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We're on the road once more, helping the police crack down on crime. | :00:00. | :00:15. | |
The Christmas party which ended in tragedy for a young mum. | :00:16. | :00:17. | |
I don't know how you could leave a person | :00:18. | :00:20. | |
for dead and I think they have got no heart. | :00:21. | :00:22. | |
The good Samaritan who saved a stranger | :00:23. | :00:27. | |
She looked at me and it was as if she was crying | :00:28. | :00:30. | |
And I'm at the final resting place of Richard III. | :00:31. | :00:40. | |
Discovered buried under a nearby carpark 500 years after his death. | :00:41. | :00:43. | |
His identity was confirmed by brilliant local scientists | :00:44. | :00:47. | |
who are now using similar DNA techniques to solve crime. | :00:48. | :00:49. | |
Hello and welcome to Crimewatch Roadshow. | :00:50. | :01:18. | |
As always, we need your help to solve the crimes | :01:19. | :01:21. | |
The scammers charging thousands for untrained assistance dogs. | :01:22. | :01:35. | |
And how your calls helped police catch a ruthless robber | :01:36. | :01:40. | |
Following the appeal we had an excellent response. | :01:41. | :01:50. | |
Rav, I'm in front of Leicester Cathedral. | :01:51. | :02:01. | |
Two years ago, crowds gathered here to lay the body | :02:02. | :02:06. | |
of King Richard III to rest inside this historic building. | :02:07. | :02:10. | |
But the city is also the birthplace of modern DNA techniques. | :02:11. | :02:15. | |
These days all sorts of clues can be unlocked from someone's DNA and I'm | :02:16. | :02:18. | |
quite nervous because I'll be finding out later what | :02:19. | :02:21. | |
Thanks, Michelle, could be interesting. | :02:22. | :02:25. | |
First, though, police in Leicestershire need your | :02:26. | :02:27. | |
help to trace the driver whose actions tore a young family | :02:28. | :02:30. | |
26 sexual ceilidh is a single mum. She lives with her five-year-old son | :02:31. | :02:49. | |
on a small village in the outskirts of Leicester. It is hard being a | :02:50. | :02:57. | |
single mum. I have lots of support, I see my friends a lot. I met her in | :02:58. | :03:11. | |
college and ever since then we have been close. A week before Christmas | :03:12. | :03:16. | |
last year Letitia decided to throw a house party for some friends. I was | :03:17. | :03:21. | |
looking forward to letting my hair down a bit, distress. Everyone was | :03:22. | :03:29. | |
having a good time, talking, drinking, dancing. Me and Kayley | :03:30. | :03:36. | |
ended up going upstairs in my bedroom and we were chilling and | :03:37. | :03:42. | |
there. In the early hours of the morning party guests heard banging | :03:43. | :03:49. | |
on the front door. Out in the street witnesses reported an argument | :03:50. | :03:52. | |
involving the driver of the white Volkswagen. That was it after that. | :03:53. | :04:03. | |
That died down. By 3:30am Kayley was ready to go warm and called for a | :04:04. | :04:09. | |
taxi. I was inside while Kayley went out to look for the taxi. As a car | :04:10. | :04:20. | |
approached Kayley assumed it was hard taxi. It was not. The car drove | :04:21. | :04:26. | |
at Kayley, mounted the pavement and hit her hard. Kayley was dragged | :04:27. | :04:32. | |
along underneath, then without stopping the car sped away. I have | :04:33. | :04:40. | |
gone outside and I looked and Kayley was on the floor. I thought she was | :04:41. | :04:54. | |
dead. I did not know what to do. Letitia called for an ambulance. | :04:55. | :04:59. | |
When the paramedics arrived Kayley was rushed to hospital. I felt | :05:00. | :05:04. | |
guilty because of it was me I can accept it because it is outside my | :05:05. | :05:08. | |
house because it was my friend I cannot accept that. Kayley's | :05:09. | :05:15. | |
injuries were terrific, broken ribs, multiple fractures to her like an | :05:16. | :05:22. | |
pelvis and she was in a coma. We went Christmas Day and we were | :05:23. | :05:26. | |
playing her video recordings on my phone and telling her to wake up. We | :05:27. | :05:32. | |
were asking the nurses and they were saying that it could be for ages so | :05:33. | :05:37. | |
we did not think she would have work up. Then they rang me Boxing Day and | :05:38. | :05:46. | |
said that she woke up. I looked a mess. I had to observe throughout. A | :05:47. | :05:53. | |
doctor came up to me and said I was an unexpected survival. It hit me | :05:54. | :05:59. | |
that I was so close to death. Her son spent Christmas without his mum. | :06:00. | :06:05. | |
They said that she was really properly. I did not see him over the | :06:06. | :06:09. | |
Christmas period. I was in too much pain. Finally Kayley and look were | :06:10. | :06:19. | |
reunited. I cried. It fill this hole that I needed. You want to be a | :06:20. | :06:24. | |
mother, you want to be there. For Kayley the last six months have been | :06:25. | :06:30. | |
a long road to recovery. I cannot do much, I cannot walk to the park, I | :06:31. | :06:35. | |
struggle taking him to school. I cannot get on the floor and play | :06:36. | :06:39. | |
with him because I cannot bend down. He has to help me a lot with | :06:40. | :06:44. | |
