Constant Signal Research Articles

On the long time behaviour of single stochastic Hodgkin-Huxley neurons with constant signal, and a construction of circuits of interacting neurons showing self-organized rhythmic oscillations

The stochastic Hodgkin-Huxley neurons considered in this paper replace time-constant deterministic input $a dt$ of the classical deterministic model by increments $\vartheta dt + dX_t$ of a stochastic process: $X$ is Ornstein-Uhlenbeck with volatility $\sigma>0$ and backdriving force $\tau>0$, and we call $\vartheta>0$ the signal. We have ergodicity and strong laws of large numbers for various functionals of the process, and characterize 'quiet behaviour' and 'regular spiking' as events whose probability depends on the parameters $(\tau,\sigma)$ and on the signal $\vartheta$. The notions of quiet behaviour and regular spiking allow for a construction of circuits of interacting stochastic Hodgkin-Huxley neurons, combining excitation with inhibition according to a bloc structure along the circuit, on which self-organized rhythmic oscillations can be observed.

Optimal output tracking of Boolean control networks

The traditional output tracking problem for a system is to design a controller such that the output of the system tracks a constant signal or a network after a finite time. However, when the output of the system can not completely track the reference signal, there is no result to show how to deal with this situation. To solve such problem, we investigate the optimal output tracking problem of Boolean control networks (BCNs) with a constant reference signal in this paper, that is, to design an appropriate control scheme such that each state will evolve to their optimal output tracking trajectory. Firstly, the optimal output tracking cycle (OTC) of each state is defined. Secondly, a method is presented to compute the cycle with certain length in the system, and the least upper bound of the length for the optimal OTC is derived. Finally, a constructive algorithm is presented to design the state feedback controllers that enable the system to realize optimal output tracking. Moreover, an illustrative example is given to show the obtained results.

Pharmacological inhibition of FOXO1 promotes lymphatic valve growth in a congenital lymphedema mouse model.

Mutations in many genes that regulate lymphatic valve development are associated with congenital lymphedema. Oscillatory shear stress (OSS) from lymph provides constant signals for the growth and maintenance of valve cells throughout life. The expression of valve-forming genes in lymphatic endothelial cells (LECs) is upregulated by OSS. The transcription factor FOXO1 represses lymphatic valve formation by inhibiting the expression of these genes, which makes FOXO1 a potential target for treating lymphedema. Here, we tested the ability of a FOXO1 inhibitor, AS1842856, to induce the formation of new lymphatic valves. Our quantitative RT-PCR and Western blot data showed that treatment of cultured human LECs with AS1842856 for 48h significantly increased the expression levels of valve-forming genes. To investigate the function of AS1842856 in vivo, Foxc2 +/- mice, the mouse model for lymphedema-distichiasis, were injected with AS1842856 for 2 weeks. The valve number in AS-treated Foxc2+/- mice was significantly higher than that of the vehicle-treated Foxc2+/- mice. Furthermore, since β-catenin upregulates the expression of Foxc2 and Prox1 during lymphatic valve formation, and AS1842856 treatment increased the level of active β-catenin in both cultured human LECs and in mouse mesenteric LECs in vivo, we used the mouse model with constitutive active β-catenin to rescue loss of lymphatic valves in Foxc2 +/- mice. Foxc2 +/- mice have 50% fewer lymphatic valves than control, and rescue experiments showed that the valve number was completely restored to the control level upon nuclear β-catenin activation. These findings indicate that pharmacological inhibition of FOXO1 can be explored as a viable strategy to resolve valve defects in congenital lymphedema.

On offset-free Model Predictive Control with Long Short-Term Memory Networks

This paper addresses offset-free reference tracking of asymptotically constant reference signals and disturbances using Model Predictive Control with a Long Short-Term Memory Network model. Basically, an error free output estimation and an error free nominal tracking for time-varying references are proposed for an Incremental Input-to-State Stable Long Short-Term Memory Network. This implies an offset-free Model Predictive Control algorithm.

Chaos Elimination for a Buck Converter Using the Multi-Objective Grey Wolf Optimiser

Abstract A wide variety of nonlinear phenomena, such as bifurcation and chaos, have been observed in power electronics converters. Much research has been conducted on these behaviours in different converter topologies. The buck converter is known to exhibit chaotic behaviour in a wide parameter range, giving rise to unstable behaviours depending on the circuit parameters values. This paper investigates this bifurcation behaviour by varying the parameters of a voltage PI (Proportional Integral) controlled buck converter operating in continuous conduction mode, using a continuous-time model and constant frequency control signal. Furthermore, a novel and improved version of the PI compensation technique, designed using the multi-objective grey wolf optimiser (MOGWO), is proposed to stabilise the buck converter from chaotic state to periodic orbit.

