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From joint sea surface temperature/sea level pressure (SST/SLP) EOF analyses, lowfrequency variability modes are compared. The multi-decadal oscillation (MDO) changed phases twice during the 20th century, with its north Atlantic SST patterns resembling the Atlantic multi-decadal oscillation (AMO). The quasi-decadal oscillation (QDO) SST patterns displayed a double tripole configuration over the entire Atlantic basin, leading to tropical inter-hemispheric out-of-phase relationship. From the mid-1960s onward, while ST anomalies were negative to the north (negative phases of MDO/AMO), the Sahelian drought persisted with a weaker hurricane power dissipation index (PDI). During that period, the QDO modulated the intensity of the Sahelian drought.
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Oscillators, Electric
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The response of the Max Planck Institute's ECHAM3 atmospheric general circulation model to a prescribed decade-long positive anomaly in sea surface temperatures (SSTs) over the North Atlantic is investigated. Two 10-yr realizations of the anomaly experiment are compared against a 100-yr control run of the model with seasonally varying climatological SST using a model spatial resolution of T42. In addition to the time-mean response, particular attention is paid to changes in intraseasonal variability, expressed in terms of North Atlantic–European weather regimes. The model regimes are quite realistic. Substantial differences are found in the 700-mb geopotential height field response between the two decadal realizations. The time-mean response in the first sample decade is characterized by the positive (zonal) phase of the North Atlantic oscillation (NAO); this response can be identified with changes in the frequency of occurrence of certain weather regimes by about one standard deviation. (Preliminary results of this numerical experiment were reported at the Atlantic Climate Variability Workshop held at the Lamont–Doherty Earth Observatory of Columbia University, Palisades, New York, 24–26 September 1997.) By contrast, the second SST anomaly decade shows a localized trough centered over the British Isles; it projects less strongly onto the model's intrinsic weather regimes. The control run itself exhibits pronounced decade-to-decade variations in the weather regimes' frequency of occurrence as well as in its NAO index. The two 10-yr anomaly experiments are insufficient, in length and number, to identify a robust SST response above this level of intrinsic variability.
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Frequencies of oscillating systems--Measurement... Nonlinear oscillators
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Oscillators, Electric
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ENSO (El Nino-Southern Oscillation) has a large influence on tropical cyclone activity. The authors examine how different environmental factors contribute to this influence, using a genesis potential index developed by Emanuel and Nolan. Four factors contribute to the genesis potential index: low-level vorticity (850hPa), relative humidity at 600hPa, the magnitude of vertical wind shear from 850 to 200hPa and potential intensity (PI). Using monthly NCEP Reanalysis data in the period of 1950-2005, we calculate the genesis potential index on a latitude strip from 60°S to 60°N. Composite anomalies of the genesis potential index are produced for El Nino and La Nina years separately. These composites qualitatively replicate the observed interannual variations of the observed frequency and location of genesis in several different basins. This justifies producing composites of modified indices in which only one of the contributing factors varies, with the others set to climatology, to determine which among the factors are most important in causing interannual variations in genesis frequency. Specific factors that have more influence than others in different regions can be identified. For example, in El Nino years, relative humidity and vertical shear are important for the reduction in genesis seen in the Atlantic basin, and relative humidity and vorticity are important for the eastward shift in the mean genesis location in the western North Pacific.
