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The Asia-Pacific Journal, Vol. 12, Issue 7, No. 4, February 17, 2014

Mind the Gap: 3.11 and the Information Vulnerable  格差に要注意 3.11と情報弱者

Shineha Ryuma and Tanaka Mikihito

Abstract After the 3.11 triple disaster, massive information flooded the media. However, a comprehensive picture of the information ecosystem regarding 3.11 is yet to emerge.This article presents a quantitative analysis of a large amount of information and discourses concerning 3.11. In addition to gaps in information about damage and danger, we found that the areas most affected by the triple disaster had a greater number of people lacking access to vital information. These people were not only left behind during the first weeks of the catastrophe, but also thereafter, in the agenda for reconstruction.

Keywords 3.11, Media analysis, Information gap, vulnerability, class

Table 1. Breakdown of damage (1)

Sources: Notification by local governments of Miyagi (Sept. 10, 2013), Iwate (Aug. 31, 2013), Fukushima (Sept. 20, 2013), and the Reconstruction Agency (Aug. 22, 2013). The number of deaths includes “3.11-related death” (震災関連死Shinsai kanren shi).

While the full consequences from the triple disaster of March 2011 (hereafter ‘3.11’) are yet to come, the event has already generated an enormous amount of information and discussion, and created confusion in understanding the information ecosystem of the event. In disaster studies, a calamity of this type is regarded as a trigger for social vulnerabilities to rise to the surface. We also have to consider the social structure behind the disaster as summarized by Wisner et al. (2003), and as pointed out by several studies in the case of the Hanshin-Awaji earthquake of 1995, the “reconstruction” might reproduce the previous structural disparities. As emphasized by Beck (1992: 35), the “history of risk distribution shows that, like wealth, risks adhere to the class pattern, only inversely: Wealth accumulates at the top, risks at the bottom. To that extent, risks seem to strengthen, not negate class society.” In other words, the weakest not only benefit less in normal times, they tend also to become the biggest risk receivers in situations of disaster or great hazard such as 3.11.

This article presents a quantitative analysis of a large amount of information and discourses regarding 3.11. First we have collected statistical data about damage from disasters and social conditions of the disaster-hit areas, issued by the local and national governments.1 This procedure was essential to analyzing the basic information and thinking about 3.11. We focused on the 37 coastal municipalities that were worst hit by the tsunami, and we tried to sketch the scope of the damage according to areas and social situations damaged before 3.11.

We then looked at the information flow concerning 3.11 in mass and social media. We draw on quantitative analysis, which includes a frequency analysis and a network analysis focusing on the co-occurrence of keywords (co-word), as well as a content analysis. Co-words and the network structure of co-words have been widely recognized as carriers of meaning and indicators of words in context (e.g. Callon et al. 1983, Braam et al. 1991, Stegman & Grohmann 2003). The method of co-word network analysis in this report depends on previous studies by Leydesdorff and Hellstein (2005, 2006), Salton’s cosine as the similarity index (Salton & McGill 1983, Jones & Fornus 1987), the description of networks by Pajek (Batagelj & Mrvar 1998), the visualizations algorithm of Kamada and Kawai (1989), and Freeman (1979)’s definition of betweenness as the index of centrality.


To begin, we need to recall that the earthquake, tsunami, and nuclear accident caused enormous damage and destruction. There were more than 20,000 cases of deaths and missing as a result of the tsunami. Additionally, at this writing, due to the tsunami and the nuclear accident, there are approximately 290,000 evacuees who are spread all over Japan. In June 2011, the national government estimated total losses for buildings, lifelines, social infrastructure, agriculture, and other damage at about 16.9 trillion yen. The disaster generated over 25 million tons of rubble and general waste.Rough sketch of damages and sites


Photo 1. Namie town, damaged by earthquake and abandoned after the Nuclear Power Plant accident (August 19, 2013)

Photo 2 Stranded Ship in the coastal area of Namie town (August 19, 2013)

