DEVELOPMENT AND VALIDATION OF ANALYTICAL METHOD FOR IRBESARTAN AND ATORVASTATIN BY SIMULTANEOUS EQUTION SPECTROSCOPIC METHOD

A simple, accurate and precise spectroscopic method was developed for simultaneous estimation of Irbesartan and atorvastatin in synthetic mixture usingsimultaneous eqution Method.In this spectroscopic  method, 226.00 nm and 246.00 nm wavelengths  were selectedfor measurement of absorptivity. Both the drugs show linearity in a concentration range of 05-30 μg/ml at theirrespective λmax. Accuracy, precision and recovery studies were done by QC samplescovering lower, medium and high concentrations of the linearity range. The relative standard deviation for accuracy,precision studies were found to be within the acceptance range (<2%). The limit of determination was 0.033μg/ml and 0.125 μg/ml for Irbesartan and atorvastatin, respectively. The limit of quantification was 0.1008 μg/ml and 0.3792 μg/ml for Irbesartan and atorvastatin, respectively. Recovery of Irbesartan and atorvastatin were found to be 99.75 % and 99.52% respectively confirming the accuracy of the proposed method. The proposed method is recommended for routine analysis since they are rapid,simple, accurate and also sensitive and specific by no heating and no organic solvent extraction.Keywords: Irbesartan, atorvastatin, simultaneous estimation, Simultaneous equation method, analysis metho

MEDICINAL PLANTS AND PHYTOCHEMICALS IN PREVENTION AND MANAGEMENT OF LIFE STYLE DISORDERS: PHARMACOLOGICAL STUDIES AND CHALLENGES

The prevalence of lifestyle disorders such as hypertension, diabetes mellitus (DM), dyslipidemia, and overweight/obesity is rising rapidly. Recently the popularity of herbal supplements among patients with lifestyle disorders has been increasing. Consumption of a plant-based diet consisted of appropriate phytochemicals has been accepted as a reliable means for the prevention and management of several disorders. Phytochemicals play a crucial role in disease prevention, especially when lifestyle changes alone are not found effective. Various human and animal trials have established the pharmacological action of phytonutrients present in herbal plants. Several bioactive compounds such as polyphenols, flavonoids, alkaloids, and stilbenes. are present in plants such as garlic, Aloe vera, turmeric, tulsi, and drumstick. that have shown a significant beneficial effect on DM, metabolic syndrome, lipid disorders, etc. This review focuses on the therapeutic effect of some of the high potential herbal plants and their phytochemicals in the management of lifestyle disorders and the challenges with the use of herbal medicines

Test-Time Amendment with a Coarse Classifier for Fine-Grained Classification

We investigate the problem of reducing mistake severity for fine-grained classification. Fine-grained classification can be challenging, mainly due to the requirement of domain expertise for accurate annotation. However, humans are particularly adept at performing coarse classification as it requires relatively low levels of expertise. To this end, we present a novel approach for Post-Hoc Correction called Hierarchical Ensembles (HiE) that utilizes label hierarchy to improve the performance of fine-grained classification at test-time using the coarse-grained predictions. By only requiring the parents of leaf nodes, our method significantly reduces avg. mistake severity while improving top-1 accuracy on the iNaturalist-19 and tieredImageNet-H datasets, achieving a new state-of-the-art on both benchmarks. We also investigate the efficacy of our approach in the semi-supervised setting. Our approach brings notable gains in top-1 accuracy while significantly decreasing the severity of mistakes as training data decreases for the fine-grained classes. The simplicity and post-hoc nature of HiE renders it practical to be used with any off-the-shelf trained model to improve its predictions further.Comment: 8 pages, 2 figures, 3 tables, Accepted at NeurIPS 202

Pattern and management of penetrating and nonpenetrating thoracic injuries

Background: Chest trauma constitutes a major public health problem which  includes the injuries to chest wall, pleura, tracheobronchial tree, lungs, diaphragm, oesophagus, heart and great vessels. It consist of more than ten percent of all traumas and twenty five percent of death due to trauma occurs because of chest injury. Chest trauma is increasing in frequency in urban hospitals. Penetrating and nonpenetrating thoracic injuries the most serious injuries leading to significant morbidity and mortality.Methods: This study was prospective observational study of 220 patients of thoracic trauma both penetrating and non-penetrating. These patients admitted in general surgical units from August 2017 to May 2018  of Pandit Bhagwat Dayal  Sharma,  PGIMS  Rohtak Haryana India. The study was pertaining to both penetrating  and non-penetrating chest trauma.Results: Out of 220 chest injury patients who were studied during the said period, Males were 203 and females 17 by a ratio of 12:1 and age ranged from lowest 18 years to 85 years of age. Majority of the patients (90.45%) sustained blunt injuries. RTA was the common mechanism of blunt injury affecting (50.45%) of patients. Multiple Rib fractures was the commonest type of chest injury (21.36%) followed by head injury (17.27%). Head injury was the commonest associated injury seen in our patients. Conclusions: Chest trauma resulting from road traffic accident remains a major mechanism of chest injury. The  measures to decrease the trauma are, educating people about traffic rules and regulations and strictly implementing them is necessary to reduce incidence of chest injuries

