"Titanic" (1997)
A Film Review by Jason Wallis
"Titanic" * * * * Starring Leonardo DiCaprio, Kate Winslet, Billy Zane, Kathy Bates, David Warner and Bill Paxton Directed by James Cameron
"Titanic": the two hundred million plus sink-or-swim epic with a boring, tired, overwrought romance for a storyline. Doesn't sound too promising, does it? I didn't think so either; I thought it was going to be just another big-budget bomb in the vein of "Waterworld" or "Speed 2: Cruise Control". It looked as though the film would sink faster than the ship. That is, until I read some of the rave reviews this has been getting by the public and critics alike. So I decided today to see what all the fuss was about.
Well, I definently found out. James Cameron's epic love story has got to be one of the most brilliantly crafted, beautifully filmed and wonderfully executed movies I have ever seen. And even with all the hype, the drawn-out story (I mean, honestly, how long can you really watch a romance involving Leonardo DiCaprio?) and long running time, Cameron has pulled it off.
At about three hours and fifteen minutes, this is by far the longest flick I've ever seen at a theater.  Oh, no. As soap operay (?) as the love theme may seem, it somehow manages to completely hold your attention for the full running time. And, as all truly great films do, it leaves you wanting more.
Just one of several things that makes the movie so worthwhile is that is works on many levels, a quality often missing from many modern films. On the surface, you have the best disaster pic of all time. You also have a wonderful romance that is the first truly moving pure love story since "Frankie and Johnny". A little deeper still, you have an excellent example of the class systems; the difference between the way the rich are treated and how the less fortunate are. "Titanic" is definently brilliant filmmaking at it's best.
The plot revolves around (of course) the sailing of the Titanic, the ship that was so callously refered to as "unsinkable". But far more intricate to the story is the relationship between Jack Dawson (Leonardo, in the best performance of his career thus far), a wandering drifter who won aticket aboard the Titanic in a poker game. He has barely anything in the world but is a pretty jolly guy anyway. On the other side of the coin, you've got Rose (Kate Winslet - shwing!), a poor little rich girl type who has it all; money, servants, a fiancee, everything. Except happiness.
 Jack saves her and the two instantly fall in love. Only she doesn't quite know it yet, so she takes some convincing. It doesn't help, either, that her jerk fiancee (Billy Zane, who deserves more credit for his performance in this film than he has gotten) is onboard, as is her snobby mother who needless to say does not take an instant liking to Jack's advances.
So the two start a heated love affair and in the middle of it all, the ship goes down. And that's basically all there is to the plot. But it is the attention to detail that Cameron puts into the picture that makes that film so worthwhile. Not to mention the actors, who put so much charisma into their characters that they help us feel like we are actually on that ship; that we are not merely watching a movie. They are just as important as the set pieces (which are amazing enough by themselves.
"Titanic" is a great film, to be sure, but it is also something more. It is a piece of art that hits you at just the right places and at just the right times that it makes you actually become extremely emotionally involved in it's characters. They hardly ever make movies like this anymore.
And one other thing. This movie should not be missed in a theater. Because of the beauty of the cinematography and the sets, you really should see this on the big screen. Several times, too. It's that great a film.
Even at it's mild pace (until the last hour, that is), "Titanic" is one of the rare flicks that carry you away to another place and another time. It's quite an experience.  So this is the one that I will be rooting for come Oscar time. In short, see this movie at all costs.
Check out Jason Wallis' Filmaholics Anonymous web page at http://www.geocities.com/Hollywood/Boulevard/7475
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Module src.utils
Some utilities functions.
Functions
| read_table (file_path:) | Read a lua-like file and return its table. |
| pack (...) | Pack arguments into a table. |
| lerp (a:, b:, t:, s:) | Get the lerp from a to b with a delta time t and a speed s. |
| serialize (object:) | Recursive function to serialize a table. |
| sort_pairs (tab:, comp:) | Pairs through a table sorted by a comparative function. |
| itermatrix (w:, h:) | Iterate through a x and y of a matrix with width w and height h. |
| split_file_path (file_path:) | Returns the path, filename and extension. |
| map (fun:, tab:) | Map a function to a table. |
Functions
- read_table (file_path:)
-
Read a lua-like file and return its table.
Parameters:
- file_path: The path of the file to read.
- pack (...)
-
Pack arguments into a table.
Parameters:
- ...
- lerp (a:, b:, t:, s:)
-
Get the lerp from a to b with a delta time t and a speed s.
Parameters:
- a: The a to go from.
- b: The b to go to.
- t: The time elapsed since last update.
- s: The speed of the movement.
- serialize (object:)
-
Recursive function to serialize a table.
Parameters:
- object: The object to serialize.
- sort_pairs (tab:, comp:)
-
Pairs through a table sorted by a comparative function.
Parameters:
- tab: The table to sort and iterate.
- comp: A comparative function to use for sorting.
- itermatrix (w:, h:)
-
Iterate through a x and y of a matrix with width w and height h.
Parameters:
- w: The width of the matrix.
- h: The height of the matrix.
- split_file_path (file_path:)
-
Returns the path, filename and extension.
Parameters:
- file_path: The path of the file.
- map (fun:, tab:)
-
Map a function to a table.
Parameters:
- fun: The function to map.
- tab: The table to map a function to.


a window with
className: "popup_effect1"
Open a window
with:
className: "popup_effect2", duration: 2, fromOpacity: 0.2, toOpacity: 0.4
It works also with moodal window


Stanford Language and Cognition Lab
Instructions
Meet the animals!
|
Monkey |
Bunny |
Dog |
Elephant |
Pig |
Bear |
|
Mouse |
Beaver |
Cat |
Sheep |
Tiger |
Frog |
|
You finished the training In the experiment, you will encounter new kinds of toys. Try your best to find out which toy they want. |
||
|
|
{{}}
{{}}
Thank you for participating!


