Specific constructions
This section will contain detailed discussion of particular linguistic constructions of interest, covering best practices for how to annotate them cross-linguistically. It is still a work in progress. At the moment, you can also see:
- Coordination: currently described under u-dep/conj
- Direct and reported speech: currently described under u-dep/parataxis
Clausal structures
Simple clauses
Simple clauses consist of a predicate together with its core nominal arguments (and may contain additional modifiers of both the predicate and its arguments).
she left
nsubj(left, she)
she left a note
nsubj(left, she)
dobj(left, note)
she left him a note
nsubj(left, she)
dobj(left, note)
iobj(left, him)
An intransitive verb takes a single argument with the u-dep/nsubj relation. A transitive verb in addition takes an argument with the u-dep/dobj relation. A ditransitive verb further adds an argument with the u-dep/iobj relation. Note that the assignment of core argument relations is independent of case marking (whether morphological or analytic). Thus, in ergative languages, the patient-like argument of a transitive verb will take the he u-dep/dobj relation despite the fact that it carries the same case marking as the u-dep/nsubj argument of an intranstive verb.
If passivization involves the promotion of an argument to subject position, then this argument gets the relation u-dep/nsubjpass to indicate that promotion has taken place. By contrast, if passivization only involves suppression of the subject without promotion of another argument, then u-dep/nsubjpass should not be used.
folk drack vin hela natten \n people drank wine all night
nsubj(drack, folk)
dobj(drack, vin)
vin dracks hela natten \n wine was-drunk all night
nsubjpass(dracks, vin)
det dracks vin hela natten \n it was-drunk wine all night
expl(dracks, det)
dobj(dracks, vin)
In nominal clauses, the predicate is a noun or an adjective, which takes a single argument with the u-dep/nsubj relation. The copula verb (if present) attaches to the predicate with the u-dep/cop relation.
he is a fool
nsubj(fool, he)
cop(fool, is)
he is tired
nsubj(tired, he)
cop(tired, is)
This analysis of copula constructions extends to adpositional phrases and oblique nominals as long as they have a predicative function. By contrast, temporal and locative modifiers are treated as dependents on the existential verb “be”.
he is in good shape
nsubj(shape, he)
cop(shape, is)
he is in the garden
nsubj(is, he)
nmod(is, garden)
Exactly where the line is drawn between nominal clauses and clauses with an existential verb may be subject to language-specific variation and should therefore be specified in the language specific documentation. The set of verbs treated as copulas may also vary between languages but should be restricted to grammaticalized copulas where at most an aspectual dimension is added to the basic function of linking a non-verbal predicate to its subject. For other copula-like verbs (like “seem”, “look”, “appear” in English), the nominal predicate is treated as a secondary predicate (see below).
Secondary predicates
A clause can contain a secondary predication or predicative. The most common case is with adjectives, although the same effect can sometimes be achieved with a predicative noun or preposition-marked phrase.
- She declared the cake beautiful.
- She declared the cake a success.
- She entered the room sad.
- She hammered the metal flat.
There are two predicates in such sentences, the main predicate and an additional one, such as the cake being beatiful or She being sad.
Huddleston and Pullum (2002) “The Cambridge Grammar of the English Language”, chapter 4 section 5.3, divide predicatives into obligatory and optional predicatives, which can be either depictives or resultatives, and which can appear in an intransitive or transitive clause, giving eight possibilities:
- He looked fantastic. [obligatory, depictive, intransitive host]
- She kept Kim warm. [obligatory, depictive, transitive host]
- The boss became angry. [obligatory, resultative, intransitive host]
- This made me furious. [obligatory, resultative, transitive host]
- He died young. [optional, depictive, intransitive host]
- He ate the steak almost raw. [optional, depictive, transitive host]
- The pond froze solid. [optional, resultative, intransitive host]
- He painted the house blue. [optional, resultative, transitive host]
In UD, obligatory predicatives are always treated as an xcomp
: The secondary predicate is attached as an xcomp
of the main predicate. In most cases, as well as an adjective depictive, you can use a verbal or nominal predicate in the same position (e.g., He looked [an idiot]; This made me [seethe with anger]).
