Incidence Rate and Risk Factors of Radial Artery Spasm during Transradial Coronary Angiography

Background: Radial artery spasm (RAS) is one of the most common complications of radial coronary angiography. Several demographic and clinical factors increase the risk of RAS in this procedure. We aimed to evaluate the effect of various risk factors on the incidence and severity of RAS in radial coronary angiography.  Methods: This cross-sectional study was performed on 120 patients who were randomly selected from candidates referred to Shahid Modarres Educational Medical Center for coronary angiography by the radial method. After angiography, radial arteriography was performed to diagnose spasms. The association of some demographic and clinical factors with the incidence and severity of RAS was evaluated. Results: 35 of the 120 patients (29.16%) developed RAS during angiography. Shorter height, shorter radius bone length, less radial artery diameter, longer procedure length, diabetes mellitus, more catheters used, and female sex were significantly associated with higher incidence. The predictive power of these factors for the occurrence of spasms was very good with AUC=0.88. Age, shorter height, higher body mass index, smaller radial artery diameter, longer procedure time, diabetes mellitus, failure of initial effort for puncture, number of catheters used, and female sex were significantly associated with the severity of spasms. Conclusions: The incidence or severity of spasms during the procedure can be reduced by examining the available risk factors for every patient before deciding to perform angiography

New methods for captive finance in project based companies using private sectors supply

Economic development in countries depends on implementing of infrastructural projects and services, furthermore, increasing efficiency and quality of offered services are of its purposes. Mention this fact that in developing countries finding the financial source is one of the main challenges that often faced up, cooperating with private sectors seems more important from day to day. The cooperative styles vary due to each project specific condition. In current research, the compilation of constructing types and financial recourse, briefly discussed in base of implementing and financing captive methods, then with mentioning the legal limitation and specific conditions in our country, the appropriate methods in different projects including oil and gas, petro chemistry and water resources are revealed. Finally, essential conditions and characteristics of these offered corporations were expanded on, for using them efficiently to provide the essential fundamental by private resources that lead to economic development and improvement

Online Optimal Neuro-Fuzzy Flux Controller for DTC Based Induction Motor Drives

In this paper a fast flux search controller based on the Neuro-fuzzy systems is proposed to achieve the best efficiency of a direct torque controlled induction motor at light load. In this method the reference flux value is determined through a minimization algorithm with stator current as objective function. This paper discusses and demonstrates the application of Neurofuzzy filtering to stator current estimation. Simulation and experimental results are presented to show the fast response of proposed controller

New methods for captive finance in project based companies using private sectors supply

Economic development in countries depends on implementing of infrastructural projects and services, furthermore, increasing efficiency and quality of offered services are of its purposes. Mention this fact that in developing countries finding the financial source is one of the main challenges that often faced up, cooperating with private sectors seems more important from day to day. The cooperative styles vary due to each project specific condition. In current research, the compilation of constructing types and financial recourse, briefly discussed in base of implementing and financing captive methods, then with mentioning the legal limitation and specific conditions in our country, the appropriate methods in different projects including oil and gas, petro chemistry and water resources are revealed. Finally, essential conditions and characteristics of these offered corporations were expanded on, for using them efficiently to provide the essential fundamental by private resources that lead to economic development and improvement

Application of Artificial Neural Networks for Seismic Analysis and Design of Buried Pipelines in Heterogeneous Soils

