The Distributed Electrometer Chain (DCE) on the Mars 2003 Lander
The Distributed Electrometer Chain (DCE) for the Mars 2003 Lander is described.
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The Distributed Electrometer Chain (DCE) for the Mars 2003 Lander is described.
Certain enzymatic and structural features of myosin, purified from rat skeletal muscles representative of the fast twitch glycolytic (type IIb), the fast twitch oxidative (type IIa), and the slow twitch oxidative (type I) fiber, were determined and the results were compared with the measured contractile properties. Good correlation was found between the shortening velocities and Ca(2+)-activated ATPase activity for each fiber type. Short term hind limb immobilization caused prolongation of contraction time and one-half relaxation time in the fast twitch muscles and a reduction of these contractile properties in slow twitch soleus. Furthermore, the increased maximum shortening velocity in the immobilized soleus could be correlated with increased Ca(2+)-ATPase, but no change was observed in the enzymatic activity of the fast twitch muscles. No alteration in light chain distribution with disuse was observed in any of the fiber types. The myosin from slow twitch soleus could be distinguished from fast twitch myosins on the basis of the pattern of peptides generated by proteolysis of the heavy chains. Six weeks of hind limb immobilization resulted in both an increased ATPase activity and an altered heavy chain primary structure in the slow twitch soleus muscle.
The influence of chain architecture on toughness is examined by testing blends of HDPE with different types of low density PEs. The LDPE and LLDPE used have reported similar molecular weights, and densities. Two structural factors differentiate these polymers, long chain branching is peculiar to LDPE, and the short chain branching distribution of the two polymers are different. LDPE has branches which are evenly distributed among all chains. In contrast, the short chain branches in LLDPE are distributed heterogeneously. LLDPE and ULDPE have similar branch distributions but, ULDPE has a higher average number of branches per 1000 carbons and consequently a lower density. The effect which these structural differences have on mechanical properties can be used to investigate which parameters control toughness in PE materials.
Several methods for computing stationary probability distributions of Markov chains are described and compared. The main linear algebra problem consists of computing an eigenvector of a sparse, usually nonsymmetric, matrix associated with a known eigenvalue. It can also be cast as a problem of solving a homogeneous singular linear system. Several methods based on combinations of Krylov subspace techniques are presented. The performance of these methods on some realistic problems are compared.
Projection methods for computing stationary probability distributions for Markov chain models are presented. A general projection method is a method which seeks an approximation from a subspace of small dimension to the original problem. Thus, the original matrix problem of size N is approximated by one of dimension m, typically much smaller than N. A particularly successful class of methods based on this principle is that of Krylov subspace methods which utilize subspaces of the form span(v,av,...,A(exp m-1)v). These methods are effective in solving linear systems and eigenvalue problems (Lanczos, Arnoldi,...) as well as nonlinear equations. They can be combined with more traditional iterative methods such as successive overrelaxation, symmetric successive overrelaxation, or with incomplete factorization methods to enhance convergence.
Information-theoretic concepts in theory of random graphs - entropy functions for probability distributions and Markov chains
Deployable subsystems are essential to mission success of most spacecraft. These subsystems enable critical functions including power, communications and thermal control. The loss of any of these functions will generally result in loss of the mission. These subsystems and their components often consist of unique designs and applications for which various standardized data sources are not applicable for estimating reliability and for assessing risks. In this study, a two stage sequential Bayesian framework for reliability estimation of spacecraft deployment was developed for this purpose. This process was then applied to the James Webb Space Telescope (JWST) Sunshield subsystem, a unique design intended for thermal control of the Optical Telescope Element. Initially, detailed studies of NASA deployment history, "heritage information", were conducted, extending over 45 years of spacecraft launches. This information was then coupled to a non-informative prior and a binomial likelihood function to create a posterior distribution for deployments of various subsystems uSing Monte Carlo Markov Chain sampling. Select distributions were then coupled to a subsequent analysis, using test data and anomaly occurrences on successive ground test deployments of scale model test articles of JWST hardware, to update the NASA heritage data. This allowed for a realistic prediction for the reliability of the complex Sunshield deployment, with credibility limits, within this two stage Bayesian framework.
