Time Delay Research Articles

Theoretical study of the second- and third-H-abstraction reactions of monomethylhydrazine and nitrogen dioxide and its application to hypergolic ignition modeling

The chemical kinetics of the second–H-abstraction and the third-H-abstraction reactions of monomethylhydrazine (MMH) and nitrogen dioxide (NO2) and its application to modeling hypergolic ignition of MMH/NO2 were investigated in this work. Potential energy surfaces (PESs) for the key reactions were obtained by employing the CCSD(T)/CBS//M06-2X/6-311++G(d,p) single-reference method and the MRCI(7e,6o)/CBS//M06-2X/6-311++G(d,p) multi-reference method. The RRKM/Master Equation approach was used to calculate the temperature- and pressure-dependent rate constants. For the second-H-abstraction reactions, the trans-CH3NNH and HNO2/HONO are the major products. For the third-H-abstraction reactions, the bimolecular reaction of cis-CH3NNH+NO2→CH3NN+HNO2 is more favorable. The calculated rate constants and thermodynamics data were fitted and incorporated into two existing mechanisms to investigate their influence on modeling MMH/NO2 hypergolic ignition. The modeling results show that the system reactivity of MMH/NO2 is promoted by the second- and third-H-abstraction reactions, as the ignition delay times decrease by a factor of two at 300–800 K. The production rate and sensitivity analyses further validate the significance of the second-H-abstraction reactions at low temperatures. The sensitivity analyses at 1000 K also indicate the necessity of further investigations on CH2O, N2H2/NO2, and CH3NH/NO2 sub-mechanisms for modeling the MMH/NO2 combustion at high temperatures. This work provides not only new kinetic and thermochemical data but also a better understanding of the hypergolic ignition of MMH/NO2.

Recovery of hydrogen plasma at the sub-nanosecond timescale in a plasma-wakefield accelerator

Plasma wakefield acceleration revolutionized the field of particle accelerators by generating gigavolt-per-centimeter fields. To compete with conventional radio-frequency (RF) accelerators, plasma technology must demonstrate operation at high repetition rates, with a recent research showing feasibility at megahertz levels using an Argon source that recovered after about 60 ns. Here we report about a proof-of-principle experiment that demonstrates the recovery of a Hydrogen plasma at the sub-nanosecond timescale. The result is obtained with a pump-and-probe setup and has been characterized for a wide range of plasma densities. We observed that large plasma densities reestablish their initial state soon after the injection of the pump beam ( < 0.7 ns). Conversely, at lower densities we observe the formation of a local dense plasma channel affecting the probe beam dynamics even at long delay times ( > 13 ns). The results are supported with numerical simulations and represent a step forward for the next-generation of compact high-repetition rate accelerators.

Optimization of Memristor Crossbar’s Mapping Using Lagrange Multiplier Method and Genetic Algorithm for Reducing Crossbar’s Area and Delay Time

Memristor crossbars offer promising low-power and parallel processing capabilities, making them efficient for implementing convolutional neural networks (CNNs) in terms of delay time, area, etc. However, mapping large CNN models like ResNet-18, ResNet-34, VGG-Net, etc., onto memristor crossbars is challenging due to the line resistance problem limiting crossbar size. This necessitates partitioning full-image convolution into sub-image convolution. To do so, an optimized mapping of memristor crossbars should be considered to divide full-image convolution into multiple crossbars. With limited crossbar resources, especially in edge devices, it is crucial to optimize the crossbar allocation per layer to minimize the hardware resource in term of crossbar area, delay time, and area–delay product. This paper explores three optimization scenarios: (1) optimizing total delay time under a crossbar’s area constraint, (2) optimizing total crossbar area with a crossbar’s delay time constraint, and (3) optimizing a crossbar’s area–delay-time product without constraints. The Lagrange multiplier method is employed for the constrained cases 1 and 2. For the unconstrained case 3, a genetic algorithm (GA) is used to optimize the area–delay-time product. Simulation results demonstrate that the optimization can have significant improvements over the unoptimized results. When VGG-Net is simulated, the optimization can show about 20% reduction in delay time for case 1 and 22% area reduction for case 2. Case 3 highlights the benefits of optimizing the crossbar utilization ratio for minimizing the area–delay-time product. The proposed optimization strategies can substantially enhance the neural network’s performance of memristor crossbar-based processing-in-memory architectures, especially for resource-constrained edge computing platforms.

