ilbmtoppm(1) ilbmtoppm(1) NAME ilbmtoppm - convert an ILBM file into a portable pixmap SYNOPSIS ilbmtoppm [-verbose] [-ignore<chunkID>] [-isham|-isehb] [-adjustcolors] [ILBMfile] DESCRIPTION Reads an IFF ILBM file as input. Produces a portable pixmap as output. Supported ILBM types are: Normal ILBMs with 1-16 planes. Amiga Extra_Halfbrite (EHB) Amiga HAM with 3-16 planes. 24 bit. Multiplatte (normal or HAM) pictures. Color map (BMHD + CMAP chunk only, nPlanes = 0). Unofficial direct color. 1-16 planes for each color component. Chunks used: BMHD, CMAP, CAMG (only HAM & EHB flags used), PCHG, BODY unoffi‐ cial DCOL chunk to identify direct color ILBM Chunks ignored: GRAB, DEST, SPRT, CRNG, CCRT, CLUT, DPPV, DRNG, EPSF Other chunks (ignored but displayed in verbose mode): NAME, AUTH, (c), ANNO, DPI Unknown chunks are skipped. OPTIONS -verbose Give some information about the ILBM file. -ignore <chunkID> Skip a chunk. <chunkID> is the 4-letter IFF chunk identifier of the chunk to be skipped. -isham | -isehb Treat the input file as a HAM or Extra_Halfbrite picture, even if these flags or not set in the CAMG chunk (or if there is no CAMG chunk). -adjustcolors If all colors in the CMAP have a value of less then 16, ilbmtoppm assumes a 4-bit colormap and gives a warning. With this option the colormap is scaled to 8 bits. BUGS The multipalette PCHG BigLineChanges and Huffman decompression code is untested. REFERENCES Amiga ROM Kernel Reference Manual - Devices (3rd Ed.) Addison Wesley, ISBN 0-201-56775-X SEE ALSO ppm(5), ppmtoilbm(1) AUTHORS Copyright (C) 1989 by Jef Poskanzer. Modified October 1993 by Ingo Wilken<EMAIL_ADDRESS>burg.de) 04 October 1993 ilbmtoppm(1)


In this case it's easy to miss the super method and suggest that the call
is referenced to the method in the containing class.
To clarify the intent it is recommended to add an explicit
super
qualifier to the method call.
Example:
class Parent {
void ambiguous(){}
}
class Example {
void ambiguous(){}
class Inner extends Parent {
void example(){
ambiguous(); //warning
}
}
}
After the quick-fix is applied:
class Parent {
void ambiguous(){}
}
class Example {
void ambiguous(){}
class Inner extends Parent {
void example(){
super.ambiguous();
}
}
}


The schema viewer allows developers to view schemas in a graphical manner. The schema viewer is illustrated below:
The icons used in the schema viewer (and in the differencing tool) are similar to Visual Studio object viewer icons. They are:
| xs:sequence | Represents a sequence of elements in a specific order | |
| xs:choice | Represents a choice (ie:choose one of) elements | |
| xs:any (or mixed content) | Identifies that the contents of the element may be anything | |
| xs:element | Represents an element (ie: <property/>) | |
| xs:attribute | Represents a an attribute (ie: <property attribute="value"/>) |
| Copyright (C) 2010, Mohawk College of Applied Arts and Technology |


Is there new items coming in to the store? Click on {{view1.dashboard}}
{{view1.dashboard}}
Expert advice on pet nutrition and providing the best care you can.
View details »
Handy training tips, tricks and help understanding your pet's Behaviour.
Have a question? Our experts are here to help!


{% extends "layout.html" %} {% block page_title %} Addresses in application {% endblock %} {% block content %} Return address if we can't legalise your documents Where would you like us to post your documents if we're unable to legalise them? Same address as beforeMark Barlow, 118, Oakfield Road, London, N10 6LL, United Kingdom Different address Current version on live Where would you like us to post your documents if we’re unable to legalise them? Same address as before Different address Mark Barlow 3 Fletton Road London N11 2QL United Kingdom Continue {% endblock %}
Where would you like us to post your documents if we're unable to legalise them?


{{sighting.description}}
Spotted on
{{sighting.datetime|date}}
by {{sighting.spotter.name}}
{% if sighting.location %}
{% endif %}
{% extends "base.html" %}
{% block content %}
{% for sighting in sightings %}
Spotted on
{{sighting.datetime|date}}
{{sighting.description}}
by {{sighting.spotter.name}}
{% if sighting.location %}
{% endif %}


Big O Complexity and Notation
Nearly all computer programs use algorithms, each with varying complexity; a basic gradebook for teachers would use simple searching algorithms to find students while something like Google Maps uses complex algorithms to find the optimal routes between two locations. For a gradebook example, the algorithm to search for students may not be that efficient, but that doesn't matter because the data size is very small--only a few hundred students. However, Google Maps has to analyze thousands or even millions of potential routes so their algorithms must be very efficient. So an important question follows: how do we determine how efficient an algorithm is, and how do we compare two algorithms? We use Big O notation.
Big O notation measures how many steps the computer needs in order to complete the algorithm based on how many inputs are provided. The 'input' is just the set of data we are operating on, so if we are searching for a student's name in a gradebook, and there are 240 total students, there would be a total of 240 inputs. If we search for a route in California in Google Maps, the size of the input would be the total number of roads (or crossroads) in California. And so on. We call the number of inputs, 'n'. As 'n', or the number of inputs, increases, so too does the time it takes to complete the algorithm. The purpose of Big O notation is to see how long the algorithm requires based on the inputs, and the notation looks like this: O(n), or O(n^2), or O(2^n), etc. An algorithm with a running time of O(n) means that the algorithm time scales linearly with the amount of inputs; for example, an arbitrary algorithm can process 1,000 inputs in a second, so with a linear algorithm, it can process 2,000 inputs in two seconds, 3,000 inputs in three seconds, and so on. An algorithm with a running time of O(n^2) scales polynomially with the amount of inputs; for example for 1,000 inputs, it may take one second to process, but for 2,000 inputs, it may need 4 seconds to process, for 3,000 inputs, it may need 9 seconds, and so on.
In the previous example, we can see that the first algorithm (the one with the running time of O(n)) can process inputs faster than the algorithm with the running time of O(n^2). The larger the 'n' in the Big O notation, generally, the slower the algorithm is. Since O(n) is smaller than O(n^2), O(n) is generally faster. One thing to note is that Big O notation does not account for constants--so for example, if an algorithm has an input of 100 items, and the algorithm searches through all the inputs twice, the running time would be 2n (where n = 100, the size of the inputs), but when we put it in Big O notation, we ignore the 2 and just write O(n) instead of O(2n). That is a limitation of Big O notation, and an algorithm with large constants (which are not reflected in Big O notation) may leave the algorithm unfeasible. Here is a better comparison of the runtimes:
- O(1) - Constant time. The amount of steps the algorithm requires is fixed
- O(log(n)) - Logarthmic time. Very fast. Scales logarthmically with the input size
- O(n) - Linear time. Fast. Scales directly with the size of inputs
- O(n^c) - c is a constant (2,3,4,etc). Polynomial time.
- O(c^n) - Exponential time. Very very slow.
- O(n!) - Factorial. Essentially the slowest run time


