Character classification data for license plates

<b>Licence Plate Character Classification Data</b><br><br>Authors:<br>Rohit Rawat, Dr. M. T. Manry, Fernando Martinez<br>Image Processing and Neural Networks Lab<br>The University of Texas at Arlington<br><u>http://www.uta.edu/faculty/manry/</u><br><br>This dataset has 49 numerical features extracted from character images extracted from license plate images. The dataset has 12757 images extracted from plate images split into training and testing sets. The data has 36 output classes belonging to letters 'A' to 'Z' excluding the characters 'O' and 'Q', numbers '0' to '9', and two state map characters.<br><br>Data is tab separated, one line per example, with the correct class between 1 and 36 at the end of the line.<br><br>This data should be cited as:<br><div><p>Rawat, Rohit; Manry, M.T.; Martinez, Fernando (2016): Character classification data for license plates. figshare.<a href="https://dx.doi.org/10.6084/m9.figshare.3113449.v1"> https://dx.doi.org/10.6084/m9.figshare.3113449.v1</a></p></div><a target="_blank"></a><br><br

Pulse pressure amplification and its determinants

<div><p><i>Background</i>. Pulse pressure (PP) amplification expressed as the peripheral-to-central PP ratio has gained importance in the assessment of cardiovascular phenotypes and cardiovascular risk. The aim of the present study was to assess the relationship between PP amplification, large vessel parameters and peripheral blood pressure (BP) to gain insights into the amplification phenomenon. <i>Methods</i>. Peripheral BP, central BP and carotid-femoral pulse wave velocity (cfPWV) were assessed using the OMRON M6, SphygmoCor and Complior devices, respectively, in 741 adults attending the hypertension outpatient clinic. Analysis of covariance, partial correlations and multiple linear regression models were performed to assess the relationship between PP amplification, peripheral BP and cfPWV. <i>Results</i>. PP amplification was inversely related to BP group. Women showed lower PP amplification than men (1.24 ± 0.18 and 1.35 ± 0.18, respectively, <i>p</i> < 0.001). Age, female gender and mean arterial pressure were inversely associated with PP amplification (<i>p</i> < 0.001), whereas heart rate and body mass index showed positive associations (<i>p</i> < 0.001 and <i>p</i> = 0.049, respectively). cfPWV was a predictor of PP amplification in men but not in women (<i>p</i> = 0.006 and <i>p</i> = 0.424, respectively). <i>Conclusions</i>. PP amplification is related to BP: the higher the BP, the lower the PP amplification. Gender, age and body composition have a significant impact on PP amplification.</p></div

Motility of <i>C. elegans</i> strains on agar plates and in the grid microstructures.

<p>A) Oscillation frequency of worms in different environments. Error bars indicate the standard deviation. B) Speed of worms only moving in the forward direction (not turning or bending) was measured. For plate measurements <i>n</i> = 10, and for grid measurements <i>n</i> = 30.</p

<i>C. elegans</i> crawling and swimming.

<p>(a) An image of a worm crawling on agar and leaving a sinusoidal trail in a bacterial lawn is shown. Since the worm moves with very little slip, the body follows the curvature of the sinusoidal waves that are propagated down the length of the animal. (b) Multiple exposure of swimming <i>C. elegans</i> in bulk liquid. The image shows the variance of a sequence of 20 images taken at 30 Hz of adult N2 worms. Grey scale level of image indicates variance, with high variance (large movements) indicated by black, and zero variance (small movements) indicated by white. Note the bi-nodal bending motions. Inset shows a series of swimming strokes through a half-cycle.</p

Post-array swimming speed versus oscillation frequency.

<p>Speed of N2 worms moving only in the forward direction (not turning or bending) was measured.</p

Multiple exposure of a worm performing enhanced swimming in an agar post array.

