NASA Flight Planning Branch Space Shuttle Lessons Learned

Planning products and procedures that allowed the mission Flight Control Teams and the Astronaut crews to plan, train and fly every Space Shuttle mission were developed by the Flight Planning Branch at the NASA Johnson Space Center in Houston, Texas. As the Space Shuttle Program came to a close, lessons learned were collected from each phase of the successful execution of these Space Shuttle missions. Specific examples of how roles and responsibilities of console positions that develop the crew and vehicle attitude timelines have been analyzed and will be discussed. Additionally, the relationships and procedural hurdles experienced through international collaboration have molded operations. These facets will be explored and related to current and future operations with the International Space Station and future vehicles. Along with these important aspects, the evolution of technology and continual improvement of data transfer tools between the Space Shuttle and ground team has also defined specific lessons used in improving the control team s effectiveness. Methodologies to communicate and transmit messages, images, and files from the Mission Control Center to the Orbiter evolved over several years. These lessons were vital in shaping the effectiveness of safe and successful mission planning and have been applied to current mission planning work in addition to being incorporated into future space flight planning. The critical lessons from all aspects of previous plan, train, and fly phases of Space Shuttle flight missions are not only documented in this paper, but are also discussed regarding how they pertain to changes in process and consideration for future space flight planning

DDR2 controls breast tumor stiffness and metastasis by regulating integrin mediated mechanotransduction in CAFs

Biomechanical changes in the tumor microenvironment influence tumor progression and metastases. Collagen content and fiber organization within the tumor stroma are major contributors to biomechanical changes (e., tumor stiffness) and correlated with tumor aggressiveness and outcome. What signals and in what cells control collagen organization within the tumors, and how, is not fully understood. We show in mouse breast tumors that the action of the collagen receptor DDR2 in CAFs controls tumor stiffness by reorganizing collagen fibers specifically at the tumor-stromal boundary. These changes were associated with lung metastases. The action of DDR2 in mouse and human CAFs, and tumors in vivo, was found to influence mechanotransduction by controlling full collagen-binding integrin activation via Rap1-mediated Talin1 and Kindlin2 recruitment. The action of DDR2 in tumor CAFs is thus critical for remodeling collagen fibers at the tumor-stromal boundary to generate a physically permissive tumor microenvironment for tumor cell invasion and metastases

Form factor for a family of quantum graphs: An expansion to third order

For certain types of quantum graphs we show that the random-matrix form factor can be recovered to at least third order in the scaled time $\tau$ from periodic-orbit theory. We consider the contributions from pairs of periodic orbits represented by diagrams with up to two self-intersections connected by up to four arcs and explain why all other diagrams are expected to give higher-order corrections only. For a large family of graphs with ergodic classical dynamics the diagrams that exist in the absence of time-reversal symmetry sum to zero. The mechanism for this cancellation is rather general which suggests that it may also apply at higher-orders in the expansion. This expectation is in full agreement with the fact that in this case the linear-$\tau$ contribution, the diagonal approximation, already reproduces the random-matrix form factor for $\tau<1$. For systems with time-reversal symmetry there are more diagrams which contribute at third order. We sum these contributions for quantum graphs with uniformly hyperbolic dynamics, obtaining $+2\tau^{3}$, in agreement with random-matrix theory. As in the previous calculation of the leading-order correction to the diagonal approximation we find that the third order contribution can be attributed to exceptional orbits representing the intersection of diagram classes.Comment: 23 pages (including 4 fig.) - numerous typos correcte

Form factor for large quantum graphs: evaluating orbits with time-reversal

It has been shown that for a certain special type of quantum graphs the random-matrix form factor can be recovered to at least third order in the scaled time \tau using periodic-orbit theory. Two types of contributing pairs of orbits were identified, those which require time-reversal symmetry and those which do not. We present a new technique of dealing with contribution from the former type of orbits. The technique allows us to derive the third order term of the expansion for general graphs. Although the derivation is rather technical, the advantages of the technique are obvious: it makes the derivation tractable, it identifies explicitly the orbit configurations which give the correct contribution, it is more algorithmical and more system-independent, making possible future applications of the technique to systems other than quantum graphs.Comment: 25 pages, 14 figures, accepted to Waves in Random Media (special issue on Quantum Graphs and their Applications). Fixed typos, removed an overly restrictive condition (appendix), shortened introductory section

Targeting the Transforming Growth Factor-β pathway inhibits human basal-like breast cancer metastasis