Robust sampled-data synchronization of chaotic fractional variable order neural networks with time delays

Robust sampled-data synchronization of chaotic fractional variable order neural networks with time delays

Dosimetric consequences of flap dose due to rapid beam off control for a high intensity carbon ion radiation therapy synchrotron.

In carbon ion radiation therapy (CIRT) the predominant method of irradiation is raster scanning, called dose driven continuous scanning (DDCS) by Hitachi, allowing for continuous synchrotron extraction. The reduction in irradiation time is highly beneficial in minimizing the impact of patient and target movement on dose distribution. The RF knock out (RFKO) slow-extraction method is commonly used for beam on/off control. When the Hitachi synchrotron receives a beam off signal the control system stops the RFKO and after some delay time (t-delay) during which the beam intensity declines, a high-speed steering magnet (HSST) is used to sweep the remaining beam from isocenter to a beam dump for safety reasons. Mayo Clinic Florida (MCF) will use a very short delay of the HSST operation from the RFKO beam OFF signal to minimize the delay time and delayed dose. MCF clinical beam intensity, a tenfold increase over HIMAK, is still less than 100 mMU/ms (approximately 4.9×109 pps for 430 MeV/u). The rapid beam off control (RBOC) proposed for MCF is associated with the occurrence of flap dose (FD), which refers to the asymmetric shoulder of the spot dose profile formed from the beam bent by HSST deviating from its planned spot position on the isocenter plane. In this study, we quantitatively assessed FD, proposed a treatment planning system (TPS) implementation using a flap spot (FS) and evaluated its impact on dose distribution. The experiments were conducted at the Osaka Heavy Ion Therapy Center (HIMAK) varying the t-delay from 0.01 to 1ms in a research environment to simulate the MCF RBOC. We studied the dependence of FD position on beam transport and its dependence on energy and beam intensity. FD was generated by delivering 10000 continuous spots on the central axis that are occasionally triggered by an external 10Hz gate signal. Measurements were conducted using an oscilloscope, and the nozzle's spot position monitor (SPM) and dose monitor (DM). All spot profile data were corrected for the gain of the SPM's beam intensity dependence. FD was determined by fitting the (SPM) Profile data to a double Gaussian. The position of the FS was found to be transport path dependent, with FS occurring on the opposite sides of the scanning x-direction for vertical and horizontal ports, respectively, as predicted by transport calculations. It was observed that the FD increases with beam intensity and did not exhibit a significant dependence on energy. The effect of FD on treatment planning is shown to have no significant dose impact on the organs at risk (OARs) near the target for clinical beam intensities and a modest increase for very high intensities. Using HIMAK in research mode the implications are that the FD has no clinical impact on the clinical CIRT beam intensities for MCF and maybe planned for higher intensities by incorporating FS into the TPS to predict the modest increased dose to OARs. A method for commissioning and quality assurance of FD has been proposed.

Root causes of first-case start time delays for elective surgical procedures: a prospective multicenter observational cohort study in Ethiopia