<p>(a) The picture contains 10 time-lapse images taken at 5 Hz, with worms swimming right to left. Post diameter is 300 microns, post spacing is 475 microns center-to-center, and post height is 110 microns. Starting at post 1, worm then contacts post 2 at half cycle, and finally post 3 for a complete cycle. Scale bar = 1 mm. (b) an isometric schematic of the worm motion as it moves in the microfabricated grid.</p

Table_1_A first look at childhood abuse in women with obstructive sleep apnea.XLSX

Study objectivesWomen who experienced childhood sexual abuse have higher rates of obesity, a risk factor for obstructive sleep apnea (OSA). We assessed if prior childhood sexual abuse was more common in women with OSA vs. those in the control group, with possible mediation by obesity.MethodsIn a secondary analysis of a larger project, we studied 21 women with OSA (age mean ± SD 59 ± 12 years, body mass index [BMI] 33 ± 8 kg/m2, respiratory event index [REI] 25 ± 16 events/hour, and Epworth Sleepiness Scale [ESS] score 8 ± 5) and 21 women without OSA (age 53 ± 9 years, BMI 25 ± 5 kg/m2, REI [in 7/21 women] 1 ± 1 events/hour, and ESS score, 5 ± 3). We evaluated four categories of trauma (general, physical, emotional, and sexual abuse) with the Early Trauma Inventory Self-Report–Short Form (ETISR-SF). We assessed group differences in trauma scores with independent samples t-tests and multiple regressions. Parametric Sobel tests were used to model BMI as a mediator for individual trauma scores predicting OSA in women.ResultsEarly childhood sexual abuse reported on the ETISR-SF was 2.4 times more common in women with vs. without OSA (p = 0.02 for group difference). Other trauma scores were not significantly different between women with and without OSA. However, BMI was a significant mediator (p = 0.02) in predicting OSA in women who experienced childhood physical abuse.ConclusionChildhood sexual abuse was more common in women with vs. without OSA. BMI was a mediator for OSA of childhood physical but not sexual abuse. This preliminary hypothesis-generating study suggests that there may be physiological impacts of childhood trauma in women that predispose them to OSA.</p

Additional file 1: of Integrative phenotyping framework (iPF): integrative clustering of multiple omics data identifies novel lung disease subphenotypes

Text S1. Materials and data collection. Text S2. Details of smoothing and Feature Topology Plots (FTP). Text S3. Simulation setting to evaluate iPF. Text S4. Comprehensive validation scheme for iPF. Figure S5. (A) An illustration of integrated omics data sets, (B) A workflow to generate future topology plot (FTP). Figure S6. Flowchart of validation scheme for Integrative phenotyping framework for multiple omics data sets. Figure S7. An example of iPF that utilizes fused multiple data sets at the stage (vi). Figure S8. Examples of iPF using various combinations of the omics data sets (pooled analysis). Figure S9A. The gap statistics and its scree plot to choose the optimal number of clustering (clinical and miRNA data). Figure S9B. The gap statistics and its scree plot to choose the optimal number of clustering (mRNA and miRNA data). Figure S9C. The gap statistics and its scree plot to choose the optimal number of clustering (mRNA and clincal data). Figure S9D. The gap statistics and its scree plot to choose the optimal number of clustering (clincal data and combined data of mRNA and miRNA). Figure S10. The best choice of the number of feature modules. Figure S11. Simulation study shows robust true feature discovery in “Feature Fusion”. The x-axis represents multiplication levels of noise features. The y-axis represents average ARIs from 100 simulations. Each figure is generated based on simulation scenarios of the different number of true features (e.g., 200, 400, and 600, respectively). Figure S12. Immunomodulating drugs target overexpressed genes in module two. Table S13. The description of mRNA and miRNA lung disease data. Table S14. Various correlation types depending on variable attributes. Table S15. The demographic summary of clinical features in each sub-cluster. Table S16. Target gene enrichment analysis (via Fisher exact test) related to twelve. Table S17. Regression analysis on target miRNA features, and coefficient of determination significant miRNA features. Table S18. The top disease or functional annotations associated with genes in module two in Cluster E patients. Figure S19. Basic consensus clustering using only gene expression data. (DOCX 6398 kb

Additional file 3: of Integrative phenotyping framework (iPF): integrative clustering of multiple omics data identifies novel lung disease subphenotypes

This file includes 669 clinical variables analyzed in this paper. (XLSX 45 kb

Standard curves and native reactivity.

<p>Typical standard curves and native reactivity against human, rat, and mouse material diluted to 1:8 as indicated for the assays C4M12a1 (A) and C4M12a3 (B). The reactivity of the C4M12a3 ELISA to the rat sequence (PGDTVFQPGP) was also tested (B). Signals are shown as optical density (OD) at 450 nm, subtracting the background at 650 nm, as a function of standard peptide concentration. UD: undiluted sample.</p