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| CSC 1020 - 001 Computing and the Web CRN: 23151 Enrollment: FULL 30 students. |
|---|
|
Days:
M
from 10:30 am to 12:20 pm
in MENDEL G86.
TR
from 10:00 am to 10:50 am
in MENDEL 154.
Instructors: Barbara Hoffman Zimmerman (P), Barbara Hoffman Zimmerman Restrictions: Must be enrolled in one of the following Levels: Undergraduate |
| CSC 1020 - 002 Computing and the Web CRN: 23152 Enrollment: FULL 28 students. |
|
Days:
M
from 12:30 pm to 02:20 pm
in MENDEL G86.
TR
from 10:00 am to 10:50 am
in MENDEL 154.
Instructors: Barbara Hoffman Zimmerman (P), Barbara Hoffman Zimmerman Restrictions: Must be enrolled in one of the following Levels: Undergraduate |
| CSC 1020 - 003 Computing and the Web CRN: 23834 Enrollment: 27 of 28 students. |
|
Days:
M
from 02:30 pm to 04:30 pm
in MENDEL G86.
TR
from 10:00 am to 10:50 am
in MENDEL 154.
Instructors: Barbara Hoffman Zimmerman (P), Barbara Hoffman Zimmerman Restrictions: Must be enrolled in one of the following Levels: Undergraduate |
| CSC 1020 - 100 Computing and the Web CRN: 23153 Enrollment: 20 of 28 students. |
|
Days:
M
from 06:00 pm to 09:00 pm
in MENDEL G86.
Instructors: Frank I Klassner (P) Restrictions: Must be enrolled in one of the following Levels: Undergraduate |
| CSC 1020 - HLD Computing and the Web CRN: 23045 Enrollment: 0 of 100 students. |
|
Days:
Comment: Fake section - used for Freshman scheduling purposes Restrictions: Must be enrolled in one of the following Levels: Undergraduate |
| CSC 1035 - 001 Databases for Beginners CRN: 23154 Enrollment: FULL 28 students. |
|
Days:
TR
from 01:00 pm to 02:15 pm
in MENDEL G86.
Instructors: Don Goelman (P) Restrictions: Must be enrolled in one of the following Levels: Undergraduate |
| CSC 1035 - HLD Databases for Beginners CRN: 23652 Enrollment: 0 of 100 students. |
|
Days:
Comment: Fake section - used for Freshman scheduling purposes Restrictions: Must be enrolled in one of the following Levels: Undergraduate |
| CSC 1040 - 001 Computing with Images CRN: 23155 Enrollment: 27 of 28 students. |
|
Days:
MW
from 09:30 am to 11:20 am
in MENDEL G88.
Instructors: Mary Angela Papalaskari (P) Restrictions: Must be enrolled in one of the following Levels: Undergraduate |
| CSC 1040 - 002 Computing with Images CRN: 23156 Enrollment: 27 of 28 students. |
|
Days:
WF
from 11:30 am to 01:20 pm
in MENDEL G86.
Instructors: Mary Angela Papalaskari (P) Restrictions: Must be enrolled in one of the following Levels: Undergraduate |
| CSC 1040 - HLD Computing with Images CRN: 23046 Enrollment: 0 of 100 students. |
|
Days:
Comment: Fake section - used for Freshman scheduling purposes Restrictions: Must be enrolled in one of the following Levels: Undergraduate |
| CSC 1051 - 001 Algorithms & Data Struc I CRN: 23157 Enrollment: 18 of 28 students. |
|
Days:
MW
from 03:00 pm to 04:15 pm
in MENDEL G87.
F
from 09:30 am to 10:20 am
in MENDEL G86.
Instructors: Daniel T. Joyce , Daniel T. Joyce (P) Restrictions: Must be enrolled in one of the following Levels: Undergraduate |
| CSC 1051 - 002 Algorithms & Data Struc I CRN: 23159 Enrollment: FULL 28 students. |
|
Days:
TR
from 11:30 am to 12:45 pm
in MENDEL G86.
F
from 10:30 am to 11:20 am
in MENDEL G86.
Instructors: Daniel T. Joyce (P) Restrictions: Must be enrolled in one of the following Levels: Undergraduate |
| CSC 1051 - 100 Algorithms & Data Struc I CRN: 23160 Enrollment: 18 of 20 students. |
|
Days:
MW
from 06:00 pm to 07:50 pm
in MENDEL G87.
Instructors: Nancy Bercich (P) Restrictions: Must be enrolled in one of the following Levels: Undergraduate |
| CSC 1052 - 100 Algorithms & Data Struc II CRN: 23161 Enrollment: FULL 22 students. |
|
Days:
TR
from 06:00 pm to 07:50 pm
in MENDEL G87.
Instructors: Jason E. Dobies (P) Restrictions: Must be enrolled in one of the following Levels: Undergraduate Prerequisites: CSC 1051 |
| CSC 1600 - 001 Operating Systems CRN: 23163 Enrollment: 27 of 28 students. |
|
Days:
TR
from 11:30 am to 12:45 pm
in MENDEL G87.
Instructors: Mirela Damian-Iordache (P) Restrictions: Must be enrolled in one of the following Levels: Undergraduate Prerequisites: CSC 2400 or ECE 2042 |
| CSC 1800 - 001 Organ of Prog Languages CRN: 23164 Enrollment: 20 of 28 students. |
|
Days:
MW
from 03:00 pm to 04:15 pm
in MENDEL G88.
Instructors: Vijay Gehlot (P) Restrictions: Must be enrolled in one of the following Levels: Undergraduate Prerequisites: CSC 1052 and ( CSC 1300 or MAT 2600) |
| CSC 1990 - 001 Enrichment Sem in Computing CRN: 23165 Enrollment: 13 of 20 students. |
|
Days:
M
from 04:30 pm to 05:45 pm
in DRSCLL 244.
Instructors: Frank I Klassner (P) Restrictions: Must be enrolled in one of the following Levels: Undergraduate |
| CSC 1990 - 002 Enrichment Sem in Computing CRN: 23166 Enrollment: FULL 20 students. |
|
Days:
M
from 04:30 pm to 05:45 pm
in DRSCLL 244.
Instructors: Frank I Klassner (P) Restrictions: Must be enrolled in one of the following Levels: Undergraduate |
| CSC 2020 - 100 Web Devel & Tech I CRN: 23167 Enrollment: FULL 22 students. |
|
Days:
R
from 06:00 pm to 08:45 pm
in MENDEL G88.
Instructors: Najib Nadi (P) Comment: No CSC majors Restrictions: Must be enrolled in one of the following Levels: Undergraduate May not be enrolled in one of the following Majors: Computer Science Prerequisites: CSC 1020 |
| CSC 2053 - 001 Alg & Data Structures III CRN: 23168 Enrollment: 15 of 28 students. |
|
Days:
TR
from 02:30 pm to 03:45 pm
in MENDEL G86.
Instructors: Catherine L. Helwig (P) Restrictions: Must be enrolled in one of the following Levels: Undergraduate Prerequisites: CSC 1052 and ( CSC 1300 or MAT 2600) |
| CSC 2400 - 001 Computer Systems I CRN: 23170 Enrollment: 18 of 28 students. |
|
Days:
MWF
from 09:30 am to 10:20 am
in MENDEL G87.
Instructors: Mirela Damian-Iordache (P) Restrictions: Must be enrolled in one of the following Levels: Undergraduate Prerequisites: CSC 1300 |
| CSC 2993 - 001 Internship in Computing CRN: 23338 Enrollment: 0 of 5 students. |
|
Days:
TBA
Location: TBA
Instructors: Robert E. Beck (P) Comment: Permission of Chairperson required; Restrictions: Must be enrolled in one of the following Levels: Undergraduate |
| CSC 2993 - VAB Internship in Computing CRN: 23339 Enrollment: 2 of 5 students. |
|
Days:
TBA
Location: TBA
Instructors: Robert E. Beck (P) Comment: Permission of Chairperson required; Vatican Program; Restrictions: Must be enrolled in one of the following Levels: Undergraduate |
| CSC 3990 - 001 Computing Research Topics CRN: 23171 Enrollment: 17 of 20 students. |
|
Days:
MW
from 01:30 pm to 02:45 pm
in MENDEL G88.
Instructors: Thomas P. Way (P) Attributes: A&S Research Requirement, Writing Intensive Requirement Restrictions: Must be enrolled in one of the following Levels: Undergraduate Prerequisites: CSC 2053 |
| CSC 4170 - 001 Theory of Computation CRN: 23172 Enrollment: 18 of 35 students. |
|
Days:
TR
from 01:00 pm to 02:15 pm
in JBARRY 201A.
Instructors: Giorgi Japaridze (P) Restrictions: Must be enrolled in one of the following Levels: Undergraduate Prerequisites: CSC 1700 |
| CSC 4480 - 001 Principles of Database Systems CRN: 23173 Enrollment: 12 of 28 students. |
|
Days:
TR
from 04:00 pm to 05:15 pm
in MENDEL G88.
Instructors: Don Goelman (P) Restrictions: Must be enrolled in one of the following Levels: Undergraduate Prerequisites: CSC 2053 Concurrency: Yes |
| CSC 4710 - 100 Info Syst Project Management CRN: 23200 Enrollment: 23 of 25 students. |
|
Days:
W
from 06:00 pm to 09:30 pm
in MENDEL G86.
Instructors: Jill S. Tilney (P) Attributes: Fast Forward Course Comment: FastForward 2; Course Dates: 10/21 - 12/9; Restricted to Part-Time Studies Students; Restrictions: Must be enrolled in one of the following Levels: Undergraduate Must be enrolled in one of the following Colleges: Part Time Studies |
| CSC 4790 - 001 Senior Projects CRN: 23175 Enrollment: 8 of 20 students. |
|
Days:
MWF
from 12:30 pm to 01:20 pm
in MENDEL 290.
Instructors: Robert E. Beck (P) Attributes: Writing Enriched Requirement Restrictions: Must be enrolled in one of the following Levels: Undergraduate Prerequisites: CSC 4700 |
| CSC 5930 - 100 Top:Safeware-Comp & Sys Safety CRN: 23176 Enrollment: 4 of 20 students. |
|
Days:
R
from 06:15 pm to 09:00 pm
in MENDEL G90.
Instructors: William M. Fleischman (P) Restrictions: Must be enrolled in one of the following Levels: Undergraduate |
| CSC 5993 - 001 Independent Study CRN: 23177 Enrollment: 0 of 5 students. |
|
Days:
TBA
Location: TBA
Restrictions: Must be enrolled in one of the following Levels: Undergraduate |
| CSC 5993 - 002 Independent Study CRN: 23178 Enrollment: 0 of 5 students. |
|
Days:
TBA
Location: TBA
Restrictions: Must be enrolled in one of the following Levels: Undergraduate |
| CSC 8000 - 001 Found of Algor & Data Struc CRN: 23179 Enrollment: 12 of 20 students. |
|
Days:
T
from 06:15 pm to 07:30 pm
in MENDEL G88.
R
from 06:15 pm to 07:30 pm
in MENDEL G86.
Instructors: Catherine L. Helwig (P) Restrictions: Must be enrolled in one of the following Levels: Graduate Arts and Sciences |
| CSC 8400 - 001 Computer Systems CRN: 23182 Enrollment: FULL 22 students. |
|
Days:
W
from 06:15 pm to 09:00 pm
in MENDEL G88.
Instructors: Thomas P. Way (P) Restrictions: Must be enrolled in one of the following Levels: Graduate Arts and Sciences |
| CSC 8490 - 001 Database Systems CRN: 23183 Enrollment: 18 of 20 students. |
|
Days:
T
from 06:15 pm to 09:00 pm
in MENDEL 258.
Instructors: Don Goelman (P) Restrictions: Must be enrolled in one of the following Levels: Graduate Arts and Sciences Prerequisites: ( CSC 8301 and CSC 8410) |
| CSC 8491 - 001 Data Mining & DB Programming CRN: 23184 Enrollment: FULL 20 students. |
|
Days:
R
from 06:15 pm to 09:00 pm
in MENDEL G92.
Instructors: James A. Dullea (P) Restrictions: Must be enrolled in one of the following Levels: Graduate Arts and Sciences |
| CSC 8510 - 001 Theory of Computability CRN: 23185 Enrollment: FULL 26 students. |
|
Days:
T
from 06:15 pm to 09:00 pm
in MENDEL G92.
Instructors: Giorgi Japaridze (P) Restrictions: Must be enrolled in one of the following Levels: Graduate Arts and Sciences Prerequisites: CSC 8301 |
| CSC 8530 - 001 Distributed Systems CRN: 23186 Enrollment: 12 of 20 students. |
|
Days:
W
from 06:15 pm to 09:00 pm
in MENDEL G90.
Instructors: Paul A. Schragger (P) Restrictions: Must be enrolled in one of the following Levels: Graduate Arts and Sciences Prerequisites: ( CSC 8301 and CSC 8410) |
| CSC 8540 - 001 Software Engineering CRN: 23187 Enrollment: FULL 21 students. |
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Days:
M
from 06:15 pm to 09:00 pm
in MENDEL G90.
Instructors: Kristin Erica Obermyer (P) Restrictions: Must be enrolled in one of the following Levels: Graduate Arts and Sciences |
| CSC 8542 - 001 Software Design and Evolution CRN: 23188 Enrollment: 12 of 20 students. |
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Days:
W
from 06:15 pm to 09:00 pm
in MENDEL G92.
Instructors: Bruce Weir (P) Restrictions: Must be enrolled in one of the following Levels: Graduate Arts and Sciences |
| CSC 8990 - 001 Graduate Computing Practicum CRN: 23189 Enrollment: 1 of 20 students. |
|
Days:
TBA
Location: TBA
Instructors: Vijay Gehlot (P) Restrictions: Must be enrolled in one of the following Levels: Graduate Arts and Sciences |
| CSC 8991 - 001 Grad Practicum Continuation CRN: 23190 Enrollment: 5 of 20 students. |
|
Days:
TBA
Location: TBA
Instructors: Vijay Gehlot (P) Restrictions: Must be enrolled in one of the following Levels: Graduate Arts and Sciences |
| CSC 9000 - 001 Guided Study CRN: 23191 Enrollment: FULL 5 students. |
|
Days:
TBA
Location: TBA
Instructors: Vijay Gehlot (P) Comment: Approval by the Graduate Director required Restrictions: Must be enrolled in one of the following Levels: Graduate Arts and Sciences |
| CSC 9000 - 002 Guided Study CRN: 23880 Enrollment: FULL 5 students. |
|
Days:
TBA
Location: TBA
Instructors: Najib Nadi (P) Comment: Approval by the Graduate Director required; Restrictions: Must be enrolled in one of the following Levels: Graduate Arts and Sciences |
| CSC 9010 - 002 TOP: Digital Libraries CRN: 23193 Enrollment: 15 of 20 students. |
|
Days:
M
from 06:15 pm to 09:00 pm
in MENDEL G88.
Instructors: Lillian Cassel (P) Restrictions: Must be enrolled in one of the following Levels: Graduate Arts and Sciences |
| CSC 9010 - 003 TOP:Safeware-Comp & Sys Safety CRN: 23194 Enrollment: 5 of 15 students. |
|
Days:
R
from 06:15 pm to 09:00 pm
in MENDEL G90.
Instructors: William M. Fleischman (P) Restrictions: Must be enrolled in one of the following Levels: Graduate Arts and Sciences |
| CSC 9020 - 001 Independent Study CRN: 23195 Enrollment: FULL 11 students. |
|
Days:
TBA
Location: TBA
Instructors: Daniel T. Joyce , Thomas P. Way (P) Restrictions: Must be enrolled in one of the following Levels: Graduate Arts and Sciences |
| CSC 9020 - 002 Independent Study CRN: 23196 Enrollment: 9 of 10 students. |
|
Days:
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Location: TBA
Instructors: Daniel T. Joyce , James A. Dullea (P) Restrictions: Must be enrolled in one of the following Levels: Graduate Arts and Sciences |
| CSC 9020 - 003 Independent Study CRN: 23197 Enrollment: 3 of 10 students. |
|
Days:
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Location: TBA
Instructors: Daniel T. Joyce (P) Restrictions: Must be enrolled in one of the following Levels: Graduate Arts and Sciences |
| CSC 9021 - 001 Independent Study Continuation CRN: 23198 Enrollment: 18 of 20 students. |
|
Days:
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| CSC 9030 - 001 Thesis Direction CRN: 23469 Enrollment: 1 of 10 students. |
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Instructors: Daniel T. Joyce (P) Restrictions: Must be enrolled in one of the following Levels: Graduate Arts and Sciences |
| CSC 9080 - 001 Thesis Continuation CRN: 23199 Enrollment: 1 of 10 students. |
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Of course when you get to the "How" page, it is just a static explanation of how the extension works and doesn't need the button up there at all, so on that page I hide it like this.
<form>
<input type = "hidden" name = "TbBModHIDE_help" value = "true" />
</form>
Things to remember!
-Button must have unique id attribute!
-Don't forget to link it to a generic page.
-No extra form needed if page is, or already has form. Just add the hidden inputs to it.
-Naming convention for inputs is "TbBModOPTION_buttonId"
-Options are HIDE, TEXT, and HREF
TbBMod can be used on internal(#link) or external AJAX pages
-You can change the button link to internal(#link) or external AJAX pages
-The ability to mod the Back Button is coming!!!!


