Interlayer segregation of Cu atoms in metal multilayers

The experimental results show that the exchange coupling field H.. of NiFe/FeMn for TalNiFe/FeMn/Ta multilayers is higher than that for the spin valve multilayers Ta/NiFe/Cu/NiFe/FeMn/Ta. The composition and chemical states at the surface of Ta(12nm)/NiFe(7nm), Th(12nm)/NiFe(7nm)/Cu(4nm) and Ta(12nm)/NiFe(7nm)/Cu(3 nm)/NiFe(5 mn) were studied by using x-ray photoelectron spectroscopy. The results show that no element from the underlayers Boats out or segregates to the surface for Th(12 nm)/NiFe(7nm), Ta(12 nm)/NiFe(7nm)/Cu(4 mn). However, Cu atoms segregate to the surface of Ta(12 nm)/NiFe(7nm)/Cu(3nm)/NiFe(5nm) multilayers, i.e. to the NiFe/FeMn interface for Ta/NiFe/Cu/NiFe/FeMn/Ta multilayers. We believe that the presence of Cu atoms at the interface of NiFe/FeMn is one of the important factors which will cause the exchange coupling field H.. of Ta/NiFe/FeMn/Ta multilayers to be higher than that of Ta/NiFe/Cu/NiFe/FeMn/Ta multilayers.

Detection of indium segregation effects in InGaAs/GaAs quantum wells using reflectance-difference spectrometry

The influence of the Indium segregation on the interface asymmetry in InGaAs/GaAs quantum wells have been studied by reflectance-difference spectroscopy (RDS). It is found that the anisotropy of the 2H1E (2HH --> 1E) transition is very sensitive to the degree of the interface asymmetry. Calculations taking into account indium segregation yield good agreement with the observed anisotropy structures. It demonstrates that the anisotropy intensity ratio of the 1L1E (1LH --> 1E) and 2H1E transitions measured by RDS can be used to characterize the interface asymmetry. (C) 2002 Elsevier Science B.V. All rights reserved.

Is there a time-transgressive Holocene optimum in the East Asian monsoon area?

IEECAS SKLLQG

Inheritance of 15 microsatellites in the Pacific oyster Crassostrea gigas: segregation and null allele identification for linkage analysis

Microsatellites were screened in a backcross family of the Pacific oyster, Crassostrea gigas. Fifteen microsatellite loci were distinguishable and polymorphic with 6 types of allele-combinations. Null alleles were detected in 46.7% of loci, accounting for 11.7% of the total alleles. Four loci did not segregate in Mendelian Ratios. Three linkage groups were identified among 7 of the 15 segregating loci. Fluorescence-based automated capillary electrophoresis (ABI 310 Genetic Analyzer) that used to detect the microsatellite loci, has been proved a fast, precise, and reliable method in microsatellite genotyping.

Chromosome segregation in fertilized eggs from triploid Pacific oysters, Crassostrea gigas (Thunberg), following inhibition of polar body 1

Chromosome segregation in fertilized eggs from triploid Pacific oysters, following inhibition of the first polar body (PB1), was studied with acetic orcein staining techniques. To block the release of PB1, fertilized eggs were treated with 0.5 mg/l of cytochalasin B (CB). Four types of segregation were observed, namely, ''tripolar segregation'' (54.5%), ''united bipolar segregation'' (12%), ''separated bipolar segregation'' (2.5%), and ''incomplete united bipolar segregation'' (4%). The remaining 23% could not be classified because of chromosome disorganization, but appeared to be variants of the above. It seemed clear that the predominant pattern that gave rise to tetraploids was united bipolar segregation, although certain separated bipolar segregations might also lead to the formation of tetraploids. The sequential events of meioses observed in CB-treated eggs are described. The asynchrony of meiotic events and possible mechanisms for the various types of chromosome segregation are discussed.

