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Background: Health and wellness canters component were launched under the ambit of Ayushman Bharat Yojana. In Kashmir, there was scarce data regarding health and wellness centers implementation therefore this study was undertaken to identify the gaps in implementation of the program at grassroot levels. Objective: to assess and compare the existing staff, services, lab services and infrastructure at health and wellness centers across ten districts of Kashmir valley. Methodology: a descriptive cross-sectional study was done to evaluate the implementation of health and wellness centers in ten districts of Kashmir valley. study population: staff at health and wellness centers study setting: selected health and wellness centers in 10 districts of Kashmir valley sampling: convenient sampling and random sampling 10 % of upgraded health and wellness center in each district at the beginning and 12 months of study. study timeline: 15months data collection 12 months interpretation 3 months study tools: preformed checklist, semi open questionnaires interviews Results: the results of the study indicated that there was still a gap in implementation of program as per guidelines. there were deficiencies in terms of yoga and wellness, proper space for health and wellness centers and staff was not trained properly about the program. Conclusion: this study was done in Kashmir valley to asess the implementation of health and wellness center component of Ayushman Bharat yojana. the study highlighted important deficiencies during the implementation of the program as per guidelines.

Graft copolymerization technique was used to synthesize novel biopolymer based terpolymeric hydrogels of xanthan gum (Gx), acrylic acid and N-Isopropyl acrylamide (NIPAM) by using chemical crosslinker N,N′-methylene bisacrylamide (MBA), ammonium persulphate (APS) as a redox initiator and sodium dodecyl sulphate (SDS) for particle size stabilization. The synthesized hydrogels were characterized through FT-IR and SEM techniques, which confirmed the hydrogels formation. Detailed rheology was investigated through applying various rheological models like Bingham model, modified Bingham model and Ostwald power law model to the hydrogels which revealed that the hydrogels were appeared to have shear thinning, non-Newtonian behavior and more elastic. Modified Bingham model provided best fit understanding to our prepared materials. The maximum activation energy (Ea) 13.87 kJ/mol was obtained for composition having more Gx compared to others, showing a strong relationship with viscosity. The hydrogels has potential to find applications in food industry, cosmetics, degradation of dyes and removal of heavy metals from waste water. [ABSTRACT FROM AUTHOR]

Intensity inhomogeneity or bias field in natural and medical images make image processing challenging. In this paper we have introduced a novel technique in which we first estimate the bias field using multi-scale filtering. Based on the bias field, the bias field corrected image is obtained which is used for accurate segmentation. For segmentation, a convex functional is proposed which is also suitable for multi-region segmentation. The proposed formulation is extended to vector-valued images and texture images. For comparison, the results are compared with state of the art models both qualitatively and quantitatively which validate strong enactment of the proposed formulation. [ABSTRACT FROM AUTHOR]

The present study was carried out at statistical Section, Ayub Agricultural Research Institute, Faisalabad, Pakistan during the year 2013 to examine the production and productivity trends of wheat in Pakistan for the period 1947-48 to 2012-13. Several nonlinear models are applied to fit the trends. Most suitable model selected on the basis of maximum Adjusted R square, relatively minimum values of mean absolute error, root mean squared error and normally, independently, identically distributed error term. None of the parametric models is selected to fit trend of area sown under wheat in Pakistan, nonparametric regression model with kernel smoothing was employed. Sinusoidal model was selected as a suitable model for the both production and productivity of wheat in Pakistan as it fits the trends with 99 percent predictability in case of production and 98 percent for productivity along with all the satisfactory assumptions regarding error term. The root mean squared error of Sinusoidal model for production (0.779) and productivity (99.58) are relatively lower than all other models compared in the study to fit the trends. Mean absolute error also observed minimum in case of Sinusoidal model for both the production and productivity with values 0.623 and 84.778 respectively. The rate of yearly change due to suggested model is 2.95 percent in case of production and 1.89 percent for productivity. [ABSTRACT FROM AUTHOR]