Laboratory Simulations of the Titan Surface to Elucidate the Huygens Probe GCMS Observations

The Cassini/Huygens mission has vastly increased the information we have available to stndy Satnro's moon Titan. The complete mission has included an array of observational methods including remote sensing techniques, upper atmosphere in-situ saropling, and the descent of the Huygens probe directly through the atmosphere to the surface [1,2]. The instruments on the Huygens probe remain the ouly source of in-situ measurements at the surface of Titan, and work evaluating these measurements to create a pict.rre of the surface environment is ongoing. In particular, the Gas Chromatograph Mass Spectrometer (GCMS) experiment on Huygens found that although there were no heavy hydrocarbons detected in the lower atmosphere, a rich spectrum of mass peaks arose once the probe landed on the surface [3,4], However, to date it has not been possible to extract the identity and abundances of the many minor components of the spectra due to a lack of temperatnre- and instrumentappropriate data for the relevant species. We are performing laboratory stndies designed to elucidate the spectrum collected on Titan's surface, utilizing a cryogenic charober maintained at appropriate temperature and pressure conditions. The experiments will simulate the temperatnre rise experienced by the surface, which led to an enhanced signal of volatiles detected by the Huygens GCMS. The objective of this study is to exaroine the characteristics of various surface analogs as measured by the Huygens GCMS flight spare instrument, which is currently housed in our laboratory at NASA Goddard Space Flight Center (GSFC). This identification cannot be adequately accomplished through theoretical work alone since the thermodynamic properties of many species at these temperatnres (94 K, HASI measurement [5]) are not known

Calibration of the Quadrupole Mass Spectrometer of the Sample Analysis at Mars Instrument Suite

The SAM suite of instruments on the "Curiosity" Rover of the Mars Science Laboratory (MSL) is designed to provide chemical and isotopic analysis of organic and inorganic volatiles for both atmospheric and solid samples. The mission of the MSL investigations is to advance beyond the successful search for aqueous transformation in surface environments at Mars toward a quantitative assessment of habitability and preservation through a series of chemical and geological measurements. The SAM suite was delivered in December 2010 (Figure 1) to the Jet Propulsion Laboratory for integration into the Curiosity Rover. We previously outlined the range of SAM solid and gas calibrations implemented or planned and here we discuss a specific set of calibration experiments to establish the response of the SAM Quadrupole Mass Spectrometer (QMS) to the four most abundant gases in the Martian atmosphere CO2, N2, Ar, and O2, A full SAM instrument description and calibration report is presently in preparation

The Composition of Titan's Lower Atmosphere and Simple Surface Volatiles as Measured by the Cassini-Huygens Probe Gas Chromatograph Mass Spectrometer Experiment

The Cassini-Huygens Probe Gas Chromatograph Mass Spectrometer (GCMS) determined the composition of the Titan atmosphere from ~140km altitude to the surface. After landing, it returned composition data of gases evaporated from the surface. Height profiles of molecular nitrogen (N2), methane (CH4) and molecular hydrogen (H2) were determined. Traces were detected on the surface of evaporating methane, ethane (C2H6), acetylene (C2H2), cyanogen (C2N2) and carbon dioxide (CO2). The methane data showed evidence that methane precipitation occurred recently. The methane mole fraction was (1.48+/-0.09) x 10(exp -2) in the lower stratosphere (139.8 km to 75.5 km) and (5.65+/-0.18) x 10(exp -2) near the surface (6.7 km to the surface). The molecular hydrogen mole fraction was (1.01+/-0.16) x 10(exp -3) in the atmosphere and (9.90+/-0.17) x 10(exp -4) on the surface. Isotope ratios were 167.7+/-0.6 for N-14/N-15 in molecular nitrogen, 91.1+/-1.4 for C-12/C-13 in methane and (1.35+/-0.30) x 10(exp -4) for D/H in molecular hydrogen. The mole fractions of Ar-36 and radiogenic Ar-40 are (2.1+/-0.8) x 10(exp -7) and (3.39 +/-0.12) x 10(exp -5) respectively. Ne-22 has been tentatively identified at a mole fraction of (2.8+/-2.1) x 10(exp -7) Krypton and xenon were below the detection threshold of 1 x 10(exp -8) mole fraction. Science data were not retrieved from the gas chromatograph subsystem as the abundance of the organic trace gases in the atmosphere and on the ground did not reach the detection threshold. Results previously published from the GCMS experiment are superseded by this publication

