Electronic noses are one of the predominant technological choices for gas mixture detection, but their application in real-world atmospheric environments still leaves several issues to be resolved. The key bottleneck is the effect of turbulence caused by the diffusion of gases in the atmosphere on the quantitative and qualitative analytical performance of the electronic nose. In light of this, this paper presents a quantitative and qualitative analysis strategy for gas mixture monitoring. This strategy adopts baseline manipulation of the raw sensor data to reduce drift interference, and then performs feature extraction on the multidimensional response signals of the MOS gas sensor array using principal component analysis (PCA). In order to improve gas mixture recognition accuracy, the whale optimization algorithm (WOA) is used to optimize the network structure of the long short-term memory (LSTM) model for turbulent gas mixture composition recognition. The least squares support vector machine (LSSVM) algorithm is adopted to implement turbulent gas mixture concentration prediction. This paper focuses on two aspects of hyper-parameter optimization for the development of an LSSVM with particle swarm optimization (PSO) and for improved training sample selection for the LSSVM which should subsequently increase the accuracy of concentration estimation. The effectiveness of the proposed strategy is evaluated with a dataset from a chemical sensor array exposed to turbulent gas mixtures. Experimental results revealed that the proposed strategy for turbulent gas mixtures has satisfactory outcomes for both qualitative gas composition recognition and quantitative gas concentration prediction.

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The use of high-energy radiation generated by electron collisions with a laser pulse is an effective method to treat cancer. In this paper, the spatial properties of radiation produced by electron collisions with a tightly focused linearly polarized laser pulse are investigated. Theoretical derivations and numerical simulations within the framework of classical electrodynamics show that the stronger the laser intensity, the higher the initial electron energy, and the longer the laser pulse, which can produce greater radiation power. An increase in the laser intensity expands the range of electron radiation and therefore reduces the collimation of the radiation. The collimation in the radiation is better when colliding with an electron of higher initial energy. The phenomenon that the radiated power of the electron varies periodically with the initial phase of the laser is also found. The results of this paper have important implications to produce strongly radiating and highly collimated rays.

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The nonlinear radiation of the electron is a distinctive feature of the action of tightly focused linearly polarized lasers. In this paper, from the perspective of radiation symmetry, the effect of laser parameters on the electron radiation power in the time domain is studied systematically. In the direction of maximum radiation, an asymmetric bimodal structure is found in the time domain. For this special structure, an explanation is given based on the electron dynamics perspective. The structure is compared with the symmetric bimodal structure in the classical theory. The increase in laser intensity, while significantly increasing the radiated power of the electron, exacerbates the asymmetry of electron radiation. The variation of the initial phase of the laser leads to a periodic variation of the electron motion, which results in a periodic extension of the electron spatial radiation with a period of π. Moreover, the existence of jump points with a phase difference of π in the range from 0 to 2π is found. The increase in pulse width reduces the radiated power, extends the radiation range, and alleviates the radiation asymmetry. Results in this paper contribute to the study of electron radiation characteristics in intense laser fields.