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The purpose of this project is to investigate and solve the problem of sticking between die and sheet metal in a punch press. Initially, the problem was thought to be caused by high pressure, but lowering the pressure did not fix the problem. Further investigation revealed that the sticking was due to the magnetic properties of the die. demagnetizing the die with a demagnetizer has been found to be an effective solution. Another proposed solution is to apply a Tin coating to the die surface to prevent sticking. The aim of this project is to provide an effective solution to reduce sticking in punch presses.

We present our contribution to the UCIS4EQ (Urgent Computing Integrated Services for EarthQuakes) workflow, where multiple realizations of ground motion fields are required to account for input and model uncertainties under emergency conditions. Our focus is on the initialization and update of an ensemble of scenarios describing the seismic source uncertainty for Urgent Computing (UC) applications.We propose an algorithm to reduce the size of the ensemble for UC usability, such that source uncertainty can be propagated to shaking with numerical simulations of a subset of seismic sources while preserving the key statistical properties of the full ensemble. As target distribution representing the expected shaking variability in the earthquake-hit area, we use the distribution of PGA (Peak Ground Acceleration) values predicted by local GMPEs (Ground Motion Prediction Equations) for the seismic scenarios in the full ensemble. Besides accounting for source uncertainty, our approach estimates the uncertainty associated with the ensemble sampling method and available GMPEs. By sampling an increasing number of seismic scenarios from the full ensemble, the algorithm estimates the total variability of the subsample and assesses its convergence to the target distribution.Besides reducing the time and cost of shaking scenarios simulations, it also enables the retrieval of probabilistic shakemaps, an evolved version of the traditional shakemaps where each POI (Point Of Interest) is assigned a probability distribution of PGA values quantifying both the source and GMPEs uncertainty.Our algorithm is written in Python and makes use of OpenQuake and Shakemap libraries., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

Volcanic and non-volcanic gas emission represent a widespread and frequent hazard. In fact, some gas species (e.g., CO2, H2S, SO2) can affect human health and even threaten life at concentrations and doses above species-specific thresholds. Depending on the starting buoyancy relative to the surrounding atmosphere at the emission location, gas emissions can be classified as dilute passive degassing (e.g. fumaroles) and dense gas flow (e.g., cold CO2 accumulation and flows onto the ground).Here we present the latest version of VIGIL (automatic probabilistic VolcanIc Gas dIspersion modeLling), a Python simulation tool capable of handling the complex and time-consuming gas dispersion simulation workflow and interfaced with two dispersion models: a dilute (DISGAS) and a dense gas (TWODEE-2) dispersion model. VIGIL allows exploring the uncertainty of the meteorological conditions and gas emission location and strength. The post-processing script offers the option to create Empirical Cumulative Distribution Functions (ECDF) of the gas concentrations combining the outputs of multiple simulations. The ECDF can be interrogated by the user to produce maps of gas concentration at specified exceedance probabilities. Tracking points can also be used to produce time series of gas concentration at selected locations and hazard curves if ECDF is produced. Furthermore, the new gas persistence calculation capability creates maps of the probability to overcome specified gas specie-specific concentration thresholds over specified durations. We also present results from applications at different volcanically and tectonically active areas showcasing the various capabilities of VIGIL., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

Probabilistic hazard assessments of volcanic gases need to account for the natural variability associated to aspects such as weather conditions, source location, emission rate, and gas species. In order to quantitatively carry out these assessments, computational tools for gas dispersal need to be validated to demonstrate the reliability of the model results. Here we provide an exemplificative gas dispersal model validation at La Solfatara (a maar crater within Campi Flegrei caldera) which hosts one of the largest and hazardous fumarolic sites of the world, by using a workflow designed for automating the simulation strategy for probabilistic gas hazard assessments. This represents the first fundamental step towards gas hazard quantification in the area.

The aim of this study was to evaluate the trough concentrations (Cp trough ) and the tacrolimus dosage regimen after the conversion of Prograf or Advagraf to Envarsus (new pharmaceutical form with MeltDose technology that improves the absorption of fat-soluble drugs) in patients with stable renal transplantation, and their renal function. We selected stable renal transplant patients who were converted to Envarsus. Two periods were defined: Baseline and Conversion (Envarsus) and they were stratified according to the pharmaceutical form used in the Baseline period. Sixty-one patients were included (24 with Advagraf and 37 with Prograf), with an average age of 52years. The mean post-transplant time at the time of conversion to Envarsus was 76.3months and the mean follow-up in the Baseline and Conversion period was 10.1months and 11.6months, respectively. In the Prograf and Envarsus group, the Cp trough medians were 6.6 vs 6.4 ng/mL (P=.636), with a mean daily dose that decreased significantly from 3mg to 2mg (P

In this paper we explore the feasibility of formulating the hazard assessment procedure to include the information of past earthquakes into the probabilistic seismic hazard analysis, together with the use of an ensemble modeling technique. This strategy allows, on the one hand, to enlarge the information used in the evaluation of the hazard, from alternative models for the earthquake generation process to past shaking and, on the other hand, to explicitly account for the uncertainties. The Bayesian scheme we propose is applied to evaluate the seismic hazard of Naples. The framework in which we have embedded the tools is flexible to include all types of uncertainties. Here we focus on a sensitive study of the earthquake occurrence by implementing models that span from random to cluster-type temporal behavior and models that include quasiperiodic occurrence of earthquakes on faults. We implement five different spatiotemporal models to parameterize the occurrence of earthquakes potentially dangerous for Naples. Subsequently, we combine these hazard curves with ShakeMaps of past earthquakes that have been felt in Naples since 1200 A.D. The results are posterior ensemble hazard curves for three exposure times, e.g., 5, 10, and 50 years, in a dense grid that covers the municipality of Naples, considering rocky soil and including the site amplification. Our results show the importance to include the data from past shaking since the difference between the prior and the posterior is about 8–15% for the different exposure times.

