Power Exponential Model Research Articles

Randomized, crossover trial: comparing the effects of standardized egg-white meal and Vital® on global gastric emptying parameters and intragastric meal distribution in healthy Asian participants.

Measurements of gastric emptying and accommodation for alternative test-meal protocol during gastric emptying scintigraphy (GES), such as high-calorie nutrient drinks, are not fully established. We aimed to compare the effects of standardized egg-white meal (EWM) versus high-calorie nutrient drink (Vital®; Abbott Laboratories) on global GES parameters and intragastric meal distribution at immediate scan (IMD0h). Of 84 screened participants, 60 asymptomatic healthy Asian population (38 females; 24.0±1.5years; 23.8±2.6kg/m2) were recruited in this 2×2 (AB/BA) crossover trial. Participants were randomized to a 4-h GES with 99mTc-radiolabeled EWM (~255.8kcal), followed by a 200mL Vital® (300kcal), or vice versa, separated by a 2-week washout period. Global meal retention (GMR), power-exponential model emptying parameters (half-emptying [T1/2], lag phases [Tlag2%, Tlag5%, Tlag10%]), and IMD0h were determined and compared. GMRs for both test meals were within the international standard references for solid GES. Compared to EWM, Vital® exhibited significantly lower GMRs (faster emptying) from 0.5 to 3h (all P<0.001) but comparable at 4h (P=0.153). Similar observations were found for the model-based T1/2 and the different Tlag thresholds (all P<0.001). Furthermore, IMD0h was found to be lower with Vital®, indicating lower gastric accommodation (faster antral filling) immediately post-ingestion (P<0.001). Both test meals showed significant moderate-to-strong positive associations at the late-phase GE (GMR 2-4h, T1/2) (all P<0.05). Overall, Vital® is an acceptable alternative test meal to the EWM for GES; however, exercise caution when interpreting early-phase GE. The normative values for global GES parameters and IMD0h are also established.

Predicting the needs of people living with a disability using the two-level logit-skewed exponential power model

Predicting the needs of people living with a disability using the two-level logit-skewed exponential power model

Facilitating Clinical Use of the Amsterdam Instrumental Activities of Daily Living Questionnaire: Normative Data and Diagnostic Cutoff Values

AbstractBackgroundThe Amsterdam Instrumental Activities of Daily Living Questionnaire(A‐IADL‐Q) measures impairments in everyday functioning in the context of dementia. To facilitate interpretation and clinical implementation of the A‐IADL‐Q, we aimed to generate demographically‐adjusted norm scores and a clinical cutoff value.MethodCross‐sectional data were used from Dutch Brain Research Registry(N = 1,064; mean (M) age = 62±11year; 69.5% female) European Medial Information Framework‐Alzheimer’s Disease(EMIF‐AD) 90+ (N = 63; Mage = 92±2year; 52.4% female), and European Prevention of Alzheimer’s Dementia Longitudinal Cohort Study(EPAD‐LCS)(N = 300; Mage = 62±7year; 71.7% female)(Table 1). Norm scores were generated using a I) linear regression model approach; and II) Box‐Cox Power Exponential(BCPE) model approach (the latter falling within the generalized model for location shape and size(GAMLSS) framework). For both methods, different combinations of the variables age, sex and education were tested (including polynomial age and age*education interaction) and the best model was selected based on the lowest Aikake Information Criteria(AIC) value. Next, diagnostic contrast was generated using an independent memory clinic sample (the Amsterdam Dementia Cohort(ADC)(N = 2,123, Mage = 64±8year, 46.1% female)(Table 1), including people with dementia (both Alzheimer’s Disease(AD) and non‐AD). The optimal cut‐off value for cognitively healthy versus dementia was determined, and corresponding diagnostic accuracy was calculated using area under the receiver operating curves(AUC‐ROC). This optimal cutoff was then applied to different diagnostic contrasts, including mild cognitive impairment(MCI) and subjective cognitive decline(SCD).ResultThe best suitable normative model was the linear regression model, including cubic polynomial for age, education, and age*education interaction. This model was considered superior to the best BCPE model, which had infinitely large residuals due to bad model fit. The optimal cutoff to distinguish normal functioning from dementia, based on bootstrap average estimates of the Youden Index, was 1.82 standard deviation(SD) below the population mean, resulting in an AUC of 0.97[95%CI 0.98‐0.98]). Normative data are made publicly available in an online tool(Fig.1).ConclusionWe established demographically adjusted norm scores for the A‐IADL‐Q using a large representative sample, and provided an optimal cutoff value for cognitively healthy versus dementia, with outstanding accuracy. Our results, captured in the online tool, can help clinicians to interpret A‐IADL‐Q scores more easily by allowing comparison of functioning against a reference population.

