Which Race Card? Understanding Racial Appeals in U.S. Politics

The recent rise in explicitly prejudicial campaign messaging, along with the complementary rise in rhetorical appeals to pro-minority sentiments, have not been fully explained by current scholarship. What factors have caused this transition in political messaging? What role do social norms play in determining the acceptability of these appeals? How can the effects of overtly prejudicial appeals be neutralized? This dissertation seeks to answer these questions by providing a comprehensive understanding of the use of appeals to pro- and anti-minority sentiments by elites and the reception of these messages by the public in contemporary U.S. politics. Section one details the factors that have transformed electoral incentives of the Democratic and Republican Parties to include explicit signaling of their stances on racial issues and provides evidence from survey experiments that, under certain conditions, using explicit appeals can be an effective electoral strategy. Section two provides a theoretical framework for the role social norms play in determining whether explicit appeals are accepted or rejected. Then, using an original measure of social norms adherence, findings from regression analyses show that norms of acceptable rhetoric vary by the group being targeted and the political party purveying the message. Finally, section three develops and tests strategies to neutralize the effects of overt prejudice on candidate and policy evaluations. These findings improve our understanding of racial appeals and specifies the central power of norms in conditioning evaluations of prejudice

Robust Registration and Tracking Using Kernel Density Correlation

Challenges to accurate registration come from three factors ---presence of background clutter, occlusion of the pattern being registered and changes in feature values across images. To address these concerns, we propose a robust probabilistic estimation approach predicated on representations of the object model and the target image using a kernel density estimate. These representations are then matched in the space of density functions using a correlation measure, termed the Kernel Density Correlation (KDC) measure. A popular metric which has been widely used by previous image registration approaches is the Mutual Information (MI) metric. We compare the proposed KDC metric with the MI metric to highlight its better robustness to occlusions and random background clutter---this is a consequence of the fact that the KDC measure forms a re-descending M-estimator. Another advantage of the proposed metric is that the registration problem can be efficiently solved using a variational optimization algorithm. We show that this algorithm is an iteratively reweighted least squares (IRLS) algorithm and prove its convergence properties. The efficacy of the proposed algorithm is demonstrated by its application on standard stereo registration data-sets and real tracking sequences

Online News Coverage of Critical Race Theory Controversies: A Dataset of Annotated Headlines

In this paper, we introduce an annotated dataset of 11,704 unique U.S. news headlines related to critical race theory and its controversies from August 2020 through December 2022. Annotations generated by GPT-4 specify the headline stance and the primary actor in the headline. GPT-4 annotations performed well on the validation dataset, with weighted average F-scores of 0.8339 for headline stance annotations and 0.7625 for primary actor annotations. Along with the annotated headlines and URLs to the full article, we augment the dataset with metrics that are relevant to future research on political polarization, news frame analysis, and regional news coverage. The dataset includes partisan audience bias scores by news source domain, tags for mentions of U.S. states in the article body, and exposure and engagement metrics for articles shared on Reddit. Among other preliminary descriptive analyses, we find that the most prevalent headline stance in our headlines dataset is anti-CRT (43.06%), and the most prevalent primary actor in our headlines dataset is political influencers (56.56%). This paper describes the data collection methodology, preliminary descriptive analysis, and possible uses of the dataset for future research in political science, computational social sciences, and natural language processing. Our dataset and replication code is available to access on Zenodo at zenodo.org/doi/10.5281/zenodo.1051619

Comparative Effect of Vagal Stimulation on Heart Rate, Blood Pressure, and Skin Hydration at Different Anatomical Sites in Prehypertensive Individuals: A Pilot Study

