Accuracy and Uncertainty Analysis of Selected Methodological Approaches to Earthquake Early Warning in Europe

Earthquake early warning (EEW) is becoming an increasingly attractive real‐time strategy for mitigating the threats posed by potentially devastating incoming seismic events. As efforts accelerate to develop practical EEW‐based solutions for earthquake‐prone countries in Europe, it is important to understand and quantify the level of performance that can be achieved by the underlying seismological algorithms. We conduct a conceptual study on EEW performance in Europe, which explicitly focuses on the accuracy and associated uncertainties of selected methodological approaches. Twenty‐three events from four diverse European testbeds are used to compare the quality of EEW predictions produced by the Virtual Seismologist and PRobabilistic and Evolutionary early warning SysTem algorithms. We first examine the location and magnitude estimates of the algorithms, accounting for both bias and uncertainty in the resulting predictions. We then investigate the ground‐shaking prediction capabilities of the source‐parameter estimates, using an error metric that can explicitly capture the propagation of uncertainties in these estimates. Our work highlights the importance of accounting for EEW parameter uncertainties, which are often neglected in studies of EEW performance. Our findings can be used to inform current and future implementations of EEW systems in Europe. In addition, the evaluation metrics presented in this work can be used to determine EEW accuracy in any worldwide setting

Comparing the Performance of Regional Earthquake Early Warning Algorithms in Europe

Several earthquake early warning (EEW) algorithms have been developed worldwide for rapidly estimating real-time information (i.e., location, magnitude, ground shaking, and/or potential consequences) about ongoing seismic events. This study quantitatively compares the operational performance of two popular regional EEW algorithms for European conditions of seismicity and network configurations. We specifically test PRobabilistic and Evolutionary early warning SysTem (PRESTo) and the implementation of the Virtual Seismologist magnitude component within SeisComP, VS(SC), which we use jointly with the SeisComP scanloc module for locating events. We first evaluate the timeliness and accuracy of the location and magnitude estimates computed by both algorithms in real-time simulation mode, accounting for the continuous streaming of data and effective processing times. Then, we focus on the alert-triggering (decision-making) phase of EEW and investigate both algorithms’ ability to yield accurate ground-motion predictions at the various temporal instances that provide a range of warning times at target sites. We find that the two algorithms show comparable performances in terms of source parameters. In addition, PRESTo produces better rapid estimates of ground motion (i.e., those that facilitate the largest lead times); therefore, we conclude that PRESTo may have a greater risk-mitigation potential than VS(SC) in general. However, VS(SC) is the optimal choice of EEW algorithm if shorter warning times are permissible. The findings of this study can be used to inform current and future implementations of EEW systems in Europe

Assessing the potential implementation of earthquake early warning for schools in the Patras region, Greece

Earthquake early warning (EEW) is currently deemed a credible approach to seismic resilience enhancement in modern societies, especially if part of a more holistic earthquake mitigation strategy involving other risk reduction tools such as structural upgrading/retrofit. Yet, there remains a strong need to 1) assess the feasibility of EEW in various seismotectonic contexts, considering specific target applications/end users; and 2) develop next-generation decision-support systems relying on interpretable probabilistic impact-based estimates toward more risk-informed decision-making on EEW installation/alert triggering. These challenges are addressed in this paper, which showcases a series of recent significant EEW contributions by the authors. First, we present the results of a state-of-the-art feasibility study for EEW in schools performed across the Patras region of Greece, attempting to spatially combine traditional seismologically-driven EEW decision criteria (i.e., warning time) with proxy risk-oriented measures for earthquake impact (i.e., building fragility and the number of exposed school students). These results show that, under certain conditions, EEW could be effective for the schools in the considered case-study region. We then demonstrate an advanced end-user-centred approach for improved risk-informed decision-making on triggering EEW alerts. The proposed methodology integrates earthquake-engineering-related seismic performance assessment procedures and metrics with multi-criteria decision-making (MCDM) within an end-to-end probabilistic framework. The performance-based earthquake engineering component of such a framework facilitates the computation of various damage/loss estimates (e.g., repair cost, downtime, and casualties) by combining target-structure-specific models of seismic response, fragility, and vulnerability with real-time ground-shaking estimates. Additionally, the incorporated MCDM methodology enables explicit consideration of end-user preferences (importance) towards the estimated consequences in the context of alert issuance. The developed approach is demonstrated using an archetype school building for the case-study region, for which we specifically investigate the optimal decision (i.e., “trigger” or “don't trigger” an EEW alert) across a range of ground-motion intensity measures. We find that the best action for a given level of ground shaking can vary as a function of stakeholder preferences

Endangered shark species traded as “cação” in São Paulo during the COVID-19 lockdown: DNA-barcoding a snapshot of products

