Molecular structure and spectroscopic properties of two radicals of C4H2N: a DFT study.

CONTEXT: The cyano propargyl radical (CH2C3N and HC3HCN) is important reaction intermediate in both combustion flames and extraterrestrial environments such as cold molecular clouds and circumstellar envelopes of carbon stars. The acquisition of spectroscopic constants and anharmonic effect facilitates a more in-depth study of this radical. However, the data available in the literature do not allow the precise predictions for it in the interstellar medium. In this work, complete spectroscopic parameters as well as anharmonic constants of two radicals of C4H2N have been evaluated by different DFT methods. The calculated results show that it is reasonable to study the molecular spectroscopic properties of C4H2N by wB97XD/6-311++G theoretical level. On this basis, the sextic centrifugal distortion constants, anharmonic constants, vibration-rotation interaction constants, and so on are predicted for the study of high-precision rovibrational spectrum. In addition, the relationship between the anharmonic effect and vibration mode of CH2C3N and HC3HCN and their infrared spectroscopic characteristics are discussed. METHODS: The calculation of the anharmonic force fields and spectroscopy properties was performed using B3LYP, B3PW91, CAM-B3LYP, and wB97XD methods combined with the 6-311++G and aug-ccpVTZ basis sets, respectively, by the Gaussian16 program suite. The IR spectra were performed with Multiwfn3.8.

[Emission Characteristics of Gas-and Particle-Phase Polycyclic Aromatic Hydrocarbons from Cooking].

Polycyclic aromatic hydrocarbons (PAHs) play a key role in the formation of secondary organic areole and ozone. This study sampled three commercial Chinese restaurants and a food plant in Shenzhen to analyze the emission characteristics of PAHs, especially the alkyl PAHs in both gas and particle phases. The results showed that the ρ(total PAHs)in the particle and gas phase were (1381.6±140.5) ng·m-3, (1030.2±116.4) ng·m-3, (908.3±111.9) ng·m-3, and (838.0±93.5) ng·m-3 in the food plant, Sichuan, Cantonese, and Zhejiang restaurants, respectively. More than 60% of the PAHs were distributed in the gas phase, especially the lower molecular weight PAHs (lower than Chrysene). The gas phase proportion of naphthalene was the highest, with over 75% of it distributed in the gas phase. However, the PAHs with a higher molecular weight than that of benzo(b)fluorescence were mainly distributed in the particle phase. The total concentration of alkyl PAHs emitted from cooking was much lower than that of the corresponding parent PAHs, and the distribution characteristics of alkyl PAHs were quite different from those of other emission sources. The linear fitting of lgKp and lgPL showed that the slopes of the three commercial restaurants ranged from -0.25 to -0.28, whereas for the food plant, the value was -0.18, which indicates that the gas-particle partitioning of PAHs were not in equilibrium.

[Review of Screening and Applications of Organic Tracers in Fine Particulate Matter].

Specific organic compounds within atmospheric particulate matter are indicators of specific pollution sources and, as such, can be used to differentiate inputs from various air pollution emissions sources in urban areas. Therefore, many studies have been conducted to detect organic particulate matter and screen the associated organic tracers that provide provenance information. This review provides a brief summary of the emission characteristics of biomass burning, cooking, fossil fuel combustion, and traffic. The particular marker compounds that carry provenance information for these four emission sources are discussed and diagnostic ratios are calculated to discuss the use of organic tracers in source apportionment. The shortcomings and new directions of using source tracer screening are also discussed.

Chemical characterization of particulate organic matter from commercial restaurants: Alkyl PAHs as new tracers for cooking.

Cooking is one of the primary sources of particulate organic matter (POM) in urban environments. Numerous experiments have been performed to investigate the composition of POM generated during cooking. However, there still remain substantial uncertainties in our knowledge regarding the emission characteristics of alkyl polycyclic aromatic hydrocarbons (PAHs) from cooking. In addition, previous studies have selected several tracers for Chinese cooking; however, these results were acquired based on observations in the Pearl River Delta region of China, and only four of the eight Chinese cooking styles were tested. Therefore, the organic compositions of the PM2.5 emitted from four Chinese cooking restaurants in different cities are examined to investigate the emission characteristics of alkyl PAH and to verify whether the selected tracers vary with geographical location and cooking styles. In this study, C1- and C2-phenanthrenes/anthracenes, and C1-pyrenes were detected in the PM2.5 from the four tested restaurants, but the concentrations of these PAH alkyl homologues were all at low levels, and also much lower than the corresponding parent PAHs. However, the distribution pattern of the alkyl PAHs in the cooking fumes was significantly different from that in the PM from other emission sources. Additionally, some candidate tracers for cooking such as levoglucosan were less influenced by cooking styles or geographical location. Thus, these alkyl PAHs in conjunction with other specific tracers for cooking were utilized to estimate the contribution of cooking to ambient organic carbon. The results showed that the estimates from the chemical mass balance model that includes alkyl PAHs will be higher than the model that does not, and in the case of high alkyl PAHs ambient concentrations, the model that includes alkyl PAHs will provide more reasonable results.

[Emission Characteristics of Particulate Organic Matter from Cooking].

Cooking is an important source of atmospheric particulate organic matter (POM). In this study, four Chinese restaurants in Shenzhen (west style, dim-sim restaurant, worker's canteen, and Korean cuisine) were sampled to examine the chemical composition of POM and research molecular tracers. The result showed that more than 60% of the PM2.5 mass was due to organic compounds. For the quantified organic compounds, the results indicated that fatty acids, dicarboxylic acids, and n-alkanes were the major organic compounds emitted from all cooking styles, PAHs, sterols, and monosaccharide anhydrides were found at relatively low levels. The composition of POM was strongly influenced by cooking style. The cooking styles of the west and Korean restaurant emitted the most abundant fatty acids, n-alkanes, and PAHs, but the least sterols and monosaccharide anhydrides, whereas the dim-sim restaurant and worker's canteen displayed the opposite results. The values of Fla/(Fla+Pyr) and LG/(Gal+Man) provided candidate tracers for cooking because they were less influenced by the cooking styles and were significantly different from other pollutant sources. Furthermore, cooking contributed significant amounts of fatty acids and dicarboxylic acids to atmospheric PM in Shenzhen.

Utilizing soft constraints to enhance medical relation extraction from the history of present illness in electronic medical records.

Relation extraction between medical concepts from electronic medical records has pervasive applications as well as significance. However, previous researches utilizing machine learning algorithms judge the semantic types of medical concept pair mentions independently. In fact, different concept pair mentions in the same context are of dependencies which can provide beneficial evidences for identifying their relation types. To the best of our knowledge, only one study has considered such dependencies in discharge summaries. However, its hard constraints are not applied effectively to the History of Present Illness (HPI) in electronic Medical Records. According to the writing characteristics of HPI records, we generalize two regularities of dependencies among concept pairs mentioned in an HPI record to enhance the performance of relation extraction. We incorporate the two soft constraints corresponding to the regularities and the posterior probabilities returned by a local classifier into a joint inference process which applies Integer Quadratic Programming method to carry out collective classification for all concept pair mentions in an HPI record. We implement four local classification models including support vector machine, logistics regression, random forest and piecewise convolutional neural networks to examine the performance of our approach. A series of experimental results demonstrate that our collective classification method has made a principal improvement and outperforms the other state-of-the-art methods.