The three prefectures of Miyagi, Iwate, and Fukushima were most affected. Table 1 indicates differences of scale, range, characters, and spectrum of damage according to the area. For example, deaths in the Miyagi prefecture reached over 10,000. Iwate and Fukushima also had several thousand deaths. Drowning from the tsunami caused more than 90 % deaths; approximately 65 % of the victims were over 60 years of age (Cabinet Office 2011). There were also numerous disappearances. This is an important feature of 3.11, which was unseen for example in the Hanshin-Awaji earthquake of 1995. In addition, a significant number of buildings collapsed because of the tsunami and earthquake; the coastline of towns for several hundred kilometers was literally wiped out. In addition, the nuclear accident led to a mandatory evacuation zone forcing thousands of people to leave their towns (particularly in the area of Futaba). While Miyagi prefecture registered a greater number of evacuees, Fukushima prefecture had a high proportion of evacuees outside the prefecture (see Table 1). Some people died on the spot for lack of quick rescue.2 Almost three years later, many of the affected areas along the coast of the Tohoku region still present landscapes of desolation with cars and ships destroyed by the tsunami scattered about (Photos 1-2).

Table 2 shows a breakdown of the damage and social conditions of 37 municipalities on the coastline of the three worst affected prefectures (Miyagi, Iwate, and Fukushima). Local towns in this area feature aging populations, rely heavily on farming and fisheries, and are poorer than in metropolitan areas. 

These municipalities, which were already lacking resources before 3.11, subsequently faced deeply indented coastlines with even more people living in narrowly habitable areas.

 

