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--- layout: post authors: ["Aleksandra Pawlik"] title: "Intel to sponsor the first Workshop for Women in Science and Engineering in the UK" date: 2015-12-03 time: "00:00:00" tags: ["WiSE", "Women in Science and Engineering"] ---
We are very happy to announce that the first UK Software Carpentry Workshop for Women in Science and Engineering received generous support from Intel. The event will take place on 14 and 15th December at the University of Manchester.
We are very grateful for Intel's support, and look forward to the event!


The device you are using does not have some of the more recent browser features required to use this app :(
Bubble is a simple web app that uses your devices gyroscope (if you have one and your browser can access it) to give you a spirit level
Bubble is a simple web app that uses your devices gyroscope to give you a spirit level
You don't even need to be connected to the internet to use it!


Discovery...
This was my second encounter with the infamous white devil and, since the last experience dispelled all of my fears about the drug, I looked forward to this with some giddy anticipation.
I did two small lines, which affected me almost instantly. There was a slight burning sensation in my nose afterward (which is to be, obviously, expected), an unpleasant taste in the back of my throat, and an almost instantaneous numbness in my lips, tongue and gums. Within minutes I experienced euphoria and intense stimulation. My thoughts were racing and my body felt invincible, as if I could fly. My muscles hardened, and I felt as if I could barrel through the thickest brick walls with my bare fists. An indescribable surge of emotion, physical pleasure, mental clarity, paranoia and apocalyptic sorrow hit me in one lump some and I felt as if I was experiencing all that could be experienced by a human being in one grand, glorious instant. Several more lines were snorted, and we ventured onward.
As my friends and I made our way to a restaurant, I found my appetite completely absent, and the thought of eating brought waves of intestinal resistance (nausea?). I kept telling my friends how much I loved them, and was overcome with the urge to embrace them all.
As the evening wore on, more lines were snorted and I seemed to remain at a state just below that of the peak until the coke ran out and we moved on to the alcohol and marijuana.
I could distinctly feel when the cocaine euphoria transitioned into the marijuana euphoria, the former heightening my standard experience of reality and 'sharpening' my mind (though, when in this state, it is very difficult to concentrate on one thing for a long period of time) while the latter 'thickens' my mind, slowing my thoughts and disconnecting them from each other and from the reality I perceive. Cocaine increases my rational and emotional range, while marijuana decreases the rational and heightens the emotional. I associate giddiness and escape with weed, and cold, powerful understanding with cocaine. I prefer the latter drug, which, ater my last experience, I have deemed the 'god' drug, for it imbues me with such feelings of stength and brilliance. It is truly an egoist's substance.
I could not really differentiate the alcohol (which takes much longer to affect me than the other said substances) from the marijuana, a drug which this time as always, gives me a profound feeling of disconnection from time and my environment. I feel 'lost' while on it, as if floating in some great oblivion while retaining consciousness (an impaired consciousess, one of a child / animal) a base consciousness in which the magnified emotions, which I believe are triggered by what is perceived and filtered through the rational mind, seem to be ddoing the thinking. This was a far cry from the very 'connected,' 'living-in-the-moment' feeling of cocaine.
Doing both together made for an interesting mental journey, one that seemed to last for days (because of the contrast of states), and, throughout my sourjour, I experienced the most intense love and compassion of which I think I am capable, the most overwhelming despair and the most glorious anger and arousal.
Alcohol, which I did not feel during this particular journey, is the opposite of cocaine, for it allows me to remain connected to that which I deem 'reality,' but it slows my thoughts and dulls my emotions. It provides a great remedy for the horrible coke come-down (prepare for despair if unarmed with some liquor). Coke brings me up, alcohol then brings me down, so that attaining the median (sober) state is more enjoyable (for lack of a better word).
That is really all I have to say. I recommend all three drugs highly, to be employed for specific purposes.
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.


{% extends 'student/index.html'%} {% import "bootstrap/wtf.html" as wtf %} {% block studentContent %}


Obsolete Members for QString
The following members of class QString are obsolete. They are provided to keep old source code working. We strongly advise against using them in new code.
Public Functions
(obsolete) QString & | sprintf(const char *cformat, ...) |
(obsolete) QByteArray | toAscii() const |
(obsolete) QString & | vsprintf(const char *cformat, va_list ap) |
Static Public Members
(obsolete) QString | fromAscii(const char *str, int size = -1) |
(obsolete) QString | fromAscii(const QByteArray &str) |
Member Function Documentation
[static]
QString QString::fromAscii(const char *str, int size = -1)
Returns a QString initialized with the first size characters from the string str.
If size is -1 (default), it is taken to be strlen(str).
This function does the same as fromLatin1().
See also toAscii(), fromLatin1(), fromUtf8(), and fromLocal8Bit().
[static]
QString QString::fromAscii(const QByteArray &str)
This is an overloaded function.
Returns a QString initialized with the string str.
This function was introduced in Qt 5.0.
QString &QString::sprintf(const char *cformat, ...)
Use asprintf(), arg() or QTextStream instead.
QByteArray QString::toAscii() const
Returns an 8-bit representation of the string as a QByteArray.
This function does the same as toLatin1().
Note that, despite the name, this function does not necessarily return an US-ASCII (ANSI X3.4-1986) string and its result may not be US-ASCII compatible.
See also fromAscii(), toLatin1(), toUtf8(), toLocal8Bit(), and QTextCodec.
QString &QString::vsprintf(const char *cformat, va_list ap)
Use vasprintf(), arg() or QTextStream instead.


The Team.js module provides the attribute to generate a character of quality q or with dice modifier m. The syntax is as follows:
Team.getTeam(); //generate a completely random character
Team.getTeam(n); //generate n completely random characters
Specific sets of entirely random characters - as in a team - can also be created by passing in a definition string:
var resultObj = Team.getTeam('1xMilitary, 2xSurvivor' or '3xGanger');
alert(resultObj.toString());
The above requests 1 Military and 2 Survivors, and 3 Gangers. To specify the gender of a request in a value object, append -M, -F, or -? to the end of the type. To specify a Star, use an asterisk for count:
*xMilitary-F, *xGanger-M, *Police-?
The above requests a Female Star Military, a Male Star Ganger, and a Star Police of random gender where in half possibly are female. Not specifying a gender notation generates solely males.
Enter a definition like '1xMilitary, 2xSurvivor' or '3xGanger-F' or '1*xPolice'


GfxMode3D
Parameters:
| mode - graphics mode number from 1 - CountGfxModes () |
Description:
| GfxMode3D returns True if the specified graphics mode is 3D-capable.
GfxMode3D is generally used after obtaining a list of available display modes from a user's system via CountGfxModes (). You apply this to each mode in turn (or a selected mode) to see if you can enter 3D mode. If this returns False, calling Graphics3D () with this mode's details will fail! If you don't wish to perform this check, the only Graphics3D call you can make with a guarantee of working on 99% of 3D graphics cards is 'Graphics3D 640, 480'. However, see GfxModeExists' gfx3d parameter for another method of performing this check. |
| For a = 1 To CountGfxModes () If GfxMode3D (a) Print "Mode " + a + " is 3D-capable" Else Print "Mode " + a + " is NOT 3D-capable" EndIf Delay 100 Next |


Code Guide and Tips¶
This is a document used to record tips in tvm codebase for reviewers and contributors. Most of them are summarized through lessons during the contributing and process.
C++ Code Styles¶
Use the Google C/C++ style.
The public facing functions are documented in doxygen format.
Favor concrete type declaration over
auto
as long as it is short.Favor passing by const reference (e.g.
const Expr&
) over passing by value. Except when the function consumes the value by copy constructor or move, pass by value is better than pass by const reference in such cases.Favor
const
member function when possible.
Python Code Styles¶
The functions and classes are documented in numpydoc format.
Check your code style using
make pylint
Handle Integer Constant Expression¶
We often need to handle constant integer expressions in tvm. Before we do so, the first question we want to ask is that is it really necessary to get a constant integer. If symbolic expression also works and let the logic flow, we should use symbolic expression as much as possible. So the generated code works for shapes that are not known ahead of time.
Note that in some cases we cannot know certain information, e.g. sign of symbolic variable, it is ok to make assumptions in certain cases. While adding precise support if the variable is constant.
If we do have to get constant integer expression, we should get the constant value using type int64_t
instead of int
, to avoid potential integer overflow. We can always reconstruct an integer with the corresponding expression type via make_const
. The following code gives an example.
Expr CalculateExpr(Expr value) {
int64_t int_value = GetConstInt<int64_t>(value);
int_value = CalculateExprInInt64(int_value);
return make_const(value.type(), int_value);
}


And it’s really impossible to tell whether anything that happens in it is Good or Bad
Once upon a time there was a Chinese farmer whose horse ran away. That evening, all of his neighbors came around to commiserate. They said,
We are so sorry to hear your horse has run away. This is most unfortunate.The farmer said,Maybe..The next day the horse came back bringing seven wild horses with it, and in the evening everybody came back and said,Oh, isn’t that lucky. What a great turn of events. You now have eight horses!The farmer again said,Maybe.The following day his son tried to break one of the horses, and while riding it, he was thrown and broke his leg. The neighbors then said,Oh dear, that’s too Bad ,and the farmer responded,Maybe.The next day the conscription officers came around to conscript people into the army, and they rejected his son because he had a broken leg. Again all the neighbors came around and said,Isn’t that great!Again, he said,”Maybe.”The whole process of nature is an integrated process of immense complexity, and it’s really impossible to tell whether anything that happens in it is Good or Bad — because you never know what will be the consequence of the misfortune; or, you never know what will be the consequences of good fortune. Alan Watts .
| Event | Good or Bad |
|---|---|
| Lose a horse | Maybe |
| Win more horses | Maybe |
| Son injury | Maybe |
| Avoid war | Maybe |
Table representing the farmer's philosophy.


