Development and Training of a Neural Controller for Hind Leg Walking in a Dog Robot

Animals dynamically adapt to varying terrain and small perturbations with remarkable ease. These adaptations arise from complex interactions between the environment and biomechanical and neural components of the animal’s body and nervous system. Research into mammalian locomotion has resulted in several neural and neuro-mechanical models, some of which have been tested in simulation, but few “synthetic nervous systems” have been implemented in physical hardware models of animal systems. One reason is that the implementation into a physical system is not straightforward. For example, it is difficult to make robotic actuators and sensors that model those in the animal. Therefore, even if the sensorimotor circuits were known in great detail, those parameters would not be applicable and new parameter values must be found for the network in the robotic model of the animal. This manuscript demonstrates an automatic method for setting parameter values in a synthetic nervous system composed of non-spiking leaky integrator neuron models. This method works by first using a model of the system to determine required motor neuron activations to produce stable walking. Parameters in the neural system are then tuned systematically such that it produces similar activations to the desired pattern determined using expected sensory feedback. We demonstrate that the developed method successfully produces adaptive locomotion in the rear legs of a dog-like robot actuated by artificial muscles. Furthermore, the results support the validity of current models of mammalian locomotion. This research will serve as a basis for testing more complex locomotion controllers and for testing specific sensory pathways and biomechanical designs. Additionally, the developed method can be used to automatically adapt the neural controller for different mechanical designs such that it could be used to control different robotic systems

Provision of ecosystem services by hedges in urban domestic gardens: focus on rainfall mitigation

In the UK urban context, domestic gardens are an important resource, taking up to 25% of an urban area, with hedges being their popular and widespread features. Garden hedges are able to provide a number of ecosystem services, including mitigation of rainfall, trapping of particulate pollution, local temperature regulation etc. Using hedges as a model, we argue that differences in plants’ capacity to provide environmental benefits should be taken into account, in addition to their suitability for particular conditions, ornamental appeal and cost, when choosing plants for green spaces. The overarching aim of our project is to quantify the simultaneous provision of multiple services by several widely used hedge species and cultivars. In this paper, we are focusing on the provision of rainfall capture by the hedges. The following species and cultivars, differing in the leaf and canopy structure and size, and in some physiological parameters, were chosen for the study: Photinia x fraseri 'Red Robin', Thuja plicata ‘Atrovirens’, Taxus baccata, Ligustrum ovalifolium ‘Aureum’ and ‘Argenteum’ and Cotoneaster franchetii. The experiments were conducted June-July 2015 in glasshouses at the University of Reading, UK. We measured the water use of different species/cultivars (6 plant ‘treatments’ and bare substrate as a control, in 10 L containers, with 6-8 replicates each) and their ability to hold water within the canopy. Plants’ leaf and root biomass and leaf area (LA) were also measured. Species/cultivars differed in the capacity of canopies to retain water after a simulated rainfall event. Ligustrum ‘Aureum’ held significantly more water within the canopy than other species/cultivars, despite not having the largest LA. Furthermore, when differences in LA were taken into the account, Cotoneaster, Thuja, Taxus and Ligustrum ‘Argenteum’ lost most water per unit leaf area suggesting that they have the greatest potential to restore soil’s capacity to receive subsequent rainfall. Our initial findings confirm the hypothesis that differences in plant structure and function lead to different capacities for rainfall capture. This could inform our planting choices and help to manage/reduce problems associated with excess rainfall

Reactive Stepping with Functional Neuromuscular Stimulation in Response to Forward-Directed Perturbations

