Cooperative object transport with a swarm of e-puck robots: robustness and scalability of evolved collective strategies

Cooperative object transport in distributed multi-robot systems requires the coordination and synchronisation of pushing/pulling forces by a group of autonomous robots in order to transport items that cannot be transported by a single agent. The results of this study show that fairly robust and scalable collective transport strategies can be generated by robots equipped with a relatively simple sensory apparatus (i.e. no force sensors and no devices for direct communication). In the experiments described in this paper, homogeneous groups of physical e-puck robots are required to coordinate and synchronise their actions in order to transport a heavy rectangular cuboid object as far as possible from its starting position to an arbitrary direction. The robots are controlled by dynamic neural networks synthesised using evolutionary computation techniques. The best evolved controller demonstrates an effective group transport strategy that is robust to variability in the physical characteristics of the object (i.e. object mass and size of the longest object’s side) and scalable to different group sizes. To run these experiments, we designed, built, and mounted on the robots a new sensor that returns the agents’ displacement on a 2D plane. The study shows that the feedback generated by the robots’ sensors relative to the object’s movement is sufficient to allow the robots to coordinate their efforts and to sustain the transports for an extended period of time. By extensively analysing successful behavioural strategies, we illustrate the nature of the operational mechanisms underpinning the coordination and synchronisation of actions during group transport

Neurocranial osteology and neuroanatomy of a late Cretaceous Titanosaurian Sauropod from Spain (Ampelosaurus sp.)

Titanosaurians were a flourishing group of sauropod dinosaurs during Cretaceous times. Fossils of titanosaurians have been found on all continents and their remains are abundant in a number of Late Cretaceous sites. Nonetheless, the cranial anatomy of titanosaurians is still very poorly known. The Spanish latest Cretaceous locality of "Lo Hueco" yielded a relatively well preserved, titanosaurian braincase, which shares a number of phylogenetically restricted characters with Ampelosaurus atacis from France such as a flat occipital region. However, it appears to differ from A. atacis in some traits such as the greater degree of dorsoventral compression and the presence of proatlas facets. The specimen is, therefore, provisionally identified as Ampelosaurus sp. It was CT scanned, and 3D renderings of the cranial endocast and inner-ear system were generated. Our investigation highlights that, although titanosaurs were derived sauropods with a successful evolutionary history, they present a remarkably modest level of paleoneurological organization. Compared with the condition in the basal titanosauriform Giraffatitan brancai, the labyrinth of Ampelosaurus sp. shows a reduced morphology. The latter feature is possibly related to a restricted range of head-turning movementsThis is a contribution to the research project CGL2009-12143 (Ministerio de Economía y Competitividad, Madrid), of which FK, who is currently supported by the Ramón y Cajal Program, is Principal Investigator. LMW and RCR acknowledge funding support from the United States National Science Foundation (IBN-9601174, IBN-0343744, IOB-0517257, IOS-1050154) and the Ohio University Heritage College of Osteopathic Medicine. The Ohio Supercomputing Center also provided suppor

Environment influences on the aromatic character of nucleobases and amino acids

Geometric (HOMA) and magnetic (NICS) indices of aromaticity were estimated for aromatic rings of amino acids and nucleobases. Cartesian coordinates were taken directly either from PDB files deposited in public databases at the finest resolution available (≤1.5 Å), or from structures resulting from full gradient geometry optimization in a hybrid QM/MM approach. Significant environmental effects imposing alterations of HOMA values were noted for all aromatic rings analysed. Furthermore, even extra fine resolution (≤1.0 Å) is not sufficient for direct estimation of HOMA values based on Cartesian coordinates provided by PDB files. The values of mean bond errors seem to be much higher than the 0.05 Å often reported for PDB files. The use of quantum chemistry geometry optimization is strongly advised; even a simple QM/MM model comprising only the aromatic substructure within the QM region and the rest of biomolecule treated classically within the MM framework proved to be a promising means of describing aromaticity inside native environments. According to the results presented, three consequences of the interaction with the environment can be observed that induce changes in structural and magnetic indices of aromaticity. First, broad ranges of HOMA or NICS values are usually obtained for different conformations of nearest neighborhood. Next, these values and their means can differ significantly from those characterising isolated monomers. The most significant increase in aromaticities is expected for the six-membered rings of guanine, thymine and cytosine. The same trend was also noticed for all amino acids inside proteins but this effect was much smaller, reaching the highest value for the five-membered ring of tryptophan. Explicit water solutions impose similar changes on HOMA and NICS distributions. Thus, environment effects of protein, DNA and even explicit water molecules are non-negligible sources of aromaticity changes appearing in the rings of nucleobases and aromatic amino acids residues

