:00:18. > :00:24.Hello and welcome to the One Show with Matt Baker and Alex Jones.
:00:25. > :00:29.Tonight, we have a man who will be headlining this summer ten nights at
:00:30. > :00:34.London's O2 Arena. With help from his friends, they are hoping to
:00:35. > :00:39.raise the roof with laughter. And the odd reference to spam, funny
:00:40. > :00:48.walks and the unexpected Spanish Inquisition. It is Terry Gilliam.
:00:49. > :00:54.200,000 people are going to come and see you. Bearing in mind the venue,
:00:55. > :01:01.who is going to be the biggest Mariah Carey of Monty Pythons? Who
:01:02. > :01:07.is the biggest diva? The last time we got together, we were at the
:01:08. > :01:11.Albert Hall, and Terry Jones, Michael Palin and myself shared a
:01:12. > :01:17.dressing room. One person had his own dressing room. John Cleves was
:01:18. > :01:23.not there that night. I think it means Eric idle. He did not share
:01:24. > :01:26.that night, and he may not share, but for ten nights, he might get
:01:27. > :01:34.away with it for one or two, but then... We will talk about that
:01:35. > :01:41.later. He is also here to talk about his new film, Zero Theorem, which
:01:42. > :01:48.deals with technology. Are you a lover or hater of technology? I
:01:49. > :01:52.think it is a Damocles sword. It has two edges. I use technology all the
:01:53. > :01:56.time, but I worry that Sony people are becoming addicted to the need to
:01:57. > :02:05.only exist as a tweet in somebody else's life. -- so many people. I
:02:06. > :02:08.have seen the movie. It is an interesting take on how technology
:02:09. > :02:14.might change the world. A US company is asking the world to assist in the
:02:15. > :02:22.search for flight MH370, by scouring satellite images of a -- of possible
:02:23. > :02:26.crashed sites. People power being used is not as unusual as you might
:02:27. > :02:31.think. The collective brainpower of the public could end up saving your
:02:32. > :02:40.life. Each week, people spend hours
:02:41. > :02:43.playing mobile phone games. Now, scientists are tapping into our love
:02:44. > :02:47.of gaming to solve a host of problems. New games are being
:02:48. > :02:54.created with the potential to pinpoint key information about
:02:55. > :03:01.diseases such as cancer and HIV. As people play along, the data is sent
:03:02. > :03:04.back to scientists to analyse. I am in Dundee meeting games developers
:03:05. > :03:10.who have designed a mobile phone game that could help to find a cure
:03:11. > :03:14.for breast cancer. This game is called genes in space. It is a bit
:03:15. > :03:19.like space invaders but instead of stars, the Galaxy is made up of the
:03:20. > :03:25.DNA information of thousands of tumour samples. Mark is one of the
:03:26. > :03:30.designers of the game. We have a single DNA sample of a single cancer
:03:31. > :03:35.cell. The peaks and troughs are the anomalies in the cancer cells that
:03:36. > :03:39.they need to find. Before the scientists can figure out why the
:03:40. > :03:44.anomalies exist, they need to know where they are. We have created a
:03:45. > :03:48.game where people identify these as part of the gameplay experience.
:03:49. > :03:52.Cambridge University provided the developers with thousands of these
:03:53. > :03:57.DNA maps, which are used as the basis of the game. Players need to
:03:58. > :04:02.work out where the most condensed areas are and fly a spaceship
:04:03. > :04:04.through them. By doing that, they automatically record key
:04:05. > :04:10.information, and every time a player completes a level, it means that one
:04:11. > :04:14.DNA sample has been mapped out. The accuracy comes from the number of
:04:15. > :04:20.people playing. The more people playing, the more data we get. Can
:04:21. > :04:25.anybody played? It does not require any specialist knowledge or
:04:26. > :04:30.training. This is not the first time the science world has turned to
:04:31. > :04:33.gamers for help. A Rubik 's cube style game helped experts at the
:04:34. > :04:40.University of Washington to get a better understanding of the protein
:04:41. > :04:43.structure of the HIV - aids virus. So why is the creation of these
:04:44. > :04:51.games proving so popular with scientists. Ken Brown is a lecture
:04:52. > :04:55.in psychology. There are certain things that computers are not good
:04:56. > :05:00.at seeing. We have simple images here. A human can perceive a
:05:01. > :05:05.triangle or a snake shape. We are predisposed to seeing patterns in a
:05:06. > :05:10.way that a computer struggles to do. So humans have the advantage over
:05:11. > :05:14.computers in some instances. Absolutely. We are good at spotting
:05:15. > :05:20.where the valuable information is. We are not distracted by clutter.
