The Adoption and Use of National Information Infrastructure: A Social Network and Stakeholder Perspective

This study draws upon stakeholder theory and social network analysis to examine the diffusion of national information infrastructure (NII) among two key stakeholders—the end users (or customers) and application/ service providers. The context chosen is Singapore ONE. The study also investigates the types of mechanisms utilized by network participants for resolving their concerns with respect to NII adoption

Mixture and Non-Mixture Bayesian Hierarchical Study of Seizure Count Data Using New Generalized Poisson Model

In this paper Bayesian methods is performed on a medical trial Seizure count data set by introducing the new three parameter generalized Poisson model GPM(α,β,l) as an alternative model to the standard Poisson model SPM(l) which is considered on an earlier work for the generalized linear mixed model. The new model is developed by introducing two more parameters α and β called indicator parameters. The main advantage of an indicator parameter is that it gives the new Poisson model the mixture (when α>0,β=1,2) and non-mixture (when α=0) options. Another feature of proposed new model is that it generalize the posterior of the parameters to predict the behavior of the Seizure counts data, in agreement with generalized linear mixed model. Unlike earlier authors, who confined and limited their work only on standard Poisson model SPM(l), to analyze the counts data in generalized linear mixed model, which make the new model more resilience and litheness. The parameters of the new model will be estimated using Bayesian approach that serves as a subtle tool for model selection and identification. An illustration is provided using the Seizure count data. The posterior summaries using Markov Chain Monte Carlo (MCMC) Gibbs sampling approach are presented for the new model for different values of the parameters. The study of the estimated parameters would help the users to have more prospect and clarity about the role of the new model. It is found that using proposed new model in generalized linear mixed model has more resiliency than standard Poisson model considered earlier. The proposed model is fully adaptive to the available data and gives scientists another option for modeling the data

IMPLEMENTATION OF QUALITY BY DESIGN (QBD) APPROACH IN FORMULATION AND DEVELOPMENT OF RITONAVIR PELLETS USING EXTRUSION SPHERONIZATION METHOD

Objective: Ritonavir is an antiretroviral drug used for HIV-AIDS treatment. The purpose of this research work was to implement the quality by design (QbD) approach in formulation of ritonavir sustained-release pellets by industrially applied extrusion spheronization technique. Methods: Pellets were prepared by extrusion spheronization method and evaluated for their physicochemical properties. Initially, on the basis of prior knowledge Quality Target Product Profile (QTTP) element was identified and further Critical Quality Attributes (CQA) elements were defined. Risk assessment (RA) was done by two tools as failure mode and effect analysis (FMEA) and fishbone diagram (Ishikawa plot). Placket Burman design was implemented as a screening design using seven high-risk factors (spheronization speed, spheronization time, extrusion speed, drying method, PVP K 30, cross povidone, and solvent). Optimization study was done by 23 full factorial design with three critical factors as (spheronization speed, extrusion speed and PVP K 30). The in vitro drug release was studied in both gastric and intestinal fluids for 12 h using USP Ι apparatus. Control space was established for the sustained release pellets. Results: Among all batches obtained in 23 full factorial design, batch R7 was found to be effective with carr’s index value of 5.281, percentage yield of 69.6%, time required to release 50% drug was 8 h and percent drug release after 12 h was found 83.132 %, R7 batch was selected as optimized batch. Statistical analysis showed model terms were significant. Conclusion: We can conclude that; sustained-release pellets of ritonavir were successfully designed using QbD approach

tert-Butyl N-{2-[bis­(prop-2-yn-1-yl)amino]­phen­yl}carbamate

In the crystal of the title compound, C17H20N2O2, the molecules are linked by C—H⋯O interactions. Intra­molecular C—H⋯O and N—H⋯N hydrogen bonds also occur

Antihypertensive and Antioxidant Action of Amlodipine and Vitamin C in Patients of Essential Hypertension

The etiology of essential hypertension includes increased oxidative stress. The role of antihypertensive drug amlodipine as an antioxidant and the benefit of addition of vitamin C, an antioxidant to antihypertensive therapy were studied. Forty male patients of essential hypertension were randomly divided into two groups and treated with 5 mg amlodipine. In addition one group also received 1000 mg vitamin C (as two 500 mg tablets) once daily for three months. Although blood pressure decreased in both groups, the systolic blood pressure in patients given vitamin C was less (126.4 ± 7.47) compared to the other group (130.9 ± 7.27). A decrease in malondialdehyde, an increase in erythrocyte sodium-potassium adenosine triphosphatase (Na+ K+ ATPase) and an increase in the superoxide dismutase levels were observed in both groups. The increase in SOD was statistically more in the patients given vitamin C in addition to amlodipine (0.1717 ± 0.0150 compared to 0.152 ± 0.0219 units/100 ml assay). In spite of the known antihypertensive, antioxidant activity, similarity in correcting endothelial dysfunction independently, giving the two drugs together and early introduction of vitamin C perhaps decreases oxidative stress and augments the antioxidant status. This may prevent further vascular damage due to oxidative stress, leading to a better prognosis in essential hypertension patients

