Real-Time Monitoring of Aluminum Oxidation Through Wide Band Gap MgF2 Layers for Protection of Space Mirrors

Because of its extraordinary and broad reflectivity, aluminum is the only logical candidate for advanced space mirrors that operate deep into the UV. However, aluminum oxidizes rapidly in the air, and even a small amount of oxide (as little as a nanometer) can have a noticeable, detrimental impact on its reflectivity at short wavelengths. Thin films of wide band gap materials like MgF2 have previously been used to protect aluminum surfaces. Here we report the first real-time, spectroscopic ellipsometry (SE) study of aluminum oxidation as a function of MgF2 over layer thickness, which ranged from 0 – 6 nm. SE data analysis was performed vis-à-vis a multilayer optical model that included a thick silicon nitride layer. The optical constants for evaporated aluminum were initially determined using a multi-sample analysis (MSA) of SE data from MgF2 protected and bare Al surfaces. Two models were then considered for analyzing the real-time data obtained from Al/MgF2 stacks. The first used the optical constants of aluminum obtained in the MSA with two adjustable parameters: the thicknesses of the aluminum and aluminum oxide layers. The thicknesses obtained from this model showed the expected trends (increasing Al2O3 layer thickness and decreasing Al layer thickness with time), but some of the Al2O3 thicknesses were unphysical (negative). Because the optical constants of very thin metals films depend strongly on their structures and deposition conditions, a second, more advanced model was employed that fit the optical constants for Al, and also the Al and Al2O3 thicknesses, for each data set. In particular, the Al and Al2O3 thicknesses and optical constants of Al were determined in an MSA for each of 50 evenly spaced analyses in each four-hour dynamic run performed. The resulting optical constants for Al were then fixed for that sample and the thicknesses of the Al and Al2O3 layers were determined. While the first and second models yielded similar Al and Al2O3 thickness vs. time trends, the film thicknesses obtained in this manner were more physically reasonable. Thicker MgF2 layers slow the oxidation rate of aluminum. The results from this work should prove useful in protecting space mirrors prior to launch

Absorption Coefficient (ABSCO) Tables for the Orbiting Carbon Observatories: Version 5.1

The accuracy of atmospheric trace gas retrievals depends directly on the accuracy of the molecular absorption model used within the retrieval algorithm. For remote sensing of well-mixed gases, such as carbon dioxide (CO₂), where the atmospheric variability is small compared to the background, the quality of the molecular absorption model is key. Recent updates to oxygen (O₂) absorption coefficients (ABSCO) for the 0.76 μm A-band and the water vapor (H₂O) continuum model within the 1.6 μm and 2.06 μm CO₂ bands used within the Orbiting Carbon Observatory (OCO-2 and OCO-3) algorithm are described here. Updates in the O₂ A-band involve the inclusion of new laboratory measurements within multispectrum fits to improve relative consistency between O₂ line shapes and collision-induced absorption (CIA). The H₂O continuum model has been updated to MTCKD v3.2, which has benefited from information from a range of laboratory studies relative to the model utilized in the previous ABSCO version. Impacts of these spectroscopy updates have been evaluated against ground-based atmospheric spectra from the Total Carbon Column Observing Network (TCCON) and within the framework of the OCO-2 algorithm, using OCO-2 soundings covering a range of atmospheric and surface conditions. The updated absorption coefficients (ABSCO version 5.1) are found to offer improved fitting residuals and reduced biases in retrieved surface pressure relative to the previous version (ABSCO v5.0) used within B8 and B9 of the OCO-2 retrieval algorithm and have been adopted for the OCO B10 Level 2 algorithm

Absorption Coefficient (ABSCO) Tables for the Orbiting Carbon Observatories: Version 5.1

