Observational and theoretical studies of the evolving structure of baroclinic waves

Dynamical processes involved in comma cloud formation, and passive tracer evolution in a baroclinic wave are discussed. An analytical solution was obtained demonstrating the complex nongeostrophic flow pattern involved in the redistribution of low level constituents in a finite amplitude baroclinic wave, and in the formation of the typical humidity and cloud distributions in such a wave. Observational and theoretical studies of blocking weather patterns in middle latitude flows were studied. The differences in the energy and enstrophy cascades in blocking and nonblocking situations were shown. It was established that pronounced upscale flow of both of these quantities, from intermediate to planetary scales, occurs during blocking episodes. The upscale flux of enstrophy, in particular, suggests that the persistence of blocking periods may be due to reduced dissipation of the large scale circulation and therefore entail some above normal predictability

NASA ground terminal communication equipment automated fault isolation expert systems

The prototype expert systems are described that diagnose the Distribution and Switching System I and II (DSS1 and DSS2), Statistical Multiplexers (SM), and Multiplexer and Demultiplexer systems (MDM) at the NASA Ground Terminal (NGT). A system level fault isolation expert system monitors the activities of a selected data stream, verifies that the fault exists in the NGT and identifies the faulty equipment. Equipment level fault isolation expert systems are invoked to isolate the fault to a Line Replaceable Unit (LRU) level. Input and sometimes output data stream activities for the equipment are available. The system level fault isolation expert system compares the equipment input and output status for a data stream and performs loopback tests (if necessary) to isolate the faulty equipment. The equipment level fault isolation system utilizes the process of elimination and/or the maintenance personnel's fault isolation experience stored in its knowledge base. The DSS1, DSS2 and SM fault isolation systems, using the knowledge of the current equipment configuration and the equipment circuitry issues a set of test connections according to the predefined rules. The faulty component or board can be identified by the expert system by analyzing the test results. The MDM fault isolation system correlates the failure symptoms with the faulty component based on maintenance personnel experience. The faulty component can be determined by knowing the failure symptoms. The DSS1, DSS2, SM, and MDM equipment simulators are implemented in PASCAL. The DSS1 fault isolation expert system was converted to C language from VP-Expert and integrated into the NGT automation software for offline switch diagnoses. Potentially, the NGT fault isolation algorithms can be used for the DSS1, SM, amd MDM located at Goddard Space Flight Center (GSFC)

A new and flexible method for constructing designs for computer experiments

We develop a new method for constructing "good" designs for computer experiments. The method derives its power from its basic structure that builds large designs using small designs. We specialize the method for the construction of orthogonal Latin hypercubes and obtain many results along the way. In terms of run sizes, the existence problem of orthogonal Latin hypercubes is completely solved. We also present an explicit result showing how large orthogonal Latin hypercubes can be constructed using small orthogonal Latin hypercubes. Another appealing feature of our method is that it can easily be adapted to construct other designs; we examine how to make use of the method to construct nearly orthogonal and cascading Latin hypercubes.Comment: Published in at http://dx.doi.org/10.1214/09-AOS757 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Stress Concentration Around Knots in Laminated Beams

A formal elastic solution of the stresses and displacements occurring in a laminated beam, with an arbitrarily located elliptic or circular knot, subjected to static bending is presented. The solutions are obtained by using the theory of complex variables in plane elasticity. Numerical examples of the stress concentration are illustrated with graphs in which comparisons are made between the cases of sound knot, decayed knot, knothole, and wooden plug. The effects of size, shape, location, orientation, and material property of the knot on the stress concentrations are discussed

Properties of Resonating-Valence-Bond Spin Liquids and Critical Dimer Models

We use Monte Carlo simulations to study properties of Anderson's resonating-valence-bond (RVB) spin-liquid state on the square lattice (i.e., the equal superposition of all pairing of spins into nearest-neighbor singlet pairs) and compare with the classical dimer model (CDM). The latter system also corresponds to the ground state of the Rokhsar-Kivelson quantum dimer model at its critical point. We find that although spin-spin correlations decay exponentially in the RVB, four-spin valence-bond-solid (VBS) correlations are critical, qualitatively like the well-known dimer-dimer correlations of the CDM, but decaying more slowly (as $1/r^a$ with $a \approx 1.20$, compared with $a=2$ for the CDM). We also compute the distribution of monomer (defect) pair separations, which decay by a larger exponent in the RVB than in the CDM. We further study both models in their different winding number sectors and evaluate the relative weights of different sectors. Like the CDM, all the observed RVB behaviors can be understood in the framework of a mapping to a "height" model characterized by a gradient-squared stiffness constant $K$. Four independent measurements consistently show a value $K_{RVB} \approx 1.6 K_{CDM}$, with the same kinds of numerical evaluations of $K_{CDM}$ give results in agreement with the rigorously known value $K_{CDM}=\pi/16$. The background of a nonzero winding number gradient $W/L$ introduces spatial anisotropies and an increase in the effective K, both of which can be understood as a consequence of anharmonic terms in the height-model free energy, which are of relevance to the recently proposed scenario of "Cantor deconfinement" in extended quantum dimer models. We also study ensembles in which fourth-neighbor (bipartite) bonds are allowed, at a density controlled by a tunable fugacity, resulting (as expected) in a smooth reduction of K.Comment: 26 pages, 21 figures. v3: final versio

Temperature Effects on Threshold Counterion Concentration to Induce Aggregation of fd Virus

