How to improve public health literacy based on polycentric public goods theory: preferences of the Chinese general population View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2022-05-09

AUTHORS

Yaxin Gao, Li Zhu, Zi Jun Mao

ABSTRACT

BackgroundIn the current era of big data, it is critical to address people’s demand for health literacy. At present, the traditional mode of communicating scientific health knowledge and information technology is interchangeable, resulting in the emergence of a new mode of communicating health literacy. To publicize health education and health literacy in a targeted way, to meet the public’s needs, and to understand how the public’s demand for subjects, contents, and forms of health literacy service has changed in the era of COVID-19, the investigation of public’s demand for health information and health literacy was conducted.ObjectiveThis study aims to understand the differences in demand for health literacy service providers, contents, channels, forms, and facilities among Chinese citizens with different genders, ages, education levels, economic conditions, and living environments, and to provide reasonable recommendations for developing public health literacy.MethodsQuestionnaire Star was used to conduct a large sample of random online surveys. In Wuhan, Hubei Province, 2184 questionnaires were issued, 8 invalid questionnaires were eliminated, and 2176 were recovered, with an effective rate of 99.6%. IBM SPSS Statistics 20 was utilized to analyze the survey data.Results(1) In health literacy service providers selected by the public, the proportion of government departments or government collaboration with other institutions exceeded 73%, indicating that health literacy services are public goods; (2) access to health literacy services was lower in township areas than in urban areas (P < 0.001, 3) internet media and communicating with acquaintances, which have the highest popularity rate, were also the two channels that were least trusted by the public; and (4) the differences in contents and service channels of health literacy among residents with different genders, ages, education levels, economic status, and living environments were statistically significant.Conclusions(1) It is recommended to establish an integrated health literacy service model with multi-center supply. Government departments, medical institutions, and media should cooperate effectively to provide health literacy services. (2) The government should pay attention to the fairness of health education and strengthen the supply of health literacy services in township areas. (3) It is critical to strengthen the public’s ability to discriminate network information and pay attention to scientific thinking cultivation. (4) Health literacy service providers must focus on the differences between public demands and improve the connotation of health literacy services. More... »

