It finished snowing again. 😦
I admit that it wasn’t always easy to get inspired to get out there. But there were a few factors that helped me keep going:
Workout notes Went ok, though I didn’t do abs.
Pull ups: 5 sets of 10
Bench: 10 x 135, 5 x 180, 4 x 180
dumbbell rows/bench: rows: 2 sets of 10 x 65, 1 set of 10 x 70, bench: 1 set of 10 x 65, 2 of 10 x 70
military, curl, pull-downs: military: 15 x 45 dumbbell, 15 x 50 dumbbell, 10 x 180 (machine),
curl: 3 sets of 10 x 70 (machine) pull downs: 1 set 7 x 162.5, 2 sets of 10 x 150.
Then: 3 miles on the treadmill: 10:19, 19:09, 27:33 (28:23 for 5K) Sped up; kept the level at 1 after a warm up.
I saw some I knew: Peggy, Bob, Rich, Ana, Cathie R. and lots of women in spandex; some very tight and clingy.
Summary of 2012 (running/walking)
I’ve added the running/walking miles since 1997; note that all miles prior to 2002 were running miles only.
|1997||1378||20:02 5K, 5:54 mile|
|1998||2129||19:53 5K, 41:27 10K, 5:41 1600|
|1999||1274||achilles, 1:34 half, 3:45 marathon|
|2000||1729||3:38 marathon, 1:35 half|
|2001||2165||1:37 half, 3:40 marathon, 20:47 5K|
|2002||1967||achilles, walking, 21:37 5K, 3:57 run, 4:44 mar. walk, 6:22 50k walk, 30:43 5K walk (j)|
|2003||2514||ultras, 2:17 half walk, 30:42 5K walk (j), 8:31 1500 m walk (j)|
|2004||2714||23:41 100 walk, 12:46 trail 50 walk, 18:03 3K walk (j), 6:20 50k walk|
|2005||2778||2 trail 100 finishes, 6:29 50K walk|
|2006||1498||piriformis, 83 24 hour walk|
|2008||2059||24:22 5K, 2:25 half walk|
|2009||1934||24:01 5K run, 5:12 mar. walk, 100 mile (47:55), knee|
|2010||1273||knee, 30 mile trail walk, 17:30 2 mile run|
|2011||1601||25:35 5K run (end), 54 mile 24 hour walk, 2:22 half m. walk.|
|2012||1922||24:34 5K, 1:23 15K, 6:59 mar. walk(!), 2:24 half mara. walk.|
|total||30,729||10642 from 97-02, 20087 from 03-12|
AG means I won an age group award or “walk category” award of some sort
Non-5K Spandex Chases
First Light Half Marathon Walk 2:34 (AG)
2012 5K runs:
26:12 Jingle Bell 5K: 7:38/8:49/9:43 (1 December) (3.15 miles?)
24:51: Boo Run 5K: 8:08/7:56/8:46 (20 October) (AG)
25:45: Bradley Homecoming Tippet 5K (13 October) (AG)
(25:53 for 3.2) 8:01, 23:53 (3). Stride to Unite (22 September) (AG)
25:27 8:00, 8:20, 9:06 Pekin Marigold 8 September (AG)
25:12 (Hanna City 25 August) 8:04, 8:05, 9:01
27:21 (Cystic Fibrosis 25 August) 8:53 8:43, 9:44
25:47 (Yates City, 18 August)
27:59 August 5 MathFest (7:36)
26:07 Run for the Health of it July 14 8:28 8:49, 8:49 (AG)
27:46 July 4 Firecracker 8:09 8:43 10:53
25:03 May 26 River Run 8:08, 8:07, 8:47
25:13 Race for the Cure May 12 (8:25, 7:34, 9:12) (AG)
24:34 May 5 Run to Remember (7:54, 7:45, 8:54)
25:41 Bradley U. April 28
25:14 CIDA March 31 (8:27, 8:17, 8:29) (AG)
25:08 Interplanatary March 24 (8:14, 8:19, 8:34) (AG)
The WordPress.com stats helper monkeys prepared a 2012 annual report for this blog.
Here’s an excerpt:
About 55,000 tourists visit Liechtenstein every year. This blog was viewed about 430,000 times in 2012. If it were Liechtenstein, it would take about 8 years for that many people to see it. Your blog had more visits than a small country in Europe!
Ok, I forced myself out into the 20 F degree winter morning (sunny) and attempted to run 10 miles on the East Peoria Trail. There were several 100 meter long ice patches; I’d say about 75 percent of the trail from the Fondulac building to what I call the 5 mile turn around (near Morton) was runnable. But those ice patches wore me out; I was reduced to shuffling and it took me 1:55 to do the course (usually 17-20 minutes less).
Even worse, my legs ached; this was sort of like trail running. I am not used to it. Or I’ll put it another way: the return trip took 1 minute LONGER than the out; usually the return is 4-5 minutes faster.
