1
00:00:00,040 --> 00:00:02,200
Speaker 1: Guess what mango with that will. So I feel like

2
00:00:02,200 --> 00:00:05,480
Speaker 1: when I've been traveling recently, I've been noticing more support

3
00:00:05,559 --> 00:00:08,440
Speaker 1: dogs traveling with passengers, and I think that's great. And

4
00:00:08,640 --> 00:00:11,000
Speaker 1: I decided to look into this because I do find

5
00:00:11,080 --> 00:00:13,280
Speaker 1: it an interesting field. And one of the facts that

6
00:00:13,320 --> 00:00:16,680
Speaker 1: I stumbled on was that sixty of dogs that try

7
00:00:16,760 --> 00:00:19,759
Speaker 1: to become guide dogs end up dropping out of school.

8
00:00:20,040 --> 00:00:23,360
Speaker 1: And it's actually a pretty expensive problem. Training a guide

9
00:00:23,400 --> 00:00:26,800
Speaker 1: dog cost about fifty thousand dollars a pup and it's

10
00:00:26,800 --> 00:00:28,720
Speaker 1: a two year training course, so it can be both

11
00:00:28,720 --> 00:00:32,559
Speaker 1: a drain on time and money. So I mean, obviously

12
00:00:32,600 --> 00:00:34,920
Speaker 1: there's a need for guide dogs though, so like, is

13
00:00:34,920 --> 00:00:37,440
Speaker 1: there some sort of like no dog left behind policy

14
00:00:37,520 --> 00:00:40,720
Speaker 1: that's getting institute, Well, not quite, but there are researchers

15
00:00:40,720 --> 00:00:42,479
Speaker 1: at Georgia Tech that are trying to come up with

16
00:00:42,520 --> 00:00:44,880
Speaker 1: a solution. In fact, they figured out a way to

17
00:00:45,000 --> 00:00:47,919
Speaker 1: draft winners before they even go to school, and this

18
00:00:48,000 --> 00:00:51,160
Speaker 1: is by using smart chew toys. So basically they put

19
00:00:51,240 --> 00:00:54,320
Speaker 1: sensors in these toys and balls to monitor how the

20
00:00:54,360 --> 00:00:57,560
Speaker 1: puppies work. They created profiles based on how they bite

21
00:00:57,560 --> 00:01:00,520
Speaker 1: and chew and tug and play, and then use this

22
00:01:00,640 --> 00:01:04,440
Speaker 1: data to pick the winners, and it's surprisingly effective. The

23
00:01:04,480 --> 00:01:06,760
Speaker 1: team claims they can select dogs who will graduate with

24
00:01:06,800 --> 00:01:11,640
Speaker 1: almost accuracy, and by using smart toys to weed out

25
00:01:11,640 --> 00:01:14,160
Speaker 1: the duds, Georgia Tech can actually save these guide schools

26
00:01:14,200 --> 00:01:17,480
Speaker 1: about five million dollars a year. And that's just the

27
00:01:17,560 --> 00:01:20,000
Speaker 1: first of nine stories and science we're about to share

28
00:01:20,040 --> 00:01:43,920
Speaker 1: with you. Let's dive in a their podcast. Listeners, Welcome

29
00:01:43,920 --> 00:01:46,280
Speaker 1: to Part Time Genius. I'm Will Pearson, and as always

30
00:01:46,319 --> 00:01:48,720
Speaker 1: I'm joined by my good friend man Guesh Ticketer and

31
00:01:48,760 --> 00:01:51,320
Speaker 1: sitting behind the soundproof glass showing off his collection of

32
00:01:51,440 --> 00:01:54,360
Speaker 1: vintage test tubes and beakers. I know he's so proud

33
00:01:54,400 --> 00:01:56,840
Speaker 1: of those things, but they really just look like regular

34
00:01:56,880 --> 00:01:59,400
Speaker 1: test tubes and beakers to me. I know, but you know,