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We consider a box model of the Arctic system to examine its natural variability pertaining to the decadal Arctic Oscillation (AO) and the multidecadal Low-Frequency Oscillation (LFO). We distinguish the hierarchical order of the winter over the summer open-areas with only the former perturbing the sea-level pressure to effect coupled balances. From such balances, we discern two feedback loops on the winter open-area: a positive ice-flux feedback that elevates its overall variance and a negative buoyancy feedback that suppresses its low-frequency variance to render a decadal AO peak when subjected to white atmospheric noise. This negative buoyancy feedback may also reproduce observed phasing among LFO signals forced by the AMV (Atlantic Multidecadal Variability), thus resolving some outstanding questions. For the summer open-area, its variance is induced mainly by the winter forcings and insensitive to the base state. Its decadal signal merely reflects the preconditioning winter open-area, but its LFO variance is induced additionally and in comparable measure by the winter SAT (surface air temperature) through the latter’s effect on the melt duration and the first-year ice thickness. As such, the summer open-area signal is dominantly multidecadal, which moreover is several times its winter counterpart, consistent with the observed disparity. Although the model is extremely crude, its explicit solution allows quantitative comparison with observations and the generally positive outcome suggests that the model has isolated the essential physics of the Arctic natural variability of our concern.
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Switching between a state of fear and safety is a critical aspect of adaptive behavior. Aversive and non-aversive associations must be formed quickly and reliably but remain malleable as these associations change dynamically. When these associations become biased towards aversive associations by traumatic and stressful circumstances, as in PTSD, fear generalization and impaired fear extinction arise. These changes are associated with reduced activity in the medial prefrontal cortex (mPFC) and enhanced activity in the basolateral amygdala (BLA). It has been hypothesized that the mPFC mediates top-down control of the BLA to signal safety. It has previously been demonstrated that synchronous activity within the mPFC-BLA circuit is strongly engaged during fear conditioning, but it is unknown how activity in this circuit changes to mediate aversive discrimination. We investigated how the mPFC and BLA cooperate to mediate successful discrimination between aversive and non-aversive stimuli both for learned and innately-valent associations. Extracellular elecrophysiological recordings were obtained simultaneously form the mPFC and BLA in mice during innate anxiety, fear discrimination, and fear extinction. Local field potentials were recorded in both structures along with single unit recordings from the BLA. We discovered that fear was associated with enhanced theta-frequency synchrony and theta-gamma coupling within the mPFC-BLA circuit. On the other hand, safety was associated with predominant mPFC-to-BLA directionality of synchronous information flow and enhanced fast gamma frequency activity in both structures. Interestingly, gamma oscillations in the BLA were strongly coupled to theta frequency activity arising in the mPFC. This data is consistent with entrainment of inhibitory circuits in the BLA by mPFC input to mediate safety.
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In 1745 a Scotch Benedictine monk Andrew Gordon discovered Contact Charge Electrophoresis (CCEP) which remained in dormant state for centuries until gaining renewed prominence in the field of particle manipulation and actuation. Contact Charge Electrophoresis (CCEP) refers to the continuous to and fro motion of a conductive object between two electrodes subject to an applied voltage. The continuous motion of the conductive particle and the low power requirement provide an attractive alternative to traditional methods for particle manipulation techniques such as dielectrophoresis. Recent efforts to understand and apply CCEP have focused on the motion of single particles and we present dynamics of multiple conductive particles dispersed in non-conducting media that utilize CCEP to perform tasks like pumping and cargo transport operations as well as multiparticle clusters capable of tailored trajectories. Chapters 1 provides motivation for this work and background on CCEP. Providing brief details on development of microfluidic devices and modeling that are covered in more details in subsequent chapters. It also focuses on the historical aspect of CCEP, relevant background, mechanism, physics, application strategies in literature, strategies developed for single particle systems and possible extension to multiparticle systems. Chapters 2 and 3 talk about the dynamics and modeling of multiple conductive particles both in dispersion and aggregates/clusters powered by CCEP. In Chapter 2, we propose a new hybrid approach based on image-based method proposed earlier by Bonnecaze[18] for modeling CCEP. It covers challenges to modeling a multiple particle system in confinement, dynamics of chain formation and dynamics of cluster comprising conductive and non-conductive particles between two electrodes. While Chapter 3 focuses