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Corporate report
The Ofsted Annual Report sets out the evidence and findings on the quality of schools, early years providers and the further education and skills sector.
PDF , 3.29MB , 156 pages
If you use assistive technology (such as a screen reader) and need a version of this document in a more accessible format, please email<EMAIL_ADDRESS>. Please tell us what format you need. It will help us if you say what assistive technology you use.
PDF , 10.7MB , 156 pages
If you use assistive technology (such as a screen reader) and need a version of this document in a more accessible format, please email<EMAIL_ADDRESS>. Please tell us what format you need. It will help us if you say what assistive technology you use.
PDF , 334KB , 9 pages
If you use assistive technology (such as a screen reader) and need a version of this document in a more accessible format, please email<EMAIL_ADDRESS>. Please tell us what format you need. It will help us if you say what assistive technology you use.
MS Word Document , 72KB
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MS Word Document , 73.5KB
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MS Word Document , 76.1KB
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MS Word Document , 77KB
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MS Word Document , 79.4KB
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MS Word Document , 79.2KB
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MS Word Document , 70.9KB
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MS Word Document , 73.3KB
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Annual Report 2015/16 from Her Majesty’s Chief Inspector Sir Michael Wilshaw. The report covers schools, early years and further education and skills.
This is Sir Michael’s last Annual Report as Her Majesty’s Chief Inspector.
The report is underpinned by the findings of almost 25,000 inspections of schools, colleges and providers of early years and further education and skills. These inspections provide a unique evidence base for the report’s conclusions.


I noted the other day that potsages [sic] would be sparse for a while, but I do not want you lot to think I am staring vacantly out of the window with nothing going on in my noggin. If anything, the Key Cranium—soon to be declared a national monument, or possibly even an international monument—is fizzing and bubbling like unto a potion in a test tube on a bench in a laboratory wherein Dr Fang and his grotesque assistant Mungo do whatever it is they do in old crackly black and white films.
So there is much tippy-tapping taking place at Haemoglobin Towers, but none of it is being posted here, or indeed anywhere. The reason for this is that I have somehow found myself having hit upon a scheme deemed to be “commercially viable”, and I am preparing a book to be brought mewling into the light by a reputable publisher next year. For that reason, too, there will not be a Hooting Yard paperback from Lulu this year, although there will be something for you to get your grubby mitts on in time for Christmas—more news of that soon.


(HTML (HEAD )HEAD (BODY (TABLE "\n (TBODY (TR "\n (TD "\n (OBJECT "\n (PARAM )PARAM "\n (EMBED )EMBED "\n \n (NOEMBED "\n )NOEMBED "\n )OBJECT "\n )TD "\n )TR "\n )TBODY )TABLE )BODY )HTML


{% extends "api/base.html" %} {% block content %}
Welcome to Django 101, a very basic Django website for practice.


Proxy server demo
This is version 3.0
Fire a request:
Server status:
Request parameter:
Server-side request counter:


DBC Week 4 Technical Blog Post
Ruby Enumerable methods
February 28, 2015
In Ruby, an enumerator is a class that allows for both internal and external iteration. They can be created by the following methods:
- Kernel#to_enum
- Kernel#enum_for
- ::new
Enumerables, by itself, contribute a lot to Ruby's ease-of-use and flexibility. They are possible in Ruby due to the notion of "mixins." If you want to write code once and share it between a bunch of unrelated classes, you can put it in modules to be "mixed in" with your classes.
One useful Ruby Enumerable method is the Enumerable#map. Using #map allows you to return a new array with the results of running block once for every element in enum . If no block is given, an enumerator is returned instead.
This is extremely helpful because it allows you to manipulate a group of elements in Ruby in a clearly defined way.


