Nonlinear loads, a crucial component of power systems grids, pose a challenge due to harmonics injection. Our research tackles this issue with a novel approach - a modified green plug / switched filter compensation scheme using fuzzy logic controllers. This innovative scheme, presented in the paper, utilizes dual action pulse width modulation to ensure switching functions from harmonic reduction and capacitive compensation for inrush nonlinear type AC loads.  The scheme's multi-loop regulations and online switching effectively handle dynamic type slow acting inrush, motorized and other rectifier type-nonlinear loads, enhancing power factor, power quality at source and load buses, and reducing total harmonic distortion at key source and sensitive nonlinear load buses. A simulation model in the MATLAB/SIMULINK software environment demonstrates the efficiency of the proposed FACTS technique. The results show that voltage, current, active power, reactive power, power factor regulation, and effective energy utilization are achievable with the designed FACTS-MFCC-SFC. The switched modulated AC green plug filter significantly improves power quality and enhances power factor in the case of inrush and nonlinear loads.

We offered the circuit of a discrete analog filter (DAF) low frequencies of second-order on switchable capacitors, which differs from the known ones in that three capacitors with one terminal are connected to a common bus, and the frequency of the DAF pole depends not only on the ratio of the capacitances of the frequency-setting capacitors, but also on the ratio of resistances two additional resistors in the feedback. This allows at constant values ​​of the capacitances and a fixed switching frequency of electronic switches, control the pole frequency by changing the resistance ratio of additional resistors. Computer simulation of the developed circuit was performed in the Micro-Cap environment. It has been established that the DAF has a transmission coefficient close to minus one at very low frequencies and a transmission coefficient close to zero at higher frequencies.

Herein, we present the design technique of a resonant rectifier for piezoelectric (PE) energy harvesting. We propose two diode equivalents to reduce the voltage drop in the rectifier operation, a minuscule-drop-diode equivalent (MDDE) and a low-drop-diode equivalent (LDDE). The diode equivalents are embedded in resonant rectifier integrated circuits (ICs), which use symmetric bias-flip to reduce the power wasted for charging and discharging the internal capacitance of a PE transducer. The self-startup function is supported by synchronously generating control pulses for the bias-flip from the PE transducer. Two resonant rectifier ICs, using both MDDE and LDDE, are fabricated in a 0.18 μm CMOS process and their performances are characterized under external and self-power conditions. Under the external-power condition, the rectifier using LDDE delivers an output power POUT of 564 μW and a rectifier output voltage VRECT of 3.36 V with a power conversion efficiency (PCE) of 90.1%. Under self-power conditions, the rectifier using MDDE delivers a POUT of 288 μW and a VRECT of 2.4 V with a corresponding PCE of 74.6%. The result shows that the power extraction capability of the proposed rectifier is 5.9 and 3.0 times higher than that of a conventional full-bridge rectifier.

In order to overcome the limitation of the traditional adaptive Unscented Kalman Filtering (UKF) algorithm in noise covariance estimation for statement and measurement, we propose a hybrid adaptive UKF algorithm based on combining Maximum a posteriori (MAP) criterion and Maximum likelihood (ML) criterion, in this paper. First, to prevent the actual noise covariance deviating from the true value which can lead to the state estimation error and arouse the filtering divergence, a real-time covariance matrices estimation algorithm based on hybrid MAP and ML is proposed for obtaining the statement and measurement noises covariance, respectively; and then, a balance equation the two kinds of covariance matrix is structured in this proposed to minimize the statement estimation error. Compared with the UFK based MAP and based ML, the proposed algorithm provides better convergence and stability.

Dried blood spot (DBS) testing on confetti is one of the most common methods used to collect and extract DNA from field samples for molecular epidemiology of malaria studies. Here, we investigated whether ethanol or other solutions used to clean scissors are a source of sample contamination. DBS were prepared from 3 drops of blood from two Plasmodium falciparum cultures spotted on confetti, and 3 solutions (water, ethanol and DNase) were used to clean scissors between spots during DNA extraction. For each cleaning solution, two blank confetti were used as negative controls. Samples were analyzed by PCR-based genotyping of merozoite surface proteins 1 & 2 (msp-1 and msp-2), and P. falciparum chloroquine resistance transporter (Pfcrt). A total of 15 samples were analyzed. Based on msp-1 and msp-2 amplification, P. falciparum was detected on blank confetti when scissors were washed with ethanol. Based on Pfcrt amplification, DNA of P. falciparum was detected on blank confetti when scissors were cleaned with ethanol or water. No P. falciparum genes were detected on blank confetti when scissors were cleaned with DNase. Scissors cleaned with DNase prevented cross-contamination between samples during processing of dried blood spots, whereas ethanol (which is commonly used) fails to avert cross-contamination.

A power factor correction (PFC) rectifier is compulsory for any electronic circuitry connected to the electrical grid. The majority of PFCs that are utilized are based on a step-up converter that supplies high DC voltage at its output terminal. Electric vehicle battery voltage varies from a few hundred to almost a thousand volts. Thus, an additional conversion step is obligatory when designing an all-brand universal charger. This paper presents a new type of front-end versatile step up / down three voltage level PFC. The rectifier can operate in continuous conduction mode or discontinuous conduction mode. First, the rectifier’s principle of operation is described, and then an innovative rectifier is analyzed for continuous and discontinuous conduction modes. Finally, the proposed theory is experimentally validated in a multiplier-less dual loop mode at discontinuous conduction modes. It was shown that although there is no multiplier use in the control circuitry, the power factor is near unity. It was revealed that the rectifier could swing the output voltage from 50 V to 900 V while the input voltage was 230 Vrms. The innovative topology suits any standard PFC rectifier, three-level voltage supplement, and dual-stage low-voltage power supply.

In this paper the one-to-one correspondences and equivalences between ideals, primals, filters and grills are introduced. It is shown the local functions and the topological spaces induced by them are the same. From this point of view, the topological properties with respect to one topology can be derived from topological properties valid in the corresponding topology.

This paper proposes a novel micro-grid structure, which can operate fully-autonomously with inherent seamless switching. It can operate independently in both grid-connected and islanded mode as a self-governed entity without relying on the utility grid. An AC/DC/AC converter is employed as the interface between the micro-grid and the utility grid, which enables the two entities to have different voltages in grid-connected mode. Seamless switching between operation modes can be achieved naturally. The micro-grid is regulated to exchange predefined amount of power with the utility grid in grid-connected mode. This will benefit the power dispatching algorithm of the power system. The predefined power is estimated based on power forecasting of local renewable generations and loads with consideration of the Sate of Charge (SOC) of the battery, and is updated and broadcasted every certain period. A small scale AC micro-grid with a rotating generator, battery storage and solar arrays etc. is built for investigation. Matlab/Simulink results are provided to validate the robustness and flexibility of proposed micro-grid and its operation strategy.

The wave packet consisting of two harmonic plane waves with the same frequencies, but with different wave vectors is considered. The dispersion relation of a packet is structurally similar to the dispersion relation of a relativistic particle with a nonzero rest mass. The possibility of controlling the group velocity of a quasi-monochromatic wave packet by varying the angle between the wave vectors of its constituent waves is discussed.

A time-sequential working, spatially multiplexed autostereoscopic 3D display design consisting of a fast switchable RGB-color filter array is presented. The wavelength-selective filter barrier emits the light from a display over a larger active area than common autostereoscopic barrier displays. An optical modelling of wavelength-selective barriers has been used for instance to calculate the light ray distribution properties of that arrangement. To find well working display designs, automated searches by simulation and computational evaluation has been proceeded. Wavelength-selective filter barrier arrangements exhibit characteristics different from common barrier displays with similar barrier pitch and ascent. In particular, these constructions show strong angular luminance dependency under barrier inclination specified by correspondent slant angle. In time-sequential implementation it is important to avoid that quick eye or eyelid movement lead to visible color artifacts. In the millisecond regime tunable liquid crystal Fabry-Pérot color filters for the colors red, green and blue are presented. They consist of a sub-micrometer thick nematic layer sandwiched between dielectric mirrors and ITO-electrodes. These cells shall switch narrow-banding light of red, green or blue. An array for a glasses-free 3D display has to be equipped with several thousand switchable filter elements having different color apertures. The newly introduced design is usable as a multi user display as well as a single user system with user adaptive control.

High-precision ground point cloud data has a wide range of applications in various fields, and the separation of ground points from non-ground points is a crucial preprocessing step. Therefore, designing an efficient, accurate, and stable ground extraction algorithm is of great significance for improving the processing efficiency and analysis accuracy of point cloud data. The study area in this article was a Park in Guilin, Guangxi, China. The point cloud was obtained by utilizing the UAV platform. In order to improve the stability and accuracy of the Filter algorithm, this article proposed a triangular grid filter based on Slope Filter, found violation points by the spatial position relationship within each point in the triangulation network, improved KD-Tree-Based Euclidean Clustering, and applied it to the non-ground points extraction, this method has good accuracy, stability and achieves good results in separating ground points from non-ground points. At first, using Slope Filter to remove some non-ground points, to reduce the error of taking ground points as non-ground points; Secondly, established a triangular grid based on the triangular relationship between each point, the violation-triangle can determin through the grid, and then the corresponding violation points were found in the violation-triangle; Thirdly, according to the three-point collinear method to extract the regular points, used these points to extract the regular landmarks by KD-Tree-Based Euclidean Clustering and Convex Hull Algorithm; Finally, removed disperse points and irregular landmarks by Clustering Algorithm. In order to confirm the superiority of this algorithm, this article compared the filter effects of various algorithms on the study area and filtered the 15 sample data provided by ISPRS, and obtained an average error of 3. 46%. The results showed that the algorithm in this article have a high processing efficiency and accuracy, which can greatly improve the processing efficiency of point cloud data in practical applications.

The state detection of power cable is very important to ensure the reliability of power supply. Traditional sensors are mostly based on electric field detection, the operation is complex, and its efficiency needs to be improved. This paper optimizes the design and development of the magnetic field detection sensor for AC power cables. Firstly, through the establishment of the magnetic field sensor model, it is determined that permalloy is the material of the magnetic core, the optimal aspect ratio of the magnetic core is 20, and the ratio of coil length to core length is 0.3. Secondly, the coil simulation model is established, and it is determined that the optimal number of turns of the coil is 11000 turns, the diameter of the enamelled copper wire is 0.08mm, and the equivalent magnetic field noise of the sensor is 0.06pT. Finally, the amplifying circuit based on negative magnetic flux feedback is designed and the sensor is assembled, and the experimental circuit is built for sensitivity test. the results show that the sensitivity of the magnetic field sensor is 327.6mV/μT. The sensor designed in this paper has the advantages of small size, high sensitivity, easy to carry and high reliability.

