What we can and cannot (yet) do with functional near infrared spectroscopy

Functional near infrared spectroscopy (NIRS) is a relatively new technique complimentary to EEG for the development of brain-computer interfaces (BCIs). NIRS-based systems for detecting various cognitive and affective states such as mental and emotional stress have already been demonstrated in a range of adaptive human–computer interaction (HCI) applications. However, before NIRS-BCIs can be used reliably in realistic HCI settings, substantial challenges oncerning signal processing and modeling must be addressed. Although many of those challenges have been identified previously, the solutions to overcome them remain scant. In this paper, we first review what can be currently done with NIRS, specifically, NIRS-based approaches to measuring cognitive and affective user states as well as demonstrations of passive NIRS-BCIs. We then discuss some of the primary challenges these systems would face if deployed in more realistic settings, including detection latencies and motion artifacts. Lastly, we investigate the effects of some of these challenges on signal reliability via a quantitative comparison of three NIRS models. The hope is that this paper will actively engage researchers to acilitate the advancement of NIRS as a more robust and useful tool to the BCI community

Does musical enrichment enhance the neural coding of syllables? Neuroscientific interventions and the importance of behavioral data

A commentary on: Music enrichment programs improve the neural encoding of speech in at-risk children by Kraus, N., Slater, J., Thompson, E. C., Hornickel, J., Strait, D. L., Nicol, T., et al. (2014). J. Neurosci. 34, 11913–11918. doi: 10.1523/JNEUROSCI.1881-14.201

The Public’s Perception of Humanlike Robots: Online Social Commentary Reflects an Appearance-Based Uncanny Valley, a General Fear of a “Technology Takeover”, and the Unabashed Sexualization of Female-Gendered Robots

Towards understanding the public’s perception of humanlike robots, we examined commentary on 24 YouTube videos depicting social robots ranging in human similarity – from Honda’s Asimo to Hiroshi Ishiguro’s Geminoids. In particular, we investigated how people have responded to the emergence of highly humanlike robots (e.g., Bina48) in contrast to those with more prototypically-“robotic” appearances (e.g., Asimo), coding the frequency at which the uncanny valley versus fears of replacement and/or a “technology takeover” arise in online discourse based on the robot’s appearance. Here we found that, consistent with Masahiro Mori’s theory of the uncanny valley, people’s commentary reflected an aversion to highly humanlike robots. Correspondingly, the frequency of uncanny valley-related commentary was significantly higher in response to highly humanlike robots relative to those of more prototypical appearances. Independent of the robots’ human similarity, we further observed a moderate correlation to exist between people’s explicit fears of a “technology takeover” and their emotional responding towards robots. Finally, through the course of our investigation, we encountered a third and rather disturbing trend – namely, the unabashed sexualization of female-gendered robots. In exploring the frequency at which this sexualization manifests in the online commentary, we found it to exceed that of both the uncanny valley and fears of robot sentience/replacement combined. In sum, these findings help to shed light on the relevance of the uncanny valley “in the wild” and further, they help situate it with respect to other design challenges for HRI

Robots Need the Ability to Navigate Abusive Interactions

Researchers are seeing more and more cases of abusive disinhibition towards robots in public realms. Because robots embody gendered identities, poor navigation of antisocial dynamics may reinforce or exacerbate gender-based violence. It is essential that robots deployed in social settings be able to recognize and respond to abuse in a way that minimises ethical risk. Enabling this capability requires designers to first understand the risk posed by abuse of robots, and hence how humans perceive robot-directed abuse. To that end, we experimentally investigated reactions to a physically abusive interaction between a human perpetrator and a victimized agent. Given extensions of gendered biases to robotic agents, as well as associations between an agent’s human likeness and the experiential capacity attributed to it, we quasi-manipulated the victim’s humanness (via use of a human actor vs. NAO robot) and gendering (via inclusion of stereotypically masculine vs. feminine cues in their presentation) across four video-recorded reproductions of the interaction. Analysis of data from 417 participants, each of whom watched one of the four videos, indicates that the intensity of emotional distress felt by an observer is associated with their gender identification, previous experience with victimization, hostile sexism, and support for social stratification, as well as the victim’s gendering

Witnessing Parental Violence and Cyber IPV Perpetration in Hispanic Emerging Adults: The Mediating Role of Attitudes Toward IPV

