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| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Object org.apache.xalan.xsltc.compiler.util.MethodGenerator.LocalVariableRegistry
protected class MethodGenerator.LocalVariableRegistry
Keeps track of all local variables used in the method.
The
MethodGen#addLocalVariable(String,Type,InstructionHandle,InstructionHandle)
and
MethodGen#addLocalVariable(String,Type,int,InstructionHandle,InstructionHandle)
methods of MethodGen
will only keep track of
LocalVariableGen
object until it'ss removed by a call to
MethodGen#removeLocalVariable(LocalVariableGen)
.
In order to support efficient copying of local variables to outlined
methods by
MethodGenerator.outline(InstructionHandle,InstructionHandle,String,ClassGenerator)
,
this class keeps track of all local variables defined by the method.
| Field Summary | |
|---|---|
protected java.util.HashMap |
_nameToLVGMap
Maps a name to a LocalVariableGen |
protected java.util.ArrayList |
_variables
A java.lang.ArrayList of all
LocalVariableGen s created for this method, indexed by the
slot number of the local variable. |
| Constructor Summary | |
|---|---|
protected |
MethodGenerator.LocalVariableRegistry()
|
| Method Summary | |
|---|---|
protected LocalVariableGen[] |
getLocals(boolean includeRemoved)
Gets all LocalVariableGen objects for this method. |
protected LocalVariableGen |
lookUpByName(java.lang.String name)
Given the name of a variable, finds a LocalVariableGen
corresponding to it. |
protected LocalVariableGen |
lookupRegisteredLocalVariable(int slot,
int offset)
Find which LocalVariableGen , if any, is registered for a
particular JVM local stack frame slot at a particular position in the
byte code for the method. |
protected void |
registerByName(LocalVariableGen lvg)
Set up a mapping of the name of the specified LocalVariableGen object to the LocalVariableGen
itself. |
protected void |
registerLocalVariable(LocalVariableGen lvg)
Registers a org.apache.bcel.generic.LocalVariableGen
for this method. |
protected void |
removeByNameTracking(LocalVariableGen lvg)
Remove the mapping from the name of the specified LocalVariableGen to itself. |
| Methods inherited from class java.lang.Object |
|---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Field Detail |
|---|
protected java.util.ArrayList _variables
A java.lang.ArrayList
of all
LocalVariableGen
s created for this method, indexed by the
slot number of the local variable. The JVM stack frame of local
variables is divided into "slots". A single slot can be used to
store more than one variable in a method, without regard to type, so
long as the byte code keeps the ranges of the two disjoint.
If only one registration of use of a particular slot occurs, the
corresponding entry of _variables
contains the
LocalVariableGen
; if more than one occurs, the
corresponding entry contains all such LocalVariableGen
s
registered for the same slot; and if none occurs, the entry will be
null
.
protected java.util.HashMap _nameToLVGMap
LocalVariableGen
| Constructor Detail |
|---|
protected MethodGenerator.LocalVariableRegistry()
| Method Detail |
|---|
protected void registerLocalVariable(LocalVariableGen lvg)
org.apache.bcel.generic.LocalVariableGen
for this method.
Preconditions:
lvg
does not
overlap with the range of instructions for any
LocalVariableGen
with the same slot index previously
registered for this method. (Unchecked.)
lvg
- The variable to be registeredprotected LocalVariableGen lookupRegisteredLocalVariable(int slot, int offset)
Find which LocalVariableGen
, if any, is registered for a
particular JVM local stack frame slot at a particular position in the
byte code for the method.
Preconditions:
InstructionList#setPositions()
has been called for
the InstructionList
associated with this
MethodGenerator
.
slot
- the JVM local stack frame slot numberoffset
- the position in the byte code
LocalVariableGen
for the local variable
stored in the relevant slot at the relevant offset; null
if there is none.protected void registerByName(LocalVariableGen lvg)
Set up a mapping of the name of the specified
LocalVariableGen
object to the LocalVariableGen
itself.
This is a bit of a hack. XSLTC is relying on the fact that the
name that is being looked up won't be duplicated, which isn't
guaranteed. It replaces code which used to call
MethodGen#getLocalVariables()
and looped through the
LocalVariableGen
objects it contained to find the one
with the specified name. However, getLocalVariables()
has the side effect of setting the start and end for any
LocalVariableGen
which did not already have them
set, which causes problems for outlining..
See also lookUpByName(String)
and
removeByNameTracking(LocalVariableGen)
lvg
- a LocalVariableGen
protected void removeByNameTracking(LocalVariableGen lvg)
LocalVariableGen
to itself.
See also registerByName(LocalVariableGen)
and
lookUpByName(String)
lvg
- a LocalVariableGen
protected LocalVariableGen lookUpByName(java.lang.String name)
Given the name of a variable, finds a LocalVariableGen
corresponding to it.
See also registerByName(LocalVariableGen)
and
removeByNameTracking(LocalVariableGen)
name
-
protected LocalVariableGen[] getLocals(boolean includeRemoved)
Gets all LocalVariableGen
objects for this method.
When the includeRemoved
argument has the value
false
, this method replaces uses of
MethodGen#getLocalVariables()
which has
a side-effect of setting the start and end range for any
LocalVariableGen
if either was null
. That
side-effect causes problems for outlining of code in XSLTC.
includeRemoved
- Specifies whether all local variables ever
declared should be returned (true
) or only those not
removed (false
)
LocalVariableGen
containing all the
local variables
|
||||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |


|
|
Enterprise IT |
Value Added Reseller / Systems Integrator |
Manufacturer |
| End User Access |
| Connect to labs via any HTML5 browser |
|
|
|
| No special software or plugins required |
|
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|
| Collaborate with others simultaneously |
|
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| View lab presentations that scale to any display or projector |
|
|
|
Stories provide step-by-step instructions to users |
|
|
|
| User Management |
| Invite specific users with Invite Codes |
|
|
|
| Receive an email alert when an Invite Code is used |
|
|
|
| Receive an email alert when someone from a specific company logs in |
|
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|
| Associate different user types with labs |
|
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| Associate specific users with labs individually or via Groups |
|
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|
| Make a labs widely available via customized URLs |
|
|
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| Create custom workflows for user access |
|
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|
| Presentation Editor |
| Choose from over 750 font families |
|
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|
| Embed YouTube or other videos |
|
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| Collaboratively edit presentations |
|
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| Roll back changes via revision history if necessary |
|
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|
| Stories |
| Share details specific to a lab instance |
|
|
|
| Avoid typos with buttons that paste text |
|
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|
| Create actions within labs |
|
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|
| Show or hide the story as needed |
|
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| Write stories with a WYSIWYG editor |
|
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|
| Manage stories with version controls |
|
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|
| Reporting |
| All active and expired labs |
|
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| Real time details of labs being created and torn down |
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| Lab instances with connection information |
|
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| Who is currently logged in |
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| Details of all running labs |
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| Tie into your brand with a custom domain and logo |
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| Lab Catalog |
| Choose from a list of published labs |
|
|
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| Reviewing the lab catalog presentation before launcing |
|
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|
| Control access to catalog items by user type |
|
|
|
| Associate specific users or groups with catalog items |
|
|
|
| VM Builder |
| Import OVAs to build new VM templates |
|
|
|
| Build VM templates from base elements in the Master Catalog |
|
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|
| Set sane defaults for key characteristics |
|
|
|
| Publish your VM to the Master Catalog |
|
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|
| Node Builder |
| Create node templates from a catalog of base VMs |
|
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| Configure the node with scripts and Puppet manifests |
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| Specify environment variables that can be set later |
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| Document node with usage notes |
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| Publish node to a node catalog |
|
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| Blueprint Builder |
| Create a blueprint from a catalog of blueprint templates |
|
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|
| Start from scratch with a blank blueprint template |
|
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| Populate your blueprint with nodes from the node catalog |
|
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| Override any default node characteristics |
|
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| Specify network connectivity and options |
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| Add scripts and Puppet manifests for additional configuration |
|
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| Event Management |
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| Give visibility and control to a trainer |
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| Specify the timing and structure of the event |
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| Manage invitations and registrations |
|
|
|
| Marketing Automation |
| Create branded email notification templates |
|
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| Send emails informing users of new labs |
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| Remind users when they haven't logged in recently |
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| Design custom interactions based on dozens of triggers |
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| Create custom integrations with your marketing automation tools |
|
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| Salesforce Integration |
| Push lab activity to Salesforce records |
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| Dynamically select from existing Salesforce accounts |
|
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| Support custom workflows and integrations |
|
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|