35
00:01:59,520 --> 00:02:01,920
Speaker 1: let's not tell him that. But that's our PALIN producer

36
00:02:02,000 --> 00:02:04,600
Speaker 1: Tristan McNeil so mago. One of the things I know

37
00:02:04,640 --> 00:02:06,800
Speaker 1: you and I both love but don't get to spend

38
00:02:06,880 --> 00:02:11,160
Speaker 1: enough time doing is finding these weird little science stories. Yeah. So,

39
00:02:11,280 --> 00:02:13,240
Speaker 1: at Mental Class we used to do a ten issue

40
00:02:13,280 --> 00:02:15,440
Speaker 1: every year, and for people who don't know, it's just

41
00:02:15,480 --> 00:02:19,320
Speaker 1: like a weird magazine issue of lists of ten So

42
00:02:19,400 --> 00:02:22,160
Speaker 1: we'd feature things like ten guys named Fred you should know,

43
00:02:22,400 --> 00:02:25,480
Speaker 1: or how ten presidents popped the question, or things like that.

44
00:02:25,600 --> 00:02:27,680
Speaker 1: And in the first few years we always did a

45
00:02:27,760 --> 00:02:30,480
Speaker 1: ten Bright Ideas and Science and then a ten not

46
00:02:30,600 --> 00:02:32,960
Speaker 1: so Bright Ideas and Science, which was, you know, a

47
00:02:33,040 --> 00:02:36,320
Speaker 1: much shorter list. And I don't think people thought it

48
00:02:36,320 --> 00:02:38,480
Speaker 1: was not funny, except we thought it was funny. So

49
00:02:38,600 --> 00:02:41,240
Speaker 1: we just kept putting it in there. Oh man, I'm

50
00:02:41,240 --> 00:02:43,440
Speaker 1: still doing and even though we're not publishing the magazine,

51
00:02:43,440 --> 00:02:45,720
Speaker 1: it's still just too much fun to do well, all right,

52
00:02:45,760 --> 00:02:48,080
Speaker 1: So we kicked off today's nine Things with a fact

53
00:02:48,120 --> 00:02:50,200
Speaker 1: about guide dogs. So so where do you want to

54
00:02:50,240 --> 00:02:53,080
Speaker 1: take it from there? Mango? How about a weirdo study

55
00:02:53,160 --> 00:02:56,160
Speaker 1: out of the University of Queensland. And this claims that

56
00:02:56,280 --> 00:02:59,600
Speaker 1: wild leopards make good neighbors and cities because they actually

57
00:02:59,600 --> 00:03:04,200
Speaker 1: protect the population from rabies. So this is obviously super

58
00:03:04,240 --> 00:03:06,640
Speaker 1: weird and the data comes from the outskirts of Bombay,

59
00:03:06,720 --> 00:03:11,200
Speaker 1: where leopards apparently live in the Sanjay Gandhi National Park. Anyway,

60
00:03:11,240 --> 00:03:13,440
Speaker 1: so as the researchers were looking into the diet of

61
00:03:13,440 --> 00:03:16,320
Speaker 1: these leopards on the city's fringe, they realized that feral

62
00:03:16,400 --> 00:03:19,280
Speaker 1: dogs from the city actually make up forty percent of

63
00:03:19,360 --> 00:03:22,800
Speaker 1: the average leopards diet. And you know, for the thirty

64
00:03:22,800 --> 00:03:26,320
Speaker 1: five leopards there, that meant fifteen hundred dogs a year.

65
00:03:26,720 --> 00:03:31,080
Speaker 1: It's obviously a lot of dogs. Yeah, But this is

66
00:03:31,080 --> 00:03:33,880
Speaker 1: where it gets even weirder. So, I mean, my family

67
00:03:33,919 --> 00:03:36,480
Speaker 1: is actually from Bombay, and this is not my experience

68
00:03:36,480 --> 00:03:38,280
Speaker 1: of the city at all. From the summers I spent

69
00:03:38,320 --> 00:03:40,760
Speaker 1: there in church, kid or vend or or whatever. And

70
00:03:41,240 --> 00:03:43,640
Speaker 1: because you know, to me, the city doesn't feel provincial

71
00:03:43,640 --> 00:03:46,240
Speaker 1: at all. It really feels more like New York City.