PAGES

921

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s12889-022-13272-z

DOI

http://dx.doi.org/10.1186/s12889-022-13272-z

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1147745873

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/35534809


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Medical and Health Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1117", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Public Health and Health Services", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "COVID-19", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "China", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Female", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Health Education", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Health Literacy", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Male", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Public Health", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Surveys and Questionnaires", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Non-traditional Security Institute, Huazhong University of Science and Technology, 430074, Wuhan, China", 
          "id": "http://www.grid.ac/institutes/grid.33199.31", 
          "name": [
            "Department of Gastrointestinal Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Jie Fang Ave, No. 1095, Wuhan, China", 
            "College of Public Administration, Huazhong University of Science and Technology, No 1037 Luau Road, Hongshan District, 430074, Wuhan, China", 
            "Non-traditional Security Institute, Huazhong University of Science and Technology, 430074, Wuhan, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Gao", 
        "givenName": "Yaxin", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Gastrointestinal Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Jie Fang Ave, No. 1095, Wuhan, China", 
          "id": "http://www.grid.ac/institutes/grid.33199.31", 
          "name": [
            "Department of Gastrointestinal Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Jie Fang Ave, No. 1095, Wuhan, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zhu", 
        "givenName": "Li", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Non-traditional Security Institute, Huazhong University of Science and Technology, 430074, Wuhan, China", 
          "id": "http://www.grid.ac/institutes/grid.33199.31", 
          "name": [
            "College of Public Administration, Huazhong University of Science and Technology, No 1037 Luau Road, Hongshan District, 430074, Wuhan, China", 
            "Non-traditional Security Institute, Huazhong University of Science and Technology, 430074, Wuhan, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Mao", 
        "givenName": "Zi Jun", 
        "id": "sg:person.010715377363.75", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010715377363.75"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "2022-05-09", 
    "datePublishedReg": "2022-05-09", 
    "description": "BackgroundIn the current era of big data, it is critical to address people\u2019s demand for health literacy. At present, the traditional mode of communicating scientific health knowledge and information technology is interchangeable, resulting in the emergence of a new mode of communicating health literacy. To publicize health education and health literacy in a targeted way, to meet the public\u2019s needs, and to understand how the public\u2019s demand for subjects, contents, and forms of health literacy service has changed in the era of COVID-19, the investigation of public\u2019s demand for health information and health literacy was conducted.ObjectiveThis study aims to understand the differences in demand for health literacy service providers, contents, channels, forms, and facilities among Chinese citizens with different genders, ages, education levels, economic conditions, and living environments, and to provide reasonable recommendations for developing public health literacy.MethodsQuestionnaire Star was used to conduct a large sample of random online surveys. In Wuhan, Hubei Province, 2184 questionnaires were issued, 8 invalid questionnaires were eliminated, and 2176 were recovered, with an effective rate of 99.6%. IBM SPSS Statistics 20 was utilized to analyze the survey data.Results(1) In health literacy service providers selected by the public, the proportion of government departments or government collaboration with other institutions exceeded 73%, indicating that health literacy services are public goods; (2) access to health literacy services was lower in township areas than in urban areas (P\u2009<\u20090.001, 3) internet media and communicating with acquaintances, which have the highest popularity rate, were also the two channels that were least trusted by the public; and (4) the differences in contents and service channels of health literacy among residents with different genders, ages, education levels, economic status, and living environments were statistically significant.Conclusions(1) It is recommended to establish an integrated health literacy service model with multi-center supply. Government departments, medical institutions, and media should cooperate effectively to provide health literacy services. (2) The government should pay attention to the fairness of health education and strengthen the supply of health literacy services in township areas. (3) It is critical to strengthen the public\u2019s ability to discriminate network information and pay attention to scientific thinking cultivation. (4) Health literacy service providers must focus on the differences between public demands and improve the connotation of health literacy services.", 
    "genre": "article", 
    "id": "sg:pub.10.1186/s12889-022-13272-z", 
    "inLanguage": "en", 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1024954", 
        "issn": [
          "1471-2458"
        ], 
        "name": "BMC Public Health", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "22"
      }
    ], 
    "keywords": [
      "health literacy", 
      "health education", 
      "public health literacy", 
      "Chinese general population", 
      "education level", 
      "health knowledge", 
      "general population", 
      "effective rate", 
      "IBM SPSS Statistics 20", 
      "SPSS Statistics 20", 
      "different genders", 
      "health information", 
      "COVID-19", 
      "medical institutions", 
      "random online survey", 
      "Statistics 20", 
      "age", 
      "economic status", 
      "providers", 
      "questionnaire", 
      "current era", 
      "invalid questionnaires", 
      "Department", 
      "gender", 
      "online survey", 
      "reasonable recommendations", 
      "differences", 
      "large sample", 
      "BackgroundIn", 
      "levels", 
      "subjects", 
      "Wuhan", 
      "rate", 
      "status", 
      "population", 
      "services", 
      "proportion", 
      "targeted way", 
      "residents", 
      "data", 
      "recommendations", 
      "living environment", 
      "institutions", 
      "study", 
      "service model", 
      "education", 
      "service providers", 
      "literacy", 
      "survey", 
      "area", 
      "literacy services", 
      "survey data", 
      "need", 
      "township areas", 
      "information", 
      "samples", 
      "ability", 
      "era", 
      "access", 
      "knowledge", 
      "form", 
      "facilities", 
      "content", 
      "investigation", 
      "public demand", 
      "attention", 
      "present", 
      "public", 
      "medium", 
      "channels", 
      "supply", 
      "collaboration", 
      "emergence", 
      "preferences", 
      "government departments", 
      "conditions", 
      "popularity rate", 
      "new mode", 
      "model", 
      "traditional modes", 
      "acquaintance", 
      "demand", 
      "mode", 
      "environment", 
      "Chinese citizens", 
      "way", 
      "information technology", 
      "economic conditions", 
      "government collaboration", 
      "technology", 
      "internet media", 
      "government", 
      "cultivation", 
      "people\u2019s demand", 
      "connotations", 
      "citizens", 
      "public goods", 
      "good theory", 
      "big data", 
      "service channels", 
      "goods", 
      "fairness", 
      "theory", 
      "network information", 
      "stars", 
      "public goods theory"
    ], 
    "name": "How to improve public health literacy based on polycentric public goods theory: preferences of the Chinese general population", 
    "pagination": "921", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1147745873"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/s12889-022-13272-z"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "35534809"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/s12889-022-13272-z", 
      "https://app.dimensions.ai/details/publication/pub.1147745873"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-06-01T22:23", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220601/entities/gbq_results/article/article_931.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1186/s12889-022-13272-z"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s12889-022-13272-z'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s12889-022-13272-z'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s12889-022-13272-z'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s12889-022-13272-z'


 

This table displays all metadata directly associated to this object as RDF triples.