Product of Spacing Estimation of Stress–Strength Reliability for Alpha Power Exponential Progressively Type-II Censored Data

The present study focuses on estimating the stress–strength parameter when the parent distribution is the alpha power exponential model and the available data are progressively Type-II censored. As a starting point, the usual maximum likelihood approach is applied to obtain point and interval estimates of the model parameters, as well as the stress–strength parameter. Another competing strategy employed in this paper is the maximum product of spacing method, which may be thought of as a rival to the maximum likelihood method. The product of spacing approach is used to obtain point and interval estimates for the various parameters. The asymptotic properties of both methods are used to obtain interval estimates of the model parameter and the stress–strength parameter, and the variance of the stress–strength parameter is approximated using the well-known delta method. Two parametric bootstrap confidence intervals are provided based on the suggested classical estimation procedures. A simulation study is also used to assess the performance of various point and interval estimations. For illustrative purposes, the proposed methods are applied to two real data sets, one for the kidney patients’ recurrence times to infection and the other for breaking the strength of jute fibers.

Dynamical Systems Analysis of f(Q) Gravity

Modified gravity theories can be used for the description of homogeneous and isotropic cosmological models through the corresponding field equations. These can be cast into systems of autonomous differential equations because of their sole dependence on a well-chosen time variable, be it the cosmological time, or an alternative. For that reason, a dynamical systems approach offers a reliable route to study those equations. Through a model-independent set of variables, we are able to study all f(Q) modified gravity models. The drawback of the procedure is a more complicated constraint equation. However, it allows the dynamical system to be formulated in fewer dimensions than using other approaches. We focus on a recent model of interest, the power-exponential model, and generalize the fluid content of the model.

Health expenditure in households with disabled people

The major goal of a household is to maximise the satisfaction of the needs of its members through the consumption of appropriate goods and services. One of the main needs, especially in households with people with disabilities, is health protection, which entails comparatively large financial outlays. The aim of this study is to recognise regularities in health expenditure of households with disabled people, to assess the significance of health expenditure in the structure of these households' expenditure, and to attempt to identify the determinants of health expenditure. The study is based on data obtained from two editions of Statistics Poland's household budget survey, performed in 2009 and in 2019. The study presents an analysis of the diversification of the level and structure of the health-related expenditure of households in Poland. The power-exponential model was used to identify the determinants of these expenses. The analysis shows that households with disabled people have a lower disposable income and, at the same time, incur higher health expenses. Health-related expenditure in households with disabled people is mainly determined by: age, level of income, the fact whether a household member/members is/are a person/s with a, significant degree of disability, and source of income.

