Effective AC and DC responses of nonlinear composites at higher concentration

For higher concentration of inclusions, an effective medium approximation (EMA) method is used to investigate the bulk effective response of weakly nonlinear composites, which are subject to the constitutive relation of electric displacement and electric field, D-alpha = epsilon E-alpha + chi(alpha)|E|(2) E. As an example of three dimensions, under the external AC and DC electric fields E-app = E-a (1 + sin omega t), we have derived the general effective nonlinear response of composites by the EMA method for higher concentration of spherical inclusions. Furthermore, the effective nonlinear responses at harmonics are predicted.

Dielectric response of spherically anisotropic graded piezoelectric composites

A graded piezoelectric composite consisting of a spherically anisotropic graded piezoelectric inclusion imbedded in an infinite nonpiezoelectric matrix, with the physical properties of the graded spherical inclusion having a power-law profile with respect to the radial variable r, is studied theoretically. Under an external uniform electric field, the electric displacement field and the elastic stress tensor field of this spherically anisotropic graded piezoelectric composite are derived exactly by means of displacement separation technique, based on the governing equations in the dilute limit. A piezoelectric response mechanism, in which the effective piezoelectric response vanishes along the z direction (or x,y directions), is revealed in this kind of graded piezoelectric composites. Furthermore, it is found that the effective dielectric constant decreases (or increases) with the volume fraction p of the inclusions if the exponent parameter k of the grading profile is larger (or smaller) than a critical value. (C) 2007 American Institute of Physics.

Photosynthesis-irradiance response at physiological level: A mechanistic model

A mechanistic model is developed to present the photosynthetic response of phytoplankton to irradiance at the physiological level. The model is operated on photosynthetic units (PSU), and each PSU is assumed to have two states: reactive and activated. Light absorption that drives a reactive PSU into the activated state results from the effective absorption of the PSU. Transitions between the two states are asymmetrical in rate. A PSU in the reactive state becomes activated much faster than it recovers from the activated state to the reactive one. The turnover time for an activated PSU to transit into the reactive one is defined by the turnover time of the electron transport chain. The present model yields a photosynthesis-irradiance curve (PE-curve) in a hyperbola, which is described by three physiological parameters: effective cross-section (sigma (PSII)), turnover time of electron transport chain (tau) and number of PSUs (N). The PE-curve has an initial slope of sigma (PSII) x N, a half-saturated irradiance of 1/(sigma (PSII)), and a maximal photosynthetic rate of Nlc at the saturated irradiance. The PE-curve from the present model is comparable to the empirical function based on the target theory described by the Poisson distribution. (C) 2001 Academic Press.

Cellular automata: Simulating alpine tundra vegetation dynamics in response to global warming

This study attempts to model alpine tundra vegetation dynamics in a tundra region in the Qinghai Province of China in response to global warming. We used Raster-based cellular automata and a Geographic Information System to study the spatial and temporal vegetation dynamics. The cellular automata model is implemented with IDRISI's Multi-Criteria Evaluation functionality to simulate the spatial patterns of vegetation change assuming certain scenarios of global mean temperature increase over time. The Vegetation Dynamic Simulation Model calculates a probability surface for each vegetation type, and then combines all vegetation types into a composite map, determined by the maximum likelihood that each vegetation type should distribute to each raster unit. With scenarios of global temperature increase of I to 3 degrees C, the vegetation types such as Dry Kobresia Meadow and Dry Potentilla Shrub that are adapted to warm and dry conditions tend to become more dominant in the study area.

Dynamic and complex microclimate responses to warming and grazing manipulations

Synthesis efforts that identify patterns of ecosystem response to a suite of warming manipulations can make important contributions to climate change science. However, cross-study comparisons are impeded by the paucity of detailed analyses of how passive warming and other manipulations affect microclimate. Here we document the independent and combined effects of a common passive warming manipulation, open-top chambers (OTCs), and a simulated widespread land use, clipping, on microclimate on the Tibetan Plateau. OTCs consistently elevated growing season averaged mean daily air temperature by 1.0-2.0 degrees C, maximum daily air temperature by 2.1-7.3 degrees C and the diurnal air temperature range by 1.9-6.5 degrees C, with mixed effects on minimum daily air temperature, and mean daily soil temperature and moisture. These OTC effects on microclimate differ from reported effects of a common active warming method, infrared heating, which has more consistent effects on soil than on air temperature. There were significant interannual and intragrowing season differences in OTC effects on microclimate. For example, while OTCs had mixed effects on growing season averaged soil temperatures, OTCs consistently elevated soil temperature by approximately 1.0 degrees C early in the growing season. Nonadditive interactions between OTCs and clipping were also present: OTCs in clipped plots generally elevated air and soil temperatures more than OTCs in nonclipped plots. Moreover, site factors dynamically interacted with microclimate and with the efficacy of the OTC manipulations.These findings highlight the need to understand differential microclimate effects between warming methods, within warming method across ecosystem sites, within warming method crossed with other treatments, and within sites over various timescales. Methods, sites and scales are potential explanatory variables and covariables in climate warming experiments. Consideration of this variability among and between experimental warming studies will lead to greater understanding and better prediction of ecosystem response to anthropogenic climate warming.