Hello InkLink admin!
Please note creating a new collection will delete the existing one.
To create items, create a zip file of folders formatted thus: itemName*itemUrl
and containing all the images for that item in png form. (please remove the 'http://' from itemUrl)


| < Day Day Up > |
Dedicated to the memory of E.F.CoddThose who are enamored of practice without theory are like a pilot who goes into a ship without rudder or compass and never has any certainty where he is going. Practice should always be based upon a sound knowledge of theory. Leonardo da Vinci (1452 – 1519) The trouble with people is not that they don't know but that they know so much that ain't so. Josh Billings (1818 – 1885) |
| < Day Day Up > |


Now let's look at some applications of CNN. First one is Neural Style Transfer. Generally speaking, it merges a content image and a style image to create a new image. So this generated image will have the same content with the content image but use the style same with the style image.
The key to achieve this goal is to make clear the following two questions:
- How to get the content of an image
- How to get the style of an image
1. Image Content
1.1 How to get the content of an image
So the idea to know the content of an image is that: suppose we have a pre-trained good CNN like VGG-19, then in some deep layer, we are reasonable to believe that the activation of that layer (The output tensor) is enough to grab the most features of an image. (Encoding of this image)
For example if we pass two images of cats through an CNN, even if the initial images look very different, after being passed through many internal layers, their representations will be very close in raw value.
I think which layer to use is a hyperparameter that need to be decided in different cases. Empirically, we will choose a layer in the middle.
1.2 Content Cost
So the activation value's difference of that layer would be the content cost. Mathematically speaking: \[J_{content}(C,G) = \frac{1}{4 \times n_H \times n_W \times n_C}\sum _{ \text{all entries}} (a^{(C)} - a^{(G)})^2 \]
Here, \(C\) represents the content image and \(G\) represents the image we are generating (We will randomly initialize it first) \(n_H, n_W\) and \(n_C\) are the height, width and number of channels of the hidden layer you have chosen, and appear in a normalization term in the cost. For clarity, note that \(a^{(C)}\) and \(a^{(G)}\) are the volumes corresponding to a hidden layer's activations.
2. Image Style
2.1 How to get the style of an image
The style of an image is a little bit tricky to understand than image content, first let's have a high level definition of the image style:
the style of an image means some kind of features will always appear together. And if we think that the kernels work as feature extractors, then the activation of each channel is just the result of that high level feature! So to get the style of it, we can simply calculate the correlations for the activations in each channel. We use 'Gram Matrix' to quantify that correlation:
The value \(G_{ij}\) measures how similar the activations of filter \(i\) are to the activations of filter \(j\).
2.2 Style Cost
So the style difference between two images will be the difference between two style matrix:
\[J_{style}^{[l]}(S,G) = \frac{1}{4 \times {n_C}^2 \times (n_H \times n_W)^2} \sum _{i=1}^{n_C}\sum_{j=1}^{n_C}(G^{(S)}_{ij} - G^{(G)}_{ij})^2\]
where \(G^{(S)}\) and \(G^{(G)}\) are respectively the Gram matrices of the "style" image and the "generated" image
3. Summary
So to make a summary about how to create a neural style transferred images, here is the steps:
- Initialize the generated image
- Find a pre-trained CNN
- Feed the content image to one layer of this CNN and get the activation value
- Feed the Style image to one layer of this CNN and get the style matrix value
- Updating generated image to minimize the linear combination cost of Content cost and Style cost
Let's look at some results of my trained model:
Reference:


The aim of this project and its authors is to bring to OpenShift platform a bunch of templates for deploying in the more easier way existing applications.
Just because many software vendor already provide a containerized version of their product, all the templates you'll find in the page would try to use any exisisting container and may give you all the necessary tips for configuring your OpenShift for better running the chosen containerized application.
Every project/template has its own git repository on GitHub with associated a github page and a custom subdomain in inmyopenshift.cloud.
Have you found a bug? Want to submit a new project/template? Make a pull request!