218 TRIPLES      21 PREDICATES      141 URIs      133 LITERALS      16 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/s12889-022-13272-z schema:about N1ba1b1d36f154aef8fec099b1ee126ca
2 N54a6f27417244bf8ab566d4bd89e4440
3 N54d5afabbb75400a803f2bc5f47bf440
4 N5be5884635544222b0d59e7ffe73d177
5 N5ebbc86e713648229e976ed464b57860
6 N686312b5ecbe4586b385426ae845e4ce
7 N9803faca1794429dbb49293ac439261b
8 Nd5866a0e934a4a5fbcbf9bf47a2b6600
9 Ne33e37dff2264b6d9b89f902cbcb0da6
10 anzsrc-for:11
11 anzsrc-for:1117
12 schema:author N08a959c47c5140879945bfcfe6051512
13 schema:datePublished 2022-05-09
14 schema:datePublishedReg 2022-05-09
15 schema:description BackgroundIn the current era of big data, it is critical to address people’s demand for health literacy. At present, the traditional mode of communicating scientific health knowledge and information technology is interchangeable, resulting in the emergence of a new mode of communicating health literacy. To publicize health education and health literacy in a targeted way, to meet the public’s needs, and to understand how the public’s demand for subjects, contents, and forms of health literacy service has changed in the era of COVID-19, the investigation of public’s demand for health information and health literacy was conducted.ObjectiveThis study aims to understand the differences in demand for health literacy service providers, contents, channels, forms, and facilities among Chinese citizens with different genders, ages, education levels, economic conditions, and living environments, and to provide reasonable recommendations for developing public health literacy.MethodsQuestionnaire Star was used to conduct a large sample of random online surveys. In Wuhan, Hubei Province, 2184 questionnaires were issued, 8 invalid questionnaires were eliminated, and 2176 were recovered, with an effective rate of 99.6%. IBM SPSS Statistics 20 was utilized to analyze the survey data.Results(1) In health literacy service providers selected by the public, the proportion of government departments or government collaboration with other institutions exceeded 73%, indicating that health literacy services are public goods; (2) access to health literacy services was lower in township areas than in urban areas (P < 0.001, 3) internet media and communicating with acquaintances, which have the highest popularity rate, were also the two channels that were least trusted by the public; and (4) the differences in contents and service channels of health literacy among residents with different genders, ages, education levels, economic status, and living environments were statistically significant.Conclusions(1) It is recommended to establish an integrated health literacy service model with multi-center supply. Government departments, medical institutions, and media should cooperate effectively to provide health literacy services. (2) The government should pay attention to the fairness of health education and strengthen the supply of health literacy services in township areas. (3) It is critical to strengthen the public’s ability to discriminate network information and pay attention to scientific thinking cultivation. (4) Health literacy service providers must focus on the differences between public demands and improve the connotation of health literacy services.
16 schema:genre article
17 schema:inLanguage en
18 schema:isAccessibleForFree true
19 schema:isPartOf N4d97b4c824f84168b888d4e247d057e1
20 N98031070d8cc4b9a90c2547b538bf169
21 sg:journal.1024954
22 schema:keywords BackgroundIn
23 COVID-19
24 Chinese citizens
25 Chinese general population
26 Department
27 IBM SPSS Statistics 20
28 SPSS Statistics 20
29 Statistics 20
30 Wuhan
31 ability
32 access
33 acquaintance
34 age
35 area
36 attention
37 big data
38 channels
39 citizens
40 collaboration
41 conditions
42 connotations
43 content
44 cultivation
45 current era
46 data
47 demand
48 differences
49 different genders
50 economic conditions
51 economic status
52 education
53 education level
54 effective rate
55 emergence
56 environment
57 era
58 facilities
59 fairness
60 form
61 gender
62 general population
63 good theory
64 goods
65 government
66 government collaboration
67 government departments
68 health education
69 health information
70 health knowledge
71 health literacy
72 information
73 information technology
74 institutions
75 internet media
76 invalid questionnaires
77 investigation
78 knowledge
79 large sample
80 levels
81 literacy
82 literacy services
83 living environment
84 medical institutions
85 medium
86 mode
87 model
88 need
89 network information
90 new mode
91 online survey
92 people’s demand
93 popularity rate
94 population
95 preferences
96 present
97 proportion
98 providers
99 public
100 public demand
101 public goods
102 public goods theory
103 public health literacy
104 questionnaire
105 random online survey
106 rate
107 reasonable recommendations
108 recommendations
109 residents
110 samples
111 service channels
112 service model
113 service providers
114 services
115 stars
