Changes to DA-CPR instructions: can we reduce time to first compression and improve quality of bystander CPR?

INTRODUCTION

Dispatcher-assisted CPR (DA-CPR) can increase rates of bystander CPR, survival, and quality of life following cardiac arrest. Dispatcher protocols designed to improve rapid recognition of arrest and coach CPR may increase survival by (1) reducing preventable time delays to start of chest compressions and (2) improving the quality of bystander CPR.

METHODS

We conducted a randomized controlled trial comparing a simplified DA CPR script to a conventional DA CPR script in a manikin cardiac arrest simulation with lay participants. The primary outcomes measured were the time interval from call receipt to the first chest compression and the core metrics of chest compression (depth, rate, release, and compression fraction). CPR was measured using a recording manikin for the first 3 min of participant CPR.

RESULTS

Of the 75 participants, 39 were randomized to the simplified instructions and 36 were randomized to the conventional instructions. The interval from call receipt to first compression was 99 s using the simplified script and 124 s using the conventional script for a difference of 24s (p<0.01). Although hand position was judged to be correct more often in the conventional instruction group (88% versus 63%, p<0.01), compression depth was an average 7 mm deeper among those receiving the simplified CPR script (32 mm versus 25 mm, p<0.05). No statistically significant differences were detected between the two instruction groups for compression rate, complete release, number of hands-off periods, or compression fraction.

DISCUSSION

Simplified DA-CPR instructions to lay callers in simulated cardiac arrest settings resulted in significant reductions in time to first compression and improvements in compression depth. These results suggest an important opportunity to improve DA CPR instructions to reduce delays and improve CPR quality.

Electric activities of time-delay memristive neuron disturbed by Gaussian white noise

To study the effect of electromagnetic induction on the electric activities of neuron, memristive neuron models have been proposed by coupling membrane potential with magnetic flux. In this paper, on the basis of memristive Hindmarsh-Rose neuron model, time-delay memristive Hindmarsh-Rose neuron model is described and the responses of neuron in electrical activities are detected. The effect of time-delay on the dynamical behaviors of the neuron is discussed and the transition of electrical activities of the neuron is investigated with the change of noise intensity. It is found that, both the time-delay and the noise have effect on the electrical activities of the neuron. Especially, by selecting appropriate parameters, the noise not only can excite neuron from quiescent state to bursting state, but also can suppress the electrical activities in neuron during certain discharge period. Results mean that multiple modes and coherence resonance can be observed by changing the size of time-delay or the noise intensity, which could be associated with memory effect and self-adaption in neurons.

Performance boost of time-delay reservoir computing by non-resonant clock cycle

The time-delay-based reservoir computing setup has seen tremendous success in both experiment and simulation. It allows for the construction of large neuromorphic computing systems with only few components. However, until now the interplay of the different timescales has not been investigated thoroughly. In this manuscript, we investigate the effects of a mismatch between the time-delay and the clock cycle for a general model. Typically, these two time scales are considered to be equal. Here we show that the case of equal or resonant time-delay and clock cycle could be actively detrimental and leads to an increase of the approximation error of the reservoir. In particular, we can show that non-resonant ratios of these time scales have maximal memory capacities. We achieve this by translating the periodically driven delay-dynamical system into an equivalent network. Networks that originate from a system with resonant delay-times and clock cycles fail to utilize all of their degrees of freedom, which causes the degradation of their performance.

Mathematical model of TGF-βsignalling: feedback coupling is consistent with signal switching

Background

Transforming growth factor β (TGF-β) signalling regulates the development of embryos and tissue homeostasis in adults. In conjunction with other oncogenic changes, long-term perturbation of TGF-β signalling is associated with cancer metastasis. Although TGF-β signalling can be complex, many of the signalling components are well defined, so it is possible to develop mathematical models of TGF-β signalling using reduction and scaling methods. The parameterization of our TGF-β signalling model is consistent with experimental data.

Results

We developed our mathematical model for the TGF-β signalling pathway, i.e. the RF- model of TGF-β signalling, using the “rapid equilibrium assumption” to reduce the network of TGF-β signalling reactions based on the time scales of the individual reactions. By adding time-delayed positive feedback to the inherent time-delayed negative feedback for TGF-β signalling. We were able to simulate the sigmoidal, switch-like behaviour observed for the concentration dependence of long-term (> 3 hours) TGF-β stimulation. Computer simulations revealed the vital role of the coupling of the positive and negative feedback loops on the regulation of the TGF-β signalling system. The incorporation of time-delays for the negative feedback loop improved the accuracy, stability and robustness of the model. This model reproduces both the short-term and long-term switching responses for the intracellular signalling pathways at different TGF-β concentrations. We have tested the model against experimental data from MEF (mouse embryonic fibroblasts) WT, SV40-immortalized MEFs and Gp130 ^F/F MEFs. The predictions from the RF- model are consistent with the experimental data.

