A Resampling Slack-Based Energy Efficiency Analysis: Application in the G20 Economies

In order to have a sustainable economic and social development, it is important to balance economic growth and ecological environmental damage. In this article, we used the resampling model under the triangular distribution to evaluate energy efficiency, because the input/output value may have measurement errors, time lag factors, arbitrariness, and other problems, causing their own DMU to change. After these factors were taken into consideration, the resampled input/output was estimated because a super-SBM efficiency value was placed in the confidence interval. From the past-present data, for the estimated data change, the time weight was provided according to the Lucas series, and the super-SBM was time-weighted. We applied this model to a dataset of G20 economies from 2010 to 2014. To the best of our knowledge, very few studies have applied the DEA method with resampling to analyze energy efficiency. Thus, our study contributes to the methodologies for energy efficiency evaluation. We found that the overall average energy efficiency is 0.653, with substantial differences between developed economies and developing economies. The most important finding is that neither overestimation nor underestimation occurred when sampling was repeated one thousand times using 95% and 80% confidence intervals, confirming the robustness of the super-SBM model. The less energy-efficient economies should adjust their energy policies appropriately and develop new clean energy technologies in the future.

Note on “Parameters estimators of irregular right-angled triangular distribution”

Simple estimators were given in (Kachiashvili & Topchishvili, 2016) for the lower and upper limits of an irregular right-angled triangular distribution together with convenient formulas for removing their bias. We argue here that the smallest observation is not a maximum likelihood estimator (MLE) of the lower limit and we present a procedure for computing an MLE of this parameter. We show that the MLE is strictly smaller than the smallest observation and we give some bounds that are useful in a numerical solution procedure. We also present simulation results to assess the bias and variance of the MLE.

Exploring the Effect of Occurrence-Bias-Adjustment Assumptions on Hydrological Impact Modeling

Bias adjustment of climate model simulations is a common step in the climate impact assessment modeling chain. For precipitation intensity, multiple bias-adjusting methods have been developed, but less so for precipitation occurrence. Intensity-bias-adjusting methods such as ‘Quantile Delta Mapping’ can adjust too many wet days, but not too many dry days. Some occurrence-bias-adjusting methods have been developed to resolve this by the addition of the ability to adjust too dry simulations. Earlier research has shown this to be important when adjusting on a continental scale, when both types of biases can occur. However, the newer occurrence-bias-adjusting methods have their weakness: they might retain a bias in the number of dry days when adjusting data in a region that only has too many wet days. Yet, if this bias is small enough, it is more practical and economical to apply the newer methods when data in the larger region are adjusted. In this study, we consider two recently introduced occurrence-bias-adjusting methods, Singularity Stochastic Removal and Triangular Distribution Adjustment, and compare them in a region with only wet-day biases. This bias adjustment is performed for precipitation intensity and precipitation occurrence, while the evaluation is performed on precipitation intensity, precipitation occurrence and discharge, which combines the former two variables. Despite theoretical weaknesses, we show that both Singularity Stochastic Removal and Triangular Distribution Adjustment perform well. Thus, the methods can be applied for both too wet and too dry simulations, although Triangular Distribution Adjustment may be preferred as it was designed with a broad application in mind.

Numerical Modeling of the Interaction of Normal Fault and Shallow Embedded Foundation

The consequences to structures caused by permanent fault displacement has been investigated for dip-slip faulting, but not for the effect of the embedment depth on the interaction between a normal fault rupture and shallow embedded foundation. This study investigated the effect of the embedment depth on the interaction of normal fault rupture and shallow foundation using a numerical model validated with centrifuge experiments. It was found that a gapping interaction mechanism and foundation distress occurred at different foundation positions relative to the fault rupture outcrop for an embedded foundation in comparison with a surface foundation. The extent of this area depended on the combined influences of the foundation position, foundation surcharge, embedment depth, and fault dip angle. The sidewalls of the shallow embedded foundation were observed to act as kinematic constraints and had considerable influence on the rotation and displacement of the foundations. With regard to the level of rotation and displacement of the embedded foundation, the lateral earth pressure distribution on the footwall sidewall was similar to that of Rankine active earth pressure in a triangular distribution and on the hangingwall sidewall as a parabolic distribution of passive earth pressure. Foundations laid on loose soil exhibited less rotation than those on dense soil because the fault ruptures were absorbed or bifurcated around both sides of the foundation.