|
Simple Graphics Library
0.9.5
SGL API
|
#include <sgl.h>
Public Member Functions | |
| GraphicalObject (double left, double bottom, double width, double height) | |
| GraphicalObject (const GraphicalObject &other) | |
| GraphicalObject & | operator= (const GraphicalObject &other) |
| virtual | ~GraphicalObject () |
| virtual double | get_left () const |
| virtual double | get_bottom () const |
| virtual double | get_width () const |
| virtual double | get_height () const |
| virtual void | set (double x, double y, double width, double height) |
| virtual void | paint () const =0 |
| virtual void | move_to (double left, double bottom) |
| virtual void | mouse_pressed (double x, double y, MouseButton button) |
| virtual void | mouse_released (double x, double y, MouseButton button) |
| virtual void | mouse_moved (double x, double y) |
| virtual void | mouse_dragged (double x, double y) |
| virtual void | key_pressed (int k, double x, double y) |
| virtual bool | hit (double x, double y) |
| virtual Window * | set_window (ObjectWindow *win) |
| virtual Window * | get_window () const |
| virtual void | set_mouse_over (bool flag) |
| virtual CursorShape | set_cursor (CursorShape cursor) |
| virtual CursorShape | get_cursor () |
Public Attributes | |
| const unsigned | id |
Protected Attributes | |
| ObjectWindow * | window |
| double | x_hit_offset |
| double | y_hit_offset |
| double | left |
| double | bottom |
| double | width |
| double | height |
| CursorShape | cursor |
| bool | mouse_over |
Represents a persistent graphical object used within a window. A graphical object is owned by a particular window.
| sgl::GraphicalObject::GraphicalObject | ( | double | left, |
| double | bottom, | ||
| double | width, | ||
| double | height | ||
| ) |
Constructor specifies the bounding box extent.
| left | the x coordinate in viewport coordinates of the left-bottom corner of the graphical object's bounding box |
| left | the y coordinate in viewport coordinates of the left-bottom corner of the graphical object's bounding box |
| width | the width in viewport coordinates of the graphical object's bounding box |
| height | the height in viewport coordinates of the graphical object's bounding box |
| sgl::GraphicalObject::GraphicalObject | ( | const GraphicalObject & | other | ) |
Copy construction creates a new graphical object with identical location. The new graphical object has the same containing window but has a unique id. The pre-existing graphical object is not affected by the copy.
| other | the graphical object from which this new graphical object is being created. |
|
virtual |
Destroys a graphical object.
|
virtual |
Returns the y value of the left-bottom corner of the graphical object's bounding box. The value is given in the viewport coordinate system.
|
virtual |
Returns the cursor shape associated with this graphical object.
|
virtual |
Returns the height in viewport coordinates of the graphical object's bounding box.
|
virtual |
Returns the x value of the left-bottom corner of the graphical object's bounding box. The value is given in the viewport coordinate system.
|
virtual |
Returns the width in viewport coordinates of the graphical object's bounding box.
|
virtual |
Get the containing window of this graphical object.
|
virtual |
Returns true if the coordinate provided is within the graphical object's bounding box; otherwise, it returns false.
| x | the x coordinate in viewport coordinates of the location to check |
| y | the y coordinate in viewport coordinates of the location to check |
|
virtual |
Called by the containing window when the user types a key when the window has keyboard focus and the mouse pointer is over the graphical object. The key pressed and the location of the mouse pointer in viewport coordinates is reported.
| k | the key typed by the user |
| x | the x coordinate in viewport coordinates of the location of the mouse pointer within the window |
| y | the y coordinate in viewport coordinates of the location of the mouse pointer within the window |
|
virtual |
Called by the containing window's mouse_dragged method when the user drags the mouse By default it relocates the (left,bottom) location of the graphical object's bounding box relative to a mouse drag event. The move is relative to the location of the last mouse event on the object. This allows the user to drag the graphical object without it "jumping" slightly at first movement. The graphical object's width and height are unaffected.
| x | the x coordinate in viewport coordinates of the mouse pointer location during the current mouse event. |
| y | the y coordinate in viewport coordinates of the mouse pointer location during the current mouse event. |