--- title: Unquoted Let layout: post tags: [] uuid: fd8ed6df-1a72-3568-7dfe-0be6fde803a0 ---
Update: The basic idea is unsound as is my implementation below.
Besides this, the cl-letf
macro can already do this sort
of thing. At the time I obviously did not fully understand Lisp macros
nor language implementation in general.  I doubt this would work well with byte-compiled code.
I'll leave this post here for historical purposes.
The lisp macro/form let
quotes variable's symbols. This
is almost always more useful than not quoting it. Otherwise, simple
use would look like,
(let (('var 100)) body)
instead of,
(let ((var 100)) body)
In elisp, this is analogous to setq
, which quotes its
first argument, and set
, which doesn't. It could be used
like so in elisp,
The unquoted let
form evalues to 20
, not 35,
because foo
evaluates to the symbol bar
,
which is bound to 10. The unquoted version is used to select variable
names dynamically.
This isn't very useful in a lexically scoped lisp because the variables that can access it are decided, well, lexically. With dynamic scoping we can use it to temporarily mask variables and select what variables to mask dynamically. I found a use for it in one of my projects.
I had a recursive function that searched a graph made of symbols. The symbols globally stored the state of the node. The current node was passed into the function, which would change the state of that node, and recurse. Here's how I was doing it,
(defun search (graph node) ... (set node 'visited) recurse (set node 'unvisited))
That looks a lot like it is emulating a let
form. If we
use an unquoted let
,
(defun search (graph node) ... (uq-let ((node 'visited)) recurse))
There, that's a lot more lispy. Here is an elisp macro for uq-let,
{% highlight cl %} (defmacro uq-let (vars &rest body) "Unquoted let." (declare (indent defun)) `(let ,(mapcar (lambda (a) (cons (eval (car a)) (cdr a))) vars) ,@body)) {% endhighlight %}
From this, making a uq-let*
is trivial. The documentation
string could use some work too.


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Model fitting: testing versus using
I’ve been dwelling recently on what a model does, in terms of how it can be used and what it means. In particular, Mathematical Psychology: An elementary introductionBy Coombs, Dawes, and Tversky from 1970 , describes two very different ways of using a model that I want to talk about here.
“For such a model there is no need to ask the question 'Is the model true?'. If 'truth' is to be the 'whole truth' the answer must be 'No'. The only question of interest is 'Is the model illuminating and useful?” - George Box All models are wrong. With that out of the way, it’s important to then realize that models can be more or less useful in different ways. Newtonian theories are incredibly useful, and even if quantum or relativistic models are technically “more right” in some sense, they might be less useful practically. Same goes for trying to have an overly detailed neural model of behavior when you’re not actually making a claim about neurons or measuring neural activity. This can easily encourage overfitting given all those extra parameters, and might not help you learn anything.
Any model with parameters you have to fit to data, and you can generally then test that fit. However the question you have isn’t always solved by a fit - often you don’t care really if the model is correct or not but rather what the parameter fit tells you. Coombs, Dawes, and Tvsersky give an interesting example comparing testing a model’s fit to test a theory versus using the model as a method of data analysis to extract information.
There’s a really good interactive introduction to Markov Chains here. I’d also suggest looking at all the other tutorials there.
Markov chains are really useful for a range of applications, since they’re so easy to analyze. Let’s say you have an experiment where the subject ran through multiple trials. Now you might want to see whether performance subsequent trials n and n+1 are correlated - that is whether a Markov chain actually fits the data.
If a Markov chain fits, then something from each trial is impacting the next. This can easily be the case in many cognitive psychology tasks, and can imply something about the cognitive processes involved in the experiment For example, there might be “interference” from the previous trial due to working memory stuff.
An example Markov chain from the development of an ethogram, called a kinematic diagram in ethology. Here the different states are different behaviors, and the interest is in seeing how it changes.
However you might not want to actually be testing a Markov assumption per say, but just using it as a way to get at the trial by trial (or time by time) correlations in the data. This is common in ethological research, where the question isn’t whether the behavior is best fit by a Markov chain, but using that assumption to help analyze behavior.
The second part is really important I think, as basically every data analysis method does this. Fitting a gaussian is less interesting than talking about the mean and standard deviation. The drift diffusion model can be fit to almost every set of reaction time data, so the real question is what it helps you say about the parameters.
Of course, the model could be so off that the parameters are completely uninterpretable. Practice safe analysis and check your assumptions!
January 1, 2017


Once_Upon_a_Time
Once Upon a Time is Fairy Tale Land. It's filled with magic, monsters and all of the characters we all know from stories growing up. It's real, and so are the people in it. But unlike the "happily ever after" you may have heard about, their stories continued, and The Evil Queen cast a Dark Curse over the land...This is Storybrooke.  The Queen's Curse has trapped them here and placed her in near-complete control. They have no real memories and no real hope.


SECTION: 950-IDEs TITLE: IntelliJ QUESTION: How do I run Jetty from IntelliJ IDEA? First set up a minimal jetty configuration in a directory in the source tree:
<?xml version="1.0"?>
<Configure class="org.mortbay.jetty.Server">
<Set name="Debug" class="org.mortbay.util.Code" type="boolean">false</Set>
<Call name="addListener">
<Arg>
<New class="org.mortbay.http.SocketListener">
<Set name="Port">
<SystemProperty name="jetty.port" default="8080"/>
</Set>
</New>
</Arg>
</Call>
<Call name="addWebApplication">
<Arg>/test</Arg>
<Arg>
<SystemProperty name="jetty.home" default="./"/>src/webapp
</Arg>
<Set name="virtualHosts">
< Array type="java.lang.String">
<Item>localhost</Item>
</Array>
</Set>
</Call>
</Configure>
Be sure that the Arg
that sets the path to the webapp in the call to addWebApplication
matches the location of your webapp.
The next step is to configure IntelliJ IDEA. For this, add the Jetty and and Jasper classlibs to the set of application libraries and add a new starter entry for Jetty:
Main-Class: org.mortbay.jetty.Server
Program parameters: path_to/jetty.xml
Working Directory: /path_your_source_root
This is all that is neaded to make IDEA run Jetty. You can debug your application like any "normal" application and make use of the new "hotswap" feature.
[Contributed by Philipp Meier 26-Mar-2004]


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I was put on Wellbutrin 150mg XL late in 2003 after unsuccessful attempts to curb my lack of focus on school, health, and well being. I have had a history of 'depression' leading up to my removal in school and placement into Rocky Mountain Academy where I later graduated in August of 2002. Since the low dosage I was put on seemed to have no affects till about 4-6 weeks later (which is normal), I started focusing more, maintaining good grades, and cut back on eating out with my friends.
This entire time it has been recommended not to smoke pot at all as it may not help the wellbutrin do its job. That was the first recommendation I blew off. I was binging on the weekends as I was getting better highs, although I can't relate this directly with Wellbutrin. Every night as I would go out, or in the mornings I would pop at least 5 pills of either extended or immediate release and head to school with no altered affects. Since looking for a cheap high was getting a lot more attention because of my lack of funds, I planned a weekend at a house unoccupied for a week.  A few people brought some bud and I brought some whiskey. I had popped a few pills earlier in the day and thought it might be fun to drink some to see what happens.
After about an accumulation of 4 drinks I sat down for a while. I gathered my thoughts that were eluding to anxiety, fear, pain, and nausea. At first I figured it was the bud, for the three of us we smoked about 2.5-3 grams throughout the morning and afternoon. I knew it wasn't the bud a few minutes later. I got overwhelming feelings of involuntary functioning. Itís hard to explain but it felt like every nerve ending in my body, external and internal were being destroyed somehow. It wasn't a sensation of light needles, because my brain acted along with my body as well. I heard hundreds of popping noises in my head, it felt like the inner lobe was boiling over.
My heart rate severely increased and I lost touch with how bad my condition was. I barely reached to notice I was having light seizures in a few muscle groups. My mouth would tense and open up and twitch, along with a few extremities. I suddenly got up and felt helpless at that point. My friends noticed and one particular friend had a similar experience with wellbutrin, said to just ride out the storm, I got pissed and realized I had taked about 450 mgs of time-released as well as the 150's SR. Somewhere around 4 I headed up to the upstairs bathroom. I had seen friends get sick before and never wanted to be seen that way, but for fucks sake I swallowed my pride and puked my brains out.
I did that for about 1 and a half hours before I caught myself drifting off into a very euphoric state. My friend came up to check on me, I said I was sick but feeling better. Around 6 I got something to eat and tried to maintain.  When I could finally manage I got up to look at my face, as it felt weird, I was as white at a ghost with flaming chapped red lips. The rest of the night was incredible. I had thoughts and feelings that I had been re-born and awakened from something.
It was hard to get rest but I eventually did have a very very light sleep, waking up to go back to high school. Some typical symptoms of a hangover were present but I have felt different since it happened only a day or so ago. Like everything in my world flipped. I was talkative, but I'm more shy now, I have a lot less anxiety about school-family, as before I stressed about everything, and I approach every situation differently, almost from a third person. In the past I have been very irresponsible, but read the labels. They are there for a good reason. Some pharmaceutical lobbyist isn't trying to spoil all your fun by sticking the (do not drink alcoholic beverages) label on your prescription.
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.


