Status: Passed, Jan 89 X3J13, as amended
Issue: STEP-ENVIRONMENT
References: STEP (CLtL p.441)
TIME (CLtL p.441)
Category: CLARIFICATION/CHANGE
Edit history: Version 1, 12-Mar-88, Moon
Version 2, 10-Jun-88, Masinter (add discussion)
Version 3, 20-Jun-88, Loosemore (not a special form)
version 4, 17-Mar-89, Masinter (as amended)
Problem description:
CLtL does not specify in what lexical environment the form given to STEP
is evaluated. Some people think it's supposed to be evaluated in the
null environment, others think it is supposed to be evaluated in the
current environment, the one in which the STEP form was evaluated.
The same considerations apply to TIME.
Proposal (STEP-ENVIRONMENT:CURRENT):
1. Clarify that STEP and TIME evaluate the form in the current environment.
2. Clarify that calls to both STEP and TIME may be compiled, but that
in the case of STEP, it is acceptable for an implementation to
interactively step through only those parts of the computation that are
interpreted.
Examples:
;Assuming X is not a special variable
(setq x 1)
(let ((x 2))
This should print and return 2, not 1, when interpreted.
Rationale:
1. It is more useful for the lexical environment to pass transparently
through STEP and TIME than to reset to the null environment.
2. Although STEP is primarily a debugging tool, there is no reason to
prevent it from being compiled correctly.
Current practice:
Vax Lisp behaves as proposed. Symbolics Common Lisp treats STEP as a special
form and does not allow it to be compiled.
Cost to Implementors:
Minimal.
Cost to Users:
None.
Cost of non-adoption:
These debugging tools will continue to have vague specifications.
Benefits:
Slightly more preicse specification of Common Lisp.
Esthetics:
Slightly improved.
Discussion:
There was some discussion of separating this out into two separate
proposals, but it didn't seem useful.
Eric Benson contributed the definition of TIME in Lucid Common Lisp:
`(time-internal #'(lambda () ,form)))
The function TIME-INTERNAL looks something like:
(defun time-internal (thunk)
(let ((before-time (get-time-state)))
(funcall thunk)
(print-time-information before-time (get-time-state)))))
The definition of STEP is similar. This is just to show that it is
easy to get the right lexical environment even though TIME and STEP
are macros.
VaxLisp expands STEP into something like:
`(let ((*eval-hook* #'step-command-loop))
,form))
Additional comments:
Verbally this was explained to mean that the body of the STEP would
not be stepped when compiled, but if it just happened to call an
interpreted function, that function would get stepped.


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tamarind
Get Version
0.4.0→ ‘tamarind’
What
Tamarind was designed to make it as easy as possible for developers to participate in the Semantic Web by exposing their data in accordance with applicable standards and ontologies. In particular, Tamarind targets developers using Ruby frameworks and ORMs.
Installing
sudo gem install tamarind
Demonstration of usage
Adding New OntologiesTo add an ontology, a developer need only follow these steps:
1. Under tamarind/branches, create a directory for the ontology along with a module that identifies the data fields necessary for filling in the ontology. (See the FOAF ontology as an example.) 2. Write the template using Ruby builder syntax and save it under the directory from step 1. Fields that must come from the database should be prefixed by the "@" sign. (Again, see the FOAF ontology as an example.) 3. There is no step three.
General Process for Using Ontologies In Your ApplicationTo use an ontology, a developer need only follow these steps:
1. Require the gem in your application
2. Check out the documentation for the gem to find what ontologies are supported and learn how to use the “offers_”
methods.
3. In your model file, call offers_
====Instructions for Merb (0.9.1 or greater)
in config/init.rb
Merb::BootLoader.before_app_loads do dependency ‘tamarind’ end
Merb::BootLoader.after_app_loads do Merb.add_mime_type(:rdf,:to_rdf,%w[application/rdf+xml]) end
in any controller that’s going to use Tamarind, add:
provides :rdf
in the model (e.g. User), add: offers_foaf :name => ‘username’, :email => ‘email’, #takes a hash mapping the ontology’s canonical attributes to the model’s accessors #defaults to using the same names
*in any view (e.g. the User show action) using Tamarind, add this to enable auto-discovery: http://groups.google.com/group/tamarindTODO – create Google Group – tamarind
How to submit patches
Read the 8 steps for fixing other people’s code and for section 8b: Submit patch to Google Groups, use the Google Group above.
The trunk repository is git://github.com/pius/tamarind.git
for anonymous access. Git it. Improve it.
License
This code is free to use under the terms of the MIT license.
Contact
Comments are welcome. Send an email to Pius Uzamere.
FIXME full name, 7th March 2008
Theme extended from Paul Battley


[1] Software that ships with same small form factor camera. EASY to upgrage into Vegas Pro software at around 100 is crippled.
[2] Software that ships with same small form factor camera.


By default, text is centered at the geometric center of the object it is associated with. The modifier ljust causes the left end to be at the specified point (which means that the text lies to the right of the specified place!), the modifier rjust puts the right end at the place. The modifiers above and below center the text one half line space in the given direction.
Text attributes can be combined:
Figure 7-1: Text attributes
What actually happens is that n text strings are centered in a box that is textwid wide by textht high. Both these variables are initially zero (that is pic’s way of not making assumptions about [tg]roff(1)’s default point size).
In GNU gpic, objects can have an aligned attribute. This only works if the postprocessor is grops or gropdf. Any text associated with an object having the aligned attribute is rotated about the center of the object so that it is aligned in the direction from the start point to the end point of the object. Note that this attribute has no effect for objects whose start and end points are coincident.


Instant Tom Yam Kung noodle soup
Instant noodles with processed spices are quick but not the most healthy. It’s important to add fresh veggies and eggs. It’s a quick tasty lunch, a life saver when going through a busy period.
- ⏲ Prep time: 10 minutes
- 🍳 Cook time: 10 minutes
- 🍽 Servings: 2 people
Ingredients
- 2 packages of vegetable- or tom yam-quick noodles
- 1 can coconut milk
- 10 small or 5 big mushrooms
- 2 eggs
- A few salad leaves (or practically any veggie you have in the fridge)
- 1 lime
- Coriander
Directions
- Put small amount of water and coconut milk to boil. Add the noodle spices.
- Chop the mushrooms and coriander (and other veggies if you wish). Cut the lime into four pieces.
- When boiling add mushroom, and crack the eggs directly into the pot (be sure not to stir after this, otherwise they will break). Wait 30 seconds to 1 minute.
- Add the noodles and salad leaves (or whatever veggie you got).
- After 3-5 minutes it’s done. Serve in deep bowls. Squeeze the lime juice and chopped coriander on top.