This is the final version. Available on open access from Springer via the DOI in this recordData availability: The data presented in this study are available in supplementary material submitted with this manuscript.Background Elasmobranch populations are declining, predominantly driven by overfishing, and over a third of global sharks, rays, and chimeras are estimated to be threatened with extinction. In terms of trade, Brazil is ranked the eleventh-largest shark producer and the top importer of shark meat in the world. Research has shown that elasmobranchs are sold in Brazil under the name “cação” (a generic designation for cartilaginous fish) to overcome consumer resistance. Methodology and results This study used DNA barcoding to investigate the sale of sharks in the State of São Paulo during the COVID-19 lockdown. A total of 35 samples of “cação” were analysed, revealing six different shark species on sale, including Carcharhinus falciformis, Carcharhinus signatus, Carcharias taurus, Isurus oxyrinchus, and Isurus paucus, that are threatened with extinction according to the IUCN red list. This study demonstrates that vulnerable elasmobranchs are being commercialised under the label “cação” in the São Paulo State and Brazil. Conclusions Comparison of shark products traded before and during the COVID-19 pandemic showed no significant difference, suggesting lockdown did not affect patterns of species commercialisation. Effective fisheries and sale monitoring, correct product labelling legislation and increased consumer awareness that “cação” is shark are needed for appropriate conservation and management of shark populations in Brazil.ExeterMarin

Prenatal smoking, alcohol and caffeine exposure and offspring externalizing disorders:a systematic review and meta-analysis

BACKGROUND AND AIMS: Several studies have indicated an association between maternal prenatal substance use and offspring externalizing disorders; however, it is uncertain whether this relationship is causal. We conducted a systematic review to determine: (1) if the literature supports a causal role of maternal prenatal substance use on offspring externalizing disorders diagnosis and (2) whether these associations differ across externalizing disorders. METHODS: We searched Web of Science, Embase, PsycINFO and Medline databases. Risk of bias assessment was conducted using the Newcastle-Ottawa Scale (NOS), and where possible meta-analysis was conducted for studies classed as low risk of bias. We included studies of any design that examined prenatal smoking, alcohol or caffeine use. Studies in non-English language, fetal alcohol syndrome and comorbid autism spectrum disorders were excluded. Participants in the included studies were mothers and their offspring. Measurements included prenatal smoking, alcohol or caffeine use as an exposure, and diagnosis of attention-deficit hyperactivity disorder (ADHD), conduct disorder (CD) and oppositional defiant disorder (ODD) in offspring as an outcome. RESULTS: We included 63 studies, 46 of which investigated smoking and ADHD. All studies were narratively synthesized, and seven studies on smoking and ADHD were meta-analysed. The largest meta-analysis based on genetically sensitive design included 1 011 546 participants and did not find evidence for an association [odds ratio (OR)  = 0.90, 95% confidence interval (CI) = 0.83-1.11; OR   = 1.04, 95% CI = 0.79-1.36). Studies on alcohol exposure in all the outcomes reported inconsistent findings and no strong conclusions on causality can be made. Studies on caffeine exposure were mainly limited to ADHD and these studies do not support a causal effect. CONCLUSIONS: There appears to be no clear evidence to support a causal relationship between maternal prenatal smoking and offspring attention-deficit hyperactivity disorder. Findings with alcohol and caffeine exposures and conduct disorder and oppositional-defiant disorder need more research, using more genetically sensitive designs

Maternal and child genetic liability for smoking and caffeine consumption and child mental health:An intergenerational genetic risk score analysis in the ALSPAC cohort

Background and aims: Previous studies suggest an association between maternal tobacco and caffeine consumption during and outside of pregnancy and offspring mental health. We aimed to separate effects of the maternal environment (intrauterine or postnatal) from pleiotropic genetic effects. Design: Secondary analysis of a longitudinal study. We (i) validated smoking and caffeine genetic risk scores (GRS) derived from published genome-wide association study (GWAS) for use during pregnancy, (ii) compared estimated effects of maternal and offspring GRS on childhood mental health outcomes and (iii) tested associations between maternal and offspring GRS on their respective outcomes. Setting: We used data from a longitudinal birth cohort study from England, the Avon Longitudinal Study of Parents and Children (ALSPAC). Participants: Our sample included 7921 mothers and 7964 offspring. Measurements: Mental health and non-mental health phenotypes were derived from questionnaires and clinical assessments: 79 maternal phenotypes assessed during and outside of pregnancy and 71 offspring phenotypes assessed in childhood (<10years) and adolescence (11–18years). Findings: The maternal smoking and caffeine GRS were associated with maternal smoking and caffeine consumption during pregnancy (2nd trimester: Psmoking=3.0 × 10−7, Pcaffeine=3.28 × 10−5). Both the maternal and offspring smoking GRS showed evidence of association with reduced childhood anxiety symptoms (βmaternal=−0.033; βoffspring=−0.031) and increased conduct disorder symptoms (βmaternal=0.024; βoffspring=0.030), after correcting for multiple testing. Finally, the maternal and offspring smoking GRS were associated with phenotypes related to sensation seeking behaviours in mothers and adolescence (e.g. increased symptoms of externalising disorders, extraversion and monotony avoidance). The caffeine GRS showed weaker evidence for associations with mental health outcomes. Conclusions: We did not find strong evidence that maternal smoking and caffeine genetic risk scores have a causal effect on offspring mental health outcomes. Our results confirm that the smoking genetic risk scores also captures liability for sensation seeking personality traits

