DEVELOPING COMPREHENSIVE ECONOMIC INFORMATION FOR REGIONAL PLANNING: A CASE STUDY

Community/Rural/Urban Development,

INTERREGIONAL AND INTERSEASONAL COMPETITION IN THE U.S. BEEF INDUSTRY: AN APPLICATION OF REACTIVE PROGRAMMING

Livestock Production/Industries,

Study of electrocardiographic differentiation between RCA and LCx occlusion in isolated inferior wall myocardial infarction

Background: Inferior myocardial infarctions account for 40 to 50% of all acute myocardial infarctions and are generally viewed as having a more favorable prognosis than anterior wall infarctions. The management, and in some instances, prevention of these complications, may be facilitated by early differentiation between AMI caused by RCA versus left circumflex coronary artery occlusion. These can be diagnosed from the electrocardiography (ECG) which remains a valuable and most widely used rational modality to diagnose and risk stratifying in an acute setting. The present study helps in Electrocardiographic differentiation between right coronary and the left circumflex coronary arterial occlusion in isolated inferior wall myocardial infarction.Methods: The present study entitled “Electrocardiographic differentiation between right coronary and the left circumflex coronary arterial occlusion in isolated inferior wail myocardial infarction” was conducted from June 2007 to November 2009 at the Department of Medicine and Cardiology, Dr. D.Y. Patil Hospital and Research Center, Nerul, Navi Mumbai, Maharashtra, India.Results: Out of 52 patients of acute inferior wall myocardial infraction, 41 were males and 11 were females. Thus the male to female ratio is 3.72:1. In the above table, the ST segment elevation in lead III was more than lead ii in42 patients. All these 42 patients were found to have RCA as the culprit vessel. The St Segment elevation in lead II was more than lead III in 9 patients. All these 9 patients were found to have LCx as the culprit vessel.Conclusions: The incidence of acute inferior wall myocardial infarction is highest in age group of 50 to 59 years. The ST segment elevation in acute isolated inferior wall myocardial infarction was greater in lead III than in lead II when right coronary artery was the culprit vessel and vice versa when the left circumflex coronary artery was the culprit vessel. ST segment depression in lead I was common when the right coronary artery was the culprit vessel and not seen with left circumflex coronary artery occlusion. An upright T wave in lead V4R in acute isolated inferior wall myocardial infarction was common when the right coronary artery was the culprit vessel and not seen with left circumflex coronary artery occlusion.

A simple and objective method for reproducible resting state network (RSN) detection in fMRI

Spatial Independent Component Analysis (ICA) decomposes the time by space functional MRI (fMRI) matrix into a set of 1-D basis time courses and their associated 3-D spatial maps that are optimized for mutual independence. When applied to resting state fMRI (rsfMRI), ICA produces several spatial independent components (ICs) that seem to have biological relevance - the so-called resting state networks (RSNs). The ICA problem is well posed when the true data generating process follows a linear mixture of ICs model in terms of the identifiability of the mixing matrix. However, the contrast function used for promoting mutual independence in ICA is dependent on the finite amount of observed data and is potentially non-convex with multiple local minima. Hence, each run of ICA could produce potentially different IC estimates even for the same data. One technique to deal with this run-to-run variability of ICA was proposed by Yang et al. (2008) in their algorithm RAICAR which allows for the selection of only those ICs that have a high run-to-run reproducibility. We propose an enhancement to the original RAICAR algorithm that enables us to assign reproducibility p-values to each IC and allows for an objective assessment of both within subject and across subjects reproducibility. We call the resulting algorithm RAICAR-N (N stands for null hypothesis test), and we have applied it to publicly available human rsfMRI data (http://www.nitrc.org). Our reproducibility analyses indicated that many of the published RSNs in rsfMRI literature are highly reproducible. However, we found several other RSNs that are highly reproducible but not frequently listed in the literature.Comment: 54 pages, 13 figure