BackgroundDelays in surgery start times can lead to poor patient outcomes and considerable increases in healthcare expenditures. This is especially true in developing countries that often face systemic inefficiencies, such as a shortage of operating rooms and trained surgical personnel. With substantial effects on patient outcomes, healthcare efficiency, and resource allocation, identifying delays in first-case elective surgery is a crucial area of research.MethodsA multicenter observational study was conducted at three comprehensive and specialized hospitals in the Amhara region of Ethiopia from May 1 to October 30, 2023. The primary aim of the study was to determine the occurrence of late first-case start times, defined as a patient being in the operating room at or after the hospital’s incision time of 2:30 a.m. The secondary aim was to discover potential root causes of delayed first-case start times. All patients scheduled for elective surgery as the first case on the operating list throughout the study period were included in the study. Every emergency, day case, after-hours case, and canceled case was excluded.ResultsA total of 530 surgical patients were included during the study window from May 1 to October 1, 2023. Of these, 41.5% were general surgeries, 20.4% were gynecology and obstetrics surgeries, and 13.2% were orthopedic surgery procedures. Before the procedure started, nine (1.7%) of the participants had prolonged discussion with a member of the surgical team. Patients who arrived in the operating room waiting area at or after 2:30 a.m. were 2.5 times more likely to experience a first-case start time delay than those who arrived before or at 2:00 a.m. (AOR = 2.50; 95% CI: 1.13–5.14). Furthermore, participants with abnormal investigation results were 2.4 times more likely to have a late first-case start time (AOR = 2.41; 95% CI: 1.06, 5.50). Moreover, the odds of a late first-case start time were increased by 10.53 times with the surgeon being in the operating room at or after 2:30 a.m. (AOR = 10.53; 95% CI: 5.51, 20.11).ConclusionThe research highlights a significant occurrence of delayed start times for the first elective surgical procedures. Therefore, directing attention to aspects such as ensuring patients and surgical teams arrive promptly (by or before 2:00 a.m.) and timely evaluation and communication of investigative findings before the scheduled surgery day could facilitate efforts to maximize operating room efficiency and enhance patient health outcomes.

Numerical integration method for two-parameter singularly perturbed time delay parabolic problem

This study presents an (ε, μ)−uniform numerical method for a two-parameter singularly perturbed time-delayed parabolic problems. The proposed approach is based on a fitted operator finite difference method. The Crank–Nicolson method is used on a uniform mesh to discretize the time variables initially. Subsequently, the resulting semi-discrete scheme is further discretized in space using Simpson's 1/3rd rule. Finally, the finite difference approximation of the first derivatives is applied. The method is unique in that it is not dependent on delay terms, asymptotic expansions, or fitted meshes. The fitting factor's value, which is used to account for abrupt changes in the solution, is calculated using the theory of singular perturbations. The developed scheme is demonstrated to be second-order accurate and uniformly convergent. The proposed method's applicability is validated by three model examples, which yielded more accurate results than some other methods found in the literature.

Full-Dimensional Proportional-Derivative Control Technique for Turing Pattern and Bifurcation of Delayed Reaction-Diffusion Bidirectional Ring Neural Networks

Abstract In neural networks, the states of neural networks often exhibit significant spatio-temporal heterogeneity due to the diffusion effect of electrons and differences in the concentration of neurotransmitters. One of the macroscopic reflections of this time-spatial inhomogeneity is Turing pattern. However, most current research in reaction-diffusion neural networks has focused only on one-dimensional location information, and the remaining results considering two-dimensional location information are still limited to the case of two neurons. In this paper, we conduct the dynamic analysis and optimal control of a delayed reaction-diffusion neural network model with bidirectional loop structure. First, several mathematical descriptions are given for the proposed neural network model and the full-dimensional partial differential proportional-derivative (PD) controller is introduced. Second, by analyzing the characteristic equation, the conditions for Hopf bifurcation and Turing instability of the controlled network model are obtained. Furthermore, the amplitude equation of the controlled neural network is obtained based on the multiscale analysis method. Subsequently, we determine the key parameters affecting the formation of Turing pattern depending on the amplitude equation. Finally, multiple sets of computer simulations are carried out to support our theoretical results. It is found that the diffusion coefficients and time delays have significant effects on spatio-temporal dynamics of neural networks. Moreover, after reasonable parameter proportioning, the full-dimensional PD control method can alleviate the spatial heterogeneity caused by diffusion projects and time delays.