Purpose: To report the early clinical outcomes of combining intensity‐modulated radiation therapy (IMRT) and intensity‐modulated proton therapy (IMPT) in comparison with IMRT alone in treating the oropharynx cancer (OPC) patients. Materials and Methods: The medical records of 148 OPC patients were retrospectively reviewed, who underwent definitive radiotherapy (RT) with concurrent systemic therapy, from January 2016 till December 2019 at Samsung Medical Center. During the 5.5 weeks’ RT course, the initial 16 (or 18) fractions were delivered by IMRT in all patients, and the subsequent 12 (or 10) fractions were either by IMRT in 81 patients (IMRT only) or by IMPT in 67 (IMRT/IMPT combination), respectively, based on comparison of adaptive re-plan profiles and availability of equipment. Propensity‐score matching (PSM) was done on 76 patients (38 from each group) for comparative analyses. Results: With the median follow‐up of 24.7 months, there was no significant difference in overall survival and progression free survival between groups, both before and after PSM. Before PSM, IMRT/IMPT combination group experienced grade ≥3 acute toxicities less frequently: mucositis in 37.0% and 13.4% (p<0.001); and analgesic quantification algorithm (AQA) in 37.0% and 19.4% (p=0.019), respectively. The same trends were observed after PSM: mucositis in 39.5% and 15.8% (p=0.021); and AQA in 47.4% and 21.1% (p=0.016), respectively. In multivariate logistic regression, grade ≥3 mucositis was significantly less frequent in IMRT/IMPT combination group, both before and after PSM (p=0.027 and 0.024, respectively). AQA score ≥3 was also less frequent in IMRT/IMPT combination group, both before and after PSM (p=0.085 and 0.018, respectively). Conclusions: In treating the OPC patients, with comparable early oncologic outcomes, more favorable acute toxicity profiles were achieved following IMRT/IMPT combination than IMRT alone.

To achieve a fast testing on barrier properties of organic coatings, immersion test, AC-DC-AC test, and coupled test of AC-DC-AC with hydrostatic pressure were conducted in seawater for a glass flake epoxy coating. Electrochemical impedance spectroscopy (EIS) was used to characterize the degradation processes of the coating during the tests, and the surface of the coating was analyzed using optical microscope, scanning electron microscope (SEM) and Fourier transform infrared spectrometer (FTIR). The results show that the periodically cathodic polarization coupled with high hydrostatic pressure can accelerate the degradation of the coating by facilitating the diffusion and uptake of electrolyte and the delamination of the coating. The coupled test method has the largest acceleration due to the synergetic effect of AC-DC-AC and hydrostatic pressure.

The formation of the required AC voltage level is currently one of the most important problems. An unstable voltage level can lead to the failure of domestic and industrial equipment, also to the appearance of a lighting equipment flicker effect, which can adversely affect the operating mode. In this regard, the development of AC voltage regulators that perform the function of stabilizers has become relevant. In turn, new topologies should be energy efficient and reliable, this can be achieved by reducing the number of semiconductor elements, which in turn will reduce losses and increase efficiency. In addition to voltage stabilization, AC voltage regulators have found application as soft-start devices for asynchronous motors, and have become competitors to frequency converters. The power level can vary from units to tens of kilowatts where such devices can be used. This paper provides a review of AC voltage regulators, which can be used both as soft starters and AC voltage stabilizers. The analysis of the circuits was carried out and the efficiency was evaluated through their total harmonic distortions (THD), power factor and efficiency coefficient. Experiments were also performed for a number of circuits, where their operating modes were evaluated. Eventually, all circuits were divided into full number of switches with two or more AC switches per phase, with a reduced number of switches, where one AC switch per phase and with low number of switches – with one complementary pair of AC switches for all three phases.

This paper focus on the modeling and time-domain analyzing method of piecewise-smooth fractional-order circuit systems. Firstly, an analytical framework is constructed based on a generalized piecewise-smooth two-port impedance network model, which takes the topological characteristics of Dickson type switched-capacitor converters (SCCs) as examples, and considers the fractional-order characteristics of class-2 X7R ceramic capacitors, which are widely used in SCCs. Secondly, the time-domain analyzing method for such a piecewise-smooth fractional-order circuit system is developed, numerical solutions are obtained, and the influence of the fractional-order capacitor on the power conversion efficiency of the system are revealed. Finally, in order to validate the analysis, both numerical simulation and experiments are provided in the work, the results of which confirm that, the proposed fractional-order analytical framework can capture the power loss mechanism of piecewise-smooth fractional-order circuit systems more effectively than the traditional integer-order based approach, thus benefiting the design of circuit systems.

At the nanoscale, metals exhibit special electrochemical and optical properties, which play an important role in nanobiosensing. In particular, the surface plasmon resonance based on precious metal nanoparticles, as a kind of tag free biosensor technology, has brought high sensitivity, high reliability and convenient operation to the sensor detection. By applying an electrochemical excitation signal on the nano plasma device, modulating its surface electron density and realizing electrochemical coupling surface plasmon resonance, it can effectively complete the joint transmission of electrical signals and optical signals, increase the resonance shift of the spectrum, and further improve the sensitivity of the designed biosensor. In addition, smartphone is playing an increasingly important role in portable mobile sensor detection systems. These systems typically connect sensing devices to smartphone to perceive different types of information, from optical signals to electrochemical signals, providing ideas for the portability and low-cost design of these sensing systems. Among them, electrochemiluminescence, as a special electrochemical coupled optical technology, has good application prospects in mobile sensing detection due to its strong anti-interference ability, which is not affected by background light. In this review, the surface plasmon resonance is introduced from nanoparticles, and its response process is analyzed theoretically. Then, the mechanism and sensing application of electrochemistry coupled surface plasmon resonance and electrochemiluminescence are emphatically introduced. Finally, it extends to the related research of electrochemical coupled optical sensing on mobile detection platforms.

A temperature-modulated pyroelectricity measurement system for a small single crystal is developed and applied to standard sample measurements performed on a thin single crystal of lithium niobate. The modulation measurement is based on the AC technique, in which the temperature of the sample is periodically oscillated, and the synchronized pyroelectric signal is extracted using a lock-in amplifier. Temperature modulation is applied by irradiating periodic light on the sample placed in the heat exchange gas. To apply this technique to the transparent reference sample, a commercially available black resin is coated on the sample’s surface to absorb the light energy and transmits it to the specimen. The experimental results are analyzed using a two-layer heat transfer model to verify the effect of the light-absorbing layer as well as the non-contact temperature modulation system.

State-of-the-art dielectrophoretic (DEP) separation techniques provide unique properties to separate particles from a liquid or particles with different properties such as material, morphology or size from each other. However, such separators do not operate at throughput that is sufficient for a vast fraction of separation tasks. The reason for this limitation is that, in order to move particles by dielectrophoresis, high electric field gradients to drive the separation are required. Conventionally, those gradients are generated by electrode microstructures that limit the maximum channel size. Here, we investigate DEP filtration, a technique that uses open porous microstructures instead of microfluidic devices to easily increase the filter cross section and therefore also the processable throughput by several orders of magnitude. Previously, we already separated baker’s yeast by DEP filtration in open porous ceramic structures. Now, we give a more elaborate experimental study about DEP filtration in these open porous structures and separate model particles, that are an order of magnitude smaller (500 nm, polystyrene), from aqueous suspensions. Almost 100% separation at flow rates of up to 9 mL min^-1 was achieved while the majority of the trapped particles could be recovered. We show how particle separation depends on key parameters (voltage, throughput, filter structure size). Further, we work towards selective particle separation and show that particle separation is very dependent on the particle polarizability: This creates the possibility to adjust selectivity by changing the electrical conductivity of the suspension around that of the particle. This study highlights the unique qualities of dielectrophoretic filtration enabling switchable, selective, and scalable particle separation to solve existing problems such as cell separation or precious metal recovery.

Due to the increased use of memristors, and its many applications, the use of emulators has grown in parallel to avoid some of the difficulties presented by real devices such as variability and reliability. In this paper, we present a memristive emulator designed using a Switched Capacitor (SC), this is, an analog component/ block and a control part or block implemented using stochastic computing (SCo) and therefore fully digital. Our design is thus a mixed signal circuit. Memristor equations are implemented using stochastic computing to generate the control signals necessary to work with the controllable resistor implemented as switched capacitor.

The growing attention for plug-in electric vehicles, and the associated high-performance demands, have initiated a development trend towards highly efficient and compact on-board battery chargers. These isolated ac-dc converters are most commonly realized using two conversion stages, combining a non-isolated power factor correction (PFC) rectifier with an isolated dc-dc converter. This, however, involves two loss stages and a relatively high component count, limiting the achievable efficiency and power density and resulting in high costs. In this paper a single-stage converter approach is analyzed to realize a single-phase ac-dc converter, combining all functionalities into one conversion stage and thus enabling a cost-effective efficiency and power density increase. The converter topology consists of a quasi-lossless synchronous rectifier followed by an isolated dual active bridge (DAB) dc-dc converter, putting a small filter capacitor in between. To show the performance potential of this bidirectional, isolated ac-dc converter, a comprehensive design procedure and multi-objective optimization with respect to efficiency and power density is presented, using detailed loss and volume models. The models and procedures are verified by a 3.7 kW hardware demonstrator, interfacing a 400 V dc-bus with the single-phase 230 V, 50 Hz utility grid. Measurement results indicate a state-of-the-art efficiency of 96.1% and power density of 2.2 kW/dm³, confirming the competitiveness of the investigated single-stage DAB ac-dc converter.

The past two decades has seen a growing demand for high-power, high-voltage utility scale inverters mostly fueled by the integration of large solar PV and wind farms. Multilevel inverters have emerged as the industry choice for these megawatt range inverters because their reduced voltage stress, capable of generating an almost sinusoidal voltage, in-built redundancy, among others. This paper present a new Switched-Source Multilevel Inverter (SS MLI) architecture. The new inverter show superior over existing topologies. It has reduced voltage stress on the semiconductor, uses less number of switches –reduced size/weight/cost and increased efficiency. The new SSMLI is comprised of two voltage sources (V₁, V₂) and 6 switches. It is capable of generating 5-level output voltage in symmetric modes (i.e., V₁ = V₂), and 7-level output voltage in asymmetric modes (i.e., V₁ ≠ V₂). To demonstrate the validity of the proposed inverter, simulations results using MATLAB^® /Simulink^® for 5- and 7-level output voltages are presented . The simulations are also verified experimentally using a laboratory prototype.

In 1935 Einstein, Podolsky, and Rosen (EPR) studied general entangled states in the two photon experiment and pointed out the contradiction between local realism and the completeness of quantum mechanism. Most of the EPR experiments in recent years are based on the detection of polarization correlations of optical photons between spatially separated photon channels, some of which are split and directed to two spatially separated Michelson interferometers. Later, the two arms of Michelson interferometers are replaced by dual-channel Fabry-Perot (F-P) interferometry enabling precise analysis of the energy-time entanglement between a pair of photons. On the other hand, F-P type detectors on gravitational radiation have caught dozens of gravitational wave (GW) events successfully. This paper proposes a combined experiment of EPR and GW, exhibiting whether the coincident rate of EPR is modulated by GW induced change of cavity length or not. Such an experiment could test the coupling of quantum mechanics and general relativity for the first time, and be a useful tool to explore the nature of quantum gravity.

Non-Linear Simulation by Harmonic Balance Techniques of Load Modulated Power Amplifier Driven by Random Modulated Signals. Comparison with measured results.