She declared the cake beautiful .
nsubj(declared, She)
dobj(declared, cake)
xcomp(declared, beautiful)
In the enhanced representation, there is an additional subject link showing the secondary predication, which is obligatorily a particular role in the higher clause:
She declared the cake beautiful .
nsubj(declared, She)
dobj(declared, cake)
xcomp(declared, beautiful)
nsubj(beautiful, cake)
A Czech example:
jmenovat někoho generálem \n to-appoint someone as-a-general
dobj(jmenovat, někoho)
xcomp(jmenovat, generálem)
The relation xcomp
is used for core arguments of clausal predicates,
so it will not be used for some other instances of secondary predication.
Optional depictives are analyzed as adjuncts, and made the acl of the nominal that they semantically modify (if one is present).
For instance, in She entered the room sad we also have a double predication (she entered the room; she was sad). But sad is not a core argument of enter: leaving it out will neither affect grammaticality nor significantly alter the meaning of the verb. On the other hand, leaving out beautiful in She declared the cake beautiful will either render the sentence ungrammatical or lead to a different interpretation of declared.
The result is that in She entered the room sad, sad will depend on She
and the relation will be acl instead of xcomp
:
She entered the room sad .
dobj(entered, room)
acl(She, sad)
He painted the model naked .
dobj(painted, model)
acl(model, naked)
If the nominal head is missing, the secondary predicate must be attached as advcl of the verbal predicate, even though it is an adjective, not an adverb. There is a second predication and the adjective heads the predication (just like in She is sad) and in this case there are simply no other words expressing this second predication:
Vstoupila do místnosti smutná . \n She-entered to room sad .
advcl(Vstoupila, smutná)
advcl(She-entered, sad)
The remaining, most subtle case is optional resultatives. For these,
we uniformly use xcomp
:
He painted the house blue .
dobj(painted, house)
xcomp(painted, blue)
Even though the resultative is optional here, one may argue that it is still a complement (an argument) of the higher verb
(he is painting something blue), in a way that is not true of depictives. Such an analysis of optional resultatives as core arguments is adopted for English by Huddleston and Pullum (p. 262). In LFG terms, we would say that the verb has acquired a new
subcategorization frame by application of a lexical rule, and that this frame
includes an additional xcomp
argument. Such an analysis is buttressed by the fact that normally intransitive verbs like to bark can also form similar resultatives by gaining a new subcategorization which adds both a dobj
and an xcomp
, as in the example below.
The dog barked the neighbors awake .
dobj(barked, neighbors)
xcomp(barked, awake)
Complex clauses
Complex clauses involving subordination arise because a core or non-core dependent is realized as a clausal structure. We distinguish four basic types:
- Clausal subjects, divided into ordinary subjects (u-dep/csubj) and passive subjects (u-dep/csubjpass).
- Clausal complements (objects), divided into those with obligatory control (u-dep/xcomp) and those without (u-dep/ccomp).
- Clausal adverbial modifiers (u-dep/advcl).
- Clausal adnominal modifiers (u-dep/acl) (with relative clauses as an important subtype in many languages).
Nominal structures
The head of a nominal structure is usually a noun, proper noun or pronoun, although in cases of ellipsis it can also be an adjective or even a determiner.
Hon såg den nya filmen . \n She saw the new film .
dobj(såg, filmen)
amod(filmen, nya)
det(filmen, den)
Hon såg Batman . \n She saw Batman .
dobj(såg, Batman)
Hon såg den . \n She saw it .
dobj(såg, den)
Hon såg den nya . \n She saw the new (one) .
dobj(såg, nya)
det(nya, den)
Adjectival and adverbial constructions
…
Comparatives
The syntax of comparative constructions poses various challenges for linguistic theory. For English, many of these are discussed in Bresnan (1973) and Huddleston and Pullum (2002, chapter 13). We give a discussion of equality comparisons (That car is as big as mine) and inequality scalar comparisons (Sue is taller than Jim).
In constructions of the form as X as Y or the same X as Y, X and Y can be of a range of syntactic types, leading to surface forms such as those exemplified below:
- Commitment is as important as a player’s talent.
- Get the cash to him as soon as possible.
- I put in as much flour as the recipe called for.
We note that the head of the whole construction appears to be the head of the X phrase. We can simply say:
- Commitment is important.