岩石中地震波速度和衰减的应力变化响应研究

Stress change is one of key factors in seismic nucleating and triggering; therefore for understanding and forecasting earthquakes, it is necessary to research on stress status and its changes in rocks. Propagating in underground structures, wave velocity and attenuation contain information on stress changes of the Earth’s interior. For a better understanding of relationship between seismic data and stress changes, modeling and ultrasonic test supply significant references. In this article, acoustoelastic theory is introduced to explain nonlinear elastic characteristics of rocks. Based on the acoustoelastic theory, a solid-fluid coupled model is given to calculate velocity under different stress for porous and liquid fulfilled rocks. Except for the stress-velocity relationship, effects of pore pressure induced stress changes on ultrasonic coda attenuation are also studied. Intrinsic attenuation quality factors are calculated for a comparison purpose. Finally, the relationship between elastic constants and stress changes is thoroughly investigated, a mixture model from two phases of Hooke media is introduced to explain the differences between dynamic and static moduli, a relation among wave length, wave velocities and elastic moduli considering dimension of microstructure, dimension and state of surface between phases is presented. The most important aspect of this work is exploring and establishing relationships between the seismic properties of rocks and changes of their stress conditions, which will have its application in earthquake forecast and seismic hazard.

中高层大气对低层大气声重波响应的分析

Acoustic Gravity waves (AGW) play an important role in balancing the atmospheric energy and momentum budget. Propagation of gravity wave in the atmosphere is one of the important factors of changing middle and upper atmosphere and ionosphere. The purpose of this dissertation is to study the propagation of gravity wave in a compression atmosphere whit means of numerical simulation and to analyze the response of middle and upper atmosphere to pulse disturbance from lower atmosphere. This work begins with the establishment of 2-D fully nonlinear compressible atmospheric dynamic model in polar coordinate, which is used ton numerically study gravity wave propagation. Then the propagation characteristics of acoustic gravity wave packets are investigated and discussed. We also simulate the response of middle and upper atmosphere to pulse disturbance of lower atmosphere in background winds or without background winds by using this model and analyze the data we obtained by using Fourier Transform (FT), Short-time Fourier Transform (STFT) and Empirical Mode Decomposition (EMD) method which is an important part of Hilbert-Huang Transform (HHT). The research content is summarized in the following: 1. By using a two-dimensional full-implicit-continuous-Eulerian (FICE) scheme and taking the atmospheric basic motion equations as the governing equations, a numerical model for nonlinear propagation of acoustic gravity wave disturbance in two-dimensional polar coordinates is solved. 2. Then the propagation characteristics of acoustic gravity wave packets are investigated and discussed. Results of numerical simulation show that the acoustic gravity wave packets propagate steadily upward and keep its shape well after several periods. 3. We simulate the response of middle and upper atmosphere to pulse disturbance of lower atmosphere in background winds or without background winds by using this model, and obtain the distribution of a certain physical quantity in time and space from earth’s surface to 300km above. The results reveal that the response of ionosphere occurs at a large horizontal distance from the source and the disturbance becomes greater with increasing of height. The situation when the direction of the background wind is opposite to or the same as the direction of disturbed velocity of gravity-wave is studied. The results show that gravity wave propagating against winds is easier than those propagating along winds and the background wind can accelerate gravity wave propagation. Just upon the source, an acoustic wave component with period of 6 min can be found. These images of simulation are similar to observations of the total electron content (TEC) disturbances caused by the great Sumatra-Andaman earthquake on December 26 in 2004. 4. Using the EMD method the disturbed velocity data of a certain physical quantity in time and space can be decomposed into a series of intrinsic mode function (IMF) and a trend mode respectively. The results of EMD reveal impact of the gravity wave frequency under the background winds.

