Selective Determination of Pyridine Alkaloids in Tobacco by PFTBA Ions/Analyte Molecule Reaction Ionization Ion Trap Mass Spectrometry

The application of perfluorotributylamine (PFTBA) ions/analyte molecule reaction ionization for the selective determination of tobacco pyridine alkaloids by ion trap mass spectrometry (IT-MS) is reported. The main three PFTBA ions (CF3+, C3F5+, and C5F10N+) are generated in the external source and then introduced into ion trap for reaction with analytes. Because the existence of the tertiary nitrogen atom in the pyridine makes it possible for PFTBA ions to react smoothly with pyridine and forms adduct ions, pyridine alkaloids in tobacco were selectively ionized and formed quasi-molecular ion [M + H]+and adduct ions, including [M + 69]+, [M + 131]+, and [M + 264]+, in IT-MS. These ions had distinct abundances and were regarded as the diagnostic ions of each tobacco pyridine alkaloid for quantitative analysis in selected-ion monitoring mode. Results show that the limit of detection is 0.2 μg/mL, and the relative standard deviations for the seven alkaloids are in the range of 0.71% to 6.8%, and good recovery of 95.6% and 97.2%. The proposed method provides substantially greater selectivity and sensitivity compared with the conventional approach and offers an alternative approach for analysis of tobacco alkaloids

Comparative study of surface integral methods in aeroacoustic prediction

Introduction: Surface integral methods based on the acoustic analogy and Kirchhoff formulation are widely employed in computational aeroacoustics. The computational accuracy is usually highly dependent on the selections of the acoustic prediction method and of the integral surfaces.Methods: This paper analyzes the pros and cons of each aeroacoustic prediction method and studies numerically sound generated from flow past a circular cylinder by employing different surface integral methods. The acoustic analogy based on the impermeable solid surfaces either ignores the quadrupole contribution or needs high computational cost to calculate the quadrupole contribution, and the acoustic analogy based on the permeable integral surfaces usually suffers from the spurious source issue.Results: Both the pressure-based or density-based Kirchhoff formulations can be used in aeroacoustic prediction, however, the numerical results indicate that the pressure-based Kirchhoff formulation also suffers from the issue of the spurious sound because the pressure fluctuations at the permeable integral surfaces are contaminated by hydrodynamic component.Discussion: It seems that only the density-based Kirchhoff formulation does not suffer from the issue of the spurious sound, but this formulation requires the acoustic sources should be extracted from compressible flow simulations

An Attention and Wavelet Based Spatial-Temporal Graph Neural Network for Traffic Flow and Speed Prediction

Traffic flow prediction is essential to the intelligent transportation system (ITS). However, due to the complex spatial-temporal dependence of traffic flow data, it is insufficient in the extraction of local and global spatial-temporal correlations for the previous process on road network and traffic flow modeling. This paper proposes an attention and wavelet-based spatial-temporal graph neural network for traffic flow and speed prediction (STAGWNN). It integrated attention and graph wavelet neural networks to capture local and global spatial information. Meanwhile, we stacked a gated temporal convolutional network (gated TCN) with a temporal attention mechanism to extract the time series information. The experiment was carried out on real public transportation datasets: PEMS-BAY and PEMSD7(M). The comparison results showed that our proposed model outperformed baseline networks on these datasets, which indicated that STAGWNN could better capture the spatial-temporal correlation information

An Attention and Wavelet Based Spatial-Temporal Graph Neural Network for Traffic Flow and Speed Prediction

Traffic flow prediction is essential to the intelligent transportation system (ITS). However, due to the complex spatial-temporal dependence of traffic flow data, it is insufficient in the extraction of local and global spatial-temporal correlations for the previous process on road network and traffic flow modeling. This paper proposes an attention and wavelet-based spatial-temporal graph neural network for traffic flow and speed prediction (STAGWNN). It integrated attention and graph wavelet neural networks to capture local and global spatial information. Meanwhile, we stacked a gated temporal convolutional network (gated TCN) with a temporal attention mechanism to extract the time series information. The experiment was carried out on real public transportation datasets: PEMS-BAY and PEMSD7(M). The comparison results showed that our proposed model outperformed baseline networks on these datasets, which indicated that STAGWNN could better capture the spatial-temporal correlation information