Conclusions

Signalling feedback loops are required to model TGF-β signal transduction and its effects on normal and cancer cells. We focus on the effects of time-delayed feedback loops and their coupling to ligand stimulation in this system. The model was simplified and reduced to its key components using standard methods and the rapid equilibrium assumption. We detected differences in short-term and long-term signal switching. The results from the RF- model compare well with experimental data and predict the dynamics of TGF-β signalling in cancer cells with different mutations.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-017-0421-5) contains supplementary material, which is available to authorized users.

An active balance board system with real-time control of stiffness and time-delay to assess mechanisms of postural stability

Increased time-delay in the neuromuscular system caused by neurological disorders, concussions, or advancing age is an important factor contributing to balance loss (Chagdes et al., 2013, 2016a,b). We present the design and fabrication of an active balance board system that allows for a systematic study of stiffness and time-delay induced instabilities in standing posture. Although current commercial balance boards allow for variable stiffness, they do not allow for manipulation of time-delay. Having two controllable parameters can more accurately determine the cause of balance deficiencies, and allows us to induce instabilities even in healthy populations. An inverted pendulum model of human posture on such an active balance board predicts that reduced board rotational stiffness destabilizes upright posture through board tipping, and limit cycle oscillations about the upright position emerge as feedback time-delay is increased. We validate these two mechanisms of instability on the designed balance board, showing that rotational stiffness and board time-delay induced the predicted postural instabilities in healthy, young adults. Although current commercial balance boards utilize control of rotational stiffness, real-time control of both stiffness and time-delay on an active balance board is a novel and innovative manipulation to reveal balance deficiencies and potentially improve individualized balance training by targeting multiple dimensions contributing to standing balance.

All-PD control of pure Integrating Plus Time-Delay processes with gain and phase-margin specifications

It is well known that PD controller, though yields good servo response, fails to provide satisfactory regulatory response for Integrating Plus Time-Delay (IPTD) processes. On the other hand, using an integral control action generally leads to large overshoot or settling time. To achieve good servo as well as regulatory response, a new all-PD control structure is proposed for IPTD processes in this paper. Design formulas are derived in terms of gain-margin and phase-margin specifications. Numerical examples on the design methodology are presented and experimentally validated on a temperature control process.

Multiscale modeling of tumor growth induced by circadian rhythm disruption in epithelial tissue

We propose a multiscale chemo-mechanical model of cancer tumor development in epithelial tissue. The model is based on the transformation of normal cells into a cancerous state triggered by a local failure of spatial synchronization of the circadian rhythm. The model includes mechanical interactions and a chemical signal exchange between neighboring cells, as well as a division of cells and intercalation that allows for modification of the respective parameters following transformation into the cancerous state. The numerical simulations reproduce different dephasing patterns--spiral waves and quasistationary clustering, with the latter being conducive to cancer formation. Modification of mechanical properties reproduces a distinct behavior of invasive and localized carcinoma.

Chaos synchronization of uncertain chaotic systems using composite nonlinear feedback based integral sliding mode control

This paper proposes a combination of composite nonlinear feedback and integral sliding mode techniques for fast and accurate chaos synchronization of uncertain chaotic systems with Lipschitz nonlinear functions, time-varying delays and disturbances. The composite nonlinear feedback method allows accurate following of the master chaotic system and the integral sliding mode control provides invariance property which rejects the perturbations and preserves the stability of the closed-loop system. Based on the Lyapunov- Krasovskii stability theory and linear matrix inequalities, a novel sufficient condition is offered for the chaos synchronization of uncertain chaotic systems. This method not only guarantees the robustness against perturbations and time-delays, but also eliminates reaching phase and avoids chattering problem. Simulation results demonstrate that the suggested procedure leads to a great control performance.

Asymptotic tracking control for time-delay nonlinear systems with parametric uncertainties and full state constraints

This article concentrates on an adaptive backstepping control design of time-delay strict-feedback uncertain nonlinear systems subject to full state constraints. The tan-type barrier Lyapunov functions (tBLFs) and Lyapunov-Krasovskii function are united together, which successfully get over the difficulties of system design in which the first function is involved to ensure full state constraints satisfaction and the second is established to eliminate the effect of delayed states. By employing a new control scheme, asymptotic tracking performance is arrived, and all the states remain in the desirable regions for all the system running time. Meanwhile, the boundedness of all signals of the closed-loop system is guaranteed. The performance of the control scheme is illustrated through a class of single degree of freedom (1-DOF) time-delay electrostatic microactuator systems.

