In experimental chambers for simulating the atmospheric near-surface conditions of Mars, or in situ measurements on Mars, the measurement of the humidity in carbon dioxide gas at low temperature and under low pressure is needed. For this purpose, polymer-based capacitive humidity sensors are used; however, these sensors are designed for measuring the humidity in the air on the Earth. The manufacturers provide only the generic calibration equation for standard environmental conditions in air, and temperature corrections of humidity signal. Because of the lack of freely available information regarding the behavior of the sensors in CO₂, the range of reliable results is limited. For these reasons, capacitive humidity sensors (Sensirion SHT75) were tested at the German Aerospace Center (DLR) in its Martian Simulation Facility (MSF). The sensors were investigated in cells with a continuously humidified carbon dioxide flow, for temperatures between −70 °C and 10 °C, and pressures between 10 hPa and 1000 hPa. For 28 temperature–pressure combinations, the sensor calibration equations were calculated together with temperature–dependent formulas for the coefficients of the equations. The characteristic curves obtained from the tests in CO₂ and in air were compared for selected temperature–pressure combinations. The results document a strong cross-sensitivity of the sensors to CO₂ and, compared with air, a strong pressure sensitivity as well. The reason could be an interaction of the molecules of CO₂ with the adsorption sites on the thin polymeric sensing layer. In these circumstances, an individual calibration for each pressure with respect to temperature is required. The performed experiments have shown that this kind of sensor can be a suitable, lightweight, and relatively inexpensive choice for applications in harsh environments such as on Mars.

Polymer-based capacitive humidity sensors emerged around 40 years ago; nevertheless, they currently constitute large part of sensors’ market within a range of medium (climatic and industrial) humidity 20−80%RH due to their linearity, stability and cost-effectiveness. However, for low humidity values (0−20%RH) that type of sensor exhibits increasingly nonlinear characteristics with decreasing of humidity values. This paper presents the results of some experimental trials of CMOS polymer-based capacitive humidity sensors, as well as of modelling the behaviour of that type of sensor. A logarithmic functional relationship between the relative humidity and the change of sensor output value at low humidity is suggested.

Graph convolutional networks (GCN) are an important research method for intelligent transportation systems (ITS), but they also face the challenge of how to describe the complex spatio-temporal relationships between traffic objects (nodes) more effectively. Although most predictive models are designed based on graph convolutional structures and have achieved effective results, they have certain limitations in describing the high-order relationships between real data. The emergence of hypergraphs breaks this limitation. A dynamic spatio-temporal hypergraph convolutional network (DSTHGCN) model is proposed in this paper. It models the dynamic characteristics of traffic flow graph nodes and the hyperedge features of hypergraphs simultaneously, achieving collaborative convolution between graph convolution and hypergraph convolution (HGCN). On this basis, a hyperedge outlier removal mechanism (HOR) is introduced during the process of node information propagation to hyper-edges, effectively removing outliers and optimizing the hypergraph structure while reducing complexity. Through in-depth experimental analysis on real-world datasets, this method has better performance compared to other methods.

This paper presents a method for implementing the configuration structure of an integrated computational core of a pulsed nuclear quadrupole resonance (NQR) sensor based on a field-programmable gate array (FPGA), which comprises the following modules: a three-channel direct digital synthesizer (DDS), a pulse sequence shaper and a software-defined radio. Experimental studies carried out using the in-circuit analyzer SignalTap Logic Analyzer have confirmed the reliability of the correct and stable operation of the functional modules of the configuration structure at all stages of signal transformations, starting from the formation of the envelope of the excitation pulses and ending with the obtainment of low-frequency quadrature signals at the outlet of the compensating filters. The time and frequency dependences of the amplitude of the output signals generated using the DDS based on a 48 bit phase accumulator are investigated. This development can be used when creating pulsed coherent NQR sensors in the frequency range of 1 MHz–50 MHz.