IGDS/TRAP Interface Program (ITIP). Detailed Design Specification (DDS)

The software modules which comprise the IGDS/TRAP Interface Program are described. A hierarchical input processing output (HIPO) chart for each user command is given. The description consists of: (1) function of the user command; (2) calling sequence; (3) moduls which call this use command; (4) modules called by this user command; (5) IGDS commands used by this user command; and (6) local usage of global registers. Each HIPO contains the principal functions performed within the module. Also included with each function are a list of the inputs which may be required to perform the function and a list of the outputs which may be created as a result of performing the function

Type Ia Supernovae, Evolution, and the Cosmological Constant

We explore the possible role of evolution in the analysis of data on SNe Ia at cosmological distances. First, using a variety of simple sleuthing techniques, we find evidence that the properties of the high and low redshift SNe Ia observed so far differ from one another. Next, we examine the effects of including simple phenomenological models for evolution in the analysis. The result is that cosmological models and evolution are highly degenerate with one another, so that the incorporation of even very simple models for evolution makes it virtually impossible to pin down the values of $\Omega_M$ and $\Omega_\Lambda$, the density parameters for nonrelativistic matter and for the cosmological constant, respectively. Moreover, we show that if SNe Ia evolve with time, but evolution is neglected in analyzing data, then, given enough SNe Ia, the analysis hones in on values of $\Omega_M$ and $\Omega_\Lambda$ which are incorrect. Using Bayesian methods, we show that the probability that the cosmological constant is nonzero (rather than zero) is unchanged by the SNe Ia data when one accounts for the possibility of evolution, provided that we do not discriminate among open, closed and flat cosmologies a priori. The case for nonzero cosmological constant is stronger if the Universe is presumed to be flat, but still depends sensitively on the degree to which the peak luminosities of SNe Ia evolve as a function of redshift. The estimated value of $H_0$, however, is only negligibly affected by accounting for possible evolution.Comment: 45 pages, 15 figures; accepted for publication in The Astrophysical Journal. Minor revisions and clarifications made including addition of recent reference

Epileptic high-frequency network activity in a model of non-lesional temporal lobe epilepsy

High-frequency cortical activity, particularly in the 250–600 Hz (fast ripple) band, has been implicated in playing a crucial role in epileptogenesis and seizure generation. Fast ripples are highly specific for the seizure initiation zone. However, evidence for the association of fast ripples with epileptic foci depends on animal models and human cases with substantial lesions in the form of hippocampal sclerosis, which suggests that neuronal loss may be required for fast ripples. In the present work, we tested whether cell loss is a necessary prerequisite for the generation of fast ripples, using a non-lesional model of temporal lobe epilepsy that lacks hippocampal sclerosis. The model is induced by unilateral intrahippocampal injection of tetanus toxin. Recordings from the hippocampi of freely-moving epileptic rats revealed high-frequency activity (4100 Hz), including fast ripples. High-frequency activity was present both during interictal discharges and seizure onset. Interictal fast ripples proved a significantly more reliable marker of the primary epileptogenic zone than the presence of either interictal discharges or ripples (100–250 Hz). These results suggest that fast ripple activity should be considered for its potential value in the pre-surgical workup of non-lesional temporal lobe epilepsy

PIE - the protein inference engine

Posttranslational modifications are vital to protein function but are hard to study, especially since several modification isoforms may be present simultaneously. Mass spectrometers are a great tool for investigating modified proteins, but the data they generate are often incomplete, ambiguous, and difficult to interpret. Combining data from multiple experimental techniques provides complementary information. Having both top-down (intact protein mass data) and bottom-up (peptide data) is especially valuable. In the context of background knowledge, combined data is used by human experts to interpret what modifications are present and where they are located. However, this process is arduous and for high-throughput applications needs to be automated. To explore a data integration methodology based on Markov chain Monte Carlo and simulated annealing, I developed the PIE (Protein Inference Engine). This java application integrates information using a modular approach which allows different types of data to be considered simultaneously and for new data types to be added as needed. Validation of the PIE was carried out using two realistically imperfect theoretical data sets. The first, based on the L7/L12 ribosomal protein, tested the limits of PIEs performance as intact mass accuracy and peptide coverage decreases. The second set, based on a mix of two modification variants of the H23c Histone protein, tested PIEs ability to handle isoform mixtures and up to eight simultaneous modifications. The PIE was then applied to analysis of experimental data from an investigation of the modification state of the L7/L12 ribosomal protein. This data consisted of a set of peptides identified as associated with some L7/L12 modification variant and nine intact masses measurements identified as an L7/ L12 modification variant. From this data, PIE was able to make consistent predictions, comparable to expert manual interpretation. Software, source code, user manuals, and demo projects replicating the analyses described in the following can be downloaded from http://pie.giddingslab.org/

