Research on layout model and construction planning of aged care institutions for disabled elders in China: based on Nanjing city data.

BACKGROUND: To meet the needs of diversified pension services and the construction of aged care institutions is one of the urgent livelihood issues in China. Under the major national needs of pension and care for the elderly, it is necessary to optimize the allocation of pension and care for the elderly resources, and formulate operational coping strategies and optimization plans. It is of great significance to deal with the urgent problem of population aging in a timely and scientific way. METHODS: The economic benefits and social costs of aged care institutions are regarded as objective functions. To satisfy the economic benefits, it is necessary to reduce the social costs, and its construction quantity can only be an integer. The multi-objective genetic algorithm is improved with integer programming, and the global optimal solution is achieved after several times of searching. Under the multi-objective optimization model, the improved genetic algorithm was combined with the superior and inferior solution distance method to solve the genetic algorithm, and the corresponding objective function value was obtained after rounding. Finally, Pareto optimal solution set is selected by multi-objective decision, and the result of construction planning is obtained. RESULTS: Based on multi-attribute decision analysis and taking three years as the construction cycle, the planning scheme of aged care institutions construction in each district of Nanjing in the next 15 years was proposed. In addition, considering the intelligent trend of future pension, the proportion of home-based pension is increasing year by year, and the model is promoted to meet the needs of diversified pension services. With the gradual increase of the elderly population in Nanjing, the proportion of intelligent home-based care has been increasing year by year since 2027, and the construction demand of aged care institutions has also increased. The number of construction at all levels rises gradually in each cycle, and the increase is more obvious after 2027. CONCLUSIONS: The layout and planning of aged care institutions proposed in this paper not only considers economic and environmental benefits, but also combines the current situation of aged care institutions in various districts of Nanjing. The model is reasonable and effective, and has practical application value. It will help China optimize the allocation of elderly care resources under the target of active aging, and scientifically and comprehensively deal with the problem of population aging.

A novel grey spatial extension relational model and its application to identify the drivers for ambient air quality in Shandong Province, China.

The ambient air quality is a complex dynamical system that is shocked by a number of subsystems, such as government policies, industry regulation adjustment and internationalization. To identify the drivers for ambient air quality, a grey spatial extension relational analysis model is proposed. Firstly, a spatial extension method for one-dimensional time series of complex systems is introduced, and the two key parameters are obtained based on the grey similarity and proximity relational analysis models. Secondly, grey relational coefficient is calculated by the difference of the three-dimensional vector, and a grey spatial extension relational analysis model is presented. Furthermore, the properties of the proposed model were investigated. Finally, the model is used to identify the drivers of the ambient air quality in eastern coastal Shandong Province, China. Results suggest that the drivers of the ambient air quality vary among cities, but with some common ones. Therefore, this paper provides an important reference for the improvement of ambient air quality.

Predicting the trend of infectious diseases using grey self-memory system model: a case study of the incidence of tuberculosis.

OBJECTIVES: The prediction and early warning of infectious diseases is an important work in the field of public health. This study constructed the grey self-memory system model to predict the incidence trend of infectious diseases affected by many uncertain factors. STUDY DESIGN: The design of this study is a combination of the prediction method and empirical analysis. METHODS: By organically coupling the self-memory algorithm with the mean GM(1,1) model, the tuberculosis incidence statistics of China from 2004 to 2018 were selected for prediction analysis. Meanwhile, by comparing with the other traditional prediction methods, three representative accuracy check indexes (MSE, AME, MAPE) were conducting for error analysis. RESULTS: Owing to the multiple time-points initial fields, which replace the single time-points, the limitation of the traditional grey prediction model, which is sensitive to the initial value, is overcome in the self-memory equation. Consequently, compared with the mean GM model and other statistical methods, the grey self-memory model shows significant forecasting advantages, and its single-step rolling prediction accuracy is superior to other prediction methods. Therefore, the incidence of tuberculosis in China in the next year can be predicted as 55.30 (unit: 1/105). CONCLUSIONS: The grey self-memory system model can closely capture the individual random fluctuation in the whole evolution trend of the uncertain system. It is appropriate for predicting the future incidence trend of infectious diseases and is worth popularizing to other similar public health prediction problems.

Scheduling optimal replacement policies for a stochastically deteriorating system subject to two types of shocks.

