Blind separation of auditory event-related brain responses into independent components

Averaged event-related potential (ERP) data recorded from the human scalp reveal electroencephalographic (EEG) activity that is reliably time-locked and phase-locked to experimental events. We report here the application of a method based on information theory that decomposes one or more ERPs recorded at multiple scalp sensors into a sum of components with fixed scalp distributions and sparsely activated, maximally independent time courses. Independent component analysis (ICA) decomposes ERP data into a number of components equal to the number of sensors. The derived components have distinct but not necessarily orthogonal scalp projections. Unlike dipole-fitting methods, the algorithm does not model the locations of their generators in the head. Unlike methods that remove second-order correlations, such as principal component analysis (PCA), ICA also minimizes higher-order dependencies. Applied to detected—and undetected—target ERPs from an auditory vigilance experiment, the algorithm derived ten components that decomposed each of the major response peaks into one or more ICA components with relatively simple scalp distributions. Three of these components were active only when the subject detected the targets, three other components only when the target went undetected, and one in both cases. Three additional components accounted for the steady-state brain response to a 39-Hz background click train. Major features of the decomposition proved robust across sessions and changes in sensor number and placement. This method of ERP analysis can be used to compare responses from multiple stimuli, task conditions, and subject states.

Blind column selection protocol for two-dimensional high performance liquid chromatography

The selection of two orthogonal columns for two-dimensional high performance liquid chromatography (LC×LC) separation of natural product extracts can be a labour intensive and time consuming process and in many cases is an entirely trial-and-error approach. This paper introduces a blind optimisation method for column selection of a black box of constituent components. A data processing pipeline, created in the open source application OpenMS®, was developed to map the components within the mixture of equal mass across a library of HPLC columns; LC×LC separation space utilisation was compared by measuring the fractional surface coverage, fcoverage. It was found that for a test mixture from an opium poppy (Papaver somniferum) extract, the combination of diphenyl and C18 stationary phases provided a predicted fcoverage of 0.48 and was matched with an actual usage of 0.43. OpenMS®, in conjunction with algorithms designed in house, have allowed for a significantly quicker selection of two orthogonal columns, which have been optimised for a LC×LC separation of crude extractions of plant material.

Geochemical Assessment and Separation of Source Waters in the Upper Boulder River Watershed Near Boulder, MT

Environmental samples were collected at three surface water sites between 5/21/2011 and 11/21/2014 along the Upper Boulder River near Boulder Montana. The sites were located at Bernice (within the mountain block), near the High Ore drainage (near the mountain block/basin transition), and at the USGS Gauging Station near Boulder, Montana (within the basin). The parameters measured in the field were SC, temperature, and alkalinity with occasional pH measurements. We collected samples for anions, cations, and stable isotopes in the catchment. We identified endmembers by sampling snow and groundwater and determined from available data an approximate endmember for rain, snow, and groundwater. We used temporal and spatial variations of water chemistry and isotopes to generate an endmember mixing model. Groundwater was found to always be an important contributor to river flow and could increase by nearly an order of magnitude during large snowmelt events. This resulted in groundwater comprising ~20% of total river flow during snowmelt at all sites. At peak snowmelt we observed that near surface water contributions to the river were from a mixture of rain and snow. Soil water, though not sampled, was hypothesized to be an important part of the hydrologic story. If so, the endmember contributions determined in this study may be different. Groundwater may have the highest variation depending on water chemistry of shallow soil water.

Clustering of ad-hoc microphone arrays for robust blind beamforming

This paper proposes a clustered approach for blind beamfoming from ad-hoc microphone arrays. In such arrangements, microphone placement is arbitrary and the speaker may be close to one, all or a subset of microphones at a given time. Practical issues with such a configuration mean that some microphones might be better discarded due to poor input signal to noise ratio (SNR) or undesirable spatial aliasing effects from large inter-element spacings when beamforming. Large inter-microphone spacings may also lead to inaccuracies in delay estimation during blind beamforming. In such situations, using a cluster of microphones (ie, a sub-array), closely located both to each other and to the desired speech source, may provide more robust enhancement than the full array. This paper proposes a method for blind clustering of microphones based on the magnitude square coherence function, and evaluates the method on a database recorded using various ad-hoc microphone arrangements.

