Increasing scepticism toward potential liars: effects of existential threat on veracity judgments and the moderating role of honesty norm activation

With the present research, we investigated effects of existential threat on veracity judgments. According to several meta-analyses, people judge potentially deceptive messages of other people as true rather than as false (so-called truth bias). This judgmental bias has been shown to depend on how people weigh the error of judging a true message as a lie (error 1) and the error of judging a lie as a true message (error 2). The weight of these errors has been further shown to be affected by situational variables. Given that research on terror management theory has found evidence that mortality salience (MS) increases the sensitivity toward the compliance of cultural norms, especially when they are of focal attention, we assumed that when the honesty norm is activated, MS affects judgmental error weighing and, consequently, judgmental biases. Specifically, activating the norm of honesty should decrease the weight of error 1 (the error of judging a true message as a lie) and increase the weight of error 2 (the error of judging a lie as a true message) when mortality is salient. In a first study, we found initial evidence for this assumption. Furthermore, the change in error weighing should reduce the truth bias, automatically resulting in better detection accuracy of actual lies and worse accuracy of actual true statements. In two further studies, we manipulated MS and honesty norm activation before participants judged several videos containing actual truths or lies. Results revealed evidence for our prediction. Moreover, in Study 3, the truth bias was increased after MS when group solidarity was previously emphasized.

Structural insights into the allosteric activation mechanism of cGMP-dependent protein kinase I

Cyclic GMP-dependent protein kinase (PKG) is a key transducer in the NO-cGMP signaling pathway. In this line, PKG has been considered an important drug target for treating hypertensive cardiovascular and pulmonary diseases. However, the investigation of PKG’s allosteric activation mechanism has been hampered by a lack of structural information. One of the fundamental questions on the cGMP-dependent activation of PKG is how the enzyme can distinguish cGMP over cAMP and selectively respond to cGMP. To ensure proper signaling, PKG must have developed unique features to ensure its activation upon the right activation signal. In this thesis, the cGMP-selective activation mechanism of PKG was studied through determining crystal structures of three truncated constructs of the regulatory domain [CNB-A (92-227), CNB-B (271-369), and CNB-A/B (92-351)] of PKG Iβ in the absence or presence of cyclic nucleotides. Herein, two individual CNB domain structures with biochemical data revealed that the C-terminal CNB domain (CNB-B) is responsible for cGMP selectivity, while the N-terminal CNB-domain (CNB-A) has a higher binding affinity for both cGMP and cAMP without showing any selectivity. Based on these crystal structures, mutagenesis studies were performed in which the critical residues for cyclic nucleotide selectivity and activation were identified. Furthermore, we discovered that the conformational changes of the C-terminal helix of the CNB-B that bridges between the regulatory and catalytic domains including the hydrophobic capping interaction are crucial for PKG activation. In addition, to observe the global conformation of the activated R-domain, I solved a co-crystal structure of the CNB-A/B with cGMP. Although a monomeric construct was crystallized, the structure displays a dimer. Strikingly, the CNB-A domain and its bound cGMP provide a key interface for this dimeric interaction. Using small angle X-ray scattering (SAXS), the existence of the cGMP-mediated dimeric interface within the CNB domains was confirmed. Furthermore, measuring cGMP-binding affinities (EC50) of the dimeric interface mutants as well as determining activation constants (Ka) revealed that the interface formation is important for PKG activation. To conclude, this thesis study provides a new mechanistic insight in PKG activation along with a newly found interface that can be targeted for designing PKG-specific activity modulators.

KAM: Automatic Planning and Interpretation of Numerical Experiments Using Geometrical Methods

KAM is a computer program that can automatically plan, monitor, and interpret numerical experiments with Hamiltonian systems with two degrees of freedom. The program has recently helped solve an open problem in hydrodynamics. Unlike other approaches to qualitative reasoning about physical system dynamics, KAM embodies a significant amount of knowledge about nonlinear dynamics. KAM's ability to control numerical experiments arises from the fact that it not only produces pictures for us to see, but also looks at (sic---in its mind's eye) the pictures it draws to guide its own actions. KAM is organized in three semantic levels: orbit recognition, phase space searching, and parameter space searching. Within each level spatial properties and relationships that are not explicitly represented in the initial representation are extracted by applying three operations ---(1) aggregation, (2) partition, and (3) classification--- iteratively.

A Distributed Model for Mobile Robot Environment-Learning and Navigation

A distributed method for mobile robot navigation, spatial learning, and path planning is presented. It is implemented on a sonar-based physical robot, Toto, consisting of three competence layers: 1) Low-level navigation: a collection of reflex-like rules resulting in emergent boundary-tracing. 2) Landmark detection: dynamically extracts landmarks from the robot's motion. 3) Map learning: constructs a distributed map of landmarks. The parallel implementation allows for localization in constant time. Spreading of activation computes both topological and physical shortest paths in linear time. The main issues addressed are: distributed, procedural, and qualitative representation and computation, emergent behaviors, dynamic landmarks, minimized communication.

Automatic Analysis and Synthesis of Controllers for Dynamical Systems Based On P

I present a novel design methodology for the synthesis of automatic controllers, together with a computational environment---the Control Engineer's Workbench---integrating a suite of programs that automatically analyze and design controllers for high-performance, global control of nonlinear systems. This work demonstrates that difficult control synthesis tasks can be automated, using programs that actively exploit and efficiently represent knowledge of nonlinear dynamics and phase space and effectively use the representation to guide and perform the control design. The Control Engineer's Workbench combines powerful numerical and symbolic computations with artificial intelligence reasoning techniques. As a demonstration, the Workbench automatically designed a high-quality maglev controller that outperforms a previous linear design by a factor of 20.