| rcompgen {utils} | R Documentation |
This page documents a mechanism to generate relevant completions from a partially completed command line. It is not intended to be useful by itself, but rather in conjunction with other mechanisms that use it as a backend. The functions listed in the usage section provide a simple control and query mechanism. The actual interface consists of a few unexported functions described further down.
rc.settings(ops, ns, args, func, ipck, S3, data, help, argdb, fuzzy, quotes, files) rc.status() rc.getOption(name) rc.options(...) .DollarNames(x, pattern) ## Default S3 method: .DollarNames(x, pattern = "") ## S3 method for class 'list' .DollarNames(x, pattern = "") ## S3 method for class 'environment' .DollarNames(x, pattern = "")
ops, ns, args, func, ipck, S3, data, help, argdb, fuzzy, quotes, files |
logical, turning some optional completion features on and off.
All settings are turned on by default except |
name, ... |
user-settable options. Currently valid names are
Usage is similar to that of |
x |
An R object for which valid names after |
pattern |
A regular expression. Only matching names are returned. |
There are several types of completion, some of which can be disabled
using rc.settings
. The most basic level, which can not be
turned off once the completion functionality is activated, provides
completion on names visible on the search path, along with a few
special keywords (e.g., TRUE
). This type of completion is not
attempted if the partial ‘word’ (a.k.a. token) being completed
is empty (since there would be too many completions). The more
advanced types of completion are described below.
$
and @
:When the ops
setting is turned on, completion after
$
and @
is attempted. This requires the prefix to
be evaluated, which is attempted unless it involves an explicit
function call (implicit function calls involving the use of
[
, $
, etc do not inhibit evaluation).
Valid completions after the $
extractor are determined by
the generic function .DollarNames
. Some basic methods are
provided, and more can be written for custom classes.
When the ns
setting is turned on, completion inside
namespaces is attempted when a token is preceded by the ::
or :::
operators. Additionally, the basic completion
mechanism is extended to include all loaded namespaces, i.e.,
foopkg::
becomes a valid completion of foo
if
"foopkg"
is a loaded namespace.
The completion of package namespaces applies only to already
loaded namespaces, i.e. if MASS
is not loaded,
MAS
will not complete to MASS::
. However, attempted
completion inside an apparent namespace will attempt to
load the namespace if it is not already loaded,
e.g. trying to complete on MASS::fr
will load
MASS
if it is not already loaded.
When the help
setting is turned on, completion on help
topics is attempted when a token is preceded by ?
.
Prefixes (such as class
, method
) are supported, as
well as quoted help topics containing special characters.
When the args
setting is turned on, completion on function
arguments is attempted whenever deemed appropriate. The mechanism
used will currently fail if the relevant function (at the point
where completion is requested) was entered on a previous prompt
(which implies in particular that the current line is being typed
in response to a continuation prompt, usually +
). Note
that separation by newlines is fine.
The list of possible argument completions that is generated can be
misleading. There is no problem for non-generic functions (except
that ...
is listed as a completion; this is intentional
as it signals the fact that the function can accept further
arguments). However, for generic functions, it is practically
impossible to give a reliable argument list without evaluating
arguments (and not even then, in some cases), which is risky (in
addition to being difficult to code, which is the real reason it
hasn't even been tried), especially when that argument is itself
an inline function call. Our compromise is to consider arguments
of all currently available methods of that generic. This
has two drawbacks. First, not all listed completions may be
appropriate in the call currently being constructed. Second, for
generics with many methods (like print
and plot
),
many matches will need to be considered, which may take a
noticeable amount of time. Despite these drawbacks, we believe
this behaviour to be more useful than the only other practical
alternative, which is to list arguments of the generic only.
Only S3 methods are currently supported in this fashion, and that
can be turned off using the S3
setting.
Since arguments can be unnamed in R function calls, other types
of completion are also appropriate whenever argument completion
is. Since there are usually many many more visible objects than
formal arguments of any particular function, possible argument
completions are often buried in a bunch of other possibilities.
However, recall that basic completion is suppressed for blank
tokens. This can be useful to list possible arguments of a
function. For example, trying to complete seq([TAB]
and
seq(from = 1, [TAB])
will both list only the arguments of
seq
(or any of its methods), whereas trying to complete
seq(length[TAB]
will list both the length.out
argument and the length(
function as possible completions.
Note that no attempt is made to remove arguments already supplied,
as that would incur a further speed penalty.
For a few special functions (library
,
data
, etc), the first argument is treated specially,
in the sense that normal completion is suppressed, and some
function specific completions are enabled if so requested by the
settings. The ipck
setting, which controls whether
library
and require
will complete on
installed packages, is disabled by default because the
first call to installed.packages
is potentially time
consuming (e.g., when packages are installed on a remote network
file server). Note, however, that the results of a call to
installed.packages
is cached, so subsequent calls
are usually fast, so turning this option on is not particularly
onerous even in such situations.
If rc.settings
is called without any arguments, it returns the
current settings as a named logical vector. Otherwise, it returns
NULL
invisibly.
rc.status
returns, as a list, the contents of an internal
(unexported) environment that is used to record the results of the
last completion attempt. This can be useful for debugging. For such
use, one must resist the temptation to use completion when typing the
call to rc.status
itself, as that then becomes the last attempt
by the time the call is executed.
The items of primary interest in the returned list are:
comps |
The possible completions generated by the last
call to |
token |
The token that was (or, is to be) completed, as
set by the last call to |
linebuffer |
The full line, as set by the last call to
|
start |
The start position of the token in the line
buffer, as set by the last call to |
end |
The end position of the token in the line
buffer, as set by the last call to |
fileName |
Logical, indicating whether the cursor is currently inside quotes. |
fguess |
The name of the function the cursor is currently inside. |
isFirstArg |
Logical. If cursor is inside a function, is it the first argument? |
In addition, the components settings
and options
give
the current values of settings and options respectively.
rc.getOption
and rc.options
behave much like
getOption
and options
respectively.
There are several unexported functions in the package. Of these, a few are special because they provide the API through which other mechanisms can make use of the facilities provided by this package (they are unexported because they are not meant to be called directly by users). The usage of these functions are:
.assignToken(text) .assignLinebuffer(line) .assignStart(start) .assignEnd(end) .completeToken() .retrieveCompletions() .getFileComp() .guessTokenFromLine() .win32consoleCompletion(linebuffer, cursorPosition, check.repeat = TRUE, minlength = -1) .addFunctionInfo(...)
The first four functions set up a completion attempt by specifying the
token to be completed (text
), and indicating where
(start
and end
, which should be integers) the token is
placed within the complete line typed so far (line
).
Potential completions of the token are generated by
.completeToken
, and the completions can be retrieved as an R
character vector using .retrieveCompletions
. It is possible for
the user to specify a replacement for this function by setting
rc.options("custom.completer")
; if not NULL
, this
function is called to compute potential completions. This facility is
meant to help in situations where completing as R code is not
appropriate. See source code for more details.
If the cursor is inside quotes, completion may be suppressed. The
function .getFileComp
can be used after a call to
.completeToken
to determine if this is the case (returns
TRUE
), and alternative completions generated as deemed useful.
In most cases, filename completion is a reasonable fallback.
The .guessTokenFromLine
function is provided for use with
backends that do not already break a line into tokens. It requires
the linebuffer and endpoint (cursor position) to be already set, and
itself sets the token and the start position. It returns the token as
a character string.
The .win32consoleCompletion
is similar in spirit, but is more
geared towards the Windows GUI (or rather, any front-end that has no
completion facilities of its own). It requires the linebuffer
and cursor position as arguments, and returns a list with three
components, addition
, possible
and comps
. If
there is an unambiguous extension at the current position,
addition
contains the additional text that should be inserted
at the cursor. If there is more than one possibility, these are
available either as a character vector of preformatted strings in
possible
, or as a single string in comps
.
possible
consists of lines formatted using the current
width
option, so that printing them on the console one line at
a time will be a reasonable way to list them. comps
is a space
separated (collapsed) list of the same completions, in case the
front-end wishes to display it in some other fashion.
The minlength
argument can be used to suppress completion when
the token is too short (which can be useful if the front-end is set up
to try completion on every keypress). If check.repeat
is
TRUE
, it is detected if the same completion is being requested
more than once in a row, and ambiguous completions are returned only
in that case. This is an attempt to emulate GNU Readline behaviour,
where a single TAB completes up to any unambiguous part, and multiple
possibilities are reported only on two consecutive TABs.
As the various front-end interfaces evolve, the details of these functions are likely to change as well.
The function .addFunctionInfo
can be used to add information
about the permitted argument names for specific functions. Multiple
named arguments are allowed in calls to it, where the tags are names
of functions and values are character vectors representing valid
arguments. When the argdb
setting is TRUE
, these are
used as a source of valid argument names for the relevant functions.
If you are uncomfortable with unsolicited evaluation of pieces of
code, you should set ops = FALSE
. Otherwise, trying to
complete foo@ba
will evaluate foo
, trying to complete
foo[i, 1:10]$ba
will evaluate foo[i, 1:10]
, etc. This
should not be too bad, as explicit function calls (involving
parentheses) are not evaluated in this manner. However, this
will affect promises and lazy loaded symbols.
Deepayan Sarkar, deepayan.sarkar@r-project.org


STANDARD
Yamaha Teal Sport Bike
$300 - $1000 /job
Custom-Made Moped
$399.99
CRUISERS
Custom-Made Sport Bullet
highest bidderBMW Road Cruiser
$8,000
Custom-Made Triumph
highest bidderCustom-Made Racer
$5,999.99
Cafe Cruiser 1150
from$2,249.99
Cafe Racer
from$3,999.99
Indian Cafe Cruiser
from$12,000
Royal Enfield
highest bidderSPORT BIKES
Honda CBR600RR
from$6,999.99
Suzuki GSX-R
from$10,999.99
Bullet Sport Bike
from$5,299.99
Ducati (red)
$65,000
TOURING
Harley Davidson (red cruiser)
from$10,000
Harley Davidson (black cruiser)
from$7,499.99
Harley Davidson
from$4,000


Marley
Marley is a movie starring Bob Marley, Ziggy Marley, and Rita Marley. A documentary on the life, music, and legacy of Bob Marley.


Copyright (c) ? ?
The game starts in 5x5 square board with the following setup:
|
| An example
Black moves from a1 to cell [1] and wins, since White is stalemated! Moving a1 to c1 is valid, since it creates a 3 cell area (a2-a1-b1). |


KLEE-related publications:
Below you can find a list of papers that use or extend KLEE. Papers
are listed in chronological order. If you would like to have your
paper listed here, please send email to the
klee-dev
mailing list.
-
KLEE: Unassisted and Automatic Generation of High-Coverage Tests for
Complex Systems Programs
Cristian Cadar, Daniel Dunbar, Dawson Engler
USENIX Symposium on Operating Systems Design and Implementation (OSDI 2008)
December 8-10, 2008, San Diego, CA, USA
-
Server-side Verification of Client Behavior in Online Games
Darrell Bethea, Robert Cochran, Michael Reiter
Network and Distributed System Security Symposium (NDSS 2010)
February 28 - March 3, San Diego, CA, USA
-
KleeNet: Discovering Insidious Interaction Bugs in Wireless Sensor Networks Before Deployment
Raimondas Sasnauskas, Olaf Landsiedel, Muhammad Hamad Alizai,
Carsten Weise, Stefan Kowalewski, Klaus Wehrle
ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN 2010)
April 12-16, 2010, Stockholm, Sweden
-
Execution Synthesis: A Technique for Automated Software Debugging
Cristian Zamfir, George Candea
ACM SIGOPS/EuroSys European Conference on Computer Systems (EuroSys 2010)
April 13-16, 2010, Paris, France
-
Reverse Engineering of Binary Device Drivers with RevNIC
Vitaly Chipounov, George Candea
ACM SIGOPS/EuroSys European Conference on Computer Systems (EuroSys 2010)
April 13-16, 2010, Paris, France
-
Testing Closed-Source Binary Device Drivers with DDT
Volodymyr Kuznetsov, Vitaly Chipounov, George Candea
USENIX Annual Technical Conference (USENIX ATC 2010)
June 22-25, 2010, Boston, MA, USA
-
Stable Deterministic Multithreading through Schedule Memoization
Heming Cui, Jingyue Wu, Chia-che Tsai, Junfeng Yang
USENIX Symposium on Operating Systems Design and Implementation (OSDI 2010)
October 4-6, 2010, Vancouver, BC, Canada
-
AEG: Automatic Exploit Generation
Thanassis Avgerinos, Sang Kil Cha, Brent Lim Tze Hao, David Brumley
Network and Distributed System Security Symposium (NDSS 2011)
February 6-9, 2011, San Diego, CA, USA