Every year, the phenomenon of earthquake causes a lot of human, financial and environmental losses. Transmission pipelines are one of the vital arteries that are very important, however, in the event of an earthquake can cause devastating damages. Safeguarding urban and interurban facilities, including electricity, water supply, oil and gas transmission lines, against these loads requires careful studies and engineering designs. Given that traditional methods for seismic design of pipelines such as FEM modeling and experimental methods are so expensive, a new combined method for predicting the strain of pipes based on the Artificial Neural Network (ANN) is proposed. For this purpose, the parameters of the pipeline including pipe and soil type, length, discharge, path slope, depth, etc. and earthquake-induced characteristics including earthquake acceleration, earthquake occurrence time, Peak ground acceleration (PGA), etc. were included in the model. Earthquake input parameters were considered as input parameters and pipe strains and stresses were considered as output parameter. ANSYS finite element software has also been used to simulate the pipeline and produce training data. The results of finite element software were used as input and output parameters for training and validating artificial neural network. 753 models created using ANSYS and its input/output data divided into three parts to creat ANN model. 70% of the total data were used for training, 15% for validating and 15% for testing the ANN model. Results show that the proposed Method provides a very good agreement with the computational results of the ANSYS with accuracy of 96 percent

The Value of Family History in Diagnosing Primary Immunodeficiency Disorders

Eliciting proper family medical history is critical in decreasing morbidity and mortality in patients with primary immunodeficiency disorders (PIDs). Communities with a common practice of consanguinity have a high rate of PIDs. We are presenting 2 cases where digging deeply into the family medical history resulted in the diagnosis of Omenn syndrome, a possibly fatal entity if not managed in a reasonable period

Experimental Study on the Effect of Eccentric Loads on the Bearing Capacity of Strip Footing Located on the Inclined Multi-Layer Soil Mass with a Weak Soil Layer

Engineers often face challenges when designing foundations that are located over and near the slopes. By using a new small-scale laboratory model, the Effect of eccentric loading on the bearing capacity of a strip footing located on the inclined multi-layer soil mass with a weak soil layer was investigated as multi-effects. Thin layers have substantial effects on the ultimate bearing capacity, despite they seem to be insignificant. A series of laboratory model tests were performed on a rigid strip footing resting on surfaces with different layered slope foundations. The experimental program considered different foundation configurations by varying the footing distance from the slope’s top and the inclination of the thin layer. It is found that the weak thin layer decreases the ultimate bearing capacity specifically. The laboratory results indicate that the value of eccentricity affects the final bearing capacity and increases this capacity by moving away from the weak layer and the slope. Also, The weak thin layer at the critical distance led to more reduction in the ultimate bearing capacity by 43%. The results were compared with analytical methods and the differences were 2 to 9.5%. Also, the numerical simulation of the physical data shows that the results can be developed into large-scale models as a prediction

Enhanced Heart Sound Classification Using Mel Frequency Cepstral Coefficients and Comparative Analysis of Single vs. Ensemble Classifier Strategies

This paper explores the efficacy of Mel Frequency Cepstral Coefficients (MFCCs) in detecting abnormal heart sounds using two classification strategies: a single classifier and an ensemble classifier approach. Heart sounds were first pre-processed to remove noise and then segmented into S1, systole, S2, and diastole intervals, with thirteen MFCCs estimated from each segment, yielding 52 MFCCs per beat. Finally, MFCCs were used for heart sound classification. For that purpose, in the single classifier strategy, the MFCCs from nine consecutive beats were averaged to classify heart sounds by a single classifier (either a support vector machine (SVM), the k nearest neighbors (kNN), or a decision tree (DT)). Conversely, the ensemble classifier strategy employed nine classifiers (either nine SVMs, nine kNN classifiers, or nine DTs) to individually assess beats as normal or abnormal, with the overall classification based on the majority vote. Both methods were tested on a publicly available phonocardiogram database. The heart sound classification accuracy was 91.95% for the SVM, 91.9% for the kNN, and 87.33% for the DT in the single classifier strategy. Also, the accuracy was 93.59% for the SVM, 91.84% for the kNN, and 92.22% for the DT in the ensemble classifier strategy. Overall, the results demonstrated that the ensemble classifier strategy improved the accuracies of the DT and the SVM by 4.89% and 1.64%, establishing MFCCs as more effective than other features, including time, time-frequency, and statistical features, evaluated in similar studies