Recent studies indicate that the perpetration of intimate partner violence via cyberspaces (cyber IPV), namely, psychological aggression, sexual aggression, and cyberstalking is high among emerging adults. However, little is known of the risk factors that lead to cyber IPV and far lesser within Hispanic adults. Based on the intergenerational transmission of violence hypothesis, the present study examined the indirect effect of witnessing parental violence during childhood on the three types of cyber IPV through attitudes condoning IPV in Hispanic men and women, separately. Participants were 1,136 Hispanic emerging adults in the age range of 18-29 years (M = 20.53 years, SD = 2.42; 72.5% women, 88% Mexican descent). Over half of the participants (54.2%) witnessed at least one instance of parental violence during childhood. In contrast to women, men were more likely to hold attitudes accepting of IPV and perpetrate cyber sexual IPV, whereas women were more likely to report cyberstalking perpetration. Men and women with exposure to mother-to-father violence held attitudes justifying IPV that was associated with perpetrating the three cyber IPV types in adulthood (women: Brange = .016-.036; men: Brange = .016-.024). No significant gender differences were found in the associations of mother-to-father WPV and father-to-mother WPV on the three types of cyber IPV perpetration. These findings are discussed in the context of Hispanic culture, which has specific implications for cyber IPV intervention strategies

Upgrade of the protection system for superconducting circuits in the LHC

Prior to the re-start of the Large Hadron Collider LHC in 2009 the protection system for superconducting magnets and bus-bars QPS will be substantially upgraded. The foreseen modifications will enhance the capability of the system in detecting problems related to the electrical interconnections between superconducting magnets as well as the detection of so-called aperture symmetric quenches in the LHC main magnets

An Efficient Method of Modeling Material Properties Using a Thermal Diffusion Analogy: An Example Based on Craniofacial Bone

The ability to incorporate detailed geometry into finite element models has allowed researchers to investigate the influence of morphology on performance aspects of skeletal components. This advance has also allowed researchers to explore the effect of different material models, ranging from simple (e.g., isotropic) to complex (e.g., orthotropic), on the response of bone. However, bone's complicated geometry makes it difficult to incorporate complex material models into finite element models of bone. This difficulty is due to variation in the spatial orientation of material properties throughout bone. Our analysis addresses this problem by taking full advantage of a finite element program's ability to solve thermal-structural problems. Using a linear relationship between temperature and modulus, we seeded specific nodes of the finite element model with temperatures. We then used thermal diffusion to propagate the modulus throughout the finite element model. Finally, we solved for the mechanical response of the finite element model to the applied loads and constraints. We found that using the thermal diffusion analogy to control the modulus of bone throughout its structure provides a simple and effective method of spatially varying modulus. Results compare favorably against both experimental data and results from an FE model that incorporated a complex (orthotropic) material model. This method presented will allow researchers the ability to easily incorporate more material property data into their finite element models in an effort to improve the model's accuracy

Observation of a multimode plasma response and its relationship to density pumpout and edge-localized mode suppression

Density pumpout and edge-localized mode (ELM) suppression by applied n=2 magnetic fields in low-collisionality DIII-D plasmas are shown to be correlated with the magnitude of the plasma response driven on the high-field side (HFS) of the magnetic axis but not the low-field side (LFS) midplane. These distinct responses are a direct measurement of a multimodal magnetic plasma response, with each structure preferentially excited by a different n=2 applied spectrum and preferentially detected on the LFS or HFS. Ideal and resistive magneto-hydrodynamic (MHD) calculations find that the LFS measurement is primarily sensitive to the excitation of stable kink modes, while the HFS measurement is primarily sensitive to resonant currents (whether fully shielding or partially penetrated). The resonant currents are themselves strongly modified by kink excitation, with the optimal applied field pitch for pumpout and ELM suppression significantly differing from equilibrium field alignment.This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Fusion Energy Sciences, using the DIII-D National Fusion Facility, a DOE Office of Science user facility, under Awards No. DE-FC02-04ER54698, No. DE-AC02-09CH11466, No. DE-FG02-04ER54761, No. DE-AC05-06OR23100, No. DE-SC0001961, and No. DE-AC05-00OR22725. S. R. H. was supported by AINSE and ANSTO

RELICS: The Reionization Lensing Cluster Survey and the Brightest High-z Galaxies

Massive foreground galaxy clusters magnify and distort the light of objects behind them, permitting a view into both the extremely distant and intrinsically faint galaxy populations. We present here the z ~ 6-8 candidate high-redshift galaxies from the Reionization Lensing Cluster Survey (RELICS), a Hubble and Spitzer Space Telescope survey of 41 massive galaxy clusters spanning an area of ≈200 arcmin². These clusters were selected to be excellent lenses, and we find similar high-redshift sample sizes and magnitude distributions as the Cluster Lensing And Supernova survey with Hubble (CLASH). We discover 257, 57, and eight candidate galaxies at z ~ 6, 7, and 8 respectively, (322 in total). The observed (lensed) magnitudes of the z ~ 6 candidates are as bright as AB mag ~23, making them among the brightest known at these redshifts, comparable with discoveries from much wider, blank-field surveys. RELICS demonstrates the efficiency of using strong gravitational lenses to produce high-redshift samples in the epoch of reionization. These brightly observed galaxies are excellent targets for follow-up study with current and future observatories, including the James Webb Space Telescope