Journals in Psychology
Journals in psychology, although most of them are not yet Open Access (optimistically speaking) as previous posts have indicated, function as working memory of scientific findings. They usually follow the idea of collecting and saving and commonly sharing findings...
[Read More]


Sri Lankan President Gotabaya Rajapaksa appoints interim Cabinet
Gotabhaya Rajapaksa as the President cannot hold ministries although he is the head of the Cabinet.
by PTISri Lankan President Gotabaya Rajapaksa on Friday appointed an interim Cabinet which is aimed to run the government until the next parliamentary election.
The 16-member Cabinet included President’s brothers- Mahinda Rajapaksa, 74, and Chamal Rajapaksa, 77, two Tamils and a woman.
This is an interim government, Gotabaya Rajapaksa said during the swearing-in ceremony.
He said ministers of state would be appointed next week.
Gotabhaya Rajapaksa as the President cannot hold ministries although he is the head of the Cabinet.
The Tamil minority members came from the Tamil dominated north and from the central tea plantations areas of Tamils of Indian origin.
Mahinda Rajapaksa, who is appointed on the post of the Prime Minister in the new Cabinet, was also named as the Minister of Defence and Finance while the eldest of the brothers Chamal Rajapaksa was named the Minister of Trade and Food Security.
Dinesh Gunawardena, 70, a veteran Marxist politician has been named as the Minister of Foreign Affairs.
The Cabinet appointment is seen as interim until the President dissolves the current parliament and go for a fresh parliamentary election.
The next parliamentary poll is scheduled only after August 2020. Constitutionally, a sitting prime minister cannot be removed unless he resigns. But following Gotabaya Rajapaksa’s win, the need for a fresh parliamentary poll to allow the new president to form his own government has gained ground.
Gotabaya Rajapaksa could dissolve the current Parliament to call for early elections after February 2020.
Speaker Karu Jayasuriya on Tuesday said that the country faces the possibility of a snap parliamentary poll.
Prime Minister Ranil Wickremesinghe is also under pressure.
“As a party which honours democracy, we will discuss with parliamentary group, the Speaker and party leaders about parliamentary elections,” a statement from Mr. Wickremesinghe’s office said on Monday.
Gotabaya Rajapaksa was on Monday sworn in as Sri Lanka’s seventh President. He defeated Sajith Premadasa, 52, by more than 13 lakh votes.


| A D a |
B E b |
C F c |
x y w |
= | Ax + By + Cw Dx + Ey + Fw ax + by + cw |
| A D a |
B E b |
C F c |
x y w |
= | Ax + By + Cw Dx + Ey + Fw ax + by + cw |
| A D a |
B E b |
C F c |
x y w |
= | Ax + By + Cw Dx + Ey + Fw ax + by + cw |
| ← | - Contents - | → |


Erector - User Guide
Make sure to check out the RDoc Documentation for more details on the API.
- The Basics
- Mixin
- API Cheatsheet
- Pretty-printing
- Using Erector from Ruby on Rails
- Erector tool: Command-line conversion to and from HTML
- Layout Inheritance
- Inline Widgets
- Needs
- Externals
- Blocks
The Basics
The basic way to construct some HTML/XML with erector is to subclass Erector::Widget and implement a content method:
class Hello < Erector::Widget def content html do head do title "Hello" end body do text "Hello, " b "world!" end end end end |
→ |
  <title>Hello</title>   Hello, world!   |
Once you have a widget class, you can instantiate it and then call its
to_s
method. If you want to pass in 'locals' (aka 'assigns'), then do so in the constructor's default hash. This will make instance variables of the same name, with Ruby's '@' sign.
class Email < Erector::Widget def content a @address, :href => "mailto:" end end >> Email.new(:address => "foo@example.com").to_s => "<a href="mailto:foo<EMAIL_ADDRESS>(If you want control over which locals are valid to be passed in to a widget, use the needs macro.)
Mixin
If all this widget stuff is too complicated, just do
include Erector::Mixin
and then call
erector { }
from anywhere in your code. It will make an inline widget for you, pass in the block, and call
to_s
on it. And if you pass any options to
erector
, like
:prettyprint => true
, it'll pass them along to
to_s
!
Examples:
erector { a "lols", :href => "http://icanhascheezburger.com/" } => "lols" erector(:prettyprint => true) do ol do li "bacon" li "lettuce" li "tomato" end end => "
\n
bacon
\n
lettuce
\n
tomato
\n
\n"
API Cheatsheet
| code | output |
|---|---|
element('foo')
|
<foo></foo>
|
empty_element('foo')
|
<foo />
|
html
|

…and likewise for all non-deprecated elements from the HTML 4.0.1 spec |
b 'foo'
|
foo
|
div { b 'foo' }
|

foo

|
text 'foo'
|
foo
|
text '&<>'
|
&<>
…all normal text is HTML escaped, which is what you generally want, especially if the text came from the user or a database |
text raw('&<>')
|
&<>
…raw text escapes being escaped |
rawtext('&<>')
|
&<>
…alias for text(raw()) |
text!('&<>')
|
&<>
…another alias for text(raw()) |
div { text 'foo' }
|

foo

|
div 'foo'
|

foo

|
foo = 'bar'
|

bar

|
a(:href => 'foo.div')
|

|
a(:href => 'q?a&b')
|

…attributes are escaped like text is |
a(:href => raw('&'))
|

…raw strings are never escaped, even in attributes |
a 'foo', :href => "bar"
|
foo
|
text nbsp('Save Doc')
|
Save Doc
…turns spaces into non-breaking spaces |
text nbsp
|

…a single non-breaking space |
text character(160)
|

…output a character given its unicode code point |
text character(:right-arrow)
|
→
…output a character given its unicode name |
instruct
|
<?xml version="1.0" encoding="UTF-8"?>
|
comment 'foo'
|

|
url 'http://example.com'
|
http://example.com
|
capture { div }
|

…returns the block as a string, doesn't add it to the current output stream |
div :class => ['a', 'b']
|

|
javascript(
|

It also collapses redundant externals, so if lots of your widgets declare the same thing (say, 'jquery.js'), it'll only get included once.
There's at least one drawback to this technique: since the externals get declared at class load time, then every external will be emitted on every page, even if that widget isn't on the page at all. This is not usually a problem, but it may lead to namespace collision, so be careful out there.
Page looks for the following externals:
| :js | included JavaScript file |
|---|---|
| :css | included CSS stylesheet |
| :script | inline JavaScript |
| :style | inline CSS style |
Instead of a string, you can also specify a File object; the file's contents get read and used as text. This allows you to inline files instead of referring to them, for potential performance benefits. Example:
external :style, File.new("./web/../public/sample.css")
Blocks
Erector is all about blocks (otherwise known as closures). Unfortunately, there are some confusing aspects to working with blocks; this section aims to clarify the issues so if you find yourself stuck on an 'undefined method' or a nil instance variable, at least you'll have some context to help debug it.
There are basically three cases where you can pass a block to Erector:
1. To an element method
This is the normal case that provides the slick HTML DSL. In the following code:
class Person < Erector::Widget def content div do h3 @name p do b "Birthday: " span @birthday end end end end
the blocks passed in to
div
and
p
are evaluated using normal
yield
semantics, and the
@name
and
@birthday
instance variables are evaluated in the context of the Person instance being rendered.
So far, so good.
2. To the constructor of an Erector::Widget
In this case you can build a widget "on the fly" and have it render whatever it wants, then call your block. This is useful for widgets like
Form
which want to wrap your HTML in some of their own tags.
class PersonActions < Erector::Widget needs :user def content div do widget(Form.new(:action =><EMAIL_ADDRESS>:method => "delete") do input :type => "submit", :value => "Remove<EMAIL_ADDRESS>end) widget(Form.new(:action =><EMAIL_ADDRESS>:method => "post") do b "Send message: " input :type => "text", :name => "message" input :type => "submit", :value => "Email<EMAIL_ADDRESS>end) end end end
In this case, you will get two
form
elements, each of which has some boilerplate HTML for emitting the form element, emitting the hidden
_method
input tag in the case of the delete method, then calling back into your widget to emit the contents of the form. In this case, as above, the
@user
instance variable will be sought inside the calling widget
(PersonActions)
, not the called widget
(Form)
.
A quirk of this technique is that methods inside the block will be called on the calling widget, not the called widget. This doesn't cause any problems for element methods (
b
and
input
above), but may be confusing if you want the block to be able to call methods on the target widget. In that case the caller can declare the block to take a parameter; this parameter will point to the nested widget instance.
widget(Form.new(:action =><EMAIL_ADDRESS>:method => "delete") do |f| span "This form's method is #{f.method}" input :type => "submit", :value => "Remove<EMAIL_ADDRESS>end)
(As a variant of this case, note that the
widget
method can accept a widget class, hash and block, instead of an instance; in this case it will set the widget's block and this code:
widget Form, :action =><EMAIL_ADDRESS>:method => "delete" do input :type => "submit", :value => "Remove<EMAIL_ADDRESS>endwill work the same as the version above.)
3. To the constructor of an Erector::InlineWidget
This is where things get hairy. Sometimes we want to construct a widget on the fly, but we're not inside a widget already. So any block we pass in will not have access to Erector methods. In this case we have a special subclass called
Erector::InlineWidget
which uses two magic tricks:
instance_eval
and
method_missing
to accomplish the following:
- inside the block,
self
points to the widget, not the caller. - methods will be looked for first on the inline widget, and then on the caller.
- instance variables will be looked for on the inline widget only. This can be the source of many a nil! As a general rule, you should probably stay away from instance variables when using inline widgets. However...
- Bound local variables will still be in scope. This means you can "smuggle in" instance variables via local variables. For example:
local_name = @name Page.new do div local_name end.to_s
When using the mixin, you get an inline widget, so the above list of tricks applies.
One note for developers: when creating a widget like
Form
that needs to call back to its block, use the method
call_block
, which calls the block and passes in self as appropriate for both inline and normal widgets.