Prognostic Significance of Growth Kinetics in Newly Diagnosed Glioblastomas Revealed by Combining Serial Imaging with a Novel Biomathematical Model

Glioblastomas (GBMs) are the most aggressive primary brain tumors characterized by their rapid proliferation and diffuse infiltration of the brain tissue. Survival patterns in patients with GBM have been associated with a number of clinico-pathologic factors, including age and neurological status, yet a significant quantitative link to in vivo growth kinetics of each glioma has remained elusive. Exploiting a recently developed tool for quantifying glioma net proliferation and invasion rates in individual patients using routinely available magnetic resonance images (MRIs), we propose to link these patient-specific kinetic rates of biological aggressiveness to prognostic significance. Using our biologically-based mathematical model for glioma growth and invasion, examination of serial pre-treatment MRIs of 32 GBM patients allowed quantification of these rates for each patient’s tumor. Survival analyses revealed that even when controlling for standard clinical parameters (e.g., age, KPS) these model-defined parameters quantifying biologically aggressiveness (net proliferation and invasion rates) were significantly associated with prognosis. One hypothesis generated was that the ratio of the actual survival time after whatever therapies were employed to the duration of survival predicted (by the model) without any therapy would provide a “Therapeutic Response Index” (TRI) of the overall effectiveness of the therapies. The TRI may provided important information, not otherwise available, as to the effectiveness of the treatments in individual patients. To our knowledge, this is the first report indicating that dynamic insight from routinely obtained pre-treatment imaging may be quantitatively useful in characterizing survival of individual patients with GBM. Such a hybrid tool bridging mathematical modeling and clinical imaging may allow for statifying patients for clinical studies relative to their pretreatment biological aggressiveness

The abundances of constituents of Titan's atmosphere from the GCMS instrument on the Huygens probe

Saturn's largest moon, Titan, remains an enigma, explored only by remote sensing from Earth, and by the Voyager and Cassini spacecraft. The most puzzling aspects include the origin of the molecular nitrogen and methane in its atmosphere, and the mechanism(s) by which methane is maintained in the face of rapid destruction by photolysis. The Huygens probe, launched from the Cassini spacecraft, has made the first direct observations of the satellite's surface and lower atmosphere. Here we report direct atmospheric measurements from the Gas Chromatograph Mass Spectrometer (GCMS), including altitude profiles of the constituents, isotopic ratios and trace species ( including organic compounds). The primary constituents were confirmed to be nitrogen and methane. Noble gases other than argon were not detected. The argon includes primordial Ar-36, and the radiogenic isotope Ar-40, providing an important constraint on the outgassing history of Titan. Trace organic species, including cyanogen and ethane, were found in surface measurements.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62703/1/nature04122.pd

