Tunability of terahertz random lasers with temperature based on superconducting materials

We theoretically demonstrate the tunabiltiy of terahertz random lasers composed of high temperature superconductorYBCO and ruby layers as active medium. The considered system is a one-dimensional disordered medium made of ruby grain and YBCO. Finite-difference time domain method is used to calculate the emission spectrum and spatial distribution of electric field at different temperatures. Our numerical results reveal that the superconductor based random lasers exhibit large temperature tunability in the terahertz domain. The emission spectrum is significantly temperature dependent, the number of lasing modes and their intensities increase with decreasing temperature. Also, we make some discussion to explain the reason for the observed tunability and the effect of temperature variation on the spatial distribution of the electric field in the disordered active medium

Ratio of Coefficients of Variation for Comparing the Dispersions of Several Independent Populations

The coefficient of variation (CV) is an important and useful statistical tool for comparing several populations. In cases where there are multiple populations with different means and variances, the ratio of the coefficients of variation (CVs) is a good way to compare the dispersion of the populations. Because of the possible minor differences between multiple CVs and the lack of a robust interpretation, the ratio of CVs is more accurate than the difference of CVs. When a statistical analysis consists of some simultaneous statistical tests such as equality of several CVs, multiple testing is useful. As an example, the multiple testing about the ratio of CVs is performed to evaluate and compare scale of hand, foot and mouth disease (SHFMD) of 79911 patients between January 2010 and December 2017 in the three Malaysian provinces

Does Tuberculosis Have a Seasonal Pattern among Migrant Population Entering Iran?

Background: There are few quantitative documents about the seasonal incidence of tuberculosis (TB) among immigrant populations. Concerning the significant role of recognizing seasonal changes of TB in improving the TB control program, this study determines the trend and seasonal temporal changes of TB among immigrants entering Iran. Methods:In this longitudinal study, data from the Iranian TB register Program (from 2005 to 2011) was used. The aggregated number of monthly and seasonal TB cases was obtained by adding the daily counts. Data was analyzed by Chi-square, Independent T-test, ANOVA, and Poisson regression using Stata 11 and SPSS 20 software. Results: Among 74,155 registered patients with TB, 14.3% (10,587) were non-Iranian who had immigrated to Iran from 29 different countries. The highest aggregated number of seasonal and monthly incidence of TB in immigrants was observed in spring (2824, P= 0.007) and in May (1037, P< 0.001). The number of non-Iranian patients with TB increased significantly over the years (β= 0.016, P= 0.001). Conclusion: This study shows that immigrants constitute a significant portion of TB patients recorded in Iran and this trend is increasing. Also, the peak incidence of this disease is the second month of the spring

The Status of the Surveillance System of Groups at Risk of Tubercolosis in Iran: AQualitative Study

Background: In order to achieve a dynamic surveillance system for the groups at risk of tuberculosis and to improve its quality, investigating its various aspects and benefiting from the opinions of the experts and experienced individuals in this field are very important. Hence, the objective of this study was to explore the status of the surveillance system for the groups at risk of tuberculosis in Iran. Methods: Data collection was carried out via interviews with 17 experts in the tuberculosis control program of Iran. In order to evaluate the validity and reliability of data, four criteria of credibility, transferability, dependability and confirmability were used. Frame analysis was used for data analysis. Results: Based on the interviewee's opinions, twelve major groups at risk of tuberculosis and seven challenges in the surveillance system were identified. For the majority of these at risk groups, there is no structured program and the status of case finding and treatment is similar to the public population. For some others (HIV/ AIDS patients, prisoners and people at exposure), there is a program, but its effectiveness is uncertain. Conclusion: Results indicate that groups at risk of tuberculosis are widespread and access to some of them is difficult; hence, these groups are the main challenges of the tuberculosis control program in Iran

Completeness and Underestimation of Cancer Mortality Rate in Iran: A Report from Fars Province in Southern Iran

