Quantification of the plant endoplasmic reticulum

One of the challenges of quantitative approaches to biological sciences is the lack of understanding of the interplay between form and function. Each cell is full of complex-shaped objects, which moreover change their form over time. To address this issue, we exploit recent advances in confocal microscopy, by using data collected from a series of optical sections taken at short regular intervals along the optical axis to reconstruct the Endoplasmic Reticulum (ER) in 3D, obtain its skeleton, then associate to each of its edges key geometric and dynamic characteristics obtained from the original filled in ER specimen. These properties include the total length, surface area, and volume of the ER specimen, as well as the length surface area, and volume of each of its branches. In a view to benefit from the well established graph theory algorithms, we abstract the obtained skeleton by a mathematical entity that is a graph. We achieve this by replacing the inner points in each edge in the skeleton by the line segment connecting its end points. We then attach to this graph the ER geometric properties as weights, allowing therefore a more precise quantitative characterisation, by thinning the filled in ER to its essential features. The graph plays a major role in this study and is the final and most abstract quantification of the ER. One of its advantages is that it serves as a geometric invariant, both in static and dynamic samples. Moreover, graph theoretic features, such as the number of vertices and their degrees, and the number of edges and their lengths are robust against different kinds of small perturbations. We propose a methodology to associate parameters such as surface areas and volumes to its individual edges and monitor their variations with time. One of the main contributions of this thesis is the use of the skeleton of the ER to analyse the trajectories of moving junctions using confocal digital videos. We report that the ER could be modeled by a network of connected cylinders (0.87μm±0.36 in diameter) with a majority of 3-way junctions. The average length, surface area and volume of an ER branch are found to be 2.78±2.04μm, 7.53±5.59μm2 and 1.81±1.86μm3 respectively. Using the analysis of variance technique we found that there are no significant differences in four different locations across the cell at 0.05 significance level. The apparent movement of the junctions in the plant ER consists of different types, namely: (a) the extension and shrinkage of tubules, and (b) the closing and opening of loops. The average velocity of a junction is found to be 0.25μm/sec±0.23 and lies in the range 0 to 1.7μm/sec which matches the reported actin filament range

Structural matching by discrete relaxation

This paper describes a Bayesian framework for performing relational graph matching by discrete relaxation. Our basic aim is to draw on this framework to provide a comparative evaluation of a number of contrasting approaches to relational matching. Broadly speaking there are two main aspects to this study. Firstly we locus on the issue of how relational inexactness may be quantified. We illustrate that several popular relational distance measures can be recovered as specific limiting cases of the Bayesian consistency measure. The second aspect of our comparison concerns the way in which structural inexactness is controlled. We investigate three different realizations ai the matching process which draw on contrasting control models. The main conclusion of our study is that the active process of graph-editing outperforms the alternatives in terms of its ability to effectively control a large population of contaminating clutter

Guiding object recognition: a shape model with co-activation networks

The goal of image understanding research is to develop techniques to automatically extract meaningful information from a population of images. This abstract goal manifests itself in a variety of application domains. Video understanding is a natural extension of image understanding. Many video understanding algorithms apply static-image algorithms to successive frames to identify patterns of consistency. This consumes a significant amount of irrelevant computation and may have erroneous results because static algorithms are not designed to indicate corresponding pixel locations between frames. Video is more than a collection of images, it is an ordered collection of images that exhibits temporal coherence, which is an additional feature like edges, colors, and textures. Motion information provides another level of visual information that can not be obtained from an isolated image. Leveraging motion cues prevents an algorithm from ?starting fresh? at each frame by focusing the region of attention. This approach is analogous to the attentional system of the human visual system. Relying on motion information alone is insufficient due to the aperture problem, where local motion information is ambiguous in at least one direction. Consequently, motion cues only provide leading and trailing motion edges and bottom-up approaches using gradient or region properties to complete moving regions are limited. Object recognition facilitates higher-level processing and is an integral component of image understanding. We present a components-based object detection and localization algorithm for static images. We show how this same system provides top-down segmentation for the detected object. We present a detailed analysis of the model dynamics during the localization process. This analysis shows consistent behavior in response to a variety of input, permitting model reduction and a substantial speed increase with little or no performance degradation. We present four specific enhancements to reduce false positives when instances of the target category are not present. First, a one-shot rule is used to discount coincident secondary hypotheses. Next, we demonstrate that the use of an entire shape model is inappropriate to localize any single instance and introduce the use of co-activation networks to represent the appropriate component relations for a particular recognition context. Next, we describe how the co-activation network can be combined with motion cues to overcome the aperture problem by providing context-specific, top-down shape information to achieve detection and segmentation in video. Finally, we present discriminating features arising from these enhancements and apply supervised learning techniques to embody the informational contribution of each approach to associate a confidence measure with each detection