72
00:03:46,320 --> 00:03:50,040
Speaker 1: But apparently these leopards were eating so many dogs that

73
00:03:50,120 --> 00:03:53,240
Speaker 1: they were actually preventing about a thousand dog bite incidents

74
00:03:53,280 --> 00:03:58,000
Speaker 1: per year and about nine cases of rabies and uh as,

75
00:03:58,120 --> 00:04:01,120
Speaker 1: one of the authors told New Scientists, quote, this study

76
00:04:01,160 --> 00:04:04,400
Speaker 1: is a striking example of a large carnivorous animal providing

77
00:04:04,400 --> 00:04:08,520
Speaker 1: a direct benefit to humans. Now, obviously I don't think

78
00:04:08,560 --> 00:04:11,360
Speaker 1: he's telling like Mayor di Blasio or other mayors, like,

79
00:04:11,480 --> 00:04:15,000
Speaker 1: if your city has a rabies epidemic, go adopt some leopards,

80
00:04:15,040 --> 00:04:18,080
Speaker 1: Because the scientists are pretty clear that there could be

81
00:04:18,120 --> 00:04:20,560
Speaker 1: some downsides to bring in a leopard population to deal

82
00:04:20,560 --> 00:04:23,839
Speaker 1: with their feral dog population. Yeah, maybe just a couple

83
00:04:23,880 --> 00:04:27,560
Speaker 1: of downsides. That is such a weird one, but it

84
00:04:27,720 --> 00:04:30,160
Speaker 1: is super interesting. All right. So, I know we did

85
00:04:30,200 --> 00:04:32,800
Speaker 1: an episode on weather We'll ever Cure Blindness a little

86
00:04:32,800 --> 00:04:35,480
Speaker 1: while back, But did you read about how Microsoft has

87
00:04:35,520 --> 00:04:38,760
Speaker 1: been working to create virtual reality for blind people? No,

88
00:04:38,960 --> 00:04:42,520
Speaker 1: that that's fascinating. How how's that work? Well, by manipulating

89
00:04:42,520 --> 00:04:45,480
Speaker 1: a walking kane or a cane troller as they call it,

90
00:04:45,480 --> 00:04:48,000
Speaker 1: it's and it's really awesome. So basically, the walking Kane

91
00:04:48,080 --> 00:04:51,320
Speaker 1: uses vibrations to make the user feel like they're exploring

92
00:04:51,360 --> 00:04:54,800
Speaker 1: new worlds filled with different types of objects. Plus there's

93
00:04:54,800 --> 00:04:56,839
Speaker 1: a vest that presses against your body to give you

94
00:04:56,880 --> 00:05:00,080
Speaker 1: the feeling of walls or other obstacles. And but is

95
00:05:00,120 --> 00:05:03,200
Speaker 1: their sound design paired with this experience, it can actually

96
00:05:03,240 --> 00:05:07,080
Speaker 1: create these amazing worlds. Obviously, the simulations can be used

97
00:05:07,120 --> 00:05:10,279
Speaker 1: for gaming, but there are practical applications as well. A

98
00:05:10,279 --> 00:05:13,800
Speaker 1: Microsoft employee expected that people will practice walking through heavy

99
00:05:13,839 --> 00:05:16,560
Speaker 1: traffic or you know, get a better feel for navigating

100
00:05:16,560 --> 00:05:19,400
Speaker 1: a city and a snowstorm. And I'm sure they're all

101
00:05:19,400 --> 00:05:21,640
Speaker 1: sorts of things we haven't thought about, but it's amazing

102
00:05:21,720 --> 00:05:24,920
Speaker 1: how well it works. People feel like they're winding through

103
00:05:25,000 --> 00:05:28,599
Speaker 1: narrow pathways and navigating icy curbs even though they're just

