Browse content similar to 13/03/2014. Check below for episodes and series from the same categories and more!
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Hello and welcome to the One Show with Matt Baker and Alex Jones. | :00:18. | :00:24. | |
Tonight, we have a man who will be headlining this summer ten nights at | :00:25. | :00:29. | |
London's O2 Arena. With help from his friends, they are hoping to | :00:30. | :00:34. | |
raise the roof with laughter. And the odd reference to spam, funny | :00:35. | :00:39. | |
walks and the unexpected Spanish Inquisition. It is Terry Gilliam. | :00:40. | :00:48. | |
200,000 people are going to come and see you. Bearing in mind the venue, | :00:49. | :00:54. | |
who is going to be the biggest Mariah Carey of Monty Pythons? Who | :00:55. | :01:01. | |
is the biggest diva? The last time we got together, we were at the | :01:02. | :01:07. | |
Albert Hall, and Terry Jones, Michael Palin and myself shared a | :01:08. | :01:11. | |
dressing room. One person had his own dressing room. John Cleves was | :01:12. | :01:17. | |
not there that night. I think it means Eric idle. He did not share | :01:18. | :01:23. | |
that night, and he may not share, but for ten nights, he might get | :01:24. | :01:26. | |
away with it for one or two, but then... We will talk about that | :01:27. | :01:34. | |
later. He is also here to talk about his new film, Zero Theorem, which | :01:35. | :01:41. | |
deals with technology. Are you a lover or hater of technology? I | :01:42. | :01:48. | |
think it is a Damocles sword. It has two edges. I use technology all the | :01:49. | :01:52. | |
time, but I worry that Sony people are becoming addicted to the need to | :01:53. | :01:56. | |
only exist as a tweet in somebody else's life. -- so many people. I | :01:57. | :02:05. | |
have seen the movie. It is an interesting take on how technology | :02:06. | :02:08. | |
might change the world. A US company is asking the world to assist in the | :02:09. | :02:14. | |
search for flight MH370, by scouring satellite images of a -- of possible | :02:15. | :02:22. | |
crashed sites. People power being used is not as unusual as you might | :02:23. | :02:26. | |
think. The collective brainpower of the public could end up saving your | :02:27. | :02:31. | |
life. Each week, people spend hours | :02:32. | :02:40. | |
playing mobile phone games. Now, scientists are tapping into our love | :02:41. | :02:43. | |
of gaming to solve a host of problems. New games are being | :02:44. | :02:47. | |
created with the potential to pinpoint key information about | :02:48. | :02:54. | |
diseases such as cancer and HIV. As people play along, the data is sent | :02:55. | :03:01. | |
back to scientists to analyse. I am in Dundee meeting games developers | :03:02. | :03:04. | |
who have designed a mobile phone game that could help to find a cure | :03:05. | :03:10. | |
for breast cancer. This game is called genes in space. It is a bit | :03:11. | :03:14. | |
like space invaders but instead of stars, the Galaxy is made up of the | :03:15. | :03:19. | |
DNA information of thousands of tumour samples. Mark is one of the | :03:20. | :03:25. | |
designers of the game. We have a single DNA sample of a single cancer | :03:26. | :03:30. | |
cell. The peaks and troughs are the anomalies in the cancer cells that | :03:31. | :03:35. | |
they need to find. Before the scientists can figure out why the | :03:36. | :03:39. | |
anomalies exist, they need to know where they are. We have created a | :03:40. | :03:44. | |
game where people identify these as part of the gameplay experience. | :03:45. | :03:48. | |
Cambridge University provided the developers with thousands of these | :03:49. | :03:52. | |
DNA maps, which are used as the basis of the game. Players need to | :03:53. | :03:57. | |
work out where the most condensed areas are and fly a spaceship | :03:58. | :04:02. | |
through them. By doing that, they automatically record key | :04:03. | :04:04. | |
information, and every time a player completes a level, it means that one | :04:05. | :04:10. | |
DNA sample has been mapped out. The accuracy comes from the number of | :04:11. | :04:14. | |
people playing. The more people playing, the more data we get. Can | :04:15. | :04:20. | |
