The functional role of the motor area of the cortex in the formation of riddance reactions in dogs

A model of instrumental conditioning similar to the classical model (Pavlovian) is proposed. Flexion of the ipsilateral forelimb was elicited while EDS was applied to the hind limb by stimulation of the motor area of the cortex (M1); both stimuli ceased during the raising of the forelimb. Uniform combinations of this kind led to the development of forepaw flexion reactions in response to the EDS of the hind paw. Prolongation of EDS by 3 sec following cortical stimulation led to rapid extinction of the developed reactions. Thus, the possibility of the effective instrumentalization of movements induced by stimulation of the M1 is proven. This argues that the forming "instrumental" connection (drive-motor structures) is addressed directly to the M1.     

Casein kinase 2 down-regulation and activation by polybasic peptides are mediated by acidic residues in the 55-64 region of the beta-subunit. A study with calmodulin as phosphorylatable substrate

The noncatalytic beta-subunit is responsible for the latency of casein kinase 2 (CK2) activity toward calmodulin. Twenty-one mutants of the beta-subunit bearing either deletions or Ala substitutions for charged residues in the 5-6, 55-70, and 171-178 sequences have been assayed for their ability to substitute for wild-type beta-subunit as a suppressor of activity toward calmodulin. The only mutations that reduced the ability of the beta-subunit to suppress calmodulin phosphorylation activity, though being compatible with normal reconstitution of CK2 holoenzyme, were those affecting Asp55, Glu57 and the whole triplet Glu59-Asp-Glu61. The activity of CK2 holoenzyme, either native or reconstituted, toward calmodulin can be elicited by a variety of polybasic effectors, including polylysine, polyarginine, salmine, and histones H4, H3, and, to a lesser extent, H2a and H2b. Histone H1 and polyamines are conversely ineffective. The latent "calmodulin kinase" activity of CK2 can also be specifically unmasked by a peptide (alpha[66-86]) reproducing a basic insert of the catalytic subunit. This effect is reversed by equimolar addition of a peptide (beta[55-71]) including the 55-64 acidic stretch of the beta-subunit. Comparable polylysine stimulation was observed with the holoenzymes reconstituted with either beta wt or the beta mutants capable of assembling with the alpha-subunit, with the notable exception of those bearing Ala substitutions for acidic residues at positions 55, 57, and 59-61. These were nearly insensitive to 42 nM polylysine, which conversely promotes a more than 10-fold increase of calmodulin phosphorylation with wild-type beta.(ABSTRACT TRUNCATED AT 250 WORDS)     

Cognitive distortions and adolescent affective disorder. Validity of the CNCEQ in an inpatient sample. Children's Negative Cognitive Error Questionnaire

Despite a proliferation of recent research examining childhood and adolescent depression, the area still lags behind the adult depression field, particularly in the investigation of cognitive correlates of affective psychopathology. To advance cognitive research with youth, the Children's Negative Cognitive Error Questionnaire (CNCEQ) was developed to provide a measure of cognitive distortions or errors in children and adolescents. Yet, few studies have employed the CNCEQ and no evidence exists supporting the validity of its four component cognitive error scales. The purpose of the present study was to examine the construct validity of the CNCEQ and its constituent scales through the use of factor analysis and criterion-group comparisons. Groups of adolescent psychiatric inpatients, diagnosed as affective or disruptive disordered, completed the CNCEQ following admission. Results failed to support the implicit four-factor structure of the CNCEQ, instead suggesting the appropriateness of a single-factor solution labeled "negative thinking." Despite no diagnostic group differences on the CNCEQ total or other scale scores, affective disordered patients evinced more cognitive errors on the Overgeneralizing scale. Findings suggest that the CNCEQ in its current stage of development holds promise, yet requires refinement to produce a valid measure of cognitive functioning in youth.     

Cytotoxicity of advanced glycation endproducts is mediated by oxidative stress

Non-enzymatic glycation of proteins with reducing sugars and subsequent transition metal catalysed oxidations leads to the formation of protein bound "advanced glycation endproducts" (AGEs). They accumulate on long-lived proteins and are for example structural components of the beta-amyloid plaques in Alzheimer's disease. Since the oxidation of glycated proteins as well as the interaction of AGEs with cell surface receptors produces superoxide radicals, it was tested in BHK 21 hamster fibroblast cells and SH-SY5Y human neuroblastoma cells if AGEs can exert cytotoxic effects on cells. Cell viability was assessed with three independent tests: MTT-assay (activity of the mitochondrial respiratory chain), lactate dehydrogenase assay (release of cytoplasmatic enzymes, membrane integrity) and Neutral Red assay (active uptake of a hydrophilic dye). Two model AGEs, chicken egg albumin-AGE and BSA-AGE, both caused significant cell death in a dose-dependent manner. The cytotoxic effects of AGEs could be attenuated by alpha-ketoglutarate and pyruvate, by antioxidants such as thioctic acid and N-acetylcysteine, and by aminoguanidine, an inhibitor of nitric oxide synthase. This suggests that reactive oxygen species as well as reactive nitrogen species contribute to AGE mediated cytotoxicity. Since AGEs accumulate on beta-amyloid plaques in AD over time, they may additionally contribute to oxidative stress, cell damage, functional loss and even neuronal cell death in the Alzheimer's disease brain.     