Background: The incidence and mortality rates of cancer are increasing worldwide, particularly in the developing countries. Valid data are needed for measuring the cancer burden and making appropriate decisions toward cancer control. We evaluated the completeness o

Completeness and Underestimation of Cancer Mortality Rate in Iran: A Report from Fars Province in Southern Iran

Background: The incidence and mortality rates of cancer are increasing worldwide, particularly in the developing countries. Valid data are needed for measuring the cancer burden and making appropriate decisions toward cancer control. We evaluated the completeness of GHDWK�UHJLVWU\�ZLWK�UHJDUG�WR�FDQFHU�GHDWK�LQ�)DUV�3URYLQFH��,��5��RI�,UDQ� Methods: We used data from three sources in Fars Province, including the national death registry (source 1), the follow-up data from the pathology-based cancer registry (source 2) and hospital based records (source 3) during 2004 – 2006. We used the capture-recapture PHWKRG�DQG�HVWLPDWHG�XQGHUHVWLPDWLRQ�DQG�WKH�WUXH�DJH�VWDQGDUGL]HG�PRUWDOLW\�UDWH��605��IRU�FDQFHU��:H�XVHG�ORJ�OLQHDU��//��PRGHOLQJ� for statistical analysis. Result: :H�REVHUYHG������������DQG�����FDQFHU�GHDWKV�LQ�VRXUFHV������DQG����UHVSHFWLYHO\��IWHU�GDWD�OLQNDJH��ZH�HVWLPDWHG�WKDW�PRUWDOLW\� UHJLVWU\�KDG�DERXW�����XQGHUHVWLPDWLRQ�IRU�FDQFHU�GHDWK��$IWHU�DGMXVWPHQW�IRU�WKLV�XQGHUHVWLPDWLRQ�UDWH��WKH�$605�RI�FDQFHU�LQ�WKH�)DUV� 3URYLQFH�IRU�DOO�FDQFHU�W\SHV�LQFUHDVHG�IURP������SHU��������������&,�������±�������WR������SHU��������������&,�������±��������DFFRXQWLQJ� IRU�����������&,�������±�������FDQFHU�GHDWKV�DQQXDOO\�� Conclusion: The mortality rate of cancer is considerably higher than the rates reported by the routine registry in Iran. Improvement in the validity and completeness of the mortality registry is needed to estimate the true mortality rate caused by cancer in Iran

Does tuberculosis have a seasonal pattern among migrant population entering Iran?

Background: There are few quantitative documents about the seasonal incidence of tuberculosis (TB) among immigrant populations. Concerning the significant role of recognizing seasonal changes of TB in improving the TB control program, this study determines the trend and seasonal temporal changes of TB among immigrants entering Iran. Methods: In this longitudinal study, data from the Iranian TB register Program (from 2005 to 2011) was used. The aggregated number of monthly and seasonal TB cases was obtained by adding the daily counts. Data was analyzed by Chi-square, Independent T-test, ANOVA, and Poisson regression using Stata 11 and SPSS 20 software. Results: Among 74,155 registered patients with TB, 14.3% (10,587) were non-Iranian who had immigrated to Iran from 29 different countries. The highest aggregated number of seasonal and monthly incidence of TB in immigrants was observed in spring (2824, P = 0.007) and in May (1037, P < 0.001). The number of non-Iranian patients with TB increased significantly over the years (β= 0.016, P = 0.001). Conclusion: This study shows that immigrants constitute a significant portion of TB patients recorded in Iran and this trend is increasing. Also, the peak incidence of this disease is the second month of the sprin