- Get the cash to him soon.
- I put in flour.
We then say that the first as is an independent modifier in the comparative, modifying something in the X phrase, in part because the following as Y is fairly optional:
- Commitment is (just) as important.
- ?Get the cash to him (just) as soon.
- I put in (just) as much flour.
However, this first as may not modify the head of X, it may modify an existing modifier of the head of X. Its role is adverbial (u-dep/advmod) consistent with other kinds of degree modification:
Commitment is as important as a player ’s talent .
advmod(important, as-3)
I put in as much flour as the recipe called for .
advmod(much, as-4)
amod(flour, much)
We then take the complement of the comparative as an oblique dependent of the first part. It is clear that the material in the complement as Y can be clausal. It is also usually optional, as indicated above. For that reason, we usually make the complement an u-dep/advcl, with the second as analyzed as a mark. That gives us:
I do n't hear from my brother as often as I previously heard from him .
nsubj(hear, I-1)
aux(hear, do)
neg(hear, n't)
case(brother, from-5)
det(brother, my)
nmod(hear, brother)
advmod(often, as-8)
advmod(hear, often)
mark(heard, as-10)
nsubj(heard, I-11)
advmod(heard, previously)
advcl(often, heard)
case(him, from-14)
nmod(heard, him)
punct(hear, .)
We take the as Y clause as a dependent of the content-word whose degree is being assessed (here often). We take its head to be the head of the clause, here heard. An initially plausible alternative analysis would be to make the clausal dependent headed by as a dependent of the comparative modifier as, more, or less, and indeed this is the analysis which Huddleston and Pullum (2002) argue for in English. However, there are several reasons to doubt this analysis. One is the general principles of UD in favoring content words as heads. A second argument is motivated by a desire for crosslinguistic adequacy: in languages such as Finnish and Japanese, this functional element is not present.
“Y” より “X” が 面白い 。 \n Y than X NOM interesting .
nsubj(面白い, “X”)
case(“X”, が)
case(“Y”, より)
nmod(面白い, “Y”)
punct(面白い, 。)
Since the first as is a functional element, the dependent can be understood to modify the whole phrase as often, and therefore is attached to the head of that phrase. Additionally, it might be noted that comparatives without a comparative word occur in certain varieties of English. For example in Indian English you find usages such as So don’t worry if you think that you have a girl-friend, who is intelligent than you. One further argument from morphological comparatives is discussed below.
The same basic analysis is given for inequality scalar comparatives, with more or less or a comparative adjective and than, parallel to the two uses of as above, except that more can also directly modify a noun, and more is then taken to have the u-dep/amod relation to the noun. In this case, we take the comparative complement as directly depending on more, roughly seeing it as elliptical for more numerous. In general, the comparative complement always depends on an adjective or adverb, and is usually an advcl except when it is directly analyzed as an nmod (as discussed at the end of this section).
more problems than you thought of last week
amod(problems, more)
advcl(more, thought)
mark(thought, than)
more important than you thought
advmod(important, more)
advcl(important, thought)
mark(thought, than)
more rapidly than you thought
advmod(rapidly, more)
advcl(rapidly, thought)
a more difficult problem than you thought
advmod(difficult, more)
amod(problem, difficult)
advcl(difficult, thought)
In addition to crosslinguistic adequacy, we can see here another possible advantage of not attaching the than clause to more: This analysis then means that the dependency structure is more parallel between cases with a periphrastic comparative like more intelligent and a morphological comparative like taller (even though in bound morpheme cases, the -er could be argued to be the comparative head).
smarter than you thought
advcl(smarter, thought)
mark(thought, than)
fiksumpi kuin luulit \n smarter than you_thought
advcl(fiksumpi, luulit)
mark(luulit, kuin)
a smarter boy than you thought
amod(boy, smarter)
advcl(smarter, thought)
mark(thought, than)
If the head is ellided, then the functional element can be promoted.
Wheat raises blood sugar even more than sugar does .
advcl(more, does)
Very commonly the complement clause in a comparative undergoes various amounts of partial reduction or ellipsis, sometimes to a quite extreme extent:
I put in as much flour as the recipe called for .
nsubj(put, I)
compound(put, in)
advmod(much, as-4)
amod(flour, much)
dobj(put, flour)
mark(called, as-7)
det(recipe, the)
nsubj(called, recipe)
advcl(much, called)
nmod(called, for)
punct(put, .)