104
00:05:28,680 --> 00:05:32,600
Speaker 1: in these wide, empty spaces. That's pretty cool. So here's

105
00:05:32,600 --> 00:05:34,760
Speaker 1: a quick one I think is pretty interesting, and it's

106
00:05:34,800 --> 00:05:37,160
Speaker 1: that Chinese scientists have actually figured out how to make

107
00:05:37,200 --> 00:05:40,479
Speaker 1: a smart wallpaper. Now, Initially, when I saw a link

108
00:05:40,480 --> 00:05:42,600
Speaker 1: to the zap Boing Boing, I figured like the wallpaper

109
00:05:42,720 --> 00:05:46,080
Speaker 1: was something that resisted stains. And I think that's just

110
00:05:46,120 --> 00:05:48,760
Speaker 1: because that's where my mind goes, having like a four

111
00:05:48,839 --> 00:05:51,320
Speaker 1: year old banksy at our house who just draws all

112
00:05:51,320 --> 00:05:55,040
Speaker 1: over the walls and crayon. But you know, the wallpaper

113
00:05:55,080 --> 00:05:57,960
Speaker 1: is actually much much smarter than that. So first off,

114
00:05:58,000 --> 00:05:59,960
Speaker 1: it's made from a material that's found in your bone

115
00:06:00,200 --> 00:06:04,160
Speaker 1: and teeth called hydroxy appetite, and according to the American

116
00:06:04,240 --> 00:06:08,160
Speaker 1: Chemical Society, that material is brittle and inflexible. But if

117
00:06:08,160 --> 00:06:11,320
Speaker 1: you make it into these really long, thin nano wires

118
00:06:11,360 --> 00:06:13,479
Speaker 1: and then join them, it kind of ends up with

119
00:06:13,480 --> 00:06:16,480
Speaker 1: the thickness of a wallpaper. And the reason it's exciting

120
00:06:16,640 --> 00:06:19,760
Speaker 1: is because that material is actually fireproof, so already that

121
00:06:19,839 --> 00:06:22,440
Speaker 1: makes it smarter, right, because it's protecting your walls and house.

122
00:06:22,520 --> 00:06:25,280
Speaker 1: But then the scientists also equipped it with these sensors

123
00:06:25,279 --> 00:06:28,640
Speaker 1: and smoke detectors. So basically, if a fire breaks out

124
00:06:28,720 --> 00:06:31,520
Speaker 1: anywhere in your house, it's both equipped to set off

125
00:06:31,520 --> 00:06:33,520
Speaker 1: an alarm within the house at the first instance of

126
00:06:33,520 --> 00:06:36,120
Speaker 1: a fire, but it can also communicate to the outside

127
00:06:36,120 --> 00:06:38,520
Speaker 1: world to like fire departments, to alert them. I mean,

128
00:06:38,560 --> 00:06:40,760
Speaker 1: this kind of stuff is so cool. It's just crazy.

129
00:06:40,800 --> 00:06:43,520
Speaker 1: You can take something like a chew toy or wallpaper

130
00:06:43,680 --> 00:06:46,840
Speaker 1: and you know and say, like, what does it connected

131
00:06:46,960 --> 00:06:50,359
Speaker 1: smart version of this really do for society? And you know,

132
00:06:50,360 --> 00:06:53,120
Speaker 1: when scientists ponder these questions, they figure out ways to

133
00:06:53,160 --> 00:06:55,839
Speaker 1: give the world more seeing eye dogs and save people

134
00:06:55,880 --> 00:06:59,240
Speaker 1: from fires. And it's just it's just incredible, all right.