Hybrid Quantum-Dot Cellular Automata Nanocomputing Circuits

Quantum-dot cellular automata (QCA) is an emerging transistor-less field-coupled nanocomputing (FCN) approach to ultra-scale ‘nanochip’ integration. In QCA, to represent digital circuitry, electrostatic repulsion between electrons and the mechanism of electron tunnelling in quantum dots are used. QCA technology can surpass conventional complementary metal oxide semiconductor (CMOS) technology in terms of clock speed, reduced occupied chip area, and energy efficiency. To develop QCA circuits, irreversible majority gates are typically used as the primary components. Recently, some studies have introduced reversible design techniques, using reversible majority gates as the main building block, to develop ultra-energy-efficient QCA circuits. However, this approach resulted in time delays, an increase in the number of QCA cells used, and an increase in the chip area occupied. This work introduces a novel hybrid design strategy employing irreversible, reversible, and partially reversible QCA gates to establish an optimal balance between power consumption, delay time, and occupied area. This hybrid technique allows the designer to have more control over the circuit characteristics to meet different system needs. A combination of reversible, irreversible, and innovative partially reversible majority gates is used in the proposed hybrid design method. We evaluated the hybrid design method by examining the half-adder circuit as a case study. We developed four hybrid QCA half-adder circuits, each of which simultaneously incorporates various types of majority gates. The QCADesigner-E 2.2 simulation tool was used to simulate the performance and energy efficiency of the half-adders. This tool provides numerical results for the circuit input/output response and heat dissipation at the physical level within a microscopic quantum mechanical model.

Dynamic analysis of a delayed pest-natural enemy model: Triple effects of non-monotonic functional response, additional food supply and habitat complexity

Considering the food diversity of natural enemy species and the habitat complexity of prey populations, a pest-natural enemy model with non-monotonic functional response is proposed for biological management of Bemisia tabaci. The dynamic characteristics of the proposed model are analyzed. In addition, considering that the conversion from prey to predator has a certain time lag rather than instantaneous, a time delay is introduced into this model, and it is shown that the Hopf bifurcation occurs at the interior equilibrium when the time delay is used as the bifurcation parameter. Furthermore, the values of the parameters that determine the direction of the Hopf bifurcation as well as the stability of the periodic solution are calculated. In order to illustrate the theoretical analysis results, numerical simulations and validation are carried out to demonstrate the effects of non-monotonic functional response, additional food supply and habitat complexity.

Combustion instability characteristics via fuel nozzle modification in a hydrogen and natural gas Co-firing gas turbine combustor

In this study, three premixed swirl gas turbine nozzles with different fuel injection hole sizes were designed to optimize combustion characteristics influenced by changes in the hydrogen mixing ratio. Experiments involved increasing the hydrogen volume fraction of the fuel from 0 to 60%. The amount of fuel supplied through the pilot flow was increased to suppress combustion instability. The OH* chemiluminescence technique was introduced to analyze flame structure. To understand combustion instability, time delay and time-delay distribution were derived from flame structure analysis and applied to the 1D thermoacoustic model. The results indicated that the amount of fuel required for pilot injection with increasing hydrogen ratio varied with fuel hole size. It was also observed that changes in fuel hole size significantly affected flame characteristic length. Findings from the 1D thermoacoustic analysis confirmed that fuel hole size variation altered combustion instability characteristics by influencing time delay and time-delay distribution variation.

Effects of Fractional Time Delay as a Low-Power True Time Delay Digital Beamforming Architecture

Effects of Fractional Time Delay as a Low-Power True Time Delay Digital Beamforming Architecture

Ultra-sensitive, graphene metasurface sensor integrated with the nonradiative anapole mode for detecting and differentiating two preservatives

Abstract Graphene-based metamaterial sensors are of significant research value for detecting food preservatives at low concentrations due to their extremely high sensitivity levels. In this work, we proposed and experimentally demonstrated an anapole resonance-based graphene metasurface (An-graphene-Ms) sensor with its conductivity altered by electrostatic doping effects for detecting and differentiating between two preservatives, sodium benzoate and potassium sorbate, in the terahertz region. Sodium benzoate, owing to its benzene ring structure, established π–π stacking interactions between the π-electrons in the benzene ring and those in graphene, amplifying the sensing effect. The amplitude changes and phase differences of the An-graphene-Ms sensor for the sodium benzoate detection were greater than those for potassium sorbate at the same concentration. Additionally, to reveal the dependence of the resonance frequency on the time delay, the measured signals were investigated using the continuous wavelet transform (CWT), and the time-frequency combination of the metasurface sensor was performed. The 2D wavelet coefficient intensity cards are effectively constructed through CWT, which also presents a more accurate approach for distinguishing and determining the concentrations of the two preservatives.

