Inter-Party Competition, Public Electoral Pressure, and Democratic Strength: Refining Political Explanations of Incarceration Trends in the U.S., 1980 – 2010

The purpose of this research is to advance the politics of mass imprisonment literature by testing and specifying the macro-explanations of the state-level incarceration change in the United States (U.S.) between 1980 and 2010. Specifically, I account for mechanisms of inter-party competition and public electoral pressure neglected in prior research. To accomplish this goal, I utilize random coefficient models designed to control for repeated annual measures of state-level data that overwhelm traditional analytic techniques. Findings suggest that violent crime, partisan affiliation of state legislators and governors, probation rates, citizen ideology, marijuana decriminalization, and recidivist-focused laws are associated with incarceration as hypothesized, as well as the African American presence net of crime and socioeconomic disadvantage. Contributing to the theoretical debates on democracy and punishment, this paper demonstrates that inter-party competition and public electoral pressure amplify incarceration in the context of Democratic Party dominance, where no liberalizing effects of competition were found. I conclude that legal and extralegal factors are associated with incarceration and suggest that the public did not oppose criminal justice expansion via democratic feedback mechanisms, so both penal populism (Pratt, 2008) and popular punitivism (Campbell et al., 2017) are valid interpretations of imprisonment politics during the analyzed period.

Household Water Insecurity Is Common and Associated With Higher Odds of Hunger and Lower Dietary Diversity Across Sub-Saharan Africa and Asia

Objectives Household water insecurity may exacerbate poor nutrition (e.g., via limited water to produce or prepare preferred foods) and health, but comparable quantification of water access and use has only recently become possible. We therefore aimed to assess the prevalence of household water insecurity and estimate its association with dietary diversity, hunger, and illness. Methods The International Food Policy Research Institute is conducting panel phone surveys among a random subsample of men and women in ongoing studies to understand the impacts of the COVID-19 pandemic. Surveys last 20–30 minutes and include information about respondent and household characteristics; experiences with household water insecurity [using the Household Water Insecurity Experiences Scale-4 (HWISE-4), range: 0–12], hunger, and illness in the prior 2 weeks; and 24-hour dietary recall (range: 0–10 food groups). We assessed the relationship between water insecurity and dietary diversity, hunger, and illness using random coefficient models (which account for variation by site and adjust for measured confounders) among sites with available baseline data: Senegal (interviews conducted June 2020, n = 501), Nepal (July 2020, n = 759), Ghana (September 2020, n = 543), Nigeria (September 2020, n = 501), Kenya (October 2020, n = 547), and Niger (October 2020, n = 364). Additional data from other sites and timepoints are forthcoming. Results The prevalence of water insecurity (HWISE-4 scores > 3) ranged from 8.9% of sampled households in Nepal to 47.4% in Ghana. In bivariate analyses for each site, household water insecurity did not differ by respondent sex but was consistently lower among households that had an on-premises compared to off-premises water source [e.g., mean, 2.3 vs. 3.7, p < 0.001 in Senegal]. In adjusted models across all sites, greater water insecurity was associated with lower dietary diversity (B: –0.08; 95% CI: –0.10, –0.05), and higher odds of experiencing hunger (OR: 1.10; 95% CI: 1.08, 1.14) and having an ill household member (OR: 1.04; 95% CI: 1.01, 1.07). Conclusions Water insecurity is experienced by many households and may be an important determinant of nutritional and physical well-being. Funding Sources The Bureau for Resilience and Food Security at the United States Agency for International Development.

Multifactor Systematic Risk Analysis Based on Time-varying Signal Processing Models

This thesis applies the time-varying signal processing models to track the multifactor systematic risk in the Fama-French model. The mean reverting, random walk and random coefficient models are used to analyze the time-varying multifactor beta based on the multivariate Kalman filter algorithm. The sudden changes in the mutifactor beta ar e captured by the piecewise constant model. Our case studies explain the impacts of economic events on the sudden changes in betas for both individual stocks and industrial portfolios. We propose a new time-varying beta model based on a piecewise mean reverting process to express the effects of different types of events on the multifactor beta.The tracking of the piecewise mean reverting beta, using the modified multivariate Kalman filter with the maximum log likelihood estimator, outperforms the traditional piecewise constant and random walk models as demonstrated in our simulations. The empirical tests indicate that the new model effectively captures the different changes in beta depending on the type of event.