Contribution
Recipe tags:
thai
quick
soup
cheesefare


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?Ludwigia
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(Jacq.)
Raven
.
JL
T.P.
Ramamoorthy
1980
Determined
by
Missouri
Botanical
Garden
REVISION
OF
JUSSIAEA
J.
suffruticosa
L.
Philip
A.
Munz
,
1939
/{J~VtAs.
-
NEW
YORK
BOTANICAL
GARDEN
CARNEGIE
INSTITUTION
OF
WASHINGTON
UNITED
STATES
NATIONAL
MUSEUM
WEST
INDIAN
EXPLORATION
1913
ST.
THOMAS
N.
L.
BRITTON
)
E.
G.
BRITTON
>?
COLLECTORS
J.
A.
SHAFER
)
JANUARY
31-FEBRUARY
4,
1913
01447546
Legend -
Level of confidence that token is an accurately-transcribed word
extremely low
very low
low
undetermined
medium
high
very high


The Voyages of Doctor Dolittle
by Hugh Lofting
Part 5, Chapter 2: "The Men of the Moving Land"
Additional Information
- Year Published: 1922
- Language: English
- Country of Origin: England
- Source: Lofting, H. (1922). The Voyages of Doctor Dolittle. London, England: Lippincott Publishing.
-
Readability:
- Flesch–Kincaid Level: 4.2
- Word Count: 896
- Genre: Fantasy
- Keywords: 20th century literature, british literature, children's literature
- ✎ Cite This
Downloads
From that time on the Indians' treatment of us was very different. We were invited to their village for a feast to celebrate the recovery of the lost families. And after we had made a litter from saplings to carry the sick woman in, we all started off down the mountain.
On the way the Indians told Long Arrow something which appeared to be sad news, for on hearing it, his face grew very grave. The Doctor asked him what was wrong. And Long Arrow said he had just been informed that the chief of the tribe, an old man of eighty, had died early that morning.
"That," Polynesia whispered in my ear, "must have been what they went back to the village for, when the messenger fetched them from the beach.—Remember?"
 asked the Doctor.
"He died of cold," said Long Arrow.
Indeed, now that the sun was setting, we were all shivering ourselves.
"This is a serious thing," said the Doctor to me. "The island is still in the grip of that wretched current flowing southward. We will have to look into this to-morrow. If nothing can be done about it, the Indians had better take to canoes and leave the island. The chance of being wrecked will be better than getting frozen to death in the ice-floes of the Antarctic."
Presently we came over a saddle in the hills, and looking downward on the far side of the island, we saw the village—a large cluster of grass huts and gaily colored totem-poles close by the edge of the sea.
"How artistic!" said the Doctor—"Delightfully situated. What is the name of the village?"
"Popsipetel," said Long Arrow. "That is the name also of the tribe. The word signifies in Indian tongue, The Men of The Moving Land. There are two tribes of Indians on the island: the Popsipetels at this end and the Bag-jagderags at the other."
"Which is the larger of the two peoples?"
"The Bag-jagderags, by far. Their city covers two square leagues. But," added Long Arrow a slight frown darkening his handsome face, "for me, I would rather have one Popsipetel than a hundred Bag-jagderags."
The news of the rescue we had made had evidently gone ahead of us. For as we drew nearer to the village we saw crowds of Indians streaming out to greet the friends and relatives whom they had never thought to see again.
These good people, when they too were told how the rescue had been the work of the strange white visitor to their shores, all gathered round the Doctor, shook him by the hands, patted him and hugged him. Then they lifted him up upon their strong shoulders and carried him down the hill into the village.
There the welcome we received was even more wonderful. In spite of the cold air of the coming night, the villagers, who had all been shivering within their houses, threw open their doors and came out in hundreds. I had no idea that the little village could hold so many. They thronged about us, smiling and nodding and waving their hands; and as the details of what we had done were recited by Long Arrow they kept shouting strange singing noises, which we supposed were words of gratitude or praise.
We were next escorted to a brand-new grass house, clean and sweet-smelling within, and informed that it was ours. Six strong Indian boys were told off to be our servants.
On our way through the village we noticed a house, larger than the rest, standing at the end of the main street. Long Arrow pointed to it and told us it was the Chief's house, but that it was now empty—no new chief having yet been elected to take the place of the old one who had died.
Inside our new home a feast of fish and fruit had been prepared. Most of the more important men of the tribe were already seating themselves at the long dining-table when we got there. Long Arrow invited us to sit down and eat.
This we were glad enough to do, as we were all hungry. But we were both surprised and disappointed when we found that the fish had not been cooked. The Indians did not seem to think this extraordinary in the least, but went ahead gobbling the fish with much relish the way it was, raw.
With many apologies, the Doctor explained to Long Arrow that if they had no objection we would prefer our fish cooked.
Imagine our astonishment when we found that the great Long Arrow, so learned in the natural sciences, did not know what the word COOKED meant!
Polynesia who was sitting on the bench between John Dolittle and myself pulled the Doctor by the sleeve.
"I'll tell you what's wrong, Doctor," she whispered as he leant down to listen to her: "THESE PEOPLE HAVE NO FIRES! They don't know how to make a fire. Look outside: It's almost dark, and there isn't a light showing ii the whole village. This is a fireless people."


AMAZING PEOPLE ARE MAKING AMAZING DISIGNS IN A FUN ENVIRONMENT
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Firmware download
Download firmware
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choose firmware
push & update
Audio update
choose audio
push & update
Please connect to the robot WI-FI before uploading!


Working with the Corda Demo on Azure Marketplace¶
Corda ships with a VM image which can be used to deploy a pre-configured virtual machine on the Microsoft Azure Marketplace
This Corda Demo VM is an easy option for running the demos; it is NOT a development environment. When you are ready to get developing on Corda and start making contributions to the project please clone the GitHub Repos instead.
Pre-requisites¶
- Ensure you have a registered Microsoft Azure account and are logged on to the Azure portal.
- It is recommended you generate a private-public SSH key pair (see here)
Deploying the VM¶
Search the Azure Marketplace for Corda. Click the ‘Create’ button.
STEP 1: Basics
- Name: Choose an appropriate descriptive name for the VM
- VM Disk Type: Select ‘SSD’
- Username: Your preferred user name for the administrator account when accessing via SSH
- Authentication type: Select ‘SSH public key’, then paste the contents of your SSH public key file (see pre-requisites, above) into the box below. Alternatively select ‘Password’ to use a password of your choice to administer the VM
- Subscription: Select your subscription name
- Resource group: Select ‘Use existing’. From the drop-down menu, select your account group
- Location: Select the geographical location physically closest to you
Click ‘OK’
STEP 2: Size
A range of available hardware configurations will be presented, along with estimated costs. For the purposes of running the demos, a configuration of 2 cores and at least 14GB is recommended
Choose the required configuration and click ‘Select’.
STEP 3: Settings
Adjust any configuration settings required. For the purposes of running the Corda demos, all settings may be left as default.
STEP 4: Summary
The banner at the top of the dialog should read ‘Validation passed’ otherwise go back and adjust settings where needed.
Click ‘OK’ to proceed.
STEP 5: Buy
Click ‘Purchase’ to complete the configuration and start the VM deployment.
The VM will begin the deployment process, which typically takes 4-5 minutes to complete. To see progress, click on the “Deploying” icon displayed.
Once deployed, click ‘Overview’ to see the virtual machine details. Note down the Public IP address. You will need this to connect to the demo screens via your web browser:
Viewing the SIMM Valuation demo¶
The SIMM Valuation demo creates three nodes, representing three parties in the example workflow (Bank A, Bank B, Bank C). Each node listens on a different port - those used by the demo are:
SIMM Valuation Demo ports: 12005 (node A for Bank A), 12007 (node B for Bank B), 12009 (node C for Bank C)
Open three browser tabs and direct each one to
http://(public IP address):(port)/web/simmvaluationdemo
specifying each of the three ports above in different windows, e.g.
http://<IP_ADDRESS>/12005/web/simmvaluationdemo
You will be able to view the basic web interface identifying the different banks.
Now let’s take a look at a transaction between Bank A and B which is not visible to Bank C. This illustrates the restricted data sharing feature of Corda, i.e. data is shared on a need-to-know basis. Nodes provide the dependency graph of a transaction they are sending to another node on demand, but there is no global broadcast of all transactions.
- In the browser tab for Bank A (the top right hand corner shows which bank you are administering) click ‘Create New Trade’ from the top navigation bar
- Select to trade with Bank B
- Select ‘EUR Fixed 1y EURIBOR 3m’ from the drop down
- Click ‘Submit’ to create the trade
- In the browser tab for Bank B click ‘View Portfolio’ from the top navigation bar to see this new trade
- In the browser tab for Bank C click ‘View Portfolio’ from the top navigation bar and you will not be able to see the trade, as expected
Note
There is a known issue whereby some users may see a 400 error when navigating the SIMM Valuation demo. If you encounter this error, simply navigate back to the root page (http://(public IP address):(port)/web/simmvaluationdemo) in the browser before continuing.
Viewing the IRS demo¶
The IRS demo creates three nodes: Bank A, Bank B and a node that runs a notary, a network map and an interest rates oracle together. The two banks agree on an interest rate swap, and then do regular fixings of the deal as the time on a simulated clock passes. Each bank node listens on a different port - those used by the demo are:
IRS demo ports: 11005 (node A for Bank A), 11007 (node B for Bank B)
Open two browser tabs and direct one to each of the following:
http://localhost:11005/web/irsdemo
http://localhost:11007/web/irsdemo
You will be able to see the nodes’ view of the ledger.
Now let’s take a look at how the interest rates oracle provides interest rates for a deal with a semi-annual payment frequency, and how the two counterparties to the trade see the same deal information on their own nodes, i.e. you see what I see.
- In the browser tab for Bank A click ‘Create Deal’ from the top navigation bar
- Modify the terms of the IRS deal, or leave as default
- Click ‘Submit’ to create the deal
- In the browser tab for Bank A click ‘Recent Deals’ from the top navigation bar to view the deal
- In the browser tab for Bank B click ‘Recent Deals’ from the top navigation bar to view the deal. Compare the economic details to those shown in the Bank A tab
Viewing logs (advanced users)¶
Users may wish to view the raw logs generated by each node, which contain more information about the operations performed by each node.
You can access these using an SSH client of your choice (e.g. Putty) and logging into the virtual machine using the public IP address. Once logged in, navigate to
/opt/simm-nodes/
for the SIMM Valuation demo logs and
/opt/irs-nodes/
for the IRS demo logs. There are separate sub-directories for each of the three nodes (nodea, nodeb, nodec), each containing a /logs sub-directory.
The name of the log file will follow the name given to the service it reflects, e.g. node-clint-vm-test.log.
You can open log files with any text editor.
Next Steps¶
Now you have taken a look at two Corda demos do go and visit the dedicated Corda website
Or to get straight into the Corda open source codebase, head over to the Github Corda repo


