One-pot synthesis and hydrogen peroxide electrochemical sensing of 3D TiO2/MnO2 nanorods assembled microspheres.

Nanorods assembled 3D microspheres of TiO2/MnO2 were prepared via a simple one-pot hydrothermal approach. The resultant composite material exhibited remarkable electrocatalytic activity for hydrogen peroxide (H2O2) in comparison to each single component. The electrochemical sensor constructed with TiO2/MnO2 exhibited a linear relationship within the range 0.0001-5.6 mmol·L-1 for H2O2. The limit of detection (LOD) and sensitivity for H2O2 were 0.03 µmol·L-1 (S/N = 3) and 316.6 µA (mmol·L-1)-1 cm-2. Moreover, this sensor can be employed to detect trace amount of H2O2 in serum and urine samples successfully, supporting an insight and strategy for a more sensitive electrochemical sensor.

Application of a Novel and Improved VGG-19 Network in the Detection of Workers Wearing Masks.

In order to work and travel safely during the outbreak of COVID-19, a method of security detection based on deep learning is proposed by using machine vision instead of manual monitoring. To detect the illegal behaviors of workers without masks in workplaces and densely populated areas, an improved convolutional neural network VGG-19 algorithm is proposed under the framework of tensorflow, and more than 3000 images are collected for model training and testing. Using VGG-19 network model, three FC layers are optimized into one flat layer and two FC layers with reduced parameters. The softmax classification layer of the original model is replaced by a 2-label softmax classifier. The experimental results show that the precision of the model is 97.62% and the recall is 96.31%. The precision of identifying the workers without masks is 96.82%, the recall is 94.07%, and the data set provided has a high precision. For the future social health and safety to provide favorable test data.

A study of vibroacoustic coupling between a pump and attached water-filled pipes.

This paper presents a model for the vibroacoustical behavior of a pump coupled with water-filled pipes. Coupling between (a) the pump and the inlet and outlet pipes, and (b) the pipe wall and the fluid contained in the pipe, is investigated through analytical modeling and numerical simulation. In the model, the pump is represented by a rigid body supported by multiple elastic mounts, and the inlet and outlet pipes by two semi-infinite water-filled pipes. The vibration characteristics of the coupled system under the excitation of mechanical forces and fluid-borne forces at the pump are calculated. The results enhance our understanding about how the input mechanical and fluid excitation energy at the pump is transmitted to the pipes and how to relate the piping vibroacoustical response to the excitations at the pump. This study assists in predicting dynamic stress in pipes for given excitations at the pump, and in developing methods to identify the nature (fluid or mechanical) of the excitation forces at the pump using the vibration and dynamic pressure measurements on the pump/pipe system.