Probabilistic Volcanic Hazard Assessment (PVHA) is the most complete scientific contribution for planning rational strategies aimed at mitigating the risk posed by volcanic activity at different time scales. The definition of the space-time window for PVHA is related to the kind of risk mitigation actions that are under consideration. During volcanic unrest episodes or eruptions, short-term PVHA is essential for crisis management, since tephra may heavily affect building stability, public health, transportations and evacuation routes (airports, trains, road traffic), and lifelines (electric power supply). In this study, we propose a new methodology for the short-term PVHA based on the Bayesian Event Tree model, in which measures from the monitoring system are used to routinely update the probabilities of ash fall loading in the surroundings of the volcano. As an example, we apply this procedure to the 1982-1984 volcanic unrest at Campi Flegrei, Italy. © 2015 Elsevier Inc. All rights reserved.

In this paper, we present a wideband subspace estimation method that characterizes the signal subspace through its orthogonal projection matrix at each frequency. Fundamentally, the method models this projection matrix as a function of frequency that can be approximated by a polynomial. It provides two improvements: a reduction in the number of parameters required to represent the signal subspace along a given frequency band and a quality improvement in wideband direction-of-arrival (DOA) estimators such as Incoherent Multiple Signal Classification (IC-MUSIC) and Modified Test of Orthogonality of Projected Subspaces (MTOPS). In rough terms, the method fits a polynomial to a set of projection matrix estimates, obtained at a set of frequencies, and then uses the polynomial as a representation of the signal subspace. The paper includes the derivation of asymptotic bounds for the bias and root-mean-square (RMS) error of the projection matrix estimate and a numerical assessment of the method and its combination with the previous two DOA estimators., Comment: Submitted to the IEEE Transactions on Signal Processing

Contents: Preface Introduction: making an invisible diaspora visible, Knut A. Jacobsen and Selva J. Raj Part 1 Europe: South Asian Christians in the UK, Eleanor Nesbitt Religion as an arena for the expression of identity. Roman Catholic Pondicherrians in France, Brigitte SA(c)bastia The 70th anniversary of 'John Matthew': on 'Indian Christians in Germany, Urmila Goel Seeking the blessing of the consolatrix afflictorum: the annual pilgrimage of Sri Lankan Tamils to the Madonna in Kevelaer (Germany), Brigitte Luchesi Perpetuating religious and social concepts in the extended motherland: Tamil Christians in Berne (Switzerland), Damaris LA thi Creating Sri Lankan Tamil Catholic space in the South Asian diaspora in Norway, Knut A. Jacobsen Goans and Damanians in Portugal: an overview of a singular diaspora, Helena Maria Mauricio C. Sant'ana Surinamese East Indian Christians in the Netherlands, Freek L. Bakker. Part 2 North America: The culture of Asian Indian Catholicism in North America, Elizabeth Cameron Galbraith New land, new challenges: the role of religion in the acculturation of Syro-Malabar Catholics in Chicago, Selva J. Raj Indian Christians and marriage patterns Farha Terniker Doing friendship, making contacts, and building trust: Christian Indian responses to religious diversity, Nori Henk From Hinduism to Christianity, from India to New York: bondage and exodus experiences in the lives of Indian Dalit Christians in the diaspora, Rachel Fell McDermott Conclusion: South Asian Christians in the West, Raymond Brady Williams Index.

The author explores his transformation from religious practitioner to ethnographer and the responses he received from academic colleagues, religious colleagues, and laypeople and the ethical challenges such responses posed. He then suggests that the scholar's performance of ethnography can be understood through a classical Hindu schema of the life cycle.

The so-called non-uniform FFT (NFFT) is a family of algorithms for efficiently computing the Fourier transform of finite-length signals, whenever the time or frequency grid is nonuniformly spaced. Following the usual classification, there exist five NFFT types. Types 1 and 2 make it possible to pass from the time to the frequency domain with nonuniform input and output grids respectively. Type 3 allows for both input and output nonuniform grids. Finally, types 4 and 5 are the inverses of types 1 and 2 and are expensive computationally, given that they involve iterative methods. In this paper, we solve this last drawback in the one-dimensional case by presenting non-iterative type 4 and 5 NFFT methods that just involve three NFFTs of types 1 or 2 plus some additional FFTs. The methods are based on exploiting the structure of the Lagrange interpolation formula. The paper includes several numerical examples in which the proposed methods are compared with the Gaussian elimination (GE) and conjugate gradient (CG) methods, both in terms of round-off error and computational burden., Comment: Submitted to the IEEE Trans. on Signal Processing

Widening the scope of human rights to specifically address the needs and interests of women is a relatively new tradition in the long-standing philosophical treatment of human rights. Feminists hav...