Business Plan – RichWorth Uniforms & Research Report

Executive Summary: India Textile Industry is one of the leading textile industries in the world. The opening up of economy gave the much-needed thrust to the Indian textile industry, which has now successfully become one of the largest in the world. The apparel industry constitutes of about 50% of the Indian textile and apparel industry. Further, the textile industry of India also contributes nearly 14% of the total industrial production of the country. It also contributes around 3% to the GDP of the country. Reports state that Asia holds a massive 43% of the world's workwear volume, for instance. The overall market is expected to rise by 8.1% between 2005 and 2012, with Asia representing a gigantic 60% of the world growth of which India has a major share of about 20% and Latin America accounting for a substantial 45%. (Ministry of Textiles, http://texmin.nic.in/). There is a clear disequilibrium in the corporate wear and workwear market in India which has been shown through reports and market analysis. The market is flooded with unorganized players but the buyers are dissatisfied due to leg in delivery time and poor quality issues. We aim to exploit this opportunity to start an organized venture with an efficient supply chain and an innovative offering called Total Uniform Solutions (TUS) which gives a total solution for uniforms requirements right from designing to delivery with a dedicated account manager and style consultants. The initial market to be tapped will be Chennai and South India in the first 5 years and then gradually capture the market in the North and also abroad. This company is a family business with the founder owner having a rich experience in the textiles and garments business. He had started a public limited company dealing in textiles, a manufacturing unit for garments export and men’s garment retail. He has two sons. The elder son heads the retail wing. The younger son will be joining to head the Uniforms wing. Both the sons have pursued education from the United Kingdom; the elder in textile technology and management and the younger in Business Administration. Therefore, it is a good mix of experience and education in this company. Therefore, the aim of this report is to create an efficient business model to integrate the uniforms wing into the existing family business and try capturing and increasing the market share year on year with effective management of finance. Following the business plan is a research report to present a literature review about the entrepreneurial opportunity found in the business plan and a few questions are attempted to be answered that arise out of the opportunity identified

Correlation between abscess size and liver function tests in cases of liver abscess

Background: Liver abscess has shown a major change in demographics, etiology, diagnosis, and treatment over the past 100 years. The modern diagnostics like ultrasound and computed tomography to locate and drain the abscess have reduced the mortality to 2-12%. However, due to the complications of liver abscess especially the amebic ones the morbidity is still high. This study aims to study the correlation of various LFT parameters with abscess volume for early detection of high risk patients and early treatment thus reducing morbidity.Methods: The study was conducted over a period of 6 months on 50 patients of liver abscess. History and physical examination was done. All patients were subjected to complete hemogram, liver function test, coagulation profile (PT/INR) and USG abdomen. The data was recorded and compiled in excel sheets and analyzed using correlation coefficient (R) method.Results: The mean age of the patients was 41.2 years with male preponderance. Amoebic liver abscess (88%) was predominant over pyogenic liver abscess (12%). Alcoholism (48%), smoking (42%) and diabetes mellitus (18%) are main predisposing factors in case of liver abscess. Hepatomegaly was found in 88% cases. Elevated ALP, low albumin, increased PT INR points to the diagnosis of liver abscess. Complications seen were pleural effusion (10%) and ascites (4%). On analysis, liver abscess size is significantly positively correlated with INR, ALP, liver enzymes, and negatively correlated with serum albumin level.Conclusions: Liver abscess size was found to be positively correlated with INR and alkaline phosphatase (ALP), liver enzymes (SGOT, SGPT) and negatively correlated with serum albumin levels. There was no correlation of abscess size and bilirubin levels. Hence, LFT can be used to estimate the liver abscess size and predict the severity and prognosis of patient

SIMULTANEOUS ESTIMATION OF IRBESARTAN AND ATORVASTATIN BY Q ABSORPTION RATIO METHOD IN THEIR SYNTHETIC MIXTURE USE IN CARDIAC CONDITION

A simple, accurate and precise spectroscopic method was developed for simultaneous estimation of Irbesartan and atorvastatin in synthetic mixture using Q absorption Ratio Method. In this spectroscopic  method, 234.7 nm (as an iso-absorptive point) and 226 nm wavelengths (λmax of any of the two drugs) were selected for measurement of absorptivity. Both the drugs show linearity in a concentration range of 05-30 μg/ml at their respective λmax and at the isoabsorptive point. Accuracy, precision and recovery studies were done by QC samples covering lower, medium and high concentrations of the linearity range. The relative standard deviation for accuracy, precision studies were found to be within the acceptance range (<2%). The limit of determination was 0.365μg/ml and 0.0622μg/ml for Irbesartan and atorvastatin, respectively. The limit of quantification was 1.108μg/ml and 0.188μg/ml for Irbesartan and atorvastatin, respectively. Recovery of Irbesartan and atorvastatin were found to be 100.51% and 100.16% respectively confirming the accuracy of the proposed method. The proposed method is recommended for routine analysis since they are rapid, simple, accurate and also sensitive and specific by no heating and no organic solvent extraction

On Diffusion Modeling for Anomaly Detection

Known for their impressive performance in generative modeling, diffusion models are attractive candidates for density-based anomaly detection. This paper investigates different variations of diffusion modeling for unsupervised and semi-supervised anomaly detection. In particular, we find that Denoising Diffusion Probability Models (DDPM) are performant on anomaly detection benchmarks yet computationally expensive. By simplifying DDPM in application to anomaly detection, we are naturally led to an alternative approach called Diffusion Time Probabilistic Model (DTPM). DTPM estimates the posterior distribution over diffusion time for a given input, enabling the identification of anomalies due to their higher posterior density at larger timesteps. We derive an analytical form for this posterior density and leverage a deep neural network to improve inference efficiency. Through empirical evaluations on the ADBench benchmark, we demonstrate that all diffusion-based anomaly detection methods perform competitively. Notably, DTPM achieves orders of magnitude faster inference time than DDPM, while outperforming it on this benchmark. These results establish diffusion-based anomaly detection as an interpretable and scalable alternative to traditional methods and recent deep-learning techniques