Called by the containing window's mouse_dragged method when the user drags the mouse when the mouse pointer is over the graphical object.
| x | the x coordinate in viewport coordinates of the mouse pointer location during the current mouse event. |
| y | the y coordinate in viewport coordinates of the mouse pointer location during the current mouse event. |
Reimplemented in sgl::TimeDisplay, sgl::Multidigit, sgl::DoubleDigit, and sgl::DisplayDigit.
|
virtual |
Called by the containing window's mouse_moved method when the user moves the mouse when the mouse pointer is over the graphical object.
| x | the x coordinate in viewport coordinates of the mouse pointer location during the current mouse event. |
| y | the y coordinate in viewport coordinates of the mouse pointer location during the current mouse event. |
|
virtual |
Called by the containing window's mouse_pressed method when the user depresses any mouse button when the mouse pointer is over the graphical object.
| x | the x coordinate in viewport coordinates of the mouse pointer location during the current mouse event. |
| y | the y coordinate in viewport coordinates of the mouse pointer location during the current mouse event. |
| button | the button that was depressed, left (LEFT_BUTTON) or right (RIGHT_BUTTON) during the current mouse event. |
|
virtual |
Called by the containing window's mouse_released method when the user releases any mouse button when the mouse pointer is over the graphical object.
| x | the x coordinate in viewport coordinates of the mouse pointer location during the current mouse event. |
| y | the y coordinate in viewport coordinates of the mouse pointer location during the current mouse event. |
| button | the button that was depressed, left (LEFT_BUTTON) or right (RIGHT_BUTTON) during the current mouse event. |
|
virtual |
Relocates the left-bottom corner of the graphical object's bounding box to the specified location. The graphical object's width and height are unaffected.
| left | the x coordinate in viewport coordinates of the left-bottom corner of the graphical object's bounding box |
| bottom | the y coordinate in viewport coordinates of the left-bottom corner of the graphical object's bounding box |
Reimplemented in sgl::TimeDisplay, sgl::Multidigit, and sgl::CompositeObject.
| GraphicalObject & sgl::GraphicalObject::operator= | ( | const GraphicalObject & | other | ) |
Assignment copies the location, size, and window container from another graphical object. The id of the window being assigned is not affected. The source graphical object is not affected by the copy.
| other | the source graphical object from which this graphical object is being assigned. |
|
pure virtual |
The paint method is called by the containing window's paint method when it renders this graphical object. This method is abstract, so concrete derived classes must provide a concrete imppementation.
Implemented in sgl::TimeDisplay, sgl::Multidigit, sgl::DoubleDigit, sgl::DisplayDigit, sgl::BitmapObject, and sgl::CompositeObject.
|
virtual |
Sets the location and size of the graphical object. Values given are in the containing viewport's coordinates. the x coordinate of the left-bottom corner of the graphical object's bounding rectangle. the y coordinate of the left-bottom corner of the graphical object's bounding rectangle. the graphical object's width in viewport coordinates. the graphical object's height in viewport coordinates.
|
virtual |
Sets the graphical object's cursor shape.
| cursor | the object's cursor shape |
|
virtual |
Activates or deactivates the graphical object
| flag | if true, activates the object; otherwise, deactivates the object |
|
virtual |
Set the containing window.
| win | a pointer to the window to make the containing window for this graphical object. |
|
protected |
y coordinate of the left-bottom corner of the graphical object's bounding box
|
protected |
Shape that the cursor should assume when the mouse hovers over this graphical object.
|
protected |
Height of the graphical object's bounding box in the viewport coordinate system
| const unsigned sgl::GraphicalObject::id |
This graphical object's unique ID
|
protected |
x coordinate of the left-bottom corner of the graphical object's bounding box
|
protected |
Indicates if this object is the one that the mouse is currently hovering over.
|
protected |
Width of the graphical object's bounding box in the viewport coordinate system
|
protected |
The window in which this graphical object is a component
|
protected |
Location of the mouse pointer's x coordinate relative to the graphical object's bounding box
|
protected |
Location of the mouse pointer's y coordinate relative to the graphical object's bounding box