Clustered blind beamforming from ad-hoc microphone arrays

Microphone arrays have been used in various applications to capture conversations, such as in meetings and teleconferences. In many cases, the microphone and likely source locations are known \emph{a priori}, and calculating beamforming filters is therefore straightforward. In ad-hoc situations, however, when the microphones have not been systematically positioned, this information is not available and beamforming must be achieved blindly. In achieving this, a commonly neglected issue is whether it is optimal to use all of the available microphones, or only an advantageous subset of these. This paper commences by reviewing different approaches to blind beamforming, characterising them by the way they estimate the signal propagation vector and the spatial coherence of noise in the absence of prior knowledge of microphone and speaker locations. Following this, a novel clustered approach to blind beamforming is motivated and developed. Without using any prior geometrical information, microphones are first grouped into localised clusters, which are then ranked according to their relative distance from a speaker. Beamforming is then performed using either the closest microphone cluster, or a weighted combination of clusters. The clustered algorithms are compared to the full set of microphones in experiments on a database recorded on different ad-hoc array geometries. These experiments evaluate the methods in terms of signal enhancement as well as performance on a large vocabulary speech recognition task.

Development of analytical methods for the separation of plutonium, americium, curium and neptunium from environmental samples

In this work, separation methods have been developed for the analysis of anthropogenic transuranium elements plutonium, americium, curium and neptunium from environmental samples contaminated by global nuclear weapons testing and the Chernobyl accident. The analytical methods utilized in this study are based on extraction chromatography. Highly varying atmospheric plutonium isotope concentrations and activity ratios were found at both Kurchatov (Kazakhstan), near the former Semipalatinsk test site, and Sodankylä (Finland). The origin of plutonium is almost impossible to identify at Kurchatov, since hundreds of nuclear tests were performed at the Semipalatinsk test site. In Sodankylä, plutonium in the surface air originated from nuclear weapons testing, conducted mostly by USSR and USA before the sampling year 1963. The variation in americium, curium and neptunium concentrations was great as well in peat samples collected in southern and central Finland in 1986 immediately after the Chernobyl accident. The main source of transuranium contamination in peats was from global nuclear test fallout, although there are wide regional differences in the fraction of Chernobyl-originated activity (of the total activity) for americium, curium and neptunium.

Distributed joint source channel coding on a multiple access channel with side information

We consider the problem of transmission of several discrete sources over a multiple access channel (MAC) with side information at the sources and the decoder. Source-channel separation does not hold for this channel. Sufficient conditions are provided for transmission of sources with a given distortion. The channel could have continuous alphabets (Gaussian MAC is a special case). Various previous results are obtained as special cases.

Highly biocompatible and water-dispersible, amine functionalized magnetite nanoparticles, prepared by a low temperature, air-assisted polyol process: a new platform for bio-separation and diagnostics

A low temperature polyol process, based on glycolaldehyde mediated partial reduction of FeCl3 center dot 6H(2)O at 120 degrees C in the presence of sodium acetate as an alkali source and 2,2'-(ethylenedioxy)-bis-(ethylamine) as an electrostatic stabilizer has been used for the gram-scale preparation of biocompatible, water-dispersible, amine functionalized magnetite nanoparticles (MNPs) with an average diameter of 6 +/- 0.75 nm. With a reasonably high magnetization (37.8 e.m.u.) and amine groups on the outer surface of the nanoparticles, we demonstrated the magnetic separation and concentration implications of these ultrasmall particles in immunoassay. MRI studies indicated that these nanoparticles had the desired relaxivity for T-2 contrast enhancement in vivo. In vitro biocompatibility, cell uptake and MR imaging studies established that these nanoparticles were safe in clinical dosages and by virtue of their ultrasmall sizes and positively charged surfaces could be easily internalized by cancer cells. All these positive attributes make these functional nanoparticles a promising platform for further in vitro and in vivo evaluations.

