Theoretical Study and Numerical Experiment on the Influence of Trend Changes on Correlation Coefficient

When one of two time series undergoes an obvious change in trend, the correlation coefficient between the two will be distorted. In the context of global warming, most meteorological time series have obvious linear trends, so how do variations in these trends affect the correlation coefficient? In this paper, the correlation between time series with trend changes is studied theoretically and numerically. Adopting the trend coefficient, which reflects the nature and size of the trend change, we derive a formula r = f(k, l) for the correlation coefficient of time series X and Y with respective trend coefficients k and l. Analysis of the function graph shows that the changes in correlation coefficient with respect to the trend coefficients produce a twisted saddle surface, and the saddle point coordinates are given by the trend coefficients of time series X and Y with the opposite signs. The curve f(k, l) = f(0, 0) divides the coordinate planes into regions where f(k, l) > f(0, 0) and f(k, l) < f(0, 0). When the trend coefficients k and l are very small and the correlation coefficient is also very small, then k > 0 and l > 0 (or k < 0 and l < 0) amplifies a positive correlation, whereas k > 0 and l < 0 (or k < 0 and l > 0) amplifies a negative correlation, as found in previous research. Finally, experiments using meteorological data verify the reliability and effectiveness of the theory.

PERAMALAN GARIS KEMISKINAN DI KABUPATEN PURBALINGGA TAHUN 2021-2023 DENGAN METODE DOUBLE EXPONENTIAL SMOOTHING LINIER SATU PARAMETER DARI BROWN

Poverty is a major problem in a country. The Indonesian government has made various efforts to tackle the problem of poverty. The main problem faced in poverty alleviation is the large number of people living below the poverty line. Therefore, this study aims to predict the poverty line in Purbalingga Regency for the next three periods as one of the efforts that can be made by the government in poverty alleviation. The method used in this study is a one-parameter linear double exponential smoothing from Brown. The software used in this research is Zaitun Time Series and Microsoft Excel. The steps taken are determining the forecasting objectives, plotting time series data, determining the appropriate method, determining the optimum parameter value, calculating the single exponential smoothing value, calculating double exponential smoothing value, calculate the smoothing constant value, calculate the trend coefficient value and perform forecasting. Based on the calculation results, the optimum alpha parameter value is 0.7 with MAPE value of 1.67866%, which means that this forecasting model has a very good performance. The forecast value of the poverty line in Purbalingga Regency for 2021 is Rp. 396,516, in 2022 it is Rp. 417,818, and in 2023 it is Rp. 439,120.

Impact of the Low-Price Medicine Policy on Medicine Supply in China: An Interrupted Time-Series Analysis

Objectives: The primary objective of the study was to assess the impact of the Low-Price Medicine Policy (LPMP) on the supply of low-price medicines (LPMs) in China. The secondary objective of the study was to describe the supply situation of LPMs from 2005 to 2018.Methods: The LPMP was launched in the third quarter of 2014 (2014Q3). An interrupted time series analysis was used to evaluate the impact of LPMP on the supply of LPMs in China. Ordinary least squares and Poisson regression models were utilized to estimate the effect of LPMP on LPMs’ supply growth rate and the number of supplied LPMs. All the LPMs were divided into two subgroups: intermittent supply and continuous supply. The trend and level changes of the quarterly average growth rate and number of quarterly supplies for different LPM groups were analyzed from 2005 to 2018.Findings: For the quarterly average growth rate, before the intervention, a significant increasing trend was observed in the total group and the continuous supply subgroup; after the introduction of LPMP, the increasing trend was ceased and a significant decrease in the trend and level was noted for both the total group (trend coefficient: β3= −0.0132, p &lt; 0.01; level coefficient: β2 = −0.1510, p &lt; 0.05) and the continuous supply subgroup (trend coefficient: β3 = −0.0133, p &lt; 0.01; level coefficient: β2 = −0.1520, p &lt; 0.05); whereas it had no significant effect for intermittent supply subgroup. For the number of quarterly supplies, after the intervention of LPMP, decline of the supply number was observed (trend coefficient: β3 = −0.0027, p &lt; 0.001; level coefficient: β2 = −0.0584, p &lt; 0.001); whereas the LPMP was associated with an upward trend and level (trend coefficient: β3 = 0.0715, p &lt; 0.001; level coefficient: β2 = 0.174) for the intermittent supply subgroup.Conclusion: For most of the LPMs, LPMP did not meet the goal of stimulating LPM production. However, for severely shortage medicines (the intermittent supply subgroup), the effect of LPMP was positive. Comprehensive policies rather than just deregulating medicine price should be introduced to alleviate the situation of medicine shortage in China.