We seek to determine the mechanism of like-charge attraction by measuring the temperature dependence of critical divalent counterion concentration ($\rm{C_{c}}$) for the aggregation of fd viruses. We find that an increase in temperature causes $\rm{C_c}$ to decrease, primarily due to a decrease in the dielectric constant ($\epsilon$) of the solvent. At a constant $\epsilon$, $\rm{C_c}$ is found to increase as the temperature increases. The effects of $T$ and $\epsilon$ on $\rm {C_{c}}$ can be combined to that of one parameter: Bjerrum length ($l_{B}$). $\rm{C_{c}}$ decreases exponentially as $l_{B}$ increases, suggesting that entropic effect of counterions plays an important role at the onset of bundle formation.Comment: 12 pages, 3 figure

Geometry dependence of the clogging transition in tilted hoppers

We report the effect of system geometry on the clogging of granular material flowing out of flat-bottomed hoppers with variable aperture size D. For such systems, there exists a critical aperture size Dc at which there is a divergence in the time for a flow to clog. To better understand the origins of Dc, we perturb the system by tilting the hopper an angle Q and mapping out a clogging phase diagram as a function of Q and D. The clogging transition demarcates the boundary between the freely-flowing (large D, small Q) and clogging (small D, large Q) regimes. We investigate how the system geometry affects Dc by mapping out this phase diagram for hoppers with either a circular hole or a rectangular narrow slit. Additionally, we vary the grain shape, investigating smooth spheres (glass beads), compact angular grains (beach sand), disk-like grains (lentils), and rod-like grains (rice). We find that the value of Dc grows with increasing Q, diverging at pi-Qr where Qr is the angle of repose. For circular apertures, the shape of the clogging transition is the same for all grain types. However, this is not the case for the narrow slit apertures, where the rate of growth of the critical hole size with tilt angle depends on the material

N-Acetyl and Glutamatergic Neurometabolites in Perisylvian Brain Regions of Methamphetamine Users.

Background:Methamphetamine induces neuronal N-acetyl-aspartate synthesis in preclinical studies. In a preliminary human proton magnetic resonance spectroscopic imaging investigation, we also observed that N-acetyl-aspartate+N-acetyl-aspartyl-glutamate in right inferior frontal cortex correlated with years of heavy methamphetamine abuse. In the same brain region, glutamate+glutamine is lower in methamphetamine users than in controls and is negatively correlated with depression. N-acetyl and glutamatergic neurochemistries therefore merit further investigation in methamphetamine abuse and the associated mood symptoms. Methods:Magnetic resonance spectroscopic imaging was used to measure N-acetyl-aspartate+N-acetyl-aspartyl-glutamate and glutamate+glutamine in bilateral inferior frontal cortex and insula, a neighboring perisylvian region affected by methamphetamine, of 45 abstinent methamphetamine-dependent and 45 healthy control participants. Regional neurometabolite levels were tested for group differences and associations with duration of heavy methamphetamine use, depressive symptoms, and state anxiety. Results:In right inferior frontal cortex, N-acetyl-aspartate+N-acetyl-aspartyl-glutamate correlated with years of heavy methamphetamine use (r = +0.45); glutamate+glutamine was lower in methamphetamine users than in controls (9.3%) and correlated negatively with depressive symptoms (r = -0.44). In left insula, N-acetyl-aspartate+N-acetyl-aspartyl-glutamate was 9.1% higher in methamphetamine users than controls. In right insula, glutamate+glutamine was 12.3% lower in methamphetamine users than controls and correlated negatively with depressive symptoms (r = -0.51) and state anxiety (r = -0.47). Conclusions:The inferior frontal cortex and insula show methamphetamine-related abnormalities, consistent with prior observations of increased cortical N-acetyl-aspartate in methamphetamine-exposed animal models and associations between cortical glutamate and mood in human methamphetamine users

Diving Deep into Sentiment: Understanding Fine-tuned CNNs for Visual Sentiment Prediction

Visual media are powerful means of expressing emotions and sentiments. The constant generation of new content in social networks highlights the need of automated visual sentiment analysis tools. While Convolutional Neural Networks (CNNs) have established a new state-of-the-art in several vision problems, their application to the task of sentiment analysis is mostly unexplored and there are few studies regarding how to design CNNs for this purpose. In this work, we study the suitability of fine-tuning a CNN for visual sentiment prediction as well as explore performance boosting techniques within this deep learning setting. Finally, we provide a deep-dive analysis into a benchmark, state-of-the-art network architecture to gain insight about how to design patterns for CNNs on the task of visual sentiment prediction.Comment: Preprint of the paper accepted at the 1st Workshop on Affect and Sentiment in Multimedia (ASM), in ACM MultiMedia 2015. Brisbane, Australi

Communicability across evolving networks

Many natural and technological applications generate time ordered sequences of networks, defined over a fixed set of nodes; for example time-stamped information about ‘who phoned who’ or ‘who came into contact with who’ arise naturally in studies of communication and the spread of disease. Concepts and algorithms for static networks do not immediately carry through to this dynamic setting. For example, suppose A and B interact in the morning, and then B and C interact in the afternoon. Information, or disease, may then pass from A to C, but not vice versa. This subtlety is lost if we simply summarize using the daily aggregate network given by the chain A-B-C. However, using a natural definition of a walk on an evolving network, we show that classic centrality measures from the static setting can be extended in a computationally convenient manner. In particular, communicability indices can be computed to summarize the ability of each node to broadcast and receive information. The computations involve basic operations in linear algebra, and the asymmetry caused by time’s arrow is captured naturally through the non-mutativity of matrix-matrix multiplication. Illustrative examples are given for both synthetic and real-world communication data sets. We also discuss the use of the new centrality measures for real-time monitoring and prediction