Modulation Process Research Articles

Transitions of thermoacoustic modes and flame dynamics in a centrally-staged swirl combustor

In the start-up process of practical gas turbine applications, the modulation of operating condition, especially the variation of global equivalence ratios (ϕglo), could cause the variations of stability regimes. The above process is accompanied by the increase of total air flow rates (ṁair) when approaching the stable operation condition, and thus the effect of this parameter should also be considered in the operating condition modulation process. This work presents an experimental investigation into the transitions of thermoacoustic modes and flame dynamics in a centrally-staged swirl combustor over a range of ϕglo and ṁair. The present thermoacoustic system exhibits two transitions of thermoacoustic modes with ϕglo variation, showing distinct characteristics of pressure oscillation (p′) and flame structures. To further explore the detailed variation of p′ characteristics and its link to flame dynamics during two transitions, a nonlinear dynamic analysis of p′ including its phase and recurrence plots as well as a proper orthogonal decomposition (POD) study have been conducted. The thermoacoustic network analysis and local Rayleigh index analysis have clarified the mode transition mechanism with varying ϕglo and ṁair. The present results can provide a guideline for quantifying the stability regimes of fuel-flexible combustors during the operating condition modulation processes.

An ultra-short coil fiber optic gyroscope

This paper presents a novel ultra-short coil fiber optic gyroscope structure. An experimental system based on the spatially non-reciprocal phase modulator is built to realize the fiber optic gyroscope (I-FOG) of a 5 m length fiber coil, and the experimental results are in good agreement with the theoretical analysis. This structure can fundamentally eliminate the limitation of modulation frequency by the transit time and reduces the complexity of the demodulation system. The theoretical analysis and experimental results both prove that the FOG has a simple modulation and demodulation process and fast response, greatly simplifying the demodulation and feedback circuit. The ultra-short coil fiber optic gyroscope realizes a novel phase modulation method, which provides an idea for the development of FOG shortened fiber coil towards miniaturization, integration and on-chip gyro, and is expected to play an important role in lowering costs and improving precision.

Effect of Scattering Parameter on Small Signal analysis in Direct Modulated Dynamic Semiconductor Lasers

Effect of scattering parameter is that the effect which it is effected on the operating characteristics of direct modulated semiconductor lasers by small signal analysis for injection current density , where this parameter is effected on amount of quantum confinement carriers density where the part of this carriers density is lost in the active region. The scattering parameter leads to appear the nonlinear gain effects which they are reduced the response frequency of the direct modulation process. We use the rate equations of the single-mode semiconductor lasers and that they have characteristics are used to continuous-wave small-signal modulation. We can presented this effect and discussion it by the simple two-port device.

Comparative and mechanistic analysis of the ethanol gas sensing properties of ZnO@In2O3 and In2O3@ZnO spherical heterostructures

The space charge region formed in the spherical heterostructure materials through the electron transfer at the heterointerface is very beneficial for enhanced gas sensing performance. In particular, the inner and outer positions of the two materials that make up the spherical structure have a great influence on its performance. Herein, the spherical heterostructure ZnO@In2O3 and In2O3@ZnO were synthesized, respectively, by two-step chemical precipitation methods to investigate the effects of electron transfer direction on their gas sensing properties. The spherical heterostructures are composed of a solid sphere with a diameter of ∼300 nm and a porous structure with a thickness of ∼40 nm. Gas sensing test results showed similar gas sensing properties. However, spherical heterostructure ZnO@In2O3 displayed better gas sensing performances to ethanol, including higher sensitivity (96.6–100 ppm ethanol at 240 ℃, 3 times higher than that of In2O3@ZnO), a faster recovery rate, and higher selectivity. By comparison, the difference in electron transfer direction of these two heterostructure materials leads to different resistance modulation processes, thereby influencing their gas sensing response. These intrinsic electronic differences of ZnO and In2O3 also play an important role in the modulation of electron transfer. It is suggested that the structural design of heterostructure material is significant for the development of highly sensitive gas sensors.

