On the dilaton and the axion potentials

We extend the Vecchia-Veneziano-Witten (VVW) model of QCD in the chiral limit and for large colour number $N_c$, by introducing an effective dilaton-gluon coupling from which we derive both the axion and dilaton potentials. Furthermore, using a string inspired model, we determine a new interquark potential as a perturbative series in terms of the interquark distance $r$. Our potential goes beyond Dick one obtained in [8] and shares the same features as the Bian-Huang-Shen potential $V_{BHS}$ which depends only on odd powers of $r$ [22].Comment: 15 pages, Late

Latency corrected wavelet filtering of the P300 event-related potential in young and old adults

The purpose of this study was to apply a nonlinear wavelet denoising Alter to the extraction of transient evoked related potentials (ERPs) from background EEG. The study introduces a new method for Altering the P300, an ERP component evoked by performing a given cognitive task, in this case, a two-choice reaction time task. The method employed latency correction of the ERPs in the time domain, followed by noise-masking in the wavelet domain. With this filtering method, the P300 component was accurately localized in both time and scale. Wilcoxon tests verified the statistical significance of P300 peak amplitude differences (p<0.0003) between two age groups (old and young). © 2007 IEEE

Latency corrected wavelet filtering of the P300 event-related potential in young and old adults

The purpose of this study was to apply a nonlinear wavelet denoising Alter to the extraction of transient evoked related potentials (ERPs) from background EEG. The study introduces a new method for Altering the P300, an ERP component evoked by performing a given cognitive task, in this case, a two-choice reaction time task. The method employed latency correction of the ERPs in the time domain, followed by noise-masking in the wavelet domain. With this filtering method, the P300 component was accurately localized in both time and scale. Wilcoxon tests verified the statistical significance of P300 peak amplitude differences (p<0.0003) between two age groups (old and young). © 2007 IEEE

Wavelet filtering of the P300 component in event-related potentials.

This paper presents an application of wavelet filtering to single-trial P300 component analysis. The objective of this study is to introduce a new method for analyzing the P300 component, when performing a given cognitive task, in this case, a two-choice reaction time task. The discrete wavelet transform with Daubechies wavelet is employed to detect the presence of P300 in individual trials. Wavelet filtering is applied to remove noise and unwanted frequency components from discrete wavelet transform (DWT) coefficients based on prior knowledge of event-related potentials (ERPs). The filtering mask is computed from the grand-average of wavelet coefficients over all participants. With this filtering, the P300 component is accurately localized in both time and scale. The findings suggest the procedure to have considerable potential for the analysis of time-series data in the behavioral neurosciences

Wavelet filtering of the P300 component in event-related potentials.

This paper presents an application of wavelet filtering to single-trial P300 component analysis. The objective of this study is to introduce a new method for analyzing the P300 component, when performing a given cognitive task, in this case, a two-choice reaction time task. The discrete wavelet transform with Daubechies wavelet is employed to detect the presence of P300 in individual trials. Wavelet filtering is applied to remove noise and unwanted frequency components from discrete wavelet transform (DWT) coefficients based on prior knowledge of event-related potentials (ERPs). The filtering mask is computed from the grand-average of wavelet coefficients over all participants. With this filtering, the P300 component is accurately localized in both time and scale. The findings suggest the procedure to have considerable potential for the analysis of time-series data in the behavioral neurosciences

A knowledge map for hospital performance concept: Extraction and analysis: A narrative review article

Background: Performance is a multi-dimensional and dynamic concept. During the past 2 decades, considerable studies were performed in developing the hospital performance concept. To know literature key concepts on hospital performance, the knowledge visualization based on co-word analysis and social network analysis has been used. Methods: Documents were identified through �PubMed� searching from1945 to 2014 and 2350 papers entered the study after omitting unrelated articles, the duplicates, and articles without abstract. After pre-processing and preparing articles, the key words were extracted and terms were weighted by TF-IDF weighting schema. Support as an interestingness measure, which considers the co-occurrence of the extracted keywords and "hospital performance" phrase was calculated. Keywords having high support with "hospital performance" are selected. Term-term matrix of these selected keywords is calculated and the graph is extracted. Results: The most high frequency words after �Hospital Performance� were �mortality� and �efficiency�. The major knowledge structure of hospital performance literature during these years shows that the keyword �mortality� had the highest support with hospital performance followed by �quality of care�, �quality improvement�, �discharge�, �length of stay� and �clinical outcome�. The strongest relationship is seen between �electronic medical record� and �readmission rate�. Conclusion: Some dimensions of hospital performance are more important such as �efficiency�, �effectiveness�, �quality� and �safety� and some indicators are more highlighted such as �mortality�, �length of stay�, �readmission rate� and �patient satisfaction�. In the last decade, some concepts became more significant in hospital performance literature such as �mortality�, �quality of care� and �quality improvement�. © 2016, Iranian Journal of Public Health. All rights reserved