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Fourier transform infrared spectroscopy(FTIR) detection technology has the characteristics of high detection accuracy, fast scanning speed and wide spectral range, which can realize qualitative and quantitative analysis of gas, liquid or solid samples, and has been widely used in petrochemical, environmental gas testing and many other industries. The paper analyzes the research progress and limitations of FTIR quantitative analysis algorithms at this stage. Taking the industry as an example, the application effect of FTIR technology in the study of coal chemical structure, coal functional groups and gas detection is discussed. Finally, it points out the main problems that restrict the application of FTIR technology in the field of coal mine gas detection.

The Chinese clinical natural language is rich in a large amount of medical record information. Naming entity recognition for electronic medical records can help establish medical auxiliary diagnostic systems, which is of great significance for the development of the medical field. At the same time, it is conducive to downstream tasks such as relationship extraction and the implementation of knowledge graphs. However, Chinese electronic medical records have problems with difficulty in Chinese word segmentation, numerous medical terminology, and special expressions, which can easily lead to incorrect expression of text features. Therefore, this paper proposes a medical named entity recognition research model based on enhanced word information and graph attention, which improves the performance of the network model by enhancing local and global features. Due to the fact that embedding a single word vector for Chinese entity recognition can easily ignore word information and semantics in the text, this paper embeds a highly correlated word vector in the word vector, which not only enhances text representation but also avoids word segmentation errors. Additionally, a Med- Bert model for learning medical knowledge is embedded in the word embedding layer, which can dynamically generate feature vectors according to different contexts, helps solve the problem of polysemy and specialized vocabulary in electronic medical records. At the same time, adding a graph attention module in the coding layer enhances the network's ability to learn text context relationships and enhances the model's learning of medical special grammar. Finally, F1 values of 86.38% and 84.76% are obtained on the cEHRNER and cMedQANER datasets, respectively, showing better robustness compared to other models. [ABSTRACT FROM AUTHOR]

Gold microspheres modified with octadecanethiol as chromatographic stationary phase were prepared. The particles were characterized by the scanning electron micrograph (SEM), Fourier transform infrared spectroscopy (FT-IR), elemental analysis and nitrogen adsorption analysis. The average diameter, the surface area and the average pore diameter were 3.5 microm, 49.0 m2/g and 5.0 nm, respectively. The IR spectra demonstrated that C18 was bonded to the surface of gold microspheres with the carbon content of 0.56%. Using these microspheres as stationary phase, a 19 cm section of a total length of 36 cm capillary (100 microm i. d.) was packed electrokinetically, and the evaluations in capillary liquid chromatography and pressurized capillary electrochromatography were performed. The mobile phases (80% methanol) with extreme pH values (pH 1.0 or pH 12.0) were used to flush the column for 140 h. In order to investigate the chemical stability of the column, the retention factors before and after flushing were calculated and compared based on the experimental results. There was no remarkable deterioration on the retention factors after flushing, which demonstrated the column was stable pounds were separated using capillary liquid chromatography to examine the retention behavior of the column, and over 50,000 theoretical plates per meter and acceptable symmetry peaks were obtained. The pressurized capillary electrochromatographic properties of the column were investigated using a separation of the mixture of aniline and benzoic acid, and the separation was obtained when a 5 kV positive or negative voltage was applied. The research work confirmed the feasibility of using the octadecanethiol modified gold microspheres as a novel stationary phase for capillary liquid chromatography and pressurized capillary electrochromatography.