He plays better drunk than sober
nsubj(plays, He)
advmod(plays, better)
acl(He, drunk)
mark(sober, than)
advcl(better, sober)
In general, we treat whatever remnant that remains as still an u-dep/advcl, as above.
However, a limiting case of this is that only a nominal is present:
- as important as a player ‘s talent
- more important than a player ‘s talent
The analysis in this case is unclear: Should the comparative complement still be analyzed as an extremely reduced complement clause or analyzed as simply a nominal modifier? There are arguments for both positions. For English, there is a long discussion of the arguments in section 2.2 of chapter 13 of Huddleston and Pullum (2002). We err on the side of minimizing the postulation of unobserved structure and opt to treat these cases as just an oblique nominal complement:
as important as a player 's talent
advmod(important, as-1)
case(talent, as-3)
nmod(important, talent)
more important than a player 's talent
advmod(important, more)
case(talent, than)
nmod(important, talent)
More than as a multi-word expression
In certain contexts the comparative complement combines both the action or adjective that is being compared and the quantity it is compared to:
- more than 90 percent (= over 90 percent)
- more than likely
- Home prices have more than doubled in the past decade.
In these cases we consider more than to be a multi-word expression because the two words are inseparable. One cannot say *more percent than 90.
That is more than likely .
nsubj(likely, That)
cop(likely, is)
advmod(likely, more)
mwe(more, than)
punct(likely, .-6)
Clause-external elements
Feedback words
In a sentence starting with a feedback word such as yes or no and continuing with a main clause, we take the predicate of the main clause to be the root of the sentence and attach the feedback word to this predicate with a discourse relation:
yes , we should apply for membership .
discourse(apply, yes)
However, when the feedback is expressed by a full clause instead of a feedback word, the predicate of this clause is taken as the root and the predicate of the following clause is attached with a parataxis relation:
I agree , we should apply for membership .
parataxis(agree, apply)
Ellipsis
Ellipsis means that there is something missing in the sentence. Something that has been omitted from the surface form, although it is understood by both the speaker and the listener. Various phenomena can be classified as ellipsis; the most important and difficult are those where the missing word has dependents. Where do we attach these orphans to?
Several different solutions can be found in treebanks.
One of them is to include an empty node (labeled NULL
, #Fantom
etc.) that represents the missing word.
Orphans are then attached to the empty node with their real dependency relation labels.
Such analysis would be linguistically adequate but it would violate our principle that dependencies exist
between real syntactic words. (It would also make parsing more difficult.)
We do not insert empty nodes.
If empty nodes are not an option, some treebanks attach all orphans to the grandparent, i.e. parent of the missing parent node. Then they may
- keep the labels they would have if attached to the missing parent
- get a special label such as the
ExD
in Prague-style treebanks - combine both (in the Danish treebank, the original labels are surrounded by angle brackets to indicate that this is not the real parent)
Another possibility is that one of the orphans gets promoted to the place of the missing parent and the other orphans are attached to it. This approach is used in Universal Dependencies when a main verb is missing and its auxiliary is promoted: I did not solve the problem but he did today.
A special case of ellipsis arises in coordinate clauses that share the same verb, and the verb is not repeated in the second clause: John bought a car and Peter a bike. Universal Dependencies annnotate such cases using the u-dep/remnant relation (for more details see there).


Dataset retracted by request of the SpeechOcean company
- The Chinese Mandarin speech recognition corpus is provided by speechocean.
- This is a 10.33 hours corpus, which is collected over 4 different microphones
simultaneously.
- The corpus was recorded by 20 speakers (10 males and 10 females) in a quiet office. Each
speaker was recorded around 120 utterances in one channel.
- Transcription files are included.
- The sentence transcription accuracy is higher than 98%.
- It is totally free to use for academic purpose.
- This corpus is a subset of a bigger corpus (159 hours). Please contact us if you are
interested.
