Flood Hazards in Flat Coastal Areas of the Eastern Iberian Peninsula: A Case Study in Oliva (Valencia, Spain)

Enhancing resilience against flooding events is of great importance. Eastern Iberian Peninsula coastal areas are well known for high intensity rainfalls known as DANA or “cold drop”. Extreme records in 24 hours can exceed the annual average of the historical series. This phenomenon occurs normally in autumn due to convective storms generated by the existence of cold air in the upper layers of the atmosphere combined with warm winds coming from the Mediterranean Sea. In many coastal areas of the Eastern Iberian Peninsula, their flat topography, sometimes of a marsh nature, and the natural (e.g., dune ridges) and man-made (e.g., infrastructures) factors, result in devastating flooding events of great potential damage and risk for urban and rural areas. In this context, this paper presents the case study of the town of Oliva (Valencia, Spain) and how in a flooding event the flow tends to spread and accumulate along the flat coastal strip of this populated area, causing great potential damage. From that point, the paper discusses the particular issues that flood studies should consider in such flat and heavy rainy areas in terms of the hydrological and hydraulic models to be conducted to serve as the key tool of a correct risk assessment. This includes the correct statistical simulation of rainfalls, the hydrological model dependency on the return period and the correct geometry definition of all possible water barriers. An analysis of the disturbance that climatic change effects may introduce in future flooding events is also performed.

Reliability assessment of the standby system with dependent components by bivariate exponential distributions

In the reliability analysis of systems, all system components are often assumed independent and failure of any component does not depend on any other component. One of the reasons for doing so is that considerations of calculation and elegance typically pull in simplicity. But in real-world applications, there are very complex systems with lots of subsystems and a choice of multiple components that may interact with each other. Therefore, components of the system can be affected by the occurrence of a failure in any of the components. The purpose of this paper is to give an explicit formula for the computation of the reliability of a system with two parallel active components and one spare component. It is assumed that parallel components are dependent and operate simultaneously. Two distributions of Freund’s bivariate exponential and Marshall–Olkin bivariate exponential are used to model dependency between components. The results show that the reliability of the system with Freund’s bivariate exponential distribution has lower reliability. The circumstances that lead to them, namely load-sharing in the case of Freund, results in lower reliability. Finally, a numerical example is solved to evaluate the proposed model and sensitivity analysis is performed on the system reliability function. The obtained results show that because the proposed model is influenced by the dependency, compared to traditional models, it has the characteristic of leading to reduced time to (first) failure for achieving specified reliability.

Online Predictive Maintenance Monitoring Adopting Convolutional Neural Networks

Thermal, electrical and mechanical stresses age the electrical insulation systems of high voltage (HV) apparatuses until the breakdown. The monitoring of the partial discharges (PDs) effectively assesses the insulation condition. PDs are both the symptoms and the causes of insulation aging and—in the long term—can lead to a breakdown, with a burdensome economic loss. This paper proposes the convolutional neural networks (CNNs) to investigate and analyze the aging process of enameled wires, thus predicting the life status of the insulation systems. The CNNs training does not require any kind of assumption of how the factors (e.g., voltage, frequency and temperature) contribute to the life model. The experiments confirm that the proposal obtains better estimations of the life status of twisted pair specimens concerning existing solutions, which are based on strong hypotheses about the life model dependency on the factors.

A Bayesian Alternative to Synthetic Control for Comparative Case Studies

This paper proposes a Bayesian alternative to the synthetic control method for comparative case studies with a single or multiple treated units. We adopt a Bayesian posterior predictive approach to Rubin’s causal model, which allows researchers to make inferences about both individual and average treatment effects on treated observations based on the empirical posterior distributions of their counterfactuals. The prediction model we develop is a dynamic multilevel model with a latent factor term to correct biases induced by unit-specific time trends. It also considers heterogeneous and dynamic relationships between covariates and the outcome, thus improving precision of the causal estimates. To reduce model dependency, we adopt a Bayesian shrinkage method for model searching and factor selection. Monte Carlo exercises demonstrate that our method produces more precise causal estimates than existing approaches and achieves correct frequentist coverage rates even when sample sizes are small and rich heterogeneities are present in data. We illustrate the method with two empirical examples from political economy.

