Rice Production in Sri Lanka

Crop Production/Industries,

Economic and environmental impact of micro‐hydro‐ and biomass‐based electricity generation in the Sri Lanka tea plantation sector

The production process of tea is such that the industry's maximum power need coincides with the power system peak demand, thus consuming expensive energy. This industry is largely located in the Central, Sabaragamuwa and Uva provinces, where the topography coupled with heavy persistent rainfall offers a good opportunity to harness hydro‐power, the most widely used power source in the plantation sector, to meet the entire power requirement of the industry. This potential remains largely underutilised, as grid electricity supply is at present available in almost all tea estates, particularly at the factories where tea is processed. These plantations also practise cultivation and harvesting of fast‐growing tree species in abandoned tea‐growing land to meet the industry's thermal energy requirements. This biomass usage could also be extended to electricity generation, though realising the scope for this application in the Sri Lankan context is in an experimental stage. Widespread use of these two indigenous energy sources by the plantation industry can be expected to reduce the peak demand while making the cost of electricity in the sector less sensitive to external factors. Further, the use of micro‐hydro and biomass can contribute to the reduction of undesirable environmental impacts associated with electricity generation. The paper discusses a detailed estimation of the aggregate potential of biomass‐ and microhydro‐based energy supplies in the tea plantation sector. Also, its substitution effect on demand for electricity in the sector in terms of its economic impact both in the plantation sector and in the national energy scenario is examined

THE PREVALENCE OF HYPERTENSION, OBESITY, DIABETES AND JOB SATISFACTION AMONG PUBLIC HEALTH WORKERS IN CENTRAL PROVINCE, SRI LANKA

Aim of this study was to assess the prevalence of hypertension, obesity, overweight, diabetes and job satisfaction among public health workers in the Central province, Sri Lanka. This cross sectional study was conducted in three districts in the Central Province, Sri Lanka. Data were collected from public health workers (PHW) (n= 336). BMI, blood pressure and random blood sugar were measured. General information and self-reported job satisfaction and coping strategies were collected by a self-administered questionnaire. Mean age of PHW was 42.5 (SD 10.3, CI=95%). There were 302 females (89%) in the group. Prevalence of overweight and obesity among PHW were 29. 5% and 16.4% respectively. Among the group 26.4 % individuals (n=89) were hypertensive and 21 (6%) individuals were living with diabetes. 57.1% of individuals (n=192) reported with moderate pressure on their work. Extremely satisfied, very satisfied and moderately satisfied unsatisfied and not at all satisfied were 31.5%, 61%, 5.4 %, 1.2% and 0.6 respectively. Field work, work load, working environment, income were found to be as the common sources for stressful circumstances at work. Study revealed that overweight and obesity prevalence among public health workers in the Central Province is considerable. Significant amount of public health workers were hypertensive and living with diabetes. More than half from the group had a moderate satisfaction with their job.&nbsp

Performance of Random Routing on Grid-Based Sensor Networks

Abstract- Random routing protocols in sensor networks forward packets to randomly selected neighbors. These packets are agents carrying information about events, or queries seeking such information. We derive the probability of a packet visiting a given node in a given step as well as the rendezvous probability of agents and queries within a specific number of hops at a given node(s) in a 2-D grid-based sensor network. The utility of the model is demonstrated by determining the protocol parameters to optimize performance of rumor routing protocol under different constraints, e.g., to evaluate the number of queries and agents to maximize the probability of rendezvous for a given amount of energy. Monte Carlo simulations are used to validate the model. The closed form exact solution presented, unlike existing models relying on asymptotic behavior, is applicable to small and medium-scale networks as well. An upper bound is provided for the case where the packet is not sent back to its immediate forwarding node. Simulation results indicate that the model is a good approximation even for sparse arrays with 75 % of the nodes. The model can be used to set parameters and optimize performance of several classes of random routing protocols. Keywords-sensor networks, Wireless, Routing,Random routing I