:05:21. > :05:24.The computer would be distracted, thinking maybe the path is up here.
:05:25. > :05:31.Humans have evolved to do this sort of thing. But are these games any
:05:32. > :05:36.good? We brought together a group of passionate gamers to test out some
:05:37. > :05:40.of the science games on offer. It is incredibly easy, if you are a
:05:41. > :05:45.beginner to games or you do not play off, it is nice and relaxing. At the
:05:46. > :05:52.same time, it is really cool to see so many people also doing it. It is
:05:53. > :05:56.just like playing a game. I don't see why it couldn't be good for lots
:05:57. > :06:00.of people to pick up and play. If you enjoy solving the puzzle that
:06:01. > :06:05.can be interesting. Do you think these kind of games will ever become
:06:06. > :06:10.really big? If they are entertaining enough, yes. It has been a month
:06:11. > :06:14.since the launch of the game, and I'm keen to find out what has been
:06:15. > :06:19.achieved so far. The University of Cambridge is analysing the data, and
:06:20. > :06:25.this professor is leading the research team. We have received 1.5
:06:26. > :06:29.million analyses. People have generated their own interpretation
:06:30. > :06:33.of the data 1.5 million times. Doing that would take a scientist, or my
:06:34. > :06:39.team, many thousands of hours to get the same thing that citizens science
:06:40. > :06:42.is getting us. He told us one analysis would take him five minutes
:06:43. > :06:48.to map out. That would mean him working nonstop for 125,000 hours,
:06:49. > :06:54.14 years, to cover the same amount of work that gamers have covered in
:06:55. > :06:58.one month. This is one of the 1.5 million plots. This person picked up
:06:59. > :07:01.that there is an aberration here, and this is important because it
:07:02. > :07:06.pinpoints that there is a cancer gene in this spot. But they did not
:07:07. > :07:12.know they were picking that up. How is it relevant to breast cancer?
:07:13. > :07:15.Cancer arises by the immolation of mutations. Having a more precise
:07:16. > :07:19.definition of the genetic make-up of the tumour, we can come up with
:07:20. > :07:26.better ways of diagnosing that and having the treatment that is
:07:27. > :07:32.tailored to that particular cancer. I was slightly sceptical before I
:07:33. > :07:37.saw that. I am sure lots of people will want to have a go at this.
:07:38. > :07:40.Researchers are hoping that 1.5 million more people will take part
:07:41. > :07:46.in that experiment. How can they do it? It is called genes in space and
:07:47. > :07:55.they need to download it onto their phone or tablet and start playing.
:07:56. > :07:58.The details are on our website. ways we can help medical research without
:07:59. > :08:03.necessarily having to leave the house. You can sit on your sofa and
:08:04. > :08:09.aid medical research. One of the things they want to try is a brain
:08:10. > :08:15.experiment. Terry, if you would be so kind. We will start you off. I
:08:16. > :08:21.want you to try level one. This is a brain game which has been developed
:08:22. > :08:27.for neuroscientists at University College London. He is so good. He
:08:28. > :08:33.has got it. Basically, he is doing a series of exercises, and we would
:08:34. > :08:37.have put his data in, so they know male or female age and that sort of
:08:38. > :08:40.stuff. Usually, they have a brain lab and they have maybe ten people
:08:41. > :08:46.who would come along, often students. We need to get this to the
:08:47. > :08:50.wider population and more samples, which is what these can do. It will
:08:51. > :08:55.come up with all sorts of results and we want to know more about how
:08:56. > :09:02.the brain works. Any idea how many people have done this? 87,000
:09:03. > :09:05.people, but they want more and more. It is really interesting research.
:09:06. > :09:09.We will be able to know whether young people are more impulsive than
:09:10. > :09:16.old people, men and women, differences in risk taking. How is
:09:17. > :09:22.it going? It was fine but I got distracted because you were talking.
:09:23. > :09:26.I am trying to do some work here! There is probably a list of things
:09:27. > :09:32.like, do not do this on live television. If people want to get
:09:33. > :09:37.involved, maybe not on the medical side... There are so many things.