LP tokens locked until 22 January 2025 through a TokenTimelockProxy it means that the creators cannot withdraw LP tokens from the Pancake contract to benefit from the BadiCoin value crash.
Crazy!
22
Shhhhhh!


Install
ElPh Requirements
Installation on local machine
Install ElPh:
pip install elph
Install gaussian:
Gaussian installation will vary group to group.
Installing Catnip
Download and install Docker
docker pull madettmann/catnip
Set environment variables
Add these lines to your configuration file (.bashrc). The following code uses example paths and must be edited according to your system.
export ELPH_CATNIP_CMD='docker run -i --rm -v $(pwd):/projects -u $(id -u):$(id -g) madettmann/catnip'
export ASE_GAUSSIAN_COMMAND='Your Gaussian Command Here < PREFIX.com > PREFIX.log'
Installation on NERSC
There is no need to install the ElPh package and its dependencies. Just these lines to your configuration file (.bashrc) in your NERSC home folder.
module use /global/common/software/m2734/ElPh/modulefiles
module load elph
Usage
Local machine
Add cif file to current working directory
Run javerage
elph --javerage
Compute the phonon modes
Refer to DCS-Flow for more information.
Run sigma
Copy FORCE_SETS, phonopy_params.yaml to your working directory
elph --sigma
Compute mobility
Write input files and define correct parameters for the specific system
elph --write_files
Run mobility
elph --mobility
Visualize sigma contribution per atom/mode
To generate the visualization per atom:
elph --view atoms
To generate the visualization per mode (n highest modes):
elph --view modes 3
NERSC
The step-by-step is basically the same as in a local machine, however add these commands to the following steps
Once all the jobs submited by the Javerage command are done, run
elph --read_javg
After all the jobs submited by the Sigma command are finished, use
elph --read_sigma