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--- layout: single author_profile: true ---
I am currently a Postdoctoral Associate and Perkins Fellow at the Center for Digital Humanities at Princeton University. I received my PhD in English and Comparative Literature from Columbia University in August 2020. I study and teach the intersection of literary form, systems of information, and labor, from the nineteenth century to the present. My research, broadly speaking, takes a historical approach to critical data studies, cultural analytics, and the history of the novel in English.
Currently, I am working on a book project about the process of information storage, organization, and retrieval that shaped the narrative techniques of British novel in the age of statistics and state archives. I’m also at work on second project: an experiment in quantitative methods and disciplinary history.
This site houses material related to my research, teaching and other professional projects. My CV, current projects, and teaching, can be found under their respective tabs.


the XML document
the patch document
Maps namespace of the given node to target document. If the given node is an element, all its attributes will be mapped too. Also, all descendants of the given node will be mapped.
An anchor
is needed because this method descends into all descendants.
Namespace lookup happens on the anchor
and the target
nodes.
a imported node that will be put to target, please note that this node may not be in the patch document.
a node in the target document.
a node in the patch document, mostly likely the node being processed currently.
Maps namespace of the given attribute to target document.
Namespace lookup happens on the anchor
and the target
nodes.
a node from patch document
a node in the target document
a node in the patch document, mostly likely the node being processed currently.
Maps namespace of the given node to target document. If the given node is
an element, all its attributes will be mapped too.
Namespace lookup happens on the anchor
and the target
nodes.
a node from patch document
a node in the target document
a node in the patch document, mostly likely the node being processed currently.
Map the given namespace to target document's namespaces.
a qualified name from patch document
a node in the target document
a node from patch document
whether it's an attribute node
Sets the node prefix, and namespace URI if provided. Please note that the
namespace lookup list (_nsMap
) is not changed.
Sets the target XML document (not the patch).
the XML document
Generated using TypeDoc


Plugin Information |
|---|
View Package Drone Deployer on the plugin site for more information. |
This plugin allow one to deploy build artifacts to a Package Drone drone instance of version 0.11.5+
Package Drone Version
This plugin requires a Package Drone instance of at least version 0.11.5.
Provided meta data
During the uploda process the following meta data will be stored with each artifact as "provided metadata":
namespace:key |
Description |
|---|---|
jenkins:buildId |
The build ID of the Jenkins build |
jenkins:buildNumber |
The build number of the Jenkins build |
jenkins:jobName |
The name of the job |
jenkins:buildUrl |
The URL to the build job |
Found an issue?
Please report it on Github.
If you know how to fix it I am gladly accepting pull requests ;-)
Eclipse Public License
This plugin is licensed under the Eclipse Public License v1.0. https://www.eclipse.org/legal/epl-v10.html