cleaning up and stuff, his toys. He has been a really good boy. The | :06:45. | :06:51. | |
police investigation is ongoing and they are urging anyone with | :06:52. | :06:57. | |
information to contact them. The car is critical to this inquiry. It was | :06:58. | :07:04. | |
used as a deadly weapon. Very nearly it was successful in causing death. | :07:05. | :07:10. | |
To the people in that car, come forward, tell us what happened, have | :07:11. | :07:16. | |
a conscience and think this was someone's mother, sister and | :07:17. | :07:24. | |
daughter. I do not know how you could leave a person for dead. I | :07:25. | :07:29. | |
think they have got no heart, no conscience, really. The DCI is with | :07:30. | :07:37. | |
me. This was very traumatic | :07:38. | :07:39. | |
for Kayley, wasn't it, Kayley was hit with great force and | :07:40. | :07:50. | |
dragged under the vehicle and it cost serious injuries. Courageously | :07:51. | :07:54. | |
she is fighting back and making a recovery. This could have been | :07:55. | :07:55. | |
fatal. So, remind us what we know | :07:56. | :07:58. | |
about the events that night. It was the early hours | :07:59. | :08:01. | |
of Sat 17th December, around 3.30am on Brackenfield Way, | :08:02. | :08:04. | |
Thurmaston, Leicestershire. The party had taken place in a quiet | :08:05. | :08:14. | |
neighbourhood and people were leaving the party and we believe a | :08:15. | :08:19. | |
dispute had taken place in the house and on the pavement outside | :08:20. | :08:22. | |
involving people at the party and the occupants of the white vehicle. | :08:23. | :08:29. | |
The car is critical to the inquiry. What do we know about it? It had | :08:30. | :08:38. | |
been rented the week before and we believe a number of people may have | :08:39. | :08:43. | |
had access to that vehicle. We have to establish who had the vehicle on | :08:44. | :08:48. | |
that night and who the driver was. It is a quiet neighbourhood. Do you | :08:49. | :08:53. | |
think there were any witnesses? I'm fully some of the neighbours | :08:54. | :08:56. | |
witnessed the incident and rang the police immediately so we were there | :08:57. | :09:01. | |
quickly. It was very dark, the middle of the night in winter. We | :09:02. | :09:05. | |
the people who were at the party to come forward and tell us what | :09:06. | :09:09. | |
happened and who the driver of the vehicle was because Kayley is | :09:10. | :09:14. | |
somebody's mother, sister and daughter and if they thought about | :09:15. | :09:19. | |
their family and as their conscience what they should do, come forward. | :09:20. | :09:25. | |
Yes, if you can help, please do get in touch. | :09:26. | :09:30. | |
Next, do you recognise any of today's criminals caught on CCTV? | :09:31. | :09:37. | |
Look carefully at the top left of your screen. Lingering in the road | :09:38. | :09:44. | |
in Peckham. What are they waiting for? Another camera reveals all. The | :09:45. | :09:53. | |
robber walks across the road and then strikes, rugby tackling a | :09:54. | :09:58. | |
security guard as he leaves a post office with the takings. They ride | :09:59. | :10:03. | |
off at speed with the cash box leaving the security guard lying in | :10:04. | :10:07. | |
the road. They got away with over three grand in cash and the stolen | :10:08. | :10:13. | |
bike was later found abandoned. They may have covered their faces but | :10:14. | :10:17. | |
someone knows who these and bikers are. It is broad daylight and these | :10:18. | :10:28. | |
two corrupted or good. This is not their fan but they have spotted | :10:29. | :10:32. | |
something they like. What they have not spotted of the camera. They | :10:33. | :10:39. | |
break and shift box after box of expensive power tools. Satisfied | :10:40. | :10:44. | |
with their look to be leaving a black Audi having nabbed up to 18 | :10:45. | :10:50. | |
grand's worth of kit. If you recognise the car or either of the | :10:51. | :10:59. | |
main collars. It is the middle of the day in this quiet part of | :11:00. | :11:03. | |
Swindon but someone is up to no good. This man decides he fancies | :11:04. | :11:08. | |
having a go at stealing a trailer that has been securely locked up but | :11:09. | :11:13. | |
how is he going to do it? Luckily for him has made over the gate and | :11:14. | :11:17. | |
seven a bag full of tricks and he gets to work. What he does not know | :11:18. | :11:23. | |
is that just out of sight of the camera the owner has spotted the | :11:24. | :11:26. | |
intruder in his backyard and still fully made his way down to the | :11:27. | :11:31. | |
trailer ready with his camera phone. Once in position he asks the man, | :11:32. | :11:39. | |
can I help you? Snap. The thief looks up and realises it is over and | :11:40. | :11:44. | |
he has been parked. He makes a run for it leaving behind his gear. It | :11:45. | :11:49. | |
is a great photo. If you recognise this, give us a call. | :11:50. | :11:55. | |
If you know the names of anyone you've just | :11:56. | :11:57. | |
Text CW, space and then your message. | :11:58. | :12:04. | |
Texts will be charged at your standard message rate. | :12:05. | :12:06. | |
We're right in the middle of Leicester city centre today, | :12:07. | :12:19. | |
and this might be the last place you'd expect us to be | :12:20. | :12:22. | |