anybody played? It does not require any specialist knowledge or | :04:21. | :04:25. | |
training. This is not the first time the science world has turned to | :04:26. | :04:30. | |
gamers for help. A Rubik 's cube style game helped experts at the | :04:31. | :04:33. | |
University of Washington to get a better understanding of the protein | :04:34. | :04:40. | |
structure of the HIV - aids virus. So why is the creation of these | :04:41. | :04:43. | |
games proving so popular with scientists. Ken Brown is a lecture | :04:44. | :04:51. | |
in psychology. There are certain things that computers are not good | :04:52. | :04:55. | |
at seeing. We have simple images here. A human can perceive a | :04:56. | :05:00. | |
triangle or a snake shape. We are predisposed to seeing patterns in a | :05:01. | :05:05. | |
way that a computer struggles to do. So humans have the advantage over | :05:06. | :05:10. | |
computers in some instances. Absolutely. We are good at spotting | :05:11. | :05:14. | |
where the valuable information is. We are not distracted by clutter. | :05:15. | :05:20. | |
The computer would be distracted, thinking maybe the path is up here. | :05:21. | :05:24. | |
Humans have evolved to do this sort of thing. But are these games any | :05:25. | :05:31. | |
good? We brought together a group of passionate gamers to test out some | :05:32. | :05:36. | |
of the science games on offer. It is incredibly easy, if you are a | :05:37. | :05:40. | |
beginner to games or you do not play off, it is nice and relaxing. At the | :05:41. | :05:45. | |
same time, it is really cool to see so many people also doing it. It is | :05:46. | :05:52. | |
just like playing a game. I don't see why it couldn't be good for lots | :05:53. | :05:56. | |
of people to pick up and play. If you enjoy solving the puzzle that | :05:57. | :06:00. | |
can be interesting. Do you think these kind of games will ever become | :06:01. | :06:05. | |
really big? If they are entertaining enough, yes. It has been a month | :06:06. | :06:10. | |
since the launch of the game, and I'm keen to find out what has been | :06:11. | :06:14. | |
achieved so far. The University of Cambridge is analysing the data, and | :06:15. | :06:19. | |
this professor is leading the research team. We have received 1.5 | :06:20. | :06:25. | |
million analyses. People have generated their own interpretation | :06:26. | :06:29. | |
of the data 1.5 million times. Doing that would take a scientist, or my | :06:30. | :06:33. | |
team, many thousands of hours to get the same thing that citizens science | :06:34. | :06:39. | |
is getting us. He told us one analysis would take him five minutes | :06:40. | :06:42. | |
to map out. That would mean him working nonstop for 125,000 hours, | :06:43. | :06:48. | |
14 years, to cover the same amount of work that gamers have covered in | :06:49. | :06:54. | |
one month. This is one of the 1.5 million plots. This person picked up | :06:55. | :06:58. | |
that there is an aberration here, and this is important because it | :06:59. | :07:01. | |
pinpoints that there is a cancer gene in this spot. But they did not | :07:02. | :07:06. | |
know they were picking that up. How is it relevant to breast cancer? | :07:07. | :07:12. | |
Cancer arises by the immolation of mutations. Having a more precise | :07:13. | :07:15. | |
definition of the genetic make-up of the tumour, we can come up with | :07:16. | :07:19. | |
better ways of diagnosing that and having the treatment that is | :07:20. | :07:26. | |
tailored to that particular cancer. I was slightly sceptical before I | :07:27. | :07:32. | |
saw that. I am sure lots of people will want to have a go at this. | :07:33. | :07:37. | |
Researchers are hoping that 1.5 million more people will take part | :07:38. | :07:40. | |
in that experiment. How can they do it? It is called genes in space and | :07:41. | :07:46. | |
they need to download it onto their phone or tablet and start playing. | :07:47. | :07:55. | |
The details are on our website. ways we can help medical research without | :07:56. | :07:58. | |
necessarily having to leave the house. You can sit on your sofa and | :07:59. | :08:03. | |
aid medical research. One of the things they want to try is a brain | :08:04. | :08:09. | |