116 status
117 study
118 subjects
119 supply
120 survey
121 survey data
122 targeted way
123 technology
124 theory
125 township areas
126 traditional modes
127 way
128 schema:name How to improve public health literacy based on polycentric public goods theory: preferences of the Chinese general population
129 schema:pagination 921
130 schema:productId N0fd6d22adf8b4d8b98621e27167dc6e3
131 N8d7332d524074c0b82acdd0cdeb10f00
132 Nbf166df0e2f14184aab5c98f3f8c6b43
133 schema:sameAs https://app.dimensions.ai/details/publication/pub.1147745873
134 https://doi.org/10.1186/s12889-022-13272-z
135 schema:sdDatePublished 2022-06-01T22:23
136 schema:sdLicense https://scigraph.springernature.com/explorer/license/
137 schema:sdPublisher Nb2dc6ae09b484b5b899faeab726a7530
138 schema:url https://doi.org/10.1186/s12889-022-13272-z
139 sgo:license sg:explorer/license/
140 sgo:sdDataset articles
141 rdf:type schema:ScholarlyArticle
142 N08a959c47c5140879945bfcfe6051512 rdf:first N09a27417b9834d52bf5df6b71daabe85
143 rdf:rest Nc1eea2826eb74d0d8384336952bd6849
144 N09a27417b9834d52bf5df6b71daabe85 schema:affiliation grid-institutes:grid.33199.31
145 schema:familyName Gao
146 schema:givenName Yaxin
147 rdf:type schema:Person
148 N0fd6d22adf8b4d8b98621e27167dc6e3 schema:name doi
149 schema:value 10.1186/s12889-022-13272-z
150 rdf:type schema:PropertyValue
151 N13ad0f74fda54e4898e77f28b64e06a8 rdf:first sg:person.010715377363.75
152 rdf:rest rdf:nil
153 N1ba1b1d36f154aef8fec099b1ee126ca schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
154 schema:name Health Literacy
155 rdf:type schema:DefinedTerm
156 N4d97b4c824f84168b888d4e247d057e1 schema:issueNumber 1
157 rdf:type schema:PublicationIssue
158 N54a6f27417244bf8ab566d4bd89e4440 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
159 schema:name Humans
160 rdf:type schema:DefinedTerm
161 N54d5afabbb75400a803f2bc5f47bf440 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
162 schema:name Public Health
163 rdf:type schema:DefinedTerm
164 N5be5884635544222b0d59e7ffe73d177 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
165 schema:name Health Education
166 rdf:type schema:DefinedTerm
167 N5ebbc86e713648229e976ed464b57860 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
168 schema:name China
169 rdf:type schema:DefinedTerm
170 N686312b5ecbe4586b385426ae845e4ce schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
171 schema:name Surveys and Questionnaires
172 rdf:type schema:DefinedTerm
173 N8d7332d524074c0b82acdd0cdeb10f00 schema:name pubmed_id
174 schema:value 35534809
175 rdf:type schema:PropertyValue
176 N98031070d8cc4b9a90c2547b538bf169 schema:volumeNumber 22
177 rdf:type schema:PublicationVolume
178 N9803faca1794429dbb49293ac439261b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
179 schema:name Male
180 rdf:type schema:DefinedTerm
181 N990f38d1c6fc4cf287c96e87235d4ef3 schema:affiliation grid-institutes:grid.33199.31
182 schema:familyName Zhu
183 schema:givenName Li
184 rdf:type schema:Person
185 Nb2dc6ae09b484b5b899faeab726a7530 schema:name Springer Nature - SN SciGraph project
186 rdf:type schema:Organization
187 Nbf166df0e2f14184aab5c98f3f8c6b43 schema:name dimensions_id
188 schema:value pub.1147745873
189 rdf:type schema:PropertyValue
190 Nc1eea2826eb74d0d8384336952bd6849 rdf:first N990f38d1c6fc4cf287c96e87235d4ef3
191 rdf:rest N13ad0f74fda54e4898e77f28b64e06a8
192 Nd5866a0e934a4a5fbcbf9bf47a2b6600 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
193 schema:name Female
194 rdf:type schema:DefinedTerm
195 Ne33e37dff2264b6d9b89f902cbcb0da6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
196 schema:name COVID-19
197 rdf:type schema:DefinedTerm
198 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
199 schema:name Medical and Health Sciences
200 rdf:type schema:DefinedTerm
201 anzsrc-for:1117 schema:inDefinedTermSet anzsrc-for:
202 schema:name Public Health and Health Services
203 rdf:type schema:DefinedTerm
204 sg:journal.1024954 schema:issn 1471-2458
205 schema:name BMC Public Health
206 schema:publisher Springer Nature
207 rdf:type schema:Periodical
208 sg:person.010715377363.75 schema:affiliation grid-institutes:grid.33199.31
209 schema:familyName Mao
210 schema:givenName Zi Jun
211 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010715377363.75
212 rdf:type schema:Person
213 grid-institutes:grid.33199.31 schema:alternateName Department of Gastrointestinal Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Jie Fang Ave, No. 1095, Wuhan, China
214 Non-traditional Security Institute, Huazhong University of Science and Technology, 430074, Wuhan, China
215 schema:name College of Public Administration, Huazhong University of Science and Technology, No 1037 Luau Road, Hongshan District, 430074, Wuhan, China
216 Department of Gastrointestinal Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Jie Fang Ave, No. 1095, Wuhan, China
217 Non-traditional Security Institute, Huazhong University of Science and Technology, 430074, Wuhan, China
218 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...