Introduction: In a Shared World - Selva J. Raj and the Study of Religion Karen Pechilis 1. Tribal Religions in India: Practicing Tradition Today Joseph Marianus Kujur 2. Hinduism: Practicing Tradition Today Vasudha Narayanan 3. Jain Traditions: Practicing Tradition Today M. Whitney Kelting 4. Buddhism in South Asia: Practicing Tradition Today Sunil Goonasekera 5. South Asian Judaisms: Practicing Tradition Today Nathan Katz 6. South Asian Christianity: Practicing Tradition Today M. Thomas Thangaraj 7. Islam in South Asia: Practicing Tradition Today Karen G. Ruffle 8. Sikhism: Practicing Tradition Today Pashaura Singh

No systematic review is available on studies conducted in Spain on human concentrations of persistent toxic substances (PTS). The objectives were: to identify studies conducted in Spain in the past 30 years that determined concentrations in humans of dichlorodiphenyltrichloroethane (DDT), dichlorodiphenyldichloroethane (DDE), hexachlorobenzene (HCB), hexachlorocyclohexane, (HCH) and polychlorinated biphenyls (PCBs); and to summarize the main characteristics and results of each study. Studies are highly heterogeneous and most lack population representativeness. Concentrations of DDT and DDE might have decreased moderately in the last 20 years. Numerous fluctuations are apparent in levels of HCB, HCHs and PCBs, in some instances compatible with some stagnation. There are enormous differences in levels detected across and within studies: PTS concentrations of some individuals may be over 200-fold higher than those of others. The actual magnitude of human contamination by PTS and their trends across Spain -as well as the geographic and social heterogeneity- remain largely unknown.

Assessing the adverse effects on human health of persistent organic pollutants (POPs) and the impact of policies aiming to reduce human exposure to POPs warrants monitoring body concentrations of POPs in representative samples of subjects. While numerous ad hoc studies are being conducted to understand POPs effects, only a few countries are conducting nationwide surveillance programs of human concentrations of POPs, and even less countries do so in representative samples of the general population. We tried to identify all studies worldwide that analyzed the distribution of concentrations of POPs in a representative sample of the general population, and we synthesized the studies' main characteristics, as design, population, and chemicals analyzed. The most comprehensive studies are the National Reports on Human Exposure to Environmental Chemicals (USA), the German Environmental Survey, and the Arctic Monitoring and Assessment Programme. Population-wide studies exist as well in New Zealand, Australia, Japan, Flanders (Belgium) and die Canary Islands (Spain). Most such studies are linked with health surveys, which is a highly-relevant additional strength. Only the German and Flemish studies analyzed POPs by educational level, while studies in the USA offer results by ethnic group. The full distribution of POPs concentrations is unknown in many countries. Knowledge gaps include also the interplay of age, gender, period and cohort effects on the prevalence of exposures observed by cross-sectional surveys. Local and global efforts to minimize POPs contamination, like the Stockholm convention, warrant nationwide monitoring of concentrations of POPs in representative samples of the general population. Results of this review show how such studies may be developed and used. (C) 2007 Elsevier Ltd. All rights reserved.

After a brief discussion of Hindu views on abortion as reflected in classical Hindu philosophical and religious texts, this article examines, from an interdisciplinary perspective, current social attitudes towards abortion among lower-income Hindu women in Calcutta and attempts to identify the reasons for the striking disparity between traditional and modern Hindu views. Does Hindu dharma have the regulatory power it wielded in the past? What accounts for the changing face of mores in urban centers like Calcutta? These and related issues are the focus of this essay.

Critical infrastructures are the backbone of modern society and provide many essential goods and services to urban areas. Given the risks associated with the impact of natural hazards on critical infrastructures, the move towards safer and more resilient cities requires the development and application of an improved risk assessment framework to address high-impact and low-probability events. In this context, the STREST project developed a stress test framework to determine the risk and resilience of non-nuclear critical infrastructures. In addition, the project developed a consistent modelling approach to hazard, vulnerability, risk and resilience assessment of low-probability and high-consequence events, considering relevant epistemic uncertainties and interdependencies of critical infrastructures. Six key representative critical infrastructures in Europe were selected for exploratory application of the stress test methodology.

The main purpose of this article is to emphasize the importance of clarifying the probabilistic framework adopted for volcanic hazard and eruption forecasting. Eruption forecasting and volcanic hazard analysis seeks to quantify the deep uncertainties that pervade the modeling of pre-, sin- and post-eruptive processes. These uncertainties can be differentiated into three fundamental types: (1) the natural variability of volcanic systems, usually represented as stochastic processes with parameterized distributions (aleatory variability); (2) the uncertainty in our knowledge of how volcanic systems operate and evolve, often represented as subjective probabilities based on expert opinion (epistemic uncertainty); and (3) the possibility that our forecasts are wrong owing to behaviors of volcanic processes about which we are completely ignorant and, hence, cannot quantify in terms of probabilities (ontological error). Here we put forward a probabilistic framework for hazard analysis recently proposed by Marzocchi & Jordan (2014), which unifies the treatment of all three types of uncertainty. Within this framework, an eruption forecasting or a volcanic hazard model is said to be complete only if it (a) fully characterizes the epistemic uncertainties in the model's representation of aleatory variability and (b) can be unconditionally tested (in principle) against observations to identify ontological errors. Unconditional testability, which is the key to model validation, hinges on an experimental concept that characterizes hazard events in terms of exchangeable data sequences with well-defined frequencies. We illustrate the application of this unified probabilistic framework by describing experimental concepts for the forecasting of tephra fall from Campi Flegrei. Eventually, this example may serve as a guide for the application of the same probabilistic framework to other natural hazards.