New models and big bang nucleosynthesis constraints in f(Q) gravity

The f(Q) theories of modified gravity arise from the consideration of non-metricity as the basic geometric quantity, and have been proven to be very efficient in describing the late-time Universe. We use the Big Bang Nucleosynthesis (BBN) formalism and observations in order to extract constraints on various classes of f(Q) models. In particular, we calculate the deviations that f(Q) terms bring on the freeze-out temperature T_f in comparison to that of the standard Lambda CDM evolution, and then we impose the observational bound on left| frac{delta {T}_f}{{T}_f}right| to extract constraints on the involved parameters of the considered models. Concerning the polynomial model, we show that the exponent parameter should be negative, while for the power-exponential model and the new hyperbolic tangent-power model we find that they pass the BBN constraints trivially. Finally, we examine two DGP-like f(Q) models, and we extract the bounds on their model parameters. Since many gravitational modifications, although able to describe the late-time evolution of the Universe, produce too-much modification at early times and thus fall to pass the BBN confrontation, the fact that f(Q) gravity can safely pass the BBN constraints is an important advantage of this modified gravity class.

Kinetics of the direct reaction between ozone and phenol by high-gravity intensified heterogeneous catalytic ozonation

In this study, high-gravity intensified heterogeneous catalytic ozonation is utilized for treatment of phenol-containing wastewater, and the kinetics of the direct reaction between ozone and phenol in the presence of excess tertiary butanol (TBA) is investigated. It is revealed that the direct reaction between ozone and phenol in the rotating packed bed (RPB) follows the pseudo-first-order kinetics with a reaction rate constant higher than that in the conventional bubbling reactor (BR). Under different conditions of temperature, initial pH, high-gravity factor, and gaseous ozone concentration, the apparent reaction rate constant varies in the range of 0.0160−0.115 min-1. An empirical power-exponential model is established to characterize the effects of these parameters on the direct reaction between ozone and phenol by high-gravity intensified heterogeneous catalytic ozonation.

Modeling asymmetric volatility of financial assets using univariate GARCH models: An Indian perspective

In recent years, numerous models with various amounts of variance have been developed to estimate and forecast important characteristics of time series data. While there are many studies on asymmetric volatility and accuracy testing of univariate Generalized Autoregressive Conditional Heteroscedasticity models, there are no parallel studies involving multiple financial assets and different heteroscedastic models and density functions. The objective of this study is to contrast the forecasting accuracy of univariate volatility models with Normal and Student-t distributions in forecasting the volatility of stock, gold futures, crude futures, exchange rate, and bond yield over a 10-year time span from January 2010 through December 2021 in Indian market. The results of exponential, threshold and asymmetric power models show that the volatility stock (–0.12047, 0.17433, 0.74020 for Nifty, and –0.1153, 0.1676, 0.7372 for Sensex), exchange rate (–0.0567, 0.0961,0.9004), crude oil futures (-0.0411, 0.0658, 0.2130), and bond yield (–0.0193, 0.0514 and –0.0663) react asymmetrically to good and bad news. In case of gold futures, an inverse asymmetric effect (0.0537, –0.01217, –0.1898) is discovered; positive news creates higher variance in gold futures than bad news. The Exponential model captures the asymmetric volatility effect in all asset classes better than any other asymmetric models. This opens the door for many studies in Indian financial market.

Lower bound estimation of recommendation error through user uncertainty modeling

In machine learning, the Bayesian error is the lower bound of the prediction error induced by data distribution. In recommender systems, this is also known as the magic barrier (MGBR). MGBR estimation is an important issue because the recommended data frequently contain considerable uncertainties that are difficult to quantify. It is possible to determine the extent to which the recommendation algorithm can be optimized by obtaining the MGBR for a given dataset. MGBR estimation generally requires real user ratings that are not affected by external factors such as human emotions and living environment, which can be extremely difficult or even impossible to gather. Existing theoretical approaches based on simple models, such as Gaussian distributions, have limited estimation capabilities. In this paper, we propose a more sophisticated mixture of exponential power (MoEP) model, which enables adaptive parameter selection for intricate uncertainty. To fit the distribution of the real data, we constructed a flexible learning model that automatically adjusts super- or sub-Gaussian uncertainties using the MoEP components. To select parameters adaptively, we employed an expectation-maximization algorithm to infer the parameters of the components. To estimate the MGBR, we explored an approach for calculating the lower bound of the prediction error under the guidance of a probability model. Experiments on the four datasets validated the rationality of the proposed method. The results show that the MGBR estimated using the new model is marginally lower than the prediction error of state-of-the-art algorithms.