135
00:06:59,279 --> 00:07:01,400
Speaker 1: So here's a study we didn't talk about in our

136
00:07:01,400 --> 00:07:04,600
Speaker 1: Science of Paying killers, but scientists in Denmark have discovered

137
00:07:04,600 --> 00:07:08,159
Speaker 1: that taking six hundred milligrams of ibuprofen twice a day

138
00:07:08,560 --> 00:07:11,240
Speaker 1: will give you hypogonadism or or what I think they

139
00:07:11,240 --> 00:07:14,680
Speaker 1: call medically. I think they call it small balls, So

140
00:07:14,960 --> 00:07:16,920
Speaker 1: I don't think that's a medical term, but I do

141
00:07:17,080 --> 00:07:20,320
Speaker 1: think you're gonna have to explain yourself. Well, from what

142
00:07:20,400 --> 00:07:23,280
Speaker 1: I understand, the scientists were looking into fertility issues, and

143
00:07:23,320 --> 00:07:25,640
Speaker 1: they got thirty one healthy guys and they had them

144
00:07:25,640 --> 00:07:28,880
Speaker 1: take ibuprofen for six weeks, and across the board, the

145
00:07:28,960 --> 00:07:32,920
Speaker 1: drug lowered their testosterone production. But what the scientists realized

146
00:07:32,960 --> 00:07:35,720
Speaker 1: was that when the body noticed the drop, the pituitary

147
00:07:35,760 --> 00:07:39,720
Speaker 1: gland kicked in another hormone and to overdrive, and that

148
00:07:39,760 --> 00:07:44,000
Speaker 1: triggered more testosterone production. And because the tests were overworked

149
00:07:44,000 --> 00:07:47,480
Speaker 1: to compensate for what the ibuprofen was doing, they basically

150
00:07:47,480 --> 00:07:51,200
Speaker 1: shrunk significantly. So I mean, is this much of an issue? Like, like,

151
00:07:51,360 --> 00:07:55,040
Speaker 1: I don't know anyone who takes ibuprofen twice a day regularly. Well,

152
00:07:55,080 --> 00:07:57,520
Speaker 1: according to the study, it can be a problem in

153
00:07:57,600 --> 00:07:59,680
Speaker 1: things like sports, where you know, apparently a lot of

154
00:07:59,680 --> 00:08:02,960
Speaker 1: athlet eats to take hyboprofen daily to reduce swelling. But

155
00:08:03,000 --> 00:08:05,520
Speaker 1: if you're looking to go back to r T S

156
00:08:05,640 --> 00:08:09,200
Speaker 1: or what we obviously know is regular testable size, all

157
00:08:09,280 --> 00:08:11,520
Speaker 1: you have to do is quit taking the eyboprofen, and

158
00:08:11,560 --> 00:08:13,440
Speaker 1: if you do it soon enough, it won't have any

159
00:08:13,480 --> 00:08:17,000
Speaker 1: permanent damage. So I'll definitely keep that in mind. And

160
00:08:17,280 --> 00:08:19,280
Speaker 1: here's one that people have been talking about for a while,

161
00:08:19,360 --> 00:08:22,560
Speaker 1: but it's fun to see finally coming true and it's

162
00:08:22,560 --> 00:08:25,920
Speaker 1: creating plants that glow. So for a while, scientists have

163
00:08:26,040 --> 00:08:28,920
Speaker 1: been able to genetically engineer plans to express the gene

164
00:08:28,920 --> 00:08:32,800
Speaker 1: that fireflies use, which is called luciferase, and it produces

165
00:08:32,840 --> 00:08:35,800
Speaker 1: this sort of weak glowing light. But unfortunately it isn't

166
00:08:35,800 --> 00:08:38,640
Speaker 1: particularly easy to do or effective, like the light that

167
00:08:38,720 --> 00:08:41,800
Speaker 1: emerges is too dim to read by, and also they

168
00:08:41,800 --> 00:08:43,480
Speaker 1: could only pull off this trick with a few types

169
00:08:43,480 --> 00:08:46,240
Speaker 1: of plants. But scientists M. I. T. Have actually figured

170
00:08:46,280 --> 00:08:49,040
Speaker 1: out this new method where they could basically turn any

171
00:08:49,120 --> 00:08:51,800
Speaker 1: plant into a glow stick. So far, they've actually done