Amino acids changes distribution in specificity regions of light polypeptide chains of immunoglobulins showing correspondence with Poisson distribution
Electron paramagnetic resonance (EPR) techniques are used to determine the number of free radicals produced during deformation leading to fracture of nylon 6 fibers. A reaction rate molecular model is proposed to explain some of the deformation and bond rupture behavior leading to fracture. High-strength polymer fibers are assumed to consist of a sandwich structure of disordered and ordered regions along the fiber axis. In the disordered or critical flaw regions, tie chains connecting the ordered or crystalline block regions are assumed to have a statistical distribution in length. These chains are, therefore, subjected to different stresses. The effective length distribution was determined by EPR. The probability of bond rupture was assumed to be controlled by reaction-rate theory with a stress-aided activation energy and behavior of various loadings determined by numerical techniques. The model is successfully correlated with experimental stress, strain, and bond rupture results for creep, constant rate loadings, cyclic stress, stress relaxation and step strain tests at room temperature.
Petri nets augmented with timing specifications gained a wide acceptance in the area of performance and reliability evaluation of complex systems exhibiting concurrency, synchronization, and conflicts. The state space of time-extended Petri nets is mapped onto its basic underlying stochastic process, which can be shown to be Markovian under the assumption of exponentially distributed firing times. The integration of exponentially and non-exponentially distributed timing is still one of the major problems for the analysis and was first attacked for continuous time Petri nets at the cost of structural or analytical restrictions. We propose a discrete deterministic and stochastic Petri net (DDSPN) formalism with no imposed structural or analytical restrictions where transitions can fire either in zero time or according to arbitrary firing times that can be represented as the time to absorption in a finite absorbing discrete time Markov chain (DTMC). Exponentially distributed firing times are then approximated arbitrarily well by geometric distributions. Deterministic firing times are a special case of the geometric distribution. The underlying stochastic process of a DDSPN is then also a DTMC, from which the transient and stationary solution can be obtained by standard techniques. A comprehensive algorithm and some state space reduction techniques for the analysis of DDSPNs are presented comprising the automatic detection of conflicts and confusions, which removes a major obstacle for the analysis of discrete time models.
Stochastic control of diffusion processes, optimal linear filtering and prediction, and optimization of control for Markov chains
Kinetic theory of fracture initiation, discussing changes in relative orientation distribution of network chains
Cyclic species in the interstellar medium have been searched for almost since the first detection of interstellar polyatomic molecules. Eleven different C3H2 rotational transitions were detected; 9 of which were studied in TMC-1, a nearby dark dust cloud, are shown. The 1 sub 10 yields 1 sub 01 and 2 sub 20 yields 2 sub 11 transitions were observed with the 43 m NRAO telescope, while the remaining transitions were detected with the 14 m antenna of the Five College Radio Observatory (FCRAO). The lines detected in TMC-1 have energies above the ground state ranging from 0.9 to 17.1 K and consist of both ortho and para species. Limited maps were made along the ridge for several of the transitions. The HC3N J = 2 yields 1 transition were mapped simultaneously with the C3H2 1 sub 10 yields 1 sub 01 line and therefore can compare the distribution of this ring with a carbon chain in TMC-1. C3H2 is distributed along a narrow ridge with a SE - NW extension which is slightly more extended than the HC2N J = 2 yields 1. Gaussian fits gives a FWHP extension of 8'5 for C3H2 while HC3N has a FWHP of 7'. The data show variations of the two velocity components along the ridge as a function of transition. Most of the transitions show a peak at the position of strongest HC3N emission while the 2 sub 21 yields 2 sub 10 transition shows a peak at the NH3 position.
The organic compositions of carbonaceous chondrite meteorites have been extensively studied; however, there have been fewer reports of other meteorite classes, and almost none from iron meteorites, which contain much less carbon than carbonaceous chondrites but make up ~4% of observed meteorite falls. Here, we report the bulk amino acid content of three iron meteorites (Campo del Cielo, IAB; Canyon Diablo, IAB; and Cape York, IIIAB) and both the metal and silicate portions of a pallasite (Imilac). We developed a novel method to prepare the samples for analysis, followed by hot water extraction and analysis via liquid chromatography‐mass spectrometry. Free amino acid abundances ranging from 301 to 1216 pmol/g were observed in the meteorites, with the highest abundance in the silicate portion of the pallasite. Although some of the amino acid content could be attributed to terrestrial contamination, evidence suggests that some compounds are indigenous. A suite of C(5) amino acids was observed with a distinct distribution favoring a straight chain (n‐pentanoic acid) structure; this straight chain dominance is suggestive of that observed in thermally altered stony meteorites. Amino acids were also observed in terrestrial iron granules that were milled and analyzed in the same way as the meteorites, although the distribution of detected amino acids was different. It is possible that similar formation mechanisms existed in both the meteorites and the terrestrial iron, or that observed amino acids resulted from reactions of precursors during sample preparation. This work suggests that iron meteorites should not be overlooked for contributions of amino acids and likely other soluble organic molecules to the early Earth. Future studies of iron–nickel meteorites and asteroids, such as Psyche, may provide further insights into their potential organic inventory.