experiment. Terry, if you would be so kind. We will start you off. I | :08:10. | :08:15. | |
want you to try level one. This is a brain game which has been developed | :08:16. | :08:21. | |
for neuroscientists at University College London. He is so good. He | :08:22. | :08:27. | |
has got it. Basically, he is doing a series of exercises, and we would | :08:28. | :08:33. | |
have put his data in, so they know male or female age and that sort of | :08:34. | :08:37. | |
stuff. Usually, they have a brain lab and they have maybe ten people | :08:38. | :08:40. | |
who would come along, often students. We need to get this to the | :08:41. | :08:46. | |
wider population and more samples, which is what these can do. It will | :08:47. | :08:50. | |
come up with all sorts of results and we want to know more about how | :08:51. | :08:55. | |
the brain works. Any idea how many people have done this? 87,000 | :08:56. | :09:02. | |
people, but they want more and more. It is really interesting research. | :09:03. | :09:05. | |
We will be able to know whether young people are more impulsive than | :09:06. | :09:09. | |
old people, men and women, differences in risk taking. How is | :09:10. | :09:16. | |
it going? It was fine but I got distracted because you were talking. | :09:17. | :09:22. | |
I am trying to do some work here! There is probably a list of things | :09:23. | :09:26. | |
like, do not do this on live television. If people want to get | :09:27. | :09:32. | |
involved, maybe not on the medical side... There are so many things. | :09:33. | :09:37. | |
This is citizen science in action. We have things like space, history, | :09:38. | :09:43. | |
climate, nature. The cyclone centre, scientists from their have asked if | :09:44. | :09:49. | |
viewers could help them. They have had 6000 downloads of their app so | :09:50. | :09:54. | |
far. It asks you to analyse some of 300,000 pictures of cyclones. You | :09:55. | :09:58. | |
are looking for observations and that will help them understand the | :09:59. | :10:01. | |
strength and how cyclones change. The details are on the website and | :10:02. | :10:06. | |
they want to get to 1 million. Does this sit comfortably with you? In | :10:07. | :10:12. | |
the old days, I could count on giving up my children for medical | :10:13. | :10:16. | |
science for experimentation. And now it has turned into some kind of | :10:17. | :10:22. | |
game. Where is the fun in that? ! It is so much fun and so important. | :10:23. | :10:27. | |
People have discovered planets that the astronomers have missed. | :10:28. | :10:33. | |
Asteroids? Did you know about the Python asteroids? Each of us is an | :10:34. | :10:43. | |
asteroid. Each of us has an asteroid named. Out of this world! Thank you. | :10:44. | :10:53. | |
31 years ago Terry and the Pythons' famous film asked what is the | :10:54. | :10:59. | |
meaning of life. Are we any closer to answering that? We consulted some | :11:00. | :11:02. | |
very wise people to see what they think. | :11:03. | :11:12. | |
What is the meaning of life? The meaning of life is in the palm of | :11:13. | :11:22. | |
your hand. You are born, you live, you die, you still pay taxes. | :11:23. | :11:33. | |
I think the meaning of life is that we spend too long worrying about our | :11:34. | :11:39. | |
past and caring about it, too long worrying about the future and we | :11:40. | :11:44. | |
forget about today. Today is a gift. Enjoy it and live it. | :11:45. | :11:53. | |
The meaning of life is to live. It comes with love, joy, peace, provide | :11:54. | :12:04. | |
for my family, be a friend in time of trouble. | :12:05. | :12:12. | |
The meaning of life, for me, is to be satisfied with what you have | :12:13. | :12:18. | |
got. Also, to be charitable and help other people. Bagel is the best | :12:19. | :12:26. | |
meaning of life. It is round. Whatever goes around comes around. | :12:27. | :12:30. | |
If you cannot go around, there is a hole in it to escape so you will be | :12:31. | :12:38. | |
happy. What is the meaning of life? The | :12:39. | :12:45. | |
first question to enquire is to actually ask what is the meaning of | :12:46. | :12:52. | |
life, the source of everything, who is the supreme? We are desperately | :12:53. | :12:56. | |