AIRSTREAM: A Neural Network Model of Auditory Scene Analysis and Source Segregation

Multiple sound sources often contain harmonics that overlap and may be degraded by environmental noise. The auditory system is capable of teasing apart these sources into distinct mental objects, or streams. Such an "auditory scene analysis" enables the brain to solve the cocktail party problem. A neural network model of auditory scene analysis, called the AIRSTREAM model, is presented to propose how the brain accomplishes this feat. The model clarifies how the frequency components that correspond to a give acoustic source may be coherently grouped together into distinct streams based on pitch and spatial cues. The model also clarifies how multiple streams may be distinguishes and seperated by the brain. Streams are formed as spectral-pitch resonances that emerge through feedback interactions between frequency-specific spectral representaion of a sound source and its pitch. First, the model transforms a sound into a spatial pattern of frequency-specific activation across a spectral stream layer. The sound has multiple parallel representations at this layer. A sound's spectral representation activates a bottom-up filter that is sensitive to harmonics of the sound's pitch. The filter activates a pitch category which, in turn, activate a top-down expectation that allows one voice or instrument to be tracked through a noisy multiple source environment. Spectral components are suppressed if they do not match harmonics of the top-down expectation that is read-out by the selected pitch, thereby allowing another stream to capture these components, as in the "old-plus-new-heuristic" of Bregman. Multiple simultaneously occuring spectral-pitch resonances can hereby emerge. These resonance and matching mechanisms are specialized versions of Adaptive Resonance Theory, or ART, which clarifies how pitch representations can self-organize durin learning of harmonic bottom-up filters and top-down expectations. The model also clarifies how spatial location cues can help to disambiguate two sources with similar spectral cures. Data are simulated from psychophysical grouping experiments, such as how a tone sweeping upwards in frequency creates a bounce percept by grouping with a downward sweeping tone due to proximity in frequency, even if noise replaces the tones at their interection point. Illusory auditory percepts are also simulated, such as the auditory continuity illusion of a tone continuing through a noise burst even if the tone is not present during the noise, and the scale illusion of Deutsch whereby downward and upward scales presented alternately to the two ears are regrouped based on frequency proximity, leading to a bounce percept. Since related sorts of resonances have been used to quantitatively simulate psychophysical data about speech perception, the model strengthens the hypothesis the ART-like mechanisms are used at multiple levels of the auditory system. Proposals for developing the model to explain more complex streaming data are also provided.

Texture Segregation By Visual Cortex: Perceptual Grouping, Attention, and Learning

A neural model is proposed of how laminar interactions in the visual cortex may learn and recognize object texture and form boundaries. The model brings together five interacting processes: region-based texture classification, contour-based boundary grouping, surface filling-in, spatial attention, and object attention. The model shows how form boundaries can determine regions in which surface filling-in occurs; how surface filling-in interacts with spatial attention to generate a form-fitting distribution of spatial attention, or attentional shroud; how the strongest shroud can inhibit weaker shrouds; and how the winning shroud regulates learning of texture categories, and thus the allocation of object attention. The model can discriminate abutted textures with blurred boundaries and is sensitive to texture boundary attributes like discontinuities in orientation and texture flow curvature as well as to relative orientations of texture elements. The model quantitatively fits a large set of human psychophysical data on orientation-based textures. Object boundar output of the model is compared to computer vision algorithms using a set of human segmented photographic images. The model classifies textures and suppresses noise using a multiple scale oriented filterbank and a distributed Adaptive Resonance Theory (dART) classifier. The matched signal between the bottom-up texture inputs and top-down learned texture categories is utilized by oriented competitive and cooperative grouping processes to generate texture boundaries that control surface filling-in and spatial attention. Topdown modulatory attentional feedback from boundary and surface representations to early filtering stages results in enhanced texture boundaries and more efficient learning of texture within attended surface regions. Surface-based attention also provides a self-supervising training signal for learning new textures. Importance of the surface-based attentional feedback in texture learning and classification is tested using a set of textured images from the Brodatz micro-texture album. Benchmark studies vary from 95.1% to 98.6% with attention, and from 90.6% to 93.2% without attention.

Stream segregation on a single electrode as a function of pulse rate in cochlear implant listeners.

While cochlear implants (CIs) usually provide high levels of speech recognition in quiet, speech recognition in noise remains challenging. To overcome these difficulties, it is important to understand how implanted listeners separate a target signal from interferers. Stream segregation has been studied extensively in both normal and electric hearing, as a function of place of stimulation. However, the effects of pulse rate, independent of place, on the perceptual grouping of sequential sounds in electric hearing have not yet been investigated. A rhythm detection task was used to measure stream segregation. The results of this study suggest that while CI listeners can segregate streams based on differences in pulse rate alone, the amount of stream segregation observed decreases as the base pulse rate increases. Further investigation of the perceptual dimensions encoded by the pulse rate and the effect of sequential presentation of different stimulation rates on perception could be beneficial for the future development of speech processing strategies for CIs.

Dynamics of Delta/Notch signaling on endomesoderm segregation in the sea urchin embryo.

