Periodization of Chaotic Oscillations by Modulation of Discharge Voltage: System Response to Changes in Square-Wave Duty Cycle

Introduction: The mechanisms through which chest compressions (CC) generate blood flow remain controversial. The thoracic pump model is CC rate insensitive in the range 60 - 150 compressions per minute (cpm) but is sensitive to change in CC duty cycle with the prediction that increasing duty cycle would result in a modest, but linear, decrease in minute blood flow at a constant rate. Thus, the recently reported relationship between CC rate and outcomes may be due to changes in duty cycle instead of changes in rate. Methods: CPR was performed on nine domestic swine (∼30 Kg) using standard physiological monitoring. Flow was measured in the abdominal aorta, the inferior vena cava (IVC), the right renal artery and vein, the right common carotid and external jugular. Ventricular fibrillation (VF) was electrically induced. Mechanical CC were started after ten minutes of VF. CC were delivered at a rate of 50, 75, 100, 125, or 150 cpm and at a depth of 2” for a total of 54 min. CC rates were changed every 2 min and were randomized. The compression time was held constant at 350 ms. Results: CC generated blood flow showed a significant rate/duty cycle dependence and time dependence in all measured blood vessels. Early in the resuscitation, blood flows were optimized by rates above 100 cpm. As CC continued both the net blood flow and the optimal CC rate decreased as shown in Figure 1. Using previously collected data at 100 cpm and varying duty cycles, we found that minute blood flow did not decrease linearly with duty cycle, as predicted by the thoracic pump model. Conclusions: The optimal CC rate during CPR changes as a function of time suggesting that a fixed CC rate is not optimal. However, the data support the choice of ∼100 cpm as the “best” choice for a fixed CC rate. While some aspects of the observed rate effect may be explained by changes in CC duty cycle, these data do not support the idea that CC generated blood flow is independent of rate in the range 60-150 cpm.

The CFA duty cycle value controls the heating and cooling of the anode vanes, leading to thermal expansion and contraction, and thereby impacting the phase characteristic of the device. CFA phase similarity with respect to duty changes are therefore important for CFAs that are installed in radar systems that use rapid duty cycle changes. Because the AEGIS AN/SPY-1 Radar System operates using rapid duty cycle changes, the AEGIS AN/SPY-1 CFA must maintain (1) transient phase similarity, and (2) steady state phase similarity, both as a function of duty cycle. Until recently, test equipment limitations prevented the transient phase similarity data from being accurately collected. Engineering testing was conducted at Naval Surface Warfare Center to determine the phase similarity characteristics of the AEGIS CFA with respect to duty cycle changes. A sample of AEGIS AN/SPY-1 CFAs were characterized using a new test method, and the data was analyzed to determine how much the phase similarity changed in the device with changes in duty cycle. This paper describes the test equipment used, the testing procedure used, along with the phase similarity data with respect to duty cycle, for the AEGIS AN/SPY-1 CFA. It is believed that this is the first time instantaneous phase response to duty cycle testing has ever been done.

The objective of the present work is to propose a method for nonfeedback anticontrol of chaos with perturbations of minimum power for a preset control goal. The noted Lorenz system is employed as the test model for chaotification with the target state specified by a prescribed positive value of the largest Lyapunov exponent (LLE), lambda[over ]>0 . Periodic and quasiperiodic perturbations are used as control signals, and the signals parameters are optimized using a genetic algorithm under restriction of minimum power. Performance of the optimized signals in triggering chaos at an ordered state, fixed point or periodic, as well as further enhancing chaoticity at a chaotic state is explored. The present numerical experiments reveal the following interesting physics about chaotification. In general, the power for chaotification increases with the preset value of lambda and quasiperiodic signals can achieve the control goal with a lower power than periodic ones. Given the same increment of LLE from that of the uncontrolled state (lambda1,0) , i.e., Deltalambda=lambda-lambda1,0, the further enhancement of chaoticity in a chaotic state needs a higher control power than the triggering of chaos from an ordered state. The minimum power required for chaotification of an ordered state increases relatively slowly for lower lambda[over ] but increases drastically as the preset target LLE reaches a certain critical value. Most strikingly, the numerical experiments demonstrate that this critical value of lambda corresponds to LLE of the nearest chaotic state in the neighborhood of the uncontrolled state. Robustness of applying the present method in the presence of external noise is also demonstrated.

In this article the periodic signal detection method on the base of Duffing system cha otic oscillations analysis is presented. This work is a development of the chaos-based signal detection technique. Generally, chaos-based signal detection is the detection of chaotic-to-periodic state transition under input periodic component influence. If the in put periodic component reaches certain threshold value, the system transforms from chaotic state to periodic state. The Duffing-type chaotic systems are often used for such a signal detection purpose because of their ability to work in chaotic state for a long time and relatively simple realization. The main advantage of chaos-based signal detection methods is the utilization of chaotic system sensitivity to weak signals. But such methods are not used in practice because of the chaotic system state control problems. The method presented does not require an exact system state control. The Duffing system works continuously in chaotic state and the periodic signal detection process is based on the analysis of Duffing system Poincare map fractal structure. This structure does not depend on noise, and therefore the minimum input signal-to-noise ratio required for periodic signal detection is not limited by chaotic system state control tolerance.

