First-in-human clinical study of novel technique to diagnose malignant melanoma via thermal conductivity measurements View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

Takahiro Okabe, Taku Fujimura, Junnosuke Okajima, Yumi Kambayashi, Setsuya Aiba, Shigenao Maruyama

ABSTRACT

Melanoma is an aggressive skin cancer that originates from melanocytes and, especially in the case of early-stage melanoma, is distributed adjacent to the epidermis and superficial dermis. Although early-stage melanoma can be distinguished from benign nevus via a dermoscopy, it is difficult to distinguish invasive melanoma in its early stages from in situ melanoma. Because invasive melanoma must undergo a sentinel lymph node biopsy to be diagnosed, a non-invasive method to detect the micro-invasion of early-stage melanoma is needed for dermato-oncologists. This paper proposes a novel quantitative melanoma identification method based on accurate measurements of thermal conductivity using a pen-shaped device. This method requires skin temperature data for one minute to determine the effective thermal conductivity of the skin, allowing it to distinguish melanoma lesions from healthy skin. Results suggest that effective thermal conductivity was negative for in situ melanoma. However, in accordance with tumour progression, effective thermal conductivity was larger in invasive melanoma. The proposed thermal conductivity measurement is a novel tool that detects the micro-invasion of melanoma. More... »

PAGES

3853

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41598-019-40444-6

DOI

http://dx.doi.org/10.1038/s41598-019-40444-6

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112604245

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30846837


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/2008/1112", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Oncology and Carcinogenesis", 
        "type": "DefinedTerm"
      }, 
      {
        "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"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Hirosaki University", 
          "id": "https://www.grid.ac/institutes/grid.257016.7", 
          "name": [
            "Graduate School of Science and Technology, Hirosaki University, Hirosaki, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Okabe", 
        "givenName": "Takahiro", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tohoku University", 
          "id": "https://www.grid.ac/institutes/grid.69566.3a", 
          "name": [
            "Graduate School of Medicine, Tohoku University, Sendai, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fujimura", 
        "givenName": "Taku", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tohoku University", 
          "id": "https://www.grid.ac/institutes/grid.69566.3a", 
          "name": [
            "Institute of Fluid Science, Tohoku University, Sendai, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Okajima", 
        "givenName": "Junnosuke", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tohoku University", 
          "id": "https://www.grid.ac/institutes/grid.69566.3a", 
          "name": [
            "Graduate School of Medicine, Tohoku University, Sendai, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kambayashi", 
        "givenName": "Yumi", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tohoku University", 
          "id": "https://www.grid.ac/institutes/grid.69566.3a", 
          "name": [
            "Graduate School of Medicine, Tohoku University, Sendai, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Aiba", 
        "givenName": "Setsuya", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "National Institute Of Technology", 
          "id": "https://www.grid.ac/institutes/grid.482504.f", 
          "name": [
            "National Institute of Technology, Hachinohe College, Hachinohe, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Maruyama", 
        "givenName": "Shigenao", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1088/0957-0233/19/7/075104", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006581659"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0738-081x(95)00073-o", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022779026"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1524-4725.1981.tb00629.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038560461"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1524-4725.1981.tb00629.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038560461"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4684-8285-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039142765", 
          "https://doi.org/10.1007/978-1-4684-8285-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4684-8285-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039142765", 
          "https://doi.org/10.1007/978-1-4684-8285-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijthermalsci.2010.10.019", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049945158"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2147/ccid.s27902", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051700233"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1088/0031-9155/55/19/020", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059028364"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1088/0031-9155/55/19/020", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059028364"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijheatmasstransfer.2017.01.072", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1083416012"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/1346-8138.13629", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1085184782"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1056/nejmoa1613210", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1085917022"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/bjd.16098", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092412815"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/jdv.14782", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1100232088"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1001/jamadermatol.2018.0212", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1103422554"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijheatmasstransfer.2018.06.039", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1104593387"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11864-018-0560-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1105179185", 
          "https://doi.org/10.1007/s11864-018-0560-y"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-12", 
    "datePublishedReg": "2019-12-01", 
    "description": "Melanoma is an aggressive skin cancer that originates from melanocytes and, especially in the case of early-stage melanoma, is distributed adjacent to the epidermis and superficial dermis. Although early-stage melanoma can be distinguished from benign nevus via a dermoscopy, it is difficult to distinguish invasive melanoma in its early stages from in situ melanoma. Because invasive melanoma must undergo a sentinel lymph node biopsy to be diagnosed, a non-invasive method to detect the micro-invasion of early-stage melanoma is needed for dermato-oncologists. This paper proposes a novel quantitative melanoma identification method based on accurate measurements of thermal conductivity using a pen-shaped device. This method requires skin temperature data for one minute to determine the effective thermal conductivity of the skin, allowing it to distinguish melanoma lesions from healthy skin. Results suggest that effective thermal conductivity was negative for in situ melanoma. However, in accordance with tumour progression, effective thermal conductivity was larger in invasive melanoma. The proposed thermal conductivity measurement is a novel tool that detects the micro-invasion of melanoma.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1038/s41598-019-40444-6", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1045337", 
        "issn": [
          "2045-2322"
        ], 
        "name": "Scientific Reports", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "9"
      }
    ], 
    "name": "First-in-human clinical study of novel technique to diagnose malignant melanoma via thermal conductivity measurements", 
    "pagination": "3853", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "90b45d46f9bc95cb65b897ba61437493b17f2962ab43949f201667c2341e36fd"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "30846837"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "101563288"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1038/s41598-019-40444-6"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1112604245"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1038/s41598-019-40444-6", 
      "https://app.dimensions.ai/details/publication/pub.1112604245"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T11:25", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000356_0000000356/records_57865_00000001.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://www.nature.com/articles/s41598-019-40444-6"
  }
]
 

