142 research outputs found
Cooperative Learning for Distributed In-Network Traffic Classification
Inspired by the concept of autonomic distributed/decentralized network management schemes, we consider the issue of information exchange among distributed network nodes to network performance and promote scalability for in-network monitoring. In this paper, we propose a cooperative learning algorithm for propagation and synchronization of network information among autonomic distributed network nodes for online traffic classification. The results show that network nodes with sharing capability perform better with a higher average accuracy of 89.21% (sharing data) and 88.37% (sharing clusters) compared to 88.06% for nodes without cooperative learning capability. The overall performance indicates that cooperative learning is promising for distributed in-network traffic classification
Mini-review on CO2 reforming methane in aspect of fibrous zeolite's properties
The threat of climate change resulting from the excessive emission of greenhouse gases remains intractable. CO2 reforming of methane (DRM) has attracted considerable attention owing to its advantages in converting two primary greenhouse gases (CH4 and CO2) into synthesis gas (H2 and CO). However, catalyst deactivation arose from sintering and carbon formation is the primary problems for DRM that must be urgently solved. In this regard, creating support materials with fibrous morphology and dendrimeric structures is becoming an intriguing approach demonstrating its advantages in improving catalyst's physicochemical properties thus promote an excellent catalytic activity, stability, and deactivation resistance during reaction. This mini-review focuses on the physicochemical features of fibrous zeolite-supported type catalysts and their significance in DRM catalytic performance, including the interaction between metal and support, metal dispersion, particle size, porosity, and surface area. This study also provide the understanding of catalytic properties and their correlation with catalytic performance needed for the design of catalysts and suitable for DRM
Mini-review on fibrous zeolite catalysts for CO2 reforming of methane
The persistent threat of climate change is brought on by extreme emissions of greenhouse gases (GHGs). Due to its advantages in converting two principal GHGs (CH4 and CO2) into a synthesis gas (H2 and CO), carbon dioxide reforming of methane has received a lot of interest. However, the main issue with a dry reforming of methane (DRM) that needs to be rapidly tackled is catalyst deactivation caused by sintering and coke formation. In this context, the development of fibrous morphological support materials has emerged as an exciting technique that has shown promise in enhancing the physicochemical characteristics of the catalyst and enabling superior catalytic activity and deactivation resistance during the reaction. The physicochemical characteristics of fibrous zeolite-supported type catalysts, including metal-support interaction, metal dispersion, particle size, surface area, and porous nature, were the main emphasis of this mini-review. Designing suitable catalysts for DRM requires a thorough examination of catalytic properties and their relationship to catalytic performance
Properties-activity correlation of Nickel supported on fibrous Zeolite-Y for dry reforming of methane
Nickel-supported Fibrous zeolite-Y (Ni/FHY) was successfully synthesized via the microemulsion method using HY as seed, followed by catalytic evaluation in dry reforming of methane (DRM) for hydrogen production. Ni/FHY possessed good NiO distribution, improved metal-support interface, and strong basicity, accredited to the fibrous structure of FHY. This unique morphology led to the enrichment in the amount of accessible Ni active sites, thus resulting in the superior activity of Ni/FHY (XCH=95.1%,XCO=91.1%,H2/CO=0.89) compared to Ni/HY (XCH=92.7%,XCO=89.8%,H2/CO=0.78). Meanwhile, the inferior performance of Ni/HY could be caused by the poor distribution of Ni with large particles, thus contributing to high carbon deposition and Ni sintering. The unique physicochemical properties and superior catalytic activity confirmed its viability in the DRM
The timing of HIV-1 infection of cells that persist on therapy is not strongly influenced by replication competency or cellular tropism of the provirus