Earthquake occurrence stems from a complex interaction of processes that are still partially unknown. This lack of knowledge is revealed by the different statistical distributions that have been so far proposed and by the different beliefs about the role of some key components as the tectonic setting, fault recurrence, seismic clusters, and fault interaction. Here, we explore these issues through a numerical model based on a realistic interacting fault system. We use an active fault system in central Italy responsible for moderate to large earthquakes, where geometric and kinematic parameters of each structure can be confidently assessed. Then, we generate synthetic catalogs by modeling different seismogenic processes and allowing coseismic and postseismic fault interaction. The comparison of synthetic and real seismic catalogs highlights many interesting features: (1) synthetic seismic catalogs reproduce the short-term clustering and the long-term modulation observed in the historical catalog of the last centuries; (2) a recurrent model of earthquake occurrence on faults is more effective than a Poisson model to explain such short-term and long-term time features; (3) a realistic fault pattern is a key component to generate stochasticity in the seismic catalog, preventing a systematic time "synchronization" of strongly coupled faults; (4) such a stochasticity may put strong limits to the forecasting capability of models based on fault interaction, even though the latter is a key component of the process. Finally, the model allows explicit predictions on future paleoseismological observations to be made. Copyright 2009 by the American Geophysical Union.

Recent natural disasters that seriously affected critical infrastructure (CI) with significant socio-economic losses and impact revealed the need for the development of reliable methodologies for vulnerability and risk assessment. In this paper, a risk-based multi-level stress test method that has been recently proposed, aimed at enhancing procedures for evaluation of the risk of critical non-nuclear infrastructure systems against natural hazards, is specified and applied to six key representative CIs in Europe, exposed to variant hazards. The following CIs are considered: an oil refinery and petrochemical plant in Milazzo, Italy, a conceptual alpine earth-fill dam in Switzerland, the Baku–Tbilisi–Ceyhan pipeline in Turkey, part of the Gasunie national gas storage and distribution network in the Netherlands, the port infrastructure of Thessaloniki, Greece, and an industrial district in the region of Tuscany, Italy. The six case studies are presented following the workflow of the stress test framework comprised of four phases: pre-assessment phase, assessment phase, decision phase and report phase. First, the goals, the method, the time frame and the appropriate stress test level to apply are defined. Then, the stress test is performed at component and system levels and the outcomes are checked and compared to risk acceptance criteria. A stress test grade is assigned, and the global outcome is determined by employing a grading system. Finally, critical components and events and risk mitigation strategies are formulated and reported to stakeholders and authorities. © 2019, Springer Nature B.V.

The NEAM Tsunami Hazard Model 2018 (NEAMTHM18) is a probabilistic hazard model for tsunamis generated by earthquakes. It covers the coastlines of the North-eastern Atlantic, the Mediterranean, and connected seas (NEAM). NEAMTHM18 was designed as a three-phase project. The first two phases were dedicated to the model development and hazard calculations, following a formalized decision-making process based on a multiple-expert protocol. The third phase was dedicated to documentation and dissemination. The hazard assessment workflow was structured in Steps and Levels. There are four Steps: Step-1) probabilistic earthquake model; Step-2) tsunami generation and modeling in deep water; Step-3) shoaling and inundation; Step-4) hazard aggregation and uncertainty quantification. Each Step includes a different number of Levels. Level-0 always describes the input data; the other Levels describe the intermediate results needed to proceed from one Step to another. Alternative datasets and models were considered in the implementation. The epistemic hazard uncertainty was quantified through an ensemble modeling technique accounting for alternative models’ weights and yielding a distribution of hazard curves represented by the mean and various percentiles. Hazard curves were calculated at 2,343 Points of Interest (POI) distributed at an average spacing of ∼20 km. Precalculated probability maps for five maximum inundation heights (MIH) and hazard intensity maps for five average return periods (ARP) were produced from hazard curves. In the entire NEAM Region, MIHs of several meters are rare but not impossible. Considering a 2% probability of exceedance in 50 years (ARP≈2,475 years), the POIs with MIH >5 m are fewer than 1% and are all in the Mediterranean on Libya, Egypt, Cyprus, and Greece coasts. In the North-East Atlantic, POIs with MIH >3 m are on the coasts of Mauritania and Gulf of Cadiz. Overall, 30% of the POIs have MIH >1 m. NEAMTHM18 results and documentation are available through the TSUMAPS-NEAM project website (http://www.tsumaps-neam.eu/), featuring an interactive web mapper. Although the NEAMTHM18 cannot substitute in-depth analyses at local scales, it represents the first action to start local and more detailed hazard and risk assessments and contributes to designing evacuation maps for tsunami early warning.

