Effects of Spatial Resolution on the Simulated Dust Aerosol Lifecycle: Implications for Dust Event Magnitude and Timing in the NASA GEOS-5 AGCM

The NASA GEOS-5 atmospheric transport model simulates global aerosol distributions with an online aerosol module. GEOS-5 may be run at various horizontal spatial resolutions depending on the research application. For example, long integration climate simulations are typically run at 2 deg or 1 deg grid spacing, whereas aerosol reanalysis and forecasting applications may be performed at O.5 deg or 0.25 deg resolutions. In this study, we assess the implications of varying spatial resolution on the simulated aerosol fields, with a particular focus on dust. Dust emissions in GEOS-5 are calculated with one of two parameterizations, one based on the Goddard Chemistry, Aerosol, Radiation, and Transport (GO CART) model and another based on the Dust Entrainment and Deposition (DEAD) model. Emission fluxes are parameterized in terms of the surface wind speed, either the 10-m (GO CART) or friction (DEAD) wind speed. We consider how surface wind speeds and thus the dust emission rates are a function of the model spatial resolution. We find that spatial resolution has a significant effect on the magnitude of dust emissions, as higher resolution versions of the model have typically higher surface wind speeds. Utilizing space-borne observations from MISR, MODIS, and CALIOP, we find that simulated Aerosol Optical Thickness (AOT) distributions respond differently to spatial resolution over the African and Asian source regions, highlighting the need to regional dust emission tuning. When compared to ground-based observations from AERONET, we found improved timing of dust events with as spatial resolution was increased. In an attempt to improve the representation of the dust aerosol lifecycle at coarse resolutions, we found that incorporating the effects of sub-grid wind variability in a course resolution simulation led to improved agreement with observed AOT magnitudes, but did not impact the timing of simulated dust events

Formation energy and interaction of point defects in two-dimensional colloidal crystals

The manipulation of individual colloidal particles using optical tweezers has allowed vacancies to be created in two-dimensional (2d) colloidal crystals, with unprecedented possibility of real-time monitoring the dynamics of such defects (Nature {\bf 413}, 147 (2001)). In this Letter, we employ molecular dynamics (MD) simulations to calculate the formation energy of single defects and the binding energy between pairs of defects in a 2d colloidal crystal. In the light of our results, experimental observations of vacancies could be explained and then compared to simulation results for the interstitial defects. We see a remarkable similarity between our results for a 2d colloidal crystal and the 2d Wigner crystal (Phys. Rev. Lett. {\bf 86}, 492 (2001)). The results show that the formation energy to create a single interstitial is $12$ lower than that of the vacancy. Because the pair binding energies of the defects are strongly attractive for short distances, the ground state should correspond to bound pairs with the interstitial bound pairs being the most probable.Comment: 5 pages, 2 figure

Equivalent Sensor Radiance Generation and Remote Sensing from Model Parameters

In this paper we describe a general procedure for calculating equivalent sensor radiances from variables output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint the algorithm takes explicit account of the model subgrid variability, in particular its description of the probably density function of total water (vapor and cloud condensate.) The equivalent sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies. We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products.) We focus on clouds and cloud/aerosol interactions, because they are very important to model development and improvement

Is sirolimus a therapeutic option for patients with progressive pulmonary lymphangioleiomyomatosis?

<p>Abstract</p> <p>Background</p> <p>Lymphangioleiomyomatosis (LAM) is a rare lung disease characterised by progressive airflow obstruction. No effective medical treatment is available but therapy with sirolimus has shown some promise. The aim of this observational study was to evaluate sirolimus in progressive LAM.</p> <p>Methods</p> <p>Sirolimus (trough level 5 - 10 ng/ml) was administered to ten female patients (42.4 ± 11.9 years) with documented progression. Serial pulmonary function tests and six-minute-walk-distance (6-MWD) assessments were performed.</p> <p>Results</p> <p>The mean loss of FEV₁was -2.30 ± 0.52 ml/day before therapy and a significant mean gain of FEV₁of 1.19 ± 0.26 ml/day was detected during treatment (p = 0.001). Mean FEV₁and FVC at baseline were 1.12 ± 0.15 l (36.1 ± 4.5%pred.) and 2.47 ± 0.25 l (69.2 ± 6.5%pred.), respectively. At three and six months during follow-up a significant increase of FEV₁and FVC was demonstrated (3 months ΔFEV₁: 220 ± 82 ml, p = 0.024; 6 months ΔFEV₁: 345 ± 58 ml, p = 0.001); (3 months ΔFVC: 360 ± 141 ml, p = 0.031; 6 months ΔFVC: 488 ± 138 ml, p = 0.006). Sirolimus was discontinued in 3 patients because of serious recurrent lower respiratory tract infection or sirolimus-induced pneumonitis. No deaths and no pneumothoraces occurred during therapy.</p> <p>Conclusions</p> <p>Our data suggest that sirolimus might be considered as a therapeutic option in rapidly declining LAM patients. However, sirolimus administration may be associated with severe respiratory adverse events requiring treatment cessation in some patients. Moreover, discontinuation of sirolimus is mandatory prior to lung transplantation.</p

