The Consolidation of the White Southern Congressional Vote

This article explores the initial desertion and continued realignment of about one-sixth of the white voters in the South who, until 1994, stood by Democratic congressional candidates even as they voted for Republican presidential nominees. Prior to 1994, a sizable share of the white electorate distinguished between Democratic congressional and presidential candidates; since 1994 that distinction has been swept away. In 1992, a majority of white southern voters was casting their ballot for the Democratic House nominee; by 1994, the situation was reversed and 64 percent cast their ballot for the Republican. Virtually all categories of voters increased their support of Republican congressional candidates in 1994 and the following elections further cement GOP congressional support in the South. Subsequent elections are largely exercises in partisanship, as the congressional votes mirror party preferences. Republicans pull nearly all GOP identifiers, most independents, and a sizeable minority of Democratic identifiers. Democrats running for Congress no longer convince voters that they are different from their party’s presidential standard bearers—a group that has consistently been judged unacceptable to overwhelming proportions of the southern white electorate.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Searching for "order" in atrial fibrillation using electrogram morphology recurrence plots

Bipolar electrograms recorded during atrial fibrillation (AF) can have an appearance of chaotic/random behavior. The aim of this study was to use a novel electrogram morphology recurrence (EMR) analysis to quantify the level of order in the morphology patterns in AF. Rapid atrial pacing was performed in seven dogs at 600bpm for 3 weeks leading to sustained AF. Open chest high density electrical recordings were made in multiple atrial sites. EMR plots of bipolar electrograms at each site were created by cross-correlating morphologies of each detected activations with morphologies of every other activation. The following features of the EMR plots were quantified: recurrence rate (RR), determinism (DET), laminarity (LAM), average diagonal line length (L), trapping time (TT), divergence (DIV), and Shannon׳s entropy (ENTR). For each recording site, these measures were calculated for the normal sequence of morphologies and also after random shuffling of the electrogram orders. Electrograms recordings from a total of 3961 sites had average cycle lengths of 104±22ms resulting in an average of 100±19 activations detected per 10-s recording and an average RR of 0.38±0.28 (range 0.02-1.00). Shuffling the order of the activation morphologies resulted in significant decreases in DET, LAM, L, TT, and ENTR and significant increases in DIV. EMR plots of AF electrograms show varying rates of recurrence with patterns that suggest an underlying deterministic structure to the activation sequences. A better understanding of AF dynamics could lead to improved methods in mapping and treating AF

Abstract 15840: Electrogram Morphology Recurrence Analysis Identifies Areas of Consistent Activation Directions and Rotor Activity in a Rapid Atrial Pacing Model of Atrial Fibrillation

Introduction: Electrogram morphology recurrence (EMR) analysis is a novel mapping technique which characterizes morphology patterns during atrial fibrillation (AF). Using high resolution electrical mapping, we tested the hypothesis that EMR analysis could identify areas of consistent activation directions and rotor activity in a canine rapid atrial pacing model of AF. Methods: Three weeks of rapid right atrial pacing (600 bpm) was performed in six dogs. A triangular plaque was used to obtain 117 simultaneous bipolar AF electrograms from two right and three left atrial locations. EMR plots for each electrogram recording were created by cross-correlation of each activation waveform with each other. The percentage of the most common morphology (REC%) and the mean cycle length (CL) of activations with the most common morphology (CLR) were computed. Activation pattern for each site was classified as either having stable rotors, passive activity, or chaotic activity. Activation vectors were computed and a vector index (VI) was used to measure vector consistency. Results: Figure A shows an example of an EMR plot map from recordings in the left atrium with red indicating areas of high EMR. The sites with the shortest CL had an average CL of 81±13 ms. The sites with the highest REC% had an average value of 99±2%. The sites with the shortest CLR had an average value of 91±17 ms. REC% was highly correlated with VI (Figure B). Minimum CL was only moderately shorter in rotor sites compared to chaotic and passive sites (Figure C). Maximum REC% was significantly higher in rotors sites than in chaotic sites, but not different from passive sites (Figure D). Minimum CLR in the rotor sites were significantly less than both the chaotic and passive sites (Figure E). Conclusions: EMR analysis is a new mapping technique that correlates well with activation vector consistency and can identify rotor activity. This is a promising method for mapping AF that may identify sources that can be targeted for ablation

Inhibition of K+ currents of outer hair cells in guinea pig cochlea by fluoxetine

Article discussing the inhibition of K+ currents of outer hair cells in guinea pig cochlea by fluoxetine