Scan-based volume animation driven by locally adaptive articulated registrations

This paper describes a complete system to create anatomically accurate example-based volume deformation and animation of articulated body regions, starting from multiple in vivo volume scans of a specific individual. In order to solve the correspondence problem across volume scans, a template volume is registered to each sample. The wide range of pose variations is first approximated by volume blend deformation (VBD), providing proper initialization of the articulated subject in different poses. A novel registration method is presented to efficiently reduce the computation cost while avoiding strong local minima inherent in complex articulated body volume registration. The algorithm highly constrains the degrees of freedom and search space involved in the nonlinear optimization, using hierarchical volume structures and locally constrained deformation based on the biharmonic clamped spline. Our registration step establishes a correspondence across scans, allowing a data-driven deformation approach in the volume domain. The results provide an occlusion-free person-specific 3D human body model, asymptotically accurate inner tissue deformations, and realistic volume animation of articulated movements driven by standard joint control estimated from the actual skeleton. Our approach also addresses the practical issues arising in using scans from living subjects. The robustness of our algorithms is tested by their applications on the hand, probably the most complex articulated region in the body, and the knee, a frequent subject area for medical imaging due to injuries.     

The Kemeny Constant for Finite Homogeneous Ergodic Markov Chains

A quantity known as the Kemeny constant, which is used to measure the expected number of links that a surfer on the World Wide Web, located on a random web page, needs to follow before reaching his/her desired location, coincides with the more well known notion of the expected time to mixing, i.e., to reaching stationarity of an ergodic Markov chain. In this paper we present a new formula for the Kemeny constant and we develop several perturbation results for the constant, including conditions under which it is a convex function. Finally, for chains whose transition matrix has a certain directed graph structure we show that the Kemeny constant is dependent only on the common length of the cycles and the total number of vertices and not on the specific transition probabilities of the chain.     

Automated bidding in computational markets: an application in market-based allocation of computing services

Autonomous agents are widely applied to automate interactions in robotics, e.g. for selling and purchasing goods on eBay, and in financial markets, e.g. in the form of quote machines and algorithmic traders. Current research investigates efficient economic mechanisms that fully automate the provisioning and usage processes of Grid-based services. On the one hand, consumers want to allocate resources on demand for their various applications, e.g. data sharing, stream processing, email, business applications and simulations. On the other hand, providers of Grid services want to govern business policies to meet their utilization and profit goals. The above-mentioned processes are not manually manageable, however, because decisions need to be taken within milliseconds. Therefore, such processes have to be automated to minimize human interactions. Hence, market mechanisms and strategic behavior play important roles when it comes to achieving automated and efficient allocation of Grid services. The paper begins by presenting a framework for automated bidding, providing a methodology for the design and implementation of configurable bidding strategies. Second, it presents a novel bidding strategy based on a reinforcement learning technique. This strategy is designed to automate the bid generation processes of consumers and providers in various market mechanisms. Third, the behavior and convergence of the strategy is evaluated in a centralized Continuous Double Auction and a decentralized on-line machine scheduling mechanism against selected benchmark bidding strategies. Fourth, we define a bidding language for communicating consumer and provider preferences to the market as well as report back the match of the market-based allocation process.     

The use of ‘exploratory learning’ for supporting immersive learning in virtual environments

User interfaces are becoming more intuitive following the requirements of the individual learner and reinforcing the drive towards more personalised learning and greater learner autonomy. There are clearly a new set of challenges emerging for teaching practitioners that will have implications upon not just what is learned but importantly upon lesson planning. This paper explores these changes to teaching through a consideration of an exploratory learning model which allows practitioners to rethink how they teach in 3D and immersive spaces where learning sequences and experiences are choreographed to support peer interactions and exchanges. The ELM extends from Kolb’s experiential learning model to adapt the use of 3D applications, and provides examples from research and development projects to exemplify how the model works in practice. Teaching in these contexts provides less emphasis upon curriculum and more emphasis upon sequencing learning experiences, meta-reflection, peer assessment and group work.     

Distributed top-<Emphasis Type="Italic">k</Emphasis> aggregation queries at large

Top-k query processing is a fundamental building block for efficient ranking in a large number of applications. Efficiency is a central issue, especially for distributed settings, when the data is spread across different nodes in a network. This paper introduces novel optimization methods for top-k aggregation queries in such distributed environments. The optimizations can be applied to all algorithms that fall into the frameworks of the prior TPUT and KLEE methods. The optimizations address three degrees of freedom: 1) hierarchically grouping input lists into top-k operator trees and optimizing the tree structure, 2) computing data-adaptive scan depths for different input sources, and 3) data-adaptive sampling of a small subset of input sources in scenarios with hundreds or thousands of query-relevant network nodes. All optimizations are based on a statistical cost model that utilizes local synopses, e.g., in the form of histograms, efficiently computed convolutions, and estimators based on order statistics. The paper presents comprehensive experiments, with three different real-life datasets and using the ns-2 network simulator for a packet-level simulation of a large Internet-style network.