Supervised Learning of Analysis-Sparsity Priors With Automatic Differentiation

Sparsity priors are commonly used in denoising and image reconstruction. For analysis-type priors, a dictionary defines a representation of signals that is likely to be sparse. In most situations, this dictionary is unknown, and is to be recovered from pairs of ground-truth signals and measurements, by minimizing the reconstruction error. This defines a hierarchical optimization problem, which can be cast as a bi-level optimization. Yet, this problem is unsolvable, as reconstructions and their derivative <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">w.r.t.</i> the dictionary have no closed-form expression. However, reconstructions can be iteratively computed using the Forward-Backward splitting (FB) algorithm. In this paper, we approximate reconstructions by the output of the FB algorithm, up to a linear transformation. Then, we leverage automatic differentiation to evaluate the gradient of this output <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">w.r.t.</i> the dictionary, which we learn with projected gradient descent. Experiments show that our algorithm successfully learns the 1D Total Variation (TV) dictionary from piecewise constant signals. For the same case study, we propose to constrain our search to dictionaries of 0-centered columns, which removes undesired local minima and improves numerical stability.

Memory Sampled-Data Controller Design for Interval Type-2 Fuzzy Systems via Polynomial-Type Lyapunov–Krasovskii Functional

This study deals with the investigation of the interval type-2 (IT2) fuzzy sampled-data (SD) stabilization problem based on nonlinearities and parameter uncertainties. For the first time, a memory SD control design involving a known signal transmission delay is adapted to address the stabilization problem for IT2 fuzzy systems. New polynomial-type Lyapunov–Krasovskii functionals (LKFs) associated with the state of constant signal transmission delay are introduced to achieve less conservative stability results. To bound the derivative of such LKFs, the Jacobi–Bessel inequality is introduced. Due to this, improved delay-dependent sufficient conditions can be obtained relating to set of linear matrix inequalities (LMIs). Thus, by solving LMIs using the LMI solver in MATLAB, the closed-loop system can be stabilized. The proposed method is verified in the simulation results with a nonlinear permanent-magnet vernier generator (PMVG)-based wind energy model and a Rossler model. Also, the applicability and superiority of the derived sufficient conditions are proved when compared with the existing results.

Time-resolved temperature-dependent photoluminescence spectroscopy of InGaAs/GaAs quantum well-dots

The paper presents the results of a study of dynamic properties of InGaAs quantum well-dots (QWD) embedded in a GaAs matrix carried out by time-resolved photoluminescence (TRPL) in the temperature range of 10–300 K. The time dependence of the PL shows a long region of constant signal intensity. It was attributed to the filling of all available QWD states due to the fast exchange with the matrix and the relatively long time of radiative recombination. The experimental results are consistent with the calculations performed in the rate equation model for a two-level system. It turned out that there is no need for the residual 2D quantum well to be taken into account, which is not typical for Stranski-Krastanow quantum dots, where the wetting layer plays an important role in carrier exchange processes. Nonradiative recombination can also be ignored, which indicates a high quality of the structure. By fitting the simulation results, the microscopic properties of the electron and hole states in QWDs were obtained for the first time: the radiative lifetime is 700 ps, the barriers for electron and hole in QWDs are 50 and 150 meV, respectively. Carrier capture time was found to be in the range of 10–30 ps.

Virtual Constant Signal Injection-Based MTPA Control for IPMSM Considering Partial Derivative Term of Motor Inductance Parameters

The dq-axis inductance parameter value of the Internal Permanent Magnet Synchronous Motor (IPMSM) will change with the dq-axis current. The Virtual Constant Signal Injection Method (VCSIM)-based Maximum Torque Per Ampere (MTPA) control ignores the partial derivative term of the dq-axis inductance to the dq-axis current when extracting the partial derivative information of the torque to the dq-axis current. This will cause the current to deviate from the MTPA point, which will have a certain impact on the output capacity and efficiency of the motor torque. To solve the above problems, this paper proposes a simple and feasible compensation method by solving the partial derivative information between the dq-axis inductance and the dq-axis current. The experimental results show that the motor efficiency and torque output capability are significantly improved after applying the proposed strategy.

