1,903 research outputs found
The KW-boundary hybrid digital waveguide mesh for room acoustics applications
The digital waveguide mesh is a discrete-time simulation used to model acoustic wave propagation through a bounded medium. It can be applied to the simulation of the acoustics of rooms through the generation of impulse responses suitable for auralization purposes. However, large-scale three-dimensional mesh structures are required for high quality results. These structures must therefore be efficient and also capable of flexible boundary implementation in terms of both geometrical layout and the possibility for improved mesh termination algorithms. The general one-dimensional N-port boundary termination is investigated, where N depends on the geometry of the modeled domain and the mesh topology used. The equivalence between physical variable Kirchoff-model, and scattering-based wave-model boundary formulations is proved. This leads to the KW-hybrid one-dimensional N-port boundary-node termination, which is shown to be equivalent to the Kirchoff- and wave-model cases. The KW-hybrid boundary-node is implemented as part of a new hybrid two-dimensional triangular digital waveguide mesh. This is shown to offer the possibility for large-scale, computationally efficient mesh structures for more complex shapes. It proves more accurate than a similar rectilinear mesh in terms of geometrical fit, and offers significant savings in processing time and memory use over a standard wave-based model. The new hybrid mesh also has the potential for improved real-world room boundary simulations through the inclusion of additional mixed modeling algorithms
'Unlicensed' natural killer cells dominate the response to cytomegalovirus infection.
Natural killer (NK) cells expressing inhibitory receptors that bind to self major histocompatibility complex (MHC) class I are 'licensed', or rendered functionally more responsive to stimulation, whereas 'unlicensed' NK cells lacking receptors for self MHC class I are hyporesponsive. Here we show that contrary to the licensing hypothesis, unlicensed NK cells were the main mediators of NK cell-mediated control of mouse cytomegalovirus infection in vivo. Depletion of unlicensed NK cells impaired control of viral titers, but depletion of licensed NK cells did not. The transfer of unlicensed NK cells was more protective than was the transfer of licensed NK cells. Signaling by the tyrosine phosphatase SHP-1 limited the proliferation of licensed NK cells but not that of unlicensed NK cells during infection. Thus, unlicensed NK cells are critical for protection against viral infection
Reduced neural sensitivity to social stimuli in infants at risk for autism
In the hope of discovering early markers of autism, attention has recently turned to the study of infants at risk owing to being the younger siblings of children with autism. Because the condition is highly heritable, later-born siblings of diagnosed children are at substantially higher risk for developing autism or the broader autism phenotype than the general population. Currently, there are no strong predictors of autism in early infancy and diagnosis is not reliable until around 3 years of age. Because indicators of brain functioning may be sensitive predictors, and atypical social interactions are characteristic of the syndrome, we examined whether temporal lobe specialization for processing visual and auditory social stimuli during infancy differs in infants at risk. In a functional near-infrared spectroscopy study, infants aged 4–6 months at risk for autism showed less selective neural responses to social stimuli (auditory and visual) than low-risk controls. These group differences could not be attributed to overall levels of attention, developmental stage or chronological age. Our results provide the first demonstration of specific differences in localizable brain function within the first 6 months of life in a group of infants at risk for autism. Further, these differences closely resemble known patterns of neural atypicality in children and adults with autism. Future work will determine whether these differences in infant neural responses to social stimuli predict either later autism or the broader autism phenotype frequently seen in unaffected family members
Context-Based Vision System for Place and Object Recognition