Probabilistic Tsunami Hazard Analysis (PTHA) quantifies the probability of exceeding a specified inundation intensity at a given location within a given time interval. PTHA provides scientific guidance for tsunami risk analysis and risk management, including coastal planning and early warning. Explicit computation of site-specific PTHA, with an adequate discretization of source scenarios combined with high-resolution numerical inundation modelling, has been out of reach with existing models and computing capabilities, with tens to hundreds of thousands of moderately intensive numerical simulations being required for exhaustive uncertainty quantification. In recent years, more efficient GPU-based High-Performance Computing (HPC) facilities, together with efficient GPU-optimized shallow water type models for simulating tsunami inundation, have now made local long-term hazard assessment feasible. A workflow has been developed with three main stages: 1) Site-specific source selection and discretization, 2) Efficient numerical inundation simulation for each scenario using the GPU-based Tsunami-HySEA numerical tsunami propagation and inundation model using a system of nested topo-bathymetric grids, and 3) Hazard aggregation. We apply this site-specific PTHA workflow here to Catania, Sicily, for tsunamigenic earthquake sources in the Mediterranean. We illustrate the workflows of the PTHA as implemented for High-Performance Computing applications, including preliminary simulations carried out on intermediate scale GPU clusters. We show how the local hazard analysis conducted here produces a more fine-grained assessment than is possible with a regional assessment. However, the new local PTHA indicates somewhat lower probabilities of exceedance for higher maximum inundation heights than the available regional PTHA. The local hazard analysis takes into account small-scale tsunami inundation features and non-linearity which the regional-scale assessment does not incorporate. However, the deterministic inundation simulations neglect some uncertainties stemming from the simplified source treatment and tsunami modelling that are embedded in the regional stochastic approach to inundation height estimation. Further research is needed to quantify the uncertainty associated with numerical inundation modelling and to properly propagate it onto the hazard results, to fully exploit the potential of site-specific hazard assessment based on massive simulations.

Regional and global tsunami hazard analysis requires simplified and efficient methods for estimating the tsunami inundation height and its related uncertainty. One such approach is the amplification factor (AF) method. Amplification factors describe the relation between offshore wave height and the maximum inundation height, as predicted by linearized plane wave models employed for incident waves with different wave characteristics. In this study, a new amplification factor method is developed that takes into account the offshore bathymetry proximal to the coastal site. The present AFs cover the North-Eastern Atlantic and Mediterranean (NEAM) region. The model is the first general approximate model that quantifies inundation height uncertainty. Uncertainty quantification is carried out by analyzing the inundation height variability in more than 500 high-resolution inundation simulations at six different coastal sites. The inundation simulations are undertaken with different earthquake sources in order to produce different wave period and polarity. We show that the probability density of the maximum inundation height can be modeled with a log-normal distribution, whose median is quite well predicted by the AF. It is further demonstrated that the associated maximum inundation height uncertainties are significant and must be accounted for in tsunami hazard analysis. The application to the recently developed TSUMAPS-NEAM probabilistic tsunami hazard analysis (PTHA) is presented as a use case.

We present the results of a statistical study on tephra dispersal in the case of a reactivation of the Campi Flegrei volcano. To represent the spectrum of possible eruptive sizes, four classes of eruptions were considered. Excluding the lava emission, three classes are explosive (Small, Medium, and Large) and can produce a significant quantity of volcanic ash. Hazard assessments were made through simulations of atmospheric dispersion of ash and lapilli, considering the full variability of winds and eruptive vents. The results are presented in form of conditional hazard curves given the occurrence of specific eruptive sizes, representative members of each size class, and then combined to quantify the conditional hazard given an eruption of any size. The main focus of this analysis was to constrain the epistemic uncertainty (i.e. associated with the level of scientific knowledge of phenomena), in order to provide unbiased hazard estimations. The epistemic uncertainty on the estimation of hazard curves was quantified, making use of scientifically acceptable alternatives to be aggregated in the final results. The choice of such alternative models was made after a comprehensive sensitivity analysis which considered different weather databases, alternative modelling of submarine eruptive vents and tephra total grain-size distributions (TGSD) with a different relative mass fraction of fine ash, and the effect of ash aggregation. The results showed that the dominant uncertainty is related to the combined effect of the uncertainty with regard to the fraction of fine particles with respect to the total mass and on how ash aggregation is modelled. The latter is particularly relevant in the case of magma-water interactions during explosive eruptive phases, when a large fraction of fine ash can form accretionary lapilli that might contribute significantly in increasing the tephra load in the proximal areas. The variability induced by the use of different meteorological databases and the selected approach to modelling offshore eruptions were relatively insignificant. The uncertainty arising from the alternative implementations, which would have been neglected in standard (Bayesian) quantifications, were finally quantified by ensemble modelling, and represented by hazard and probability maps produced at different confidence levels.

