Drawing upon data from the 2018 CHARLS, this paper utilizes MEPI and a 10% threshold indicator to, respectively, assess the energy poverty (EP) status among middle-aged and older adults in China, focusing on the unavailability and unaffordability of energy services. Additionally, an econometric model is constructed to investigate the effects of EP on the health and welfare of middle-aged and older adults. Regression results indicate that EP exerts a significant negative impact on the health and welfare of middle-aged and older adults. This conclusion remains robust after conducting endogeneity and robustness tests, demonstrating its validity. Finally, based on the calculation results, we propose relevant policy recommendations including enhancing energy services for older adults in rural areas, integrating household energy alternatives with targeted poverty alleviation, enhancing monitoring mechanisms, and conducting energy education activities to alleviate EP and improve the quality of life of middle-aged and older adults.

Estimation of body mass from skeletal metrics can reveal important insights into the paleobiology of archeological or fossil remains. The standard approach constructs predictive equations from postcrania, but studies have questioned the reliability of traditional measures. Here, we examine several skeletal features to assess their accuracy in predicting body mass.
Antemortem mass measurements were compared with common skeletal dimensions from the same animals postmortem, using 115 rhesus macaques (male: n = 43; female: n = 72). Individuals were divided into training (n = 58) and test samples (n = 57) to build and assess Ordinary Least Squares or multivariate regressions by residual sum of squares (RSS) and AIC weights. A leave-one-out approach was implemented to formulate the best fit multivariate models, which were compared against a univariate and a previously published catarrhine body-mass estimation model.
Femur circumference represented the best univariate model. The best model overall was composed of four variables (femur, tibia and fibula circumference and humerus length). By RSS and AICw, models built from rhesus macaque data (RSS = 26.91, AIC = -20.66) better predicted body mass than did the catarrhine model (RSS = 65.47, AIC = 20.24).
Body mass in rhesus macaques is best predicted by a 4-variable equation composed of humerus length and hind limb midshaft circumferences. Comparison of models built from the macaque versus the catarrhine data highlight the importance of taxonomic specificity in predicting body mass. This paper provides a valuable dataset of combined somatic and skeletal data in a primate, which can be used to build body mass equations for fragmentary fossil evidence.

Agriculture has been and continues to assume center stage in the economic policy of Ethiopia. Coffee is one of the most vital sources of income for many coffee growers and continues to be still the leading export commodity in the national economy of the country. Despite the economic use, the productivity and quality of the coffee are unsatisfactory. The adoption of coffee yield-enhancing technical efficiency is key to improving coffee productivity and quality. Therefore, this study aims to investigate determinants that influence the technical efficiency of coffee production in Jimma Zone, Southwest Ethiopia. The primary data was collected among 398 coffee growers in research locations during the 2020/21 season. Descriptive statistics and econometric methods were developed for the data analysis. The estimated average value of technical, allocative, and economic efficiencies was 82.63%, 78.35%, and 74.65% respectively, which shows the existence of inefficiency in coffee production in the study area. The findings of OLS regression indicated that technical inefficiency is affected by age, sex, education status, landholding, livestock holding, credit uses, the extension uses, off-farm activity, land ownerships, seed, and variety of coffee planted. Coffee yield technical efficiency was associated with a significantly higher coffee yield and per capita annual income of coffee cultivators. Concerned bodies should give important attention to coffee yield enhancing technical efficiency which is base for improving production. The summary of this coffee production technical efficiency by policymakers and plan designers could bring better enhancement to the coffee cultivator in the study area.

Coronavirus Disease 2019 (COVID-19) is spreading across the world, and vaccinations are running parallel. Coronavirus has mutated into a triple-mutated virus, rendering it deadlier than before. It spreads quickly from person to person by contact and nasal or pharyngeal droplets. The COVID-19 database \'Our World in Data\' was analyzed from February 24, 2020, to September 26, 2021, and predictions on the COVID positives and their mortality rate were made. Factors such as Vaccine data for the First and Second Dose vaccinated individuals and COVID positives that influence the fluctuations in the COVID-19 death ratio were investigated and linear regression analysis was performed. Based on vaccination doses (partial or complete vaccinated), models are created to estimate the number of patients who die from COVID infection. The estimation of variance in the datasets was investigated using Karl Pearson\'s coefficient. For COVID-19 cases and vaccination doses, a quartic polynomial regression model was also created. This predictor model helps to predict the number of deaths due to COVID-19 and determine the susceptibility to COVID-19 infection based on the number of vaccine doses received. SVM was used to analyze the efficacy of models generated.

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Public pro-environmental behavior plays a positive role in solving environmental pollution problems. In a real socioeconomic system, because public pro-environmental behavior has characteristics of externality and interactivity, a number of factors, such as external information and the behavior of others, could affect the pro-environmental behavior of individuals who optimize their own strategies by interacting with the outside world; thus, public pro-environmental behavior and social interaction are very closely related. In order to study the impact of social interaction on public pro-environmental behavior and its mechanisms, the authors of this paper conducted an empirical study based on an Ordinary Least Square (OLS) regression model and data from the Chinese General Social Survey (CGSS). The empirical results show that: (1) social interaction has a promoting effect on public environmental protection behavior, and social interaction has a more significant impact on private environmental protection behavior; (2) the public will not only adjust their own environmental protection behavior by directly observing the behavior of others, they will also obtain environmental protection knowledge through social interactions which thus have a positive impact on their behavior. It is of great practical significance to study the impact of social interactions on public pro-environmental behavior.

This study discusses quantile regression methodology and its usefulness in education and social science research. First, quantile regression is defined and its advantages vis-à-vis vis ordinary least squares regression are illustrated. Second, specific comparisons are made between ordinary least squares and quantile regression methods. Third, the applicability of quantile regression to empirical work to estimate intervention effects is demonstrated using education data from a large-scale experiment. The estimation of quantile treatment effects at various quantiles in the presence of dropouts is also discussed. Quantile regression is especially suitable in examining predictor effects at various locations of the outcome distribution (e.g., lower and upper tails).

Using a large sample of adjudicated delinquent male youth (N = 696), we compared data from youth who had been adjudicated for sexually aggressive crimes and those who had been adjudicated for nonsexual offenses on eating dysfunction, body disapproval, history of sexual abuse, and pornography exposure. The sample included 526 (75.8%) youth adjudicated for sexual offenses and 170 (24.4%) youth adjudicated for nonsexual crimes. The average age of the sample was 16.8 years (SD = 1.6), and approximately half of the sample (47.7%, n = 310) self-identified as White. The results of hierarchical multiple regressions indicated that sexually aggressive youth scored significantly higher than nonsexually offending youth on both eating dysfunction and body disapproval measures. Pornography exposure and substance use predicted body disapproval and eating dysfunction in the entire sample of adjudicated youth. History of sexual abuse was a significant predictor of body disapproval in all adjudicated youth but was not a significant predictor of eating dysfunction. Implications for research and practice are offered.