A Data-driven Approach Towards Human-robot Collaborative Problem Solving in a Shared Space

We are developing a system for human-robot communication that enables people to communicate with robots in a natural way and is focused on solving problems in a shared space. Our strategy for developing this system is fundamentally data-driven: we use data from multiple input sources and train key components with various machine learning techniques. We developed a web application that is collecting data on how two humans communicate to accomplish a task, as well as a mobile laboratory that is instrumented to collect data on how two humans communicate to accomplish a task in a physically shared space. The data from these systems will be used to train and fine-tune the second stage of our system, in which the robot will be simulated through software. A physical robot will be used in the final stage of our project. We describe these instruments, a test-suite and performance metrics designed to evaluate and automate the data gathering process as well as evaluate an initial data set.Comment: 2017 AAAI Fall Symposium on Natural Communication for Human-Robot Collaboratio

Palpable Purpura in a Vietnamese Teenage Girl

A 19-year-old Vietnamese female with no significant past medical history presented to the emergency department (ED) with fevers, sore throat, generalized myalgias, arthralgias, and a worsening lower extremity rash for the past two weeks. Approximately one week after the onset of constitutional symptoms, the patient noticed a rash developing on the anterior surface of her legs. Three days prior to hospitalization, her primary care physician prescribed cephalexin for her, but she didn’t recall what it was for. When her symptoms continued to worsen the next few days, she presented to the ED. In the ED, she also complained of abdominal tenderness. She had no previous hospitalizations, and her vaccinations were up to date. She also had a small tattoo noted on her neck that she reported receiving at a reputable place four years ago. She was sexually active with her boyfriend, and did not regularly use condoms. However, she denied any genitourinary symptoms

Estimation of the spatial profile of neuromodulation and the temporal latency in motor responses induced by focused ultrasound brain stimulation

This study investigates the spatial profile and the temporal latency of the brain stimulation induced by the transcranial application of pulsed focused ultrasound (FUS). The site of neuromodulation was detected using 2-deoxy-2-[18F]fluoro-d-glucose PET immediately after FUS sonication on the unilateral thalamic area of Sprague–Dawley rats. The latency of the stimulation was estimated by measuring the time taken from the onset of the stimulation of the appropriate brain motor area to the corresponding tail motor response. The brain area showing elevated glucose uptake from the PET image was much smaller (56±10% in diameter, 24±6% in length) than the size of the acoustic focus, which is conventionally defined by the full-width at half-maximum of the acoustic intensity field. The spatial dimension of the FUS-mediated neuromodulatory area was more localized, approximated to be full-width at 90%-maximum of the acoustic intensity field. In addition, the time delay of motor responses elicited by the FUS sonication was 171±63 (SD) ms from the onset of sonication. When compared with latencies of other nonultrasonic neurostimulation techniques, the longer time delay associated with FUS-mediated motor responses is suggestive of the nonelectrical modes of neuromodulation, making it a distinctive brain stimulation method

Wavelet-based Gaussian-mixture hidden Markov model for the detection of multistage seizure dynamics: A proof-of-concept study

<p>Abstract</p> <p>Background</p> <p>Epilepsy is a common neurological disorder characterized by recurrent electrophysiological activities, known as seizures. Without the appropriate detection strategies, these seizure episodes can dramatically affect the quality of life for those afflicted. The rationale of this study is to develop an unsupervised algorithm for the detection of seizure states so that it may be implemented along with potential intervention strategies.</p> <p>Methods</p> <p>Hidden Markov model (HMM) was developed to interpret the state transitions of the <it>in vitro </it>rat hippocampal slice local field potentials (LFPs) during seizure episodes. It can be used to estimate the probability of state transitions and the corresponding characteristics of each state. Wavelet features were clustered and used to differentiate the electrophysiological characteristics at each corresponding HMM states. Using unsupervised training method, the HMM and the clustering parameters were obtained simultaneously. The HMM states were then assigned to the electrophysiological data using expert guided technique. Minimum redundancy maximum relevance (mRMR) analysis and Akaike Information Criterion (AICc) were applied to reduce the effect of over-fitting. The sensitivity, specificity and optimality index of chronic seizure detection were compared for various HMM topologies. The ability of distinguishing early and late tonic firing patterns prior to chronic seizures were also evaluated.</p> <p>Results</p> <p>Significant improvement in state detection performance was achieved when additional wavelet coefficient rates of change information were used as features. The final HMM topology obtained using mRMR and AICc was able to detect non-ictal (interictal), early and late tonic firing, chronic seizures and postictal activities. A mean sensitivity of 95.7%, mean specificity of 98.9% and optimality index of 0.995 in the detection of chronic seizures was achieved. The detection of early and late tonic firing was validated with experimental intracellular electrical recordings of seizures.</p> <p>Conclusions</p> <p>The HMM implementation of a seizure dynamics detector is an improvement over existing approaches using visual detection and complexity measures. The subjectivity involved in partitioning the observed data prior to training can be eliminated. It can also decipher the probabilities of seizure state transitions using the magnitude and rate of change wavelet information of the LFPs.</p

