Optical study of lateral carrier transfer in (In,Ga)As/GaAs quantum-dot chains

We have studied the lateral carrier transfer in a specially designed quantum dot chain structure by means of time-resolved photoluminescence (PL) and polarization PL. The PL decay time increases with temperature, following the T-1/2 law for the typical one-dimensional quantum system. The decay time depends strongly on the emission energy: it decreases as the photon energy increases. Moreover, a strong polarization anisotropy is observed. These results are attributed to the efficient lateral transfer of carriers along the chain direction. (c) 2008 American Institute of Physics.

Study on Mechanics Parameters of Unloaded Rock Mass about the Underground Powerhouse of Jin-ping Hydroelectric Station

After the excavation of Jinping underground cavern, a strong expansion appears along the unloading direction of the rock mass, mainly in the type of tensile rupture, accompanied by shear destruction, unloading resulted in significant deterioration of mechanical properties of rock. Based on the in-site investigation of rock mass structure, via analyzing the acoustic testing data, we identify the unloading range of the side walls and the division of rock types, and carry out with the solution of rock mechanical parameters about different unloading zone, providing geological foundation for the supporting design of the following design of the side walls, at the same time, providing reference for the selection of mechanical parameters of other underground excavation engineering with similar geological conditions.

TIME-DEPENDENT DENSITY FUNCTIONAL STUDY OF MULTIELECTRON TRANSFER IN Cq+-Na-4 COLLISIONS

The process of multielectron transfer from a Na-4 cluster induced by highly charged C6+, C4+, C2+ and C+ ions is studied using the method of time-dependent density functional theory within the local density approximation combined with the use of pseudopotential. The evolution of dipole moment changes and emitted electrons in Na-4 isobtained and the time-dependent probabilities with various charges are deduced. It is shown that the Na-4 cluster is strongly ionized by C6+ and that the number of emitted electrons per atom of Na-4 is larger than that of Na-2 under the same condition. One can find that the detailed information of the emitted electrons from Na-4 is different from the same from Na-2, which is possibly related to the difference in structure between the two clusters.

Brittle-ductile transition of polypropylene/ethyllene-propylene-diene monomer blends induced by size, temperature, and time

To study the brittle-ductile transition (BDT) of polypropylene (PP)/ethylene-propylene-diene monomer (EPDM) blends induced by size, temperature, and time, the toughness of the PP/EPDM blends was investigated over wide ranges of EPDM content, temperature, and strain rate. The toughness of the blends was determined from the tensile fracture energy of the side-edge notched samples. The concept of interparticle distance (ID) was introduced into this study to probe the size effect on the BDT of PP/EPDM blends, whereas the effect of time corresponded to that of strain rate. The BDT induced by size, temperature, and time was observed in the fracture energy versus ID, temperature, and strain rate. The critical BDT temperatures for various EPDM contents at different initial strain rates were obtained from these transitions. The critical interparticle distance (IDc) increased nonlinearly with increasing temperature, and when the initial strain rate was lower, the IDc was larger. Moreover, the variation of the reciprocal of the initial strain rate with the reciprocal of temperature followed different straight lines for various EPDM contents. These straight lines were with the same slope.

In situ analysis of electropolymerization of aniline by combined electrochemistry and surface plasmon resonance

The combination of electrochemistry with surface plasmon resonance (SPR) has been used to characterize the growth of polyaniline (PAn) on a gold electrode surface during potential cycling. Potential-modulated SPR characteristics of the PAn film were also revealed. The potential switch between the oxidized and reduced states of PAn can lead to a large change of SPR response due to the variation in the imaginary part of the dielectric constant of PAn film resulting from the transition of the film in conductivity. The redox transition of the PAn film during potential cycling is very profitable to the SPR measurements. Two modes of SPR measurement, SPR angular scan (R-theta) and the time evolution of the reflectivity change at a fixed angle (R-t), were displayed to study the growth process of the PAn film. The angle shift of the resonance minimum recorded at each cathodic limit of cyclic potential scanning allows for the unambiguous measurement of the film growth. During cyclic potential scanning, the R-t curve was repeatedly modulated with the direction of the potential ramp as a result of the redox switch of the PAn film, and the amplitude of potential-modulated reflectivity change was well correlated with the cyclic number. The time differential of the R-t curve permits continuous monitoring of the film growth process. These results illustrate that the combined technique is suitable for studying the electropolymerization process of a conducting polymer.

