QUEEN OF OUTER SPACE A film review by Steve Rhodes Copyright 1996 Steve Rhodes
RATING (0 TO ****): ***
Some movies are so bad, they are good. So it is with classic B movie director Edward Bernds's QUEEN OF OUTER SPACE (1958) staring that memorable Hollywood celebrity Zsa Zsa Gabor.
Although you may not recall the name Edward Bernds, he, like Ed Wood (PLAN 9 FROM OUTER SPACE), made low budget schlock pictures (THE THREE STOOGES IN ORBIT, HIGH SCHOOL HELLCATS, and THE BOWERY BOYS MEET THE MONSTERS). Unlike Ed Wood, his movies have a bit more polished look.
QUEEN OF OUTER SPACE is a parody of science fiction films. Whether it meant to be so at the time is another question. The dialog by Charles Beaumont (based on a story by Ben Hecht) is so totally ridiculous that it had the audience at San Jose's Towne Theater in stitches.
Four American astronauts, Eric Fleming (Gil Favor in TV's "Rawhide") as Capt. Neal Patterson, Dave Willock as Lt. Mike Cruze, Patrick Waltz as Lt. Larry Turner, and Paul Birch as Prof. Konrad, are on their way to Venus when a mysterious ray causes them to crash into the planet. Once there, they find the planet is inhabited by nothing but women. Hey, this is Venus remember. You know, Goddess of Love and all that.
The costumes by Irene Caine and Thomas Pierce are the piece de resistance of the picture. The earthmen have boring padded blue space suits, but, ah, the Venusian women. They all wear brightly colored micro-miniskirts, low cut tops, and high heeled shoes that appear to be made of cellophane. Only Queen Yllana (Laurie Mitchell) dresses differently preferring skintight silver petal pushers instead of skirts. The queen also wears a mask, which appears to have been borrowed from a Greek tragedy that was being made in the next studio.
The casting of the film was its other success. Bernds seems bent on finding people without any talent. Proof of acting ability would probably have been sufficient prima facie evidence to disqualify them for QUEEN OF OUTER SPACE. The women did have to meet a single qualification -- attractive legs.
Soon after the earthlings arrive, they are seized by the women. The men are portrayed as nincompoops who utter one insulting sexist phrase after another.  Later, he can not believe they could have invented the ray gun and "even if they invented it, how could they drive it. You know how women drivers are."
The more I watched the film, the more I became convinced that there would soon be a remake of it. I kept seeing director Renny Harlin remaking it with his wife Geena Davis playing a slightly tougher version of the Zsa Zsa Gabor character. For the astronauts I thought Tom Hanks would be good for the Captain's role since he is smartest of a dumb lot.
The sets are hokey and constructed with bright and gaudy colors. The "Beta Disintegrater" looks like something a kindergarten class might put together. The print of the film is a fresh one with strong color rendition. It is in surprisingly excellent shape.
Eventually, a renegade group lead by Talleah (Gabor) comes to the aid of the earthmen. Lt. Turner welcomes them with, "Hi ya, dolls. Glad to hear you're on our side."
After the queen is overthrown, the men's Base Commander (Gerry Gaylor) tells them from earth that, "I know you men are anxious to return home, but you must endure your privations and hardships" for a few more years until a rescue mission can be sent. The men are too busy enjoying being outnumbered to ever want to return.
My favorite in the film has to be Zsa Zsa. She is a hoot.
Just so long as you can get into the spirit of the parody, this is one funny show. Sort of the AIRPORT of the time.
QUEEN OF OUTER SPACE runs just 1:20. It is not rated but would be PG. There is no sex, nudity, bad language, or violence other than people vanishing when shot with ray guns. There are numerous hot kisses. I suspect kids would have to be ten or so to enjoy the picture. I expected to hate the film, but instead found myself laughing hard and often. I recommend this spoof to you and award it ***.
**** = One of the top few films of this or any year. A must see film. *** = Excellent show. Look for it. ** = Average movie. Kind of enjoyable. * = Poor show.  Totally unbearable.
REVIEW WRITTEN ON: November 24, 1996
Opinions expressed are mine and not meant to reflect my employer's.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


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{% extends "layout.html" %} {% block content %} {% cache 36000, "faq" %}
If you have questions that are not covered in this FAQ please contact us at<EMAIL_ADDRESS>The NZ ORCID Hub is a web service that assists the research organisations you're associated with to authoritatively assert these relationships in your ORCID record. Whether you are a student, a member of staff, or (coming soon) have been a recipient of funding, these relationships can be written to your ORCID record, with the source of the information displayed as coming from the organisation involved. This benefits you as it proves that you have a bona fide affiliation with that institution.
Back to topFirstly, make sure the organisation you’re associated with is shown as using the Hub. For a researcher belonging to a Tuakiri-member organisation, simply log in and use the Tuakiri Directory Service to select your home organisation where you'll be able to use your institutional credentials to log in and be returned, authenticated to the Hub. For non-Tuakiri members, you'll first need to receive an email invitation from your organisation. Once the Hub has been involved in writting to your ORCID record, your ORCID iD and organisational relationship is known and you're able to use the login via ORCID route.
Back to topIf you have logged into the Hub using your institutional credentials simply click the button to "Give Your Organisation
Permission To Access Your ORCID Record" and follow the on-screen prompts. The Hub uses the information reported about you
by your organisation: if you're reported as being "staff" and/or "faculty" an employment affilation is written; if you're reported
as being a "student", an education affilation is written; and if neither employment nor education can be detected the Hub
will show you a warning.
If you've come to the Hub through an email invitation, you've already given your organisation
the necessary permissions. Once you have done this, on signing into your ORCID record, you will see that your employment
(or education if you are a student) now has an entry with the source of that information being your institution.
Anyone can sign up for an ORCID iD and say that they are a student or staff at a respected organisation. By allowing your organisation to connect to your ORCID record and verify that you are, indeed, affiliated to that place, the source of this information in your record is more credible than if it is entered by you, manually. By providing an authenticated ORCID iD to your organisation, you're making their work easier and can expect them to be putting processes in place to draw administrative content from your ORCID record to make your life easier as well.
Back to topNot yet.
The use of your home organisation’s login credentials to access services provided by another organisation
is enabled by Federated Identity Management. ORCID's ‘Institutional Account’ sign-in supports Federated Identity Management
for members through the eduGAIN interfederation service. Tuakiri, the New Zealand Access Federation, is in the process of
becoming a full participating member of eduGAIN. Once that happens, individuals at Tuakiri member organisations will be able
to use their home credentials to access their ORCID records.
Your ORCID record belongs to you! If you don't want your organisation to connect to it, you are free to say "No" or to revoke permission if you've already given it. If, at any point, you wish to stop an organisation from accessing your ORCID record, simply log in to your ORCID record and, from the ‘Account Settings’ page, delete the organisation’s entry from your ‘Trusted Organisations’ list. Once removed, the organisation will no longer be able to read your limited-access content or write to your ORCID record until they gain your permission again. If you want to remove yourself, and the record of your ORCID iD from the Hub, simply contact us and we'll delete your Hub record; please note however that information that you've made public in ORCID should be regarded as discoverable even if deleted or subsequently marked as private.
Back to topORCID allows three setting of privacy, with each item in your record able to have its privacy setting specified. The three options are: public, i.e., anyone can see it; private, i.e., only you and the source can see it; and trusted-party, where the item is only visible to you, the source, and anyone you've given read-limited permission to.
Back to topThe Hub requests permission to create and update activities. In the current ORCID schema (v2.0), activities encompass employment, education, funding and research works.
Back to topThe Hub requests long-term permission, as shown by the ticked box in the ORCID permission form stating "Unchecking this box will grant permission this time only". Long-term permissions last for 20 years, and will allow your organsiation to update the items it writes without requiring your intervention. Unchecking this box produces a permission that expires after an hour; i.e., to make changes after this, the organisation will need to get your permission again.
Back to topYour ORCID record really belongs to you! The default level of permission requested through the Hub is a combined ability to both "read your trusted-party information" and "create or update activities", where activities covers your affiliations, funding and research works. If, when asked by ORCID to "Authorize" or "Deny" the request, you select "Deny" you'll be returned to the Hub and given the option of granting lower level permissions, i.e., just "read your trusted-party information", and "know your ORCID iD".
Back to topIn your ORCID record, go to 'account settings' and delete your organisation from the list of 'trusted organisations'. This will also remove it from your Hub connections. When you next visit your Hub profile while logged in with that organisation, you'll be offered the chance to "Give Your Organisation Permission To Access Your ORCID Record" again.
Back to topYes, but like everything in your ORCID record you can choose which entry you make public.
Back to topThe default affiliation written by a Tuakiri-mediated login is rather plain, being only: the organisation, city, country, and whether it's an employment or education affiliation. If your organisation provides a record detailing your affiliation in greater detail, e.g. your study course or job title, start and stop dates, etc, then the Hub is able to write this in place of the Tuakiri-mediated affiliation. Feel free to contact us or your Technical Contact to find out if your organisation has plans to do this.
Back to topYes, definitely. Simply follow the on-screen prompt in the Hub to create an ORCID record when it asks you to sign in or create one.
Back to topContact your institution’s ORCID administrator. This will be the Technical Contact listed for your organisation on this page. If your Technical Contact is not listed, please contact<EMAIL_ADDRESS>and we'll try to assist you
Back to topYes. The Hub is designed to be of use to all NZ ORCID Consortium members. The only requirement is that your organisation is actually using the Hub, and for non-Tuakiri members, you need to recieve an email invitation triggered by your organisation administrator in the Hub. Back to top
This depends on how your organisation manages staff when they leave. If your organisation disables institution credentials, you will no longer be able to log into the Hub using your Tuakiri-mediated log in; however, if you've ever linked your ORCID iD to an organisation with the Hub you'll be able to log in with your ORCID record.
Back to topIf you’re interested in following the Hub’s progress, it’s an open development. Keep an eye on the resources available on the Hub page at the Royal Society Te Apārangi’s website. If you're interested in what's coming up, the Hub's test environment is where features we think are ready for exposure are shown.
Back to top


---
layout: pattern
category: grouping-content
name: blockquote
usage: Represents content that is quoted from another source, optionally with a citation which must be within a footer
or cite
element, and optionally with in-line changes such as annotations and abbreviations. Content inside a blockquote
other than citations and in-line changes must be quoted from another source, whose address, if it has one, may be cited in the cite
attribute.
---
I contend that we are both atheists. I just believe in one fewer god than you do. When you understand why you dismiss all the other possible gods, you will understand why I dismiss yours.


