A novel phase-sensitive scanning near-field optical microscope

Phase is one of the most important parameters of electromagnetic waves. It is the phase distribution that determines the propagation, reflection, refraction, focusing, divergence, and coupling features of light, and further affects the intensity distribution. In recent years, the designs of surface plasmon polariton （SPP） devices have mostly been based on the phase modulation and manipulation. Here we demonstrate a phase sensitive multi-parameter heterodyne scanning near-field opti- cal microscope （SNOM） with an aperture probe in the visible range, with which the near field optical phase and amplitude distributions can be simultaneously obtained. A novel architecture combining a spatial optical path and a fiber optical path is employed for stability and flexibility. Two kinds of typical nano-photonic devices are tested with the system. With the phase-sensitive SNOM, the phase and amplitude distributions of any nano-optical field and localized field generated with any SPP nano-structures and irregular phase modulation surfaces can be investigated. The phase distribution and the interference pattern will help us to gain a better understanding of how light interacts with SPP structures and how SPP waves generate, localize, convert, and propagate on an SPP surface. This will be a significant guidance on SPP nano-structure design and optimization.

Advances in Phase Detection Technique of Surface Plasmon Resonance Biosensor

Surface plasmon resonance (SPR) sensing is an optical method based on evanescent wave.SPR biosensor can detect interaction of label-free biomolecules in real-time.With further development,it can become a research instrument in proteomics.SPR biosensor can be divided intensity measurement and phase measurement,and the latter possesses higher sensitivity than the former one.This paper attempts to summarize the SPR phase detection theory,discuss the major developments,compare the merits and deficiencies of various methods,and look forward to future prospects.

Line spectrum detection algorithm based on the phase feature of target radiated noise

In order to improve the performance of line spectrum detection,according to the feature that the underwater target radiated noise containing stable line spectrum,the differences of the phase difference between line spectrum and background noise,a weighted line spectrum detection algorithm based on the phase variance is proposed in frequency domain.After phase difference alignment,the phase variance of line spectrum and the phase of background noise,respectively,are small and big in frequency domain,this method utilizes the weighted statistical algorithm to cumulate the frequency spectrum based on the phase variance,which can restrain the background noise disturbance,and enhance the signal to noise ratio（SNR）.The theory analysis and experimental results both verify that the proposed method can well enhance the energy of line spectrum,restrain the energy of background noise,and have better detection performance under lower SNR.

General seismic wave and phase detection software driven by deep learning

We developed an automatic seismic wave and phase detection software based on PhaseNet,an efficient and highly generalized deep learning neural network for P-and S-wave phase picking.The software organically combines multiple modules including application terminal interface,docker container,data visualization,SSH protocol data transmission and other auxiliary modules.Characterized by a series of technologically powerful functions,the software is highly convenient for all users.To obtain the P-and S-wave picks,one only needs to prepare threecomponent seismic data as input and customize some parameters in the interface.In particular,the software can automatically identify complex waveforms(i.e.continuous or truncated waves)and support multiple types of input data such as SAC,MSEED,NumPy array,etc.A test on the dataset of the Wenchuan aftershocks shows the generalization ability and detection accuracy of the software.The software is expected to increase the efficiency and subjectivity in the manual processing of large amounts of seismic data,thereby providing convenience to regional network monitoring staffs and researchers in the study of Earth's interior.

A Simple Model for On-Sensor Phase-Detection Autofocusing Algorithm

A simple model of the phase-detection autofocus device based on the partially masked sensor pixels is described. The cross-correlation function of the half-images registered by the masked pixels is proposed as a focus function. It is shown that—in such setting—focusing is equivalent to searching of the cross-correlation function maximum. Application of stochastic approximation algorithms to unimodal and non-unimodal focus functions is shortly discussed.

Arrival picking method for microseismic phases based on curve fi tting

Microseismic phase detection and arrival picking are critical steps in the processing of hydraulic fracturing microseismic monitoring data.As the signal-to-noise ratios of P-and S-waves diff er because of the infl uence of focal mechanisms,geometry,and background noise,diffi culties are introduced in the eff ective discrimination of seismic phases and the accurate acquisition of arrivals in conventional processing methods.In this paper,we propose a method for identifying microseismic phase arrival time by comprehensively analyzing the variation of moveout curves and combining the intra-event waveform similarities with the energy ratio of multitrace signals.First,a curve-fi tting formula is constructed with perforation arrivals,and event detection is achieved by adopting an energy-weighted similarity coeffi cient that seeks plausible fi tting curves with a sliding time window in continuous microseismic recordings.Then,the P-and S-waves are separated by the fitting parameters.The known arrival time trend of the microseismic phase is employed to calculate residual time corrections.Finally,the accurate arrival results of the microseismic phases can be obtained by picking the arrivals of stacked traces.The reliability and eff ectiveness of the proposed method for microseismic phase detection and arrival picking were determined through tests using field data.Arrival results indicate that the proposed method can improve accuracy compared with the traditional energy ratio method.

TOPOLOGICAL STRUCTURE OF THE SINGULAR POINTS OF THE THIRD ORDER PHASE LOCKED LOOP EQUATIONS WITH THE CHARACTER OF DETECTED PHASE BEING g(φ)=(1+k)sinφ/(1+kcosφ)

In this paper, we study the topological structure of the singular points of the third order phase locked loop equations with the character of detected phase being g(?) =(1+k)sin?/1+kcos?.

NON-AQUEOUS REVERSED PHASE HPLC WITH LOW-WAVELENGTH UV DETECTION FOR TRIGLYCERIDE ANALYSIS

Glycerides are first separated to classes of triglycerides(TGs), diglycerides(DGs) and monoglycerides(MGs) by normal phase HPLC on silica gel column. Individual triglyceride separation is then achieved by non-aqueous reversed phase(NARP) HPLC on C_(18) column with UV detection at 215nm.

Time Synchronous Averaging Based on Cross-power Spectrum

Periodic components are of great significance for fault diagnosis and health monitoring of rotating machinery.Time synchronous averaging is an effective and convenient technique for extracting those components.However,the performance of time synchronous averaging is seriously limited when the separate segments are poorly synchronized.This paper proposes a new averaging method capable of extracting periodic components without external reference and an accurate period to solve this problem.With this approach,phase detection and compensation eliminate all segments'phase differences,which enables the segments to be well synchronized.The effectiveness of the proposed method is validated by numerical and experimental signals.

RNN-Based Demand Awareness in Smart Library Using CRFID

To provide more intelligence service in the smart library, we need to better perceive the reader’s preferences. In addition to perceiving online records based on readers’ search history and borrowing records, advanced information technologies give us more chance to perceive the behavior of readers in the actual reading process and further discover the need for reading. In this paper, we use CRFID and RNN deep learning network to recognize book motions in the reading process, so as to judge readers’ need degree for the book, which can provide a basis for library book purchases and readers personalized service. In order to improve the recognition accuracy, we use the RSS as well as acceleration magnitude gathered from CRFID as the input data for RNN, and design a new encoding scheme. We trained and tested the deep learning network using real-world data, recorded during actual reading in our lab environment which mimics a typical reading room, from the experimental results, we conclude that our approach is feasible to recognize different reading phase to perceiving the needs of the readers.

High-Sensitivity Sensor Based on Surface Plasmon Resonance Enhanced Lateral Optical Beam Displacements

We present a new optical sensor based on surface plasmon resonance （SPIt） enhanced lateral optical beam displacements. Compared with the traditional SPIt methods, the new method provides higher sensitivity to the sensor system. Theoretical simulations show that the refractive index （RI） detection sensitivity of the SPR sensor based on the displacement measurement has a strong dependence on the thickness of the metal film. When the optimal thickness of the metal film is selected, the RI resolutlon of the SPIt sensor is predicted to be 2.2 × 10^-7 refractive index units （RIU）. Furthermore, it is found that the incidence angle can be used as a parameter to adjust the operating range of the sensor to different refractive index ranges.

Photoacoustic viscoelasticity imaging dedicated to mechanical characterization of biological tissues

Since changes in mechanical properties of biological tissues are often closely related to pathology,the viscoelastic properties are important physical parameters for medical diagnosis.A photoacoustic(PA)phase-resolved method for noninvasively characterizing the biological tissue viscoelasticity has been proposed by Gao et al.[G.Gao,S.Yang,D.Xing,\Viscoelasticity imaging of biological tissues with phase-resolved photoacoustic measurement,"Opt.Lett.36,3341–3343(2011)].The mathematical relationship between the PA phase delay and the viscosity–elasticity ratio has been theoretically deduced.Moreover,systems of PA viscoelasticity(PAVE)imaging including PAVE microscopy and PAVE endoscopy were developed,and high-PA-phase contrast images re°ecting the tissue viscoelasticity information have been successfully achieved.The PAVE method has been developed in tumor detection,atherosclerosis characterization and related vascular endoscopy.We reviewed the development of the PAVE technique and its applications in biomedical¯elds.It is believed that PAVE imaging is of great potential in both biomedical applications and clinical studies.

Multichannel Microwave Interferometer for Simultaneous Measurement of Electron Density and its Fluctuation on HL-2A Tokamak

A nmltichannel microwave interferometer system has been developed on the HL- 2A tokomak. Its working frequency is well designed to avoid the fringe jump effect. Taking the structure of HL-2A into account, its antennas are installed in the horizontal direction, i.e. one launcher in high field side （HFS） and four receivers in low field side （LFS）. The fan-shaped measurement area covers those regions where the magnetohydrodynamics （MHD） instabilities are active. The heterodyne technique contributes to its high temporal resolution （1 μs）. It is possible for the multichannel system to realize simultaneous measurements of density and its fluctuation. The quadrature phase detection based on the zero-crossing method is introduced to density measureinent. With this system, reliable line-averaged densities and density profiles are obtained. The location of the saturated internal kink mode can be figured out from the mode showing different intensities on four channels, and the result agrees well with that measured by electron cyclotron emission imaging （ECEI）.

Study on Technique of Surface Plasmon Resonance Imaging Sensing for Biomolecular Interaction

High resolution of surface plasmon resonance (SPR) detection is of vital importance.SPR biosensing system resolution is determined by intrinsic sensitivity of biochip and light signal acquisition system.In this article,different signal acquisition system resolutions on photodetector were analyzed based on light intensity and phase detection.Result shows that charge coupled device (CCD) with larger numbers of pixels is potential to achieve higher detection resolution.A 64 pixel line array CCD and a 12 bit ADC can achieve resolution of 10^(-7) refractive index unit (RIU).In array detection mode,increasing of detection throughput is at the cost of decreasing system resolution.Simulation analysis indicates that,if noise is taken into account,phase modulation methods are capable of providing better noise reduction performance than intensity methods.

Improved iterative convergence method in Q-ary LDPC coded high order PR-CPM

The Q-ary low-density parity-check（LDPC） coded high order partial response continuous phase modulation（PR-CPM） with double iterative loops is investigated. This scheme shows significant improvements in power and bandwidth efficiency, but at the expense of long iterative decoding delay and computational complexity induced by the improper match between the demodulator and the decoder. To address this issue, the convergence behavior of Q-ary LDPC coded CPM is investigated for the Q=2 and Q〉2 cases, and an optimized design method based on the extrinsic information transfer chart is proposed to improve the systematic iterative efficiency. Simulation results demonstrate that the proposed method can achieve a perfect tradeoff between iterative decoding delay and bit error rate performance to satisfy real-time applications.

FPGA-based amplitude and phase detection in DLLRF

The new generation particle accelerator requires a highly stable radio frequency（RF） system. The stability of the RF system is realized by the Low Level RF（LLRF） subsystem which controls the amplitude and phase of the RF signal. The detection of the RF signal＇s amplitude and phase is fundamental to LLRF controls. High-speed ADC（Analog to Digital Converter） ,DAC（Digital to Analog Converter） and FPGA（Field Programmable Gate Array） play very important roles in digital LLRF control systems. This paper describes the implementation of real-time amplitude and phase detection based of the FPGA with an analysis of the main factors that affect the detection accuracy such as jitter,algorithm＇s defects and non-linearity of devices,which is helpful for future work on high precision detection and control.

A Phase Shift Demodulation Technique： Verification and Application in Fluorescence Phase Based Oxygen Sensors

A phase shift demodulation technique based on subtraction capable of measuring 0.03 phase degree limit between sinusoidal signals is presented in this paper. A self-gain module and a practical subtracter act the kernel parts of the phase shift demodulation system. Electric signals in different phases are used to verify the performance of the system. In addition, a new designed optical source, laser fiber differential source （LFDS）, capable of generating mini phase is used to further verify the system reliability. R-square of 0.99997 in electric signals and R-square of 0.99877 in LFDS are achieved, and 0.03 degree measurement limit is realized in experiments. Furthermore, the phase shift demodulation system is applied to the fluorescence phase based oxygen sensors to realize the fundamental function. The experimental results reveal that a good repetition and better than 0.02% oxygen concentration measurement accuracy are realized. In addition, the phase shift demodulation system can be easily integrated to other applications.

Floating silver film： A flexible surface-enhanced Raman spectroscopy substrate for direct liquid phase detection at gas-liquid interfaces

In recent years, surface-enhanced Raman spectroscopy （SERS） has developed rapidly and is used for the detection of molecules and biomolecules in liquids. However, few studies have focused on SERS using a water surface as the substrate. A floating metal film on water is desirable for an enhanced SERS performance. In this work, silver nanopartides （Ag NPs） encased in poly（vinylpyrrolidone） films （Ag-PVP films） were synthesized on the surface of an aqueous solution by room temperature electron reduction. A floating silver film on a water surface was thereby achieved and is reported for the first time. The synthesized Ag-PVP film is an excellent flexible substrate for SERS and has other potential appli- cations. Using the floating silver film as a flexible SERS substrate, 10-11 M of 4-aminothiophenol, 10^-6 M of riboflavin, 10^-9 M of 4-mercaptobenzoic acid, 10^-7 M of 4-mercaptophenol, and 10^-7 M of 4-aminobenzoic acid are identified, demonstrating potential use for the floating substrate in the liquid-phase detection of molecules.

Hardware-Software Collaborative Techniques for Runtime Profiling and Phase Transition Detection

Dynamic optimization relies on runtime profile information to improve the performance of program execution. Traditional profiling techniques incur significant overhead and are not suitable for dynamic optimization. In this paper, a new profiling technique is proposed, that incorporates the strength of both software and hardware to achieve near-zero overhead profiling. The compiler passes profiling requests as a few bits of information in branch instructions to the hardware, and the processor executes profiling operations asynchronously in available free slots or on dedicated hardware. The compiler instrumentation of this technique is implemented using an Itanium research compiler. The result shows that the accurate block profiling incurs very little overhead to the user program in terms of the program scheduling cycles. For example, the average overhead is 0.6% for the SPECint95 benchmarks. The hardware support required for the new profiling is practical. The technique is extended to collect edge profiles for continuous phase transition detection. It is believed that the hardware-software collaborative scheme will enable many profile-driven dynamic optimizations for EPIC processors such as the Itanium processors.