Complexity analysis of cold chain transportation in a vaccine supply chain considering activity inspection and time-delay

The development of COVID-19 vaccine is highly concerned by all countries in the world. So far, many kinds of COVID-19 vaccines have entered phase III clinical trial. However, it is difficult to deliver COVID-19 vaccines efficiently and safely to the areas affected by the epidemic. This paper focuses on vaccine transportation in a supply chain model composed of one distributor and one retailer (clinic or hospital), in which the distributor procures COVID-19 vaccines from the manufacturer and then resells them to the retailer. Distributor detects the activity level of the vaccines, and retailer is responsible for transportation of the vaccines. Firstly, we establish a difference equations model with time-delay. Secondly, we investigate the impact of time-delay on the stability of vaccine supply chain. In addition, we explore the influence of decision adjustment speed of the distributor (or retailer) on the stability of vaccine supply chain. Finally, we verify the theoretical results by a two-dimensional bifurcation diagram, the largest Lyapunov exponent, entropy, and domain of attraction. The results show that when the decision delay-time or the adjustment speed of decision variables exceeds a certain threshold, it brings a negative impact on the stability of vaccine supply chain system. The stability domain of the system shrinks as customers' sensitivity to cold chain transportation decreases and by contrast expends as customers' sensitivity to vaccine prices decreases. When the vaccine supply chain is in a state of chaos, the effect of external control over the system is superior to that of internal control over the system.

Stabilization and PID tuning algorithms for second-order unstable processes with time-delays

Open-loop unstable systems with time-delays are often encountered in process industry, which are often more difficult to control than stable processes. In this paper, the stabilization by PID controller of second-order unstable processes, which can be represented as second-order deadtime with an unstable pole (SODUP) and second-order deadtime with two unstable poles (SODTUP), is performed via the necessary and sufficient criteria of Routh-Hurwitz stability analysis. The stability analysis provides improved understanding on the existence of a stabilizing range of each PID parameter. Three simple PID tuning algorithms are proposed to provide desired closed-loop performance-robustness within the stable regions of controller parameters obtained via the stability analysis. The proposed PID controllers show improved performance over those derived via some existing methods.

A delayed plant disease model with Caputo fractional derivatives

We analyze a time-delay Caputo-type fractional mathematical model containing the infection rate of Beddington-DeAngelis functional response to study the structure of a vector-borne plant epidemic. We prove the unique global solution existence for the given delay mathematical model by using fixed point results. We use the Adams-Bashforth-Moulton P-C algorithm for solving the given dynamical model. We give a number of graphical interpretations of the proposed solution. A number of novel results are demonstrated from the given practical and theoretical observations. By using 3-D plots we observe the variations in the flatness of our plots when the fractional order varies. The role of time delay on the proposed plant disease dynamics and the effects of infection rate in the population of susceptible and infectious classes are investigated. The main motivation of this research study is examining the dynamics of the vector-borne epidemic in the sense of fractional derivatives under memory effects. This study is an example of how the fractional derivatives are useful in plant epidemiology. The application of Caputo derivative with equal dimensionality includes the memory in the model, which is the main novelty of this study.

Tuning of Smith predictor based generalized ADRC for time-delayed processes via IMC

A control strategy combining generalized active disturbance rejection control (GADRC) with Smith predictor (SP) is investigated for time-delayed systems. It takes all available model information into consideration, including the plant dynamic and the time delay, thus inherits the advantages of both SP-ADRC and GADRC. Since SP-GADRC can be transformed into a two-degree-of-freedom (TDF) feedback control structure, it is simply interpreted and tuned through the equivalent TDF internal model control (TDF-IMC) by using the delay-free part of the system as the nominal model for the IMC design and selecting the bandwidths of controller and extended state observer (ESO) for SP-GADRC as the inverse of the time constants of the setpoint filter and the disturbance-rejection filter in IMC, respectively. The analysis and tuning is of tutorial value for practitioners and engineers, and the effectiveness is validated by a few comparative simulations.