THE X-FILES
A Film Review by James Berardinelli
RATING: *** OUT OF ****
United States, 1998 U.S. Release Date: 6/19/98 (wide) Running Length: 1:58 MPAA Classification: PG-13 (Violence, gore, mature themes) Theatrical Aspect Ratio: 2.35:1
Cast: David Duchovny, Gillian Anderson, Martin Landau, Blythe Danner, William B. Davis, Armin Mueller-Stahl, John Neville, Terry O'Quinn Director: Rob Bowman Producers: Chris Carter, Daniel Sackheim Screenplay: Chris Carter Cinematography: Ward Russell Music: Mark Snow U.S. Distributor: Twentieth Century Fox
There are two kinds of viewers for THE X-FILES movie: those have seen at least a few episodes of the TV series and those who have never watched it. I am a member of the latter group, so that's the perspective from which this review is written. As a result, I cannot assess how the film will appeal to a die-hard follower of the program. But, for the "uneducated" movie-goer, THE X-FILES offers two hours of solid entertainment. (Of course, one unanswered question is how many non-X FILES aficionados will exhibit sufficient interest to venture into a theater showing this picture.)
Transferring a television program to the big screen has become a routine procedure for a film industry starved for ideas, but this is a rare occasion when the movies continue the adventures begun on the small screen, with no re-casting involved. To date, the only TV-to-motion picture series to successfully make the transfer is STAR TREK, which brought the tales of Captain Kirk and his crew to the theaters, then eventually transferred command to Captain Picard after STAR TREK: THE NEXT GENERATION went off the air. Twentieth Century Fox is hoping THE wrinkle: the television series is still going strong.
In interviews, writer/producer/series creator Chris Carter has stated that his goal with THE X-FILES was to make a movie that could stand on its own. There's no question that he has succeeded. The script can be followed by someone with literally no previous knowledge of the characters or situations. FBI special agents Fox Mulder (David Duchovny) and Dana Scully (Gillian Anderson) are introduced as any motion protagonists might be, and we're presented with bits and pieces of information about their background through cleverly constructed dialogue. (By "cleverly," I mean that these passages don't cry out, "Character exposition!") Although I'm told that the storyline picks up where the last season of the TV program left off, there's no sense that new viewers are entering in the middle of things. The only obvious concession to the ongoing series is the ending, which includes several hooks that can be used to launch stories in the upcoming season.
As the film opens, the X-Files special unit of the FBI has been disbanded. Mulder and Scully have exchanged their investigations of things paranormal and extraterrestrial for more mundane matters such as terrorism. But, when an Oklahoma City-like bomb explosion destroys a $45 million building in Dallas, Mulder and Scully appear to be the FBI's first choice for fall guys. Their research to clear their names reveals what could be the tip of a massive cover-up of alien activity on Earth. And, as their search stretches from Texas to Washington D.C. to Antarctica, they come face-to-face with the dark secret that endangers the future of the human species.
Plot-wise, THE X-FILES bears more than a passing resemblance to 1996's alien invasion/conspiracy movie, THE ARRIVAL. (In fairness to THE X-FILES, the TV program preceded THE ARRIVAL by several years, and the latter probably owes more to the former than the other way around.) Although things get sloppy near the end, when several story holes are ignored or ineffectively plugged, the script as a whole exhibits an uncommon intelligence for this type of movie. In addition, director Rob Bowman (who has helmed a number of the TV episodes) maintains a fairly high level of tension as the complexities of the multi-layered plot mount. The movie is perhaps a little too long; cutting ten or fifteen minutes would have made for a better focused adventure.
It's not hard to understand the appeal of Mulder and Scully. Both are competent, intelligent, and resourceful, and their different approaches to their jobs (he's a believer; she's a skeptic) enable them to compliment one another. It also doesn't hurt that they're both likable and neither is hard on the eyes. Actors David Duchovny (who's no stranger to movies; his most recent foray being PLAYING GOD) and Gillian Anderson (who is more familiar to viewers of the small screen than the large one) are both accomplished and entirely believable in these roles. Of course, we would expect no less of them, since they have been inhabiting these fictitious shells for five years. The chemistry between them is palpable, blending camaraderie and respect with a little subtle romance.
The supporting cast is comprised of faces from the TV show, such as William B. Davis' mysterious cigarette-smoking figure and John Neville's "Well Manicured Man", and movie actors who are around for one-off appearances. These include Blythe Danner as the by-the- book FBI assistant director who is looking into the Dallas bombing, Martin Landau as a conspiracy theorist who occasionally feeds hints to Mulder about what's going on, Armin Mueller-Stahl as the leader of the cartel behind the global betrayal, and Terry O'Quinn as Mulder and Scully's (temporary) boss.
Having seen the movie, it's easy for me to comprehend why so many people are enamored with the series. Although a lot of the material explored in THE X-FILES isn't new or revolutionary, the style of presentation and the quality of the writing set this above most other conspiracy theory/alien invasion pictures. I won't claim that the experience of having watched this film will suddenly convert me into a weekly viewer of the TV show, but at least now I'm aware of what awaits if I choose to catch an episode. In a summer that has been characterized by over-hyped and largely pointless big-budget films, THE offerings.
Copyright 1998 James Berardinelli
- James Berardinelli e-mail<EMAIL_ADDRESS>Now with more than 1400 reviews... The ReelViews web site: http://movie-reviews.colossus.net/
"My belief is that no movie, nothing in life, leaves people neutral.
-- David Puttnam
The review above was posted to the
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The Internet Movie Database accepts no responsibility for the contents of the
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belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
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L'Auto (1998, NR)
Written and Directed by Richard Ferrando
Starring Aaron Miller and Brad J. Tarratt
Available at:
http://www.geocities.com/~yevlar//films/leauto/lauto-movie2.rm
As Reviewed by James Brundage
A word of advice to colleagues and independent film fans alike: watch the newsgroups. The newsgroups, the very item upon which you are most likely reading this review, is the ultimate in the form of free press. Anyone, even in the most oppressive totalitarian regime anywhere in the world, can post anything they would like to a newsgroup… provided they have access to a terminal with which to do so. Free speech exists there in its perfect form. On the very humble server (only 20,000 groups or so) that I use, news.alltel.net, you can find newsgroups ranging from alt.books.thomas-pynchon to microsoft.public.java.visualj++ to, being tongue-in-cheek, free.sex.
It was in search in alt.movies.cinematography that I discovered a link to the homepage of Rigor Mortis Productions, a company that has, in the span of three years (1997-1999), turned out 7 short films, including the brilliant sketch L'Auto.
Do not be scared away by its French name: this interesting little company is completely American, filming mostly in Royal Oak, Michigan. The imdb user commends for L'Auto was what originally brought it to the peak of my strange tastes an senses: A man has an interesting conversation with his car.
Going to the official website, I was expecting to hear something along the lines of the objects-as-narrators voice that novelist Tom Robbins has used, but instead was greeted by a nicely packaged, quick download (1.5 MB) RealVideo file of the entire film.
The free-expression artist in myself must stop to laud these people on that measure only. Far from worrying about making a profit off this film, it has become one of the first to enter the public domain. You do not have to pay to see it: all you need is an ISP and RealVideo. For those who do not have the internet, going and viewing this at your public library is an option. To see people not as concerned with making money hand over fist is music to my independent-film-loving ears.
As I was saying before I embarked on my crusade towards public-domain (long live MP3's), I expected Tom Robbins. Tom Robbins has a quiet humor, but nothing too over-the-top with each of his objects that he uses. Not only that, Tom Robbins spends countless hours inserting message into his novels, pondering over social issues, and telling an entertaining story.
Do not run away! Only number three applies to L'Auto!
L'Auto goes beyond entertaining… and into the realm of complete hilarity with this picturesque sketch where, when a man (John, played by Aaron Miller) yells at his Ford one too many times, the Ford (voiced by Brad J. Taratt) gets fed up and yells back.
What I was reminded of watching this was not Tom Robbins, not Michner, not anyone literary who uses objects or locations as narrators, but instead of … (drumroll, please) MONTY PYTHON. The entire effort seemed inspired by the Python film …And Now For Something Completely Different, a collection of the most famous Python sketches and short collected into one long, disjointed, and ungodly hilarious film.
The conversation has the Ford take the upper hand, yell at its driver in a British accent and complain about a rash the size of a Buick on its ass, to which John responds: "Not one single part of you is the size of a Buick!" only to have the Ford retort: "I was speaking metaphorically."
Like Monty Python, the only legitimate gripe that I have is that the acting isn't all that great.
The film makes fun in all sorts of ways, showing intelligence beyond what you would expect: who would think of a French title to an American film, only to joke? Not to mention it makes you think. It may be like the self-defense-against-a-vegetable-sketch from …And Now For Something Completely Different, but it does actually make you think.
I'm not going to say I can write a paper on this film, because I can't. In fact, this review is probably longer than the script, but damn, people, it's funny. Independent film fans, people who like off-the-wall-humor, and fellow critics alike, view this film. It's only ten minutes out of your day.
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


§533-4 Not in lands mortgaged for purchase money during coverture as against mortgagee. When a husband purchases lands during coverture, and at the same time mortgages his estate in the lands to secure the payment of the purchase money, his widow shall not be entitled to dower out of the lands, as against the mortgagee or those claiming under him, although she has not united in the mortgage, but she shall be entitled to her dower as against all other persons. [CC 1859, §1302; RL 1925, §3020; RL 1935, §4833; RL 1945, §12103; RL 1955, §319-4; HRS §533-4]
Case Notes
See 16 H. 489, 495.


