Optimization of Bayesian repetitive group sampling plan for quality determination in Pharmaceutical products and related materials

Sampling plans are extensively used in pharmaceutical industries to test drugs or other related materials to ensure that they are safe and consistent. A sampling plan can help to determine the quality of products, to monitor the goodness of materials and to validate the yields whether it is free from defects or not. If the manufacturing process is precisely aligned, the occurrence of defects will be an unusual occasion and will result in an excess number of zeros (no defects) during the sampling inspection. The Zero Inflated Poisson (ZIP) distribution is studied for the given scenario, which helps the management to take a precise decision about the lot and it can certainly reduce the error rate than the regular Poisson model. The Bayesian methodology is a more appropriate statistical procedure for reaching a good decision if the previous knowledge is available concerning the production process. This article proposed a new design of the Bayesian Repetitive Group Sampling plan based on Zero Inflated Poisson distribution for the quality assurance in pharmaceutical products and related materials. This plan is studied through the Gamma-Zero Inflated Poisson (G-ZIP) model to safeguard both the producer and consumer by minimizing the Average Sample Number. Necessary tables and figures are constructed for the selection of optimal plan parameters and suitable illustrations are provided that are applicable for pharmaceutical industries.

Diagnostic and age composition of excess mortality associated with the New Year holidays in Russia

Statistics show that in many countries of the world holidays are associated with an increase in morbidity and mortality; this is especially pronounced during the New Year and Christmas period. This article presents an estimate of the excess number of deaths in Russia during the January holidays in 2011–2019 by main classes of causes of death and by age groups. The study relies on the Rosstat dataset of 16.83 million individual non-personalized death records referring to 2011–2019. The authors of the paper estimate excess mortality for each cause and age group as the difference between actually observed mortality and the LOWESS moving average calculated for non-holiday period, extrapolated to the holidays. The calculations showed that the period of excess mortality lasted from January 1 to January 22 with a maximum on January 1. Over 22 days, excess mortality in 2011–2019 amounted to 89.0 thousand cases or 8.4% in relation to mortality on non-holidays; excess mortality on January 1 amounted to 11.4 thousand cases. In contrast to mortality from diseases of the circulatory, respiratory, and digestive systems, the contribution of which to excess mortality was proportional to their prevalence on non-holidays, proportion of excess mortality from external causes almost doubled (23.6% versus 12.7 % on weekdays). January 1 saw the highest excess mortality from external causes, including that of alcohol poisoning, homicide, and suicide, in all age groups; on January 2 the highest increase was observed in mortality from diseases of the circulatory system; on January 9 and 10 — from the pathologies of the respiratory and digestive systems. January holidays in Russia are associated with significant excess mortality, primarily as a result of the abuse of strong alcoholic beverages. Informing the population about the fatal consequences of such a consumption regime and a decrease in the availability of strong alcohol, the maximum sales of which falls on December, can reduce the damage during the January holidays.

Workload Analysis in Determining the Needs Analysis of the Number in Education Personnel at XYZ University Yogyakarta

Background – XYZ University in Yogyakarta is one of the new state universities which, is currently preparing to enter the Public Service Agency in determining the number of technicians to be distributed to work units. There is no standard provision until now. The actual condition so far is a gap in the number of technicians in several work units. Every team has an excess number of Education Personnel, but in other work units, they experience a shortage. This clear interferes with the tendons' expected performance of the tendons, thus impacting the work unit. Research Purpose - Based on these conditions, this study analyzed the need for educational personnel based on workload analysis. Research Methodology- The study conducted in several units with resource determination method used purposive samplings (specific criteria) at XYZ University in Yogyakarta. Methods of data collection with interviews and documentation. Sources of data in the form of primary and secondary data. The results of this study are expected to be useful for institutional leaders regarding the proportional number of education personnel needed in each work unit. Research Result /Contribution – This research shows that some excess human resources and units lack human resources. However, when viewed from the job description, it turns out that several jobs are routinely low on a daily or weekly basis. But there is a relatively high need for hours in annual activities so, that the workload is uneven. The management needs to be considered the number of when analyzing employees in each work unit. The results provide an overview to the management of XYZ University in planning employee needs in the future period.