Comparison of monte carlo, percus-yevick integral equations and convolution-hypernetted-chain methods for computing radial distribution functions of gaussian model
Gravitational wave detectors in the mHz band (such as the Laser Interferometer Space Antenna, or LISA) will observe thousands of compact binaries in the galaxy which can be used to better understand the structure of the Milky Way. To test the effectiveness of LISA to measure the distribution of the galaxy, we simulated the Close White Dwarf Binary (CWDB) gravitational wave sky using different models for the Milky Way. To do so, we have developed a galaxy density distribution modeling code based on the Markov Chain Monte Carlo method. The code uses different distributions to construct realizations of the galaxy. We then use the Fisher Information Matrix to estimate the variance and covariance of the recovered parameters for each detected CWDB. This is the first step toward characterizing the capabilities of space-based gravitational wave detectors to constrain models for galactic structure, such as the size and orientation of the bar in the center of the Milky Way
This work presents a computationally-ecient approach for damage determination that quanti es uncertainty in the provided diagnosis. Given strain sensor data that are polluted with measurement errors, Bayesian inference is used to estimate the location, size, and orientation of damage. This approach uses Bayes' Theorem to combine any prior knowledge an analyst may have about the nature of the damage with information provided implicitly by the strain sensor data to form a posterior probability distribution over possible damage states. The unknown damage parameters are then estimated based on samples drawn numerically from this distribution using a Markov Chain Monte Carlo (MCMC) sampling algorithm. Several modi cations are made to the traditional Bayesian inference approach to provide signi cant computational speedup. First, an ecient surrogate model is constructed using sparse grid interpolation to replace a costly nite element model that must otherwise be evaluated for each sample drawn with MCMC. Next, the standard Bayesian posterior distribution is modi ed using a weighted likelihood formulation, which is shown to improve the convergence of the sampling process. Finally, a robust MCMC algorithm, Delayed Rejection Adaptive Metropolis (DRAM), is adopted to sample the probability distribution more eciently. Numerical examples demonstrate that the proposed framework e ectively provides damage estimates with uncertainty quanti cation and can yield orders of magnitude speedup over standard Bayesian approaches.
The effects of 1, 2, and 3 wk of hindlimb suspension (HS) on force-velocity and power characteristics of single rat soleus fibers were determined. After 1, 2, or 3 wk of HA, small fiber bundles were isolated, placed in skinning solution, and stored at -20 C until studied. Single fibers were isolated and placed between a motor arm and force transducer, functional properties were studied, and fiber protein content was subsequently analyzed by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). Additional fibers were isolated from soleus of control after 1 and 3 wk of HS, and fiber type distribution and myosin light chain stoichiometry were determined from SDS-PAGE analysis. After 1 wk of HS, percent type I fibers declined from 82 to 74%, whereas hybrid fibers increased from 10 to 18%. Percent fast type II fibers increased from 8% in control and 1 wk of HS to 26% by 3 wk of HS. Most fibers showed an increased unloaded maximal shortening velocity (V sub O)), but myosin heavy chain remained entirely slow type I. The mechanism for increased V(sub O) is unknown. There was a progressive decrease in fiber diameter and peak force after 1, 2, and 3 wk of HS, respectively. One week of HS resulted in a shift of the force-velocity curve, and between 2 and 3 wk of HS the curve shifted further such that V(sub O) was higher than control at all relative loads less than 45% peak isometric force. Peak absolute power output of soleus fibers progressively decreased through 2 wk of HS but showed no further change at 3 wk. The results suggest that between 2 and 3 wk the HS-induced alterations in the force-velocity relationship act to maintain the power output of single soleus fibers despite a continued reduction in fiber force.