Analysis of selected maternal factors for development trends in Sainthamaruthu moh division

Prevalence of low birth weight (LBW) in Sri Lanka is 22 % and in the Ampara district it is 15.8%. It is believed the Sainthamaruthu Medical Officer of Health (MOH) division which is a suburban area in the Ampara district has improved maternal health facilities and this should have different statistics. In this descriptive research study, all the pregnant women who delivered babies in 2015 in Sainthamaruthu MOH area were studied for the selected maternal factors and this statistics were comparedfor development trend with2009. The associated maternal factors related to LBW were also studied. The study results revealed that theprevalence of LBW was 12.65% which is significantly less than the district statistics (p = 0.032). The mean birth weight was 2997.47 g. The initial weight of the pregnant mothers was significantly associated with LBW (p = 0.0073). The relative risk of delivering LBW babies in 2015 compare to that of 2009 was between 0.866 to 1.969 (OR=1.3059, 95% CI: 0.866, 1.969). Therefore no improvement has occurred which is not a good contribution to the millennium development goal and therefore it is recommended to identify the high risk mothers early during their pregnancy time to provide special prenatal car

A Solution for the problems caused by Eichornia crassipes in the Ampara District

Eichornia crassipes (Japan Jabara/Japan Japarli/Aathu Valai/Water hyacinth) is a nonnative invasive freshwater plant to Sri Lanka, which blocks the drainage and irrigation cannels. During heavy rainy season Eichornia crassipes plants block the flow of rivers and by spreading over the paddy fields cause floods frequently, destroy the aesthetic value of the water bodies and obstructs the fishing activities. Due to very rapid growth and spread rate, farmers and local authorities need to spent significant amount of money to remove these plants and need large dumping areas for disposing of these plants. A study was conducted to prepare compost using Eichornia crassipes as the main resource material along with paddy straw and cow dung. Multiple layers of these materials were mixed at 3rd and 6th weeks and the moisture content was maintained at 50 - 60%. In the 10th week, compost was ready and it was sieved. The return percentage of compost from the input was 65. The moisture percentage of the produced compost was 50.3 and the volatile solid percentage was 22.8. The compost contained 39.5 % carbon, the pH was 8.1 and 73.5 % of the produced compost was sieved through 4 mm sieve. The total production cost was Rs 4.40 kg-I and it had very good demand and the selling price was Rs. 13.00 kg-

Neurobehavioral Mechanisms of Temporal Processing Deficits in Parkinson's Disease

Parkinson's disease (PD) disrupts temporal processing, but the neuronal sources of deficits and their response to dopamine (DA) therapy are not understood. Though the striatum and DA transmission are thought to be essential for timekeeping, potential working memory (WM) and executive problems could also disrupt timing.The present study addressed these issues by testing controls and PD volunteers 'on' and 'off' DA therapy as they underwent fMRI while performing a time-perception task. To distinguish systems associated with abnormalities in temporal and non-temporal processes, we separated brain activity during encoding and decision-making phases of a trial. Whereas both phases involved timekeeping, the encoding and decision phases emphasized WM and executive processes, respectively. The methods enabled exploration of both the amplitude and temporal dynamics of neural activity. First, we found that time-perception deficits were associated with striatal, cortical, and cerebellar dysfunction. Unlike studies of timed movement, our results could not be attributed to traditional roles of the striatum and cerebellum in movement. Second, for the first time we identified temporal and non-temporal sources of impaired time perception. Striatal dysfunction was found during both phases consistent with its role in timekeeping. Activation was also abnormal in a WM network (middle-frontal and parietal cortex, lateral cerebellum) during encoding and a network that modulates executive and memory functions (parahippocampus, posterior cingulate) during decision making. Third, hypoactivation typified neuronal dysfunction in PD, but was sometimes characterized by abnormal temporal dynamics (e.g., lagged, prolonged) that were not due to longer response times. Finally, DA therapy did not alleviate timing deficits.Our findings indicate that impaired timing in PD arises from nigrostriatal and mesocortical dysfunction in systems that mediate temporal and non-temporal control-processes. However, time perception impairments were not improved by DA treatment, likely due to inadequate restoration of neuronal activity and perhaps corticostriatal effective-connectivity

Semi-elliptical exponentially weighted moving average scheme for jointly monitoring mean and variance of Gaussian processes

Shewhart, cumulative sum and exponentially weighted moving average control charts were introduced for monitoring process mean. These charts were subsequently used for monitoring process variance. Later, it was realized that process monitoring is a bivariate problem and several joint monitoring scheme for process mean and variance were introduced by many authors. The challenge in the advanced joint monitoring scheme is that it should be sensitive for both small and larger changes either in process mean, variance or both. In this thesis, a new advanced joint monitoring scheme for process mean and variance called semi-elliptical exponentially weighted moving average scheme is proposed for Gaussian processes with its design procedure for the industry. The performance of this new scheme is compared with the joint monitoring schemes suggested by other authors using a new comparison index proposed in this thesis. Application of this new scheme is tested with real and simulated data sets. Most frequently, this new scheme detected various magnitudes ofshifts in mean and variance quicker than any other schemes. In overall, the new scheme developed in this study performs better than the existing schemes with some limitations when the shift in mean, variance or both is large. A big advantage ofthis new scheme is, the design parameters are independent ofsample size. As this scheme use the standardized mean and variance, this scheme can be used to monitor several parameters at a time in a single display. Unlike most ofthe joint monitoring scheme, this new scheme takes the drop in variance as the desirable state when the mean is on target. Therefore this scheme can be recommended for advanced joint monitoring of process mean and variance. The new methodology is very useful for many industrial applications. Furthermore improvements are suggested on this scheme to monitor multi quality parameters simultaneously

Design of exponentially weighted moving average chart for monitoring standardized process variance

Control charts for monitoring of process variance are developed based on Shewhart, exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) control charts for mean. In all these variance control charts, log transformation of the sample variance is used. The design procedure of this chart is complex and it is poorly understood by the industry. In this paper a EWMA chart for monitoring standardized variance is developed which is having several advantages over the existing charts such as sample number free design, use in the joint monitoring scheme of process mean and variance and fit to multivariate monitoring. In industrial application this chart can be used to monitor few variables in one display simultaneously

Performance comparison of shewhart joint monitoring schemes for mean and variance

In quality control, joint monitoring schemes for mean and variance are preferred for situations in which special causes can result in change in both the mean and the variance. Several such joint monitoring schemes are reported in the literature to monitor the mean and variance simultaneously of a normally distributed process. Like in the single monitoring of one variable, in the joint monitoring also, combined Shewhart scheme for mean and variance is preferred by many practitioners because of its simplicity compared to combined cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) schemes. Four such Shewhart combined schemes are proposed by three authors in the literature. In this study, the performances of these four schemes are compared using average run length properties under a common platform. Overall, the Shewhart distance scheme performs best and the poorest performance is observed for Shewhart scheme with rectangular acceptance region