This paper is aimed at scheduling optimal preventive replacement policies for a single unit system which is subject to stochastic deterioration and concurrently suffers from external shocks. Different from existing literature, two types of shocks are taken into account according to the effectiveness upon arrival of a random shock, in which Type Ⅰ shock is a non-fatal one increasing the damage magnitude on current degradation amount and Type Ⅱ shock is a fatal one resulting in system catastrophic failure immediately. System survival function is investigated numerically based on the degradation-threshold-shock (DTS) modelling framework, and subsequently, two categories of bivariate maintenance policies are scheduled from different perspectives. The optimal solutions for both policies are derived analytically, and the relative gain on the optimal average maintenance cost rate is incorporated to determine which policy is more profitable. An illustrative example is provided to validate the theoretical results.

A prediction method for plasma concentration by using a nonlinear grey Bernoulli combined model based on a self-memory algorithm.

The goal of this work is to present and explore the application of a novel nonlinear grey Bernoulli combined model based on a self-memory algorithm, abbreviated as SA-NGBM, for modeling single-peaked sequences of time samples of acetylsalicylate plasma concentration following oral dosing. The self-memorization SA-NGBM routine reduces the dependence on a solitary initial value, as the initial state of the model utilizes multiple time samples. To test its forecasting performance, the SA-NGBM was used to extrapolate the plasma concentration predicted data, in comparison with the later time samples. The results were contrasted with those of the traditional optimized NGBM (ONGBM), exponential smoothing (ES) and simple moving average (SMA) using four popular accuracy and significance tests. That comparison showed that the SA-NGBM was much more accurate and efficient for matching the individual, nonlinear-system stochastic fluctuations than the existing ONGBM, ES and SMA models. The findings have potential applications for signal matching to similar small sample size, single-peaked, plasma concentration series.

Patients' satisfaction and public and private sectors' health care service quality in Pakistan: Application of grey decision analysis approaches.

PURPOSE: The study aims to evaluate the comprehensive relationship between patient satisfaction and five dimensions of health care service quality in Pakistani public/private health care sectors, using a novel grey relational analysis (GRA) models and the Hurwicz criteria of decision making under uncertainty. DESIGN/METHODOLOGY/APPROACH: Data were collected from private and public health care facilities of Pakistan through an improved SERVQUAL instrument. Deng's GRA, absolute GRA, and the second synthetic GRA models were applied to address the problem under study. FINDINGS: Grey relational analysis models revealed that reliability and responsiveness are most strongly predicting patient satisfaction in public and private health care sectors, respectively. The Hurwicz criteria showed that patients are more likely to be satisfied from private health care facilities. LIMITATIONS/IMPLICATIONS: Limitations of SERVQUAL model are also the limitations of the study; eg, the study suggests that because of the absence of "cost," which is a key quality indicator of Pakistani public sector health care facilities, the model was unable to comprehensively evaluate the health care situation in light of the observations of price-focused Pakistani patients. The study recommends tailoring of SERVQUAL model for the resource-scant and underdeveloped countries where people's evaluation of the quality of the hospitals is likely to be influenced by the price of services. ORIGINALITY/VALUE: The study is a pioneer in health care evaluation of public and private sectors of Lahore and Rawalpindi while using GRA models, in general, and the second synthetic GRA model, in particular. It presents an alternative method to the statistical way of analyzing data by successfully demonstrating the use of grey methods, which can make reasonable decisions even through small samples.

Application of a novel grey self-memory coupling model to forecast the incidence rates of two notifiable diseases in China: dysentery and gonorrhea.

OBJECTIVE: In this study, a novel grey self-memory coupling model was developed to forecast the incidence rates of two notifiable infectious diseases (dysentery and gonorrhea); the effectiveness and applicability of this model was assessed based on its ability to predict the epidemiological trend of infectious diseases in China. METHODS: The linear model, the conventional GM(1,1) model and the GM(1,1) model with self-memory principle (SMGM(1,1) model) were used to predict the incidence rates of the two notifiable infectious diseases based on statistical incidence data. Both simulation accuracy and prediction accuracy were assessed to compare the predictive performances of the three models. The best-fit model was applied to predict future incidence rates. RESULTS: Simulation results show that the SMGM(1,1) model can take full advantage of the systematic multi-time historical data and possesses superior predictive performance compared with the linear model and the conventional GM(1,1) model. By applying the novel SMGM(1,1) model, we obtained the possible incidence rates of the two representative notifiable infectious diseases in China. CONCLUSION: The disadvantages of the conventional grey prediction model, such as sensitivity to initial value, can be overcome by the self-memory principle. The novel grey self-memory coupling model can predict the incidence rates of infectious diseases more accurately than the conventional model, and may provide useful references for making decisions involving infectious disease prevention and control.