Radar Technology

In this book “Radar Technology”, the chapters are divided into four main topic areas: Topic area 1: “Radar Systems” consists of chapters which treat whole radar systems, environment and target functional chain. Topic area 2: “Radar Applications” shows various applications of radar systems, including meteorological radars, ground penetrating radars and glaciology. Topic area 3: “Radar Functional Chain and Signal Processing” describes several aspects of the radar signal processing. From parameter extraction, target detection over tracking and classification technologies. Topic area 4: “Radar Subsystems and Components” consists of design technology of radar subsystem components like antenna design or waveform design

Quantification of the plant endoplasmic reticulum

One of the challenges of quantitative approaches to biological sciences is the lack of understanding of the interplay between form and function. Each cell is full of complex-shaped objects, which moreover change their form over time. To address this issue, we exploit recent advances in confocal microscopy, by using data collected from a series of optical sections taken at short regular intervals along the optical axis to reconstruct the Endoplasmic Reticulum (ER) in 3D, obtain its skeleton, then associate to each of its edges key geometric and dynamic characteristics obtained from the original filled in ER specimen. These properties include the total length, surface area, and volume of the ER specimen, as well as the length surface area, and volume of each of its branches. In a view to benefit from the well established graph theory algorithms, we abstract the obtained skeleton by a mathematical entity that is a graph. We achieve this by replacing the inner points in each edge in the skeleton by the line segment connecting its end points. We then attach to this graph the ER geometric properties as weights, allowing therefore a more precise quantitative characterisation, by thinning the filled in ER to its essential features. The graph plays a major role in this study and is the final and most abstract quantification of the ER. One of its advantages is that it serves as a geometric invariant, both in static and dynamic samples. Moreover, graph theoretic features, such as the number of vertices and their degrees, and the number of edges and their lengths are robust against different kinds of small perturbations. We propose a methodology to associate parameters such as surface areas and volumes to its individual edges and monitor their variations with time. One of the main contributions of this thesis is the use of the skeleton of the ER to analyse the trajectories of moving junctions using confocal digital videos. We report that the ER could be modeled by a network of connected cylinders (0.87μm±0.36 in diameter) with a majority of 3-way junctions. The average length, surface area and volume of an ER branch are found to be 2.78±2.04μm, 7.53±5.59μm2 and 1.81±1.86μm3 respectively. Using the analysis of variance technique we found that there are no significant differences in four different locations across the cell at 0.05 significance level. The apparent movement of the junctions in the plant ER consists of different types, namely: (a) the extension and shrinkage of tubules, and (b) the closing and opening of loops. The average velocity of a junction is found to be 0.25μm/sec±0.23 and lies in the range 0 to 1.7μm/sec which matches the reported actin filament range.EThOS - Electronic Theses Online ServiceEngineering and Physical Sciences Research Council (Great Britain) (EPSRC)University of Warwick. Molecular Organisation and Assembly in Cells (MOAC)Rodger, AlisonGBUnited Kingdo

Magnetic Tunnel Junctions based on spinel ZnxFe3-xO4: Magnetic Tunnel Junctions based onspinel ZnxFe3-xO4

