Assessment of energy, exergy, environmental, and economic study of an evacuated tube solar dryer for drying Krishna Tulsi.

In the present work, experimental studies of drying Krishna tulsi leaves in an in-house fabricated evacuated tube solar collector (ETSC) connected with an indirect solar dryer are carried out. The acquired findings are compared to those obtained from drying the leaves in open sun drying (OSD). The developed dryer takes 8 h to dry Krishna tulsi leaves; it takes 22 h in the OSD to reach a final moisture content of 12% (db) from an initial moisture content of 47.26% (db). The collector and dryer efficiencies range from 42 to 75%, 0-18%, respectively, with an average solar radiation of 720 ± 20 W/m2. The ETSC and drying chamber exergy inflow and outflow vary from 200 to 1400 W, 0 to 60 W, and from 0 to 50 W,  0 to 14 W, respectively. The ETSC and cabinet exergetic efficiencies range from 0.6-4% and 2-85%, respectively. The exergetic loss of the overall drying process is estimated to be 0-40%. The drying system sustainability indices, including improvement potential (IP), sustainability index (SI), and waste exergy ratio (WER), are calculated and presented. The value of the embodied energy of the fabricated dryer is 349.874 kWh. For an expected life span of 20 years, the dryer will reduce CO2 by 13.2 tonnes and earn carbon credits worth between 10,894 and 43,576 INR. The proposed dryer has a payback period of 0.4 years.

ADL-CDF: A Deep Learning Framework for COVID-19 Detection from CT Scans Towards an Automated Clinical Decision Support System.

The emergence of deep learning has paved to solve many problems in the real world. COVID-19 pandemic, since the late 2019, has been affecting lives of people across the globe. Chest CT scan images are used to detect it and know its severity in patients. The problem with many existing solutions in COVID-19 detection using CT scan images is that inability to detect the infection when it is in initial stages. As the infection can exist on varied scales, there is need for more comprehensive approach that can ascertain the disease at all scales. Towards this end, we proposed a deep learning-based framework known as Automated Deep Learning-based COVID-19 Detection Framework (ADL-CDF). It does not need a human medical expert in diagnosis as it is capable of detecting automatically. The framework is assisted by two algorithms that involve image processing and deep learning. The first algorithm known as Region of Interest (ROI)-based Image Filtering (ROI-IF) which analyses given input CT scan images of a patient and discards the ones where ROI is missing. This algorithm minimizes time taken for processing besides reducing false positive rate. The second algorithm is known as Multi-Scale Feature Selection algorithm that fits into the deep learning framework's pipeline to leverage detection performance of the ADL-CDF. The proposed framework is evaluated against ResNet50V2 and Xception. Our empirical study revealed that our model outperforms the state of the art.

Effect of end-stage renal disease on oral health in patients undergoing renal dialysis: A cross-sectional study.

AIMS AND OBJECTIVES: To evaluate the effect of chronic renal failure on oral health in renal dialysis patients. To assess and improvise awareness of staff regarding oral health care of the patients in hemodialysis unit. MATERIALS AND METHODS: A cross-sectional questionnaire survey and oral health examination study were conducted on 206 end-stage chronic renal failure patients (stage V) who were undergoing renal dialysis in Guntur city. The study included the questionnaire form and modified WHO proforma to record their oral health status. Oral examination was done in American Dental Association (ADA) type III method by using mouth mirror and community periodontal index (CPI) probe. Questionnaire survey was conducted among the nursing staff in the hemodialysis unit. RESULTS: Mean age of the study subjects was 46.79 ± 12.78 years; 81.1% were males and 18.9% were females. Candidiasis (8.3%) was the most frequently seen oral mucosal condition in these subjects. Majority of the subjects (44.2%) showed periodontal diseases (CPI score 3: Pocket depth of 4-5 mm). Caries prevalence of 56.3% was seen in this study group. Higher incidence of hepatitis C was significantly associated with higher duration of dialysis. There was very little awareness among the nursing staff regarding dental care. CONCLUSION: There is greater deterioration of periodontal health among dialysis patients with chronic renal disease. Awareness regarding dental care is very less among patients undergoing renal dialysis. These patients should be monitored carefully to maintain their oral health. Awareness must be increased among dialysis patients and nursing staff about the need for primary prevention of dental diseases.

The metabolic syndrome and associated risk factors in an urban industrial male population in South India.