Source-channel coding for Gaussian sources over a Gaussian multiple access channel

We consider the problem of distributed joint source-channel coding of correlated Gaussian sources over a Gaussian Multiple Access Channel (MAC). There may be side information at the encoders and/or at the decoder. First we specialize a general result in [16] to obtain sufficient conditions for reliable transmission over a Gaussian MAC. This system does not satisfy the source channel separation. Thus, next we study and compare three joint source channel coding schemes available in literature.

Real source-sink pair

This work is concerned with the interaction of a source-sink pair. The main parameters of the problem are source and sink flow rates, the axial and lateral separations of the source and sink, and the angle between the axes of source and sink. Of concern is the percentage of source fluid that enters the sink as a function of these parameters. The experiments have been carried using the source nozzle diameter of 6 mm and the sink pipe diameter of two sizes: 10 mm and 20 mm. The Reynolds numbers of the source jet is about 3200. The main diagnostics are flow visualization using dye, laser induced fluorescence (LIF), particle streak photographs and particle image velocimetry (Ply). To obtain the removal effectiveness (that is percentage of source fluid that is going through the sink pipe), titration method is used. The sink diameter and the angle between source and the sink axes do not influence efficiencies as do the sink flow rate and the lateral separation. Data from experiments have been consolidated so that these results can be used for designing sinks for removal of heat and pollutants. (C) 2011 Elsevier Ltd. All rights reserved.

Identification of Active Sources in Single-Channel Convolutive Mixtures Using Known Source Models

We address the problem of identifying the constituent sources in a single-sensor mixture signal consisting of contributions from multiple simultaneously active sources. We propose a generic framework for mixture signal analysis based on a latent variable approach. The basic idea of the approach is to detect known sources represented as stochastic models, in a single-channel mixture signal without performing signal separation. A given mixture signal is modeled as a convex combination of known source models and the weights of the models are estimated using the mixture signal. We show experimentally that these weights indicate the presence/absence of the respective sources. The performance of the proposed approach is illustrated through mixture speech data in a reverberant enclosure. For the task of identifying the constituent speakers using data from a single microphone, the proposed approach is able to identify the dominant source with up to 8 simultaneously active background sources in a room with RT60 = 250 ms, using models obtained from clean speech data for a Source to Interference Ratio (SIR) greater than 2 dB.

On the transition from displacement to mixing ventilation with a localized heat source

We investigate the steady state natural ventilation of a room heated at the base and consisting of two vents at different levels. We explore how the air flow rate and internal temperature relative to the exterior vary as a function of the vent areas, position of the vents and heat load in order to establish appropriate ventilation strategies for a room. When the room is heated by a distributed source, the room becomes well mixed and the steady state ventilation rate depends on the heating rate, the area of the vents and the distance between the lower and upper level vents. However, when the room is heated by a localised source the room becomes stratified. If the effective ventilation area is sufficiently large, then the interface separating the two layers lies above the inlet vent and the lower layer is comprised of ambient fluid. In this case the upper layer is warmer than in the well mixed case and the ventilation rate is smaller. However, if the effective area for ventilation is sufficiently small, then the interface separating the two layers lies below the inlet vent and the lower layer is comprised of warm fluid which originates as the cold incoming fluid mixes during descent from the vent through the upper layer. In this case both the ventilation rate and the upper layer temperature are the same as in the case of a distributed heat load. As the vertical separation between lower and upper level vents decreases, then the temperature difference between the layers falls to zero and the room becomes approximately well mixed. These findings suggest how the appropriate ventilation strategy for a room can be varied depending on the exterior temperature, with mixing ventilation more suitable for winter conditions and displacement ventilation for warmer external temperatures.