Electronic skin (e-skin) with excellent flexibility and comfortable wearability has attracted considerable attention in the past decade. Flexible strain sensors are one of the key elements of e-skins, which are always attached to the joints of humans or robots for motion monitoring. However, most strain sensors previously reported cannot fit different joints to measure the bending angles without calibration. This work aims to propose a flexible strain sensor with an adaptive model for automatically calculating the bending angle of different joints. The proposed sensor is a screen-printed liquid metal strain sensor with a size of 120 mm (L) $\times20$ mm (W) $\times 400\mu $ m (H). The real-time changes in different curvatures as the sensor bend has been investigated. Based on the curvature-strain-bending angle relationship of different joints, we use the Gaussian function to model the bending angle solution for adaptive curvature. Experimental results show that the proposed sensor can be served as the electronic skin on the joint’s surface to measure the bending angle adaptively, which provides a promising path for adaptive motion monitoring in human movement, soft robotics, prosthetic devices, etc.

With the growth of industrialization in recent years, the quality of drinking water has been a great concern due to increasing water pollution from industries and industrial farming. Many monitoring stations are constructed near drinking water sources for the purpose of fast reactions to water pollution. Due to the relatively low sampling frequencies in practice, mathematic prediction models are clearly needed for such monitoring stations to reduce the delay between the time points of pollution occurrences and water quality assessments. In this work, 2190 sets of monitoring data from automatic water quality monitoring stations in the Qiandao Lake, China from 2019 to 2020 were collected, and served as training samples for prediction models. A grey relation analysis-enhanced long short-term memory (GRA-LSTM) algorithm was used to predict the key parameters of drinking water quality. In comparison with conventional LSTM models, the mean absolute errors (MAEs) to predict the four parameters of water quality, i.e., dissolved oxygen (DO), permanganate index (COD), total phosphorus (TP), and potential of hydrogen (pH), were reduced by 23.03%, 10.71%, 7.54%, and 43.06%, respectively, using our GRA-LSTM algorithm, while the corresponding root mean square errors (RMSEs) were reduced by 24.47%, 5.28%, 6.92%, and 35.89%, respectively. Such an algorithm applies to predictions of events with small amounts of data, but with high parametric dimensions. The GRA-LSTM algorithm offers data support for subsequent water quality monitoring and early warnings of polluting water sources, making significant contributions to real-time water management in basins.

The quality of the air exerts considerable effects on human health, and meteorological factors affect air quality. The relationships between meteorological factors and air quality parameters are complex dependency correlations. This article is based on the air quality monitoring data and meteorological monitoring data obtained from a monitoring station in Binjiang District, Hangzhou City, China, spanning from 01:00 on 14 April 2021 to 23:00 on 31 December 2021. The Informer model was used to explore the air quality parameters’ response to meteorological factors. By analyzing 12 different kinds of 2-Minute Average Wind Speed (2-MAWSP), 10-Minute Average Wind Speed (10-MAWSP), and Maximum Wind Speed (MXSPD); 16 different kinds of Hourly Precipitation (HP) and Air Temperature (AT); 11 different kinds of Relative Humidity (RH); and 8 different kinds of Station Pressure (STP), the following results were obtained: (1) The influence of wind speed on various air quality parameters is multifaceted and lacks a standardized form, potentially influenced by factors like wind direction and geographical location. One clear effect of wind speed is evident in the levels of particulate matter 10 (with an aerodynamic diameter smaller than 10 μm, PM₁₀), as the values of this parameter first decrease and then increase with increasing wind speed. (2) HP has an evident reducing effect on most air quality parameters, including particulate matter (including PM_2.5 and PM₁₀), ozone (O₃), sulfur dioxide (SO₂), and nitrogen dioxide (NO₂), as well as nitrogen oxides (NO_x). (3) The increase in AT has a clear reducing effect on the concentration of NO₂, while the trend for the concentrations of PM₁₀ and NO_x is one of initial decrease followed by a gradual rise. (4) RH only reduces the concentrations of SO₂ and PM₁₀. (5) With the rise in STP, the concentrations of most air quality parameters generally rise as well, except for the decrease in NO_x concentration. This can give some indications and assistance to meteorological and environmental departments for improving air quality. This model can be used for a performance analysis and the forecasting of multi-parameter non-correlated systems.

Computational and experimental methods were used to study a propeller coated with hydrophobic material and a propeller with a conventional surface for comparison. In CFD simulations, the blade surface mesh was arranged in a way to set non-slip or free slip wall boundary conditions with different proportions to define the level of surface slip. The conventional and the hydrophobic material propellers defined by different surface slip rates were simulated under different advance speed coefficients and different rotational speeds. Propeller performance results, blade pressure, and the Liutex vorticity distribution were studied. An experimental platform was established to study the velocity field around the propeller using a Particle Image Velocimetry (PIV) device. The CFD calculation results were compared with the PIV results. It was found that the calculation results using a 75% surface slip rate were closer to the experimental results. The calculation results show that the propeller coated with hydrophobic material has improved thrust and efficiency compared with the propeller with conventional material. The hydrophobic material can significantly reduce the low-speed region downstream of the propeller hub. The hub and the tip vortices shown by the Liutex are also significantly reduced. Those changes help to improve the propulsion efficiency.