OLSA level control in monaural speech audiometry in background noise for the evaluation of the CI fitting result

Speech audiometry measurements under the influence of background noise are a fundamental part of evaluating the outcome of hearing care. As yet far, there are no recommendations for selecting a suitable method for adaptive speech audiometry measurements in background noise in cochlear implant (CI) care, so either the choice the adaptive level change of the speech signal (S) with constant noise (N) or the adaptive level change of N with constant S. Do the measurement results of the monaural speechrecognition threshold in noise (SRT) with the Oldenburg Sentence Test (OLSA) depend on the choice of level control? A total of 50 series of measurements with OLSA in noise and the Freiburg speech intelligibility test in quiet (FBE) on middle-aged CIpatients from clinical routine. There is no significant difference in the measurement results with different level controls when the SRT is less than 5 [Formula: see text]. Below 55 % monosyllabic intelligibility in quiet, the SRT in noise becomes greater than 5 [Formula: see text]. From a clinical, audiological and methodological point of view, it is advisable to carry out the adaptive monaural speech intelligibility measurement with a constant speech signal at 65 [Formula: see text].

Orthogonality constrained analytic CMA for blind signal extraction improvement

The well-known Analytic Constant Modulus Algorithm (ACMA) is a classic algebraic method for signal separation and equalization, which can achieve blind signal recovery and fast convergence. In this paper, we explore new means for incorporating the inherent statistical signal orthogonality in ACMA for improved signal separation and recovery. This statistical orthogonality constraint adds new restrictions to ACMA, leading to a novel approach we denote as Orthogonality Constrained Analytic Constant Modulus Algorithm (OC-ACMA). We further generalize OC-ACMA for applications in blind equalization. Results show that OC-ACMA can successfully separate and recover constant modulus signals at higher accuracy.

Insulation Parameter Online Measurement Technology Based on Extended Zero-Sequence Circuits for Resonant Grounding Distribution Networks

To eliminate the measurement errors of insulation parameters caused by the internal impedance of VT (voltage transformer) and the damping resistance in resonant grounding distribution networks, a new online measurement technology based on an extended zero-sequence circuit is proposed. A constant current signal with variable frequency is injected into distribution network through a VT, and the return voltage is measured from another unloaded VT. An extended zero-sequence circuit is established to ensure that the injected current and the return voltage directly act on the insulation branch to ground; thus, the influence of the VT internal impedance can be eliminated. The resonance frequency is obtained according to the phase difference between the injected current and the return voltage, and the measurement error caused by damping resistance can be eliminated. Then, the capacitance to ground and leakage conductance can be accurately calculated. A measuring device based on the proposed technology was developed, and tests were carried out on a 10-kV distribution network laboratory and an actual 10-kV substation. The test results show that the proposed method has high measurement accuracy. The measurement process does not require a power interruption, and it does not affect the normal operation of the power system.

Effective spectrum sensing using cognitive radios in 5G and wireless body area networks

Wireless Body Area Network (WBAN) is one of the wireless networks vertical purviews, which supports for constant physiological signal monitoring of human body and attracts both academic and industry in the field of research. In this wireless communication incorporating cognitive radio supports for providing opportunistic wireless link to user optimally by sensing spectral environment. Since the sensors used are battery dependent, increasing the lifetime of network is an essential task, implementing machine learning approach dynamically indicate path for effective data transmission between network intermediate and server. Consequently, energy harvesting and standard deviation of utilised energy estimation also need to be concentrated in this work while number sensors are incorporated in WBAN. Proposed scheme is validated with effectiveness of numerical results and proposes modified algorithm with low computational complexity. Reducing energy consumption of mobile communication networks has gained significant attentions since it takes a major part of the total energy consumption of information and communication technology (ICT).

Temperature-Independent Fault Detection of Solenoid-Actuated Proportional Valve

Most electrically actuated hydraulic valves utilize solenoids as the actuating element due to their robustness and simplicity. This goes for both <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on–off</small> and proportional-type valves. However, despite their robustness, solenoid coil malfunction is the largest single failure mode in solenoid actuated valves. An outspoken fault is here solenoid winding short-circuit, i.e., two windings short-circuiting, which may ultimately lead to solenoid failure if more windings short-circuit. Research has therefore also focused on detecting winding short-circuits. Common for the approaches are that they, directly or indirectly, depend on the coil winding temperature, as this directly influences the coil resistance. Alternatively, the approaches are based on injection of high-frequency signals, which is typically a costly solution, which is not a feasible approach for use in hydraulic valves, with the limitations imposed by the control electronics. Therefore, this article focuses on a temperature-independent algorithm to detect coil winding short-circuit, which is easy to implement and only relies on existing position and current sensors. The proposed algorithm is based on an extended Kalman filter, which estimates the coil resistance. As this resistance estimate is indirectly dependent on the coil temperature, a window-based cumulative sum fault detection method is included to detect transient changes in the coil resistance while compensating for the temperature variations. The algorithm is developed based on an experimentally validated model of the valve, and has been tested for several different situations through both simulations and experimentally. Based on the presented results, it is found that the algorithm can consistently detect resistance changes down to 0.11 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\Omega$</tex-math></inline-formula> for constant input signals and down to 0.17 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\Omega$</tex-math></inline-formula> for sinusoidal-varying input signals. This while stillbeing robust to parameter variations, such as increased valve friction, spring coefficients, and sensor signal deviations.