172
00:08:51,840 --> 00:08:56,000
Speaker 1: it with a arugula, kale, spinach, water cross. I. I

173
00:08:56,080 --> 00:08:58,480
Speaker 1: don't know why it's only vegetables for some reason, I

174
00:08:58,559 --> 00:09:01,520
Speaker 1: was gonna but from the photos you can actually read

175
00:09:01,559 --> 00:09:04,800
Speaker 1: by the plant's glow. And what's cooler is that the

176
00:09:04,840 --> 00:09:06,600
Speaker 1: next iteration of this is to be able to like

177
00:09:06,679 --> 00:09:10,440
Speaker 1: create a spray that sprays nanoparticles onto plants to have

178
00:09:10,559 --> 00:09:13,880
Speaker 1: that same effect. So it isn't a far fetched idea

179
00:09:14,000 --> 00:09:16,120
Speaker 1: like this should be able to be done fairly soon,

180
00:09:16,240 --> 00:09:18,840
Speaker 1: and the result is that instead of like our neighborhoods

181
00:09:18,920 --> 00:09:22,240
Speaker 1: using lamp posts, we'd have like glowing trees casting light

182
00:09:22,280 --> 00:09:25,360
Speaker 1: for us. Or if you like ambient light around your house,

183
00:09:25,440 --> 00:09:28,520
Speaker 1: like you might purchase tulip bulbs instead of light bulbs.

184
00:09:28,600 --> 00:09:31,439
Speaker 1: It's not awesome, that's that is really cool. Or well,

185
00:09:31,480 --> 00:09:33,120
Speaker 1: here's another idea I saw out of M I T.

186
00:09:33,360 --> 00:09:36,040
Speaker 1: And and the backstory of this is ridiculous. And this

187
00:09:36,080 --> 00:09:38,839
Speaker 1: is from new scientists, always with the great stories. But

188
00:09:39,120 --> 00:09:41,719
Speaker 1: apparently a professor named Jeffrey Lipton at M I T

189
00:09:42,040 --> 00:09:45,520
Speaker 1: was friends with a carpenter who accidentally cut off each

190
00:09:45,559 --> 00:09:49,559
Speaker 1: of his thumbs with a saw twice. That's four thumbs, mango.

191
00:09:50,000 --> 00:09:51,920
Speaker 1: I don't know how many thumbs this guy had and

192
00:09:52,040 --> 00:09:54,839
Speaker 1: how that happened exactly, but I just like to leave

193
00:09:54,880 --> 00:09:56,920
Speaker 1: it at that, know that he cut off four thumbs.

194
00:09:56,920 --> 00:10:00,719
Speaker 1: But anyway to prevent this from happening again, you would think,

195
00:10:00,760 --> 00:10:02,480
Speaker 1: like to prevent this of it happening again, would just

196
00:10:02,480 --> 00:10:06,520
Speaker 1: be like, don't use this is four thumbs. This is

197
00:10:06,520 --> 00:10:09,760
Speaker 1: a problem anyway. So Lipton and his team have designed

198
00:10:09,760 --> 00:10:12,960
Speaker 1: a system where you submit a design for tables or

199
00:10:13,040 --> 00:10:15,520
Speaker 1: sheds or frames or whatever it is, and then the

200
00:10:15,559 --> 00:10:18,160
Speaker 1: team of robots cut all the pieces out for you,

201
00:10:18,200 --> 00:10:20,600
Speaker 1: and it's it's pretty amazing because what you end up

202
00:10:20,640 --> 00:10:24,640
Speaker 1: with is basically this personalized flat pack furniture. But the

203
00:10:24,679 --> 00:10:27,560
Speaker 1: funnier part is how he built the things. So to

204
00:10:27,559 --> 00:10:30,880
Speaker 1: cut wavy patterns, he attached a jigsaw to a roomba.