But surprisingly, the Cathedral has become home for some creatures | :12:23. | :12:26. | |
which are often victims of crime themselves. | :12:27. | :12:27. | |
Birds of prey are subjected to hundreds of crimes against them | :12:28. | :12:31. | |
each year, from poisoning and shooting to having | :12:32. | :12:33. | |
But two of them have found a safe haven here. | :12:34. | :12:40. | |
magnificent pelican Falcons, the fastest creatures on earth. They | :12:41. | :12:58. | |
were reserved for high status individuals in medieval times and | :12:59. | :13:02. | |
falconry is still prized today here and in the Middle East. How is such | :13:03. | :13:07. | |
an amazing kick .my creature ended up on the cathedral? They think it | :13:08. | :13:14. | |
is a cliff. Lots of pigeons. A wonderful year. It is replicating | :13:15. | :13:22. | |
their natural habitat. Yes. The number of pigeons being fed, they | :13:23. | :13:31. | |
are in clover. What about breeding? They are trying to. We have had two | :13:32. | :13:36. | |
Brits but they have been unsuccessful. We are not sure why. | :13:37. | :13:42. | |
The eggs do not seem as strong as usual. We are working with the | :13:43. | :13:47. | |
University and DNA fingerprinting using the same techniques pioneered | :13:48. | :13:51. | |
by Professor Jeffries to work out why they have failed. I hope it | :13:52. | :13:54. | |
works out. It seems the perfect environment for | :13:55. | :14:02. | |
these creatures. But until relatively recently | :14:03. | :14:08. | |
Richard III's surroundings It was the discovery that made | :14:09. | :14:20. | |
headlines around the world. Five years ago a skeleton was found | :14:21. | :14:24. | |
buried under the council car park in Leicester. It was believed to be | :14:25. | :14:28. | |
that of King Richard III, famously killed in battle. Experts here at | :14:29. | :14:34. | |
the University of Leicester were called upon to unravel this ancient | :14:35. | :14:42. | |
murder mystery. I was asked to look at the Skull and it arrived in the | :14:43. | :14:46. | |
lab with various tool marks on it and what we were interested in was | :14:47. | :14:51. | |
working out what tools had been used to create those injuries. This large | :14:52. | :14:56. | |
injury to the right-hand side of the base of the skull was likely to have | :14:57. | :15:01. | |
been caused by a substantial weapon, so we think this was caused by an | :15:02. | :15:08. | |
axe on the blade and would have been capable of doing this. Some of the | :15:09. | :15:13. | |
injuries penetrated to considerable depth, so they went through the base | :15:14. | :15:17. | |
of the skull and the brain and onto the inside of the skull. That had to | :15:18. | :15:22. | |
be a weapon that was long and thin and it was likely to be a short | :15:23. | :15:28. | |
sword or a long dagger. But what we found from all the injuries that we | :15:29. | :15:32. | |
saw is they were consistent with the stories we heard about the Battle | :15:33. | :15:36. | |
and consistent with him having been pulled off his horse and those final | :15:37. | :15:40. | |
injuries being inflicted while he was on the ground. The physical | :15:41. | :15:46. | |
injuries seemed to match what was known about the way the monarch had | :15:47. | :15:50. | |
died. But to confirm it was indeed Richard III, they were able to link | :15:51. | :15:58. | |
DNA taken from the skeleton to 21st-century relatives on Richard's | :15:59. | :16:05. | |
mother's side. He had no known descendants, but we do know he has a | :16:06. | :16:09. | |
female line of relatives who are alive today. We took their DNA to | :16:10. | :16:13. | |
see if it matched that of the skeleton. The DNA taken from the | :16:14. | :16:19. | |
skeleton and the relative alive today was practically a perfect | :16:20. | :16:24. | |
match. The identity of the long lost King was confirmed, but what else | :16:25. | :16:29. | |
could his DNA tell us about him? I have been looking at his entire | :16:30. | :16:35. | |
genomics. Because there are no contemporary portraits, they all | :16:36. | :16:38. | |
postdate his death by about 30 years, but looking at the Jinan you | :16:39. | :16:45. | |
can say what their eye colour is. We know he had a 96% chance of having | :16:46. | :16:51. | |
blue eyes and a 76% chance of having blond hair. But that could change | :16:52. | :16:57. | |
with age. But you can apply this to crime scenes and these are | :16:58. | :17:02. | |
externally visible characteristics. Even without seeing the criminal you | :17:03. | :17:04. | |
can start to say something about what they might look like. As well | :17:05. | :17:11. | |
as using DNA to work out what people might look like, the team is | :17:12. | :17:16. | |
developing a way to narrow down names of potential offenders by | :17:17. | :17:20. | |
examining DNA found at crime scenes. As things progress into the future, | :17:21. | :17:25. | |
there is only going to be more ways in which you are able to work with | :17:26. | :17:30. | |
the police. Yes, it has been suggested what if we had a database | :17:31. | :17:37. | |
that type surnames and you go to the crime scene and you type the live | :17:38. | :17:41. | |
chromosome and see what surnames it brings up. If you have someone in | :17:42. | :17:46. | |