Uncertainty representation of grey numbers and grey sets.

In the literature, there is a presumption that a grey set and an interval-valued fuzzy set are equivalent. This presumption ignores the existence of discrete components in a grey number. In this paper, new measurements of uncertainties of grey numbers and grey sets, consisting of both absolute and relative uncertainties, are defined to give a comprehensive representation of uncertainties in a grey number and a grey set. Some simple examples are provided to illustrate that the proposed uncertainty measurement can give an effective representation of both absolute and relative uncertainties in a grey number and a grey set. The relationships between grey sets and interval-valued fuzzy sets are also analyzed from the point of view of the proposed uncertainty representation. The analysis demonstrates that grey sets and interval-valued fuzzy sets provide different but overlapping models for uncertainty representation in sets.

A grey NGM(1,1, k) self-memory coupling prediction model for energy consumption prediction.

Energy consumption prediction is an important issue for governments, energy sector investors, and other related corporations. Although there are several prediction techniques, selection of the most appropriate technique is of vital importance. As for the approximate nonhomogeneous exponential data sequence often emerging in the energy system, a novel grey NGM(1,1, k) self-memory coupling prediction model is put forward in order to promote the predictive performance. It achieves organic integration of the self-memory principle of dynamic system and grey NGM(1,1, k) model. The traditional grey model's weakness as being sensitive to initial value can be overcome by the self-memory principle. In this study, total energy, coal, and electricity consumption of China is adopted for demonstration by using the proposed coupling prediction technique. The results show the superiority of NGM(1,1, k) self-memory coupling prediction model when compared with the results from the literature. Its excellent prediction performance lies in that the proposed coupling model can take full advantage of the systematic multitime historical data and catch the stochastic fluctuation tendency. This work also makes a significant contribution to the enrichment of grey prediction theory and the extension of its application span.

[Epidemiological analysis for Quzhou pesticide poisoning of year 2008 to 2010].

OBJECTIVE: To provide scientific evidence of making measures for prevention of pesticide poisoning, the investigation on the condition of pesticide poisoning was carried out in Quzhou. METHODS: Registration data of pesticide poisoning from 2008 to 2010 in Quzhou were collected and statistically analyzed by SPSS 12.0. RESULTS: During the three years, there were 1222 cases reported for pesticide poisoning. Among them, the number of occupational poisoning was 225 (1 case died), with fatality rate of 0.44%. The number of non-occupational poisoning was 997 (77 cases died), and its fatality rate was 7.72% . The incidence of occupational poisoning and non-occupational poisoning accounted for 18.4% and 81.6% respectively. Male patients were in the majority in occupational pesticides poisoning (accounting for 76.4%), female patients in non-occupational poisoning (accounting for 52.1%). The pesticide poisoning mainly occurred from July to September. Occupational poisoning and non-occupational poisoning cases mainly concentrated in over 65 age group, accounting for 36.0% (81 cases) and 26.3% (262 cases) respectively. Insecticide ranks the first in the terms of total poisoning cases caused by pesticide, and organophosphate poisoning ranks the first in all insecticides. CONCLUSION: Pesticides poisoning has badly threatened the public health in Quzhou, attention should be paid to non-occupational poisoning. The pesticides poisoning was mainly caused by organophosphate insecticides.

[An FTIR and XPS study of immobilization of chromium with fly ash based geopolymers].

Immobilization of Cr3+ with fly ash geopolymers was investigated by Fourier transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopic (XPS) techniques. The chromium sludge, as Cr(OH)3, was prepared with chemical precipitation method. The amounts of aluminum and silicon leached before and after the chromium sludge addition were measured using ICP-AES. The results suggested that the amounts of silicon and aluminum leached were reduced for the fly ash geopolymers after chromium sludge was incorporated. The decrease of silicon leaching was more pronounced than aluminum. FTIR results showed that the intensity of the main peak shifted into lower and the wave number of Si--O--Si and Al--O--Si became higher. The XPS results indicated that the O(1s) bind energy decreased, Si(2p) and Cr(2p) bind energy increased, while Al(2p) bind energy remained unchanged due to Cr3+ addition. It was also confirmed that the chromium is easily incorporated into the fly ash geopolymers paste, and polymerized with silicate units. The immobilization of Cr3+ using fly ash geopolymers is attributed not only to physical encapsulation, but also to chemical reaction.