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Over at The Dabbler, Gaw has been taking a stroll through the “tended decadence” of Abney Park Cemetery, prompting Nige to recall a fine gravestone epitaph in his local churchyard. Which in turn prompts me to recall one of my own favourite epitaphs, that of the quack doctor Lionel Lockyer (1600–1672), whose miracle pills included sunbeams among their ingredients, in Southwark Cathedral:
Here Lockyer; lies interr'd enough; his name
Speakes one hath few competitors in fame;
A name soe Great, soe Generall't may scorne
Inscriptions whch doe vulgar tombs adorne.
A diminution 'tis to write in verse
His eulogies whch most mens mouths rehearse.
His virtues and his PILLS are soe well known..
That envy can't confine them vnder stone.
But they'll survive his dust and not expire
Till all things else at th'universall fire.
This verse is lost, his PILL Embalmes him safe
To future times without an Epitaph
Photo courtesy of Nick Garrod


Q1.
- Where did I first encounter this particular cultural material?
- Is there a strong reason why I chose to borrow from this particular culture?
Q2.
- What is the goal of my project? Why do I need this particular cultural material?
- Do I have enough resources on this culture? If not, how are you going to obtain them?
Q3.
- Can I explain why using this particular material may cause dispute in some cultures?
- Have I found examples that utilize this particular cultural material I am going to use?
Q4.
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Non-credible sources are social networks, blogs, materials published over 10 years ago, and articles without citations.
-
Credible sources are academic databases, websites registered by government and educational institutions, and research articles with proper citations.


Batting Statisticks Portal
Batting Statisticks - India.
batting statistics of the Indian team for a T20 cricket match


ProtParCon
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Knowing ProtParCon
ProtParCon at a glance
Work-Flow of ProtParCon
Walk-through of an example
What just happened?
What else?
What’s next?
Installing ProtParCon
Install ProtParCon
Install ProtParCon to a virtual environment (recommended)
Things that are good to know
Using ProtParCon
Use ProtParCon in Python
Import ProtParCon
Align multiple sequences
Infer Maximum-Likelihood tree
Reconstruct ancestral states
Simulate protein sequences
Topology test
Identify molecular convergence in proteins
Using ProtParCon in terminal
Check ProtParCon command-line toolsets
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API Reference
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Building a custom model¶
Depending on your research, you might want to build a custom model to do your literature surveys in. This tutorial goes through the steps needed to do this from scratch.
Note: You do not need to do this if you’re just using the pre-trained model. This is only for the use-case where you’d like to build a model of your own!
[1]:
import chaotic_neural as cn
print('Running chaotic_neural version:', cn.__version__)
print('Running gensim version:', cn.gensim.__version__)
print('Running numpy version:', cn.np.__version__)
Running chaotic_neural version: 0.0.3
Running gensim version: 4.0.1
Running numpy version: 1.20.3
1. Running a simple ArXiv query and printing the results¶
For various queries, use the following from the ArXiv API.
prefix |
explanation |
|---|---|
ti |
Title |
au |
Author |
abs |
Abstract |
co |
Comment |
jr |
Journal Reference |
cat |
Subject Category |
rn |
Report Number |
id |
Id (use id_list instead) |
all |
All of the above |
If while running the query you get a ConnectionResetError: [Errno 104] Connection reset by peer
, it’s probably because you’ve made too many queries in too short a period of time, and might be best to wait for a while before trying again, and using a larger delay_sec
while running the make_feeds()
function.
[2]:
n_papers = 3
feed = cn.run_simple_query(search_query='au:iyer_kartheik', max_results = n_papers)
cn.print_feed_entries(feed, num_entries = n_papers)
e-print metadata
arxiv-id: 2104.06514v1
Published: 2021-04-13T20:58:32Z
Title: Star Formation Histories from SEDs and CMDs Agree: Evidence for
Synchronized Star Formation in Local Volume Dwarf Galaxies over the Past 3
Gyr
Authors: Charlotte Olsen, Eric Gawiser, Kartheik Iyer, Kristen B. W. McQuinn, Benjamin D. Johnson, Grace Telford, Anna C. Wright, Adam Broussard, Peter Kurczynski
abs page link: http://arxiv.org/abs/2104.06514v1
pdf link: http://arxiv.org/pdf/2104.06514v1
Journal reference: No journal ref found
Comments: Accepted for publication in ApJ, 25 pages, 18 figures, 3 tables
--------------
e-print metadata
arxiv-id: 2010.01132v1
Published: 2020-10-02T18:00:00Z
Title: IQ Collaboratory II: The Quiescent Fraction of Isolated, Low Mass
Galaxies Across Simulations and Observations
Authors: Claire M Dickey, Tjitske K Starkenburg, Marla Geha, ChangHoon Hahn, Daniel Anglés-Alcázar, Ena Choi, Romeel Davé, Shy Genel, Kartheik G Iyer, Ariyeh H Maller, Nir Mandelker, Rachel S Somerville, L Y Aaron Yung
abs page link: http://arxiv.org/abs/2010.01132v1
pdf link: http://arxiv.org/pdf/2010.01132v1
Journal reference: No journal ref found
Comments: 19 pages, 8 figures. Figure 4 presents the main result. Code used in
this work may be accessed at github.com/IQcollaboratory/orchard. Submitted to
ApJ
--------------
e-print metadata
arxiv-id: 2007.07916v1
Published: 2020-07-15T18:00:49Z
Title: The Diversity and Variability of Star Formation Histories in Models of
Galaxy Evolution
Authors: Kartheik G. Iyer, Sandro Tacchella, Shy Genel, Christopher C. Hayward, Lars Hernquist, Alyson M. Brooks, Neven Caplar, Romeel Davé, Benedikt Diemer, John C. Forbes, Eric Gawiser, Rachel S. Somerville, Tjitske K. Starkenburg
abs page link: http://arxiv.org/abs/2007.07916v1
pdf link: http://arxiv.org/pdf/2007.07916v1
Journal reference: No journal ref found
Comments: 31 pages, 17 figures (+ appendix). Resubmitted to MNRAS after
responding to referee's comments. Comments are welcome!
--------------
2. Next, we want to generalize this to a large set of feeds corresponding to a particular topic¶
This can be done using the make_feeds()
and read_corpus()
functions. Here we’ll create a corpus consisting of the 30,000 most recent ‘astrophysics of galaxies’ (astro-ph.GA)
category of papers in the ArXiv (specified by the max_setsize
argument). If you’d like to try this with a different category, please check arxiv.org for the full list. If there aren’t as many papers as specified by max_setsize
, it’ll get as many as it can get. For better
processing, the queries are broken down into chunk (specified by the chunksize
argument).
Note for scraping large amounts of data from the API user manual:
In cases where the API needs to be called multiple times in a row, we encourage you to play nice and incorporate a 3 second delay in your code. The detailed examples below illustrate how to do this in a variety of languages. Because of speed limitations in our implementation of the API, the maximum number of results returned from a single call (max_results) is limited to 30000 in slices of at most 2000 at a time, using the max_results and start query parameters. For example to retrieve matches 6001-8000: http://export.arxiv.org/api/query?search_query=all:electron&start=6000&max_results=8000
Large result sets put considerable load on the server and also take a long time to render. We recommend to refine queries which return more than 1,000 results, or at least request smaller slices. For bulk metadata harvesting or set information, etc., the OAI-PMH interface is more suitable. A request with max_results >30,000 will result in an HTTP 400 error code with appropriate explanation. A request for 30000 results will typically take a little over 2 minutes to return a response of over 15MB. Requests for fewer results are much faster and correspondingly smaller.
Note: bioRxiv
has a similar (although not identical) API, but I haven’t yet had the chance to implement it within chaotic_neural
yet. If you are interested in helping set this up, please get in touch with me or open an issue on GitHub!
[3]:
bigquery = 'cat:astro-ph.GA'
gal_feeds = cn.make_feeds(arxiv_query = bigquery, chunksize = 30, max_setsize = 30000, delay_sec = 0.1)
100%|██████████| 1000/1000 [15:53<00:00, 1.05it/s]
[4]:
with open("gal_feeds.pkl", "wb") as fp: #Pickling
cn.pickle.dump(gal_feeds, fp)
[5]:
with open("gal_feeds.pkl", "rb") as fp:
gal_feeds = cn.pickle.load(fp)
[6]:
# Let's print the status of the feeds for recordkeeping purposes
from datetime import date
bigquery = 'cat:astro-ph.GA'
today = date.today()
d2 = today.strftime("%B %d, %Y")
print("Updated feed for query: \"%s\" with %i most recent feeds as of:" %(bigquery, len(gal_feeds)*len(gal_feeds[0].entries)), d2)
Updated feed for query: "cat:astro-ph.GA" with 30000 most recent feeds as of: May 23, 2021
3. Training the model¶
Having collected our feeds from the ArXiv (up to date as of today), we can now train our doc2vec model on the abstracts corresponding to each paper. This corresponds to using the
[7]:
d2 = today.strftime("%d%B%Y")
train_start_time = cn.time.time()
# I'm running the training here with 100 epochs and 12 workers (correpsonding to my machine)
# but you might want to change this to whatever works best for you.
model, train_corpus, test_corpus = cn.build_and_train_model(gal_feeds,
fname_tag = 'astro-ph-GA-'+d2,
cn_dir='../../chaotic_neural/',
vector_size = 50, min_count = 2,
epochs = 100, workers = 12)
train_end_time = cn.time.time()
print('Training done. Time taken: %.2f mins.' %((train_end_time-train_start_time)/60))
100%|██████████| 1000/1000 [00:04<00:00, 229.62it/s]
100%|██████████| 1000/1000 [00:04<00:00, 237.41it/s]
100%|██████████| 1000/1000 [00:00<00:00, 6218.52it/s]
Training done. Time taken: 5.11 mins.
4. Loading the trained model and checking that it works!¶
[8]:
d2 = today.strftime("%d%B%Y")
modeldata = cn.load_trained_doc2vec_model(fname_tag = 'astro-ph-GA-'+d2, cn_dir='../../chaotic_neural/',)
[9]:
similar_papers = cn.list_similar_papers(modeldata, '2007.07916', input_type='arxiv_id', show_summary=True)
ArXiv id: 2007.07916
Title: The Diversity and Variability of Star Formation Histories in Models of
Galaxy Evolution
-----------------------------
Most similar/relevant papers:
-----------------------------
0 The Diversity and Variability of Star Formation Histories in Models of
Galaxy Evolution (Corrcoef: 0.99 )
Summary:------
Quenching can induce $\sim0.4-1$ dex of additional power on timescales $>1$ Gyr. The dark matter accretion histories of galaxies have remarkably self-similar PSDs and are coherent with the in-situ star formation on timescales $>3$ Gyr. There is considerable diversity among the different models in their (i) power due to SFR variability at a given timescale, (ii) amount of correlation with adjacent timescales (PSD slope), (iii) evolution of median PSDs with stellar mass, and (iv) presence and locations of breaks in the PSDs. The PSD framework is a useful space to study the SFHs of galaxies since model predictions vary widely.
1 A Method to Measure the Unbiased Decorrelation Timescale of the AGN
Variable Signal from Structure Functions (Corrcoef: 0.66 )
Summary:------
We show that the signal decorrelation timescale can be measured directly from the SF as the timescale matching the amplitude 0.795 of the flat SF part (at long timescales), and only then the measurement is independent of the ACF PE power.
2 Surrogate modelling the Baryonic Universe II: on forward modelling the
colours of individual and populations of galaxies (Corrcoef: 0.65 )
Summary:------
We additionally provide a model-independent fitting function capturing how the level of unresolved star formation variability translates into imprecision in predictions for galaxy colours; our fitting function can be used to determine the minimal SFH model that reproduces colours with some target precision.
3 Impact of an AGN featureless continuum on estimation of stellar
population properties (Corrcoef: 0.64 )
Summary:------
At the empirical AGN detection threshold $x_{\mathrm{AGN}}\simeq 0.26$ that we previously inferred in a pilot study on this subject, our results show that the neglect of a PL component in spectral fitting can lead to an overestimation by $\sim$2 dex in stellar mass and by up to $\sim$1 and $\sim$4 dex in the light- and mass-weighted mean stellar age, respectively, whereas the light- and mass-weighted mean stellar metallicity are underestimated by up to $\sim$0.3 and $\sim$0.6 dex, respectively.
4 The gas fractions of dark matter haloes hosting simulated $\sim L^\star$
galaxies are governed by the feedback history of their black holes (Corrcoef: 0.63 )
Summary:------
We examine the origin of scatter in the relationship between the gas fraction and mass of dark matter haloes hosting present-day $\sim L^\star$ central galaxies in the EAGLE simulations.
5 Optical variability of AGN in the PTF/iPTF survey (Corrcoef: 0.61 )
Summary:------
We utilize both the structure function (SF) and power spectrum density (PSD) formalisms to search for links between the optical variability and the physical parameters of the accreting supermassive black holes that power the quasars.
This effect is also seen in the SF analysis of the (i)PTF data, and in a PSD analysis of quasars in the SDSS Stripe 82.
6 Reionization with galaxies and active galactic nuclei (Corrcoef: 0.60 )
Summary:------
We explore a wide range of combinations for the escape fraction of ionizing photons (redshift-dependent, constant and scaling with stellar mass) from both star formation ($\langle f_{\rm esc}^{\rm sf} \rangle$) and AGN ($f_{\rm esc}^{\rm bh}$) to find: (i) the ionizing budget is dominated by stellar radiation from low stellar mass ($M_*<10^9 {\rm M_\odot}$ ) galaxies at $z>6$ with the AGN contribution (driven by $M_{bh}>10^6 {\rm M_\odot}$ black holes in $M_* > 10^9 {\rm M_\odot}$ galaxies) dominating at lower redshifts; (ii) AGN only contribute $10-25\%$ to the cumulative ionizing emissivity by $z=4$ for the models that match the observed reionization constraints; (iii) if the stellar mass dependence of $\langle f_{\rm esc}^{\rm sf} \rangle$ is shallower than $f_{\rm esc}^{\rm bh}$, at $z<7$ a transition stellar mass exists above which AGN dominate the escaping ionizing photon production rate; (iv) the transition stellar mass decreases with decreasing redshift.
7 Building Blocks of the Milky Way's Accreted Spheroid (Corrcoef: 0.60 )
Summary:------
Combining the Munich-Groningen semi-analytical model of galaxy formation with the high resolution Aquarius simulations of dark matter haloes, we study the assembly history of the stellar spheroids of six Milky Way-mass galaxies, focussing on building block properties such as mass, age and metallicity.
8 The origin of the $α$-enhancement of massive galaxies (Corrcoef: 0.59 )
Summary:------
In the absence of feedback from active galactic nuclei (AGN), however, $[\alpha/\mathrm{Fe}]_{\ast}$ in $M_{\ast} > 10^{10.5}$ M$_{\odot}$ galaxies is roughly constant with stellar mass and decreases with mean stellar age, extending the trends found for lower-mass galaxies in both simulations with and without AGN.
9 JINGLE -- IV. Dust, HI gas and metal scaling laws in the local Universe (Corrcoef: 0.58 )
Summary:------
We find that these scaling laws for galaxies with $-1.0\lesssim \log M_{\text{HI}}$/$M_{\star}\lesssim0$ can be reproduced using closed-box models with high fractions (37-89$\%$) of supernova dust surviving a reverse shock, relatively low grain growth efficiencies ($\epsilon$=30-40), and long dus lifetimes (1-2\,Gyr).
[ ]:


At Champion we believe that every student should have access to resources and people that will help them succeed. At Champion students are able to find sponsors who are willing to help fund student projects or education. With your help we can alleviate student debt.
We want to build a web application that will enable students who are passionate about learning to be able to use it as a tool for self-promotion, networking and portfolio/ experience building. The app will allow them to find people who are willing to fund their education or passion projects. The main purpose of this web application is to alleviate the amount of student debt that our country has accumulated. Students who are entering college can create an account on this app and will be able to create a bio which states their major, interests, hobbies, achievements, ongoing projects, completed projects, resume, portfolio and photos that describe what they are passionate about and what they want to learn more about.


[§323D-44.6] Review of certain applications for certificate of need; waiver. The subarea council, the review panel, and the statewide council may, at their discretion, choose to waive their respective prerogatives of review of any certificate of need application. [L 1987, c 270, pt of §2]


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Replacing the board won't fix crisis at Prasa, says Mbalula | IOL News
Johannesburg - The embattled Passenger Rail Agency of SA (Prasa) had been placed under administration by Transport Minister Fikile Mbalula, who dissolved the entity’s interim board.
Addressing the media on the decision, Mbalula said the crisis at the rail agency could not be solved by replacing the current board with a new one.
He said the continued decline of the quality of service provided by Prasa to the commuting public required urgent intervention.
Last week, Mbalula had indicated the process of making changes to the leadership of Prasa was at an advanced stage.
On Monday, he said the entity had been riddled with mismanagement and governance challenges over the past decade of its existence.


Data Tables allow the consumer to show large amounts of complex data in tabular form, with rows and columns. Columns can be named through the use of headers.
Data table wrapped in a card with selectable rows.
Data table wrapped in a card with sorting. In this example the
Name
,
Height
&
Weight
headings are sortable. We recommend to visit the
MDN docs
on sorting, if you're performing client side sorting.
Please note that the Kirby data table does not do any sorting. The sorting logic must be
implemented manually and can be triggered by adding the Angular
(click)
event listener as shown in the code example above. By adding
[sortable]="true"
to a
th
element, it will render the sorting icon (up/down arrow) when the element is clicked.


