Biologically inspired visual landmark processing for simultaneous localization and mapping

This paper illustrates a method for finding useful visual landmarks for performing simultaneous localization and mapping (SLAM). The method is based loosely on biological principles, using layers of filtering and pooling to create learned templates that correspond to different views of the environment. Rather than using a set of landmarks and reporting range and bearing to the landmark, this system maps views to poses. The challenge is to produce a system that produces the same view for small changes in robot pose, but provides different views for larger changes in pose. The method has been developed to interface with the RatSLAM system, a biologically inspired method of SLAM. The paper describes the method of learning and recalling visual landmarks in detail, and shows the performance of the visual system in real robot tests.

A modified particle filter for simultaneous robot localization and landmark tracking in an indoor environment

This paper presents the implementation of a modified particle filter for vision-based simultaneous localization and mapping of an autonomous robot in a structured indoor environment. Through this method, artificial landmarks such as multi-coloured cylinders can be tracked with a camera mounted on the robot, and the position of the robot can be estimated at the same time. Experimental results in simulation and in real environments show that this approach has advantages over the extended Kalman filter with ambiguous data association and various levels of odometric noise.

Evaluation and comparison of mammalian subcellular localization prediction methods

Background: Determination of the subcellular location of a protein is essential to understanding its biochemical function. This information can provide insight into the function of hypothetical or novel proteins. These data are difficult to obtain experimentally but have become especially important since many whole genome sequencing projects have been finished and many resulting protein sequences are still lacking detailed functional information. In order to address this paucity of data, many computational prediction methods have been developed. However, these methods have varying levels of accuracy and perform differently based on the sequences that are presented to the underlying algorithm. It is therefore useful to compare these methods and monitor their performance. Results: In order to perform a comprehensive survey of prediction methods, we selected only methods that accepted large batches of protein sequences, were publicly available, and were able to predict localization to at least nine of the major subcellular locations (nucleus, cytosol, mitochondrion, extracellular region, plasma membrane, Golgi apparatus, endoplasmic reticulum (ER), peroxisome, and lysosome). The selected methods were CELLO, MultiLoc, Proteome Analyst, pTarget and WoLF PSORT. These methods were evaluated using 3763 mouse proteins from SwissProt that represent the source of the training sets used in development of the individual methods. In addition, an independent evaluation set of 2145 mouse proteins from LOCATE with a bias towards the subcellular localization underrepresented in SwissProt was used. The sensitivity and specificity were calculated for each method and compared to a theoretical value based on what might be observed by random chance. Conclusion: No individual method had a sufficient level of sensitivity across both evaluation sets that would enable reliable application to hypothetical proteins. All methods showed lower performance on the LOCATE dataset and variable performance on individual subcellular localizations was observed. Proteins localized to the secretory pathway were the most difficult to predict, while nuclear and extracellular proteins were predicted with the highest sensitivity.

Probabilistic visual recognition of artificial landmarks for simultaneous localization and mapping

Probabilistic robotics most often applied to the problem of simultaneous localisation and mapping (SLAM), requires measures of uncertainty to accompany observations of the environment. This paper describes how uncertainty can be characterised for a vision system that locates coloured landmarks in a typical laboratory environment. The paper describes a model of the uncertainty in segmentation, the internal cameral model and the mounting of the camera on the robot. It explains the implementation of the system on a laboratory robot, and provides experimental results that show the coherence of the uncertainty model.

Studies on Wilson loops, correlators and localization in supersymmetric quantum field theories

