Manifold learning for robot navigation

In this paper we introduce methods to build a SOM that can be used as an isometric map for mobile robots. That is, given a dataset of sensor readings collected at points uniformly distributed with respect to the ground, we wish to build a SOM whose neurons (prototype vectors in sensor space) correspond to points uniformly distributed on the ground. Manifold learning techniques have already been used for dimensionality reduction of sensor space in navigation systems. Our focus is on the isometric property of the SOM. For reliable path-planning and information sharing between several robots, it is desirable that the robots build an internal representation of the sensor manifold, a map, that is isometric with the environment. We show experimentally that standard Non-Linear Dimensionality Reduction (NLDR) algorithms do not provide isometric maps for range data and bearing data. However, the auxiliary low dimensional manifolds created can be used to improve the distribution of the neurons of a SOM (that is, make the neurons more evenly distributed with respect to the ground). We also describe a method to create an isometric map from a sensor readings collected along a polygonal line random walk.     

Active navigation with a monocular robot

 A scheme is presented that uses the self-motion of a robot, equipped with a single visual sensor, to navigate in a safe manner. The motion strategy used is modelled on the motion of insects that effectively have a single eye and must move in order to determine range. The essence of the strategy is to employ a zigzag motion in order to (a) estimate the range to objects and (b) know the safe distance of travel in the present direction. An example is presented of a laboratory robot moving in a cluttered environment. The results show that this motion strategy can be successfully employed in an autonomous robot to avoid collisions. Received: 17 August 1993/Accepted: 2 May 1994     

Case study on a self-organizing spiking neural network for robot navigation

This paper presents a Spiking Neural Network (SNN) architecture for mobile robot navigation. The SNN contains 4 layers where dynamic synapses route information to the appropriate neurons in each layer and the neurons are modeled using the Leaky Integrate and Fire (LIF) model. The SNN learns by self-organizing its connectivity as new environmental conditions are experienced and consequently knowledge about its environment is stored in the connectivity. Also a novel feature of the proposed SNN architecture is that it uses working memory, where present and previous sensor states are stored. Results are presented for a wall following application.     

Waypoint based path planner for socially aware robot navigation

Cluster Computing - Social navigation is beneficial for mobile robots in human inhabited areas. In this paper, we focus on smooth path tracking and handling disruptions during plan execution in...     

Drosophila pacemaker neurons require g protein signaling and GABAergic inputs to generate twenty-four hour behavioral rhythms

Intercellular signaling is important for accurate circadian rhythms. In Drosophila, the small ventral lateral neurons (s-LN(v)s) are the dominant pacemaker neurons and set the pace of most other clock neurons in constant darkness. Here we show that two distinct G protein signaling pathways are required in LN(v)s for 24?hr rhythms. Reducing signaling in LN(v)s via the G alpha subunit Gs, which signals via cAMP, or via the G alpha subunit Go, which we show signals via Phospholipase 21c, lengthens the period of behavioral rhythms. In contrast, constitutive Gs or Go signaling makes most flies arrhythmic. Using dissociated LN(v)s in culture, we found that Go and the metabotropic GABA(B)-R3 receptor are required for the inhibitory effects of GABA on LN(v)s and that reduced GABA(B)-R3 expression in?vivo lengthens period. Although no clock neurons produce GABA, hyperexciting GABAergic neurons disrupts behavioral rhythms and s-LN(v) molecular clocks. Therefore, s-LN(v)s require GABAergic inputs for 24?hr rhythms.     

Emergent properties in the behaviour of a virtual spider robot

Using a virtual spider robot, we studied hypotheses about the weaving behaviour of orb spiders. Our model spiders built virtual webs that mimicked perfectly the visual architecture of real webs of the garden cross spider Araneus diadematus. The matching of capture spiral and auxiliary spiral pitch was an apparently emergent property in both types of web. This validated our interpretation of the garden spider''s web-building decision rules, which use strictly local interactions with previously placed threads to generate global architecture.     