your suspect list, go to them first if they have that surname. It helps | :17:47. | :17:52. | |
please prioritise. It does not have to be you that is on the DNA | :17:53. | :17:58. | |
database, just somebody with the same surname as you and they would | :17:59. | :18:04. | |
get that hit. It seems the possibilities of DNA analysis are | :18:05. | :18:08. | |
endless. I want to see first-hand just how revealing this information | :18:09. | :18:13. | |
can be. So she is going to take a sample of my DNA. What is the method | :18:14. | :18:19. | |
for testing? I need to get some of your saliva I am afraid to get your | :18:20. | :18:26. | |
DNA. Spit in this glamorous spit kit. We need to collect saliva up to | :18:27. | :18:34. | |
about that line. That is a lot. Go off somewhere and sit by yourself | :18:35. | :18:38. | |
and when you come back we will process that and I can extract your | :18:39. | :18:43. | |
DNA. What will you be able to tell about me? It will tell you a region | :18:44. | :18:50. | |
where your female ancestry comes from and I can tell you about your | :18:51. | :18:55. | |
hair colour and Europe eye colour and I can tell you whether you are | :18:56. | :18:58. | |
lactose intolerant or whether you are sensitive to caffeine. And that | :18:59. | :19:06. | |
is all from spit? Yes, it is amazing what you can do these days. | :19:07. | :19:09. | |
Yes, it is amazing what you can do these days. | :19:10. | :19:11. | |
Well, I'm really intrigued to know what my results will say about me. | :19:12. | :19:14. | |
I'll be getting them later in the programme. | :19:15. | :19:17. | |
Now, the experts here in Leicester have gained a well-deserved | :19:18. | :19:19. | |
reputation for forensic brilliance and not just with ancient bones. | :19:20. | :19:21. | |
The scientists at Leicester University are often called | :19:22. | :19:23. | |
on by police to help with all kinds of cases. | :19:24. | :19:25. | |
And Dr Robert Hillman is with me now. | :19:26. | :19:28. | |
And PhD student Jodie. We are going to get an experiment going. | :19:29. | :19:37. | |
Tell me a bit more about the work you are doing. My background is in | :19:38. | :19:45. | |
chemistry and we have been developing methods to reveal latent | :19:46. | :19:51. | |
or non-visible fingerprints on objects made of metal and paper and | :19:52. | :19:57. | |
other substances. If we look at this bullet casing the fingerprints are | :19:58. | :20:03. | |
very clearly visible. How will we make my fingerprints on that side | :20:04. | :20:08. | |
visible? We have a reagent that we have developed that contains silver. | :20:09. | :20:13. | |
All of your fingerprint Richard Marx that you have left on there, we will | :20:14. | :20:20. | |
blanket of parts of the surface and this reagent will react with all the | :20:21. | :20:26. | |
bare copper in the brass and we will have a silver deposit that will give | :20:27. | :20:33. | |
us an image of the fingerprint. And that is so clear. Is this technique | :20:34. | :20:39. | |
police forces are using the moment? Not at the moment, we developed it | :20:40. | :20:43. | |
in the research laboratory and we are trying to transfer that to the | :20:44. | :20:47. | |
practical laboratories and the police are very interested in it. It | :20:48. | :20:53. | |
is very effective and it would be brilliant to work alongside the | :20:54. | :21:02. | |
police. I suspect? Of course you are. You saw it here first. | :21:03. | :21:09. | |
Right, lots more to come this morning, including: The young woman | :21:10. | :21:13. | |
subjected to a terrifying attack as she walked home from the shops. | :21:14. | :21:16. | |
He said, "if you do anything, if you say anything, | :21:17. | :21:19. | |
And the robber who preyed on a vulnerable student, now behind bars, | :21:20. | :21:33. | |
thanks for your help. When we got the call we were really pleased. | :21:34. | :21:37. | |
For more than 7,000 disabled people in Britain assistance dogs offer | :21:38. | :21:39. | |
They can also help with practical tasks. | :21:40. | :21:42. | |
But a charity is warning people to be cautious about where they get | :21:43. | :21:45. | |
these dogs from after a series of investigations into | :21:46. | :21:47. | |
Peter Gorbing from Assistance Dogs UK is here. | :21:48. | :21:51. | |
Peter, we'll talk to you in a moment. | :21:52. | :21:53. | |
But first, let's hear from Wayne Deacy. | :21:54. | :21:55. | |
He paid almost ?5,000 for a dog for his grandson who has autism | :21:56. | :21:59. | |
and his granddaughter who has anxiety. | :22:00. | :22:02. | |
But rather than helping the children, the dog attacked them. | :22:03. | :22:08. | |
The dog would run past the children to follow us and knock the children | :22:09. | :22:17. | |
flying. On this one occasion I saw the dog bite my grandson when he | :22:18. | :22:25. | |
walked past him. The next day he scratched him down the face because | :22:26. | :22:28. | |
my boy had a biscuit and we knew we could not keep the dog any more. | :22:29. | :22:32. | |
Having children with their disabilities is hard and having a | :22:33. | :22:37. | |
dog who is supposed to change that and help them and it does not and | :22:38. | :22:41. | |