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Troubleshooting tips¶
Diagnose: Customer complains they receive a HTTP status 500 when trying to browse containers¶
This entry is prompted by a real customer issue and exclusively focused on how
that problem was identified.
There are many reasons why a http status of 500 could be returned. If
there are no obvious problems with the swift object store, then it may
be necessary to take a closer look at the users transactions.
After finding the users swift account, you can
search the swift proxy logs on each swift proxy server for
transactions from this user. The linux bzgrep
command can be used to
search all the proxy log files on a node including the .bz2
compressed
files. For example:
$ PDSH_SSH_ARGS_APPEND="-o StrictHostKeyChecking=no" pdsh -l <yourusername> -R ssh \
-w <redacted>.68.[4-11,132-139 4-11,132-139],<redacted>.132.[4-11,132-139] \
'sudo bzgrep -w AUTH_redacted-4962-4692-98fb-52ddda82a5af /var/log/swift/proxy.log*' | dshbak -c
.
.
----------------
<redacted>.132.6
----------------
Feb 29 08:51:57 sw-aw2az2-proxy011 proxy-server <redacted>.16.132
<redacted>.66.8 29/Feb/2012/08/51/57 GET /v1.0/AUTH_redacted-4962-4692-98fb-52ddda82a5af
/%3Fformat%3Djson HTTP/1.0 404 - - <REDACTED>_4f4d50c5e4b064d88bd7ab82 - - -
tx429fc3be354f434ab7f9c6c4206c1dc3 - 0.0130
This shows a GET
operation on the users account.
Note
The HTTP status returned is 404, Not found, rather than 500 as reported by the user.
Using the transaction ID, tx429fc3be354f434ab7f9c6c4206c1dc3
you can
search the swift object servers log files for this transaction ID:
$ PDSH_SSH_ARGS_APPEND="-o StrictHostKeyChecking=no" pdsh -l <yourusername> -R ssh \
-w <redacted>.72.[4-67|4-67],<redacted>.[4-67|4-67],<redacted>.[4-67|4-67],<redacted>.204.[4-131] \
'sudo bzgrep tx429fc3be354f434ab7f9c6c4206c1dc3 /var/log/swift/server.log*' | dshbak -c
.
.
----------------
<redacted>.72.16
----------------
Feb 29 08:51:57 sw-aw2az1-object013 account-server <redacted>.132.6 - -
[29/Feb/2012:08:51:57 +0000|] "GET /disk9/198875/AUTH_redacted-4962-4692-98fb-52ddda82a5af"
404 - "tx429fc3be354f434ab7f9c6c4206c1dc3" "-" "-"
0.0016 ""
----------------
<redacted>.31
----------------
Feb 29 08:51:57 node-az2-object060 account-server <redacted>.132.6 - -
[29/Feb/2012:08:51:57 +0000|] "GET /disk6/198875/AUTH_redacted-4962-
4692-98fb-52ddda82a5af" 404 - "tx429fc3be354f434ab7f9c6c4206c1dc3" "-" "-" 0.0011 ""
----------------
<redacted>.204.70
----------------
Feb 29 08:51:57 sw-aw2az3-object0067 account-server <redacted>.132.6 - -
[29/Feb/2012:08:51:57 +0000|] "GET /disk6/198875/AUTH_redacted-4962-
4692-98fb-52ddda82a5af" 404 - "tx429fc3be354f434ab7f9c6c4206c1dc3" "-" "-" 0.0014 ""
Note
The 3 GET operations to 3 different object servers that hold the 3
replicas of this users account. Each GET
returns a HTTP status of 404,
Not found.
Next, use the swift-get-nodes
command to determine exactly where the
user’s account data is stored:
$ sudo swift-get-nodes /etc/swift/account.ring.gz AUTH_redacted-4962-4692-98fb-52ddda82a5af
Account AUTH_redacted-4962-4692-98fb-52ddda82a5af
Container None
Object None
Partition 198875
Hash 1846d99185f8a0edaf65cfbf37439696
Server:Port Device <redacted>.31:6202 disk6
Server:Port Device <redacted>.204.70:6202 disk6
Server:Port Device <redacted>.72.16:6202 disk9
Server:Port Device <redacted>.204.64:6202 disk11 [Handoff]
Server:Port Device <redacted>.26:6202 disk11 [Handoff]
Server:Port Device <redacted>.72.27:6202 disk11 [Handoff]
curl -I -XHEAD "`http://<redacted>.31:6202/disk6/198875/AUTH_redacted-4962-4692-98fb-52ddda82a5af"
<http://<IP_ADDRESS>:6202/disk6/198875/AUTH_db0050ad-4962-4692-98fb-52ddda82a5af>`_
curl -I -XHEAD "`http://<redacted>.204.70:6202/disk6/198875/AUTH_redacted-4962-4692-98fb-52ddda82a5af"
<http://<IP_ADDRESS>:6202/disk6/198875/AUTH_db0050ad-4962-4692-98fb-52ddda82a5af>`_
curl -I -XHEAD "`http://<redacted>.72.16:6202/disk9/198875/AUTH_redacted-4962-4692-98fb-52ddda82a5af"
<http://<IP_ADDRESS>:6202/disk9/198875/AUTH_db0050ad-4962-4692-98fb-52ddda82a5af>`_
curl -I -XHEAD "`http://<redacted>.204.64:6202/disk11/198875/AUTH_redacted-4962-4692-98fb-52ddda82a5af"
<http://<IP_ADDRESS>:6202/disk11/198875/AUTH_db0050ad-4962-4692-98fb-52ddda82a5af>`_ # [Handoff]
curl -I -XHEAD "`http://<redacted>.26:6202/disk11/198875/AUTH_redacted-4962-4692-98fb-52ddda82a5af"
<http://<IP_ADDRESS>:6202/disk11/198875/AUTH_db0050ad-4962-4692-98fb-52ddda82a5af>`_ # [Handoff]
curl -I -XHEAD "`http://<redacted>.72.27:6202/disk11/198875/AUTH_redacted-4962-4692-98fb-52ddda82a5af"
<http://<IP_ADDRESS>:6202/disk11/198875/AUTH_db0050ad-4962-4692-98fb-52ddda82a5af>`_ # [Handoff]
ssh <redacted>.31 "ls -lah /srv/node/disk6/accounts/198875/696/1846d99185f8a0edaf65cfbf37439696/"
ssh <redacted>.204.70 "ls -lah /srv/node/disk6/accounts/198875/696/1846d99185f8a0edaf65cfbf37439696/"
ssh <redacted>.72.16 "ls -lah /srv/node/disk9/accounts/198875/696/1846d99185f8a0edaf65cfbf37439696/"
ssh <redacted>.204.64 "ls -lah /srv/node/disk11/accounts/198875/696/1846d99185f8a0edaf65cfbf37439696/" # [Handoff]
ssh <redacted>.26 "ls -lah /srv/node/disk11/accounts/198875/696/1846d99185f8a0edaf65cfbf37439696/" # [Handoff]
ssh <redacted>.72.27 "ls -lah /srv/node/disk11/accounts/198875/696/1846d99185f8a0edaf65cfbf37439696/" # [Handoff]
Check each of the primary servers, <redacted>.31, <redacted>.204.70 and <redacted>.72.16, for this users account. For example on <redacted>.72.16:
$ ls -lah /srv/node/disk9/accounts/198875/696/1846d99185f8a0edaf65cfbf37439696/
total 1.0M
drwxrwxrwx 2 swift swift 98 2012-02-23 14:49 .
drwxrwxrwx 3 swift swift 45 2012-02-03 23:28 ..
-rw------- 1 swift swift 15K 2012-02-23 14:49 1846d99185f8a0edaf65cfbf37439696.db
-rw-rw-rw- 1 swift swift 0 2012-02-23 14:49 1846d99185f8a0edaf65cfbf37439696.db.pending
So this users account db, an sqlite db is present. Use sqlite to checkout the account:
$ sudo cp /srv/node/disk9/accounts/198875/696/1846d99185f8a0edaf65cfbf37439696/1846d99185f8a0edaf65cfbf37439696.db /tmp
$ sudo sqlite3 /tmp/1846d99185f8a0edaf65cfbf37439696.db
sqlite> .mode line
sqlite> select * from account_stat;
account = AUTH_redacted-4962-4692-98fb-52ddda82a5af
created_at =<PHONE_NUMBER>.42190
put_timestamp =<PHONE_NUMBER>.61411
delete_timestamp =<PHONE_NUMBER>.00514
container_count = 0
object_count = 0
bytes_used = 0
hash = eb7e5d0ea3544d9def940b19114e8b43
id = 2de8c8a8-cef9-4a94-a421-2f845802fe90
status = DELETED
status_changed_at =<PHONE_NUMBER>.00514
metadata =
Next try and find the DELETE
operation for this account in the proxy
server logs:
$ PDSH_SSH_ARGS_APPEND="-o StrictHostKeyChecking=no" pdsh -l <yourusername> -R ssh \
-w <redacted>.68.[4-11,132-139 4-11,132-139],<redacted>.132.[4-11,132-139|4-11,132-139] \
'sudo bzgrep AUTH_redacted-4962-4692-98fb-52ddda82a5af /var/log/swift/proxy.log* \
| grep -w DELETE | awk "{print $3,$10,$12}"' |- dshbak -c
.
.
Feb 23 12:43:46 sw-aw2az2-proxy001 proxy-server <redacted> <redacted>.66.7 23/Feb/2012/12/43/46 DELETE /v1.0/AUTH_redacted-4962-4692-98fb-
52ddda82a5af/ HTTP/1.0 204 - Apache-HttpClient/4.1.2%20%28java%201.5%29 <REDACTED>_4f458ee4e4b02a869c3aad02 - - -
tx4471188b0b87406899973d297c55ab53 - 0.0086
From this you can see the operation that resulted in the account being deleted.
Procedure: Deleting objects¶
Simple case - deleting small number of objects and containers¶
Note
swift-direct
is specific to the Hewlett Packard Enterprise Helion Public Cloud.
Use swiftly
as an alternative.
Note
Object and container names are in UTF8. Swift direct accepts UTF8 directly, not URL-encoded UTF8 (the REST API expects UTF8 and then URL-encoded). In practice cut and paste of foreign language strings to a terminal window will produce the right result.
Hint: Use the head
command before any destructive commands.
To delete a small number of objects, log into any proxy node and proceed as follows:
Examine the object in question:
$ sudo -u swift /opt/hp/swift/bin/swift-direct head<PHONE_NUMBER>12345 container_name obj_name
See if X-Object-Manifest
or X-Static-Large-Object
is set,
then this is the manifest object and segment objects may be in another
container.
If the X-Object-Manifest
attribute is set, you need to find the
name of the objects this means it is a DLO. For example,
if X-Object-Manifest
is container2/seg-blah
, list the contents
of the container container2 as follows:
$ sudo -u swift /opt/hp/swift/bin/swift-direct show<PHONE_NUMBER>12345 container2
Pick out the objects whose names start with seg-blah
.
Delete the segment objects as follows:
$ sudo -u swift /opt/hp/swift/bin/swift-direct delete<PHONE_NUMBER>12345 container2 seg-blah01
$ sudo -u swift /opt/hp/swift/bin/swift-direct delete<PHONE_NUMBER>12345 container2 seg-blah02
etc
If X-Static-Large-Object
is set, you need to read the contents. Do this by:
- Using swift-get-nodes to get the details of the object’s location.
- Change the
-X HEAD
to-X GET
and runcurl
against one copy. - This lists a JSON body listing containers and object names
- Delete the objects as described above for DLO segments
Once the segments are deleted, you can delete the object using
swift-direct
as described above.
Finally, use swift-direct
to delete the container.
Procedure: Decommissioning swift nodes¶
Should Swift nodes need to be decommissioned (e.g.,, where they are being re-purposed), it is very important to follow the following steps.
- In the case of object servers, follow the procedure for removing the node from the rings.
- In the case of swift proxy servers, have the network team remove the node from the load balancers.
- Open a network ticket to have the node removed from network firewalls.
- Make sure that you remove the
/etc/swift
directory and everything in it.