Massive emissions of deep CO2 coupled to the 2009–2018 Central Italy earthquakes., Deep CO2 emissions characterize many nonvolcanic, seismically active regions worldwide, and the involvement of deep CO2 in the earthquake cycle is now generally recognized. However, no long-time records of such emissions have been published, and the temporal relations between earthquake occurrence and tectonic CO2 release remain enigmatic. Here, we report a 10-year record (2009–2018) of tectonic CO2 flux in the Apennines (Italy) during intense seismicity. The gas emission correlates with the evolution of the seismic sequences: Peaks in the deep CO2 flux are observed in periods of high seismicity and decays as the energy and number of earthquakes decrease. We propose that the evolution of seismicity is modulated by the ascent of CO2 accumulated in crustal reservoirs and originating from the melting of subducted carbonates. This large-scale, continuous process of CO2 production favors the formation of overpressurized CO2-rich reservoirs potentially able to trigger earthquakes at crustal depth.

Volcanic islands pose several major types of natural hazards, often interconnected and concentrated in relatively small areas. The quantification of these hazards must be framed from a multi-hazard perspective whilst building on existing single-hazard analyses. Ischia is a densely inhabited volcanic island with a long eruptive history lasting more than 150 ka (last in 1302 AD) characterized by the significant asymmetric resurgence of a caldera block. Here, we review the state-of-art of the natural hazards of Ischia, aiming at building a solid base for future holistic multi-hazard quantifications. We frame our analysis in three steps: i) review of geological, historical and current activity; ii) review of available hazard models and analyses; iii) development of an interpretative framework for the interdependent hazards. The results highlight that volcanic activity has been quite intense and many volcano-related hazardous phenomena have affected the island including in very recent times, both for eruptive (phreatic or magmatic eruptions) and non-eruptive (earthquakes, landslides, and tsunamis) phenomena. The effects of some of them (e.g. tsunamis, tephra) are also relevant beyond the island territory. Quantitative hazard assessments are almost absent and should be developed in the future considering the evident interconnections between hazards. To this end, we propose a conceptual interpretative multi-hazard framework that highlights the fundamental role played by the resurgent block in controlling and connecting the different hazards, in terms of both spatial distribution of the sources and temporal clustering.

Transportation infrastructures are complex systems of various connected components like bridges, roads, tunnels, embankments, retaining walls in case of a highway system or wharfs, cranes, buildings, utility systems in case of port facilities. Due to their spatial extent, they are exposed to variable natural hazards such as earthquakes, tsunami or landslides. Experience from past disastrous events shows that transportation infrastructures are quite vulnerable due to the lack of redundancy, the lengthy repair time, the rerouting difficulties or the cascading failures and interdependencies. Their damage could be greatly disruptive in terms of safety of life, business disruption, access to emergency services and key lifelines utilities, rescue operations and socio-economic impacts. Therefore, in terms of resilience it is important to recognize and quantify the risks and global losses associated to damages of transportation systems and to establish efficient risk mitigation strategies. These include, among others, enhancement of emergency preparedness, strengthening of existing structures and improvement of the recovery planning. Herein an integrated framework for the probabilistic systemic vulnerability and risk assessment of transportation and utility networks is presented, based on the achievements of the recently completed EC project SYNER-G (www.syner-g.eu) and the ongoing EC project STREST (www.strest-eu.org). The infrastructure is modeled according to a detailed taxonomy. The framework encompasses in an integrated fashion all aspects in the chain, from regional hazard to fragility assessment of components to the socio-economic impacts of a natural disaster, accounting for relevant uncertainties within an efficient quantitative simulation scheme, and modeling interactions between multiple component systems in the taxonomy. Selected Performance Indicators (PIs) are calculated for each network based on the estimated damages and functionality losses of the different components under the given hazards. The methodology and tools are demonstrated through case studies in the road network and the harbor of Thessaloniki city, Greece, under seismic hazard and associated geotechnical hazards (i.e. soil liquefaction). The applications include assessments of systems' performance considering the spatial seismic hazard with correlation of ground motion intensities, the vulnerability of the network components, and the effect of interactions within the system, as well as, between components of different systems. In particular, road disruptions can be caused due to direct damage of road segments and bridges, as well as building and overpass collapses. Harbor operations can be disturbed due to failures of waterfront structures and cargo handling equipment, as well as disruptions to the electric power supply and building collapses. The systemic risk for the road network and harbor is calculated, specifically focusing on the short-term impact of seismic events (just after the earthquake) and the risk curves (i.e. mean annual rates of exceedance for loss in performance of the infrastructures) are provided. The significant elements for the functionality of each system are defined through correlation factors to the system PIs. Such results can contribute to the decision-making regarding the enhancement of existing and the robust development of new infrastructures in the frame of safety and resiliency. Language: en