Characterization of alcohol polygenic risk scores in the context of mental health outcomes:Within-individual and intergenerational analyses in the Avon Longitudinal Study of Parents and Children

Background: Heavy alcohol consumption often co-occurs with mental health problems; this could be due to confounding, shared biological mechanisms, or causal effects. Polygenic risk scores (PRS) for alcohol use can be used to explore this association at critical life stages. Design: We characterized a PRS reliably associated with patterns of adult alcohol consumption by 1) validating whether it predicts own alcohol use at different life-stages (pregnancy, adolescence) of interest for mental health impact. Additionally, we explored associations of alcohol PRS on mental health phenotypes 2) within-individuals (using own alcohol PRS on own phenotypes) and 3) intergenerationally (using maternal alcohol PRS on offspring phenotypes). We used data from the Avon Longitudinal Study of Parents and Children (ALSPAC) (n = 960–7841). Additional substance abuse behaviors and mental health/behavioral outcomes were investigated (alcohol phenotypes n = 22; health phenotypes n = 91). Findings: Maternal alcohol PRS was associated with consumption during pregnancy (strongest signal: alcohol frequency at 18 weeks’ gestation: β = 0.041, 95%CI = 0.0.02–0.06), p = 1.01 × 10−5, adjusted R2 = 1.6 %), offspring alcohol PRS did not predict offspring alcohol consumption. We found evidence for an association of maternal alcohol PRS with own perinatal depression (OR = 1.10, 95% CI = 1.02 to 1.18, p = 0.022) and decreased offspring intellectual ability (β=-0.209, 95% CI -0.38 to -0.04, p= 0.016). Conclusions: These alcohol PRS are a valid proxy for maternal alcohol use in pregnancy. Offspring alcohol PRS was not associated with drinking in adolescence. Consistently with results from different study designs, we found evidence that maternal alcohol PRS are associated with both prenatal depression and decreased offspring intellectual ability

Arachidonic acid-evoked Ca^{2+} signals promote nitric oxide release and proliferation in human endothelial colony forming cells

Arachidonic acid (AA) stimulates endothelial cell (EC) proliferation through an increase in intracellular Ca^{2+} concentration ([Ca^{2+}]_{i}), that, in turn, promotes nitric oxide (NO) release. AA-evoked Ca^{2+} signals are mainly mediated by Transient Receptor Potential Vanilloid 4 (TRPV4) channels. Circulating endothelial colony forming cells (ECFCs) represent the only established precursors of ECs. In the present study, we, therefore, sought to elucidate whether AA promotes human ECFC (hECFC) proliferation through an increase in [Ca^{2+}]_{i} and the following activation of the endothelial NO synthase (eNOS). AA induced a dose-dependent [Ca^{2+}]_{i} raise that was mimicked by its non-metabolizable analogue eicosatetraynoic acid. AA-evoked Ca^{2+} signals required both intracellular Ca^{2+} release and external Ca^{2+} inflow. AA-induced Ca^{2+} release was mediated by inositol-1,4,5-trisphosphate receptors from the endoplasmic reticulum and by two pore channel 1 from the acidic stores of the endolysosomal system. AA-evoked Ca^{2+} entry was, in turn, mediated by TRPV4, while it did not involve store-operated Ca^{2+} entry. Moreover, AA caused an increase in NO levels which was blocked by preventing the concomitant increase in [Ca^{2+}]_{i} and by inhibiting eNOS activity with NG-nitro-l-arginine methyl ester (l-NAME). Finally, AA per se did not stimulate hECFC growth, but potentiated growth factors-induced hECFC proliferation in a Ca^{2+} - and NO-dependent manner. Therefore, AA-evoked Ca^{2+} signals emerge as an additional target to prevent cancer vascularisation, which may be sustained by ECFC recruitment

The Amborella genome: an evolutionary reference for plant biology

The nuclear genome sequence of Amborella trichopoda, the sister species to all other extant angiosperms, will be an exceptional resource for plant genomics