parts = signal.split(".")
path = ".".join(parts[:-1])
__import__(path)
signals[parts[-1]] = getattr(sys.modules[path], parts[-1])
return signals
signals = property(signals)
extra_signals = []
for signal in extra_signals:
mod_path, signal_name = signal.rsplit(".", 1)
signals_mod = import_module(mod_path)
signals[signal_name] = getattr(signals_mod, signal_name)
return signals
def process_response(self, request, response):


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Guillaume Calmettes
To answer a question about a population (of data).
In a perfect world, we would have access to the full population so we would be able to answer the question based on data collected on all the observational units of the population. We would know the value of the true parameter we are interested in.
But usually we just have one sample.
Statistics is about using that single sample to make inferences about the population parameter.
Let's consider that we are in charge of running a new health campaign that targets the students of a particular school. This school has 500 students. We want to know if using TV ads would be an efficient way of making the students aware of this new campaign.
One parameter that could be of interest to answer this question is the average time a student spend per quarter watching TV.
If we could collect data on all the students, then the data would look like this:
We only have a limited budget ($\$$60) to investigate our question ("What is the value of $\mu$?"), and it costs $\$$10/student to collect information.
We randomly select 6 students in the school to obtain a representative sample we can work with. From this sample (n=6) we calculate the average time spent per student watching TV per quarter (if representative sample, $\bar{x}\approx\mu$).
If we had randomly selected another sample, the value of $\bar{x}$ obtained would have been a bit different (but still $\bar{x}\approx\mu$).
Lots of possible different samples from the
population, lots of slightly different
values for the statistics of interest ($\bar{x}\approx\mu$).
All of these possible statistics of interest define the
sampling distribution of the statistic.
Any statistical test/procedure relies on the sampling distribution:
In the case of a null hypothesis significance testing, we are interested in the sampling distribution of the statistic of interest of the null hypothesis we are testing.
When we want to determine an estimate (confidence intervals) of a parameter of interest, we are interested in the sampling distribution of the sample statistic.
What is the probability that the statistic I calculated from my sample(s) comes from the sampling distribution of the null hypothesis? (p-value)
What would be a range of possible values for the parameter of interest? (This estimate depends on how variable the sampling distribution of the statistic is)
When we perform a null hypothesis test on a one-sample dataset, we are usually interested in knowing if the parameter of the population our sample is coming from is different from a specific value.
Categorical sample: the sampling distribution we are comparing our statistic to is usually linked to a chance model with a specific probability of success.
Quantitative sample: unless we have a specific model for the null hypothesis we want to compare our sample to, then we cannot really generate a reliable null sampling distribution without making strong assumptions.
Ex: we have a machine generating series of numbers, and
we want to know if a particular series of numbers that we
found could have come from this machine.
generate
the sampling distribution of $\bar{x}$ (from samples obtained from the machine) and assess the likelyhood of our original
sample $\bar{x}$ to come from this distribution.
When performing a two-sample null hypothesis test, the question is usually whether we can consider the two samples as different (coming from different populations). We can characterize this difference using the sampling distribution of a single statistic of interest:
Categorical samples: the difference in conditional proportions ($\overset{\hat{}}{p}_1-\overset{\hat{}}{p}_2$), or the relative risk ($\frac{\overset{\hat{}}{p}_1}{\overset{\hat{}}{p}_2}$).
Quantitative samples: the difference in mean/median ($\bar{x}_1-\bar{x}_2$, $m_1-m_2$) or the ratio of the mean/median ($\frac{\bar{x}_1}{\bar{x}_2}$, $\frac{m_1}{m_2}$)
Difference between the observed statistic and the null hypothesis parameter value ($\overset{\hat{}}{p}-\pi_0$)
Sample size
Whether we do a one- or two-sided test
How accurate is your sampling distribution
NHST is all nice and sweet, but in the end, we spend time answering a question coming from the "wrong angle": instead on focusing on what our data are, we focus on where our data would stand if the null hypothesis was true.
Determining confidence intervals is a way at looking at the same thing than NHST, but using what we know (observed statistic), not an hypothesized situation ("what would [something] be if [something]").
But again, this involves looking directly at the sampling distribution of your statistic of interest! (obtained directly from the population of your data, not an hypothesized null distribution)
We want to determine the sampling distribution of our statistic of interest, to know how variable it is and get an estimate of the true value of the parameter.
We do not have the full population, so we are using the sample as a surrogate for the population (bootstrap resampling, with replacement).
The sampling distribution obtained will be centered at the statistic of interest calculated from the original sample(s).
The $\alpha$ level chosen will determine which interval to consider.
Estimate of the true value of the parameter
Can be used for hypothesis testing
Is the parameter of the
null distribution inside the confidence interval?
The different possible study designs
Collection of data:
Observational unit: one word
Variable or interest: length of the word
Analysis of data:
Observational unit: one set of 10 words
Variable of interest: average word length in the set


A societal issue is a problem that influences a considerable number of individuals within a society. It is often the consequence of factors extending beyond an individual's control, and is the source of a conflicting opinion on the grounds of what is perceived as a morally just personal life or societal order. Outside the political process, people donate or share their time, money, energy, or other resources. This often takes the form of volunteering. Nonprofit organizations are often formed for the sole purpose of solving a social issue. Community organizing involves gathering people together for a common purpose.
Advertising
Mumbai: Armed with roses, 35 kids fight against child labour, sensitise mill owners
35 children are part of an initiative to curb child labour, started by the Mumbai Police along with the Labour Commission and two NGOs. Launched on Children’s Day, the six-day campaign aims to convey a message among factory and hotel owners to stop employing children. The children will offer roses to these owners of commercial establishments to sensitise them.Dressed in a pink frock, a nine-year-old girl presented a pink rose to the owner of a mill, manufacturing leather bags in Dharavi, on Wednesday morning. “Bachho ko kaam pe mat rakho, uncle… Unko ko padhao or behtar banao (Don’t make children work, help them get education to improve their lives),” she said.


CITY OF JOY A film review by Jaideep Mukherjee Copyright 1992 Jaideep Mukherjee
There is no gainsaying the fact that looking at a society from a distance can often provide new insights into its underlying dynamics. However, when a disproportionate amount of attention is paid to the observer-observed interface, all too often, the messenger becomes more important than the message.
This is what happens in CITY OF JOY almost right from the word "go." Employing a footage that seems suspiciously contrived (smelt like herring to me) to produce shock in a Western audience, Roland Joffe proceeds to tell a story of the triumph of Western optimism and enterprise over a thousand years' worth of superstition and passivity in a "cesspool of a country."
A Texas doctor (Patrick Swayze) chooses to seek the meaning of life in a foreign land, after realising he can't handle death. Having reached his destination, Calcutta, he quickly learns that salvation does not lie in winning speed drinking contests with teenage prostitutes (okay, so she was 20) but in confronting the evils of destitution and hopelessness that seem to be endemic in this "City of Joy." With a little help from a British nurse (Pauline Collins), he manages to rescue assorted poor people (rickshaw pullers, lepers, etc.) from the clutches of the local don (Shyamanand Jalan) and his crony, played by Art Malik. (Clearly not an idea as ridiculous, as say, the big B singlehandedly liberating Goa from Portugese occupation, but this is not a Hindi Movie, right :-) ).
The histrionic abilities of Swayze and Collins, if they exist, were carefully concealed from this viewer, thanks to a decidedly underwhelming script. The underutilization of an extremely talented cast was a pity though. Shabana Azmi, Om Puri, Shyamanand Jalan, Rudraprasad Sengupta, Anjan Datta, Pavan Malhotra et al have all acted in better productions than this one.
I did not find the basic premise of the film disagreeable simply because it attempts to reinforce the all too familiar stereotype of white folks delivering coloured people from their collective misery. In many Indian films, and even in real life, one encounters this idea in a different form. Only there the operating premise seems to be that doing away with poverty, inequality and exploitation involves shoving superior morals down the unwilling throats of the huddled masses.
This point of view fails to recognize that people's values are, up to a large measure, determined by objective economic conditions. Based on similar economic situations, people tend to polarize into self-contained societal pockets within which values are roughly constant. In my book a film, which pretends to deal with marginalized people as its subject, is a success only when it recognizes the above dynamic. By this yardstick, I would rate Susman and Mandi (both Shyam Benegal) as examples of successful movies made in this category.
I don't know why, but as I was walking out of the hall after seeing this film, I found myself thinking that renaming that street with the American Consulate after Uncle Ho wasn't such a bad thing, after all.
Jaideep
.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


We are team of creatively diverse. driven. innovative individuals working in various locations from the world