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“I've invested with the team at Scoutpads over the last year or so and have been blown away with the results. As someone who is super busy and focused on my career, Scoutpads was able to introduce me to real estate deals that were off market and have terrific projected returns.”
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Estimates correlation coefficients with associated confidence limits for bivariate, partially censored survival times. Uses the iterative multiple imputation approach proposed by Schemper, Kaider, Wakounig and Heinze, Statistics in Medicine 2013. Provides a scatterplot function to visualize the bivariate distribution, either on the original time scale or as copula.
| Version: | 1.0 |
| Depends: | R (≥ 3.0.2) |
| Imports: | survival, fields |
| Published: | 2015-02-26 |
| Author: | Meinhard Ploner, Alexandra Kaider and Georg Heinze |
| Maintainer: | Georg Heinze <georg.heinze at meduniwien.ac.at> |
| License: | GPL-2 | GPL-3 [expanded from: GPL] |
| NeedsCompilation: | no |
| In views: | Survival |
| CRAN checks: | SurvCorr results |
| Reference manual: | SurvCorr.pdf |
| Package source: | SurvCorr_1.0.tar.gz |
| Windows binaries: | r-devel: SurvCorr_1.0.zip, r-release: SurvCorr_1.0.zip, r-oldrel: SurvCorr_1.0.zip |
| OS X binaries: | r-release: SurvCorr_1.0.tgz, r-oldrel: SurvCorr_1.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=SurvCorr to link to this page.


 Originally, though, the post was intended to be about what I was developing for Twitter. It’s nothing amazing or even complicated, but it was a fun learning experience… Twitter itself not withstanding. I made a Twitter bot tweeting different shades of pink each day. Since that’ll most likely seem nonsensical to most people, let me explain.
Background⌗
A little over a year ago, a friend and I started a podcast. I won’t go into the backstory of why we named it what we did, but the name of the podcast revolved around the color pink due to an inside joke between my friend and I. We ended up publishing 21 episodes in the span of a year before we decided to stop it. I had moved about an hour away from where I previously lived for a new job, so recording in-person involved a decent bit of travel for one of us. Then the coronavirus pandemic really started to take off in my country, and given what a dumpster fire trying to record a podcast remotely is, my friend and I jointly decided to shutter the podcast. It was a fun experience, but nothing either of us were really wanting to keep putting time and money into. As is typically the case, we reached this conclusion just a month after the hosting for both the podcast and our website renewed. Go figure.
That being said, we had set up social media for the podcast, and that social media was now doing exactly nothing. While I didn’t want to do anything with the Facebook or Instagram accounts that my co-host ran (you couldn’t pay me to touch a Facebook property), I thought about what I could do with the lingering Twitter account. I eventually decided to make a simple bot that would tweet a different shade of the color pink each day.
Python and Beautiful Soup⌗
As I mentioned previously, the actual code to post to Twitter ended up being extremely simple. I just used the Twython library to do the heavy lifting. What ended up being more interesting was how to create the database of colors I would use. After all, I don’t personally know that many different shades fo pink, and I wanted to include the RGB and hex color codes for each shade in the daily post. I basically needed a repository of shades of pink. After some DuckDuckGo-fu, I eventually found a page that included not just the RGB and hex color codes, but also a name. It was exactly what I needed.
The only problem was how to get the information from that page into something I could use in my script for the bot. My immediate thought was to copy and paste all of the information, but along with being error-prone over hundreds of shades, that’s also insanely tedious. In a shell script, something like xmllint
would fit the bill. Since I was already working in Python, though, I decided to use Beautiful Soup. I had actually used Beautiful Soup one time before on a project years ago where I admittedly didn’t really know Python and most definitely didn’t understand what I was doing with Beautiful Soup; I just ended up copying and pasting a bunch of code from the Internet until things worked the way I wanted.
This time, I took just a little time to read the documentation for Beautiful Soup and understand what I was actually doing. The crux of my script comes down to:
divisions = soup.find_all("div", {"class": "color-inner"})
This gets me each of the div
groupings for a color. With each of those groupings defined, it was then simple to get the name, hex, and RGB information I needed:
for division in divisions:
color_name = division.find("span", {"class": "color-sub"}).get_text()
color_hex = division.find("span", {"class": "color-id"}).get_text()
color_rgb = division.find("span", {"class": "color-rgb"}).get_text()
Instead of trying to copy everything by hand, I had a working script to get all of the colors without needing to worry about human error. Plus, if the source website adds any new colors it’s trivial to re-run the script and get an updated list. I ended up making a map for each color and adding all of the maps to a list.
rows.append({"name": color_name, "hex": color_hex, "rgb": color_rgb})
Then I wrapped it all up at the end by exporting the list of maps to a JSON file.
with open('pinks.json', 'w') as outfile:
json.dump(all_colors, outfile)
My other script which actually pushes the post to Twitter ingests this JSON file and then selects a random shade from it.
Twitter Still Sucks⌗
As if further proof was needed that Twitter is garbage, though, I found myself simultaneously amused and irritated just a few days ago when I saw that a daily post had not been completed. When logging into the account for the bot, I received a notification that the account had been flagged for “suspicious activity”, and I had to walk through a verification process before the account could post again. It’s amazing to me that a platform which tolerates the most hateful and dangerous rhetoric chooses to flag a clear bot that makes a single post each day with details on a different shade of the color pink as “suspicious.” It’s just further proof that Twitter really isn’t worth anyone’s time at this point.
My latest project, though, involves pushing data to Mastodon instead of Twitter. This post will serve as the first test of it, so assuming everything works look for a post on that in the near future.