Any trustworthy probabilistic seismic-hazard analysis (PSHA) has to account for the intrinsic variability of the system (aleatory variability) and the limited knowledge of the system itself (epistemic uncertainty). The most popular framework for this purpose is the logic tree. Notwithstanding its vast popularity, the logic-tree outcomes are still interpreted in two different and irreconcilable ways. In one case, practitioners claim that the mean hazard of the logic tree is the hazard and the distribution of all outcomes does not have any probabilistic meaning. On the other hand, other practitioners describe the seismic hazard using the distribution of all logic-tree outcomes. In this article, we explore in detail the reasons for this controversy regarding the interpretation of logic tree, showing that the distribution of all outcomes is more appropriate to provide a joined, full description of aleatory variability and epistemic uncertainty. Then, we provide a more general framework, that we call ensemble modeling, in which the logic-tree outcomes can be embedded. In this framework, the logic tree is not a classical probability tree, but it is just a technical tool that samples epistemic uncertainty. Ensemble modeling consists of inferring the parent distribution of the epistemic uncertainty from which this sample is drawn. Ensemble modeling offers some remarkable additional features. First, it allows a rigorous and meaningful validation of any PSHA; this is essential if we want to keep PSHA within the scientific domain. Second, it provides a proper and clear description of the aleatory variability and epistemic uncertainty that can help stakeholders appreciate the whole range of uncertainties in PSHA. Third, it may help to reduce the computational timewhen the logic tree becomes computationally intractable because of too many branches. © 2015, Seismological Society of America. All rights reserved.

During volcanic crises, volcanologists estimate the impact of possible imminent eruptions usually through deterministic modeling of the effects of one or a few preestablished scenarios. Despite such an approach may bring an important information to the decision makers, the sole use of deterministic scenarios does not allow scientists to properly take into consideration all uncertainties, and it cannot be used to assess quantitatively the risk because the latter unavoidably requires a probabilistic approach. We present a model based on the concept of Bayesian event tree (hereinafter named BET-VH-ST, standing for Bayesian event tree for short-term volcanic hazard), for short-term near-real-time probabilistic volcanic hazard analysis formulated for any potential hazardous phenomenon accompanying an eruption. The specific goal of BET-VH-ST is to produce a quantitative assessment of the probability of exceedance of any potential level of intensity for a given volcanic hazard due to eruptions within restricted time windows (hours to days) in any area surrounding the volcano, accounting for all natural and epistemic uncertainties. BET-VH-ST properly assesses the conditional probability at each level of the event tree accounting for any relevant information derived from the monitoring system, theoretical models, and the past history of the volcano, propagating any relevant epistemic uncertainty underlying these assessments. As an application example of the model, we apply BET-VH-ST to assess short-term volcanic hazard related to tephra loading during Major Emergency Simulation Exercise, a major exercise at Mount Vesuvius that took place from 19 to 23 October 2006, consisting in a blind simulation of Vesuvius reactivation, from the early warning phase up to the final eruption, including the evacuation of a sample of about 2000 people from the area at risk. The results show that BET-VH-ST is able to produce short-term forecasts of the impact of tephra fall during a rapidly evolving crisis, accurately accounting for and propagating all uncertainties and enabling rational decision making under uncertainty. ©2014. American Geophysical Union. All Rights Reserved.

The societal importance and implications of seismic‐hazard assessment forces the scientific community to pay increasing attention to the evaluation of uncertainty in order to provide accurate assessments. Probabilistic seismic hazard assessment (PSHA) formally accounts for the natural variability of the involved phenomena, from seismic sources to wave propagation. Recently, increased attention has been paid to the consequences of alternative modeling procedures on hazard results. This uncertainty, essentially of epistemic nature, has been shown to have major impacts on PSHA results, leading to extensive applications of techniques like the logic tree. Here, we develop a formal Bayesian inference scheme for PSHA that allows us, on the one hand, to explicitly account for all uncertainties and, on the other hand, to consider a larger set of sources of information, from heterogeneous models to past data. This process decreases the chance of undesirable biases and leads to a controlled increase of the precision of the probabilistic assessment. In addition, the proposed Bayesian scheme allows (1) the assignment of a subjective reliability to single models, without requirement of completeness or homogeneity, and (2) a transparent and uniform evaluation of the strength of each piece of information used on the final results. The applicability of the method is demonstrated through the assessment of seismic hazard in the Emilia–Romagna region of northern Italy. In this application the results of a traditional Cornell–McGuire hazard model based on a logic tree are updated with the historical macroseismic records to provide a unified assessment that accounts for both sources of information.

We present the realization of a fault-source data set designed to become the starting point in regional-scale tsunami hazard studies. Our approach focuses on the parametric fault characterization in terms of geometry, kinematics, and assessment of activity rates, and includes a systematic classification in six justification levels of epistemic uncertainty related with the existence and behaviour of fault sources. We set up a case study in the central Mediterranean Sea, an area at the intersection of the European, African, and Aegean plates, characterized by a complex and debated tectonic structure and where several tsunamis occurred in the past. Using tsunami scenarios of maximum wave height due to crustal earthquakes (Mw=7) and subduction earthquakes (Mw=7 and Mw=8), we illustrate first-order consequences of critical choices in addressing the seismogenic and tsunamigenic potentials of fault sources. Although tsunamis generated by Mw=8 earthquakes predictably affect the entire basin, the impact of tsunamis generated by Mw=7 earthquakes on either crustal or subduction fault sources can still be strong at many locales. Such scenarios show how the relative location/orientation of faults with respect to target coastlines coupled with bathymetric features suggest avoiding the preselection of fault sources without addressing their possible impact onto hazard analysis results.

