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The purpose of this paper is to investigate the superior relationship between blood lipid- and cardiovascular disease (CVD)-related hematological parameters using superior grey relational analysis (GRA).

A total of 294 individuals who underwent simultaneous routine blood examination and blood lipid examination in the Physical Examination Center of the First Affiliated Hospital of Shantou University Medical College were included in this study. Superior GRA was performed to find out the superior factor in CVD-related hematological parameters and blood lipids. CVD-related hematological parameters included red blood cell distribution width, white cell count, and platelet count, platelet distribution width, mean platelet volume, as well as platelet crit. The indicators of blood lipids analyzed here consist of low-density lipoprotein, high-density lipoprotein, triglyceride and total cholesterol.

The results showed that all the grey relational degree of hematological parameters and blood lipids were over 0.8; the superior factor in hematological parameters was PLT, whereas TC was the superior factor in blood lipids.

Findings of this study suggested that hematological parameters are closely related to blood lipids and a potential role for hematological parameters in the prediction of dyslipidemia, which need further study; TC has the greatest influence on hematological parameters, whereas TG displays a minimal impact.

To the authors’ best knowledge, it was the first study to analyze the relationship between various CVD-related hematological parameters and blood lipids via superior GRA.

Based on the prediction of the consumption of medical materials, the purpose of this paper is to study the applicability of the grey model method to the field and its predicted accuracy.

The ABC classification method is used to classify medical consumables and select the analysis objects. The GM (1,1) model predicts the annual consumption of medical materials. The GM (1,1) modeling of the consumption of the selected medical materials in 2006~2017 was carried out by using the metabolite sequence and the sequence topology subsequence, respectively. The average rolling error and the average rolling accuracy are calculated to evaluate the prediction accuracy of the model.

The ABC classification results show that Class A projects, which account for only 9.79 percent of the total inventory items, occupy most of the inventory funds. Eight varieties with varying purchases and usages and complete historical data were selected for further analysis. The subsequence GM(1,1) model group constructed by two different methods predicts and scans the annual consumption of eight kinds of medical materials, and the rolling precision can reach more than 90 percent.

The metabolic GM (1,1) model is an ideal predictive model that can meet the requirements for a short-term prediction of medical material consumption (Zhang et al., 2014). The GM (1,1) model is more suitable for a short-term prediction of medical material consumption with less data modeling.

In recent years, with the rapid development of the Internet and e-commerce, the online retail business has grown rapidly. E-commerce platforms can track different click data to understand consumer behavior and demand preferences, so as to make better demand forecasts, and strategically share this information with upstream suppliers. When the platform charges a certain fee for the shared data, the suppliers face the question of whether to purchase demand information. This article aims to analyze the influence of price competition and advertising competition on the suppliers' decisions to purchase information and the online platform for data pricing.

By using static game with incomplete information, this paper explores information-sharing strategies of an online platform with two competitive brand suppliers. The authors use Nash game to analyze the suppliers' purchasing information decision and then obtain the optimal information price of the online platform with information-sharing contract.

This paper shows that demand information sharing benefits both the platform and the suppliers. Without information contracts, the online platform is willing to share demand information with at least one supplier. Especially, when the consumer's sensitivity to advertising is larger and the commission fee charged by the online platform is small, the online platforms will share information with only one supplier. Based on the game outcomes between the suppliers, two pricing strategies for information are proposed under which at least one supplier purchases information. If the consumers are less (more) sensitive to advertising competition, pricing strategy of the online platform induces both suppliers (only one supplier) to purchase information.

At present, most of the information-sharing articles are based on the traditional purchase and sale mode. Based on the background of e-commerce, this paper examines the online platform's information-sharing strategies, which has certain innovation. In addition, the results show that the information-sharing strategy of the online platform is affected by both the price and advertising competitiveness, which provides a new expansion and supplement for the information-sharing literature.

This paper aims to solve the disadvantages of content-based domain ontology (CBDO) and metadata-based domain ontology (MDO) and improve organization and discovery efficiency of library resources by resource ontology (RO).

The paper constructed an RO model. Methods of informetrics are utilized to reveal semantic relationships among library resources. Methods of ontology, ontology-relational database mapping (O-R mapping) and relational database modelling are utilized to construct RO. Take author co-occurrence for example, the paper demonstrated the capability of RO model.

RO not only revealed the deep-level semantic relationships of metadata of library resources but also realized totally computer-automated processing. RO improved the efficiency of knowledge organization and discovery.

Semantic relationships revealed by RO are limited to simple metadata, which makes it difficult to reveal fine-grained semantic relationships. Ongoing research focuses on the revelation of semantic relationships based on the title and abstract.

The paper includes implications for utilizing methods of Informetrics to construct ontology.

This paper proposed a standardized process of ontology construction in library resources. It may be of potential interest for anyone who needs to effectively organize library resources.