The overall error of the Monte-Carlo approximation given in Eq. (56) always scales like 1∕, which is independent of the dimensionality of the phase-space. It is easy to demonstrate that the overall error of the usual regular-grids approximation to the integration scales like 1∕N′1∕d, where d is the dimension of the phase space[4]. This fact implies that Monte-Carlo approximation is more accurate than the regular-grids methods for high-dimension (d ≥ 3) integration. Due to this reason, particle methods can be considered more accurate than the Euler-grid-based methods for the same number of sampling points in a high-dimensional (≥ 3) phase space.
On the other hand, PIC simulations obviously contain unphysical noise. The noise is due to the discrete marker eﬀects, which can be further categorized into two types: sampling noise (ﬂuctuation of the sampling error) and remaining unwanted collisions in a collisionless simulation.
Due to the limited small number of markers used in PIC code, there are considerable time and spatial ﬂuctuation over the the number of markers in a spatial-cell. This ﬂuctuation in the number of sampling points (i.e., ﬂuctuation of the sampling error) gives rise to the sampling noise.
Inaccuracy in a PIC simulation is also related to the fact that the phase-space volume sampled by a marker is assumed to be constant in a PIC code but this assumption is not strictly satisﬁed in practice due to (1) the number of markers being not large enough and (2) the resulting self-consistent ﬁeld being not smooth enough, which introduce eﬀective collisional eﬀects, making the conservation of the phase-space volume less accurate. How well the phase-space volume is conserved depends on the smoothness of the ﬁeld: smooth ﬁeld means less collisions and thus phase-space volume are better conserved. PIC simulation codes seek to reduce the collision through using ﬁnite-size particles (discussed in Sec. 3) and averaging in a spatial cell in solving for the electromagnetic ﬁelds, which eﬀectively smooth the ﬁelds. This kind of PIC simulations are thus designed for collisionless plasmas. And the remaining collisional eﬀect should be small enough to not aﬀect the process of interest. And this remaining collisional eﬀects should be viewed as numerical artifacts rather than a modeling of any real collisional eﬀect in plasmas. If we want to model the real collisional eﬀect in PIC simulation, we need to use other techniques rather than relying on the remaining collisions mentioned above because the latter is not easy to control and ideally should be completely removed.
Various noise reduction techniques in PIC codes (e.g., ﬁnite-size particles, grids, and perturbative δf method) can be used when the marker number is ﬁxed. When exhausting all these methods, the ﬁnal brute-force method of reducing noise (reducing collisions) is to increase the marker number. Therefore the noise issue is ﬁnally a convergence issue about the marker number.
From the view of particle simulations, the gyrokinetic model can also be considered as a noise reduction technique, where the gyro-averaging process makes the ﬁeld on a marker more smooth.
(Noise in PIC code is equivalent to the remaining artiﬁcial collision eﬀect? We can test this by doing a test particle simulation, in which we loaded a group of markers to sample a distribution function in the phase space and then compute the density evolution of the sampled distribution under a given smooth electromagnetic ﬁeld (i.e., eliminating the collisional eﬀect). If there is still signiﬁcant noise in the time evolution, then this indicates there are factors other than collisions that contribute to the noise. I did this when I studied Landau damping, the results indicate there is still signiﬁcant noise in the solution, indicating the discrete phase space sampling is the root of the noise.)
One thing to note is that the noisy results obtained in particle method are not necessarily less accurate than the smooth results obtained in Euler-grid-based methods because bigger errors may be hidden in smooth results when one uses coarse grids.


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Comments
-
Greg Hurrell
Thanks for the request. Rather than have two items, I think it would be better to modify WinSwitch to allow you to display the name and the icon at the same time (in a single item).
At the moment I am working full time on other projects and so there's not much time for WinSwitch, but the source code is available (see the downloads page) if you want to look into implementing this.
-
Tyler Weisman
Wince,
That definitely would be acceptable. Unforunately, I am no programmer, so the issue must be left to another. I would like to know if anyone else reading this would be interested in implementing this feature.
Tyler
-
Greg Hurrell
I'm marking all WinSwitch issues closed seeing as I personally no longer use it, and in fact haven't for around 4 years now.
WinSwitch addressed a real problem with the initial implementation of Fast User Switching in Panther (released October 2003), namely, the excessive screen real estate that it chewed up. Apple fixed that problem in Tiger, if I recall correctly, which came out in April 2005 (or if I'm wrong about it being Tiger, then it was definitely fixed by the time Leopard came out, in October 2007).
With this change, most of the justification for WinSwitch's existence went away, at least for me. So that's why I'm going to close all these tickets: I can't really support something that I don't use myself.
But it's open source (see http://git.wincent.com/WinSwitch.git), so if any one wants to tackle any of these issues and submit patches, I'll be happy to accept them.
-
Greg Hurrell
Status changed:
- From: new
- To: closed
Add a comment
Comments are now closed for this issue.


The Bone Collector A review by Joe Chamberlain
Starring Denzel Washington; Angelina Jolie; Queen Latifah; Michael Rooker & Mike McGlone
As action/suspense movies go, this is one that ranks above average. But, make no mistake about it -- it isn't quite in the same league with movies like Seven or Silence Of The Lambs. Although, it does try very hard to get there. Including generous use of grisly, but not overly gratuitous, scenes featuring butchered dead bodies.
Denzel Washington plays Lincoln Rhyme, a police forensic specialist who had suffered a spinal injury several years before which left him a quadriplegic. Rhyme now only has movement from his neck up, and limited movement in his little finger. But even though he is no longer able to go into the field, he still has the best investigative mind around and is called upon frequently by the New York Police Department in serious cases. This is one of those cases. A serial killer called The Bone Collector is posing as a cab driver and kidnapping people. He then brutally kills them and leaves little clues with the butchered bodies, taunting the police to put the pieces together and find him before he kills again. Angelina Jolie plays a young officer who finds one of The Bone Collector's victims and impresses Rhyme with her natural ability in forensics. So much so, that he shanghais the reluctant woman into joining him on the investigation. She is to serve as his eyes and ears in the field while he talks her through the investigation from his bed. No surprise that the investigation takes her to some of the deepest recesses of New York city on her mission to stop the killer before he strikes again.
First, let me say that Phillip Noyce did an excellent job of directing The Bone Collector. Like the movie that this is most easily compared to, Seven, much of the action takes place in dimly lit areas. Unlike Seven, which seemed to take place in a perpetual rainstorm, it is abandoned subway tunnels and decaying buildings that give The Bone Collector it's feel of impending death. A great soundtrack also helps to darken the mood considerably.
Washington may have given his best performance ever in this film. It is truly a credit to his abilities that he plays such an integral and interesting part in this movie based solely on his facial expressions and tone of voice. But as good as Washington is, this is Angelina Jolie's movie. This is really Jolie's first major starring role and she carries the movie beautifully. The fact that she is one of the most beautiful women in Hollywood doesn't hurt either. Am I the only one that thinks she has the most amazing lips ever? Washington and Jolie also have a great deal of help from the supporting cast. Michael Rooker (Cliffhanger) is Jolie's nemesis, the head of the police forensics department, and plays up the character's arrogance to the hilt. Queen Latifah also does a solid job in her fairly small role as Rhyme's personal aid. The two biggest surprises would have to be Ed O'Neill and Luis Guzman. O'Neill plays the lead detective on the case and gives a performance that I never would have expected from the man best known as Al Bundy. But the biggest treat was Guzman as Eddie, an NYPD forensic technician. He had some of the best one-liners in the film and stole just about every scene that he was in. My only complaint with him was that he didn't get more screen time.
The comparisons between this film and Seven are inevitable, and very understandable. But The Bone Collector is more than able to stand on its own besides the obvious similarities. If I had one major complaint, it would be the film's ending. Without giving anything away, I thought the choice of the killer was a bit weak, and the ending was just a bit too formula for an otherwise clever movie. I haven't read the novel by Jeffery Deaver upon which this movie is based, but I have read the sequel, The Coffin Dancer. Knowing how clever that book was, I wouldn't be at all surprised to find that The Bone Collector lost a little something in the translation from the page to the big screen.
Regardless of its flaws, The Bone Collector is still a great movie. The story is entertaining, albeit a bit gory in places, and the directing is superb. But the best reason to check out this movie is for the cast. All the performances are bang on and Jolie shows why she is an actress to watch in the coming years.
8/10
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Photos released of suspects in Upper West Side home invasion robbery
by WABCUPPER WEST SIDE, Manhattan (WABC) -- Police have released photos of the suspects who broke into a Manhattan apartment Friday and beat the man inside.
Police say once the suspects got into the apartment on West 83rd Street, they grabbed 21-year-old Thomas Dorcey and punched him in the face.
One man grabbed the victim's girlfriend by her hair.
They even took the owner's service dog outside. The dog was later found safe.
The suspects got away with a Playstation 4, a debit card and a cell phone.
The investigation is ongoing, and anyone with information is urged to call the NYPD's Crime Stoppers Hotline at 1-800-577-TIPS (8477).