External URL
http://en.speechocean.com/member/details/52.html
Contact Information
Email<EMAIL_ADDRESS>Web: http://en.speechocean.com
About Speechocean
Speechocean always devoted itself to providing specialized engineering data products and
services to enterprises and scientific research institutions in the whole industry chain of AI. Our
business involves various domains such as speech recognition, speech synthesis, computer
vision, lexicon, and natural language processing and provides relevant services for the design,
collection, transcription, annotation, etc. of data.


Hi, I'm a physicist-turned-artist who works across genre and medium. I like to work on art/design projects that involve computer/internet/digital media as a tool to create a new immersive experience or to provide a fresh perpective.
I have also been involved with theater for most of my life, and thus I frequently act, direct, write and now also design for the stage.
I graduated with a Bachelor's in Physics and Humanitties from Massachusetts Institue of Technology in 2013. And currently I'm at Harvard Graduate School of Design pursuing a Master's in Design and Technology.


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Chan's Pizza
Pizza Order
Crust
Brooklyn Style
Hand Tossed
Crunchy Thin Crust
Topping
Pepperoni
Beef
Ham
Philly Steak
Size
Small (10")
Medium (12")
Large (14")
X-Large (16")
Delivery
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crust:
size:
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price: $
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total pizzas:
total cost: $


{% if scrollToAnchor %} {% endif %}
Bill is an anti-procrastination system that uses imaging to see if you're doing work. Bill is activated via speech and then sends auditory prompts to get you to focus.
Speak to the user!


--- title: URL Shortening layout: post tags: [rant] uuid: a9b40c57-21dd-31fb-e1a0-da44677cd727 ---
There has been a lot of talk online about the fragility of URL shortening services, particularly in relation to Twitter and its 140 character limit on posts (based on SMS limits). These services create a single point of failure and break mechanisms of the web that we rely on. Several solutions have been proposed, so over the next couple years we get to see which ones end up getting adopted.
There are many different URL shortening services out there. They take a large URL, generate a short URL, and store the pair in a database. Several of these services have already shut down in response to abuse by spammers who hide fraudulent URLs behind shortened ones. If these services ever went down all at once, these shortened URLs would rot, destroying many of the connections that make up the world wide web. This is called the rot link apocalypse, and it has some people worried.
I am not very worried about this, though. I don't use Twitter, or any other service that puts such ridiculous restrictions on message sizes. Nor do I think information on Twitter is very important.
In any case, short URLs may be useful sometimes, especially if a URL needs to be memorized or if the URL is extremely long. Or, it could be used to get around a design flaw in an inferior browser.
One idea that I have not yet seen implemented is simple data compression. When a short URL is needed, a user can apply a compression algorithm to the URL. The original URL can be recovered from this alone, so we don't have to rely on third parties to store any data.
I have doubts this would work in practice, though. Generic compression algorithms cannot compress such a small amount of data because their overhead is too large in relation. Go ahead, try pushing a URL through gzip. It will only get longer. We would need a special URL compression algorithm.
For example, I could harvest a large number of URLs from around the web, probably sticking to a single language, and use it to make a Huffman coding frequency table. Then I use this to break URLs into symbols to encode. The ".com/" symbol would likely be mapped to one or two bits. Finally, this compressed URL is encoded in base 64 for use. The client, who already has the same URL frequency table, would use it to decode the URL.
URLs don't seem to have too many common bits, so I doubt this would work well. I should give it a shot to see how well it works.
We probably need to stick with lookup tables mapping short strings to long strings. Instead of using a third party, which can disappear with the valuable data, we do the URL shortening at the same location as the data. If the URL shortening mechanism disappears, so did the data. The URL shortening loss wouldn't matter thanks to this coupling. Getting the shortened URL to users can be tricky, though.
One proposal wants to
set the rev
attribute of the link
tag to
"canonical" and point to the short URL.
To understand this one must first understand the rel
attribute. rel
defines how the linked URL is related to
the current document. rev
is the opposite, describing how
the current page is related to the linked page. To say
rev="canonical"
means "I am the canonical URL for this
page".
However, I don't think this will get far. Several search engines,
including Google, have already adopted a
rel="canonical"
for regular use. It's meant to be placed
with the short URL and will cause search engines to treat it as if it
was a 301
redirect. This won't help someone find the short URL from the long
URL, though. It is also likely to be confused with the
rev
attribute by webmasters.