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.10.1038/s41598-019-40444-6'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/s41598-019-40444-6'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/s41598-019-40444-6'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/s41598-019-40444-6'


 

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

151 TRIPLES      21 PREDICATES      44 URIs      21 LITERALS      9 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1038/s41598-019-40444-6 schema:about anzsrc-for:11
2 anzsrc-for:1112
3 schema:author N94bfccd437bb40068aef149cae71e88c
4 schema:citation sg:pub.10.1007/978-1-4684-8285-0
5 sg:pub.10.1007/s11864-018-0560-y
6 https://doi.org/10.1001/jamadermatol.2018.0212
7 https://doi.org/10.1016/0738-081x(95)00073-o
8 https://doi.org/10.1016/j.ijheatmasstransfer.2017.01.072
9 https://doi.org/10.1016/j.ijheatmasstransfer.2018.06.039
10 https://doi.org/10.1016/j.ijthermalsci.2010.10.019
11 https://doi.org/10.1056/nejmoa1613210
12 https://doi.org/10.1088/0031-9155/55/19/020
13 https://doi.org/10.1088/0957-0233/19/7/075104
14 https://doi.org/10.1111/1346-8138.13629
15 https://doi.org/10.1111/bjd.16098
16 https://doi.org/10.1111/j.1524-4725.1981.tb00629.x
17 https://doi.org/10.1111/jdv.14782
18 https://doi.org/10.2147/ccid.s27902
19 schema:datePublished 2019-12
20 schema:datePublishedReg 2019-12-01
21 schema:description Melanoma is an aggressive skin cancer that originates from melanocytes and, especially in the case of early-stage melanoma, is distributed adjacent to the epidermis and superficial dermis. Although early-stage melanoma can be distinguished from benign nevus via a dermoscopy, it is difficult to distinguish invasive melanoma in its early stages from in situ melanoma. Because invasive melanoma must undergo a sentinel lymph node biopsy to be diagnosed, a non-invasive method to detect the micro-invasion of early-stage melanoma is needed for dermato-oncologists. This paper proposes a novel quantitative melanoma identification method based on accurate measurements of thermal conductivity using a pen-shaped device. This method requires skin temperature data for one minute to determine the effective thermal conductivity of the skin, allowing it to distinguish melanoma lesions from healthy skin. Results suggest that effective thermal conductivity was negative for in situ melanoma. However, in accordance with tumour progression, effective thermal conductivity was larger in invasive melanoma. The proposed thermal conductivity measurement is a novel tool that detects the micro-invasion of melanoma.
22 schema:genre research_article
23 schema:inLanguage en
24 schema:isAccessibleForFree true
25 schema:isPartOf Nc4f64f1936f644bbb9a2ef6b274bb6d8
26 Nd09b8790d45c4958b26a11137579d522
27 sg:journal.1045337
28 schema:name First-in-human clinical study of novel technique to diagnose malignant melanoma via thermal conductivity measurements
29 schema:pagination 3853
30 schema:productId N1612ed2050f9492c9e30ff27af831da4
31 N463283cccf6048f9b9e799f5a0fd447c
32 N6c330f846b5e4adba243383a002532b3
33 Nb27e3d25b02343d3beaa527a609b1dec
34 Nec69bbcec3ee4b8a84c11bc7bea90b7e
35 schema:sameAs https://app.dimensions.ai/details/publication/pub.1112604245
36 https://doi.org/10.1038/s41598-019-40444-6
