Graphics software tool for VT terminals (VTGRAPH)

VTGRAPH is a graphics software tool for using DEC/VT or VT compatible terminals. It allows the user to deal with computer environments which use VT terminals for window management and graphics systems. VTGRAPH was developed using the Re'Gis Graphics set and it was written in FORTRAN language. It provides window management and a PLOT10-like package plus color or shade capability

Automatic mathematical modeling for space application

A methodology for automatic mathematical modeling is described. The major objective is to create a very friendly environment for engineers to design, maintain and verify their model and also automatically convert the mathematical model into FORTRAN code for conventional computation. A demonstration program was designed for modeling the Space Shuttle Main Engine simulation mathematical model called Propulsion System Automatic Modeling (PSAM). PSAM provides a very friendly and well organized environment for engineers to build a knowledge base for base equations and general information. PSAM contains an initial set of component process elements for the Space Shuttle Main Engine simulation and a questionnaire that allows the engineer to answer a set of questions to specify a particular model. PSAM is then able to automatically generate the model and the FORTRAN code. A future goal is to download the FORTRAN code to the VAX/VMS system for conventional computation

High-Dimensional Joint Estimation of Multiple Directed Gaussian Graphical Models

We consider the problem of jointly estimating multiple related directed acyclic graph (DAG) models based on high-dimensional data from each graph. This problem is motivated by the task of learning gene regulatory networks based on gene expression data from different tissues, developmental stages or disease states. We prove that under certain regularity conditions, the proposed $\ell_0$-penalized maximum likelihood estimator converges in Frobenius norm to the adjacency matrices consistent with the data-generating distributions and has the correct sparsity. In particular, we show that this joint estimation procedure leads to a faster convergence rate than estimating each DAG model separately. As a corollary, we also obtain high-dimensional consistency results for causal inference from a mix of observational and interventional data. For practical purposes, we propose \emph{jointGES} consisting of Greedy Equivalence Search (GES) to estimate the union of all DAG models followed by variable selection using lasso to obtain the different DAGs, and we analyze its consistency guarantees. The proposed method is illustrated through an analysis of simulated data as well as epithelial ovarian cancer gene expression data

Automatic mathematical modeling for real time simulation program (AI application)

A methodology is described for automatic mathematical modeling and generating simulation models. The major objective was to create a user friendly environment for engineers to design, maintain, and verify their models; to automatically convert the mathematical models into conventional code for computation; and finally, to document the model automatically

Direct Estimation of Differences in Causal Graphs

We consider the problem of estimating the differences between two causal directed acyclic graph (DAG) models with a shared topological order given i.i.d. samples from each model. This is of interest for example in genomics, where changes in the structure or edge weights of the underlying causal graphs reflect alterations in the gene regulatory networks. We here provide the first provably consistent method for directly estimating the differences in a pair of causal DAGs without separately learning two possibly large and dense DAG models and computing their difference. Our two-step algorithm first uses invariance tests between regression coefficients of the two data sets to estimate the skeleton of the difference graph and then orients some of the edges using invariance tests between regression residual variances. We demonstrate the properties of our method through a simulation study and apply it to the analysis of gene expression data from ovarian cancer and during T-cell activation

Automatic detection of electric power troubles (AI application)

The design goals for the Automatic Detection of Electric Power Troubles (ADEPT) were to enhance Fault Diagnosis Techniques in a very efficient way. ADEPT system was designed in two modes of operation: (1) Real time fault isolation, and (2) a local simulator which simulates the models theoretically

Dynamic deformability of individual PbSe nanocrystals during superlattice phase transitions

The behavior of individual nanocrystals during superlattice phase transitions can profoundly affect the structural perfection and electronic properties of the resulting superlattices. However, details of nanocrystal morphological changes during superlattice phase transitions are largely unknown due to the lack of direct observation. Here, we report the dynamic deformability of PbSe semiconductor nanocrystals during superlattice phase transitions that are driven by ligand displacement. Real-time high-resolution imaging with liquid-phase transmission electron microscopy reveals that following ligand removal, the individual PbSe nanocrystals experience drastic directional shape deformation when the spacing between nanocrystals reaches 2 to 4 nm. The deformation can be completely recovered when two nanocrystals move apart or it can be retained when they attach. The large deformation, which is responsible for the structural defects in the epitaxially fused nanocrystal superlattice, may arise from internanocrystal dipole-dipole interactions

Detecting Water In the atmosphere of HR 8799 c with L-band High Dispersion Spectroscopy Aided By Adaptive Optics

High dispersion spectroscopy of brown dwarfs and exoplanets enables exciting science cases, e.g., mapping surface inhomogeneity and measuring spin rate. Here, we present $L$ band observations of HR 8799 c using Keck NIRSPEC (R=15,000) in adaptive optics (AO) mode (NIRSPAO). We search for molecular species (H$_2$O and CH$_4$) in the atmosphere of HR 8799 c with a template matching method, which involves cross correlation between reduced spectrum and a template spectrum. We detect H$_2$O but not CH$_4$, which suggests disequilibrium chemistry in the atmosphere of HR 8799 c, and this is consistent with previous findings. We conduct planet signal injection simulations to estimate the sensitivity of our AO-aided high dispersion spectroscopy observations. We conclude that $10^{-4}$ contrast can be reached in $L$ band. The sensitivity is mainly limited by the accuracy of line list used in modeling spectra and detector noise. The latter will be alleviated by the NIRSPEC upgrade.Comment: 14 pages, 5 figures, 5 tables, accepted for publication on AJ, references update