Robust stability criterion for fractional-order systems with interval uncertain coefficients and a time-delay

This study investigates the robust stability of fractional-order systems with interval coefficients and a time-delay. By the Minkowski Sum, the vertices of value set with respect to the characteristic function of the investigated fractional-order system are offered, avoiding the calculations of the redundant vertices. Meanwhile, a function depending on the obtained vertices is defined to represent the position relationship between the origin and the value set. Based on the zero exclusion principle, we propose sufficient and necessary conditions to determine the robust stability of fractional-order systems with interval uncertain coefficients and a time-delay. Finally, illustrative examples are offered to verify the effectiveness of the proposed robust stability criterion.

Multisine frequency modulation of intra-epidermal electric pulse sequences: A novel tool to study nociceptive processing

A sustained sensory stimulus with a periodic variation of intensity creates an electrophysiological brain response at associated frequencies, referred to as the steady-state evoked potential (SSEP). The SSEPs elicited by the periodic stimulation of nociceptors in the skin may represent activity of a brain network that is primarily involved in nociceptive processing. Exploring the behavior of this network could lead to valuable insights regarding the pathway from nociceptive stimulus to pain perception. We present a method to directly modulate the pulse rate of nociceptive afferents in the skin with a multisine waveform through intra-epidermal electric stimulation. The technique was demonstrated in healthy volunteers. Each subject was stimulated using a pulse sequence modulated by a multisine waveform of 3, 7 and 13 Hz. The EEG was analyzed for the presence of the base frequencies and associated (sub)harmonics. Topographies showed significant central and contralateral SSEP responses at 3, 7 and 13 Hz in respectively 7, 4 and 3 out of the 9 participants included for analysis. As such, we found that intra-epidermal stimulation with a multisine frequency modulated pulse sequence can generate nociceptive SSEPs. The possibility to stimulate the nociceptive system using multisine frequency modulated pulses offers novel opportunities to study the temporal dynamics of nociceptive processing.

Robust adaptive identification for sandwich systems with unknown time-delay

A discrete time, robust adaptive estimator is developed to identify the time-delay and sandwich systems parameters. To obtain explicitly the expression of delay parameter, the observation and augmented data are reconstructed. By using the filter operator and some auxiliary vectors, the parameter identification error vector is derived. Based on the parameter identification error term and initial estimation error term, a novel criterion function is invented. In comparison to the common criterion function, a classy estimation property is provided based on the criterion function in that paper because the identification error term can lift estimation accuracy, and the initial estimation error term speeds up the convergence. Under the persistent excitation condition, convergence of the developed estimator is analyzed. The availability and superiority of proposed identification scheme are verified by both numerical simulation and a turntable servo system.

Finite-time stability and stabilization for stochastic markov jump systems with mode-dependent time delays

This paper is concerned with the problems of finite-time stability and stabilization for stochastic Markov systems with mode-dependent time-delays. In order to reduce conservatism, a mode-dependent approach is utilized. Based on the derived stability conditions, state-feedback controller and observer-based controller are designed, respectively. A new N-mode algorithm is given to obtain the maximum value of time-delay. Finally, an example is used to show the merit of the proposed results.

A generalized predictive control for remote cardiovascular surgical systems

Robot-assisted cardiovascular surgery is used to avoid surgeon suffering from X-ray radiation and relieve fatigue caused by long-time standing wearing protective clothing. Its remote surgery can alleviate the lack of experienced doctors in remote areas. Due to the existence of time-delay phenomena, flexible deformation and nonlinearity of interventional instruments, it is difficult to ensure system transparency. This paper analyzes the evaluation index of system transparency. A generalized predictive control (GPC) is developed to suppress the effect of time-varying delay and parameter identification error. Moreover, a terminal sliding mode controller (SMC) is designed to improve the robustness of the system under consideration. Simulation results are provided to show that the proposed control strategy can improve transparency of the remote vascular interventional surgery system.

Stability analysis of hybrid time-delay systems using homogeneity property

In this paper, stability analysis is studied for hybrid time-delay systems (HTDSs) with homogeneity. Using Lyapunov-Krasovskii functional method, a novel and relaxed condition is derived to analyze pre-asymptotic stability of the considered systems with homogeneity. Then, the connections of solutions are established between the systems with different sizes. Based on the established connections, some homogeneous properties are introduced to analyze stability of the HTDSs with different sizes or degrees, and then some necessary and sufficient stability conditions are obtained. Finally, numerical examples are provided to show the effectiveness of the results obtained in this paper.