The use of CAM and conventional treatments among primary care consulters with chronic musculoskeletal pain

Chronic musculoskeletal pain is the single most cited reason for use of complementary and alternative medicine (CAM). Primary care is the most frequent conventional medical service used by patients with pain in the UK. We are unaware, however, of a direct evidence of the extent of CAM use by primary care patients, and how successful they perceive it to be. Methods Aims and objectives To determine CAM use among patients with chronic musculoskeletal pain who have consulted about their pain in primary care. Study design Face-to-face interview-based survey. Setting Three general practices in North Staffordshire. Participants Respondents to a population pain survey who had reported having musculoskeletal pain in the survey and who had consulted about their pain in primary care in the previous 12 months as well as consenting to further research and agreeing to an interview. Information was gathered about their pain and the use of all treatments for pain, including CAM, in the previous year. Results 138 interviews were completed. 116 participants (84%) had used at least one CAM treatment for pain in the previous year. 65% were current users of CAM. The ratio of over-the-counter CAM use to care from a CAM provider was 3:2. 111 participants (80%) had used conventional treatment. 95 (69%) were using a combination of CAM and conventional treatment. Glucosamine and fish oil were the most commonly used CAM treatments (38%, 35% respectively). Most CAM treatments were scored on average as being helpful, and users indicated that they intended to use again 87% of the CAM treatments they had already used. Conclusion We provide direct evidence that most primary care consulters with chronic musculoskeletal pain have used CAM in the previous year, usually in combination with conventional treatments. The high prevalence and wide range of users experiences of benefit and harm from CAM strengthen the argument for more research into this type of medicine to quantify benefit and assess safety. The observation that most users of conventional medicine also used CAM suggests a continuing need for more investigation of effective pain management in primary care

Modeling the Spatial Distribution and Fruiting Pattern of a Key Tree Species in a Neotropical Forest: Methodology and Potential Applications

Damien Caillaud is with UT Austin and Max Planck Institute for Evolutionary Anthropology; Margaret C. Crofoot is with the Smithsonian Tropical Research Institute, Max Planck Institute for Ornithology, and Princeton University; Samuel V. Scarpino is with UT Austin; Patrick A. Jansen is with the Smithsonian Tropical Research Institute, Wageningen University, and University of Groningen; Carol X. Garzon-Lopez is with University of Groningen; Annemarie J. S. Winkelhagen is with Wageningen University; Stephanie A. Bohlman is with Princeton University; Peter D. Walsh is with VaccinApe.Background -- The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we demonstrate how advances in statistics permit the combination of sparse ground sampling with remote sensing imagery to generate biological relevant, spatially and temporally explicit distributions of food resources. We illustrate our procedure by creating a detailed simulation model of fruit production patterns for Dipteryx oleifera, a keystone tree species, on Barro Colorado Island (BCI), Panama. Methodology and Principal Findings -- Aerial photographs providing GPS positions for large, canopy trees, the complete census of a 50-ha and 25-ha area, diameter at breast height data from haphazardly sampled trees and long-term phenology data from six trees were used to fit 1) a point process model of tree spatial distribution and 2) a generalized linear mixed-effect model of temporal variation of fruit production. The fitted parameters from these models are then used to create a stochastic simulation model which incorporates spatio-temporal variations of D. oleifera fruit availability on BCI. Conclusions and Significance -- We present a framework that can provide a statistical characterization of the habitat that can be included in agent-based models of animal movements. When environmental heterogeneity cannot be exhaustively mapped, this approach can be a powerful alternative. The results of our model on the spatio-temporal variation in D. oleifera fruit availability will be used to understand behavioral and movement patterns of several species on BCI.The National Center For Ecological Analysis is supported by NSF Grant DEB-0553768, the University of California Santa Barbara and the State of California. The Forest Dynamics Plots were funded by NSF Grants to Stephen Hubbell DEB-0640386, DEB-0425651, DEB-0346488, DEB-0129874, DEB-00753102, DEB-9909347, DEB-9615226, DEB-9615226, DEB-9405933, DEB-9221033, DEB-9100058, DEB-8906869, DEB-8605042, DEB-8206992, DEB-7922197, and by the Center for Tropical Forest Science, the Smithsonian Tropical Forest Research Institute, The John D. and Catherine T. MacArthur Foundation, the Mellon Foundation and the Celera Foundation. DC is supported by NSF grant DEB-0749097 to L.A. Meyers. SS is supported by an NSF Graduate Research Fellowship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Biological Sciences, School o