Why deep learning became relevant
In the last decade, there’s been a widespread interest in artificial intelligence, particularly machine learning, and even more specifically deep learning. Curiously, this topic has not only resurged within academia but rather it has also been commonly showcased on non-technical mediums.
Why these topics became so popular now? Certainly, recent feats such as AlphaGo or Waymo may raise awareness and hint to potential implications in our social organization, especially in the labor sector. Still, but what underlying technical advances have enabled these achievements - and what makes deep learning a paradigm so relevant within the past few years?
In the aforementioned fields, one common task is to reason upon prior knowledge to derive plausible conclusions, a task known as inference. On this matter, strategies within artificial intelligence like expert systems had shared some success by encapsulating an expert’s rationale into knowledge bases. These databases were then used by an inference engine, typically using logical rules, to reason out conclusions.
However, as tasks grow in complexity, performance becomes hindered by computational limitations of reaching a decision using an inference engine in a large database. Not just that, but the lack of satisfactory techniques for reasoning under uncertainty was also an important obstacle that hampered the further development of expert systems (Heathfield (1999)).
A different paradigm, brought forward by machine learning, is to derive the relationships needed for inference using observations. More importantly, these models must be able to generalize this behavior for unseen instances of the given problem. Oftentimes, these relationships within data can be quite convoluted and in recent decades, a class of learning algorithms came to attention by the ability to derive these mappings: local kernel methods.
This family of methods is a fairly recent grouping of techniques that have been developed independently for several years. They are called so due to the transformation performed so-called kernel function onto the input data, and some examples of models are Support Vector Machines, Gaussian processes, among other techniques. A local kernel method can be defined as:
$$f(x) = b + \sum^n_{i=1} \alpha_iK_D\left(x, x_i\right)$$
where $b$ is the bias term, $D$ is the set of observations of cardinality $n$, $α_i$ is scalar chosen by the learning algorithm upon $D$, $x_i$’s are the training input observations and $K_D$ is the kernel function. These methods are more effective than linear models by being able to generate more favorable representations of feature space by using kernels (usually non-linear), achieving fairly positive results in several applications.
Transformation of features to generate a linearly-separable decision space. On the left the original dataset with two classes. On the right a transformation using PCA with a Gaussian kernel.
One typical kernel function is the Gaussian kernel:
$$K_\sigma(u, v) = e^{-\frac{\left\Vert u-v \right\Vert^2}{2\sigma^{2}}}$$
where $\sigma^2$ is the equivalent of the variance in a gaussian probability density function. Note that the function is symmetric and as $u$ and $v$ become very distant from each other, the function approaches zero. This means that for the estimation of a query point $u$, the neighboring values of $u$ have much more influence than those further away from it.
As postulated by David Wolpert in his no free lunch theorem, no model performs better than random guess without any kind of assumption. Local kernel methods are no exception: they implicitly or explicitly partition the input space, obtaining good generalization for a new query point by exploiting the training examples in its neighborhood. This comes at the price of the so-called smoothness prior, meaning that these models expect a target function with little variation of results among neighboring observations.
We may insert additional priors through the choice of the kernel as well as the feature representation. This is why for these types of models it might be beneficial to generate alternative representations of the input data. Rather than using their raw representation, these modifications could more closely conform to the model smoothness prior, yielding better results. Although not targeted at handcrafting representations, Bengio et al. (2014) provides a thorough analysis of good characteristics for representations of features.
However, for particular types of problems the smoothness assumption may not hold, posing a predicament to this family of methods. As an illustration, consider the task of recognizing a character from a $\texttt{20×20}$ pixel grid. If we consider the number of variations of a simple horizontal translation, we notice that a particular observation of the letter $O$ has much more similarity with the letter $U$ in the exact position and orientation that the same letter $O$ shifted horizontally, for instance.
Demonstrations of the amount of variation among observations inter and intra-class.
This indicates that the target function may not be as smooth as expected. In this highly non-linear function, local kernel methods require a very large number of training examples to cover all the desired variations within a class. Hence, the number of necessary templates can grow exponentially with the intrinsic dimension of a class manifold (Bengio and Lecun (2007)).
The set of observations associated with the same class forms a manifold or a set of disjoint manifolds, i.e. regions of lower dimension than the original space of images. When this manifold is smooth, it can be approximated locally by linear patches, tangent to the manifold. However, as the manifold becomes irregular and highly dimensional, patches become smaller and exponentially many patches, as well as data, are required to obtain a good generalization. Source: Bengio (2009)
Note that this does not confront the ability of local kernel methods to approximate functions, rather their efficiency on approximating a function in regards to data. By contrast, neural network models are capable of dealing with intra-class variations more effortlessly. While each kernel function is activated in a small area of the input space, feature detectors of neural networks are capable of detecting certain patterns (edges or curvatures) almost independently from its orientation. The combination of these feature detectors is what makes neural network representations so efficient.
As an illustration, consider the task of representing a number from 0-7. The representation generated by local methods can be seen as a one-hot encoding, signaling that each representation is mutually exclusive, for instance, $\texttt{0000001}$ signals $1$ and $\texttt{0000010}$ signals $2$ but the representation $\texttt{0000011}$ does not convey any valid information. Conversely, a representation of a neural network can be seen as a binary representation, much more efficient: $\texttt{001}$ is equal to $1$, $\texttt{010}$ to 2 and $\texttt{011}$ to $3$.
In terms of classification, local methods produce mutually exclusive partitions onto the feature space which it oftentimes makes it difficult to generalize for unseen instances of the problem, if the target function is not smooth. On the other hand, neural networks generate several partitions which are compositional, presenting a more efficient decision surface that can be more robust to unseen query points.
Sketch of a partition of the feature space produced by local methods (left) and neural networks (right). Note that the sub-partitions of the right figure can be combined to infer unseen instances of the problem, represented by the symbol $?$. These sub-partitions can be seen as potential explanatory factors. As an illustration, these can be the color, shape, and texture in the task of detecting particular types of fruits. Conversely, the partitions on the left symbolize specific combinations of these factors that can indicate a certain fruit. Source: Bengio (2009)
The set of tasks illustrated so far are relatively simple in comparison to those that we see today, as in multi-class object detection. In previous decades, these simpler tasks were carried out relying on a shallow neural network architecture, i.e. using only a small number of layers. However, as the complexity of applications increase, this approach tends to fail.
Complex image classification tasks, for instance, pose a challenge to these methods namely because it becomes overwhelmingly difficult to combine a larger number of low-level features (pixels) to determine a contrasting abstract outcome (object). Alternatively, deep learning is able to better accomplish this task (Bradley (2010, pg. 22)), as experimental outlines in He et al. (2015) and Krizhevsky et al. (2012) indicate breakthrough performances upon increase in network depth.
Results of the 2012 ImageNet classification competition. Only the first out of 5 top models was a deep neural network, which achieved unprecedented performance. Source: ImageNet
Hierarchical learning, deep structured learning, or simply deep learning can be defined as a class of machine learning techniques that exploit many layers of non-linear units (Deng and Yu (2013, pg. 199)). This better capability is attained by the substantial coupling of non-linear operations, deriving complex feature hierarchies from low-level inputs.
Compositional representation of features throughout layers: from pixels to gradients and edges.
Source: Goodfellow et al. (2016, pg. 6)
As illustrated, different representations are synthesized along the layers and as representations become more related to the task in hand, the better the model can perform. However, how many layers are necessary to well approximate a function? In reality, the absolute number of layers is not the important factor, rather how many of these are necessary to effectively represent the target function, denominated as the compact representation. Moreover, if a configuration is smaller than the compact representation, that can generate a negative effect on performance.
It turns out that a configuration with one layer less than the compact representation may need an exponential number of neurons to achieve the same performance. This can be illustrated by the awarded work of Håstad (1986). By analogy, if we consider neural networks as simple logic circuits (which they are able to emulate), we can observe that a logic architecture limited in-depth presents an exponential number of components in comparison with a deep counterpart. Consider the calculation of the parity function, defined as:
$$f:\{0,1\}^{n}\rightarrow\{0,1\},\thinspace f(x)=\left(\overset{|x]}{\underset{i=1}{\sum}}x_{i}\right) mod\space 2$$
The number of logical components for a depth-limited architecture of 2 layers and $N$ inputs is of an order of $O(2^{N})$. On the other hand, unbounded architectures can produce less complex systems, such as the daisy-chain structure of complexity $O(N\thinspace log\thinspace N)$.
Distinct architectures to compute the parity function. A Disjunctive normal form structure (left) with a complexity of $2^{N-1}$ and a balanced tree structure (right) with 5 layers and complexity of $O(N\thinspace log\thinspace N)$.
Conversely, what could happen when freely adding more layers? In principle, besides the additional computational cost, this would not imply any counterpoints to approximating the target function, since the spare layers could simply replicate the second-to-last representation output. However, as in the shallow case, the model may carry too many parameters and insufficient training examples. This, in turn, would have statistical drawbacks: instead of approximating the desired mapping, the model starts to memorize the training data, causing overfitting, i.e. poor generalization1.
Despite the remarked capacity, deep architectures were not widely researched in the past as today. The reasons for this may encompass the former contemptuous view of researchers on this topic, or an insufficient computational power especially compared to contemporary standards. This, however, will not be covered in this series. The challenges of employing such architectures were also imposed by the difficulty in training neural networks with more than two layers, ultimately delivering poor generalization (Bengio et al. (2007))2.
1 This is a generally accepted consequence of very deep models that do not have enough training observations. However, recent research by Nakkiran et al. points to a completely different direction [return].
2 Bengio (2009, pg. 24) appropriately points out that Convolutional Neural Networks with up to seven layers did not suffer as other types of models. This may be due to what the author denominates as a Topographic Structure, suggesting that each neuron in a layer is associated with a small portion of the input. From this, two favorable aspects are hypothesized: the gradient is propagated less diffusely and this hierarchical local connectivity structure may be more suited for image recognition tasks, which is the most common use for such architecture [return].
References
- Heathfield, H. (1999). The rise and “fall” of expert systems in medicine. Expert Systems. 183–188.
- Wolpert, D. (1996), The Lack of A Priori Distinctions between Learning Algorithms. Neural Computation, 1341-1390.
- Bengio, Y., Courville, A. and Vincent, P. (2014). Representation Learning: A Review and New Perspectives
- Bengio, Y. and LeCun, Y. (2007). Scaling Learning Algorithms towards AI. 41.
- Bengio, Y. (2009). Learning Deep Architectures for AI. Foundations and Trends in Machine Learning. 1-127.
- Bengio, Y., Lamblin, P., Popovici, D., and Larochelle, H. (2007). Greedy Layer-Wise Training of Deep Networks. In Advances in Neural Information Processing Systems 19, 153-160.
- Bradley, D. M. (2010). Learning In Modular Systems. PhD Thesis, Carnegie Mellon University.
- Olah, C. (2014). Neural Networks, Manifolds, and Topology. Colah's blog
- Deng, L. and Yu, D. (2013). Deep Learning: Methods and Applications. Foundations and Trends in Signal Processing, 7-197.
- Krizhevsky, A., Sutskever, I., and Hinton, G. E. (2012). ImageNet Classification with Deep Convolutional Neural Networks. Advances in Neural Information Processing Systems 25, 1097-1105.
- He, K., Zhang, X., Ren, S., and Sun, J. (2015). Deep Residual Learning for Image Recognition. Proceedings of the IEEE conference on computer vision and pattern recognition.
- Goodfellow, I., Bengio, Y., and Courville, A. (2016). Deep Learning. MIT Press.