Influence of a mobile robot on the spatial behaviour of quail chicks

Quail chicks encountered an autonomous mobile robot during their early development. The robot incorporated a heat source that stimulated following of chicks. The spatial behaviour of grown-up chicks was tested in an exploration test and a detour test. Chicks that grew with the mobile robot exhibited better spatial abilities than chicks grown with a static heat source. We discuss these results in the perspective of animal-robot interaction and of the role of early spatial experience on the behavioural development.     

LINKER: a program to generate linker sequences for fusion proteins

The construction of functional fusion proteins often requires a linker sequence that adopts an extended conformation to allow for maximal flexibility. Linker sequences are generally selected based on intuition. Without a reliable selection criterion, the design of such linkers is often difficult, particularly in situations where longer linker sequences are required. Here we describe a program called LINKER which can automatically generate a set of linker sequences that are known to adopt extended conformations as determined by X-ray crystallography and NMR. The only required input to the program is the desired linker sequence length. The program is specifically designed to assist in fusion protein construction. A number of optional input parameters have been incorporated so that users are able to enhance sequence selection based on specific applications. The program output simply contains a set of sequences with a specified length. This program should be a useful tool in both the biotechnology industry and biomedical research. It can be accessed through the Web page http://www.fccc. edu/research/labs/feng/linker.html.     

Litter inputs to a tropical Australian rainforest stream

Abstract Vertical litterfall and lateral litter movement were monitored in the riparian zone of Birthday Creek, a small upland rainforest stream in north Queensland, from June 1987 to May 1990. Total litterfall (mean = 484 g m^?2 year-1) was low in comparison with other tropical sites both within Australia and elsewhere. Litterfall was distinctly seasonal, with maxima occurring in the spring (October-November) and minima in winter (June–July). Tropical storms caused short-term increases in litterfall, especially of the small wood fraction. Overall, laterally transported litter contributed 6.8% of the total litter input to the monitored section of the stream. Lateral movement varied according to bank slope and microtopographic features and was not related to wind. Nitrogen and phosphorus concentration of leaves were low (mean N= 1.26%, P = 0.029% by weight). Nitrogen concentration of laterally transported levels overall was about 19% higher than that of leaves falling directly into the stream.     

Actin on multiple fronts to generate a muscle fiber

How the actin cytoskeleton is harnessed to fulfill its diverse cellular functions is a recurrent and intriguing question. In this issue of Developmental Cell, Kim et al. and Massarwa et al. describe a new role for F-actin, and more specifically the actin regulator WASp, in myoblast fusion in Drosophila.     

Distinguishing signals and cues: bumblebees use general footprints to generate adaptive behaviour at flowers and nest

Chemicals used in communication are divided into signals and cues. Signals are moulded by natural selection to carry specific meanings in specific contexts. Cues, on the other hand, have not been moulded by natural selection to carry specific information for intended receivers. Distinguishing between these two modes of information transfer is difficult when animals do not perform obvious secretion behaviours. Although a number of insects have been suspected of leaving cues at food sites and nest entrances, studies have not attempted to experimentally distinguish between cues and signals. Here, we examine the chemical composition of the scent marks left by the bumblebee Bombus terrestris at food sites and compare it to those found at a neutral location. If bees are depositing a cue, we expect the same chemicals to be found at both sites, but if they deposit a signal we only expect to find the scent marks at the food site. We were also interested in identifying the chemicals left at the nest entrance to determine if they differed from those used to mark food sites. We find that bees deposit the same chemicals at food, nest and neutral sites. Therefore, bumblebees leave behind general chemical footprints everywhere they walk and we propose that they learn to use these footprints in a manner that ultimately enhances their fitness, for example, to improve their foraging efficiency and locate their nest. Experimentally, distinguishing these two modes of information transfer is crucial for understanding how they interact to shape animal behaviour and what chemical bouquets are under natural selection. Handling Editor: Heikki Hokkanen     

MaGIC: a program to generate targeted marker sets for genome-wide association studies