Inferences of a Mixture Bivariate Alpha Power Exponential Model with Engineering Application

The univariate alpha power exponential (APE) distribution has several appealing characteristics. It behaves similarly to Weibull, Gamma, and generalized exponential distributions with two parameters. In this paper, we consider different bivariate mixture models starting with two independent univariate APE models, and, in the latter case, starting from two dependent APE models. Several useful structural properties of such a mixture model (under the assumption of two independent APE distribution) are discussed. Bivariate APE (BAPE), in short, modelled under the dependent set up are also discussed in the context of a copula-based construction. Inferential aspects under the classical and under the Bayesian paradigm are considered to estimate the model parameters, and a simulation study is conducted for this purpose. For illustrative purposes, a well-known motor data is re-analyzed to exhibit the flexibility of the proposed bivariate mixture model.

Description and prediction of stress-strain curve of loess

The accurate description of the stress-strain relationships of rock and soil is very important to analyze its mechanical properties, but the forms of stress-strain curves are different, which can be softening, hardening, or ideal elastoplastic. With the change of confining pressure, they can be transformed into each other. Taking one of loess as the research object, consolidated drained triaxial tests of undisturbed loess under different confining pressures are carried out. The stress-strain relationship obtained is described by the composite power exponential model (CPE model). According to the results, the critical confining pressure during the transformation of the stress-strain curve and the stress-strain relationship under a given confining pressure are predicted. The comparison with the experimental data shows that the CPE model has high accuracy in description and prediction, and the predicted critical confining pressure can correctly judge the type of stress-strain curve of undisturbed loess under different confining pressures. The predicted ideal elastic-plastic stress-strain curve and the curves under given confining pressures conform to the curve change law, which can reflect the real characteristics of loess. Finally, the stress-strain curves of coral clay, silica sand and cement mortar are described and predicted by the CPE model, and then compared with the experimental data. The high consistency between the two further verifies the wide applicability of the CPE model. It provides a method to infer the results under other conditions from a limited number of test results, which will help to correctly analyze the mechanical properties of loess, clay, sand, cement mortar and other materials in practical projects, and to be realized in numerical analysis.

Optimal Plan of Multi-Stress–Strength Reliability Bayesian and Non-Bayesian Methods for the Alpha Power Exponential Model Using Progressive First Failure

It is extremely frequent for systems to fail in their demanding operating environments in many real-world contexts. When systems reach their lowest, highest, or both extreme operating conditions, they usually fail to perform their intended functions, which is something that researchers pay little attention to. The goal of this paper is to develop inference for multi-reliability using unit alpha power exponential distributions for stress–strength variables based on the progressive first failure. As a result, the problem of estimating the stress–strength function R, where X, Y, and Z come from three separate alpha power exponential distributions, is addressed in this paper. The conventional methods, such as maximum likelihood for point estimation, Bayesian and asymptotic confidence, boot-p, and boot-t methods for interval estimation, are also examined. Various confidence intervals have been obtained. Monte Carlo simulations and real-world application examples are used to evaluate and compare the performance of the various proposed estimators.

Permeability change with respect to different hydrate saturation in clayey-silty sediments