Endomesoderm is the common progenitor of endoderm and mesoderm early in the development of many animals. In the sea urchin embryo, the Delta/Notch pathway is necessary for the diversification of this tissue, as are two early transcription factors, Gcm and FoxA, which are expressed in mesoderm and endoderm, respectively. Here, we provide a detailed lineage analysis of the cleavages leading to endomesoderm segregation, and examine the expression patterns and the regulatory relationships of three known regulators of this cell fate dichotomy in the context of the lineages. We observed that endomesoderm segregation first occurs at hatched blastula stage. Prior to this stage, Gcm and FoxA are co-expressed in the same cells, whereas at hatching these genes are detected in two distinct cell populations. Gcm remains expressed in the most vegetal endomesoderm descendant cells, while FoxA is downregulated in those cells and activated in the above neighboring cells. Initially, Delta is expressed exclusively in the micromeres, where it is necessary for the most vegetal endomesoderm cell descendants to express Gcm and become mesoderm. Our experiments show a requirement for a continuous Delta input for more than two cleavages (or about 2.5 hours) before Gcm expression continues in those cells independently of further Delta input. Thus, this study provides new insights into the timing mechanisms and the molecular dynamics of endomesoderm segregation during sea urchin embryogenesis and into the mode of action of the Delta/Notch pathway in mediating mesoderm fate.

Cross-hemispheric collaboration and segregation associated with task difficulty as revealed by structural and functional connectivity.

Although it is known that brain regions in one hemisphere may interact very closely with their corresponding contralateral regions (collaboration) or operate relatively independent of them (segregation), the specific brain regions (where) and conditions (how) associated with collaboration or segregation are largely unknown. We investigated these issues using a split field-matching task in which participants matched the meaning of words or the visual features of faces presented to the same (unilateral) or to different (bilateral) visual fields. Matching difficulty was manipulated by varying the semantic similarity of words or the visual similarity of faces. We assessed the white matter using the fractional anisotropy (FA) measure provided by diffusion tensor imaging (DTI) and cross-hemispheric communication in terms of fMRI-based connectivity between homotopic pairs of cortical regions. For both perceptual and semantic matching, bilateral trials became faster than unilateral trials as difficulty increased (bilateral processing advantage, BPA). The study yielded three novel findings. First, whereas FA in anterior corpus callosum (genu) correlated with word-matching BPA, FA in posterior corpus callosum (splenium-occipital) correlated with face-matching BPA. Second, as matching difficulty intensified, cross-hemispheric functional connectivity (CFC) increased in domain-general frontopolar cortex (for both word and face matching) but decreased in domain-specific ventral temporal lobe regions (temporal pole for word matching and fusiform gyrus for face matching). Last, a mediation analysis linking DTI and fMRI data showed that CFC mediated the effect of callosal FA on BPA. These findings clarify the mechanisms by which the hemispheres interact to perform complex cognitive tasks.

Predictions of segregation of granular material with the aid of PHYSICA, a 3-D unstructured finite-volume modelling framework

In this paper a continuum model for the prediction of segregation in granular material is presented. The numerical framework, a 3-D, unstructured grid, finite-volume code is described, and the micro-physical parametrizations, which are used to describe the processes and interactions at the microscopic level that lead to segregation, are analysed. Numerical simulations and comparisons with experimental data are then presented and conclusions are drawn on the capability of the model to accurately simulate the behaviour of granular matter during flow.

Macro-segregation of multi-component alloys in shape casting simulation

The objective of this work is to present a new scheme for temperature-solute coupling in a solidification model, where the temperature and concentration fields simultaneously satisfy the macro-scale transport equations and, in the mushy region, meet the constraints imposed by the thermodynamics and the local scale processes. A step-by-step explanation of the macrosegregation algorithm, implemented in the finite volume unstructured mesh multi-physics modelling code PHYSICA, is initially presented and then the proposed scheme is validated against experimental results obtained by Krane for binary and a ternary alloys.

On the continuum modelling of segregation of granular mixtures during hopper emptying in core flow mode

In this paper, the application of a continuum model is presented, which deals with the discharge of multi-component granular mixtures in core flow mode. The full model description is given (including the constitutive models for the segregation mechanism) and the interactions between particles at the microscopic level are parametrised in order to predict the development of stagnant zone boundaries during core flow discharges. Finally, the model is applied to a real industrial problem and predictions are made for the segregation patterns developed during mixture discharge in core flow mode.