Background: Implanted motor system neuroprostheses can be effective at increasing personal mobility of persons paralyzed by spinal cord injuries. However, currently available neural stimulation systems for standing employ patterns of constant activation and are unreactive to changing postural demands. Methods: In this work, we developed a closed-loop controller for detecting forward-directed body disturbances and initiating a stabilizing step in a person with spinal cord injury. Forward-directed pulls at the waist were detected with three body-mounted triaxial accelerometers. A finite state machine was designed and tested to trigger a postural response and apply stimulation to appropriate muscles so as to produce a protective step when the simplified jerk signal exceeded predetermined thresholds. Results: The controller effectively initiated steps for all perturbations with magnitude between 10 and 17.5 s body weight, and initiated a postural response with occasional steps at 5% body weight. For perturbations at 15 and 17.5% body weight, the dynamic responses of the subject exhibited very similar component time periods when compared with able-bodied subjects undergoing similar postural perturbations. Additionally, the reactive step occurred faster for stronger perturbations than for weaker ones (p \u3c .005, unequal varience t-test.) Conclusions: This research marks progress towards a controller which can improve the safety and independence of persons with spinal cord injury using implanted neuroprostheses for standing

Biomechanical and Sensory Feedback Regularize the Behavior of Different Locomotor Central Pattern Generators

This work presents an in-depth numerical investigation into a hypothesized two-layer central pattern generator (CPG) that controls mammalian walking and how different parameter choices might affect the stepping of a simulated neuromechanical model. Particular attention is paid to the functional role of features that have not received a great deal of attention in previous work: the weak cross-excitatory connectivity within the rhythm generator and the synapse strength between the two layers. Sensitivity evaluations of deafferented CPG models and the combined neuromechanical model are performed. Locomotion frequency is increased in two different ways for both models to investigate whether the model’s stability can be predicted by trends in the CPG’s phase response curves (PRCs). Our results show that the weak cross-excitatory connection can make the CPG more sensitive to perturbations and that increasing the synaptic strength between the two layers results in a trade-off between forced phase locking and the amount of phase delay that can exist between the two layers. Additionally, although the models exhibit these differences in behavior when disconnected from the biomechanical model, these differences seem to disappear with the full neuromechanical model and result in similar behavior despite a variety of parameter combinations. This indicates that the neural variables do not have to be fixed precisely for stable walking; the biomechanical entrainment and sensory feedback may cancel out the strengths of excitatory connectivity in the neural circuit and play a critical role in shaping locomotor behavior. Our results support the importance of including biomechanical models in the development of computational neuroscience models that control mammalian locomotion

Empiric Deworming and CD4 Count Recovery in HIV-Infected Ugandans Initiating Antiretroviral Therapy

Background: There is conflicting evidence on the immunologic benefit of treating helminth co-infections (“deworming”) in HIV-infected individuals. Several studies have documented reduced viral load and increased CD4 count in antiretroviral therapy (ART) naïve individuals after deworming. However, there are a lack of data on the effect of deworming therapy on CD4 count recovery among HIV-infected persons taking ART. Methodology/Principal Findings To estimate the association between empiric deworming therapy and CD4 count after ART initiation, we performed a retrospective observational study among HIV-infected adults on ART at a publicly operated HIV clinic in southwestern Uganda. Subjects were assigned as having received deworming if prescribed an anti-helminthic agent between 7 and 90 days before a CD4 test. To estimate the association between deworming and CD4 count, we fit multivariable regression models and analyzed predictors of CD4 count, using a time-by-interaction term with receipt or non-receipt of deworming. From 1998 to 2009, 5,379 subjects on ART attended 21,933 clinic visits at which a CD4 count was measured. Subjects received deworming prior to 668 (3%) visits. Overall, deworming was not associated with a significant difference in CD4 count in either the first year on ART (β = 42.8; 95% CI, −2.1 to 87.7) or after the first year of ART (β = −9.9; 95% CI, −24.1 to 4.4). However, in a sub-analysis by gender, during the first year of ART deworming was associated with a significantly greater rise in CD4 count (β = 63.0; 95% CI, 6.0 to 120.1) in females. Conclusions/Significance: Empiric deworming of HIV-infected individuals on ART conferred no significant generalized benefit on subsequent CD4 count recovery. A significant association was observed exclusively in females and during the initial year on ART. Our findings are consistent with recent studies that failed to demonstrate an immunologic advantage to empirically deworming ART-naïve individuals, but suggest that certain sub-populations may benefit