The jmap
command-line utility prints memory-related statistics for a running VM or core file.
The utility can also use the jsadebugd
daemon to query a process or core file on a remote machine. Note: The output takes longer to print in this case.
The release of JDK 8 introduced Java Mission Control, Java Flight Recorder, and jcmd
utility for diagnosing problems with JVM and Java applications. It is suggested to use the latest utility, jcmd
instead of the previous jmap
utility for enhanced diagnostics and reduced performance overhead.
If jmap
is used with a process or core file without any command-line options, then it prints the list of shared objects loaded (the output is similar to the pmap
utility on Oracle Solaris operating system). For more specific information, you can use the options -heap
, -histo
, or -permstat
. These options are described in the subsections that follow.
In addition, the JDK 7 release introduced the -dump:format=b,file=
filename option, which causes jmap
to dump the Java heap in binary HPROF format to a specified file. This file can then be analyzed with the jhat
tool.
If the jmap
pid command does not respond because of a hung process, then the -F
option can be used (on Oracle Solaris and Linux operating systems only) to force the use of the Serviceability Agent.
For more details on the jmap
utility, see the jmap
command man page.
The following sections describe jmap
command usage and troubleshooting techniques with examples that print memory-related statistics for a running VM or a core file.
The -heap
option is used to obtain the following Java heap information:
Information specific to the garbage collection (GC) algorithm, including the name of the GC algorithm (for example, parallel GC) and algorithm-specific details (such as number of threads for parallel GC).
Heap configuration that might have been specified as command-line options or selected by the VM based on the machine configuration.
Heap usage summary: For each generation (area of the heap), the tool prints the total heap capacity, in-use memory, and available free memory. If a generation is organized as a collection of spaces (for example, the new generation), then a space specific memory size summary is included.
Example 2-22 shows output from the jmap -heap
command.
Example 2-22 Java Heap Information from jmap -heap Command
$ jmap -heap 29620
Attaching to process ID 29620, please wait...
Debugger attached successfully.
Client compiler detected.
JVM version is 1.6.0-rc-b100
using thread-local object allocation.
Mark Sweep Compact GC
Heap Configuration:
MinHeapFreeRatio = 40
MaxHeapFreeRatio = 70
MaxHeapSize = 67108864 (64.0MB)
NewSize = 2228224 (2.125MB)
MaxNewSize =<PHONE_NUMBER> (4095.9375MB)
OldSize = 4194304 (4.0MB)
NewRatio = 8
SurvivorRatio = 8
PermSize = 12582912 (12.0MB)
MaxPermSize = 67108864 (64.0MB)
Heap Usage:
New Generation (Eden + 1 Survivor Space):
capacity = 2031616 (1.9375MB)
used = 70984 (0.06769561767578125MB)
free = 1960632 (1.8698043823242188MB)
3.4939673639112905% used
Eden Space:
capacity = 1835008 (1.75MB)
used = 36152 (0.03447723388671875MB)
free = 1798856 (1.7155227661132812MB)
1.9701276506696428% used
From Space:
capacity = 196608 (0.1875MB)
used = 34832 (0.0332183837890625MB)
free = 161776 (0.1542816162109375MB)
17.716471354166668% used
To Space:
capacity = 196608 (0.1875MB)
used = 0 (0.0MB)
free = 196608 (0.1875MB)
0.0% used
tenured generation:
capacity = 15966208 (15.2265625MB)
used = 9577760 (9.134063720703125MB)
free = 6388448 (6.092498779296875MB)
59.98769400974859% used
Perm Generation:
capacity = 12582912 (12.0MB)
used = 1469408 (1.401336669921875MB)
free = 11113504 (10.598663330078125MB)
11.677805582682291% used
The jmap
command with the -histo
option can be used to obtain a class specific histogram of the heap. Depending on the parameter specified, the jmap -histo
command can print out the heap histogram for a running process or a core file.
When the command is executed on a running process, the tool prints the number of objects, memory size in bytes, and fully qualified class name for each class. Internal classes in the Java HotSpot VM are enclosed in angle brackets. The histogram is useful in understanding how the heap is used. To get the size of an object, you must divide the total size by the count of that object type.
Example 2-23 shows output from the jmap -histo
command when it is executed on a process with PID number 29620.
Example 2-23 Class Specific Histogram of Java Heap for a Process
$ jmap -histo 29620
num #instances #bytes class name
--------------------------------------
1: 1414 6013016 [I
2: 793 482888 [B
3: 2502 334928 <constMethodKlass>
4: 280 274976 <instanceKlassKlass>
5: 324 227152 [D
6: 2502 200896 <methodKlass>
7: 2094 187496 [C
8: 280 172248 <constantPoolKlass>
9: 3767 139000 [Ljava.lang.Object;
10: 260 122416 <constantPoolCacheKlass>
11: 3304 112864 <symbolKlass>
12: 160 72960 java2d.Tools$3
13: 192 61440 <objArrayKlassKlass>
14: 219 55640 [F
15: 2114 50736 java.lang.String
16: 2079 49896 java.util.HashMap$Entry
17: 528 48344 [S
18: 1940 46560 java.util.Hashtable$Entry
19: 481 46176 java.lang.Class
20: 92 43424 javax.swing.plaf.metal.MetalScrollButton
... more lines removed here to reduce output...
1118: 1 8 java.util.Hashtable$EmptyIterator
1119: 1 8 sun.java2d.pipe.SolidTextRenderer
Total 61297 10152040
When the jmap -histo
command is executed on a core file, the tool prints the size, count, and class name for each class. Internal classes in the Java HotSpot VM are prefixed with an asterisk (*).
Example 2-24 shows output of the jmap -histo
command when it is executed on a core file.
Example 2-24 Histogram of Java Heap for a Core File
& jmap -histo /net/koori.sfbay/onestop/jdk/6.0/promoted/all/b100/binaries/solaris-sparcv9/bin/java core
Attaching to core core from executable /net/koori.sfbay/onestop/jdk/6.0/
promoted/all/b100/binaries/solaris-sparcv9/bin/java, please wait...
Debugger attached successfully.
Server compiler detected.
JVM version is 1.6.0-rc-b100
Iterating over heap. This may take a while...
Heap traversal took 8.902 seconds.
Object Histogram:
Size Count Class description
-------------------------------------------------------
4151816 2941 int[]
2997816 26403 * ConstMethodKlass
2118728 26403 * MethodKlass
1613184 39750 * SymbolKlass
1268896 2011 * ConstantPoolKlass
1097040 2011 * InstanceKlassKlass
882048 1906 * ConstantPoolCacheKlass
758424 7572 char[]
733776 2518 byte[]
252240 3260 short[]
214944 2239 java.lang.Class
177448 3341 * System ObjArray
176832 7368 java.lang.String
137792 3756 java.lang.Object[]
121744 74 long[]
72960 160 java2d.Tools$3
63680 199 * ObjArrayKlassKlass
53264 158 float[]
... more lines removed here to reduce output...
The permanent generation is the area of the heap that holds all the reflective data of the virtual machine itself, such as class and method objects. This area is also called "method area" in The Java Virtual Machine Specification.
Configuring the size of the permanent generation can be important for applications that dynamically generate and load a very large number of classes (for example, Java Server Pages or web containers). If an application loads too many classes, then it is possible it will terminate with the following error:
Exception in thread thread_name java.lang.OutOfMemoryError: PermGen space
For a description of this and other variants of the OutOfMemoryError
exception, see Understand the OutOfMemoryError Exception.
To get further information about the permanent generation, you can use the -permstat
option of the jmap
command to print statistics for the objects in the permanent generation.
Example 2-25 shows output from the jmap -permstat
command executed on a process with PID number 29620.
Example 2-25 Permanent Generation Statistics of Java Heap for a Process
$ jmap -permstat 29620
Attaching to process ID 29620, please wait...
Debugger attached successfully.
Client compiler detected.


The devtools library is required for installation:
#install.packages("devtools") devtools::install_github("CrumpLab/vertical")
# initialize new project from console
vertical::vertical_project()
# build the website
vertical::build_vertical()
NOTE: after restarting RStudio, you can make a vertical project by choosing File > New Project… in RStudio, and choosing the Vertical Research Project template.
Read the getting started tutorial to learn more about using vertical
. And, watch vertical tutorials on youtube, still in progress adding more as we find time.
vertical
is a workflow for creating, curating, and communicating research assets in psychological science in the form of a website and/or R package. It is effectively a wrapper for suggesting R Markdown templates for creating various psych research assets, and suggesting the R Package standard to curate the assets. vertical
installs an RStudio project template with the vertical
workflow structure, and compiles content in a vertical
project to an R package and pkgdown website for sharing the assets.


Protest Locations
AbstractThis project was a data visualization exercise to map all the major BLM protest that have happened in the United States. The end result looks like the first picture on the left.
As seen in the second picture, every blue dot represents a protest and hovering over the data point launches a popup that details the location and some information about the protest. For example, when was the protest? how many people showed up? what was the protesting route? and, occasionally, what was the police responce like?
Lastly, the map also allows you to zoom into each state and see some of the previous protests that have happened in your state.
Full map on Github as map.html and data.txt can be found on kaggle.com


---
title: Interview Questions for Data Scientist Positions
date: '2015-07-14T19:00:13+05:30'
tags:
- ml
tumblr_url: https://sureshshanmugam.com/post/124066436714/interview-questions-for-data-scientist-positions
---
Interview Questions for Data Scientist Positions


A simple muzzle energy computer.
Requires JavaScript to function. Without JavaScript, this page is all you'll ever see.
GitHub


Dig into the code on GitHub
You can follow the work we do, be part of on-going discussions, and examine our improvement ideas on the GitHub issues page.
If you're a newcomer, check out the good first issue label.
If you're ready to jump in and add code, tests, or help with documentation, follow the guidelines in the contributing documentation.


Did you look for Bros Dynamics? Oh, we are just hatching...
Take your time and coffee. We are getting ready for you...


StrF()
语法
Result$ = StrF(Value.f [, NbDecimal])概要
Converts a float number into a string.
参数
Value.f The value to convert. NbDecimal (optional) The maximum number of decimal places for the converted number. If omitted, it will be set to 10 decimal places, with removing the trailing zeros. The number will be rounded, if 'NbDecimal' is smaller than existing decimal places of 'Value.f'.
返回值
A string holding the converted value.
备注
Signed integer numbers have to be converted with Str() and unsigned numbers with StrU(). It is possible to omit this command when concatenating string and float, it will then use the default behaviour of StrF().
示例
value.f = 10.54 Debug "Result: " + StrF(value) ; we do not use the 2nd parameter, so we get a float number rounded to 10 decimal places Debug "Result: " + value ; same as previous line Debug "Result: " + StrF(value,2) ; we want a result with two decimal places, no rounding needed as we have only two Debug "Result: " + StrF(value,0) ; we want a result with no decimal places, so the value is rounded
参阅
StrD(), Str(), StrU()
已支持操作系统
所有


Redirect Bing to Google
Redirect Search
Redirect Images
Redirect Videos
Redirect Maps
Redirect All Other Searches to the Google Homepage


FG releases lists of items exempted from VAT
by The Eagle OnlineThe Federal Government has announced exemption of basic food items, educational materials and medical supplies from Value Added Tax.
This was made known by the Minister of Finance, Zainab Ahmed, while justifying the proposed Finance Bill before the Senate Committee on Finance.
Ahmed said: “The bill proposes to introduce tax reform which will help government achieve its revenue projections for the 2020 budget.
“Some of these proposals include an increase in the VAT rate, moderation of inefficient and ineffective tax incentives and closing loopholes in the existing tax laws that allow tax avoidance resulting in tax revenue.
“The Finance Bill also proposes essential palliative to support MSME and mitigate the impact of the VAT rate increase on the most vulnerable businesses, communities and citizens in the economy.
“Some of these measures include: expanding the list of VAT-exempt items e.g. basic food items, educational materials and medical supplies.”
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A recipe is a set of instructions that describes how to prepare or make something, especially a dish of prepared food.
The term recipe is also used in medicine or in information technology (e.g., user acceptance). A doctor will usually begin a prescription with recipe, Latin for take, usually abbreviated as Rx or the equivalent symbol (℞).