Animated virtual agents to cue user attention: comparison of static and dynamic deictic cues on gaze and touch responses

This paper describes an experiment developed to study the performance of virtual agent animated cues within digital interfaces. Increasingly, agents are used in virtual environments as part of the branding process and to guide user interaction. However, the level of agent detail required to establish and enhance efficient allocation of attention remains unclear. Although complex agent motion is now possible, it is costly to implement and so should only be routinely implemented if a clear benefit can be shown. Pevious methods of assessing the effect of gaze-cueing as a solution to scene complexity have relied principally on two-dimensional static scenes and manual peripheral inputs. Two experiments were run to address the question of agent cues on human-computer interfaces. Both experiments measured the efficiency of agent cues analyzing participant responses either by gaze or by touch respectively. In the first experiment, an eye-movement recorder was used to directly assess the immediate overt allocation of attention by capturing the participant’s eyefixations following presentation of a cueing stimulus. We found that a fully animated agent could speed up user interaction with the interface. When user attention was directed using a fully animated agent cue, users responded 35% faster when compared with stepped 2-image agent cues, and 42% faster when compared with a static 1-image cue. The second experiment recorded participant responses on a touch screen using same agent cues. Analysis of touch inputs confirmed the results of gaze-experiment, where fully animated agent made shortest time response with a slight decrease on the time difference comparisons. Responses to fully animated agent were 17% and 20% faster when compared with 2-image and 1-image cue severally. These results inform techniques aimed at engaging users’ attention in complex scenes such as computer games and digital transactions within public or social interaction contexts by demonstrating the benefits of dynamic gaze and head cueing directly on the users’ eye movements and touch responses.

Dynamic Window-Constrained Scheduling for Real-Time Media Streaming

This paper describes an algorithm for scheduling packets in real-time multimedia data streams. Common to these classes of data streams are service constraints in terms of bandwidth and delay. However, it is typical for real-time multimedia streams to tolerate bounded delay variations and, in some cases, finite losses of packets. We have therefore developed a scheduling algorithm that assumes streams have window-constraints on groups of consecutive packet deadlines. A window-constraint defines the number of packet deadlines that can be missed in a window of deadlines for consecutive packets in a stream. Our algorithm, called Dynamic Window-Constrained Scheduling (DWCS), attempts to guarantee no more than x out of a window of y deadlines are missed for consecutive packets in real-time and multimedia streams. Using DWCS, the delay of service to real-time streams is bounded even when the scheduler is overloaded. Moreover, DWCS is capable of ensuring independent delay bounds on streams, while at the same time guaranteeing minimum bandwidth utilizations over tunable and finite windows of time. We show the conditions under which the total demand for link bandwidth by a set of real-time (i.e., window-constrained) streams can exceed 100% and still ensure all window-constraints are met. In fact, we show how it is possible to guarantee worst-case per-stream bandwidth and delay constraints while utilizing all available link capacity. Finally, we show how best-effort packets can be serviced with fast response time, in the presence of window-constrained traffic.

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.

Simulations of X and Y Retinal Ganglion Cell Behavior with a Nonlinear Push-pull Model of Spatiotemporal Retinal Processing

This article describes a nonlinear model of neural processing in the vertebrate retina, comprising model photoreceptors, model push-pull bipolar cells, and model ganglion cells. Previous analyses and simulations have shown that with a choice of parameters that mimics beta cells, the model exhibits X-like linear spatial summation (null response to contrast-reversed gratings) in spite of photoreceptor nonlinearities; on the other hand, a choice of parameters that mimics alpha cells leads to Y-like frequency doubling. This article extends the previous work by showing that the model can replicate qualitatively many of the original findings on X and Y cells with a fixed choice of parameters. The results generally support the hypothesis that X and Y cells can be seen as functional variants of a single neural circuit. The model also suggests that both depolarizing and hyperpolarizing bipolar cells converge onto both ON and OFF ganglion cell types. The push-pull connectivity enables ganglion cells to remain sensitive to deviations about the mean output level of nonlinear photoreceptors. These and other properties of the push-pull model are discussed in the general context of retinal processing of spatiotemporal luminance patterns.

A Neural Network Model for the Spatial and Temporal Response of Retinal Ganglion Cells

This article introduces a quantitative model of early visual system function. The model is formulated to unify analyses of spatial and temporal information processing by the nervous system. Functional constraints of the model suggest mechanisms analogous to photoreceptors, bipolar cells, and retinal ganglion cells, which can be formally represented with first order differential equations. Preliminary numerical simulations and analytical results show that the same formal mechanisms can explain the behavior of both X (linear) and Y (nonlinear) retinal ganglion cell classes by simple changes in the relative width of the receptive field (RF) center and surround mechanisms. Specifically, an increase in the width of the RF center results in a change from X-like to Y-like response, in agreement with anatomical data on the relationship between α- and