Finite-Time Stabilization of Inertial Memristive Neural Networks via Nonreduced Order Method.

This article investigates the finite-time stabilization problem of inertial memristive neural networks (IMNNs) with bounded and unbounded time-varying delays, respectively. To simplify the theoretical derivation, the nonreduced order method is utilized for constructing appropriate comparison functions and designing a discontinuous state feedback controller. Then, based on the controller, the state of IMNNs can directly converge to 0 in finite time. Several criteria for finite-time stabilization of IMNNs are obtained and the setting time is estimated. Compared with previous studies, the requirement of differentiability of time delay is eliminated. Finally, numerical examples illustrate the usefulness of the analysis results in this article.

Effect of Changing the Time Delay on Absorption Coefficient of (rhodamine 6G) Dye Utilizing Laser Probe Technique

Effect of Changing the Time Delay on Absorption Coefficient of (rhodamine 6G) Dye Utilizing Laser Probe Technique

Bioinspired molecular communications system for targeted drug delivery with IoBNT-based sustainable biocyber interface

This paper presents a sustainable biocyber interface approach for an intelligent targeted drug delivery system (TDDS). The proposed approach employs a bioinspired molecular communications (MC) system in which molecules are used as information carriers and a multi-input multi-output (MIMO) Forster resonance energy transfer (FRET) nanorelay to efficiently transfer therapeutic drugs from extravascular (outside blood vessels) to intravascular (within blood vessels) sites that are targeting diseased tissue. The proposed approach consists of a number of bio-nano things (BNTs) implanted inside the human intra-body nanonetwork near the diseased site. The communication among BNTs is accomplished by a sequential multistep FRET, and the nanonetwork is controlled by the Internet of Bio-Nano Thing (IoBNT) paradigm sustained by an uplink/downlink biocyber interface. The bit error rate (BER) and molecular channel capacity are utilized to evaluate the performance of the proposed approach. In addition, a Markov model decision in terms of the number of nanomachines is presented to calculate the successful probability of drug delivery and the average delay time. The numerical results show how effective the suggested method is at transmitting therapeutic medication information with an attainable bit-rate error.

Jet ignition characteristics of ammonia-hydrogen passive pre-chamber: Emphasis on equivalence ratio and hydrogen/ammonia ratio

Ammonia-hydrogen blend fuels offer the potential for zero-carbon emissions in internal combustion (IC) engines. To improve combustion performance, considerable attention has been focused on pre-chamber jet ignition technologies. Passive pre-chamber featuring a simple structure can be installed in the spark plug hole without modifying the cylinder head. However, the jet ignition characteristics of ammonia-hydrogen passive pre-chambers are not fully understood, and there is a lack of visualized evidence on how critical parameters (e.g., equivalence ratio and hydrogen/ammonia ratio) impact ignition processes. This work investigated the effects of equivalence ratio and hydrogen/ammonia ratio on ammonia-hydrogen jet ignition characteristics in a rapid compression machine with passive pre-chamber. High-speed photography and instantaneous pressure acquisition were employed to capture detailed ignition and combustion evolutions. Results show that under low hydrogen/ammonia ratio conditions, there exists a combustion regime with noticeable fluctuations in jet penetration, indicating degenerate ignition performance. As the hydrogen/ammonia ratio increases from 0 % to 20 %, the ignition delay time of mixtures in the main chamber is reduced by 70 %, suggesting an improved overall ignition performance. Regarding the equivalence ratio, more pronounced effects on jet ignition and flame propagation are identified under lean-burning conditions. For mixtures at the hydrogen/ammonia ratio of 20 %, as the equivalence ratio increases from 0.6 to 0.8 and from 0.8 to 1.0, the decay rates for 10 %–90 % combustion duration are 82.5 % and 20.6 %, respectively. Besides, with the increase of equivalence ratio, flame initiation is shifted from the jet head to the side surface. The role of hydrogen/ammonia ratio and equivalence ratio is different, with the former modifying mixture reactivity while the latter affecting ignition energy.