you are left with the aftermath and it is just horrendous. | :22:42. | :22:47. | |
A terrible ordeal for Wayne and his family, but his case is not unique. | :22:48. | :22:54. | |
There have been a number of cases and it is a terrible turmoil for the | :22:55. | :22:58. | |
families and huge financial hardship. We can see what a genuine | :22:59. | :23:04. | |
assistance dog can be like now in some footage. This is what they | :23:05. | :23:08. | |
should be like and how much of a great help they can be. They need | :23:09. | :23:14. | |
incredible, careful selection, training and matching and a lot of | :23:15. | :23:18. | |
support goes into the families, for example with this child with autism. | :23:19. | :23:24. | |
It is not about dominating and control of the dog, but building a | :23:25. | :23:28. | |
relationship with the dog so it feels confident to be in a lot of | :23:29. | :23:31. | |
different environments and that takes time. Nice and calm and what | :23:32. | :23:37. | |
we want to see. What can be done to ensure that everyone who gets the | :23:38. | :23:41. | |
dog has been trained to that good standard? We work to international | :23:42. | :23:48. | |
standards and they are accredited against those. Sadly there are not | :23:49. | :23:53. | |
standards in the UK, but we are working with the government and | :23:54. | :23:57. | |
other organisations to see if we can rectify that so people can be | :23:58. | :24:01. | |
confident so this never happens again. What advise you can give | :24:02. | :24:06. | |
people to make sure they do not get their fingers burned? If you see a | :24:07. | :24:10. | |
website that offers all sorts of different kinds of disabilities and | :24:11. | :24:16. | |
dogs, I would be wary because I do not think those people have the | :24:17. | :24:19. | |
skills to do that. Check out the organisation. Can you visit? Can you | :24:20. | :24:26. | |
see the dogs being trained? If someone says you can have a dog very | :24:27. | :24:30. | |
quickly, I would be very wary because this takes a lot of time and | :24:31. | :24:33. | |
preparation to get the right dog for you to stop we have heard of all | :24:34. | :24:41. | |
sorts of stories. Never buy a dog from a service station. That is | :24:42. | :24:45. | |
totally wrong place to be working with a dog. Be careful and do due | :24:46. | :24:49. | |
diligence. I know people are desperate, but be careful. Great | :24:50. | :24:54. | |
advice, thank you so much for coming in. | :24:55. | :24:58. | |
Next to a crime which happened just two months ago here | :24:59. | :25:00. | |
in the centre of Leicester, when a young woman found | :25:01. | :25:03. | |
herself caught up in a terrifying street robbery. | :25:04. | :25:08. | |
He grabbed my wrist and that is when I felt like, oh, God, help me, what | :25:09. | :25:19. | |
is going to happen? I then started crying hysterically and that is when | :25:20. | :25:25. | |
he started saying, you are going to get stabbed, you need to stop right | :25:26. | :25:36. | |
now. This 29-year-old lives in the city centre of Leicester. I have | :25:37. | :25:41. | |
been in Leicester for ten years. I came to university and stayed. I am | :25:42. | :25:46. | |
involved in a community of international students and people | :25:47. | :25:50. | |
who travel around a lot and we do a lot of social activities like | :25:51. | :25:52. | |
learning Spanish and playing the guitar. On the evening of Easter | :25:53. | :26:02. | |
Monday she had been to her local supermarket to buy food and was on | :26:03. | :26:08. | |
her way back home. I was walking just past the student halls, it was | :26:09. | :26:12. | |
not an unsafe route, I have wanted a million times before. But this time | :26:13. | :26:20. | |
as she walked along York Road, she realised she was being followed. | :26:21. | :26:25. | |
There was a gentleman who was walking close to me. He grabbed my | :26:26. | :26:36. | |
wrists. That is when I felt like, oh, God, help me. What is going to | :26:37. | :26:45. | |
happen? That is when I felt like it was my worst nightmare realise. I | :26:46. | :26:48. | |
never imagined anything like this would happen to me. He said, what we | :26:49. | :26:53. | |
are going to do is go to the cashpoint and get some cash out. I | :26:54. | :26:58. | |
started screaming because there were people in the street, but no one | :26:59. | :27:03. | |
responded. Then her ordeal took an even more terrifying time. At this | :27:04. | :27:09. | |
point he said he had a knife. He kept saying, if you make a noise, | :27:10. | :27:14. | |
scream or say anything, I will stab you. If I did not stop crying and | :27:15. | :27:18. | |
get myself together, he would stab me. But the attack had been spotted | :27:19. | :27:28. | |
by a passing student. The moment she started crying and he put his arm | :27:29. | :27:31. | |
around her that is when I knew straightaway I have got to follow, I | :27:32. | :27:38. | |
cannot leave her alone. The man marched along the road, passing | :27:39. | :27:43. | |
several people. Somebody turned the corner and he said if you do or say | :27:44. | :27:48. | |
anything, I will stab you. Make sure you are a good girl and nothing will | :27:49. | :27:52. | |
happen to you if you do that. Get the cash out and we will be OK. A | :27:53. | :27:59. | |