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Access and review the Unit Text List.
Note the information that is included about each text. You will notice that each text has an icon by it. These indicate where the text is located, which corresponds to the Location column in the Unit Text List.
Then review the Independent Reading Text Options. Here, you will find suggested options for independent reading related to the unit.
ABOUT THE AUTHOR, CONCEPT, TEXT, TOPIC
The Unit Text List is a student-facing version of the Text Overview document, which is located on the unit’s landing page. The Text Overview contains qualitative analyses, and the Unit Text List does not.
TEACHING STRATEGIES AND DECISIONS
An independent reading program might be a part of your classroom, school, or district practice. The Independent Reading Text Options provides a list of texts that are linked thematically, topically, or by genre to the unit. You and your students might select independent reading texts from the options provided to build additional knowledge on the topics or texts in the unit. If you have a media specialist or librarian, you can share this list with them to see what resources are available and to generate an extended list of related resources.
Note that students are frequently directed to take notes in a “Learning Log.” A Learning Log does not refer to a specific tool or material; students can use any note-taking method, such as a notebook, binder, or other electronic tool. This may stem from personal preference or from teacher or school guidance or policy.
If you are using this unit in a remote- or virtual-learning context, you might consult two resources: the general Odell Education Remote Learning Guide and the unit-specific Things Fall Apart Remote Learning Guide. The Odell Education Remote Learning Guide provides general guidance for strategies and structures that can be used for synchronous and asynchronous learning, flipped classrooms, and blended learning. The Things Fall Apart Remote Learning Guide provides remote learning suggestions for each lesson.
STUDENT SUPPORT AND DIFFERENTIATION
This unit, like all units in the Odell Education High School Literacy Program, employs a suite of tools and resources from the Odell Education Literacy Toolbox as well as tools specific to the unit’s content and instructional sequences. Students can be supported throughout the unit by using materials from the Literacy Toolbox, beyond those that are referenced in the unit. Tools are graphic organizers that support students’ reading and writing by helping them think through text, find pertinent textual details, and develop ideas for their writing. Note that many, such as the Analyzing Relationships Tool and the Forming Evidence-Based Claims Tool are text agnostic—they are designed to be used with any text. Others, such as some note-taking tools, have instructions or structures that are specific to the unit topic or text. These tools help students develop and internalize analytical processes. Since they are scaffolds, they can be assigned at your discretion, or students might develop their own system for using them if they encounter difficult sections of text. See the Tools Reference Guide for a list of core tools.
Reference guides provide centralized explanations and examples of concepts and processes common to English language arts. They make important connections to the pertinent tools and provide additional resources related to the concept. The Assessing Sources Reference Guide provides a process to assess sources for bias, credibility, and accuracy, and the Tone Reference Guide provides information for understanding and identifying tone in a text. While activities suggest when to use reference guides during instruction, you might refer students to them throughout the unit to reinforce understanding around a particular concept or process.
Tools and reference guides specific to lessons and activities can be found in their respective Materials tabs. The teaching notes might also suggest tools or reference guides as additional supports for students. Since these supplemental materials are not mentioned in the student directions, they do not appear in the Materials tab. They can be found in the Literacy Toolbox located on the grade level’s homepage under Program Resources.
Note: In order to edit a Google Doc, you will first need to create your own copy by completing the following steps:
We will have a class discussion. To prepare for that discussion, answer these questions:
What are some examples of things falling apart in life? In each example, what caused things to fall apart?
ABOUT THE AUTHOR, CONCEPT, TEXT, TOPIC
Chinua Achebe’s (1930-2013) masterful trilogy begins with Things Fall Apart,a novel set in pre-colonial Nigeria and often called “The Great African novel.” Born in an Igbo village in Nigeria, Achebe grew up in colonized Nigeria, where he was influenced by both Christian and Igbo beliefs. Things Fall Apart is followed by two additional novels, No Longer at Ease and Arrow of God, which follow the story. Achebe’s awards include the Man Booker International Prize for fiction and the Dorothy and Lillian Gish Prize.
When referring to the novel in this unit, all pages refer to the following version: Achebe, Chinua. Things Fall Apart. Random House, 1992 [ISBN: 978-0-679-44623-1].
Activating students’ prior knowledge helps you gather information about what students already know or misunderstand about a topic. This process can illuminate students’ underlying beliefs about the topic under investigation, expose misunderstandings, and uncover their preexisting knowledge. This gives you an opportunity to know what students do and do not know or understand, providing an opportunity for you to adjust instruction.
Students will return to the Central Question in each section of the unit to reflect on how their understanding has evolved or become more nuanced as a result of their learning.
TEACHING STRATEGIES AND DECISIONS
You might choose to expand this activity with an Anticipation Guide. The use of an Anticipation Guide activates students' prior knowledge and builds curiosity about a new topic. Before reading, students respond to several statements that challenge or support their preconceived ideas about key concepts in the text. You should encourage students to draw on their cultural and social backgrounds to make connections. Anticipation Guides challenge students to think critically about what they know—or do not know—about a topic. Anticipation Guides can be revisited later to evaluate how well students understood the material and to correct any misconceptions.
Other strategies to activate background knowledge include using the K-W-L protocol or a Notice and Wonder table. The K-W-L (Know, Want to Know, Learn) protocol asks students to identify what they know about the topic at the beginning of the unit, lesson, or activity; generate questions about what they want to know about the topic; and, at the end, determine what they learned about the topic. In a Notice and Wonder table, students take note about parts of the text in one column and write "I wonder" statements based on those observations in a second column.
STUDENT SUPPORT AND DIFFERENTIATION
The activity approaches student learning through an asset based lens. Students are encouraged to bring the knowledge, insight, and curiosity they already have to enhance their experience in the unit. English learners in particular benefit from making connections to their cultural and social backgrounds.
As a class, discuss the following questions:
ABOUT THE AUTHOR, CONCEPT, TEXT, TOPIC
Chinua Achebe’s (1930-2013) masterful trilogy begins with Things Fall Apart,a novel set in pre-colonial Nigeria and often called “The Great African novel.” Born in an Igbo village in Nigeria, Achebe grew up in colonized Nigeria, where he was influenced by both Christian and Igbo beliefs. Things Fall Apart is followed by two additional novels, No Longer at Ease and Arrow of God, which follow the story. Achebe’s awards include the Man Booker International Prize for fiction and the Dorothy and Lillian Gish Prize.
When referring to the novel in this unit, all pages refer to the following version: Achebe, Chinua. Things Fall Apart. Random House, 1992 [ISBN: 978-0-679-44623-1].
Activating students’ prior knowledge helps you gather information about what students already know or misunderstand about a topic. This process can illuminate students’ underlying beliefs about the topic under investigation, expose misunderstandings, and uncover their preexisting knowledge. This gives you an opportunity to know what students do and do not know or understand, providing an opportunity for you to adjust instruction.
Students will return to the Central Question in each section of the unit to reflect on how their understanding has evolved or become more nuanced as a result of their learning.
TEACHING STRATEGIES AND DECISIONS
You might choose to expand this activity with an Anticipation Guide. The use of an Anticipation Guide activates students' prior knowledge and builds curiosity about a new topic. Before reading, students respond to several statements that challenge or support their preconceived ideas about key concepts in the text. You should encourage students to draw on their cultural and social backgrounds to make connections. Anticipation Guides challenge students to think critically about what they know—or do not know—about a topic. Anticipation Guides can be revisited later to evaluate how well students understood the material and to correct any misconceptions.
Other strategies to activate background knowledge include using the K-W-L protocol or a Notice and Wonder table. The K-W-L (Know, Want to Know, Learn) protocol asks students to identify what they know about the topic at the beginning of the unit, lesson, or activity; generate questions about what they want to know about the topic; and, at the end, determine what they learned about the topic. In a Notice and Wonder table, students take note about parts of the text in one column and write "I wonder" statements based on those observations in a second column.
STUDENT SUPPORT AND DIFFERENTIATION
The activity approaches student learning through an asset based lens. Students are encouraged to bring the knowledge, insight, and curiosity they already have to enhance their experience in the unit. English learners in particular benefit from making connections to their cultural and social backgrounds.
In your Learning Log, write a response to the unit’s central question: What does it mean for things to fall apart?
As you write your answer, consider:
How do you think this question relates to the texts or topic of the unit?
You will return to this initial response in later lessons to examine how your understanding of the Central Question has evolved.
ABOUT THE AUTHOR, CONCEPT, TEXT, TOPIC
Chinua Achebe’s (1930-2013) masterful trilogy begins with Things Fall Apart,a novel set in pre-colonial Nigeria and often called “The Great African novel.” Born in an Igbo village in Nigeria, Achebe grew up in colonized Nigeria, where he was influenced by both Christian and Igbo beliefs. Things Fall Apart is followed by two additional novels, No Longer at Ease and Arrow of God, which follow the story. Achebe’s awards include the Man Booker International Prize for fiction and the Dorothy and Lillian Gish Prize.
When referring to the novel in this unit, all pages refer to the following version: Achebe, Chinua. Things Fall Apart. Random House, 1992 [ISBN: 978-0-679-44623-1].
Activating students’ prior knowledge helps you gather information about what students already know or misunderstand about a topic. This process can illuminate students’ underlying beliefs about the topic under investigation, expose misunderstandings, and uncover their preexisting knowledge. This gives you an opportunity to know what students do and do not know or understand, providing an opportunity for you to adjust instruction.
Students will return to the Central Question in each section of the unit to reflect on how their understanding has evolved or become more nuanced as a result of their learning.
TEACHING STRATEGIES AND DECISIONS
You might choose to expand this activity with an Anticipation Guide. The use of an Anticipation Guide activates students' prior knowledge and builds curiosity about a new topic. Before reading, students respond to several statements that challenge or support their preconceived ideas about key concepts in the text. You should encourage students to draw on their cultural and social backgrounds to make connections. Anticipation Guides challenge students to think critically about what they know—or do not know—about a topic. Anticipation Guides can be revisited later to evaluate how well students understood the material and to correct any misconceptions.
Other strategies to activate background knowledge include using the K-W-L protocol or a Notice and Wonder table. The K-W-L (Know, Want to Know, Learn) protocol asks students to identify what they know about the topic at the beginning of the unit, lesson, or activity; generate questions about what they want to know about the topic; and, at the end, determine what they learned about the topic. In a Notice and Wonder table, students take note about parts of the text in one column and write "I wonder" statements based on those observations in a second column.
STUDENT SUPPORT AND DIFFERENTIATION
The activity approaches student learning through an asset based lens. Students are encouraged to bring the knowledge, insight, and curiosity they already have to enhance their experience in the unit. English learners in particular benefit from making connections to their cultural and social backgrounds.
Read the Culminating Task Checklist. Determine what skills and knowledge you need to succeed on the Culminating Task.
Think about your responses to the following questions:
Then discuss the questions as a class.
ABOUT THE AUTHOR, CONCEPT, TEXT, TOPIC
Students can use the Culminating Task Checklist to determine what knowledge and skills they will need to succeed on the Culminating Task.
Progress monitoring—being aware of one’s own progress and using it to determine what skills and knowledge still need to be mastered—improves student progress. As students become more aware of their own performance, they learn how to more accurately predict their future performance on a range of other tasks. By identifying and self-evaluating initial mastery levels, students can focus on the skills and knowledge they need to build. Finally, this kind of practice can help you make more finely tuned instructional decisions because you have feedback from students about the skills they need to practice.
TEACHING STRATEGIES AND DECISIONS
You might ask students to complete the checklist at the beginning of the unit and after each Section Diagnostic. Consider collecting the checklists as students complete them throughout the unit to monitor how they are evaluating their progress. Such information will help you make instructional decisions that are finely tuned to students’ learning needs.
STUDENT SUPPORT AND DIFFERENTIATION
Some groups might need support in unpacking the Culminating Task prompt and the evaluation criteria. You might check on students individually to probe their understanding of what is being asked of them. Using that information, you might end the activity with a whole-class discussion to ensure the students have a clear understanding of the task.
Fill out the Culminating Task Progress Tracker to determine what you need to know and do to succeed on the Culminating Task. For each knowledge and skill identified, assess how prepared you are.
ABOUT THE AUTHOR, CONCEPT, TEXT, TOPIC
Students can use the Culminating Task Checklist to determine what knowledge and skills they will need to succeed on the Culminating Task.
Progress monitoring—being aware of one’s own progress and using it to determine what skills and knowledge still need to be mastered—improves student progress. As students become more aware of their own performance, they learn how to more accurately predict their future performance on a range of other tasks. By identifying and self-evaluating initial mastery levels, students can focus on the skills and knowledge they need to build. Finally, this kind of practice can help you make more finely tuned instructional decisions because you have feedback from students about the skills they need to practice.
TEACHING STRATEGIES AND DECISIONS
You might ask students to complete the checklist at the beginning of the unit and after each Section Diagnostic. Consider collecting the checklists as students complete them throughout the unit to monitor how they are evaluating their progress. Such information will help you make instructional decisions that are finely tuned to students’ learning needs.
STUDENT SUPPORT AND DIFFERENTIATION
Some groups might need support in unpacking the Culminating Task prompt and the evaluation criteria. You might check on students individually to probe their understanding of what is being asked of them. Using that information, you might end the activity with a whole-class discussion to ensure the students have a clear understanding of the task.