INVESTIGATION OF ELECTRIC DICHROISM OF CETYLPYRIDINIUM BROMIDE BY SPECTROELECTROCHEMISTRY WITH A LONG OPTICAL-PATH LENGTH THIN-LAYER CELL

In this paper, the electric dichroism of cetylpyridinium bromide (CPB) has been found and studied by spectroelectrochemistry with a long optical path length thin-layer cell (LOPTLC) for the first time. The CPB molecule with a long carbon chain and a polar pyridinium ring is anisotropic in molecular configuration or in polarizability. In the electric field of a thin-layer cell, the CPB molecule reorientates along the direction of the electric field and exhibits electric dichroism, which results in the increase of absorbance of CPB in the UV-vis range. By use of in situ measurement of spectroelectrochemistry, the order parameters of long molecular axis (S = 0.845) and short molecular axis (D = 0.155) and the angle between the long axis direction of the CPB molecule and the direction normal to the electrode surface (theta = 18-degrees 44') have been determined. These data were used to describe the state of arrangement of the molecules in the solution. The reorientation of CPB molecules is the result of the interaction between the anisotropic molecules and electric field. The effects of the concentration of CPB and of the applied electric field on the electric dichroism have been investigated.

Observations of Kuroshio intrusion into the South China Sea

To discuss the intrusion of the Kuroshio into the SCS, we examined the mixing between the North Pacific and South China Sea (SCS) waters based on in-situ CTD data collected in August and September 2008 and the moored ADCP data taken from mid September 2008 to early July 2009. The CTD survey included four meridional sections from 119A degrees E to 122A degrees E around the Luzon Strait, during which pressure, temperature, and salinity were measured. The CTD data show that the isopycnal surface tilted from the SCS to the North Pacific; and it was steeper in the lower layers than in the upper ones. Meanwhile, we found strong vertical mixing taken place in the areas near 121A degrees E. The Kuroshio in high temperature and salinity intruded westward through Luzon Strait. The frequency of buoyancy was one order of magnitude greater than that of the common ones in the ocean, suggesting stronger stratification in the northeastern SCS. On the other hand, the long-term ADCP data show that before late October 2008, the direction of water flow in the SCS was eastward, and from November 2008 to late February 2009, it turned northwestward in the layers shallower than 150 m, while remained unchanged in deep layers from 200 to 450 m. From March to June 2009, the direction shifted with increasing depth from northward to southward, akin to the Ekman spiral. EOF analysis of the current time series revealed dominant empirical modes: the first mode corresponded to the mean current and showed that the Kuroshio intrusion occurred in the upper layers only from late December to early March. The temporal coefficient of the first and the second mode indicated clearly a dominant signal in a quasi-seasonal cycle.

An Analog VLSI Chip for Estimating the Focus of Expansion

For applications involving the control of moving vehicles, the recovery of relative motion between a camera and its environment is of high utility. This thesis describes the design and testing of a real-time analog VLSI chip which estimates the focus of expansion (FOE) from measured time-varying images. Our approach assumes a camera moving through a fixed world with translational velocity; the FOE is the projection of the translation vector onto the image plane. This location is the point towards which the camera is moving, and other points appear to be expanding outward from. By way of the camera imaging parameters, the location of the FOE gives the direction of 3-D translation. The algorithm we use for estimating the FOE minimizes the sum of squares of the differences at every pixel between the observed time variation of brightness and the predicted variation given the assumed position of the FOE. This minimization is not straightforward, because the relationship between the brightness derivatives depends on the unknown distance to the surface being imaged. However, image points where brightness is instantaneously constant play a critical role. Ideally, the FOE would be at the intersection of the tangents to the iso-brightness contours at these "stationary" points. In practice, brightness derivatives are hard to estimate accurately given that the image is quite noisy. Reliable results can nevertheless be obtained if the image contains many stationary points and the point is found that minimizes the sum of squares of the perpendicular distances from the tangents at the stationary points. The FOE chip calculates the gradient of this least-squares minimization sum, and the estimation is performed by closing a feedback loop around it. The chip has been implemented using an embedded CCD imager for image acquisition and a row-parallel processing scheme. A 64 x 64 version was fabricated in a 2um CCD/ BiCMOS process through MOSIS with a design goal of 200 mW of on-chip power, a top frame rate of 1000 frames/second, and a basic accuracy of 5%. A complete experimental system which estimates the FOE in real time using real motion and image scenes is demonstrated.