:09:38. > :09:43.This is citizen science in action. We have things like space, history,
:09:44. > :09:49.climate, nature. The cyclone centre, scientists from their have asked if
:09:50. > :09:54.viewers could help them. They have had 6000 downloads of their app so
:09:55. > :09:58.far. It asks you to analyse some of 300,000 pictures of cyclones. You
:09:59. > :10:01.are looking for observations and that will help them understand the
:10:02. > :10:06.strength and how cyclones change. The details are on the website and
:10:07. > :10:12.they want to get to 1 million. Does this sit comfortably with you? In
:10:13. > :10:16.the old days, I could count on giving up my children for medical
:10:17. > :10:22.science for experimentation. And now it has turned into some kind of
:10:23. > :10:27.game. Where is the fun in that? ! It is so much fun and so important.
:10:28. > :10:33.People have discovered planets that the astronomers have missed.
:10:34. > :10:43.Asteroids? Did you know about the Python asteroids? Each of us is an
:10:44. > :10:53.asteroid. Each of us has an asteroid named. Out of this world! Thank you.
:10:54. > :10:59.31 years ago Terry and the Pythons' famous film asked what is the
:11:00. > :11:02.meaning of life. Are we any closer to answering that? We consulted some
:11:03. > :11:12.very wise people to see what they think.
:11:13. > :11:22.What is the meaning of life? The meaning of life is in the palm of
:11:23. > :11:33.your hand. You are born, you live, you die, you still pay taxes.
:11:34. > :11:39.I think the meaning of life is that we spend too long worrying about our
:11:40. > :11:44.past and caring about it, too long worrying about the future and we
:11:45. > :11:53.forget about today. Today is a gift. Enjoy it and live it.
:11:54. > :12:04.The meaning of life is to live. It comes with love, joy, peace, provide
:12:05. > :12:12.for my family, be a friend in time of trouble.
:12:13. > :12:18.The meaning of life, for me, is to be satisfied with what you have
:12:19. > :12:26.got. Also, to be charitable and help other people. Bagel is the best
:12:27. > :12:30.meaning of life. It is round. Whatever goes around comes around.
:12:31. > :12:38.If you cannot go around, there is a hole in it to escape so you will be
:12:39. > :12:45.happy. What is the meaning of life? The
:12:46. > :12:52.first question to enquire is to actually ask what is the meaning of
:12:53. > :12:56.life, the source of everything, who is the supreme? We are desperately
:12:57. > :13:07.trying to find happiness, to find our father. We are looking full of.
:13:08. > :13:11.-- we are looking for love. The meaning of life is like this job.
:13:12. > :13:17.You switch on your meter, do your work, take your money and go home.
:13:18. > :13:21.That's life. The only certainty in life is death. Everything in between
:13:22. > :13:31.is a bonus so get on with it and enjoy it. That is the spirit! Don't
:13:32. > :13:37.you feel better after watching that? I don't understand the whole bagel
:13:38. > :13:42.thing. Just be satisfied. Watch it before you go up that massive rock!
:13:43. > :13:49.Terry, let's talk about the meaning of life. You are renowned for really
:13:50. > :13:52.delving into the world of the lead character you are directing. The
:13:53. > :13:56.whole point of Zero Theorem is to find the meaning of life. 31 years
:13:57. > :14:02.on from when you first set out, are you any closer? No, I just keep
:14:03. > :14:07.asking the question and keep searching for it. All that I know is
:14:08. > :14:14.that life has no meaning in itself. It is molecules. Things happen. It
:14:15. > :14:18.is an extraordinary world and I love the mystery of it. Science runs
:14:19. > :14:26.around and we can do the gene a lot of things, but we never really get
:14:27. > :14:30.down to the death of it. For me, a lot of people are quite wonderful.
:14:31. > :14:36.You have to make your life meaningful. It is down to you, isn't
:14:37. > :14:41.it? Totally down to you. In Zero Theorem, the man is waiting for a
:14:42. > :14:47.telephone call to give him the meaning of life. This is madness. It
:14:48. > :14:51.is like when you see adverts on the television, on the street, this car,
:14:52. > :14:56.that perfused that will give meaning to your life. Nonsense. You have to
:14:57. > :15:04.work at it a bit. Let's have a look at the trailer for the film.
:15:05. > :15:13.Everyone is getting rich, except you. What seems to be the problem?