A system of two identical superconducting quantum interference devices (SQUIDs) symmetrically coupled through their mutual inductance and driven by a sinusoidal field is investigated numerically with respect to dynamical properties such as its multibranched resonance curve, its bifurcation structure and transition to chaos as well as its synchronization behavior. The SQUID dimer is found to exhibit a hysteretic resonance curve with a bubble connected to it through Neimark-Sacker (torus) bifurcations, along with coexisting chaotic branches in their vicinity. Interestingly, the transition of the SQUID dimer to chaos occurs through a torus-doubling cascade of a two-dimensional torus (quasiperiodicity-to-chaos transition). Periodic, quasiperiodic, and chaotic states are identified through the calculated Lyapunov spectrum and illustrated using Lyapunov charts on the parameter plane of the coupling strength and the frequency of the driving field. The basins of attraction for chaotic and non-chaotic states are determined. Bifurcation diagrams are constructed on the parameter plane of the coupling strength and the frequency of the driving field, and they are superposed to maps of the three largest Lyapunov exponents on the same plane. Furthermore, the route of the system to chaos through torus-doubling bifurcations and the emergence of Hénon-like chaotic attractors are demonstrated in stroboscopic diagrams obtained with varying driving frequency. Moreover, asymmetric states that resemble localized synchronization have been detected using the correlation function between the fluxes threading the loop of the SQUIDs.

Mapping ion stability in digitally driven ion traps and guides

In this paper, we describe the statistical characteristics of weak signal detection by a chaotic Duffing oscillator, and present a new method for signal detection and estimation using the largest Lyapunov exponent. Previous research has shown that weak signals can be detected by a chaotic system. Many researchers use the Lyapunov exponent to flag the detection of a chaotic state, but our research shows that the Lyapunov exponent follows statistical characteristics, and therefore more factors should be considered in flagging chaotic weak signals. Here, we analyze the statistical characteristics inherent in the Lyapunov exponent calculation steps, and build up a statistical model for different chaotic states based on simulation data. Furthermore, we provide expressions for false-alarm and detection probabilities, selection of driving force threshold and detection of signal-noise-ratio. Finally, we summarize the method of signal amplitude estimation. Our research indicates that the performance of the detection system is related to sampling times and intervals, in accord with the theory of statistical signal detection.

Isolated rat diaphragm muscle was stimulated repetitively to induce fatigue, and the work done during each contraction was measured. Work per cycle was calculated by measuring force as the activated muscle was subjected to sinusoidal length changes (from 97 to 103% of L0, where L0 is rest length). Work was calculated from the loop formed when force was plotted against length. Work done was positive when the muscle was shortening and was negative when it was lengthening; net work was the difference. Work output was varied by changing the stimulus duty cycle (4, 8, or 16% of the total cycle duration) and cycle frequency (1, 2, or 4 Hz). The rate and extent of the decrease in power was influenced much more by changes in cycle frequency than by changes in duty cycle. Duty cycle and cycle frequency combinations that resulted in greater power in the prefatigue trials were associated with a more rapid rate of fatigue. However, net positive power at the end of the 15-min fatigue period was greater under these same conditions (i.e., high duty cycle and high cycle frequency). Fatigue in working diaphragm muscle depends more on cycle frequency than on duty cycle.

Chaos in a fixed frequency dc chopper fed PMDC drive system is realized in current control mode. The dynamical system of voltage and current control mode are described by the state space representation in the continuous conduction mode. Two different tools are used to detect the chaos. The chaotic phenomena are observed by varying the speed error amplifier gain of the motor. A special observation is investigated that the switching loss is less when the system is in chaotic state. To justify the realization switching loss in voltage mode and current controlled mode is calculated. The study is helpful in selecting the range and combination of parameters to run the motor at desired speed with or without chaos.

Glow discharge plasmas exhibit various types of self-excited oscillations for different initial conditions like discharge voltages and filling pressures. The behavior of such oscillations associated with the anode glow has been investigated using nonlinear techniques like correlation dimension, largest Lyapunov exponent, etc. It is seen that these oscillations go to an ordered state from a chaotic state with an increase in input energy, i.e., with discharge voltages implying occurrence of inverse bifurcations. These results are different from the other observations wherein the fluctuations have been observed to go from ordered to chaotic state.