37 schema:sdDatePublished 2019-04-11T11:25
38 schema:sdLicense https://scigraph.springernature.com/explorer/license/
39 schema:sdPublisher N1978a88277a543529da4ecca95c51d16
40 schema:url https://www.nature.com/articles/s41598-019-40444-6
41 sgo:license sg:explorer/license/
42 sgo:sdDataset articles
43 rdf:type schema:ScholarlyArticle
44 N1612ed2050f9492c9e30ff27af831da4 schema:name pubmed_id
45 schema:value 30846837
46 rdf:type schema:PropertyValue
47 N1978a88277a543529da4ecca95c51d16 schema:name Springer Nature - SN SciGraph project
48 rdf:type schema:Organization
49 N3140bbcd996445b3a1788d84ce9bf13f schema:affiliation https://www.grid.ac/institutes/grid.482504.f
50 schema:familyName Maruyama
51 schema:givenName Shigenao
52 rdf:type schema:Person
53 N463283cccf6048f9b9e799f5a0fd447c schema:name doi
54 schema:value 10.1038/s41598-019-40444-6
55 rdf:type schema:PropertyValue
56 N5fedac61f4fd46fc90352260094b83d0 schema:affiliation https://www.grid.ac/institutes/grid.69566.3a
57 schema:familyName Kambayashi
58 schema:givenName Yumi
59 rdf:type schema:Person
60 N690e0336d14147ac8b6f61319ae25b6d schema:affiliation https://www.grid.ac/institutes/grid.69566.3a
61 schema:familyName Okajima
62 schema:givenName Junnosuke
63 rdf:type schema:Person
64 N6c330f846b5e4adba243383a002532b3 schema:name dimensions_id
65 schema:value pub.1112604245
66 rdf:type schema:PropertyValue
67 N7e85cce1a3ad4aae945b514861a42799 rdf:first N5fedac61f4fd46fc90352260094b83d0
68 rdf:rest N9b671b75aa4e4d1792bad413c5ecb13e
69 N928a26b8fa7646cc9a8104d1259ccf9e rdf:first N690e0336d14147ac8b6f61319ae25b6d
70 rdf:rest N7e85cce1a3ad4aae945b514861a42799
71 N94bfccd437bb40068aef149cae71e88c rdf:first Nfea8c7ce99024c6294f09c93c10d14fb
72 rdf:rest Needd113f4c5c4af7865eac746d60165c
73 N9b671b75aa4e4d1792bad413c5ecb13e rdf:first Nfe172f283c1e4457b38379f1433e19f4
74 rdf:rest Ne9d89d47eeb74bf592465a4ea20c48ef
75 Nb18dd0a3cb2749ebb238bc817be96755 schema:affiliation https://www.grid.ac/institutes/grid.69566.3a
76 schema:familyName Fujimura
77 schema:givenName Taku
78 rdf:type schema:Person
79 Nb27e3d25b02343d3beaa527a609b1dec schema:name nlm_unique_id
80 schema:value 101563288
81 rdf:type schema:PropertyValue
82 Nc4f64f1936f644bbb9a2ef6b274bb6d8 schema:issueNumber 1
83 rdf:type schema:PublicationIssue
84 Nd09b8790d45c4958b26a11137579d522 schema:volumeNumber 9
85 rdf:type schema:PublicationVolume
86 Ne9d89d47eeb74bf592465a4ea20c48ef rdf:first N3140bbcd996445b3a1788d84ce9bf13f
87 rdf:rest rdf:nil
88 Nec69bbcec3ee4b8a84c11bc7bea90b7e schema:name readcube_id
89 schema:value 90b45d46f9bc95cb65b897ba61437493b17f2962ab43949f201667c2341e36fd
90 rdf:type schema:PropertyValue
91 Needd113f4c5c4af7865eac746d60165c rdf:first Nb18dd0a3cb2749ebb238bc817be96755
92 rdf:rest N928a26b8fa7646cc9a8104d1259ccf9e
93 Nfe172f283c1e4457b38379f1433e19f4 schema:affiliation https://www.grid.ac/institutes/grid.69566.3a
94 schema:familyName Aiba
95 schema:givenName Setsuya
96 rdf:type schema:Person
97 Nfea8c7ce99024c6294f09c93c10d14fb schema:affiliation https://www.grid.ac/institutes/grid.257016.7
98 schema:familyName Okabe
99 schema:givenName Takahiro
100 rdf:type schema:Person
101 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
102 schema:name Medical and Health Sciences
103 rdf:type schema:DefinedTerm