Time-Frequency Representations for Speech Signals

This work addresses two related questions. The first question is what joint time-frequency energy representations are most appropriate for auditory signals, in particular, for speech signals in sonorant regions. The quadratic transforms of the signal are examined, a large class that includes, for example, the spectrograms and the Wigner distribution. Quasi-stationarity is not assumed, since this would neglect dynamic regions. A set of desired properties is proposed for the representation: (1) shift-invariance, (2) positivity, (3) superposition, (4) locality, and (5) smoothness. Several relations among these properties are proved: shift-invariance and positivity imply the transform is a superposition of spectrograms; positivity and superposition are equivalent conditions when the transform is real; positivity limits the simultaneous time and frequency resolution (locality) possible for the transform, defining an uncertainty relation for joint time-frequency energy representations; and locality and smoothness tradeoff by the 2-D generalization of the classical uncertainty relation. The transform that best meets these criteria is derived, which consists of two-dimensionally smoothed Wigner distributions with (possibly oriented) 2-D guassian kernels. These transforms are then related to time-frequency filtering, a method for estimating the time-varying 'transfer function' of the vocal tract, which is somewhat analogous to ceptstral filtering generalized to the time-varying case. Natural speech examples are provided. The second question addressed is how to obtain a rich, symbolic description of the phonetically relevant features in these time-frequency energy surfaces, the so-called schematic spectrogram. Time-frequency ridges, the 2-D analog of spectral peaks, are one feature that is proposed. If non-oriented kernels are used for the energy representation, then the ridge tops can be identified, with zero-crossings in the inner product of the gradient vector and the direction of greatest downward curvature. If oriented kernels are used, the method can be generalized to give better orientation selectivity (e.g., at intersecting ridges) at the cost of poorer time-frequency locality. Many speech examples are given showing the performance for some traditionally difficult cases: semi-vowels and glides, nasalized vowels, consonant-vowel transitions, female speech, and imperfect transmission channels.

An Ounce of Prevention is Worth a Pound of Cure: Towards Physically-Correct Specifications of Embedded Real-Time Systems

Predictability — the ability to foretell that an implementation will not violate a set of specified reliability and timeliness requirements - is a crucial, highly desirable property of responsive embedded systems. This paper overviews a development methodology for responsive systems, which enhances predictability by eliminating potential hazards resulting from physically-unsound specifications. The backbone of our methodology is a formalism that restricts expressiveness in a way that allows the specification of only reactive, spontaneous, and causal computation. Unrealistic systems — possessing properties such as clairvoyance, caprice, infinite capacity, or perfect timing — cannot even be specified. We argue that this "ounce of prevention" at the specification level is likely to spare a lot of time and energy in the development cycle of responsive systems - not to mention the elimination of potential hazards that would have gone, otherwise, unnoticed.

Simultaneous Learning of Nonlinear Manifold and Dynamical Models for High-dimensional Time Series

The goal of this work is to learn a parsimonious and informative representation for high-dimensional time series. Conceptually, this comprises two distinct yet tightly coupled tasks: learning a low-dimensional manifold and modeling the dynamical process. These two tasks have a complementary relationship as the temporal constraints provide valuable neighborhood information for dimensionality reduction and conversely, the low-dimensional space allows dynamics to be learnt efficiently. Solving these two tasks simultaneously allows important information to be exchanged mutually. If nonlinear models are required to capture the rich complexity of time series, then the learning problem becomes harder as the nonlinearities in both tasks are coupled. The proposed solution approximates the nonlinear manifold and dynamics using piecewise linear models. The interactions among the linear models are captured in a graphical model. By exploiting the model structure, efficient inference and learning algorithms are obtained without oversimplifying the model of the underlying dynamical process. Evaluation of the proposed framework with competing approaches is conducted in three sets of experiments: dimensionality reduction and reconstruction using synthetic time series, video synthesis using a dynamic texture database, and human motion synthesis, classification and tracking on a benchmark data set. In all experiments, the proposed approach provides superior performance.

Simultaneous Learning of Non-Linear Manifold and Dynamical Models for High-Dimensional Time Series

The goal of this work is to learn a parsimonious and informative representation for high-dimensional time series. Conceptually, this comprises two distinct yet tightly coupled tasks: learning a low-dimensional manifold and modeling the dynamical process. These two tasks have a complementary relationship as the temporal constraints provide valuable neighborhood information for dimensionality reduction and conversely, the low-dimensional space allows dynamics to be learnt efficiently. Solving these two tasks simultaneously allows important information to be exchanged mutually. If nonlinear models are required to capture the rich complexity of time series, then the learning problem becomes harder as the nonlinearities in both tasks are coupled. The proposed solution approximates the nonlinear manifold and dynamics using piecewise linear models. The interactions among the linear models are captured in a graphical model. The model structure setup and parameter learning are done using a variational Bayesian approach, which enables automatic Bayesian model structure selection, hence solving the problem of over-fitting. By exploiting the model structure, efficient inference and learning algorithms are obtained without oversimplifying the model of the underlying dynamical process. Evaluation of the proposed framework with competing approaches is conducted in three sets of experiments: dimensionality reduction and reconstruction using synthetic time series, video synthesis using a dynamic texture database, and human motion synthesis, classification and tracking on a benchmark data set. In all experiments, the proposed approach provides superior performance.

