Study of the productivity of MWCNT over Fe and Fe–Co catalysts supported on SiO2, Al2O3 and MgO

AbstractIn the present study, multi-walled carbon nanotubes (MWCNT) were prepared in good quality and quantity, MWCNT were produced using the catalytic chemical vapor deposition (CCVD) technique and the carbon source was acetylene. Different catalysts were synthesized based on iron and a mixture of iron and cobalt metal supported on SiO2, Al2O3 or MgO. The effect of parameters such as iron concentration, support type, bimetallic catalyst and the method of catalyst preparation has been investigated in the production of MWCNT. The quality of as-made nanotubes was investigated by the high-resolution transmission electron microscopy (HRTEM) and thermogravimetric analysis (TGA). The best yield of MWCNT was 30 times of the amount of the used catalyst. The high yield of MWCNT was gained by 40wt.% Fe on alumina support which was prepared by the sol–gel method. TEM analysis was done for the carbon deposit, which revealed that the walls of the MWCNT were graphitized, with regular inner channel and uniform diameter. It reflected a reasonable degree of purity. The TGA showed that MWCNT was decomposed at 635°C by a small rate indicating a high thermal stability and well crystalline formation of the produced MWCNT

High performance supercapacitor based on laser induced graphene for wearable devices

To ensure maximum comfort for the wearer, electronic components that include energy harvesters need to be mechanically conformable. In this context, we demonstrate a versatile, cost-effective and efficient method for fabricating graphene supercapacitor electrodes using Laser Induced Graphene (LIG). A CO2 laser beam instantly transforms the irradiated polyethersulfone polymer (PES) into a highly porous carbon structure. The LIG method was used to deposit graphene layers on graphite sheets to produce the supercapacitor electrodes. Graphene formation and morphology were examined and confirmed using several techniques including Scanning Electron Microscopy (SEM), Energy Dispersive X-ray (EDX) spectroscopy, Raman Spectroscopy and Fourier transform infrared spectroscopy (FTIR). Moreover, the electrochemical characterization was performed in different electrolytes (NaOH and KOH). At 5 mV s-1, the LIG electrode achieved 165 mF cm-2 and 250 mF cm-2 in NaOH and KOH electrolytes, respectively. Consequently, we show that a wearable symmetric supercapacitor device with LIG electrodes achieved 98.5 mF cm-2 at 5 mV s-1 in KOH electrolyte. The device demonstrated an energy density of 11.3 μWh.cm-2 with power density of 0.33 mWcm-2 at 0.5 mA cm-2. The retention of capacitance was 75% after 2000 cycles, with outstanding performance for the comparable graphene-based electrodes. These results further validate the use of LIG for developing flexible energy harvesters for wearable applications

Multi-fidelity efficient global optimization : Methodology and application to airfoil shape design

Predictions and design engineering decisions can be made using a variety of informa- tion sources that range from experimental data to computer models. These information sources could consist of different mathematical formulations, different grid resolutions, dif- ferent physics, or different modeling assumptions that simplify the problem. This leads to information sources with varying degrees of fidelity, each with an associated accuracy and querying cost. In this paper, we propose a novel and flexible way to use multi-fidelity informa- tion sources optimally in the context of airfoil shape optimization using both Xfoil and ADflow. The new developments are based on Bayesian optimization and kriging metamodeling and allow the aerodynamic optimization to be sped up. In a constrained optimization example with 15-design variables problem, the proposed approach reduces the total cost by a factor of two compared to a single Bayesian based fidelity optimization and by a factor of 1.5 compared to sequential quadratic programming

A Python surrogate modeling framework with derivatives

The surrogate modeling toolbox (SMT) is an open-source Python package that contains a collection of surrogate modeling methods, sampling techniques, and benchmarking functions. This package provides a library of surrogate models that is simple to use and facilitates the implementation of additional methods. SMT is different from existing surrogate modeling libraries because of its emphasis on derivatives, including training derivatives used for gradient-enhanced modeling, prediction derivatives, and derivatives with respect to training data. It also includes unique surrogate models: kriging by partial least-squares reduction, which scales well with the number of inputs; and energy- minimizing spline interpolation, which scales well with the number of training points. The efficiency and effectiveness of SMT are demonstrated through a series of examples. SMT is documented using custom tools for embedding automatically tested code and dynamically generated plots to produce high-quality user guides with minimal effort from contributors. SMT is maintained in a public version control repository

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$, 2020 US$ per capita, purchasing-power parity-adjusted US$per capita, and as a proportion of gross domestic product. We used various models to generate future health spending to 2050. Findings In 2019, health spending globally reached$8. 8 trillion (95% uncertainty interval [UI] 8.7-8.8) or $1132 (1119-1143) per person. Spending on health varied within and across income groups and geographical regions. Of this total,$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 $54.8 billion in development assistance for health was disbursed in 2020. Of this,$13.7 billion was targeted toward the COVID-19 health response. $12.3 billion was newly committed and$1.4 billion was repurposed from existing health projects. $3.1 billion (22.4$2.4 billion (17.9%) was for supply chain and logistics. Only $714.4 million (7.7$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 comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: A systematic analysis for the Global Burden of Disease Study 2015

Background: The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods: We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings: Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation: Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding: Bill & Melinda Gates Foundation

Measurement of the mass difference between top quark and antiquark in pp collisions at root s=8 TeV

Peer reviewe

Search for heavy resonances decaying into a vector boson and a Higgs boson in final states with charged leptons, neutrinos, and b quarks

Peer reviewe

Search for neutral resonances decaying into a Z boson and a pair of b jets or τ leptons

A search is performed for a new resonance decaying into a lighter resonance and a Z boson. Two channels are studied, targeting the decay of the lighter resonance into either a pair of oppositely charged τ leptons or a bb‾ pair. The Z boson is identified via its decays to electrons or muons. The search exploits data collected by the CMS experiment at a centre-of-mass energy of 8 TeV, corresponding to an integrated luminosity of 19.8 fb −1 . No significant deviations are observed from the standard model expectation and limits are set on production cross sections and parameters of two-Higgs-doublet models