A Unified Model of Spatiotemporal Processing in the Retina

A computational model of visual processing in the vertebrate retina provides a unified explanation of a range of data previously treated by disparate models. Three results are reported here: the model proposes a functional explanation for the primary feed-forward retinal circuit found in vertebrate retinae, it shows how this retinal circuit combines nonlinear adaptation with the desirable properties of linear processing, and it accounts for the origin of parallel transient (nonlinear) and sustained (linear) visual processing streams as simple variants of the same retinal circuit. The retina, owing to its accessibility and to its fundamental role in the initial transduction of light into neural signals, is among the most extensively studied neural structures in the nervous system. Since the pioneering anatomical work by Ramón y Cajal at the turn of the last century[1], technological advances have abetted detailed descriptions of the physiological, pharmacological, and functional properties of many types of retinal cells. However, the relationship between structure and function in the retina is still poorly understood. This article outlines a computational model developed to address fundamental constraints of biological visual systems. Neurons that process nonnegative input signals-such as retinal illuminance-are subject to an inescapable tradeoff between accurate processing in the spatial and temporal domains. Accurate processing in both domains can be achieved with a model that combines nonlinear mechanisms for temporal and spatial adaptation within three layers of feed-forward processing. The resulting architecture is structurally similar to the feed-forward retinal circuit connecting photoreceptors to retinal ganglion cells through bipolar cells. This similarity suggests that the three-layer structure observed in all vertebrate retinae[2] is a required minimal anatomy for accurate spatiotemporal visual processing. This hypothesis is supported through computer simulations showing that the model's output layer accounts for many properties of retinal ganglion cells[3],[4],[5],[6]. Moreover, the model shows how the retina can extend its dynamic range through nonlinear adaptation while exhibiting seemingly linear behavior in response to a variety of spatiotemporal input stimuli. This property is the basis for the prediction that the same retinal circuit can account for both sustained (X) and transient (Y) cat ganglion cells[7] by simple morphological changes. The ability to generate distinct functional behaviors by simple changes in cell morphology suggests that different functional pathways originating in the retina may have evolved from a unified anatomy designed to cope with the constraints of low-level biological vision.

Typical delay determines waiting time on periodic-food schedules: Static and dynamic tests.

Pigeons and other animals soon learn to wait (pause) after food delivery on periodic-food schedules before resuming the food-rewarded response. Under most conditions the steady-state duration of the average waiting time, t, is a linear function of the typical interfood interval. We describe three experiments designed to explore the limits of this process. In all experiments, t was associated with one key color and the subsequent food delay, T, with another. In the first experiment, we compared the relation between t (waiting time) and T (food delay) under two conditions: when T was held constant, and when T was an inverse function of t. The pigeons could maximize the rate of food delivery under the first condition by setting t to a consistently short value; optimal behavior under the second condition required a linear relation with unit slope between t and T. Despite this difference in optimal policy, the pigeons in both cases showed the same linear relation, with slope less than one, between t and T. This result was confirmed in a second parametric experiment that added a third condition, in which T + t was held constant. Linear waiting appears to be an obligatory rule for pigeons. In a third experiment we arranged for a multiplicative relation between t and T (positive feedback), and produced either very short or very long waiting times as predicted by a quasi-dynamic model in which waiting time is strongly determined by the just-preceding food delay.

Thermodynamic and dynamic contributions to future changes in regional precipitation variance: focus on the Southeastern United States

© 2014, Springer-Verlag Berlin Heidelberg.The frequency and severity of extreme events are tightly associated with the variance of precipitation. As climate warms, the acceleration in hydrological cycle is likely to enhance the variance of precipitation across the globe. However, due to the lack of an effective analysis method, the mechanisms responsible for the changes of precipitation variance are poorly understood, especially on regional scales. Our study fills this gap by formulating a variance partition algorithm, which explicitly quantifies the contributions of atmospheric thermodynamics (specific humidity) and dynamics (wind) to the changes in regional-scale precipitation variance. Taking Southeastern (SE) United States (US) summer precipitation as an example, the algorithm is applied to the simulations of current and future climate by phase 5 of Coupled Model Intercomparison Project (CMIP5) models. The analysis suggests that compared to observations, most CMIP5 models (~60 %) tend to underestimate the summer precipitation variance over the SE US during the 1950–1999, primarily due to the errors in the modeled dynamic processes (i.e. large-scale circulation). Among the 18 CMIP5 models analyzed in this study, six of them reasonably simulate SE US summer precipitation variance in the twentieth century and the underlying physical processes; these models are thus applied for mechanistic study of future changes in SE US summer precipitation variance. In the future, the six models collectively project an intensification of SE US summer precipitation variance, resulting from the combined effects of atmospheric thermodynamics and dynamics. Between them, the latter plays a more important role. Specifically, thermodynamics results in more frequent and intensified wet summers, but does not contribute to the projected increase in the frequency and intensity of dry summers. In contrast, atmospheric dynamics explains the projected enhancement in both wet and dry summers, indicating its importance in understanding future climate change over the SE US. The results suggest that the intensified SE US summer precipitation variance is not a purely thermodynamic response to greenhouse gases forcing, and cannot be explained without the contribution of atmospheric dynamics. Our analysis provides important insights to understand the mechanisms of SE US summer precipitation variance change. The algorithm formulated in this study can be easily applied to other regions and seasons to systematically explore the mechanisms responsible for the changes in precipitation extremes in a warming climate.