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Purpose: The purpose of this paper is to construct a grey incidence model for panel data that can reflect the incidence direction and degree between indicators. Design/methodology/approach: Firstly, this paper introduces the concept of a negative matrix and preprocesses the data of each indicator matrix to eliminate differences in dimensions and magnitudes between indicators. Then a model is constructed to measure the incidence direction and degree between indicators, and the properties of the model are studied. Finally, the model is applied to a practical problem. Findings: The grey-directed incidence degree is 1 if and only if corresponding elements between the feature indicator matrix and the factor indicator matrix have a positive linear relationship. This degree is −1 if and only if corresponding elements between the feature indicator matrix and the factor indicator matrix have a negative linear relationship. Practical implications: The example shows the number of days with good air quality is negatively correlated with the annual average concentration of each pollutant index. PM2.5, PM10 and O3 are the main pollutants affecting air quality in northern Henan. Originality/value: This paper introduces the negative matrix and constructs a model from the holistic perspective to measure the incidence direction and level between indicators. This model can effectively measure the incidence between the feature indicator and factor indicator by integrating information from the point, row, column and matrix. [ABSTRACT FROM AUTHOR]

Almost all cities of Pakistan are economically affected by the electricity shortage due to the continuously increasing demand for electricity. To correctly forecast the seasonal fluctuations of the electricity consumption of Lahore city in Pakistan, we proposed the SDGPM(1,1,N) model, which is a seasonal discrete grey polynomial model combined with seasonal adjustment. We conducted an empirical analysis using the proposed model based on the seasonal electricity consumption data of Lahore city in Pakistan from 2014 to 2021. The findings from the SDGPM (1,1,N) model are compared with those collected through the original grey model DGPM(1,1,N) and other eight models. The comparison's findings demonstrated that the SDGPM(1,1,N) model is indeed capable of correctly identifying seasonal fluctuations of electricity consumption in Lahore city and its prediction accuracy is significantly higher than the original DGPM(1,1,N) model and the other seven models. The SDGPM(1,1,N) model's forecast findings for Lahore from 2022 to 2025 indicate that the city's energy consumption is expected to rise marginally, although there will still be significant seasonal fluctuations. It is predicted that the annual electricity consumption from 2022 to 2025 will be 26249, 26749, 27928, and 28136 with an annual growth rate of 7.18%. This forecast can provide policymakers ahead start in planning to ensure that supply and demand are balanced. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to propose a pseudo-grey metabolic grey Markov model to deal with the prediction issue in which the original sequences are oscillation sequences. Design/methodology/approach: First, the original sequences were processed with the accelerated advection transformation and the weighted mean generation transformation to make them smoother. Then, the mean GM (1, 1) model was applied to the multi-step prediction of the pre-processed data sequences. Finally, with the help of the optimal partitioning method, the pseudo-grey metabolic Markov model was used to correct the prediction results and determine the final prediction values. Findings: The results demonstrate that the accuracy of this model is significantly higher than that of the traditional grey Markov model, which further verifies the rationality of the proposed model. Therefore, scientific and reasonable prediction of urban rainfall is of great theoretical significance and application value for the government and decision-making departments to formulate drought prevention and disaster mitigation measures. Originality/value: The model in this paper not only provides new ideas for the data preprocessing problem of the grey Markov model, but also solves the problem of errors due to individual subjectivity in state interval division. It provides a novel idea for the development of grey prediction models. The rationality and validity of the model are illustrated by taking the Zhengzhou City of Henan Province as examples. [ABSTRACT FROM AUTHOR]

This paper is concerned with the existence of entire solutions of some reaction-diffusion systems. We first consider Belousov-Zhabotinskii reaction model. Then we study a general model. Using the comparing argument and sub-super-solutions method, we obtain the existence of entire solutions which behave as two wavefronts coming from the both sides of x-axis, where an entire solution is meant by a classical solution defined for all space and time variables. At last, we give some examples to explain our results for the general models. [ABSTRACT FROM AUTHOR]

Purpose – For the multi-stage and multi-attribute risk group decision-making problem, the attribute weight, decision-maker weight and time weight are unknown. The attribute value is grey information. The purpose of this paper is to discuss a decision-making method. Design/methodology/approach – Analysis techniques and the theory about distance degree are used to determine the decision-maker weight within single stage. Grey relational analysis method is applied to determine the attribute weight. Moreover, the uncertainty of time weight and the proximity between the attribute value and positive/negative value are taken into account. A multi-objective optimization model is established based on maximum entropy to obtain time weights, so the comprehensive value is determined. Findings – An example shows the effectiveness and practicability. Originality/value – For a decision-making process, the results are different in different periods. This method is computationally very simple, easily comprehensible. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we investigate the convergence of the time-dependent and non-isentropic Euler–Maxwell equations to incompressible Euler equations in a torus via the combined quasi-neutral and non-relativistic limit. For well prepared initial data, the convergences of solutions of the former to the solutions of the latter are justified rigorously by an analysis of asymptotic expansions and energy method. [Copyright &y& Elsevier]

To study the chemical constituents of Artemisia lactiflora. The compounds were isolated by column chromatography with silica gel, C18 reverse-phase silica gel, semi-preparative HPLC, and their structures were elucidated on the basis of spectral analysis. Twelve compounds were isolated from alcohol extracts of A. lactiflora and identified as 7-hydroxycoumarin (1), 7-methoxycoumarin (2), balanophonin (3), aurantiamide (4), aurantiamide acetate (5), isovitexin (6), kaempferol-3-O-beta-D-rutinoside (7), rutin (8), caffeic acid ethyl ester (9), quercetin (10), methyl 3, 5-di-O-caffeoyl quinate (11) and methyl 3, 4-di-O-caffeoyl quinate (12), respectively. Compounds 3-12 were obtained from this plant for the first time.