Qualitative and quantitative analysis of four different polarity fractions from Huang-Lian-Jie-Du-Decoction by HPLC-DAD-ESI-MS/MS and their related neuroprotective effects

Huang-Lian-Jie-Du-Decoction （HLJDD） has been widely used for the treatment of Alzheimer＇s disease （AD） in clinic. However, the relationship between its chemical profile and neuroprotective bioactivity was not clearly clarified yet. In present study, the water extract of HLJDD and subsequent three polarity fractions divided by different reagents were investigated. A total of 17 chromatographic peaks were confirmed by comparison with standards and their UV, MS spectra. Among them, 11 major compounds were determined by HPLC-DAD method with good linear regression relationship （r2, 0.9994-0.9999）, precisions （inter-day precision RSD, 0.79%-1.07%; intra-day precision RSD, 1.59%-2.10%）, repeatability （RSD, 1.66%-3.67%）, stability （RSD, 1.26%-4.77%） and recovery （95.24%-105.41%, RSD, 0.29%-2.69%）. Furthermore, PC12 cells and primary neurons cells were used for the neuroprotective effective assessment of aforementioned four samples from HLJDD. 3＂he total aqueous extract and n-butanol extract of HLJDD presented more significant effects than the other two parts. According to their quality and quantity determination results, iridoids and alkaloids have a positive correlation with the neuroprotective effectiveness of HLJDD.

Qualitative and quantitative analysis of atmospheric methanol using a continuous-wave terahertz spectrometer

We present a specific-window method to subtract the interference of water vapor on terahertz frequency-domain spectroscopy（THz-FDS） at ambient temperature and pressure. A continuous-wave spectrometer based on photomixing was utilized to obtain THz-FDS of methanol vapor in the range of 50–1200 GHz. The distinctly spaced absorption features in the neighborhood of atmospheric windows of transparency were selected to perform linear fitting versus the calculated absorption cross section and obtain the concentration of methanol. Furthermore, the gradually decreased methanol vapor was quantified to demonstrate the reliability of the method.

GRINDING OF DOUBLE DISC GRINDING MACHINE

The grinding of two parallel sides of a component is accomplished with theaccuracy and higher productivity by passing a blank through the truncated cone shape grinders, whichare turned angles. The machine is designated by the name of double disc grinding machine (DDGM).Usually, it is used in the mass production. The relationship between these angles, the accuracy,productivity, allowance and parameters of the machine and technology is explained in detail by math,such as vector analysis, transformation of 3D space coordinates, etc. Therefore, in the aspects ofqualitative and quantitative analyses, the grinding potential of DDGM is enormous increased andsuperior to conventional methods. Furthermore, the theoretical foundation of DDGM grinding designand technology is provided to improve, to expand and to create for future. The established machinedesign and practical experience of grinding technology will get great benefit by them.

Reliability Optimization in the Islanded Mode of Microgrid

A microgrid is a combination of distributed energy resources and controllable loads. The main objective of this research is to optimize energy flow within a microgrid with regards to reliability in grid connected mode. A microgrid with combined heat and power, natural gas generator, diesel generator, solar energy, wind energy, and battery energy storage along with a critical load is considered in this research. An event oriented analytical method called FTA （fault trees analysis） is implemented for reliability optimization using PTC Windchill Solutions software in a microgrid. The reliability of each component in each energy source of the microgrid is calculated using FTA. The reliability of the critical load is evaluated. The quantitative and qualitative results of FTA are evaluated in order to interpret the results of fault tree. The sensitivity and uncertainty of the fault tree results for critical load is deduced by calculating the importance measures such as risk achievement worth, risk reduction worth, criticality importance and Fussel-Vesely importance. Finally from the results the components that are sensitive and at high risk are deduced.

Parametric sensitivity analysis of precipitation and temperature based on multi-uncertainty quantification methods in the Weather Research and Forecasting model

Sensitivity analysis(SA) has been widely used to screen out a small number of sensitive parameters for model outputs from all adjustable parameters in weather and climate models, helping to improve model predictions by tuning the parameters. However, most parametric SA studies have focused on a single SA method and a single model output evaluation function, which makes the screened sensitive parameters less comprehensive. In addition, qualitative SA methods are often used because simulations using complex weather and climate models are time-consuming. Unlike previous SA studies, this research has systematically evaluated the sensitivity of parameters that affect precipitation and temperature simulations in the Weather Research and Forecasting(WRF) model using both qualitative and quantitative global SA methods. In the SA studies, multiple model output evaluation functions were used to conduct various SA experiments for precipitation and temperature. The results showed that five parameters(P3, P5, P7, P10, and P16) had the greatest effect on precipitation simulation results and that two parameters(P7 and P10) had the greatest effect for temperature. Using quantitative SA, the two-way interactive effect between P7 and P10 was also found to be important, especially for precipitation. The microphysics scheme had more sensitive parameters for precipitation, and P10(the multiplier for saturated soil water content) was the most sensitive parameter for both precipitation and temperature. From the ensemble simulations, preliminary results indicated that the precipitation and temperature simulation accuracies could be improved by tuning the respective sensitive parameter values, especially for simulations of moderate and heavy rain.