Stress among Isfahan medical sciences students

Background: This study was undertaken to determine the prevalence of psychological stress among Isfahan medical sciences students. Methods: Cross-sectional, questionnaire-based survey was carried out among the 387 medical sciences students (medicine, pharmacy, and dentistry) of Isfahan, Iran through census. In academic year 2010-2011, Kessler-10 questionnaire was given to the students a month before semester examinations. Scores �20 were considered as indicative of positive stress symptoms. Results: The overall prevalence of stress among medical sciences students was found to be about 76.1%. The prevalence of stress among medicine students was 22.7% mild, 23% moderate and 21.4% severe while 32.8% showed no stress. The prevalence of stress among pharmacy students was 22.22%, 22.22%, 26.19%, and 29.36% mild, moderate, and severe and no stress, respectively. The prevalence of stress among dentistry students was 25% mild, 27% moderate, and 10% severe while 37.5% showed no stress. The prevalence of stress was higher (70.6%) in pharmacy students when compared with medicine (66.1%) and dentistry (62.5%) students. The odds of student having stress is higher in dentistry students (OR: 1.44, P= 0.33), where as the odds are decreasing in pharmacy student (OR: 1.16, P= 0.66). There is no statistically significant association between gender, ages, and term and having stress symptoms. Conclusions: The high level of stress necessitates interventions like social and psychological support to improve the student's well-being. A prospective study is needed to study the association of psychological morbidity with sources of stress and coping strategies

Automatic detection of coronaries ostia in computed tomography angiography volume data

Background: Heart coronaries emerge from the ascending aorta lateral sides from two points called the coronaries ostia. To automatically segment the heart coronaries; there must be a starting point (seed) for the segmentation. In this paper we present a fully automatic approach to segment the coronaries ostia towards automatic seeding for heart coronaries segmentation.Methods: Our algorithm takes as an input a CTA volume of segmented aorta cross sections that represents our region of interest. Then the ostia detection algorithm traverses that volume looking for the ostia points in an automatic fashion. The proposed algorithm depends on the anatomical features of the ostia. The main anatomic feature of the ostia is that it appears like a curvature or corner on the segmented ascending aorta cross section. Therefore we adopted in our methodology a modified version of Harris Corner Detection; besides inducing some anatomical features of the ostia location with respect to the aortic valve.Results: The proposed algorithm is tested and validated on the computed tomography angiography database provided by the Rotterdam coronary artery algorithm evaluation framework. The proposed automatic ostia detection algorithm succeeded to detect both ostia points in all the test cases. Also, the detected ostia points’ coordinates are validated versus a ground truth provided by the same framework with deviation between the results of the detection process and the ground truth having a min of 0 pixels and a max of 10 pixels for all test cases.Conclusions: Thus the proposed algorithm gives accurate results in comparison with the ground truth, which proves the efficiency of the proposed algorithm and its applicability to be extended as a seed for heart coronaries segmentation

Broadband angle of arrival estimation methods in a polynomial matrix decomposition framework

A large family of broadband angle of arrival estimation algorithms are based on the coherent signal subspace (CSS) method, whereby focussing matrices appropriately align covariance matrices across narrowband frequency bins. In this paper, we analyse an auto-focussing approach in the framework of polynomial covariance matrix decompositions, leading to comparisons to two recently proposed polynomial multiple signal classification (MUSIC) algorithms. The analysis is complemented with numerical simulations

Model-based Automatic Segmentation of Ascending Aorta from Multimodality Medical Data

Automatic Ascending Aorta Segmentation is one of the important steps towards automatic segmentation of the whole cardiac tree. This paper presents a novel approach for the automatic segmentation of the ascending aorta from two imaging modalities: CTA (Computed Tomography Angiography) and PC-MRI (Phase-Contrast Magnetic Resonance Images). The novel approach is an algorithm that works without the need for setting manual seed points or applying preprocessing steps or setting a region of interest. Instead, the proposed algorithm automatically detects and segments the ascending aorta using an ascending aorta model built from its anatomical features. The proposed segmentation algorithm begins with aorta detection through features model fitting augmented with Hough transform, where the ascending aorta is identified from the descending aorta and any other circular structures based on the proposed model. After detection, the whole ascending aorta is segmented up from the aortic arch down to the ostia points using a novel automatic seeded region growing algorithm. The proposed algorithm is fully automatic, works in real-time and robust as parameters used are the same for all the tested datasets. The detection and segmentation of the ascending aorta succeeded in all test cases acquired from the two imaging modalities; proving the robustness of the proposed ascending aorta model and algorithm for the automatic segmentation process even on data from different modalities and different scanner types. The accuracy of the segmentation has a mean Dice Similarity Coefficient (DSC) of 94.72% for CTA datasets and 97.13% for PC-MRI datasets

Aerothermal modeling program, phase 2. Element C: Fuel injector-air swirl characterization

The main objectives of the NASA-sponsored Aerothermal Modeling Program, Phase 2--Element C, are experimental evaluation of the air swirler interaction with a fuel injector in a simulated combustor chamber, assessment of the current two-phase models, and verification of the improved spray evaporation/dispersion models. This experimental and numerical program consists of five major tasks. Brief descriptions of the five tasks are given

Aerothermal modeling program, Phase 2, Element C: Fuel injector-air swirl characterization

The main objectives of the NASA sponsored Aerothermal Modeling Program, Phase 2, Element C, are to collect benchmark quality data to quantify the fuel spray interaction with the turbulent swirling flows and to validate current and advanced two phase flow models. The technical tasks involved in this effort are discussed

A wideband circularly polarised cross-slot antenna with an L-shaped feed-line

This paper presents a new wideband and circularly polarised (CP) slot antenna realised by using an L-shaped feed underneath the cross-slot antenna, and tapered to the conventional microstrip feed-line. The proposed antenna is fabricated with an area of 75 × 80 mm2. The simulated results showed that the antenna had an impedance matching bandwidth of 34% from 1.3 to 1.83 GHz, and an axial ratio (AR) bandwidth of 20% from 1.36 to 1.66 GHz. A maximum gain value of 3.4 – 3.8 dBi has been achieved within the operating band. The proposed antenna is of a simple and single-substrate structure, suitable for the Global Navigation Satellite Systems (GNSS) application. The impedance bandwidth and radiation patterns have been confirmed by measurement