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--- layout: default title: Data and resources description: Data portals, APIs, tools, tutorials and free developer infrastructure for making civic apps in Chicago. redirect_from: resources.html ---
Browse the data portals, government websites, APIs and tools available in Chicago.
One of the best places to get open government data is from their official data portal. Chicago, Cook County, Illinois and the US Federal Government post their data on these portals for anyone to access for free.
Open data portals and APIs available in Chicago. Are we missing any? Add them to our list!
| Title | Category | Description |
|---|


Through the font object, you can also make speci c text italic. This is done by specifying the font-style for the text. The following code demonstrates applying the italic style to all "Paragraph" elements on the webpage:
The font-weight CSS property accepts the following values to specify how bold you would like the text to be: lighter, normal, bold, and bolder. In addition, the numeric values 100 (lighter) to 900 (darker) are supported. The values increase by 100, providing nine values in total to control the weight of the text.


Equation:
(ex: a+b=c)
Source:
(To move the a, enter a 0 here. To move the b, enter a 2.)
Destination:
(Over which term the a will end up)
Bugs:
Clicking the = sign will cause the program to fail.
a+b=c -> (a+b)-c=0
No support for custom invertible functions
Cx=y ->movement should only be C when clicked, not Cx


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| PREV NEXT | FRAMES NO FRAMES |
| Packages that use net.jini.lease | |
| com.sun.jini.lease | Some basic utility classes for helping with client-side lease renewal operations. |
| net.jini.lease | Standard service and utility classes for managing leases. |
| net.jini.lookup | Standard utility classes for managing the join state of a service and the service discovery duties of a client or service. |
| Classes in net.jini.lease used by com.sun.jini.lease | |
| LeaseRenewalSet
A collection of leases being managed by a lease renewal service. |
|
| RenewalFailureEvent
Event generated by a lease renewal set when it can't renew a lease it is responsible for. |
| Classes in net.jini.lease used by net.jini.lease | |
| LeaseListener
The interface that receivers of LeaseRenewalEvent
instances must implement.
|
|
| LeaseRenewalEvent
Event generated when a LeaseRenewalManager cannot renew
a lease.
|
|
| LeaseRenewalManager
Provides for the systematic renewal and overall management of a set of leases associated with one or more remote entities on behalf of a local entity. |
|
| LeaseRenewalSet
A collection of leases being managed by a lease renewal service. |
|
| LeaseUnmarshalException
Exception thrown when a lease renewal set can't unmarshal one or more leases being returned by a getLeases call.
|
| Classes in net.jini.lease used by net.jini.lookup | |
| LeaseRenewalManager
Provides for the systematic renewal and overall management of a set of leases associated with one or more remote entities on behalf of a local entity. |
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| PREV NEXT | FRAMES NO FRAMES |


