Build seismic cycle balance deformation with InSAR in Northen Chile

2020 ◽  
Author(s):  
Lauriane Bayle ◽  
Romain Jolivet ◽  
Nadaya Cubas ◽  
Laetitia Le Pourhiet
Keyword(s):  
Time Series ◽  
Subduction Zones ◽  
Permanent Deformation ◽  
Seismic Cycle ◽  
Seismic Displacement ◽  
Uplift Rates ◽  
Short And Long Term ◽  
Period Data ◽  
Illapel Earthquake

<p>Lauriane Baylé (1), Romain Jolivet (2), Nadaya Cubas (1) and Laetitia Le</p><p>Pourhiet (1)</p><p>(1) Institut des Sciences de la Terre de Paris, UMR 7193, UPMC UniversitéParis 6, CNRS, Paris,</p><p>France</p><p>(2) Laboratoire de Géologie, Département de Géosciences, École Normale Supérieure, CNRS UMR 8538,</p><p>PSL ResearchUniversity, Paris, France</p><p>Recent studies have pointed out to a discrepancy between the short- and long-</p><p>term deformation of overriding plates in subduction zones. This led to debates</p><p>about when and how permanent deformation is acquired. This contradiction</p><p>has notably been observed along the Central Andes Subduction Zone, where</p><p>the coast subsides during and shortly after major earthquakes while a coastal</p><p>uplift with rates ranging between 0.1 and 0.3 mm/yr has been inferred the</p><p>last 4000 ky. For instance, during the 15th September 2015 Mw 8.3 Illapel</p><p>earthquake the geodetics (GPS and InSAR) data show a coastal subsidence</p><p>along the line-of-sight of 20 cm in InSAR.</p><p>To reconcile the seemingly contradictory observations, we here propose to</p><p>provide a seismic cycle uplift balance by constrainning inter-, co- and post-</p><p>seismic vertical velocities from InSAR time series. The study focuses on La</p><p>Serena peninsula (71.3°W, 30°S, Chile) along which the Illapel earthquake</p><p>occurred and for which long-term uplift rates have been provided by previous</p><p>geomorphological studies.</p><p>To build this seismic cycle balance, we use InSAR data (Sentinel-1) acqui-</p><p>red between the September 15, 2015 and January 19, 2019. The time series</p><p>for the ascendant orbite is calculated and the accumulated vertical displace-</p><p>ment extracted providing co- and post-seismic displacement. The co-seismic</p><p>displacement are similar to those previously obtain. To constrain the displa-</p><p>cement during the inter-seismic period, data on both sides of the peninsula</p><p>are used. In that respect, we aim determining when, during the seismic cycle,</p><p>and where, along the coast, the uplift occurs.</p><p>The deduced time series will then be confronted to numerical modelling</p><p>to provide the short- and long-term mechanics reproducing the short- and</p><p>long-term observations.</p>

scholarly journals Effect of Oxidative Aging on the Engineering Properties of DGAMs

2018 ◽  
Vol 7 (4) ◽  
pp. 50
Author(s):  
Al-Hadidy A.I. ◽  
Abdullah M. Rashed
Keyword(s):  
Service Life ◽  
Flexural Strength ◽  
Permanent Deformation ◽  
Engineering Properties ◽  
Base Layer ◽  
Short Term ◽  
Asphalt Cement ◽  
Oxidative Aging ◽  
Short And Long Term

Short and long term aging were conducted on the dense graded asphalt mixtures (DGAMs) containing 40-50 penetration grade asphalt cement binders. The short term oven aging (STOA) was conducted on loose mixtures at temperature of 135 °C for four hours and at temperature of 154 °C for two hours, whereas, the long term oven aging (LTOA) was conducted at temperature of 85 °C and at two periods of time between four and eight days. Marshall properties, tensile and compressive strength at 25 and 60°C, flexural strength at 0 and -10°C, cohesion at 60°C, tensile strength ratio, and index of retained strength were carried out on unaged and aged DGAM. A mechanistic-empirical design approach using BISAR program was adopted for estimating the improvement in service life of the pavement or reduction in thickness of DGAM and base layer for the same service life due to the aging of DGAM. The results showed that the STOA and LTOA: (1) increases resistance of DGAM against permanent deformation, stripping, and flexural strength; (2) increases traffic benefit ratio between 10 and 20%; (3) reduces the thickness of the surface layer between 8 and 14%; and (4) the base thickness reduces between 35% and 57%.

scholarly journals Characterizing scaling laws in gut microbial dynamics from time series data: caution is warranted

2021 ◽  
Author(s):  
Xu-Wen Wang ◽  
Yang-Yu Liu
Keyword(s):  
Time Series ◽  
Gut Microbiota ◽  
Scaling Laws ◽  
Time Series Data ◽  
Series Data ◽  
Temporal Variance ◽  
Short And Long Term ◽  
Human And Mouse ◽  
Mouse Gut Microbiota