On the Unix-like operating systems, the order in which static libraries are specified when invoking the linker is important, because by default, the linker uses one pass though the libraries list. Passing the libraries in the incorrect order will lead to a link error. Further, this behaviour is often used to make one library override symbols from another. So, sometimes it's necessary to force specific order of libraries.
Boost.Build tries to automatically compute the right order. The primary rule is that if library a "uses" library b, then library a will appear on the command line before library b. Library a is considered to use b is b is present either in the sources of a or in its requirements. To explicitly specify the use relationship one can use the <use> feature. For example, both of the following lines will cause a to appear before b on the command line:
lib a : a.cpp b ; lib a : a.cpp : <use>b ;
The same approach works for searched libraries, too:
lib z ; lib png : : <use>z ; exe viewer : viewer png z ;


Your Happiness Index
Start tracking your emotions at work or in the office. Create a blog, record the emotions and analyze them with statistics and calendar view.
Mood Board For The Team
Easy-to-use online Mood Board for your team. It is up to you if it is anonymous or not. Create a blog and share the link with your team.
Opinions for Your Product
Do you want to know what people think about your product or service ? Ask them! Create a blog and share with the users.


Njoroge G. Edward
Cell: +254 700 187 754Mail<EMAIL_ADDRESS>Professional Summary
A software developer proficient with all stages of the software development lifecycle. Extensive experience in object-oriented, modular programming and use of data structures and algorithms to provide efficient solutions. Expertise in design, programming, trouble shooting, debugging and documentation in C, C++, Java, Python, HTML5, CSS3, JavaScript, PHP and MySQL.
Areas of Expertise
- Programming:
- Desktop: C, C++, Java, Python.
- Web: HTML5, CSS3, JavaScript, PHP, MySQL.
- Frameworks:
- Desktop: Qt C++, Qt QML, JavaFx.
- Web: Bootstrap, W3CSS, Laravel.
- Software Engineering:
- Agile(eXtreme programming, Scrum).
- Unified Modelling Language.
- System Analysis and Design.
- Optimization:
- Data Structures and Algorithms.
- Systems:
- LAMP Stack.
- GNU/Linux operating system.
Skills and Work Experience
- Skills:
- Ability to work in a team.
- Strong work ethics.
- Analytical and quantitative skills.
- Fast learning.
- Ability to adapt quickly to change.
- Creative and innovative.
- Work Experience:
- Freelance Software Developer(2015 - 2017): I worked at freelancer.com while still at school.
- Personal Pet Projects: At leisure, I develop pet projects to brush up on my programming skills.
Education and Qualifications
| Jomo Kenyatta University (2014 - 2018) | BSc. Mathematics and Computer Science |
| Chuka Boys High School (2010 - 2013) | Attained an A- of 78 out of 84 points |
<EOF>


Patient Dies In An Ambulance Ramped Outside Flinders
An elderly patient waited in an ambulance outside Flinders Medical Centre for “over two hours” before he “died in the back of an ambulance”, according to the Ambulance Employees Association.
The union’s Phil Palmer spoke to FIVEaa’s Leon Byner on Monday following the death on Friday.
“We’ve spoken to the crew, we’ve spoken to people who were actually there… two hours and 10 minutes it was,” Mr Palmer said.
“An elderly patient ramped for that period of time became increasingly uncomfortable and anxious about his health status. One of the crew members went into the ED at about the two hour mark to see if they could get him in more quickly and by the time he came back the patient had died basically…
“Ramped for over two hours, deteriorated rapidly, should’ve been inside the hospital. Had that patient been inside the hospital much better chance of survival… where life was declared extinct is another matter but where the patient died was in the back of an ambulance, yes.”
LISTEN:


Nadal sweats on semis spot at ATP Finals
London - Rafael Nadal recovered to beat Stefanos Tsitsipas 6-7 (4/7), 6-4, 7-5 on Friday, but faces an anxious wait to find out whether he will play Roger Federer in the last four at the ATP Finals.
The Spanish top seed is pinning his hopes on Daniil Medvedev beating defending champion Alexander Zverev in the evening match in Group Andre Agassi in London.
Nadal's efforts will count for nothing unless Medvedev, who now has nothing to play for, beats Zverev. A win for the German would send Nadal home.
"I don't know if I will see you tomorrow because it depends on the match of this evening, but I did all the things that I could today," said Nadal.
"I fought until the end two days ago and today, so if I am able to play in front of you tomorrow against Roger it will be a huge honour. If not, I really hope to see you next year."
Nadal, who has already secured the year-end number one ranking, has never won the end-of-season tournament and had a miserable start at the O2 Arena, being outplayed by Germany's Zverev.
But the 19-time Grand Slam champion produced an astonishing comeback to defeat Medvedev, the Russian fourth seed, on Wednesday and give himself a chance of qualifying from the round-robin phase.
Tsitsipas, 21, had already qualified for the semi-finals before Friday's match after beating Medvedev and Zverev.
Serve dominated in the first set on Friday, with neither Nadal nor Tsitsipas facing a break point as the match drifted inexorably towards a tie-break.
The Greek sixth seed came out on top, hammering an ace on his first match point to seal the set.
The second set followed a similar pattern until the fifth game, when a Tsitsipas double-fault handed Nadal two break points - the first of the match.
The Spaniard could not capitalise but he upped the pressure in Tsitsipas's next service game and earned another break point, which the Greek again survived.
But Nadal earned a fourth break point in Tsitsipas's next service game and this time the Greek player slapped a regulation forehand wide and Nadal went on to level the match.
A pumped-up Nadal maintained his momentum in the early stages of the deciding set, putting consistent pressure on his opponent's serve but he failed to convert a clutch of break points.
Nadal earned two more break points in the 11th game and this time made it count as Tsitsipas put a backhand wide and he served out to win the match.
After the match Nadal received the trophy for finishing the year as the top-ranked player.
"I'm super happy," he said.
"Honestly, after all the things I went through in my career in terms of injuries I never thought at the age of 33-and-a-half I would have this trophy in my hands again.
"It's something really, really emotional for me. A lot of work in the shadows to be where we are today."
Six-time champion Federer, who was in Group Bjorn Borg, secured a spot in the semi-finals for the 16th time in his career on Thursday by beating Novak Djokovic in straight sets.
Austrian fifth seed Dominic Thiem also qualified for Saturday's semi-finals.
Results on the sixth day of the ATP Finals at London's O2 Arena on Thursday (x denotes seeding):
Singles
Group Andre Agassi
Rafael Nadal (ESP x1) bt Stefanos Tsitsipas (GRE x6) 6-7 (4/7), 6-4, 7-5
Playing later
Daniil Medvedev (RUS x4) v Alexander Zverev (GER x7)
Doubles
Group Max Mirnyi
Juan Sebastian Cabal/Robert Farah (COL/COL x1) bt Kevin Krawietz/Andreas Mies (GER/GER x3) 7-6 (9/7), 6-2
Playing later
Jean-Julien Rojer/Horia Tecau (NED/ROU x6) v Pierre-Hugues Herbert/Nicolas Mahut (FRA/FRA x7)


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Click to hide Nature.
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Click to show Snow.
Add Borders to all Pictures
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Located in /Token.php (line 12)
Test the current token for a type. The first argument is the type of the token (if not given Twig_Token::NAME_TYPE), the second the value of the token (if not given value is not checked).
the token value can be an array if multiple checks should be performed.
Documentation generated on Sun, 24 Oct 2010 20:29:23 +0200 by phpDocumentor 1.4.3