few metres behind, Rebecca was watching the attack unfold. It was | :28:00. | :28:03. | |
literally like she was crying for help in that split second. I knew I | :28:04. | :28:08. | |
had to do something because I was really angry because she was so | :28:09. | :28:14. | |
small in comparison to him. As the man forced her to withdraw ?140, | :28:15. | :28:23. | |
Rebecca sprung into action. From behind as a girl pushed him away | :28:24. | :28:27. | |
from the cashpoint and attacked him. I pushed myself in between them and | :28:28. | :28:34. | |
grab his arm. They got into a bit of a scuffle. He was surprised a woman | :28:35. | :28:41. | |
was fighting him and was giving a pretty good fight. I realised I was | :28:42. | :28:48. | |
free, I had left my card in the cashpoint, I did not care, I wanted | :28:49. | :28:53. | |
to be safe. I tried to grab as much of the money as I could, but he was | :28:54. | :29:00. | |
stronger, so I could not manage it. The attacker ran off with the money. | :29:01. | :29:05. | |
Thanks to Rebecca, her ordeal was finally over. She is just so brave. | :29:06. | :29:15. | |
Oh people just do not get involved. The fact that she intercepted, I am | :29:16. | :29:21. | |
eternally grateful. For Amy catching the culprit would mean everything. | :29:22. | :29:29. | |
Even now if somebody comes up behind me it scares me, I feel a bit on | :29:30. | :29:34. | |
edge watching out around me now and I do not know how to get out of it. | :29:35. | :29:37. | |
He got to me. Well, DC Jim Muzzell | :29:38. | :29:41. | |
from Leicestershire Police is here. This must have been a really | :29:42. | :29:44. | |
frightening experience. It was extremely traumatic, coupled | :29:45. | :29:53. | |
with a fact that a knife was threatened against Ireland the | :29:54. | :29:56. | |
incident lasted between four and five minutes. What do we know about | :29:57. | :30:09. | |
the guy who did this? We have created an e-fit. | :30:10. | :30:15. | |
The suspect is a man, described as mixed race, | :30:16. | :30:18. | |
he's between 25 and 30 years old, around 5ft 11ins | :30:19. | :30:20. | |
The attacker's behaviour was worrying. Yes. That is why we are | :30:21. | :30:33. | |
keen to apprehend him. He was methodical in his approach, he has | :30:34. | :30:37. | |
picked up a vulnerable female and when he realised she did not have | :30:38. | :30:41. | |
any cash on her person he led her to a cashpoint machine and forced her | :30:42. | :30:47. | |
to take a shot. This was a Bank Holiday Monday, a busy area, why did | :30:48. | :30:51. | |
you think no one intervened before Rebecca? Speaking with the victim | :30:52. | :30:59. | |
people may have thought it was a domestic argument taking place | :31:00. | :31:02. | |
between girlfriends and boyfriends and do not want to get involved. It | :31:03. | :31:09. | |
was a Bank Holiday Monday, we believe there were loads of people | :31:10. | :31:14. | |
around. It is an arterial route out of Leicester and passers-by would | :31:15. | :31:18. | |
have seen her particularly at the cashpoint and we are appealing for | :31:19. | :31:23. | |
members of the public to provide us with an formation either about the | :31:24. | :31:29. | |
subject -- axel suspect of other information that would assist us. | :31:30. | :31:32. | |
And remember, as well as our numbers on screen | :31:33. | :31:35. | |
you can also call Crimestoppers anonymously on 0800 555 111. | :31:36. | :31:38. | |
Also, if you've been a victim of any crime | :31:39. | :31:42. | |
you can speak to Victim Support on 08 08 16 89 111. | :31:43. | :31:47. | |
Now, for most people, this is a sign you'll recognise, | :31:48. | :31:49. | |
8.7 million people in the UK are members of the scheme, | :31:50. | :31:55. | |
and this year it marks its 35th anniversary. | :31:56. | :31:57. | |
I'm joined by Lynn Farrar, the Chair of Neighbourhood Watch, | :31:58. | :32:01. | |
and Gill Faulkner, who is a member of a Neighbourhood Watch scheme | :32:02. | :32:04. | |
Lynn, 35 years is quite an achievement. | :32:05. | :32:09. | |
Remind us what the scheme's all about. | :32:10. | :32:17. | |
It is about preventing crime in the community. Figures show that fewer | :32:18. | :32:23. | |
remember of a neighbourhood watch scheme it can reduce crime up to | :32:24. | :32:30. | |
21%. A massive amount. We can see some of the pictures of the | :32:31. | :32:33. | |
community spirit you mention, it is about people helping each other out. | :32:34. | :32:39. | |
You are a member of a neighbourhood watch scheme and you helped stop a | :32:40. | :32:44. | |
crime. It was around midnight and my husband spotted three people | :32:45. | :32:50. | |
loitering around a neighbour's house across the road and he informed me | :32:51. | :32:56. | |
they were dismantling the garden furniture ready to take away so he | :32:57. | :33:00. | |
asked me to call the police. I rang the police and then I rang the lady | :33:01. | :33:06. | |
who lived opposite me and informed her that they were stealing the | :33:07. | :33:12. | |
garden furniture. Within five minutes the police arrived, they | :33:13. | :33:18. | |
arrested the three people and they were charged. It was a huge success. | :33:19. | :33:23. | |