Tourism Growth Prediction Based on Deep Learning Approach

The conventional tourism demand prediction models are currently facing several challenges due to the excess number of search intensity indices that are used as indicators of tourism demand. In this work, the framework for deep learning-based monthly prediction of the volumes of Macau tourist arrivals was presented. The main objective in this study is to predict the tourism growth via one of the deep learning algorithms of extracting new features. The outcome of this study showed that the performance of the adopted deep learning framework was better than that of artificial neural network and support vector regression models. Practitioners can rely on the identified relevant features from the developed framework to understand the nature of the relationships between the predictive factors of tourist demand and the actual volume of tourist arrival.

ZERO-INFLATED POISSON REGRESSION MODELS: APPLICATIONS IN THE SCIENCES AND SOCIAL SCIENCES

This paper makes a theoretical contribution by presenting a detailed derivation of a zero-inflated Poisson (ZIP) model, and then deriving the parameters of the ZIP model using a fishing data set. This model has several practical applications, and is largely performed to model count data that have an excess number of zero counts. In the scope of the paper, we introduce the complete formulae, the likelihood and log-likelihood functions and the estimating equation of the ZIP model. We then investigate the theory of large sample properties of this model under some regularity conditions. A simulation study and a fishing data set are studied for the ZIP model. The results in the actual application in this work are meaningful, useful and crucial in reality. The results also provide reliable evidence for obtaining the largest number of fish while fishing. This is the contribution of this research in terms of applications. Finally, the important applications of this model in practice, some conclusions, and future work is also presented for consideration.

A Quantitative Benefit–Risk Analysis of ChAdOx1 nCoV-19 Vaccine among People under 60 in Italy

The Oxford-AstraZeneca ChAdOx1 nCoV-19 is a vaccine against the COVID-19 infection that was granted a conditional marketing authorization by the European Commission in January 2021. However, following a report from the Pharmacovigilance Risk Assessment Committee (PRAC) of European Medicines Agency, which reported an association with thrombo-embolic events (TEE), in particular disseminated intravascular coagulation (DIC) and cerebral venous sinus thrombosis (CVST), many European countries either limited it to individuals older than 55–60 years or suspended its use. We used publicly available data to carry out a quantitative benefit–risk analysis of the vaccine among people under 60 in Italy. Specifically, we used data from PRAC, Eudravigilance and ECDC to estimate the excess number of deaths for TEE, DIC and CVST expected in vaccine users, stratified by age groups. We then used data from the National Institute of Health to calculate age-specific COVID-19 mortality rates in Italy. Preventable deaths were calculated assuming a 72% vaccine efficacy over an eight-month period. Finally, the benefit–risk ratio of ChAdOx1 nCoV-19 vaccination was calculated as the ratio of preventable COVID-19 deaths to vaccine-related deaths, using Monte-Carlo simulations. We found that among subjects aged 20–29 years the benefit–risk (B-R) ratio was not clearly favorable (0.70; 95% Uncertainty Interval (UI): 0.27–2.11). However, in the other age groups the benefits of vaccination largely exceeded the risks (for age 30–49, B-R ratio: 22.9: 95%UI: 10.1–186.4). For age 50–59, B-R ratio: 1577.1: 95%UI: 1176.9–2121.5). Although many countries have limited the use of the ChAdOx1 nCoV-19 vaccine, the benefits of using this vaccine clearly outweigh the risks in people older than 30 years. Study limitations included risk of underreporting and that we did not provide age-specific estimates. The use of this vaccine should be a strategic and fundamental part of the immunization campaign considering its safety and efficacy in preventing COVID-19 and its complications.

Zero-Inflated Generalized Linear Mixed Models: A Better Way to Understand Data Relationships

Our article explores an underused mathematical analytical methodology in the social sciences. In addition to describing the method and its advantages, we extend a previously reported application of mixed models in a well-known database about corruption in 149 countries. The dataset in the mentioned study included a reasonable amount of zeros (13.19%) in the outcome variable, which is typical of this type of research, as well as quite a bit of social sciences research. In our paper, present detailed guidelines regarding the estimation of models where the data for the outcome variable includes an excess number of zeros, and the dataset has a natural nested structure. We believe our research is not likely to reject the hypothesis favoring the adoption of mixed modeling and the inflation of zeros over the original simpler framework. Instead, our results demonstrate the importance of considering random effects at country levels and the zero-inflated nature of the outcome variable.