:15:14. > :15:22.We are dying. There is only one of you. So it would appear. How is it
:15:23. > :15:30.hanging? Not at all well. We are seeing nothing most of all. Are you
:15:31. > :15:39.trying to be difficult? Nobody lasts, it is a guaranteed burn-out
:15:40. > :15:45.project. Zero Theorem. Is that a clear view of where you think things
:15:46. > :15:47.are heading? I fear they are. I worry about the connectivity of the
:15:48. > :15:52.world, where people don't know who they are as individuals, just a
:15:53. > :15:55.reflection of other people through their tweets. I hate the money
:15:56. > :16:01.people aren't living in the moment. I go to concerts and before the
:16:02. > :16:07.first song is finished, people are tweeting. The concert becomes
:16:08. > :16:13.wallpaper, background for them. Be there, let it happen. I left with a
:16:14. > :16:16.feeling of as long as you feel something it is better than waiting
:16:17. > :16:22.for someone else telling you how to feel. Peer pressure, what do they
:16:23. > :16:27.think of me? You two are very similar in your thought process, on
:16:28. > :16:32.Twitter. It is a way of connecting people, maybe not in reality, but
:16:33. > :16:37.people do connect and yourself this afternoon can make you did a
:16:38. > :16:42.question and answer on it. I was forced, as part of promoting this
:16:43. > :16:46.film I was shackled and I had to tweet. It is a chance for people to
:16:47. > :16:51.get to the heart of it come the director of the film, and ask
:16:52. > :16:55.questions. That is fine, interesting, but to sit there in the
:16:56. > :17:00.middle of a meal and take a picture of the food and send it to your
:17:01. > :17:05.friends, come on, eat the food and enjoy it. Everybody is a critic and
:17:06. > :17:09.commentator like everybody on television too quickly. On
:17:10. > :17:13.Facebook, lots of people want to know, because you have been working
:17:14. > :17:18.on this film, who killed Don Quixote, for 20 years, and you are
:17:19. > :17:24.starting it again in September. Are you going to finish it this time?
:17:25. > :17:32.Who knows! Will you give it a good go? Every time I finish a film I go
:17:33. > :17:35.into my default position, which is the man who killed -- The Man Who
:17:36. > :17:38.Killed Don Quixote. We will start to shoot at the end of September, what
:17:39. > :17:43.happens may be slightly different than my virtual world. People would
:17:44. > :17:47.love to see it and The Zero Theorem is out in cinemas from tomorrow. You
:17:48. > :17:52.can see it when you get back from Utah. While the weather may be
:17:53. > :17:56.improving around the country, many people hit by the recent floods are
:17:57. > :17:59.still living in temporary accommodation. Mike Dilger went to
:18:00. > :18:06.meet the volunteers working hard to get the residents of Moorland in
:18:07. > :18:10.Somerset back into their homes. The water may have retreated but 90%
:18:11. > :18:15.of the residents can't even live here because tonnes of mud and
:18:16. > :18:20.debris need to be shifted before they can return home. Welcome to
:18:21. > :18:26.operation flood clean up, as jobs go it does not get any bigger than
:18:27. > :18:31.this. The main thing is, make sure everyone is covered up, you have a
:18:32. > :18:35.face mask and hand gloves on. Has anyone any questions? It is from
:18:36. > :18:40.this derelict building that the clean-up is being operated from
:18:41. > :18:46.flooding on the levels action group, which helps flood victims.
:18:47. > :18:51.23-year-old Stuart Smith in charge. They have come from local towns and
:18:52. > :18:55.villages, people from London, Leeds, Bradford, Worcester, and a gentleman
:18:56. > :19:00.has come from Switzerland for a month. Of the 100 houses in the
:19:01. > :19:06.village, 79 were flooded. Today, Stuart and his team start to clear
:19:07. > :19:11.out the carpets from this home. He has only lived here for eight
:19:12. > :19:15.months. We have lost our furniture, the kitchen is ruined, everything
:19:16. > :19:21.really. Where do you think you would be without this army of volunteers?