Configuration options are specified as arguments to the configure script. Following is a summary of the current options:
Usage: configure [options] [host]
Options: [defaults in brackets after descriptions]
Configuration --cache-file=FILE cache test results in FILE -- help &n bsp; print this message --no- create do not create output files --quiet, --silent do not print `checking...' messages -- version   ; print the version of autoconf that created configure Directory and file names --prefix=PREFIX install architecture-independent files in PREFIX [/usr/local] --exec-prefix=EPREFIX install architecture-dependent files in EPREFIX [same as prefix] -- bindir=DIR user executables in DIR [EPREFIX/bin] -- sbindir=DIR system admin executables in DIR [EPREFIX/sbin] --libexecdir=DIR program executables in DIR [EPREFIX/libexec] -- datadir=DIR read- only architecture-independent data in DIR [PREFIX/share] --sysconfdir=DIR read-only single-machine data in DIR [PREFIX/etc] --sharedstatedir=DIR modifiable architecture- independent data in DIR [PREFIX/com] --localstatedir=DIR modifiable single-machine data in DIR [PREFIX/var] -- libdir=DIR object code libraries in DIR [EPREFIX/lib] --includedir=DIR C header files in DIR [PREFIX/include] --oldincludedir=DIR C header files for non-gcc in DIR [/usr/include] -- infodir=DIR info documentation in DIR [PREFIX/info] -- mandir=DIR man documentation in DIR [PREFIX/man] -- srcdir=DIR find the sources in DIR [configure dir or ..] --program-prefix=PREFIX prepend PREFIX to installed program names --program-suffix=SUFFIX append SUFFIX to installed program names --program-transform-name=PROGRAM run sed PROGRAM on installed program names Host type -- build=BUILD configure for building on BUILD [BUILD=HOST] -- host=HOST &nb sp; configure for HOST [guessed] --target=TARGET configure for TARGET [TARGET=HOST]
Features and packages --disable-FEATURE do not include FEATURE (same as --enable- FEATURE=no) --enable-FEATURE[=ARG] include FEATURE [ARG=yes] --with-PACKAGE[=ARG] use PACKAGE [ARG=yes] --without-PACKAGE do not use PACKAGE (same as --with-PACKAGE=no) --x-includes=DIR X include files are in DIR --x-libraries=DIR X library files are in DIR --enable- and --disable- with options recognized debugging Include debugging code [enable] gdt- surveying Include GDT survey code [disable] md5 &nb sp; Include support for MD5 keys [enable] des &nb sp; Include support for DES keys [enable] all- clocks Include drivers for all reference clocks [enable] Radio Clocks (these are ordinarily enabled, if supported by the machine and operating system) ACTS &n bsp; NIST dialup clock ARBITER   ; Arbiter 1088A/B GPS receiver AS2201 Austron 2200A or 2201A GPS receiver ATOM &n bsp; ATOM clock BANCOMM   ; BANCOMM clock CHU &nb sp; CHU clock DATUM & nbsp; Datum Programmable Time System DCF7000   ; ELV/DCF7000 GPSVME GPS-VME Clock HEATH & nbsp; HeathKit GC-1000 Most Accurate Clock HOPF6021 &nbs p; HOPF6021 Radio Clock support HPGPS & nbsp; HP 58503A GPS Time & Frequency receiver IRIG &n bsp; IRIG (Audio) Clock LEITCH Leitch CSD 5300 Master Clock System Driver LOCAL- CLOCK Local Clock driver MEINBERG &nbs p; Meinberg clocks MSFEES MSFEES clock MOTO &n bsp; Motorola GPS clock MX4200 MX4200 clock NMEA &n bsp; NMEA GPS clock PARSE & nbsp; PARSE clock code PST &nb sp; PST/Traconex 1020 WWV/H receiver PTBACTS   ; PTB dialup clock support RAWDCF use raw DCF77 time code RCC8000   ; RCC8000 Radio Clock support SCHMID SCHMID DCF77 clock support TRAK &n bsp; TRAK 8810 GPS station clock TPRO &n bsp; KSI/Odetics TPRO/S IRIG Interface TRIMTAIP &nbs p; Trimble GPS/TAIP Protocol TRIMTSIP &nbs p; Trimble GPS/TSIP Protocol TRUETIME &nbs p; Kinemetrics/TrueTime (generic) receiver WWVB &n bsp; Spectracom 8170 or Netclock/2 WWVB receiver USNO &n bsp; US Naval Observatory dialup clock Miscellany accurate-adjtime The adjtime() call is accurate kmem &n bsp; Read kmem tick=VALUE Force a value for 'tick' tickadj=VALUE Force a value for 'tickadj' udp- wildcard Use UDP wildcard delivery slew- always Always slew the time step- slew Step and slew the time ntpdate- step If ntpdate should step the time hourly-todr-sync If we should sync TODR hourly


EastEnders fans beg Jack Branning to bring down Leo Cameron
Leo has bad intentions for Whitney!
by Charlotte RodriguesFans of EastEnders are begging Jack Branning to bring down Leo Cameron.
Viewers know Leo has been targeting Whitney Dean for several weeks and trying to gain her trust.
Leo is the son of paedophile Tony King, the man who groomed Whitney from the ages of 12 to 16.
Read More: EastEnders fans spot 'clue' that Chantelle will murder abuser Gray
However, Leo believes his father was innocent and is out for revenge on Whitney, who is now an adult. But will his plan be rumbled by Jack?
In Thursday night's episode of EastEnders (November 22 2019), Jack was in court seeing to a case of a man who was up for perverting the court of justice, but it was apparent he should also be up for murder.
As the accused came into the courthouse, Leo began grabbing at him calling him "murdering scum" and telling him he doesn't get to hide.
Witnessing Leo's outburst, Jack had him arrested but Leo was able to talk his way out of it without being charged, as he's a paralegal.
Later in The Vic while Leo and Whitney had a drink, Jack walked in and Whitney introduced Leo to her Uncle, but of course they already knew each other.
Leo soon started looking Jack up online and later threatened him, pointing out that he didn't have the cleanest record.
Read More: Strictly's Michelle Visage vying for guest role in EastEnders
Viewers have begged for Jack to bring Leo down.
It looks like fans may not have to wait long for Whitney to find out Leo's identity.
In pictures obtained by Metro.co.uk, Whitney can be seen having a confrontation with Leo in a graveyard.
But what will the outcome be?
EastEnders airs Monday and Friday at 8pm and Tuesday and Thursday at 7.30pm on BBC One.
Leave us a comment on our Facebook page @EntertainmentDailyFix and let us know what you think!


The Standard Parser¶
The StandardFeedParser
is the default parser used when calling
parseFeed
, and should be enough for most, if not all, RSS feeds.
Upon parsing a feed, the StandardFeedParser
does the following:
1. Downloads a feed served by the URL.
2. Parses each entry, excluding those:
- Without a valid link (Valid Links)
- Published before the given timestamp
- For each remaining entry, it creates an Episode object.
On the rare occasion, a feed will be formatted in a way that doesn’t conform to
the format podfeed
expects. In this case, a custom parser can be created by
subclassing the StandardFeedParser
: Custom Parsers
Valid Links¶
In order for a link to be considered valid, it must meet the following requirements:
- Must be present under a “links” section in the parsed feed entry.
- Must have an audio extension (mp3, wav, flac, etc.)
Custom Parsers¶
By default, the standard parser looks for episode links under a “links” section. This may not always be the case, however. Links may end up in another section, or under another name. These feeds can still be parsed, but a custom parser is needed to find the link.
To create a custom parser, subclass StandardFeedParser
and override the
getTrackLink(self, entry)
method. In this method, entry
will be a
dictionary parsed from the feed. Once the link is found, it should be returned
as a string. If no link is present, None
should be returned.
An example parser that retrieves a link under “urls” is below:
import podfeed
class CustomParser(StandardFeedParser):
def getMp3Link(self, entry):
if ("urls" in entry) and (len(entry.urls) > 0):
return entry.urls[0]
else:
return None


--- layout: default title: "404: Page not found" sitemap: false ---
Not to worry.