Recent findings support an association between childhood maltreatment and the presence of elevated psychopathic traits in adulthood. Using a community sample recruited online (N = 210), we sought to (1) confirm the relationship between childhood traumas and psychopathic traits, and (2) investigate the role of parenting styles in psychopathic traits. Consistent with our predictions, we found an association between all types of childhood traumas and disinhibition. Age and gender moderated the relations between psychopathic traits and childhood maltreatments. Parental rejection and overprotection were positively correlated with the presence of psychopathic traits, while parental emotional warmth was negative correlated. Although our results converge with previous findings, the strength of the correlations observed was not as compelling as in research on undergraduate students. We discuss the numerous interpretations for our findings, and highlight the limitations of research in the field of psychopathy and childhood trauma in the general population.

The matrix converter converts the input line voltage into a variable voltage with an unrestricted output frequency without using an intermediate circuit, dc link circuit. A pure sine in and pure sine out is the unique feature of the matrix converter. This research paper also analyzes the basic operating principle and the simulation modeling of the direct matrix converter, which is controlled by the Space Vector Pulse Width Modulation technique by using the software which is known as MATLAB/Simulink. The most desirable features in the power frequency changes can be fulfilled by using the matrix converters, and this is the reason for the tremendous interest in the topology. Since the power electronic circuits which is known as the motor drives are used to operate the AC motors at the frequencies other than that of the supply.

The advancement of technology and the availability of specialized digital signal processing chips have made digital filter design and implementation more feasible in a variety of fields, including biomedical engineering. This paper makes two key contributions. First, it uses a genetic algorithm to optimize the coefficients of Finite Impulse Response (FIR) filters. Second, it conducts a case study on using genetic algorithms to optimize FIR filters for electrocardiogram (ECG) biomedical signal noise removal. The goal of the proposed filter design approach is to achieve the desired signal bandwidth while minimizing the side lobe level and eliminating unwanted signals using a genetic algorithm. The results of the comprehensive analysis of the impact of different genetic operators show that the genetic algorithm-based filter outperforms conventional filter designs.

This paper presents sufficient conditions for almost global stability of nonlinear switched systems consisting of both stable and unstable subsystems. Techniques from the stability analysis of switched systems have been combined with the multiple Lyapunov density approach - recently proposed by the authors for the almost global stability of nonlinear switched systems composed of stable subsystems. By using slow switching for stable subsystems and fast switching for unstable subsystems lower and upper bounds for mode-dependent average dwell times are obtained. In addition to that, by allowing each subsystem to perform slow switching and using some restrictions on total operation time of unstable subsystems and stable subsystems, we have obtained a lower bound for an average dwell time.

The light response and resistance switching behavior in BaTiO3 (BTO) films are studied for a symmetric Pt/BTO/Pt structure. The resistance of films as a function of time with and without ultraviolet light has been studied. Furthermore, resistance switching behavior was clearly observed based on the application of 365 nm wavelength ultraviolet light. Consequently, the polarities of resistance switching can be controlled by ultraviolet light when the energy is larger than the band excitation energy. It is proposed that the polarity of the resistance switching is dictated by the competition of the ferroelectricity and oxygen vacancy migration. This provides a new mechanism for modulating the state of ferroelectric resistive memory devices.

This paper investigates a distributed, coordinated motion control network based on multiple direct-drive, linear switched reluctance machines (LSRMs). A hierarchical, two-level synchronization control strategy is proposed for the four LSRMs based motion control network. The high-level, reference signals agreement algorithm is first employed to correct the asynchronous behaviors of the position commands. Then, the low-level tracking synchronization method is applied for the collaborative position control of the four LSRMs. The proposed two-level, fault-tolerant control strategy eliminates the asynchrony of the reference signals and it also guarantees the coordinated tracking control performance of the four LSRMs. Experimental results demonstrate that effective coordinated tracking control can be ensured, based on successful agreement of reference signals and an absolute tracking error falling within 2 mm can be achieved.

Triangular resonators re-shaped with the Sierpinski geometry and U-shaped resonators have been designed, linking them with single-pole-double-through (SPDT) RF MEMS switches to provide frequency tuning for potential applications in the K-Band. Prototypes of band-stop narrowband filters working around 20 GHz and 26 GHz, interesting for RADAR and satellite communications, have been studied in coplanar waveguide (CPW) configuration, and the tuning was obtained by switching between two paths of the devices loaded with different resonators. As a result, dual-band operation or fine-tuning can be obtained depending on the choice of the resonator, acting as a building block. The studied filters belong to the more general group of devices inspired by the metamaterial design.

Transcutaneous electrical stimulation of the spinal cord is used to restore locomotion and body weight support in patients with severe motor disorders. We studied effects of this non-invasive stimulation on postural control in healthy subjects. Stimulation at the L1-L2 vertebrae was performed to activate the extensor muscles of the lower limbs. Because postural regulation depends on the cognitive style, the effects of the stimulation were analyzed separately in field-dependent (FD) and field-independent (FI) participants. During the study young adults (N=16, half FD and half FI participants, all right dominant leg) stood on a force platform in a soundproof chamber with their eyes closed. Stimulation was applied in the midline between the L1-L2 vertebrae or over the left or right dorsal roots of the spinal cord; under control condition there was no stimulation. Stimulation destabilized posture in healthy subjects, whereas patients with movement disorders usually showed an improvement in postural control. In FD participants, left dorsal root and midline stimulation increased several postural parameters by up to 30%. Dorsal root stimulation on the side of the supporting leg reduced postural control, while stimulation on the side of the dominant leg did not. No significant changes were observed in the FI participants.

Visual Evoked Potentials (VEPs) are used in clinical applications in ophthalmology, neurology and extensively in brain computer interface (BCI) research. BCI literature covers steady state VEP (SSVEP) and code modulated VEP (c-VEP) BCIs along with sophisticated methods to improve information transfer rates (ITR). There is a gap of knowledge regarding the VEP adaptation dynamics, physiological generation mechanisms and relation with BCI performance. A simple dual display VEP switch was developed to test signatures elicited by non-isochronic, non-singular, low jitter stimuli at the rates of 10, 32, 50 and 70 reversals per second (rps). Non-isochronic, low-jitter stimulation elicits Quasi-Steady-State VEPs (QSS-VEPs) that are utilized for simultaneous generation of transient VEP and QSS-VEP. QSS-VEP is a special case of c-VEPs and it is assumed that it shares the similar generators of the SSVEPs. Eight subjects were recorded and the performance of the overall system was analyzed by means of Receiver Operating Characteristic (ROC) curves, accuracy plots and ITRs. In summary QSS-VEPs performed better than transient VEPs. It was found that in general 32rps stimulation had the highest ROC area, accuracy and ITRs in general. To investigate the reasons behind this, adaptation dynamics of transient VEPs and QSS-VEPs at all four rates were analyzed and speculated. Moreover, QSS-VEPs were found to lead to higher accuracy by the template matching compared to SSVEPs at 10rps and 32rps.

Neural-objective and image optimization approaches for drilling fluid rheology automation are crucial for drilling engineering optimization. A myriad of intelligent computational models are employed to predict and monitor the parameters of mud rheology and filter cake permeability posture using an artificial neural network feedforward (ANN-FF) function, a non-ANN-FF function, an image processing tool, and a model optimization tool. 498 datasets of synthetic-based mud (SBM) flat rheology from a drilling mud laboratory at Nazarbayev University were imported into a user-friendly MATLAB application using image processing and nftool. Apart from the Google TensorFlow Sequential API DNN architecture used, a Levenberg-Marquardt training algorithm with input sigmoid hidden neurons 10, 12, and 18 coupled with a linear output layer was also used to predict the SBM flow index. OBM and SBM filter cakes were processed for void spaces; however, a model study was extrapolated to maximize filtration volume Vf. The study’s findings show that the ANN-FF model employed for rheological property monitoring and prediction had higher steady and exponential levels of accuracy and a correlation coefficient of 0.96-0.99. More so, SBM and OBM image processing presented an area of void spaces of 1790M2 and 1739M2, respectively. The porosity and permeability postures of both SBM and OBM resulted in a significant void space capable of maximizing the flow index. In addition, the single-objective modelling based on a genetic algorithm did validate the experimental rheological data for flow index or filtration volume Vf optimization; the study resulted in the finding that the constrained physics-informed objective function hindered maximizing oil recovery and instead predicted possible formation damage. It is empirical to note that automating flow predictions with neural, objective, and image functions has presented an alternative novel method for non-programmers using MATLAB and Google Colabs that is capable of enhancing mud rheological parameters, drilling efficiency, and hydrocarbon recovery.

Guided image filter implicitly balances noise and details based on local variance, achieving noise suppression while preserving prominent edges. However, we have observed limitations in using variance to distinguish between noise and image details, resulting in the suppression of fine structures alongside noise. Furthermore, the goal of enhancing image details, which is crucial in image filtering, has not been adequately addressed in edge-preserving filter design. In this paper, we approach image filtering as a problem of spectral energy reconfiguration, where the gain of each spectral band is adaptively regulated to achieve simultaneous noise suppression and detail enhancement. Instead of relying on variance, we employ a linear noise estimator to obtain the Signal-to-Noise Ratio (SNR) measurement necessary for dynamic gain regulation. Similar to the guided image filter, we determine the filter coefficients by solving the closed-form solution of the optimizer. We demonstrate that the proposed extended guided filter effectively integrates information from multiple spectral bands locally, allowing for the joint enhancement of meaningful details while simultaneously smoothing noise.

Face detection is an important problem in computer vision because it enables a wide range of applications, such as facial recognition and analysis of human behavior. The problem is challenging because of the large variations in facial appearance across different individuals and different lighting and pose conditions. One way to detect faces is to utilize a highly advanced face detection method, such as RetinaFace, which uses deep learning techniques to achieve high accuracy in various datasets. However, even the best face detectors can produce false positives, which can lead to incorrect or unreliable results. In this paper, we propose a method for reducing false positives in face detection by using information from a depth map. A depth map is a two-dimensional representation of the distance of objects in an image from the camera. By using the depth information, the proposed method is able to better differentiate between true faces and false positives. The authors evaluate their method on a combined dataset of 549 images, containing a total of 614 upright frontal faces. The results show that the proposed method is able to significantly reduce the number of false positives without sacrificing the overall detection rate. This indicates that the use of depth information can be a useful tool for improving face detection performance.

Diarylethene is a prototypical molecular switch that can be reversibly photoisomerized between its open and closed forms. Ligands bpy-DAE-bpy, consisting of a phenyl-diarylethene-phenyl (DAE) central core and bipyridine (bpy) terminal substituents, are able to self-organize. They are investigated by scanning tunneling microscopy at the solid-liquid interface. Upon light irradiation, cooperative photochromic switching of the ligands is recognized down to the sub-molecular level. The closed isomers show different electron density of states (DOS) contrasts, attributed to the HOMO or LUMO molecular orbitals observed. More importantly, the LUMO images show remarkable differences between the open and closed isomers, attributed to combined topographic and electronic contrasts mainly on the DAE moieties. The electronic contrasts from multiple HOMO or LUMO distributions, combined with topographic distortion of the open or closed DAE, are interpreted by density functional theory (DFT) calculations.

