Eruption Scenarios of Active Volcanoes in Indonesia

2019 ◽  
Vol 14 (1) ◽  
pp. 40-50
Author(s):  
Setsuya Nakada ◽  
Fukashi Maeno ◽  
Mitsuhiro Yoshimoto ◽  
Natsumi Hokanishi ◽  
Taketo Shimano ◽  
...  
Keyword(s):  
Time Windows ◽  
Field Research ◽  
Monitoring Data ◽  
Event Tree ◽  
Geochemical Monitoring ◽  
Short Term ◽  
Discharge Rates ◽  
Magma Discharge ◽  
Event Trees ◽  
Active Volcanoes

Eruption scenarios were prepared as possible sequences in event trees for six active volcanoes in Indonesia, that are located near populated areas or have erupted in recent years (Galunggung, Guntur, Kelud, Merapi, Semeru, and Sinabung). The event trees prepared here show sequences of possible eruption phenomena without probabilities on branches and cover sequences experienced in historical and pre-historical eruptions based on archives and field research results. Changing magma discharge rates during eruption sequences were considered for the event tree of Merapi. This conceptual event tree can also be used as a short-term event tree in which forecasting the coming eruption became possible with geophysical and geochemical monitoring data. Eruption event trees prepared for selected time windows cannot illustrate all plausible hazards and risks associated with an eruption. Therefore, hazards and risks generated from an eruption should be considered in different domains from the event tree.

scholarly journals Kecerdasan Emosi Dan Depresi Pada Mahasiswa Yang Sudah Menikah

2019 ◽  
Vol 6 (2) ◽  
pp. 146
Author(s):  
Azizah Fitriah
Keyword(s):  
Emotional Intelligence ◽  
Hypothesis Test ◽  
Negative Relationship ◽  
Field Research ◽  
Short Term ◽  
Significant Negative Relationship ◽  
Correlational Approach ◽  
The Individual ◽  
Married Students ◽  
The Relationship

Every human being will one day experience a tense period in the short term when facing known problems such as career pressures, family disputes or quarrels, material pressures, and personal despair, and we will think that this is depression, which is not is an important problem because it will resolve itself, but none of these fleeting conditions is depression. Good emotional intelligence can reduce aggression, especially in adolescents. Therefore, if emotions are managed successfully, the individual will be able to entertain themselves when overwritten by sadness, can release anxiety, moodiness or offense and rise quickly again from it all. This research is field research with a correlational approach, exploring the relationship between depression and emotional intelligence in married students. The results of the hypothesis test show that between emotional intelligence and depression in married students has a significant negative relationship (XY = -0.411; sig = 0.014 <0.05). This is in accordance with the data obtained from the SPSS 19 for Windows program, stating that r table 0.334 and r xy (r hit) -0.411, said to be significant if r xy = 0.411> r table = 0.334. In other words, the higher the emotional intelligence of students who are married, the lower the possibility of depression.

scholarly journals Exploring the Effects of COVID-19 Containment Policies on Crime: An Empirical Analysis of the Short-term Aftermath in Los Angeles

2020 ◽  
Author(s):  
Gian Maria Campedelli ◽  
Alberto Aziani ◽  
Serena Favarin
Keyword(s):  
Los Angeles ◽  
Time Windows ◽  
Intimate Partner ◽  
Policy Implications ◽  
Crime Trends ◽  
Short Term ◽  
Post Intervention ◽  
Structural Time Series ◽  
Deadly Weapon ◽  
Partner Assault

This work investigates whether and how COVID-19 containment policies had an immediate impact on crime trends in Los Angeles. The analysis is conducted using Bayesian structural time-series and focuses on nine crime categories and on the overall crime count, daily monitored from January 1st 2017 to March 28th 2020. We concentrate on two post-intervention time windows—from March 4th to March 16th and from March 4\textsuperscript{th} to March 28th 2020—to dynamically assess the short-term effects of mild and strict policies. In Los Angeles, overall crime has significantly decreased, as well as robbery, shoplifting, theft, and battery. No significant effect has been detected for vehicle theft, burglary, assault with a deadly weapon, intimate partner assault, and homicide. Results suggest that, in the first weeks after the interventions are put in place, social distancing impacts more directly on instrumental and less serious crimes. Policy implications are also discussed.