Jump and Run Game
Restart
Icons made by Pixel perfect from www.flaticon.com
Design Vektor erstellt von pikisuperstar - de.freepik.com
Icons made by Vectors Market from www.flaticon.com


This is a simple grid component that takes a set of data builds a normal table, then adds sorting, grouping, summing and averaging. It is still very much a work in progress. I would like to add asynchronous updating and a whole host of features
example markup:
<p id="grid" simpltry_widget="grid" simpltry_options='
data:{headers: ["cat","hat","count"],
rows: [
["red","baseball", "1"],
["black", "fedora", "3"],
["blue", "fedora", "3"],
["blue", "bowler", "2"],
["red", "bowler", "5"],
["black", "baseball", "101"]
]},
beforeEachRow:
function(tr, i) {
tr.appendChild(Builder.node("td", {}, [i+1]))
},
beforeHeaderRow:
function(tr) {
tr.appendChild(Builder.node("th"))
},
beforeFooterRow:
function(tr) {
tr.appendChild(Builder.node("td"))
}'>
</p>
Above you can see what the "data" format should look like. It has two properties headers and rows. headers is an array of strings, those get built as the table headers. rows is an array of arrays where each array represents a row in your table. You can also pass in some callbacks to be called while the table is being rendered. For instance beforeEachRow gets called before the data is put into the tr, in our example we are simply printing out the row number.
The color picker is builds a dynamic table. Simpltry tries to put css classes on different parts of the widget. Here are a list of the classes that you can use. For any information about which element these classes get placed on there is two things you have to do. First use Firefox and second install the firebug extension. That allows your to inspect your DOM after it has been built, not just the page source that gets downloaded.
A good starting off point is the style sheet we used for this demo. demo style sheet


Module pl.file
File manipulation functions: reading, writing, moving and copying
Functions
| read (filename) | return the contents of a file as a string |
| write (filename, str) | write a string to a file |
| copy (src, dest, flag) | copy a file |
| move (src, dest) | move a file |
| access_time (path) | Return the time of last access as the number of seconds since the epoch |
| creation_time (path) | Return when the file was created |
| modified_time (path) | Return the time of last modification |
| delete (path) | Delete a file |
Functions
- read (filename)
-
return the contents of a file as a string
Parameters:
filename
: The file path
Returns:
-
file contents
- write (filename, str)
-
write a string to a file
Parameters:
filename
: The file pathstr
: The string
- copy (src, dest, flag)
-
copy a file
Parameters:
src
: source filedest
: destination fileflag
: true if you want to force the copy (default)
Returns:
-
true if operation succeeded
- move (src, dest)
-
move a file
Parameters:
src
: source filedest
: destination file
Returns:
-
true if operation succeeded, else false and the reason for the error.
- access_time (path)
-
Return the time of last access as the number of seconds since the epoch
Parameters:
path
: A file path
- creation_time (path)
-
Return when the file was created
Parameters:
path
: A file path
- modified_time (path)
-
Return the time of last modification
Parameters:
path
: A file path
- delete (path)
-
Delete a file
Parameters:
path
: A file path


Abstract
Poetry has been around for thousands of years, yet it always lived in a fluid state of development. Given the current technological development applied to literature studies, the classification of emotional states from poetry has not been receiving enough attention in the NLP world given its flexible connection to traditional grammatical structure. This paper discusses Reading Between the Lines, a sentiment visualization project specifically designed for poetry. The project intends provide assistance to build alternative view for readers when interpret the expression of emotions in poetic works.
Project by Charles N.H. Wu


$$ \nabla \times \mathbf{B} = \mu_0 \mathbf{J}$$ Consider a section of a plane that contains a uniform magnetic field. The introduction of a current $\mathbf{J}$ that passes through every point in this section of the plane changes the field around it such that the magnitude of the magnetic field only changes if you move in a direction that is perpendicular to the field. This is the definition of curl. The introduction of the current density has induced a curl in the magnetic field. Consider a plane in which there is some magnetic field. Taking an infinitesimal point in the plane, we see that the introduction of a current into this infinitesimal point in the plane cause the local magnetic field's magnitude to vary in a direction that is perpendicular to the direction of the magnetic field. This is the definition of curl.


Marvel Sends NYC Council Member Ben Kallos Cease & Desist Letter
by L.D. NolanNew York City Council Member Ben Kallos received a cease and desist letter from Marvel over his use of the company's characters in campaign materials.
As part of his campaign for Manhattan Borough President, Council Member Kallos' team sent out a "Superhero Alert" asking for donations on Friday. The email featured a picture of Kallos dressed as Captain America and used the phrase "he can do this all day" as the subject line, a reference to Steve Rogers' iconic statement. The message makes several more references to Marvel throughout.
Later that same day, Kallos posted a letter from Marvel's Deputy Chief Counsel Eli Bard to his personal Twitter. "Got this charming letter from [Marvel]," Kallos wrote, "and got a kick out of it, thought you might too!"
"I write to request that your campaign refrain from using Marvel's characters in its advertisements for your quest for the Borough Presidency or otherwise," Bard's letter to Kallos reads. "While Marvel appreciates your obvious affection for our properties and welcome your support as a fan, we ask that our characters not be used for political purposes or to support political campaigns."
Taking office in 2014, Kallos is a Reform Democrat currently representing New York's 5th District, which includes Manhattan's Upper East Side, Midtown East, Roosevelt Island and East Harlem. Kallos has been outspoken about his love of geek and nerd culture over the years, having hosted screenings for Avengers: Endgame and attended Anime NYC.
(via Graphic Policy)
https://schema.orgBreadcrumbListListItem1Homehttps://www.cbr.com/ListItem2Comicshttps://www.cbr.com/category/comics/ListItem3Comic Newshttps://www.cbr.com/category/comics/news/ListItem4Marvel Sends NYC Council Member Ben Kallos Cease & Desist Letterhttps://www.cbr.com/marvel-ben-kallos-cease-desist-letter/


intro
So I needed to learn golang.. I tought I’ll share my experiences.
Of course I made some assosations in my mind with C/C++/python. I know golang tutorials let you know that you should not make such assumptions.. but I could not help my self but to make them anyway.
So here is what I learned this far :
standalone binary/executable
The thing why I really like golang (so far) is that it makes standalone executable.
Of course this means that everything is staticly linked to the executable/binary and the size grows compared e.g C.. but compared to benefit of having executable standalone, I could not care less.
No different path settings/exports/registry entries, install programs etc.. just run or compile+run the binary ;)
have you ever seen python or ruby script to fail due imported library incombability ;)
And so far what I have tried, the same code compiles to windows and runs the same way.. standalone. (You can even copile it at linux for windows).
first look
e.g edited https://tour.golang.org/basics/4
package main
import "fmt"
func add(x int, y int) int {
return x + y
}
func main() {
a := "hello"
b := 123456
fmt.Println(add(42, 13))
}
nothing too complicated.. they(=golang developers) just switched variable first and type after that.
variable type fixed to the type of initialized… fine. Return value is at the end of function defination.. makes sence.
You need brackes if you have more than one return value (btw really nice feature).
I think it is stated somewhere but I missed first that if function name starts with CAPITAL e.f Foo() it is public when in package.
funtions
Basic function is simple as above. But then there is sometimes stuff just after the ‘func’ keyword, tutorials somehow seem to skip this .. I leared this by googling the very similar question.
But then function can be also ‘class/struct’ function.
That is the stuff in brackets after ‘func’ is like automaticly made class/struct instance.. and used like this-pointer in C++.
package main
import "fmt"
type zoo struct {
i string
}
func (y zoo) Foo(x int) {
fmt.Printf("something %d %s\n", x, y.i)
}
func main() {
y := zoo{}
y.i = "hello"
y.Foo(5)
}
output of this is : something 5 hello
go routines
I think them as threads, fork etc.
Here main() waits for childs to exit and first foo() finnishes last.
package main
import "fmt"
import "time"
func foo(id int) {
sleepTime := 100*time.Millisecond
sleepTime = sleepTime * time.Duration(id)
fmt.Printf("%d: hello from go func, sleep %d\n", id, sleepTime)
time.Sleep(sleepTime)
fmt.Printf("%d: exit go func\n",id)
}
func main() {
threadId := 3
fmt.Printf("hello from main\n")
go foo(threadId)
threadId = 1
go foo(threadId)
time.Sleep(500*time.Millisecond)
}
For some really good reason there ++really is no++ official api/function to get the go routine id (thread id). So I just use some id for now. I did try to use uuid but those make log line too long.
Perhaps in future I’ll use the ‘context’ stuff they included quite resently. I also heard that golang has inbuilt thread/go routine/function engine.. so you should be able to run more than real threads.. never needed that much yet.
struct
struct is like class in C++.
packages
package imports are like the one’s in python, and acts like class in C++. Each package file can even have init() function.. like class constructor in C++.
As I wrote earlier funtion names with starting capitals are public with small letter private to the file (or in C++ to the class).
This does not only apply to the functions but also to the e.g constans, structs etc.
Again nothing really compilated.
in file src/my_utils.go
import "fmt"
func Foo(x int) {
fmt.Printf("foo %d", x)
}
so in my_prog.go I can call it.
package main
import my_utils
func main() {
Foo(5)
}
imported packages
Public funtions you can overwrite, like virtual function in C++. Now the real mess starts when you include/import some package that uses private structs and/or constants.
in file my_utils.go, I added private my_server
package my_utils
import "fmt"
type my_server struct {
bar string
}
func Foo(x int, y my_server) {
fmt.Printf("foo %d, %s\n", x, y)
}
At main I try to use it.
package main
import "my_utils"
func main() {
var y my_utils.my_server
y.bar = "not bar"
my_utils.Foo(5, y)
}
Because my_server is private I can not use public funtion Foo(). I can not even access/set the bar variable if I change the my_server to public My_server !! Same apply if the private is the this-pointer instance I mentioned at function paragraph.
In C++ you could inherit the whole class (my_utils), and then overwrite the Foo().
As far I know ,you can not do this in golang with out tricks ;(
some whining about this issue
“They are privat for a reason”.. bollocks, my personal quess is that I would do it.. because as said in C++ you can just inherit and do what ever you want with members.
Yeah, I know this is what the golang interface stuff is for but you see this all the time.. and end up ripping others code.
A lot of code/project what I have seen are not writen to be extended or used anywhere else than specific case, even the projects intention was to create interface !
In general I have started to be little sceptical of projects started 2/3 years ago.. A lot of them seem to be playing with golang and just dumped to github. I hope standard library has sceptical members what to put there or were are in the mess as some many other languages.
So I learned my lesson, I have to think what members really need be private or use interface in an github project. If I think it is any use to anybody other than just cut and paste code.
The end so far.
Comments
Want to leave a comment? Visit this post's issue page on GitHub (you'll need a GitHub account).