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LUCA LUSSO
(from drupal.org documentation)
PHP is a very loosely typed language. It doesn’t have a clear definition of the different types of data it deals with.
Therefore Drupal used to be the same. For example, there was no consistent way of telling if a field value is a string, an integer or a timestamp.
Or even, to tell if something is translatable or accessible (as in permissions).
Even if you as a developer happen to know that the value of a text field happens to be a string, there’s no consistent programmatic way of fetching this information.
This expose us to (at least) two kinds of problems:
$stub_form = drupal_get_form(
$node_type . '_node_form', (object) $stub_node
);
$form_state['triggering_element'] = $stub_form['actions']['submit'];
drupal_form_submit(
$node_type . '_node_form', $form_state, (object)$stub_node
);
if ($errors = form_get_errors()) {
return services_error(
implode(" ", $errors), 406, array('form_errors' => $errors));
}
How the Services module saves a node posted to a REST endpoint.
function email_field_validate($obj_type, $object, $field, $instance, $langcode, $items, &$errors) {
foreach ($items as $delta => $item) {
if ($item['email'] != '' && !valid_email_address(trim($item['email']))) {
$message = t('"%mail" is not a valid email address', array('%mail' => $item['email']));
$errors[$field['field_name']][$langcode][$delta][] = array(
'error' => "email_invalid",
'message' => $message,
);
}
}
}
Email module hook_field_validate.
The Typed Data API was created to provide developers with a consistent way of interacting with data in different ways.
The Typed Data API provides means of fetching more information, or metadata, about the actual data.
(partial) class diagram of Typed Data API.
The Typed Data API mainly provides three different interfaces.
Implementations of this interface are used for data that is composed of named properties with more pieces of data.
Implementations of this interface are used for something that is composed of a sequential list of other things, for instance a list of other complex pieces of data. Lists are ordered and may contain duplicate items.
Implementations of this interface are used for something that represents a single piece of typed data, like a string or integer.
This is the smallest building block in the Typed Data API.
TypedDataInterface are implemented as Drupal 8 plugins (with @DataType annotation).
/**
* @DataType(
* id = "string",
* label = @Translation("String")
* )
*/
class StringData extends PrimitiveBase implements StringInterface {
TypedDataInterface implementations stores the data, the metadata are stored in other classes that implements DataDefinitionInterface.
And we can derive the DataDefinition from the TypedData and vice-versa
TypedDataInterface::getDataDefinition();
DataDefinitionInterface::getDataType();
// Create a new DataDefinition instance
// wrapping the 'string' TypedData.
$definition = DataDefinition::create('string');
// Create a new data based on the previous definition
$data = \Drupal::typedDataManager()
->create($definition, 'my string');
$defintion = ListDataDefinition::create('string');
$list = \Drupal::typedDataManager()
->create($defintion, ['my string1', 'my string2']);
$title = DataDefinition::create('string');
$title_data = \Drupal::typedDataManager()
->create($title, 'Link title');
$url = DataDefinition::create('uri');
$url_data = \Drupal::typedDataManager()
->create($url, 'http://www.drupal.org');
$link = MapDataDefinition::create();
$link_data = \Drupal::typedDataManager()
->create($link);
$link_data->set('title', $title_data);
$link_data->set('url', $url_data);
DataDefinitions can have constraints to limit the data that they accept.
Constraints are Drupal 8 plugins (with @Constraint annotation) and are build on the Symfony Validator component.
$definition = DataDefinition::create('string')
->addConstraint('Length', ['max' => 5]);
$data = \Drupal::typedDataManager()
->create($definition, 'my string');
$definition = DataDefinition::create('string')
->addConstraint('Length', ['max' => 5]);
$data = \Drupal::typedDataManager()
->create($definition, 'my string');
$validations = $data->validate();
$validations is an instance of \Symfony\Component\Validator\ConstraintViolationList
The Drupal 8 entity API is built on the Typed Data API.
An entity is a complex piece of data it is composed of other pieces of data, like fields with a list of items.
Entities are complex.
$entity instanceof ComplexDataInterface;
Properties are not complex, they’re only a list of items.
$entity->get('image') instanceof ListInterface;
Items are complex.
$entity->get('image')
->offsetGet(0) instanceof ComplexDataInterface;
Item values are primitive.
$entity->get('image')
->offsetGet(0)->get('alt') instanceof TypedDataInterface;
Get an array with named keys for all fields and their definitions.
$property_definitions = $entity->getFieldDefinitions();
Get an array with name keys for all properties and their definitions.
$property_definitions = $entity->image
->getFieldDefinition()->getPropertyDefinitions();
Get only definition for the ‘alt’ property.
$string_definition = $entity->image
->getFieldDefinition()->getPropertyDefinition('alt');
Entity API add two plugin instances to TypedData.
entity plugin
/**
* @DataType(
* id = "entity",
* label = @Translation("Entity"),
* description =
@Translation("All kind of entities, e.g. nodes, commentss"),
* deriver =
"\Drupal\Core\Entity\Plugin\DataType\Deriver\EntityDeriver",
* definition_class =
"\Drupal\Core\Entity\TypedData\EntityDataDefinition"
* )
*/
field_item plugin
/**
* @DataType(
* id = "field_item",
* label =
@Translation("Field item"),
* list_class =
"\Drupal\Core\Field\FieldItemList",
* deriver =
"Drupal\Core\Field\Plugin\DataType\Deriver\FieldItemDeriver"
* )
*/
Book you test with a tweet with #tyds hashtag
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Some div2 text
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Some outer text
Count all Paragraphs
Count all Paragraphs in First DIV
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Button 1
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TRAMP, a novel apoptosis-mediating receptor with sequence homology to tumor necrosis factor receptor 1 and Fas (Apo-1/CD95).
Abstract
A novel member of the tumor necrosis factor (TNF) receptor family, designated TRAMP, has been identified. The structural organization of the 393 amino acid long human TRAMP is most homologous to TNF receptor 1. TRAMP is abundantly expressed on thymocytes and lymphocytes. Its extracellular domain is composed of four cysteine-rich domains, and the cytoplasmic region contains a death domain known to signal apoptosis. Overexpression of TRAMP leads to two major responses, NF-kappaB activation and apoptosis. TRAMP -induced cell death is inhibited by an inhibitor of ICE-like proteases, but not by Bcl-2. In addition, TRAMP does not appear to interact with any of the known apoptosis-inducing ligands of the TNF family.


