Publications by authors named "Ma Changzheng"

We report a 2-µm all-fiber nonlinear pulse compressor based on a tapered Pb-silicate photonic crystal fiber (PCF), which is capable of achieving large compression with low pedestal energy. A tapered Pb-silicate photonic crystal fiber with increased nonlinear coefficients is proposed for achieving self-similar pulse compression (SSPC) at 2 µm. The dynamic evolution of the fundamental order soliton is numerically analyzed based on the designed tapered fiber.

View Article and Find Full Text PDF
Article Synopsis
  • Researchers developed a new type of anti-resonant fiber (ARF) using an adaptive particle swarm optimization (PSO) algorithm, which differs from traditional methods that rely on stacking and parameter optimization.
  • The innovative approach involves breaking down classic fiber structures into points and optimizing their positions, leading to the creation of low confinement loss (CL) and high higher order mode extinction ratio (HOMER) structures called "bulb-shaped ARFs."
  • Among these new structures, the best performance achieved a CL of 2.21 × 10 dB/m at 1300 nm and a HOMER surpassing 14,000, offering a flexible method for designing non-uniform waveguides and exploring novel fiber configurations.
View Article and Find Full Text PDF
Article Synopsis
  • Screening patients for precancerous lesions of gastric cancer (PLGC) is crucial for prevention, and machine learning can enhance screening accuracy by analyzing noninvasive tongue images.
  • The study introduced a deep learning model, AITongue, which successfully identified links between tongue image features and PLGC and showed a 10.3% improvement in screening capability compared to traditional methods.
  • A smartphone app leveraging the AITongue model was also developed, making it easier for high-risk populations in China to access screenings and ultimately improve early detection.
View Article and Find Full Text PDF

Understanding the biological functions of molecules in specific human tissues or cell types is crucial for gaining insights into human physiology and disease. To address this issue, it is essential to systematically uncover associations among multilevel elements consisting of disease phenotypes, tissues, cell types and molecules, which could pose a challenge because of their heterogeneity and incompleteness. To address this challenge, we describe a new methodological framework, called Graph Local InfoMax (GLIM), based on a human multilevel network (HMLN) that we established by introducing multiple tissues and cell types on top of molecular networks.

View Article and Find Full Text PDF

Unmanned aerial vehicle borne frequency modulated continuous wave synthetic aperture radars are attracting more and more attention due to their low cost and flexible operation capacity, including the ability to capture images at different elevation angles for precise target identification. However, small unmanned aerial vehicles suffer from large trajectory deviation and severe range-azimuth coupling due to their simple navigational control and susceptibility to air turbulence. In this paper, we utilize the squint minimization technique to reduce this coupling while simultaneously eliminating intra-pulse motion-induced effects with an additional spectrum scaling.

View Article and Find Full Text PDF

In inverse synthetic aperture radar (ISAR) imaging, a target is usually regarded as consist of a few strong (specular) scatterers and the distribution of these strong scatterers is sparse in the imaging volume. In this paper, we propose to incorporate the sparse signal recovery method in 3D multiple-input multiple-output radar imaging algorithm. Sequential order one negative exponential (SOONE) function, which forms homotopy between 1 and 0 norms, is proposed to measure the sparsity.

View Article and Find Full Text PDF
Article Synopsis
  • Large 2-D sparse arrays produce high-resolution microwave images, but the presence of high sidelobes creates artifacts that reduce dynamic range.
  • The paper proposes using the CLEAN technique for removing these artifacts, although it acknowledges that the traditional DFT method for estimating signal amplitudes is not very effective.
  • Instead, it combines DFT for initial estimates with a maximum likelihood estimation method to improve accuracy and uses time domain information to lessen sidelobe effects, demonstrating improved results in numerical simulations.
View Article and Find Full Text PDF