The rev
attribute is also considered too difficult to
understand, which is why it was removed from HTML5.
Another idea rests in just using the rel
attribute by
setting it to various values: "short", "shorter", "shortlink",
"alternate shorter", "shorturi", "shortcut", "short_url". This website does a good
job of describing why they are all not very good (misleading, ugly, or
wrong), and it goes on to recommend "shorturl".
I went with this last one and added a "short permalink" link in all
of my posts. (Removed after changing web hosts.) This
points to a 28 letter link that will 301 direct to the canonical post
URL. In order to avoid trashing my root namespace, all of the short
URLs begin with an asterisk. The 4 letter short code is derived from
the post's internal name.
I also took the time to make a long version of the URL that is more
descriptive. It contains the title of the post in the URL so a user
has an idea of the destination topic before following through. The
title is actually complete fluff and simply ignored. Naturally this
link's rel
attribute is set to "longurl".
Keep your eyes open to see where this URL shortening stuff ends up going.


Match Play. Red trails 0-2 to 7. How should Red play 31?
pips Red=204 White=39
(CorrectAnswer= 0/0, ErrorScore= 0)
This position was kindly sent to me by Leo Waters. Complex back games like this are very, very difficult to play well and accurately. Even XG struggles with these.
There are multiple moves to choose from, but the key here is not to give up any of the points in White’s home board because it is not clear to do so. Keeping the points will (hopefully) generate multiple shots for Red but hitting and then containing a blot will be very problematic because of Red’s very weak home board.
Red will win the game nearly 50% of the time but he will lose a gammon 40% of the time and a backgammon about 11% of the time.
Which is the best move? XG has 18/15, 16/15 as best, perhaps because it blocks a future double fives from the bar by White but any move that doesn’t break the rear points is OK.
There are multiple moves to choose from, but the key here is not to give up any of the points in White’s home board because it is not clear to do so. Keeping the points will (hopefully) generate multiple shots for Red but hitting and then containing a blot will be very problematic because of Red’s very weak home board.
Red will win the game nearly 50% of the time but he will lose a gammon 40% of the time and a backgammon about 11% of the time.
Which is the best move? XG has 18/15, 16/15 as best, perhaps because it blocks a future double fives from the bar by White but any move that doesn’t break the rear points is OK.
1. Cubeful 2-ply 18/17 16/13 Eq.: -0.783 0.434 0.000 0.000 - 0.566 0.439 0.097 2. Cubeful 2-ply 16/15 16/13 Eq.: -0.815 (-0.032) 0.430 0.000 0.000 - 0.570 0.444 0.098 3. Cubeful 2-ply 18/15 16/15 Eq.: -0.818 (-0.036) 0.430 0.000 0.000 - 0.570 0.448 0.094 4. Cubeful 2-ply 16/12 Eq.: -0.821 (-0.039) 0.429 0.000 0.000 - 0.571 0.444 0.100 5. Cubeful 2-ply 18/14 Eq.: -0.862 (-0.079) 0.423 0.000 0.000 - 0.577 0.450 0.098


Objects are a critical element in SMART COSMOS Objects. To put it simply, objects present things both tangible and intangible -- your car is an object because it presents a unique thing only one of which exists in the world. However, your car also represents a model of a car, and this model can shared among thousands of other cars.
Objects by themselves are not very interesting. Each object has a type and name not necessarily unique to that object, which assists in grouping and classifying different objects.


An urgent message from the HQ!
"Our defensive line is shrinking day by day, and if this trend continues, our only way to survive is to make it through the siege until reinforcements arrive. To do that, our people would need supplies. Director, you are hence tasked with preparing and hiding those supplies in the warehouses that are indicated in this message. We understand that your recourses are limited, therefore prepare what you can. However, keep in mind that some of those supplies are vital and are required for us to endure this siege.
P.S. Beware, the enemy got a hold of coordinates to one of the warehouses, and it is unknown which one was exposed. Be ready for anything."
Produce supply for the battlefield before the enemy's air raid strike us!
You start with a specific amount of material, food, and chemical resources.
Select directive 1 or 0 to and click
to start queueing the factory to produce the equipment.