The successful pilot trial of methane hydrate production in the South China Sea has proven the technical feasibility of natural gas hydrates (NGHs) exploitation in clayey-silty reservoirs. As a key issue of NGHs exploitation in clayey-silty sediments, the variation of permeability with hydrate saturation (Sh) has not been thoroughly studied. In this study, a triaxial core holder was designed to simulate the synthesis and dissociation of gas hydrates in a clayey-silty core plug sample. In the process of hydrate synthesis and multi-step dissociation, the water content and distribution in different pores were quantitatively determined by a nuclear magnetic resonance (NMR) spectrometer, and the variation of water content under different Sh was successively monitored. Meanwhile, in each depressurization phase, the gas permeabilities k(Sh) with respect to different Sh were measured under constant effective stress. Results highlight that the change of k(Sh) is more prevalent in clayey-silty sediments than that in sandstones. As Sh increases from 0 to 10.43%, the permeability ratio (k(Sh) to sedimentary permeability ks) in clayey-silty sediments decreases to 0.01–0.02; whereas in sandstones, the permeability ratio falls between 0.4 and 0.8. To predicate the permeability change in clayey-silty sediments, the previous Cubic model is improved and a Power-exponential model is presented. In the updated model, the variable of power parameter n can characterize different reservoir types. Specifically, in artificial sandstones, sandpacks or sandy reservoirs, the n values range from 3.1 to 8.3, while in clay packs or clayey-silty sediments, the n values are from 19.1 to 30.7. The Power-exponential model provides reference values for the prediction of different types of gas hydrate reservoirs such as permafrost and marine sediments.

Extended Half-Power Exponential Distribution with Applications to COVID-19 Data

In this paper, the Extended Half-Power Exponential (EHPE) distribution is built on the basis of the Power Exponential model. The properties of the EHPE model are discussed: the cumulative distribution function, the hazard function, moments, and the skewness and kurtosis coefficients. Estimation is carried out by applying maximum likelihood (ML) methods. A Monte Carlo simulation study is carried out to assess the performance of ML estimates. To illustrate the usefulness and applicability of EHPE distribution, two real applications to COVID-19 data in Chile are discussed.

Deep root information “hidden in the dark”: A case study on the 21-m soil profile of Robinia pseudoacacia in the critical zone of the Chinese loess Plateau

Deep roots can uptake deep soil water to support plant growth and mitigate climate change in water-limited ecosystems. Few studies have been conducted on the deep root characteristics in the soil profile as limited field data are available. To explore the relationship between the deep root characteristics, depth, and soil water status, we obtained the distribution pattern of deep roots and soil water content along a 21-m soil profile (n = 22) in a mature Robinia pseudoacacia plantation. The maximum rooting depth, mean root biomass, and mean depths corresponding to 50% and 90% of the total root biomass of 17-year-old R. pseudoacacia trees were >20 m, 0.083 ± 0.029 g·cm−2, 1.17 ± 1.74, and 6.15 ± 3.98 m, respectively. We established an exponential power model to fit the relationship between the deep root biomass and soil depth, which had a higher goodness-of-fit than the typical exponential model, logistic model, and piecewise linear model. The root morphological characteristics along the 21-m vertical profile rapidly decreased with depth in the 0–1-m layer, and then stabilized, while the specific root length (SRL) and specific root area (SRA) increased with depth. The relationships between the SRL, SRA, and soil water content in the dried soil layers with roots (SWC-DSL) were significantly positive (both p < 0.01), while those between average root diameter density and SWC-DSL were significantly negative (p < 0.001), suggesting that roots increased their length rather than diameter to acquire water resources with relatively low carbon investment. The soil depth and soil water availability co-controlled root biomass and root morphological characteristics. Our findings highlight the importance and complexity of deep roots and their morphological characteristics, which are fundamental for forest models and management to maintain sustainable development between soil water and root water uptake.

Economic Aspects of Population Aging. Modeling Senior Household Ependiture

Purpose: The purpose of the present article is to model senior citizens' household expenditure and try to identify factors that influence consumer behavior in this social group. Analyses of Polish households were used as a case study. Design/Methodology/Approach: The study used selected structure description parameters to characterize the studied population synthetically. Power-exponential econometric models were used to characterize consumer goods and services expenditure in households headed by persons aged 65+. Findings: The power-exponential models used in the article proved to be a valuable tool in the research into spending on consumer goods and services. In all the models, the level of the overall income per capita was found to have a significant positive impact. Another important finding was that the preferences differed depending on the class of the locality of residence, the subjective assessment of the material situation of one's household, the number of persons in the household, and the level of educational background, and the age of the person heading the household. Practical Implications: The research results presented in the paper are of considerable importance for developing a policy addressing the needs of the elderly, including, for example, creating appropriate marketing instruments and preparing an offer aimed at the ever-growing group of senior citizens. Originality/Value: The present article contributes to the most recent European and global scientific discussions on the significance of the elderly for the development of economies from the perspective of their impact on the markets for goods and services.

