Photometric Calibrations of Metallicity and Temperature For M Dwarfs

Based on a carefully collected sample of dwarf stars, a new empirical photometric calibration to estimate the metallicity of late-type K and early-to-mid-type M dwarfs is presented. The calibration sample has two parts; the first part includes 21 M dwarfs in common proper motion pairs with an FGK star or early-type M dwarf of known metallicity and the second part contains 50 dwarfs with metallicities obtained through moderate-resolution spectra. Using the most recent BT-Settl model atmospheres and the estimated effective temperatures of stars in the calibration sample, the synthetic colour-colour diagram most sensitive to M-dwarf temperatures is identified. By applying these methods to a large sample of around 1,300,000 M dwarfs from the Sloan Digital Sky Survey (SDSS) and the Two-Micron All Sky Survey (2MASS), the metallicity and temperature distributions of these small stars are determined. Using a photometric parallax, the Galactic heights of stars in the large sample are calculated. Our results show a shift in metallicity distribution toward lower metallicities as a function of Galactic height. The relation between metallicity and absolute magnitude is also investigated. A scarcity of metal-poor dwarf stars in the metallicity distribution relative to the Simple Closed Box Model indicates the existence of the “M dwarf problem,” similar to the previously known G and K dwarf problems. It is shown that the Galactic chemical evolution models proposed to solve the G and K dwarf problems could also be a solution of the M dwarf problem as well

Chemical Properties of the Local Galactic Disk and Halo Using Low-Resolution Spectroscopy of M dwarfs and M subdwarfs

Due to their ubiquity and very long main-sequence lifetimes, M dwarfs provide an excellent tool to study the formation and chemical enrichment history of our Galaxy. However, owing to their intrinsic faintness, the acquisition of high-resolution, high signal-to-noise spectra of low-mass stars has been limited to small numbers of very nearby stars, mostly from the Galactic disk population. On the other hand, large numbers of low-resolution spectra of M-type dwarf stars from both the local Galactic disk and halo can be available from various surveys. In order to fully exploit these data, we develop a template-fit method using a set of empirically assembled M dwarf/subdwarf classification templates, based on the measurements of the TiO and CaH molecular bands near 7000 Å, which are used to classify M dwarfs/subdwarfs by spectral type and metallicity class. We further present a pipeline to automatically determine the effective temperature Teff, metallicity [M/H], alpha-element to iron abundance ratio [alpha/Fe], and surface gravity log(g) of M dwarfs/subdwarfs using the latest version of BT-Settl model atmospheres. We apply this pipeline to analyze the low-resolution (R∼2000) spectra of a set of 1700 high proper-motion stars in Chapter 2 and its improved version to a set of 3745 low/high proper-motion M dwarfs/subdwarfs in Chapter 3. These spectra were collected at the MDM Observatory, Lick Observatory, Kitt Peak National Observatory, and Cerro Tololo Interamerican Observatory. We examine variations of the inferred chemical parameters [M/H] and [alpha/Fe] in the HR diagram constructed from their Gaia DR2/EDR3 parallaxes and magnitudes. We also study the distribution of our stars in the abundance diagram of [alpha/Fe] versus [M/H] and inspect the variations of the parameters such as metallicity class MC, effective temperature Teff and surface gravity in this diagram. In addition, the variation of the derived chemical parameters in the kinematic planes is analyzed. The precision of the pipeline is confirmed by comparing the chemical parameters of the primaries and their companions in a set of binary systems

Estimation of Levelized Costs of Electricity Generation in Renewable and Fossil Power Plants

The existence of a comprehensive model that enables the calculation of the real price of electricity production along with its environmental costs is one of the most important analytical tools in energy economics. It is now different from when virtual water costs and other environmental costs of power generation are taken into account. In this article, information from 56 power plants across the country was used. In this paper, an algorithm for calculating the Levelized Cost of Electricity (LCOE) is presented. Among these, common technologies in the production sector, including heating, gas, combined cycle, wind, and photovoltaic power plants, have been studied from an economic perspective and the results of calculating their cost price have been presented. The results show that the highest costs are related to electricity generation using gas technology (18.86 cents per kilowatt hour with subsidized fuel and 35.98 cents per kilowatt hour with exported fuel) and the lowest cost of generating electricity through a wind farm is 6.59 cents per kilowatt hour. In the calculations, the cost of fuel in the form of subsidies and exports and the cost of virtual water in the production process are also considered. One of the reasons for the slow growth of renewable energy development is that the fuel price of gas and oil for power plants in Iran was not realistic despite the fuel subsidy, so electricity production in thermal power plants is cost-effective and electricity production from renewable energies such as wind and photovoltaic power plants in a superficial view has no economic justification.

Touchstone Stars: Highlights from the Cool Stars 18 Splinter Session

We present a summary of the splinter session on "touchstone stars" -- stars with directly measured parameters -- that was organized as part of the Cool Stars 18 conference. We discuss several methods to precisely determine cool star properties such as masses and radii from eclipsing binaries, and radii and effective temperatures from interferometry. We highlight recent results in identifying and measuring parameters for touchstone stars, and ongoing efforts to use touchstone stars to determine parameters for other stars. We conclude by comparing the results of touchstone stars with cool star models, noting some unusual patterns in the differences.Comment: Proceedings of the 18th Cambridge Workshop on Cool Stars, Stellar Systems, and the Sun, Eds G. van Belle & H. Harri

Elemental Abundances of the Super-Neptune WASP-107b's Host Star Using High-resolution, Near-infrared Spectroscopy