Activity supplier application. Receives and fulfils Activity orders from OPC.
Supplies the activities for vacations. It exposes a web service to accept a supplier
purchase order. When it finishes its part of the order, it sends an invoice to the
order processing center web service.


{% extends 'core/base_invite.html' %} {% load i18n %} {% block title %}{% trans 'Success' %}{% endblock %} {% block body %}
{% blocktrans with name=object.company.name|capfirst %}You've successfully joined lunch group «{{ name }}»!{% endblocktrans %}
{% blocktrans %}Now you just have to wait until we match your lunchmate. We'll send link to their account on Monday.{% endblocktrans %}


Designed like insurance - every entry or exit in the contract delivers 10% proportionally to all other members. Members earn dividends they can withdraw or reinvest at anytime. The contract can always be audited for accuracy.
Read through the four unchangeable core rules that are the foundation for the system. These economic rules emphasize long-term holding over short term profit seeking. There are no centralized administrators.
The entire system is self-governed on the decentralized Ethereum Classic blockchain. This contract has been audited and cannot be modified, removed, or tampered with. Think insurance, with the strength of Bitcoin.
Make sure you keep your seedwords safe! Saturn wallet and Metamask cannot run at the same time. See here for help
1. You buy into the contract by purchasing P3C, every token purchased increases the P3C
price
by +0.00000001 ETC.
2. 10% of what you spend to buy the P3C gets distributed proportionally to all other P3C
holders.
3. When you sell your P3C, you get back ETC at the specified price, and the global price
per
P3C goes down by -0.00000001 ETC.
4. 10% of what you would get back for the sale is distributed to all other P3C holders
proportionally.
Remember, the contract holds enough ETC to pay everyone, but the price you'll get is always changing.
A: P3C is a tool for people that want the freedom to save for retirement, but also want to be able to pull money in and out of their savings without restriction on age or nationality. As more and more people around the world stop working regular full-time jobs, the need for P3C will expand. These are the users P3C wants to serve.
Even if they choose to sell the P3C immediately, you know that 10% of that money is going back to the rest of the community. If enough people build businesses on top of P3C, more people will want to hold it so even if the business you originally supported fails, the network can still grow.
A: Ethereum Classic is a system that allows you to run contracts, like P3C, in a trustless way. This means that the contract and any funds inside of it is protected by computers all throughout the world. Ethereum Classic system also stands for the idea that code is law, which means that however the program runs, even if the results are unexpected, is valid. To use Ethereum Classic, you need ETC which is the native currency. There can only be 210 million ETC. You can purchase ETC on exchanges like Coinbase or Binance.
A: Yes! You can install Trust Wallet on iOS or on Android and enter your same seed words from Saturn to have full access to your Saturn account! We are listed as official token in the Trust wallet marketplace, with full compatability. You can send, receive, and buy P3C with ease.
A: Yes, in fact we encourage it! You can go to the source code and simply follow the README to build your own version in minutes. With your own version, you collect a contract bonus of all transactions going through the website.
A: Re-investing means that you are choosing to take all your ETC earnings (dividends) and exchange them for additional P3C tokens. During re-investment, the 10% community fee is incurred as with all transactions. In this way, reinvesting your tokens increases your holdings, thereby increasing future earnings. Think "compound interest". By default you have auto-compounding turned on.


Hey there! What's upccc?
Checking out iOS7 you know..
Check out this bubble!
It's pretty cool!
Yeah it's pure CSS & HTML
Wow that's impressive. But what's even more impressive is that this bubble is really high.


Terminate uptime monitoring and delete your data.
WARNING: This Action Cannot Be Undone
Open Source Project Created With <3 By Anthony Kung


|
Houzi Game Engine
|
Non copyable class. More...
#include <non_copyable.hpp>
Public Member Functions | |
| non_copyable () noexcept | |
| default constructor | |
| virtual | ~non_copyable () |
| Destructor. | |
| non_copyable (const non_copyable &)=delete | |
| Deleted copy constructor. | |
| non_copyable (non_copyable &&)=default | |
| Defaulted move constructor. | |
| non_copyable & | operator= (const non_copyable &)=delete |
| Deleted copy assignment operator. | |
| non_copyable & | operator= (non_copyable &&)=default |
| Defaulted move assignment operator. | |
Non copyable class.
A class inheriting from non_copyable cannot be copied.


[Erowid Warning: Our understanding of the literature is that there is no such thing as safe use of volatile solvents, aerosols and other street inhalants : their psychoactive effects are inseparable from nerve and organ damage. We have chosen to include these reports to help document the real world use of inhalants, but their inclusion is not intended to imply that they are anything but dangerous.]
I've been addicted to many drugs in my life time ranging from coke to meth but nothing is worse than an addiction to huffing gasoline. Itís a mind trip that no one should be asked to handle. This account of my worst trip ever will forever haunt my mind.
It was a sunny morning in my small hometown and I was feeling a bit perturbed because it had been several days since I'd done any sort of drug. For me, not consuming any kind of drug for more than a 24 hour period is incredible, so I was ready to get back to my usual habits not knowing that the worst was yet to come.
As any other day I was glued in front of the television trying to control my boredom, when the 'unforgettable' taste came lingering into my mouth. I knew the taste well, it was the haunting taste of gas. At this moment I immediately searched for any money to buy something else so I could fight the urge. I was panicked because I knew if I couldnít find money I would cave in to temptation. Sweaty from anxiety I ended up empty handed and the urge to huff was still running strong. I said to myself, ' I'll just huff a little', but knew that I would fail.
I quickly ran to the kitchen and grabbed one of those plastic freezer bags from the drawer. As I walked towards my garage I felt a sort of eeriness but decided to forget about it. Grabbing the red gas can out of the corner I filled the plastic bag half full and began to huff. After about 15 mins I started to feel the incredible buzz, I huffed a bit more(5mins) and then it hit me!
The high started out like it usually did, me wandering around in my backyard thinking I was in a magical land of freedom. The sounds of birds chirping, cars passing and lawnmowers starting, created a sort of dream like state of mind. Getting nauseous and a bit lightheaded I sat on my swing to relax. As I sat there, I heard a tremendous Mac truck flying towards my house(didnít know if it was real or a figment of my imagination) getting scared as it came close, I closed my eyes and it seemed as if the truck hit me and all at once this vision of my self appeared on the other seat on my swing. It came down in 3-D pieces and had a weird echo to it and then I snapped back into reality.
That was the last time I have ever huffed anything and still to this day fear the sound of passing big rigs.
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.


