This paper mainly uses the idea of pedigree clustering analysis, gray prediction and principal component analysis. The clustering analysis model, GM (1,1) model and principal component analysis model were established by using SPSS software to analyze the correlation matrices and principal component analysis. MATLAB software was used to calculate the correlation matrices. In January, The difference in price changes of major food prices in cities is calculated, and had forecasted the various food prices in June 2016. For the first issue, the main food is classified and the data are processed. After that, the SPSS software is used to classify the 27 kinds of food into four categories by using the pedigree cluster analysis model and the system clustering. The four categories are made by EXCEL. The price of food changes over time with a line chart that analyzes the characteristics of food price volatility. For the second issue, the gray prediction model is established based on the food classification of each kind of food price. First, the original data is cumulated, test and processed, so that the data have a strong regularity, and then establish a gray differential equation, and then use MATLAB software to solve the model. And then the residual test and post-check test, have C <0.35, the prediction accuracy is better. Finally, predict the price trend in June 2016 through the function. For the third issue, we analyzed the main components of 27 kinds of food types by celery, octopus, chicken (white striped chicken), duck and Chinese cabbage by using the data of principal given and analyzed by principal component analysis. It can be detected by measuring a small amount of food, this predict CPI value relatively accurate. Through the study of the characteristics of the region, select Shanghai and Shenyang, by looking for the relevant CPI and food price data, using spss software, principal component analysis, the impact of the CPI on several types of food, and then calculated by matlab algorithm weight, and then the data obtained by the analysis and comparison, different regions should be selected for different types of food for testing.

Using matricant method elastic moduli of occasionally heterogeneous isotropic and anisotropic elastic media were received. Anisotropic behaviour and conditions for change in anisotropy of media associated with averaging of one-dimensional periodic structures was determined.

Atom transfer radical polymerization (ATRP) is a kind of controllable reactive radical polymerization method with potential application value. The modification of graphene oxide (GO) by ATRP reaction can effectively control various graft polymer molecules Chain length and graft density, giving GO different functionality, such as good solvent dispersibility, environmental sensitive stimulus responsiveness, biocompatibility, and the like. In this paper, ATRP reaction and GO surface non-covalent bonding ATRP polymer molecular chain were directly initiated from GO surface immobilization initiator. The ATRP reaction modified GO was reviewed, and the process conditions and research methods of ATRP modification reaction were summarized, as well as pointed out the functional characteristics and application prospect of GO functionalized composites.

This paper concerns a miniature gasifier fed with a constant ambient-pressure flow of air to study the pyrolysis and subsequent combustion stage of a single wood pellet at T = 800 ℃. The alkali release and the concentration of simple gases were recorded simultaneously using an improved alkali surface ionisation detector and a mass spectrometer in time steps of 1 s and 1.2 s, respectively. It showed alkali release during both stages. During combustion, the MS data showed almost complete oxidation of the charred pellet to CO₂. The derived alkali release, “O₂ consumed”, and “CO₂ produced” conversion rates all indicated very similar temporal growth and coalescence features with respect to the varying char pore surface area underlying the original random pore model of Bhatia and Perlmutter. But, also large, rapid signal accelerations near the end and marked peak-tails with O₂ and CO₂ after that, but not with the alkali release data. The latter features appear indicative of alkali–deprived char attributable to the preceding pyrolysis with flowing air. Except for the peak-tails, all other features were reproduced well with the modified model equations of Struis et al. and the parameter values resembled closely those reported for fir charcoal gasified with CO₂ at T = 800 ℃.

The purpose of this study is to predict the frequency of mortality from urban traffic injuries for the most vulnerable road users before, during and after the confinement caused by COVID-19 in Santiago de Cali, Colombia. Descriptive statistical methods were applied to the frequency of traffic crash frequency to identify vulnerable road users. Spatial georeferencing was carried out to analyze the distribution of road crashes in the three moments, before, during, and after confinement, subsequently, the behavior of the most vulnerable road users at those three moments was predicted within the framework of the probabilistic random walk. The statistical results showed that the most vulnerable road user was the cyclist, followed by motorcyclist, motorcycle passenger, and pedestrian. Spatial georeferencing between the years 2019 and 2020 showed a change in the behavior of the crash density, while in 2021 a trend like the distribution of 2019 was observed. The predictions of the daily crash frequencies of these road users in the three moments were very close to the reported crash frequency. The predictions were strengthened by considering a descriptive analysis of a range of values that may indicate the possibility of underreporting in cases registered in the city’s official agency. These results provide new elements for policy makers to develop and implement preventive measures, allocate emergency resources, analyze the establishment of policies, plans and strategies aimed at the prevention and control of crashes due to traffic injuries in the face of extraordinary situations such as the COVID-19 pandemic or other similar events.

The effect of foliar treatment with brassinosteroid (BR) on gender distribution in flowers of walnut (Juglans regia L. cv. Chandler) was investigated. Grafted walnut saplings (‘Chandler’) on the wild walnut (Juglans regia L.) rootstock were planted into 70-liter pots with a soil: peat: perlite medium and grown in pots between 2016–2020. BRs (24-epibrassinolide; EBR and 22(S), 23(S)-homobrassinolide; HBR) were applied at a concentration of 1 mg L^–1 for four consecutive years at the time of flower differentiation. The experimental design was completely randomized with three replicates. The results show that BR applications could alter the sexual distribution of the walnut’s flower. BRs application significantly increased the number of total flowers and female flowers per tree. The number of female flowers was also increased by the season. The highest number of female flowers (20.9) was observed in the trees in 2020 and the application of 1 mg L^–1 of HBR. It was determined that the annual growth of the plant and the increase in the number of females and total flowers were positively related. The effect of BRs indicated that the response was BR-type specific.