NEW SEISMIC SOURCE ZONE MODEL FOR PORTUGAL AND AZORES

The development of seismogenic source models is one of the first steps in seismic hazard assessment. In seismic hazard terminology, seismic source zones (SSZ) are polygons (or volumes) that delineate areas with homogeneous characteristics of seismicity. The importance of using knowledge on geology, seismicity and tectonics in the definition of source zones has been recognized for a long time [1]. However, the definition of SSZ tends to be subjective and controversial. Using SSZ based on broad geology, by spreading the seismicity clusters throughout the areal extent of a zone, provides a way to account for possible long-term non-stationary seismicity behavior [2,3]. This approach effectively increases seismicity rates in regions with no significant historical or instrumental seismicity, while decreasing seismicity rates in regions that display higher rates of seismicity. In contrast, the use of SSZ based on concentrations of seismicity or spatial smoothing results in stationary behavior [4]. In the FP7 Project SHARE (Seismic Hazard Harmonization in Europe), seismic hazard will be assessed with a logic tree approach that allows for three types of branches for seismicity models: a) smoothed seismicity, b) SSZ, c) SSZ and faults. In this context, a large-scale zonation model for use in the smoothed seismicity branch, and a new consensus SSZ model for Portugal and Azores have been developed. The new models were achieved with the participation of regional experts by combining and adapting existing models and incorporating new regional knowledge of the earthquake potential. The main criteria used for delineating the SSZ include distribution of seismicity, broad geological architecture, crustal characteristics (oceanic versus continental, tectonically active versus stable, etc.), historical catalogue completeness, and the characteristics of active or potentially-active faults. This model will be integrated into an Iberian model of SSZ to be used in the Project SHARE seismic hazard assessment

COMPILATION OF ACTIVE FAULT DATA IN PORTUGAL FOR USE IN SEISMIC HAZARD ANALYSIS

To estimate where future earthquakes are likely to occur, it is essential to combine information about past earthquakes with knowledge about the location and seismogenic properties of active faults. For this reason, robust probabilistic seismic hazard analysis (PSHA) integrates seismicity and active fault data. Existing seismic hazard assessments for Portugal rely exclusively on seismicity data and do not incorporate data on active faults. Project SHARE (Seismic Hazard Harmonization in Europe) is an EC-funded initiative (FP7) that aims to evaluate European seismic hazards using an integrated, standardized approach. In the context of SHARE, we are developing a fully-parameterized active fault database for Portugal that incorporates existing compilations, updated according to the most recent publications. The seismogenic source model derived for SHARE will be the first model for Portugal to include fault data and follow an internationally standardized approach. This model can be used to improve both seismic hazard and risk analyses and will be combined with the Spanish database for use in Iberian- and European-scale assessments

Effect of air pollution on diabetes and cardiovascular diseases in São Paulo, Brazil

Type 2 diabetes increases the risk of cardiovascular mortality and these patients, even without previous myocardial infarction, run the risk of fatal coronary heart disease similar to non-diabetic patients surviving myocardial infarction. There is evidence showing that particulate matter air pollution is associated with increases in cardiopulmonary morbidity and mortality. The present study was carried out to evaluate the effect of diabetes mellitus on the association of air pollution with cardiovascular emergency room visits in a tertiary referral hospital in the city of São Paulo. Using a time-series approach, and adopting generalized linear Poisson regression models, we assessed the effect of daily variations in PM10, CO, NO2, SO2, and O3 on the daily number of emergency room visits for cardiovascular diseases in diabetic and non-diabetic patients from 2001 to 2003. A semi-parametric smoother (natural spline) was adopted to control long-term trends, linear term seasonal usage and weather variables. In this period, 45,000 cardiovascular emergency room visits were registered. The observed increase in interquartile range within the 2-day moving average of 8.0 µg/m³ SO2 was associated with 7.0% (95%CI: 4.0-11.0) and 20.0% (95%CI: 5.0-44.0) increases in cardiovascular disease emergency room visits by non-diabetic and diabetic groups, respectively. These data indicate that air pollution causes an increase of cardiovascular emergency room visits, and that diabetic patients are extremely susceptible to the adverse effects of air pollution on their health conditions.Disciplina de Clínica Médica, Departamento de MedicinaUniversidade de São Paulo - Laboratório de Poluição Atmosférica Experimental, Faculdade de Medicina, USP (FM-USP

Big Data in Transfusion Medicine and Artificial Intelligence Analysis for Red Blood Cell Quality Control

peer reviewedBackground: ``Artificial intelligence'' and ``big data'' increasingly take the step from just being interesting concepts to being relevant or even part of our lives. This general statement holds also true for transfusion medicine. Besides all advancements in transfusion medicine, there is not yet an established red blood cell quality measure, which is generally applied. Summary: We highlight the usefulness of big data in transfusion medicine. Furthermore, we emphasize in the example of quality control of red blood cell units the application of artificial intelligence. Key Messages: A variety of concepts making use of big data and artificial intelligence are readily available but still await to be implemented into any clinical routine. For the quality control of red blood cell units, clinical validation is still required

Antiproliferative activity of synthetic fatty acid amides from renewable resources

