Development of a sensitive and stable GC-MS/MS method for simultaneous determination of four N-nitrosamine genotoxic impurities in sartan substances

Recently, N-nitrosamines have been unexpectedly found in generic sartan products. Herein, we developed a sensitive and stable GC-MS/MS method with multiple reactions monitoring mode for the simultaneous determination of four N-nitrosamines in sartan substances, namely, N-nitrosodimethylamine, N-nitrosodiethylamine, N-nitrosodibutylamine, and N-nitrosodiisopropylamine. The conditions of gas chromatography and mass spectrometry were optimized. The method was validated according to the International Council for Harmonization guidelines in terms of sensitivity, linearity, accuracy, precision, specificity, and stability. The limits of detection of N-nitrosamines in sartan substances ranged from 0.002 to 0.150 ppm, and the corresponding limits of quantification were in the range of 0.008-0.500 ppm, which met the sensitivity requirements for the limits set by the Food and Drug Administration of the United States. The internal standard curve of four N-nitrosamines showed good linearity of regression coefficients over 0.99. The recoveries of N-nitrosamines in selected sartan drugs ranged from 87.68 to 123.76%. The intraday and interday relative standard deviation values were less than 9.15%. Therefore, this proposed method exhibited good sensitivity and precision, high accuracy, and fast analysis speed, which provide a reliable method for quality control of N-nitrosamines in sartan products.

Predicting the performance of the players in NBA Players by divided regression analysis

A divided regression model is built to predict the performance of the players in the National Basketball Association (NBA) from year 1997 until year 2017. The whole data set is divided into five groups of sub data sets and multiple linear regression model is employed to model each of the sub data set. In addition, the relationships among independent variables are checked by using variance inflation factor (VIF) to identify the risk of having multicollinearity in the data. Moreover, non-linearity of regression model, non-constancy of error variance and non-normality of error terms are investigated by plotting residual plots and quantile-quantile plots. Finally, a divided regression model is built by combining the results obtained from the sub data sets and the performance of the divided regression model is verified.

Analysis and interdependence of morphometric characters in the Hill stream fish Mastacembelus armatus (Lacepede) from Garhwal Himalaya

Study of morphometric characters is generally carried out for species identification in fish biology. It includes the measurements of all body lengths and their inter relationships in terms of ratios and percentages to the independent lengths (Total length, standard length and head length). Present paper deals with the analysis of various morphometric characters with species characteristics in Mastacembelus armatus (Lacepede), which is one of the most important eel like hillstream fish belonging to order Mastacembeliformes and family Mastacembelidae from river Western Nayar (290 45’ to 300 15’ latitude and 780 34’ to 790 12’ longitude ). Total length, standard length and head lengths were considered as an independent variables in ratio of which other lengths (caudal length, pre orbital length, post orbital length, maximum body depth, snout length and eye diameter) were analysed. The maximum size of fish was observed as 60 cm and the minimum being 10 cm. By using regression and correlation analysis, the modelling of data is presented to find out their interrelationship. The closest correlation was in between total length and standard length (r= 0.999) and the farthest between total length and caudal length ( r= 0.878). The linearity of regression was tested by the analysis of variance (ANOVA) which showed that all the relationships were significant at the level of 5 % significance. The multivariate analysis was also done by using cluster technique which sowed except caudal length rest all characters were forming a close cluster.

Development of an HPLC Method for Absolute Quantification and QAMS of Flavonoids Components inPsoralea corylifoliaL.

The seeds ofPsoralea corylifoliaL. (Fabaceae) are a commonly used medicinal herb in eastern Asia with many beneficial effects in clinical therapies. In this study, a simple, sensitive, precise, and specific reverse phase high-performance liquid chromatography (HPLC) method was established for quantification of 9 flavonoids inP. corylifolia, including isobavachin, neobavaisoflavone, bavachin, corylin, bavachalcone, bavachinin, isobavachalcone, corylifol A, and 4′-O-methylbavachalcone. Based on this method, a quantitative analysis of multicomponents by single marker (QAMS) was carried out, and the relative correction factors (RCFs) were calculated for determining the contents of other flavonoids. The accuracy of QAMS method was verified by comparing with the results of external standard method, as well as the feasibility and adaptability of the method applied on quality control ofP. corylifolia. The 9 compounds were baseline separated in 60 min with a good linearity of regression coefficient(R2)over 0.9991. The accuracies of QAMS were between 92.89% and 109.5%. The RSD values offin different injection volume were between 2.3% and 3.6%. The results obtained from QAMS suggested that it was a convenient and accurate method to determine multicomponents especially when some authentic standard substances were unavailable. It can be used to control the quality ofP. corylifolia.

Hubungan Antara Minat Bekerja di Industri Dengan Prestasi Belajar Praktek Kerja Industri (Prakerin) Pada Siswa Kelas Xi Jurusan Teknik Gambar Bangunan Tahun Akademik 2011/2012 SMK NEGERI 35 JAKARTA

This study aims to determine the relationship between interest in working in the industry with industry practice learning achievement (prakerin) in class XI jurusa drawing technique building academic year 2011/2012 SMK Negeri 35 Jakarta. The study lasted for 3 months from August to November 2013.The place of research conducted at SMK Negeri 35 Jakarta. The population in this study were students of class XI academic year 2011/2012 majoring in engineering drawings are 39 people. The method used in this study is a method of filling a questionnaire survey to obtain primary data for the variables X and secondary data from prakerin value for the variable Y, the approach used is correlational approach. Trial questionnaire instrument conducted by 10 respondents majoring in engineering drawing class XI buildings. After the test phase results obtained valid instrument for data collection on a sample, the number of items valid statement after test instruments is 40 statement items.Data analysis techniques starts with finding the simple linear regression equation Ŷ = 93,64 + (- 0,062 X). While testing requirements analysis is to test the normality of the estimated regression error Y over X with Liliefors test produces a maximum of 0,1057 whereas Lcount, Ltable on stage at significance level (α) of 0,05 obtained a value of 0,1418 then obtained Lcount <Ltable or 0,1057 < 0,1418 thus it can be concluded that the estimated regression error Y over X is normally distributed. Linearity of regression test yield of Fcount = 1,45 while the Ftable = 2,72, then the results show that the Fcount < Ftable which means the linear regression, followed by testing the significance of regression produces that (Fcount = 0,789) < (Ftable = 4,11) so the regression by no means. The results of calculations conclude that there is negative relationship between the Interests Working in the Industry Achievement Industry Practice.