Syntax file to benchmark Select a syntax file to be benchmarked.
Alternate syntax file for comparison Optionally select another syntax file to be run in alternation with the first one. This is useful when you have two version of syntax and want to compare their resource use.
Processes to Measure Check boxes for the Statistics processes to be measured. These can be the Statistics frontend, the backend, and the Python and R programmability processes.
• The names of the processes vary some among Statistics versions. If you cannot specify a process you want to monitor, paste the syntax and edit the name.
Start the R process The R process must be started before running the benchmark command if it is to be measured. Check this box if that process has not been started, and you want the dialog box to do this.
• If the R Essentials are not installed, do not check this box.
Output File to Create Specify a file name to receive the recorded statistics. The file will be in csv format and can be read using File>Read Text Data. It will contain variable names on the first line. The variables include the process name, the cmdset, and the repetition number and the statistics values at the start and stop of each syntax file run. There is one record for each process.
Number of repetitions Specify the number of times that the syntax files should be run.
Choose the particular statistics to be measured each time a syntax file is run.
All statistics Check this box to generate all available statistics.
• The other checkboxes are ignored if this box is checked.
• Checking this box generates some statistics not listed elsewhere in this dialog.
Time The total time for a job is the sum of the User and Kernel time. The process creation time is often not meaningful.
I/O In addition to the number of reads and writes, by using syntax the bytes counts are also available.
Memory The working set size tells you the number of pages in the process' memory. The page fault statistics tell you how many times the system had to retrieve code and other resources from disk because it was not in memory when needed.
This dialog generates syntax for the STATS BENCHMRK extension command. To display help for this command, run the following syntax:
STATS BENCHMRK /HELP.
ęCopyright IBM Corp. 1989, 2012


baseFrequency = 0.01
baseFrequency = 0.02
baseFrequency = 0.03
baseFrequency = 0.04
baseFrequency = 0.05
baseFrequency = 0.06


Torrentz is a free, fast and powerful meta-search engine combining results from dozens of search engines
Indexing 45,839,182 active torrents from 163,051,514 pages on 25 domains
Torrentz | Torrentz Proxy | Torrents Mirror | μTorrent Plugin


Key
vpn_key
Holder
Online software righ-of-use authenticator
Register a new KHID
person
lock
lock
Choose Your Licence Plan
Licence Count:
Estimated Cost:
I read and agree to the
terms of usage
.
APPLY


Lamdin Cement is considering buying a limestone quarry to secure a supply of raw materials into the future. Is this a good idea?
Basic Points
- Yes if likely to yield a positive ROI
- This depends on a number of factors: quarry purchase price, operating costs, lifetime of resources, quality of resources, market price of limestone aggregate materials in future
Advanced Comments
- Approach: The answer to this questions is very situation dependent. Yes if.... No if.... Therefore management needs to conduct a search of quarries which might actually be available for sale. They should capture all the key information about these quarries including type of materials, lifetime available, extraction costs etc
- Research: Conduct research on likely trends in aggregate prices e.g. volume of material available at what price points vs demand. This will affect what management is prepared to pay now for these resources.
- Valuation: Value quarries based on different scenarios in demand and price


--- layout: post title: "No Title" ---
Many bloggers and writers hate Twitter because it’s boring. Just like I hate basketballs because they never go into the hoop.


All addresses below are assumed to be prefixed by https://taxonomy.jgi-psf.org, e.g. /name/homo_sapiens implies a full URL of:
- https://taxonomy.jgi-psf.org/name/homo_sapiens
For a simplified taxonomic tree, add "simple". This will ignore unranked or uncommon levels like tribe and parvorder, and only display the following levels: SUBSPECIES, SPECIES, GENUS, FAMILY, ORDER, CLASS, PHYLUM, KINGDOM, SUPERKINGDOM, DOMAIN For example:
- /simple/id/1234
To print taxonomy from the command line in Linux, use curl:
- curl https://taxonomy.jgi-psf.org/id/9606
Queries longer than around 8kB can be sent via POST: curl https://taxonomy.jgi-psf.org/POST...where the data sent is, for example:
- name/e.coli,h.sapiens,c.lupus


--- layout: post title: 'InfoQ: WebSockets versus REST?' url: http://www.infoq.com/news/2012/02/websockets-rest source: http://www.infoq.com/news/2012/02/websockets-rest domain: www.infoq.com image: http://kinlane-productions.s3.amazonaws.com/ap-evangelist-site/curated/screenshots/9352_api500_com.png ---
For the past few years WebSockets has been gaining in popularity and availability.At the end of last year it moved one step closer to a standard by becoming a W3C Candidate Recommendation.Oracle and others have also recently submitted a request to start a standardisation effort around WebSockets (JSR 356) in the next version of Java Enterprise Edition.All of the major browsers, such as Chrome, Firefox, Safari and IE, support one of the WebSockets revisions and will ultimately adopt whatever the standard eventually becomes.In a relatively short period of time, WebSockets has almost become an integral part of the Web.


Powered by &
Use this panel to provide information related to you project.
Orbit camera with left click and drag
Here you can place any UI elements that allow users to adjust settings that influence the opporation of your project. Dat.GUI is a popular choice for quickly creating GUI elements.
Loading...


I have worked for the last nine years at Aisle Rocket Studios, where each day is a little bit different and brings a unique set of marketing challenges to solve. One week, I’ll write training articles to educate Sears sales associates on the latest Maytag laundry pairs, undertake a re-branding initiative for a group of Catholic schools, train junior copywriters on SEO best practices, and brainstorm theme names for a joint event between Lowes and Whirlpool. And the following week? I’ll write product descriptions for Kimberly-Clark with HTML code, B2C emails for Kmart, and build a site map for an e-commerce website. With nine years of ad agency experience, I intuitively know what to do when a new creative brief lands in my inbox.


Playdar.js is a JavaScript client library for interacting with the Playdar HTTP API.
Download latest: playdar.js
Source code and full documentation (GitHub)
| BSD licensed
| Issue tracker
Here’s how you can use it to query Playdar for a specific track.
Don’t have Playdar installed? Download a build for Mac or Windows, or compile the latest source then come back here or check the websites below for a demo.
Fill in the form values and press return or click the “go” button for a live demo. The number of results will appear below:
In Progress No Results Partial Matches Perfect Match


Welcome To DuxPanel!
A set of draggable React panels and dialogs
DuxPanel is set of responsive, mobile-ready React components that implement draggable and fixed-position
panels and dialogs. The panels and dialogs can be modal and respond to key presses like Escape and Enter.
Why Another Panel Framework?
DuxPanel offers the following notable features.
- Panels and dialogs are draggable or fixed-position
- Responsive and mobile-ready
- Modal or non-modal
- Stackable
- Responds to Escape and Enter
- Convenience dialogs such as Ok/Cancel, Yes/No, and progress.
- All panels and dialogs can be styled with CSS
GitHub Repository
This project's GitHub can found at
https://github.com/kenschenke/duxpanel.


Get Humidity Conditions From Anywhere!
Enter a location:
Get Current Humidity!
Get Temperature Conditions From Anywhere!


{% extends "siem/base.html" %} {% block sub-title %}Daemon Documentation | {% endblock %} {% block content-main %}
Parser and sentry daemons can be started, restarted, and stopped with scripts/logesp, which includes options for setting the LogESP base directory and virtual environment base directory.
Usage: logesp [-hv] {start|stop|restart|status|clean} [-lps] [-b LOGESPBASE] [-e ENVBASE] Optional arguments: -h Print this help message -v Print the version number -l Clean old events using local EOL date -p Run parser only (no sentry) -s Run sentry only (no parser) -b LOGESPBASE Set the LogESP base directory -e ENVBASE Set a virtual environment
Daemons can be started manually, or by /etc/rc.local. Parser configuration is located in config/parser.conf inside the repository. Cleaning can be done manually, or by cron.
{% endblock %}


Why should you rename your files for plex?
Although PLEX's media scanners are pretty robust, sometimes they cannot find your files if they do not follow a certain naming convention. PLEX specifies
how to name your files in order to make it simple for the media scanner to find.
PLEX File Renamer simplifies this task by automating the process of renaming all the files in a folder to the PLEX naming conventions
- Auto detect series name and season when folder is selected
- Rename all files in selected folder to the plex standard
- Rename entire series including season folders to the plex standard
So What Does the Program Do?
Turns this...
To THIS
Improve Your Media Experience
Follow the blog for info on development and upcoming features!


Enable no delay provision strategy.
Disabled by default.
Enabling of this setting will disable default Jenkins behavior for particular cloud and ask this cloud to provision new agents almost as soon as new jobs appear in queue.
When this option is disable (by default). Each time when Jenkins doesn't have enough agent to execute all jobs in a queue. Jenkins starts provision of new agents. Default strategy is trying to keep amount of agents as small as possible. It waits a little bit until queue will not reach some limit or jobs in a queue will not reach some age. As result before scheduled job will be executed you can see some delay.
Note Enabling of this setting could increase chance of over provision, because of that
make sure that your Max Idle Minutes Before Scaledown
has expected value so
free capacity could be scale in. While Linux capacity billing per minute, Windows capacity
billing per hour, so be careful with this option.