:19:22. > :19:26.We would be knee deep in rubbish in the house. They have been fantastic
:19:27. > :19:30.and we are grateful. You would think the loss adjusters and insurance
:19:31. > :19:36.would take it away. The problem is because the water has been in for
:19:37. > :19:40.such a long time, they were not allowed in for health and safety
:19:41. > :19:45.reasons. One of the volunteers, Penny, is a nurse, and has been
:19:46. > :19:50.offering emotional support. I found there was a need to talk to some of
:19:51. > :19:53.the residents really. It is not just about clearing houses. If you think
:19:54. > :19:59.that for years and years they have collected all this stuff and it is
:20:00. > :20:05.very hard for them to suddenly let it all go, it is hard. The next port
:20:06. > :20:12.of call for Stuart is the clearing out the freezer on a nearby farm. It
:20:13. > :20:21.sounds like a smelly job. Yes, you are in for a shock. O! We need to
:20:22. > :20:26.document everything that comes out, that is the only thing. Is that what
:20:27. > :20:36.you are doing? Ella bobbin are you ready? Stuart and his team are doing
:20:37. > :20:42.this for Henry Davie, who has lived here for 55 years. When will you be
:20:43. > :20:46.back in the house? Next weekend. They are tough up here. He has a
:20:47. > :20:53.smile on his face despite everything. No point crying about
:20:54. > :20:57.it, is there? A month ago Stuart was a car salesman. I came to mall and
:20:58. > :21:03.just for a weekend to help out where I could -- I came to Moorland. I
:21:04. > :21:07.messaged my boss to say, sorry, I am not coming back in for a while
:21:08. > :21:12.because they need my help here. You have given up your job. How are you
:21:13. > :21:17.coping? Ella bobbin I am living of savings to support my family, I am
:21:18. > :21:23.not worrying about that right now, it is not my priority. The
:21:24. > :21:26.priorities the people. Yes, the people and the community. The final
:21:27. > :21:31.stop of the day is to clear out debris from Maria's house. The water
:21:32. > :21:34.was three feet deep ear and home insurance does not cover her.
:21:35. > :21:40.Without Stuart's help, she would have no one to turn to. It came up
:21:41. > :21:46.to here, literally the whole house, from here to the end of the annex.
:21:47. > :21:50.Without these guys this place would be a mess. They came in, ten of
:21:51. > :21:57.them, washing, drying, packing. It was like someone had sent them from
:21:58. > :22:01.above. I can't put it any better. Two days ago I could not hold a
:22:02. > :22:05.conversation with her, she was in tears most of the time. We are
:22:06. > :22:10.trying to bring her spirits up, we have the food waste out, the fridge
:22:11. > :22:15.is out, now we will build step by step and work with her and make it
:22:16. > :22:21.better. Still some way to go. There is a long way to go. See you
:22:22. > :22:25.tomorrow. See you tomorrow, goodbye. Just how long it is going to be
:22:26. > :22:30.before things return to normal here if anyone's guess but one thing is
:22:31. > :22:33.for certain. Thanks to people like Stuart and his amazing team, from
:22:34. > :22:38.now on things are only going to get better.
:22:39. > :22:43.I will second that, I was down there a couple of weeks ago and I met
:22:44. > :22:48.Stuart and he is an inspiration. Lovely. Terry, the other thing we
:22:49. > :22:54.must talk about is the price since reuniting. Not for one, but ten
:22:55. > :22:59.nights at the O2 in July. Oh, yes, he says! Are you honestly a bit
:23:00. > :23:06.gutted it has gone from one night, to ten. It wasn't part of my plan.
:23:07. > :23:09.Why not? I had Don Quixote, this film, and Opera, I am trying to
:23:10. > :23:15.finish an autobiography, the last thing I needed was ten nights of
:23:16. > :23:21.price and again. So why decide to do it again? We need it and it is
:23:22. > :23:26.keeping the group together. It is great to be lads working together in
:23:27. > :23:32.the good old days. Are you rehearsing? Will you win it and see
:23:33. > :23:36.what develops? We have a weak's rehearsal before we start. The set
:23:37. > :23:41.is quite spectacular. There is going to be a lot of big, shiny things.
:23:42. > :23:47.But then literally nobody is doing much until that week. Are you
:23:48. > :23:52.directing and set designing yourself? I am good at that. I think
:23:53. > :23:56.the odd thing about the show is Graham is no longer with us so we're
:23:57. > :24:01.having to swap around and do things that we didn't do before. I have got
:24:02. > :24:06.stuck having to step into Michael Palin's she was on a sketch and it
:24:07. > :24:10.is terrifying. He is such a genius, brilliant, and I can only fail
:24:11. > :24:15.miserably. We all look forward to seeing what happens to stop Yes.
