187 research outputs found

    Trends in rural fiscal decentralisation in India’s Karnataka state: a focus on public health

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    For decades, decentralisation reforms have been seen as a powerful instrument by health policy advocates to improve health sector performance in developing countries. In India, the 73rd Constitutional Amendment introduced in 1992 called for strengthening the fiscal autonomy and service delivery capacity of rural local governments. This paper explores how decentralised governance influences public health sector resource allocation, equity and efficiency in rural Karnataka. For this, the authors analysed administrative data published by the Karnataka state government to create tailored standardised performance measures that capture the degree of local governments’ fiscal discretion in implementing public health programmes from 2011–18 at the district level. The findings highlight sector-specific differences in fiscal autonomy, ranging from high local discretion over funds in the nutrition sector to very limited discretion in the medical and public health sector. They also show that decentralised public health funding is not well-targeted to areas of greatest need in Karnatak

    Adaptive Optimized Discriminative Learning based Image Deblurring using Deep CNN

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    Image degradation plays a major problem in many image processing applications. Due to blurring, the quality of an image is degraded and there will be a reduction in bandwidth. Blur in an image is due to variations in atmospheric turbulence, focal length, camera settings, etc. Various types of blurs include Gaussian blur, Motion blur, Out-of-focus blur. The effect of noise along with blur further corrupts the captured image. Many techniques have evolved to deblur the degraded image. The leading approach to solve various degraded images are either based on discriminative learning models or on optimization models. Each method has its own advantages and disadvantages.  Learning by discriminative methods is faster but restricted to a specific task whereas optimization models handle flexibly but consume more time. Integrating optimization models suitably by learning with discriminative manner results in effective image restoration. In this paper, a set of effective and fast Convolutional Neural Networks (CNNs) are employed to deblur the Gaussian, motion and out-of-focus blurred images that integrate with optimization models to further avoid noise effects. The proposed methods work more efficiently for applications with low-level vision

    A New Modular Multilevel Inverter Topology of Reduced Components

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    Harmonic content of the yield voltage waveform diminishes as the quantity of yield voltage level increments. The primary focal points are lower Total Harmonic Distortion (THD), less weight on the power switches and higher proficiency. Be that as it may, increment in the gadget number because of expanded voltage levels makes the control strategy complex and subsequently costly. This venture displays a nine level inverter with lessened DC sources which is equipped for acquiring all added substance and subtractive mixes of information DC levels. This topology requires less power changes contrasted with regular multilevel inverter and less entryway drives. The proposed topology is exhibited through a nine-level inverter with a proper balance plot and definite reproduction has been done in MATLAB/Simulink. A correlation is made between proposed topology and the customary multilevel topology on the premise of gadget include, number of levels the yield voltage and THD

    Analysis of plasma myeloperoxidase levels and functional gene –463G>A and –129G>A polymorphisms with early onset of coronary artery disease in South Indian population

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    Introduction. The present investigation is pursued to study the possible association of –463G>A and –129G>A polymorphism in MPO gene and assessment of plasma MPO levels with the risk of developing coronary artery disease.Material and methods. A total of 200 angiographically documented CAD patients and 200 age, gender ethnicity matched healthy controls were recruited for the study. Plasma MPO levels were assessed using enzyme-linked immunosorbent assay (ELISA) kit and genotypes were determined by PCR-RFLP technique.Results. The MPO levels were found to be significantly increased in CAD patients when compared with controls (p < 0.04) but there were no significant effect of –463G>A gene polymorphism on MPO levels. A significant association of –463G>A polymorphism was observed with coronary artery disease. The frequency of recessive genotype “AA” at –463 promoter site was considerably lesser in patients (4%) relative to controls (11%) (odds ratio [OR] = 0.3371, 95% confidence interval [CI] 0.1463–0.7766, p = 0.012). However we did not find significant association of –129G>A polymorphism with CAD. Additionally, haplotype analysis revealed that single nucleotide polymorphisms (SNP) 1 of AA genotype and SNP 2 of GG genotype showed significant protective effect with disease (OR = 0.64; 95% CI [0.42–0.96], p = 0.032).Conclusion. The results revealed that –463G>A polymorphism in the MPO gene lowers the CAD related condition in patients by down regulating serum MPO concentration, which is known to aggravate the atherosclerotic events observed in CAD

    UV SPECTROPHOTOMETRIC METHOD DEVELOPMENT AND VALIDATION FOR SIMULTANEOUS ESTIMATION OF ALPRAZOLAM AND MEBEVERINE HYDROCHLORIDE IN BULK DRUG AND PHARMACEUTICAL FORMULATION