Numerical Study of Porous Treatments on Controlling Flow around a Circular Cylinder

Porous materials fixed on and downstream the cylinder can reach a much better effect in suppressing wall pressure fluctuations. In the present paper, numerical comparative studies have been conducted to investigate passive control of flow past a cylinder surface, in which three schemes with different porous treatments are applied to compare their pros and cons. The results show all of the three schemes of porous materials increase the time-averaged flow drag and reduce fluctuations of lift and drag forces. It can be concluded the velocity gradient reduction inside the boundary layer and the vortex shedding delay through porous coating, as well as reverse transition from turbulent vortex shedding into laminar through porous treatment downstream the cylinder, are main flow control mechanisms of porous materials. These mechanisms all reduce fluctuations of lift and drag fluctuations, but have a distinct effect on the features of wake evolution, such as the wake width and length as well as the fluctuating components of the flow velocity. In addition, the wake evolution is highly affected by the location of porous materials

Numerical Study of Porous Treatments on Controlling Flow around a Circular Cylinder

Porous materials fixed on and downstream the cylinder can reach a much better effect in suppressing wall pressure fluctuations. In the present paper, numerical comparative studies have been conducted to investigate passive control of flow past a cylinder surface, in which three schemes with different porous treatments are applied to compare their pros and cons. The results show all of the three schemes of porous materials increase the time-averaged flow drag and reduce fluctuations of lift and drag forces. It can be concluded the velocity gradient reduction inside the boundary layer and the vortex shedding delay through porous coating, as well as reverse transition from turbulent vortex shedding into laminar through porous treatment downstream the cylinder, are main flow control mechanisms of porous materials. These mechanisms all reduce fluctuations of lift and drag fluctuations, but have a distinct effect on the features of wake evolution, such as the wake width and length as well as the fluctuating components of the flow velocity. In addition, the wake evolution is highly affected by the location of porous materials

Non-Woven Fabric Thermal-Conductive Triboelectric Nanogenerator via Compositing Zirconium Boride

With the vigorous development of the Internet of Things, 5G technology, and artificial intelligence, flexible wearable sensors have received great attention. As a simple and low-cost power supply in wearable sensors, the triboelectric nanogenerator (TENG) has a wide range of applications in the field of flexible electronics. However, most polymers are thermally poor conductors (less than 0.1 W/(m·K)), resulting in insufficient heat dissipation performance and limiting the development of TENG. In this study, a high-performance non-woven fabric TENG with strong thermal conductivity (0.26 W/m·K) was achieved by introducing ZrB2 into the polyurethane (PU) matrix. The excellent output performance with an open circuit voltage (Voc) of 347.6 V, a short circuit current (Isc) of 3.61 μA, and an accumulated charge of 142.4 nC endows it with good sensitivity. The electrospun PU/ZrB2 composites exhibit excellent sensing performance to detect body movements in situ, such as pressing, clapping, running, and walking. Moreover, the generated power can light up 224 LED bulbs as a demonstration of self-powering ability