We present the first elemental abundance measurements of the K dwarf (K7V) exoplanet-host star WASP-107 using high-resolution (R = 45,000), near-infrared (H- and K-band) spectra taken from Gemini-S/IGRINS. We use the previously determined physical parameters of the star from the literature and infer the abundances of 15 elements: C, N, O, Na, Mg, Al, Si, K, Ca, Ti, V, Cr, Mn, Fe, and Ni, all with precision < 0.1 dex, based on model fitting using MARCS model atmospheres and the spectral synthesis code Turbospectrum. Our results show near-solar abundances and a carbon-to-oxygen ratio (C/O) of 0.50 (+/-0.10), consistent with the solar value of 0.54 (+/-0.09). The orbiting planet, WASP-107b, is a super Neptune with a mass in the Neptune regime (= 1.8 M_Nep) and a radius close to Jupiter's (= 0.94 R_Jup). This planet is also being targeted by four JWST Cycle 1 programs in transit and eclipse, which should provide highly precise measurements of atmospheric abundances. This will enable us to properly compare the planetary and stellar chemical abundances, which is essential in understanding the formation mechanisms, internal structure, and chemical composition of exoplanets. Our study is a proof-of-concept that will pave the way for such measurements to be made for all JWST's cooler exoplanet-host stars.Comment: 19 pages, 8 figures, Accepted to Ap

Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980-2017 : a systematic analysis for the Global Burden of Disease Study 2017

Background Global development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017. Methods The causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODErn), to generate cause fractions and cause specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised. Findings At the broadest grouping of causes of death (Level 1), non-communicable diseases (NC Ds) comprised the greatest fraction of deaths, contributing to 73.4% (95% uncertainty interval [UI] 72.5-74.1) of total deaths in 2017, while communicable, maternal, neonatal, and nutritional (CMNN) causes accounted for 186% (17.9-19.6), and injuries 8.0% (7.7-8.2). Total numbers of deaths from NCD causes increased from 2007 to 2017 by 22.7% (21.5-23.9), representing an additional 7.61 million (7. 20-8.01) deaths estimated in 2017 versus 2007. The death rate from NCDs decreased globally by 7.9% (7.08.8). The number of deaths for CMNN causes decreased by 222% (20.0-24.0) and the death rate by 31.8% (30.1-33.3). Total deaths from injuries increased by 2.3% (0-5-4-0) between 2007 and 2017, and the death rate from injuries decreased by 13.7% (12.2-15.1) to 57.9 deaths (55.9-59.2) per 100 000 in 2017. Deaths from substance use disorders also increased, rising from 284 000 deaths (268 000-289 000) globally in 2007 to 352 000 (334 000-363 000) in 2017. Between 2007 and 2017, total deaths from conflict and terrorism increased by 118.0% (88.8-148.6). A greater reduction in total deaths and death rates was observed for some CMNN causes among children younger than 5 years than for older adults, such as a 36.4% (32.2-40.6) reduction in deaths from lower respiratory infections for children younger than 5 years compared with a 33.6% (31.2-36.1) increase in adults older than 70 years. Globally, the number of deaths was greater for men than for women at most ages in 2017, except at ages older than 85 years. Trends in global YLLs reflect an epidemiological transition, with decreases in total YLLs from enteric infections, respirator}, infections and tuberculosis, and maternal and neonatal disorders between 1990 and 2017; these were generally greater in magnitude at the lowest levels of the Socio-demographic Index (SDI). At the same time, there were large increases in YLLs from neoplasms and cardiovascular diseases. YLL rates decreased across the five leading Level 2 causes in all SDI quintiles. The leading causes of YLLs in 1990 neonatal disorders, lower respiratory infections, and diarrhoeal diseases were ranked second, fourth, and fifth, in 2017. Meanwhile, estimated YLLs increased for ischaemic heart disease (ranked first in 2017) and stroke (ranked third), even though YLL rates decreased. Population growth contributed to increased total deaths across the 20 leading Level 2 causes of mortality between 2007 and 2017. Decreases in the cause-specific mortality rate reduced the effect of population growth for all but three causes: substance use disorders, neurological disorders, and skin and subcutaneous diseases. Interpretation Improvements in global health have been unevenly distributed among populations. Deaths due to injuries, substance use disorders, armed conflict and terrorism, neoplasms, and cardiovascular disease are expanding threats to global health. For causes of death such as lower respiratory and enteric infections, more rapid progress occurred for children than for the oldest adults, and there is continuing disparity in mortality rates by sex across age groups. Reductions in the death rate of some common diseases are themselves slowing or have ceased, primarily for NCDs, and the death rate for selected causes has increased in the past decade. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.Peer reviewe

Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017

Background: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of “leaving no one behind”, it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990–2017, projected indicators to 2030, and analysed global attainment. Methods: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0–100, with 0 as the 2\ub75th percentile and 100 as the 97\ub75th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings: The global median health-related SDG index in 2017 was 59\ub74 (IQR 35\ub74–67\ub73), ranging from a low of 11\ub76 (95% uncertainty interval 9\ub76–14\ub70) to a high of 84\ub79 (83\ub71–86\ub77). SDG index values in countries assessed at the subnational level varied substantially, particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attainment by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation: The GBD study offers a unique, robust platform for monitoring the health-related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health-related SDG indicators, NCDs, NCD-related risks, and violence-related indicators will require a concerted shift away from what might have driven past gains—curative interventions in the case of NCDs—towards multisectoral, prevention-oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the SDGs. What is clear is that our actions—or inaction—today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030

Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017.

BACKGROUND: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of 'leaving no one behind', it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990-2017, projected indicators to 2030, and analysed global attainment. METHODS: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0-100, with 0 as the 2·5th percentile and 100 as the 97·5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator