Real-time frequency measurement based on parallel pipeline FFT for time-stretched acquisition system

Real-time frequency measurement for non-repetitive and statistically rare signals are challenging problems in the electronic measurement area, which places high demands on the bandwidth, sampling rate, data processing and transmission capabilities of the measurement system. The time-stretching sampling system overcomes the bandwidth limitation and sampling rate limitation of electronic digitizers, allowing continuous ultra-high-speed acquisition at refresh rates of billions of frames per second. However, processing the high sampling rate signals of hundreds of GHz is an extremely challenging task, which becomes the bottleneck of the real-time analysis for non-stationary signals. In this work, a real-time frequency measurement system is designed based on a parallel pipelined FFT structure. Tens of FFT channels are pipelined to process the incoming high sampling rate signals in sequence, and a simplified parabola fitting algorithm is implemented in the FFT channel to improve the frequency precision. The frequency results of these FFT channels are reorganized and finally uploaded to an industrial personal computer for visualization and offline data mining. A real-time transmission datapath is designed to provide a high throughput rate transmission, ensuring the frequency results are uploaded without interruption. Several experiments are performed to evaluate the designed real-time frequency measurement system, the input signal has a bandwidth of 4 GHz, and the repetition rate of frames is 22 MHz. Experimental results show that the frequency of the signal can be measured at a high sampling rate of 20 GSPS, and the frequency precision is better than 1 MHz.Comment: 11 pages, 14 figure

Multi-level feature fusion network combining attention mechanisms for polyp segmentation

Clinically, automated polyp segmentation techniques have the potential to significantly improve the efficiency and accuracy of medical diagnosis, thereby reducing the risk of colorectal cancer in patients. Unfortunately, existing methods suffer from two significant weaknesses that can impact the accuracy of segmentation. Firstly, features extracted by encoders are not adequately filtered and utilized. Secondly, semantic conflicts and information redundancy caused by feature fusion are not attended to. To overcome these limitations, we propose a novel approach for polyp segmentation, named MLFF-Net, which leverages multi-level feature fusion and attention mechanisms. Specifically, MLFF-Net comprises three modules: Multi-scale Attention Module (MAM), High-level Feature Enhancement Module (HFEM), and Global Attention Module (GAM). Among these, MAM is used to extract multi-scale information and polyp details from the shallow output of the encoder. In HFEM, the deep features of the encoders complement each other by aggregation. Meanwhile, the attention mechanism redistributes the weight of the aggregated features, weakening the conflicting redundant parts and highlighting the information useful to the task. GAM combines features from the encoder and decoder features, as well as computes global dependencies to prevent receptive field locality. Experimental results on five public datasets show that the proposed method not only can segment multiple types of polyps but also has advantages over current state-of-the-art methods in both accuracy and generalization ability

The multifunctional ascorbate peroxidase MoApx1 secreted by Magnaporthe oryzae mediates the suppression of rice immunity

Fungi secrete effector proteins, including extracellular redox enzymes, to inhibit host immunity. Redox enzymes have been hypothesized to inhibit host reactive oxygen species (ROS); however, how they suppress host immunity remains unknown. We characterized an extracellular ascorbate peroxidase (MoApx1) that is secreted into rice chloroplasts by the rice blast fungus Magnaporthe oryzae. MoApx1 displays multifunctional capabilities that significantly contribute to fungal virulence. Firstly, MoApx1 neutralizes host-derived H2O2 within the chloroplast through its peroxidase activity, thereby inhibiting chloroplast ROS (cROS)-mediated defense responses. Secondly, MoApx1 targets the photosystem I subunit OsPsaD, disrupting photosynthetic electron transport to further suppress cROS production. Most importantly, MoApx1 has evolved a fungal-specific starch-binding domain that binds host starch, inhibiting its degradation and disrupting the energy supply required for host resistance. Our findings underscore the importance of a novel multifaceted strategy, potentially widely employed by other fungal pathogens, in suppressing host immunity during host–microbe interactions

A multi-tissue single-cell expression atlas in cattle

Systematic characterization of the molecular states of cells in livestock tissues is essential for understanding the cellular and genetic mechanisms underlying economically and ecologically important physiological traits. Here, as part of the Farm Animal Genotype-Tissue Expression (FarmGTEx) project, we describe a comprehensive reference map including 1,793,854 cells from 59 bovine tissues in calves and adult cattle, spanning both sexes, which reveals intra-tissue and inter-tissue cellular heterogeneity in gene expression, transcription factor regulation and intercellular communication. Integrative analysis with genetic variants that underpin bovine monogenic and complex traits uncovers cell types of relevance, such as spermatocytes, responsible for sperm motility and excitatory neurons for milk fat yield. Comparative analysis reveals similarities in gene expression between cattle and humans, allowing for the detection of relevant cell types to study human complex phenotypes. This Cattle Cell Atlas will serve as a key resource for cattle genetics and genomics, selective breeding and comparative biology

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data