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Vibration measurement and analysis play an important role in diagnosing mechanical faults, but existing vibration sensors are limited by issues such as dependence on external power sources and high costs. To overcome these challenges, the use of triboelectric nanogenerator (TENG)−based vibration sensors has recently attracted attention. These vibration sensors measure a small range of vibration frequencies and are not suitable for measuring high-frequency vibrations. Herein, a self-powered vibration sensor based on an elastic steel triboelectric nanogenerator (ES−TENG) is proposed. By optimizing the elastic steel sheet structure and combining time-frequency transformation and filtering processing methods, the measurement of medium- and high-frequency vibrations is achieved. These results demonstrate that the ES−TENG can perform vibration measurements in the range of 2–10,000 Hz, with a small average error (~0.42%) between the measured frequency and external vibration frequency values. Therefore, the ES−TENG can be used as a self-powered, highly-accurate vibration sensor for intelligent machinery monitoring.

The gut microbiome is associated with hepatitis B virus (HBV)-induced liver disease, which progresses from chronic hepatitis B, to liver cirrhosis, and eventually to hepatocellular carcinoma. Studies have analyzed the gut microbiome at each stage of HBV-induced liver diseases, but a consensus has not been reached on the microbial signatures across these stages. Here, we conducted by a systematic meta-analysis of 486 fecal samples from publicly available 16S rRNA gene datasets across all disease stages, and validated the results by a gut microbiome characterization on an independent cohort of 15 controls, 23 chronic hepatitis B, 20 liver cirrhosis, and 22 hepatocellular carcinoma patients. The integrative analyses revealed 13 genera consistently altered at each of the disease stages both in public and validation datasets, suggesting highly robust microbiome signatures. Specifically, Colidextribacter and Monoglobus were enriched in healthy controls. An unclassified Lachnospiraceae genus was specifically elevated in chronic hepatitis B, whereas Bilophia was depleted. Prevotella and Oscillibacter were depleted in liver cirrhosis. And Coprococcus and Faecalibacterium were depleted in hepatocellular carcinoma. Classifiers established using these 13 genera showed diagnostic power across all disease stages in a cross-validation between public and validation datasets (AUC = 0.65–0.832). The identified microbial taxonomy serves as non-invasive biomarkers for monitoring the progression of HBV-induced liver disease, and may contribute to microbiome-based therapies.

Harvesting wind energy from the ambient environment is a feasible method for powering wireless sensors and wireless transmission equipment. Triboelectric nanogenerators (TENGs) have proven to be a stable and promising technology for harvesting ambient wind energy. This study explores a new method for the performance enhancement and practical application of TENGs. An array of flag-type triboelectric nanogenerators (F-TENGs) for harvesting wind energy is proposed. An F-TENG consists of one piece of polytetrafluoroethylene (PTFE) membrane, which has two carbon-coated polyethylene terephthalate (PET) membranes on either side with their edges sealed. The PTFE was pre-ground to increase the initial charge on the surface and to enhance the effective contact area by improving the surface roughness, thus achieving a significant improvement in the output performance. The vertical and horizontal arrays of F-TENGs significantly improved the power output performance. The optimal power output performance was achieved when the vertical parallel distance was approximately 4D/15 (see the main text for the meaning of D), and the horizontal parallel distance was approximately 2D. We found that the peak output voltage and current of a single flag-type TENG of constant size were increased by 255% and 344%, respectively, reaching values of 64 V and 8 μA, respectively.

A cubic trigonometric Bezier curve analogous to the cubic Bezier curve, with two shape parameters, is presented in this work. The shape of the curve can be adjusted by altering the values of shape parameters while the control polygon is kept unchanged. With the shape parameters, the cubic trigonometric Bezier curves can be made close to the cubic Bezier curves or closer to the given control polygon than the cubic Bezier curves. The ellipses can be represented exactly using cubic trigonometric Bezier curves.

A new formulation for the representation and designing of curves and surfaces is presented. It is a novel generalization of Bézier curves and surfaces. Firstly, a class of polynomial basis functions with n adjustable shape parameters is present. It is a natural extension to classical Bernstein basis functions. The corresponding Bézier curves and surfaces, the so-called Quasi-Bézier (i.e., Q-Bézier, for short) curves and surfaces, are also constructed and their properties studied. It has been shown that the main advantage compared to the ordinary Bézier curves and surfaces is that after inputting a set of control points and values of newly introduced n shape parameters, the desired curve or surface can be flexibly chosen from a set of curves or surfaces which differ either locally or globally by suitably modifying the values of the shape parameters, when the control polygon is maintained. The Q-Bézier curve and surface inherit the most properties of Bézier curve and surface and can be more approximated to the control polygon. It is visible that the properties of end-points on Q-Bézier curve and surface can be locally controlled by these shape parameters. Some examples are given by figures.