trying to find happiness, to find our father. We are looking full of. | :12:57. | :13:07. | |
-- we are looking for love. The meaning of life is like this job. | :13:08. | :13:11. | |
You switch on your meter, do your work, take your money and go home. | :13:12. | :13:17. | |
That's life. The only certainty in life is death. Everything in between | :13:18. | :13:21. | |
is a bonus so get on with it and enjoy it. That is the spirit! Don't | :13:22. | :13:31. | |
you feel better after watching that? I don't understand the whole bagel | :13:32. | :13:37. | |
thing. Just be satisfied. Watch it before you go up that massive rock! | :13:38. | :13:42. | |
Terry, let's talk about the meaning of life. You are renowned for really | :13:43. | :13:49. | |
delving into the world of the lead character you are directing. The | :13:50. | :13:52. | |
whole point of Zero Theorem is to find the meaning of life. 31 years | :13:53. | :13:56. | |
on from when you first set out, are you any closer? No, I just keep | :13:57. | :14:02. | |
asking the question and keep searching for it. All that I know is | :14:03. | :14:07. | |
that life has no meaning in itself. It is molecules. Things happen. It | :14:08. | :14:14. | |
is an extraordinary world and I love the mystery of it. Science runs | :14:15. | :14:18. | |
around and we can do the gene a lot of things, but we never really get | :14:19. | :14:26. | |
down to the death of it. For me, a lot of people are quite wonderful. | :14:27. | :14:30. | |
You have to make your life meaningful. It is down to you, isn't | :14:31. | :14:36. | |
it? Totally down to you. In Zero Theorem, the man is waiting for a | :14:37. | :14:41. | |
telephone call to give him the meaning of life. This is madness. It | :14:42. | :14:47. | |
is like when you see adverts on the television, on the street, this car, | :14:48. | :14:51. | |
that perfused that will give meaning to your life. Nonsense. You have to | :14:52. | :14:56. | |
work at it a bit. Let's have a look at the trailer for the film. | :14:57. | :15:04. | |
Everyone is getting rich, except you. What seems to be the problem? | :15:05. | :15:13. | |
We are dying. There is only one of you. So it would appear. How is it | :15:14. | :15:22. | |
hanging? Not at all well. We are seeing nothing most of all. Are you | :15:23. | :15:30. | |
trying to be difficult? Nobody lasts, it is a guaranteed burn-out | :15:31. | :15:39. | |
project. Zero Theorem. Is that a clear view of where you think things | :15:40. | :15:45. | |
are heading? I fear they are. I worry about the connectivity of the | :15:46. | :15:47. | |
world, where people don't know who they are as individuals, just a | :15:48. | :15:52. | |
reflection of other people through their tweets. I hate the money | :15:53. | :15:55. | |
people aren't living in the moment. I go to concerts and before the | :15:56. | :16:01. | |
first song is finished, people are tweeting. The concert becomes | :16:02. | :16:07. | |
wallpaper, background for them. Be there, let it happen. I left with a | :16:08. | :16:13. | |
feeling of as long as you feel something it is better than waiting | :16:14. | :16:16. | |
for someone else telling you how to feel. Peer pressure, what do they | :16:17. | :16:22. | |
think of me? You two are very similar in your thought process, on | :16:23. | :16:27. | |
Twitter. It is a way of connecting people, maybe not in reality, but | :16:28. | :16:32. | |
people do connect and yourself this afternoon can make you did a | :16:33. | :16:37. | |
question and answer on it. I was forced, as part of promoting this | :16:38. | :16:42. | |
film I was shackled and I had to tweet. It is a chance for people to | :16:43. | :16:46. | |
get to the heart of it come the director of the film, and ask | :16:47. | :16:51. | |
questions. That is fine, interesting, but to sit there in the | :16:52. | :16:55. | |
middle of a meal and take a picture of the food and send it to your | :16:56. | :17:00. | |
friends, come on, eat the food and enjoy it. Everybody is a critic and | :17:01. | :17:05. | |
commentator like everybody on television too quickly. On | :17:06. | :17:09. | |
Facebook, lots of people want to know, because you have been working | :17:10. | :17:13. | |
on this film, who killed Don Quixote, for 20 years, and you are | :17:14. | :17:18. | |