The accuracy of atmospheric trace gas retrievals depends directly on the accuracy of the molecular absorption model used within the retrieval algorithm. For remote sensing of well-mixed gases, such as carbon dioxide (CO₂), where the atmospheric variability is small compared to the background, the quality of the molecular absorption model is key. Recent updates to oxygen (O₂) absorption coefficients (ABSCO) for the 0.76 μm A-band and the water vapor (H₂O) continuum model within the 1.6 μm and 2.06 μm CO₂ bands used within the Orbiting Carbon Observatory (OCO-2 and OCO-3) algorithm are described here. Updates in the O₂ A-band involve the inclusion of new laboratory measurements within multispectrum fits to improve relative consistency between O₂ line shapes and collision-induced absorption (CIA). The H₂O continuum model has been updated to MTCKD v3.2, which has benefited from information from a range of laboratory studies relative to the model utilized in the previous ABSCO version. Impacts of these spectroscopy updates have been evaluated against ground-based atmospheric spectra from the Total Carbon Column Observing Network (TCCON) and within the framework of the OCO-2 algorithm, using OCO-2 soundings covering a range of atmospheric and surface conditions. The updated absorption coefficients (ABSCO version 5.1) are found to offer improved fitting residuals and reduced biases in retrieved surface pressure relative to the previous version (ABSCO v5.0) used within B8 and B9 of the OCO-2 retrieval algorithm and have been adopted for the OCO B10 Level 2 algorithm

Absence of Evidence Is Not Evidence of Absence: The Color-Density Relation at Fixed Stellar Mass Persists to z ~ 1

We use data drawn from the DEEP2 Galaxy Redshift Survey to investigate the relationship between local galaxy density, stellar mass, and rest-frame galaxy color. At z ~ 0.9, we find that the shape of the stellar mass function at the high-mass (log (M*/Msun) > 10.1) end depends on the local environment, with high-density regions favoring more massive systems. Accounting for this stellar mass-environment relation (i.e., working at fixed stellar mass), we find a significant color-density relation for galaxies with 10.6 < log(M*/Msun) < 11.1 and 0.75 < z < 0.95. This result is shown to be robust to variations in the sample selection and to extend to even lower masses (down to log(M*/Msun) ~ 10.4). We conclude by discussing our results in comparison to recent works in the literature, which report no significant correlation between galaxy properties and environment at fixed stellar mass for the same redshift and stellar mass domain. The non-detection of environmental dependence found in other data sets is largely attributable to their smaller samples size and lower sampling density, as well as systematic effects such as inaccurate redshifts and biased analysis techniques. Ultimately, our results based on DEEP2 data illustrate that the evolutionary state of a galaxy at z ~ 1 is not exclusively determined by the stellar mass of the galaxy. Instead, we show that local environment appears to play a distinct role in the transformation of galaxy properties at z > 1.Comment: 10 pages, 5 Figures; Accepted for publication in MNRA

Desert Research and Technology Studies (DRATS) 2010 Science Operations: Operational Approaches and Lessons Learned for Managing Science during Human Planetary Surface Missions

Desert Research and Technology Studies (Desert RATS) is a multi-year series of hardware and operations tests carried out annually in the high desert of Arizona on the San Francisco Volcanic Field. These activities are designed to exercise planetary surface hardware and operations in conditions where long-distance, multi-day roving is achievable, and they allow NASA to evaluate different mission concepts and approaches in an environment less costly and more forgiving than space.The results from the RATS tests allows election of potential operational approaches to planetary surface exploration prior to making commitments to specific flight and mission hardware development. In previous RATS operations, the Science Support Room has operated largely in an advisory role, an approach that was driven by the need to provide a loose science mission framework that would underpin the engineering tests. However, the extensive nature of the traverse operations for 2010 expanded the role of the science operations and tested specific operational approaches. Science mission operations approaches from the Apollo and Mars-Phoenix missions were merged to become the baseline for this test. Six days of traverse operations were conducted during each week of the 2-week test, with three traverse days each week conducted with voice and data communications continuously available, and three traverse days conducted with only two 1-hour communications periods per day. Within this framework, the team evaluated integrated science operations management using real-time, tactical science operations to oversee daily crew activities, and strategic level evaluations of science data and daily traverse results during a post-traverse planning shift. During continuous communications, both tactical and strategic teams were employed. On days when communications were reduced to only two communications periods per day, only a strategic team was employed. The Science Operations Team found that, if communications are good and down-linking of science data is ensured, high quality science returns is possible regardless of communications. What is absent from reduced communications is the scientific interaction between the crew on the planet and the scientists on the ground. These scientific interactions were a critical part of the science process and significantly improved mission science return over reduced communications conditions. The test also showed that the quality of science return is not measurable by simple numerical quantities but is, in fact, based on strongly non-quantifiable factors, such as the interactions between the crew and the Science Operations Teams. Although the metric evaluation data suggested some trends, there was not sufficient granularity in the data or specificity in the metrics to allow those trends to be understood on numerical data alone