Die vorliegende Arbeit befasst sich mit magnetischen Tunnelkontakten (magnetic tunnel junctions, MTJs) auf Basis des Oxids Zinkferrit (ZnxFe3-xO4). Dabei soll das Potential dieses Materials durch die Demonstration des Tunnelmagnetowiderstandes (tunnel magnetoresistance, TMR) in zinkferritbasierten Tunnelkontakten gezeigt werden. Dazu wurde ein Probendesign für MTJs auf Basis der „pseudo spin valve“-Geometrie entwickelt. Die Basis für dieseStrukturen ist ein Dünnfilmstapel aus MgO (Substrat) / TiN / ZnxFe3-xO4 / MgO / Co. Dieser ist mittels gepulster Laserabscheidung (pulsed laser deposition, PLD) hergestellt. Im Rahmen dieser Arbeit wurden die strukturellen, elektrischen und magnetischen Eigenschaften der Dünnfilme untersucht. Des weiteren wurden die fertig prozessierten MTJ-Bauelemente an einem im Rahmen dieser Arbeit entwickeltem und aufgebautem TMR-Messplatz vermessen. Dabei ist es gelungen einen TMR-Effekt von 0.5% in ZnxFe3-xO4-basierten MTJs nachzuweisen. Das erste Kapitel der Arbeit gibt eine Einführung in die spintronischen Effekte Riesenmagnetowiderstand (giant magnetoresistance, GMR) und Tunnelmagnetowiderstand (TMR). Deren technologische Anwendungen sowie die grundlegenden physikalischen Effekte und Modelle werden diskutiert. Das zweite Kapitel gibt eine Übersicht über die Materialklasse der spinellartigen Ferrite. Der Fokus liegt auf den Materialien Magnetit (Fe3O4) sowie Zinkferrit (ZnxFe3-xO4). Die physikalischen Modelle zur Beschreibung der strukturellen, magnetischen und elektrischen Eigenschaften dieser Materialien werden dargelegt sowie ein Literaturüberblick über experimentelle und theoretische Arbeiten gegeben. Im dritten Kapitel werden die im Rahmen dieser Arbeit verwendeten Probenpräparations- und Charakterisierungsmethoden vorgestellt und technische Details sowie physikalische Grundlagen erläutert. Die Entwicklung eines neuen Probendesigns zum Nachweis des TMR-Effekts in ZnxFe3-xO4-basierten MTJs ist Gegenstand des vierten Kapitels. Die Entwicklung des Probenaufbaus sowie die daraus resultierende Probenprozessierung werden beschrieben. Die beiden letzten Kapitel befassen sich mit der strukturellen, elektrischen und magnetischen Charakterisierung der mittels PLD abgeschiedenen Dünnfilme sowie der Tunnelkontaktstrukturen

NASA Tech Briefs, September 2008

Topics covered include: Nanotip Carpets as Antireflection Surfaces; Nano-Engineered Catalysts for Direct Methanol Fuel Cells; Capillography of Mats of Nanofibers; Directed Growth of Carbon Nanotubes Across Gaps; High-Voltage, Asymmetric-Waveform Generator; Magic-T Junction Using Microstrip/Slotline Transitions; On-Wafer Measurement of a Silicon-Based CMOS VCO at 324 GHz; Group-III Nitride Field Emitters; HEMT Amplifiers and Equipment for their On-Wafer Testing; Thermal Spray Formation of Polymer Coatings; Improved Gas Filling and Sealing of an HC-PCF; Making More-Complex Molecules Using Superthermal Atom/Molecule Collisions; Nematic Cells for Digital Light Deflection; Improved Silica Aerogel Composite Materials; Microgravity, Mesh-Crawling Legged Robots; Advanced Active-Magnetic-Bearing Thrust- Measurement System; Thermally Actuated Hydraulic Pumps; A New, Highly Improved Two-Cycle Engine; Flexible Structural-Health-Monitoring Sheets; Alignment Pins for Assembling and Disassembling Structures; Purifying Nucleic Acids from Samples of Extremely Low Biomass; Adjustable-Viewing-Angle Endoscopic Tool for Skull Base and Brain Surgery; UV-Resistant Non-Spore-Forming Bacteria From Spacecraft-Assembly Facilities; Hard-X-Ray/Soft-Gamma-Ray Imaging Sensor Assembly for Astronomy; Simplified Modeling of Oxidation of Hydrocarbons; Near-Field Spectroscopy with Nanoparticles Deposited by AFM; Light Collimator and Monitor for a Spectroradiometer; Hyperspectral Fluorescence and Reflectance Imaging Instrument; Improving the Optical Quality Factor of the WGM Resonator; Ultra-Stable Beacon Source for Laboratory Testing of Optical Tracking; Transmissive Diffractive Optical Element Solar Concentrators; Delaying Trains of Short Light Pulses in WGM Resonators; Toward Better Modeling of Supercritical Turbulent Mixing; JPEG 2000 Encoding with Perceptual Distortion Control; Intelligent Integrated Health Management for a System of Systems; Delay Banking for Managing Air Traffic; and Spline-Based Smoothing of Airfoil Curvatures