104 anzsrc-for:1112 schema:inDefinedTermSet anzsrc-for:
105 schema:name Oncology and Carcinogenesis
106 rdf:type schema:DefinedTerm
107 sg:journal.1045337 schema:issn 2045-2322
108 schema:name Scientific Reports
109 rdf:type schema:Periodical
110 sg:pub.10.1007/978-1-4684-8285-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039142765
111 https://doi.org/10.1007/978-1-4684-8285-0
112 rdf:type schema:CreativeWork
113 sg:pub.10.1007/s11864-018-0560-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1105179185
114 https://doi.org/10.1007/s11864-018-0560-y
115 rdf:type schema:CreativeWork
116 https://doi.org/10.1001/jamadermatol.2018.0212 schema:sameAs https://app.dimensions.ai/details/publication/pub.1103422554
117 rdf:type schema:CreativeWork
118 https://doi.org/10.1016/0738-081x(95)00073-o schema:sameAs https://app.dimensions.ai/details/publication/pub.1022779026
119 rdf:type schema:CreativeWork
120 https://doi.org/10.1016/j.ijheatmasstransfer.2017.01.072 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083416012
121 rdf:type schema:CreativeWork
122 https://doi.org/10.1016/j.ijheatmasstransfer.2018.06.039 schema:sameAs https://app.dimensions.ai/details/publication/pub.1104593387
123 rdf:type schema:CreativeWork
124 https://doi.org/10.1016/j.ijthermalsci.2010.10.019 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049945158
125 rdf:type schema:CreativeWork
126 https://doi.org/10.1056/nejmoa1613210 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085917022
127 rdf:type schema:CreativeWork
128 https://doi.org/10.1088/0031-9155/55/19/020 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059028364
129 rdf:type schema:CreativeWork
130 https://doi.org/10.1088/0957-0233/19/7/075104 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006581659
131 rdf:type schema:CreativeWork
132 https://doi.org/10.1111/1346-8138.13629 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085184782
133 rdf:type schema:CreativeWork
134 https://doi.org/10.1111/bjd.16098 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092412815
135 rdf:type schema:CreativeWork
136 https://doi.org/10.1111/j.1524-4725.1981.tb00629.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1038560461
137 rdf:type schema:CreativeWork
138 https://doi.org/10.1111/jdv.14782 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100232088
139 rdf:type schema:CreativeWork
140 https://doi.org/10.2147/ccid.s27902 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051700233
141 rdf:type schema:CreativeWork
142 https://www.grid.ac/institutes/grid.257016.7 schema:alternateName Hirosaki University
143 schema:name Graduate School of Science and Technology, Hirosaki University, Hirosaki, Japan
144 rdf:type schema:Organization
145 https://www.grid.ac/institutes/grid.482504.f schema:alternateName National Institute Of Technology
146 schema:name National Institute of Technology, Hachinohe College, Hachinohe, Japan
147 rdf:type schema:Organization
148 https://www.grid.ac/institutes/grid.69566.3a schema:alternateName Tohoku University
149 schema:name Graduate School of Medicine, Tohoku University, Sendai, Japan
150 Institute of Fluid Science, Tohoku University, Sendai, Japan
151 rdf:type schema:Organization
 




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


...