Zernike Phase Contrast Cryo-Electron Microscopy and Tomography for Structure Determination at Nanometer and Subnanometer Resolutions

Zernike phase contrast cryo-electron microscopy (ZPC-cryoEM) is an emerging technique that is capable of producing higher image contrast than conventional cryoEM. By combining this technique with advanced image processing methods, we achieved subnanometer resolution for two biological specimens: 2D bacteriorhodopsin crystal and epsilon15 bacteriophage. For an asymmetric reconstruction of epsilon15 bacteriophage, ZPC-cryoEM can reduce the required amount of data by a factor of ~3, compared with conventional cryoEM. The reconstruction was carried out to 13 Å resolution without the need to correct the contrast transfer function. New structural features at the portal vertex of the epsilon15 bacteriophage are revealed in this reconstruction. Using ZPC cryo-electron tomography (ZPC-cryoET), a similar level of data reduction and higher resolution structures of epsilon15 bacteriophage can be obtained relative to conventional cryoET. These results show quantitatively the benefits of ZPC-cryoEM and ZPC-cryoET for structural determinations of macromolecular machines at nanometer and subnanometer resolutions.National Institutes of Health (U.S.) (Grant P41RR002250)National Institutes of Health (U.S.) (Grant R01AI0175208)National Institutes of Health (U.S.) (Grant PN1EY016525)Robert Welch Foundation (Q1242

Idealized model for changes in equilibrium temperature, mixed layer depth, and boundary layer cloud over land in a doubled CO2 climate

An idealized equilibrium model for the undisturbed partly cloudy boundary layer (BL) is used as a framework to explore the coupling of the energy, water, and carbon cycles over land in midlatitudes and show the sensitivity to the clear‐sky shortwave flux, the midtropospheric temperature, moisture, CO2, and subsidence. The changes in the surface fluxes, the BL equilibrium, and cloud cover are shown for a warmer, doubled CO2 climate. Reduced stomatal conductance in a simple vegetation model amplifies the background 2 K ocean temperature rise to an (unrealistically large) 6 K increase in near‐surface temperature over land, with a corresponding drop of near‐surface relative humidity of about 19%, and a rise of cloud base of about 70 hPa. Cloud changes depend strongly on changes of mean subsidence; but evaporative fraction (EF) decreases. EF is almost uniquely related to mixed layer (ML) depth, independent of background forcing climate. This suggests that it might be possible to infer EF for heterogeneous landscapes from ML depth. The asymmetry of increased evaporation over the oceans and reduced transpiration over land increases in a warmer doubled CO2 climate

Hypothalamic-pituitary-adrenal stress axis function and the relationship with chronic widespread pain and its antecedents

In clinic studies, altered hypothalamic-pituitary-adrenal (HPA) axis function has been associated with fibromyalgia, a syndrome characterised by chronic widespread body pain. These results may be explained by the associated high rates of psychological distress and somatisation. We address the hypothesis that the latter, rather than the pain, might explain the HPA results. A population study ascertained pain and psychological status in subjects aged 25 to 65 years. Random samples were selected from the following three groups: satisfying criteria for chronic widespread pain; free of chronic widespread pain but with strong evidence of somatisation ('at risk'); and a reference group. HPA axis function was assessed from measuring early morning and evening salivary cortisol levels, and serum cortisol after physical (pain pressure threshold exam) and chemical (overnight 0.25 mg dexamethasone suppression test) stressors. The relationship between HPA function with pain and the various psychosocial scales assessed was modelled using appropriate regression analyses, adjusted for age and gender. In all 131 persons with chronic widespread pain (participation rate 74%), 267 'at risk' (58%) and 56 controls (70%) were studied. Those in the chronic widespread pain and 'at risk' groups were, respectively, 3.1 (95% CI (1.3, 7.3)) and 1.8 (0.8, 4.0) times more likely to have a saliva cortisol score in the lowest third. None of the psychosocial factors measured were, however, associated with saliva cortisol scores. Further, those in the chronic widespread pain (1.9 (0.8, 4.7)) and 'at risk' (1.6 (0.7, 3.6)) groups were also more likely to have the highest serum cortisol scores. High post-stress serum cortisol was related to high levels of psychological distress (p = 0.05, 95% CI (0.02, 0.08)). After adjusting for levels of psychological distress, the association between chronic widespread pain and post-stress cortisol scores remained, albeit slightly attenuated. This is the first population study to demonstrate that those with established, and those psychologically at risk of, chronic widespread pain demonstrate abnormalities of HPA axis function, which are more marked in the former group. Although some aspects of the altered function are related to the psychosocial factors measured, we conclude that the occurrence of HPA abnormality in persons with chronic widespread pain is not fully explained by the accompanying psychological stress