Effects of restrictive-prescribing stewardship on antibiotic consumption in primary care in China: an interrupted time series analysis, 2012–2017

Background The overuse of antibiotics has been a major public health problem worldwide, especially in low- and middle- income countries (LMIC). However, there are few policies specific to antibiotic stewardship in primary care and their effectiveness are still unclear. A restrictive-prescribing stewardship targeting antibiotic use in primary care has been implemented since December 2014 in Hubei Province, China. This study aimed to evaluate the effects of the restrictive-prescribing stewardship on antibiotic consumption in primary care so as to provide evidence-based suggestions for prudent use of antibiotics. Methods Monthly antibiotic consumption data were extracted from Hubei Medical Procurement Administrative Agency (HMPA) system from Sept 1, 2012, to Aug 31, 2017. Quality Indictors of European Surveillance of Antimicrobial Consumption (ESAC QIs) combined with Anatomical Therapeutic Chemical (ATC) classification codes and DDD per 1000 inhabitants per day (DID) methodology were applied to measure antibiotic consumption. An interrupted time series analysis was performed to evaluate the effects of restrictive-prescribing stewardship on antibiotic consumption. Results Over the entire study period, a significant reduction (32.58% decrease) was observed in total antibiotic consumption, which declined immediately after intervention (coefficient = − 2.4518, P = 0.005) and showed a downward trend (coefficient = − 0.1193, P = 0.017). Specifically, the use of penicillins, cephalosporins and macrolides/lincosamides/streptogramins showed declined trends after intervention (coefficient = − 0.0553, P = 0.035; coefficient = − 0.0294, P = 0.037; coefficient = − 0.0182, P = 0.003, respectively). An immediate decline was also found in the contribution of β-lactamase-sensitive penicillins to total antibiotic use (coefficient = − 2.9126, P = 0.001). However, an immediate increase in the contribution of third and fourth-generation cephalosporins (coefficient = 5.0352, P = 0.005) and an ascending trend in the contribution of fluoroquinolones (coefficient = 0.0406, P = 0.037) were observed after intervention. The stewardship led to an immediate increase in the ratio between broad- and narrow-spectrum antibiotic use (coefficient = 1.8747, P = 0.001) though they both had a significant downward trend (coefficient = − 0.0423, P = 0.017; coefficient = − 0.0223, P = 0.006, respectively). An immediate decline (coefficient = − 1.9292, P = 0.002) and a downward trend (coefficient = − 0.0815, P = 0.018) were also found in the oral antibiotic use after intervention, but no significant changes were observed in the parenteral antibiotic use. Conclusions Restrictive-prescribing stewardship in primary care was effective in reducing total antibiotic consumption, especially the use of penicillins, cephalosporins and macrolides/lincosamides/streptogramins. However, the intervention effects were limited regarding the use of combinations of penicillins with ß-lactamase inhibitors, the third and fourth-generation cephalosporins, fluoroquinolones and parenteral antibiotics. Stronger administrative regulations focusing on specific targeted antibiotics, especially the use of broad-spectrum antibiotics and parenteral antibiotics, are in urgent need in the future.

Effects of Restrictive-prescribing Stewardship on Antibiotic Consumption in Primary Care in China: An Interrupted Time Series Analysis, 2012-2017

Background:The overuse of antibiotics has been a major public health problem worldwide, especially in low- and middle- income countries (LMIC). However, there are few policies specific to antibiotic stewardship in primary care and their effectiveness are still unclear. This study aimed to evaluate the effects of a restrictive-prescribing stewardship on antibiotic consumption in primary care so as to provideevidence-based suggestions for prudent use of antibiotics.Methods:Monthly antibiotic consumption data were extracted from Hubei Medical Procurement Administrative Agency (HMPA) system from Sept 1, 2012, to Aug 31, 2017. Quality Indictors of European Surveillance of Antimicrobial Consumption (ESAC QIs) combined with Anatomical Therapeutic Chemical (ATC) classification codes and DDD per 1000 inhabitants per day (DID) methodologywere applied to measure antibiotic consumption. An interrupted time series analysis was performed to evaluate the effects of restrictive-prescribing stewardship on antibiotic consumption.Results: Over the entire study period, a significant reduction (declined by 32.58%) was observed in total antibiotic consumption, which declined immediately after intervention (coefficient=-2.4518, P=0.005) and showed a downward trend (coefficient =-0.1193, P=0.017).Specifically,the use of penicillins, cephalosporins and macrolides/lincosamides/streptogramins showed declined trends after intervention (coefficient=-0.0553, P=0.035; coefficient=-0.0294, P=0.037; coefficient=-0.0182, P=0.003, respectively). An immediate decline was also found in the contribution of β-lactamase-sensitive penicillins of total antibiotic use (coefficient=-2.9126, P=0.001). However, an immediate increase in the contribution of third and fourth-generation cephalosporins (coefficient=5.0352, P=0.005) and an ascending trend in the contribution of fluoroquinolones (coefficient=0.0406, P=0.037) were observed after intervention. The stewardship led to an immediate increase in the ratio between broad- and narrow-spectrum antibiotic use (coefficient=1.8747, P=0.001) though they both had a significant downward trend (coefficient=-0.0423, P=0.017; coefficient=-0.0223, P=0.006, respectively). An immediate decline (coefficient=-1.9292, P=0.002) and an ascending trend (coefficient=-0.0815, P=0.018) were also found in the oral antibiotic use after intervention, but no significant changes were observed in the parenteral antibiotic use. Conclusions:Restrictive-prescribing stewardship in primary care was effective in reducing total antibiotic consumption, especially use of penicillins, cephalosporins and macrolides/lincosamides/streptogramins. However, the intervention effects were mixed. Stronger administrative regulation focusing on specific antibiotics, such as the third and fourth-generation cephalosporins, fluoroquinolones, broad-spectrum antibiotics and parenteral antibiotics, is in urgent need in the future.