It is all about helping your neighbours out. Well done. We need a | :33:24. | :33:29. | |
neighbour like you. It has been around for 35 years but you have had | :33:30. | :33:34. | |
to evolve, what have you done? We have had to modernise. Prime has | :33:35. | :33:39. | |
changed. Although we still have burglaries we are concentrating more | :33:40. | :33:44. | |
on online crimes such as scams and online fraud. We are enabling our | :33:45. | :33:52. | |
members through the website so all the information is there and we hope | :33:53. | :33:56. | |
that people will visit the website and find out more. You also use | :33:57. | :34:01. | |
social media to spread the word. Yes. You are keeping up with the | :34:02. | :34:11. | |
times. We are. Happy anniversary to neighbourhood watch and happy | :34:12. | :34:11. | |
birthday to you. And of course, similar | :34:12. | :34:15. | |
to Neighbourhood Watch, this programme relies on the help | :34:16. | :34:16. | |
of the public to solve crimes. Just like the case we featured | :34:17. | :34:19. | |
last summer of a young student who was mugged | :34:20. | :34:22. | |
on his university campus. For any teenager, starting out at | :34:23. | :34:34. | |
University is a daunting time. Before I began university I had some | :34:35. | :34:40. | |
level of anxiety but I was really excited because I knew so much about | :34:41. | :34:47. | |
my life would change. When Alex left for university we were both very | :34:48. | :34:50. | |
sad. I was in tears but I thought he is a young man and he has to go out | :34:51. | :34:56. | |
and he has to enjoy life. When a child has a disability it is very | :34:57. | :35:02. | |
hard. Alex has spina bifida, a neurological condition that affects | :35:03. | :35:07. | |
the spinal-cord. I have a very poor mobility and doing any amount of | :35:08. | :35:12. | |
walking is quite a challenge. I do not have any feeling below the knee. | :35:13. | :35:16. | |
When we came to visit Newcastle we were very pleased and we thought his | :35:17. | :35:21. | |
lectures and where he has the go is very close, he does not have far to | :35:22. | :35:25. | |
walk. I felt very safe, I never sensed any danger and did not think | :35:26. | :35:31. | |
anything was realistically going to happen to me. On a Sunday afternoon | :35:32. | :35:38. | |
in February last year Alex was targeted by a callous criminal. It | :35:39. | :35:44. | |
was Valentine's Day. Alex was walking through the university | :35:45. | :35:49. | |
campus on his way home. He was being followed. Walking slowly, a man was | :35:50. | :36:00. | |
keeping a close eye on him. Waiting for an opportunity to strike. Alex | :36:01. | :36:06. | |
had no idea he was being watched. Then things turned nasty. Just as | :36:07. | :36:13. | |
Alex got his phone out, the man confronted him. He barged into me | :36:14. | :36:19. | |
and then he came up in front of me and threatened me if I did not give | :36:20. | :36:26. | |
him my phone. Alex was terrified. The attacker snatched his Ford, | :36:27. | :36:30. | |
demanding to know his PIN number and made off. I felt so sick inside. I | :36:31. | :36:41. | |
was livid. Absolutely livid. He had phoned independence and somebody had | :36:42. | :36:50. | |
taken that away in a flash. Police turn to crime watch to see whether | :36:51. | :36:56. | |
viewers could help solve this case. Within days of last summer's appeal | :36:57. | :37:00. | |
their investigation took a big step forward. Clearly this was a | :37:01. | :37:05. | |
despicable crime and one which the police were prim, committed to | :37:06. | :37:11. | |
finding the person responsible. We had an excellent response from the | :37:12. | :37:14. | |
public including Paula who watched the show and identify the person. | :37:15. | :37:20. | |
This corroborated telecoms analysis we had conducted. The 18-year-old | :37:21. | :37:26. | |
admitted two counts of robbery against two university students. In | :37:27. | :37:31. | |
the case of Alex the court took account of his vulnerability and the | :37:32. | :37:34. | |
fact he had been threatened with the use of a gun. He was put before | :37:35. | :37:39. | |
Newcastle Crown Court and sentenced to 3.5 years in custody which sends | :37:40. | :37:44. | |
a strong message that the police, the courts and the public will not | :37:45. | :37:48. | |
tolerate criminals targeting vulnerable members of our community. | :37:49. | :37:53. | |
When we got the phone call to say he had been caught we were really | :37:54. | :37:58. | |
pleased. His anxiety was quite high so we had a long road. He is getting | :37:59. | :38:04. | |
there slowly, but he is getting there. After the attack Alex was too | :38:05. | :38:08. | |
afraid to continue living in the City centre. I definitely had a | :38:09. | :38:16. | |
desire to move home. I felt like I could no longer do the things | :38:17. | :38:21. | |
Newcastle I had previously done. With his attacker off the streets | :38:22. | :38:24. | |
his confidence is growing again and he is studying hard for his degree. | :38:25. | :38:32. | |
I you looking forward to your exams? You can look forward to exams. I | :38:33. | :38:39. | |
feel like it generated significant public attention towards the case. I | :38:40. | :38:46. | |