Electrophysiological Correlates of Changes in Reaction Time Based on Stimulus Intensity

Background: Although reaction time is commonly used as an indicator of central nervous system integrity, little is currently understood about the mechanisms that determine processing time. In the current study, we are interested in determining the differences in electrophysiological events associated with significant changes in reaction time that could be elicited by changes in stimulus intensity. The primary objective is to assess the effect of increasing stimulus intensity on the latency and amplitude of afferent inputs to the somatosensory cortex, and their relation to reaction time. Methods: Median nerve stimulation was applied to the non-dominant hand of 12 healthy young adults at two different stimulus intensities (HIGH &amp; LOW). Participants were asked to either press a button as fast as possible with their dominant hand or remain quiet following the stimulus. Electroencephalography was used to measure somatosensory evoked potentials (SEPs) and event related potentials (ERPs). Electromyography from the flexor digitorum superficialis of the button-pressing hand was used to assess reaction time. Response time was the time of button press. Results: Reaction time and response time were significantly shorter following the HIGH intensity stimulus compared to the LOW intensity stimulus. There were no differences in SEP (N20 &amp; P24) peak latencies and peak-to-peak amplitude for the two stimulus intensities. ERPs, locked to response time, demonstrated a significantly larger pre-movement negativity to positivity following the HIGH intensity stimulus over the Cz electrode

In Vivo Imaging of Vesicular Monoamine Transporters in Human Brain Using [ 11 C]Tetrabenazine and Positron Emission Tomography

The pharmacokinetics of [ 11 CJtetrabenazine, a high-affinity radioligand for the monoamine vesicular transporter, were determined in living human brain using in vivo imaging by positron emission tomography (PET). The radiotracer showed high brain uptake and rapid washout from all brain regions with relatively slower clearance from regions of highest concentrations of monoamine vesicular transporters (striatum), resulting in clear differential visualization of these structures at short intervals after injection (10–20 min). As the first human PET imaging study of a vesicular neurotransmitter transporter, these experiments demonstrate that external imaging of vesicular transporters forms a new and valuable approach to the in vivo quantification of monoaminergic neurons, with potential application to the in vivo study of neurodegenerative disorders such as Parkinson's disease.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65743/1/j.1471-4159.1993.tb03521.x.pd

Implementing an application programming interface for PROMIS measures at three medical centers

BACKGROUND: There is an increasing body of literature advocating for the collection of patient-reported outcomes (PROs) in clinical care. Unfortunately, there are many barriers to integrating PRO measures, particularly computer adaptive tests (CATs), within electronic health records (EHRs), thereby limiting access to advances in PRO measures in clinical care settings. OBJECTIVE: To address this obstacle, we created and evaluated a software integration of an Application Programming Interface (API) service for administering and scoring Patient-Reported Outcomes Measurement Information System (PROMIS) measures with the EHR system. METHODS: We created a RESTful API and evaluated the technical feasibility and impact on clinical workflow at three academic medical centers. RESULTS: Collaborative teams (i.e., clinical, information technology [IT] and administrative staff) performed these integration efforts addressing issues such as software integration as well as impact on clinical workflow. All centers considered their implementation successful based on the high rate of completed PROMIS assessments (between January 2016 and January 2021) and minimal workflow disruptions. CONCLUSION: These case studies demonstrate not only the feasibility but also the pathway for the integration of PROMIS CATs into the EHR and routine clinical care. All sites utilized diverse teams with support and commitment from institutional leadership, initial implementation in a single clinic, a process for monitoring and optimization, and use of custom software to minimize staff burden and error

Internal Physical Features of a Land Surface Model Employing a Tangent Linear Model

The Earth's land surface, including its biomass, is an integral part of the Earth's weather and climate system. Land surface heterogeneity, such as the type and amount of vegetative covering., has a profound effect on local weather variability and therefore on regional variations of the global climate. Surface conditions affect local weather and climate through a number of mechanisms. First, they determine the re-distribution of the net radiative energy received at the surface, through the atmosphere, from the sun. A certain fraction of this energy increases the surface ground temperature, another warms the near-surface atmosphere, and the rest evaporates surface water, which in turn creates clouds and causes precipitation. Second, they determine how much rainfall and snowmelt can be stored in the soil and how much instead runs off into waterways. Finally, surface conditions influence the near-surface concentration and distribution of greenhouse gases such as carbon dioxide. The processes through which these mechanisms interact with the atmosphere can be modeled mathematically, to within some degree of uncertainty, on the basis of underlying physical principles. Such a land surface model provides predictive capability for surface variables including ground temperature, surface humidity, and soil moisture and temperature. This information is important for agriculture and industry, as well as for addressing fundamental scientific questions concerning global and local climate change. In this study we apply a methodology known as tangent linear modeling to help us understand more deeply, the behavior of the Mosaic land surface model, a model that has been developed over the past several years at NASA/GSFC. This methodology allows us to examine, directly and quantitatively, the dependence of prediction errors in land surface variables upon different vegetation conditions. The work also highlights the importance of accurate soil moisture information. Although surface variables are predicted imperfectly due to inherent uncertainties in the modeling process, our study suggests how satellite observations can be combined with the model, through land surface data assimilation, to improve their prediction