AbstractMany studies have revealed that both host and environmental factors can impact the gut microbial compositions, implying that the gut microbiota is considerably dynamic1–5. In their Article, Ji et al.6 performed comprehensive analysis of multiple high-resolution time series data of human and mouse gut microbiota. They found that both human and mouse gut microbiota dynamics can be characterized by several robust scaling laws describing short- and long-term changes in gut microbiota abundances, distributions of species residence and return times, and the correlation between the mean and the temporal variance of species abundances. They claimed that those scaling laws characterize both short- and long-term dynamics of gut microbiota. However, we are concerned that their interpretation is quite misleading, because all the scaling laws can be reproduced by the shuffled time series with completely randomized time stamps of the microbiome samples.

scholarly journals Air pollution, SARS-CoV-2 transmission, and COVID-19 outcomes: A state-of-the-science review of a rapidly evolving research area

2020 ◽  
Author(s):  
Anushka Bhaskar ◽  
Jay Chandra ◽  
Danielle Braun ◽  
Jacqueline Cellini ◽  
Francesca Dominici
Keyword(s):  
Air Pollution ◽  
Time Series ◽  
Health Outcomes ◽  
Study Design ◽  
Air Pollutant ◽  
Short Term ◽  
Cross Sectional ◽  
Short And Long Term ◽  
Long Term Studies

Background: As the coronavirus pandemic rages on, 692,000 (August 7, 2020) human lives and counting have been lost worldwide to COVID-19. Understanding the relationship between short- and long-term exposure to air pollution and adverse COVID-19 health outcomes is crucial for developing solutions to this global crisis. Objectives: To conduct a scoping review of epidemiologic research on the link between short- and long-term exposure to air pollution and COVID-19 health outcomes. Method: We searched PubMed, Web of Science, Embase, Cochrane, MedRxiv, and BioRxiv for preliminary epidemiological studies of the association between air pollution and COVID-19 health outcomes. 28 papers were finally selected after applying our inclusion/exclusion criteria; we categorized these studies as long-term studies, short-term time-series studies, or short-term cross-sectional studies. One study included both short-term time-series and a cross-sectional study design. Results: 27 studies of the 28 reported evidence of statistically significant positive associations between air pollutant exposure and adverse COVID-19 health outcomes; 11 of 12 long-term studies and all 16 short-term studies reported statistically significant positive associations. The 28 identified studies included various confounders, spatial and temporal resolutions of pollution concentrations, and COVID-19 health outcomes. Discussion: We discuss methodological challenges and highlight additional research areas based on our findings. Challenges include data quality issues, ecological study design limitations, improved adjustment for confounders, exposure errors related to spatial resolution, geographic variability in testing, mitigation measures and pandemic stage, clustering of health outcomes, and a lack of publicly available data and code.

scholarly journals Evaluation of the Performance of a Warm Mix Asphalt (WMA) Considering Aged and Unaged Specimens

Coatings ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 1241
Author(s):  
Giuseppe Piccone ◽  
Giuseppe Loprencipe ◽  
Arminda Almeida ◽  
Nicola Fiore
Keyword(s):  
Fatigue Behavior ◽  
Permanent Deformation ◽  
Road Construction ◽  
Warm Mix Asphalt ◽  
Environmental Aspects ◽  
Bituminous Mixtures ◽  
Water Sensitivity ◽  
Short And Long Term ◽  
High Level

In the last decades, all technology production sectors reached a high level of development, without neglecting the attention to environmental aspects and safeguarding energy resources. Moreover, in the sector of pavement industry, some alternatives of bituminous mixtures were proposed to reduce the greenhouse gas emissions. One of these is the warm mix asphalt (WMA), a mixture produced and compacted at lower temperatures compared to traditional hot mix asphalt (HMA) (about 40 °C less), to allow a reduction of emissions into the atmosphere and the costs. Other operative benefits concern the health of workers during the whole road construction process, the reduction of distances to which the mixture can be transported, and therefore also the positioning of the plants. However, it is not all benefits, since reduced production temperatures can bring short- and long-term water sensitivity issues, which could threaten the pavement performance. This paper evaluated the performance (water sensitivity, stiffness, fatigue, and permanent deformation) of a WMA produced using a warm mix fabrication bitumen and compared it with an HMA tested in parallel. In general, except for the resistance to permanent deformation, the WMA presented performances comparable to HMA. Regarding the fatigue behavior of asphalt mixtures, the WMA was less affected by ageing conditions, despite it showing lower performance than HMA.

Relationships between deformation and morphology of forearc wedges and earthquake ruptures

2021 ◽  
Author(s):  
Nadaya Cubas
Keyword(s):  
Subduction Zones ◽  
Permanent Deformation ◽  
Seismic Cycle ◽  
Earthquake Rupture ◽  
Earthquake Ruptures ◽  
Mechanical Modelling ◽  
Seismic Behaviors ◽  
Deformation Patterns ◽  
Rupture Properties ◽  
Effective Friction