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Returns encrypted accountId from param Strings are assumed to be ids.
Gets name from argument. String are assumed to be names.
Returns encryptedSummonerId from argument. Strings are assumed to be ids.
Return puuid from argument Strings are assumed to be ids.
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CRAZY IN ALABAMA (Columbia) Starring: Melanie Griffith, David Morse, Lucas Black, Meat Loaf Aday, Cathy Moriarty, John Beasley, Richard Schiff, Rod Steiger. Screenplay: Mark Childress, based on his novel. Producers: Meir Teper, Linda Goldstein Knowlton, Debra Hill, Diane Sillan Isaacs. Director: Antonio Banderas. MPAA Rating: PG-13 (violence, adult themes, profanity) Running Time: 112 minutes. Reviewed by Scott Renshaw.
I spent much of CRAZY IN ALABAMA trying to figure out the connection between its two largely parallel storylines. I spent much of the rest of the time surprised how little I cared. And I spent the final ten minutes marvelling how quickly a pleasant little film can turn ghastly. Adapted by Mark Childress from his own novel and directed by erstwhile Zorro Antonio Banderas, CRAZY IN ALABAMA takes us back to 1965 in the small town of Industry (accent on the second syllable), Alabama. Our narrator is Peter Joseph "Peejoe" Bullis (Lucas Black), a 13-year-old orphan living with his grandmother.  Meanwhile, back in Industry, the influx of kids sends Peejoe and his brother Wiley to live with Uncle Dove (David Morse), the segregated town's mortician for whites. Soon Peejoe becomes aware of racial unrest stirring in the town, and becomes an eyewitness to the extreme response of Sheriff John Doggett (Meat Loaf Aday).
I must confess that I kept forgiving CRAZY IN ALABAMA its excess just because it was so unexpectedly weird at times, primarily in the Lucille-on-the-lam segments. Melanie Griffith is an eccentric hoot as Lucille, carrying around her husband's head in a Tupperware container because she wants him around to see her make it as an actress. Her adventures are so ridiculous it's hard not to smile.  She wins $13,000 playing roulette in Las Vegas. She turns the hostess (a splendidly uptight Elizabeth Perkins) at a Hollywood party into a catatonic mess with hubby's strategically-placed noggin. She even does a guest spot on "Bewitched," reading her lines to toneless stand-ins for Sam, Darrin and company. The story keeps hopping in so many directions, zestfully directed by Banderas, that it's almost impossible to lose interest for long.
It also hops back in the direction of Peejoe's story, where strangeness generally gives way to sluggish sincerity. CRAZY IN ALABAMA plays its racial themes deadly straight, turning Peejoe into a preternaturally wise and moral lad who even gets to shake Dr. Martin Luther King's hand. In more ways than one, it's all black and white -- the buffoonishly nasty sheriff, the calmly liberal father figure, the noble African-American protesters whose plight is rendered in grainy newsreel-style footage. Everyone carries on in the expected ways on the expected subjects, all leading to the one-would-hope-obvious conclusion that segregation was a very bad thing indeed, and thank heaven for a few good white people to help set things right.
Still, the zestful style of the Lucille storyline makes it possible to get past the heavy-handedness of the Peejoe storyline ... until Lucille returns to Industry. Thus is set in motion one of the most painful courtroom finales in cinema's long, sad history of painful courtroom finales, presided over by Rod Steiger as the judicial equivalent of Col. Kurtz. First Lucille tells her tale of woe to the jury, rambling on about the horrors of domestic abuse for reasons too contrived to fathom. You'd suspect it was a matter of Banderas indulging his real-life leading lady, if not for the fact that Steiger follows Lucille's monologue with a rant of his own. Banderas loses complete control over his actors at the film's conclusion. Worse yet, the film takes two sensitive issues -- the subjugation of African-Americans and the subjugation of women -- and, in attempting to equate them, doesn't do justice to either one. It's a tragic miscalculation in a film which at least had a chance when it was quirky and frivolous. The real craziness in CRAZY IN ALABAMA is that a viewer might spend so much time giving it the benefit of the doubt.
On the Renshaw scale of 0 to 10 Southern discomforts: 4.
Visit Scott Renshaw's Screening Room http://www.inconnect.com/~renshaw/ *** Subscribe to receive new reviews directly by email! See the Screening Room for details, or reply to this message with subject "Subscribe".
The review above was posted to the
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Related links: index of all rec.arts.movies.reviews reviews


When you boot a GitHub Enterprise Server instance for the first time, you can use the following endpoint to upload a license:
POST /setup/api/start
Note that you need to POST to
/setup/api/configure
to start the actual configuration process.
When using this endpoint, your GitHub Enterprise Server instance must have a password set. This can be accomplished two ways:
| Name | Type | Description |
|---|---|---|
license |
string |
Required. The content of your .ghl license file. |
password |
string |
You must provide a password only if you are uploading your license for the first time. If you previously set a password through the web interface, you don't need this parameter. |
settings |
string |
An optional JSON string containing the installation settings. |
For a list of the available settings, see the Get settings endpoint.
curl -L -X POST 'https://hostname:admin_port/setup/api/start' -F<EMAIL_ADDRESS>-F "password=your-amazing-password" -F "settings=</path/to/settings.json"
HTTP/1.1 202 Created Location: http://hostname:admin_port/setup/api/configcheck


Train Schedule
Wooo hooo
Current Train Schedule
Train Name
Destination
Frequency (mins)
Next Arrival
Minutes Away
Add Train
Train Name
Destination
First Train Time(HH:MM - Military Time)
Frequency (min)
Submit


{% extends "app/app_base.html" %} {% import "bootstrap/wtf.html" as wtf %} {% import "_macros.html" as macros %} {% block title %}BrainDump | Add Task {% endblock %} {% block page_content %}
Add a New Task


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yetris- Navigate the piece horizontally:
Left|Right arrow key- Rotate the piece clockwise or counterclockwise:
x|z- Hold a piece (only one allowed at a time):
c- Soft drop the piece:
Down arrow key- Hard drop the piece:
Spacebar- Pause/unpause the game:
p- Quit the game:
q


Ruins & Raiders
a roleplaying game
v3.0
1. Introduction
1.1 Overview
1.2 Quick Reference
2. Adventurers
2.1 Traits
2.2 Skills
2.3 Gifts
2.4 Fortune
2.5 Equipment
2.6 Spells
3. Combat
3.1 Conflict
3.2 Swords, Slings, and Arrows
3.3 Casting Spells
3.4 Pain and Suffering
4. The World
4.1 Ruins of 1985
4.2 Monsters and Horrors
4.3 Adventurer Archetypes
4.4 Example Mage Spells
4.5 Example Sorcerer Spells


Vagrant is an amazing tool for short-lived and automated virtual machines, but the boxes are often quite outdated. boxes is a tool for automating building Vagrantboxes in many different styles. This is a list of recently constructed boxes, which are rebuilt every month.
Add a box as you would usually:
$ vagrant box add {title} {url}
$ vagrant init {title}
$ vagrant up
Additionally, it’ll work with the vagrant-box-updater plugin.