Periodicity and multi-periodicity generated by impulses control in delayed Cohen-Grossberg-type neural networks with discontinuous activations

This paper discusses the periodicity and multi-periodicity in delayed Cohen-Grossberg-type neural networks (CGNNs) possessing impulsive effects, whose activation functions possess discontinuities and are allowed to be unbounded or nonmonotonic. Based on differential inclusion and cone expansion-compression fixed-point theory of set-valued mapping, several improved criteria are given to derive the positive solution with ω-periodicity and ω-multi-periodicity for delayed CGNNs under impulsive control. These ω-periodicity/ω-multi-periodicity orbits are produced by impulses control. The analytical method and theoretical results presented in this paper are of certain significance to the design of neural network models or circuits possessing discontinuous neuron activation and impulsive effects in periodic environment.

Consensus of a class of discrete-time nonlinear multi-agent systems in the presence of communication delays

In this paper, we study the consensus problem for a class of discrete-time nonlinear multi-agent systems. The dynamics of each agent is input affine and the agents are connected through a connected undirected communication network. Distributed control laws are proposed and consensus analysis is conducted both in the absence and in the presence of communication delays. Both theoretical analysis and numerical simulation show that our control laws ensure state consensus of the multi-agent system.

A composite feedback approach to stabilize nonholonomic systems with time varying time delays and nonlinear disturbances

In this work, we propose a robust stabilizer for nonholonomic systems with time varying time delays and nonlinear disturbances. The proposed approach implements a composite nonlinear feedback structure in which a linear controller is designed to yield a fast response and a nonlinear feedback control law is considered to increase the system's damping ratio. This structure results in the simultaneous improvement of the steady-state accuracy and transient performance of time-delay nonholonomic systems. Asymptotic stability of the proposed feedback control approach is derived using a Lyapunov-Krasovskii functional aimed at reaching a compromise between system's transient performance and asymptotic stability. Simulation and analytical results are considered to highlight the robustness and superior performance of the proposed approach in controlling high-order-time-delay nonholonomic systems with nonlinear disturbances.

Transience after disturbance: Obligate species recovery dynamics depend on disturbance duration

After a disturbance event, population recovery becomes an important species response that drives ecosystem dynamics. Yet, it is unclear how interspecific interactions impact species recovery from a disturbance and which role the disturbance duration (pulse or press) plays. Here, we analytically derive conditions that govern the transient recovery dynamics from disturbance of a host and its obligately dependent partner in a two-species metapopulation model. We find that, after disturbance, species recovery dynamics depend on the species' role (i.e. host or obligately dependent species) as well as the duration of disturbance. Host recovery starts immediately after the disturbance. In contrast, for obligate species, recovery depends on disturbance duration. After press disturbance, which allows dynamics to equilibrate during disturbance, obligate species immediately start to recover. Yet, after pulse disturbance, obligate species continue declining although their hosts have already begun to increase. Effectively, obligate species recovery is delayed until a necessary host threshold occupancy is reached. Obligates' delayed recovery arises solely from interspecific interactions independent of dispersal limitations, which contests previous explanations. Delayed recovery exerts a two-fold negative effect, because populations continue declining to even smaller population sizes and the phase of increased risk from demographic stochastic extinction in small populations is prolonged. We argue that delayed recovery and its determinants -species interactions and disturbance duration - have to be considered in biodiversity management.

System identification with measurement noise compensation based on polynomial modulating function for fractional-order systems with a known time-delay

This study presents a system identification method based on polynomial modulating function for fractional-order systems with a known time-delay involving input and output noises in the time domain. Based on the polynomial modulating function and fractional-order integration by parts, the identified fractional-order differential equation is transformed into an algebraic equation. By using the numerical integral formula, the least squares form for the system identification is obtained. In order to reduce the effect of noises existing in the input and output measurements, the compensation method for the input and output noises is also studied by introducing an auxiliary high-order fractional-order system in the revised identification algorithm. Finally, the effectiveness of the proposed algorithm is verified by the simulation result of an illustrative example and the experimental result of temperature identification for a thermal system.

Fault-tolerant finite-time fuzzy control for nonlinear power systems with time delays and actuator faults

To ensure the stability of nonlinear power systems with actuator faults and time delays, this study aims to design an adaptive fuzzy finite-time control scheme. To deal with this control issue, firstly, we propose an adaptive fault-tolerant finite-time controller using backstepping technique. To aid the controller design, fuzzy logic systems are applied to approximate the uncertain nonlinear terms without the prior information. Then, it is proved that the designed controller can ensure the stability in a finite time for the nonlinear power systems with actuator faults and time delays using Lyapunov-Krasovskii method. Finally, numerical simulations of a 4-machine power system with Thyristor Controlled Series Compensation (TCSC) illustrate the applicability of the proposed control methodology.