Proteolysis of proBDNF Is a Key Regulator in the Formation of Memory

It is essential to understand the molecular processes underlying long-term memory to provide therapeutic targets of aberrant memory that produce pathological behaviour in humans. Under conditions of recall, fully-consolidated memories can undergo reconsolidation or extinction. These retrieval-mediated memory processes may rely on distinct molecular processes. The cellular mechanisms initiating the signature molecular events are not known. Using infusions of protein synthesis inhibitors, antisense oligonucleotide targeting brain-derived neurotrophic factor (BDNF) mRNA or tPA-STOP (an inhibitor of the proteolysis of BDNF protein) into the hippocampus of the awake rat, we show that acquisition and extinction of contextual fear memory depended on the increased and decreased proteolysis of proBDNF (precursor BDNF) in the hippocampus, respectively. Conditions of retrieval that are known to initiate the reconsolidation of contextual fear memory, a BDNF-independent memory process, were not correlated with altered proBDNF cleavage. Thus, the processing of BDNF was associated with the acquisition of new information and the updating of information about a salient stimulus. Furthermore, the differential requirement for the processing of proBDNF by tPA in distinct memory processes suggest that the molecular events actively engaged to support the storage and/or the successful retrieval of memory depends on the integration of ongoing experience with past learning

Systems Biology by the Rules: Hybrid Intelligent Systems for Pathway Modeling and Discovery

Background: Expert knowledge in journal articles is an important source of data for reconstructing biological pathways and creating new hypotheses. An important need for medical research is to integrate this data with high throughput sources to build useful models that span several scales. Researchers traditionally use mental models of pathways to integrate information and development new hypotheses. Unfortunately, the amount of information is often overwhelming and these are inadequate for predicting the dynamic response of complex pathways. Hierarchical computational models that allow exploration of semi-quantitative dynamics are useful systems biology tools for theoreticians, experimentalists and clinicians and may provide a means for cross-communication. Results: A novel approach for biological pathway modeling based on hybrid intelligent systems or soft computing technologies is presented here. Intelligent hybrid systems, which refers to several related computing methods such as fuzzy logic, neural nets, genetic algorithms, and statistical analysis, has become ubiquitous in engineering applications for complex control system modeling and design. Biological pathways may be considered to be complex control systems, which medicine tries to manipulate to achieve desired results. Thus, hybrid intelligent systems may provide a useful tool for modeling biological system dynamics and computational exploration of new drug targets. A new modeling approach based on these methods is presented in the context of hedgehog regulation of the cell cycle in granule cells. Code and input files can be found at the Bionet website: www.chip.ord/~wbosl/Software/Bionet. Conclusion: This paper presents the algorithmic methods needed for modeling complicated biochemical dynamics using rule-based models to represent expert knowledge in the context of cell cycle regulation and tumor growth. A notable feature of this modeling approach is that it allows biologists to build complex models from their knowledge base without the need to translate that knowledge into mathematical form. Dynamics on several levels, from molecular pathways to tissue growth, are seamlessly integrated. A number of common network motifs are examined and used to build a model of hedgehog regulation of the cell cycle in cerebellar neurons, which is believed to play a key role in the etiology of medulloblastoma, a devastating childhood brain cancer

The Mycobacterium tuberculosis Drugome and Its Polypharmacological Implications

We report a computational approach that integrates structural bioinformatics, molecular modelling and systems biology to construct a drug-target network on a structural proteome-wide scale. The approach has been applied to the genome of Mycobacterium tuberculosis (M.tb), the causative agent of one of today's most widely spread infectious diseases. The resulting drug-target interaction network for all structurally characterized approved drugs bound to putative M.tb receptors, we refer to as the ‘TB-drugome’. The TB-drugome reveals that approximately one-third of the drugs examined have the potential to be repositioned to treat tuberculosis and that many currently unexploited M.tb receptors may be chemically druggable and could serve as novel anti-tubercular targets. Furthermore, a detailed analysis of the TB-drugome has shed new light on the controversial issues surrounding drug-target networks [1]–[3]. Indeed, our results support the idea that drug-target networks are inherently modular, and further that any observed randomness is mainly caused by biased target coverage. The TB-drugome (http://funsite.sdsc.edu/drugome/TB) has the potential to be a valuable resource in the development of safe and efficient anti-tubercular drugs. More generally the methodology may be applied to other pathogens of interest with results improving as more of their structural proteomes are determined through the continued efforts of structural biology/genomics