Nonparametric estimation of trend for stochastic differential equations driven by sub-fractional Brownian motion

We discuss nonparametric estimation of a trend coefficient in models governed by a stochastic differential equation driven by a sub-fractional Brownian motion with small noise.

Research on Multi-Time-Delay Gene Regulation Network Based on Fuzzy Label Propagation

In view of time delay existing in gene regulation, by using the analysis idea and methods of complex network, this paper proposes a multi-time-delay gene regulation network analysis method based on the fuzzy label propagation. The algorithm takes the relative change trend coefficient, the correlation coefficient, and the mutual information as the similarity measurement indexes for the gene pair, fully reflecting the correlation of gene pairs and simultaneously obtaining the gene regulation relationship and the time delay through the fuzzy label propagation algorithm of the semisupervised learning. Experimental results of the cell cycle-regulated genes of yeast show that the proposed construction method of GRN can not only correctly select potential regulation genes but also provide details about the gene regulator model, thereby more accurately constructing gene regulation network.

Spatial trend analysis of gridded temperature data at varying spatial scales

Classical assessments of trends in gridded temperature data perform independent evaluations across the grid, thus, ignoring spatial correlations in the trend estimates. In particular, this affects assessments of trend significance as evaluation of the collective significance of individual tests is commonly neglected. In this article we build a space–time hierarchical Bayesian model for temperature anomalies where the trend coefficient is modelled by a latent Gaussian random field. This enables us to calculate simultaneous credible regions for joint significance assessments. In a case study, we assess summer season trends in 65 years of gridded temperature data over Europe. We find that while spatial smoothing generally results in larger regions where the null hypothesis of no trend is rejected, this is not the case for all subregions.

Generalized trend constants of Lipschitz mappings

In 2015, Goebel and Bolibok defined the initial trend coefficient of a mapping and the class of initially nonexpansive mappings. They proved that the fixed point property for nonexpansive mappings implies the fixed point property for initially nonexpansive mappings. We generalize the above concepts and prove an analogous fixed point theorem. We also study the initial trend coefficient more deeply.

Variability of hygro-climatic conditions of forest vegetation in Poland during the period of 1951–2015

This work presents an assessment of changes in the hygro-climatic conditions determining the vegetation and productivity of forest areas. Selected indices such as the radiant index of climate aridity – RIA, optimal precipitation – Popt, critical value of precipitation – Pkrt and CVP index (Climate, Vegetation, Productivity), which describe annual biomass and wood production under climatic conditions, were used. The analysis is based on standard meteorological measurements taken from 21 stations from the period of 1951–2015. The daily data were employed to calculate the previously mentioned indices, and the next linear trend coefficient was used to assess changes in hygro-climatic conditions. The results show an increasing tendency towards dry climate conditions (positive values of the RIA linear trend coefficient) in a large part of the area consisting of Wielkopolska, the Silesian lowlands, and southern Poland. These areas are also characterized by the fastest increase in the most favourable sum of precipitation Popt and critical precipitation Pkrt for forest vegetation. This means that water resources in the environment and hygro-climatic conditions important for vegetation and the productivity of forest vegetation are deteriorating. On the other hand, the results of the CVP change assessment show an improvement in the climatic conditions influencing vegetation and forest productivity. The greatest positive changes of the CVP index are observed in the areas of south-eastern Poland.