Liver Disease Recognition: A Discrete Hidden Markov Model Approach

The liver alongside the heart and the brain is the largest and the most vital organ within the human body whose absence leads to certain death. In addition, diagnosis of liver diseases takes a long time and requires sufficient expertise of physicians. To this end, statistical methods as automatic prediction systems can help specialists to diagnose liver diseases quickly and accurately. The Discrete Hidden Markov Model (DHMM) is an intelligent and a strong statistical model used to predict the types of liver diseases in patients in this study. The data in this crosssectional study included information elicited from the records of 1143 patients with 5 different types of liver diseases including cirrhosis of the liver, liver cancer, acute hepatitis, chronic hepatitis, and fatty liver disease admitted to Afzalipour Hospital in the city of Kerman in the time period of 2006-2013. At first, the type of diseases for each patient was identified; however, it was assumed that the type of diseases is unknown and there were attempts to diagnose the type of the disease through the DHMM to examine its accuracy. Therefore, the DHMM was fitted to the data and its performance was evaluated by using the parameters of accuracy, sensitivity, and specificity. Such parameters of the model were separately calculated for the diagnosis of liver diseases. The highest levels of accuracy, sensitivity, and specificity were associated with the diagnosis of cirrhosis of the liver and equal to 0.77, 0.82, 0.96, respectively; and the lowest levels were related to the diagnosis of fatty liver disease with an accuracy level of 0.65 and a sensitivity level of 0.69. As well, the specificity level in the diagnosis of fatty liver disease was 0.94. The results of this study indicated the potential ability of the DHMM; thus, the use of this model in terms of diagnosing liver diseases was strongly recommended

Assessment of Trend and Seasonality in Road Accident Data: An Iranian Case Study

Background: Road traffic accidents and their related deaths have become a major concern, particularly in developing countries. Iran has adopted a series of policies and interventions to control the high number of accidents occurring over the past few years. In this study we used a time series model to understand the trend of accidents, and ascertain the viability of applying ARIMA models on data from Taybad city. Methods : This study is a cross-sectional study. We used data from accidents occurring in Taybad between 2007 and 2011. We obtained the data from the Ministry of Health (MOH) and used the time series method with a time lag of one month. After plotting the trend, non-stationary data in mean and variance were removed using Box-Cox transformation and a differencing method respectively. The ACF and PACF plots were used to control the stationary situation. Results : The traffic accidents in our study had an increasing trend over the five years of study. Based on ACF and PACF plots gained after applying Box-Cox transformation and differencing, data did not fit to a time series model. Therefore, neither ARIMA model nor seasonality were observed. Conclusion : Traffic accidents in Taybad have an upward trend. In addition, we expected either the AR model, MA model or ARIMA model to have a seasonal trend, yet this was not observed in this analysis. Several reasons may have contributed to this situation, such as uncertainty of the quality of data, weather changes, and behavioural factors that are not taken into account by time series analysis

Prevalence of Carpal Tunnel Syndrome in Diabetic Patients with and without Metabolic Syndrome

Background and Objectives: Carpal tunnel syndrome (CTS) is defined as the impaction of the median nerve in the carpal tunnel of the wrist. Metabolic disorders are closely associated with CTS; and metabolic syndrome (MS) is found to be more in patients with CTS. Metabolic syndrome is highly prevalent in patients with type 2 diabetes. This study was conducted to determine the prevalence of CTS in diabetic patients with and without metabolic syndrome. Material and Methods: In this cross-sectional study, 439 diabetic patients that participated in the study of risk factors for coronary artery disease in Kerman (KERCADRS) were enrolled. People with positive clinical symptoms for CTS and a positive Boston questionnaire, were referred to a neurologist for further diagnosis. For the diagnosis of metabolic syndrome, three criteria (ATPIII, IDF and new criteria in Kerman) were used. Also, electro-diagnostic tests were used for the diagnosis of CTS. Data were analyzed by independent t-test and chi square test in SPSS20. Results: The prevalence of CTS in diabetic patients was 24.23%. The prevalence of the disorder in male and female patients was 16.21% and 30.65%, respectively. The results showed that there is no significant difference in the prevalence of CTS in diabetic people with and without metabolic syndrome, in overall as well as sex subgroups. Discussion and Conclusion: The higher prevalence of CTS in diabetic patients in this study compared to other studies shows the lack of prevention and case finding in diabetic patients. Therefore, screening, educating and informing at risk people about the disease is necessary