Just a few months away from the next ITMAASIA+CITME to be held in Shanghai from June 22 to 26,Italy’s leadership position among textile machinery technology suppliers is highlighted bythe high number of Italian manuf...Just a few months away from the next ITMAASIA+CITME to be held in Shanghai from June 22 to 26,Italy’s leadership position among textile machinery technology suppliers is highlighted bythe high number of Italian manufacturers展开更多
As we know,English writing is an important part of communicative competence.But for many English majors,it is hard to express their thoughts clearly.In order to find out the main problems and corresponding measures,th...As we know,English writing is an important part of communicative competence.But for many English majors,it is hard to express their thoughts clearly.In order to find out the main problems and corresponding measures,the author analyzes many compositions written by English majors.With some academic opinions and the author’s own analysis,some problems existing in students’writing are listed.According to the problems,the author summarizes some influencing factors.Finally,the author gives some relevant solutions.Through analyzing those samples,the author hopes it has some help for English majors’writing.展开更多
Objective: Genetic and neurobiological factors are considered to be the major causes of major depressive disorder (MDD). However, over last few years study results revealed that socio-demographic factors contribute a ...Objective: Genetic and neurobiological factors are considered to be the major causes of major depressive disorder (MDD). However, over last few years study results revealed that socio-demographic factors contribute a significant role in abnormal functional activity and recognized as major causative factors to the pathogenesis and severity of MDD. The aim of this study was to assess the socio-demographic characteristics of Bangladeshi MDD patients and to discover their role on the severity of disease. Material and Methods: A retrospective review of the case notes of psychiatry outpatients at Bangabandhu Sheikh Mujib Medical University (B中央人民政府) was carried out between Sep-Nov 2016. A total of 234 MDD patients (aged 18 to 60 years) were randomly recruited. Relevant information was obtained by collection of prescription details from the patients or their relatives by face to face interview. Results: Mean age and body mass index (BMI) were found 34.734 years (SEM ± 0.842) and 22.014 kg/m2 respectively. Among all respondents, 56% (133) were male and 44% (106) were female where mean income was 26.84 KBDT (Kilo Bangladeshi Taka) (SEM ± 0.749). Roughly 46% (111) patients were found to be below secondary level of education. Married people (56%) had a tendency to develop depression compare to unmarried people (36%). Urban residents (64%) are more prone to suffer from depression than rural residents (36%). There was mild depression in 28% (68), moderate in 37% (157), and severe in 14% (34) patients. Correlation analysis shows that age, sex, marital status, education, family income, and area of residence (p-values 0.004, 0.001, 0.000, 0.011, 0.000 and 0.000, respectively) are associated with the severity of disease. Moreover, among all significant correlations age, marital status and area of residence were positively correlated with the severity of MDD (r = 0.184, r = 0.238 and r = 0.256) while sex, education and family income were negatively correlated with the severity of depression (r = ﹣0.207, r = ﹣0.164 and r = ﹣0.722). Conclusion: Current study shows that age, gender, marital status, education, family income, and area of residence are associated with the severity of depression. Age, marital status and residence of MDD patients are positively correlated with the severity of disease while gender, education and family income are negatively correlated with the severity of depression. It is predicted that this study will be helpful for the management and assortment of MDD patients with more accuracy based on their socio-demographic features.展开更多
Factor analysis (FA) is a time-honored multivariate analysis procedure for exploring the factors underlying observed variables. In this paper, we propose a new algorithm for the generalized least squares (GLS) estimat...Factor analysis (FA) is a time-honored multivariate analysis procedure for exploring the factors underlying observed variables. In this paper, we propose a new algorithm for the generalized least squares (GLS) estimation in FA. In the algorithm, a majorization step and diagonal steps are alternately iterated until convergence is reached, where Kiers and ten Berge’s (1992) majorization technique is used for the former step, and the latter ones are formulated as minimizing simple quadratic functions of diagonal matrices. This procedure is named a majorizing-diagonal (MD) algorithm. In contrast to the existing gradient approaches, differential calculus is not used and only elmentary matrix computations are required in the MD algorithm. A simuation study shows that the proposed MD algorithm recovers parameters better than the existing algorithms.展开更多
文摘Just a few months away from the next ITMAASIA+CITME to be held in Shanghai from June 22 to 26,Italy’s leadership position among textile machinery technology suppliers is highlighted bythe high number of Italian manufacturers
文摘As we know,English writing is an important part of communicative competence.But for many English majors,it is hard to express their thoughts clearly.In order to find out the main problems and corresponding measures,the author analyzes many compositions written by English majors.With some academic opinions and the author’s own analysis,some problems existing in students’writing are listed.According to the problems,the author summarizes some influencing factors.Finally,the author gives some relevant solutions.Through analyzing those samples,the author hopes it has some help for English majors’writing.
文摘Objective: Genetic and neurobiological factors are considered to be the major causes of major depressive disorder (MDD). However, over last few years study results revealed that socio-demographic factors contribute a significant role in abnormal functional activity and recognized as major causative factors to the pathogenesis and severity of MDD. The aim of this study was to assess the socio-demographic characteristics of Bangladeshi MDD patients and to discover their role on the severity of disease. Material and Methods: A retrospective review of the case notes of psychiatry outpatients at Bangabandhu Sheikh Mujib Medical University (B中央人民政府) was carried out between Sep-Nov 2016. A total of 234 MDD patients (aged 18 to 60 years) were randomly recruited. Relevant information was obtained by collection of prescription details from the patients or their relatives by face to face interview. Results: Mean age and body mass index (BMI) were found 34.734 years (SEM ± 0.842) and 22.014 kg/m2 respectively. Among all respondents, 56% (133) were male and 44% (106) were female where mean income was 26.84 KBDT (Kilo Bangladeshi Taka) (SEM ± 0.749). Roughly 46% (111) patients were found to be below secondary level of education. Married people (56%) had a tendency to develop depression compare to unmarried people (36%). Urban residents (64%) are more prone to suffer from depression than rural residents (36%). There was mild depression in 28% (68), moderate in 37% (157), and severe in 14% (34) patients. Correlation analysis shows that age, sex, marital status, education, family income, and area of residence (p-values 0.004, 0.001, 0.000, 0.011, 0.000 and 0.000, respectively) are associated with the severity of disease. Moreover, among all significant correlations age, marital status and area of residence were positively correlated with the severity of MDD (r = 0.184, r = 0.238 and r = 0.256) while sex, education and family income were negatively correlated with the severity of depression (r = ﹣0.207, r = ﹣0.164 and r = ﹣0.722). Conclusion: Current study shows that age, gender, marital status, education, family income, and area of residence are associated with the severity of depression. Age, marital status and residence of MDD patients are positively correlated with the severity of disease while gender, education and family income are negatively correlated with the severity of depression. It is predicted that this study will be helpful for the management and assortment of MDD patients with more accuracy based on their socio-demographic features.
文摘Factor analysis (FA) is a time-honored multivariate analysis procedure for exploring the factors underlying observed variables. In this paper, we propose a new algorithm for the generalized least squares (GLS) estimation in FA. In the algorithm, a majorization step and diagonal steps are alternately iterated until convergence is reached, where Kiers and ten Berge’s (1992) majorization technique is used for the former step, and the latter ones are formulated as minimizing simple quadratic functions of diagonal matrices. This procedure is named a majorizing-diagonal (MD) algorithm. In contrast to the existing gradient approaches, differential calculus is not used and only elmentary matrix computations are required in the MD algorithm. A simuation study shows that the proposed MD algorithm recovers parameters better than the existing algorithms.