scholarly journals Short-term volcano-tectonic earthquake forecasts based on a MRT algorithm: the El Hierro seismo-volcanic crisis experience

2016 ◽  
Author(s):  
A. García ◽  
S. De La Cruz-Reyna ◽  
J. M. Marrero ◽  
R. Ortiz
Keyword(s):  
Time Windows ◽  
Decision Makers ◽  
Recurrence Time ◽  
Large Magnitude ◽  
Short Term ◽  
Tectonic Earthquake ◽  
El Hierro ◽  
Tectonic Earthquakes ◽  
Volcanic Islands ◽  
Repetitive Pattern

Abstract. Under certain conditions volcano-tectonic (VT) earthquakes may pose significant hazards to people living in or near active volcanic regions, especially on volcanic islands; however, hazard arising from VT activity caused by localized volcanic sources is rarely addressed in the literature. The evolution of VT earthquakes resulting from a magmatic intrusion shows some orderly behavior that may allow forecasting the occurrence and magnitude of major events. Thus govern-mental decision-makers can be supplied of warnings of the increased probability of larger-magnitude earthquakes in the short term time-scale. We present here a methodology for forecasting the occurrence of large-magnitude VT events during volcanic crises; it is based on a Mean Recurrence Time (MRT) algorithm that translates the Gutenberg-Richter distribution parameter fluctuations into time windows of increased probability of a major VT earthquake. The MRT forecasting algorithm was developed after observing a repetitive pattern in the seismic swarm episodes occurring between July and November 2011 at El Hierro (Canary Islands). From then on, this methodology has been applied to the consecutive seismic crises registered at El Hierro, achieving a high success rate in the real-time forecasting, within 10 day time-windows, of volcano-tectonic earthquakes

scholarly journals Tipping points of Mississippi Delta marshes due to accelerated sea-level rise

2020 ◽  
Vol 6 (21) ◽  
pp. eaaz5512 ◽  
Author(s):  
Torbjörn E. Törnqvist ◽  
Krista L. Jankowski ◽  
Yong-Xiang Li ◽  
Juan L. González
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Mississippi Delta ◽  
Time Windows ◽  
Open Water ◽  
Tipping Points ◽  
Coastal Marshes ◽  
Short Term ◽  
Global Sea Level ◽  
Coastal Louisiana

Coastal marshes are threatened by relative sea-level (RSL) rise, yet recent studies predict marsh survival even under the high rates of RSL rise expected later in this century. However, because these studies are mostly based on short-term records, uncertainty persists about the longer-term vulnerability of coastal marshes. We present an 8500-year-long marsh record from the Mississippi Delta, showing that at rates of RSL rise exceeding 6 to 9 mm year−1, marsh conversion into open water occurs in about 50 years. At rates of RSL rise exceeding ~3 mm year−1, marsh drowning occurs within a few centuries. Because present-day rates of global sea-level rise already surpass this rate, submergence of the remaining ~15,000 km2 of marshland in coastal Louisiana is probably inevitable. RSL-driven tipping points for marsh drowning vary geographically, and those for the Mississippi Delta may be lower than elsewhere. Nevertheless, our findings highlight the need for consideration of longer time windows in determining the vulnerability of coastal marshes worldwide.

scholarly journals A Heuristic Methodology for Efficient Reduction of Large Multistate Event Trees

2013 ◽  
Vol 2013 ◽  
pp. 1-14
Author(s):  
Eftychia C. Marcoulaki
Keyword(s):  
Risk Assessment ◽  
Quantitative Risk Assessment ◽  
Event Tree ◽  
Event Space ◽  
Simultaneous Treatment ◽  
Risk Quantification ◽  
Efficient Reduction ◽  
System Components ◽  
Event Trees ◽  
The Given

This work proposes a new methodology for the management of event tree information used in the quantitative risk assessment of complex systems. The size of event trees increases exponentially with the number of system components and the number of states that each component can be found in. Their reduction to a manageable set of events can facilitate risk quantification and safety optimization tasks. The proposed method launches a deductive exploitation of the event space, to generate reduced event trees for large multistate systems. The approach consists in the simultaneous treatment of large subsets of the tree, rather than focusing on the given single components of the system and getting trapped into guesses on their structural arrangement.