BACKGROUND: The metabolic syndrome is characterized by clustering of risk factors, which predisposes subjects to increased risk of diabetes and cardiovascular disease. Objectives of this study were to estimate prevalence of the metabolic syndrome and determine the association of risk factors with the metabolic syndrome in an urban industrial male population in Chennai, India. METHODS: We conducted a cross-sectional survey for male employees working in an industrial unit. The survey included questionnaire for risk factors, anthropometric and blood pressure measurements. Blood samples were collected for the fasting plasma glucose, serum cholesterol, high-density lipoprotein cholesterol and triglycerides. The metabolic syndrome was defined using International Diabetes Federation (IDF) and American Heart Association (AHA)/National Heart Lung and Blood Institute (NHLBI) criteria. RESULTS: The total numbers of male subjects included in the study were 1077. The prevalence of the metabolic syndrome was 41.3% and 51.4% using IDF and AHA/NHLBI criteria respectively. Risk factors were age above 35 years, family history of diabetes and body mass index (BMI) above 23.9 kg/m2. The consumption of more than three servings of fruits and vegetables was protective. CONCLUSION: The prevalence of the metabolic syndrome was very high in select industrial population in south India. Higher BMI and low intake of fruits and vegetables are modifiable by life style modification. Work site screening for the metabolic syndrome would facilitate the early detection and treatment.

A comparison of anthropometric indices for predicting hypertension and type 2 diabetes in a male industrial population of Chennai, South India.

OBJECTIVES: To assess the association of four obesity-related indices--body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-stature ratio (WSR)--with hypertension and type 2 diabetes among a male industrial population in south India. DESIGN, SETTING, AND PARTICIPANTS: A cross sectional study of 2148 men aged 18-69 years in two purposely selected industrial units in Chennai, India, in 2003-2005. MAIN OUTCOME MEASURES: The examination included blood pressure and anthropometric measurements (height, weight, hip circumference, and WC) to calculate BMI, WHR, and WSR. Fasting blood samples were taken to assess plasma glucose. RESULTS: Prevalence of overweight was 43.4%; prevalences of central obesity using WC > or = 90.0 cm and WHR > 0.90 were 50.0% and 70%, respectively. The prevalences of hypertension and type 2 diabetes were 26.5% and 16.3%, respectively. There was a significant increase in the prevalence of type 2 diabetes and hypertension across the quintiles for the four anthropometric indices. In logistic regression analysis, BMI and WC showed a significant graded increase in the odds ratio for hypertension after adjusting for age. In case of type 2 diabetes, only WHR showed significant increase in odds ratio across quintiles after adjusting for age and BMI. CONCLUSIONS: WHR was the best predictor for type 2 diabetes in the study sample. BMI and WC were good predictors for hypertension. We recommend that WHR should be routinely used in this clinical setting in addition to BMI to detect persons at high risk in these industrial units. Prospective studies are needed to provide evidence of the predictive power of anthropometric indices for Asian Indians.

Antiphospholipid antibodies in blood and cerebrospinal fluids of patients with psychosis.

Antiphospholipid antibodies (aPL) have been reported in the cerebrospinal fluids (CSF) of neurology patients but no CSF studies with psychiatric patients exist. We tested serum from 100 hospitalized psychotic patients having hallucinations and/or delusions for aPL. Patients with positive serum aPL findings were asked to submit CSF for aPL testing. Five CSF samples had aPL specificities not found in the patient's serum suggesting the possibility of intrathecal synthesis. Specificity and isotype discordance between CSF and blood aPL in these psychiatric patients implicates a central nervous system independent autoimmune process that may have an underlying association with the pathophysiology of their diseases.

Assessment of groundwater quality in a structurally deformed granitic terrain in Hyderabad, India.

Geochemical study of groundwater from a structurally deformed granitic terrain near Hyderabad (India) was carried out to understand and evaluate the hydrogeochemical processes and quality of groundwater. Several trace elements (Fe, Mn, Be, Al, V, Cr, Co, Ni, Cu, Zn, As, Sr, Mo, Cd, Sb, Ba, Pb, U) along with major ions and minor elements were precisely estimated in shallow and drilled wells to know the suitability of water for drinking and irrigation purposes. Analytical data shows that pH and major ion chemistry in dug wells and bore wells do not vary significantly, while some trace elements (Fe, Mn, Al, Be, Co, Pb, U and Zn) vary in dug wells and bore wells, which can be attributed to differential mineral weathering and dissolution/precipitation reactions along fractures/joints. Although the water is not potable, it was found to be suitable for irrigation with little danger in the development of harmful level of exchangeable sodium. It is inferred that the chemical composition of the groundwater in this region is likely to have its origin from silicate weathering reactions and dissolution/precipitation processes supported by rainfall and groundwater flow.