205
00:10:31,440 --> 00:10:33,640
Speaker 1: So I really want to watch the team of machines

206
00:10:33,640 --> 00:10:36,120
Speaker 1: at work. It sounds kind of amazing. Yeah, so Lipton

207
00:10:36,200 --> 00:10:38,920
Speaker 1: expects you'll see these robot carpenters in the next few years.

208
00:10:38,920 --> 00:10:42,199
Speaker 1: But until then, he's begging people, please don't just trap

209
00:10:42,200 --> 00:10:45,079
Speaker 1: a jigsaw to a room. But unless you're a roboticistem

210
00:10:45,640 --> 00:10:48,120
Speaker 1: that's pretty good advice. So we've got two more facts

211
00:10:48,120 --> 00:10:50,120
Speaker 1: to do before we declare winner. But let's take a

212
00:10:50,200 --> 00:11:06,000
Speaker 1: quick break. First, welcome back to Part Time Genius, where

213
00:11:06,000 --> 00:11:09,760
Speaker 1: we're talking about some new science studies we've been reading about. So, Mago,

214
00:11:09,880 --> 00:11:11,920
Speaker 1: this is your last fact. What do you got for us?

215
00:11:12,880 --> 00:11:14,800
Speaker 1: So there are a ton of studies we won't get

216
00:11:14,800 --> 00:11:17,680
Speaker 1: to today, Like there was one on babies and how

217
00:11:17,760 --> 00:11:21,120
Speaker 1: they actually expect adults to behave morally, like babies are

218
00:11:21,160 --> 00:11:23,040
Speaker 1: kind of born with ethics, which is kind of amazing.

219
00:11:23,080 --> 00:11:26,680
Speaker 1: And uh, there was one on woodpeckers possibly being communists,

220
00:11:26,840 --> 00:11:29,160
Speaker 1: which I really like, Like, there's a lot of great

221
00:11:29,160 --> 00:11:32,000
Speaker 1: stuff we'll get into in future episodes. But there's a

222
00:11:32,000 --> 00:11:34,360
Speaker 1: study that actually kind of bothered me, and it was

223
00:11:34,400 --> 00:11:37,280
Speaker 1: about how people who are more disgusted by body odor

224
00:11:37,600 --> 00:11:40,920
Speaker 1: prefer to vote for authoritarian leaders. Next, there's just like

225
00:11:41,080 --> 00:11:44,120
Speaker 1: so much bad news going on right now that I

226
00:11:44,200 --> 00:11:46,720
Speaker 1: kind of wanted something the opposite of that. So I

227
00:11:46,760 --> 00:11:48,840
Speaker 1: was looking for, like, what's the study on something that

228
00:11:48,880 --> 00:11:52,320
Speaker 1: actually increases empathy? And it turns out one thing that

229
00:11:52,400 --> 00:11:56,319
Speaker 1: will increase empathy is reading Harry Potter. H Yeah, So

230
00:11:56,440 --> 00:11:59,480
Speaker 1: this comes from the Journal of Applied Social Psychology, and

231
00:11:59,520 --> 00:12:02,679
Speaker 1: this is why epacific standard. But in two different studies

232
00:12:02,679 --> 00:12:05,640
Speaker 1: in Italy, kids who paid attention to Harry Potter's behavior

233
00:12:05,679 --> 00:12:09,600
Speaker 1: to marginalized groups and characters actually reduced their prejudices and

234
00:12:09,640 --> 00:12:13,560
Speaker 1: became more empathetic for marginalized communities. And obviously there's a

235
00:12:13,640 --> 00:12:16,120
Speaker 1: lot of this in the book, right, like Harry himself

236
00:12:16,160 --> 00:12:19,240
Speaker 1: as an outsider, he's making friends with people like Hagrid

237
00:12:19,400 --> 00:12:23,920
Speaker 1: and these muggles and animals and house elves. And the

238
00:12:23,920 --> 00:12:26,520
Speaker 1: study also showed that kids who read Harry Potter tend

239
00:12:26,640 --> 00:12:30,120
Speaker 1: to have fewer homophobic tendencies, which is equally amazing to me.