Gender activation in transparent and opaque words

Resumen tomado de la publicaci??n

Automatic self-configuration of the logical network using distributed software agents

We present a system for dynamic network resource configuration in environments with bandwidth reservation. The proposed system is completely distributed and automates the mechanisms for adapting the logical network to the offered load. The system is able to manage dynamically a logical network such as a virtual path network in ATM or a label switched path network in MPLS or GMPLS. The system design and implementation is based on a multi-agent system (MAS) which make the decisions of when and how to change a logical path. Despite the lack of a centralised global network view, results show that MAS manages the network resources effectively, reducing the connection blocking probability and, therefore, achieving better utilisation of network resources. We also include details of its architecture and implementation

Automatic classification of breast density

A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. However, recent studies have shown that their sensitivity is significantly decreased as the density of the breast increases. This dependence is method specific. In this paper we propose a new approach to the classification of mammographic images according to their breast parenchymal density. Our classification uses information extracted from segmentation results and is based on the underlying breast tissue texture. Classification performance was based on a large set of digitised mammograms. Evaluation involves different classifiers and uses a leave-one-out methodology. Results demonstrate the feasibility of estimating breast density using image processing and analysis techniques

Overview of coded light projection techniques for automatic 3D profiling

Obtaining automatic 3D profile of objects is one of the most important issues in computer vision. With this information, a large number of applications become feasible: from visual inspection of industrial parts to 3D reconstruction of the environment for mobile robots. In order to achieve 3D data, range finders can be used. Coded structured light approach is one of the most widely used techniques to retrieve 3D information of an unknown surface. An overview of the existing techniques as well as a new classification of patterns for structured light sensors is presented. This kind of systems belong to the group of active triangulation method, which are based on projecting a light pattern and imaging the illuminated scene from one or more points of view. Since the patterns are coded, correspondences between points of the image(s) and points of the projected pattern can be easily found. Once correspondences are found, a classical triangulation strategy between camera(s) and projector device leads to the reconstruction of the surface. Advantages and constraints of the different patterns are discussed

The Role of Kinaesthetic Motor Imagery in Promoting Activation of the Lumbrical Muscles in the Hemiparetic Hand: a Randomised Controlled Study

The objective of the investigation who gave as result this work was to investigate the effectiveness of kinaesthetic motor imagery in the activation of the hemiplegic hand muscles following stroke. The experiment consisted of two random groups. Movements were measured after treatment. The participants were ten patients with hemiplegic hands (men who mean age was 74.4 years; mean time since stroke 3.05 months). All patients received three sessions of physical treatment based on an identical treatment protocol. Five patients were randomly assigned to an experimental group practising kinaesthetic motor imagery of a grasp using the 'lumbrical action' (experimental group). The others five (control group) followed a relaxation script. All the patients were then asked to grasp an object using the 'lumbrical action'. The grasps were recorded using an optoelectronic motion capture system. The magnitude of the extension of the index finger and the correlation of the angular displacement of the proximal phalangeal joints and the metacarpophalangeal joints were calculated. The movement time for the whole grip was calculated. The experimental group demonstrated higher extension in the index finger (p = < 0.01) and they had a higher correlation coefficient (0.99) than the control group (0.77) for the displacement of the proximal interphalangeal joint and the metacarpophalangeal joints. The movement time for the experimental group was faster, although the difference was not significant.

An automatic correction tool for relational database schemas

A Web-based tool developed to automatically correct relational database schemas is presented. This tool has been integrated into a more general e-learning platform and is used to reinforce teaching and learning on database courses. This platform assigns to each student a set of database problems selected from a common repository. The student has to design a relational database schema and enter it into the system through a user friendly interface specifically designed for it. The correction tool corrects the design and shows detected errors. The student has the chance to correct them and send a new solution. These steps can be repeated as many times as required until a correct solution is obtained. Currently, this system is being used in different introductory database courses at the University of Girona with very promising results

Automatic generation of active coordinates for quantum dynamics calculations: application to the dynamics of benzene photochemistry

A new practical method to generate a subspace of active coordinates for quantum dynamics calculations is presented. These reduced coordinates are obtained as the normal modes of an analytical quadratic representation of the energy difference between excited and ground states within the complete active space self-consistent field method. At the Franck-Condon point, the largest negative eigenvalues of this Hessian correspond to the photoactive modes: those that reduce the energy difference and lead to the conical intersection; eigenvalues close to 0 correspond to bath modes, while modes with large positive eigenvalues are photoinactive vibrations, which increase the energy difference. The efficacy of quantum dynamics run in the subspace of the photoactive modes is illustrated with the photochemistry of benzene, where theoretical simulations are designed to assist optimal control experiments

Front spreading in population dynamic models. Theory and application to the Neolithic transition

This thesis presents population dynamics models that can be applied to predict the rate of spread of the Neolithic transition (change from hunter-gathering to farming economics) across the European continent, which took place about 9000 to 5000 years ago. The first models in this thesis provide predictions at a continental scale. We develop population dynamics models with explicit kernels and apply realistic data. We also derive a new time-delayed reaction-diffusion equation which yields speeds about a 10% slower than previous models. We also deal with a regional variability: the slowdown of the Neolithic front when reaching the North of Europe. We develop simple reaction-diffusion models that can predict the measured speeds in terms of the non-homogeneous distribution of pre-Neolithic (Mesolithic) population in Europe, which were present in higher densities at the North of the continent. Such models can explain the observed speeds.