Optical Measurements of Surface Topography for Materials with Scattering Light Reflection by Images Processing using Origin Lab

A method of non-contact optical measurements of surfaces topologies for materials with scattering light reflection using OriginLab images module processing is described. The images were captured under high lighting levels and close distances at photographing. Digital images were converted by OriginLab software into a data matrix, each element of which contains information about the level of reflected light from individual sections of the surface with different depths. Than the image data was converted into worksheet data and calculated to data with real geometric parameters. The length, width and depth of can be measured with special image OriginLab tools The processing of hyper spectral images obtained using a very narrow spectral band (through filters of Asahi Spectra Co.Ltd) with proposed optical method makes possibilities for determination geometrical parameters of damages surface biological objects. Different surfaces with scattering light reflection from 0.1 mm till 10 cm is analyzed. Keywords— scattering light reflection, image processing, optical measurement, geometric parameters.

Sigma Receptors – Literature Review

The paper reviewed data confirming that sigma1 receptors modulate NMDA neurotransmission. It has been established that they can enhance the spontaneous release of glutamate in the hippocampus, potentiate the release of a neurotrophic factor induced by glutamate, and also participate in the processes of synaptic restructuring (facilitation of long-term potentiation) in the mammalian hippocampus. But the use of high doses of agonists or antagonists of sigma1 receptors in animal models does not have any effect on memory modulation or learning processes in control animals. These findings indicate that sigma1 receptors do not affect the physiological (normal) processes of memory consolidation. The effects of sigma1 receptors considered in the work speak of effects on cognitive processes only in conditions of neurotransmitter imbalance. In a number of works, with the participation of various experimental models, the possible involvement of sigma1 receptors in the processes of memory recovery was revealed. A real breakthrough in the treatment of affective disorders is being made in our time due to an increasingly detailed study of the mechanisms of intracellular receptor structures and chaperone proteins, in particular, sigma receptors. By acting on these mechanisms, side effects in the treatment of depression, inevitable with the use of traditional antidepressants, can be avoided. Also, thanks to modern drugs based on interaction with sigma receptors, it is possible to influence neurogenesis, learning and memory processes. Thus, the sigma-1 receptor is an extremely promising object that can be considered as a potential therapeutic target for the treatment of neuropathological diseases

ARM CORTEX-M3 MİKRODENETLEYİCİ KULLANIMI İLE ÇOK TAŞIYICILI GÖRÜNÜR IŞIK HABERLEŞME SİSTEMİ GELİŞTİRİLMESİ

With the development of technology, the constraints and the needs in the field of communication have increased. Especially, limited and licensed radio frequencies that can cause electromagnetic interference and health problems in the use of wireless communication make the visible light communication (VLC) technologies very important. In this study, an ARM based VLC system design has been realized to implement a unique product with the use of low-cost and commercial off-the-shelf electronic components. In this context, receiver and transmitter circuits are designed, printed circuit boards and appropriate enclosures have been produced, as a result, a system prototype has been created to use in interior applications with standard ceiling height. The design is also one of the few implementations in which orthogonal frequency division multiplexing (OFDM) modulation and digital signal processing applications are performed by using ARM based microcontroller. Consequently, the system communication is achieved at a data rate of 3.5 kbps from a distance 1.8 m to 3 m. Also the system communication is successfully performed from the center of the light source up to 85 cm distance on the direct side and up to an angle of 50° on the azimuth.

Instantaneous Frequency Measurement with Reasonable Resolution and Simple Structure

Microwave signals carry important intelligence information in electronic warfare. Hence, the measurement of microwave signals plays a very important role. Traditional electronic microwave measurement systems are not appropriate for the instantaneous frequency measurement (IFM) of high-speed signals. A simple and low-cost photonic approach to the IFM based on frequency-to-power mapping is proposed and demonstrated with a reasonable resolution. The measurement is performed on account of a double Mach–Zehnder modulator (MZM), single-mode fiber (SMF), photodetector (PD), and signal processing. The scheme using four wavelengths achieves resolutions of ±0.1 and ±0.09 GHz respectively for the 15.8–18.4 and 18.4−21.2 GHz frequency measurement ranges. Therefore, the scheme is a broad prospects method for high-resolution IFM. Moreover, it is of great importance for applications in electronic warfare and high-resolution sensor systems.