Permutation conditional mutual information to quantify TMS-evoked cortical connectivity in disorders of consciousness.

To improve the understanding and diagnostic accuracy of disorders of consciousness (DOC) by quantifying transcranial magnetic stimulation evoked electroencephalography (TMS-EEG) connectivity using Permutation Conditional Mutual Information (PCMI).&#xD;Approach: PCMI can characterize the functional connectivity between different brain regions. This study employed PCMI to analyze TMS-evoked cortical connectivity (TEC) in 154 DOC patients and 16 normal controls, focusing on optimizing parameter selection for PCMI (Data length, Order length, Time delay). We compared short-range and long-range PCMI values across different consciousness states-unresponsive wakefulness syndrome (UWS), minimally conscious state (MCS), and normal (NOR)-and assessed various feature selection and classification techniques to distinguish these states. &#xD;Main Results: 1) PCMI can quantify TEC. We found optimal parameters to be Data length: 500ms; Order: 3; Time delay: 6ms. 2) TMS evoked potentials (TEP) for NOR showed a rich response, while MCS patients showed only a few components, and UWS patients had almost no significant components. The values of PCMI connectivity metrics demonstrated its usefulness for measuring cortical connectivity evoked by TMS. From NOR to MCS to UWS, the number and strength of TEC decreased. Quantitative analysis revealed significant differences in the strength and number of TEC in the entire brain, local regions and inter-regions among different consciousness states. 3) A decision tree with feature selection by mutual information performed the best (balanced accuracy: 87.0% and accuracy: 83.5%). This model could accurately identify NOR (100.0%), but had lower identification accuracy for UWS (86.5%) and MCS (74.1%). &#xD;Significance: The application of PCMI in measuring TMS-evoked connectivity provides a robust metric that enhances our ability to differentiate between various states of consciousness in DOC patients. This approach not only aids in clinical diagnosis but also contributes to the broader understanding of cortical connectivity and consciousness.&#xD.

Gaussian and Lévy noises excited delayed tumor growth model: first-passage behavior and stochastic resonance

In this paper, we analyze the dynamical behavior of a delayed tumor growth model under the joint effect of Gaussian white noise and Lévy noise by studying the mean first passage time (MFPT) and stochastic resonance (SR). Firstly, the tumor growth model under the joint effect of Gaussian white noise, Lévy noise and time delay is introduced. Then, the Lévy noise sequence is simulated by Janicki-Weron algorithm, and the MFPT and signal-to-noise ratio(SNR) of the system are simulated by using fourth-order stochastic Runge–Kutta algorithm. The effects of noise parameters, time delay and periodic signal parameters on MFPT, SR are discussed in detail, respectively. In addition, we find the phenomenon of noise enhanced stability. The results of the study can help to select the optimal regulatory parameters in the tumor growth model and promote the treatment of tumors.

Admissible and dissipative synchronisation of fractional order singular systems with time delay using event-triggered feedback control

The purpose of this work is to study the admissible and dissipative synchronisation of fractional order singular systems with time delay. The key goal is to use as few network resources as possible while retaining the desired closed-loop performance. An event-triggered control method is used to accomplish this. The Lyapunov function method, linear matrix inequality approach, and mathematical techniques are used to develop new synchronisation criteria that assure the synchronisation error system is Mittag–Leffler stable. Because fractional order differential equations have memory characteristics, which are very different from ordinary differential equations, leading to difficulties in preventing Zeno behaviour related to the event-triggered mechanism of fractional order systems, especially of delayed fractional order singular systems. To solve this issue, we propose a new theoretical framework and a new condition to preclude Zeno behaviours. This derived conditions use inequality techniques and take advantage of a number of fundamental aspects of fractional order calculus. Furthermore, the dissipative synchronous problem of delayed fractional order singular systems is also solved for the first time using the suggested stable criterion in conjunction with some auxiliary characteristics of fractional calculus. Two numerical examples are provided to demonstrate the usefulness of the proposed strategy.