While navigating in an environment, a vision system has to be able to recognize where it is and what the main objects in the scene are. In this paper we present a context-based vision system for place and object recognition. The goal is to identify familiar locations (e.g., office 610, conference room 941, Main Street), to categorize new environments (office, corridor, street) and to use that information to provide contextual priors for object recognition (e.g., table, chair, car, computer). We present a low-dimensional global image representation that provides relevant information for place recognition and categorization, and how such contextual information introduces strong priors that simplify object recognition. We have trained the system to recognize over 60 locations (indoors and outdoors) and to suggest the presence and locations of more than 20 different object types. The algorithm has been integrated into a mobile system that provides real-time feedback to the user
Model reconstruction from temporal data for coupled oscillator networks
In a complex system, the interactions between individual agents often lead to
emergent collective behavior like spontaneous synchronization, swarming, and
pattern formation. The topology of the network of interactions can have a
dramatic influence over those dynamics. In many studies, researchers start with
a specific model for both the intrinsic dynamics of each agent and the
interaction network, and attempt to learn about the dynamics that can be
observed in the model. Here we consider the inverse problem: given the dynamics
of a system, can one learn about the underlying network? We investigate
arbitrary networks of coupled phase-oscillators whose dynamics are
characterized by synchronization. We demonstrate that, given sufficient
observational data on the transient evolution of each oscillator, one can use
machine learning methods to reconstruct the interaction network and
simultaneously identify the parameters of a model for the intrinsic dynamics of
the oscillators and their coupling.Comment: 27 pages, 7 figures, 16 table
Role of substrate supply on microbial carbon use efficiency and its role in interpreting soil microbial community-level physiological profiles (CLPP)
Pulmonary Artery Acceleration Time Provides a Reliable Estimate of Invasive Pulmonary Hemodynamics in Children
Background
Pulmonary artery acceleration time (PAAT) is a non-invasive method to assess pulmonary hemodynamics, but lacks validity in children. This study sought to evaluate the accuracy of Doppler echocardiography (DE) derived PAAT in predicting right heart catheterization (RHC) derived pulmonary arterial pressure (PAP), pulmonary vascular resistance (PVR) and compliance in children.
Methods
Prospectively acquired and retrospectively measured DE derived PAAT and RHC derived systolic PAP (sPAP), mean PAP (mPAP), index PVR (PVRi) and compliance were compared by regression analysis in a derivation cohort of 75 children (median age, 5.3 years; 1.3–12.6) with wide ranges of pulmonary hemodynamics. To account for heart rate variability, PAAT was adjusted for right ventricle ejection time (RVET) and corrected by the RR interval. Regression equations incorporating PAAT and PAAT:RVET from the derivation cohort were then evaluated for the accuracy of its predictive values for invasive pulmonary hemodynamics in a validation cohort of 50 age- and weight- matched children with elevated PAP and PVR.
Results
There were significant inverse correlations between PAAT and RHC derived mPAP (r = −0.82) and PVRi (r= −0.78) and direct correlation (r= 0.78) between PAAT and pulmonary compliance in the derivation cohort. For detection of pulmonary hypertension (PRVi > 3 WU x m2 and mPAP > 25 mmHg), PAAT < 90 msec and PAAT:RVET < 0.31 resulted in a sensitivity of 97% and a specificity of 95%. In the derivation cohort, the regression equations relating PAAT with mPAP and PVRi were: mPAP = 48 – 0.28 x PAAT and PVRi = 9 –0.07 x PAAT. These PAAT integrated equations predicted RHC measured pulmonary hemodynamics in the validation cohort with good correlations (r = 0.88, 0.83 respectively), small biases (<10%), and minimal coefficient of variation (<8%).
Conclusions
PAAT inversely correlates with RHC measured pulmonary hemodynamics and directly correlates with pulmonary arterial compliance in children. The study established PAAT based regression equations in children to accurately predict RHC derived PAP and PVR
The Australia Telescope 20GHz Survey: Hardware, Observing Strategy, and Scanning Survey Catalog
The Australia Telescope 20GHz (AT20G) survey is a large area (2{\pi} sr),
sensitive (40mJy), high frequency (20GHz) survey of the southern sky. The
survey was conducted in two parts: an initial fast scanning survey, and a
series of more accurate follow-up observations. The follow-up survey catalog
has been presented by Murphy et al. 2010. In this paper we discuss the hardware
setup and scanning survey strategy as well as the production of the scanning
survey catalog.Comment: 32 pages, 20 figures, accepted for publication in experimental
astronom
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