Application of green-synthesized carbon dots for imaging of cancerous cell lines and detection of anthraquinone drugs using silica-coated CdTe quantum dots-based ratiometric fluorescence sensor

Chemotherapy drugs of daunorubicin and doxorubicin treat cancers with many side effects. So, detection of them in the biological system for regulation and controlling of usage is essential. In this study, a ratiometric fluorescent method was introduced for detection of daunorubicin and doxorubicin using bell pepper-based carbon dots, as the variable signal, and silica-coated CdTe quantum dots, as the constant signal. The detection was done based on variations of carbon dots intensity in the presence of drugs in comparison with the constant intensity of silica-coated CdTe quantum dots. The proposed ratiometric fluorescent method was successfully used for detection of daunorubicin and doxorubicin range of 54.37–13594.34 nmolL−1 and 86.2–17242 nmolL−1, with a detection limit of 18.53 nmolL−1 and 29 nmolL−1, respectively. Also, this method was used for detection of drugs in serum samples with recovery ranges of 86.14–99.62 (RSD 3–1.47%) and 86.32–97.53 (3.38–1.48%), respectively. Finally, after evaluation of carbon dots toxicity by MTT test, carbon dots was applied for imaging of prostate cancer cell lines (PC-3) and breast cancer cell lines (MCF7). The results demonstrated that despite improvement of the repeatability and interferences reduction by ratiometric method, also carbon dots were successfully applied for imaging of cell lines.

Low‐gain integral control for a class of discrete‐time Lur'e systems with applications to sampled‐data control

AbstractWe study low‐gain (P)roportional (I)ntegral control of multivariate discrete‐time, forced Lur'e systems to solve the output‐tracking problem for constant reference signals. We formulate an incremental sector condition which is sufficient for a usual linear low‐gain PI controller to achieve exponential disturbance‐to‐state and disturbance‐to‐tracking‐error stability in closed‐loop, for all sufficiently small integrator gains. Output tracking is achieved in the absence of exogenous disturbance (noise) terms. Our line of argument invokes a recent circle criterion for exponential incremental input‐to‐state stability. The discrete‐time theory facilitates a similar result for a continuous‐time forced Lur'e system in feedback with sampled‐data low‐gain integral control. The theory is illustrated by two examples.

Differentiating between artificial and natural sources of electromagnetic radiation at a seismogenic fault

Ultralow frequency (ULF) to low frequency (LF) electromagnetic radiation represents one of the most promising effects of brittle rock strain and microcracking that might be potentially helpful for short term earthquake forecasting. In this study the results of a six month monitoring campaign are presented from Obir Cave in the eastern Alps. Direct experimental observations of electromagnetic radiation have been made using a customised broadband data logger installed next to the Obir Fault - this seismogenic fault near the Periadriatic Lineament is known to be related to at least three large prehistoric earthquakes. On the basis of these measurements it has been possible to characterise a number of distinct signals: artificial constant narrowband signals at discrete frequencies; short serial broadband impulses; high energy broadband impulses; and low energy broadband impulses. The narrowband artificial signals were removed from the electromagnetic radiation time series analysis so that the natural signals were enhanced and could be compared more easily to meteorological parameters and rock strain indicators. Critically, the high energy broadband impulses show a strong correlation with lightning activity across much of central Europe and the eastern Mediterranean while the low energy broadband impulses appear to be associated with local rock strain in and around Obir Cave. Unfortunately, it seems certain that some of the essential strain related impulses are likely to have been overprinted by the larger lightning related impulses.

