Laminar mixing of heterogeneous axisymmetric coaxial confined jets Final report

Laminar mixing of heterogeneous axisymmetrical coaxial confined jets for application to nuclear rocket propulsio

Impaired generalization of speaker identity in the perception of familiar and unfamiliar voices

In 2 behavioral experiments, we explored how the extraction of identity-related information from familiar and unfamiliar voices is affected by naturally occurring vocal flexibility and variability, introduced by different types of vocalizations and levels of volitional control during production. In a first experiment, participants performed a speaker discrimination task on vowels, volitional (acted) laughter, and spontaneous (authentic) laughter from 5 unfamiliar speakers. We found that performance was significantly impaired for spontaneous laughter, a vocalization produced under reduced volitional control. We additionally found that the detection of identity-related information fails to generalize across different types of nonverbal vocalizations (e.g., laughter vs. vowels) and across mismatches in volitional control within vocalization pairs (e.g., volitional laughter vs. spontaneous laughter), with performance levels indicating an inability to discriminate between speakers. In a second experiment, we explored whether personal familiarity with the speakers would afford greater accuracy and better generalization of identity perception. Using new stimuli, we largely replicated our previous findings: whereas familiarity afforded a consistent performance advantage for speaker discriminations, the experimental manipulations impaired performance to similar extents for familiar and unfamiliar listener groups. We discuss our findings with reference to prototype-based models of voice processing and suggest potential underlying mechanisms and representations of familiar and unfamiliar voice perception. (PsycINFO Database Record (c) 2016 APA, all rights reserved

How many voices did you hear? Natural variability disrupts identity perception from unfamiliar voices

Our voices sound different depending on the context (laughing vs. talking to a child vs. giving a speech), making within‐person variability an inherent feature of human voices. When perceiving speaker identities, listeners therefore need to not only ‘tell people apart’ (perceiving exemplars from two different speakers as separate identities) but also ‘tell people together’ (perceiving different exemplars from the same speaker as a single identity). In the current study, we investigated how such natural within‐person variability affects voice identity perception. Using voices from a popular TV show, listeners, who were either familiar or unfamiliar with this show, sorted naturally varying voice clips from two speakers into clusters to represent perceived identities. Across three independent participant samples, unfamiliar listeners perceived more identities than familiar listeners and frequently mistook exemplars from the same speaker to be different identities. These findings point towards a selective failure in ‘telling people together’. Our study highlights within‐person variability as a key feature of voices that has striking effects on (unfamiliar) voice identity perception. Our findings not only open up a new line of enquiry in the field of voice perception but also call for a re‐evaluation of theoretical models to account for natural variability during identity perception

Flexible voices : Identity perception from variable vocal signals

Human voices are extremely variable: The same person can sound very different depending on whether they are speaking, laughing, shouting or whispering. In order to successfully recognise someone from their voice, a listener needs to be able to generalize across these different vocal signals (‘telling people together’). However, in most studies of voice-identity processing to date, the substantial within-person variability has been eliminated through the use of highly controlled stimuli, thus focussing on how we tell people apart. We argue that this obscures our understanding of voice-identity processing by controlling away an essential feature of vocal stimuli that may include diagnostic information. In this paper, we propose that we need to extend the focus of voice-identity research to account for both “telling people together” as well as “telling people apart.” That is, we must account for whether, and to what extent, listeners can overcome within-person variability to obtain a stable percept of person identity from vocal cues. To do this, our theoretical and methodological frameworks need to be adjusted to explicitly include the study of within-person variability

Synthetic Protocells Interact with Viral Nanomachinery and Inactivate Pathogenic Human Virus

We present a new antiviral strategy and research tool that could be applied to a wide range of enveloped viruses that infect human beings via membrane fusion. We test this strategy on two emerging zoonotic henipaviruses that cause fatal encephalitis in humans, Nipah (NiV) and Hendra (HeV) viruses. In the new approach, artificial cell-like particles (protocells) presenting membrane receptors in a biomimetic manner were developed and found to attract and inactivate henipavirus envelope glycoprotein pseudovirus particles, preventing infection. The protocells do not accumulate virus during the inactivation process. The use of protocells that interact with, but do not accumulate, viruses may provide significant advantages over current antiviral drugs, and this general approach may have wide potential for antiviral development

Distinct neural systems recruited when speech production is modulated by different masking sounds

When talkers speak in masking sounds, their speech undergoes a variety of acoustic and phonetic changes. These changes are known collectively as the Lombard effect. Most behavioural research and neuroimaging research in this area has concentrated on the effect of energetic maskers such as white noise on Lombard speech. Previous fMRI studies have argued that neural responses to speaking in noise are driven by the quality of auditory feedback—that is, the audibility of the speaker's voice over the masker. However, we also frequently produce speech in the presence of informational maskers such as another talker. Here, speakers read sentences over a range of maskers varying in their informational and energetic content: speech, rotated speech, speech modulated noise, and white noise. Subjects also spoke in quiet and listened to the maskers without speaking. When subjects spoke in masking sounds, their vocal intensity increased in line with the energetic content of the masker. However, the opposite pattern was found neurally. In the superior temporal gyrus, activation was most strongly associated with increases in informational, rather than energetic, masking. This suggests that the neural activations associated with speaking in noise are more complex than a simple feedback response. I. INTRODUCTIO

Learning Two-input Linear and Nonlinear Analog Functions with a Simple Chemical System

The current biochemical information processing systems behave in a predetermined manner because all features are defined during the design phase. To make such unconventional computing systems reusable and programmable for biomedical applications, adaptation, learning, and self-modification baaed on external stimuli would be highly desirable. However, so far, it haa been too challenging to implement these in real or simulated chemistries. In this paper we extend the chemical perceptron, a model previously proposed by the authors, to function as an analog instead of a binary system. The new analog asymmetric signal perceptron learns through feedback and supports MichaelisMenten kinetics. The results show that our perceptron is able to learn linear and nonlinear (quadratic) functions of two inputs. To the best of our knowledge, it is the first simulated chemical system capable of doing so. The small number of species and reactions allows for a mapping to an actual wet implementation using DNA-strand displacement or deoxyribozymes. Our results are an important step toward actual biochemical systems that can learn and adapt

Self-assembled photosystem-I biophotovoltaics on nanostructured TiO2 and ZnO

The abundant pigment-protein membrane complex photosystem-I (PS-I) is at the heart of the Earth’s energy cycle. It is the central molecule in the “Z-scheme” of photosynthesis, converting sunlight into the chemical energy of life. Commandeering this intricately organized photosynthetic nanocircuitry and re-wiring it to produce electricity carries the promise of inexpensive and environmentally friendly solar power. We here report that dry PS-I stabilized by surfactant peptides functioned as both the light-harvester and charge separator in solar cells self-assembled on nanostructured semiconductors. Contrary to previous attempts at biophotovoltaics requiring elaborate surface chemistries, thin film deposition, and illumination concentrated into narrow wavelength ranges the devices described here are straightforward and inexpensive to fabricate and perform well under standard sunlight yielding open circuit photovoltage of 0.5 V, fill factor of 71%, electrical power density of 81 µW/cm2 and photocurrent density of 362 µA/cm2, over four orders of magnitude higher than any photosystem-based biophotovoltaic to date