Compressive Creep Behavior of Cellulose Fiber Reinforced Concrete

The effect of cellulose fiber on the long-term compressive creep performance of concrete was clarified. For this, the long-term compressive creep properties of four cellulose fiber reinforced concrete (CFRC) groups with contents of 0, 0.9 kg/m3, 1.1 kg/m3, and 1.3 kg/m3 were investigated using a spring creep tester. Loading ages of 7 days, 14 days, and 28 days, and a loading stress ratio of 0.40 were employed. Furthermore, the creep model of CFRC was established. The results revealed that the creep of concrete at three loading ages decreases by 16%, 12%, and 17%, respectively, after adding cellulose fiber to the concrete. With increasing loading age, the difference of creep degree of CFRC with different cellulose fiber content decreased gradually. Furthermore, the range of specific creep decreased from 8 × 10−6 / MPa for a 7 day loading age to 2 × 10−6 / MPa for a 28 day loading age. The change regulation of CFRC creep coefficient was similar to that of the specific creep. The influence of the cellulose fiber on the creep performance of the concrete was reflected in two aspects. On the one hand, the internal curing effect of cellulose fiber can optimize the microstructure of concrete and reduce the creep deformation. On the other hand, the fiber increases the water migration channel and defects of interface transition zone, which will increase the creep deformation. The power exponential function model for CFRC creep provided a good description of the relationship between creep and loading age and holding time. This model can be used to predict the long-term creep of CFRC under different loading ages.

Evaluation of the lifetime performance index on first failure progressive censored data based on Topp Leone Alpha power exponential model applied on HPLC data

ABSTRACT In this paper, the statistical inference of the lifetime performance index for the first failure progressive censoring schemes for the Topp Leone Alpha power exponential distribution (TLAPE) which excluded from a new structure of distribution models called T-Alpha Power X (T-APX) family is introduced. The proposed statistical inference of the lifetime performance index is applied on the High-Performance Liquid Chromatography data of blood samples from organ transplant recipients which is known as HPLC. The goodness of fit criteria of TLAPE for HPLC data proved the potentiality of TLAPE compared with other well-known distributions. This result has an effect on achieving the required results in testing procedure of the Lifetime performance index. Moreover, the statistical and reliability characteristics of TLAPE are studied. A simulation study is performed to examine the performance of the ML parameter estimates in terms of bias and mean square error. Two real data sets for survival and breast cancer are modeled using the TLAPE distribution and compared with other well-known distributions, to illustrate its performance. The results emphasize that the TLAPE distribution has a superior fitting performance to cancer data than the compared distributions.

An improved strength degradation model for fatigue life prediction considering material characteristics

Experimental results show that when the loading sequence of fatigue loads changes, the fatigue cumulative damage prediction based on Miner's rule will have a large error, even as high as 252.83%. In an effort to improve the fatigue life predictions, based on the residual strength degradation rule, a power exponential fatigue equivalent damage model is presented in this paper, which contains two material parameters. Experimental data were cited to verify the residual strength model, and the statistical results showed that this model is capable of describing the residual strength degradation of materials. Furthermore, a fatigue cumulative damage model based on residual strength is established to predict the fatigue life. The Miner's rule and other models were compared to validate the model by referring to the test data of different materials under different loading stress levels. And the accuracy of the fatigue life predicted by this model is twice as good as that predicted by others models.