Library ListFacts
Assorted facts about lists that are not in Coq's standard library.
Implicit arguments are declared by default in this library.
Implicit arguments are declared by default in this library.
Lemma cons_eq_app : ∀ (A : Type) (z : A) (xs ys zs : list A),
z :: zs = xs ++ ys →
(∃ qs, xs = z :: qs ∧ zs = qs ++ ys) ∨
(xs = nil ∧ ys = z :: zs).
Lemma app_eq_cons : ∀ (A : Type) (z : A) (xs ys zs : list A),
xs ++ ys = z :: zs →
(∃ qs, xs = z :: qs ∧ zs = qs ++ ys) ∨
(xs = nil ∧ ys = z :: zs).
Lemma nil_eq_app : ∀ (A : Type) (xs ys : list A),
nil = xs ++ ys →
xs = nil ∧ ys = nil.
Lemma app_cons_not_nil : ∀ (A : Type) (y : A) (xs ys : list A),
xs ++ y :: ys ≠ nil.
Lemma InA_In : ∀ (A : Type) (x : A) (xs : list A),
InA (@eq _) x xs → In x xs.
Lemma InA_iff_In : ∀ (A : Type) (x : A) (xs : list A),
InA (@eq _) x xs ↔ In x xs.
This page has been generated by coqdoc


It’s designed to help you create materials that look, sound and feel like Facebook IQ, no matter the audience.
This guide should be used in conjunction with Facebook's content standards and visual design guidelines.
Mission Statement Strategy Voice + Tone
Logo Color Typography
People Places Moments Video
Infographics Dot Grid Illustration Shapes Iconography Layering
Digital Print Signage & Swag


Robotic Arts Intro Fall 2017 (IA277.01)
- Instructor: Lucas Haroldsen<EMAIL_ADDRESS>- Class Site: yasunaga.work/raif17
- syllabus: syllabus.pdf
- Resources: links.html
09/12: Arduino is here --- [Connecting/Architecture/Digital IO]
How are your day bugs and night bugs?
First things first,
- Let's take a look at what everyone has done with the day bugs and night bugs!
- Documenting the bugs!
Today, we will go over together:
- What is arduino?
- Architecture (hardware) of arduino
- Overview of Arduino IDE (software)
- Basic coding structure
- What is a variable?
- Blinking LEDs with arduino
- Digital input and Digital output
- Conditional logic
- Using switches
and we we will work on:
- Using 2 or more digital outputs
- Using 2 or more switches
- Expanding simple switches
arduino documentary (2010)
Marshall McLuhan - The Medium Is The Message[1977]
arduino as a political object name arduino
Italian name arduino on first-names-meanings.com
Printer Shake by Joe Winter
Céleste Boursier
Ryota Kuwakubo
HOMEWORK
Handmade Switches
-
Make a simple circuit with arduino using the button sketch.
- 1 ---One that uses different parts of the body and its movements and gestures to be activated (other than a simple press)
- 2a --- uses tools or objects to be activated
- 2b --- needs two or more people to be activated
Design 2 switches:
and one that either:
or
Reading
- Medium from Abstracting Craft: The Practiced Digital Hand by Malcolm McCullough
- Come up with two questions from the reading


$var title: More examples
Since game.robots is a dictionary of robots with locations as keys and robots as values, you can use:
game.robots
(x, y) in game.robots
which is True if there's a robot at (x, y) and False otherwise.
True
(x, y)
False


{{ config.site_name }}
The Redis plugins for Grafana let you connect Grafana to Redis to
visualize more types of data in more ways than otherwise would be
possible.
All the increased functionality comes with a more streamlined
workflow.
Introduction
Quickstart


{% extends "auth/base.html" %} {% import "bootstrap/wtf.html" as wtf %} {% block title %}COMPEIT Dashboard - Log in{% endblock %} {% block page_content %}
Note that this is an early prototype and your user, settings and information may be deleted at any time.
This prototype is provided for piloting purposes and should not be used for activities where errors in its operation would cause significant harm. This service has been produced with the assistance of the European Union. Its functioning is however the sole responsibility of the COMPEIT consortium.


The TDAmeritradeFeeModel
models the fees of TD Ameritrade.
security.SetFeeModel(new TDAmeritradeFeeModel());
security.SetFeeModel(TDAmeritradeFeeModel())
The TDAmeritradeFeeModel
charges $0 USD for Equity trades.
To view the implementation of this model, see the LEAN GitHub repository.


| Methods' Summary |
| getAttribute |
Retrieves an attribute value by name.
|
| getAttributeNode |
Retrieves an attribute node by name.
|
| getAttributeNodeNS |
Retrieves an Attr node by local name and namespace URI.
|
| getAttributeNS |
Retrieves an attribute value by local name and namespace URI.
|
| getElementsByTagName |
Returns a NodeList of all descendant Elements with a given tag name,
in the order in which they are
encountered in a preorder traversal of this Element tree.
|
| getElementsByTagNameNS |
Returns a NodeList of all the descendant Elements with a given local
name and namespace URI in the order in which they are encountered in
a preorder traversal of this Element tree.
|
| getTagName |
The name of the element.
|
| hasAttribute |
Returns true when an attribute with a given name is specified on this
element or has a default value, false otherwise.
|
| hasAttributeNS |
Returns true when an attribute with a given local name and namespace
URI is specified on this element or has a default value, false otherwise.
|
| removeAttribute |
Removes an attribute by name.
Throws:
DOMException - NO_MODIFICATION_ALLOWED_ERR: Raised if this node is readonly.
|
| removeAttributeNode |
Removes the specified attribute node.
Throws:
DOMException - NO_MODIFICATION_ALLOWED_ERR: Raised if this node is readonly.
NOT_FOUND_ERR: Raised if oldAttr is not an attribute of the element.
|
| removeAttributeNS |
Removes an attribute by local name and namespace URI.
Throws:
DOMException - NO_MODIFICATION_ALLOWED_ERR: Raised if this node is readonly.
|
| setAttribute |
Adds a new attribute.
Throws:
DOMException - INVALID_CHARACTER_ERR: Raised if the specified name contains an illegal character.
NO_MODIFICATION_ALLOWED_ERR: Raised if this node is readonly.
|
| setAttributeNode |
Adds a new attribute node.
Throws:
DOMException - WRONG_DOCUMENT_ERR: Raised if newAttr was created from a different document than the one that created the element.
NO_MODIFICATION_ALLOWED_ERR: Raised if this node is readonly.
INUSE_ATTRIBUTE_ERR: Raised if newAttr is already an attribute of another Element object. The DOM user must explicitly clone Attr nodes to re-use them in other elements.
|
| setAttributeNodeNS |
Adds a new attribute.
Throws:
DOMException - WRONG_DOCUMENT_ERR: Raised if newAttr was created from a different document than the one that created the element.
NO_MODIFICATION_ALLOWED_ERR: Raised if this node is readonly.
INUSE_ATTRIBUTE_ERR: Raised if newAttr is already an attribute of another Element object. The DOM user must explicitly clone Attr nodes to re-use them in other elements.
NOT_SUPPORTED_ERR: Always thrown if the current document does not support the "XML" feature, since namespaces were defined by XML.
|
| setAttributeNS |
Adds a new attribute.
Throws:
DOMException - INVALID_CHARACTER_ERR: Raised if the specified qualified name contains an illegal character, per the XML 1.0 specification .
NO_MODIFICATION_ALLOWED_ERR: Raised if this node is readonly.
NAMESPACE_ERR: Raised if the qualifiedName is malformed per the Namespaces in XML specification, if the qualifiedName has a prefix and the namespaceURI is null, if the qualifiedName has a prefix that is "xml" and the namespaceURI is different from " http://www.w3.org/XML/1998/namespace", or if the qualifiedName, or its prefix, is "xmlns" and the namespaceURI is different from " http://www.w3.org/2000/xmlns/".
NOT_SUPPORTED_ERR: Always thrown if the current document does not support the "XML" feature, since namespaces were defined by XML.
|
| Methods' Details |
getAttribute
| string |
| getAttribute( |
[in] string |
name ); |
- Description
- Retrieves an attribute value by name.
|
|
getAttributeNode
| XAttr |
| getAttributeNode( |
[in] string |
name ); |
- Description
- Retrieves an attribute node by name.
|
|
getAttributeNodeNS
| XAttr |
| getAttributeNodeNS( |
[in] string |
namespaceURI, |
| [in] string |
localName ); |
- Description
- Retrieves an Attr node by local name and namespace URI.
|
|
getAttributeNS
| string |
| getAttributeNS( |
[in] string |
namespaceURI, |
| [in] string |
localName ); |
- Description
- Retrieves an attribute value by local name and namespace URI.
|
|
getElementsByTagName
| XNodeList |
| getElementsByTagName( |
[in] string |
name ); |
- Description
- Returns a NodeList of all descendant Elements with a given tag name,
in the order in which they are
encountered in a preorder traversal of this Element tree.
|
|
getElementsByTagNameNS
| XNodeList |
| getElementsByTagNameNS( |
[in] string |
namespaceURI, |
| [in] string |
localName ); |
- Description
- Returns a NodeList of all the descendant Elements with a given local
name and namespace URI in the order in which they are encountered in
a preorder traversal of this Element tree.
|
|
getTagName
- Description
- The name of the element.
|
|
hasAttribute
| boolean |
| hasAttribute( |
[in] string |
name ); |
- Description
- Returns true when an attribute with a given name is specified on this
element or has a default value, false otherwise.
|
|
hasAttributeNS
| boolean |
| hasAttributeNS( |
[in] string |
namespaceURI, |
| [in] string |
localName ); |
- Description
- Returns true when an attribute with a given local name and namespace
URI is specified on this element or has a default value, false otherwise.
|
|
removeAttribute
| void |
| removeAttribute( |
[in] string |
name ) |
| raises( |
DOMException ); |
- Description
- Removes an attribute by name.
Throws:
DOMException - NO_MODIFICATION_ALLOWED_ERR: Raised if this node is readonly.
|
|
removeAttributeNode
- Description
- Removes the specified attribute node.
Throws:
DOMException - NO_MODIFICATION_ALLOWED_ERR: Raised if this node is readonly.
NOT_FOUND_ERR: Raised if oldAttr is not an attribute of the element.
|
|
removeAttributeNS
| void |
| removeAttributeNS( |
[in] string |
namespaceURI, |
| [in] string |
localName ) |
| raises( |
DOMException ); |
- Description
- Removes an attribute by local name and namespace URI.
Throws:
DOMException - NO_MODIFICATION_ALLOWED_ERR: Raised if this node is readonly.
|
|
setAttribute
| void |
| setAttribute( |
[in] string |
name, |
| [in] string |
value ) |
| raises( |
DOMException ); |
- Description
- Adds a new attribute.
Throws:
DOMException - INVALID_CHARACTER_ERR: Raised if the specified name contains an illegal character.
NO_MODIFICATION_ALLOWED_ERR: Raised if this node is readonly.
|
|
setAttributeNode
- Description
- Adds a new attribute node.
Throws:
DOMException - WRONG_DOCUMENT_ERR: Raised if newAttr was created from a different document than the one that created the element.
NO_MODIFICATION_ALLOWED_ERR: Raised if this node is readonly.
INUSE_ATTRIBUTE_ERR: Raised if newAttr is already an attribute of another Element object. The DOM user must explicitly clone Attr nodes to re-use them in other elements.
|
|
setAttributeNodeNS
- Description
- Adds a new attribute.
Throws:
DOMException - WRONG_DOCUMENT_ERR: Raised if newAttr was created from a different document than the one that created the element.
NO_MODIFICATION_ALLOWED_ERR: Raised if this node is readonly.
INUSE_ATTRIBUTE_ERR: Raised if newAttr is already an attribute of another Element object. The DOM user must explicitly clone Attr nodes to re-use them in other elements.
NOT_SUPPORTED_ERR: Always thrown if the current document does not support the "XML" feature, since namespaces were defined by XML.
|
|
setAttributeNS
| void |
| setAttributeNS( |
[in] string |
namespaceURI, |
| [in] string |
qualifiedName, |
| [in] string |
value ) |
| raises( |
DOMException ); |
- Description
- Adds a new attribute.
Throws:
DOMException - INVALID_CHARACTER_ERR: Raised if the specified qualified name contains an illegal character, per the XML 1.0 specification .
NO_MODIFICATION_ALLOWED_ERR: Raised if this node is readonly.
NAMESPACE_ERR: Raised if the qualifiedName is malformed per the Namespaces in XML specification, if the qualifiedName has a prefix and the namespaceURI is null, if the qualifiedName has a prefix that is "xml" and the namespaceURI is different from " http://www.w3.org/XML/1998/namespace", or if the qualifiedName, or its prefix, is "xmlns" and the namespaceURI is different from " http://www.w3.org/2000/xmlns/".
NOT_SUPPORTED_ERR: Always thrown if the current document does not support the "XML" feature, since namespaces were defined by XML.
|
|
Copyright © 2013, The Apache Software Foundation, Licensed under the Apache License, Version 2.0. Apache, the Apache feather logo, Apache OpenOffice and OpenOffice.org are trademarks of The Apache Software Foundation. Other names may be trademarks of their respective owners.