starting it again in September. Are you going to finish it this time? | :17:19. | :17:24. | |
Who knows! Will you give it a good go? Every time I finish a film I go | :17:25. | :17:32. | |
into my default position, which is the man who killed -- The Man Who | :17:33. | :17:35. | |
Killed Don Quixote. We will start to shoot at the end of September, what | :17:36. | :17:38. | |
happens may be slightly different than my virtual world. People would | :17:39. | :17:43. | |
love to see it and The Zero Theorem is out in cinemas from tomorrow. You | :17:44. | :17:47. | |
can see it when you get back from Utah. While the weather may be | :17:48. | :17:52. | |
improving around the country, many people hit by the recent floods are | :17:53. | :17:56. | |
still living in temporary accommodation. Mike Dilger went to | :17:57. | :17:59. | |
meet the volunteers working hard to get the residents of Moorland in | :18:00. | :18:06. | |
Somerset back into their homes. The water may have retreated but 90% | :18:07. | :18:10. | |
of the residents can't even live here because tonnes of mud and | :18:11. | :18:15. | |
debris need to be shifted before they can return home. Welcome to | :18:16. | :18:20. | |
operation flood clean up, as jobs go it does not get any bigger than | :18:21. | :18:26. | |
this. The main thing is, make sure everyone is covered up, you have a | :18:27. | :18:31. | |
face mask and hand gloves on. Has anyone any questions? It is from | :18:32. | :18:35. | |
this derelict building that the clean-up is being operated from | :18:36. | :18:40. | |
flooding on the levels action group, which helps flood victims. | :18:41. | :18:46. | |
23-year-old Stuart Smith in charge. They have come from local towns and | :18:47. | :18:51. | |
villages, people from London, Leeds, Bradford, Worcester, and a gentleman | :18:52. | :18:55. | |
has come from Switzerland for a month. Of the 100 houses in the | :18:56. | :19:00. | |
village, 79 were flooded. Today, Stuart and his team start to clear | :19:01. | :19:06. | |
out the carpets from this home. He has only lived here for eight | :19:07. | :19:11. | |
months. We have lost our furniture, the kitchen is ruined, everything | :19:12. | :19:15. | |
really. Where do you think you would be without this army of volunteers? | :19:16. | :19:21. | |
We would be knee deep in rubbish in the house. They have been fantastic | :19:22. | :19:26. | |
and we are grateful. You would think the loss adjusters and insurance | :19:27. | :19:30. | |
would take it away. The problem is because the water has been in for | :19:31. | :19:36. | |
such a long time, they were not allowed in for health and safety | :19:37. | :19:40. | |
reasons. One of the volunteers, Penny, is a nurse, and has been | :19:41. | :19:45. | |
offering emotional support. I found there was a need to talk to some of | :19:46. | :19:50. | |
the residents really. It is not just about clearing houses. If you think | :19:51. | :19:53. | |
that for years and years they have collected all this stuff and it is | :19:54. | :19:59. | |
very hard for them to suddenly let it all go, it is hard. The next port | :20:00. | :20:05. | |
of call for Stuart is the clearing out the freezer on a nearby farm. It | :20:06. | :20:12. | |
sounds like a smelly job. Yes, you are in for a shock. O! We need to | :20:13. | :20:21. | |
document everything that comes out, that is the only thing. Is that what | :20:22. | :20:26. | |
you are doing? Ella bobbin are you ready? Stuart and his team are doing | :20:27. | :20:36. | |
this for Henry Davie, who has lived here for 55 years. When will you be | :20:37. | :20:42. | |
back in the house? Next weekend. They are tough up here. He has a | :20:43. | :20:46. | |
smile on his face despite everything. No point crying about | :20:47. | :20:53. | |
it, is there? A month ago Stuart was a car salesman. I came to mall and | :20:54. | :20:57. | |
just for a weekend to help out where I could -- I came to Moorland. I | :20:58. | :21:03. | |
messaged my boss to say, sorry, I am not coming back in for a while | :21:04. | :21:07. | |
because they need my help here. You have given up your job. How are you | :21:08. | :21:12. | |
coping? Ella bobbin I am living of savings to support my family, I am | :21:13. | :21:17. | |