Design of Artificial Intelligence Epidemic Big Data Prevention and Control Early Warning System

The artificial intelligence epidemic big data prevention and early warning system of the project includes client, cloud database, information acquisition module and information processing module. The client communicates with the cloud database, the cloud database connects with multiple information collection modules, and the cloud database communicates with multiple information processing modules. The client is used for backstage personnel to watch the information, As well as the feedback and display of background information, the cloud database is used to store the information entered by the information collection module, and the information processing module is used to compare and process the information entered by the information collection module. This project involves the field of epidemic prevention and early warning technology. The artificial intelligence epidemic big data prevention and control early warning system solves the problem that the existing epidemic big data early warning system is inconvenient for real-time detection of health monitoring, personnel positioning and trajectory tracking.

Skin Pain Sensation Under Mechanical Stimulus: Wind-Up and Ramp-Off

Abstract Researchers have been studying the pain sensation extensively in the past few decades. Quantitative simulation and theoretical modeling of pain sensation based on experimental results are necessary for pain research. Many theories have been proposed to explain the mechanism of pain from molecular, cellular, and neuron network perspectives. But some phenomena in pain sensation are not fully understood, including wind-up and ramp-off. This paper focused on the theoretical model of wind-up and ramp-off phenomena in the pain sensation. With the addition of the transduction model, the generation mechanism of wind-up and ramp-off is better explained. The simulations were carried out to analyze the skin pain sensation under the mechanical stimulus, consisting of four different parts: the mechanical model of skin, transduction, transmission, modulation, and perception. The stress distribution on the skin was obtained based on the elastic theory. And the modified Hodgkin and Huxley model and the mathematical model of gate control theory were utilized to analyze the process of transduction, modulation, and perception, respectively. The numerical experiments demonstrated the wind-up occurs with a frequent stimulus of 1 Hz and 2 Hz, and ramp-off appears with the withdrawal of constant mechanical stimulus, which could contribute to the understanding of the pain sensation mechanism.

Lysozyme allosteric interactions with β-blocker drugs

Effective and reliable prediction of allosteric molecular interactions involved in protein-ligand systems are essential to understand pharmacological modulation and toxicology processes that are driven by multiple factors covering from the atomistic to cellular level. Even though the interactions taking place within a defined biophysical environment are usually intricate and complex, having a preliminary knowledge of the structural determinant and biochemical function of target enzyme in the physiological or unbound state represent a step forward in the characterization of the forces involved these processes under interaction conditions as induced by drugs. In the present work, we tackle the study of relevant binding interactions between two well-recognized betablocker drugs and the lysozyme biological target from an experimental-computational perspective. In this way, molecular docking, machine learning and perturbation analysis combined with UV–vis and fluorescence measurements will allow us to determine the allosteric regulation and functional dynamics of lysozyme by binding propranolol and acebutolol.

Quetiapine Ameliorates MIA-Induced Impairment of Sensorimotor Gating: Focus on Neuron-Microglia Communication and the Inflammatory Response in the Frontal Cortex of Adult Offspring of Wistar Rats.

The maternal immune activation produced by the systemic administration of lipopolysaccharide (LPS) in rats provides valuable insights into the basis of behavioural schizophrenia-like disturbances and biochemical changes in the brains of the offspring, such as microglial activation. Regarding therapy, antipsychotics continually constitute the cornerstone of schizophrenia treatment. To their various efficacy and side effects, as well as not fully recognised mechanisms of action, further characteristics have been suggested, including an anti-inflammatory action via the impact on neuron–microglia axes responsible for inhibition of microglial activation. Therefore, in the present study, we sought to determine whether chronic treatment with chlorpromazine, quetiapine or aripiprazole could influence schizophrenia-like behavioural disturbances at the level of sensorimotor gating in male offspring prenatally exposed to LPS. Simultaneously, we wanted to explore if the chosen antipsychotics display a positive impact on the neuroimmunological parameters in the brains of these adult animals with a special focus on the ligand-receptor axes controlling neuron–microglia communication as well as pro- and anti-inflammatory factors related to the microglial activity. The results of our research revealed the beneficial effect of quetiapine on deficits in sensorimotor gating observed in prenatally LPS-exposed offspring. In terms of axes controlling neuron–microglia communication and markers of microglial reactivity, we observed a subtle impact of quetiapine on hippocampal Cx3cl1 and Cx3cr1 levels, as well as cortical Cd68 expression. Hence, further research is required to fully define and explain the involvement of quetiapine and other antipsychotics in Cx3cl1-Cx3cr1 and/or Cd200-Cd200r axes modulation and inflammatory processes in the LPS-based model of schizophrenia-like disturbances.