A Eulerian Multi-Fluid Model for High-Speed Evaporating Sprays

Advancements in internal combustion technology, such as efficiency improvements and the usage of new complex fuels, are often coupled with developments of suitable numerical tools for predicting the complex dynamic behavior of sprays. Therefore, this work presents a Eulerian multi-fluid model specialized for the dynamic behavior of dense evaporating liquid fuel sprays. The introduced model was implemented within the open-source OpenFOAM library, which is constantly gaining popularity in both industrial and academic settings. Therefore, it represents an ideal framework for such development. The presented model employs the classes method and advanced interfacial momentum transfer models. The droplet breakup is considered using the enhanced WAVE breakup model, where the mass taken from the parent droplets is distributed among child classes using a triangular distribution. Furthermore, the complex thermal behavior within the moving droplets is considered using a parabolic temperature profile and an effective thermal conductivity approach. This work includes an uncertainty estimation analysis (for both spatial and temporal resolutions) for the developed solver. Furthermore, the solver was validated against two ECN Spray A conditions (evaporating and non-evaporating). Overall, the presented results show the capability of the implemented model to successfully predict the complex dynamic behavior of dense liquid sprays for the selected operating conditions.

Gut Microbiome of Indonesian Adults Associated with Obesity and Type 2 Diabetes: A Cross-Sectional Study in an Asian City, Yogyakarta

Indonesia is a developing country facing the national problem of the growing obesity and diabetes in its population due to recent drastic dietary and lifestyle changes. To understand the link between the gut microbiome, diet, and health of Indonesian people, fecal microbiomes and metabolomes of 75 Indonesian adults in Yogyakarta City, including obese people (n = 21), type 2 diabetes (T2D) patients (n = 25), and the controls (n = 29) were characterized together with their dietary and medical records. Variations of microbiomes showed a triangular distribution in the principal component analysis, driven by three dominant bacterial genera, namely Bacteroides, Prevotella, and Romboutsia. The Romboutsia-driven microbiome, characterized by low bacterial diversity and high primary bile acids, was associated with fat-driven obesity. The Bacteroides-driven microbiome, which counteracted Prevotella but was associated with Ruminococcaceae concomitantly increased with high-carbohydrate diets, showed positive correlation with T2D indices but negative correlation with body mass index. Notably, Bacteroides fragilis was increased in T2D patients with a decrease in fecal conjugated bile acids, particularly tauroursodeoxycholic acid (TUDCA), a farnesoid X receptor (FXR) antagonist with anti-diabetic activity, while these features disappeared in patients administered metformin. These results indicate that the gut microbiome status of Indonesian adults is differently associated with obesity and T2D under their varied dietary habits.

Gut Microbiome of Indonesian Adults Differently Associated with Obesity and type 2 Diabetes under Varied Dietary Habits: A Cross-sectional Study in an Asian Developing City, Yogyakarta