| DOSE: |
8 hits |
oral |
LSD |
(liquid) |
It had been about 8 or 9 months since my last trip, and during that time I was constantly looking for acid. Finally, about 2 or 3 weeks ago a shitload of what I would find to be VERY strong acid came through town. So my friend A called me up and asked if I wanted to buy some and trip with him the next day. I, of course, agreed and we put our money together and purchased about 15 hits.
The next day, I went over to his house at about 10:00 AM and we ended up dropping at about 10:30 after his mom left for work. Right after we dropped we started to clear his room of anything that might scare us into a bad trip. After that we started listening to some music.
Suprisingly, I could feel it start to come on about 20 minutes after dropping. I was feeling giggly and lightheaded. We went into his living room and watched the ceiling wave and the streams of color flow through it.  This is when it gets a little fuzzy. Altough I was already tripping hard I could still feel it coming on stronger. Before J got there we went back to A's room and chilled. That is my last fully clear memory of the trip, but I also remember a few scattered things.
I remember J being in the room and laying on A's bed when J informs us that A's dad just got home. It was hard for me to understand what was going on, because I would see like a few little frames of what was happening, then I would fall into my trip, and then I would come back out and see a few more frames like time had completely stopped while I was in my deep trip. The next thing I remember is A begging J to take him to the hospital. Then I remember being outside and running around in A's front yard into bushes and stuff. Then I remember J holding onto me and I asked him if he was really J. He then asked me who I was and I told him I was my drug dealer N. Then I remember being on a porch swing and seeing the real N, some girl, some guy, and A naked in the backseat of a car. At the time I thought that these were all hallucinations, but I later found out that they were all real. Then we went in N's house and I came down at about 6 or 7 PM.
During my trip I thought that all of these things were a dream. There was even a period between running in A's front yard and sitting in the swing where J took me to his friend's house and I played with Christmas lights and could only say 'Whoa' and 'What?' that I don't remember at all. I later learned that I had eaten 8 hits of what was said to be REALLY good acid. A also neglected to mention that the dude he bought it from said we shouldn't take more than two. This experience taught me that LSD is way more powerful than I thought and to respect it. A has sworn off acid for good, I however will probably continue to explore my mind, but at much lower dosages.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


#primary_key
[ GitHub ]# File 'activerecord/lib/active_record/connection_adapters/abstract/schema_definitions.rb', line 133
def primary_key [:primary_key] || default_primary_key end
123456789_123456789_123456789_123456789_123456789_
| Relationships & Source Files | |
| Super Chains via Extension / Inclusion / Inheritance | |
|
Class Chain:
self,
::Struct
|
|
|
Instance Chain:
self,
::Struct
|
|
| Inherits: | Struct |
| Defined in: | activerecord/lib/active_record/connection_adapters/abstract/schema_definitions.rb |
Alias for #validate?.
::Struct
- InheritedBoolean
(readonly)
# File 'activerecord/lib/active_record/connection_adapters/abstract/schema_definitions.rb', line 149
def custom_primary_key? [:primary_key] != default_primary_key end
Boolean
(readonly)
# File 'activerecord/lib/active_record/connection_adapters/abstract/schema_definitions.rb', line 158
def export_name_on_schema_dump? !ActiveRecord::SchemaDumper.fk_ignore_pattern.match?(name) if name end
# File 'activerecord/lib/active_record/connection_adapters/abstract/schema_definitions.rb', line 124
ForeignKeyDefinition = Struct.new(:from_table, :to_table, : )
# File 'activerecord/lib/active_record/connection_adapters/abstract/schema_definitions.rb', line 124
ForeignKeyDefinition = Struct.new(:from_table, :to_table, : )
Boolean
(readonly)
Also known as: #validated?
# File 'activerecord/lib/active_record/connection_adapters/abstract/schema_definitions.rb', line 153
def validate? .fetch(:validate, true) end
Alias for #validate?.
# File 'activerecord/lib/active_record/connection_adapters/abstract/schema_definitions.rb', line 156
alias validated? validate?
# File 'activerecord/lib/active_record/connection_adapters/abstract/schema_definitions.rb', line 129
def column [:column] end
# File 'activerecord/lib/active_record/connection_adapters/abstract/schema_definitions.rb', line 169
def default_primary_key "id" end
# File 'activerecord/lib/active_record/connection_adapters/abstract/schema_definitions.rb', line 145
def deferrable [:deferrable] end
Boolean
# File 'activerecord/lib/active_record/connection_adapters/abstract/schema_definitions.rb', line 162
def defined_for?(to_table: nil, validate: nil, ** ) (to_table.nil? || to_table.to_s == self.to_table) && (validate.nil? || validate == self. .fetch(:validate, validate)) && .all? { |k, v| self. [k].to_s == v.to_s } end
# File 'activerecord/lib/active_record/connection_adapters/abstract/schema_definitions.rb', line 125
def name [:name] end
# File 'activerecord/lib/active_record/connection_adapters/abstract/schema_definitions.rb', line 137
def on_delete [:on_delete] end
# File 'activerecord/lib/active_record/connection_adapters/abstract/schema_definitions.rb', line 141
def on_update [:on_update] end
# File 'activerecord/lib/active_record/connection_adapters/abstract/schema_definitions.rb', line 133
def primary_key [:primary_key] || default_primary_key end


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{% extends "free_software.html" %} {% block logo %} {% endblock %} {% block software %}
G Suite is Google’s hosted product featuring all the Google Apps you’ve come to love: Gmail, Google Drive, Google Groups, and many more.
Users of G Suite for Nonprofits receive access to all Google Apps like Gmail, Drive, and Groups (up to 30 GB of file storage). The email service can be tied to a custom domain for your Brigade.
You will have an administrator ability to manage users and groups within your brigade.
We can set you up as an organization underneath Code for America’s G Suite for free. Email<EMAIL_ADDRESS>to get started.
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Although we believe that accounts will be isolated from each other, we ask that you never attempt to interact with the files or domains of other users. If you find a place where you can access other brigades' files, please report it to<EMAIL_ADDRESS>immediately.
{% endblock %}


This tests for a bug where centering two paragraphs would center the third. Only the selected paragraphs should be selected.