helpers
discernFileFormatter(fileName)
Returns a formatter that will format json data to file type specified by the extension in fileName
. Used internally by .writeData
and .writeDataSync
.
| parameter | type | description |
|---|---|---|
| fileName |
String
|
the name of the file |
Object
:
a formatter that can write the file
var formatter = io.discernFileFormatter('path/to/data.tsv');
var csv = formatter(json);
discernFormat(fileName)
Given a fileName
return its file extension. Used internally by .discernPaser
and .discernFileFormatter
.
| parameter | type | description |
|---|---|---|
| fileName |
String
|
the name of the file |
String
:
the file's extension
io.discernFormat('path/to/data.csv') -> 'csv'
discernParser(fileName, delimiter)
Given a fileName
, optionally a delimiter, return a parser that can read that file as json. Used internally by .readData
and .readDataSync
.
| parameter | type | description |
|---|---|---|
| fileName |
String
|
the name of the file |
| delimiter |
String
|
optional delimiter |
Object
:
a parser that can read the file
var parser = io.discernParser('path/to/data.csv');
var json = parser('path/to/data.csv');
readers
readCsv(fileName, callback)
Asynchronously read a comma-separated value file.
| parameter | type | description |
|---|---|---|
| fileName |
String
|
the name of the file |
| callback |
Function
|
callback used when read data is read, takes error (if any) and the data read |
readCsvSync(fileName)
Synchronously read a comma-separated value file.
| parameter | type | description |
|---|---|---|
| fileName |
String
|
the name of the file |
Object
:
the contents of the file as JSON
readData(fileName, delimiter, callback)
Asynchronously read data given a path ending in the file format.
Supported formats:
.json
Array of objects.csv
Comma-separated.tsv
Tab-separated.psv
Pipe-separatedNote: Does not currently support .dbf files.
| parameter | type | description |
|---|---|---|
| fileName |
String
|
the name of the file |
| delimiter |
String
|
optional delimiter to use when reading the file |
| callback |
Function
|
callback used when read data is read, takes error (if any) and the data read |
readDataSync(fileName, delimiter)
Syncronous version of readers#readData
| parameter | type | description |
|---|---|---|
| fileName |
String
|
the name of the file |
| delimiter |
String
|
optional delimiter to use when reading the file |
Object
:
the contents of the file as JSON
readDbf(fileName, callback)
Asynchronously read a dbf file.
| parameter | type | description |
|---|---|---|
| fileName |
String
|
the name of the file |
| callback |
Function
|
callback used when read data is read, takes error (if any) and the data read |
readJson(fileName, callback)
Asynchronously read a JSON file.
| parameter | type | description |
|---|---|---|
| fileName |
String
|
the name of the file |
| callback |
Function
|
callback used when read data is read, takes error (if any) and the data read |
readJsonSync(fileName)
Synchronously read a JSON file.
| parameter | type | description |
|---|---|---|
| fileName |
String
|
the name of the file |
Object
:
the contents of the file as JSON
readPsv(fileName, callback)
Asynchronously read a pipe-separated value file.
| parameter | type | description |
|---|---|---|
| fileName |
String
|
the name of the file |
| callback |
Function
|
callback used when read data is read, takes error (if any) and the data read |
readPsvSync(fileName)
Synchronously read a pipe-separated value file.
| parameter | type | description |
|---|---|---|
| fileName |
String
|
the name of the file |
Object
:
the contents of the file as JSON
readTsv(fileName, callback)
Asynchronously read a tab-separated value file.
| parameter | type | description |
|---|---|---|
| fileName |
String
|
the name of the file |
| callback |
Function
|
callback used when read data is read, takes error (if any) and the data read |
readTsvSync(fileName)
Synchronously read a tab-separated value file.
| parameter | type | description |
|---|---|---|
| fileName |
String
|
the name of the file |
Object
:
the contents of the file as JSON
readdirExclude(path, includes, callback)
Get a list of the files in a directory that do not have the selected extentions.
| parameter | type | description |
|---|---|---|
| path |
String
|
the directory to read from |
| includes |
Array<String > or String
|
the file extention(s) to include |
| callback |
Function
|
the callback that will accept the filtered files, takes an optional error and an array of file names |
readdirExcludeSync(path, includes)
Synchronously get a list of the files in a directory that do not have the selected extentions.
| parameter | type | description |
|---|---|---|
| path |
String
|
the directory to read from |
| includes |
Array<String > or String
|
the file extention(s) to include |
Array<String
>
:
the matching files' paths
readdirInclude(path, includes, callback)
Get a list of the files in a directory with selected extentions.
| parameter | type | description |
|---|---|---|
| path |
String
|
the directory to read from |
| includes |
Array<String > or String
|
the file extention(s) to include |
| callback |
Function
|
the callback that will accept the filtered files, takes an optional error and an array of file names |
readdirIncludeSync(path, includes)
Synchronously get a list of the files in a directory with selected extentions.
| parameter | type | description |
|---|---|---|
| path |
String
|
the directory to read from |
| includes |
Array<String > or String
|
the file extention(s) to include |
Array<String
>
:
the matching files' paths
writers
appendData(fileName, data, callback)
Append to an existing data object, creating a new file if one does not exist
Supported formats:
.json
Array of objects.csv
Comma-separated.tsv
Tab-separated.psv
Pipe-separatedNote: Does not currently support .dbf files.
| parameter | type | description |
|---|---|---|
| fileName |
String
|
the name of the file |
| data |
Object
|
the data to write |
| callback |
Function
|
callback that takes an error, if any |
appendDataSync(fileName, data)
Synchronous version of writers#appendData
| parameter | type | description |
|---|---|---|
| fileName |
String
|
the name of the file |
| data |
Object
|
the data to write |
writeData(fileName, data, callback)
Write the data object, inferring the file format from the file ending specified in fileName
.
Supported formats:
.json
Array of objects.csv
Comma-separated.tsv
Tab-separated.psv
Pipe-separatedNote: Does not currently support .dbf files.
| parameter | type | description |
|---|---|---|
| fileName |
String
|
the name of the file |
| data |
Object
|
the data to write |
| callback |
Function
|
callback that takes an error, if any |
writeDataSync(fileName, data)
Syncronous version of writers#writeData
| parameter | type | description |
|---|---|---|
| fileName |
String
|
the name of the file |
| data |
Object
|
the data to write |
writeDbfToData(inFileName, outFileName, callback)
Reads in a dbf file with .readDbf
and write to file using .writeData
.
| parameter | type | description |
|---|---|---|
| inFileName |
String
|
the input file name |
| outFileName |
String
|
the output file name |
| callback |
Function
|
callback that takes error (if any) |


An EA framework is a set of assumptions, concepts, values, and practices that constitutes a way of looking at enterprise reality via views on (architectural) models. It offers a fundamental structure, serving as a scaffold for developing, maintaining, and using EA.
Over the last 25 years, a number of enterprise architecture frameworks have come and gone. These frameworks have originated from different sources and have been applied in different contexts. Philip Allega, research analyst at Gartner, highlights an overwhelming proliferation of EA frameworks with a bit of frustration. In a blog entry titled “My Mother has an EA Definition, too,” he commented on the introduction of a new EA definition by the Enterprise Architecture Research Forum (EARF), South Africa, in August 2010:
If they’d only add a framework/approach to this definition I could notch my list of EA frameworks/approaches I’m tracking up by one (note: if you’re curious, I’m at 77 right now and if you’ve got one, please let me know). For those of you who aren’t used to reading with a sarcastic voice, please try using sarcasm when you say (out loud): The world really needs yet another definition of enterprise architecture <large, tired, shoulder shrugging sigh>
The true number of EA frameworks depends on what you count as a “framework”, but there is definitely an abundance of them. Moreover, they are quite different from each other. For instance, the Zachman Framework for Enterprise Architectures and The Open Group Architecture Framework (TOGAF) have hardly anything common between them except two words: architecture and framework. TOGAF, in fact, acknowledges Zachman as a complementing framework, which implies that TOGAF and Zachman indeed have only minimal overlap.
We cannot cover all the frameworks (or approaches, or methods—whatever you call them) that are out there.2 We will not assess, compare, nor endorse any of them, either. For the sake of brevity, we will simply have a quick glance at the methods we listed in the introduction:
We have selected each of them intentionally:
Of course, these frameworks are not the only ones that constitute the EA body of knowledge, as pointed out earlier. We do not intend to endorse these three frameworks as the best ones. However, these three are de facto among the most widely known approaches today. This is perhaps due to their versatility, visibility, and market impact so far.
EA has also received significant attention from academia, consulting firms, and governments. A number of academic institutions offer research briefings and learning programs regarding EA approaches and practices. They have been quite active and visible with their research on various EA topics in the last five years. Just to name a few prominent examples:
In addition, many established IT consulting firms, such as Accenture, Boston Consulting, Cap Gemini, Deloitte, Forrester, Gartner, HP, IBM, McKinsey & Company, and others, usually have their own EA approaches or methods (proprietary frameworks, so to speak) that they use while performing EA activities for their clients.
Finally, we should mention the Federal Enterprise Architecture (FEA). It is the enterprise architecture for the largest and most complex enterprise on Earth: the US federal government. Although FEA has been available only since 2006, its history dates back to 1996, when the US Congress passed a bill known as the Clinger Cohen Act.3 This bill mandates that all government agencies take steps to improve the effectiveness of their IT investments. FEA enables them to do that. The US government is one of the most serious adopters of enterprise architecture. The claim can be made that no enterprise has spent more money in EA than what has gone into FEA to date
Is there hope that this zoo of frameworks will disappears in the future and give room to only a few best-in-class frameworks? The answer to this question is tricky—maybe or maybe not. The main reasons for this state of affairs are as follows:


Ottawa Marathon
Ottawa ON/CAN
Web Site: www.runottawa.ca
Race Winners
(45 runnings)
2:28:45.9 2:32:14.0 2:28:19.0 2:27:40.9 2:28:43.9 27 May 2007
2:10:35.4
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2:18:24
2:54:25
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2:47:56
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2:50:50
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2:48:54
11 May
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2:42:50
13 May
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2:18:05
2:47:58
14 May
1978
2:16:03
2:47:37
15
May
1977
2:18:05
3:02:22
02 May
1976
2:16:32
3:09:27
25 May
1975
2:26:39
3:27:28
Notes: The inaugural year was 1975. Prior to 2003, this race was known as the National Capital Marathon. A marshalling
error in the 2006 race caused the first ten runners to run short by about 400 meters. They were subsequently awarded
places 3-12 and awarded an undisclosed amount of "compensation."
.
26 May
2019
2:08:02.7
Albert Korir (KEN)
2:26:33.8
Tigist Girma (ETH)
27 May
2018
2:08:52
Yemane Adhane Tsegay-2
2:22:17
Gelete Burka (ETH)
28 May
2017
2:10:13.2
Eliud Kiptanui (KEN)
2:30:17.5
Guteni Shone Imana (ETH)
29 May
2016
2:08:13.7
Dino Sefir Kemal (ETH)
2:27:05.4
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2015
2:08:13.4
Birhanu Gebre Girma (ETH)
2:25:29.8
Aberu Mekuria Zennebe (ETH)
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2014
2:06:54.0
Yemane Adhane Tsegay (ETH)
(nc)
2:24:30.3
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(nc)
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(nc)
2:25:30.1
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Laban Moiben-2
(nc)
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(nc)
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Laban Moiben (KEN)
(nc)
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(nc)
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2010
2:09:33.4
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Merima Mohammed (ETH) (nc)
24 May
2009
2:13:22.6
David Cheruiyot
Emmanuel-4 (nc)
Asmae Leghzaoui-2 (nc)
25 May
2008
2:10:59.8
David Cheruiyot
Emmanuel-3 (nc)
Asmae Leghzaoui (MAR) (nc)
David Cheruiyot
Emmanuel-2 (nc)
Lyudmila Korchagina-4 (nc)
Abderrahim Bouramdhane (MAR) (nc)
Lyudmila Korchagina-3 (CAN) (nc)
David Cheruiyot
Emmanuel (KEN) (nc)
Lidiya Vasilevskaya (RUS) (nc)
Elly Rono (KEN) (nc)
Lyudmila Korchagina-2 (nc)
Joseph Ndiritu-3
Sandy Jacobson (CAN)
Joseph Ndiritu-2 (nc)
Lyudmila Korchagina (RUS) (nc)
Joseph Ndiritu (KEN) (nc)
Danuta Bartosek (ON/CAN) (nc)
Bruce Deacon (CAN) (nc)
Veronique vanderSmissen-2 (nc)
Bruce Raymer (CAN)
Veronique vanderSmissen (CAN)
Malcolm Campbell (SCO)
Leslie Carson (ON/CAN)
Nick Tsioros (CAN)
Laura Ruptash (CAN)
Jean Legarde-4
Kimberly Webb (CAN)
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Noeleen Wadden (CAN)
Michael Petrocci-2
Betsy Kneale (USA)
Michael Petrocci (CAN) (nc)
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(nc)
Peter Maher (CAN)
Dorothy Goertzen (CAN)
Bruce Wainman (CAN)
Joan Groothvysen (CAN)
Ric Sayre (USA)
Marian Teitsch (USA)
David Edge (CAN) (nc)
Sylvie Ruegger (CAN) (nc)
Michael Dyon-3
Celia McInnis (CAN)
Gregory Leroy (OK/USA)
Margo Elson (CA/USA)
Michael Dyon-2
Kathryn Tanner (CAN)
Patrick Montuoro (CAN)
Christine Lavalee-2
Jerome Drayton (CAN)
Jacqueline Gareau (CAN)
Brian Maxwell (CAN)
Christine Lavalee (CAN) (nc)
Michael Dyon (CAN)
Joann McKinty-Heale (CAN)
Wayne Yetman (CAN)
Eleanor Thomas-2 (nc)
Mehdi Jaouhar (CAN)
Eleanor Thomas (CAN)
(nc) =>
national championship
2014 Eric Gillis was the national champion (8th
place,2:13:47)
2014 Rhiannon Johns was the national champion (9th place,2:47:11.8)
2013 Robyn Watson was the national champion (10th
place,2:18:33.3)
2013 Lyudmila Korchagina was the national champion (8th
place,2:33:10.2)
2012 Rejean Chiasson was the national champion (12th
place,2:19:54.6)
2012 Lisa Avery was the national champion (6th place, 2:42:52.8)
2011 Lucas McAneney was the national champion (11th place, 2:19:51.9)
2011 Emily Kroshus was the national champion (6th place, 2:42:26.2)
2010 Stephen Drew was the national champion (11th place, 2:21:46.3)
2010 Krista Duchene was the national champion (6th place, 2:39:07.3)
2009 Reid Coolsaet was the national champion (8th place, 2:17:09.5)
2009 Lyudmila Korchagina was the national champion (2nd place, 2:32:09.8)
2008 Giitha Macharia was the national champion (14th place, 2:16:54.1)
2008 Tara Quinn was the national champion (4th place, 2:33:58.3)
2007 Matthew McInnes was the national champion (10th place, 2:18:06.9)
2006 Charles Bedley was the national champion (19th place, 2:27:58)
2005 James Finlayson was the national champion (7th place, 2:18:20.7)
2005 Lyudmila Kotchagina was the national champion (2nd place, 2:32:18.5)
2004 Matthew McInnes was the national champion (7th place, 2:18:52.4)
2004 Nicole Stevenson was the national champion (3rd place, 2:34:45.0)
2002 Bruce Deacon was the national champion (2nd place, 2:15:46)
2002 Tania Jones was the national champion (2nd place, 2:39:17)
2001 Bruce Deacon was the national champion (2nd place, 2:18:54)
1988 Jean Payette was the national champion (2nd place, 2:54:27)
Most Wins
(1975-date)
Men
4
Jean Legarde (CAN)
1993-96
David Cheruiyot
Emmanuel (KEN)
2005,2007-09
Women
4
Lyudmila Korchagina (RUS)
2002,2004,2006-07
Prize Money
(ADR qualified runners)
Year Men Women Total 2017 $69,555 $73,270 $142,825 2016 77,665 78,070 155,735 2015 79,910 80,315 160,225 2014 85,970 67,920 153,890 2013 78,390 78,880 157,270 2012 73,825 66,510 140,335 2011 67,240 66,475 133,715 2010 74,565 52,285 126,850 2009 46,845 50,690 97,535 2008 61,095 55,675 116,770 2007 63,195 51,675 114,870 2006 38,800 49,350 88,150 2005 42,270 45,125 87,395 2004 32,855 31,830 64,685 2003 19,400 23,555 42,955 2002 20,600 20,320 40,920 2001 12,400 14,885 27,285 2000 2,495 2,360 4,855 1999 4,065 3,585 7,650 1998 1,045 2,090 3,135 1997 1,440 1,800 3,240 1996 2,220 1,850 4,070 1995 1,155 1,155 2,310 .... 1992 2,905 2,075 4,980 1991 2,935 2,590 5,525 1990 6,935 2,625 9,560 1989 7,820 3,060 10,880 1988 6,000 n/a 6,000 Sums $983,595 $930,020 $1,913,615
Race Time Bias (sec/km)
Year Men Women 2017 -2.9 +4.5 2016 +1.2 +0.0 2015 +0.8 n/c 2014 -1.8 n/c 2013 n/c -3.3 2012 -1.8 n/c 2011 -0.2 n/c 2010 -0.6 n/c 2009 +1.3 n/c 2008 -2.4 +0.7 2007 -1.7 -0.7 .... 2005 +0.8 -0.5 2004 -0.4 +0.9 2003 +0.5 n/c 2002 -1.1 +0.0 2001 +1.8 n/c .... 1984 -2.7 -3.3 Avgs -1.0 -0.2
Competitive Level (1990-date)
Year Men Women 2017<PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER> 105 n/c 2002<PHONE_NUMBER> 283 n/c
Quality Performances through 2019
Men <2:08 1 <2:09 11 <2:10 22 <2:11 44 <2:12 63 <2:13 72 <2:14 83 <2:15 96 Women <2:26 7 <2:28 20 <2:30 32 <2:32 43 <2:34 66 <2:36 77 <2:38 95 <2:40 111
Ottawa 10 km
Race Winners
(34 runnings)
33:12.8 31:43.2 32:11.5 31:50.4 32:42.1 26 May
2007
28:29.1
33:01.2
27 May
2006
28:29.5
32:05.0
28 May
2005
28:55.7
31:24.4
29 May
2004
28:59.8
32:30.3
10 May
2003
28:23.6
32:16.4
11 May
2002
28:29.8
32:57.7
12 May
2001
28:28.3
32:31.7
13 May
2000
29:32.1
33:36.2
08 May
1999
29:54
34:16.4
09 May
1998
29:06
34:28
10 May
1997
29:41
33:26
11 May 1996
29:55
34:54
14 May
1995
29:25
35:29
07 May
1994
29:52
34:32
08 May
1993
30:03
34:16
09 May
1992
28:56
33:20
11 Apr
1991
29:21
35:03
12 May
1990
29:22
34:28
13 May
1989
29:08
32:11
14 May
1988
28:12
34:24
09 May
1987
30:18
n/a
10 May
1986
29:30
35:37
25 May
2019
28:11.5
Mohammed Ziani (MAR) (nc)
31:08.8
Dorcas Kimeli (KEN) (nc)
26 May
2018
27:48
Andamlak Berta (ETH) (nc)
31:36
Alia Mohammed (UAE) (nc)
27 May
2017
28:42.1
Leul Gebreselasie Aleme
(ETH) (nc)
31:34.1
Netsanet Gudeta Kebede
(ETH) (nc)
28 May
2016
28:36.5
Mohamed Ziani (MAR)
31:28.8
Peres Chepchirchir (KEN)
23 May
2015
27:55.0
Nicholas Kipchirchir Bor
(KEN)
30:55.3
Gladys Cherono (KEN)
24 May
2014
28:00.7
Wilson Kiprop (KEN)
31:22.0
Mary Keitany Chepkosgei
(KEN)
25 May
2013
27:36.6
El Hassan El Abbassi
(MAR)
31:45.7
Malika Asahssah (MAR)
26 May
2012
27:41.4
Geoffrey Mutai Kiprono (KEN)
Lindsey Scherf (OR/USA)
28 May
2011
28:30.3
Deribe Merga Ejigu-2
Dire
Tune Arissi-2
29 May
2010
28:08.9
Lelisa Desisa Benti (ETH)
Dire Tune Arissi (ETH)
23 May
2009
27:23.9
Deribe Merga Ejigu (ETH)
Teyiba Erkiso Waka (ETH)
24 May
2008
28:37.0
Julius Kiptoo (KEN)
Emebet Bacha (ETH)
Simon Bairu (CAN)
Catherine Ndereba (KEN)
George Kirwa
Misoi-2
Tatyana Hladyr (UKR)
George Kirwa
Misoi (KEN)
Grace Momanyi
Kwamboka (KEN)
Duncan Kibet
Kirong (KEN) (nc)
Aster Demissie (ETH)
(nc)
Yevgeniy Bozhko (UKR)
Lyudmila Biktasheva (RUS)
Enos
Keter Kibet (KEN)
Uta Pippig-2
Julius Nderitu (KEN)
Uta Pippig (GER)
Paul Mbugua-3
Grace Momanyi
Kwamboka (KEN)
Paul Mbugua-2
Danuta Bartoszek (CAN)
Paul Mbugua (KEN)
Isabelle LeDroit (CAN)
Rachid Tbahi (MAR)
Sarah Dillabough (CAN)
Steve Boyd-2
Tania Jones-2
John Halvorsen-4
Tania Jones (CAN)
Jeff Lockyer (CAN)
Lisa Presedo-2
Steve Boyd (CAN)
Lisa Presedo (CAN)
John Halvorsen-3
Carole Rouillard (CAN)
John Halvorsen-2
Odette LaPierre-2
Paul McCloy (CAN)
Odette LaPierre (CAN)
Alberto Maravilha (POR)
Albertina Dias (POR)
John Halvorsen (NOR)
Sheryl Reid (CAN)
Paul Williams (CAN)
n/a
Robert Rice (CAN)
Maureen de St Croix (CAN)
Notes: 1986 was the inaugural year. Times for 2017 are net times.
(nc) =>
national championship
Dylan Wykes was the 2019 champion (29:56, 6th place)
Natasha Wodak was the 2019 champion (32:31, 8th place)
Evan Esselink was the 2018 champion (30:31, 9th place)
Rachel Cliff was the 2018 champion (32:23, 5th place)
Eric Gillis was the 2017 champion (30:09.0, 8th place)
Rachel Cliff was the 2017 champion (33:34.3, 5th place)
Taylor Murphy was the 2004 champion (30:38.7, 7th place)
Lucille Smith was the 2004 champion (32:52.1, 2nd place)
Most Wins (1986/date)
Men
4
John Halvorsen (NOR)
1988,1991-92,1995
Women
2
Odette LaPierre (CAN)
1990-91
.
Lisa Presedo (CAN)
1993-94
.
Tania Jones (CAN)
1995-96
.
Uta Pippig (GER)
2001-02
Dire Tune Arissi (ETH)
2010-11
Prize Money
(ADR qualified runners)
Year Men Women Total 2017 $21,600 $21,900 $43,500 2016 23,720 23,745 47,465 2015 23,900 26,375 50,275 2014 16,460 23,610 40,070 2013 23,235 19,720 42,955 2012 23,015 19,490 42,505 2011 19,600 23,850 43,450 2010 16,105 20,425 36,530 2009 22,695 15,680 38,375 2008 21,545 16,290 37,835 2007 20,835 15,505 36,340 2006 14,690 14,470 29,160 2005 12,255 14,925 27,180 2004 8,665 9,035 17,700 2003 9,250 9,435 18,685 2002 8,050 8,145 16,195 2001 8,325 8,240 16,565 2000 2,020 2,020 4,040 1999 1,690 1,690 3,380 1998 1,220 1,220 2,440 1997 1,080 1,260 2,340 1996 1,110 1,110 2,220 1995 770 770 1,540 1994 740 740 1,480 1993 1,110 1,295 2,405 1992 2,285 1,870 4,155 1991 2,165 865 3,030 1990 1,905 1,905 3,810 1989 2,300 1,465 3,765 1988 1,650 1,275 2,925 Sums $313,790 $308,325 $622,115
Race Time Bias (sec/km)
Year Men Women 2017 +0.6 +0.8 2016 +6.1 +4.8 2015 -3.2 -1.7 2014 +0.8 -1.4 2013 -2.6 n/c 2012 +2.3 -1.4 2011 +0.6 +0.4 2010 +0.6 -0.2 2009 -0.5 -1.9 2008 +1.9 +1.7 2007 +0.4 +1.3 2006 -0.4 +0.8 2005 -0.4 +1.2 2004 +0.0 -5.0 2003 -2.1 -2.3 2002 -3.2 -1.8 2001 -2.7 -3.7 2000 -0.5 -1.7 Avgs -0.1 -0.6
Competitive Level (1990-date)
Year Men Women 2017<PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER> 358 226
Quality Performances through 2019
Men <27:40 4 <28:00 7 <28:20 18 <28:40 47 <29:00 70
Women <31:00 1 <31:30 8 <32:00 21 <32:30 38 <33:00 65 <33:30 87 <34:00 126
Last Updated on 29 May 2019 mp
Contributors: Jim Robinson, Malcolm Heyworth, Marty Post, Maurice Wilson (11), Klaas Loonstra (1), Manny Rodrigues, Juraj Gasparovic (3), Elizabeth @ Sportstats, Jonathan Plata, John Halvorsen