People with HIV-1 (PWH) on antiretroviral therapy (ART) can maintain undetectable virus levels, but a small pool of infected cells persists. This pool is largely comprised of defective proviruses that may produce HIV-1 proteins but are incapable of making infectious virus, with only a fraction (~10%) of these cells harboring intact viral genomes, some of which produce infectious virus following ex vivo stimulation (i.e. inducible intact proviruses). A majority of the inducible proviruses that persist on ART are formed near the time of therapy initiation. Here we compared proviral DNA (assessed here as 3’ half genomes amplified from total cellular DNA) and inducible replication competent viruses in the pool of infected cells that persists during ART to determine if the original infection of these cells occurred at comparable times prior to therapy initiation. Overall, the average percent of proviruses that formed late (i.e. around the time of ART initiation, 60%) did not differ from the average percent of replication competent inducible viruses that formed late (69%), and this was also true for proviral DNA that was hypermutated (57%). Further, there was no evidence that entry into the long-lived infected cell pool was impeded by the ability to use the CXCR4 coreceptor, nor was the formation of long-lived infected cells enhanced during primary infection, when viral loads are exceptionally high. We observed that infection of cells that transitioned to be long-lived was enhanced among people with a lower nadir CD4+ T cell count. Together these data suggest that the timing of infection of cells that become long-lived is impacted more by biological processes associated with immunodeficiency before ART than the replication competency and/ or cellular tropism of the infecting virus or the intactness of the provirus. Further research is needed to determine the mechanistic link between immunodeficiency and the timing of infected cells transitioning to the long-lived pool, particularly whether this is due to differences in infected cell clearance, turnover rates and/or homeostatic proliferation before and after ART
Evaluation of sesamum gum as an excipient in matrix tablets
In developing countries modern medicines are often beyond the affordability of the majority of the population. This is due to the reliance on expensive imported raw materials despite the abundance of natural resources which could provide an equivalent or even an improved function. The aim of this study was to investigate the potential of sesamum gum (SG) extracted from the leaves of Sesamum radiatum (readily cultivated in sub-Saharan Africa) as a matrix former. Directly compressed matrix tablets were prepared from the extract and compared with similar matrices of HPMC (K4M) using theophylline as a model water soluble drug. The compaction, swelling, erosion and drug release from the matrices were studied in deionized water, 0.1 N HCl (pH 1.2) and phosphate buffer (pH 6.8) using USP apparatus II. The data from the swelling, erosion and drug release studies were also fitted into the respective mathematical models. Results showed that the matrices underwent a combination of swelling and erosion, with the swelling action being controlled by the rate of hydration in the medium. SG also controlled the release of theophylline similar to the HPMC and therefore may have use as an alternative excipient in regions where Sesamum radiatum can be easily cultivated
Tracking development assistance for health and for COVID-19 : a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990-2050
Background The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020. Methods We estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US per capita, purchasing-power parity-adjusted US8. 8 trillion (95% uncertainty interval [UI] 8.7-8.8) or 40.4 billion (0.5%, 95% UI 0.5-0.5) was development assistance for health provided to low-income and middle-income countries, which made up 24.6% (UI 24.0-25.1) of total spending in low-income countries. We estimate that 13.7 billion was targeted toward the COVID-19 health response. 1.4 billion was repurposed from existing health projects. 2.4 billion (17.9%) was for supply chain and logistics. Only 1519 (1448-1591) per person in 2050, although spending across countries is expected to remain varied. Interpretation Global health spending is expected to continue to grow, but remain unequally distributed between countries. We estimate that development organisations substantially increased the amount of development assistance for health provided in 2020. Continued efforts are needed to raise sufficient resources to mitigate the pandemic for the most vulnerable, and to help curtail the pandemic for all. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.Peer reviewe
Global, regional, and national burden of stroke and its risk factors, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019
Background
Regularly updated data on stroke and its pathological types, including data on their incidence, prevalence, mortality, disability, risk factors, and epidemiological trends, are important for evidence-based stroke care planning and resource allocation. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) aims to provide a standardised and comprehensive measurement of these metrics at global, regional, and national levels.
Methods
We applied GBD 2019 analytical tools to calculate stroke incidence, prevalence, mortality, disability-adjusted life-years (DALYs), and the population attributable fraction (PAF) of DALYs (with corresponding 95% uncertainty intervals [UIs]) associated with 19 risk factors, for 204 countries and territories from 1990 to 2019. These estimates were provided for ischaemic stroke, intracerebral haemorrhage, subarachnoid haemorrhage, and all strokes combined, and stratified by sex, age group, and World Bank country income level.
