The Economic and Demographic Determinants of Oregon Lottery Sales

Understanding the determinants of Oregon lottery sales is important, as lottery revenues fund a variety of government programs. Our research uses Oregon county-level per capita income data collected from the Bureau of Economic Analysis, and county-level demographic data collected from GeoFred, the Bureau of Economic Analysis, and Portland State Population Demographics to estimate how economic and demographic factors impact lottery sales in Oregon. The results indicate that the income elasticity of demand for the Oregon lottery is 1, implying that lottery sales represent a constant share of Oregonians’ incomes. Additionally, we find that lottery sales vary as a function of gender, age, and education levels

What Attributes Explain Variation in the Prices of Willamette Valley Pinot Noir?

Oregon Pinot Noir is known around the world for having a price point that many can afford while not abandoning the quality that was once only produced by reputable French Chateaus. Understanding what makes one bottle cost more than another is something that must be considered in order to find a price that will satisfy both the consumer and the winemaker. The hedonic pricing model used in this research employs data collected from winery websites such as the WineMag, a highly regarded website for ratings of wines across all price points. A cross sectional model is estimated. Results show that three factors of the eight tested are significant in explaining the prices of Pinot Noir. The significant factors are the alcohol percentage of the wine, LIVE (a sustainability certification), and the rating provided by the WineMag

Adding to the shame of poverty: the public, politicians and the media

The denigration of people in poverty is not new. It has been evident since at least the dissolution of the monasteries under Henry VIII when the Tudor state assumed de facto responsibility for the care of ‘paupers’, and the terms ‘deserving’ and ‘undeserving’ were coined. The words used have changed and the vehemence of the language has ebbed and flowed, but the divisive, self-justifying distinction between the workless, rogues, idlers and scroungers on the one hand and the hardworking, law-abiding, responsible, ‘middle class’, taxpayer has not. Robert Walker and Elaine Chase draw on their recent research to highlight how recent welfare reforms continue our long tradition of shaming people who live in poverty

The indignity of the Welfare Reform Act

At the 101st session of its conference in June this year, the International Labour Organization agreed Recommendation 202 on national social protection floors. Esoteric though it sounds, this sets standard that has the potential to require the radical upgrading of the British social security system. Robert Walker, Elaine Chase and Ivar Lødemel provide an overview of the Recommendation’s context, and argue why its rights-based approach and emphasis on dignity matter to UK anti-poverty programmes

Athletic Trainers\u27 Perceptions of the BOC\u27s Testing Over Practical Knowledge and Application in Daily Practice

Please enjoy Volume 7, Issue 1 of the JSMAHS. In this issue, you will find Professional, Graduate, and Undergraduate research abstracts, and case reports. Thank you for viewing this 7th Annual OATA Special Edition

Integrated Decision Gradients: Compute Your Attributions Where the Model Makes Its Decision

Attribution algorithms are frequently employed to explain the decisions of neural network models. Integrated Gradients (IG) is an influential attribution method due to its strong axiomatic foundation. The algorithm is based on integrating the gradients along a path from a reference image to the input image. Unfortunately, it can be observed that gradients computed from regions where the output logit changes minimally along the path provide poor explanations for the model decision, which is called the saturation effect problem. In this paper, we propose an attribution algorithm called integrated decision gradients (IDG). The algorithm focuses on integrating gradients from the region of the path where the model makes its decision, i.e., the portion of the path where the output logit rapidly transitions from zero to its final value. This is practically realized by scaling each gradient by the derivative of the output logit with respect to the path. The algorithm thereby provides a principled solution to the saturation problem. Additionally, we minimize the errors within the Riemann sum approximation of the path integral by utilizing non-uniform subdivisions determined by adaptive sampling. In the evaluation on ImageNet, it is demonstrated that IDG outperforms IG, left-IG, guided IG, and adversarial gradient integration both qualitatively and quantitatively using standard insertion and deletion metrics across three common models.Comment: 18 pages, 8 figures, submitted to NeurIPS 2023, the full code implementation of the paper results is located at: https://github.com/chasewalker26/Integrated-Decision-Gradient

Systematically Searching for New Resonances at the Energy Frontier using Topological Models