Parameter estimation of Markov modulated fluid arrival processes

Markov modulated discrete arrival processes have a wide literature, including parameter estimation methods based on expectation–maximization (EM). In this paper, we investigate the adaptation of these EM based methods to Markov modulated fluid arrival processes (MMFAP), and conclude that only the generator matrix of the modulating Markov chain of MMFAPs can be approximated by EM based method. For the rest of the parameters, the fluid rates and the fluid variances, we investigate the efficiency of numerical likelihood maximization.To reduce the computational complexity of the likelihood computation, we accelerate the numerical inverse Laplace transformation step of the procedure with function fitting.

OPTIMAL PULSE WIDTH MODULATION IN THE ELECTRIC DRIVE CONTROL SYSTEM

The process of pulse width modulation (PWM) in the converter - electric motor system is considered. It is noted that the main task of pulse-width modulation of the voltage generated by the electron-key converter in the converter - electric motor system is to reduce current pulsations during the modulation period. It is proved that the dynamic process of changing the current in an electric machine on the PWM period can be approximated by an R, L-filter. It is established that the most important task of PWM is to minimize the current modulation error in the electric motor. The analysis of possible criteria for assessing the quality of the modulation process in electric drive control systems is carried out. It is shown that as an optimality criterion for assessing the quality of modulation in a converter - electric motor system, it is advisable to use an integral quadratic criterion of relative error, called local current dispersion, as well as the average value of local current dispersion over the period of the modulating function, called integral current dispersion. The process of single-phase modulation on a single-phase load is considered. Analytical estimates of the load current dispersion for this process are obtained. A condition, under which the current dispersion takes a minimum value, is recorded. The efficiency of pulse-width modulation optimization by the criterion of current dispersion is investigated. The average dispersion of currents in the load with a centrally symmetric arrangement of pulses on the modulation interval is taken as the base value of the dispersion. An expression that allows us to evaluate the efficiency of optimizing the current dispersion, taking into account the increment of the center of the modulation interval, is obtained. The dependence illustrating the efficiency of optimization by the criterion of pulse displacement relative to the center of the PWM interval on the relative frequency of modulation at different amplitudes of the modulating voltage is constructed. An expression is obtained for estimating the average value of the local current dispersion over the half-period of the modulating function.

A novel silent speech recognition approach based on parallel inception convolutional neural network and Mel frequency spectral coefficient.

Silent speech recognition breaks the limitations of automatic speech recognition when acoustic signals cannot be produced or captured clearly, but still has a long way to go before being ready for any real-life applications. To address this issue, we propose a novel silent speech recognition framework based on surface electromyography (sEMG) signals. In our approach, a new deep learning architecture Parallel Inception Convolutional Neural Network (PICNN) is proposed and implemented in our silent speech recognition system, with six inception modules processing six channels of sEMG data, separately and simultaneously. Meanwhile, Mel Frequency Spectral Coefficients (MFSCs) are employed to extract speech-related sEMG features for the first time. We further design and generate a 100-class dataset containing daily life assistance demands for the elderly and disabled individuals. The experimental results obtained from 28 subjects confirm that our silent speech recognition method outperforms state-of-the-art machine learning algorithms and deep learning architectures, achieving the best recognition accuracy of 90.76%. With sEMG data collected from four new subjects, efficient steps of subject-based transfer learning are conducted to further improve the cross-subject recognition ability of the proposed model. Promising results prove that our sEMG-based silent speech recognition system could have high recognition accuracy and steady performance in practical applications.

Amplification and interaction of two optical waves with third harmonic spectral delay

In the present paper the parametric interaction between two optical waves, which are propagating in few-mode optical fibers, is investigated. This occurs under the influence of the processes of third harmonic generation, self-phase modulation and cross-phase modulation. The generation of third-harmonic or THz generation in femtosecond region is described by a system of two coupled nonlinear differential equations. A new analytical solution of this system, which characterizes the periodic energy exchange between the two waves, is found. Depending on the wavenumber mismatch Δk, the obtained result can be used for studying different optical processes of generation of signal wave in nonlinear dispersive media. The mentioned effects are strongly related to modern optical sensors, parametric amplifiers and communication systems.

