Investigating multi-polarization GPR wave transmission through thin layers: Implications for vertical fracture characterization

This is the published version. Copyright 2006 American Geophysical Union. All Rights Reserved.We investigate the controls governing the response of ground-penetrating radar (GPR) wave transmission through thin layers in order to explore the use of variable polarization GPR signals for remote characterization of fracture aperture and fluid-fill. We employ an experimental setting that provides controlled observations of the effects of thin-layer properties to the transmitted GPR wavefield. GPR signals of variable polarization, variable angle of incidence, and variable frequency are transmitted through an air- and water-filled layer of variable thickness. We observe that at high angles of incidence, variable polarization GPR signals display characteristic and quantifiable phase and amplitude responses that are related to thin-layer properties. The GPR data are in agreement to analytical solutions of plane-wave oblique-incidence transmission through layered media. We conclude that multi-polarization GPR observations can be exploited to determine fracture properties. This work has implications in the remote determination of fractured formation anisotropic properties, such as fluid-flow

The Psychology of Two-Part Tariffs

This paper investigates preferences for two-part tariff pricing plans which require consumers to pay a flat fee plus a per unit surcharge for usage beyond an allowance. People have difficulty estimating the effective cost of a two-part tariff, so they apply heuristics to the most salient attributes. Compared to a normative benchmark of expected cost, these heuristics lead people to excessively choose plans with smaller flat fees, larger usage allowances, and lower overage rates. When these attributes are in conflict, people assign greater importance to comparisons of the two attributes that provide upside protection against overage charges: the usage allowance and the overage rate. The presence of usage uncertainty heightens the reliance on these comparisons, and calculating a cost does not appear to reduce them

Adherence to U.S. Physical Activity and Dietary Guidelines Among A Mexican American Cohort

Purpose: The purpose of this study is to examine adherence to risk factors for chronic diseases among Mexican Americans residing along Texas / Mexico border. Method: Data was derived from the Cameron County Hispanic Cohort (CCHC), a prospective cohort study of over 2600 Mexican American adults aged 18 years and older living in a large and poor city along the Texas / Mexico border. Descriptive statistics and regression analysis were used to analyze the data. Results:The sample (67.06% female) has a mean age of 48.06 ± 15.60 years, 48.81% employed, 45.66% has less than high school education, 77.57% completed the survey in Spanish, and 31.65% has some type of public or private insurance. More than 85% of the sample were either overweight (25≤BMI Conclusions: Preventive behaviors including regular moderate to vigorous physical activity and a diet rich with fruit and vegetables are uncommon among Mexican Americans. Younger age and lower BMI were associated with meeting preventive behavior guidelines along Texas / Mexico border Mexican Americans

Conditional Generative Data Augmentation for Clinical Audio Datasets

In this work, we propose a novel data augmentation method for clinical audio datasets based on a conditional Wasserstein Generative Adversarial Network with Gradient Penalty (cWGAN-GP), operating on log-mel spectrograms. To validate our method, we created a clinical audio dataset which was recorded in a real-world operating room during Total Hip Arthroplasty (THA) procedures and contains typical sounds which resemble the different phases of the intervention. We demonstrate the capability of the proposed method to generate realistic class-conditioned samples from the dataset distribution and show that training with the generated augmented samples outperforms classical audio augmentation methods in terms of classification performance. The performance was evaluated using a ResNet-18 classifier which shows a mean Macro F1-score improvement of 1.70% in a 5-fold cross validation experiment using the proposed augmentation method. Because clinical data is often expensive to acquire, the development of realistic and high-quality data augmentation methods is crucial to improve the robustness and generalization capabilities of learning-based algorithms which is especially important for safety-critical medical applications. Therefore, the proposed data augmentation method is an important step towards improving the data bottleneck for clinical audio-based machine learning systems

Undiagnosed Diabetes and Pre-Diabetes in Health Disparities

Globally half of all diabetes mellitus is undiagnosed. We sought to determine the extent and characteristics of undiagnosed type 2 diabetes mellitus and pre-diabetes in Mexican Americans residing in the United States. This disadvantaged population with 50% lifetime risk of diabetes is a microcosm of the current pandemic. We accessed baseline data between 2004 and 2014 from 2,838 adults recruited to our Cameron County Hispanic Cohort (CCHC); a two-stage randomly selected \u27Framingham-like\u27 cohort of Mexican Americans on the US Mexico border with severe health disparities. We examined prevalence, risk factors and metabolic health in diagnosed and undiagnosed diabetes and pre-diabetes. Two thirds of this Mexican American population has diabetes or pre-diabetes. Diabetes prevalence was 28.0%, nearly half undiagnosed, and pre-diabetes 31.6%. Mean BMI among those with diabetes was 33.5 kg/m2 compared with 29.0 kg/m2 for those without diabetes. Significant risk factors were low income and educational levels. Most with diabetes had increased waist/hip ratio. Lack of insurance and access to health services played a decisive role in failure to have diabetes diagnosed. Participants with undiagnosed diabetes and pre-diabetes had similar measures of poor metabolic health similar but generally not as severe as those with diagnosed diabetes. More than 50% of a minority Mexican American population in South Texas has diabetes or pre-diabetes and is metabolically unhealthy. Only a third of diabetes cases were diagnosed. Sustained efforts are imperative to identify, diagnose and treat individuals in underserved communities

Transition from pre-diabetes to diabetes and predictors of risk in Mexican-Americans

Background: No studies have examined risk factors for the transition from pre-diabetes to diabetes in populations with widespread obesity and diabetes. We determined proximal changes and factors affecting the transition among Mexican-Americans with pre-diabetes. Methods: Participants with pre-diabetes (n=285) were recruited from our randomly sampled population-based Cameron County Hispanic Cohort. These participants were followed for an average of 27 months with repeat examination every 3 to 4 months. Metabolic health was defined as having less than 2 metabolic abnormalities (e.g., hypertension, elevated low-density lipoprotein, etc). Diabetes was identified as fasting blood glucose ≥126 mg/dL, glycated hemoglobin ≥6.5% and/or on hypoglycemic medication. Results: Ninety-six of 285 (33.7%) participants transitioned to overt diabetes. The increased risk of diabetes in the metabolically unhealthy varying with follow-up time was 81% (adjusted odds ratio [OR]: 1.81; 95% CI: 1.09–3.02). The risk of diabetes increased 8% for each kg/m2 of increase in body mass index (BMI, OR: 1.08; 95% CI: 1.05–1.11) independent of covariates. Transition to diabetes was accompanied by a mean increase in BMI of 0.28 kg/m2, and deterioration in metabolic health of 9% (OR: 1.09; 95% CI: 1.003–1.18) compared with those who did not transition. Conclusions: Deteriorating metabolic health and/or increasing BMI significantly raises the risk of transitioning from pre-diabetes to diabetes. Transition itself was accompanied by further increase in BMI and deterioration in metabolic health. These data underline the importance of improving metabolic health and avoiding weight gain in pre-diabetes as simple but clear diabetes prevention targets, and emphasize the importance of lifestyle management