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Among the Weapons of Mass Destruction, chemical warfare (CW) is probably one of the most brutal created by mankind in comparison with biological and nuclear warfare. Chemical weapons are inexpensive and are relatively easy to produce, even by small terrorist groups, to create mass casualties with small quantities. The characteristics of various CW agents, general information relevant to current physical as well as medical protection methods, detection equipment available and decontamination techniques are discussed in this review article. A brief note on Chemical Weapons Convention is also provided.

We report a rare case of gallbladder duplication in a young male patient with acute pyocoele in one vesicle and acute cholecystitis with cystadenoma in the other; another unusual feature was the absent or obliterated cystic duct in the proximal vesicle and non-communication with the second vesicle or the biliary system. Ultrasound examination had suggested a septate gallbladder; the diagnosis of dual gallbladder was made per-operatively during separation of the distal moiety which was presumed to be an adherent duodenum initially. Intraoperative cholecystogram confirmed the diagnosis and both gallbladders were removed successfully laparoscopically. A high degree of awareness, detailed preoperative investigations when anomalies are suspected and intraoperative cholangiography are necessary for accurate detailing of the biliary tree to avoid inadvertent damage to the biliary ductal system and overlooking of second or third gallbladder during surgery.

Abstract Currently available vaccines for the pandemic Influenza A (H1N1) 2009 produced in chicken eggs have serious impediments viz limited availability, risk of allergic reactions and the possible selection of sub-populations differing from the naturally occurring virus, whereas the cell culture derived vaccines are time consuming and may not meet the demands of rapid global vaccination required to combat the present/future pandemic. Hemagglutinin (HA) based subunit vaccine for H1N1 requires the HA protein in glycosylated form, which is impossible with the commonly used bacterial expression platform. Additionally, bacterial derived protein requires extensive purification and refolding steps for vaccine applications. For these reasons an alternative heterologous system for rapid, easy and economical production of Hemagglutinin protein in its glycosylated form is required. The HA gene of novel H1N1 A/California/04/2009 was engineered for expression in Pichia pastoris as a soluble secreted protein. The full length HA- synthetic gene having α-secretory tag was integrated into P. pastoris genome through homologous recombination. The resultant Pichia clones having multiple copy integrants of the transgene expressed full length HA protein in the culture supernatant. The Recombinant yeast derived H1N1 HA protein elicited neutralising antibodies both in mice and rabbits. The sera from immunised animals also exhibited Hemagglutination Inhibition (HI) activity. Considering the safety, reliability and also economic potential of Pichia expression platform, our preliminary data indicates the feasibility of using this system as an alternative for large-scale production of recombinant influenza HA protein in the face of influenza pandemic threat.

Process capability analysis is a valuable tool in quality assurance, but deviations from normal distribution necessitate adjustments to basic process capability indices. Process control literature offers solutions for non-normality, with data transformation being a common approach. The Box-Cox transformation (BCT) is often used to normalize non-normal data, relying on maximum likelihood estimation (MLE) to determine the transformation parameter, lambda. Alternative methods exist for estimating the single transformation parameter lamda, employing goodness-of-fit tests instead of the MLE method. This study explores two expressions within the Box-Cox transformation (BCT), encompassing both optimal and rounded values of lambda. The primary goal is to identify an effective method for transforming non-normal data into a distribution closer to normality through goodness-of-fit tests, aiming to obtain accurate estimates for process capability analysis in alignment with six sigma standards. Furthermore, this study focuses on the influence of utilizing both optimal and rounded values of lambda when transforming non-normal data to normal, and how these lambda values impact the estimates of process capability analysis. The findings reveal that methods such as Shapiro-Wilk's (SW) and Artificial Covariate (AC) outperform the MLE method. Moreover, employing the optimal lambda value during data transformation leads to improved estimates of process capability. Data simulation and analysis were conducted using Minitab software and the R programming language. [ABSTRACT FROM AUTHOR]

Process Capability Analysis (PCA) helps to improve and monitor the quality of the manufacturing products in industries. The most commonly and traditionally applied indices are process capability index and process capability ratio. Many statistical tests require the condition that the data to be approximately normally distributed. When it comes to reality the data often do not follow a normal distribution. In such instances, different approaches are employed. Box-Cox Transformation (BCT) is one such methodology that is often used by quality practitioners relying on single transforming parameter lamda to transform the non-normal data into normal data. The widely used approach to decide the transforming parameter lamda is based on the rounded value of lamda instead of an optimal value of lamda. There are two transforming expressions available in BCT method. The choice of the value for lamda in BCT can have a significant impact on the results. This paper concentrates on the impact of data transformation in BCT method through two different expressions based on an optimal as well as a rounded value of lamda. The influence made by the estimates of process capability and process performance indices is also studied in this paper. The result of the analysis clearly indicates that the optimal value of lamda when employed in the first BCT transformation expression to estimate the process capability indices for non-normal data provides improvised results. For data analysis, Ms-Excel and Minitab 21 software has been used in this study. [ABSTRACT FROM AUTHOR]

A life test is a random experiment performed on manufactured products such as electrical and electronic components to estimate their life period based on a randomly chosen components. The lifespan of a component is considered as a random variable that follows a certain continuous-type distribution, called the lifetime distribution. Reliability sampling is one of the decision-making methodologies in product control and deals with inspection procedures for sentencing one or more lots or batches of items submitted for inspection. The concept of sampling plans for life tests involving with two random samples is employed in the present study under the assumption that the lifetime random variable is described by the Lomax distribution. A procedure based on mean / median life criterion is developed for designing the optimum plans with minimum sample sizes when two points on the desired operating characteristic curve are prescribed to ensure protection to the producer and the consumer. [ABSTRACT FROM AUTHOR]

Process capability analysis is an effective and efficient tool for quality assurance. When the distribution of the underlying quality characteristics is not normal, modifications of the basic process capability indices are required. Literature in process control provides avenues to resolve the issue of nonnormality and data transformation is one of the approaches frequently applied in practice. Primarily the Box - Cox transformation (BCT) is employed to transform the non normal data into normal data which originally utilizes the method of maximum likelihood estimation (MLE) to find the single transformation parameter ν. There are alternative methods to estimate the optimal parametric value ν using goodness of fit tests rather using MLE method. In order to bring improved estimates, this paper makes a fresh attempt to estimate process capability analysis (PCA) using transformed data through different goodness of fit tests. The simulation study uses variety of asymmetric behaviors from a Weibull distribution generating a random sample of 100 data points to find the best goodness of fit test for better process capability estimates that are compared to the standard of six sigma results for nonnormal data. Final result shows that Shapiro-Wilk's (SW) and Artificial Covariate (AC) methods are performing well when compared to the method of MLE. Minitab software and R programming language were utilized for data simulation and analysis. [ABSTRACT FROM AUTHOR]