Temporal Dynamics of Decision-Making during Motion Perception in the Visual Cortex

How does the brain make decisions? Speed and accuracy of perceptual decisions covary with certainty in the input, and correlate with the rate of evidence accumulation in parietal and frontal cortical "decision neurons." A biophysically realistic model of interactions within and between Retina/LGN and cortical areas V1, MT, MST, and LIP, gated by basal ganglia, simulates dynamic properties of decision-making in response to ambiguous visual motion stimuli used by Newsome, Shadlen, and colleagues in their neurophysiological experiments. The model clarifies how brain circuits that solve the aperture problem interact with a recurrent competitive network with self-normalizing choice properties to carry out probablistic decisions in real time. Some scientists claim that perception and decision-making can be described using Bayesian inference or related general statistical ideas, that estimate the optimal interpretation of the stimulus given priors and likelihoods. However, such concepts do not propose the neocortical mechanisms that enable perception, and make decisions. The present model explains behavioral and neurophysiological decision-making data without an appeal to Bayesian concepts and, unlike other existing models of these data, generates perceptual representations and choice dynamics in response to the experimental visual stimuli. Quantitative model simulations include the time course of LIP neuronal dynamics, as well as behavioral accuracy and reaction time properties, during both correct and error trials at different levels of input ambiguity in both fixed duration and reaction time tasks. Model MT/MST interactions compute the global direction of random dot motion stimuli, while model LIP computes the stochastic perceptual decision that leads to a saccadic eye movement.

The Perception of Globally Coherent Motion

How do human observers perceive a coherent pattern of motion from a disparate set of local motion measures? Our research has examined how ambiguous motion signals along straight contours are spatially integrated to obtain a globally coherent perception of motion. Observers viewed displays containing a large number of apertures, with each aperture containing one or more contours whose orientations and velocities could be independently specified. The total pattern of the contour trajectories across the individual apertures was manipulated to produce globally coherent motions, such as rotations, expansions, or translations. For displays containing only straight contours extending to the circumferences of the apertures, observers' reports of global motion direction were biased whenever the sampling of contour orientations was asymmetric relative to the direction of motion. Performance was improved by the presence of identifiable features, such as line ends or crossings, whose trajectories could be tracked over time. The reports of our observers were consistent with a pooling process involving a vector average of measures of the component of velocity normal to contour orientation, rather than with the predictions of the intersection-of-constraints analysis in velocity space.

Manipulation of magnetic anisotropy in nanostructures

Of late, the magnetic properties of micro/nano-structures have attracted intense research interest both fundamentally and technologically particularly to address the question that how the manipulation in the different layers of nanostructures, geometry of a patterned structure can affect the overall magnetic properties, while generating novel applications such as in magnetic sensors, storage devices, integrated inductive components and spintronic devices. Depending on the applications, materials with high, medium or low magnetic anisotropy and their possible manipulation are required. The most dramatic manifestation in this respect is the chance to manipulate the magnetic anisotropy over the intrinsic preferential direction of the magnetization, which can open up more functionality particularly for device applications. Types of magnetic anisotropies of different nanostructured materials and their manipulation techniques are investigated in this work. Detail experimental methods for the quantitative determination of magnetic anisotropy in nanomodulated Ni45Fe55 thin film are studied. Magnetic field induced in-plane rotations within the nanomodulated Ni45Fe55 continuous films revealed various rotational symmetries of magnetic anisotropy due to dipolar interactions showing a crossover from lower to higher fold of symmetry as a function of modulation geometry. In a second approach, the control of exchange anisotropy at ferromagnetic (FM) – aniferomagnetic (AFM) interface in multifferoic nanocomposite materials, where two different phase/types of materials were simultaneously synthesized, was investigated. The third part of this work was to study the electroplated thin films of metal alloy nanocomposite for enhanced exchange anisotropy. In this work a unique observation of an anti-clock wise as well as a clock wise hysteresis loop formation in the Ni,Fe solid solution with very low coercivity and large positive exchange anisotropy/exchange bias have been investigated. Hence, controllable positive and negative exchange anisotropy has been observed for the first time which has high potential applications such as in MRAM devices.