Multi-risk approaches have been recently proposed to assess and compare different risks in the same target area. The key points of multi-risk assessment are the development of homogeneous risk definitions and the treatment of risk interaction. The lack of treatment of interaction may lead to significant biases and thus to erroneous risk hierarchization, which is one of primary output of risk assessments for decision makers. In this paper, a formal statistical model is developed to treat interaction between two different hazardous phenomena in long-term multi-risk assessments, accounting for possible effects of interaction at hazard, vulnerability and exposure levels. The applicability of the methodology is demonstrated through two illustrative examples, dealing with the influence of (1) volcanic ash in seismic risk and (2) local earthquakes in tsunami risk. In these applications, the bias in single-risk estimation induced by the assumption of independence among risks is explicitly assessed. An extensive application of this methodology at regional and sub-regional scale would allow to identify when and where a given interaction has significant effects in long-term risk assessments, and thus, it should be considered in multi-risk analyses and risks hierarchization. © 2013 Springer Science+Business Media Dordrecht.

The inter-arrival times of the post 2000 seismicity at Campi Flegrei caldera are statistically distributed into different populations. The low inter-arrival times population represents swarm events, while the high inter-arrival times population marks background seismicity. Here, we show that the background seismicity is increasing at the same rate of (1) the ground uplift and (2) the concentration of the fumarolic gas specie more sensitive to temperature. The seismic temporal increase is strongly correlated with the results of recent simulations, modelling injection of magmatic fluids in the Campi Flegrei hydrothermal system. These concurrent variations point to a unique process of temperature-pressure increase of the hydrothermal system controlling geophysical and geochemical signals at the caldera. Our results thus show that the occurrence of background seismicity is an excellent parameter to monitor the current unrest of the caldera.

Assessment of volcanic hazards is necessary for risk mitigation. Typically, hazard assessment is based on one or a few, subjectively chosen representative eruptive scenarios, which use a specific combination of eruptive sizes and intensities to represent a particular size class of eruption. While such eruptive scenarios use a range of representative members to capture a range of eruptive sizes and intensities in order to reflect a wider size class, a scenario approach neglects to account for the intrinsic variability of volcanic eruptions, and implicitly assumes that inter-class size variability (i.e. size difference between different eruptive size classes) dominates over intra-class size variability (i.e. size difference within an eruptive size class), the latter of which is treated as negligible. So far, no quantitative study has been undertaken to verify such an assumption. Here, we adopt a novel Probabilistic Volcanic Hazard Analysis (PVHA) strategy, which accounts for intrinsic eruptive variabilities, to quantify the tephra fallout hazard in the Campania area. We compare the results of the new probabilistic approach with the classical scenario approach. The results allow for determining whether a simplified scenario approach can be considered valid, and for quantifying the bias which arises when full variability is not accounted for. This work was partially supported by the MED-SUV Project funded by the European Union (FP7 Grant Agreement n.308665), the “Futuro in Ricerca 2008 FIRB” ByMuR Project [RBFR0880SR] funded by MIUR (the Italian Ministry of Education, University and Research), and the DPC-INGV V1 (2013–2015) Project, funded by DPC (the Italian Department of Civil Protection) within the agreement between DPC and INGV. Background roadmap, terrain or satellite images in all the pictures were downloaded from Google Maps. The FALL3D simulations have been run at BSC using the MareNostrum supercomputer. We are very grateful to Mary Anne Thompson for providing us with helpful comments. We wish to thank the anonymous reviewers for their suggestions that significantly improved the quality of the manuscript.

The Campi Flegrei caldera is a restless structure affected by general subsidence and ongoing resurgence of its central part. The persistent activity of the system and the explosive character of the volcanism lead to a very high volcanic hazard that, combined with intense urbanization, corresponds to a very high volcanic risk. One of the largest sources of uncertainty in volcanic hazard/risk assessment for Campi Flegrei is the spatial location of the future volcanic activity. This paper presents and discusses a long-term probability hazard map for vent opening in case of renewal of volcanism at the Campi Flegrei caldera, which shows the spatial conditional probability for the next vent opening, given that an eruption occurs. The map has been constructed by building a Bayesian inference scheme merging prior information and past data. The method allows both aleatory and epistemic uncertainties to be evaluated. The probability map of vent opening shows that two areas of relatively high probability are present within the active portion of the caldera, with a probability approximately doubled with respect to the rest of the caldera. The map has an immediate use in evaluating the areas of the caldera prone to the highest volcanic hazard. Furthermore, it represents an important ingredient in addressing the more general problem of quantitative volcanic hazards assessment at the Campi Flegrei caldera. © 2011 Springer-Verlag.

Reliable forecasting of the next eruption at Vesuvius is the main scientific factor in defining effective strategies to reduce volcanic risk in one of the most dangerous volcanic areas of the world. In this paper, we apply a recently developed probabilistic code for eruption forecasting to new and independent historical data related to the pre-eruptive phase of the 1631 eruption. The results obtained point out three main issues: (1) the importance of "cold" historical data (according to Guidoboni 2008) related to pre-eruptive phases for evaluating forecasting tools and possibly refining them; (2) the BET_EF code implemented for Vesuvius would have forecasted the 1631 eruption satisfactorily, marking different stages of the pre-eruptive phase; (3) the code shows that pre-eruptive signals that significantly increase the probability of eruption were likely detected more than 2 months before the event. © Springer-Verlag 2009.