feel like that with a very big role in my attacker eventually being | :38:47. | :38:46. | |
caught and arrested. Really great to see | :38:47. | :38:49. | |
the difference your calls can make. Talking of which, take a look | :38:50. | :38:52. | |
at today's Wanted Faces. He was arrested by detectives | :38:53. | :38:54. | |
investigating a telephone fraud in which victims lost more than half | :38:55. | :39:00. | |
a million pounds. He was released on police bail | :39:01. | :39:03. | |
but has failed to return Dogra is 34 and originally | :39:04. | :39:06. | |
from India with friends in London. He was due to appear in court | :39:07. | :39:10. | |
in connection to allegations that elderly people were charged | :39:11. | :39:17. | |
for shoddy or uncompleted He didn't turn up for his trial | :39:18. | :39:19. | |
though and a warrant has been The 41-year-old has links to Sussex, | :39:20. | :39:24. | |
Hampshire, Surrey and Hertfordshire. This is Hakeem Shittu, | :39:25. | :39:29. | |
although he also uses Detectives would like to speak | :39:30. | :39:31. | |
to him in connection to the supply The 31-year-old has a bullet | :39:32. | :39:37. | |
scar on his left leg He has friends and family | :39:38. | :39:42. | |
in Northolt and Uxbridge in West London and also in Oxford, | :39:43. | :39:48. | |
Abingdon and Witney. Finally today, this | :39:49. | :39:52. | |
is Lukasz Malisz. The 30-year-old is wanted | :39:53. | :39:55. | |
for questioning after drugs and more than ?13,000 of cash were found | :39:56. | :39:59. | |
at a house in Cardiff. Originally from Poland, | :40:00. | :40:02. | |
he now has links across south Wales. If you know where any | :40:03. | :40:05. | |
of these men are make sure you get in touch | :40:06. | :40:07. | |
using the numbers on screen. I'm here with Professor Turi King, | :40:08. | :40:15. | |
one of the team of pioneering forensic scientists | :40:16. | :40:17. | |
at Leicester University. Turi, your colleagues were actually | :40:18. | :40:20. | |
the first in the world to use DNA profiling techniques | :40:21. | :40:23. | |
to solve a murder case. It was one of the most amazing | :40:24. | :40:36. | |
inventions in forensic science in the 80s, Alec Jeffreys' team. You | :40:37. | :40:43. | |
took a sample of my saliva to test my DNA. What did you find out? I was | :40:44. | :40:49. | |
looking at mitochondrial DNA which comes down through the female line. | :40:50. | :40:53. | |
One of the nice things about yours as it shows as you have got what | :40:54. | :40:58. | |
looks like European ancestry. I do not know if you know about this but | :40:59. | :41:04. | |
it is a type phoned at its highest frequencies in Europe. Did you know | :41:05. | :41:09. | |
about this? My mum is mixed race, so my family are from Ghana and | :41:10. | :41:17. | |
Britain. That is what is showing up in your mitochondrial DNA. No then | :41:18. | :41:24. | |
European. If you did not know this it is a starting off point for | :41:25. | :41:28. | |
looking at your ancestry. It is really nice because without knowing | :41:29. | :41:33. | |
anything about you I can say something about your ancestry and | :41:34. | :41:36. | |
this is what is going on in forensics, you can use a person's | :41:37. | :41:41. | |
DNA to say where their ancestry is likely to come, here and I colour. | :41:42. | :41:48. | |
It is interesting what you can find out about someone without even | :41:49. | :41:52. | |
meeting them. This is what we want to be able to do with forensics. If | :41:53. | :41:56. | |
you have no suspects and you want to build a profile these are the bits | :41:57. | :42:00. | |
of DNA we are interested in looking at. It is a great way to work | :42:01. | :42:07. | |
alongside the police. Yeah. It is fascinating. Thank you. Not at all. | :42:08. | :42:14. | |
Turi, thank you, I've certainly learned a lot this | :42:15. | :42:17. | |
morning and now you've got my DNA on file I'd better behave myself! | :42:18. | :42:20. | |
Time now for a look at what's been coming in on the calls, | :42:21. | :42:25. | |
Yesterday we showed you the shocking case of a mother and her young | :42:26. | :42:29. | |
daughter who were injured when a car crashed into them. Footage showed | :42:30. | :42:32. | |
the crash on the two men who left the scene. You have called in with | :42:33. | :42:36. | |
potential names and addresses which officers say are of great interest. | :42:37. | :42:41. | |
Excellent work. Thank you. Keep them coming. | :42:42. | :42:43. | |
Well, Rav, I'll be heading to my home town next week. | :42:44. | :42:48. | |
Where we'll have an exclusive interview with the Chief Constable | :42:49. | :42:50. | |
In his first extended TV interview since the arena terrorist atrocity | :42:51. | :42:58. | |
Ian Hopkins will be telling us about the moment the first 999 calls | :42:59. | :43:06. | |
came in, the selfless work of his officers. | :43:07. | :43:08. | |
For more details about the crimes on today's programme, | :43:09. | :43:16. | |
And before we go, here's another look at this | :43:17. | :43:19. | |
If any of them look familiar, pick up the phone and tell | :43:20. | :43:23. | |
We'll be back on Monday at 9:15am after Breakfast. | :43:24. | :43:26. | |
Across the country, 11 million people | :43:27. | :44:04. |