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Tag: {{ page.tag }}
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{% for post in site.posts %}
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According to documentation, arrays should be filterable
with `where_exp`, but I couldn't get it to work.
{%endcomment%}
{% if post.tags contains page.tag %}
{% include post_listing.html %}
{% endif %}
{% endfor %}


Here are the links for the demo 👇
- Dropdown button
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| optimx-package | A replacement and extension of the optim() function, plus various optimization tools |
| as.data.frame.optimx | General-purpose optimization |
| axsearch | Perform axial search around a supposed minimum and provide diagnostics |
| bmchk | Check bounds and masks for parameter constraints used in nonlinear optimization |
| bmstep | Compute the maximum step along a search direction. |
| checksolver | Test if requested solver is present |
| coef.opm | Summarize opm object |
| coef.optimx | Summarize opm object |
| coef<- | Summarize opm object |
| coef<-.opm | Summarize opm object |
| coef<-.optimx | Summarize opm object |
| ctrldefault | set control defaults |
| dispdefault | set control defaults |
| fnchk | Run tests, where possible, on user objective function |
| gHgen | Generate gradient and Hessian for a function at given parameters. |
| gHgenb | Generate gradient and Hessian for a function at given parameters. |
| grback | Backward difference numerical gradient approximation. |
| grcentral | Central difference numerical gradient approximation. |
| grchk | Run tests, where possible, on user objective function and (optionally) gradient and hessian |
| grfwd | Forward difference numerical gradient approximation. |
| grnd | A reorganization of the call to numDeriv grad() function. |
| hesschk | Run tests, where possible, on user objective function and (optionally) gradient and hessian |
| hjn | Compact R Implementation of Hooke and Jeeves Pattern Search Optimization |
| kktchk | Check Kuhn Karush Tucker conditions for a supposed function minimum |
| multistart | General-purpose optimization - multiple starts |
| opm | General-purpose optimization |
| optchk | General-purpose optimization |
| optimr | General-purpose optimization |
| optimx | General-purpose optimization |
| optsp | Forward difference numerical gradient approximation. |
| polyopt | General-purpose optimization - sequential application of methods |
| proptimr | Compact display of an 'optimr()' result object |
| Rcgmin | An R implementation of a nonlinear conjugate gradient algorithm with the Dai / Yuan update and restart. Based on Nash (1979) Algorithm 22 for its main structure. |
| Rcgminb | An R implementation of a bounded nonlinear conjugate gradient algorithm with the Dai / Yuan update and restart. Based on Nash (1979) Algorithm 22 for its main structure. CALL THIS VIA 'Rcgmin' AND DO NOT USE DIRECTLY. |
| Rcgminu | An R implementation of an unconstrained nonlinear conjugate gradient algorithm with the Dai / Yuan update and restart. Based on Nash (1979) Algorithm 22 for its main structure. CALL THIS VIA 'Rcgmin' AND DO NOT USE DIRECTLY. |
| Rvmmin | Variable metric nonlinear function minimization, driver. |
| Rvmminb | Variable metric nonlinear function minimization with bounds constraints |
| Rvmminu | Variable metric nonlinear function minimization, unconstrained |
| scalechk | Check the scale of the initial parameters and bounds input to an optimization code used in nonlinear optimization |
| snewton | Safeguarded Newton methods for function minimization using R functions. |
| snewtonm | Safeguarded Newton methods for function minimization using R functions. |
| summary.optimx | Summarize optimx object |
| tn | Truncated Newton minimization of an unconstrained function. |
| tnbc | Truncated Newton function minimization with bounds constraints |
| [.optimx | General-purpose optimization |


WITNESS LIST Jurisprudence Committee July 21, 2003 - 9:00A HB 3 AGAINST: Barnes, Michael (Self), Austin, TX Bartholomew, Dana (Self), Pflugerville, TX Blumberg, Mary (People of Texas), Austin, TX Fralin, Richard (Self), Austin, TX Gray, Diana (Self), Austin, TX Nickerson, Jim (Self), Pittsburg, TX Robbins, Paul (Self), Austin, TX Smith, Clinton (Gray Panthers of Texas), Austin, TX Strain, H.W. "Sputnik" (Self), Alvin, TX Thomas, Kathleen (my family), Austin, TX Wood, Marjorie (Self), Austin, TX Registering, but not testifying: Against: Bond, Joe (Self), Austin, TX Brownlee, Randy (Self), Austin, TX Cardenas, Roberto (Self), Austin, TX Clark-Bradley, Vicki (Self), Austin, TX Conner, Tiffany (Self), Austin, TX Harris, William (Self), Austin, TX Malewitz, Melanie (Self), Austin, TX Satagaj*, Sallie Ann (Self), Lockhart, TX Schwartz, Andrea (Self), Austin, TX Smith, Eleanor (Self), Austin, TX Smolinsky, Gerald (Self), Austin, TX Smolinsky, Marilyn (Self), Austin, TX Thomas, Jennifer (Self), Austin, TX HB 3 Witness List Notes ON: * (indicates illegible handwriting on witness affirmation cards)


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Obama Goes 'Japanese' $447 Billion Of New Infrastructure ...
By Jeff Harding, on September 8th, 2011. The President just finished his . banks that put us in recession. $447 Billion to be spent to pull us out of recession.
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The Great Depression, Great Recession, and Depression of 1920 ...
Aug 23, 2012 . As Woods wrote, [I]nstead of 'fiscal stimulus,' Harding cut the . stimulus projects, and easy money were to move the country out of recession.
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Limbaugh, Hannity ignore '80's interest rate cuts in prescribing ...
Feb 11, 2009 . The recession to which Hannity and Limbaugh referred began in July 1981 and . The only way you can say the tax cuts didn't lift us out of a recession is if you . And Coolidge and the great Warren Harding were successful.
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Reagan is inaugurated as the fortieth President of the United States. . Reagan lifts a grain embargo imposed on Soviet Union by President Carter. . Reagan orders the dismissal of 13,000 PATCO air traffic controllers out on strike, citing their . dramatic growth for the first quarter of 1983, signaling the end of the recession.
http://millercenter.org/president/keyevents/reagan
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We were known as a very good private school, but it's really put us on the map, so to speak. . As a result of the economic recession, many families are cutting back their . Each summer we swap out about 400 computers, says Pritchett. . all have a job to do, and sometimes it's hard, but we try to help and lift each other up.
http://www.harding.edu/Mag_fall09/campus.html
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Arlene Tognetti History Channel is the best in helping us all rediscover and uncover our history, . Depression and it was only luck that WWII came along to lift us out of economic stagnation. . Carl Kidder Buchanan and Harding were far, far worse....a few others as well . Pearl Harbor 9/11 great depression great recession!
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US jobs increase gives markets a lift - FT.com
Feb 1, 2013 . The US economy added more jobs than previously announced in 2012's final . By Robin Harding in Washington and Stephen Foley in New York . an Employment Tax Credit Program as a stimulus to recover from the recession. . This article fails to mention the 169,000 that dropped out of the workforce.
http://www.ft.com/cms/s/0/8c2e3258-6c74-11e2-b73a-00144feab49a.html
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8 U.S. Presidents Who Ran Their Own Businesses (PHOTOS)
Jul 19, 2012 . Lincoln went on to own a law practice and invent machinery to lift riverboats . The highly profitable newspaper would eventually provide Harding with the . The store was open from 1919 to 1922, but eventually fell victim to the post-war recession. . That would have gotten us out of the Great Depression.
http://www.huffingtonpost.com/2012/07/19/presidents-entrepreneurs_n_1684521.html
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Alben W. Barkley - Wikipedia, the free encyclopedia
Laura Louise married Douglas MacArthur II, a U.S. diplomat and nephew of General . campaigned for his re-election in 1916, using the slogan "he kept us out of war". . Republican Warren G. Harding defeated Cox in the general election, and . During speeches, he would lift a glass of water to his lips, then mockingly .
http://en.wikipedia.org/wiki/Alben_W._Barkley
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Can a tax cut deepen the recession? | Intellectual Takeout (ITO)
Can a tax cut deepen the recession? Gauti B. Eggertsson. Federal Reserve Bank of New York. December 2008. "This paper shows that at zero short-term .
http://www.intellectualtakeout.org/library/research-analysis-reports/can-tax-cut-deepen-recession
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The Leonard Lopate Show: Crossing Over - WNYC
Jan 24, 2013 . And we'll find out about the decline in corporate outsourcing and . and hopes that it will lift that country out of its lasting recession. . Journalist Eamonn Fingleton and Financial Times U.S. economics editor Robin Harding .
http://www.wnyc.org/shows/lopate/2013/jan/24/
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Sultan of smooth - NYTimes.com
Feb 7, 2008 . Dietrich, you are aware that there was no Clinton-Gore recession, right? . Witness TeaPot Dome under Harding, the S & L fiasco under Reagan, the . it with new stainless steel appliances will not lift us out of our recession.
http://krugman.blogs.nytimes.com/2008/02/07/sultan-of-smooth/
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Who Will Buy All Those Treasury Bonds When The Fed Stops ...
Jan 9, 2013 . Sy Harding, Contributor . And indeed, the 20-year U.S. Treasury bond recently lost 11% of its value just since its late July peak. . in an effort to do its part in helping to lift the economy out of the worst recession in 80 years.
http://www.forbes.com/sites/greatspeculations/2013/01/09/who-will-buy-all-those-treasury-bonds-when-the-fed-stops/
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HISTORICAL RANKING OF UNITED STATES PRESIDENTS - best ...
His tax cuts led us out of an economic downturn. . for the Great Depression, just as the policies of Bush set up for the Great Recession. . When the 1920 Depression broke out, the Harding/Coolidge team cut taxes and . He didn't lift a finger to try to stop the South from seceding, made no attempts to preserve the Union.
http://shareranks.com/838,HISTORICAL-RANKING-OF-UNITED-STATES-PRESIDENTS
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VP Biden: For the millions of Americans without jobs, the U.S. ...
Oct 19, 2009 . When your brother- in-law's out of work, it's a recession. When you're out of . What if I really, really need a face lift and tummy tuck, but can't quite afford it? . Posted by: James Harding | October 20, 2009, 9:26 am 9:26 am .
http://abcnews.go.com/blogs/politics/2009/10/vp-biden-for-the-millions-of-americans-without-jobs-the-us-economy-is-in-a-depression/
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David Huebner - US Ambassador to New Zealand
6 days ago . Friendly salt-of-the-Earth New Englanders round out the experience, making the . For those of us with an appetite, Austin regularly clocks in as one of the . Harrison, William McKinley, William Howard Taft, and Warren G. Harding. . a post-recession renaissance that is highlighting the city's diversity.
http://blogs.newzealand.usembassy.gov/


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There are times, I think, when the gods who order our puny human affairs take their lead from Hooting Yard. How else to explain this magnificent headline?
MP Blunkett injured in cow attack
Incidentally, it is somewhat disconcerting that the BBC feels it necessary to qualify the numinous Blunkett name with the designation “MP”, as if there might be other newsworthy Blunketts in the known universe. There are not.
I am going to go on a little trip now. I will be gone only for a couple of days, and will return in time for this week's Hooting Yard On The Air at teatime on Thursday. I live in hope that a brief change of scene, and the thought of that cow, will loosen up the cranial integuments, the knotting of which has caused such regrettable silence of late.


{% extends "base.html" %} {% block title %}Delete profile{% endblock title %} {% block content %}
Do you really want to delete your profile?