High-throughput genotyping technologies such as DNA pooling and DNA microarrays mean that whole-genome screens are now practical for complex disease gene discovery using association studies. Because it is currently impractical to use all available markers, a subset is typically selected on the basis of required saturation density. Restricting markers to those within annotated genomic features of interest (e.g., genes or exons) or within feature-rich regions, reduces workload and cost while retaining much information. We have designed a program (MaGIC) that exploits genome assembly data to create lists of markers correlated with other genomic features. Marker lists are generated at a user-defined spacing and can target features with a user-defined density. Maps are in base pairs or linkage disequilibrium units (LDUs) as derived from the International HapMap data, which is useful for association studies and fine-mapping. Markers may be selected on the basis of heterozygosity and source database, and single nucleotide polymorphism (SNP) markers may additionally be selected on the basis of validation status. The import function means the method can be used for any genomic features such as housekeeping genes, long interspersed elements (LINES), or Alu repeats in humans, and is also functional for other species with equivalent data. The program and source code is freely available at http://cogent.iop.kcl.ac.uk/MaGIC.cogx.     

Nested reentrant and recurrent computation in early vision: a Bayesian neuromorphic model applied to hyperacuity

 Hyperacuity is demonstrated in a neuromorphic model of the early visual system. The model incorporates Bayesian principles which are embodied in the dynamics of reentrant and recurrent feedback processes. Each retinotopically mapped area in the model represents a transformation of data from the visual field. Sensory information propagates in a bottom-up direction from one area to the next, while information based on Bayesian priors propagates in a top-down direction through reentrant connections. The ‘bottom-up’ and ‘top-down’ information maintain a separate existence in distinct layers of the model, but they interact through local connections within each area. Transformations between one area and the next are defined by the reentrant synaptic connections between areas, while local prior probability maps are defined by local recurrent connections within layers. The representation of hyperacuity is accomplished using a model of functional multiplicity: the large ratio of neurons in striate cortex compared with the number of afferent fibers projecting from the lateral geniculate nucleus. High functional multiplicity, in conjunction with hierarchical reentrant processing, allows the model to represent a fine-grained restoration of the line structure of visual input. Received : 26 April 1995 / Accepted in revised form : 27 July 1996     

Sensitivity to dimethyl sulphide suggests a mechanism for olfactory navigation by seabirds

Petrels, albatrosses and other procellariiform seabirds have an excellent sense of smell, and routinely navigate over the world's oceans by mechanisms that are not well understood. These birds travel thousands of kilometres to forage on ephemeral prey patches at variable locations, yet they can quickly and efficiently find their way back to their nests on remote islands to provision chicks, even with magnetic senses experimentally disrupted. Over the seemingly featureless ocean environment, local emissions of scents released by phytoplankton reflect bathymetric features such as shelf breaks and seamounts. These features suggest an odour landscape that may provide birds with orientation cues. We have previously shown that concentrated experimental deployments of one such compound, dimethyl sulphide (DMS), attracts procellariiforms at sea, suggesting that some species can use it as a foraging cue. Here we present the first physiological demonstration that an Antarctic seabird can detect DMS at biogenic levels. We further show that birds can use DMS as an orientation cue in a non-foraging context within a concentration range that they might naturally encounter over the ocean.     

SimPed: a simulation program to generate haplotype and genotype data for pedigree structures

With the widespread availability of SNP genotype data, there is great interest in analyzing pedigree haplotype data. Intermarker linkage disequilibrium for microsatellite markers is usually low due to their physical distance; however, for dense maps of SNP markers, there can be strong linkage disequilibrium between marker loci. Linkage analysis (parametric and nonparametric) and family-based association studies are currently being carried out using dense maps of SNP marker loci. Monte Carlo methods are often used for both linkage and association studies; however, to date there are no programs available which can generate haplotype and/or genotype data consisting of a large number of loci for pedigree structures. SimPed is a program that quickly generates haplotype and/or genotype data for pedigrees of virtually any size and complexity. Marker data either in linkage disequilibrium or equilibrium can be generated for greater than 20,000 diallelic or multiallelic marker loci. Haplotypes and/or genotypes are generated for pedigree structures using specified genetic map distances and haplotype and/or allele frequencies. The simulated data generated by SimPed is useful for a variety of purposes, including evaluating methods that estimate haplotype frequencies for pedigree data, evaluating type I error due to intermarker linkage disequilibrium and estimating empirical p values for linkage and family-based association studies.     