Increased definite power, reduced cost, and dynamic construction are the important features required by electric motors for various applications. One such motor accommodating all the requisites mentioned above is Switched reluctance. Applications pertaining to small, commercial, and EV find Switched reluctance machine as a developing competitor to the conventional induction and permanent magnet motors. Though SRMS contribute a considerable number of advantages over induction motors and permanent magnet motors, the primary disadvantages pertaining to SRMs are the torque ripple, especially at high-speed operation, and the resulting acoustic noise. These disadvantages may not always be detrimental to the systems in entirely all cases, but depending on the application to be employed, torque ripple and acoustic noise form are detrimental to the system. This paper reviews the technology status and recent trends in the minimization of torque ripples switched reluctance machines.

In this paper, we address the problem of stabilization of switched linear systems. The idea is to look for a state feedback control law using evolutionary algorithms (EA) in order to assure the stability of the switched linear systems under control constraints. In some cases when states are not available and only outputs are measurable, the previous method is applied to design an output feedback controller which stabilizes the system. Both stabilizing controllers are developed using deferential evolution and genetic algorithm. Two numerical examples illustrate our proposed theory and point out the effectiveness of our proposed approaches.

One of the notable temporal properties of dynamical systems is that a set of initial states leads the solutions to reach desired states avoiding a predetermined unsafe set.This property, that we call safe reachability has been studied in literature for autonomous systems using Barrier functionand Barrier densities [1]. In this paper, we generalize a sufficient condition for safe reachability of autonomous systemto switched systems under arbitrary switching signals. The condition relies upon the existence of a common Barrier density function for each subsystem. We apply the condition using the sum of squares method together with Putinar Positivstellensatz.

For a dynamical system, it is known that the existence of a Lyapunov density implies almost global stability of an equilibrium. It is then natural to ask whether the existence of a common Lyapunov density for a nonlinear switched system implies almost global stability, in the same way as a common Lyapunov function implies global stability for nonlinear switched systems. In this work, the answer to this question is shown to be affirmative as long as switchings satisfy a dwell-time constraint with an arbitrarily small dwell time. As a straightforward extension of this result, we employ multiple Lyapunov densities in analogy with the role of multiple Lyapunov functions for the global stability of switched systems. This gives rise to a minimum dwell time estimate to ensure almost global stability of nonlinear switched systems, when a common Lyapunov density does not exist. The results obtained for continuous-time switched systems are based on some sufficient conditions for the almost global stability of discrete-time non-autonomous systems. These conditions are obtained using the duality between Frobenius-Perron operator and Koopman operator.

We investigate numerically the interactions of in-phase Airy beams modulated by a fundamental Gaussian beam and fourth-order diffraction in Kerr nonlinear media. Directly numerical simulations show that normal (anomalous) fourth-order diffractions and in-phase (out-of-phase) Gaussian beam affect the interactions of solitons generated from Airy beams in unique manners. Different from previous results that interactions between in-phase (out-of-phase) conventional beams are always attractive (repulsive), many anomalous interactions of Airy beams are obtained. Stable bound states of breathing Airy soliton pairs can be formed with the help of fourth-order diffraction and fundamental Gaussian beam.

Time-modulated sparse circular array (TMSCA) with elements uniformly excited is designed and synthesized in this paper. By utilizing rotationally symmetric structure, the array geometry and the time modulation of the TMSCA is presented, and the radiation patterns in frequency domain are formulated. In order to achieve the desired radiation pattern at the operating frequency and suppress the sideband radiation, the synthesis problem is established and solved by the proposed harmony search-convex programming (HS-CP) algorithm in two dependent optimizations. Two designs are presented, and the numerical results indicate that the TMSCA with rotationally symmetric structure has the advantages of designing time-modulated sparse arrays with superior performance.

The dynamic response of a Bell-and-Bloom magnetometer to a parallel (to the bias field) time-dependent field is modelled beyond the commonly assumed quasi-static regime. The results unveil features that are related to the parametric nature of the considered system. It is shown that a for low-amplitude time-dependent field different operating conditions are possible and that, beside the commonly reported low-pass-filter behaviour, a band-pass response emerges. Moreover, we numerically show that for larger field amplitude the system, due to its parametric nature, has a kind of ``non-linear'' response.

We demonstrate that the conductivity of graphene on thin-film polymer substrates can be accurately determined by reflection-mode air-plasma-based THz time-domain spectroscopy (THz-TDS). The phase uncertainty issue associated with reflection measurements is discussed, and our implementation is validated by convincing agreement with graphene electrical properties extracted from more conventional transmission-mode measurements. Both the reflection and transmission THz-TDS measurements reveal strong nonlinear and instantaneous conductivity depletion across an ultra-broad bandwidth under relatively high incident THz electrical field strengths.

The evolution in semiconducting devices has introduced flexible control on a system but it has also penetrated harmonics in the grid, which results in extra electrical stress and load. Limiting the presence of harmonics in the grid and low power factor maintained by consumers has become of utmost priority to the power system analyst. Hence, the need for Active Filter emerges. Here, a real-time simulation, in dSPACE- Targetlink, of shunt harmonics active filter is propounded. The possible basic control strategy used in the simulation is ”Instantaneous Power Theory”. Control logic of two features of Active Filter viz., Global Harmonics Elimination, and Reactive Power Compensation are produced in the paper. The results obtained in ”Software In Loop Mode” of dSPACE are discussed and verified in detail. The richness of the code generated by the dSPACE- Target link can be reasoned by observing the results which are well aligned with the industrial standards regarding the harmonics.

The solid-state technique was utilized to make a single phase of delafossite CuAlO2, along with 1%, 2%, 3% and 4% silver doped CuAlO2 samples in this study. The content of the samples was investigated using energy dispersive X-ray spectroscopy (EDS) equipped with a field emission scanning electron microscope (FE-SEM). The polycrystalline nature of all of the analyzed cases was confirmed by structural analyses utilizing an X-ray diffraction (XRD) pattern with a simple typical peak of CAO rhombohedral phase. Raman, FT-IR and UV–Vis spectroscopy were used to study the structural, and optical energy band gap (Eg) of Ag doped CuAlO2 nanoparticles. The Kubelka–Munk function was used to calculate the optical band gap of ACAO alloys using diffuse reflectance spectra, and it altered as the Ag ion concentration increased. A. c. impedance spectroscopy was used to investigate the dielectric characteristics of Ag doped CuAlO2 nanoparticles.

This paper discusses about control of the linear switched reluctance machines (LSRMs) network for the zero phase-difference tracking to a sinusoidal reference. The dynamics of each LSRM is derived by online system identification and modeled as a second-order linear system. Accordingly, based on the coupled harmonic oscillators synchronization manner, a distributed control is proposed to synchronize each LSRM state to a virtual LSRM node representing the external sinusoidal reference for tracking it with zero phase-difference. Subsequently, a simulation scenario and an experimental platform with the identical parameter setup are designed to investigate the tracking performance of the LSRMs network constructed by the proposed distributed control. Finally, the simulation and experimental results verify the effectiveness of the proposed LSRMs network controller, and also prove that the coupled harmonic oscillators synchronization method can improve the synchronization tracking performance and precision.

In the context of cognitive radio, smart city and Internet-of-Things, the need of advanced radio spectrum monitoring becomes crucial. However, surveillance of a wide frequency band without using extremely expensive high sampling rates devices is a challenging task. The recent development of compressed sampling approaches offers a promising solution to these problems. In this context, the Modulated Wideband Converter (MWC), a blind sub-Nyquist sampling system, is probably the most realistic approach and was successfully validated in real-world conditions. The MWC can be realized with existing analog components and there exist calibration methods which are able to integrate the imperfections of the mixers, filters and ADCs, hence allowing its use in real-world. The MWC underlying model is based on signal processing concepts such as filtering, modulation, Fourier series decomposition, oversampling and undersampling, spectrum aliasing, and so on, as well as in-flow data processing. In this paper we develop an MWC model which is entirely based on linear algebra, matrix theory and block processing. We show that this approach has many interests: straightforward translation of mathematical equations into simple and efficient software programming, suppression of some constraints of the initial model, and providing a basis for the development of an extremely fast system calibration method. With a typical MWC acquisition device we obtained a speed up of a factor greater than 20 of the calibration computation time, compared with a previous implementation.

Mast cells (MCs) play a crucial role during infections with Leishmania, that is transmitted through the bite of an infected sand fly that injects saliva together with the parasite. Sand fly saliva is a complex fluid that modulates the host immune response. In addition, hormonal factors modulate the host immune response, impacting the susceptibility to infections. Thus, to assess the impact of androgens and salivary proteins of sand fly vectors on the mast cell (MC) response to Leishmania infections, we infected orchiectomized male mice with the parasite in the presence or absence of sand fly salivary proteins and analyzed the inflammatory response of MCs. Our results showed a differential MC response to the parasite and to vector salivary proteins in mice deprived of gonadal hormones, as compared to sham-operated mice. Orchidectomy induced a different pattern of activation in MC of animals infected with Leishmania and vector-salivary proteins. Our results show that during Leishmania infection, androgens modulate the innate immunity response against the parasite and salivary proteins of the sand fly vector.

We present improvements in n-best rescoring of code-switched speech achieved by n-gram augmentation as well as optimised pretraining of long short-term memory (LSTM) language models with larger corpora of out-of-domain monolingual text. In addition, we consider the application of large pretrained transformer-based architectures. Our experimental evaluation is performed on an under-resourced corpus of code-switched speech comprising four bilingual code-switched sub-corpora, each containing a Bantu language (isiZulu, isiXhosa, Sesotho, or Setswana) and English. We find in our experiments that, by combining n-gram augmentation with the optimised pretraining strategy, speech recognition errors are reduced for each individual bilingual pair by 3.51% absolute on average over the four corpora. Importantly, we find that even speech recognition at language boundaries improves by 1.14% even though the additional data is monolingual. Utilising the augmented n-grams for lattice generation, we then contrast these improvements with those achieved after fine-tuning pretrained transformer-based models such as distilled GPT-2 and M-BERT. We find that, even though these language models have not been trained on any of our target languages, they can improve speech recognition performance even in zero-shot settings. After fine-tuning on in-domain data, these large architectures offer further improvements, achieving a 4.45% absolute decrease in overall speech recognition errors and a 3.52% improvement over language boundaries. Finally, a combination of the optimised LSTM and fine-tuned BERT models achieves a further gain of 0.47% absolute on average for three of the four language pairs compared to M-BERT. We conclude that the careful optimisation of the pretraining strategy used for neural network language models can offer worthwhile improvements in speech recognition accuracy even at language switches, and that much larger state-of-the-art architectures such as GPT-2 and M-BERT promise even further gains.

This work describes and compares the backpropagation algorithm with the Extended Kalman filter, a second-order training method which can be applied to the problem of learning neural network parameters and is known to converge in only a few iterations. The algorithms are compared with respect to their effectiveness and speed of convergence using simulated data for both, a regression and a classification task.