scholarly journals Short-term volcano-tectonic earthquake forecasts based on a moving mean recurrence time algorithm: the El Hierro seismo-volcanic crisis experience

2016 ◽  
Vol 16 (5) ◽  
pp. 1135-1144 ◽  
Author(s):  
Alicia García ◽  
Servando De la Cruz-Reyna ◽  
José M. Marrero ◽  
Ramón Ortiz
Keyword(s):  
Time Windows ◽  
Time Algorithm ◽  
Decision Makers ◽  
Recurrence Time ◽  
Large Magnitude ◽  
Short Term ◽  
Tectonic Earthquake ◽  
El Hierro ◽  
Tectonic Earthquakes ◽  
Volcanic Islands

Abstract. Under certain conditions, volcano-tectonic (VT) earthquakes may pose significant hazards to people living in or near active volcanic regions, especially on volcanic islands; however, hazard arising from VT activity caused by localized volcanic sources is rarely addressed in the literature. The evolution of VT earthquakes resulting from a magmatic intrusion shows some orderly behaviour that may allow the occurrence and magnitude of major events to be forecast. Thus governmental decision makers can be supplied with warnings of the increased probability of larger-magnitude earthquakes on the short-term timescale. We present here a methodology for forecasting the occurrence of large-magnitude VT events during volcanic crises; it is based on a mean recurrence time (MRT) algorithm that translates the Gutenberg-Richter distribution parameter fluctuations into time windows of increased probability of a major VT earthquake. The MRT forecasting algorithm was developed after observing a repetitive pattern in the seismic swarm episodes occurring between July and November 2011 at El Hierro (Canary Islands). From then on, this methodology has been applied to the consecutive seismic crises registered at El Hierro, achieving a high success rate in the real-time forecasting, within 10-day time windows, of volcano-tectonic earthquakes.

scholarly journals Design and evaluation of mobile monitoring campaigns for air pollution exposure assessment in epidemiologic cohorts

2021 ◽  
Author(s):  
Magali N. Blanco ◽  
Annie Doubleday ◽  
Elena Austin ◽  
Julian D. Marshall ◽  
Edmund Seto ◽  
...  
Keyword(s):  
Air Pollution ◽  
Study Design ◽  
Monitoring Data ◽  
Mobile Monitoring ◽  
Short Term ◽  
Balanced Design ◽  
Air Pollution Exposure ◽  
Balanced Designs ◽  
Pollution Exposure

AbstractMobile monitoring makes it possible to estimate the long-term trends of less commonly measured pollutants through the collection of repeated short-term samples. While many different mobile monitoring approaches have been taken, few studies have looked at the importance of study design when the goal is application to epidemiologic cohort studies. Air pollution concentrations include random variability and systematic variability, and we hypothesize that mobile campaigns benefit from temporally balanced designs that randomly sample from all seasons of the year, days of the week, and hours of the day. We carried out a simulation study of fixed-site monitors to better understand the role of short-term mobile monitoring design on the prediction of long-term air pollution exposure surfaces. Specifically, we simulated three archetypal sampling designs using oxides of nitrogen (NOx) monitoring data from 69 California air quality system (AQS) sites: (1) a year-around, Balanced Design, (2) a Rush Hours Design, and (3) a Business Hours Design. We used Monte Carlo resampling to investigate the range of possible outcomes (i.e., the resulting annual average concentration prediction) from each design against the “truth”, the actual monitoring data. We found that the Balanced Design consistently yielded the most accurate annual averages; Rush Hours and Business Hours Designs generally resulted in comparatively more biased estimates and model predictions. Importantly, the superior performance of the Balanced Design was evident when predictions were evaluated against true concentrations but less detectable when predictions were evaluated against the measurements from the same sampling campaign since these were themselves biased. This result is important since mobile monitoring campaigns that use their own measurements to test the robustness of the results may underestimate the level of bias in their results. Appropriate study design is crucial for mobile monitoring campaigns aiming to assess accurate long-term exposure in epidemiologic cohorts. Campaigns should aim to implement balanced designs that sample during all seasons of the year, days of the week, and all or most hours of the day to produce generally unbiased, long-term averages. Furthermore, differential exposure misclassification could result from unbalanced designs, which may result in misleading health effect estimates in epidemiologic investigations.

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