Statistical Thermodynamics

Contains research objectives and reports on one research project.U. S. Air Force (Office of Scientific Research, Air Research and Development Command) under Contract AF49(638)-9

Diffusion in a Granular Fluid - Simulation

The linear response description for impurity diffusion in a granular fluid undergoing homogeneous cooling is developed in the preceeding paper. The formally exact Einstein and Green-Kubo expressions for the self-diffusion coefficient are evaluated there from an approximation to the velocity autocorrelation function. These results are compared here to those from molecular dynamics simulations over a wide range of density and inelasticity, for the particular case of self-diffusion. It is found that the approximate theory is in good agreement with simulation data up to moderate densities and degrees of inelasticity. At higher density, the effects of inelasticity are stronger, leading to a significant enhancement of the diffusion coefficient over its value for elastic collisions. Possible explanations associated with an unstable long wavelength shear mode are explored, including the effects of strong fluctuations and mode coupling

Methoden zur Analyse der vokalen Gestaltung populärer Musik

Although voice and singing play a crucial role in many genres of popular music, to date there are only few approaches to an in-depth exploration of vocal expression. The paper aims at presenting new ways for describing, analysing and visualizing several aspects of singing using computer-based tools. After outlining a theoretical framework for the study of voice and singing in popular music, some of those tools are introduced and exemplified by vocal recordings from various genres (blues, gospel music, country music, jazz). Firstly, pitch gliding (slurs, slides, bends, melismas) and vibrato are discussed referring to a computer-based visualization of pitch contour. Secondly, vocal timbre and phonation (e.g. vocal roughness) are explored and visualized using spectrograms

C-ME: A 3D Community-Based, Real-Time Collaboration Tool for Scientific Research and Training

The need for effective collaboration tools is growing as multidisciplinary proteome-wide projects and distributed research teams become more common. The resulting data is often quite disparate, stored in separate locations, and not contextually related. Collaborative Molecular Modeling Environment (C-ME) is an interactive community-based collaboration system that allows researchers to organize information, visualize data on a two-dimensional (2-D) or three-dimensional (3-D) basis, and share and manage that information with collaborators in real time. C-ME stores the information in industry-standard databases that are immediately accessible by appropriate permission within the computer network directory service or anonymously across the internet through the C-ME application or through a web browser. The system addresses two important aspects of collaboration: context and information management. C-ME allows a researcher to use a 3-D atomic structure model or a 2-D image as a contextual basis on which to attach and share annotations to specific atoms or molecules or to specific regions of a 2-D image. These annotations provide additional information about the atomic structure or image data that can then be evaluated, amended or added to by other project members

Preferred Spatial Frequencies for Human Face Processing Are Associated with Optimal Class Discrimination in the Machine

Psychophysical studies suggest that humans preferentially use a narrow band of low spatial frequencies for face recognition. Here we asked whether artificial face recognition systems have an improved recognition performance at the same spatial frequencies as humans. To this end, we estimated recognition performance over a large database of face images by computing three discriminability measures: Fisher Linear Discriminant Analysis, Non-Parametric Discriminant Analysis, and Mutual Information. In order to address frequency dependence, discriminabilities were measured as a function of (filtered) image size. All three measures revealed a maximum at the same image sizes, where the spatial frequency content corresponds to the psychophysical found frequencies. Our results therefore support the notion that the critical band of spatial frequencies for face recognition in humans and machines follows from inherent properties of face images, and that the use of these frequencies is associated with optimal face recognition performance

Bacterial Chemotaxis in an Optical Trap

An optical trapping technique is implemented to investigate the chemotactic behavior of a marine bacterial strain Vibrio alginolyticus. The technique takes the advantage that the bacterium has only a single polar flagellum, which can rotate either in the counter-clock-wise or clock-wise direction. The two rotation states of the motor can be readily and instantaneously resolved in the optical trap, allowing the flagellar motor switching rate to be measured under different chemical stimulations. In this paper the focus will be on the bacterial response to an impulsive change of chemoattractant serine. Despite different propulsion apparati and motility patterns, cells of V. alginolyticus apparently use a similar response as Escherichia coli to regulate their chemotactic behavior. Specifically, we found that the switching rate of the bacterial motor exhibits a biphasic behavior, showing a fast initial response followed by a slow relaxation to the steady-state switching rate . The measured can be mimicked by a model that has been recently proposed for chemotaxis in E. coli. The similarity in the response to the brief chemical stimulation in these two different bacteria is striking, suggesting that the biphasic response may be evolutionarily conserved. This study also demonstrated that optical tweezers can be a useful tool for chemotaxis studies and should be applicable to other polarly flagellated bacteria

Computational Model of the Insect Pheromone Transduction Cascade

A biophysical model of receptor potential generation in the male moth olfactory receptor neuron is presented. It takes into account all pre-effector processes—the translocation of pheromone molecules from air to sensillum lymph, their deactivation and interaction with the receptors, and the G-protein and effector enzyme activation—and focuses on the main post-effector processes. These processes involve the production and degradation of second messengers (IP3 and DAG), the opening and closing of a series of ionic channels (IP3-gated Ca2+ channel, DAG-gated cationic channel, Ca2+-gated Cl− channel, and Ca2+- and voltage-gated K+ channel), and Ca2+ extrusion mechanisms. The whole network is regulated by modulators (protein kinase C and Ca2+-calmodulin) that exert feedback inhibition on the effector and channels. The evolution in time of these linked chemical species and currents and the resulting membrane potentials in response to single pulse stimulation of various intensities were simulated. The unknown parameter values were fitted by comparison to the amplitude and temporal characteristics (rising and falling times) of the experimentally measured receptor potential at various pheromone doses. The model obtained captures the main features of the dose–response curves: the wide dynamic range of six decades with the same amplitudes as the experimental data, the short rising time, and the long falling time. It also reproduces the second messenger kinetics. It suggests that the two main types of depolarizing ionic channels play different roles at low and high pheromone concentrations; the DAG-gated cationic channel plays the major role for depolarization at low concentrations, and the Ca2+-gated Cl− channel plays the major role for depolarization at middle and high concentrations. Several testable predictions are proposed, and future developments are discussed

Efficient, intelligent systems for navigating the biological literature. Final report, September 15, 1993--September 14, 1996

The biological literature is huge and increasingly moving to electronic form. By developing a variety of new techniques, it should be possible to take advantage of this huge and growing electronic store. Computers should allow one to use the literature with greater efficiency and insight to disseminate information and to advance scientific understanding. Though there is a great deal of research and development effort focused on electronic text, e.g., the Digital Libraries initiative, little attention has been paid to the diagrammatic content of documents. However, it is common knowledge among biologists, and scientists in general, that the figures in documents are of critical importance. Little work has been done to develop principles and systems for analyzing, representing, and indexing and searching the diagrammatic content of electronic documents. This has been the main thrust of this research project. The primary work in the world on the analysis of graphics in documents has been focused on low-level issues relating to scanning legacy documents (hardcopy) and trying to discover the graphics elements in them. Graphics files, as opposed to image files, have lines, curves, polygons, text, etc., represented as discrete objects, as they are originally generated in drawing and graphing applications. This has been their focus, the starting point for all their analysis. Using their Diagram Understanding System the authors have been able to automatically analyze (parse) a score of complex data graphs and gene diagrams, accomplishing something that no other research group (or commercial product) has been able to achieve. These diagrams were ones drawn directly from published papers, not ones they made up