on details of methods and techniques used in development of the simulation for dispersion of conductive particles in confinement. Here we also illustrate variation of conductivity for complete range of electrode separation with varying volume fraction. Chapter 4 expands on multiple particle CCEP and shows that when we physically constrain particle trajectories to parallel tracks between the electrodes, the traveling waves of mechanical actuation can be realized in linear arrays of electromechanical oscillators that move and interact via electrostatic forces. Conductive spheres oscillate between biased electrodes through cycles of contact charging and electrostatic actuation. The combination of repulsive interactions among the particles and spatial gradients in their natural frequencies lead to phase locked states characterized by gradients in the oscillation phase. The frequency and wavelength of these traveling waves can be specified independently by varying the applied voltage and the electrode separation. We demonstrate how traveling wave synchronization can enable the directed transport of material cargo. Our results suggests that simple energy inputs can power complex patterns of mechanical actuation with potential opportunities for soft robotics and colloidal machines. Chapter 5 systematically investigate the dynamics of cluster comprising multiple spherical conductive particles driven via contact charge electrophoresis (CCEP). We are specifically interested in understanding dynamics of closed packed cluster of particles with both conductive and non-conductive particles in three dimensions(3D). Finally, Chapter 6 summarizes new ideas and proposes possible applications for multiple particle Contact charge electrophoresis motivated by this dissertation.
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Uncertainty propagation in engineering mechanics and dynamics is a highly challenging problem that requires development of analytical/numerical techniques for determining the stochastic response of complex engineering systems. In this regard, although Monte Carlo simulation (MCS) has been the most versatile technique for addressing the above problem, it can become computationally daunting when faced with high-dimensional systems or with computing very low probability events. Thus, there is a demand for pursuing more computationally efficient methodologies. Further, most structural systems are likely to exhibit nonlinear and time-varying behavior when subjected to extreme events such as severe earthquake, wind and sea wave excitations. In such cases, a reliable identification approach is behavior and for assessing its reliability. Current work addresses two research themes in the field of stochastic engineering dynamics related to the above challenges. In the first part of the dissertation, the recently developedWiener Path Integral (WPI) technique for determining the joint response probability density function (PDF) of nonlinear systems subject to Gaussian white noise excitation is generalized herein to account for non-white, non-Gaussian, and non-stationary excitation processes. Specifically, modeling the excitation process as the output of a filter equation with Gaussian white noise as its input, it is possible to define an augmented response vector process to be considered in the WPI solution technique. A significant advantage relates to the fact that the technique is still applicable even for arbitrary excitation power spectrum forms. In such cases, it is shown that the use of a filter approximation facilitates the implementation of the WPI technique in a straightforward manner, without compromising its accuracy necessarily. Further, in addition to dynamical systems subject to stochastic excitation, the technique can also account for a special class of engineering mechanics problems where the media properties are modeled as non-Gaussian and non-homogeneous stochastic fields. Several numerical examples pertaining to both single- and multi-degree-of freedom systems are considered, including a marine structural system exposed to flow-induced non-white excitation, as well as a beam with a non-Gaussian and non-homogeneous Young’s modulus. Comparisons with MCS data demonstrate the accuracy of the technique. In the second part of the dissertation, a novel multiple-input/single-output (MISO) system identification technique is developed for parameter identification of nonlinear time-variant multi-degree-of-freedom oscillators with fractional derivative terms subject to incomplete non-stationary data. The technique utilizes a representation of the nonlinear restoring forces as a set of parallel linear subsystems. In this regard, the oscillator is transformed into an equivalent MISO system in the wavelet domain. Next, a recently developed L1-norm minimization procedure based on compressive sampling theory is applied for determining the wavelet coefficients of the available incomplete non-stationary input-output (excitation-response) data. Finally, these wavelet coefficients are utilized to determine appropriately defined time- and frequency-dependent wavelet based frequency response functions and related oscillator parameters. A nonlinear time-variant system with fractional derivative elements is used as a numerical example to demonstrate the reliability of the technique even in cases of noise corrupted and incomplete data.
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