Autumn MIST 2019

Maria-Theresia Walach, Greg Hunt, Alexandra Fogg and Alexander Bader report on the rescheduled Autumn MIST Meeting for 2019, organized by the MIST Council, which took place in January 2020

Infrared Spectral Energy Distributions of Seyfert Galaxies: Spitzer Space Telescope Observations of the 12 micron Sample of Active Galaxies

The mid-far-infrared spectral energy distributions (SEDs) of 83 active galaxies, mostly Seyfert galaxies, selected from the extended 12 micron sample are presented. The data were collected using all three instruments, IRAC, IRS, and MIPS, aboard the Spitzer Space Telescope. The IRS data were obtained in spectral mapping mode, and the photometric data from IRAC and IRS were extracted from matched, 20 arcsec diameter circular apertures. The MIPS data were obtained in SED mode, providing very low resolution spectroscopy (R ~ 20) between ~ 55 and 90 microns in a larger, 20 by 30 arcsec synthetic aperture. We further present the data from a spectral decomposition of the SEDs, including equivalent widths and fluxes of key emission lines; silicate 10 and 18 micron emission and absorption strengths; IRAC magnitudes; and mid-far infrared spectral indices. Finally, we examine the SEDs averaged within optical classifications of activity. We find that the infrared SEDs of Seyfert 1s and Seyfert 2s with hidden broad line regions (HBLR, as revealed by spectropolarimetry or other technique) are qualitatively similar, except that Seyfert 1s show silicate emission and HBLR Seyfert 2s show silicate absorption. The infrared SEDs of other classes with the 12 micron sample, including Seyfert 1.8-1.9, non-HBLR Seyfert 2 (not yet shown to hide a type 1 nucleus), LINER and HII galaxies, appear to be dominated by star-formation, as evidenced by blue IRAC colors, strong PAH emission, and strong far-infrared continuum emission, measured relative to mid-infrared continuum emission.Comment: 78 pages, 13 figure

Testing the Void against Cosmological data: fitting CMB, BAO, SN and H0

In this paper, instead of invoking Dark Energy, we try and fit various cosmological observations with a large Gpc scale under-dense region (Void) which is modeled by a Lemaitre-Tolman-Bondi metric that at large distances becomes a homogeneous FLRW metric. We improve on previous analyses by allowing for nonzero overall curvature, accurately computing the distance to the last-scattering surface and the observed scale of the Baryon Acoustic peaks, and investigating important effects that could arise from having nontrivial Void density profiles. We mainly focus on the WMAP 7-yr data (TT and TE), Supernova data (SDSS SN), Hubble constant measurements (HST) and Baryon Acoustic Oscillation data (SDSS and LRG). We find that the inclusion of a nonzero overall curvature drastically improves the goodness of fit of the Void model, bringing it very close to that of a homogeneous universe containing Dark Energy, while by varying the profile one can increase the value of the local Hubble parameter which has been a challenge for these models. We also try to gauge how well our model can fit the large-scale-structure data, but a comprehensive analysis will require the knowledge of perturbations on LTB metrics. The model is consistent with the CMB dipole if the observer is about 15 Mpc off the centre of the Void. Remarkably, such an off-center position may be able to account for the recent anomalous measurements of a large bulk flow from kSZ data. Finally we provide several analytical approximations in different regimes for the LTB metric, and a numerical module for CosmoMC, thus allowing for a MCMC exploration of the full parameter space.Comment: 70 pages, 12 figures, matches version accepted for publication in JCAP. References added, numerical values in tables changed due to minor bug, conclusions unaltered. Numerical module available at http://web.physik.rwth-aachen.de/download/valkenburg