<p>Over the last decade, we have accumulated evidence that, along subduction zones, a significant part of the seismic cycle deformation is permanently acquired by the medium and reflects the variation of rupture properties along the megathrust. Assuming a persistence of the megathrust segmentation over several hundred thousand years, this permanent deformation and the forearc topography could thus reveal the mechanics of the megathrust. Numerous recent studies have also shown that the megathrust effective friction appears to differ significantly between aseismic or seismic areas. From mechanical modelling, I will first discuss how such differences in effective friction are significant enough to induce wedge segments with varying morphologies and deformation patterns. I will present examples from different subduction zones characterized by either erosive or accretionary wedges, and by different seismic behaviors. Secondly, I will present how this long-lived deformation can in turn control earthquake ruptures. I will show, that along the Chilean subduction zone, all recent mega-earthquakes are surrounded by basal erosion and underplating. Therefore, the deformation and morphology of forearcs would both be partly linked to the megathrust rupture properties and should be used in a more systematic manner to improve earthquake rupture prediction.</p>

Continuous Dynamical Combination of Short and Long-Term Forecasts for Nonstationary Time Series

2014 ◽  
Vol 25 (1) ◽  
pp. 241-246 ◽  
Author(s):  
Domingos Savio Pereira Salazar ◽  
Paulo Jorge Leitao Adeodato ◽  
Adrian Lucena Arnaud
Keyword(s):  
Time Series ◽  
Nonstationary Time Series ◽  
Short And Long Term

scholarly journals INTRODUCTION TO TIME-VARYING MODELING WITH MACROECONOMIC AND FINANCIAL DATA

2012 ◽  
Vol 16 (S2) ◽  
pp. 167-175 ◽  
Author(s):  
Fredj Jawadi
Keyword(s):  
Time Series ◽  
Time Variation ◽  
Moving Average ◽  
Statistical Properties ◽  
Financial Data ◽  
Time Varying ◽  
Arch Model ◽  
Financial Variables ◽  
Short And Long Term

The dynamics of macroeconomic and financial series has evolved swiftly and asymmetrically since the end of the 1970s, and their statistical properties have also changed over time, suggesting complex relationships between economic and financial variables. The transformations can be explained by considerable changes in householder's behavior, market structures, and economic systems and by the alternation of exogenous shocks and financial crises that have affected the economic cycle, with significant evidence of time variation in the major economic variables. Hence, there is a need for new econometric protocols to take such changes into consideration. The introduction of ARMA (autoregressive moving average models) by Box and Jenkins (1970) led to the development of time-series econometrics, which had a major impact on the conceptual analysis of economic and financial data. This type of modeling offered a transition from a static setup to a new modeling process that reproduces the time-varying features of macroeconomic and financial series. However, the ARMA modeling system retains the constancy of the first and second moments, limits the phases of a cycle to symmetrical instances, and only reproduces the dynamics of stationary variables. It thus fails to adequately reproduce the nonstationary relationships between major economic and financial variables. Abrupt changes in economies and financial systems have given evidence of nonstationary series whose statistical properties are also time-varying, making it necessary to develop new econometric tools to capture the time variation of economic and financial series in the mean and in the variance, and to apprehend their dynamics in the short and long term. Among the most important and influential studies in the 1980s' econometrics literature were therefore those that dealt with the introduction of the ARCH (autoregressive conditional heteroskedasticity) model by Engle (1982) and the cointegration theory by Engle and Granger (1987). The ARCH model, which focuses on the time-varying features of volatility structure, was a major breakthrough, as it highlighted the importance of the second moment of time series, while the cointegration framework enabled the short- and long-term dynamics of nonstationary variables to be modeled.

scholarly journals Modelling Short- and Long-Term Dependencies of Clustered High-Threshold Exceedances in Significant Wave Heights

Mathematics ◽  
2021 ◽  
Vol 9 (21) ◽  
pp. 2817
Author(s):  
Pushpa Dissanayake ◽  
Teresa Flock ◽  
Johanna Meier ◽  
Philipp Sibbertsen
Keyword(s):  
Time Series ◽  
Long Range ◽  
High Threshold ◽  
Peaks Over Threshold ◽  
Significant Wave ◽  
Wave Heights ◽  
Short And Long Term ◽  
Significant Wave Heights ◽  
Threshold Exceedances

The peaks-over-threshold (POT) method has a long tradition in modelling extremes in environmental variables. However, it has originally been introduced under the assumption of independently and identically distributed (iid) data. Since environmental data often exhibits a time series structure, this assumption is likely to be violated due to short- and long-term dependencies in practical settings, leading to clustering of high-threshold exceedances. In this paper, we first review popular approaches that either focus on modelling short- or long-range dynamics explicitly. In particular, we consider conditional POT variants and the Mittag–Leffler distribution modelling waiting times between exceedances. Further, we propose a new two-step approach capturing both short- and long-range correlations simultaneously. We suggest the autoregressive fractionally integrated moving average peaks-over-threshold (ARFIMA-POT) approach, which in a first step fits an ARFIMA model to the original series and then in a second step utilises a classical POT model for the residuals. Applying these models to an oceanographic time series of significant wave heights measured on the Sefton coast (UK), we find that neither solely modelling short- nor long-range dependencies satisfactorily explains the clustering of extremes. The ARFIMA-POT approach, however, provides a significant improvement in terms of model fit, underlining the need for models that jointly incorporate short- and long-range dependence to address extremal clustering, and their theoretical justification.

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