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BREAD BEACON
A Resource for Hungry Students
OVERVIEW
HEADING
Heading
SECTION HEADING
Another Heading
THE TEAM
Together


We didn’t get to where we are by doing things the same way everyone else does. Neither did any
of the people we collaborate with every day. See more about the people and places that insprie us.
We didn’t get to where we are by doing things the same way everyone else does.Neither did any
of the people we collaborate with every day. See more about the people and places that insprie us.
THE TEAM
Our crew is motley. Our interests are varied. Our skills are mixed. And we wouldn’t have it any other way.
We didn’t get to where we are by doing things the same way everyone else does.Neither did any
of the people we collaborate with every day. See more about the people and places that insprie us.


Hello I'm Serena and welcome to my blog. I post some tech things as well as my nonsense projects. I do the SRE thing and recently got into CTFs.


Hangman
Find the hidden word by typing the letters!
Keyboard
Play Again
You have already entered this letter


Dataloaders for AffSpec¶
AffSpec Transform¶
-
class
dataloader.custom_transforms.
FaceCrop
(scale=1.3)[source]¶ Crop the face region from an image
- Parameters
scale (float) – The scale is numerical ratio for cropping the face. e.g. If it is greater than 1, then the cropped face will be bigger than the detected face (crop more in backgrounds) If it is smaller than 1, then the cropped face will be smaller than the detected face (hair, chin, etc are cropped away)
- Returns
the PIL image.
- Return type
image (Image.array)


Classes
The following classes are available globally.
-
M3U8Parser
handles parsing all type of playlists (master/video/audio/subtitles).The parser can be used multiple times, but make sure to reset the state.
See moreDeclaration
Swift
public class M3U8Parser
-
See moreM3U8Manager
is an helper class for fetching and parsing playlists. This class is used for convenience, and its functionality can be mimiced by using theM3U8Parser
,PlaylistFetcher
and other required params.Declaration
Swift
public class M3U8Manager
-
See morePlaylistOperation
operation handles fetching and parsing a single playlist object.Declaration
Swift
public class PlaylistOperation: Operation
-
Repesents
See moreEXT-X-TARGETDURATION
tag.Declaration
Swift
public class EXT_X_TARGETDURATION: BaseValueTag<Int>
-
Repesents
See moreEXT-X-VERSION
tag.Declaration
Swift
public class EXT_X_VERSION: BaseValueTag<Int>
-
Repesents
See moreEXT-X-MEDIA-SEQUENCE
tag.Declaration
Swift
public class EXT_X_MEDIA_SEQUENCE: BaseValueTag<Int>
-
Repesents
See moreEXT-X-PLAYLIST-TYPE
tag.Declaration
Swift
public class EXT_X_PLAYLIST_TYPE: BaseValueTag<PlaylistTagType>
-
Repesents
See moreEXT-X-ALLOW-CACHE
tag.Declaration
Swift
public class EXT_X_ALLOW_CACHE: BaseValueTag<BoolTagType>
-
Repesents
See moreEXT-X-BITRATE
tag.Declaration
Swift
public class EXT_X_BITRATE: BaseValueTag<Int>
-
Repesents
See moreEXTINF
tag.Declaration
Swift
public class EXTINF: BaseValueTag<Double>, MultilineTag
-
Repesents
See moreEXT-X-KEY
tag.Declaration
Swift
public class EXT_X_KEY: BaseAttributedTag
-
Repesents
See moreEXT-X-STREAM-INF
tag.Declaration
Swift
public class EXT_X_STREAM_INF: BaseAttributedTag, MultilineTag
-
Repesents
See moreEXT-X-MEDIA
tag.Declaration
Swift
public class EXT_X_MEDIA: BaseAttributedTag
-
MediaPlaylistTagsBuilder
used to buildMediaPlaylistTags
object. Aggregates the results when parsing and building at the end.Declaration
Swift
public class MediaPlaylistTagsBuilder
-
Undocumented
See moreDeclaration
Swift
public class DefaultPlaylistFetcher: PlaylistFetcher
-
A base tag that represent tags with single value.
See moreDeclaration
Swift
public class BaseValueTag<T: StringInitializable>: Tag
-
A base attribute tag, the holds tag info + attributes.
See moreDeclaration
Swift
public class BaseAttributedTag: AttributedTag


Quality Model
Provide linguistic feedback in SDL Trados Studio using a unified comment tool.
More »
Subtitle Converter
Convert film scripts from Excel format into well-formated text files so that you can create Subtitles in Subtitle Edit.

More »
Excel Splitter
Split up any Excel workbook with multiple worksheets into seperate files for each sheet.
More »
VobSub Exporter
Raise your wand and curse Imperio! onto Subtitle Edit: Automatically turn your selected text files into VobSub files to overlay them on VLC.
More »
Look Up Text
Look up any highlighted text in Trados or the most recently opened PDF file.
More »
Script Preparer (AutoHighlight)
Auto-prepares Film Scripts (Excel) for the AutoHighlight PDF tool (Final QC).
More »
Trados Hotkeys
Quickly jump between several Trados tabs, locate the source segment in an opened PDF, and more!
More »
Length Counter
Learn to count with the count! Quickly identify the character length of a text, either with or without spaces.
More »
Caption Comparer
Quickly scroll through two sets of PDFs (source and translation) to compare large amounts of files in hyperspeed.
More »
PDF Page Jumper
Jump to the next page in all PDF windows – instantly, in 1 click!
Flash Page Jumper
Scroll through source and translation flash files as well as through the translated PDF, all in the same time!
AutoHighlight
Highlight a selected list of terms across multilple PDFs in order to quickly identify key terms and compare translation and source to each other.
More »
Volume Control
Regulate the volume and press play or pause all via keyboard!

