto de Salud Carlos III and cofinanced by the European Union (FEDER) “Una manera de hacer Europa.” AMA thanks the support of the Spanish Ministry of Science and Innovation (PI18/00789, PI21/00787) integrated into the Plan Nacional de I+D+I and cofinanced by ISCIII-Subdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (FEDER); the ISCIII; the CIBER of Mental Health (CIBERSAM); the Secretaria d’Universitats i Recerca del Departament d’Economia i Coneixement (2017 SGR 1365); the CERCA Programme; and the Departament de Salut de la Generalitat de Catalunya for the Pla estratègic de recerca I innovació en salut (PERIS) grant SLT006/17/00177. AM thanks the support of the Spanish Ministry of Science and Innovation (PI19/00672) integrated into the Plan Nacional de I+D+I and cofinanced by the ISCIII-Subdirección General de Evaluación and the FEDER. GF is supported by a fellowship from “La Caixa” Foundation (ID 100010434)—fellowship code—LCF/BQ/DR21/11880019. SA has been supported by a Sara Borrell contract (CD20/00177), funded by ISCIII and founded by the European Social Fund “Investing in your future.” EV thanks the support of the Spanish Ministry of Science, Innovation and Universities (PI15/00283, PI18/00805, PI19/00394, PI21/00787, and CPII19/00009) integrated into the Plan Nacional de I+D+I and cofinanced by the ISCIII-Subdirección General de Evaluación and the FEDER; the ISCIII; the CIBER of Mental Health (CIBERSAM); the Secretaria d’Universitats i Recerca del Departament d’Economia i Coneixement (2017 SGR 1365), and the CERCA Programme or Generalitat de Catalunya. We would like to thank the Departament de Salut de la Generalitat de Catalunya for the PERIS grant SLT006/17/00357. DHM´s research was supported by Juan Rodés JR18/00021 granted by the ISCIII. The PRESTO project has been funded by Fundació Clínic per a la Recerca Biomèdica through the Pons Bartran 2020 grant (PI046549). The development of a version of the digital solution adapted to health workers is funded by the Spanish Foundation for Psychiatry and Mental Health, Spanish Psychiatric Society, and Spanish Society of Biological Psychiatry (PI046813). The enhancement of the digital solution with Natural Language Processing techniques in a chatbot user-interface in collaboration with the text mining technologies in the health domain of the Barcelona Supercomputing Center is funded by the Agència de Gestió d’Ajudes Universitàries I de Investigació—PANDÈMIES 2020 grant (PI047003), from La Generalitat de Catalunya.Peer Reviewed"Article signat per 50 autors/es: Gerard Anmella; Miriam Sanabra; Mireia Primé-Tous; Xavier Segú; Myriam Cavero; Ivette Morilla; Iria Grande; Victoria Ruiz; Ariadna Mas; Inés Martín-Villalba; Alejandro Caballo; Julia-Parisad Esteva; Arturo Rodríguez-Rey; Flavia Piazza; Francisco José Valdesoiro; Claudia Rodriguez-Torrella; Marta Espinosa; Giulia Virgili; Carlota Sorroche; Alicia Ruiz; Aleix Solanes; Joaquim Radua; María Antonieta Also; Elisenda Sant; Sandra Murgui; Mireia Sans-Corrales; Allan H Young; Victor Vicens; Jordi Blanch; Elsa Caballeria; Hugo López-Pelayo; Clara López; Victoria Olivé; Laura Pujol ; Sebastiana Quesada; Brisa Solé; Carla Torrent; Anabel Martínez-Aran; Joana Guarch; Ricard Navinés; Andrea Murru; Giovanna Fico; Michele de Prisco; Vicenzo Oliva; Silvia Amoretti ; Casimiro Pio-Carrino; María Fernández-Canseco; Marta Villegas; Eduard Vieta; Diego Hidalgo-Mazzei"Postprint (published version

Aerosol optical properties at Santiago Island, Cape Verde.

European Aerosol Conference. Granada, Spain, 2-7 September 2012.> huge amounts of mineral dust are emitted every year from the Sahara desert to the atmosphere; > optical parameters of mineral aerosols determine the direct interaction of solar and terrestrial radiation in the atmosphere through scattering and absorption; > mineral dust has a great impact on cloud formation leading to additional indirect radiation effects; > The dense haze from dust events is also known to affect visibility

Pre-trained biomedical language models for clinical NLP in Spanish

This work presents the first large-scale biomedical Spanish language models trained from scratch, using large biomedical corpora consisting of a total of 1.1B tokens and an EHR corpus of 95M tokens. We compared them against general-domain and other domain-specific models for Spanish on three clinical NER tasks. As main results, our models are superior across the NER tasks, rendering them more convenient for clinical NLP applications. Furthermore, our findings indicate that when enough data is available, pre-training from scratch is better than continual pre-training when tested on clinical tasks, raising an exciting research question about which approach is optimal. Our models and fine-tuning scripts are publicly available at HuggingFace and GitHub.This work was funded by the Spanish State Secretariat for Digitalization and Artificial Intelligence (SEDIA) within the framework of the Plan-TLPeer ReviewedPostprint (published version