| Answer 1 | ||||||||||||
| Independent variable is the The
type of test or word condition provided to the candidate, that is whether the words shown are congruent with the ink colors or if they are incongruent with ink colors. "An independent variable is that which stands alone and is not changes by the other variables we are trying to measure. In the given problem, type of test given/ condition provided to the participants: ""a congruent words condition, and an incongruent words condition"", is an independent variable. Where as the ""time takem by the participant to take the names of color in equally sized list"" is a dependent variable. Independent variable causes the change in dependent variable and vice-a-versa is not true. " |
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| Links | https://nces.ed.gov/nceskids/help/user_guide/graph/variables.asp | |||||||||||
| Answer 2a | ||||||||||||
| As far as assigning appropriate
set of hypotheses for this task is conserned, we have two hypotheses, 1. Null Hypotheses: The results or the performance of candicates in congruent words condition and an incongruent words condition remains same. 2. Alternative Hypotheses: The results or the performance of candicates in congruent words condition and an incongruent words condition is different, it either increases or decreases. MUc : average of scores of participants who particiapted in congruent word condition. MUi : average of scores of participants who particiapted in incongruent word condition. Null Hypotheses: MUc - MUi = 0 Alternative Hypotheses: MUc - MUi 0 |
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| Answer 2b | ||||||||||||
| Since Our Null Hypothesis is MUc
= MUi, that means different word conditions doesnot affect our output. So we
will check the Standard deviation of the sample and check if its
t-stetistical value is within the t-critical bounds (as in whichever
direction the t-statistical value goes, if the variation is in t-critical
region, we can say that the type of test conditions have definately affected
the test results). Reason for taking t-test insted of z-test is we don't know the population mean and poulation's standard devication. Stetistical test which I expect to perform is: t-test: Since each participant completes each of the word condition tests, we will be performing dependent t-test for paired samples. As two tasks are given to same candidate and output is recorded on both the conditions. Measures of Center: 1. Mean of both the "congruent words condition and an incongruent words condition" test ouput. This gives us the average test scores. 2. Mod: Gives us the most frequent value in the data set 3. Median: THe value in the middle of the distribution is median, this dont have any effect of outliers. 1. Range of data: This provides the value which shows the spread of the data. Measures of Variability: 1. Deviation from Mean 2. Find Variance: THis shows how spread out the data is. 2. Find Standard deviation: This defines how far from the average each score is. Also, an assumption is made that all these test were performed at same time for all the participants in similar conditions (for example similar lighing condition, same time, etc) |
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| links | 1.
https://classroom.udacity.com/courses/ud134-nd/lessons/4615238546/concepts/773674770923 2. https://classroom.udacity.com/courses/ud134-nd/lessons/4615238546/concepts/773450610923 3. https://study.com/academy/lesson/measures-of-variability-range-variance-standard-deviation.html |
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| Answer 3 | ||||||||||||
| Mean of the provided data: 1. Congruent: 14.051125 2. Incongruent: 22.01591667 |
Congruent | Incongruent | devication from
mean Congruent |
Square of
devication from mean Congruent |
devication from
mean InCongruent |
Square of
devication from mean InCongruent |
Sorted Congruent |
Sorted Incongruent |
||||
| Median of the provided
data: 1. Congruent: 14.3565 2. Incongruent: 21.0175 |
12.079 | 19.278 | -1.972125 | 3.889277016 | -2.737916667 | 7.496187674 | 8.63 | 15.687 | ||||
| Variance ofprovided data: 1. Congruent: 12.66902907 2. Incongruent: 23.01175704 |
16.791 | 18.741 | 2.739875 | 7.506915016 | -3.274916667 | 10.72507917 | 8.987 | 17.394 | ||||
| Standard Deviation of the
provided data: 1. Congruent: 3.559357958 2. Incongruent: 4.797057122 |
9.564 | 21.214 | -4.487125 | 20.13429077 | -0.801916667 | 0.64307034 | 9.401 | 17.425 | ||||
| 8.63 | 15.687 | -5.421125 | 29.38859627 | -6.328916667 | 40.05518617 | 9.564 | 17.51 | |||||
| 14.669 | 22.803 | 0.617875 | 0.381769516 | 0.787083333 | 0.619500174 | 10.639 | 17.96 | |||||
| 12.238 | 20.878 | -1.813125 | 3.287422266 | -1.137916667 | 1.29485434 | 11.344 | 18.644 | |||||
| 14.692 | 24.572 | 0.640875 | 0.410720766 | 2.556083333 | 6.533562007 | 12.079 | 18.741 | |||||
| 8.987 | 17.394 | -5.064125 | 25.64536202 | -4.621916667 | 21.36211367 | 12.13 | 19.278 | |||||
| 9.401 | 20.762 | -4.650125 | 21.62366252 | -1.253916667 | 1.572307007 | 12.238 | 20.33 | |||||
| 14.48 | 26.282 | 0.428875 | 0.183933766 | 4.266083333 | 18.19946701 | 12.369 | 20.429 | |||||
| 22.328 | 24.524 | 8.276875 | 68.50665977 | 2.508083333 | 6.290482007 | 12.944 | 20.762 | |||||
| 15.298 | 18.644 | 1.246875 | 1.554697266 | -3.371916667 | 11.36982201 | 14.233 | 20.878 | |||||
| 15.073 | 17.51 | 1.021875 | 1.044228516 | -4.505916667 | 20.30328501 | 14.48 | 21.157 | |||||
| 16.929 | 20.33 | 2.877875 | 8.282164516 | -1.685916667 | 2.842315007 | 14.669 | 21.214 | |||||
| 18.2 | 35.255 | 4.148875 | 17.21316377 | 13.23908333 |<PHONE_NUMBER> | 14.692 | 22.058 | |||||
| 12.13 | 22.158 | -1.921125 | 3.690721266 | 0.142083333 | 0.020187674 | 15.073 | 22.158 | |||||
| 18.495 | 25.139 | 4.443875 | 19.74802502 | 3.123083333 | 9.753649507 | 15.298 | 22.803 | |||||
| 10.639 | 20.429 | -3.412125 | 11.64259702 | -1.586916667 | 2.518304507 | 16.004 | 23.894 | |||||
| 11.344 | 17.425 | -2.707125 | 7.328525766 | -4.590916667 | 21.07651584 | 16.791 | 24.524 | |||||
| 12.369 | 34.288 | -1.682125 | 2.829544516 | 12.27208333 |<PHONE_NUMBER> | 16.929 | 24.572 | |||||
| 12.944 | 23.894 | -1.107125 | 1.225725766 | 1.878083333 | 3.527197007 | 18.2 | 25.139 | |||||
| 14.233 | 17.96 | 0.181875 | 0.033078516 | -4.055916667 | 16.45046001 | 18.495 | 26.282 | |||||
| 19.71 | 22.058 | 5.658875 | 32.02286627 | 0.042083333 | 0.001771007 | 19.71 | 34.288 | |||||
| 16.004 | 21.157 | 1.952875 | 3.813720766 | -0.858916667 | 0.73773784 | 22.328 | 35.255 | |||||
| Sigma calculated by Excel Formula | 3.559357958 | 4.797057122 | ||||||||||
| n | 24 | |||||||||||
| n-1 | 23 | |||||||||||
| mean: | 14.051125 | 22.01591667 | ||||||||||
| median | 14.3565 | 21.0175 | ||||||||||
| mode | No
value is repeated, but we can say that mode is around 12 |
No
value is repeated, but we can say that mode is around 17 and 20 |
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| variance | 12.66902907 | 23.01175704 | ||||||||||
| SD (sigma, calculated manually) | 3.559357958 | 4.797057122 | ||||||||||
| Answer 4 | ||||||||||||
| For Congruent words condition,
as shown in the below histogram graph, the data is positively skewed with interval size of 2.538. shown below: |
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|
|
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| For Incongruent words condition,
as shown in the below histogram graph, the data is positively skewed with interval size of 2.538. Also there lies few outliers as shown in the graph below: |
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|
|
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| Link | http://www.shodor.org/interactivate/activities/Histogram/ | |||||||||||
| Answer 5 | ||||||||||||
| Since the data is collected from
same participants, for two different test conditions, we will calculate Dependent t-test for paired samples. |
Congruent | Incongruent | Di | Di-Dbar | (Di-Dbar) ^2 | |||||||
| Statistical
Results: All the results are
marked in cells highlighted in Yellow color |
12.079 | 19.278 | -7.199 | 0.765791667 | 0.586436877 | |||||||
| Confidance Interval for alpha : 0.05 is -> -11.968 to -3.961 | 16.791 | 18.741 | -1.95 | 6.014791667 | 36.17771879 | |||||||
| d-bar: -7.964791667 | 9.564 | 21.214 | -11.65 | -3.685208333 | 13.58076046 | |||||||
| Variance of Differences: 23.66654087 | 8.63 | 15.687 | -7.057 | 0.907791667 | 0.82408571 | |||||||
| Standard Devication of Differences: 4.86482691 | 14.669 | 22.803 | -8.134 | -0.169208333 | 0.02863146 | |||||||
| Standard Error of Mean Diff: 0.993028635 | 12.238 | 20.878 | -8.64 | -0.675208333 | 0.455906293 | |||||||
| t-statistics: -8.020706944 | 14.692 | 24.572 | -9.88 | -1.915208333 | 3.66802296 | |||||||
| Cohen's d: -1.637219949 | 8.987 | 17.394 | -8.407 | -0.442208333 | 0.19554821 | |||||||
| Confidance Interval: -10.01936791 to -5.910215421 | 9.401 | 20.762 | -11.361 | -3.396208333 | 11.53423104 | |||||||
| p-value: The
two-tailed P value is less than 0.0001 By conventional criteria, this difference is considered to be extremely statistically significant. |
14.48 | 26.282 | -11.802 | -3.837208333 | 14.72416779 | |||||||
| Based on all the
calculated statistics, as t-stetistic is significantly lower than the t-critical value, we "Reject the Null Hypothesis". |
22.328 | 24.524 | -2.196 | 5.768791667 | 33.27895729 | |||||||
| Consclusion:
1. We Reject the Null hypothesis, that means there is significant difference in result outcome beteen Congruent and Incongruent word condition tests results. 2. Based on the Confidence interwal we can say that all the participants performes 5 to 10 less errors in the test given on Congruent word coditions. |
15.298 | 18.644 | -3.346 | 4.618791667 | 21.33323646 | |||||||
| Result Expectations: Yes these results match my expectations as the Incongruent word condition based test was way more difficult than the other. | 15.073 | 17.51 | -2.437 | 5.527791667 | 30.55648071 | |||||||
| 16.929 | 20.33 | -3.401 | 4.563791667 | 20.82819438 | ||||||||
| 18.2 | 35.255 | -17.055 | -9.090208333 | 82.63188754 | ||||||||
| 12.13 | 22.158 | -10.028 | -2.063208333 | 4.256828627 | ||||||||
| 18.495 | 25.139 | -6.644 | 1.320791667 | 1.744490627 | ||||||||
| 10.639 | 20.429 | -9.79 | -1.825208333 | 3.33138546 | ||||||||
| 11.344 | 17.425 | -6.081 | 1.883791667 | 3.548671043 | ||||||||
| 12.369 | 34.288 | -21.919 | -13.95420833 |<PHONE_NUMBER> | ||||||||
| 12.944 | 23.894 | -10.95 | -2.985208333 | 8.911468793 | ||||||||
| 14.233 | 17.96 | -3.727 | 4.237791667 | 17.95887821 | ||||||||
| 19.71 | 22.058 | -2.348 | 5.616791667 | 31.54834863 | ||||||||
| 16.004 | 21.157 | -5.153 | 2.811791667 | 7.906172377 | ||||||||
| x-bar (Confruent) | 14.051125 | |||||||||||
| x-bar (InConfruent) | 22.01591667 | |||||||||||
| Sample Size | 24 | |||||||||||
| degree of freedom | 23 | |||||||||||
| point estimate | -7.964791667 | |||||||||||
| d-bar( mean of differences) | -7.964791667 | |||||||||||
| variance of diffences | 23.66654087 | |||||||||||
| S (stndard deviation of defferences | 4.86482691 | |||||||||||
| Standard Error of Mean Diff | 0.993028635 | |||||||||||
| t-statistics | -8.020706944 | t-critical for alpha : 0.05 |
-2.069 | to | 2.069 | |||||||
| margin of error | 2.054576245 | |||||||||||
| Cohen's d | -1.637219949 | |||||||||||
| Confidance Interval | Left: | -10.01936791 | ||||||||||
| Right: | -5.910215421 | |||||||||||
| p-value | The
two-tailed P value is less than 0.0001 By conventional criteria, this difference is considered to be extremely statistically significant. |
|||||||||||
| links | 1.
https://www.graphpad.com/quickcalcs/pValue2/ 2. https://s3.amazonaws.com/udacity-hosted-downloads/t-table.jpg |
|||||||||||
| Answer 6 | ||||||||||||
| Reason of the effect observed
between the two above mentioned samples: with Incongruent word sampels, as soon as we see the word subconciusly we try to read the word rather than observe the coler and end up mentioning what the word reads rather than what is the color of the word. |