Introduction: Prehypertension is the precursor to high Blood Pressure (BP), which can lead to severe consequences such as cardiovascular disease, stroke, acute myocardial infarction, heart failure, peripheral arterial disease, and cerebrovascular complications, ultimately resulting in mortality. Vagal stimulation is frequently employed by therapists, along with various therapeutic exercises, to treat or manage Heart Rate (HR) and BP in prehypertensive individuals. The vagus nerve plays a vital role in maintaining internal physiological balance, known as homeostasis, which includes reflex pathways that regulate cardiac function. Auricular neuromodulation of the vagus nerve can be achieved through stimulation of the ear lobule, cymba concha, or tragus in the outer ear. Aim: To compare and determine the optimal anatomical site for vagal stimulation, specifically the ear lobule, cymba concha, or tragus, to improve HR, BP, and skin hydration in prehypertensive individuals. Materials and Methods: The present pilot study conducted a pre-post comparative analysis in the Outpatient Department (OPD) of Physiotherapy at the Institute of Applied Medicines and Research Centre, Ghaziabad, Uttar Pradesh, India. The study duration was nine months, from January 2022 to September 2022. A total of 30 subjects aged 30-55 years were divided into three groups (10 participants in each group: A, B, and C) using sealed envelopes. Group A received vagal stimulation on the ear lobule, Group B received vagal stimulation on the cymba concha, and Group C received vagal stimulation on the tragus. Baseline measurements were taken prior to treatment, including HR, BP, and skin hydration. Vagal stimulation was administered using a low-frequency Transcutaneous Electrical Nerve Stimulation (TENS) machine at 25 Hertz and a pulse width of 120 ms. The stimulus was continuously applied for 30 minutes, five days a week, for four weeks. After a 10-minute relaxation period, HR, BP, and skin hydration were measured both pre and post-intervention. The data was statistically analysed using Statistical Package for Social Sciences (SPSS) version 24.0, employing paired t-tests to compare means within groups and Analysis of Variance (ANOVA) to compare between the three groups. Results: There were no statistical differences in the baseline among all three groups. Group C, which received vagal stimulation on the tragus, demonstrated statistically significant improvements in BP and skin hydration. The t-value and p-value for Systolic Blood Pressure (SBP) were 11.513 and p<0.001, for Diastolic Blood Pressure (DBP) were 10.411 and p<0.001, for HR were 15.231 and p<0.001, and for skin hydration were 9.474 and p<0.001, respectively. When comparing HR, BP, and skin hydration among the groups using one-way ANOVA f- value and p-value showed significant difference between the groups in all parameters. Conclusion: The study concludes that vagal stimulation on the tragus is a superior intervention compared to vagal stimulation on the cymba concha or ear lobule for controlling HR, BP, and skin hydration in prehypertensive individual

A Robust Nonparametric Estimation Framework for Implicit Image Models

Robust model fitting is important for computer vision tasks due to the occurrence of multiple model instances, and, unknown nature of noise. The linear errors-in-variables (EIV) model is frequently used in computer vision for model fitting tasks. This paper presents a novel formalism to solve the problem of robust model fitting using the linear EIV framework. We use Parzen windows to estimate the noise density and use a maximum likelihood approach for robust estimation of model parameters. Robustness of the algorithm results from the fact that density estimation helps us admit an a priori unknown multimodal density function and parameter estimation reduces to estimation of the density modes. We also propose a provably convergent iterative algorithm for this task. The algorithm increases the likelihood function at each iteration by solving a generalized eigenproblem. The performance of the proposed algorithm is empirically compared with Least Trimmed Squares(LTS) — a state-of-the-art robust estimation technique, and Total Least Squares(TLS) — the optimal estimator for additive white Gaussian noise. Results for model fitting on real range data are also provided. 1

Intralenticular foreign bodies: Report of eight cases and review of management

<b>Purpose:</b> The management of intralenticular foreign bodies (ILFBs) with or without cataract has varied from time to time in the last century. We evaluated the surgical removal of the ILFBs with cataract extraction as a single-stage procedure. <b>Methods:</b> Eight consecutive cases with intralenticular foreign bodies presenting to the trauma centre at our institute, were included in the study. Planned ILFB removal with cataract extraction and IOL implantation as a single-stage procedure was done in all the patients. They were followed up from 2 months to 2 years after the surgery. <b>Results:</b> ILFBs were removed with Kelman-Mcpherson forceps in seven cases and in one it was expressed with the nucleus during extra capsular cataract extraction. Co-existent posterior capsular tears were seen in two eyes, of which only one needed a localized vitrectomy. Posterior chamber intraocular lens implantation was possible without any complication in all the cases. Postoperative uveitis seen in three cases was easily controlled with periocular steroids. Best corrected visual acuity at last examination was 6/9 or better in 7 cases and 6/12 in one case with posterior capsular opacification. <b>Conclusions:</b> Timing and necessity of ILFB removal may be adjusted according to the foreign body characteristics and associated ocular trauma, choosing, as far as possible, the least traumatic procedure. Use of forceps rather than magnets is safer for the removal of the ILFB. Co-existent posterior capsular tears need to be anticipated and dealt with when encountered