Indonesia is a developing country facing the national problem of the growing obesity and diabetes in its population due to recent drastic dietary and lifestyle changes. To understand the interface between the gut microbiome, diet, and health of Indonesian people, we characterized fecal microbiomes and metabolomes of 75 Indonesian adults in Yogyakarta City, including 21 obese people and 25 type 2 diabetes (T2D) patients, together with their dietary and medical records. Variations of microbiomes showed a triangular distribution in the principal component analysis, driven by three dominant bacterial genera, namely Bacteroides, Prevotella, and Romboutsia. The Romboutsia-driven microbiome, characterized by low bacterial diversity and high primary bile acids, was associated with fat-driven obesity. The Bacteroides-driven microbiome, which counteracted Prevotella but was associated with Ruminococcaceae concomitantly increased with high-carbohydrate diets, showed positive correlation with T2D indices but negative correlation with body mass index. Notably, Bacteroides fragilis was increased in T2D patients with a decrease of fecal conjugated bile acids, particularly tauroursodeoxycholic acid, a farnesoid X receptor antagonist with anti-diabetic activity, while these features disappeared in patients administered metformin. These results indicate that the gut microbiome status of Indonesian adults is differently associated with obesity and T2D under their varied dietary habits.

Risk Analysis of Live Fire Shoot House Containment Systems Against Multiple Projectile Impacts

Many analytical and numerical models exist that can describe the effect of single projectile impacts on steel targets. These models are not adequate for the evaluation of live fire shoot house containment systems, which are subjected to repeated impact loading from small caliber projectiles over the lifetime of the structure. Models assuming perfectly rigid projectiles over-predict penetration depths. Models assuming rigid targets cannot predict any penetration, and hydrodynamic models are best suited to high velocity impacts well above the ranges of conventional ordinance. Development of sufficient analytical or numerical tools using traditional techniques would be either intractable, empirically based and unique to a given scenario, require unique material properties that are not commonly available, or require significant computational effort. Due to the limited amount of empirical data on multiple impact failure, classical reliability methods are not suitable for assessing the probability of containment system perforation. Using existing experimental results of .223 caliber ammunition against AR500 steel panels with 2-inch ballistic rubber, a commonly found protective system in these facilities, the cumulative effects of multiple projectiles were quantified to estimate the number of impacts required to perforate the target material. Impacts were simulated from normal distributions of the x and y coordinates describing the impact point using a cartesian coordinate plane. The impact resistance of the steel was also simulated from a triangular distribution to account for the variability of the experimental results. Monte Carlo Simulation was then used to estimate the expected number of impacts to cause failure at a single point on the target. Using this collective model, it was possible to determine that the distribution of the number of rounds to cause target failure approached a normal distribution. The results indicated that the mean impacts at failure was 11800 with a standard deviation of 800 impacts. Finally, targeting the allowable risk level for structural failure from the JCSS probabilistic model code from the simulated normal distribution, it was determined that the safe number of impacts was approximately 7996. Decision makers can utilize the safe number of impacts to inform training guidance for the future use of facilities and to develop effective inspection requirements. This model can also be adapted to evaluate similar training facilities and to assess how other small caliber projectile impacts would affect live fire shoot house containment systems, providing a useful tool for the design and analysis of future and the assessment of existing facilities for use with ammunition that did not exist during its design.

On the Distribution in Height of Base Shear Forces in Linear Static Analysis of Base-Isolated Structures

Although base isolation is nowadays a well-established seismic-protection technique for both buildings and bridges, and several issues are still open and attract the interest of the research community. Among them, the formulation of computationally efficient and accurate analysis methods is a relevant aspect in structural design of seismic-isolated buildings. In fact, codes and guidelines currently in force in various parts of the world generally include the possibility for designers to utilize linear-elastic analysis methods based on equivalent linearization of the non-linear force-displacement response of isolators. This paper proposes a formula for defining the force distribution in height that should be considered in linear-static analyses to obtain a more accurate approximation of the actual structural response, supposedly simulated by means of non-linear time history analysis. To do that, it summarizes the results of a wide parametric analysis carried out on a batch of structures characterized by three different heights and various properties of base isolators. The reported results highlight that the equivalent static force distribution provided by both Italian and European codes tend to underestimate the actual seismic lateral forces acting on base-isolated buildings, whereas the inverted triangular distribution, proposed in various American codes and standards, is often conservative.