:24:16. > :24:20.Most people think that dogs have simple tastes, regular meals, a bit
:24:21. > :24:25.of TLC and the ball to chase. It sounds like a man I know! It would
:24:26. > :24:32.work for me. Apparently dogs are more discerning when it comes to
:24:33. > :24:39.music. Neuer-macro dog owners often marvel at their pet's musical
:24:40. > :24:44.powers. They are -- there are countless online videos of dogs
:24:45. > :24:52.howling along to music. But do our dogs actually appreciate music, and
:24:53. > :24:55.if so, what music do they like best? It is common for dog owners to leave
:24:56. > :25:00.their Radio one, especially if they are worried the dog might get lonely
:25:01. > :25:07.whilst they are out. But does this music have any effect? Charlie is a
:25:08. > :25:14.behavioural officer at Bath cats and dogs home. Their music of choice?
:25:15. > :25:18.Classical. So what do they do? It seems to help them calm down and
:25:19. > :25:22.stop Barb edge-macro barking and they sleep, lie down. It can make
:25:23. > :25:27.them more appealing to adopters and helps them find a home more easily.
:25:28. > :25:31.US research backs up their anecdotal evidence. It found music promotes
:25:32. > :25:34.restful behaviour and that some kinds of music were more successful
:25:35. > :25:42.than others at reducing stress levels. Time for The One Show to put
:25:43. > :25:46.this to the test. We are going to play different types of music to
:25:47. > :25:53.different dogs and watch their reactions. With 18 muscles in their
:25:54. > :25:58.ears and the ability to hear many sounds, dogs should be a discerning
:25:59. > :26:01.audience. If you have something playing which is very repetitive and
:26:02. > :26:06.predictable, then the dog is less likely to alert and react to it than
:26:07. > :26:12.something which is variable and different. So, which John Roder
:26:13. > :26:16.would get the paws up in our canine experiment? -- which type of music
:26:17. > :26:22.would get the paws up? Eight dogs are tested in their own's houses. We
:26:23. > :26:25.are rigging up a home with this tiny camera, so the dogs won't be
:26:26. > :26:29.disturbed. The owners will be wearing head cameras. They will
:26:30. > :26:33.begin the room during the experiment so the dogs don't become stressed,
:26:34. > :26:39.but they have been asked not to respond to their pet's reactions.
:26:40. > :26:49.First, pop and what else but puppy love? This is Melvin. he is cute,
:26:50. > :26:55.isn't he? He is not moving at all. He is asleep. He's totally unfazed.
:26:56. > :27:01.So, onto something classical. Beethoven. This version plays at 140
:27:02. > :27:07.beats per minute, a tempo similar to the heart rate of the average dog.
:27:08. > :27:14.Let's see how they react. So this is the Beethoven. The classical track
:27:15. > :27:19.is quite calm and repetitive. He has gone to sleep. He is relaxed. He is
:27:20. > :27:24.relaxing much more in this, you can see the tension has gone out of his
:27:25. > :27:31.face and he looks like he is going to sleep. His ears are not pulled
:27:32. > :27:36.back, tense. At a far higher tempo, motorhead's ace of spades causes a
:27:37. > :27:42.dramatic response. Gosh, look at the reaction! The kind of things we are
:27:43. > :27:49.looking for are things like ear position. His ears are back and he
:27:50. > :27:55.is showing signs of tension. They are trying to get the double. The
:27:56. > :28:01.interesting thing is she seems more relaxed in the rock track. We know
:28:02. > :28:08.her owners play a lot of loud rock music, so rock music for her is
:28:09. > :28:12.normal. It -- if you like rock music, introduce it when you are
:28:13. > :28:17.playing a game with the dog. So unless you are long heard metal fan,
:28:18. > :28:22.the next time you leave your dog home alone, turn on the radio and
:28:23. > :28:30.switched to the classics. To increase -- to reduce the bark,
:28:31. > :28:36.increase the Bach. This is it, this is the moment, a
:28:37. > :28:41.big moment, Alex is about to leave for Utah to go and climb this. Have
:28:42. > :28:46.a look at that. Look at the size of this. 1200 feet, all the way to the
:28:47. > :28:50.top. We have been inundated with good luck messages. You can do this,
:28:51. > :28:55.you have the whole of the UK behind you lifting you up the face. Don't
:28:56. > :29:01.look down. And a message from someone you know very well from last
:29:02. > :29:12.year's Rickshaw Challenge. Good luck climbing the huge rock. Remember,
:29:13. > :29:19.keep singing, I love you, Alex. Let's do this thing.
:29:20. > :29:24.Do this thing. Yes, off tomorrow. We wish you all the very best. Thank
:29:25. > :29:28.you for your support. Be as generous as you can and I will try my best to
:29:29. > :29:33.get to the top. Terry, thanks for joining us. Good night. See you
:29:34. > :29:35.soon, goodbye.