The inaccurate estimates of linear prediction coefficient (LPC) and noise variance introduce bias in Kalman filter (KF) gain and degrades speech enhancement performance. The existing methods proposed a tuning of the biased Kalman gain particularly in stationary noise condition. This paper introduces a tuning of the KF gain for speech enhancement in real-life noise conditions. First, we estimate noise from each noisy speech frame using a speech presence probability (SPP) method to compute the noise variance. Then construct a whitening filter (with its coefficients computed from the estimated noise) and employed to the noisy speech, yielding a pre-whitened speech, from where the speech LPC parameters are computed. Then construct KF with the estimated parameters, where the robustness metric offsets the bias in Kalman gain during speech absence to that of the sensitivity metric during speech presence to achieve better noise reduction. Where the noise variance and the speech model parameters are adopted as a speech activity detector. The reduced-biased Kalman gain enables the KF to minimize the noise effect significantly, yielding the enhanced speech. Objective and subjective scores on NOIZEUS corpus demonstrates that the enhanced speech produced by the proposed method exhibits higher quality and intelligibility than some benchmark methods.

A three-phase multilevel inverter (MLI) synthesized with 31-levels in the output voltage is used to provide ac supply to a three-phase, squirrel-cage induction motor. The gating angles required for thirty power switches in MLI are optimized by both Genetic Algorithm (GA) and Gray Wolf Op-timization (GWO). In the optimization technique, the optimal angles are determined by solving the trigonometric equations from the Fourier analysis for targeting minimum total harmonic distortion (THD) at the MLI output. Simulation model and experimental prototype are developed for performance analysis and validation. The results obtained demonstrate that the MLI is effec-tively able to produce 31-levels of three-phase ac output voltages with THD not exceeding 5% when loaded with a resistive load and a three-phase induction motor. The voltages and currents are measured and recorded for different loads and operating conditions, including the amount of energy consumed by the loads, as well as frequency analysis, which shows the absence of most of the triple harmonics that have a negative impact on the efficiency of the inverter.

Switched model predictive control (S-MPC) and recurrent neural network with long short-term memory (RNN-LSTM) are powerful control methods that have been extensively studied for energy management in microgrids (MGs). These methods are complementary in terms of constraint satisfaction, computational demand, adaptability, and comprehensibility, but typically one method is chosen over the other. The S-MPC method selects optimal models and control strategies dynamically based on the system’s operating mode and performance objectives. On the other hand, integration of auto-regressive (AR) with these powerful control methods improves prediction accuracy and system conditions’ adaptability. This paper compares the two approaches to control and proposes a novel algorithm called Switched Auto-regressive Neural Control (S-ANC) that combines their respective strengths. Using a control formulation equivalent to S-MPC and the same controller model for learning, the results indicate that pure RNN-LSTM cannot provide constraint satisfaction. The novel S-ANC algorithm can satisfy constraints and deliver comparable performance to MPC while enabling continuous learning. Results indicate that S-MPC optimization increases power flows within the MG, resulting in efficient utilization of energy resources. By merging the AR and LSTM, the model’s computational time decreased by nearly 47.2%. Also, this study evaluated our predictive model’s accuracy: (i) R-squared error is 0.951, indicating strong predictive ability, and (ii) mean absolute error (MAE) and mean square error (MSE) values of 0.571 indicate accurate predictions with minimal deviations from actual values.

This paper proposes a novel symmetrical active-switched coupled-inductor high-step-up DC/DC converter. A new active-switched coupled inductor is used to allow much higher voltage gain of the proposed converter. The symmetrical circuit structure of the proposed converter evenly divides large input currents and reduce input current ripple by operating in interleaved mode so power density is increased. The switches also have low voltage stress. The operating principle and design considerations for the converter topology are described. The proposed converter with an input voltage of 40 V, an output voltage of 400 V and an output of 1000 W at a switching frequency of 50 kHz is implemented. The simulations and experimental results are thus depicted to verify the theoretical analysis. The highest efficiency is 95.5% at 200 W measured by using a HIOKI 3390. Consequently, the proposed converter is suitable for renewable energy generation systems that require high power, high voltage gain and high efficiency.

A modular switched-capacitor (SC) DC-DC converter (MSCC) is introduced in this paper. It is designed to boost a low input voltage to a high voltage level and can be applied for photovoltaics and electric vehicles. This topology has high extensibility for high voltage gain output. The merits of the converters also lie in the fault tolerance operation and the voltage regulation with a minimum change in the duty ratio. Those features are built in when designing the modules and then integrating these into the DC-DC converter. Converter performance including voltage gain, voltage and current stress are focused and tested. The converter is modelled analytically, and its control algorithm is analyzed in detailed. Both simulation and experiment are carried out to verify the topology under normal operation and fault mode operation.

Exact sequential state estimation of orbiting objects in space can be found by predicting the state using Fokker Planck Kolmogorov Equation (FPKE) and measurement correction using Bayes’ conditional/posterior Probability Density Function (PDF). Posterior PDF can be expressed as Gaussian density expanded in terms of Hermite polynomials named as Gram Charlier Series (GCS). This research is an extension of an earlier work on second order linearized solution to nonlinear Bayesian filtering using Taylor series and third order GCS expansion of posterior PDF. In this new extension, Bayes’ posterior PDF is approximated by a mixture of GCS functions for which the parameters are propagated using linear propagation theory. The update of weights of different components of GCS mixture model uses the FPKE error as feedback to adapt for the amplitude of different GCS components while solving a quadratic programming problem earlier used for Gaussian Mixture Model (GMM) PDF. Proposed filtering method is applied on tracking of space debris. The simulation results for the filter shows performance is moderately better than single GCS filter, Extended Kalman Filter (EKF) and Gaussian Sum Filter (GSF) under space debris’ highly uncertain initial conditions and sparse measurement availability.

This paper presents an alternative process to fabricate flexible bandpass filters by using embroidered yarn conductor on electronic-textile. The novelty of the proposed miniaturized filter is its complete integration on the outfit, with benefits in terms of compressibility, stretch ability and high geometrical accuracy, opening the way to develop textile filters in sport and medicine wearable applications. The proposed design consists of a fully embroidered microstrip topology with a length equal to quarter wavelength (λ/4) to develop a bandpass filter frequency response. A drastic reduction in size of the filter was achieved by taking advantage of a simplified architecture based on meandered-line stepped impedance resonator. The e-textile microstrip filter has been designed, simulated, fabricated and measured, with experimental validation at a 7.58 GHz frequency. The insertion loss obtained by simulation of the filter is substantially small. The return loss is greater than 20 dB for bands. To explore the relations between physical parameters and filter performance characteristics, theoretical equivalent circuit model of the filter constituent components were studied. The effect of bending of the e-textile filter is also studied. The results show that by changing the radius of bending up to 40 mm, the resonance frequency is shifted up 4.25 MHz/mm.

As screen sizes are becoming larger and larger, which are beyond human’s physical limitation for direct touching interaction, remote controls are inevitable. However, as techniques applied so far, inertial gyroscopes are susceptible to position inaccuracies, and gesture recognition is limited by cameras’ focus depth and viewing angle. Grating antenna light trapping technology will be an ideal candidate providing the ghost point problem for multipoint inputs can be solved. Therefore, we propose a differential amplitude modulation scheme for grating antenna based multi beam optical touch, which can recognize different incidence points. Where, the amplitude of the incident beams was coded with different pulse width at first. Then, after been trapped by the grating antenna and been transferred into currents by the lined detector arrays, the incident points of the individual beams were recognized and differentiated. The scheme was successfully verified on an 18-inch screen, where two-point optical touch with position accuracy error under 3mm and response time less than 7ms under modulation frequency of 10kHz on both incident beams are obtained. This work paves a practical way for remote multi-point touch, which can make digital mouse in consistent to the users pointing direction obeying natural three-point one ling aiming rule instantaneously.

Whole-brain radiation therapy and stereotactic radiosurgery are two treatment modalities commonly utilized to treat brain metastases (BMs). The aim of this study is to retrospectively analyze the main radio-oncologic and clinical-demographic aspects of a cohort of BM patients treated with Volumetric Modulated Arc Therapy for radiosurgery (VMAT-RS). This is a cross-sectional observational design study with retrospective review of medical records of patients with brain metastases treated with VMAT- RS between 2012 and 2018. Clinical and demographic data, with special attention to sex, age, primary tumor, brain tumor-related epilepsy (BTRE), number and brain location of BMs, Karnofsky Performance Status (KPS), the updated DS-GPA prognostic index and the survival estimated according to the Kaplan-Meier model from the date of radiosurgery were analyzed. One hundred and twenty-one patients with 229 BMs were treated with VMAT-RS. Patients presented 1-4 BMs, which were treated with 5 non-coplanar VMAT arcs. Sixty-eight percent of the patients had lung cancer and 35% of the BMs were in the frontal lobe. Proportion of local control was 88.5%. BTRE prevalence was 30.6%. The median survival time (MST) was 7.7 months. In the multivariate analysis of the Cox Regression model KPS70 (HRKPS&lt;70=2.59; p=0.001) and higher DS-GPA (HRDS-GPAII =0.55, p=0.022; HRDS-GPAIII-IV =0.38, p=0.006) were associated with improved survival. In the univariate analysis, primary tumor, age and the presence of metastases in the posterior fossa (PFBMs) were also significative. In conclusion, the VMAT-RS is a technique with an overall survival comparable to other radiosurgery techniques. The median survival is significantly longer in those with higher KPS and DS-GPA. Other variables such as the type of primary tumor, age and PFBMs could also influence survival, although further studies are needed.

Macrophage migration inhibitory factor (MIF) is a multifunctional cytokine that contributes to the progression of several cancers. MIF overexpression has been reported in head and neck squamous cell carcinoma (HNSCC) patients. However, the exact role of MIF in HNSCC is not fully understood. Our aim was to evaluate the amount of secreted MIF and the role of MIF in the proliferation, cell cycle, and apoptosis in HNSCC cell lines. The MIF levels in conditioned media from human primary (HN18 and HN30) and metastatic (HN17 and HN31) HNSCC cell lines were evaluated using ELISA. The HNSCC cell lines were treated with recombinant MIF and its effect on proliferation, cell cycle, and apoptotic status was determined by MTT and flow cytometry, respectively. The HNSCC-secreted MIF concentration ranged from 49.33‒860 pg/ml. Exogenous MIF (25 ng/ml) significantly increased HN18, HN30, and HN31 cell proliferation. Moreover, MIF induced cell cycle progression and inhibited apoptosis in these cells. However, MIF did not affect growth or apoptosis in HN17 cell. In conclusion, the HNSCC cell lines were evaluated secrete MIF. Exogenous MIF promotes various effects on proliferation, cell cycle, and apoptosis in HNSCC cells.