not worrying about that right now, it is not my priority. The | :21:18. | :21:23. | |
priorities the people. Yes, the people and the community. The final | :21:24. | :21:26. | |
stop of the day is to clear out debris from Maria's house. The water | :21:27. | :21:31. | |
was three feet deep ear and home insurance does not cover her. | :21:32. | :21:34. | |
Without Stuart's help, she would have no one to turn to. It came up | :21:35. | :21:40. | |
to here, literally the whole house, from here to the end of the annex. | :21:41. | :21:46. | |
Without these guys this place would be a mess. They came in, ten of | :21:47. | :21:50. | |
them, washing, drying, packing. It was like someone had sent them from | :21:51. | :21:57. | |
above. I can't put it any better. Two days ago I could not hold a | :21:58. | :22:01. | |
conversation with her, she was in tears most of the time. We are | :22:02. | :22:05. | |
trying to bring her spirits up, we have the food waste out, the fridge | :22:06. | :22:10. | |
is out, now we will build step by step and work with her and make it | :22:11. | :22:15. | |
better. Still some way to go. There is a long way to go. See you | :22:16. | :22:21. | |
tomorrow. See you tomorrow, goodbye. Just how long it is going to be | :22:22. | :22:25. | |
before things return to normal here if anyone's guess but one thing is | :22:26. | :22:30. | |
for certain. Thanks to people like Stuart and his amazing team, from | :22:31. | :22:33. | |
now on things are only going to get better. | :22:34. | :22:38. | |
I will second that, I was down there a couple of weeks ago and I met | :22:39. | :22:43. | |
Stuart and he is an inspiration. Lovely. Terry, the other thing we | :22:44. | :22:48. | |
must talk about is the price since reuniting. Not for one, but ten | :22:49. | :22:54. | |
nights at the O2 in July. Oh, yes, he says! Are you honestly a bit | :22:55. | :22:59. | |
gutted it has gone from one night, to ten. It wasn't part of my plan. | :23:00. | :23:06. | |
Why not? I had Don Quixote, this film, and Opera, I am trying to | :23:07. | :23:09. | |
finish an autobiography, the last thing I needed was ten nights of | :23:10. | :23:15. | |
price and again. So why decide to do it again? We need it and it is | :23:16. | :23:21. | |
keeping the group together. It is great to be lads working together in | :23:22. | :23:26. | |
the good old days. Are you rehearsing? Will you win it and see | :23:27. | :23:32. | |
what develops? We have a weak's rehearsal before we start. The set | :23:33. | :23:36. | |
is quite spectacular. There is going to be a lot of big, shiny things. | :23:37. | :23:41. | |
But then literally nobody is doing much until that week. Are you | :23:42. | :23:47. | |
directing and set designing yourself? I am good at that. I think | :23:48. | :23:52. | |
the odd thing about the show is Graham is no longer with us so we're | :23:53. | :23:56. | |
having to swap around and do things that we didn't do before. I have got | :23:57. | :24:01. | |
stuck having to step into Michael Palin's she was on a sketch and it | :24:02. | :24:06. | |
is terrifying. He is such a genius, brilliant, and I can only fail | :24:07. | :24:10. | |
miserably. We all look forward to seeing what happens to stop Yes. | :24:11. | :24:15. | |
Most people think that dogs have simple tastes, regular meals, a bit | :24:16. | :24:20. | |
of TLC and the ball to chase. It sounds like a man I know! It would | :24:21. | :24:25. | |
work for me. Apparently dogs are more discerning when it comes to | :24:26. | :24:32. | |
music. Neuer-macro dog owners often marvel at their pet's musical | :24:33. | :24:39. | |
powers. They are -- there are countless online videos of dogs | :24:40. | :24:44. | |
howling along to music. But do our dogs actually appreciate music, and | :24:45. | :24:52. | |
if so, what music do they like best? It is common for dog owners to leave | :24:53. | :24:55. | |
their Radio one, especially if they are worried the dog might get lonely | :24:56. | :25:00. | |
whilst they are out. But does this music have any effect? Charlie is a | :25:01. | :25:07. | |
behavioural officer at Bath cats and dogs home. Their music of choice? | :25:08. | :25:14. | |
Classical. So what do they do? It seems to help them calm down and | :25:15. | :25:18. | |