Nationwide NRC
If an Assam-like National Register of Citizens (NRC) exercise is to be undertaken across the country, is the government going to build thousands of detention centres to hold those excluded? And has it also planned to create hundreds of tribunals to assist those who are not able to provide adequate documents? And finally, what is the future course of action to deal with the excluded? Where will they go? It is clear that such an exercise, if undertaken, will prove to be more disastrous than even demonetisation.
Ratnaraj Jain,
Rajahmundry, Andhra Pradesh


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.°E .°N climate distribution species suitable camphor model temperature data tree change variables used areas MaxEnt area {border-style px;} range #ffffff;} Figure growth environmental habitat Climate future high niche potential test < RCP. habitats response warming ./j.-...x climatic current variable Cinnamomum annual different jackknife model. precipitation study suitability using AUC Ecol. curve ecological global information predicted px; rate results showed {font-family (L.) Biol. Modeling based conditions distributions font-size geographical modeling models presence region, trees China. Glob. Wang camphora double; entropy importance moisture probability shown ./s--- Change China EXT However, L.Z.; Maxent Nature Predicting Table addition, bold border-color border-width changes contribution distributed effects forest impacts important increase index latitudes mean points predict prediction regions selected soil solid; species. study, threshold {font-style {font-weight August Biogeogr. Chang. Forestry Mean Model PAS Potential Presl S.J. Sci. Thomas Zhang [], accumulated affect analysis average background biodiversity change, climate, courier; curves deviation em; evaluation extreme factors gradually impact lower method month mutual obtained pt;} replicate role scenarios, shifts significant species, standard time unsuitable value year years °C,


+++ title = "Transsexual at Cabaré Tito" slug = "transsexual-at-cabare-tito" date = 2007-02-22T00:00:00+10:00 tags = ["disco", "eccentric-encounters", "entertainment", "music"] locations = ["mexico/mexico-city"] draft = false summary = """
Two crazy Danish girls grabbed three unsuspecting guys from the hostel (one of whom was me), and took us to the crazy bar called Cabaré Tito, in Mexico City's Zona Rosa district.
Only in Cabaré Tito can you watch a transsexual singer performing live. It's that kind of place. The performance was disturbing, to say the least.
""" +++Two crazy Danish girls grabbed three unsuspecting guys from the hostel (one of whom was me), and took us to the crazy bar called Cabaré Tito, in Mexico City's Zona Rosa district.
Only in Cabaré Tito can you watch a transsexual singer performing live. It's that kind of place. The performance was disturbing, to say the least.
{{< galleryphoto "2007-02-22-00-00-00--transsexual-at-cabare-tito.jpg" >}}My only advice about Cabaré Tito is this: it's not for the faint-hearted! Personally, I'm not going back there ever again.


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this is the workhorse function, that makes the internal state consistent sets: self._mockAxis self._ndim self._shape |
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| Generated by Epydoc 3.0.1 on Mon Nov 22 14:59:36 2010 | http://epydoc.sourceforge.net |


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The Cancer Cell Line Encyclopedia (CCLE) Explorer enables users to browse relative mRNA expression data for cancer cell lines from the CCLE by tissue of origin using Clustergrammer. Click on a tissue type to view a clustergram of the top 250 most variable genes within a tissue - by default Haematopoietic and Lymphoid Tissue expression is shown. These heatmaps can be used to identify sub-category behavior within tissues and are pre-loaded with enrichment analysis from Enrichr for Gene Ontology Biological Process.
Above is a similarity matrix of the columns in your input matrix. The cells in the matrix represent the similarity between columns, where red/blue represent positive/negative similarity (measured as 1 - cosine-distance). Similarity matrices offer a more detailed view of the similarities and differences between rows/columms, e.g. blue cells indicate data points that behave 'oppositely' and this can not be easily seen in a clustergram/heatmap view.
Above is a similarity matrix of the columns in your input matrix. The cells in the matrix represent the similarity between columns, where red/blue represent positive/negative similarity (measured as 1 - cosine-distance). Similarity matrices offer a more detailed view of the similarities and differences between rows/columms, e.g. blue cells indicate data points that behave 'oppositely' and this can not be easily seen in a clustergram/heatmap view.


World Wide Web Access Statistics
File Accesses by Domain for IUSOCS
July 1999
There were no accesses from this domain.
There were no accesses from this domain.
Requests Received During Summary Period 37
Bytes Transmitted During Summary Period 141714
Average Requests Received Daily 6
Average Bytes Transmitted Daily 23619
Requests Received During Summary Period 11
Bytes Transmitted During Summary Period 39252
Average Requests Received Daily 11
Average Bytes Transmitted Daily 39252
Requests Received During Summary Period 116
Bytes Transmitted During Summary Period 204223
Average Requests Received Daily 5
Average Bytes Transmitted Daily 8509
Requests Received During Summary Period 11
Bytes Transmitted During Summary Period 20085
Average Requests Received Daily 3
Average Bytes Transmitted Daily 5021
Requests Received During Summary Period 6
Bytes Transmitted During Summary Period 46757
Average Requests Received Daily 2
Average Bytes Transmitted Daily 11689


railActive is a dashboard that uses realtime data to forecast New Jersey Transit train delays. The railActive model was built using a Random Forest classifier and the front end is implemented using Shiny.
GitHub SlideShareThis box allows you to select which train line to monitor and to chose how frequently the predictions are updated.
Provides a forecast of a delay occuring on the selected line as well as relevant information about current travel conditions.
A summary plot showing how the current conditions impact the delay forecast.
A plot forecasting the possibility of a delay on the line for the next 12 hours.


--- layout: post title: Amazing date: 2009-11-14 16:21:36 -06:00 comments: true categories: posterous_id: 7492968 ---
This video shows Oli Lemieux practicing on the trampoline wall of Cirque du Soleil and I've watched it twice already. I keep searching for clues that it's just a cleverly edited video, that someone couldn't possibly really do these stunts.
Despite all the discussion of what the human body can be pushed to do, I feel feel a sense of disbelief watching Oli jumping around. I know that he's a talented man and that this clip is almost certainly not edited in ways that enhance the stunts. But a part of me desperately wants the video to be fake, because, despite the many years of practice it must've taken him to make everything look easy, Oli has forced me to realize my own personal limitations.


Let us show you how STiQR can help your stuff return back to you.
You create your STiQR account with the best ways to reach you.
We design your personal QR code and send you a set of our extra durable and versatile stickers that you can stick on anything.
When someone finds the item you lost and scans the STiQR they will be taken to your profile and can contact you through our safe and secure site.
I'm always leaving my wallet at the bar or some other place. I stuck a STiQR on it and it's been returned to me twice in the last month!
I had just changed my phone number and my dog ran off the other day, but the person that found him was still able to contact me through STiQR.
I left my new phone on the bus last month and thank goodness for STiQR, some kind person scanned it and got it back to me good as new!


@(aa: models.asset.AllAttributes, user: User)(implicit flash: Flash, req: Request[AnyContent]) @import helper._ @import _root_.util.plugins.Provisioner @import _root_.util.views.ProvisionerHelper @container("provision-server", "Provision Server", true) { @if(aa.asset.isIncomplete) { @header("Activate Server", Some("Warning")) } else { @header("Provision Server", Some("Warning")) } @form(app.routes.CookieApi.provisionAsset(aa.asset.tag), 'class -> "form-horizontal", Symbol("data-form") -> "true", Symbol("data-error") -> "provisionError", Symbol("data-modal") -> "provision-server", Symbol("data-refresh") -> ".window") {
Activating a server takes a couple of days. When the server has been activated out of the softlayer spare pool, it will be allocated during the reconciler run automatically. Once allocated, we will begin getting billed.
} else {Provisioning a server is a destructive process. Be certain that you want to do this. The provisioner will:
If that all sounds good, choose an appropriate profile below and provide your contact for notification


pip_services3_commons.commands.CommandSet module¶
pip_services3_commons.commands.CommandSet¶
Command set implementation
| copyright: | Conceptual Vision Consulting LLC 2018-2019, see AUTHORS for more details. |
|---|---|
| license: | MIT, see LICENSE for more details. |
-
class
pip_services3_commons.commands.CommandSet.
CommandSet
¶ Bases:
object
Contains a set of commands and events supported by a ICommandable object. The CommandSet supports command interceptors to extend and the command call chain.
CommandSets can be used as alternative commandable interface to a business object. It can be used to auto generate multiple external services for the business object without writing much code.
- Example:
- class MyDataCommandSet(CommandSet):
_controller = None
- def __init__(self, controller):
super(MyDataCommandSet, self).__init__()
self._controller = controller
self.add_command(self._make_get_my_data_command())
- def _make_get_my_data_command(self):
- def handler(correlation_id, args):
- param = args.get_as_string(‘param’) return self._controller.get_my_data(correlation_id, param)
- return Command(
- “get_mydata”, None, handler
)
-
add_command
(command)¶ Adds a ICommand command to this command set.
Parameters: command – a command instance to be added
-
add_command_set
(command_set)¶ Adds all of the commands and events from specified CommandSet command set into this one.
Parameters: command_set – a commands set to add commands from
-
add_commands
(commands)¶ Adds multiple ICommand commands to this command set.
Parameters: commands – the array of commands to add.
-
add_event
(event)¶ Adds an IEvent event to this command set.
Parameters: event – an event instance to be added
-
add_events
(events)¶ Adds multiple IEvent events to this command set.
Parameters: events – the array of events to add.
-
add_intercepter
(intercepter)¶ Adds a ICommandInterceptor command interceptor to this command set.
Parameters: intercepter – an intercepter instance to be added.
-
add_listener
(listener)¶ Adds a IEventListener listener to receive notifications on fired events.
Parameters: listener – a listener to be added
-
execute
(correlation_id, command, args)¶ Executes a ICommand command specificed by its name.
Parameters: - correlation_id – (optional) transaction id to trace execution through call chain.
- command – the name of that command that is to be executed.
- args – the parameters (arguments) to pass to the command for execution.
Returns: the execution result.
Raises: ValidationException: when execution fails for any reason.
-
find_command
(command)¶ Searches for a command by its name.
Parameters: command – the name of the command to search for. Returns: the command, whose name matches the provided name.
-
find_event
(event)¶ Searches for an event by its name in this command set.
Parameters: event – the name of the event to search for. Returns: the event, whose name matches the provided name.
-
get_commands
()¶ Gets all commands registered in this command set.
Returns: ICommand list with all commands supported by component.
-
get_events
()¶ Gets all events registered in this command set.
Returns: ICommand list with all events supported by component.
-
notify
(correlation_id, event, value)¶ Fires event specified by its name and notifies all registered IEventListener listeners
Parameters: - correlation_id – (optional) transaction id to trace execution through call chain.
- event – the name of the event that is to be fired.
- value – the event arguments (parameters).
-
remove_listener
(listener)¶ Removes previosly added IEventListener listeners.
Parameters: listener – a listener to be removed
-
validate
(command, args)¶ Validates Parameters args for command specified by its name using defined schema. If validation schema is not defined than the methods returns no errors. It returns validation error if the command is not found.
Parameters: - command – the name of the command for which the ‘args’ must be validated.
- args – the parameters (arguments) to validate.
Returns: an array of ValidationResults. If no command is found by the given name, then the returned array of ValidationResults will contain a single entry, whose type will be ValidationResultType.Error.


Test for gallery-user-patch-2529808
Scrollable YUI 3.3.0 DataTable with delayed loading of data via DataSource
If datatable is populated with data, patch works!
If nothing shows up, patch fails.


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