Analysis of patent application attention: a network analysis method

Patent is an important embodiment of innovation. Before patent application, many people will check a patent application process on the Internet to understand the steps of a patent application. In fact, these people’s search is also a means to understand whether innovative enterprises or individuals imply the importance of innovation. It has become a new crucial problem to obtain more information about time-series data. Research has found that the concept of VG can provide deeper information in time-series data so that it can understand the information of patent applications more comprehensively. After analyzing the data from 1 January 2011 to 31 December 2018, we find: i) there are very few peaks and valleys, and 80% of searches are in the normal range. ii) according to the central value of the ranking, it can be found that the peaks of the annual patent application search times time series occurred in December last year, after January, February of this year or after August-October, and iii) after clustering the time series data, we find that the attention of people shows noticeable segmentation effect.Published versionThis paper is supported in part by the National Natural Science Foundation of China under Grant 71871159, in part by the Fujian innovation strategy research plan project under Grant 2020R0021, in part by the Fujian Social Science Planning Project under Grant FJ2020B024, in part by the 2nd Fujian Young Eagle Program Youth Top Talent Program, and in part by the Fujian science and technology economic integration service platform. The Academy-Locality Cooperation Project of the Chinese Academy of Engineering under Grant 2021-FJZD-4

Records of fire and its controls on coastal plain of Laizhou Bay, China since 5000 years

Disentangling fire and its controls over thousands of years ago is a major challenge in the study of paleofires. In this paper, we synthesize sedimentary charcoal and black carbon from the coastal plain of Laizhou Bay, China to improve our ability to reconstruct fire history in the past 5000 years, and to assess the controls of fire using principal component analysis and multiple regression approach. The results show that there were three distinct fire episodes at the intervals of 5300-5100 yr BP., 1190-1060 yr BP., and 300-0 yr BP., based on the Changyi (CY) profile. A large-scale fire episode was synchronous with a rapid climate variability that occurred 5300 yr BP., which had frequent drought and cold epoch. High fluxes of black carbon and charcoal were closely related to mass migration and the use of fire for land reclamation from 1190 to 1060 yr BP. Subsequently, anthropogenic biomass burning for cereal cultivation has reached a higher level over the past 300 years. However, between 4600 and 4000 yr BP. the shifts in the frequency of high-magnitude floods and climate aridity consequently resulted in the decline of fire-episode frequency and the abandonment of the late Neolithic settlements in the study region. Therefore, climate is still a prerequisite factor for fire occurrence on the southern coast of Laizhou Bay in the past 5000 years. A rapid climate variability was not only responsible for various fire patterns, but also could affect human settlements and the mode of production during middle-late Holocene. In the past 1000 years, human land use has been a more important control of fire. However, temperature has become one of the evidently identified controls of fire across the study area in recent decades. To synthesize the methods of Principal Component Analysis and Multiple Regression Analysis with multi-proxy evidence is necessary for us to better understand fire and its controls on coastal plain of Laizhou Bay at the region

Characterization of Traditional Chinese Sesame Oil by Using Headspace Solid-Phase Microextraction/Gas Chromatography–Mass Spectrometry, Electronic Nose, Sensory Evaluation, and RapidOxy

Xiao Mo Xiang You (XMXY) is a traditional Chinese sesame oil variety that is obtained through a hot water flotation process. This unique process gives the oil a unique aroma, health benefits, and excellent product stability. Although XMXY is always the most expensive among all the sesame oil varieties, it is usually used as a flavoring in many traditional Chinese daily food products and is increasingly popular. In order to reveal the characteristics of the oil, the volatile components, sensory evaluation, and oxidation stability of five XMXY samples were, respectively, analyzed by using headspace solid-phase microextraction/gas chromatography–mass spectrometry, an electronic nose, sensory evaluation, and RapidOxy. Comparisons and multidimensional statistical analysis were also carried out to distinguish XMXY from roasted sesame oil (RSO) and cold-pressed sesame oil (CSO) samples. In total, 69 volatiles were identified from XMXY, RSO, and CSO samples. Some compounds possessed high odor activity value (OAV > 1) in XMXY, including heterocyclic compounds, phenols, and sulfur-containing compounds. Additionally, they were also the main volatile components that distinguish XMXY from RSO and CSO. Roasted and nutty aromas were the dominant aroma attributes of XMXY. XMXY had better flavor intensity and oxidation stability than the other two sesame oil samples. These results are very valuable for the quality control and product identification of traditional Chinese sesame oil