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Face quality evaluation can filter out low quality face image to save computational resources and improve the system performance, labeling the face image quality score by manual consume too much manpower. To solve this problem, an unsupervised face image evaluation based on face recognition is proposed. We use the face recognition model to calculate the features of faces and label the images quality score. The face recognition model is compressed by knowledge distillation method to obtain efficient quality assessment model. Experimental results show that this method can effectively evaluate the quality of face image and improve the performance of face recognition.

We investigate the fragmentation and isomerization of toluene molecules induced by strong-field ionization with a femtosecond near-infrared laser pulse. Momentum-resolved coincidence time-of-flight ion mass spectrometry is used to determine the relative yield of different ionic products and fragmentation channels as a function of laser intensity. Ultrafast electron diffraction is used to capture the structure of the ions formed on a picosecond time scale by comparing the diffraction signal with theoretical predictions. Through the combination of the two measurements and theory, we are able to determine the main fragmentation channels and to distinguish between ions with identical mass but different structures. In addition, our diffraction measurements show that the independent atom model, which is widely used to analyze electron diffraction patterns, is not a good approximation for diffraction from ions. We show that the diffraction data is in very good agreement with ab initio scattering calculations.

The safe and reliable operation of power transmission lines is the key to the sustainable and stable operation of power grids. Using the artificial intelligence techniques for the channel status monitoring greatly improves the inspection efficiency of transmission lines. However, the discrimination is mostly conducted on the cloud side, which does not meet the requirement of real-time processing. In this paper, we build an intelligent monitoring system for transmission lines based on edge computing. According to the specific characteristics of the real-world power filed applications, a lightweight deep learning algorithm model is designed. It is then transplanted on a self-developed AI chip and a field test is carried out. The experimental results show that the model designed in this paper balances well between the accuracy, the model size and the inference speed. It realizes status local discrimination of the transmission lines, and promising detection results are obtained.

An enormous challenge still exists for designing molecules with the second near-infrared (NIR-II, 1000-1700 nm) window absorption, NIR-II fluorescence emission, and batch-to-batch reproducibility, which is the premise for high-performance NIR-II phototheranostics. Although organic small molecules and polymers have been largely explored for phototheranostics, it is difficult to satisfy the above three elements simultaneously. In this work, molecular oligomerization (the general structure is S-D-A-D'-A-D-S) and donor engineering (changing the donor linker D') strategies are applied to design phototheranostic agents. Such strategies are proved to be efficient in adjusting molecular configuration and energy level, affecting the optical and thermal properties. Three oligomers (O-T, O-DT, and O-Q) are further prepared into water-soluble nanoparticles (NPs). Particularly, the O-T NPs exhibit a higher molar extinction coefficient at 1064 nm (≈4.3-fold of O-DT NPs and ≈4.8-fold of O-Q NPs). Furthermore, the O-T NPs show the highest NIR-II fluorescence brightness and heating capacity (PCE = 73%) among the three NPs under 1064 nm laser irradiation and served as agents for NIR-II imaging guided in vivo photothermal therapy. Overall, by using molecular oligomerization and donor engineering strategies, a powerful example of constructing high-performance NIR-II phototheranostics for clinical translation is given.

Ultrafast electron diffraction and time-resolved serial crystallography are the basis of the ongoing revolution in capturing at the atomic level of detail the structural dynamics of molecules. However, most experiments capture only the probability density of the nuclear wavepackets to determine the time-dependent molecular structures, while the full quantum state has not been accessed. Here, we introduce a framework for the preparation and ultrafast coherent diffraction from rotational wave packets of molecules, and we establish a new variant of quantum state tomography for ultrafast electron diffraction to characterize the molecular quantum states. The ability to reconstruct the density matrix, which encodes the amplitude and phase of the wavepacket, for molecules of arbitrary degrees of freedom, will enable the reconstruction of a quantum molecular movie from experimental x-ray or electron diffraction data., Ultrafast diffraction is fundamental in capturing the structural dynamics of molecules. Here, the authors establish a variant of quantum state tomography for arbitrary degrees of freedom to characterize the molecular quantum states, which will enable the reconstruction of a quantum molecular movie from diffraction data.

This paper reports a method for the preparation of glass by reflowing commercial mixed micro and nano powders. High-quality micro-structure glass is formed by a microfabrication process combined with reflow process of the mixed micro and nano powders. The quality of glass prepared by different components was investigated and analyzed. Characterization of the formed glass micro-structure was performed by combining scanning electrical microscopy, energy dispersive spectroscopy, x-ray diffraction, and x-ray photoelectron spectroscopy. The glass reflow results were compared with the anodic bonding sample, which showed micro-structure glass prepared by our method was well-formed with high density and transparency. These results may inspire new possibilities for glass-based microsystems and MEMS applications.

Gas phase electron diffraction is a powerful technique to measure the structure of molecules in the gas phase, and time-resolved ultrafast electron diffraction has been successful in capturing structural dynamics taking place on femtosecond and picosecond time scales. Diffraction measurements, however, are not sensitive to isotope substitution, and thus cannot distinguish between isotopologues. Here we show that by impulsively aligning the molecules with a short laser pulse and observing the anisotropy in the diffraction signal over multiple revivals of the rotational wavepacket, the relative abundance of molecules with different isotopes can be determined. We demonstrate the technique experimentally and theoretically by studying the rotational dynamics of chloromethane with two naturally occurring chlorine isotopes 35Cl and 37Cl. We have determined the relative abundance and mass difference of the isotopes. This new methodology adds a new capability to the existing technique of ultrafast electron diffraction.

A space- and time-resolved flat-field soft X-ray spectrometer with the wavelength range of 1–13 nm has been developed to study impurity behavior on the Experimental Advanced Superconducting Tokamak (EAST). Using an entrance slit, a varied line spacing grating (2400 grooves/mm at the grating center), and a charged coupled device (CCD) system, time evolution of profiles of impurity line emissions were recorded. The spectral resolution of the spectrometer is 0.006 nm at 5 nm when the width of entrance slit is set at 0.03 mm. The best spatial resolution obtained is 24.5 mm with the height of slit at 1.0 mm. The spectrometer is placed 8000 mm away from the plasma center and the observed spatial range covers 0–450 mm from the equatorial plane of EAST. The first experimental results were obtained from the recent EAST campaign. The system was shown to be capable of observing spectral lines from both intrinsic low- Z impurities (C, O, et al.) and highly ionized medium- and high- Z impurities (Fe, Cr, Ni, Cu, et al.). Spectral lines from the full wavelength range (1–13 nm) can be obtained by moving the position of the CCD. Spectra with the wavelength intervals of 1–2 nm show strong metal lines for H-mode discharges. Time evolutions of C VI (3.373 nm) and O VIII (1.897 nm) lines are presented and detail analysis is performed combining electron density intensity, D α and soft X-ray and extreme ultraviolet (XUV) radiation intensities. Evolutions of profiles of C VI (3.373 nm) and O VIII (1.897 nm) at core plasma were also shown, indicating that the spectrometer can be applied for impurity transport studies

In order to implement the high-speed data transmission in wireless communication system, the signal bandwidth becomes wider. However this results in high Nyquist sampling rate which will beyond the capacity of the hardware device. The analog-to-information conversion (AIC) based on compressed sensing (CS) is proposed to sample signals at a sub-Nyquist rate. The circulant matrix (CM) instead of the random Bernoulli matrix is used as the measurement matrix in this paper. Compared with the structure based on random Bernoulli matrix, this CM based architecture, in a certain extent, can reduce system complexity. Simulations which show the efficiency of the proposed approach are also presented.

In many applications, such as communication, speech coding, and audio technology, not only the sampling frequency but also the actual sampling instants are of crucial importance. Fractional sample delay has been widely used in the domain of signal processing. There are many methods to obtain higher delay resolution. However the common defect is that they can not provide a continuous variable accurate delay. In this paper we take into account the characteristic of the information carried by the signal, which is the essence of the signal. A novel method based on the signal sparsity is prosed. Compared to the traditional interpolation algorithm, this method has lower normalized mean square error (NMSE) and can obtain arbitrary sample delay.

With the advent of Multi Input Multi Output (MIMO) systems, the system performance is highly dependent on the accurate representation of the channel condition that causes the wireless channel emulation to become increasingly important. The conventional Finite Impulse Response (FIR) based emulator has a high real-time but the complexity rapidly becomes impractical for larger array sizes. However, the frequency domain approach can avoid this problem and reduce the complexity for higher order arrays. The complexity comparison between in time domain and in frequency domain is made in this paper. The Fast Fourier Transform (FFT) as an important component of signal processing in frequency domain is briefly introduced and an FGPA system architecture based on CORDIC algorithm is proposed. The full design is implemented in Xilinx’s Virtex-5.

The Edge rotation and temperature diagnostic system (ERD) on EAST tokamak is designed to obtain profiles of the ion temperature and rotation velocity at the edge of the plasma. Multiple toroidal and poloidal chords are coupled to the entrance multi-slit of one spectrometer equipped with back-illuminated charged coupled device (CCD) camera that has a high quantum efficiency and high-readout speed. The cameral records spatially and spectrally resolved emission profiles with real time digitization. Line-integrated radiation from different ionization stages in the visible range is chosen as representative of the plasma in their regions of maximum emission. The diagnostic including the diagnostic cannula, collection assembly and spectrometer as well as CCD is discussed. The initial test results of the system are given.

Closed-loop MIMO technique standardized in LTE can support different layer transmissions through precoding operation to match the channel multiplexing capability. However, the performance of the limited size codebook still needs to be evaluated in real channel environment for further insights. Based on the wideband MIMO channel measurement in a typical indoor scenario, capacity loss (CL) of the limited size codebook relative to perfect precoding is studied first in two extreme channel conditions. The results show that current codebook design for single layer transmission is nearly capacity lossless, and the CL will increase with the number of transmitted layers. Furthermore, the capacity improvement of better codebook selection criterions is very limited compared to CL. Then we define the maximum capacity boost achieved by frequency domain layer adaption (FDLA) and investigate its sensitivity to SNR and channel condition. To survey the effect of frequency domain channel variation on MIMO-OFDM system, we define a function to measure the fluctuation levels of the key channel metrics within a subband and reveal the inherent relationship between them. Finally, a capacity floor resulted as the feedback interval increases in frequency domain.

A quantitative evaluation of various deconvolution methods and their applications in processing plasma emitted spectra was performed. The iterative deconvolution algorithms evaluated here include Jansson's method, Richardson–Lucy's method, the maximum a posteriori method and Gold's method. The evaluation criteria include minimization of the sum of squared errors and the sum of squared relative error of parameters, and their rate of convergence. After comparing deconvolved results using these methods, it was concluded that Jansson's and Gold's methods were able to provide good profiles that are visually close to the original spectra. Additionally, Gold's method generally gives the best results when considering all the criteria above. The applications to the actual plasma spectra obtained from the EAST tokamak with these methods are also presented in this paper. The deconvolution results with Gold's and Jansson's methods show that the effects of instruments can be satisfactorily eliminated and clear spectra are recovered.