Total population

Total number of houses

Population ratio under 15

Population ratio from 15 to 64

Population ratio over 65

Population ratio of primary industry

Population ratio of secondary manufacturing

Population ratio of tertiary industry

Area of municipality

Sendai

1045903

530660

13.4

68.7

15.5

0.1

11.7

88.2

784

Ishinomaki

160704

64870

14.2

64.7

25.2

1.9

25.4

72.7

556

Siogama

56490

23250

13.3

67.0

24.7

0.6

23.7

75.8

18

Kesennuma

73494

25670

14.2

63.4

28.5

2.4

26.3

71.4

333

Natori

73140

25820

15.0

62.4

16.2

0.1

21.5

78.4

100

Tagajo

62979

26810

15.6

68.8

15.2

0.0

18.9

81.1

20

Iwanuma

44198

17010

15.2

66.6

17.4

0.3

25.6

74.1

61

Higashi-Matsushima

42908

15450

15.3

64.8

20.6

1.6

22.7

75.7

102

Watari

34846

11520

14.3

65.8

20.7

1.6

38.2

60.2

73

Yamamoto

16711

5310

11.8

64.8

29.4

1.2

39.5

59.3

64

Matsuhima

15089

5560

12.2

66.2

28.6

0.7

12.7

86.6

54

Shichigahama

20419

6650

16.1

68.2

18.8

1.5

24.6

73.9

13

Rifu

34000

11420

16.7

65.0

13.1

0.0

29.5

70.5

45

Onagawa

10051

-

12.7

62.0

32.0

2.1

34.3

63.6

66

Minami-Sanriku

17431

5540

15.0

62.4

29.5

3.4

32.7

63.9

164

Rikuzentakada

23302

8550

14.0

59.7

32.3

3.0

29.3

67.6

232

Ofunato

40738

16580

14.6

62.7

28.8

2.7

27.2

70.2

323

Kamaishi

39578

18420

13.2

61.5

33.9

1.7

28.8

69.4

441

Otsuchi

15277

6130

14.1

63.2

30.8

2.4

34.1

63.5

201

Yamada

18625

7950

15.1

62.7

30.3

2.5

34.1

63.3

263

Miyako

59442

25010

14.2

63.7

29.1

3.7

24.0

72.2

1260

Iwaizumi

10804

-

12.9

59.5

37.8

10.4

25.7

63.9

993

Tanobata

3843

-

15.0

62.2

33.2

4.2

34.4

61.4

156

Fudai

3088

-

13.6

64.8

30.3

8.6

26.4

64.9

70

Noda

4632

-

15.6

63.7

29.0

10.8

20.1

69.1

81

Kuji

36875

15810

16.7

64.2

25.2

3.1

28.3

68.6

623

Yono

17910

6650

15.3

64.7

29.1

8.2

27.7

64.0

303

Soma

37796

15030

15.2

62.7

24.4

1.2

38.2

60.6

198

Minami-Soma

70895

25050

14.6

62.9

25.2

1.6

30.7

67.6

399

Hirono

5418

-

15.5

63.7

23.0

1.0

41.4

57.6

58

Naaraha

7701

-

16.1

64.4

25.7

1.9

36.4

61.7

103

Tomioka

15996

6880

15.7

63.5

19.7

1.4

28.7

69.9

68

Okuma

11511

-

15.3

60.8

19.4

1.3

32.3

66.4

79

Futaba

6932

-

14.7

63.4

25.3

0.4

42.0

57.6

51

Namie

20908

7830

14.9

63.5

24.9

1.2

30.4

68.4

223

Shinchi

8218

-

15.1

62.7

26.6

3.7

38.4

57.9

46

Iwaki

342198

147740

15.2

65.0

23.2

0.9

27.2

71.8

1231

                   
 

Financial capability index

Municipal income per capita (1000yen)

Number of death

Number of destroyed houses

Death ratio

Ratio of destroyed houses

Area of flooded land

Ratio of flooded area

Ratio of population living in flooded area

Sendai

0.86

2786

704

68920

0.07

13.0

52

6.6

2.9

Ishinomaki

0.51

2108

3160

22603

1.97

34.8

73

13.1

69.9

Siogama

0.54

2218

20

3466

0.04

14.9

6

33.3

33.1

Kesennuma

0.43

1982

1007

10846

1.37

42.3

18

5.4

54.9

Natori

0.75

2491

911

3719

1.25

14.4

27

27.0

16.6

Tagajo

0.74

2627

188

4693

0.30

17.5

6

30.0

27.2

Iwanuma

0.8

2548

183

2301

0.41

13.5

29

47.5

18.2

Higashi-Matsushima

0.45

2114

1045

10833

2.44

70.1

37

36.3

79.3

Watari

0.59

2153

257

3501

0.74

30.4

35

48.0

40.4

Yamamoto

0.41

1964

670

3256

4.01

61.3

24

37.5

53.8

Matsuhima

0.53

2068

2

1637

0.01

29.4

2

3.7

26.9

Shichigahama

0.61

2371

66

1189

0.32

17.9

5

38.5

44.8

Rifu

0.85

2820

49

637

0.14

5.6

1

2.2

1.6

Onagawa

1.41

2228

547

3276

5.44

-

3

4.6

80.1

Minami-Sanriku

0.31

1829

551

3299

3.16

59.5

10

6.1

80.1

Rikuzentakada

0.28

1766

1549

3341

6.65

39.1

13

5.6

82.5

Ofunato

0.43

2023

337

3629

0.83

21.9

8

2.5

46.8

Kamaishi

0.51

2409

883

3723

2.23

20.2

7

1.6

33.3

Otsuchi

0.32

1737

800

3677

5.24

60.0

4

2.0

78.0

Yamada

0.28

1698

600

3184

3.22

40.1

5

1.9

61.3

Miyako

0.36

2297

420

4675

0.71

18.7

10

0.8

30.9

Iwaizumi

0.15

1645

7

197

0.06

-

1

0.1

10.5

Tanobata

0.14

1510

14

270

0.36

-

1

0.6

41.2

Fudai

0.14

1816

0

0

0.00

-

1

1.4

36.1

Noda

0.18

1676

38

478

0.82

-

2

2.5

68.6

Kuji

0.39

2140

2

274

0.01

1.7

4

0.6

19.4

Yono

0.23

1616

0

26

0.00

0.4

1

0.3

15.3

Soma

0.56

2721

454

1692

1.20

11.3

29

14.7

27.6

Minami-Soma

0.65

2612

640

5657

0.90

22.6

39

9.8

18.9

Hirono

1.25

5641

2

-

0.04

-

2

3.5

25.6

Naaraha

1.12

4555

11

50

0.14

-

3

2.9

22.7

Tomioka

0.92

3939

19

-

0.12

-

1

1.5

8.8

Okuma

1.5

4835

76

30

0.66

-

2

2.5

9.8

Futaba

0.78

4608

30

63

0.43

-

3

5.9

18.4

Namie

0.47

2557

144

-

0.69

-

6

2.7

16.1

Shinchi

0.86

2845

108

548

1.31

-

11

23.9

56.8

Iwaki

0.7

2711

309

21044

0.09

14.2

15

1.2

9.5

Table 2. Social structure and damage in 37 municipalities on the coasts of Miyagi, Iwate and Fukushima Prefectures. Sources: See Table 1.