With the polarization of quantum-dot cell and quantum phase serving as state variables, this paper does both theoretical analysis and simulation for the complex nonlinear dynamical behaviour of a three-cell-coupled Quantum Cellular Neural Network (QCNN), including equilibrium points, bifurcation and chaotic behaviour. Different phenomena, such as quasi-periodic, chaotic and hyper-chaotic states as well as bifurcations are revealed. The system's bifurcation and chaotic behaviour under the influence of the different coupling parameters are analysed. And it finds that the unbalanced cells coupled QCNN is easy to cause chaotic oscillation and the system response enters into chaotic state from quasi-periodic state by quasi-period bifurcation; however, the balanced cells coupled QCNN also can be chaotic when coupling parameters is in some region. Additionally, both the unbalanced and balanced cells coupled QCNNs can possess hyper-chaotic behaviour. It provides valuable information about QCNNs for future application in high-parallel signal processing and novel ultra-small chaotic generators.

We investigated the selective effects of changes in transdiaphragmatic pressure (Pdi) and duty cycle on diaphragmatic blood flow in supine dogs at normal arterial pressure (N), moderate hypotension (MH), and severe hypotension (SH) [mean arterial pressure (Part) of 116, 75, and 50 mmHg, respectively]. The diaphragm was paced at a rate of 12/min by bilateral phrenic nerve stimulation. Left phrenic (Qphr-T) and left internal mammary (Qim-T) arterial flows were measured by electromagnetic flow probes. Changes in Pdi and duty cycle were achieved by changing the stimulation frequencies and the duration of contraction, whereas Part changes were produced by bleeding. With N and at a duty cycle of 0.5, incremental increases in Pdi produced peaks in Qphr-T and Qim-T at 30% maximum diaphragmatic pressure (Pdimax) with a gradual decline at higher Pdi. With MH and SH, blood flow peaked at 10% Pdimax. At any given Pdi, blood flow was lower with MH and SH in comparison to N. The effect of duty cycle was tested at two levels of Pdi. With N and at low Pdi (25% Pdimax), blood flow rose progressively with increases in duty cycle, whereas at moderate Pdi level (50% Pdimax) blood flow peaked at a duty cycle of 0.3, with no increase thereafter. With MH, blood flow at low Pdi rose linearly with increasing duty cycle but to a lesser extent than with N, and at a moderate Pdi flow peaked at a duty cycle of 0.3. With SH, blood flow at low and moderate Pdi was limited at duty cycles greater than 0.3 and 0.1, respectively.(ABSTRACT TRUNCATED AT 250 WORDS)

Influence of duty cycle on the microstructure and microhardness of pulse electrodeposited Ni–CeO 2 nanocomposite coating

Synthesis of functionally gradient coating was the main goal of researches to cover some deficiencies of metallic coatings. In this study, a new strategy for generating functionally gradient coatings of nickel-chromium on a carbon steel substrate using pulse electrodeposition has been presented. The gradual changes of the duty cycle and pulse frequency were used to generate the functionally gradient coating, and the chemical composition, microstructure, microhardness, wear and corrosion of them were investigated. Gradual changes of the duty cycle from 45 to 80% led to a gradient structure with a chromium content of 83% on the surface and 3% in the vicinity of the interface. Frequency changes had no significant effect on the chemical composition and did not result in the production of gradient coatings. In both groups, wear resistance improved related to the monolayer one so that weight loss in former group is reduced about 33-62% and in later group decreased almost 13-30%. Also, the corrosion current density in the samples deposited by gradual change of duty cycle was approximately 0.01-0.04 times of that for monolayer coatings. The microhardness value in the top layers of FGD coating was in the range of 650-800 HV 0.01 which reduced gradually towards the substrate. The high Cr content in the top layers is the reason for high hardness and good corrosion resistance.

High-frequency transformers are subject to excitation with a changing duty cycle during operation. Due to magnetic relaxation, the duty cycle of the rectangular wave affects the magnetization time of nanocrystalline alloy for the core material, which affects whether the transformer can reach the saturation operating point. Based on the micromagnetic theory, a three-dimensional model of the nanocrystalline alloy is established, and rectangular wave excitation with different duty cycle D is applied to the micro-model. The influence of D on the magnetization process is analyzed in terms of the hysteresis loss Pv and magnetic moment deflection angular velocity ω. The results indicate that when D = 0.5, Pv is the smallest, and when D increases or decreases, Pv increases. Furthermore, Pv remains the same under the rectangular wave excitation that satisfies the sum of different duty cycles of 1. Regarding ω, the smallest value occurs at the rising edge of the excitation when D = 0.1, while the largest value occurs when D = 0.9. During the falling edge stage, ω is smallest when D = 0.9 and largest when D = 0.1. These results demonstrate that the duty cycle D influences the magnetization time of the material. Due to magnetic relaxation, changing the magnetization time determines whether the material can reach saturation magnetization. Therefore, there is a critical state, which is defined as the critical duty cycle Dc. The results show that for D < 0.5, the range of Dc1 is between 0.2 and 0.21, and for D > 0.5, the range of Dc2 is between 0.8 and 0.81. Increasing the amplitude of the excitation source causes a decrease in Dc, while increasing the frequency causes an increase in Dc.