When the timer ends one warehouse will be destroyed by enemy's air strike. If by then the safe warehouse contains the correct amount of equipments, you win the game.


--- layout: post title: 'Absolutely beautiful Wi-fi detector (via Jane & Richard)' date: 2004-09-03 00:00:00 category: links ---


| DOSE: |
1080 mg |
oral |
DXM |
(capsule) |
DXM messed up my mind. I took a big dose, 40 robo-gels and 16 triple-c tabs (1080mg) in mid-November. My pupils were still dilated for five days after the trip, but itís what happened after that. November 30, 2008: I take the recommend dose of Robo syrup for a cold. The night of December 1st, only three weeks after my mega-dose, begins the most desperate and terrifying month and a half that I hope I never will experience again.
It was a psychotic episode that never ends. For solid week I experienced a different type of hallucination, if you can imagine, every single night, and then the rest of the time I had dissociative symptoms, like feeling I was floating away from my body, not as pleasant as it was during the trip, and other frightening delusions. Every day I was hanging on to my sanity by a thread. I didnít even bother looking for a job during this time. I finally came out of it a few weeks ago, in mid-January, with the aid of heavy anti-psychotics that have given me a little blood sugar problem, but I can deal with that.
Was DXM the sole cause of this nightmare? No. Bipolar disorder has cycles like this. However, according to my psychiatrist, the DXM made these symptoms worse and harder to treat, and may have even pushed me over the edge. Go back a year ago. Mid-October 2007. I had been taking smaller doses of DXM since the summer. I stepped up the dose and took 20 Robo gels (300mg). I had a little psychosis the next day, and I randomly slashed the tires of the car next to me. Next month I had full blown psychotic mania and was in the hospital for a week. They gave me the infamous 'shock treatment', which really isnít that bad.
In any case, people who are normally susceptible to psychosis, such as schizophrenics, obsessive-compulsives, depressives, and bipolars, should probably stay away from the stuff, since it can aggravate the illness and make it harder to treat. Would it really have taken over a month to shake off the psychosis had I not taken the DXM? That question canít be answered, but the conclusions are somewhat obvious considering how much I took and when I took it. Bottom line is, if youíre already crazy, donít take something thatís going to make you even crazier. I hope I never do this drug again. That one big dose has given me strong cravings for it, but God help me if I ever give in to those cravings.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


PatientLevelPrediction is part of the OHDSI Methods Library.
PatientLevelPrediction is an R package for building and validating patient-level predictive models using data in the OMOP Common Data Model format.
Reps JM, Schuemie MJ, Suchard MA, Ryan PB, Rijnbeek PR. Design and implementation of a standardized framework to generate and evaluate patient-level prediction models using observational healthcare data. J Am Med Inform Assoc. 2018;25(8):969-975.
The figure below illustrates the prediction problem we address. Among a population at risk, we aim to predict which patients at a defined moment in time (t = 0) will experience some outcome during a time-at-risk. Prediction is done using only information about the patients in an observation window prior to that moment in time.
To define a prediction problem we have to define t=0 by a Target Cohort (T), the outcome we like to predict by an outcome cohort (O), and the time-at-risk (TAR). Furthermore, we have to make design choices for the model we like to develop, and determine the observational datasets to perform internal and external validation. This conceptual framework works for all type of prediction problems, for example those presented below (T=green, O=red).
PatientLevelPrediction is an R package, with some functions implemented in C++ and python.
Requires R (version 3.3.0 or higher). Installation on Windows requires RTools. Libraries used in PatientLevelPrediction require Java and Python.
The python installation is required for some of the machine learning algorithms. We advise to install Python 3.7 using Anaconda (https://www.continuum.io/downloads).
To install the package please read the Package Installation guide
Have a look at the video below for an extensive demo of the package.
Please read the main vignette for the package:
In addition we have created vignettes that describe advanced functionality in more detail:
Package manual: PatientLevelPrediction.pdf
We like to get involved in the development of this package through pull requests to our development branch.


ColladaModel objects are used to display custom 3D graphics in a simulation model. The COLLADA file format (.DAE) is an interchange file format used for 3D graphics. Any 3D object such as a DisplayEntity and most of its sub-classes can accept a ColladaModel as its DisplayModel.