AbstractIn the work, the in vitro antiproliferative activity of a series of synthetic fatty acid amides were investigated in seven cancer cell lines. The study revealed that most of the compounds showed antiproliferative activity against tested tumor cell lines, mainly on human glioma cells (U251) and human ovarian cancer cells with a multiple drug-resistant phenotype (NCI-ADR/RES). In addition, the fatty methyl benzylamide derived from ricinoleic acid (with the fatty acid obtained from castor oil, a renewable resource) showed a high selectivity with potent growth inhibition and cell death for the glioma cell line—the most aggressive CNS cancer

Incorporating Descriptive Metadata into Seismic Source Zone Models for Seismic Hazard Assessment: A case study of the Azores-West Iberian region

In probabilistic seismic-hazard analysis (PSHA), seismic source zone (SSZ) models are widely used to account for the contribution to the hazard from earth- quakes not directly correlated with geological structures. Notwithstanding the impact of SSZ models in PSHA, the theoretical framework underlying SSZ models and the criteria used to delineate the SSZs are seldom explicitly stated and suitably docu- mented. In this paper, we propose a methodological framework to develop and docu- ment SSZ models, which includes (1) an assessment of the appropriate scale and degree of stationarity, (2) an assessment of seismicity catalog completeness-related issues, and (3) an evaluation and credibility ranking of physical criteria used to delin- eate the boundaries of the SSZs. We also emphasize the need for SSZ models to be supported by a comprehensive set of metadata documenting both the unique character- istics of each SSZ and the criteria used to delineate its boundaries. This procedure ensures that the uncertainties in the model can be properly addressed in the PSHA and that the model can be easily updated whenever new data are available. The pro- posed methodology is illustrated using the SSZ model developed for the Azores–West Iberian region in the context of the Seismic Hazard Harmonization in Europe project (project SHARE) and some of the most relevant SSZs are discussed in detail

Compilation of parameterized seismogenic sources in Iberia for the SHARE European-scale seismic source model.

Abstract: SHARE (Seismic Hazard Harmonization in Europe) is an EC-funded project (FP7) that aims to evaluate European seismic hazards using an integrated, standardized approach. In the context of SHARE, we are compiling a fully-parameterized active fault database for Iberia and the nearby offshore region. The principal goal of this initiative is for fault sources in the Iberian region to be represented in SHARE and incorporated into the source model that will be used to produce seismic hazard maps at the European scale. The SHARE project relies heavily on input from many regional experts throughout the Euro-Mediterranean region. At the SHARE regional meeting for Iberia, the 2010 Working Group on Iberian Seismogenic Sources (WGISS) was established; these researchers are contributing to this large effort by providing their data to the Iberian regional integrators in a standardized format. The development of the SHARE Iberian active fault database is occurring in parallel with IBERFAULT, another ongoing effort to compile a database of active faults in the Iberian region. The SHARE Iberian active fault database synthesizes a wide range of geological and geophysical observations on active seismogenic sources, and incorporates existing compilations (e.g., Cabral, 1995; Silva et al., 2008), original data contributed directly from researchers, data compiled from the literature, parameters estimated using empirical and analytical relationships, and, where necessary, parameters derived using expert judgment. The Iberian seismogenic source model derived for SHARE will be the first regional-scale source model for Iberia that includes fault data and follows an internationally standardized approach (Basili et al., 2008; 2009). This model can be used in both seismic hazard and risk analyses and will be appropriate for use in Iberian- and European-scale assessments

Diversity and patterns of marine non‐native species in the archipelagos of Macaronesia

Aims The present study is the first attempt to grasp the scale and richness of marine biological invasions in Macaronesia. We pioneered a comprehensive non-native species (NNS), inventory in the region to determine their diversity patterns and native distribution origins. NNS were defined here as the result of both introductions and range expansions. We also used statistical modelling to examine relationships among NNS richness, anthropogenic activities, demographic and geographical variables across Macaronesia. Location Macaronesia. Methods A comprehensive literature search was conducted for marine NNS records in Macaronesia, registering the first record's location and year from 1884 to 2020. We used univariate and multivariate analyses to evaluate differences and similarities in community composition. By applying a Generalized Linear Model (GLM), we tested hypotheses regarding NNS richness as a function of anthropogenic activities, demographic and geographical variables. Results A total of 144 marine non-native species (NNS) were recorded for the whole of Macaronesia. The highest NNS richness was registered in the Canary Islands (76 NNS), followed by the Azores (66 NNS), Madeira (59 NNS) and finally Cabo Verde (18 NNS). Some differences amongst archipelagos were observed, such as the high number of non-native macroalgae in the Azores, fishes in the Canary Islands and tunicates in Cabo Verde. Overall, macroalgae, tunicates and bryozoans were the predominant taxonomic groups in the Macaronesian archipelagos. Madeira and Canary Islands were the archipelagos with more similarity in marine NNS, and Cabo Verde the most divergent. Finally, GLM suggested that non-native richness patterns across Macaronesia were dependent on the considered archipelago and strongly affected by (1) minimum distance to the mainland, (2) the total number of ports and marinas and (3) total marinas area (km2). Conclusions The model results and NNS listing in the present study will likely raise the awareness and response regarding marine NNS in the whole Macaronesia region, serving as a baseline for future research as well as implementing and enforcing regulations related to the introduction of marine NNS in oceanic islands