Before Change
float(pixel_count))
percent_saturation_name = "%s_%s_%s"%(IMAGE_QUALITY, PERCENT_SATURATION,
image_name)
percent_maximal_name = "%s_%s_%s"%(IMAGE_QUALITY, PERCENT_MAXIMAL,
image_name)
workspace.add_measurement(cpmeas.IMAGE, percent_saturation_name,
percent_saturation)
workspace.add_measurement(cpmeas.IMAGE, percent_maximal_name,
percent_maximal)
return [["%s saturation"%image_name,"%.1f %%"%percent_saturation],
["%s maximal"%image_name, "%.1f %%"%percent_maximal]]
def calculate_threshold(self, image_group, workspace):
After Change
float(pixel_count))
percent_minimal = (100.0 * float(number_pixels_minimal) /
float(pixel_count))
percent_maximal_name = "%s_%s_%s"%(IMAGE_QUALITY, PERCENT_MAXIMAL,
image_name)
percent_minimal_name = "%s_%s_%s"%(IMAGE_QUALITY, PERCENT_MINIMAL,
image_name)
workspace.add_measurement(cpmeas.IMAGE, percent_maximal_name,
percent_maximal)
workspace.add_measurement(cpmeas.IMAGE, percent_minimal_name,
percent_minimal)
return [["%s maximal"%image_name,"%.1f %%"%percent_maximal],
["%s minimal"%image_name, "%.1f %%"%percent_minimal]]


SheetJS CFB Preview Live Demo Source Code Repo Issues? Something look weird? Click here and report an issueDrop an XLS file here to see the CFB structure.Advanced Demo Options: Use readAsBinaryString: (when available) Export Current File - Export data as CFB - Export data as ZIP


Referencing call, apply or bind in Angular expressions is disallowed! Expression: {0}
Occurs when an expression attempts to invoke Function's 'call', 'apply' or 'bind'.
Angular bans the invocation of 'call', 'apply' and 'bind' from within expressions since access is a known way to modify the behaviour of existing functions.
To resolve this error, avoid using these methods in expressions.
Example expression that would result in this error:
<div>{{user.sendInfo.call({}, true)}}</div>


1. Find 10 words from your own writing that you’ve spelt incorrectly.
2. Search the internet one picture that reminds you of each word.
3.  Each week, print out a copy of your spelling words page and write the words next to each image.
1. Take some 'selfies' with a camera, smart phone or iPad.
2. Choose your favourite selfie and print it out on an A4 piece of paper.
3. Decide materials you want to use to make your self-portrait.
4. Collect all the materials you need an create your self portrait.
1. Find 10 words from your own writing that you’ve spelt incorrectly.
2. Search the internet one picture that reminds you of each word.
3.  Each week, print out a copy of your spelling words page and write the words next to each image.
1. Take some 'selfies' with a camera, smart phone or iPad.
2. Choose your favourite selfie and print it out on an A4 piece of paper.
3. Decide materials you want to use to make your self-portrait.
4. Collect all the materials you need an create your self portrait.
3. Create a document containing the images of the spelling words
2. Choose your favourite selfie and print it out on an A4 piece of paper.
4. Each week, print out a copy of your spelling words page and write the words next to each image.
4. Collect all the materials you need an create your self portrait.


{% extends "base.html" %} {% block content %}
Load files containing model conditions that change during the simulation. These can be environmental conditions, chemical species concentrations, or rates/rate constants for reactions with a MUSICA name
. Evolving conditions take precedence over initial conditions specified here.


None as of yet
Stars: {{review.stars}} {{review.body}} {{review.author}}
Stars: {{reviewCtrl.review.stars}} {{reviewCtrl.review.body}} {{reviewCtrl.review.author}}


{% include 'includes.html' %}
{% include 'top.html' %}
{% if data.session.username > '' %}{{ data.session.username }}{% endif %} are you sure you wish to logout?
Yes, Logout
{#
Sign Out from Google
#}
{% include 'footer.html' %}


Hello, I am Nataliia Bazaka and I really want to be a proffecional creator.
Enjoy travelling and engaging with different cultures. Reading, drawing, photographing, dreaming, doing sport, going out with friends, making plans for future and other things to make life memorable.


-
The Secret Goldman Sachs Tapes
www.bloombergview.com
The public doesn't seem to understand just how dysfunctional our financial regulatory system is, Michael Lewis writes. That may change today with a ...
-
The Internet Braces for the Crazy Shellshock Worm | WIRED
www.wired.com
A nasty bug in many of the world’s Linux and Unix operating systems could allow malicious hackers to create a computer worm that wreaks havoc on ...
-
Apple Still Has Plenty of Your Data for the Feds - The Intercept
firstlook.org
Improved Apple encryption is a welcome step toward thwarting the surveillance state. But it seriously oversold Apple's commitment to privacy.
-
Apple's "warrant canary" disappears, suggesting new Patriot Act demands
gigaom.com
Apple included language in its first Transparency Report to say that it had not been subject to a Section 215 Patriot Act request. That language is ...
-
Shellshock DHCP RCE Proof of Concept -
www.trustedsec.com
DHCP bash shellshock POC: 1) Just about any DHCP string value should work for the exploit. Value 114 is URL, which is a string and should be reliable ...
-
Kevin Mitnick, Once the World's Most Wanted Hacker, Is Now Selling ...
www.wired.com
As a young man, Kevin Mitnick became the world’s most notorious black hat hacker, breaking into the networks of companies like IBM, Nokia, Motorola, ...
-
Who profits from our new war? Inside NSA and private contractors’ secret ...
www.salon.com
A massive war operation is being waged to track and kill ISIS -- and it's a lot more than cruise missiles
-
Another Patent Troll Slain.  I say “ex-troll” because its patent, US Pat. No. 6,326,978, has been declared unpatentable by the ...
-
New Video Exposes Canadian Spy Agency's Unchecked Surveillance Program
www.eff.org
The Canadian government's surveillance of innocent Canadians is secretive, expensive, and out-of-control—that’s the message of a new video launched ...
-
StopMotionsolo On the front lines
www.ustream.tv
Stay informed. Get involved. Be active. Follow me on twitter @stopmotionsolo on twitter Support my work with as little as $2 donation on PAYPAL Check ...
-
Let’s Stand Together to Promote Open Access Worldwide.
act.eff.org
Diego Gomez, a Colombian graduate student, currently faces up to eight years in prison for doing something thousands of researchers do every day: ...
-
Ello | waxpancake
ello.co
Ello is a beautiful, simple, and ad-free social network. The Ello interface supports posting and private messaging. Ello allows users to share ...
-
Australian Government Scrambles to Authorize Mass Surveillance
www.eff.org
This week, Australian Prime Minister Tony Abbott used recent terrorist threats as the backdrop of a dire warning to Australians that “for some time ...
-
BitPay And PayPal, An Unbeatable Payment Partnership | The BitPay Blog
blog.bitpay.com
Today we are excited to reveal our relationship with PayPal to increase the adoption of bitcoin worldwide. The first project we have completed is an ...
-
Emma Watson HeForShe Speech at the United Nations | UN Women 2014
www.youtube.com
UN Women Global Goodwill Ambassador, Emma Watson, delivers her moving remarks during the HeForShe Special Event at United Nations Headquarters in New ...
-
Help Anontana with Trial Expenses
www.youcaring.com
This is a fundraiser to help Anontana, one of the #Payback6, cover his trial expenses.
-
Obama actually said this stuff and it will make you cringe
cms.fightforthefuture.org
President Obama sure did care a lot about net neutrality ... until he became President! Tell him to keep his word.
-
Before deploying StingRays, police departments must sign nondisclosure ...
www.beaconreader.com
A nondisclosure agreement released by the Tacoma Police Department confirms the FBI’s intimate role in overseeing StingRay trackers nationwide, as ...
-
Loyalty Nearly Killed My Beehive - Issue 16: Nothingness - Nautilus
nautil.us
Some time ago I read a short story by Roald Dahl called “Royal Jelly.” It’s the tale of a father desperately searching for ways…
-
Courage: It’s not just for white men | Jillian C. York
jilliancyork.com
Yesterday, my dear friend Morgan re-posted the following image with this comment : “It appears that courage is a white dude thang….”
-
EFF to Defend Student Bitcoin Developers in Court
www.eff.org
Newark, NJ - Electronic Frontier Foundation (EFF) Staff Attorney Hanni Fakhoury will appear before a New Jersey Superior Court judge on Monday, Sept. ...
-
Opportunity Missed: Why We're Not Thrilled By Restoration of PACER Access ...
www.eff.org
The Administrative Office of the United States Courts (AO) announced on Friday that it would make reams of court records once again accessible ...
-
This is why your Internet is slow. And it’ll get worse. Unless you take 1 ...
www.battleforthenet.com
You’re our only hope.
-
Re: [Trans] Threat model outline, attack model
www.ietf.org
Attachment: signature.asc Description: Message signed with OpenPGP using GPGMail
-
Eric Holder didn't send a single banker to jail for the mortgage crisis. ...
www.theguardian.com
US attorney general’s tenure has proven unhelpful to the five million victims of mortgage abuses in the US, writes David Dayen
-
Insane Traffic Stop Tests 'Show Me Your Papers' Law - The Intercept
firstlook.org
A mother of three with a pending domestic violence visa was detained for five days over a traffic violation. Now she's a legal test case.
-
Women and children bear brunt of domestic violence, Stanford scholar says
news.stanford.edu
Nine times as many people around the world are killed in disputes between individuals, including domestic violence, than are killed in civil wars, ...


ARPES Cryostat Temperature
ULV - Channel A
Top-Braid - Channel A
Off
Low
Medium
High
Set Heater Range
Off
Low
Medium
High
Set Heater Range
Set Temperature (K)
Set Temperature


T1 E-PASS APPLICATION FORM
Co-Passenger Details
Co-Passenger 1
Name
Age
Gender :
Male
Female
Other
Adhar Number
Co-Passenger 2
Name:
Age
Gender :
Male
Female
Other
Adhar Number
Co-Passenger 3
Name:
Age
Gender :
Male
Female
Other
Adhar Number
SUBMIT