@(snippet: CodeSnippet, analysisResult: Option[AnalysisResult]) @severityCssClass(severity: AnalysisResult.ComplaintSeverity) = { @severity match { case AnalysisResult.ComplaintSeverity.Fatal => {alert-danger} case AnalysisResult.ComplaintSeverity.Warning => {alert-warning} case _ => {} } } @main("Snippet") {
This snippet is still being analyzed, please wait...
(why you're here!)
@analysisResult match { case None => {In progress...
} case Some(analysis) if analysis.complaints.isEmpty => {Everything looks great!
} case Some(analysis) => {


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2021 Volvo S90 and V90 Facelift Wear Useless Camouflage Winter Testing
by Alex OaganaArguably, every single Volvo model unveiled after Geely purchased the Swedish company has been a massive improvement from its predecessor, but the S90/V90 lineup is probably the best example.
Despite featuring transverse engines and an FWD-based architecture, they have similar premium proportions as their German RWD rivals from BMW and Mercedes-Benz. Together with the “Thor's hammer” headlamp design and Scandinavian minimalist interiors, the two models represent the best that Volvo has to offer nowadays.
That said, even best-sellers need refreshing from time to time, especially since both have been continuously built with the same design since 2016. To be officially unveiled in the first half of 2020, the revamped Volvo S90 and V90 are currently cold-weather testing near the Arctic Circle.
Since the original recipe appears to still work, we won't be seeing an entirely different car when the facelift comes out, with Volvo choosing to keep the exterior modifications to the minimum.
In fact, we don't even understand why engineers bothered to camouflage parts of the prototypes, drawing even more attention from spy photographers in the process. The only exterior differences will be found in the lower part of the bumpers and the taillights.
The main changes will be found inside, where a new infotainment system is expected to find its home, while most of the engine lineup will be completely revamped to feature the 48-volt mild-hybrid technology already used on the refreshed XC90 II and the XC60 crossovers.
Thanks to an integrated starter-generator that can either reduce engine load or simply boost it to offer better acceleration in certain driving scenarios, the facelifted S90 and V90 should feel slightly sportier in a straight line while offering improved fuel economy. Obviously, the T8 AWD Twin Engine version will still feature a plug-in hybrid setup.
New exterior and interior colors are also expected, with the upholstery and cockpit design to be slightly refreshed as well. 🏁


A little bit about me
I've made my home base in Providence, Rhode Island, with my small growing family. My journey into tech started with a degree in journalism. As I started sharing my writing online, I was fascinated with how easily I could get my voice out there. I was hooked and wanted to learn how to build my own site to fit my own specific needs.
That curiosity then opened a door that could never be shut. When I learned how to build my first website, I realized I found something that gave me the freedom and versatility I was looking for in my work. Now I've made a full switch to front-end development, where I can use my organization skills and eye for detail to write clean, elegant code.
Hand-Coded HTML
My focus is on writing clean, well-formatted, semantic HTML5 by hand to make sure that the content is easy to read, easy to collaborate, trouble-shoot, and accessible.
Well-Organized CSS
I pride myself on writing CSS that is easy to read and build on. I focus on keeping my CSS lean and fast to load, and I make a habit to stay up to date on current best practices.
Ease Converting Design into Code
You can trust me to take a designer's PSD and quickly & accurately convert it into a webpage that is a pixel-perfect match.


