2,486 research outputs found
Primary Phagocytosis of Neurons by Inflamed Microglia: Potential Roles in Neurodegeneration
Microglial phagocytosis of dead or dying neurons can be beneficial by preventing the release of damaging and/or pro-inflammatory intracellular components. However, there is now evidence that under certain conditions, such as inflammation, microglia can also phagocytose viable neurons, thus executing their death. Such phagocytic cell death may result from exposure of phosphatidylserine (PS) or other eat-me signals on otherwise viable neurons as a result of physiological activation or sub-toxic insult, and neuronal phagocytosis by activated microglia. In this review, we discuss the mechanisms of phagocytic cell death and its potential roles in Alzheimer’s Disease, Parkinson’s Disease, and Frontotemporal Dementia
The robustness of speech representations obtained from simulated auditory nerve fibers under different noise conditions
Different methods of extracting speech features from an auditory model were systematically investigated in terms of their robustness to different noises. The methods either computed the average firing rate within frequency channels (spectral features) or inter-spike-intervals (timing features) from the simulated auditory nerve response. When used as the front-end for an automatic speech recognizer, timing features outperformed spectral features in Gaussian noise. However, this advantage was lost in babble, because timing features extracted the spectro-temporal structure of babble noise, which is similar to the target speaker. This suggests that different feature extraction methods are optimal depending on the background noise
Application of missing feature theory to the recognition of musical instruments in polyphonic audio
A system for musical instrument recognition based on a Gaussian Mixture Model (GMM) classifier is introduced. To enable instrument recognition when more than one sound is present at the same time, ideas from missing feature theory are incorporated. Specifically, frequency regions that are dominated by energy from an interfering tone are marked as unreliable and excluded from the classification process. The approach has been evaluated on clean and noisy monophonic recordings, and on combinations of two instrument sounds. These included random chords made from two isolated notes and combinations of two realistic phrases taken from commercially available compact discs. Classification results were generally good, not only when the decision between reliable and unreliable features was based on the knowledge of the clean signal, but also when it was solely based on the pitch and harmonic overtone series of the interfering sound
Testing asteroseismology with Gaia DR2: Hierarchical models of the Red Clump
Asteroseismology provides fundamental stellar parameters independent of
distance, but subject to systematics under calibration. Gaia DR2 has provided
parallaxes for a billion stars, which are offset by a parallax zero-point. Red
Clump (RC) stars have a narrow spread in luminosity, thus functioning as
standard candles to calibrate these systematics. This work measures how the
magnitude and spread of the RC in the Kepler field are affected by changes to
temperature and scaling relations for seismology, and changes to the parallax
zero-point for Gaia. We use a sample of 5576 RC stars classified through
asteroseismology. We apply hierarchical Bayesian latent variable models,
finding the population level properties of the RC with seismology, and use
those as priors on Gaia parallaxes to find the parallax zero-point offset. We
then find the position of the RC using published values for the zero-point. We
find a seismic temperature insensitive spread of the RC of ~0.03 mag in the
2MASS K band and a larger and slightly temperature-dependent spread of ~0.13
mag in the Gaia G band. This intrinsic dispersion in the K band provides a
distance precision of ~1% for RC stars. Using Gaia data alone, we find a mean
zero-point of -41 10 as. This offset yields RC absolute magnitudes
of -1.634 0.018 in K and 0.546 0.016 in G. Obtaining these same
values through seismology would require a global temperature shift of ~-70 K,
which is compatible with known systematics in spectroscopy.Comment: Accepted for publication in MNRA
Stability analysis of static solutions in a Josephson junction
We present all the possible solutions of a Josephson junction with bias
current and magnetic field with both inline and overlap geometry, and examine
their stability. We follow the bifurcation of new solutions as we increase the
junction length. The analytical results, in terms of elliptic functions in the
case of inline geometry, are in agreement with the numerical calculations and
explain the strong hysteretic phenomena typically seen in the calculation of
the maximum tunneling current. This suggests a different experimental approach
based on the use, instead of the external magnetic field the modulus of the
elliptic function or the related quantity the total magnetic flux to avoid
hysteretic behavior and unfold the overlapping curves.Comment: 36 pages with 17 figure