<p>Abstract</p> <p>Background</p> <p>Transforming Growth Factor β (TGF-β) plays an important role in tumor invasion and metastasis. We set out to investigate the possible clinical utility of TGF-β antagonists in a human metastatic basal-like breast cancer model. We examined the effects of two types of the TGF-β pathway antagonists (1D11, a mouse monoclonal pan-TGF-β neutralizing antibody and LY2109761, a chemical inhibitor of TGF-β type I and II receptor kinases) on sublines of basal cell-like MDA-MB-231 human breast carcinoma cells that preferentially metastasize to lungs (4175TR, 4173) or bones (SCP2TR, SCP25TR, 2860TR, 3847TR).</p> <p>Results</p> <p>Both 1D11 and LY2109761 effectively blocked TGF-β-induced phosphorylation of receptor-associated Smads in all MDA-MB-231 subclones <it>in vitro</it>. Moreover, both antagonists inhibited TGF-β stimulated <it>in vitro </it>migration and invasiveness of MDA-MB-231 subclones, indicating that these processes are partly driven by TGF-β. In addition, both antagonists significantly reduced the metastatic burden to either lungs or bones <it>in vivo</it>, seemingly independently of intrinsic differences between the individual tumor cell clones. Besides inhibiting metastasis in a tumor cell autonomous manner, the TGF-β antagonists inhibited angiogenesis associated with lung metastases and osteoclast number and activity associated with lytic bone metastases. In aggregate, these studies support the notion that TGF-β plays an important role in both bone-and lung metastases of basal-like breast cancer, and that inhibiting TGF-β signaling results in a therapeutic effect independently of the tissue-tropism of the metastatic cells. Targeting the TGF-β pathway holds promise as a novel therapeutic approach for metastatic basal-like breast cancer.</p> <p>Conclusions</p> <p>In aggregate, these studies support the notion that TGF-β plays an important role in both bone-and lung metastases of basal-like breast cancer, and that inhibiting TGF-β signaling results in a therapeutic effect independently of the tissue-tropism of the metastatic cells. Targeting the TGF-β pathway holds promise as a novel therapeutic approach for metastatic basal-like breast cancer.</p

A Model for (Quasi-)Periodic Multiwavelength Photometric Variability in Young Stellar Objects

We present radiation transfer models of rotating young stellar objects (YSOs) with hotspots in their atmospheres, inner disk warps and other 3-D effects in the nearby circumstellar environment. Our models are based on the geometry expected from the magneto-accretion theory, where material moving inward in the disk flows along magnetic field lines to the star and creates stellar hotspots upon impact. Due to rotation of the star and magnetosphere, the disk is variably illuminated. We compare our model light curves to data from the Spitzer YSOVAR project (Morales-Calderon et al. 2014, Cody et al. 2014) to determine if these processes can explain the variability observed at optical and mid-infrared wavelengths in young stars. We focus on those variables exhibiting "dipper" behavior that may be periodic, quasi-periodic, or aperiodic. We find that the stellar hotspot size and temperature affects the optical and near-infrared light curves, while the shape and vertical extent of the inner disk warp affects the mid-IR light curve variations. Clumpy disk distributions with non-uniform fractal density structure produce more stochastic light curves. We conclude that the magneto-accretion theory is consistent with certain aspects of the multi-wavelength photometric variability exhibited by low-mass YSOs. More detailed modeling of individual sources can be used to better determine the stellar hotspot and inner disk geometries of particular sources.Comment: Accepted to Ap

PNNL: A Supervised Maximum Entropy Approach to Word Sense Disambiguation

In this paper, we described the PNNL Word Sense Disambiguation system as applied to the English All-Word task in Se-mEval 2007. We use a supervised learning approach, employing a large number of features and using Information Gain for dimension reduction. Our Maximum Entropy approach combined with a rich set of features produced results that are significantly better than baseline and are the highest F-score for the fined-grained English All-Words subtask

The BLAST Survey of the Vela Molecular Cloud: Physical Properties of the Dense Cores in Vela-D

The Balloon-borne Large-Aperture Submillimeter Telescope (BLAST) carried out a 250, 350 and 500 micron survey of the galactic plane encompassing the Vela Molecular Ridge, with the primary goal of identifying the coldest dense cores possibly associated with the earliest stages of star formation. Here we present the results from observations of the Vela-D region, covering about 4 square degrees, in which we find 141 BLAST cores. We exploit existing data taken with the Spitzer MIPS, IRAC and SEST-SIMBA instruments to constrain their (single-temperature) spectral energy distributions, assuming a dust emissivity index beta = 2.0. This combination of data allows us to determine the temperature, luminosity and mass of each BLAST core, and also enables us to separate starless from proto-stellar sources. We also analyze the effects that the uncertainties on the derived physical parameters of the individual sources have on the overall physical properties of starless and proto-stellar cores, and we find that there appear to be a smooth transition from the pre- to the proto-stellar phase. In particular, for proto-stellar cores we find a correlation between the MIPS24 flux, associated with the central protostar, and the temperature of the dust envelope. We also find that the core mass function of the Vela-D cores has a slope consistent with other similar (sub)millimeter surveys.Comment: Accepted for publication in the Astrophysical Journal. Data and maps are available at http://blastexperiment.info

Ontological Annotation with WordNet

Semantic Web applications require robust and accurate annotation tools that are capable of automating the assignment of ontological classes to words in naturally occurring text (ontological annotation). Most current ontologies do not include rich lexical databases and are therefore not easily integrated with word sense disambiguation algorithms that are needed to automate ontological annotation. WordNet provides a potentially ideal solution to this problem as it offers a highly structured lexical conceptual representation that has been extensively used to develop word sense disambiguation algorithms. However, WordNet has not been designed as an ontology, and while it can be easily turned into one, the result of doing this would present users with serious practical limitations due to the great number of concepts (synonym sets) it contains. Moreover, mapping WordNet to an existing ontology may be difficult and requires substantial labor. We propose to overcome these limitations by developing an analytical platform that (1) provides a WordNet-based ontology offering a manageable and yet comprehensive set of concept classes, (2) leverages the lexical richness of WordNet to give an extensive characterization of concept class in terms of lexical instances, and (3) integrates a class recognition algorithm that automates the assignment of concept classes to words in naturally occurring text. The ensuing framework makes available an ontological annotation platform that can be effectively integrated with intelligence analysis systems to facilitate evidence marshaling and sustain the creation and validation of inference models