- Version:  Hyperledger Fabric Bftsmart v1.1.1
- Size:  5 Peers, 1 Orderer(bftsmart)
- Distribution:  Single Host
 System Under Test
- Name:  Supply Chain network Benchmark
- Description:  This is an example benchmark for caliper, to test the backend DLT's performance with simple account opening & querying transactions
- report
 Benchmark
Agricultural
Food Supply Chain By Blockchain - Network Benchmark
Performance
- Transactions
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Submitted: 0, Succeeded: 0, Failed: 0
- Throughput
- Latency
Log
waiting for benchmark to start


EUR/USD Technical Analysis: On the back foot below 2-week-old horizontal area
by Anil Panchal- EUR/USD extends a breakdown of a weeklong rising trend line.
- November 11 high, 1.1016/15 could appear next on the sellers’ radar.
- 61.8% Fibonacci retracement adds to the resistance.
With its failure to cross a fortnight-long horizontal resistance area, EUR/USD declines to 1.1075 while heading into the European session on Wednesday.
The quote now aims to revisit November 11 high around 1.1045 ahead of revisiting the 1.1016/15 multiple support zone.
If prices refrain from bouncing off 1.1015, the monthly low near 1.0990 will be on their radars prior to October bottom of 1.0880.
On the upside break of the 1.1090/95 resistance area, buyers need to conquer the weeklong support-turned-resistance around 1.1100 while 61.8% Fibonacci retracement level of the current month downside, at 1.1105 could question the bulls afterward.
In a case of pair’s successful rise beyond 1.1105, 1.1140 and monthly top close to 1.1180 will come back on the chart
EUR/USD 4-hour chart
Trend: Bearish
additional important levels
| Overview | |
|---|---|
| Today last price | 1.1076 |
| Today Daily Change | -1 pip |
| Today Daily Change % | -0.01% |
| Today daily open | 1.1077 |
| Trends | |
|---|---|
| Daily SMA20 | 1.1081 |
| Daily SMA50 | 1.1043 |
| Daily SMA100 | 1.1093 |
| Daily SMA200 | 1.1177 |
| Levels | |
|---|---|
| Previous Daily High | 1.1086 |
| Previous Daily Low | 1.1062 |
| Previous Weekly High | 1.1058 |
| Previous Weekly Low | 1.0989 |
| Previous Monthly High | 1.118 |
| Previous Monthly Low | 1.0879 |
| Daily Fibonacci 38.2% | 1.1077 |
| Daily Fibonacci 61.8% | 1.1071 |
| Daily Pivot Point S1 | 1.1065 |
| Daily Pivot Point S2 | 1.1052 |
| Daily Pivot Point S3 | 1.1041 |
| Daily Pivot Point R1 | 1.1088 |
| Daily Pivot Point R2 | 1.1098 |
| Daily Pivot Point R3 | 1.1111 |


Markstrom helps Canucks to shootout win over Capitals
Jacob Markstrom stopped 32 shots and then denied seven more during an extended shootout, helping the Vancouver Canucks beat the Washington Capitals 2-1 on Saturday.
Elias Pettersson scored his 10th goal for Vancouver, which earned its second straight win since a stretch of seven losses in eight games. It was the Canucks’ 12th power-play goal in their last seven games.
Bo Horvat scored the decisive goal in the seventh round of the shootout.
Washington finished with one goal for the third time this season despite Vancouver losing defenceman Alexander Edler to an upper-body injury.


Gatekeeper Bella:
Your pet shall be a wolf. You must learn more about them.
Wolves are biologically classified as canines. Canines are extremely varied, and include dogs, raccoons, foxes, jackals, and even timberwolves. The lifespan of wolves in the wild is unknown, but wolves in captivity can live from 12 to 15 years.


Simon Cowell grins as he ditches healthy diet to sneak a cheeky beer and a cigarette
X Factor boss Simon Cowell couldn't stop smiling as he puffed on a fag and swigged a beer on a night out in London
by Louise Randell, https://www.mirror.co.uk/authors/louise-randell/Simon Cowell couldn't stop smiling as he ditched his healthy diet to sneak a cheeky beer and a cigarette on a night out in London.
The X Factor boss, 60, has lost an incredible 1.5 stone by becoming a vegan and embracing a new exercise regime.
However, he couldn't hide his delight as he clenched a cigarette between his teeth and clutched a bottle of beer after a night out with partner Lauren Silverman.
Simon flashed a huge grin in the car and continued puffing away in the back of his luxury ride.
The couple had been attending the Shooting Star Ball in West London, and it looks like they had a fun evening.
After deciding to overhaul his lifestyle, Simon was advised to give up booze along with sweet treats and bread.
In an interview with Extra, he explained: "I went to see this guy who’s very well-known.
"And he said to me, after doing some blood work, 'You can’t have red meat, dairy, sugar, bread or gluten.'
"I’m thinking, 'What about alcohol?' And he said, 'Maybe not quite as much as you had before.' And I did it and I stuck to it and it’s easy."
However, he hasn't given p booze completely as his Britain's Got Talen co-star Amanda Holden revealed Simon had switched to low alcohol "skinny lager".
During an appearance on Good Morning Britain, she said: "He’s drinking lightweight beers, that’s the secret.
"And I tasted it because I thought it was gonna taste, like, naff. Actually it’s quite decent. You could take a tip from him!"
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--- layout: archive title: Zulip Chat Archive permalink: /stream/113488-general/topic/coe.20mv_polynomial.html ---
Why is C
not a coercion α → mv_polynomial σ α
? Is this somehow a bad coercion?
These coercions are possible but limited in scope
you have to use has_coe_t
Also, aren't the terms big enough already? using coe
will only make them bigger
That's true. But now we have ↑n : mv_polynomial _ α
for n : ℕ
and also C (n : α)
.
Maybe we can still tag the relevant lemmas with norm_cast
even if it is not a coe?
It would be nice to normalise these things. I don't yet know what the normal form should be.
those two are not comparable - you need a lemma to connect them
I guess I would simp C ↑n = ↑n
and possibly use this backwards sometimes
Ok, thanks
{% endraw %}Last updated: Apr 24 2020 at 19:02 UTC


Frank K. 2000. Impact of a Confounding Variable on the Inference of a Regression Coefficient. Sociological Methods and Research, 29(2), 147-194.
Frank, K. A., & Min, K. (2007). Indices of Robustness for Sample Representation. Sociological Methodology. 37(1). 349-392. (equal first authors.)
Pan, W., & Frank, K.A. (2004). “An Approximation to the Distribution of the Product of Two Dependent Correlation Coefficients.” Journal of Statistical Computation and Simulation, 74(6), 419-443.
Pan, W., & Frank, K.A. (2004). “A probability index of the robustness of a causal inference,” Journal of Educational and Behavioral Statistics, 28(4), 315-337.
Frank, K. A., Sykes, G., Anagnostopoulos, D., Cannata, M., Chard, L., Krause, A., & McCrory, R. (2008). Does NBPTS certification affect the number of colleagues a teacher helps with instructional matters?. Educational Evaluation and Policy Analysis, 30(1), 3-30.
Frank, K. A., Maroulis, S. J., Duong, M. Q., & Kelcey, B. M. (2013). What would it take to change an inference? Using Rubin’s causal model to interpret the robustness of causal inferences. Educational Evaluation and Policy Analysis, 35(4), 437-460.
Xu, R., Frank, K. A., Maroulis, S. J., & Rosenberg, J. M. (2019). konfound: Command to quantify robustness of causal inferences. The Stata Journal, 19(3), 523–550. https://doi.org/10.1177/1536867X19874223
Li, T., & Frank, K. (2020). The probability of a robust inference for internal validity. Sociological Methods & Research. https://doi.org/10.1177/0049124120914922


The open source iRODS (Integrated Rule-Oriented Data System) data management platform presents a virtual filesystem, metadata catalog, and policy engine designed to give organizations maximum control and flexibility over their data management practices and enforcement. Since iRODS defines its own RPC API and protocol, interoperability with other software has always lagged new server features and functionality. In the last few years, the iRODS Community has been working on multiple ways to present the iRODS protocol more conveniently to other software.
This talk covers the efforts to present iRODS as WebDAV, FUSE, REST, NFS, SFTP, K8s CSI, and S3.
The iRODS Consortium was started as an open-source software development organization in 2013 by members of the research and storage communities. The technology has roots from an earlier project started in 1995. The Consortium was launched as a response to a major scale increase in management and storage needs driven by the advent of "big data". The member community is now comprised of over 30 members and spans the globe from the Australia to Japan and much of the EU.


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