A number of other 3D formats can be used in addition to Collada. At the present time, JaamSim supports DAE, OBJ, and JSB formats as well as zipped versions of these files (ZIP). The JSB format is specific to JaamSim:
The JSB format is a binary format that allows complex 3D objects to be loaded much faster than is possible with the DAE and OBJ formats. A JSB file can be exported by right clicking on a ColladaModel in the Object Selector and selecting "Export 3D Binary File (*.jsb)". Note that the exported JSB will look for the same textures as the DAE file and that these should be located in the same relative position to the JSB file as they were to the DAE file.
Managing 3D assets can be complicated because of the large file sizes and the need to provide separate files for the textures. It is recommended that the user place each 3D asset and its texture files in its own ZIP file. This approach greatly reduces the number and size of the files being handled, and ensures that the files can be moved between computers without breaking the file paths. Note that it is often necessary to edit the DAE file with a text editor, such as Notepad++, to convert any absolute file paths for texture files to relative ones.
The Actions keyword allows 3D animations included in the imported 3D file (.DAE, .JSB, etc.) to be reproduced by any DisplayEntity (or sub-class) that uses this ColladaModel. The animations imported with the 3D file are listed by the Actions output for ColladaModel. The input to the Actions keyword consists of a list of action name / output name pairs, with each pair enclosed by braces, e.g.
{ ActionName1 OutputName1 } { ActionName2 OutputName2 }
In this example, ActionName1 is the name of one of the animations listed in the Actions output for the ColladaModel, and OutputName1 is the name of an output provided by the DisplayEntity (or sub-class) that uses this ColladaModel as the input to its DisplayModel keyword. The output must return a dimensionless number which is interpreted by the ColladaModel as the number of seconds that have elapsed in the animation. This value can be related to the simulation time in the model (after a suitable offset) or it can vary arbitrarily to move the animation forward or backward as required. The same ColladaModel can be shared by more than one DisplayEntity with each DisplayEntity showing a different point in the same animation.
The '3D Animation Example' provided under Help > Examples demonstrates how to use animations in a JaamSim model.
ColladaModel Inputs
|
Keyword |
Description |
|
Key Inputs |
|
|
Description |
A free-form string describing the object. |
|
ColladaFile |
A file path to the DAE, OBJ, or JSB file to be used for this DisplayModel. A ZIP file containing one of these files and its related texture files can also be used, and is the recommended option for this input. The file path must be enclosed in single quotes if it contains spaces. |
|
Actions |
Entity outputs that drive the animated actions for the ColladaModel. The actions for a ColladaModel are defined as part of its ColladaFile input. They are listed in the 'Actions' output for the ColladaModel. |
ColladaModel Outputs
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Output Name |
Description |
|
Entity |
|
|
Name, ObjectType, SimTime, Parent |
See Section 11.1. |
|
ColladaModel |
|
|
Actions |
Names of the animations contained in the 3D model. |
|
Vertices |
Number of vertices contained in the 3D model. |
|
Triangles |
Number of triangles contained in the 3D model. |
|
VertexShareRatio |
Number of triangles divided by one-third of the number of vertices. A value > 1 indicates that vertices were shared between multiple triangles. |
|
NumSubInstances |
Number of sub-instances contained in the 3D model. |
|
NumSubMeshes |
Number of sub-meshes contained in the 3D model. |


The Philly Tweet Dashboard is an ongoing project to provide demographic and topic information of tweets referencing Philadelphia. All tweets used in the analysis contain the term Philly or Philadelphia.
The charts above provide hourly tallies of tweets referencing Philadelphia sorted by age group and gender over the last 24 hours. The gender and age of the author is estimated using lexica provided in Sap, et al.(2014) available courtesy of the World-Well Being Project.
The charts above provide an insight into the topics that are most prevalent in tweets referencing Philadelphia on the given date. The chart on the left provides a visualization of the distance between topics. (Chuang, et al.,2012) Essentially this is a measure of how different one topic is from another. The plot on the right shows the overall frequency of the term (red) and the estimated frequency in the given topic (blue). The relevance metric, λ, determines the terms which will be displayed. In general:
Topics are estimated using Latent Direchlet Allocation (Blei, et al.,2003) implemented with Gensim and visualized using pyldavis.