The ENIGMA sports injury working group - an international collaboration to further our understanding of sport-related brain injury

Sport-related brain injury is very common, and the potential long-term effects include a wide range of neurological and psychiatric symptoms, and potentially neurodegeneration. Around the globe, researchers are conducting neuroimaging studies on primarily homogenous samples of athletes. However, neuroimaging studies are expensive and time consuming, and thus current findings from studies of sport-related brain injury are often limited by small sample sizes. Further, current studies apply a variety of neuroimaging techniques and analysis tools which limit comparability among studies. The ENIGMA Sports Injury working group aims to provide a platform for data sharing and collaborative data analysis thereby leveraging existing data and expertise. By harmonizing data from a large number of studies from around the globe, we will work towards reproducibility of previously published findings and towards addressing important research questions with regard to diagnosis, prognosis, and efficacy of treatment for sport-related brain injury. Moreover, the ENIGMA Sports Injury working group is committed to providing recommendations for future prospective data acquisition to enhance data quality and scientific rigor

Linking Symptom Inventories using Semantic Textual Similarity

An extensive library of symptom inventories has been developed over time to measure clinical symptoms, but this variety has led to several long standing issues. Most notably, results drawn from different settings and studies are not comparable, which limits reproducibility. Here, we present an artificial intelligence (AI) approach using semantic textual similarity (STS) to link symptoms and scores across previously incongruous symptom inventories. We tested the ability of four pre-trained STS models to screen thousands of symptom description pairs for related content - a challenging task typically requiring expert panels. Models were tasked to predict symptom severity across four different inventories for 6,607 participants drawn from 16 international data sources. The STS approach achieved 74.8% accuracy across five tasks, outperforming other models tested. This work suggests that incorporating contextual, semantic information can assist expert decision-making processes, yielding gains for both general and disease-specific clinical assessment

Rare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease

We identified rare coding variants associated with Alzheimer’s disease (AD) in a 3-stage case-control study of 85,133 subjects. In stage 1, 34,174 samples were genotyped using a whole-exome microarray. In stage 2, we tested associated variants (P<1×10-4) in 35,962 independent samples using de novo genotyping and imputed genotypes. In stage 3, an additional 14,997 samples were used to test the most significant stage 2 associations (P<5×10-8) using imputed genotypes. We observed 3 novel genome-wide significant (GWS) AD associated non-synonymous variants; a protective variant in PLCG2 (rs72824905/p.P522R, P=5.38×10-10, OR=0.68, MAFcases=0.0059, MAFcontrols=0.0093), a risk variant in ABI3 (rs616338/p.S209F, P=4.56×10-10, OR=1.43, MAFcases=0.011, MAFcontrols=0.008), and a novel GWS variant in TREM2 (rs143332484/p.R62H, P=1.55×10-14, OR=1.67, MAFcases=0.0143, MAFcontrols=0.0089), a known AD susceptibility gene. These protein-coding changes are in genes highly expressed in microglia and highlight an immune-related protein-protein interaction network enriched for previously identified AD risk genes. These genetic findings provide additional evidence that the microglia-mediated innate immune response contributes directly to AD development