I saw a couple of other runners out there and a couple of walkers; and there was the usual 18-19 minute a mile couple going out for their 2 mile walk giving the exaggerated GOOD MORNING at about the time I was struggling. I gurgled a greeting back; I wanted to flip them off. 🙂
Why I hate winter:
3. Static electricity (I get shocked all winter long, though the use of lotion reduces this somewhat)
5. Pounds of extra sweaty gear.
6. putting on and peeling off all of that sweaty gear.
7. scraping the car
8. People who like winter, especially couch potatoes who like winter. My response to “I hope that we get snow” is “f*ck you!”.
9. Holidays: socializing that I don’t want to do and travel that I don’t want to do.
10. Early darkness.
Every year, I complain about winter all winter long; I whine and grumble and wish that I had written a better dissertation so I could have landed a job in a warm weather location.
All of my miles, save the 4 I just walked, have been inside. The cold really isn’t that bad and the footing isn’t that bad right now. But I just don’t feel like fighting the cold outside; that is unusual for me.
The Illinois River is NOT frozen though there is some thin ice in the marinas. I saw a couple of dog walkers and a couple of runners; that is about it. Though the temperature was only in the mid 20’s, the wind really kicked up and I pulled up my hood.
My mood went from “being down” to perking up a bit.
Football: right now, Navy is being blown away by Arizona State; sorry to say I am not surprised. Navy doesn’t have the speed to stay with the Sun Devil pass receivers.
Well, one thing about being a non-custodial parent in a case in which one lives a great distance away from one’s kid is that some things can come up that upset visit plans.
My daughter was scheduled to fly into Chicago today, but she ended up throwing out her back and wasn’t in shape to fly; the doctor prescribed a few days of bed rest followed by a few days of very light activity.
Unfortunately, my back issues started an an earlier time in my life, and as a young man (18) I had such a problem that required bed rest followed by physical therapy. It wouldn’t surprise me if I passed these “tricky back” genes onto her. That is far from fatal though; I am pretty active most of the time. But alas, no winter visit from my daughter this year.
Hence in a few days, I’ll drive to go see her; fortunately hotel rooms aren’t that expensive. It is a long trip, but getting out of the cold is always nice, though winter has not terribly bad by our standards…so far. And, she can use the money sunk into the airline tickets within the next year to come see me; perhaps this summer.
Who knows; perhaps by the time I am through with this trip we’ll have a reasonable deal on the fiscal cliff, though no deal is better than a bad one.
And please, stop it about “Obama is raising Congressional pay>” What has happened is that he has lifted a federal pay freeze, which mostly affects low to middle income federal employees, many who are facing either a lay-off or a furlough. It would be wise politics for Congress to exempt itself from this.
Workout notes Weights then a 4 mile treadmill walk. In all honesty, I walked on the treadmill because I was lazy; the roads aren’t that bad.
pull ups: 5 sets of 10
superset: abs and incline bench press: 10 x 135, 4 x 155, 5 x 150, 6 x 145
superset rows and dumbbell bench press: rows: 3 sets of 10 x 65, bench press: 2 sets of 10 x 65, 1 set of 10 x 70
superset: military press, pull down, curl: military press: 2 sets of 15 x 50 dumbbell, 1 set of 10 x 70 (each) machine,
pull down: 3 sets of 10 with 160 (one with a rotated grip), curl: 3 sets of 10 x 70 (machine).
walking: treadmill, 2 miles at 15 mpm where I upped the incline from 1 to 8 (every two minutes) and then back down, then with the incline decreasing from 5 to eventually 1, increased the speed to 12 mpm. Second 2 miles took 25:10. Again, I was too lazy to put on cold weather gear.
But it paid off as it turns out that Barbara was leaving HER workout (third one in the last few days) and so I caught her in time for us to eat at the Indian buffet.
I admit that this is a cool video:
So what is going on? This is an example of mathematical projection: the image you are seeing is a projection of objects in 3 space being projected onto a 2 dimensional screen (sort of). Our brain attempt to decode what it sees.
Schematically, it is something like this:
Imagine a light at the origin and a vertical screen 3 units away. In between you can place objects; here you see the “semi-circle” (looks too bent to be a circle) and the line segment are different objects at different distances from the screen, yet BOTH objects cast the same “shadow” or “image”. You could NOT distinguish these two objects by the image they cast on the screen.
In short, “projection” loses information, by design.
There are all sorts of examples and implications of this concept. One of the most interesting ones comes from statistics and the famous Anscombe data sets. These are 4 very different data sets which, when one applies simple linear regression, yields not only the same regression line, but also the same correlation coefficient and the same confidence intervals for the regression coefficients (up to a tiny difference).
Mathematically, think of it this way: a linear regression in this case can be thought of as a map from the set of, in this case, 11 different vectors in (denoted by ) to 5 real numbers: . (linear algebra exercise: write these 5 quantities in terms of the inner products of the various vectors and vector components). Or, one could see this as a projection from the sets of two 11 dimensional vectors (one consisting of the x components, one of the y components) onto the same set of numbers.
Why? Remember that the linear regression coefficients, the confidence intervals and the correlation coefficients are completely determined by these 5 quantities. So, a linear regression is a type of projection, and yes, you lose information when you do it.
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