240
00:12:30,240 --> 00:12:33,120
Speaker 1: But all of this comes with the catch, So the

241
00:12:33,200 --> 00:12:36,720
Speaker 1: empathy only increases with young readers who actually feel connected

242
00:12:36,720 --> 00:12:39,520
Speaker 1: to Harry, and for those who are on Team Baltimore,

243
00:12:39,760 --> 00:12:42,400
Speaker 1: the researchers didn't see the same changes. No way, is

244
00:12:42,440 --> 00:12:45,040
Speaker 1: that really true. That's pretty wild. I mean, of course,

245
00:12:45,120 --> 00:12:47,320
Speaker 1: natural born Slytherins aren't going to look out for others,

246
00:12:47,320 --> 00:12:50,080
Speaker 1: so I guess we can't be that surprised. But I

247
00:12:50,120 --> 00:12:53,000
Speaker 1: do like that reading Harry Potter has this positive impact

248
00:12:53,040 --> 00:12:55,240
Speaker 1: on so many people's lives. But I do have to

249
00:12:55,280 --> 00:12:58,880
Speaker 1: say I also like my last fact, and yeah, that's

250
00:12:58,920 --> 00:13:01,680
Speaker 1: that any type of regular reading might help you live longer.

251
00:13:02,000 --> 00:13:03,760
Speaker 1: So this comes from mental flaws and it's about a

252
00:13:03,800 --> 00:13:07,000
Speaker 1: study at Yale. But basically, the scientists there have looked

253
00:13:07,000 --> 00:13:09,640
Speaker 1: at things like how watching TV and being a couch

254
00:13:09,679 --> 00:13:12,960
Speaker 1: potato can reduce your lifespan. So they decided to turn

255
00:13:12,960 --> 00:13:16,680
Speaker 1: their attention to reading and analyze people over the age

256
00:13:16,679 --> 00:13:19,480
Speaker 1: of fifty. And here's how the study worked. They started

257
00:13:19,480 --> 00:13:22,160
Speaker 1: by sorting the groups into people who didn't read books,

258
00:13:22,520 --> 00:13:24,600
Speaker 1: people who read up to three and a half hours

259
00:13:24,600 --> 00:13:27,440
Speaker 1: a week and people who read more than that. Then

260
00:13:27,480 --> 00:13:30,280
Speaker 1: they followed up with them twelve years later, and after

261
00:13:30,360 --> 00:13:34,160
Speaker 1: adjusting for factors like education, income, health, and a few

262
00:13:34,160 --> 00:13:37,320
Speaker 1: other things, actually found that quote book readers experience the

263
00:13:38,040 --> 00:13:40,800
Speaker 1: reduction and the risk of mortality over the twelve years

264
00:13:40,800 --> 00:13:44,080
Speaker 1: of follow up compared to non book readers. On average,

265
00:13:44,080 --> 00:13:47,120
Speaker 1: the book readers lived twenty three months more than non readers,

266
00:13:47,360 --> 00:13:49,680
Speaker 1: which the author points out should make everyone want to

267
00:13:49,720 --> 00:13:52,880
Speaker 1: get a library card. Oh. I like that. Hooray for reading.

268
00:13:53,000 --> 00:13:54,920
Speaker 1: And there are a lot of fun facts in here.

269
00:13:54,920 --> 00:13:56,800
Speaker 1: But I I think the fact that we both got

270
00:13:56,800 --> 00:13:58,600
Speaker 1: to plug books and reading at the end of it

271
00:13:58,640 --> 00:14:00,760
Speaker 1: makes us both winners. So what do you say we

272
00:14:00,760 --> 00:14:03,319
Speaker 1: share today's prize. I think that's a great idea. Well,

273
00:14:03,320 --> 00:14:05,120
Speaker 1: that's it for today's episode. We'll be back with a

274
00:14:05,160 --> 00:14:08,319
Speaker 1: full length episode tomorrow. Thanks so much for listening. H