We propose a new strategy to systematically search for new physics processes in particle collisions at the energy frontier. An examination of all possible topologies which give identifiable resonant features in a specific final state leads to a tractable number of `topological models' per final state and gives specific guidance for their discovery. Using one specific final state, $\ell\ell jj$, as an example, we find that the number of possibilities is reasonable and reveals simple, but as-yet-unexplored, topologies which contain significant discovery potential. We propose analysis techniques and estimate the sensitivity for $pp$ collisions with $\sqrt{s}=14$ TeV and $\mathcal{L}=300$ fb$^{-1}$

Predicting Resting Metabolic Rate in Healthy Adults using Body Composition and Circumference Measurements

Measurement of resting metabolic rate (RMR) is an important factor for weight management. Previous research has reported several variables to estimate RMR such as body size, percent fat (%BF), age, and sex; however, little is known regarding the effect of circumference measures in estimating RMR. PURPOSE: The purpose of this study was to develop a model to estimate RMR using waist circumference (WC), an easily obtainable measure, and cross-validate it to previously published models. METHODS:Subjects were 140 adult men and women, ages 18-65 years. RMR was measured through indirect calorimetry, %BF was measured through air displacement plethysmography, and fat mass and fat-free mass were determined from %BF and weight. Other variables collected were: weight, height, age, sex, ethnicity, body mass index, WC, hip circumference, waist-to-hip ratio, waist-to-height ratio, and %BF estimated from bioelectrical impedance analysis. Subjects were randomly divided into derivation and cross-validation samples. A multiple regression model was developed to determine the most accurate estimation of RMR in the derivation sample. The cross-validation sample was used to confirm the accuracy of the model and to compare the accuracy to published models. RESULTS:The best predictors for estimating RMR were body weight, r = 0.70, p= 0.031, age, r = -0.30, p= 0.012, and sex, r = 0.51, p= 0.018. Other factors failed to account for significant variation in the model. The derived equation for estimating RMR is: RMR (kcal/day) = 843.11 + 8.77(weight) – 4.23(age) + 228.54(sex, M = 1, F = 0), R2= 0.68, SEE = 173 kcal/day. Cross-validation statistics were: R2= 0.54, p £0.05, SEE = 199 kcal/day, and total error = 198 kcal/day. In published models, R2ranged from 0.47 to 0.57, SEE ranged from 192 to 213 kcal/day, and total error ranged from 212 to 1311 kcal/day. CONCLUSIONS:Cross-validation to published models for estimating RMR were similar to those of the derived model; however, the total error in the derived equation was lower than any of the previously published models. Several published models considerably overestimate RMR compared to the current model. The results of this study suggest that RMR can be reasonably estimated with easily obtainable measures which allow for estimation and implementation of RMR for weight management in clinical practice

Period and chemical evolution of SC stars

The SC and CS stars are thermal-pulsing AGB stars with C/O ratio close to unity. Within this small group, the Mira variable BH Cru recently evolved from spectral type SC (showing ZrO bands) to CS (showing weak C2). Wavelet analysis shows that the spectral evolution was accompanied by a dramatic period increase, from 420 to 540 days, indicating an expanding radius. The pulsation amplitude also increased. Old photographic plates are used to establish that the period before 1940 was around 490 days. Chemical models indicate that the spectral changes were caused by a decrease in stellar temperature, related to the increasing radius. There is no evidence for a change in C/O ratio. The evolution in BH Cru is unlikely to be related to an on-going thermal pulse. Periods of the other SC and CS stars, including nine new periods, are determined. A second SC star, LX Cyg, also shows evidence for a large increase in period, and one further star shows a period inconsistent with a previous determination. Mira periods may be intrinsically unstable for C/O ~ 1; possibly because of a feedback between the molecular opacities, pulsation amplitude, and period. LRS spectra of 6 SC stars suggest a feature at wavelength > 15 micron, which resembles one recently attributed to the iron-sulfide troilite. Chemical models predict a large abundance of FeS in SC stars, in agreement with the proposed association.Comment: 14 pages, 20 figures. MNRAS, 2004, accepted for publication. Janet Mattei, one of the authors, died on 22 March, 2004. This paper is dedicated to her memor