   

Gap of information as infrastructure

In addition to gaps in damage and social conditions, the information gap might be considered as one of the most significant issues of 3.11. The spread and access of the Internet enable us to make and use countless amounts of information, a situation that has been reinforced by the appearance of social network services such as Twitter, Facebook, etc. During a disaster, these tools offer a base for sharing information. But as several studies have noted, the myth of a “one hundred million middle class” (ichi oku sōchūryū) cannot be supported by a careful analysis of the disparities of media usage, for which the term “digital divide” only shows one aspect. For example, people with lower social capital use a mobile phone but not a Smartphone or they do not have a PC and despite sometimes playing role games online, they are light Internet users.3 As another example, TV audiences are part-time workers. On the other hand, people with higher social capital hold Smartphones, they are users of tablet PCs and SNS, and so on.

Figure 1. Time-lined change of number of news articles and appearance ratio of keywords (Asahi newspaper)


According to a government report on the current status of Japanese Internet usage (Sōmu-shō 2011), though the coefficient of use remains relatively high for the 60-70 age group (between 57 and 70%), it drops to less than 40% for those over 70, and less than 20% for those over 80 years old. While families with high annual income (over 6 million Yen) have a coefficient use of 80%, this drops to 63% for families earning less than 2 million Yen a year.4 And of course the Tohoku region has a much lower score compared to metropolitan areas. The large majority of Internet users during the disaster and its immediate aftermath were thus in metropolitan areas, while the victims were unable to collect or send information effectively.

Figure 2. Keyword network of Asahi newspaper from March 11 to March 17, 2011


As a means to clarify the consequences of the gap of information for the victims of 3.11, we focused on newspapers, web news, blogs, and Twitter. Figure 1 shows the timeline change of article numbers and appearance of keywords in the Asahi newspaper: the appearance of the word “earthquake” gradually decreased as references to the nuclear accident increased. Looking at the 400 most frequentlyused keywords in each term from March 11 to March 17 (Figure 2), then from March 15 to March 20 (Figure 3), we can find a clear difference in co-word network that represents the degree of the organization of topics. During the first week of the disaster, there was a tremendous confusion of topics and agendas. Furthermore, the keyword cluster around “earthquake and tsunami” networks closely parallels a cluster around “Nuclear Power Plant accident and electricity.” This trend is seen in all co-word networks each week. However, in the co-word network in the sixth week, this close relationship relaxed to some degree.

To evaluate the differences in appearance of topics among newspapers, we conducted a comparison of resonance of agenda, topics and argument between the “big four” Japanese major national newspapers. After a content analysis and classification of arguments, we calculated the Spearman’s Rank Correlation Coefficient (data not shown). The result shows a high correlation between newspapers, which means that there was a resonance of trends in topics. Concerning argumentation level, there was resonance between the liberal pole (Asahi newspaper and Mainichi Newspaper) and the conservative pole (Yomiuri Newspaper and Nikkei).

Figure 3. Keyword network of Asahi newspaper from April 15 to April 20, 2011

If we look at the trends in social media, Figure 4 shows a timeline change in contents uploaded in blog entries. As a result, after a rapid decrease of “earthquake” and “tsunami”, the keywords “radiation exposure” and “nuclear accident” rapidly increased; however, interest in these new topics was not sustained. In summary, interest in the disasters and the nuclear accident has rapidly faded. The remaining and more stable interests have been about “low radiation exposure” and “internal exposure.”

For an analysis of Twitter (Figure 5), we categorized a variety of topics such as “nuclear accident” and “nuclear power policy.” In the aftermath of the accident, tweets regarding the nuclear accident occupied over 10% of all tweets in Japan. However, by the third month after the accident, this had fallen to less than 2%.

Shortly after, in the Internet sphere, there was also a rapid fall in attention to the nuclear accident and 3.11 more generally. Compared to newspapers (Figure 6), web news showed a rapid decrease in topics on the disaster, while there was a simultaneous increase in “entertainment,” “sports,” “economics,” and so on. Although this shift of central topics is common to each media outlet, the difference of degree between the media is clear. One interpretation of this is that as newspapers continued to cover the triple disaster more actively than web news, it sustained public interest. However, as mentioned above, we should not overlook the fact that topics on 3.11 in newspapers had also been mainly occupied by topics regarding “Nuclear Power Plant (NPP).”

