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Get to Know Me Uncomfortably Well

1. What is you middle name?

2. How old are you?

3. What is your birthday?

4. What is your zodiac sign?

5. What is your favorite color?

6. What’s your lucky number?

7. Do you have any pets?

8. Where are you from?

9. How tall are you?

10. What shoe size are you?

11. How many pairs of shoes do you own?

12. What was your last dream about?

13. What talents do you have?

14. Are you psychic in any way?

15. Favorite song?

16. Favorite movie?

17. Who would be your ideal partner?

18. Do you want children?

19. Do you want a church wedding?

20. Are you religious?

21. Have you ever been to the hospital?

22. Have you ever got in trouble with the law?

23. Have you ever met any celebrities?

24. Baths or showers?

25. What color socks are you wearing?

26. Have you ever been famous?

27. Would you like to be a big celebrity?

28. What type of music do you like?

29. Have you ever been skinny dipping?

30. How many pillows do you sleep with?

31. What position do you usually sleep in?

32. How big is your house?

33. What do you typically have for breakfast?

34. Have you ever fired a gun?

35. Have you ever tried archery?

36. Favorite clean word?

37. Favorite swear word?

38. What’s the longest you’ve ever gone without sleep?

39. Do you have any scars?

40. Have you ever had a secret admirer?

41. Are you a good liar?

42. Are you a good judge of character?

43. Can you do any other accents other than your own?

44. Do you have a strong accent?

45. What is your favorite accent?

46. What is your personality type?

47. What is your most expensive piece of clothing?

48. Can you curl your tongue?

49. Are you an innie or an outie?

50. Left or right handed?

51. Are you scared of spiders?

52. Favorite food?

53. Favorite foreign food?

54. Are you a clean or messy person?

55. Most used phrased?

56. Most used word?

57. How long does it take for you to get ready?

58. Do you have much of an ego?

59. Do you suck or bite lollipops?

60. Do you talk to yourself?

61. Do you sing to yourself?

62. Are you a good singer?

63. Biggest Fear?

64. Are you a gossip?

65. Best dramatic movie you’ve seen?

66. Do you like long or short hair?

67. Can you name all 50 states of America?

68. Favorite school subject?

69. Extrovert or Introvert?

70. Have you ever been scuba diving?

71. What makes you nervous?

72. Are you scared of the dark?

73. Do you correct people when they make mistakes?

74. Are you ticklish?

75. Have you ever started a rumor?

76. Have you ever been in a position of authority?

77. Have you ever drank underage?

78. Have you ever done drugs?

79. Who was your first real crush?

80. How many piercings do you have?

81. Can you roll your Rs?“

82. How fast can you type?

83. How fast can you run?

84. What color is your hair?

85. What color is your eyes?

86. What are you allergic to?

87. Do you keep a journal?

88. What do your parents do?

89. Do you like your age?

90. What makes you angry?

91. Do you like your own name?

92. Have you already thought of baby names, and if so what are they?

93. Do you want a boy a girl for a child?

94. What are you strengths?

95. What are your weaknesses?

96. How did you get your name?

97. Were your ancestors royalty?

98. Do you have any scars?

99. Color of your bedspread?

100. Color of your room?

Computer scientists and mathematicians at the CEU Cardenal Herrera University in Valencia have developed a prediction model that can warn epileptic sufferers of an upcoming seizure with 20 minutes notice. 

Being able to predict the onset of a debilitating seizure would significantly improve the quality of life of epileptics. With this goal, scientists from around the world competed in the American Epilepsy Society Seizure Prediction Challenge in 2014. A team from the Universidad Cardenal Herrera CEU (CEU-UCH) reached third place overall, winning them an invitation to the Society’s annual meeting in Seattle. Their prediction model has recently been published in the article Crowdsourcing reproducible seizure forecasting in human and canine epilepsy in the OUP’s Brain.

CEU-UCH researchers Juan Pardo, Javier Muñoz, Francisco Zamora and Paloma Botella developed an algorithm able to interpret the relevant data and predict a seizure up to 20 minutes before it occurs, giving the patient time to take their medication and nip it in the bud. Their model came third out of 502 submissions.

The idea is that a portable device like a mobile phone or a smartwatch reads signals sent from a microchip implanted in the patient’s brain, interpreting the data according to the researchers’ prize-winning algorithm and warning the patient of an upcoming seizure. The benefits of this set-up are two-fold: not only would epilepsy sufferers only have to take their medication in the event of a predicted seizure and not constantly throughout the day, mitigating any adverse effects, but they would also be able to reclaim a convincing semblance of a normal life, only avoiding ‘high-risk’ activities like driving or swimming until the risk of their having a seizure had passed.

Talking to the University back in 2014, Juan Pardo, director of the Department of Physical Sciences, Mathematics and Computing, said that “we are not doctors, but we are experts in massive data processing”, known today as Big Data. “This work shows how computer scientists and mathematicians are needed in many fields to help solve pressing issues, in this instance in neuroscience”.

It wasn’t made with light though. The image visualizes the flux of neutrinos coming from the Sun. Neutrinos are sub-atomic particles created in the nuclear furnace of the sun, and they can pass through nearly anything. Billions of neutrinos shoot through our bodies every second, and they fly with ease through the rocky bulk of the earth.

Scientists have built a giant neutrino observatory in an abandoned mine shaft 3,000 ft below Mount Kamioka in Japan (all that rock shelter the sensors from the noise of cosmic rays). It’s called the Super-Kamiokande - and it’s essentially a 13 million gallon tank of ultra-pure water, rigged with sensors that can detect the extremely weak interaction of neutrinos with other matter.

Work at Super-Kamiokande helped establish that neutrinos have mass. One of scientists on this project, Takaaki Kajita, has just won the Nobel Prize for Physics.

2) SpaceX’s Falcon Heavy, set to launch in 2015, produces more thrust than the Saturn V did. 

People with a severe form of schizophrenia have major differences in their brain networks compared to others with schizophrenia, bipolar disorder and healthy individuals, a new study from the Centre for Addiction and Mental Health (CAMH) shows.