Social behaviour of dogs encountering AIBO, an animal-like robot in a neutral and in a feeding situation

The use of animal-like autonomous robots might offer new possibilities in the study of animal interactions, if the subject recognises it as a social partner. In this paper we investigate whether AIBO, a dog-like robot of the Sony Corp. can be used for this purpose. Twenty-four adult and sixteen 4-5 months old pet dogs were tested in two situations where subjects encountered one of four different test-partners: (1) a remote controlled car; (2) an AIBO robot; (3) AIBO with a puppy-scented furry cover; and (4) a 2-month-old puppy. In the neutral situation the dog could interact freely with one of the partners for 1 min in a closed arena in the presence of its owner. In the feeding situation the encounters were started while the dog was eating food. Our results show that age and context influence the social behaviour of dogs. Further, we have found that although both age groups differentiated the living and non-living test-partners for some extent, the furry AIBO evoked significantly increased responses in comparison to the car. These experiments show the first steps towards the application of robots in behavioural studies, notwithstanding that at present AIBO's limited ability to move constrains its effectiveness as social partner for dogs.     

A novel mechanism for acetylcholine to generate diacylglycerol in brain

The classical scheme involving inositol phospholipid breakdown by phospholipase C as the sole source of diacylglycerol (DAG) has recently been challenged by evidence that phosphatidylcholine (PC) is an alternative source. In synaptic membranes of canine cerebral cortex, cholinergic agonists caused rapid accumulation of [3H]phosphatidic acid (PA) from [3H]PC within 15 s, whereas [3H]DAG formation showed a transient lag period before becoming elevated and then exceeding the amount of [3H]PA. Additional evidence shows that DAG is produced from PC by the action of phospholipase D to yield PA, which is further dephosphorylated to DAG by PA phosphatase. Our results indicate that this muscarinic acetylcholine receptor-regulated PC phospholipase D-PA phosphatase pathway may be a novel mechanism in cell signal transduction processes for activation of protein kinase C in brain.     

Using cellular automata to generate image representation for biological sequences

Summary. A novel approach to visualize biological sequences is developed based on cellular automata (Wolfram, S. Nature 1984, 311, 419–424), a set of discrete dynamical systems in which space and time are discrete. By transforming the symbolic sequence codes into the digital codes, and using some optimal space-time evolvement rules of cellular automata, a biological sequence can be represented by a unique image, the so-called cellular automata image. Many important features, which are originally hidden in a long and complicated biological sequence, can be clearly revealed thru its cellular automata image. With biological sequences entering into databanks rapidly increasing in the post-genomic era, it is anticipated that the cellular automata image will become a very useful vehicle for investigation into their key features, identification of their function, as well as revelation of their fingerprint. It is anticipated that by using the concept of the pseudo amino acid composition (Chou, K.C. Proteins: Structure, Function, and Genetics, 2001, 43, 246–255), the cellular automata image approach can also be used to improve the quality of predicting protein attributes, such as structural class and subcellular location.     

Systematic search for recipes to generate induced pluripotent stem cells

Generation of induced pluripotent stem cells (iPSCs) opens a new avenue in regenerative medicine. One of the major hurdles for therapeutic applications is to improve the efficiency of generating iPSCs and also to avoid the tumorigenicity, which requires searching for new reprogramming recipes. We present a systems biology approach to efficiently evaluate a large number of possible recipes and find those that are most effective at generating iPSCs. We not only recovered several experimentally confirmed recipes but we also suggested new ones that may improve reprogramming efficiency and quality. In addition, our approach allows one to estimate the cell-state landscape, monitor the progress of reprogramming, identify important regulatory transition states, and ultimately understand the mechanisms of iPSC generation.