Figure 4. Time-lined change of topics that appeared in blogs

Our analysis suggested several trends in national newspapers: “Decrease of earthquake,” “increase of NPP,” and a dense co-word network between “earthquake and tsunami” and “NPP accident and electricity.” The resonance of agenda and argument in different newspapers was also observed. Our interpretation is that the nuclear accident played a strong, agenda-setting topic and smothered interest in “earthquake and tsunami.” Then the topics on 3.11 themselves decreased rapidly (Figures 4-6).

Discussion: Disaster capitalism and “Reconstruction”

Our report shows significant “gaps” in damage and social conditions in devastated areas. These areas are primary industrial and aging societies. It is possible that local gaps of damage and social conditions caused a lag in reconstruction, like the Matthew effect. Furthermore, the vulnerability and gaps of damage, economy, and reconstruction connect gaps in the variety of resources, information, and access to power. Naomi Klein’s bestseller Shock Doctrine: The Rise of Disaster Capitalism, which was translated and published in Japan in September 2011, looked at the examples of 9.11, the Iraq War, Hurricane Katrina, the Sumatra tsunami and other “disasters” to point out the gap structures that are spread, reinforced, and reproduced in the course of work, and for which the word “reconstruction” is mobilized as a mantra.

Figure 5. Time-lined change of appearance ratio of tweets on NPP accident in Twitter

Following on Klein, Tsukahara Togo (2011) called attention to the risk of disaster capitalism in the context of 3.11, taking the case of the Great Hanshin-Awaji earthquake as an emblematic lesson. In the earthquake that hit the city of Kōbe in January 1995, 6,434 individuals died, an outbreak of fire caused the destruction of 7,035 houses and approximately 250,000 houses were seriously damaged. Tsukahara pointed out the two distinct forms of disasters: one was direct damage by earthquake and fires to humans and houses; another was the collapse of the local community and alienation of residents in the course of reconstruction and land readjustment. In the district of Nagata (downtown Kōbe), there were a large number of devastating fires which was ten times greater than that of other seriously affected areas. The damaged area was rapidly reconstructed, and the so-called “Miracle of Nagata” offers new and handsome buildings, streets with new shops, and a monument. Meanwhile more than 30,000 people had definitely left the Nagata area: while in October 1994, the population of Nagata had over 130,000, after the earthquake of January 1995, it rapidly decreased to 96,000. Although the population had somewhat recovered to approximately 108,000 by 1998, population decline continued to 101,000 by 2010. Even though the decrease started before the Hanshin-Awaji earthquake, it is clear that the decrease of population was accelerated by the urban planning launched after the earthquake.

Figure 6. Comparison between media: time-lined change of appearance ratio of topics


Statistics suggest the effect of the Hanshin-Awaji earthquake was worse for the poor, the elderly and the disadvantaged, i.e. the most vulnerable. Investigations have pointed out that about 70 % of the residents of Nagata had an annual average income under three million yen (Shinsai fukkō chōsa, 1997; Inoue 2008; Yoshii 2007). According to other studies on the Hanshin-Awaji earthquake (Iwasaki et al. 1999, Tanaka & Shiosaki 2008), before the earthquake most of the residents had their own home, but after the earthquake over 70% of those who came back in the area now lived in rented apartments because they could not afford to rebuild their house. As highlighted by Tsukahara, in the course of the “miracle reconstruction”, there was a widening gap and alienation of inhabitants. In summary, reconstruction and land readjustment after the disaster are closely related with power and politics of economic and urban design.

We can expect a similar process in the case of 3.11. As a contribution to clarifying the social disparities that might be either reinforced or generated by the triple disaster of 3.11, we have chosen to examine the information gap. Previous media studies discussed and theorized the social function of media as “agenda setting,” “agenda building,” “attention cycle,” and so on (e.g., MacCombs & Shaw, 1972; Entman, 1993; Scheufele, 1999). Our focus was rather directed at trends and discourses in the media sphere that affect social agendas and distribution of social resources, capital and public interest. Our hypothesis was that people needed access to a large choice of information and some media activity to participate in agenda setting and the rebuilding process. There were differences of power concerning information, and these differences were, at least partly, defined by gaps of social conditions and damages. We can define those who have been alienated from agenda setting and rebuilding as the information vulnerable.