Findings
In 2019, there were 12·2 million (95% UI 11·0–13·6) incident cases of stroke, 101 million (93·2–111) prevalent cases of stroke, 143 million (133–153) DALYs due to stroke, and 6·55 million (6·00–7·02) deaths from stroke. Globally, stroke remained the second-leading cause of death (11·6% [10·8–12·2] of total deaths) and the third-leading cause of death and disability combined (5·7% [5·1–6·2] of total DALYs) in 2019. From 1990 to 2019, the absolute number of incident strokes increased by 70·0% (67·0–73·0), prevalent strokes increased by 85·0% (83·0–88·0), deaths from stroke increased by 43·0% (31·0–55·0), and DALYs due to stroke increased by 32·0% (22·0–42·0). During the same period, age-standardised rates of stroke incidence decreased by 17·0% (15·0–18·0), mortality decreased by 36·0% (31·0–42·0), prevalence decreased by 6·0% (5·0–7·0), and DALYs decreased by 36·0% (31·0–42·0). However, among people younger than 70 years, prevalence rates increased by 22·0% (21·0–24·0) and incidence rates increased by 15·0% (12·0–18·0). In 2019, the age-standardised stroke-related mortality rate was 3·6 (3·5–3·8) times higher in the World Bank low-income group than in the World Bank high-income group, and the age-standardised stroke-related DALY rate was 3·7 (3·5–3·9) times higher in the low-income group than the high-income group. Ischaemic stroke constituted 62·4% of all incident strokes in 2019 (7·63 million [6·57–8·96]), while intracerebral haemorrhage constituted 27·9% (3·41 million [2·97–3·91]) and subarachnoid haemorrhage constituted 9·7% (1·18 million [1·01–1·39]). In 2019, the five leading risk factors for stroke were high systolic blood pressure (contributing to 79·6 million [67·7–90·8] DALYs or 55·5% [48·2–62·0] of total stroke DALYs), high body-mass index (34·9 million [22·3–48·6] DALYs or 24·3% [15·7–33·2]), high fasting plasma glucose (28·9 million [19·8–41·5] DALYs or 20·2% [13·8–29·1]), ambient particulate matter pollution (28·7 million [23·4–33·4] DALYs or 20·1% [16·6–23·0]), and smoking (25·3 million [22·6–28·2] DALYs or 17·6% [16·4–19·0]).
Interpretation
The annual number of strokes and deaths due to stroke increased substantially from 1990 to 2019, despite substantial reductions in age-standardised rates, particularly among people older than 70 years. The highest age-standardised stroke-related mortality and DALY rates were in the World Bank low-income group. The fastest-growing risk factor for stroke between 1990 and 2019 was high body-mass index. Without urgent implementation of effective primary prevention strategies, the stroke burden will probably continue to grow across the world, particularly in low-income countries.publishedVersio
A case study of an individual participant data meta-analysis of diagnostic accuracy showed that prediction regions represented heterogeneity well
The diagnostic accuracy of a screening tool is often characterized by its sensitivity and specificity. An analysis of these measures must consider their intrinsic correlation. In the context of an individual participant data meta-analysis, heterogeneity is one of the main components of the analysis. When using a random-effects meta-analytic model, prediction regions provide deeper insight into the effect of heterogeneity on the variability of estimated accuracy measures across the entire studied population, not just the average. This study aimed to investigate heterogeneity via prediction regions in an individual participant data meta-analysis of the sensitivity and specificity of the Patient Health Questionnaire-9 for screening to detect major depression. From the total number of studies in the pool, four dates were selected containing roughly 25%, 50%, 75% and 100% of the total number of participants. A bivariate random-effects model was fitted to studies up to and including each of these dates to jointly estimate sensitivity and specificity. Two-dimensional prediction regions were plotted in ROC-space. Subgroup analyses were carried out on sex and age, regardless of the date of the study. The dataset comprised 17,436 participants from 58 primary studies of which 2322 (13.3%) presented cases of major depression. Point estimates of sensitivity and specificity did not differ importantly as more studies were added to the model. However, correlation of the measures increased. As expected, standard errors of the logit pooled TPR and FPR consistently decreased as more studies were used, while standard deviations of the random-effects did not decrease monotonically. Subgroup analysis by sex did not reveal important contributions for observed heterogeneity; however, the shape of the prediction regions differed. Subgroup analysis by age did not reveal meaningful contributions to the heterogeneity and the prediction regions were similar in shape. Prediction intervals and regions reveal previously unseen trends in a dataset. In the context of a meta-analysis of diagnostic test accuracy, prediction regions can display the range of accuracy measures in different populations and settings
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Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk.
Lung-function impairment underlies chronic obstructive pulmonary disease (COPD) and predicts mortality. In the largest multi-ancestry genome-wide association meta-analysis of lung function to date, comprising 580,869 participants, we identified 1,020 independent association signals implicating 559 genes supported by ≥2 criteria from a systematic variant-to-gene mapping framework. These genes were enriched in 29 pathways. Individual variants showed heterogeneity across ancestries, age and smoking groups, and collectively as a genetic risk score showed strong association with COPD across ancestry groups. We undertook phenome-wide association studies for selected associated variants as well as trait and pathway-specific genetic risk scores to infer possible consequences of intervening in pathways underlying lung function. We highlight new putative causal variants, genes, proteins and pathways, including those targeted by existing drugs. These findings bring us closer to understanding the mechanisms underlying lung function and COPD, and should inform functional genomics experiments and potentially future COPD therapies
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