Doctor of Philosophy

dissertationThis dissertation studies detection-based methods to increase the estimation precision of single point-source emitters in the field of localization microscopy. Localization microscopy is a novel method allowing for the localization of optical point-source emitters below the Abbe diffraction limit of optical microscopy. This is accomplished by optically controlling the active, or bright, state of individual molecules within a sample. The use of time-multiplexing of the active state allows for the temporal and spatial isolation of single point-source emitters. Isolating individual sources within a sample allows for statistical analysis on their emission point-spread function profile, and the spatial coordinates of the point-source may be discerned below the optical response of the microscope system. Localization microscopy enables the identification of individual point-source emitter locations approximately an order of magnitude below standard, diffraction-limited optical techniques. The precision of localization microscopy methods is limited by the statistical uncertainty in which the location of these sources may be estimated. By utilizing a detection- based interferometer, an interference pattern may be super-imposed over the emission signal. Theoretical analysis and Monte-Carlo simulations by means of Fisher information theory demonstrate that the incorporation of a modulation structure over the emission signal allow for a more precise estimation when compared to conventional localization methods for the same number of recorded photons. These theoretical calculation and simulations are demonstrated through the use of two proof-of-concept experiments utilizing a modified Mach-Zehnder interferometer. The first methodology improves the localization precision of a single nanoparticle over the theoretical limit for an Airy-disk point-spread function by using self-interference to spatially modulate the recorded point-spread function. Experimental analysis demonstrates an improvement factor of ~3 to 5 over conventional localization methods. A related method employs the phase induced onto the Fourier domain signal due to path length differences in the Mach-Zehnder interferometer to improve localization precision. The localization capability of a modified Fourier domain signal generated by self-interference is utilized to yield a two-fold improvement in the localization precision for a given number of photons compared to a standard Gaussian intensity distribution of the corresponding point-spread function

Microsaccadic sampling of moving image information provides Drosophila hyperacute vision.

Small fly eyes should not see fine image details. Because flies exhibit saccadic visual behaviors and their compound eyes have relatively few ommatidia (sampling points), their photoreceptors would be expected to generate blurry and coarse retinal images of the world. Here we demonstrate that Drosophila see the world far better than predicted from the classic theories. By using electrophysiological, optical and behavioral assays, we found that R1-R6 photoreceptors' encoding capacity in time is maximized to fast high-contrast bursts, which resemble their light input during saccadic behaviors. Whilst over space, R1-R6s resolve moving objects at saccadic speeds beyond the predicted motion-blur-limit. Our results show how refractory phototransduction and rapid photomechanical photoreceptor contractions jointly sharpen retinal images of moving objects in space-time, enabling hyperacute vision, and explain how such microsaccadic information sampling exceeds the compound eyes' optical limits. These discoveries elucidate how acuity depends upon photoreceptor function and eye movements