Reliability Prediction Updating Through Computational Bayesian for Mixed and Non-mixed Lifetime Data Using More Flexible New Extra Modified Weibull Model

A new lifetime reliability model with four parameters is proposed. We call it the extra modified Weibull model (EMWM), which is an extension of the modified Weibull model (MWM), capable of modeling a different shapes of hazard function. The new model is developed by introducing fourth parameter in MWM called indicator parameter. The main advantage of an indicator (fourth) parameter is that it gives the new model mixture and non-mixture options, besides different shapes of hazard function including bathtub. The model parameters can be estimated based on a Bayesian generalized posterior method that serves as a tool for model identification, and it gives an efficient computational updating approach with new ways of predicting and measuring behavior. To have insight of the new indicator parameter and to see its importance, we have considered three data sets [Murthy et al [1], Badar and Priest [2], and  Aarset [3]) which have been studied in the past. A prediction updating of the earlier studies of the data sets through the generalized posterior summaries using Markov Chain Monte Carlo (MCMC) Gibbs sampling approach are presented for the proposed model for the different parameters. The behavior of the parameters would help the users to have more clarity about the role of the indicator parameter, and hence may be useful for certain sets of data. The proposed model is fully adaptive to the available failure data and gives reliability engineers and scientists another option for modeling the life time data. We provide description of the mathematical properties of the new model along with failure rate function

Dilemmas and Perceptionsregarding Medical Education in Hindi medium among Medical Community of Northern India: A Cross Sectional study

Introduction: The medical curriculum, the medium of instruction and evaluation in India, is primarily English. While it has the advantage of preparing Indian medical graduates to represent and interact globally, it also translates into learning difficulties for a substantial population of Indian medical students. Hindi is the common language of communication among majority of the population in Uttar Pradesh.Madhya Pradesh Government in India has already started the option of pursuing the allopathic graduate medical course in Hindi. There is paucity of data regarding opinion of medical professionals about implementation of Medical Education in Hindi in Uttar Pradesh and nearby states.Objective: To assess the attitude and opinion of medical students and medical professionals towards using Hindi in Medical Education. Method: A cross-sectional web-based online survey was conducted between 1st December 2022 and 31st January 2023. Undergraduate medical students, interns, residents and faculty from medical colleges, hospitals of Uttar Pradesh and neighbouring states (Uttarakhand and Bihar) were contacted to participate in this survey using pretested structured questionnaire. Results: A total of 1606 participants responded and answered the questionnaire and 1575 responses were found complete and used in analysis.Most participants (52.8%) believed that Medical Education in Hindi would attract more students from Hindi backgrounds to join the medical field. Similarly, 58.9% of participants were of the opinion that Medical Education in Hindi would improve patient communication skills. However, about half of the participants (49.5%) perceived teaching in Hindi as a hurdle in acquiring higher education. Conclusion: More than half of the participants thought that medical education in Hindi will attract more students from Hindi backgrounds to join the medical field. Similarly, Medical Education in Hindi was perceived to improve communication skills with patients, at least where Hindi is a vernacular language by majority of the participants

Identification of Hemorrhage and Infarct Lesions on Brain CT Images using Deep Learning

Head Non-contrast computed tomography (NCCT) scan remain the preferred primary imaging modality due to their widespread availability and speed. However, the current standard for manual annotations of abnormal brain tissue on head NCCT scans involves significant disadvantages like lack of cutoff standardization and degeneration identification. The recent advancement of deep learning-based computer-aided diagnostic (CAD) models in the multidisciplinary domain has created vast opportunities in neurological medical imaging. Significant literature has been published earlier in the automated identification of brain tissue on different imaging modalities. However, determining Intracranial hemorrhage (ICH) and infarct can be challenging due to image texture, volume size, and scan quality variability. This retrospective validation study evaluated a DL-based algorithm identifying ICH and infarct from head-NCCT scans. The head-NCCT scans dataset was collected consecutively from multiple diagnostic imaging centers across India. The study exhibits the potential and limitations of such DL-based software for introduction in routine workflow in extensive healthcare facilities