Chapter 5 Introduction to R
5.1 Learning Objectives
- Define the following terms as they relate to R: object, assign, call, function, arguments, options.
- Assign values to objects in R.
- Learn how to name objects
- Use comments to inform script.
- Solve simple arithmetic operations in R.
- Call functions and use arguments to change their default options.
- Inspect the content of vectors and manipulate their content.
- Subset and extract values from vectors.
- Analyze vectors with missing data.
5.2 Creating objects in R
You can get output from R simply by typing math in the console:
## [1] 8
However, to do useful and interesting things, we need to assign values to objects. To create an object, we need to give it a name followed by the assignment operator <-, and the value we want to give it:
<-
is the assignment operator. It assigns values on the right to objects on the left. So, after executing x <- 3
, the value of x
is 3
. The arrow can be read as 3 goes into x
. For historical reasons, you can also use = for assignments, but not in every context. Because of the slight differences in syntax, it is good practice to always use <-
for assignments.
In RStudio, typing Alt + -
(push Alt
at the same time as the -
key) will write <-
in a single keystroke in a PC, while typing Option + -
(push Option
at the same time as the -
key) does the same in a Mac.
Objects can be given any name such as x
, current_temperature
, or subject_id
. You want your object names to be explicit and not too long. They cannot start with a number (2x
is not valid, but x2
is). R is case sensitive (e.g., weight_kg
is different from Weight_kg
).
There are some names that cannot be used because they are the names of fundamental functions in R (e.g., if
, else
, for
). In general, even if it’s allowed, it’s best to not use other function names (e.g., c
, T
, mean
, data
, df
, weights
).
If in doubt, check the help to see if the name is already in use. It’s also best to avoid dots (.) within an object name as in my.dataset. There are many functions in R with dots in their names for historical reasons, but because dots have a special meaning in R (for methods) and other programming languages, it’s best to avoid them.
It is also recommended to use nouns for object names, and verbs for function names. It’s important to be consistent in the styling of your code (where you put spaces, how you name objects, etc.). Using a consistent coding style makes your code clearer to read for your future self and your collaborators. In R, three popular style guides are Google’s, Jean Fan’s and the tidyverse’s. You can install the lintr
package to automatically check for issues in the styling of your code.
5.2.1 Objects vs. variables
What are known as objects in R are known as variables in many other programming languages. Depending on the context, object and variable can have drastically different meanings. However, in this lesson, the two words are used synonymously.
When assigning a value to an object, R does not print anything. You can force R to print the value by using parentheses or by typing the object name:
## [1] 55
## [1] 55
Now that R has weight_kg
in memory, we can do arithmetic with it. For instance, we may want to convert this weight into pounds (weight in pounds is 2.2 times the weight in kg):
## [1] 121
We can also change an object’s value by assigning it a new one:
## [1] 126.5
This means that assigning a value to one object does not change the values of other objects For example, let’s store the animal’s weight in pounds in a new object, weight_lb:
and then change weight_kg
to 100.
5.2.3 Functions and their arguments
Functions are “canned scripts” that automate more complicated sets of commands including operations assignments, etc. Many functions are predefined, or can be made available by importing R packages (more on that later). A function usually takes one or more inputs called arguments. Functions often (but not always) return a value. A typical example would be the function sqrt(). The input (the argument) must be a number, and the return value (in fact, the output) is the square root of that number. Executing a function (‘running it’) is called calling the function. An example of a function call is:
b <- sqrt(a)
Here, the value of a
is given to the sqrt()
function, the sqrt()
function calculates the square root, and returns the value which is then assigned to the object b
. This function is very simple, because it takes just one argument.
The return ‘value’ of a function need not be numerical (like that of sqrt()
), and it also does not need to be a single item: it can be a set of things, or even a dataset. We’ll see that when we read data files into R.
Arguments can be anything, not only numbers or filenames, but also other objects. Exactly what each argument means differs per function, and must be looked up in the documentation. Some functions take arguments which may either be specified by the user, or, if left out, take on a default value: these are called options. Options are typically used to alter the way the function operates, such as whether it ignores ‘bad values’, or what symbol to use in a plot. However, if you want something specific, you can specify a value of your choice which will be used instead of the default.
Let’s try a function that can take multiple arguments: round()
.
## [1] 3
Here, we’ve called round()
with just one argument, 3.14159
, and it has returned the value 3
. That’s because the default is to round to the nearest whole number. If we want more digits we can see how to do that by getting information about the round function. We can use args(round)
to find what arguments it takes, or look at the help for this function using ?round
.
## function (x, digits = 0)
## NULL
We see that if we want a different number of digits, we can type digits = 2
or however many we want.
## [1] 3.14
If you provide the arguments in the exact same order as they are defined you don’t have to name them:
## [1] 3.14
And if you do name the arguments, you can switch their order:
## [1] 3.14
It’s good practice to put the non-optional arguments (like the number you’re rounding) first in your function call, and to then specify the names of all optional arguments. If you don’t, someone reading your code might have to look up the definition of a function with unfamiliar arguments to understand what you’re doing.
5.3 Vectors and data types
A vector is the most common and basic data type in R, and is pretty much the workhorse of R. A vector is composed by a series of values, which can be either numbers or characters. We can assign a series of values to a vector using the c()
function. For example we can create a vector of animal weights and assign it to a new object weight_g
:
## [1] 50 60 65 82
A vector can also contain characters:
## [1] "mouse" "rat" "dog"
The quotes around “mouse”, “rat”, etc. are essential here. Without the quotes R will assume objects have been created called mouse
, rat
and dog
. As these objects don’t exist in R’s memory, there will be an error message.
There are many functions that allow you to inspect the content of a vector. length()
tells you how many elements are in a particular vector:
## [1] 4
## [1] 3
An important feature of a vector, is that all of the elements are the same type of data. The function class()
indicates the class (the type of element) of an object:
## [1] "numeric"
## [1] "character"
The function str()
provides an overview of the structure of an object and its elements. It is a useful function when working with large and complex objects:
## num [1:4] 50 60 65 82
## chr [1:3] "mouse" "rat" "dog"
You can use the c()
function to add other elements to your vector:
## [1] 50 60 65 82 90
## [1] 30 50 60 65 82 90
In the first line, we take the original vector weight_g
, add the value 90 to the end of it, and save the result back into weight_g
. Then we add the value 30 to the beginning, again saving the result back into weight_g
.
We can do this over and over again to grow a vector, or assemble a dataset. As we program, this may be useful to add results that we are collecting or calculating.
An atomic vector is the simplest R data type and is a linear vector of a single type. Above, we saw 2 of the 6 main atomic vector types that R uses: "character"
and "numeric"
(or "double"
).  The other 4 atomic vector types are:
"logical"
forTRUE
andFALSE
(the boolean data type)"integer"
for integer numbers (e.g.,2L
, theL
indicates to R that it’s an integer)"complex"
to represent complex numbers with real and imaginary parts (e.g.,1 + 4i
) and that’s all we’re going to say about them"raw"
for bitstreams that we won’t discuss further
You can check the type of your vector using the typeof()
function and inputting your vector as the argument.
Vectors are one of the many data structures that R uses. Other important ones are lists (list
), matrices (matrix
), data frames (data.frame
), factors (factor
) and arrays (array
).
5.4 Subsetting vectors
If we want to extract one or several values from a vector, we must provide one or several indices in square brackets. For instance:
## [1] "rat"
## [1] "dog" "rat"
We can also repeat the indices to create an object with more elements than the original one:
## [1] "mouse" "rat" "dog" "rat" "mouse" "cat"
R indices start at 1. Programming languages like Fortran, MATLAB, Julia, and R start counting at 1, because that’s what human beings typically do. Languages in the C family (including C++, Java, Perl, and Python) count from 0 because that’s simpler for computers to do.
5.4.1 Conditional subsetting
Another common way of subsetting is by using a logical vector. TRUE
will select the element with the same index, while FALSE
will not:
## [1] 21 39 54
Typically, these logical vectors are not typed by hand, but are the output of other functions or logical tests. For instance, if you wanted to select only the values above 50:
## [1] FALSE FALSE FALSE TRUE TRUE
So we can use this to select only the values above 50
## [1] 54 55
You can combine multiple tests using & (both conditions are true, AND) or | (at least one of the conditions is true, OR):
## [1] 21 54 55
## numeric(0)
Here, <
stands for “less than”, >
for “greater than”, >=
for “greater than or equal to”, and ==
for “equal to”. The double equal sign ==
is a test for numerical equality between the left and right hand sides, and should not be confused with the single =
sign, which performs variable assignment (similar to <-
).
A common task is to search for certain strings in a vector. One could use the “or” operator |
to test for equality to multiple values, but this can quickly become tedious. The function %in%
allows you to test if any of the elements of a search vector are found:
animals <- c("mouse", "rat", "dog", "cat")
animals[animals == "cat" | animals == "rat"] # returns both rat and cat
## [1] "rat" "cat"
## [1] FALSE TRUE TRUE TRUE
## [1] "rat" "dog" "cat"
5.5 Missing data
As R was designed to analyze datasets, it includes the concept of missing data (which is uncommon in other programming languages). Missing data are represented in vectors as NA
.
When doing operations on numbers, most functions will return NA
if the data you are working with include missing values. This feature makes it harder to overlook the cases where you are dealing with missing data. You can add the argument na.rm = TRUE
to calculate the result while ignoring the missing values.
## [1] NA
## [1] NA
## [1] 4
## [1] 6
If your data include missing values, you may want to become familiar with the functions is.na()
, na.omit()
, and complete.cases()
. See below for examples.
## [1] 2 4 4 6
## Returns the object with incomplete cases removed. The returned object is an atomic vector of type `"numeric"` (or `"double"`).
na.omit(heights)
## [1] 2 4 4 6
## attr(,"na.action")
## [1] 4
## attr(,"class")
## [1] "omit"
## Extract those elements which are complete cases. The returned object is an atomic vector of type `"numeric"` (or `"double"`).
heights[complete.cases(heights)]
## [1] 2 4 4 6
Now that we have learned how to write scripts, and the basics of R’s data structures, we are ready to start working with an ADSL dataset!
5.2.2 Comments
The comment character in R is #, anything to the right of a # in a script will be ignored by R. It is useful to leave notes and explanations in your scripts. RStudio makes it easy to comment or uncomment a paragraph: after selecting the lines you want to comment, press at the same time on your keyboard
Ctrl + Shift + C
. If you only want to comment out one line, you can put the cursor at any location of that line (i.e. no need to select the whole line), then pressCtrl + Shift + C
.


Discover what’s included in Bootstrap, including our precompiled and source code flavors. Remember, Bootstrap’s JavaScript plugins require jQuery.
Once downloaded, unzip the compressed folder and you’ll see something like this:
This is the most basic form of Bootstrap: precompiled files for quick drop-in usage in nearly any web project. We provide compiled CSS and JS (bootstrap.*
), as well as compiled and minified CSS and JS (bootstrap.min.*
). source maps (bootstrap.*.map
) are available for use with certain browsers’ developer tools. Bundled JS files (bootstrap.bundle.js
and minified bootstrap.bundle.min.js
) include Popper, but not jQuery.
Bootstrap includes a handful of options for including some or all of our compiled CSS.
| CSS files | Layout | Content | Components | Utilities |
|---|---|---|---|---|
bootstrap.css bootstrap.min.css |
Included | Included | Included | Included |
bootstrap-grid.css bootstrap-grid.min.css |
Only grid system | Not included | Not included | Only flex utilities |
bootstrap-reboot.css bootstrap-reboot.min.css |
Not included | Only Reboot | Not included | Not included |
Similarly, we have options for including some or all of our compiled JavaScript.
| JS files | Popper | jQuery |
|---|---|---|
bootstrap.bundle.js bootstrap.bundle.min.js |
Included | Not included |
bootstrap.js bootstrap.min.js |
Not included | Not included |
The Bootstrap source code download includes the precompiled CSS and JavaScript assets, along with source Sass, JavaScript, and documentation. More specifically, it includes the following and more:
The scss/
and js/
are the source code for our CSS and JavaScript. The dist/
folder includes everything listed in the precompiled download section above. The docs/
folder includes the source code for our documentation, and examples/
of Bootstrap usage. Beyond that, any other included file provides support for packages, license information, and development.


