The hawk/goose story: The classical ethological experiments of Lorenz and Tinbergen, revisited.

We present a historical account of the story behind the famous hawk/goose experiments of Lorenz and Tinbergen in a wider context of cognitive ethology. We discuss their significance, for ethological experimentation in general, and specifically for understanding innate constraints on cognition. As examples of the continuing significance of the hawk/goose paradigm of selective habituation, we discuss its relation to “exposure therapy” of human phobias and the use of hawk silhouettes as deterrents for songbirds. Finally we rephrase Uexküll's thesis of taxon-specific worlds (“Umwelten”) as a “Theory of World.” (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

A Novel Nanoparticle‐Based Disposable Electrochemical Immunosensor for Diagnosis of Exposure to Toxic Organophosphorus Agents

A novel disposable electrochemical immunosensor for highly selective and sensitive detection of organophosphorylated butyrylcholinesterase (OP‐BChE), a specific biomarker for exposure to toxic organophosphorus agents, is presented. In this new approach, zirconia nanoparticles (ZrO₂) were employed to selectively capture the OP moiety of OP‐BChE adducts, followed by quantum dot (QD)‐tagged anti‐BChE antibodies for amplified quantification. The captured CdSe‐QD tags can be sensitively detected by stripping voltammetry using an in situ bismuth‐plating method. The OP agent, diisopropylfluorophosphate (DFP), was selected to prepare OP‐BChE adducts in various matrices. The formation of OP‐BChE adducts in plasma sample was confirmed using mass spectroscopy. The developed electrochemical immunosensor demonstrates a highly linear voltammetric response over the range of 0.1 to 30 nM OP‐BChE, with a detection limit of 0.03 nM (based on signal/noise = 3), coupled with a good reproducibility (relative standard deviation 4.5%). Moreover, the immunosensor has been validated with biomonitoring of OP‐BChE adducts in the plasma samples. This novel nanoparticle‐based electrochemical immunosensor thus provides an alternative way for designing a sensitive and cost‐effective sensing platform for on‐site screening/evaluating exposure to a variety of OP agents.     

CommunityMirrors als Informationsstrahler in Unternehmen

Informations- und Kooperationssysteme nutzen heute meist Desktoparbeitspl?tze oder Laptops als prim?re Schnittstelle zu Benutzern. Dies führt zu Problemen bei der Integration in den sozialen Kontext realer Arbeitsumgebungen sowie zu Defiziten bei der Versorgung mit Information, nach der nicht aktiv gesucht wird. Mit dem Konzept der CommunityMirrors stellen wir eine Erg?nzung zu heutigen (modularen und anpassbaren) Informationssystemen vor, die eine Integration in reale Arbeitsumgebungen erlaubt und so verschiedene Potenziale bezüglich der Sichtbarkeit von Information und der Kollaboration rund um Information realisiert. Die Grundidee von CommunityMirrors besteht darin, in IT-Systemen enthaltene Information jenseits klassischer Desktoprechner sichtbar, greifbar und erlebbar zu machen und so eine in den sozialen Kontext eingebettete Benutzungsschnittstelle als ,,Informationsstrahler“ bereitzustellen. Neben der Vorstellung des Grundkonzeptes und der Potenziale dieser Idee pr?sentieren wir im Folgenden auch erste Erkenntnisse und Anregungen zur Umsetzbarkeit in der Praxis, die in verschiedenen Feldtests in den vergangenen Jahren gewonnen wurden.     

Can Variational Models for Correspondence Problems Benefit from Upwind Discretisations?

Optic flow and stereo reconstruction are important examples of correspondence problems in computer vision. Correspondence problems have been studied for almost 30 years, and energy-based methods such as variational approaches have become popular for solving this task. However, despite the long history of research in this field, only little attention has been paid to the numerical approximation of derivatives that naturally occur in variational approaches.     