Nonlinear Marine Structures With Random Excitation

Introduction Some of the classical nonlinear and time-varying equations of engineering mathematics appear in the modeling of the dynamic behavior of offshore structures. The dynamics of free-hanging risers, tension leg platforms and suspended loads can be cast in the form of Mathieu's equation; wave excitation causes the time variation of the spring parameter (references Disturbingly large subharmonic resonances or chaotic motions can result if the nonlinear equations (reference [4]) or the spring in the Mathieu equation varies harmonically (reference [1] ). This paper presents physical and mathematical arguments which indicate that these large responses are caused by a phase lock between the motion of the structure and the external excitation, something which is generally unlikely to last for long if a structure is subject to a random excitation. To test these predictions, two typical systems are simulated and randomness is introduced into the previously regular forcing in three different ways; as additive white noise, as frequency wander and as bandwidth spread. The responses are Fourier analyzed and maximum, minimum, mean and rms values are recorded. Random inputs cause the Poincare points to wander in a "Poincare region"; these are displayed as a function of the randomness parameter. The size of the subharmonic motions decays quickly with increasing values of the randomness parameter and they are generally small for realistically random wave forcing signals. Where the motion of a vessel is a significant input to a dynamic system, the filtering action of the vessel's dynamics driven by the wave action can generate a relatively regular motion; Pate

Bayesian Analysis of Two Stellar Populations in Galactic Globular Clusters II: NGC 5024, NGC 5272, and NGC 6352

We use Cycle 21 Hubble Space Telescope (HST) observations and HST archival ACS Treasury observations of Galactic Globular Clusters to find and characterize two stellar populations in NGC 5024 (M53), NGC 5272 (M3), and NGC 6352. For these three clusters, both single and double-population analyses are used to determine a best fit isochrone(s). We employ a sophisticated Bayesian analysis technique to simultaneously fit the cluster parameters (age, distance, absorption, and metallicity) that characterize each cluster. For the two-population analysis, unique population level helium values are also fit to each distinct population of the cluster and the relative proportions of the populations are determined. We find differences in helium ranging from $\sim$0.05 to 0.11 for these three clusters. Model grids with solar $\alpha$-element abundances ([$\alpha$/Fe] =0.0) and enhanced $\alpha$-elements ([$\alpha$/Fe]=0.4) are adopted.Comment: ApJ, 21 pages, 14 figures, 7 table

High-Frequency network activity, global increase in Neuronal Activity, and Synchrony Expansion Precede Epileptic Seizures In Vitro

How seizures start is a major question in epilepsy research. Preictal EEG changes occur in both human patients and animal models, but their underlying mechanisms and relationship with seizure initiation remain unknown. Here we demonstrate the existence, in the hippocampal CA1 region, of a preictal state characterized by the progressive and global increase in neuronal activity associated with a widespread buildup of low-amplitude high-frequency activity (HFA) (100 Hz) and reduction in system complexity.HFAis generated by the firing of neurons, mainly pyramidal cells, at much lower frequencies. Individual cycles ofHFAare generated by the near-synchronous (within 5 ms) firing of small numbers of pyramidal cells. The presence of HFA in the low-calcium model implicates nonsynaptic synchronization; the presence of very similar HFA in the high-potassium model shows that it does not depend on an absence of synaptic transmission. Immediately before seizure onset, CA1 is in a state of high sensitivity in which weak depolarizing or synchronizing perturbations can trigger seizures. Transition to seizure is haracterized by a rapid expansion and fusion of the neuronal populations responsible for HFA, associated with a progressive slowing of HFA, leading to a single, massive, hypersynchronous cluster generating the high-amplitude low-frequency activity of the seizure