A new low-pass filter (LPF) circuit with independent adjustment of various, incl. digitally controlled, pole frequency resistors, pole quality factor and transmission coefficient. The proposed low-pass filter is based on the use of the properties of a multi-differential operational amplifier that performs the functions of a signal adder. The peculiarity of the filter is that it has three inputs, with respect to which different transmission coefficients are implemented, incl. inverting (-1) and non-inverting (+1). To check these properties of a low-pass filter in the Micro-Cap environment, computer simulation of a specific circuit was performed on a multi-differential operational amplifier AD 8130. Mathematical expressions are given for the main parameters of the proposed low-pass filter, which allow parametric synthesis of elements of a specific circuit under given restrictions on the used element base.

Determining the vibration environment is crucial to analyzing a design of any mechanical system, especially such dynamic systems as sounding rockets. Accuracy of measurement using accelerometers could be improved by application of mechanical vibration filtering and amplifying devices. This work presents a theoretical description of a tunable filter and amplifier. Principle of work is provided as well as results from application of the device on a sounding rocket are provided. It is shown that implementation of such devices allowed for enhancing the accuracy of acceleration measurements. Conclusions on future implementations are also provided.

Aiming for the problems emerging in the PWM drive system with long cables, accurate modeling of power cables is the premise to predict and analyze the relevant phenomenon, and a proper filter design is the key solution to these problems. This paper proposes high-frequency cable models to represent the frequency-dependent characteristics, especially for the high-frequency resistance of the cable that is an easily overlooked factor but determines the damping of overvoltage. The proposed models can be used for accurately representing the cable parameters in a wide frequency range, and correctly simulating the differential mode (DM) overvoltage and common mode (CM) current, including the peak value, oscillation frequency and damping of the transient waveform. In addition, improved filter networks are proposed to suppress the DM voltage and CM current, with the merit of low losses, small volume and an excellent ability of suppressing overvoltage. The proposed cable models and the filter design have been validated in a 750W PWM drive system with 200m power cables.

We have presented a controllable and human-readable polynomial neural network (CR-PNN) that is the first human-readable neural network. One can imagine its influence on system identification. Subsequently, we developed a relation spectrum in a medical application, which is likely to stand alongside the Fourier spectrum. However, the system analysis methodology is incomplete in contrast to signal processing methodology. Here, we presented the system filters for the first time. In this paper, we used the simulation system to verify the availability of the system analysis methodology. The system analysis methodology showed great properties in system identification and filter. The contribution of this paper is the system analysis methodology: transform method (CR-PNN), relation spectrum, and system filter design.

The purpose of this paper is to provide a structural review of the progress made on detection and localization of leaks in pipelines by using approaches based on the Kalman filter. This is, to the best of our knowledge, the first review on the t opic. In particular, it is the first to try to draw the attention of the leak detection community to the important contributions that use the Kalman filter as the core of a computational pipeline monitoring system. Without being exhaustive, we try to gather the results from different research groups and present them in a unified fashion. For this reason, we propose a classification of the current approaches based on the Kalman filter. For each of the existing approaches within this classification, the basic concepts, fundamental results, and relations with the other approaches are discussed in detail. The review starts from a short summary of basic concepts about state observers. Then, a brief history of the use of the Kalman filter for diagnosing leaks is described by mentioning the most outstanding approaches. At last, we briefly discuss some emerging research problems, such as the leak detection in pipelines transporting heavy oils, and we discuss the main challenges and some open problems.

Warming-induced drought stress and El Nino associated summer precipitation failure are responsible for increased forest fire intensities of tropical and temperate forests in Asia and Australia. However, both effects are unclear for boreal forests, the largest biome and carbon stock over land. Here we combined fire frequency, burned area and climate data in the Altai boreal forests, the southmost extension of Siberia boreal forest into China, and explored their link with ENSO (El Nino and South Oscillation). Surprisingly, both summer drought severity and fire occurrence have shown significant (P&lt;0.05) teleconnections with La Nina events of the previous year, and therefore provide an important reference for forest fire prediction and prevention in Altai. Despite a significant warming trend, the increased moisture over Altai has largely offset the effect of warming-induced drought stress, and lead to an insignificant fire frequency trend in the last decades, and largely reduced burned area since the 1980s. The reduced burned area could also benefit from the fire suppression efforts and greatly increased investment in fire prevention since 1987.

Translation is spatiotemporally regulated and ER-associated mRNAs are generally in efficient translation. It is unclear whether the ER-associated mRNAs are deadenylated or degraded on the ER surface in situ or in the cytosol. Here, we showed that ER possessed active deadenylases, particularly the poly(A)-specific ribonuclease (PARN), in common cell lines and mouse tissues. Consistently, purified recombinant PARN exhibited a strong ability to insert into the Langmuir monolayer and liposome. ER-anchored PARN was found to be able to reshape the poly(A) length profile of the ER-associated RNAs by suppressing long poly(A) tails without significantly influencing the cytosolic RNAs. The shortening of long poly(A) tails did not affect global translation efficiency, suggesting that the non-specific action of PARN towards long poly(A) tails was beyond the scope of translation regulation on the ER surface. Transcriptome sequencing analysis indicated that the ER-anchored PARN trigged the degradation of a small subset of ER-enriched transcripts. The ER-anchored PARN modulated the translation of its targets by redistributing ribosomes to heavy polysomes, suggesting that PARN may play a role in dynamic ribosome reallocation. During DNA damage response, MK2 phosphorylated PARN-Ser557 to modulate PARN translocation from the ER to cytosol. By promoting the decay of ER-associated MDM2 transcripts with low ribosome occupancy, the ER-anchored PARN modulated DNA damage response and thereby cell viability. These findings revealed that a highly regulated communication between mRNA degradation rate and translation efficiency is present on the ER surface in situ and that PARN may contribute to this communication by modulating the dynamic ribosome reallocation between transcripts with low and high ribosome occupancies.

This study investigates the nonlinearities in three-phase inverters for SiC-based systems and compares their performance to IGBT-based systems. An analytical model of inverter voltage distortion is developed, which accounts not only for dead time (td), switching delay time, switching frequency (fs), and voltage drops of power devices, but also for output parasitic capacitance (Cout). Experimental tests validate the model, which provides a more accurate estimate of the inverter’s output phase voltage distortion. The power device characteristics are obtained from datasheets, while Cout is determined through experimentation. Three-phase inverters with varying switching frequencies, fundamental frequencies, and dead-time values are used in simulations and experiments to determine the influence of nonlinearity on phase voltage deviation and current distortion. The results show that, due to SiC devices’ faster switching time, the phase voltage deviation and phase current distortion are lower in SiC-based inverters than in IGBT-based ones for high-frequency applications, as the dead time can be reduced.

β-Ga2O3 crystal have attracted great attentions in the fields of photonics and photoelectronics because of its ultra wide-band gap and high thermal conductivity. Here, pure β-Ga2O3 crystal was successfully grown by optical floating zone (OFZ) method, and used as saturable absorbers to realize a passively Q-switched all-solid-state 1μm laser for the first time. By placing the as-grown β-Ga2O3 crystal into the resonator of Nd:GYAP solid-state laser, a Q-switched pulses at the center wavelength of 1080.4 nm are generated under a output coupling of 10%. The maximum output power is 191.5 mW while the shortest pulse width is 606.54 ns, and the maximum repetition frequency is 344.06 kHz. The maximum pulse energy and peak power are 0.567 μJ and 0.93 W, respectively. Our experimental results show that β-Ga2O3 crystal has great potential in the development of all-solid-state 1μm pulsed laser.

Loose Tangle is a concept in graph theory that has a dual relationship with branch-width which is well-known graph width parameter. Ultrafilter, a fundamental notion in mathematics, is similarly known to have a dual relationship with branch-width when extended to a connectivity system (X, f). In this compact paper, we revisit and contemplate the interplay between Loose Tangle and Filter through the lens of a submodular partition function.

In this paper, we introduce the evolve-then-filter (EF) regularization method for reduced order modeling of convection-dominated stochastic systems. The standard Galerkin projection reduced order model (G-ROM) yield numerical oscillations in a convection-dominated regime. The evolve-then-filter reduced order model (EF-ROM) aims at the numerical stabilization of the standard G-ROM, which uses explicit ROM spatial filter to regularize various terms in the reduced order model (ROM). Our numerical results based on a stochastic Burgers equation with linear multiplicative noise. It shows that the EF-ROM is significantly better results than G-ROM.

High Efficiency Video Coding (HEVC) uses an 8-point filter and a 7-point filter, which are based on the discrete cosine transform (DCT), for the 1/2-pixel and 1/4-pixel interpolations, respectively. In this paper, discrete sine transform (DST)-based interpolation filters (IF) are proposed. The first proposed DST-based IFs (DST-IFs) use 8-point and 7-point filters for the 1/2-pixel and 1/4-pixel interpolations, respectively. The final proposed DST-IFs use 12-point and 11-point filters for the 1/2-pixel and 1/4-pixel interpolations, respectively. These DST-IF methods are proposed to improve the motion-compensated prediction in HEVC. The 8-point and 7-point DST-IF methods showed average BD-rate reductions of 0.7% and 0.3% in the random access (RA) and low delay B (LDB) configurations, respectively. The 12-point and 11-point DST-IF methods showed average BD-rate reductions of 1.4% and 1.2% in the RA and LDB configurations for the Luma component, respectively.

This paper presents the mathematical modeling for designing a 10[kW] DC-AC inverter system from 48 [V] DC to 120 V ACrms, considering its non-linear operation, allowing to obtain a detailed simulation to assess the proposed fuzzy PI control (with anti-windup action) and its optimal operation. The performance assessment of the converter was carried out with the discrete treatment of the voltage and current signals using spectral analysis, filtering considerations, and evaluation of limit cycle technique to determine the system's stability. The main results showed that THD at the filter output (transformer and capacitor) was around 0.0322% and 0.0632% at nominal load in open loop and closed loop, respectively. The inverter system presented more sensitivity in the current signal with a ripple at 120 [Hz] of 2.02% and at 5000 [Hz] of 10.62% (at nominal load). However, when the system operates in a closed loop, the current ripple at 120 [Hz] is 2.38% and at 5000 [Hz] is 10.62%.

The aim of our study was to evaluate the impact of T. gondii status on eosinophils count (PNE), eosinophil to lymphocyte ratio (ELR) and eosinophil to neutrophil to lymphocytes ratio (ENLR) before and after can-nabis cessation in patients with psychiatric disorders. One hundred and eighty-eight patients were includ-ed in the study. T. gondii, PNE, ELR, ENLR, and urinary cannabis were measured at baseline and after 4 weeks of cannabis cessation. Highest PNE (p = .02), ELR (p = .03) and ENLR levels (p = .031) and highest increase of PNE (p = .044), and ENLR (p = .036) levels were found in patients after cannabis cessation only in the Toxo+ group. At four weeks, significant interactions between cannabis and T. gondii status for PNE (p = .038), and for ENLR (p = .043) levels were found, as well as for the evolution between baseline and 4 weeks for ENLR level (p = .049). After cannabis cessation, we found a positive correlation between negative symptoms and PNE levels at 4 weeks in the Toxo+ group. This study shows that the increase of inflammation after cannabis cessation might be modulated by T. gondii seropositivity status in patient after cannabis cessation.

A high step-up DC-to-DC converter that integrates an isolated transformer and a switched-clamp capacitor is presented in this study. The voltage stress of the main power switch should be clamped to 1/4 V by using the turn ratio and switched-clamp capacitor of an isolated transformer to achieve a high voltage gain. In addition, a passive clamp circuit is employed reduce voltage stress on the main power switch. The energy of the leakage inductor can be recycled by the clamp capacitor because of the passive clamp circuit, thereby improving the power converter efficiency. The converter consists of one isolated transformer, one main switch, three capacitors, and four diodes. Operating principle and steady-state analyses are also discussed. Finally, a 24-V-input voltage to 200-V-output voltage and a 150 W output power prototype converter are fabricated in the laboratory. The maximum efficiency of the converter is 95.1 at 60 W.

γδT have functions of innate and adaptive immunity, with the potential to induce durable responses while being well-tolerated, with limited adverse effects, making it attractive as a tool for immunotherapy. γδT faces challenges as a frontline tool in clinical oncology, with limited response rates due to difficulties in reaching tumor sites with consistent cytotoxic activity and strength. Modulated Electro-hyperthermia (mEHT) is a loco-regional treatment, whereby energy-transmission from an electromagnetic field selectively targets the plasma membrane of tumor cells, inducing apoptosis and activating immune cells. We hypothesized that mEHT could enhance therapeutic effects by drawing γδT to tumor cells, while also rendering tumor cells to be more susceptible to cytotoxic effects. In this study, NOD/SCID mice harboring subcutaneous human HepG2 tumors were treated with intravenous injections of γδT after mEHT treatment. This method increased infiltration of γδT into the tumor site, significantly inhibiting tumor growth as compared to monotherapy with either modality. These data suggest that γδT could mediate a potent anti-tumor effect when combined with mEHT, and provide a strong rationale for combining these modalities in clinical application for cancer treatment.

Text-based CAPTCHA remains the most widely adopted security scheme, which is the first barrier to securing websites. Deep learning methods, especially Convolutional Neural Networks (CNNs) are the mainstream approach for text-CAPTCHA recognition, which are widely used in CAPTCHA vulnerability assessment and data collection. However, verification code recognizers are mostly deployed on the CPU platform as part of a web crawler and security assessment, they are required to have both low complexity and high recognition accuracy. Due to the specifically designed anti-attack mechanisms like noise, interference, geometric deformation, twisting, rotation, and character adhesion in text CAPTCHAs, some characters are difficult to efficiently identify with high accuracy in these complex CAPTCHA images. This paper proposed a recognition model named Adaptive-CAPTCHA with a CRNN module and trainable and configurable filtering networks, which effectively handle the interference and learn the correlation between characters in CAPTCHAs to enhance recognition accuracy. Experimental results on two datasets of different complexity show that compared with the baseline model Deep-CAPTCHA, the number of parameters of our proposed model is reduced by about 70% and the recognition accuracy is improved by more than 10 percentage points in the two datasets. In addition, the proposed model has a faster training convergence speed.

The task of determining the distance from one object to another is one of the important tasks solved in robotics systems. Conventional algorithms rely on an iterative process of predicting distance estimates, which results in an increased computational burden. Algorithms used in robotic systems should require minimal time costs, as well as be resistant to the presence of noise. To solve these problems, the paper proposes an algorithm for Kalman combination filtering with a Goldschmidt divisor and a median filter. Software simulation showed an increase in the accuracy of predicting the estimate of the developed algorithm in comparison with the traditional filtering algorithm, as well as an increase in the speed of the algorithm. The results obtained can be effectively applied in various computer vision systems.

Interleaved power factor correction (PFC) is widely used circuit topology due to good efficiency and power density for single-switch boost PFC. As the differential mode (DM) electromagnetic interference (EMI) noise magnitude depends upon the input current ripple, this research details a comprehensive study of DM EMI filter design for interleaved boost PFC with the aim of minimizing the component size. It is also demonstrated that the different numbers of interleaved stages and switching frequency influence the filter attenuation requirement and, thus, the EMI filter size. First, an analytical model is derived on the basis of the Norton equivalent circuit model for the differential mode noises of interleaved boost PFC within the frequency range of 9-500 kHz. The derived model can help identify the optimal phase shifting among the interleaved boost converters in order to minimize the considered differential mode noises at the filter design frequency. So, a novel phase-shift method is developed to get a minimized attenuation required by a filter in Band B. Further, a volume optimization of the required DM filter was introduced based on the calculated filter attenuation and volumetric component parameters. Based on the obtained results, unconventional and conventional phase shifts have demonstrated a good performance in decreasing the EMI filter volume in Band B and Band A, respectively. A 2-kW interleaved PFC case study is presented to verify the theoretical analyses and the impact of phase-shifting on EMI filter size.

During the COVID-19 pandemic face masks grew in importance as their use by the general population was recommended by health officials in order to minimize the risk of infection and prevent further spread of the virus. To ensure health protection of medical personal and other system relevant staff, it is of considerable interest to quickly test if a certain lot of filtering facepiece masks meets the requirements or if the permeability changes under different conditions. As certified penetrometers are rather expensive and were difficult to obtain during the COVID-19 pandemic, we describe two quite simple and cheap methods to quickly test the filter permeability based on an electronic cigarette. The first method uses a precision scale, the second method uses a light scattering detector to measure the filter penetration. To make sure these two methods yield reliable results, both were tested with freshly cut filter samples covering the range of approx. 7% to 60% permeability and compared to the results of a certified penetrometer. The comparison of the two methods with the certified penetrometer showed a good correlation and therefore allow a quick and rather reliable estimation of the permeability. Several examples about the use of faulty masks and the resulting health risks show that simple, fast, cheap and broadly available methods for filter characterization might be useful in these days.

The Bayes filters, such as Kalman and particle filters, have been used in sensor fusion to integrate two sources of information and obtain the best estimate of the unknowns. Efficient integration of multiple sensors requires deep knowledge of their error sources and it is not trivial for complicated sensors, such as Inertial Measurement Unit (IMU). Therefore, IMU error modelling and efficient integration of IMU and Global Navigation Satellite System (GNSS) observations has remained a challenge. In this paper, we develop deep Kalman filter to model and remove IMU errors and consequently, improve the accuracy of IMU positioning. In other words, we add modelling step to the prediction and update steps of Kalman filter and the IMU error model is learned during integration. Therefore, our deep Kalman filter outperforms Kalman filter and reaches higher accuracy.

This work investigates the sliding mode control (SMC) problem for a class of uncertain switched systems subject to asynchronous switching and an assigned finite time constraint. Two important issues are how to ensure the reachability of state trajectories within the assigned time and the input-to-output finite-time stability (IO-FTS) of the closed-loop switched systems during the whole phase under asynchronous switching. To achieve these objectives, an asynchronous sliding mode controller with adjustable parameters is constructed to drive the state trajectories onto the sliding surface during the assigned finite-time interval. By means of the partitioning strategy, sufficient conditions for the IO-FTS of the closed-loop switched are derived during the whole phase [0,T] using the multiple Lyapunov function (MLF) approach. Additionally, the asynchronous characteristics are detailedly investigated while analyzing the reachability of a specified sliding surface. Finally, an illustrative example is given to illustrate the effectiveness of the proposed method.

The influence of a background vortex flow on clustering of floating tracer is addressed. The vortex flow considered is induced by an ellipsoidal vortex evolving in a deformation. The system exhibits various vortex motion regimes: (i) steady state, (ii) oscillation and (iii) rotation of the ellipsoidal vortex core. The latter two induce unsteady velocity field for the tracer thus leading to irregular (chaotic) tracer motion. Superimposing a stochastic divergent velocity field onto the deterministic vortex flow allows us to observe significantly different tracer evolution. We use the method of characteristics to integrate the floating tracer density evolution equation and the Euler-Ito scheme for obtaining the floating tracer trajectories with the random velocity field. The cluster area and cluster mass from the statistical topography were used as the quantitative diagnostics of floating-tracer’s clustering. For the case of the steady ellipsoidal vortex embedded into the deformation flow with a random velocity field component we found that clustering characteristics are weakened by the steady vortex. For the cases of an unsteady ellipsoidal vortex, we observed clustering in the floating-tracer density field if the contribution of the divergent component is higher or equal to that of the rotational (nondivergent) component. Even when the initial floating tracer patch was set on the boundary of oscillating ellipsoidal vortex, we observed formation of clusters. In the case of a rotating ellipsoidal vortex, we also observed pronounced clustering. Thus, we argue that unsteady ellipsoidal vortex regimes (oscillation and rotation), which induce chaotic motion of the nearby passive tracer’s trajectories, are still conducive to clustering of floating tracer observed in the density field despite the intense deformation introduced by strain and shear.

A refractive lens is one of the simplest, cost-effective and easily available imaging elements. With a spatially incoherent illumination, a refractive lens can faithfully map every object point to an image point in the sensor plane, when the object and image distances satisfy the imaging conditions. However, static imaging is limited to the depth of focus, beyond which the point-to-point mapping can be only obtained by changing either the location of the lens or the imaging sensor. In this study, the depth of focus of a refractive lens in static mode has been expanded using a recently developed computational reconstruction method, Lucy-Richardson-Rosen algorithm (LRRA). The technique consists of three steps. In this first step, the point spread functions (PSFs) were recorded along different depths and stored in the computer as PSF library. In the next step, the object intensity distribution was recorded. The LRRA was then applied to deconvolve the object information from the recorded intensity distributions in the final step. The results of LRRA were compared against two well-known reconstruction methods namely Lucy-Richardson algorithm and non-linear reconstruction.

We propose a spectral filter based on Plastic Optical Fiber with micro-holes as a low-cost, robust, and highly reproducible spectral filter. The spectral filter is explored for two configurations: fiber extended in a straight line, and a fiber optic loop mirror scheme configuration. The transmission traces indicate a spectral blue shift of peak transmission, at 587 nm, 567 nm, 556 nm, and 536 nm for 0, 1, 2, and 3 holes in the fiber, respectively. The filter exhibits a bandpass period of approximately 120 nm. Additionally, we conducted a comparison of the transmission with holes separated by distances of 1 cm and 500 μm. The results demonstrate that the distance between holes does not alter the spectral transmission of the filter. In the case of the fiber loop mirror configuration, we observed that the bandpass can be adjusted, suggesting the presence of multimode interference. Exploring variations in the refractive index within the holes by filling them with glucose solutions at various concentrations, we determined that the filtering band and spectral shape remains unaltered, ensuring a stable and robust operation of our spectral filter.

Silicon Photomultipliers find applications across various fields. One potential Silicon Photomultiplier application domain is neutrino telescopes, where they may enhance the angular resolution. However, the elevated dark count rate associated with Silicon Photomultipliers represents a significant challenge to their widespread utilization. To address this issue, it is proposed to use Silicon Photomultipliers and Photomultiplier Tubes together. The Photomultiplier Tubes signals would serve as a trigger to mitigate the dark count rate, thereby preventing undue saturation of the available bandwidth. This paper presents an investigation into a fast and resource-efficient method for filtering Silicon Photomultiplier dark count rate. A low-resource and fast coincident filter has been developed, which removes the Silicon Photomultiplier dark count rate by using as trigger the Photomultiplier Tube input signals. The architecture of the coincidence filter, together with the first results obtained, which validate the effectiveness of this method are presented.

The vast rise in the number of Internet-connected devices necessitates a more accessible spectrum. As a result, Cognitive Radio was already proposed as a solution to the problem of restricted spectrum resources by utilizing available spectrum which is assigned to primary users. This method allows the secondary user to utilize the spectrum whenever the primary user is not using it, and it does so without intruding with the primary user. Whenever the secondary user detects the spectrum, it faced some issues, such as complexity in sensing leading to a lack of noise value, and the primary user is hidden to all secondary users. In order to tackle these challenges, an adaptive threshold matched filter detector and a cooperative matched filter detector are utilized in this paper to detect the spectrum. The probability of detection (Pd), probability of miss detection (Pm), and probability of false alarm (Pf) are the metrics used to assess sensing accuracy. To simulate suggested detectors, the MATLAB R2020a software was utilized. In comparison to earlier studies, the simulation conclusions reveal that the detection process starts with lower SNR values.

The on-site wastewater treatment system (OWTS) with a sand trench is an economical option for residents in rural areas or the countryside where a centralised sewer system is inaccessible. 2A sand achieves improved filtration, microbial activity and consistent long term performance when compared to gravel or scoria based trench systems. However, it is expensive and only readily available in a few areas across New Zealand. Additionally, it has a reputation for premature blockage when overloaded or compacted. The aim of this study is not only to critically evaluate the performance of Crushed Glass (CG) with respect to 2A sand, but also to investigate different loading rates for CG when treating primary treated effluent from a septic tank. A test rig was designed and constructed to simulate the real environment of the sand column in a discharge control trench. The treatment efficiency of three filters was recorded and compared in this study. Overall, the CG loaded at 25mm/day (CG₂₅) and 50mm/day (CG₅₀) provided an average of 13% and 6% more Total Nitrogen (TN) reduction than the sand filter, respectively. The removal rates for the TN were up to 69.5%. The CG₅₀ filter performed similarly at 50mm/day as the 2A sand filter in terms of Total Suspended Solids (TSS) and Biochemical Oxygen Demand (BOD)₅ removal of more than 94%. The CG₂₅ removal rates for TSS and BOD₅ at the start of the trial (likely due to residual liquid contamination from the bottles when crushed) improved over the sampling period and ultimately achieved similar results of 92% and 91.3% to the filters loaded at 50mm/day. Lifecycle cost analyses and carbon balances were completed for the two media. It highlighted that the current price of CG is only half of 2A sand, yet it produces significantly less CO₂ emissions than 2A sand. A 3-bedroom dwelling could save up to $500 and reduce 200kg of CO₂ released to the environment annually when 2A sand is substituted for CG. Based on the findings of this paper, it is likely that the reduced installation cost, lessened environmental impact and theoretical availability will lead to CG systems becoming more common in New Zealand and abroad.

The consequences of a fall on an elderly person can be diminished if the accident is attended by medical personnel within the first hour. Independent elderly people use to stay alone for long periods of time, being in more risk if they suffer a fall. The literature offers several approaches for detecting falls with embedded devices or smartphones using a triaxial accelerometer. Most of these approaches were not tested with the objective population, or are not feasible to be implemented in real-life conditions. In this work we propose a Kalman-filter-based fall detection methodology that includes a periodicity detector to reduce the false positive rate. Moreover, this methodology requires a sampling rate of only 25 Hz, it does not require large computations or memory, and it is robust among devices. We tested our approach with the SisFall dataset. Then, we validated it with a new round of simulated activities with young adults and an elderly person achieving 99.4 % of accuracy. Finally, we gave the devices to three elderly persons during two days for full-day validations. They continued with their normal life and the devices behaved as expected.

The switched inertance hydraulic system (SIHS) is a novel high-bandwidth and energy-efficient digital device which can adjust or control flow and pressure by a means that does not rely on throttling the flow and dissipation of power. An SIHS can provide an efficient step-up or step-down of pressure or flow rate by using a digital control signal. In this article, analytical models of an SIHS in a four-port high-speed switching valve configuration are proposed, and the system dynamics and performance are investigated theoretically and experimentally. The flow responses, system characteristics and power consumption can be predicted effectively and accurately by using the proposed models, which were validated by comparing with experiments and with numerical simulation. The four-port configuration is compared with the three-port configuration, and it is concluded that the former one is less efficient for valves of the same size, but provides a bi-direction control capability. As bi-direction control is a common requirement, this constitutes an important contribution to the development of efficient digital hydraulics.

A scientific consensus is emerging on the benefits of dc distribution in medium voltage power systems of ships and cities. At least 50% space savings and increased power transfer capacity are estimated with enhanced voltage dc operation of electric cables. The goal of this research is to contribute to developing the empirical knowledge on the insulation performance in order to validate the feasibility of such anticipated gains of dc versus ac, and to determine the comparative impact of different operational conditions from a component engineering point of view. The partial discharge (PD) activity in cables is measured under ac and dc conditions as an indicator of insulation performance. Specifically, PDs in defects at the semicon-insulation interface are studied in terms of inception voltage, repetition rate and discharge magnitude. Empirical understanding is drawn for operating voltage and frequency dependence of the discharge behavior in such voids in the range of 10 to 20\,kV and 0 to 0.1\,Hz, respectively. The change in PD activity with void evolution is explored.

In this study, a new diphosphate compound, Ag0.2Na0.6FeP2O7, was synthesized using a solid-state reaction method and extensively studied using various techniques. The compound's structure was confirmed through X-ray diffraction analysis, revealing a single-phase monoclinic structure with the P21/C space group. The electrical behavior of the compound was investigated, and its conductivity followed Jonscher's universal law. The correlated barrier hopping (CBH) model explained the temperature-dependent ac conductivity and parameter "s" well. The study also explored the contribution of single-polaron and bipolaron hopping to the a.c. conductivity and discussed the ionic conductivity in relation to the structural characteristics of the sample. Overall, this investigation significantly enhances our comprehension of the distinctive electrical properties of Ag0.2Na0.6FeP2O7 and its potential practical applications.

Filter Media (FM) sourced from recycled organic and mineral material offers a low cost and effective means of treating urban stormwater. Using recycled materials rather than from an increasingly scarce source of virgin materials (typically sandy loam soil) can ensure a sustainable long-term economy and environment. This paper presents results from the laboratory analysis and mathematical modeling to highlight the performance of recycled organic and mineral material in removing nutrients and metals from stormwater. Analysis included physical and chemical characterisation such as particle size distribution, saturated hydraulic conductivity (Ksat), bulk density, effective cation exchange capacity, and pollutant removal performance. Design mixes (DM), comprising a combination of organic and mineral materials, were characterised and used to develop/derive modelling design within the Model for Urban Stormwater Improvement Conceptualisation (MUSIC v6) [1]. Comparison is made to the Adoption Guidelines for Stormwater Biofiltration Systems - Summary Report [2] which were based on the Facility for Advancing Water Biofiltration (FAWB) guidelines to assist in the development of biofiltration systems, including the planning, design, construction and operation of those systems. An observed outcome from over two decades of biofiltration guideline development has been the exclusion of alternative biofilter materials due to claims of excessive leaching. Results from this study indicate that high nutrient and metal removal rates can be achieved over a range of hydraulic conductivities using design mixes of recycled organic and mineral materials that have a demonstrated equivalence to existing guideline specifications.

In this work, an algorithm was developed to measure the respiration rate for an embedded device that can be used by a field robot for relief operation. With this algorithm, the rate measurement was calculated based on direct influences of respiratory-induced intensity variation (RIIV) on blood flow in cardiovascular pathways. For that, a photoplethysmogram (PPG) sensor was used to determine changes in heartbeat frequencies. The PPG sensor readings were filtered using an Information Filter and a Fast Fourier transform (FFT) to determine the state of RIIV. With a relatively light initialization, the information filter can estimate unknown variables based on a series of measurements containing noise and other inaccuraties. Therefore, this filter is suitable for application on an embedded device. For faster calculation time in the implementation, the FFT analysis was calculated only for a major peak in the frequency domain. Test and measurement of respiration rate was conducted based on the device algorithm and spirometer. Heartbeat measurement was also evaluated by comparing the heartbeat data of the PPG sensor and the medical tool kit. Based on the test, the implemented algorithm can measure respiration rate with about 80% accuracy compared with the spirometer.

Financial system is essentially chaotic and unstable if there is not any external inputs. By means of Lyapunov function method, design of switching law, novel fuzzy assumption, $L^p$ estimation technique and Laplace semigroup theory, the author presents the boundedness and LMI-based (globally) asymptotical input-to-state stability criteria of financial systems. Particularly, the globally asymptotical stability in the meaning of switching implies that when the time $t$ is big enough, the dynamic of any subsystem must approach its unique equilibrium point. Besides, the global financial crisis often erupts periodically, which illuminates that the global stability in the classical sense is actually meaningless. So the stability in the meaning of switching proposed in this paper is suitable and appropriate. Numerical examples illuminate the effectiveness of the obtained results.

A sufficient condition for the almost global sta-bility of nonlinear switched systems under average dwell timerestriction is obtained. This condition is derived leaning uponthe existence of multiple Lyapunov densities, which are associ-ated to subsystems and satisfy some compatibility conditions.An upper bound for the average dwell time that ensures almostglobal stability is obtained.

Ultra-thin Fe–6.5wt.%Si ribbons with 35 μm in thickness were prepared by melt-spinning. The magnetic properties were investigated before and after annealing 1000 ºC. DC properties and low-frequency (400 Hz ~ 10 kHz) iron losses have significantly improved after heat treatment. A simplified formula based on Steinmetz law which can be used to predict the AC iron loss is presented. According to the results of some iron losses data, a simplified formula has been determined, and the extent of AC iron losses can be predicted. The results obtained from the formula predict AC iron loss to a good degree. The method developed in this work could be extended to other magnetic materials for predicting AC iron loss with greater ease.

With the growing demand for positioning services, angle-of-arrival (AoA) estimation or direction-finding (DF) has been widely investigated for applications in fifth-generation (5G) technologies. Many existing AoA estimation algorithms only require the measurement of the direction of the incident wave at the transmitter to obtain correct results. However, for most of the cellular systems such as Bluetooth indoor positioning system due to multipath and non-line-of-sight (NLOS) propagation, the indoor positioning accuracy is severely affected. In this paper a comprehensive algorithm is investigated that combines radio measurements from Bluetooth AoA local navigation systems with indoor position estimates obtained using particle filtering, which allows us to explore new optimised methods to reduce estimation errors in indoor positioning. First, particle filtering is used to predict the rough position of a moving target. Then, an algorithm with robust beam weighting is used to estimate the AoA of the multipath components. Based on this, a system of pseudo-linear equations for target positioning based on the probabilistic framework of PF and AoA measurement is derived. Theoretical analysis and simulation results show that the algorithm can improve the positioning accuracy by about 25.7% on average.