Click on button to test HiDPI.
Take zooming into account: https://developer.mozilla.org/en-US/docs/Web/API/Window/devicePixelRatio
Chek HiDPI


--- layout: default ---
I've been in political science after I completed my undergraduate in the spring of 2006. Over those 12+ years, I've acquired several books along the way for either grad seminars or research. They make for a nice library but the truth is I don't need a lot of these books anymore. I want to give them to people who do need them.
That leads to this, for lack of a better term, "book co-op." Feel free to browse my collection. If you see anything you like, reach out to me via Twitter or via email and let me know what you want. I'll send them to you with only a polite nudge that you could maybe pay it forward by chipping in some money to my PayPal or maybe my Amazon account as a thanks or a means to help defray future shipping costs. You could also find me at a political science conference like MPSA and buy me a beer.


This is the documentation for glc. I suggest you start by reading the intro section. Follow along with that and actually type and run the examples there. Then scan through the Objects, Styles and Property Types sections and try out different objects and styles. Once you get the hang of the program, check the Tips and Advance Use section to take it to the next level.
You can also check out the GLC Blog, where new features, sample code and small tutorials are posted from time to time.


NUnit isolates test assemblies from its own code and from one another by use of separate AppDomains and/or Processes.
By default, NUnit loads a test assembly into a separate AppDomain, while its own code runs in the primary AppDomain.
When multiple assemblies are run at the same time, NUnit loads them differently depending on how they were specified. For assemblies that are part of an NUnit project, then a single AppDomain is used. If the assemblies were specified on the console runner command line, then a separate AppDomain is used for each of them.
If greater separation is desired, test assemblies may be loaded into a separate Process or into multiple processes. This is done automatically by NUnit in the case where the tests are to be run under a different runtime from the one that NUnit is currently using.
Beyond the NUnit default behavior, the user may control the level of isolation through the command line or through NUnit's general settings. Process and AppDomain isolation may also be specified as part of the settings of an NUnit project.
Assembly Isolation may be specified on the console runner commandline using the /process and /domain options. See for more information.
The built-in NUnit defaults may be overridden using the Assembly Isolation panel of the NUnit Settings Dialog. Settings made here are saved and become the new default values for all executions of NUnit until changed. For more info, see the page.
Isolation settings may be specified for an individual NUnit project using the .


$mdBottomSheet
opens a bottom sheet over the app and provides a simple promise API.
Restrictions
- The bottom sheet's template must have an outer
<md-bottom-sheet>
element.
- Add the
md-grid
class to the bottom sheet for a grid layout.
- Add the
md-list
class to the bottom sheet for a list layout.
Usage
Open a Bottom Sheet!
var app = angular.module('app', ['ngMaterial']);
app.controller('MyController', function($scope, $mdBottomSheet) {
$scope.openBottomSheet = function() {
$mdBottomSheet.show({
template: 'Hello!'
});
};
});
Methods
-
$mdBottomSheet.show(options);
Show a bottom sheet with the specified options.
| Parameter |
Type |
Description |
* options
object
|
object |
An options object, with the following properties:
templateUrl - {string=} : The url of an html template file that will
be used as the content of the bottom sheet. Restrictions: the template must
have an outer md-bottom-sheet element.
template - {string=} : Same as templateUrl, except this is an actual
template string.
scope - {object=} : the scope to link the template / controller to. If none is specified, it will create a new child scope.
This scope will be destroyed when the bottom sheet is removed unless preserveScope is set to true.
preserveScope - {boolean=} : whether to preserve the scope when the element is removed. Default is false
controller - {string=} : The controller to associate with this bottom sheet.
locals - {string=} : An object containing key/value pairs. The keys will
be used as names of values to inject into the controller. For example,
locals: {three: 3} would inject three into the controller with the value
of 3.
targetEvent - {DOMClickEvent=} : A click's event object. When passed in as an option,
the location of the click will be used as the starting point for the opening animation
of the the dialog.
resolve - {object=} : Similar to locals, except it takes promises as values
and the bottom sheet will not open until the promises resolve.
controllerAs - {string=} : An alias to assign the controller to on the scope.
parent - {element=} : The element to append the bottom sheet to. The parent may be a function , string ,
object , or null. Defaults to appending to the body of the root element (or the root element) of the application.
e.g. angular.element(document.getElementById('content')) or "#content"
disableParentScroll - {boolean=} : Whether to disable scrolling while the bottom sheet is open.
Default true.
|
| Returns |
Description |
promise |
A promise that can be resolved with $mdBottomSheet.hide() or
rejected with $mdBottomSheet.cancel() .
|
-
$mdBottomSheet.hide([response]);
Hide the existing bottom sheet and resolve the promise returned from
$mdBottomSheet.show()
. This call will close the most recently opened/current bottomsheet (if any).
| Parameter |
Type |
Description |
response
*
|
* |
An argument for the resolved promise.
|
-
$mdBottomSheet.cancel([response]);
Hide the existing bottom sheet and reject the promise returned from
$mdBottomSheet.show()
.
| Parameter |
Type |
Description |
response
*
|
* |
An argument for the rejected promise.
|


After four years dormancy, the Johns Hopkins University chapter of the Institute of Electrical and Electronics Engineers (IEEE) is making a comeback.
[Read more about it here!]
JHU IEEE welcomes any undergraduate studying electrical engineering or computer engineering.
If you are interested in joining, please contact Dana Walter-Shock
Chair: Kevin Nodarse
Vice Chair: Madeline Chabab
Secretary: Eric Rong
Treasurer: Amanda Fernandes
Photos: Will Kirk
Story: Wick Eisenberg
Website: Helena Hahn
Barton Hall, Johns Hopkins University
3400 North Charles St
Baltimore, MD 21218


A bit about myself...
![bloomberg](images/bloomberg-logo.svg)
Infrastructure Engineer
Hackathons
Organiser / Mentor / Hacker
![bt](images/bt.svg)
![ibm](images/ibm.svg)
![helper.io](images/helper.svg)
Applied machine learning in:
* network security
* enterprise software management
* employment
## What is Machine Learning?
A mechanism for machines to **learn** behaviour with no human
intervention
Programs that can **adapt** when exposed to new data
Based on **pattern recognition**
![education](images/application1.jpg)
![security](images/application2.jpg)
![robotics](images/application3.jpg)
![finance](images/application4.jpg)
![speech recognition](images/application5.jpg)
![advertising](images/application6.jpg)
### Huge Growth
### Why?
* cheaper computing computer
* cheaper data storage
* more data than ever ‐ everyone is online
* produces:
- greater volume
- greater variety
* because it's *cool*
### The Difference
![venn diagram](images/venn-diagram.svg)
## Supervised Learning
Use labeled historical data to predict future outcomes
Given some input data, predict the correct output
![shapes](images/shapes.svg)
What **features** of the input tell us about the output?
Feature Space
A feature is some property that describes raw input data
An input can be represented as a vector in
feature space
2 features = 2D vector = 2D space
### Why Use Feature Space?
![feature-extractor](images/feature-extractor.svg)
* Could simply use raw binary data as input
* Raw inputs are complex and noisy
* Abstract the complexity away by using features
Training data is used to produce a model
f(x̄) = mx̄ + c
Model divides feature space into segments
Each segment corresponds to one output class
Use trained model to classify new, unseen inputs
Choosing a Suitable Model
### Evaluation
* Many ways to evaluate
- overall accuracy, number of false positives, etc.
* Depends on what problem you're trying to solve
- are false positive acceptable?
* `k`-fold cross validation commonly used
![k fold cross validation](images/k-fold-cross-validation.svg)
* testing accuracy just using the training dataset is bad
* classifier should generalise to unseen data points
* split training data into two sets
- one for training
- one for testing
* perform this process *k* times using different splits
### Discrete or Continuous?
* Classification
- output is from a finite, discrete set
- of *'classes'*
* Regression
- output is a real number from a continuous range
## Process
[Jason Brownlee's Process](http://machinelearningmastery.com/process-for-working-through-machine-learning-problems/):
1. define the problem
2. prepare data
3. spot check algorithms
4. tuning
5. present results
### 1. Define the Problem
Models are useless if you're solving the wrong problem
* what is it you exactly want to do?
* primary requirement: speed? correctness?
* what does the data come from?
* how will users/systems be affected by your model?
### Faces vs Vegetables
![face-veg-img](demo/data/face1.jpg)
![face-veg-img](demo/data/vegetable1.jpg)
![face-veg-img](demo/data/face5.jpg)
![face-veg-img](demo/data/vegetable10.jpg)
![face-veg-img](demo/data/vegetable19.jpg)
![face-veg-img](demo/data/vegetable7.jpg)
| | |
| ----------- | ------------------ |
| **Input:** | image (rgb pixels) |
| **Output:** | face or vegetable |
### 2. Prepare the Data
Garbage in, garbage out
* What's the source of the data?
- collected by your system(s)?
- provided by third-parties?
* Which features to extract?
- more features **≠** better accuracy
- how long does it take to extract features?
### Data Source
* 40 images
- 20 faces
- 20 vegetables
* manually labelled by a friend
- who we trust
### Features to Extract from Images
* average intensity of each colour channel across all pixels
- red, green, blue
* average saturation across all pixels
- bright and strong colours
![sobel edge detection](images/sobel-edge-detection.png)
* how about the complexity of the images?
* more complicated shapes have more edge pixels
* feature:
- proportion of pixels are 'edge pixels'
* **sobel edge detection** used to find edge pixels
1. mean red colour
2. mean green colour
3. mean blue colour
4. mean saturation
5. edge pixel ratio
- \# edge pixels / \# total pixels
### 3. Spot Check Algorithms
![](images/machinelearningalgorithms.png)
![recursive data space](images/data-space2.png)
![decision tree](images/decision-tree.png)
![arbitrary data space](images/data-space3.png)
![neural network](images/neural-network.png)
Which algorithm to use?
* Humans can be biased
* Take the decision out of our hands entirely
* **Automate** the selection of algorithms
Spot check every algorithm you can!
* Run your dataset(s) across dozens of algorithms
* **10-fold cross-validation**
- measure accuracy, false positives and false negatives
* compare results of each algorithm using statistical tests
- say *"algorithm A is better than B"* with confidence
### Let's try it out!
![python](images/python.svg)
![sklearn](images/sklearn.svg)
* Python
* scikit-learn
* Could also use:
* Pylearn2, MILK, Theano, ...
```
from sklearn import svm
from sklearn import tree
from sklearn import naive_bayes
classifiers = {
'SVM':
svm.SVC(kernel='linear', C=1),
'Decision Tree':
tree.DecisionTreeClassifier(criterion='gini', split='best'),
'Gaussian Naive Bayes':
naive_bayes.GaussianNB(),
...
}
```
```
from sklearn import preprocessing
from sklearn import cross_validation
featureVecs = preprocessing.normalize(featureVectors)
cross_validation.cross_val_score(
classifier, featureVectors, labels, cv=kFolds)
```
| Classifier | Mean Acc. | Confidence Interval | Lower Bound Acc |
| ------------------------ | --------- | ------------------- | --------------- |
| Gaussian Naive Bayes | 0.975 | 0.15 | 0.825 |
| Decision Tree | 0.95 | 0.2 | 0.75 |
| Multi-Nomial Naive Bayes | 0.85 | 0.331662 | 0.518338 |
| SVM | 0.775 | 0.415331 | 0.359669 |
| Neural Network (Sigmoid) | 0.525 | 0.269258 | 0.255742 |
| Bernoulli Naive Bayes | 0.5 | 0 | 0.5 |
Decision tree had good performance
![face veg decision tree](images/face-veg-decision-tree.svg)
### 4. Tuning
* Pick top `x` algorithms from previous step
* Smaller set of algorithms to manually investigate
* Greater confidence chosen algorithms are naturally good at
picking out the structure of the dataset / feature space
#### Squeeze out Remaining Performance
1. algorithm tuning
- tune each algorithm for better accuracy
- search hyperparameter space
2. ensembles
- combine multiple 'okay' models into one, better model
3. feature refinement
#### Hyperparameter Optimisation
* Learn model **parameters**
* Must set model's **hyperparameters** before training
* Tune performance by searching hyperparameter space
![hyperparameter_optimisation](images/hyperparameter_optimisation.jpg)
[**auto_sklearn**](https://github.com/automl/auto-sklearn)
Library on top of `sklearn`
Automates the spot check and tuning stages
Automatically build ensemble of models
Learns best model types and hyperparameters for you
It's as easy as:
```python
# Train classifier for up to two minutes.
# Longer training time, better accuracy (in general).
autoClassifier = autosklearn.classification.AutoSklearnClassifier(
time_left_for_this_task=120)
autoClassifier.fit(trainingFeatures, trainingLabels)
# Output accuracy of classifier when run against test dataset.
print(autoClassifier.score(testFeatures, testLabels))
print(autoClassifier.show_models())
```
```
Score: 0.987452948557
[(0.940000, SimpleClassificationPipeline(configuration={
'balancing:strategy': 'none',
'classifier:__choice__': 'adaboost',
'classifier:adaboost:algorithm': 'SAMME',
'classifier:adaboost:learning_rate': 1.2306208006800998,
'classifier:adaboost:max_depth': 6,
'classifier:adaboost:n_estimators': 499,
'imputation:strategy': 'median',
'one_hot_encoding:use_minimum_fraction': 'False',
'preprocessor:__choice__': 'extra_trees_preproc_for_classification',
'preprocessor:extra_trees_preproc_for_classification:bootstrap': 'True',
'preprocessor:extra_trees_preproc_for_classification:criterion': 'entropy',
'preprocessor:extra_trees_preproc_for_classification:max_depth': 'None',
'preprocessor:extra_trees_preproc_for_classification:max_features': 3.5347851525007146,
'preprocessor:extra_trees_preproc_for_classification:min_samples_leaf': 6,
'preprocessor:extra_trees_preproc_for_classification:min_samples_split': 8,
'preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf': 0.0,
'preprocessor:extra_trees_preproc_for_classification:n_estimators': 100,
'rescaling:__choice__': 'standardize'})),
(0.020000, SimpleClassificationPipeline(configuration={
'balancing:strategy': 'none',
'classifier:__choice__': 'adaboost',
'classifier:adaboost:algorithm': 'SAMME',
'classifier:adaboost:learning_rate': 1.0081104516473922,
'classifier:adaboost:max_depth': 6,
'classifier:adaboost:n_estimators': 468,
'imputation:strategy': 'mean',
'one_hot_encoding:use_minimum_fraction': 'False',
'preprocessor:__choice__': 'liblinear_svc_preprocessor',
'preprocessor:liblinear_svc_preprocessor:C': 1.1828431725901418,
'preprocessor:liblinear_svc_preprocessor:dual': 'False',
'preprocessor:liblinear_svc_preprocessor:fit_intercept': 'True',
'preprocessor:liblinear_svc_preprocessor:intercept_scaling': 1,
'preprocessor:liblinear_svc_preprocessor:loss': 'squared_hinge',
'preprocessor:liblinear_svc_preprocessor:multi_class': 'ovr',
'preprocessor:liblinear_svc_preprocessor:penalty': 'l1',
'preprocessor:liblinear_svc_preprocessor:tol': 0.0022792606924326923,
'rescaling:__choice__': 'min/max'})),
(0.020000, SimpleClassificationPipeline(configuration={
'balancing:strategy': 'weighting',
'classifier:__choice__': 'proj_logit',
'classifier:proj_logit:max_epochs': 11,
'imputation:strategy': 'median',
'one_hot_encoding:minimum_fraction': 0.002883367159521145,
'one_hot_encoding:use_minimum_fraction': 'True',
'preprocessor:__choice__': 'gem',
'preprocessor:gem:N': 16,
'preprocessor:gem:precond': 0.30628439346357783,
'rescaling:__choice__': 'standardize'})),
(0.020000, SimpleClassificationPipeline(configuration={
'balancing:strategy': 'weighting',
'classifier:__choice__': 'passive_aggressive',
'classifier:passive_aggressive:C': 0.0036975653885940544,
'classifier:passive_aggressive:fit_intercept': 'True',
'classifier:passive_aggressive:loss': 'hinge',
'classifier:passive_aggressive:n_iter': 326,
'imputation:strategy': 'mean',
'one_hot_encoding:use_minimum_fraction': 'False',
'preprocessor:__choice__': 'kitchen_sinks',
'preprocessor:kitchen_sinks:gamma': 0.6227804363658538,
'preprocessor:kitchen_sinks:n_components': 1821,
'rescaling:__choice__': 'normalize'})),
]
```
### 5. Present Results
* Produce document that explains:
- problem
- solution (final algorithm/features/datasets used)
- accuracy / speed of solution
- limitations of solution
* Be sure to list any other insights discovered along the way
![process](images/process.svg)
### Automation is Key
* Create a test harness that:
- feature extraction
- trains models using many algorithms
- evaluates models in a rigorous way
* Ensure you can trust that harness
## Summary
Machine learning is all about **automation**.
It's about automatically finding patterns in data...
...and building models to fit that data.
Models that also *generalise*.
Follow the five step process:
1. define problem
2. prepare data
3. spot check algorithms
4. tuning
5. present results
Automate as much as you can.
So you can focus on **feature engineering**.
Don't reinvent the wheel.
Use the **hundreds of tools** already there.
### Tools
![r](images/r.svg)
![python](images/python.svg)
![java](images/java.svg)
![scala](images/scala.svg)
![sklearn](images/sklearn.svg)
![theano](images/theano.png)
![mdp](images/mdp.png)
![spark](images/spark.png)
### Useful Resources
[Data Mining: Practical Machine Learning Tools and Techniques](http://machinelearningmastery.com/6-practical-books-for-beginning-machine-learning/)
[A Tour of Machine Learning Algorithms](http://machinelearningmastery.com/a-tour-of-machine-learning-algorithms/)
[Jason Brownlee's Process](http://machinelearningmastery.com/process-for-working-through-machine-learning-problems/)
[Introduction to Machine Learning with sci-kit Learn](http://scikit-learn.org/stable/tutorial/basic/tutorial.html)
[Efficient and Robust Automated Machine Learning](https://papers.nips.cc/paper/5872-efficient-and-robust-automated-machine-learning.pdf)
### This Presentation
[donaldwhyte.github.io/intro-to-ml/automated](http://donaldwhyte.github.io/intro-to-ml/automated)
[github.com/DonaldWhyte/intro-to-ml/](http://github.com/DonaldWhyte/intro-to-ml)


A primer on the World Wide Web for those who’re beginning to design & develop for it.
“…there was different information on different computers, but you had to log on to different computers to get at it. Also, sometimes you had to learn a different program on each computer. Often it was just easier to go and ask people when they were having coffee…”
— Sir Tim Berners Lee
Inventor of the World Wide Web
The markup (formatting) language for the Web.
A kind of “address” that is unique and used to identify to each resource on the Web. It is also commonly called a URL.
Allows for the retrieval of linked resources from across the Web.
HTML
CSS
JavaScript
Front End
Back End
Decentralisation
Non-discrimination
Bottom-up Design
Universality
Consensus
Open Source
Open Data
Open Government
Open Access
WebGL
Service Workers
Application Programming Interface (API)
Internet of Things (IoT)
Computer Vision
…and more!


mice Figure P(I:C) immune cytokine JAK liver IFN analysis weight Data using OpenUrl mouse presented calculated pathology significance storm treatment Statistical cytokines mean hours levels results cell response indicated lethal loss treated including mice. relative Kaplan-Meier chromosome increased measured (or SEM. Type blood ***p<;., **p<;., *p<;., COVID- T-test. expression mice, TLR inflammatory inhibition injection signaling CrossRef cells chronic data days. experiment inhibitors littermates samples significantly versus viral Download activation animals day evaluated littermates. observed production responses sham) IFNAR Student’s clinical display higher human indicate inflammation interferon model new single types used INCB Ifnrs Open Student[[#x]]s acute analyzed circulating data-hide-link-title=""> data-icon-position="" figure flow gene inhibitor lost markers mg/kg mortality obtained received receptor strain syntenic tab therapeutic values vehicle ****p<;.. IFN-α Log-rank Mantel-Cox Q-RT-PCR associated daily elevated experimental minutes models surface <;strong>;A<;/strong>;. <;strong>;B<;/strong>;. ****p<;..<;/div>;<;/div>;" ;<;div Cytokine IL- Science Table View Web approved blocks chemokines cluster compared end endpoint exacerbated experiment. genes humane inflammation, occurred patients prior provided ratios representative stimulated stimulation syndrome trials whichever xmlns=";http://www.w.org//xhtml";>;<;span (sham) Altogether, Blood Expression Flow IFNAR, IL-, Importantly, Liver Percentage STAT caused causes cells, collected course cytokines, imiquimod impact innate leading pandemic. pathology, phosphorylation potential strategy study test. time twice &; (chronic Abstract Circulating DS, Furthermore, IFNR IP-, Institute NIH SARS-CoV- SEM Trisomy U/mL) WBC agonist alanine anti-viral apoptotic attenuating beginning block changes co-treated cohort consistent cytometry cytometry. diverse doses elicited encoded experiments. hepatocytes, hypersensitivity independent indicated. indicates induction infections, investigated key kinase mimetic molecular organ parallel people peripheral region respiratory response). rheumatoid sensitivity serum signaling. stained strains studies survived syndrome. systemic transaminase treatment, types. various


The Game
A David Fincher movie
With Michael Douglas, Sean Penn, Deborah Unger, Jim Feingold and others
We've all been there at some point: a brother's birthday approaches and you've no idea what to give him. They guy has got everything. Including more money than you have. So you buy a nice tie. Or you hand bro a gift certificate.
Conrad van Orton (Sean Penn) give his brother Nick (Michael Douglas) a certificate from Consumer Recreation Services. Nick is supposed to play a mysterious game. All he knows about it is that it will change his life.
And his life needs changing. Nick has money galore, but he's been divorced for a long time and instead of friends he has business partners whom he doesn't treat too well (WALL STREET revisited).
So Nick hands in his certificate.
But there's more. He looses everything he owns, shoots his brother by mistake and like his father many years ago sees only one way out of his dilemma: suicide. He jumps off a roof - and lands on a giant air cushion in the middle of his birthday party. After all, it's just a game.
 I found that much harder to believe than all the strange things that happened to Nick during the Game.
The movie is well made and features some superb acting especially by Deborah Unger and Michael Douglas, but the ending ruined it a bit for me. David Fincher cleverly made Nick van Orton a believable character without slowing down the pace of the movie. In the end I just expected more than a big grin plastered on Michael Douglas' face.
Book and movie reviews http://www.inka.de/sites/darwin
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Exercise 7.
Method: Apply "reverse quantitative analysis" (RQA), or working backwards from the numerical result to assess the error, biases, assumptions, uncertainties, exaggerations, dramatization, etc.., to this headline: "Social Isolation Is As Deadly As Smoking Up to 15 Cigarettes a Day," in a public policy/campaign ad by Meals on Wheels (www.mealsonwheelsamerica.org
) to encourage viewers/readers to donate money.
Instructions
First, from a "math for the people" point of view, what are the most important words in the headline?
Research this 'claim" by doing as much searching on the internet as possible and write up your findings.
Ask yourself how do they define "social isolation?" How do they measure it?
Explain to yourself how they have arrived at this association between social isolation and smoking.
Apply the 5 Cs to this situation.
Would you characterize this statement as good information, misleading information, misinformation, or a flat out lie? Or a worthwhile dramatization, useful exaggeration, or hype?


Options
The Options dialog is used to configure the application.
Send To Command Use this field to define one or more send to commands. If the command uses long file names the path and executable filename should be enclosed in double quotes.
KSS supports two special tokens for use in the edit commands (note: the tokens are not case sensitive):
%1 or %file
represents the currently selected filename.
%2 or %line represents the currently selected line number for editors that provide a command line
option to open the file at a specific line number.
The special <Use Windows Default> command cannot be removed from the list and instructs to program to use Windows file associations to determine the Send To command.
Press the ellipsis [...] button to use the Windows Explorer to select the Send To command executable.
Prompt for Command If more than one send to command is defined and this option is checked, the user is prompted to select which command to use.
KSS performs special processing on Clarion file types. This special processing consists of identifying procedure names, code and data sections, and optional comment removal. To accomplish this special processing it is necessary to parse the entire file; if there are many files to process the presentation of the results will be delayed. For the best performance, it is recommended to enumerate the file extensions that will receive this special processing.
Clarion Help File Use the ellipsis button to the right of the field to select the Clarion Help file you would like the application to use. Any Hot Spots in the Text Editor will invoke the selected Clarion help file when clicked with the mouse.
Apply Clarion processing to all files Check this option to ignore the Clarion File Extensions list and apply special processing to all files (not recommended).
Clarion File Extensions Use the Insert, Edit, and Delete buttons to manage the extensions in the list. The listed extensions are matched anywhere in the file name so, and entry of '.CLW', for example will match files named xyz.clw, xyz.clw.old, xyz.bad.clw.copy, etc.
Properties The Properties list contains the names of all property files found by the application. These special property files are used to define the keywords and styles used by the application to provide syntax and lexigraphical highlighting based on a files extension. You can set the font name, size and use of bold, italic and underline, foreground and background colors. You can also choose to hide text with a given style, display all characters as upper or lower case and mark language elements as Hot Spots to trigger a call to the Clarion Help file.
Press the [Edit] button below the properties list, or double click on an entry, to open the Property Editor dialog.
Confirm results deletions
The default behaviour for the program is to display a warning message to
the user when thay are about to delete more than 1 line from the results list. There are three choices
in the associated drop list:
Never - the warning message is never displayed
Always - the warning message is always displayed
When - this choice displays and additional field
removing at least N rows. Use the spin control to set the row limit
for displaying the warning message.
Result List The font Name, Size, Style, and Fore color of the results list.
Application The background color of the main application window.
Toolbar The background color of the application toolbar.
Selected The background color to be used for selected text.
Bookmark The background color to use for bookmarks.
Link Paths and Files with Find Text The Search for dialog has many independent fields and options. When this option is enabled, all options in effect when you press the Search button are saved with the Find text. The next time the Find text is selected from the Most Recently Used list, the options associated with that text are restored to their previous state.
Allow Multiple Instances When this option is selected the user will be allowed to start multiple instances of the application. Note all instances of the application share the same file for linking paths and files with the find text. Much like concurrency in database appplications, the last search for a particular text string will overwrite any previous search for the same text even if it is from a different instance of the application.
Auto Resize Result Columns With this option selected, the application will resize the columns to accommodate the data in the column when the result list is initially loaded.
Restore Point Timer The application can maintain a restore point for your session. This is useful if you work within the application for extended periods and occassionally experience an abnormal termination of the program. The timer value represents the frequency, in minutes, at which Restore Points are created. Set this value to zero to disable the Restore Point feature. Restore Points are deleted when the application terminates normally. If a restore point is detected when the application starts, the user is given the opportunity to recover to the restore point.
Application Function Keys The key combinations associated with the 'Jump to Previous Result Line' and 'Jump to Next Result Line' functions can be reassigned to support alternate keyboard types. Click the adjacent ellipsis buttons to display the Application Function Key Assignment dialog.
Register This button only appears on the unlicensed evaluation copy and is used to register the key provided when the product is purchased. Once the key is registered, the evaluation period is removed and the button will no longer be displayed on the Options dialog.
Apply Closes the window and applies any changes to the application.


[§302A-628] Change in classification. Any teacher who qualifies for a higher class shall be transferred to the higher class as of the beginning of the next semester and shall receive the salary at the appropriate step and range of the higher class. [L 1996, c 89, pt of §2]


07 April 1999
Disease Outbreak Reported
During the last week of March, an outbreak of an unidentified haemorrhagic fever was reported from Rumbek county. The number of cases and deaths is unknown. Samples were immediately sent for testing to the National Institute for Virology in South Africa. A team from WHO has now reached the area in order to: (1) continue the investigation of the etiology of the outbreak; (2) provide barrier nursing material and training to health care workers; and (3) determine the need for additional on-site personnel.


Always interacts with co-workers and other departments in a respectful manner and values their contributions. Cooperate with co-workers and assists them when help is needed. Is complimentary of other departments and a job well done. Arrives on time for scheduled meetings, events or activities.
Honesty and loyalty are key. If two people can be honest with each other about everything, that's probably the biggest key to success.
Success is no accident. It is hard work, perseverance, learning, studying, sacrifice and most of all, love of what you are doing or learning to do.


So far we’ve covered the basics of using AngularJS to interact with RESTful services and Filtering / Ordering views in AngularJS. Using AngularJS Routes, we are going to add a bit of structure to this example app.
If you have not already, please take a look at Part 1 and Part 2 as we will be working with the app we have started there…
First off, lets open our index.ejs file. As you may notice this file is an unstructured mess. We want to break apart the controllers and templates into their own files so our architecture of our demo app is a bit more clear. When we’re done, we will have the following files:
- app.js under /assets/js/angular/
- controllers.js under /assets/js/angular/
- list.html under /public/templates/ – there is a better way to use Angular with Sails, however, for the sake of example this is okay
- detail.html under /public/templates/
- edit.html under /public/templates/
app.js
App.js is where we’re storing our module definition (that we added in Part 1), our factory defintion and our routes. The factory is exactly the same as before except we’ve added an update endpoint.
Resource
1 2 3 |
|
By default, the Angular resource module has get/save/query/remove/delete methods but no update. What’s more, we want to make sure we are using a PUT method for storing our modified food items so Sails knows that we’re trying to modify an existing record. Thankfully, we can add custom actions (as you may have noticed above) by simply adding a hash after our route parameters object in the resource defintion like so { update: {method:'PUT' } }
. Since this is just a hash, you can add as many definitions as you would like (e.g. { update: {method: 'PUT' }, somethingelse: {method: 'DELETE'} }
).
Routing
In Part 1 we are showing/hiding a form based on a $scope variable on our controller. While this works, it may be a bit cleaner to use routing and separate our views by their function. Routing in Angular is pretty straight forward – especially if you have routing experience in other frameworks.
1 2 3 4 5 6 7 8 |
|
When the URL matches one of the route values, the visitor will be directed to the template and given controller (you will notice that we’re using the same controller for all our routes). Additionally, the routes that have :id will have a route parameter of id available in the controller (more on this later). If none of the routes are matched we default to /food. We won’t focus too much on the views becuase they are mostly the same as our old index.ejs, however, they are available in the gist created for this post.
controllers.js
Our controller is mostly the same as before except we’re no longer maintaining which page we’re showing. The whole controller is available as a gist however, some of the more interesting parts are as follows:
1 2 3 4 5 6 |
|
This is checking for the route parameter that we are setting in our route – if it’s there, we get the individual food item with that ID. When the parameter is not there, we get all the food items to be displayed in a list (and initialize a Food item for creates).
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 |
|
In this method we are adding our food item or updating an existing food item. We start by checking the food item’s id. If it has an id, we go ahead and get the server version and update the properties with the form values. If it doesn’t have an id, we save the food item and redirect to the list view. Food.$save is calling the built in resource action where Food.$update is calling the custom resource action we created above – both of these actions then interact with the Sails API on the server.
Wrapping Up
So there we have it. While this is still an example app – it’s way more organized than the previous iterations. The code files are available in this gist.


Safe and Smart Mobility Research Cluster
Loughborough University, Loughborough. LE11 3TU. UK
Tel: +44 1509 226931 | email<EMAIL_ADDRESS>A Quick Guide on using the SafetyCube DSS is available, with instructions on how to browse the system, make a search and further refine the results. The Quick Guide is available for download here. Introductory videos to the SafetyCube DSS can be found here. A full webinar on the SafetyCube DSS is available here.


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Composable Annotations with Overridable Attributes
Generics-based Injection Matching
Many Further Container Refinements
- @Autowired @Lazy on injection points
- requesting a lazy-initialization proxy individually per injection point
- Ordered injection of arrays and lists
- sorting injected beans by Ordered / @Order
- Target-class proxies for classes with arbitrary constructors
- creating CGLIB proxies using Objenesis, not invoking any constructor
- Composable annotations in the test context framework
- e.g. @ContextConfiguration, @WebAppConfiguration, @ActiveProfiles
- Time zone management with dedicated Spring MVC support
- through LocaleContextResolver and TimeZoneAwareLocaleContext


Add a function to your project
- Right click on the project
- Choose "Add", then "Add Azure Function"
- Select your desired function template
- For connection strings, provide a connection string name and specify the value in the project's appsettings.json
Provide Feedback
Report any issues or suggestions by filing an issue in our GitHub repo; include “Visual Studio” in the title


| allMissing {checkmate} | R Documentation |
Supported are atomic types (see is.atomic
), lists and data frames.
Missingness is defined as NA
or NaN
for atomic types and data frame columns,
NULL
is defined as missing for lists.
allMissing
applied to a data.frame
returns TRUE
if at least one column has
only non-missing values. If you want to perform the less frequent check that there is not a single
non-missing observation present in the data.frame
, use all(sapply(df, allMissing))
instead.
allMissing(x) anyMissing(x)
x |
[ |
[logical(1)
] Returns TRUE
if any (anyMissing
) or all (allMissing
)
elements of x
are missing (see details), FALSE
otherwise.
allMissing(1:2) allMissing(c(1, NA)) allMissing(c(NA, NA)) x = data.frame(a = 1:2, b = NA) # Note how allMissing combines the results for data frames: allMissing(x) all(sapply(x, allMissing)) anyMissing(c(1, 1)) anyMissing(c(1, NA)) anyMissing(list(1, NULL)) x = iris x[, "Species"] = NA anyMissing(x) allMissing(x)


Apparently there is no <canvas>.
Change size
Toggle animation
Wibbliness:
Boatometer:
Zoom:
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Speed:
Smooth avg=
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Smooth dev≅
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Main
Map
Volcano
Tsunami
Earthquake
Top 10
Total Number of damaged houses grouped in EMS-98 Damage classes by evaulated communes
Grouped
Stacked
evaluated communes
Dominant land use


Vitalik Buterin Lays Roadmap for Ethereum Visa Levels Quadratic Sharding
“The ethereum killer is ethereum, the ethereum of China is ethereum, the ethereum of Taiwan is ethereum… 2.0.”
Recently, the Beyond Block 2017 was held in Taipei. “The ethereum killer is ethereum, the ethereum of China is ethereum, the ethereum of Taiwan is ethereum… 2.0.” Vitalik Buterin, Ethereum’s inventor, said in his opening remarks. In the meeting, he laid out a plan to reach Visa levels scalability within the next 3-5 years.
Buterin continued by describing the four areas where he sees a need for improvement on the current Ethereum platform. These were privacy, consensus safety, smart contract safety and scalability.
For each of the first three, the Ethereum co-founder sees a solution that is actively developing. However, the problem of scaling is substantial. Vitalik explained that decentralization, scalability and security are a complex trifecta that can present major challenges in the future. While it’s relatively easy to have any two of the three creating a system where all three are functional has proven difficult.
Scalability on the Ethereum, according to Buterin needs to be thousands of transactions per second, be on-chain only, and be without any supernodes. In other words, it must deal with all three of the issues. The solution, per Vitalik, is found in sharding or allowing side chains were protocol changes can be upgraded while keeping the main chain intact.
The change from Proof of Work to Proof of Stake will be a requirement, and Buterin indicated that the timeline is likely three to five years, though he sees a substantial amount of change happening in the near term, as these upgrades begin to take shape.
About Privacy
That upgrade introduced some fairly fancy new cryptographic algorithms, Buterin says, including zero-knowledge proofs and ring signatures which don’t solve the privacy problem on their own but can give coders tools to build solutions.
From a base layer perspective, the privacy problem is three quarters of the way to being solved, he said. The one quarter that isn’t solved… there’s still leaks at the protocol level. Suggesting base layer privacy has been solved, at least conceptually, by zk-Snarks which give you the ability to hide a transaction from all at the same time as allowing you to choose who you wish to show that transaction.
Ethereum’s main problems
Safety, of course, isn’t a problem you solve, only minimize or maximize as may be the case. But one problem that could be solved is scalability.
However it’s a hard problem due to the trilema of decentralization, security, and scalability. Having two out of three is easy he says, providing examples of current solutions that have made that two out of three trade-off:
Existing blockchains, like Ethereum and Bitcoin in their current state, sacrifice scalability, he says, while super big blocks, at the size of 10GB, would sacrifice decentralization, Buterin says.
But ethereum aims to have all three without sacrificing either. One such way is through second layer solutions, like Plasma, Raiden, or the Lightning Network, however ethereum also aims to achieve the trilemma of decentralization, safety and scalability, all on-chain.
He says ethereum aims to scale on-chain, to thousands of transactions, without masternodes, consortium nodes, or any other centralizing aspects. Therefore he presents a first and somewhat basic conceptualized version of sharding.
“The way I generally describe sharding is… you can think of it as, in a fairly simple version, creating a blockchain where you have, lets say, a hundred different universes and each of these universes is a different account space. So you can have an account in some universe or you can have a contract in some universe and you can send a transaction in some universe and if you send a transaction in some universe it only affects stuff in some universe.
” Buterin says before adding:
You might have some protocol of transferring resources, transferring data, between these universes, but it could be more limited, it could be something asynchronous, it could have a two weeks delay, and generally it’s not as clean and convenient as doing stuff in one universe.
But these 100 universes are not just separate blockchains, they are systems that are also interconnected with each other. Particularly, they share consensus. So in order to break even one of them, you have to break the whole thing.
Here’s one example of something we can design fairly easily in the near term. Let’s imagine we keep the main blockchain and into the main blockchain we would publish a contract, and this contract would be called the validator manager contract [which] would maintain an internal Proof of Stake (PoS) system…
This doesn’t describe every possible sharding solution out there, and we can really ratchet things up on the margins and eventually make communications between these different universes really good and possibly even blur the distinction between going across universes and between universes, but this is one simple way of thinking about it.
How would an instantiation of this actually work on ethereum? We could try think about the very far end of what the optimal system would look like, or we can try think about what we can design fairly easily in the near term.
Each of these shards have blocks and transactions, but we are not going to put all of those blocks and transactions into the main chain. Instead, what we are going to do, we are going to take the same structure ethereum currently has, where you have a big block that gets represented by a tiny header, and we’re just going to replicated again one level down.
At the shard level we would have things called collations. A collation is basically just a group of transactions and the collation would have a collation header that would be basically a PoS signed block header, and these collation headers would be pushed into the validator manager contract, but all of the actual transactions in the shards, all of the shards states, all of the shards collations, that would go off-chain.
You’d have these two worlds, Buterin says. You’d have the old world that keeps operating with the same level of scalability which currently is limited as each transaction is replicated by each node that has to run on a laptop.
And this new world with its own rules which has quadratic scalability as nodes validate certain shards and act as light clients for other shards, with this new world potentially having even higher levels of scalability dependent on how sharding is implemented or incrementally improved.
This is all in the early stages of sharding, Buterin says, laying out the roadmap of how it would progress, with it eventually being incorporated at a protocol level through “tight coupling.”
That being, the ethereum network upgrades so that clients enforce a rule which says if the blockchain contains a sharding header that is invalid then the entire blockchain is invalid.
“So basically tight coupling is where the validity of layer two becomes a condition for the validity of layer one,” Buterin says. At which stage the entire sharding system would have the same level of uniform security and it would all be governed by hardforks.
Initially there would be a two speeds ethereum with individuals running an eth node and a sharding node connected to the eth node. The two then eventually, once the network moves to tight coupling, are merged together.
The new shards create a new address space, he says, which means it doesn’t affect normal transactions and the current network.
Allowing devs to engage in important innovations, Buterin says, as they can operate more freely on the shards by turning on improvements only on the shards.
Eventually the main-chain will need to be upgraded, but we can do that later he says as there is no need to slow down by requiring constant on-chain backwards incompatible upgrades.
Ethereum, thus, is to transition into a two speeds lane until it eventually merges again into one road down the line.With developers working on new shards, incrementally improving the code, adding zk-Snarks to shards and other features, increasing their ability to share data and communicate, and then continuously refining it through relatively minor improvements.
The time-line laid out is 3-5 years, thus around 2020. But one of the most difficult aspects, the architecture, seems to have reached a stable conceptual level, so we might perhaps see prototypes even by next year and potential first alpha versions in 2019 or earlier.
References：http://www.trustnodes.com/2017/11/25/vitalik-buterin-lays-roadmap-ethereum-visa-levels-quadratic-sharding https://cointelegraph.com/news/vitalik-lays-out-ethereum-20-roadmap-in-taiwan
「 Declaration: Please indicate the source if repost the article in UNITIMES. Opinions expressed by Contributors belong to themselves. 」


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|
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stackArmor
ThreatAlert Report for {{ report_date }}
Account: {{ account_identifier }} / {{ account_name }}
|
{# X (20) Most Recent Security Configuration Findings #}
Most Recent Security Configuration Findings
| # |
Technology |
Finding |
Note |
Severity |
{% set findings = recent_findings.get('items',None) %}
{% for finding in findings %}
| {{ findings.index(finding) + 1 }} |
{{ finding.technology }} |
{{ finding.finding }}
|
{{ finding.notes }} |
{{ finding.severity }} |
{% else %}
|
No activity
|
{% endfor %}
{# X (20) Most Recent Security Operations Findings #}
Most Recent Security Operations Findings
| # |
Issue |
Severity |
{% set findings = recent_guardduty_findings.get('items',None) %}
{% for finding in findings %}
| {{ findings.index(finding) + 1 }} |
{{ finding.issue }} |
{{ finding.severity }} |
{% else %}
|
No activity
|
{% endfor %}
This is a stackArmor ThreatAlert Daily
Alert. Please review the information and send us an email at
<EMAIL_ADDRESS>for additional support.
|


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You will read short conversations. These are transcriptions of real conversations
real people had over the phone. The last sentence of each conversation will be marked in red. Your task is
to answer a question about the red sentence to the best of your ability.
The HIT will take approximately 15 minutes. Let's start with two examples!
LEGAL INFORMATION:
We invite
you to participate in a research study on language production and comprehension. Your experimenter will
ask you to do a linguistic task such as reading sentences or words, naming pictures or describing scenes,
making up sentences of your own, or participating in a simple language game. You will be paid for
your participation at the posted rate. There are no risks or benefits of any kind involved in this
study. If you have read this form and have decided to participate in this experiment, please
understand your participation is voluntary and you have the right to withdraw your consent or discontinue
participation at any time without penalty or loss of benefits to which you are otherwise entitled. You have
the right to refuse to do particular tasks. Your individual privacy will be maintained in all published and
written data resulting from the study. You may print this form for your records.
CONTACT
INFORMATION:
If you have any questions, concerns or complaints about this research study, its procedures,
risks and benefits, you should contact the Protocol Director Meghan Sumner at<PHONE_NUMBER>
If
you are not satisfied with how this study is being conducted, or if you have any concerns, complaints, or
general questions about the research or your rights as a participant, please contact the Stanford
Institutional Review Board (IRB) to speak to someone independent of the research team at<PHONE_NUMBER> or
toll free at 1-866-680-2906. You can also write to the Stanford IRB, Stanford University, 3000 El Camino
Real, Five Palo Alto Square, 4th Floor, Palo Alto, CA 94306 USA.>
If you agree to participate, please
proceed to the study tasks.
On the following pages, you will see several conversations.
At then end of each one, there will be a sentence in red text.
After reading the conversation and the sentence in red, consider the two sentences on either end of the scale. One will contain the word could and one will contain the word should. Rate which best expresses the meaning of the sentence in red. If both sentences seem like a good fit for the meaning of the sentence in red, choose a number in the middle of the scale.
Speaker #1: I think you should talk to Eric, Maya, or Lindsay if you want help on your project.
Speaker #2: Are any of them an expert on global warming? That's what my project topic is.
Speaker #1: I think Maya is.
Speaker #2: Ok, then I know who I have to talk to.
| I know who I could talk to. | I know who I should talk to. | |||||||
| 1 | 2 | 3 | 4 | 5 | 6 | 7 |
In your rating, consider whether the sentence with should or could best expresses the meaning of the red sentence.
Speaker #1: During this investigation, there are some people you aren't allowed to talk to.
Speaker #2: What do you mean? Like who?
Speaker #1: Didn't you see the court papers on your desk?
Speaker #2: Oh, ok, yes, I did see that. Don't worry. I know who I'm able to talk to.
| I know who I could talk to. | I know who I should talk to. | |||||||
| 1 | 2 | 3 | 4 | 5 | 6 | 7 |
In your rating, consider whether the sentence with should or could best expresses the meaning of the red sentence.
Great! Now we can start the real experiment.
You will now read 20 conversations. You won't always need to read the whole conversation to decide what the speaker means. If both sentences seem like possible meanings, choose a rating in the middle of the scale.
Sometimes, both the sentences on the scale will sound strange. In this case, make your best guess about which one best captures what you think the speaker meant, and then check the box 'Both sentences sound strange.'
Note: these are transcripts of real phone conversations so sometimes the text will be a little jumbled. Do your best and remember that you will have an opportunity to make comments at the end of the experiment.
| could | should | |||||||
| 1 | 2 | 3 | 4 | 5 | 6 | 7 |
Make sure you selected a radio button before clicking 'Continue'
Answering these questions is optional, but will help us understand your answers.
Did you read the instructions and do you think you did the HIT correctly?
Gender:
Age:
Level Of Education:
Native Language:
Do you think the payment was fair?
Did you enjoy the hit?
We would be interested in any comments you have about this experiment. Please type them here:
Thanks for your Time!


Click "MY PROFILE" to return to the "about me" page. Also below "MY PROFILE", you will find some of the projects, several unfinished, that I've been working on. Please click the different ones below (listed in no particular order) to see some of my progress.
Additionally please see the following links for both the Github page, and its respective repository.


An eager-compatible version of recompute_grad.
tf.compat.v1.recompute_grad
tf.compat.v2.recompute_grad
tf.recompute_grad(f)
For f(args, *kwargs), this supports gradients with respect to args, or to gradients with respect to any variables residing in the kwarg 'variables'. Note that for keras layer and model objects, this is handled automatically.
Warning: If f
was originally a tf.keras Model or Layer object, g
will not
be able to access the member variables of that object, because g
returns
through the wrapper function inner
. When recomputing gradients through
objects that inherit from keras, we suggest keeping a reference to the
underlying object around for the purpose of accessing these variables.
f
: function f(*x)
that returns a Tensor
or sequence of Tensor
outputs.A function g
that wraps f
, but which recomputes f
on the backwards
pass of a gradient call.


Questions, suggestions or concerns? Let us know.
The Texas Legislative Guide was designed and developed by Becca Aaronson, Emily Albracht, Daniel Craigmile, Annie Daniel, Ben Hasson and Ryan Murphy for The Texas Tribune. The Tribune is a nonpartisan, nonprofit media organization that promotes civic engagement and discourse on public policy, politics, government and other matters of statewide concern.


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I am now a tenure-track Research Professor and Ph.d supervisor at the School of Big Data & Software Engineering, Chongqing University, China. Prior to joining Chongqing University, I was a Postdoc at Zhejiang Univeristy advised by Prof.Shanping Li and Dr. Xin Xia. I got my Ph.D degree in June 2017 under the supervision of Prof. Xiaohong Zhang from Chongqing University, China.
My currently research focuses on how to improve developers' productivity, how to improve software quality and how to reduce the effort during software development by analyzing rich software repository data. In terms of the techniques, I am interested in adopting different data analytics techniques, including data mining, information retrieval, machine learning and program analysis.
My Chinese homepage can be found at here.


About The Photographer
Stephanie Castro is a student in the School of Communications at the University of Miami. Email<EMAIL_ADDRESS>for inquiries
About The Photos
My main source of inspiration is Miami. The culture, diversity, and history of Miami are all left on my backburner whenever (and wherever) I photograph.
About The Lens
Most of my pictures are taken with a Canon EOS Rebel T6 or the iPhone 7.