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This was provided and transferred to Google Drive: https://drive.google.com/file/d/1RtxqYvPMmcVhZWrww6fFJv8HhdJKJsGV/view?usp=sharing
closed
by James R. Griffin III at 2020-12-16 15:22:25.review_requested
by Axa Mei Liauw at 2020-12-16 13:19:57.referenced
by Kevin Reiss at 2020-12-16 15:37:18.merged
by Kevin Reiss at 2020-12-16 15:37:18.closed
by Kevin Reiss at 2020-12-16 15:37:18.head_ref_deleted
by Kevin Reiss at 2020-12-16 15:37:26.referenced
by Kate Lynch at 2020-12-16 14:17:14.merged
by Kate Lynch at 2020-12-16 14:17:14.closed
by Kate Lynch at 2020-12-16 14:17:14.referenced
by Kate Lynch at 2020-12-16 14:37:50.merged
by Kate Lynch at 2020-12-16 14:37:51.closed
by Kate Lynch at 2020-12-16 14:37:51.This doesn't prevent a merge, however an expansion of this might be linking to some of the external resources we consult for coming up with this line of reasoning. I'll make an issue for this, for later discussion.
referenced
by Kate Lynch at 2020-12-16 14:40:06.merged
by Kate Lynch at 2020-12-16 14:40:06.closed
by Kate Lynch at 2020-12-16 14:40:06.closed
by Kate Lynch at 2020-12-16 14:40:06.closed
by Kate Lynch at 2020-12-16 14:43:59.closed
by Kate Lynch at 2020-12-16 14:43:59.closed
by Kate Lynch at 2020-12-16 14:43:59.closed
by Kate Lynch at 2020-12-16 14:43:59.referenced
by Kate Lynch at 2020-12-16 14:43:59.merged
by Kate Lynch at 2020-12-16 14:43:59.closed
by Kate Lynch at 2020-12-16 14:44:00.This needs to be updated in priority following a meeting on 12/16/20, and the dspace-cli with the Scholarly Communications Librarian. They shall provide the body for the e-mail being sent in response to submissions and releases.
One should be able to support asynchronous listening with the following PostgreSQL statements:
NOTIFY workflowitem_transaction;
CREATE TRIGGER "on_workflowitem_transaction"
AFTER INSERT OR DELETE OR UPDATE
ON public.workflowitem
FOR EACH ROW
NOTIFY workflowitem_transaction, json_build_object('table', TG_TABLE_NAME, 'action', TG_OP, 'old_data', OLD, 'new_data', NEW);
A client would the subscribe using the following:
sql
LISTEN workflowitem_transaction;
Listening for these updates can be supported in Ruby using https://github.com/ged/ruby-pg/blob/master/spec/pg/connection_spec.rb#L477
Implementing a new daemon process for systemd
should involve the following:
$stdout.reopen('/var/log/dspace-listener.log', 'a')
$stdout.sync = true
loop.with_index do |_, i|
# ...
sleep(3)
end
For the systemd
service file:
```properties
[Unit]
Description=DSpace JRuby Event Listener
[Service] User=username Group=username WorkingDirectory=/home/username Restart=always ExecStart=/usr/bin/ruby dspace_listener.rb ```
$ systemctl start dspace-listener
# ...
$ systemctl status dspace-listener
● dspace-listener.service - DSpace JRuby Event Listener
assigned
by James R. Griffin III at 2020-12-16 15:41:18.labeled
by James R. Griffin III at 2020-12-16 15:41:25.renamed
by James R. Griffin III at 2020-12-16 15:42:05.Coverage remained the same at 76.876% when pulling 81fbdb92a3a6fc98461ac5baab8916fcfce77fca on 859-sqs into aba24c5c94dea07a0d9556c550b617970596d041 on alma.
review_requested
by Christina Chortaria at 2020-12-16 15:43:43.head_ref_force_pushed
by None at 2020-12-16 16:44:04.referenced
by Christina Chortaria at 2020-12-16 16:55:05.merged
by Christina Chortaria at 2020-12-16 16:55:05.closed
by Christina Chortaria at 2020-12-16 16:55:05.head_ref_deleted
by Christina Chortaria at 2020-12-16 16:55:06.review_requested
by Kevin Reiss at 2020-12-16 14:14:52.referenced
by None at 2020-12-16 18:57:11.merged
by None at 2020-12-16 18:57:11.closed
by None at 2020-12-16 18:57:11.head_ref_deleted
by None at 2020-12-16 18:57:12.renamed
by Kevin Reiss at 2020-12-16 14:59:48.assigned
by None at 2020-12-16 19:00:16.Coverage remained the same at 76.876% when pulling b28ea56f20108ed261b2879c29639a3490b05f37 on readme-updates into c216b41af16df8e327ae4cb677796a71d5295379 on alma.
review_requested
by Christina Chortaria at 2020-12-16 21:08:21.referenced
by Christina Chortaria at 2020-12-16 21:09:35.merged
by Christina Chortaria at 2020-12-16 21:09:35.closed
by Christina Chortaria at 2020-12-16 21:09:35.head_ref_deleted
by Christina Chortaria at 2020-12-16 21:09:36.Coverage decreased (-5.2%) to 76.876% when pulling 42aca287ac26563b53fef040f5c5e8cfa50c7dfc on alma into d2923fd010050b3acf04ce4de47e1727e9442bc4 on main.
Current path for incremental partner updates: /scsb-test/data-exports/PUL/MarcXML/Incremental Current path for incremental partner deletes: /scsb-test/data-exports/PUL/Json/Incremental Current path for full partner updates: /scsb-test/data-exports/PUL/MarcXML/Full
Coverage remained the same at 76.876% when pulling 32a1642a3edc1a44b4178e51a16e3213e0e4cab9 on 926-catalog-date-publishing-job into 42aca287ac26563b53fef040f5c5e8cfa50c7dfc on alma.
head_ref_force_pushed
by Christina Chortaria at 2020-12-16 16:53:16.head_ref_force_pushed
by Christina Chortaria at 2020-12-16 22:22:46.review_requested
by Christina Chortaria at 2020-12-16 23:01:06.assigned
by None at 2020-12-16 15:08:24.head_ref_force_pushed
by None at 2020-12-16 18:31:34.referenced
by Kevin Reiss at 2020-12-16 20:33:49.merged
by Kevin Reiss at 2020-12-16 20:33:49.closed
by Kevin Reiss at 2020-12-16 20:33:49.head_ref_deleted
by Kevin Reiss at 2020-12-16 20:33:53.Resolved: Confluence is back up in 3f6d075
.
labeled
by Francis Kayiwa at 2020-12-16 03:54:01.labeled
by Francis Kayiwa at 2020-12-16 03:54:01.locked
by Francis Kayiwa at 2020-12-16 03:54:02.closed
by Francis Kayiwa at 2020-12-16 04:29:28.


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A year on Mercury is just 88 days long.
One solar day (the time from noon to noon on the planet’s surface) on Mercury lasts the equivalent of 176 Earth days while the sidereal day (the time for 1 rotation in relation to a fixed point) lasts 59 Earth days. Mercury is nearly tidally locked to the Sun and over time this has slowed the rotation of the planet to almost match its orbit around the Sun. Mercury also has the highest orbital eccentricity of all the planets with its distance from the Sun ranging from 46 to 70 million km.
Mercury is the smallest planet in the Solar System.
One of five planets visible with the naked eye a, Mercury is just 4,879 Kilometres across its equator, compared with 12,742 Kilometres for the Earth.
Mercury is the second densest planet.
Even though the planet is small, Mercury is very dense. Each cubic centimetre has a density of 5.4 grams, with only the Earth having a higher density. This is largely due to Mercury being composed mainly of heavy metals and rock.
Mercury has wrinkles.
As the iron core of the planet cooled and contracted, the surface of the planet became wrinkled. Scientist have named these wrinkles, Lobate Scarps. These Scarps can be up to a mile high and hundreds of miles long.
Mercury has a molten core.
In recent years scientists from NASA have come to believe the solid iron core of Mercury could in fact be molten. Normally the core of smaller planets cools rapidly, but after extensive research, the results were not in line with those expected from a solid core. Scientists now believe the core to contain a lighter element such as sulphur, which would lower the melting temperature of the core material. It is estimated Mercury’s core makes up 42% of its volume, while the Earth’s core makes up 17%.
Mercury is only the second hottest planet.
Despite being further from the Sun, Venus experiences higher temperatures. The surface of Mercury which faces the Sun sees temperatures of up to 427°C, whilst on the alternate side this can be as low as -173°C. This is due to the planet having no atmosphere to help regulate the temperature.
Mercury is the most cratered planet in the Solar System.
Unlike many other planets which “self-heal” through natural geological processes, the surface of Mercury is covered in craters. These are caused by numerous encounters with asteroids and comets. Most Mercurian craters are named after famous writers and artists. Any crater larger than 250 kilometres in diameter is referred to as a Basin. The Caloris Basin is the largest impact crater on Mercury covering approximately 1,550 km in diameter and was discovered in 1974 by the Mariner 10 probe.

Owing to its proximity to the Sun, Mercury is a difficult planet to visit. During 1974 and 1975 Mariner 10 flew by Mercury three times, during this time they mapped just under half of the planet’s surface. On August 3rd 2004, the Messenger probe was launched from Cape Canaveral Air Force Station, this was the first spacecraft to visit since the mid 1970’s.
Mercury is named for the Roman messenger to the gods.
The exact date of Mercury’s discovery is unknown as it pre-dates its first historical mention, one of the first mentions being by the Sumerians around in 3,000 BC.
Mercury has an atmosphere (sort of).
Mercury has just 38% the gravity of Earth, this is too little to hold on to what atmosphere it has which is blown away by solar winds. However while gases escape into space they are constantly being replenished at the same time by the same solar winds, radioactive decay and dust caused by micrometeorites