Evaluation of black carbon emission inventories using a Lagrangian dispersion model - a case study over southern India

We evaluated three emission inventories of black carbon (BC) using Lagrangian particle dispersion model simulations and BC observations from a rural site in southern India (Gadanki; 13.48 degrees N, 79.18 degrees E) from 2008 to 2012. We found that 93 to 95% of the BC load at the observation site originated from emissions in India and the rest from the neighbouring countries and shipping. A substantial fraction (33 to 43%) of the BC was transported from northern India. Wet deposition is found to play a minor role in reducing BC mass at the site because of its proximity to BC sources during rainy season and relatively short rainy season over western and northern parts of India. Seasonally, the highest BC concentration (approx. 3.3 ug m^-3) is observed during winter, followed by spring (approx. 2.8 ug m^-3). While the model reproduced well the seasonal cycle, the modelled BC concentrations are significantly lower than observed values, especially in spring. The model bias is correlated to fire radiative power - a proxy of open biomass burning activity. Using potential emission sensitivity maps derived using the model, we suggest that underestimation of BC mass in the model during spring is due to the underestimation of BC fluxes over southern India (possibly from open-biomass-burning/forest-fires). The overall performance of the model simulations using three different emission inventories (SAFAR-India, ECLIPSE and RETRO) is similar, with ECLIPSE and SAFAR-India performing marginally better as both have about 30% higher emissions for India than RETRO. The ratio of observed to modelled annual mean BC conentration was estimated as 1.5 for SAFAR, 1.7 for ECLIPSE and 2.4 for RETRO

Economic Impact of Custom Hiring Service Centres in Maize Cultivation: A Case Study from Karnataka

In order to overcome the problem of acute labour scarcity, Government of Karnataka in collaboration with Shri Kshetra Dharmastala Rural Development Project has established custom hiring service centres (CHSCs) on public private partnership mode in the year 2014 to provide services of machines and implements to farming community at affordable rates. The study has been conducted to examine the economic performance of the centre and economic benefits accrued to maize farmers of Shimoga district, representative of Malnad region of Karnataka in terms of reduced cost of cultivation, increased productivity, increased profit and reduced drudgery. The results indicated that maize farmers reaped additional profit of Rs. 5554.39 (24 percent) and saved cost of Rs. 2928.46 (15.71 percent) per acre by availing machines from CHSCs compared to private individual farmers. The reduced dependence on human labour was to the tune of 16.29 percent and increased yield observed was about 4.90 per cent compared to those farms who have availed services from private individual farmers. The economic performance of selected CHSC in terms of net returns over total cost was negative. The negative performance was due to the magnitude of dead investment made by the centre in terms of erroneous selection of non-location specific machineries and implements. Though, the performance of these centres was not satisfactory but by looking at the magnitude of economic gains realised by the farmers, Government of Karnataka should think of proliferating the number of centres with a caution of minimising dead investment through proper choice of implements and machineries

A Young Lady with a Swelling over the Back: A Rare Case of Tuberculosis

Musculoskeletal tuberculosis accounts for 1-2% of all types of tuberculosis. Tubercular abscess of the chest wall accounts for 1-5% of all cases of musculoskeletal tuberculosis. Herein, we report a case of tubercular abscess of the chest wall. The occurrence of caries rib and cold abscess of the chest wall with concomitant pulmonary tuberculosis, and tubercular lymphadenitis of neck and mediastinum has rarely been described in an immunocompetent individual. The rarity of our case lies in the fact that the patient was immunocompetent with cold abscess due to caries rib, with rare association of pulmonary tuberculosis and tubercular lymphadenitis of neck and mediastinum

Economic Utilisation of Areca Leaf Sheaths for Rural Livelihood

The enormous supply of areca leaf sheaths coupled with raising consciousness among society towards usage of eco-friendly products have paved a way for emergence of rural based areca leaf product manufacturing units. Areca growers reaped net profit of Rs.7120 per acre by selling leaf sheaths to manufacturing units. The industry has generated employment ranging from 2 labourers in very small units to 242 labourers in very large units per unit per annum depending upon the size of the industry. The manufacturers reaped net returns ranging from 0.65 lakh in very small units to 121.9 lakhs in very large units. The capital budgeting analysis indicated wealth generation of Rs. 0.72 lakhs in very small units and Rs. 59.09 crores in very large units with the annual rate of return of 17 and 88 per cent, respectively, indicating economic worthwhileness of areca leaf products manufacturing units. It is noteworthy that very large units repaid the initial investment in 0.13 years while others took more than one year. The data envelopment analysis indicated that very small, small and very large units were found to be cost inefficient with efficiency scoring of 0.5, 0.79 and 0.72, respectively. It was evident from the conjoint analysis that the consumer preference was influenced by quality parameters like desired dimensions, portability, ecofriendly nature and price of leaf products. There exists vast scope for development of this vital industry with potential supply of raw materials at 144 crore leaf sheaths produced in the state per annum. Hence, it is suggested that Government should encourage such agro based rural industries for development of rural economy

Application of machine learning methods for diagnosis of dementia based on the 10/66 battery of cognitive function tests in South India

Background: There is limited data on the use of Machine learning methods for automating clinical aspects of dementia in low and middle income country (LMIC) settings including India. A culture and education fair battery of cognitive tests was developed, validated and normed for use in LMICs including south India by the 10/66 Dementia Research Group. We explored the machine learning algorithms to determine if the analysis of neuropsychological data from the 10/66 battery of cognitive tests can be automated for the diagnosis of dementia in south India.Methods: The data sets for 466 men and women aged 55- 80 yrs were obtained from the on-going Mysore Studies of Natal effect of Health and Ageing (MYNAH), in south India. This includes subject demographics, performance on the 10/66 cognitive function tests, diagnosis of mental disorders and population based normative data for the 10/66 battery of cognitive function tests. We examined the diagnostic properties of the battery of cognitive tests and derived an equation to enhance the accuracy of diagnosis of dementia. Machine learning techniques were applied to the data set. Results: Of 466 subjects, 27 had 10/66 diagnosis dementia. 19 of them were correctly identified as having dementia by Jrip classification with 100% accuracy. Conclusions: This pilot exploratory study indicates that machine learning methods can help to identify community dwelling older adults with 10/66 criterion diagnosis of dementia with good accuracy in a LMIC setting like India. This should reduce the duration of the diagnostic assessment and make the process easier and quicker for both the clinicians and patients