Constant-Envelope OFDM for Power-Efficient and Nonlinearity-Tolerant Heterodyne MMW-RoF System With Envelope Detection

The radio over fiber (RoF) system using optical heterodyne (OH) for broadband up-conversion and envelope detection (ED) for phase-noise-insensitive down-conversion stands out as a simple, robust, and cost-effective solution for exploiting the abundant bandwidth resource at the millimeter-wave (MMW) band. In this paper, we dedicate efforts to experimentally investigate such an MMW-RoF system based on the constant-envelope orthogonal frequency division multiplexing (OFDM) (CE-OFDM) technique. A critical benefit of employing CE-OFDM is its excellent tolerance to the nonlinear distortions, which are essential for the wide acceptance of analog RoF systems. Also, thanks to the analog angle modulation transforming the OFDM signal to a constant envelope signal, the carrier-suppressed double-sideband (CS-DSB) modulation can be implemented for encoding the CE-OFDM signal onto the optical carrier, leading to significant improvements in power efficiencies of both fiber and radiofrequency (RF) links. In experiments, a 60-GHz OH-ED MMW-RoF system is established, of which the distances of fiber and MMW wireless transmissions are 10 km and 1.2 m respectively. Under the case of 2-GHz 64-quadrature amplitude modulation (QAM) OFDM baseband signal, the achieved experimental results show that the proposed OH-ED MMW-RoF system outperforms its counterpart using the conventional OFDM in terms of nonlinearity insensitivity, RF and optical power efficiency enhancements (indicated by over 11.5-dB and 3.2-dB reductions in the lowest transmit RF and receive optical powers for satisfying the 8% error-vector-magnitude (EVM) limit). In addition, when the QAM order of the 2.5-GHz OFDM baseband signal reaches 256, the CS-DSB CE-OFDM scheme enables an acceptable EVM performance of 4.43%.

Improving the sensitivity for hydrogen peroxide determination with active V2O5 nanocubes incorporated on mesoporous TiO2

The capacity to generate a constant signal response from an enzyme on an electrode surface has been a fascinating topic of research from the past three decades. To nourish the enzymatic activity during electrochemical reactions, the immobilization of dual enzymes on the electrode surface could prevent the enzymatic loss without denaturation and thus long-term stability can be achieved. For effective immobilization of dual enzymes, mesoporous materials are the ideal choice because of its numerous advantages such as 1. The presence of porous structure facilitates high loading of enzymes 2. The formation of protective environment can withstand the enzymatic activity even at acidic or basic pH values and even at elevated temperatures. Herein, we develop bienzymatic immobilization of horseradish peroxidase (HRP) and cholesterol oxidase (ChOx) on mesoporous V2O5–TiO2 based binary nanocomposite for effective sensing of hydrogen peroxide (H2O2) in presence of redox mediator hydroquinone (HQ). The utilization of redox mediator in second-generation biosensing of H2O2 can eliminate the interference species and reduces the operating potential with higher current density for electrochemical reduction reaction. Using this mediator transfer process approach at HRP/ChOx/V2O5–TiO2 modified GC, the H2O2 can be determined at operating potential (-0.2 V) with good linear range (0.05–3.5 mM) higher sensitivity (1040 μAμM−1 cm−2) and lower detection limit of about 20 μM can be attained, which is due to higher mediation of electrons were transferred to the enzyme cofactors. These interesting characteristics could be due to mesoporous structure of V2O5–TiO2 can induce large immobilization and facilitate higher interaction with enzymes for wide range of biosensing applications.

A Study of the Nonlinear Thomson Effect Produced by Changing the Current in a Thermoelectric Cooler

Abstract This work describes the nonlinear Thomson effect produced by a transient current source powering a thermoelectric cooler. The electric effect of the capacitive impedance in the semiconductors was considered in the equations as a novelty term that naturally appears by solving the Boltzmann equation to find the mathematical form of the current density. Thus, considering the new term and heath energy balances, a one-dimensional mathematical model for a thermoelectric cooler (TEC) powered by a time-dependent current was developed, finding a new nonlinear Thomson effect in the heath transfer equations. To evaluate the impact of the nonlinear effect on the thermodynamic behavior of the thermoelectric cooler, a continuous, sinusoidal and square-pulse current conditions were simulated. The temperature profile, temporal evolution, and the effective coefficient of performance (COP) were calculated. The results revealed a new thermoelectric heat transfer in addition to the Thomson flow created by virtual junctions throughout the semiconductors caused by the instantaneous change of current. This fact was evidenced by three results: the shifting of the temperature mean value due to the peak current change 0.45 A is 1.68 K 1.68\hspace{0.1667em}\mathrm{K} and 2.56 K 2.56\hspace{0.1667em}\mathrm{K} to sinusoidal and square current supplies, respectively; it was determined that a TEC powered by a square-pulse current signal had greater effective efficacy, having more pronounced cold side supercooling temperature peaks compared to those powered by a constant sinusoidal current signal.