Laser vision : lidar as a transformative tool to advance critical zone science

© The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Hydrology and Earth System Sciences 19 (2015): 2881-2897, doi:10.5194/hess-19-2881-2015.Observation and quantification of the Earth's surface is undergoing a revolutionary change due to the increased spatial resolution and extent afforded by light detection and ranging (lidar) technology. As a consequence, lidar-derived information has led to fundamental discoveries within the individual disciplines of geomorphology, hydrology, and ecology. These disciplines form the cornerstones of critical zone (CZ) science, where researchers study how interactions among the geosphere, hydrosphere, and biosphere shape and maintain the "zone of life", which extends from the top of unweathered bedrock to the top of the vegetation canopy. Fundamental to CZ science is the development of transdisciplinary theories and tools that transcend disciplines and inform other's work, capture new levels of complexity, and create new intellectual outcomes and spaces. Researchers are just beginning to use lidar data sets to answer synergistic, transdisciplinary questions in CZ science, such as how CZ processes co-evolve over long timescales and interact over shorter timescales to create thresholds, shifts in states and fluxes of water, energy, and carbon. The objective of this review is to elucidate the transformative potential of lidar for CZ science to simultaneously allow for quantification of topographic, vegetative, and hydrological processes. A review of 147 peer-reviewed lidar studies highlights a lack of lidar applications for CZ studies as 38 % of the studies were focused in geomorphology, 18 % in hydrology, 32 % in ecology, and the remaining 12 % had an interdisciplinary focus. A handful of exemplar transdisciplinary studies demonstrate lidar data sets that are well-integrated with other observations can lead to fundamental advances in CZ science, such as identification of feedbacks between hydrological and ecological processes over hillslope scales and the synergistic co-evolution of landscape-scale CZ structure due to interactions amongst carbon, energy, and water cycles. We propose that using lidar to its full potential will require numerous advances, including new and more powerful open-source processing tools, exploiting new lidar acquisition technologies, and improved integration with physically based models and complementary in situ and remote-sensing observations. We provide a 5-year vision that advocates for the expanded use of lidar data sets and highlights subsequent potential to advance the state of CZ science.The workshop forming the impetus for this paper was funded by the National Science Foundation (EAR 1406031). Additional funding for the workshop and planning was provided to S. W. Lyon by the Swedish Foundation for International Cooperation in Research and Higher Education (STINT grant no. 2013-5261). A. A. Harpold was supported by an NSF fellowship (EAR 1144894)

Curiosity's Sample Analysis at Mars (SAM) Investigation: Overview of Results from the First 120 Sols on Mars

During the first 120 sols of Curiosity s landed mission on Mars (8/6/2012 to 12/7/2012) SAM sampled the atmosphere 9 times and an eolian bedform named Rocknest 4 times. The atmospheric experiments utilized SAM s quadrupole mass spectrometer (QMS) and tunable laser spectrometer (TLS) while the solid sample experiments also utilized the gas chromatograph (GC). Although a number of core experiments were pre-programmed and stored in EEProm, a high level SAM scripting language enabled the team to optimize experiments based on prior runs

Mathematical Modeling of Human Glioma Growth Based on Brain Topological Structures: Study of Two Clinical Cases

Gliomas are the most common primary brain tumors and yet almost incurable due mainly to their great invasion capability. This represents a challenge to present clinical oncology. Here, we introduce a mathematical model aiming to improve tumor spreading capability definition. The model consists in a time dependent reaction-diffusion equation in a three-dimensional spatial domain that distinguishes between different brain topological structures. The model uses a series of digitized images from brain slices covering the whole human brain. The Talairach atlas included in the model describes brain structures at different levels. Also, the inclusion of the Brodmann areas allows prediction of the brain functions affected during tumor evolution and the estimation of correlated symptoms. The model is solved numerically using patient-specific parametrization and finite differences. Simulations consider an initial state with cellular proliferation alone (benign tumor), and an advanced state when infiltration starts (malign tumor). Survival time is estimated on the basis of tumor size and location. The model is used to predict tumor evolution in two clinical cases. In the first case, predictions show that real infiltrative areas are underestimated by current diagnostic imaging. In the second case, tumor spreading predictions were shown to be more accurate than those derived from previous models in the literature. Our results suggest that the inclusion of differential migration in glioma growth models constitutes another step towards a better prediction of tumor infiltration at the moment of surgical or radiosurgical target definition. Also, the addition of physiological/psychological considerations to classical anatomical models will provide a better and integral understanding of the patient disease at the moment of deciding therapeutic options, taking into account not only survival but also life quality