HI aperture synthesis and optical observations of the pair of galaxies NGC 6907 and 6908

NGC 6908, a S0 galaxy situated in direction of NGC 6907, was only recently recognized as a distinct galaxy, instead of only a part of NGC 6907. We present 21 cm radio synthesis observations obtained with the GMRT and optical images and spectroscopy obtained with the Gemini North telescope of this pair of interacting galaxies. From the radio observations we obtained the velocity field and the HI column density map of the whole region containing the NGC 6907/8 pair, and by means of the Gemini multi-object spectroscopy we obtained high quality photometric images and $5 {\AA}$ resolution spectra sampling the two galaxies. By comparing the rotation curve of NGC 6907 obtained from the two opposite sides around the main kinematic axis, we were able to distinguish the normal rotational velocity field from the velocity components produced by the interaction between the two galaxies. Taking into account the rotational velocity of NGC 6907 and the velocity derived from the absorption lines for NGC 6908, we verified that the relative velocity between these systems is lower than 60 km s$^{-1}$. The emission lines observed in the direction of NGC 6908, not typical of S0 galaxies, have the same velocity expected for the NGC 6907 rotation curve. Some of them, superimposed on the absorption profiles, which reinforces the idea that they were not formed in NGC 6908. Finally, the HI profile exhibits details of the interaction, showing three components: one for NGC 6908, another for the excited gas in the NGC 6907 disk and a last one for the gas with higher relative velocities left behind NGC 6908 by dynamical friction, used to estimate the time when the interaction started in $(3.4 \pm 0.6)\times10^7$ years ago.Comment: 11 pages, 5 tables, 13 figures. Corrected typos. Accepted for publication in MNRAS. The definitive version will be available at http://www.blackwell-synergy.co

The Frequency-dependent Damping of Slow Magnetoacoustic Waves in a Sunspot Umbral Atmosphere

High spatial and temporal resolution images of a sunspot, obtained simultaneously in multiple optical and UV wavelengths, are employed to study the propagation and damping characteristics of slow magnetoacoustic waves up to transition region heights. Power spectra are generated from intensity oscillations in sunspot umbra, across multiple atmospheric heights, for frequencies up to a few hundred mHz. It is observed that the power spectra display a power-law dependence over the entire frequency range, with a significant enhancement around 5.5 mHz found for the chromospheric channels. The phase-difference spectra reveal a cutoff frequency near 3 mHz, up to which the oscillations are evanescent, while those with higher frequencies propagate upwards. The power-law index appears to increase with atmospheric height. Also, shorter damping lengths are observed for oscillations with higher frequencies suggesting frequency-dependent damping. Using the relative amplitudes of the 5.5 mHz (3 minute) oscillations, we estimate the energy flux at different heights, which seems to decay gradually from the photosphere, in agreement with recent numerical simulations. Furthermore, a comparison of power spectra across the umbral radius highlights an enhancement of high-frequency waves near the umbral center, which does not seem to be related to magnetic field inclination angle effects

The Mars Environmental Dynamics Analyzer, MEDA. A Suite of Environmental Sensors for the Mars 2020 Mission

86 pags, 49 figs, 24 tabsNASA's Mars 2020 (M2020) rover mission includes a suite of sensors to monitor current environmental conditions near the surface of Mars and to constrain bulk aerosol properties from changes in atmospheric radiation at the surface. The Mars Environmental Dynamics Analyzer (MEDA) consists of a set of meteorological sensors including wind sensor, a barometer, a relative humidity sensor, a set of 5 thermocouples to measure atmospheric temperature at ∼1.5 m and ∼0.5 m above the surface, a set of thermopiles to characterize the thermal IR brightness temperatures of the surface and the lower atmosphere. MEDA adds a radiation and dust sensor to monitor the optical atmospheric properties that can be used to infer bulk aerosol physical properties such as particle size distribution, non-sphericity, and concentration. The MEDA package and its scientific purpose are described in this document as well as how it responded to the calibration tests and how it helps prepare for the human exploration of Mars. A comparison is also presented to previous environmental monitoring payloads landed on Mars on the Viking, Pathfinder, Phoenix, MSL, and InSight spacecraft.This work has been funded by the Spanish Ministry of Economy and Competitiveness, through the projects No. ESP2014-54256-C4-1-R (also -2-R, -3-R and -4-R) and AYA2015-65041-P; Ministry of Science, Innovation and Universities, projects No. ESP2016-79612-C3-1-R (also -2-R and -3-R), ESP2016-80320-C2-1-R, RTI2018-098728-B-C31 (also -C32 and -C33) and RTI2018-099825-B-C31; Instituto Nacional de Tecnica Aeroespacial; Ministry of Science and Innovation's Centre for the Development of Industrial Technology; Grupos Gobierno Vasco IT1366-19; and European Research Council Consolidator Grant no 818602.Peer reviewe

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation