Next Generation Transcriptome Sequencing and Quantitative Real-Time PCR Technologies for Characterisation of the Bemisia tabaci Asia 1 mtCOI Phylogenetic Clade

A programme of functional genomics research is underway at the University of Greenwich,UK,to develop and apply genomics technologies to characterise an economically-important but under-researched Bemisia tabaci（Hemiptera：Aleyrodidae）,the Asia 1 mtCOI phylogenetic group.A comparison of this putative species from India with other important B.tabaci populations and insect species may provide targets for the development of more effective whitefly control strategies.As a first step,next-generation sequencing（NGS）has been used to survey the transcriptome of adult female whitefly,with high quality RNA preparations being used to generate cDNA libraries for NGS using the Roche 454 Titanium DNA sequencing platform.Contig assemblies constructed from the resultant sequences（301 094 reads）using the software program CLC Genomics Workbench generated 3 821 core contigs.Comparison of a selection of these contigs with related sequences from other B.tabaci genetic groups has revealed good alignment for some genes（e.g.,HSP90）but misassemblies in other datasets（e.g.,the vitellogenin gene family）,highlighting the need for manual curation as well as collaborative international efforts to obtain accurate assemblies from the existing next generation sequence datasets.Nevertheless,data emerging from the NGS has facilitated the development of accurate and reliable methods for analysing gene expression based on quantitative real-time RT-PCR,illustrating the power of this approach to enable rapid expression analyses in an organism for which a complete genome sequence is currently lacking.

High Resolution Radar Real-Time Signal and Information Processing

Radar is an electronic device that uses radio waves to determine the range, angle, or velocity of objects. Real-time signal and information processor is an important module for real-time positioning, imaging, detection and recognition of targets. With the development of ultra-wideband technology, synthetic aperture technology, signal and information processing technology, the radar coverage, detection accuracy and resolution have been greatly improved, especially in terms of one-dimensional(1D) high-resolution radar detection, tracking, recognition, and two-dimensional(2D) synthetic aperture radar imaging technology. Meanwhile, for the application of radar detection and remote sensing with high resolution and wide swath, the amount of data has been greatly increased. Therefore, the radar is required to have low-latency and real-time processing capability under the constraints of size, weight and power consumption. This paper systematically introduces the new technology of high resolution radar and real-time signal and information processing. The key problems and solutions are discussed, including the detection and tracking of 1D high-resolution radar, the accurate signal modeling and wide-swath imaging for geosynchronous orbit synthetic aperture radar, and real-time signal and information processing architecture and efficient algorithms. Finally, the latest research progress and representative results are presented, and the development trends are prospected.

Study on characteristics of acoustic signals generated by different DC discharge modes

Acoustic signals contain rich discharge information.In this study,the acoustic signal characteristics of transient glow,spark,and glow discharges generated through DC pin–pin discharge were investigated.The signals were analyzed in the time,frequency,and time–frequency domains,and the correlation between the electric and the acoustic signal was studied statistically.The results show that glow discharge does not produce measurable sound signals.For the other modes,with a decrease in the discharge gap,the amplitude of the acoustic signal increases sharply with mode transformation,the short-time average energy becomes higher,and the frequency components are more abundant.Meanwhile,the current pulse and sound pressure pulse have a one-to-one relationship in the transient glow and spark regimes,and they are positively correlated in amplitude.A brief theoretical analysis of the mechanism of plasma sound and the trends of signals in different modes is presented.Essentially,the change in the discharge energy is closely related to the sound generation of the plasma.

Machine learning for parameters diagnosis of spark discharge by electro-acoustic signal

Discharge plasma parameter measurement is a key focus in low-temperature plasma research.Traditional diagnostics often require costly equipment,whereas electro-acoustic signals provide a rich,non-invasive,and less complex source of discharge information.This study harnesses machine learning to decode these signals.It establishes links between electro-acoustic signals and gas discharge parameters,such as power and distance,thus streamlining the prediction process.By building a spark discharge platform to collect electro-acoustic signals and implementing a series of acoustic signal processing techniques,the Mel-Frequency Cepstral Coefficients(MFCCs)of the acoustic signals are extracted to construct the predictors.Three machine learning models(Linear Regression,k-Nearest Neighbors,and Random Forest)are introduced and applied to the predictors to achieve real-time rapid diagnostic measurement of typical spark discharge power and discharge distance.All models display impressive performance in prediction precision and fitting abilities.Among them,the k-Nearest Neighbors model shows the best performance on discharge power prediction with the lowest mean square error(MSE=0.00571)and the highest R-squared value(R^(2)=0.93877).The experimental results show that the relationship between the electro-acoustic signal and the gas discharge power and distance can be effectively constructed based on the machine learning algorithm,which provides a new idea and basis for the online monitoring and real-time diagnosis of plasma parameters.

Low-Power Operational Amplifier for Real-Time Signal Processing System of Micro Air Vehicle

A low-power complementary metal oxide semiconductor（CMOS） operational amplifier （op-amp） for real-time signal processing of micro air vehicle （MAV） is designed in this paper.Traditional folded cascode architecture with positive channel metal oxide semiconductor（PMOS） differential input transistors and sub-threshold technology are applied under the low supply voltage.Simulation results show that this amplifier has significantly low power,while maintaining almost the same gain,bandwidth and other key performances.The power required is only 0.12 mW,which is applicable to low-power and low-voltage real-time signal acquisition and processing system.

Real-Time Traffic Signal Timing for Urban Road Multi-Intersection

this paper develops a real-time traffic signal timing model which is to be integrated into a single intersection for urban road, thereby solving the problem of traffic congestion. We analyze the current situation of the traffic flow with release matrix firstly, and then put forward the basic models to minimize total delay time of vehicles at the intersection. The optimal real-time signal timing model (non-fixed cycle and non-fixed split) is built with the Webster split optimal model. At last, the simulated results, which are compared with conventional model, manifest the promising properties of proposed model.

Real-Time Discrete Adaptive Control of Robot Arm Based on Digital Signal Processing

A discrete model reference adaptive controller of robot arm is obtained by integrating the reduced dynamic model of robot, model reference adaptive control （MRAC） and digital signal processing （DSP） computer system into an electromechanical system. With the DSP computer system, the control signal of each joint of the robot arm can be processed in real time and independently. The simulation and experiment results show that with the control strategy, the robot achieved a good trajectory following precision, a good decoupling performance and a high real-time adaptivity.

Simulation of large-scale numerical substructure in real-time dynamic hybrid testing

A solution scheme is proposed in this paper for an existing RTDHT system to simulate large-scale finite element （FE） numerical substructures. The analysis of the FE numerical substructure is split into response analysis and signal generation tasks, and executed in two different target computers in real-time. One target computer implements the response analysis task, wherein a large time-step is used to solve the FE substructure, and another target computer implements the signal generation task, wherein an interpolation program is used to generate control signals in a small time-step to meet the input demand of the controller. By using this strategy, the scale of the FE numerical substructure simulation may be increased significantly. The proposed scheme is initially verified by two FE numerical substructure models with 98 and 1240 degrees of freedom （DOFs）. Thereafter, RTDHTs of a single frame-foundation structure are implemented where the foundation, considered as the numerical substructure, is simulated by the FE model with 1240 DOFs. Good agreements between the results of the RTDHT and those from the FE analysis in ABAQUS are obtained.

A Novel Method for Real-Time Monitoring of Channel Siltation Based on Bistatic Scattering Theory

Monitoring the thickness changes of channel siltation is paramount in safeguarding navigation and guiding dredging, This paper presents a novel method for realizing the field monitoring of channel siltation in real time. The method is based on the bistatic scattering theory and concerned more with the receiving and processing of multipath signal at high-frequency and small grazing angle. By use of the multipath propagation structure of underwater acoustic channel, the method obtains the silt thickness by calculating the relative time delay of acoustic signals between the direct and the shortest bottom reflected paths. Bistatic transducer pairs are employed to transmit and receive the acoustic signals, and the GPS time synchronization technology is introduced to synchronize the transmitter and receiver, The WRELAX （Weighted Fourier transforul and RELAX） algorithm is used to obtain the high resolution estimation of muhipath time delay. To examine the feasibility of the presented method and the accuracy and precision of the developed system, a series of sea trials are conducted in the southwest coast area of Dalian City, north of the Yellow Sea. The experimental results are compared with that using high-resolution dual echo sounder HydroBoxTM, and the uncertainty is smaller than ＋ 0.06 m. Compared with the existing means for measuring the silt thickness, the present method is innovative, and the system is stable, efficient and provides a better real-time performance. It especially suits monitoring the narrow channel with rapid changes of siltation.

Real-time measurement of high rotational projectile axial acceleration based on 2-axis acceleration sensor

The real-time measurement principle of high rotational projectile＇s angular velocity based on 2-axis acceleration sensor and the axial acceleration measurement error caused by the installation error are discussed.The 2-axis acceleration sensor is applied to measure the high rotational projectile＇s angular velocity and the measurement value of axial acceleration,the axial acceleration of the high rotational projectile equals the measurement value of axial acceleration subtracting the centrifugal acceleration component,so that the high-accuracy real-time measurement of axial acceleration is realized.The memory test has confirmed the strike tally of the theoretical analysis and the test result.The measurement technique can satisfy the high-accuracy measurement of the high rotational projectile axial acceleration in the self-determination course correction fuze projectile.

Real-Time Maqam Estimation Model in Max/MSP Configured for the Nāy

Automatic maqam estimation is considered significant toward improving multimedia live music performances and automatic accompaniment. This contribution proposed a real-time maqam estimation model developed in the visual programming language MAX/MSP and configured for the nāydukah. The model’s design stood on basic formulas of Arab music maqamat as explained in theory and applied in practice. The model consisted of different layers of competition;the first was for the identification of the instant tonic of the melodic figure, and the second was for the recognition of its identifying E (E, E half-flat and E flat). Those two competitions were used to estimate the maqam in real-time. Then, accumulated estimation results were used to estimate the maqam in longer durations;five-second and full duration. The model was evaluated using professionally performed nāy improvisations. Results reflected a success in estimating all the studied maqamat when the full improvisation was considered. In addition, results were very good for real-time and five-second estimation where average estimation confidence was 75.98% and 80.04%, respectively.

A Low-Cost Efficient Hardware-in-the-Loop Testbed for Distributed Generation Penetration Analysis

In this paper a real-time testbed using hardware-in-the-loop for the analysis of the effects of DGs （distributed generators） on microgrids is presented. The distribution network is implemented in SIMULINK using the IEEE 15-node distribution feeder connected to two DGs feeding the grid using two smart inverters. The inverters＇ active and reactive power control is performed by TI C2000-based controllers and the hardware connections to the system are done through dSPACE interface module. The system is designed such that it can easily be modified to change the location of the DGs and/or to change the number of DGs connected to the grid. Several case study results are presented and compared against simulations to verify the effectiveness and accuracy of the system, model, and the employed power control schemes.

A Parallel Approach for Real-Time Power Flow in Distribution Networks

The new reality of smart distribution systems with use of generation sources of small and medium sizes brings new challenges for the operation of these systems. The complexity and the large number of nodes requires use of methods which can reduce the processing time of algorithms such as power flow, allowing its use in real time. This paper presents a known methodology for calculating the power flow in three phases using backward/forward sweep method, and also considering other network elements such as voltage regulators, shunt capacitors and sources of dispersed generation of types PV （active power and voltage） and PQ （active and reactive power）. After that, new elements are introduced that allow the parallelization of this algorithm and an adequate distribution of work between the available processors. The algorithm was implemented using a multi-tiered architecture; the processing times were measured in many network configurations and compared with the same algorithm in the serial version.

Inhibition of Ehrlich ascites carcinoma growth by melatonin:Studies with micro-CT

Melatonin is a versatile indolamine synthesized and secreted by the pineal gland in response to the photoperiodic information received by the retinohypothalamic signaling pathway.Melatonin has many benefits,such as organizing circadian rhythms and acting as a powerful hormone.We aimed to show the antitumor effects of melatonin in both in vivo and in vitro models through the mammalian target of rapamycin(mTOR)signaling pathway and the Argyrophilic Nucleolar Regulatory Region(AgNOR),using the Microcomputed Tomography(Micro CT).Ehrlich ascites carcinoma(EAC)cells were administered into the mice by subcutaneous injection.Animals with solid tumors were injected intraperitoneally with 50 and 100 mg/kg melatonin for 14 days.Volumetric measurements for the taken tumors were made with micro-CT imaging,immunohistochemistry(IHC),real-time polymerase chain reaction(PCR)and AgNOR.Statistically,the tumor tissue volume in the Tumor+100 mg/kg melatonin group was significantly lower than that in the other groups in the data obtained from micro-CT images.In the IHC analysis,the groups treated with Tumor+100 mg/kg melatonin were compared when the mTOR signaling pathway and factor 8(F8)expression were compared with the control group.It was determined that there was a significant decrease(p<0.05).Significant differences were found in the total AgNOR area/nuclear area(TAA/NA)ratio in the treatment groups(p<0.05).Furthermore,there were significant differences between the amount of mTOR mRNA for the phosphatidylinositol 3-kinase(PI3K),AKT Serine/Threonine Kinase(PKB/AKT)genes(p<0.05).Cell apoptosis was evaluated with Annexin V in an in vitro study with different doses of melatonin;It was observed that 100µg/mL melatonin dose caused an increase in the apoptotic cell death.In this study,we have reported anti-tumor effects of melatonin in cell culture studies as well as in mice models.Comprehensive characterization of the melatonin-mediated cancer inhibitory effects will be valuable in advancing our fundamental molecular understanding and translatability of pre-clinical findings to earlier phases of clinical trials.

Photonic generation of ASK microwave signals with SSB format

Optical beating is the usual approach to generation of microwave signals.However,the highest frequency achievable for microwave signals is limited by the bandwidths of optoelectronic devices.To maximize the microwave frequency with a limited bandwidth of a photodetector(PD)and relieve the bandwidth bottleneck,we propose to generate microwave signals with the single sideband(SSB)format by beating a continuous wave(CW)light with an optical SSB signal.By simply adjusting the frequency diference between the CW light and the carrier of the optical SSB signal,the frequency of the generated microwave SSB signal is changed correspondingly.In the experiment,amplitude shift keying(ASK)microwave signals with the SSB format are successfully generated with diferent carrier frequencies and coding bit rates,and the recovered coding information agrees well with the original pseudo random binary sequence(PRBS)of 2^(7)−1 bits.The proposed approach can signifcantly relieve the bandwidth restriction set by optoelectronic devices in high-speed microwave communication systems.

Applications of advanced signal processing and machine learning in the neonatal hypoxic-ischemic electroencephalography

Perinatal hypoxic-ischemic-encephalopathy significantly contributes to neonatal death and life-long disability such as cerebral palsy. Advances in signal processing and machine learning have provided the research community with an opportunity to develop automated real-time identification techniques to detect the signs of hypoxic-ischemic-encephalopathy in larger electroencephalography/amplitude-integrated electroencephalography data sets more easily. This review details the recent achievements, performed by a number of prominent research groups across the world, in the automatic identification and classification of hypoxic-ischemic epileptiform neonatal seizures using advanced signal processing and machine learning techniques. This review also addresses the clinical challenges that current automated techniques face in order to be fully utilized by clinicians, and highlights the importance of upgrading the current clinical bedside sampling frequencies to higher sampling rates in order to provide better hypoxic-ischemic biomarker detection frameworks. Additionally, the article highlights that current clinical automated epileptiform detection strategies for human neonates have been only concerned with seizure detection after the therapeutic latent phase of injury. Whereas recent animal studies have demonstrated that the latent phase of opportunity is critically important for early diagnosis of hypoxic-ischemic-encephalopathy electroencephalography biomarkers and although difficult, detection strategies could utilize biomarkers in the latent phase to also predict the onset of future seizures.

A HIGH PERFORMANCE UWB LFM WAVEFORM GENERATOR

In this paper, the design and implementation of a high performance Ultra-WideBand (UWB) Linear Frequency Modulation (LFM) waveform generator at Very High Frequency/Ultra High Frequency (VHF/UHF) band are introduced. Firstly, the design ideas for a high performance UWB LFM waveform generator are described. Then, a generation scheme for UWB LFM waveforms is presented according to the baseband digital generation method combining with the bandwidth ex-tension method via frequency doubling. An experimental system has been implemented and tested. The results show that the UWB LFM waveform generator achieves very high performance.

5G Oriented Exponential Effective Signal to Interference plus Noise Ratio Mapping Algorithm Based on Channel Classification

In the future the fifth generation( 5 G) communication systems,channel models may be very complicated and it is difficult to calculate equivalent signal to interference plus noise ratio( SINR)of a random fading channel. Therefore,methods for the calculation of equivalent SINR of a random fading channel are very necessary.In this paper,an enhanced algorithm on the exponential effective SINR mapping( EESM) model for random fading channels was proposed. First, the optimal adjustment parameters of typical channel fading models including extended pedestrian A( EPA)model,extended vehicular A( EVA) model and extended typical urban( ETU) model were obtained by simulation. Then the proposed solution was used to actualize channel classification according to the maximum multipath delay and the average power of the random channel. The solution can determine the typical channel closest to random channel for obtaining the optimal adjustment value of EESM. The evaluation results indicate that the proposed one can improve the whole system throughput significantly and meanwhile the accuracy of the link prediction algorithm is also guaranteed.

A primary model of THz and far-infrared signal generation and conduction in neuron systems based on the hypothesis of the ordered phase of water molecules on the neuron surface Ⅰ: signal characteristics

In this paper, we use the theory of quantum optics and electrodynamics to study the electromagnetic field problem in the nervous system based on the assumption of an ordered arrangement of water molecules on the neuronal surface. Using the Lagrangian of the water molecule-field ion, the dynamic equations for neural signal generation and transmission are derived. Perturbation theory and the numerical method are used to solve the dynamic equations, and the characteristics of high-frequency signals(the dispersion relation, the time domain of the field, the frequency domain waveform, etc.) are discussed.This model predicts some intrinsic vibration modes of electromagnetic radiation on the neuronal surface.The frequency range of these vibration modes is in the THz and far-infrared ranges.

A new viewpoint and model of neural signal generation and transmission: Signal transmission on unmyelinated neurons

We establish a preliminary model of neural signal generation and transmission based on our previous research,and use this model to study signal transmission on unmyelinated nerves.In our model,the characteristics of neural signals are studied both on a long-time and a short time scale.On the long-time scale,the model is consistent with the circuit model.On the short time scale,the neural system exhibits a THz and infrared electromagnetic oscillation but the energy envelope curve of the rapidly oscillating signal varies slowly.In addition,the numerical method is used to solve the equations of neural signal generation and transmission,and the effects of the temperature on signal transmission are studied.It is found that overly high and overly low temperatures are not conducive to the transmission of neural signals.