The utilisation of systematic review evidence in formulating India's National Health Programme guidelines between 2007 to 2021

Evidence informed policymaking integrates the best available evidence on programme outcomes to guide decisions at all stages of the policy process and its importance becomes more pronounced in resource constrained settings. In this paper, we have reviewed the use of systematic review evidence in framing National Health Programme (NHP) guidelines in India. We searched official websites of the different NHPs, linked to the main website of the Ministry of Health and Family Welfare (MoHFW), in December 2020 and January 2021. NHP guideline documents with systematic review evidence were identified and information on the use of this evidence was extracted. We classified the identified systematic review evidence according to its use in the guideline documents and analysed the data to provide information on the different factors and patterns linked to the use of systematic review evidence in these documents. Systematic reviews were mostly visible in guideline documents addressing maternal and newborn health, communicable diseases and immunization. These systematic reviews were cited in the guidelines to justify the need for action, to justify recommendations for action and opportunities for local adaptation; and to highlight implementation challenges and justify implementation strategies. Guideline documents addressing implementation cited systematic reviews about the problems and policy options more often than citing systematic reviews about implementation. Systematic reviews were linked directly to support statements in few guideline documents, and sometimes the reviews were not appropriately cited. Most of the systematic reviews providing information on the nature and scale of the policy problem included Indian data. It was seen that since 2014, India has been increasingly using systematic review evidence for public health policymaking particularly for some of its high priority NHPs. This complements the increasing investment in research synthesis centres and procedures to support evidence informed decision making, demonstrating the continued evolution of India's evidence policy system

A highly efficient multi-core algorithm for clustering extremely large datasets

<p>Abstract</p> <p>Background</p> <p>In recent years, the demand for computational power in computational biology has increased due to rapidly growing data sets from microarray and other high-throughput technologies. This demand is likely to increase. Standard algorithms for analyzing data, such as cluster algorithms, need to be parallelized for fast processing. Unfortunately, most approaches for parallelizing algorithms largely rely on network communication protocols connecting and requiring multiple computers. One answer to this problem is to utilize the intrinsic capabilities in current multi-core hardware to distribute the tasks among the different cores of one computer.</p> <p>Results</p> <p>We introduce a multi-core parallelization of the k-means and k-modes cluster algorithms based on the design principles of transactional memory for clustering gene expression microarray type data and categorial SNP data. Our new shared memory parallel algorithms show to be highly efficient. We demonstrate their computational power and show their utility in cluster stability and sensitivity analysis employing repeated runs with slightly changed parameters. Computation speed of our Java based algorithm was increased by a factor of 10 for large data sets while preserving computational accuracy compared to single-core implementations and a recently published network based parallelization.</p> <p>Conclusions</p> <p>Most desktop computers and even notebooks provide at least dual-core processors. Our multi-core algorithms show that using modern algorithmic concepts, parallelization makes it possible to perform even such laborious tasks as cluster sensitivity and cluster number estimation on the laboratory computer.</p

Carbon Monoxide Poisoning and Improved Method of its Spot Detection

The paper reviews some investigations on carbon monoxide poisoning and describes a detailed method for detection of carbon monoxide. A comparative study indicating the scope, limitation and range of the various other methods of spot detection has also been given

A Bench Model Methanometer Based on Catalytic oxidation of Methane

The bench model methanometer proposed in this paper is based on catalytic oxidation of methane and has been included in the programme of development of methane monitoring devices taken up at the Central Mining Research Station, Dhanbad. The easy and almost unskilled manipulation, quick analysis and reliable results may introduce the proposed apparatus to the mining industry as a useful tool to control fire damp in the underground mines

Synthesis and 2D self‐assembly at the liquid–solid interface of novel H‐bonding linear π‐conjugated oligomers terminated by uracil and melamine units

International audienceno abstrac

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Not AvailableMajor nutrient management systems for rice-wheat cropping were compared for their potential to credit organic carbon (C) to the soil, its fractionation into active (very labile, VLc; labile, Lc) and passive (less labile, LLc; non-labile, NLc) pools, and crop yield responses. A ten-year long experiment was used to study effects of: (i) no inputs (Control, O), (ii) 100% inorganic fertilizers (F) compared to reduced fertilizers inputs (55%) supplemented with biomass incorporation from (iii) opportunity legume crop (Vigna radiata) (LE), (iv) green manure (Sesbania aculeata) (GM), (v) farmyard manure (FYM), (vi) wheat stubble (WS), and (vii) rice stubble (RS). Maximum C input to soil (as the percentage of C assimilated in the system) was in GM (36%) followed by RS (34%), WS (33%), LE (24%), and FYM (21%) compared to O (15%) and F (15%). Total C input to soil had a direct effect on soil C stock, soil C fractions (maximum in VLc and LLc), yet the responses in terms of biological yield were controlled by the quality of the biomass (C:N ratio, decomposition, etc.) incorporated. Legume-based biomass inputs accrued most benefits for soil C sequestration and biological productivity.Not Availabl