As we have shown, compared to urban areas, even before the event, the areas that were most affected by the triple disaster of March 11 had a much great number of the information vulnerable. It is obvious that after 3.11, compared to young city dwellers, older people in the devastated areas have had difficultly getting and using information. What is less easy to see is why the victims of the disaster tended to be those who could not collect or discuss information effectively. The information vulnerable were not only left behind during the first weeks of the catastrophe, but also thereafter, in the agenda for “reconstruction”. In comparison with Hanshin earthquake which happened at a time when the diffusion of the Internet was only starting, the paradox is that despite the illusion of a greater distribution of information, we also discern greater disparities of access to relevant information.

In addition, there were gaps in the information taken up by the mass media. At least in national newspapers, interest was rapidly directed to the NPP accident, while in the electronic media the earthquake and tsunami faded into the background. Then, not only were victims of the tsunami relegated to a secondary role, but there was also a rapid decrease in media attention to the range of issues of 3.11. Comparative analysis between national and local newspapers would probably reinforce that analysis.

So far, we have not seen any social mobilization to reverse the balance of power between the most heavily damaged areas, with their comparatively poor and aging population, and urban Japan. We can therefore expect the information gap to widen and bring negative effects during “reconstruction.” The phenomenon that needs to be addressed here is much more than a “digital divide” between those who can “enjoy” Internet and its vast amount of information, and those who don’t: if the existence of such a divide is now well accepted, we have yet to fully understand the myriad consequences for those affected by disasters such as big earthquakes and such a complex mix as 3.11.

Shineha Ryuma is Assistant Professor at the Graduate University for Advanced Studies, Kanagawa. Tanaka Mikihito is Associate Professor at Waseda University, Tokyo.

Shineha Ryuma and Tanaka Mikihito have studied the media discourses regarding life-science, science journalism, and science & technology policy. They have published a book in Japanese on 3.11 (The Disaster Vulnerable and the Vulnerable) and a book chapter in Science Information and Politics after the Disaster of March 11 in Japan edited by Nakamura Masaki (see the full references in the list supra).

Recommended Citation: Shineha Ryuma and Tanaka Mikihito, "Mind the Gap: 3.11 and the Information Vulnerable," The Asia-Pacific Journal, Vol. 12, Issue 7, No. 4, February 17, 2014.

Related articles

This article is part of 3.11 + 3: Special Issue on Japan’s Triple Disaster Three Years On edited by Paul Jobin and David McNeill. Other articles include:

David McNeill and Paul Jobin, Introduction

Philip C. Brown, Call it A ’Wash’? Historical Perspectives on Conundrums of Technological Modernization, Flood Amelioration and Disasters in Modern Japan

Kyle Cleveland, Mobilizing Nuclear Bias: The Fukushima Nuclear Crisis and the Politics of Uncertainty

Yasuhito ABE, Safecast or the Production of Collective Intelligence on Radiation Risks after 3.11

Notes

1 We collected information from official issues, which were published by the Reconstruction Agency, the Cabinet Office, the Statics Bureau of the Ministry of Internal Affairs and Communications, and local governments of Miyagi, Iwate, and Fukushima Prefectures.

2 For example, a surgeon who conducted autopsies of victims said several victims died from starvation after suffering leg injuries and receiving no help in the evacuated area around the plant. (Asahi-Shimbun, May 25, 2012).

3 See: 中央調査社 (Central Survey Society), パーソナル先端商品の利用状況 (Current situation on the use of personal electronic commodities), April 2012: www.crs.or.jp/data/pdf/ptg2012.pdf

And: D.A. Consortium, スマートフォン・iPad・一般携帯電話に関する利用実態調査 2010(Survey on the use of Smartphones, iPad and average mobile phones): http://www.dac.co.jp/Contents/pdf/press/20100924_sp_research.pdf

4 To be precise, the coefficient use is 70.1% for those aged 60–64, 57% for the group 65–69, 39.2% for the group 70–79 and 20.3% for those over 80 years old; 63.1%, for the families with annual income under 2 million Yen, 68.6% for those between 2 and 4 million Yen, 80% for those over 6 million Yen.

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Authors: For all articles by the author, click on author's name.   Shineha Ryuma, Tanaka Mikihito