Multifactor Systematic Risk Analysis Based on Time-varying Signal Processing Models

This thesis applies the time-varying signal processing models to track the multifactor systematic risk in the Fama-French model. The mean reverting, random walk and random coefficient models are used to analyze the time-varying multifactor beta based on the multivariate Kalman filter algorithm. The sudden changes in the mutifactor beta ar e captured by the piecewise constant model. Our case studies explain the impacts of economic events on the sudden changes in betas for both individual stocks and industrial portfolios. We propose a new time-varying beta model based on a piecewise mean reverting process to express the effects of different types of events on the multifactor beta.The tracking of the piecewise mean reverting beta, using the modified multivariate Kalman filter with the maximum log likelihood estimator, outperforms the traditional piecewise constant and random walk models as demonstrated in our simulations. The empirical tests indicate that the new model effectively captures the different changes in beta depending on the type of event.

Projecting results of zoned multi-environment trials to new locations using environmental covariates with random coefficient models: accuracy and precision

Key message We propose the utilisation of environmental covariates in random coefficient models to predict the genotype performances in new locations. Abstract Multi-environment trials (MET) are conducted to assess the performance of a set of genotypes in a target population of environments. From a grower’s perspective, MET results must provide high accuracy and precision for predictions of genotype performance in new locations, i.e. the grower’s locations, which hardly ever coincide with the locations at which the trials were conducted. Linear mixed modelling can provide predictions for new locations. Moreover, the precision of the predictions is of primary concern and should be assessed. Besides, the precision can be improved when auxiliary information is available to characterize the targeted locations. Thus, in this study, we demonstrate the benefit of using environmental information (covariates) for predicting genotype performance in some new locations for Swedish winter wheat official trials. Swedish MET locations can be stratified into zones, allowing borrowing information between zones when best linear unbiased prediction (BLUP) is used. To account for correlations between zones, as well as for intercepts and slopes for the regression on covariates, we fitted random coefficient (RC) models. The results showed that the RC model with appropriate covariate scaling and model for covariate terms improved the precision of predictions of genotypic performance for new locations. The prediction accuracy of the RC model was competitive compared to the model without covariates. The RC model reduced the standard errors of predictions for individual genotypes and standard errors of predictions of genotype differences in new locations by 30–38% and 12–40%, respectively.

The influence of environmental and core temperature on cyclooxygenase and PGE2 in healthy humans

Whether cyclooxygenase (COX)/prostaglandin E2 (PGE2) thermoregulatory pathways, observed in rodents, present in humans? Participants (n = 9) were exposed to three environments; cold (20 °C), thermoneutral (30 °C) and hot (40 °C) for 120 min. Core (Tc)/skin temperature and thermal perception were recorded every 15 min, with COX/PGE2 concentrations determined at baseline, 60 and 120 min. Linear mixed models identified differences between and within subjects/conditions. Random coefficient models determined relationships between Tc and COX/PGE2. Tc [mean (range)] increased in hot [+ 0.8 (0.4–1.2) °C; p < 0.0001; effect size (ES): 2.9], decreased in cold [− 0.5 (− 0.8 to − 0.2) °C; p < 0.0001; ES 2.6] and was unchanged in thermoneutral [+ 0.1 (− 0.2 to 0.4) °C; p = 0.3502]. A relationship between COX2/PGE2 in cold (p = 0.0012) and cold/thermoneutral [collapsed, condition and time (p = 0.0243)] was seen, with higher PGE2 associated with higher Tc. A within condition relationship between Tc/PGE2 was observed in thermoneutral (p = 0.0202) and cold/thermoneutral [collapsed, condition and time (p = 0.0079)] but not cold (p = 0.0631). The data suggests a thermogenic response of the COX/PGE2 pathway insufficient to defend Tc in cold. Further human in vivo research which manipulates COX/PGE2 bioavailability and participant acclimation/acclimatization are warranted to elucidate the influence of COX/PGE2 on Tc.