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    A simple, accurate, precise, sensitive, rapid and economical spectrophotometric method was developed and validated for simultaneous estimation of Alprazolam (ALP) and Mebeverine HCl (MBH) in bulk drug and pharmaceutical formulation. The estimation of these drugs was carried out by using 0.1M HCl as a solvent. The wavelength maxima for Alprazolam and Mebeverine HCl were found to be 262.3 nm and 222.5 nm. The linearity range was observed in the concentration range of 3-15 µg/ml for both drugs and regression equation was found to be for ALP 0.0565x+0.0138 and for MBH 0.049x-0.0126. Percentage recoveries for Alprazolam and Mebeverine HCl were found to be 99.84% and 99.47% respectively. % RSD values for Intra-day precision were found to be for ALP 1.18% and for MBH 0.59%. Inter-day precision %RSD values were found to be for ALP 0.94% and for MBH 0.69%. LOD was found to be for ALP 1.42 (µg/ml) and for MBH 2.1542 (µg/ml). LOQ was found to be for ALP 4.3242 (µg/ml) and for MBH 6.5442 (µg/ml). The %Assay of Alprazolam and Mebeverine HCl were found to be 99.20% and 100.02% respectively. Statistical analysis proved that the developed method can be successfully used for simultaneous analysis of Alprazolam and Mebeverne HCl in pure and tablet dosage forms

    DESIGN AND ANALYSIS OF THERMO HYDRO DYNAMIC PLAIN JOURNAL BEARING BY USING FSI TOOL

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    Journal bearings have the longest history of scientific study of any class of fluid film bearings. In a fluid film bearing, the pressure in the oil film satisfies the Reynolds equation which intern is a function of film thickness. Structural distortion of the housing and the development of thermo hydrodynamic pressure in a full journal bearing are strongly coupled thus require a combined solution.Oil film pressure is one of the key operating parameters describing the operating conditions in thermo hydrodynamic journal bearings. Thermo hydrodynamic journal bearings are analyzed by using Computational fluid dynamics (CFD) and fluid structure interaction (FSI) approach in order to find deformation of the bearing.In this thesis journal bearings for different L/D ratios and eccentricity ratios are modeled in 3D modeling software Pro/Engineer. The L/D ratios considered are 0.5, 1.0, 1.5 and eccentricity ratios considered are 0.3, 0.5, 0.7 and 0.9. Journal bearing models are developed for speed of 2000 rpm to study the interaction between the fluid and elastic behavior of the bearing. The speed is the input for CFD analysis and the pressure obtained from the CFD analysis is taken as input for structural analysis.Computational fluid dynamics (CFD) and fluid structure interaction (FSI) is done in Ansys

    Implementation of TCP Congestion Control mechanism for Wireless Networks using TCP Reserved Field and Signal to Noise Ratio (SNR)

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    TCP is the most popular and widely used network transmission protocol. All most 90% of the Internet connections make use of TCP for communication. TCP is reliable for wired networks and it considers all packet timeouts in wired networks as due to network congestion and not because of bit errors. However, TCP suffers from performance degradation over error-prone wireless links, as it has no technique to distinguish error deficits from congestion deficits, with networking becoming more divergent, with wired and wireless topologies. It considers all packet deficits are due to congestion and subsequently reduces the packet burst transmission, at the same time decreasing the network throughput. In this paper a new TCP congestion control mechanism is proposed that is suitable and applicable for wireless and also for wired networks and is capable of distinguishing congestion deficits from error deficits. The proposed technique uses the reserved field of the TCP header to indicate whether the connection established is over a wired or a wireless link. Further, the proposed technique influences the usage of Signal to Noise Ratio (SNR) to discover the reliability of the link and determine whether to decrease the packet burst or retransmit the timed-out packet. Investigations performed, revealed that the proposed mechanism confirmed to function amend in circumstances where timeouts were due to error and not due to congestion. Further, the future work can be enhanced upon the proposed mechanism so that it can leverage Cyclic Redundancy Check(CRC) and Header Error Check(HEC) errors so that it can be properly determined the reason for initializing transmission timeouts in wireless networks.

    Inactivation of Factor VIIa by Antithrombin In Vitro, Ex Vivo and In Vivo: Role of Tissue Factor and Endothelial Cell Protein C Receptor

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    Recent studies have suggested that antithrombin (AT) could act as a significant physiologic regulator of FVIIa. However, in vitro studies showed that AT could inhibit FVIIa effectively only when it was bound to tissue factor (TF). Circulating blood is known to contain only traces of TF, at best. FVIIa also binds endothelial cell protein C receptor (EPCR), but the role of EPCR on FVIIa inactivation by AT is unknown. The present study was designed to investigate the role of TF and EPCR in inactivation of FVIIa by AT in vivo. Low human TF mice (low TF, ∼1% expression of the mouse TF level) and high human TF mice (HTF, ∼100% of the mouse TF level) were injected with human rFVIIa (120 µg kg−1 body weight) via the tail vein. At varying time intervals following rFVIIa administration, blood was collected to measure FVIIa-AT complex and rFVIIa antigen levels in the plasma. Despite the large difference in TF expression in the mice, HTF mice generated only 40–50% more of FVIIa-AT complex as compared to low TF mice. Increasing the concentration of TF in vivo in HTF mice by LPS injection increased the levels of FVIIa-AT complexes by about 25%. No significant differences were found in FVIIa-AT levels among wild-type, EPCR-deficient, and EPCR-overexpressing mice. The levels of FVIIa-AT complex formed in vitro and ex vivo were much lower than that was found in vivo. In summary, our results suggest that traces of TF that may be present in circulating blood or extravascular TF that is transiently exposed during normal vessel damage contributes to inactivation of FVIIa by AT in circulation. However, TF’s role in AT inactivation of FVIIa appears to be minor and other factor(s) present in plasma, on blood cells or vascular endothelium may play a predominant role in this process
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