stop Barb edge-macro barking and they sleep, lie down. It can make | :25:19. | :25:22. | |
them more appealing to adopters and helps them find a home more easily. | :25:23. | :25:27. | |
US research backs up their anecdotal evidence. It found music promotes | :25:28. | :25:31. | |
restful behaviour and that some kinds of music were more successful | :25:32. | :25:34. | |
than others at reducing stress levels. Time for The One Show to put | :25:35. | :25:42. | |
this to the test. We are going to play different types of music to | :25:43. | :25:46. | |
different dogs and watch their reactions. With 18 muscles in their | :25:47. | :25:53. | |
ears and the ability to hear many sounds, dogs should be a discerning | :25:54. | :25:58. | |
audience. If you have something playing which is very repetitive and | :25:59. | :26:01. | |
predictable, then the dog is less likely to alert and react to it than | :26:02. | :26:06. | |
something which is variable and different. So, which John Roder | :26:07. | :26:12. | |
would get the paws up in our canine experiment? -- which type of music | :26:13. | :26:16. | |
would get the paws up? Eight dogs are tested in their own's houses. We | :26:17. | :26:22. | |
are rigging up a home with this tiny camera, so the dogs won't be | :26:23. | :26:25. | |
disturbed. The owners will be wearing head cameras. They will | :26:26. | :26:29. | |
begin the room during the experiment so the dogs don't become stressed, | :26:30. | :26:33. | |
but they have been asked not to respond to their pet's reactions. | :26:34. | :26:39. | |
First, pop and what else but puppy love? This is Melvin. he is cute, | :26:40. | :26:49. | |
isn't he? He is not moving at all. He is asleep. He's totally unfazed. | :26:50. | :26:55. | |
So, onto something classical. Beethoven. This version plays at 140 | :26:56. | :27:01. | |
beats per minute, a tempo similar to the heart rate of the average dog. | :27:02. | :27:07. | |
Let's see how they react. So this is the Beethoven. The classical track | :27:08. | :27:14. | |
is quite calm and repetitive. He has gone to sleep. He is relaxed. He is | :27:15. | :27:19. | |
relaxing much more in this, you can see the tension has gone out of his | :27:20. | :27:24. | |
face and he looks like he is going to sleep. His ears are not pulled | :27:25. | :27:31. | |
back, tense. At a far higher tempo, motorhead's ace of spades causes a | :27:32. | :27:36. | |
dramatic response. Gosh, look at the reaction! The kind of things we are | :27:37. | :27:42. | |
looking for are things like ear position. His ears are back and he | :27:43. | :27:49. | |
is showing signs of tension. They are trying to get the double. The | :27:50. | :27:55. | |
interesting thing is she seems more relaxed in the rock track. We know | :27:56. | :28:01. | |
her owners play a lot of loud rock music, so rock music for her is | :28:02. | :28:08. | |
normal. It -- if you like rock music, introduce it when you are | :28:09. | :28:12. | |
playing a game with the dog. So unless you are long heard metal fan, | :28:13. | :28:17. | |
the next time you leave your dog home alone, turn on the radio and | :28:18. | :28:22. | |
switched to the classics. To increase -- to reduce the bark, | :28:23. | :28:30. | |
increase the Bach. This is it, this is the moment, a | :28:31. | :28:36. | |
big moment, Alex is about to leave for Utah to go and climb this. Have | :28:37. | :28:41. | |
a look at that. Look at the size of this. 1200 feet, all the way to the | :28:42. | :28:46. | |
top. We have been inundated with good luck messages. You can do this, | :28:47. | :28:50. | |
you have the whole of the UK behind you lifting you up the face. Don't | :28:51. | :28:55. | |
look down. And a message from someone you know very well from last | :28:56. | :29:01. | |
year's Rickshaw Challenge. Good luck climbing the huge rock. Remember, | :29:02. | :29:12. | |
keep singing, I love you, Alex. Let's do this thing. | :29:13. | :29:19. | |
Do this thing. Yes, off tomorrow. We wish you all the very best. Thank | :29:20. | :29:24. | |
you for your support. Be as generous as you can and I will try my best to | :29:25. | :29:28. | |
get to the top. Terry, thanks for joining us. Good night. See you | :29:29. | :29:33. | |
soon, goodbye. | :29:34. | :29:35. |