A computational model for signaling pathways in bounded small-world networks corresponding to brain size

A computational model, the bounded composite inverse-d architecture (BCIA), was developed to characterize signaling in small-world networks with large but bounded numbers of nodes, as in human brains. The model is based upon an N-dimensional symmetrical grid with borders, with complete local connections from each node and relatively fewer long-range connections. The length of the signaling pathway generated by a greedy algorithm between two nodes exhibited polylogarithmic behavior when the grid distance between the nodes was less than m, the maximal length of a long-range connection for that network. The simulated length of signaling pathway became linear with internode distance when the grid distance between the two nodes was greater than m. The intensity of long-range connections among nodes was found to be negatively related to the simulated length of signaling pathway. For a constant grid distance between nodes, the average length of a simulated signaling pathway increased with dimension of the BCIA graph. Most strikingly, BCIA simulations of networks with large but bounded numbers (10⁹–10¹³) of nodes, approximating the number of neurons in the human brain, found that the length of simulated signaling pathway can be substantially shorter than that predicted by the best known asymptotic theoretical bound in small-world networks of infinite size.     

A Multi-Scale Vectorial L<Superscript><Emphasis Type=Italic>τ</Emphasis></Superscript>-TV Framework for Color Image Restoration

A general multi-scale vectorial total variation model with spatially adapted regularization parameter for color image restoration is introduced in this paper. This total variation model contains an L ^τ -data fidelity for any τ∈[1,2]. The use of a spatial dependent regularization parameter improves the reconstruction of features in the image as well as an adequate smoothing for the homogeneous parts. The automated adaptation of this regularization parameter is made according to local statistical characteristics of the noise which contaminates the image. The corresponding multiscale vectorial total variation model is solved by Fenchel-duality and inexact semismooth Newton techniques. Numerical results are presented for the cases τ=1 and τ=2 which reconstruct images contaminated with salt-and-pepper noise and Gaussian noise, respectively.     

Recipes for Spatial Statistics with Global Datasets: A Martian Case Study

The Mars Odyssey Gamma Ray Spectrometer has yielded planetary data of global extent. Such remote-sensing missions usually assign the value of a continuous-valued geospatial attribute to a uniform latitude-longitude grid of bins. Typical attributes include elemental-mass fraction, areal fraction of a mineral type, areal fraction of rocks, thermal inertia, etc. The fineness of the grid is chosen according to the spatial resolution of the orbiter and concomitant data processing. We describe methods to maximize the information extracted from both bin and regional data. Rigorous use of statistical parameters and related methods for inter- and intra- regional comparisons are also discussed. While we discuss results from the Mars Odyssey mission, the techniques we describe are applicable whenever continuous-valued attributes of a planet’s surface are characterized with bins and regions. Our goal is to distill the simplest statistical methods for regional comparisons that would be intuitively accessible to planetary scientists.     

Measuring optical distortion in aircraft transparencies: a fully automated system for quantitative evaluation

We describe a complete system for quantitatively measuring the optical distortion in aircraft windshields and automatically classifying that distortion as acceptable or not. The system comprises two parts: The first uses digital imaging of a known grid pattern through the windshield of interest to create a distortion map of that windshield; the second uses the distortion maps created for 100 windshields (some acceptable and some not) and automatically learns a decision-tree-based classifier. We show results that highlight the robustness of this system, including a demonstration that the distortion map for a windshield is consistently measured over 3 years, and cross-validation study shows that we can effectively classify windshields based on the distortion maps.     

Weighted argument systems: Basic definitions, algorithms, and complexity results

We introduce and investigate a natural extension of Dung's well-known model of argument systems in which attacks are associated with a weight, indicating the relative strength of the attack. A key concept in our framework is the notion of an inconsistency budget, which characterises how much inconsistency we are prepared to tolerate: given an inconsistency budget β, we would be prepared to disregard attacks up to a total weight of β. The key advantage of this approach is that it permits a much finer grained level of analysis of argument systems than unweighted systems, and gives useful solutions when conventional (unweighted) argument systems have none. We begin by reviewing Dung's abstract argument systems, and motivating weights on attacks (as opposed to the alternative possibility, which is to attach weights to arguments). We then present the framework of weighted argument systems. We investigate solutions for weighted argument systems and the complexity of computing such solutions, focussing in particular on weighted variations of grounded extensions. Finally, we relate our work to the most relevant examples of argumentation frameworks that incorporate strengths.