Thermodynamic Model for Energy-Constrained Open-System Evolution of Crustal Magma Bodies Undergoing Simultaneous Recharge, Assimilation and Crystallization: the Magma Chamber Simulator
The Magma Chamber Simulator quantifies the impact of simultaneous recharge, assimilation and crystallization through mass and enthalpy balance in a multicomponent–multiphase (melt + solids ± fluid) composite system. As a rigorous thermodynamic model, the Magma Chamber Simulator computes phase equilibria and geochemical evolution self-consistently in resident magma, recharge magma and wallrock, all of which are connected by specified thermodynamic boundaries, to model an evolving open-system magma body. In a simulation, magma cools from its liquidus temperature, and crystals ± fluid are incrementally fractionated to a separate cumulate reservoir. Enthalpy from cooling, crystallization, and possible magma recharge heats wallrock from its initial subsolidus temperature. Assimilation begins when a critical wallrock melt volume fraction (0·04–0·12) in a range consistent with the rheology of partially molten rock systems is achieved. The mass of melt above this limit is removed from the wallrock and homogenized with the magma body melt. New equilibrium states for magma and wallrock are calculated that reflect conservation of total mass, mass of each element and enthalpy. Magma cooling and crystallization, addition of recharge magma and anatectic melt to the magma body (where appropriate), and heating and partial melting of wallrock continue until magma and wallrock reach thermal equilibrium. For each simulation step, mass and energy balance and thermodynamic assessment of phase relations provide major and trace element concentrations, isotopic characteristics, masses, and thermal constraints for all phases (melt + solids ± fluid) in the composite system. Model input includes initial compositional, thermal and mass information relevant to each subsystem, as well as solid–melt and solid–fluid partition coefficients for all phases. Magma Chamber Simulator results of an assimilation–fractional crystallization (AFC) scenario in which dioritic wallrock at 0·1 GPa contaminates high-alumina basalt are compared with results in which no assimilation occurs [fractional crystallization only (FC-only)]. Key comparisons underscore the need for multicomponent–multiphase energy-constrained thermodynamic modeling of open systems, as follows. (1) Partial melting of dioritic wallrock yields cooler silicic melt that contaminates hotter magma. Magma responds by cooling, but a pulse of crystallization, possibly expected based on thermal arguments, does not occur because assimilation suppresses crystallization by modifying the topology of multicomponent phase saturation surfaces. As a consequence, contaminated magma composition and crystallizing solids are distinct compared with the FC-only case. (2) At similar stages of evolution, contaminated melt is more voluminous (∼3·5×) than melt formed by FC-only. (3) In AFC, some trace element concentrations are lower than their FC-only counterparts at the same stage of evolution. Elements that typically behave incompatibly in mafic and intermediate magmas (e.g. La, Nd, Ba) may not be ‘enriched’ by crustal contamination, and the most ‘crustal’ isotope signatures may not correlate with the highest concentrations of such elements. (4) The proportion of an element contributed by anatectic melt to resident magma is typically different for each element, and thus the extent of mass exchange between crust and magma should be quantified using total mass rather than the mass of a single element. Based on these sometimes unexpected results, it can be argued that progress in quantifying the origin and evolution of open magmatic systems and documenting how mantle-derived magmas and the crust interact rely not only on improvements in instrumentation and generation of larger datasets, but also on continued development of computational tools that couple thermodynamic assessment of phase equilibria in multicomponent systems with energy and mass conservation
Mask estimation based on sound localisation for missing data speech recognition
ABSTRACT This paper describes a perceptually motivated computational auditory scene analysis (CASA) system that combines sound separation according to spatial location with 'missing data' techniques for robust speech recognition in noise. Missing data time-frequency masks are produced using cross-correlation to estimate interaural time differenre (ITD) and hence spatial azimuth; this is used to determine which regions of the signal constitute reliable evidence of the target speech signal. Three experiments are performed that compare the effects of different reverberation surfaces, localisation methods and azimuth separations on recognition accuracy, together with the effects of two post-processing techniques (morphological operations and supervised learning) for improving mask estimation. Both post-processing techniques greatly improve performance; the best performance occurs using a learnt mapping
Exploiting deep neural networks and head movements for binaural localisation of multiple speakers in reverberant conditions
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