The impact of COVID-19 on CO2 emissions in the Los Angeles and Washington DC/Baltimore metropolitan areas

<div> <div> <div> <p>Responses to COVID-19 have resulted in unintended reductions of city-scale carbon dioxide (CO2) emissions. Here we detect and estimate decreases in CO2 emissions in Los Angeles and Washington DC/Baltimore during March and April 2020. Our analysis uses three lines of evidence with increasing model dependency. The first detects the timing of emissions declines using the variability in atmospheric CO2 observations, the second assesses the continuation of reduced emissions using CO2 enhancements, and the third employs an inverse model to estimate the relative emissions changes in 2020 compared to 2018 and 2019. Emissions declines began in mid-March in both cities. The March decrease (25%) in Washington DC/Baltimore is largely supported by a drop in natural gas consumption associated with a warm spring whereas the decrease in April (33%) correlates with changes in gasoline fuel sales, a proxy for vehicular emissions. In contrast, only a fraction of the March (17%) and April (34%) reduction in Los Angeles is explained by traffic declines, while the remainder of the emissions reduction remains unexplained. To help diagnose such observed changes in emissions, more reliable, publicly available emission information from all significant sectors needs to be made available. Methods and measurements used herein highlight the advantages of atmospheric CO2 observations for providing timely insights into rapidly changing urban emissions patterns that can empower cities to course-correct mitigation activities more efficiently.</p> </div> </div> </div>

Pengembangan Model dan Metode Perhitungan Bonus Demografi

Previously research on bonus demographic measurement is still only focused on one model, namely dependency ratio which coverage two methods namely Cheung et al and Adioetomo. This research was carried out in East Lombok Regency and consist of two models, namely dependency ratio model and economic lifetime model. Dependency ratio model which coverage four methods namely Cheung et al, Adioetomo, Komine & Kabe, and Golini. Meanwhile economic lifetime model which coverage two methods namely support ratio and ratio of lifecycle pension wealth to total labour income. The aimed of this research is to determine model and method of bonus demographic measurement. This research used descriptive quantitative method. Based on the data analysis the results obtained that model that developed for measurement of demographic bonus is only dependency ratio model, meanwihle economic lifetime model isn’t developed yet. Refer to the fourth method of dependency ratio model, three methods have been developed namely Cheung et al, Adioetomo, Komine and Kabe, meanwhile Golini hasn’t been developed yet. Based on Cheung et al method East Lombok Timur Regency has been achieved demographic bonus between 2035 and 2045, but based on Adioetomo method between 2020 and 2045 has not been achieved demographic bonus yet and based on Komine and Kabe method will be achieved demographic bonus between 2020 and 2045. Keywords: demographic bonus, dependency ratio, economic lifetime

Properties of the Hyades, the eclipsing binary HD 27130, and the oscillating red giant ϵ Tauri

Context. The derivation of accurate and precise masses and radii is possible for eclipsing binary stars, allowing for insights into their evolution. When residing in star clusters, they provide measurements of even greater precision, along with additional information on their properties. Asteroseismic investigations of solar-like oscillations offers similar possibilities for single stars. Aims. We wish to improve the previously established properties of the Hyades eclipsing binary HD 27130 and re-assess the asteroseismic properties of the giant star ϵ Tau. The physical properties of these members of the Hyades can be used to constrain the helium content and age of the cluster. Methods. New multi-colour light curves were combined with multi-epoch radial velocities to yield masses and radii of HD 27130. Measurements of Teff were derived from spectroscopy and photometry, and verified using the Gaia parallax. We estimated the cluster age from re-evaluated asteroseismic properties of ϵ Tau while using HD 27130 to constrain the helium content. Results. The masses, radii, and Teff of HD 27130 were found to be M = 1.0245 ± 0.0024 M⊙, R = 0.9226 ± 0.015 R⊙, Teff = 5650 ± 50 K for the primary, and M = 0.7426 ± 0.0016 M⊙, R = 0.7388 ± 0.026 R⊙, Teff = 4300 ± 100 K for the secondary component. Our re-evaluation of ϵ Tau suggests that the previous literature estimates are trustworthy and that the HIPPARCOS parallax is more reliable than the Gaia DR2 parallax. Conclusions. The helium content of HD 27130 and, thus, of the Hyades is found to be Y = 0.27 but with a significant model dependency. Correlations with the adopted metallicity result in a robust helium enrichment law, with ΔY/ΔZ close to 1.2 We estimate the age of the Hyades to be 0.9 ± 0.1 (stat) ±0.1 (sys) Gyr, which is in slight tension with recent age estimates based on the cluster white dwarfs. The precision of the age estimate can be much improved via asteroseismic investigations of the other Hyades giants and by future improvements to the Gaia parallax for bright stars.

Model Dependency in the Analysis of Women's Electoral Success

Maciej Górecki provides a detailed and interesting discussion of our analysis regarding women's electoral success in the Polish open-list proportional representation (PR) system and the impact of a gender quota implemented in 2011. In essence, he claims that it remains an open question whether the gender quota had a ‘paradoxical’ effect (i.e., whether the introduction of the gender quota had a negative impact on female candidates) due to ‘debatable’ methodological choices in our analysis. In this article, we respond to Górecki's critique. First, we demonstrate that we do not necessarily disagree on the paradoxical impact of the gender quota but rather on the strength of the paradoxical effect. Second, we discuss some drawbacks of using the raw number of votes cast for a candidate as the dependent variable. Finally, we respond to the critique of including the ballot position in the regression model. We emphasize that even if one agrees with Górecki's critique that the ballot position is endogenous, excluding this variable leads to a severely misspecified model that does not allow one to reliably identify the effect of gender.