More »
Caption Compiler
Export all captions (highlighted rows) from multiple Excel files and display them in one tidily formatted Excel sheet!
More »


Name
Street
State
Select One
IOWA
NY
Zip Code
How many seats?
Which taxi do you require?
CAR
VAN
TUK TUK
Extras
Baby Seat
WheelChair Access
Stock Tip
Special Instructions


TeaToken is an utility token compliant with Ethereum's ERC20 Token Standard which helps to facilitate transactions between Tea businesses and Tea customers all over the world through the TeaBay™ platform. The TeaBay platform will be a marketplace in which farmers, business owners and tea consumers will be able to trade products and services.
The main purporse of the Token is meant to help fuel transactions within the TeaBay platform. Although not the main purpose, the token can be traded outside the TeaBay platform.
As an utility Token it represents a mean of interaction between users of the TeaToken platform. Ownership of the tokens represents no more than the right to participate in the TeaToken platform. The tokens are not intended to be a security, commodity or any other kind of financial instrument.
As an ERC20 Standard Token, you can view your token balance in any Ethereum Wallet with ERC20 Tokens support.
TeaToken is an ERC20 Token and can be stored in any Ethereum ERC20 compatible wallets. The most popular on Ethereum are Ledger Nano S hardware wallet and MyEtherWallet online Wallet.


Features¶
Overview¶
With the great success of deep learning,DNN-based techniques have been widely used in CTR estimation task.
DNN based CTR estimation models consists of the following 4 modules:
Input,Embedding,Low-order&High-order Feature Extractor,Prediction
- Input&Embedding
The data in CTR estimation task usually includes high sparse,high cardinality categorical features and some dense numerical features.
Since DNN are good at handling dense numerical features,we usually map the sparse categorical features to dense numerical through embedding technique.
For numerical features,we usually apply discretization or normalization on them.
- Feature Extractor
Low-order Extractor learns feature interaction through product between vectors. Factorization-Machine and it’s variants are widely used to learn the low-order feature interaction.
High-order Extractor learns feature combination through complex neural network functions like MLP,Cross Net,etc.
Models¶
FNN (Factorization-supported Neural Network)¶
According to the paper,FNN learn embedding vectors of categorical data via pre-trained FM. It use FM’s latent vector to initialiaze the embedding vectors.During the training stage,it concatenates the embedding vectors and feeds them into a MLP(MultiLayer Perceptron).
FNN api link
PNN (Product-based Neural Network)¶
PNN concatenates sparse feature embeddings and the product between embedding vectors as the input of MLP.
PNN api link
Wide & Deep¶
WDL’s deep part concatenates sparse feature embeddings as the input of MLP,the wide part use handcrafted feature as input. The logits of deep part and wide part are added to get the prediction probability.
WDL api link
DeepFM¶
DeepFM can be seen as an improvement of WDL and FNN.Compared with WDL,DeepFM use FM instead of LR in the wide part and use concatenation of embedding vectors as the input of MLP in the deep part. Compared with FNN,the embedding vector of FM and input to MLP are same. And they do not need a FM pretrained vector to initialiaze,they are learned end2end.
DeepFM api link
MLR(Mixed Logistic Regression/Piece-wise Linear Model)¶
MLR can be viewed as a combination of 2*m LR model,m is the piece(region) number. m LR model learns the weight that the sample belong to each region,another m LR model learn sample’s click probability in the region. Finally,the sample’s CTR is a weighted sum of each region’s click probability.Notice the weight is normalized weight.
MLR api link
NFM (Neural Factorization Machine)¶
NFM use a bi-interaction pooling layer to learn feature interaction between embedding vectors and compress the result into a singe vector which has the same size as a single embedding vector. And then fed it into a MLP.The output logit of MLP and the output logit of linear part are added to get the prediction probability.
NFM api link
AFM (Attentional Factorization Machine)¶
AFM is a variant of FM,tradional FM sums the inner product of embedding vector uniformly. AFM can be seen as weighted sum of feature interactions.The weight is learned by a small MLP.
AFM api link
DCN (Deep & Cross Network)¶
DCN use a Cross Net to learn both low and high order feature interaction explicitly,and use a MLP to learn feature interaction implicitly. The output of Cross Net and MLP are concatenated.The concatenated vector are feed into one fully connected layer to get the prediction probability.
DCN api link
DIN (Deep Interest Network)¶
DIN introduce a attention method to learn from sequence(multi-valued) feature. Tradional method usually use sum/mean pooling on sequence feature. DIN use a local activation unit to get the activation score between candidate item and history items. User’s interest are represented by weighted sum of user behaviors. user’s interest vector and other embedding vectors are concatenated and fed into a MLP to get the prediction.
xDeepFM¶
xDeepFM use a Compressed Interaction Network (CIN) to learn both low and high order feature interaction explicitly,and use a MLP to learn feature interaction implicitly. In each layer of CIN,first compute outer products between \(x^k\) and \(x_0\) to get a tensor \(Z_{k+1}\),then use a 1DConv to learn feature maps \(H_{k+1}\) on this tensor. Finally,apply sum pooling on all the feature maps \(H_k\) to get one vector.The vector is used to compute the logit that CIN contributes.
xDeepFM api link
AutoInt(Automatic Feature Interaction)¶
AutoInt use a interacting layer to model the interactions between different features.  By stacking multiple interacting layers,AutoInt is able to model different orders of feature interactions.
AutoInt api link


Let's walk through the process of making a simple game with the PushButton Engine.
TODO: Use the project manager!
TODO: Edit the level pbe file!
TODO: Add references to external components.
TODO: Create/edit an existing component!

TODO: How do you view the logger output?


| Class | Description |
|---|---|
| AliasAnalysis |
Compute an approximate may-alias relation for record type variables
We say that two record variables x and y may-alias if there is a way for them to
point to the same record.
|
| AstToUntypedIRVisitor |
Created by gcampagn on 1/20/17.
|
| CompileToIRPass |
Compile each event from symbols to TypedIR in SSA form
Created by gcampagn on 1/20/17.
|
| ConstantFolding |
Created by gcampagn on 2/15/17.
|
| ConstantFolding.ConstantState | |
| CopyPropagation |
Created by gcampagn on 2/16/17.
|
| DeadControlFlowElimination |
Eliminate if statements with constant branches
Created by gcampagn on 2/16/17.
|
| DeadStoreEliminationPass |
Like dead value elimination, but also eliminates field stores to
records that don't alias
The goal is to eliminate dumb code that sets a field but does not
save the record, which would confuse the operation analysis
Created by gcampagn on 2/15/17.
|
| DeadValueEliminationPass |
Eliminates instructions with no side effects that
compute unused values.
|
| IntoSSAPass |
Convert the IR into SSA form, renaming the registers and
adding any necessary phi nodes
To convert into SSA, we first compute reaching definitions
for each variable at the start of each block.
|
| IntoSSAPass.Definition | |
| IntoSSAPass.PhiNode | |
| LowerIRPass |
Lower IR before it is consumed by code generation backends.
|
| OptimizePass |
Wrap all IR optimizations in a single pass
Created by gcampagn on 2/21/17.
|
| OutofSSAPass |
Converts an IR in SSA form into an IR with no phi nodes
The algorithm is pretty simple: for every phi node, we know
which basic block the value comes from, so we add a move from
phi source to the phi dest at the end of that block
Created by gcampagn on 2/8/17.
|
| Registers |
Created by gcampagn on 1/23/17.
|
| TypeResolvePass |
Converts tree-like UntypedIR to TypedIR, checking the type of
expressions and converting to control flow graph in the process
Created by gcampagn on 1/23/17.
|
| UnusedVariableRemovalPass |
Removes (undeclares) variables that are completely unused.
|
| Enum | Description |
|---|---|
| BinaryOperation |
Created by gcampagn on 1/23/17.
|
| ComparisonOperation |
Created by gcampagn on 1/23/17.
|
| ConstantFolding.ConstantState.Level | |
| UnaryOperation |
Created by gcampagn on 1/23/17.
|


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