Assessing Direct Marketing Effectiveness at a Retailer’s: a Mixed-Effects Model of Heterogeneous Responsiveness to Personalized Promotions

This study proposed a mixed linear modeling framework for revealing the average treatment effects of coupon promotions as well as for figuring out what kind of customers are more responsive to coupon promotions. The analysis used detailed data on 2,469 households who are frequent shoppers at a retailer over one year. A series of models starting from fixed parameters OLS regression to more flexible random coefficient models were built. The results showed that receiving more coupon promotions does not lead to higher spending among households. None of the available demographic characteristics was significantly linearly related to the responsiveness to coupon promotions according the initial model with cross-level interaction terms. However, exploratory analysis of random slopes with the help of a regression tree allowed to correct the specification, which allowed confirming that people aged 25+ with annual household income exceeding $25,000 are more responsive, yet their response is insignificantly different from zero. Keywords: Mixed-Effects Model, Multilevel Analysis, Heterogeneous Responsiveness, Promotions.

PSVII-24 Weight at maturity of water buffaloes determined by body chemical composition

This study determined the weight at maturity (WM) of water buffaloes of three genetic groups (GG:Jafarabadi, Mediterranean, and Murrah) slaughtered at different weights (420, 480, and 540 kg). One-hundred-fifty-three non-castrated male (means of initial body weight and age of 314 ±117 kg and 390 ±32 days, respectively) from two similar experiments were used. The animals were slaughtered and the non-carcass components of each animal were weighed to obtain the empty body weight (EBW). The left half-carcasses were dissected into muscle, fat, and bone. Each tissue of each animal was ground separately and subsequently aliquoted for further analyses. The determination of moisture, crude protein (CP), ether extract (EE), and ash was performed by the classical method. Nonlinear regressions were used to predict the body composition of water, CP and ash. An exponential model was used to adjust the data for the content of the EE. Random coefficient models were used to identify fixed and random effects using the NLMIXED procedure in SAS. The genetic group was tested as fixed effect and year as a random effect. Body CP was determined based on CP fat-free dry matter (CPFFDM). The equations predicted the body composition of CP, EE, water and ash, and the results were expressed as a percentage of the EBW. WM was estimated when the non-significant increase in CPFFDM was no longer observed. There was effect of GG for WM model (P = 0.037), thus the WM was determined for each GG. The models suggest that Jafarabadi reach maturity at ~505.93kg of EBW [WMCPFFDM=79.279×(1–1.17×e-0.010×EBW)]; Mediterranean reach maturity at ~494.40kg of EBW [WMCPFFDM=79.186×(1–1.18×e-0.011×EBW)]; Murrah reach maturity at ~423.79kg of EBW [WMCPFFDM=78.793×(1–11.99×e-0.018×EBW)]. In conclusion, the WM of water buffaloes is dependent on the GG reaching 505.93, 494.90, 423.79 kg of EBW for the Jafarabadi, Mediterranean, and Murrah genetic groups, respectively.

Sexual satisfaction of middle-aged and older adults: longitudinal findings from a nationally representative sample

Background whilst previous studies have investigated the determinants of sexual satisfaction (i) using longitudinal data or (ii) among older adults, only a few studies have done both at the sametime. Objective the purpose of this study was to investigate the determinants of sexual satisfaction longitudinally among middle-aged and older adults. Design nationally representative longitudinal study (German Ageing Survey—DEAS). Setting community-dwelling individuals in Germany. Data drawn from three waves (2002, 2008, 2011). Subjects individuals aged 40–95 (36.9% age group 65+). At wave 2 in the year 2002, n = 3,843 individuals took part. Methods well-established and widely used scales were used to quantify the independent variables. We included variables such as sociodemographic factors, self-rated health, physical functioning, depression and loneliness in our analysis. Sexual satisfaction was our outcome measure. Results were stratified by age (40–64, 65+). To take into account the multilevel data structure, we used random coefficient models. Results random-effects regressions showed that increased sexual satisfaction was consistently associated with the following variables in both age groups: lower number of physical illnesses, β = −0.03, P &lt; 0.001 (betas coefficients given for individuals 65 years and over); better self-rated health, β = −0.06, P &lt; 0.001; absence of depression, β = −0.16, P &lt; 0.01; and higher importance of sexuality and intimacy, β = 0.08, P &lt; 0.001. Moreover, sexual satisfaction was associated with having a partner: β = 0.16, P &lt; 0.001; living with a partner in the same household, β = 0.26, P &lt; 0.001; and a lower score of loneliness, β = −.28, P &lt; 0.001. In contrast, sexual satisfaction was, for example, not associated with cognitive functioning. Conclusions the most surprising findings were that among both middle-aged and older adults, almost the same determinants (with exception of sociodemographic factors) were associated with satisfaction with sexlife.