In this thesis we study at perturbative level correlation functions of Wilson loops (and local operators) and their relations to localization, integrability and other quantities of interest as the cusp anomalous dimension and the Bremsstrahlung function. First of all we consider a general class of 1/8 BPS Wilson loops and chiral primaries in N=4 Super Yang-Mills theory. We perform explicit two-loop computations, for some particular but still rather general configuration, that confirm the elegant results expected from localization procedure. We find notably full consistency with the multi-matrix model averages, obtained from 2D Yang-Mills theory on the sphere, when interacting diagrams do not cancel and contribute non-trivially to the final answer. We also discuss the near BPS expansion of the generalized cusp anomalous dimension with L units of R-charge. Integrability provides an exact solution, obtained by solving a general TBA equation in the appropriate limit: we propose here an alternative method based on supersymmetric localization. The basic idea is to relate the computation to the vacuum expectation value of certain 1/8 BPS Wilson loops with local operator insertions along the contour. Also these observables localize on a two-dimensional gauge theory on S^2, opening the possibility of exact calculations. As a test of our proposal, we reproduce the leading Luscher correction at weak coupling to the generalized cusp anomalous dimension. This result is also checked against a genuine Feynman diagram approach in N=4 super Yang-Mills theory. Finally we study the cusp anomalous dimension in N=6 ABJ(M) theory, identifying a scaling limit in which the ladder diagrams dominate. The resummation is encoded into a Bethe-Salpeter equation that is mapped to a Schroedinger problem, exactly solvable due to the surprising supersymmetry of the effective Hamiltonian. In the ABJ case the solution implies the diagonalization of the U(N) and U(M) building blocks, suggesting the existence of two independent cusp anomalous dimensions and an unexpected exponentation structure for the related Wilson loops.

Effect of vesicle size on tissue localization and immunogenicity of liposomal DNA vaccines

The formulation of plasmid DNA (pDNA) in cationic liposomes is a promising strategy to improve the potency of DNA vaccines. In this respect, physicochemical parameters such as liposome size may be important for their efficacy. The aim of the current study was to investigate the effect of vesicle size on the in vivo performance of liposomal pDNA vaccines after subcutaneous vaccination in mice. The tissue distribution of cationic liposomes of two sizes, 500 nm (PDI 0.6) and 140 nm (PDI 0.15), composed of egg PC, DOPE and DOTAP, with encapsulated OVA-encoding pDNA, was studied by using dual radiolabeled pDNA-liposomes. Their potency to elicit cellular and humoral immune responses was investigated upon application in a homologous and heterologous vaccination schedule with 3 week intervals. It was shown that encapsulation of pDNA into cationic lipsomes resulted in deposition at the site of injection, and strongest retention was observed at large vesicle size. The vaccination studies demonstrated a more robust induction of OVA-specific, functional CD8+ T-cells and higher antibody levels upon vaccination with small monodisperse pDNA-liposomes, as compared to large heterodisperse liposomes or naked pDNA. The introduction of a PEG-coating on the small cationic liposomes resulted in enhanced lymphatic drainage, but immune responses were not improved when compared to non-PEGylated liposomes. In conclusion, it was shown that the physicochemical properties of the liposomes are of crucial importance for their performance as pDNA vaccine carrier, and cationic charge and small size are favorable properties for subcutaneous DNA vaccination.

Understanding the role of self-identity in habitual risky behaviours: pedestrian road-crossing decisions across the lifespan

Self-identity as a careful pedestrian has not been fully considered in previous work on predicting intention to cross the road, or actual crossing behaviour, in non-optimal situations. Evidence suggests that self-identity may be a better predictor than attitudes in situations where decision-making styles have become habitual ways to respond. This study compared contributions of self-identity and attitudes to the prediction of intentions in two situations differing in level of habitual crossing expectation, and to crossing behaviour. Three hundred and sixty-two adults (17–92 years) completed a questionnaire measuring self-identity, attitudes, intentions, experience, social identity variables (e.g. age, gender) and personal limitations (mobility). Two hundred and five participants also completed a road-crossing simulation. Self-identity and attitude were both shown as significant independent predictors of intention in both situations. However, self-identity was less effective as a predictor in the higher risk scenario, where intention to perform the behaviour was lower, and for participants aged >75 years who had lower intention across scenarios. Self-identity strongly predicted intention to cross, which in turn predicted behaviour, but self-identity did not directly predict behaviour. Self-identity was strongly predicted by age. Implications for theories of compensation in older age and for design and targeting of pedestrian safety education are discussed.