Understanding the blade coated to roll-to-roll coated performance gap in organic photovoltaics

The fabrication of efficient organic photovoltaic (OPV) modules via high throughput methods is a crucial milestone to facilitate their commercialization. The achievement of reliable printing and coating processes for large-scale modules has, however, been challenging thus far. Indeed, the performance gap is large between cells produced at lab-scale and those resulting from industrial methods. Therefore, understanding the critical steps in the upscaling process is decisive to address the research efforts towards decreasing the aforementioned gap. In this contribution, we analyze the efficiency losses associated with several of the main steps involved in the up-scaling pathway of the OPV devices, from lab-scale blade coating to pre-industrial slot die roll-to-roll coating. We show that when using materials in the active layer for which the performance is tolerant to thickness/microstructure variations, the critical steps are related to the charge carrier blocking layers, as well as potential losses due to parasitic absorption in the semitransparent electrodes.

Recent progress in label-free techniques for characterization of extracellular vesicle heterogeneity

<p indent="0mm">Extracellular vesicles (EVs) are small <sc>(30–1000 nm)</sc> membrane-enclosed vesicles produced by cells for the purpose of communication and environment manipulation. Despite their biological and clinical relevance only being realized within the past <sc>15 years,</sc> they are already considered to be one of the most critical factors in cell-cell communication, cancer-host modulation, and other dynamic processes. However, their small size, fragility, and tendancy to aggregate make them challenging samples to be studied by traditional analytical chemistry techniques. Currently the majority of EV characterization takes the form of “bulk analysis” where millions or billions of EVs are pooled to provide enough sample for downstream analysis. However, there is a recent trend, driven by the increasing appreciation for EV heterogeneity, for characterization methods that can study individual EVs. In this review, we survey several optical and non-optical methods for single-EV characterization without labels, including Raman spectroscopy, plasmonic techniques, atomic force microscopy (AFM), and electron microscopy. Results show that single-vesicle techniques can provide a wealth of information beyond that obtained by traditional bulk analysis methods, with strong prospects for future fundamental discoveries in biology and medicine.

Extended Harmonic Resonance Analysis of Grid-Connected Converters Considering the Frequency Coupling Effect

Existing studies about the harmonic analysis of grid-connected converters (GCCs) mainly focus on the frequency range below Nyquist sampling frequency (NSF) or switching frequency (SF) to make full use of linearization. However, in some actual high-power industrial applications; e.g., electric railways or wind power generation, harmonic problems are challenging in a wide frequency that can be as high as thousands of hertz. This is much higher than the NSF and SF. In order to bridge the gap, this article extends the harmonic analysis frequency to the entire frequency range by addressing the aliasing effect and sideband effect. These two effects can be neglected at the low frequency for simplification while they will make great differences at the high frequency, as demonstrated in this article, due to the frequency coupling and nonlinear characteristics. In this regard, a regression method based on an artificial neural network is used to map the in–out relation of the pulsewidth modulation process. By adopting the methodology of this article, harmonic performances of GCCs can be analyzed comprehensively and explicitly in terms of harmonic instability, harmonic resonance, harmonic overvoltage, filter design, and so on. Finally, experiments are presented to verify the effectiveness and accuracy of the analysis.

The effect and properties of drifts in the heliosphere

We investigate the properties of drifts and their effect on cosmic ray modulation in the heliosphere using a numerical modulation model based on the solution of a set of stochastic differential equations that was derived from the Parker transport equation. The illustrative capabilities of the numerical model are exploited to yield a better understanding of the physical modulation processes involved. Various studies have indicated that drifts need to be scaled down towards solar maximum conditions and the present study looks at how this can be achieved. Drifts are scaled down directly by multiplying the drift coefficient by a factor of less than unity as well as indirectly through the drift–diffusion relation, that is, by modifying the diffusion coefficient so as to cause a change in the drift effects through altered gradients in particle intensity. Contour plots of particle exit positions and exit energies are presented for both of these cases, and it is illustrated that drifts in the model lead to larger energy losses. This is explained with the aid of figures indicating the relative amount of time spent by pseudo-particles in different regions of the heliosphere during the modulation process. These figures also indicate that an increase in diffusion leads to a suppression or reduction of drift effects. Finally, the figures also show that drift effects are reduced as a function of increasing particle energy; even though the drift coefficient increases with particle energy, the total drift effect, taking into account the contribution from the increased diffusion associated with larger energies, causes drift effects to be reduced with an increase in energy.