Analysis of spatial pattern and influencing factors of private clinics in the main urban area of Guiyang in China from 2021 to 2022 based on multi-source data.

BACKGROUND: Private clinics are important places for residents to obtain daily medical care. However, previous researches mainly focused on public medical institutions but ignored the issue of systematic allocation of social medical resources such as clinics. It is critical to understand the private clinics distribution to analyze the rational allocation of medical resources and the spatial difference. METHODS: Based on the field survey, land census, population density, and economic data from Guiyang, this study analyzes the spatial pattern of private clinics in the main urban area of Guiyang and the influencing factors by using spatial analysis methods such as kernel density, standard deviation ellipses, and geo-detector. RESULTS: The private clinics in the main urban area of Guiyang are characterized by "inner dense, outer sparse dense," showing an overall spatial clustering feature of "four cores and two belts with many points" and "dense inside and sparse outside." Different types of private clinics have distinct spatial distribution characteristics and agglomeration forms. The growth of private clinics is closely linked to the population growth of mountainous cities. The most important factors influencing the spatial pattern of private clinics are residential land factors, followed by traffic factors and population density. The impact of economic, natural, and spatial factors is minimal. When using a geo-detector, the results of multi-factor interaction differ from those of single factors, and factor interactions have greater explanatory power than single factors in clinic distribution. CONCLUSION: This study investigates the geographic distribution and influencing variables of private clinics in typical mountain cities and identifies the causes of the current disparity in the distribution of healthcare resources. It is necessary to gradually develop the primary healthcare system in mountainous cities with legislation, counterpart support, and social resources. While ensuring equal access to health care for low-income people and mobile populations, various medical needs of community members should be fully considered and implemented as soon as possible.

Quantum private set intersection cardinality based on bloom filter.

Private Set Intersection Cardinality that enable Multi-party to privately compute the cardinality of the set intersection without disclosing their own information. It is equivalent to a secure, distributed database query and has many practical applications in privacy preserving and data sharing. In this paper, we propose a novel quantum private set intersection cardinality based on Bloom filter, which can resist the quantum attack. It is a completely novel constructive protocol for computing the intersection cardinality by using Bloom filter. The protocol uses single photons, so it only need to do some simple single-photon operations and tests. Thus it is more likely to realize through the present technologies. The validity of the protocol is verified by comparing with other protocols. The protocol implements privacy protection without increasing the computational complexity and communication complexity, which are independent with data scale. Therefore, the protocol has a good prospects in dealing with big data, privacy-protection and information-sharing, such as the patient contact for COVID-19.

An improved and efficient mutual authentication scheme for session initiation protocol.

Qiu et al. made a security analysis about the protocols of Chaudhry et al. and Kumari et al. in 2018, and they pointed out that there are many security weaknesses in the protocols. To improve the security, Qiu et al. proposed an advanced authentication scheme for Session Initiation Protocol on the basis of the previous protocols and claimed that their own protocol was very secure and practical. However, we demonstrate that the protocol of Qiu et al. has a serious mistake which causes their protocol cannot be executed normally. Beyond that, we also find out that their protocol cannot withstand insider attack and denial service attack. In order to remove these weaknesses, we propose an efficient provably secure mutual authentication scheme. Furthermore, our scheme provides security analysis with the help of Burrows-Abadi-Needham (BAN) logic. Compared with their protocol, ours has greater security and better performance.