A quantitative risk-benefit analysis of ChAdOx1 nCoV-19 vaccine among people under 60 in Italy

ChAdOx1 nCoV-19 is a vaccine against the COVID-19 infection that was granted a conditional marketing authorization by the European Commission in January 2021. However, following a report from the Pharmacovigilance Risk Assessment Committee (PRAC) of European Medicines Agency, which reported an association with thrombo-embolic events (TEE), in particular Disseminated intravascular coagulation (DIC) and Cerebral venous sinus thrombosis (CVST), many European countries either limited to individuals older than 55-60 years or suspended its use. We used publicly available data to carry out a quantitative risk-benefit analysis of the vaccine among people under 60 in Italy. Specifically, we used data from PRAC, Eudravigilance and ECDC to estimate the excess number of deaths for TEE, DIC and CVST expected in vaccine users, stratified by age groups. We then used data from the National Institute of Health to calculate age-specific COVID-19 mortality rates in Italy. Preventable deaths were calculated assuming a 72% vaccine efficacy over an 8-month period. Finally, benefit-risk ratio of ChAdOx1 nCoV-19 vaccination was calculated as the ratio between preventable COVID-19 deaths and vaccine-related deaths, using Monte-Carlo simulations. We found that among subjects aged 20-29 years the benefit-risk [B-R] ratio was not clearly favorable (0.70; 95% Uncertainty Interval [UI]: 0.27-2.11). However, in the other age groups the benefits of vaccination largely exceeded the risks (for age 30-49, B-R ratio: 22.9: 95%UI: 10.1-186.4). For age 50-59, B-R ratio: 1577.1: 95%UI: 1176.9-2121.5). Although many countries have limited the use of the ChAdOx1 nCoV-19 vaccine, the benefits of using this vaccine clearly outweigh the risks in people older than 30 years. The use of this vaccine should be a strategic and fundamental part of the immunization campaign considering its safety and efficacy in preventing COVID-19 and its complications.

Use of estradiol benzoate to limit triplets in a low dose FSH model of twinning

Background: Estrogen could limit the nondominant follicles development after the first deviation by inhibition of the FSH secretion through the negative feedback loop, which ensure that the number of dominant follicles would be in a moderate level. Methods: The objective of the present study was to evaluate the effect of estradiol benzoate (EB) on inhibiting the development of nondominant follicles and inducing twin calves in beef heifers. Beef heifers were synchronized using an estradiol (E2)- plus- progesterone (P4)- based and superovulated using small dose follicle- stimulating hormone (FSH) protocol. From days 6.5 to 7.5 every heifer was treated with variety dose of estradiol benzoate (EB) for 3 times with 12 h intervals to eliminate the excess number of dominant follicles. Results: The diameters of the two largest follicles (F1 and F2) continually increased from day 3.5 to day 10. However, the growth rate was constrained by exogenous EB, and the degree of suppression was greatest in the 0.5 mg EB treatment compared with other treatments. As a result, the number of large follicles (≥ 10 mm) was also reduced along with the dose of EB increased. The double/triple ovulations rate, pregnancy rate and twin were all demonstrate the highest in 0.2 mg EB treatment group than in other treatments. Conclusions：The present study describes an efficient protocol that can be used to stimulate the development of a small number of dominant follicles i.e. 2-3 at the deviation stage through a FSH and 0.2 mg EB combine treatment, which can further result in the production of two calves. The appropriate dose of EB treatment during FSH induced superovulation procedure could limit the number of dominant follicles development and eventually increase the calf production efficiency.

Molecular organization of cytokinesis node predicts the constriction rate of the contractile ring

The molecular organization of cytokinesis proteins governs contractile ring function. We used single molecule localization microscopy in live cells to elucidate the molecular organization of cytokinesis proteins and relate it to the constriction rate of the contractile ring. Wild-type fission yeast cells assemble contractile rings by the coalescence of cortical proteins complexes called nodes whereas cells without Anillin/Mid1p (Δmid1) lack visible nodes yet assemble contractile rings competent for constriction from the looping of strands. We leveraged the Δmid1 contractile ring assembly mechanism to determine how two distinct molecular organizations, nodes versus strands, can yield functional contractile rings. Contrary to previous interpretations, nodes assemble in Δmid1 cells. Our results suggest that Myo2p heads condense upon interaction with actin filaments and an excess number of Myo2p heads bound to actin filaments hinders constriction thus reducing the constriction rate. Our work establishes a predictive correlation between the molecular organization of nodes and the behavior of the contractile ring.