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Organization and Labs*Innovation for Development(http://i4d.mit.edu) *Laboratory of Computational Intelligence @UBC,Vancuover *Materials Engineering Laboratory, VIT University Vellore *Maker/ presenter @makerfest_MJFF_2014 *R&D intern with GLOCAL, medtech team *Jugaadathon~ Proud participant and alumni Canwheel
Created 26 October 2014. |


Every Tuesday and Thursday I go running with UCC's running club. It lasts for an hour of intense and invigorating exercise. During the hour we do a combination of hill runs and laps of UCC's greatest amenities, the running track in the Mardyke Arena. I feel it is very important to get in regular excercise and to push yourself as often as you can.
Every Sunday (weather dependent of course) I go to Sunday's Well Tennis Club to play tennis. It is run by UCC and I find it a great way to meet new people. Tennis has always been a passion of mine and I was happy to find out I was able to pick it up again once I arrived at UCC.
During the summer days I enjoy playing golf with my family. Whether it's pitch & put, the driving range or a simple game of crazy golf, I find it very relaxing and fun while also being able to get out of the house for a couple of hours.


The Rings¶
The rings determine where data should reside in the cluster. There is a separate ring for account databases, container databases, and individual object storage policies but each ring works in the same way. These rings are externally managed, in that the server processes themselves do not modify the rings, they are instead given new rings modified by other tools.
The ring uses a configurable number of bits from a path’s MD5 hash as a partition index that designates a device. The number of bits kept from the hash is known as the partition power, and 2 to the partition power indicates the partition count. Partitioning the full MD5 hash ring allows other parts of the cluster to work in batches of items at once which ends up either more efficient or at least less complex than working with each item separately or the entire cluster all at once.
Another configurable value is the replica count, which indicates how many of the partition->device assignments comprise a single ring. For a given partition number, each replica will be assigned to a different device in the ring.
Devices are added to the ring to describe the capacity available for part-replica assignment. Devices are placed into failure domains consisting of region, zone, and server. Regions can be used to describe geographical systems characterized by lower-bandwidth or higher latency between machines in different regions. Many rings will consist of only a single region. Zones can be used to group devices based on physical locations, power separations, network separations, or any other attribute that would lessen multiple replicas being unavailable at the same time.
Devices are given a weight which describes relative weight of the device in comparison to other devices.
When building a ring all of each part’s replicas will be assigned to devices according to their weight. Additionally, each replica of a part will attempt to be assigned to a device who’s failure domain does not already have a replica for the part. Only a single replica of a part may be assigned to each device - you must have as many devices as replicas.
Ring Builder¶
The rings are built and managed manually by a utility called the ring-builder. The ring-builder assigns partitions to devices and writes an optimized Python structure to a gzipped, serialized file on disk for shipping out to the servers. The server processes just check the modification time of the file occasionally and reload their in-memory copies of the ring structure as needed. Because of how the ring-builder manages changes to the ring, using a slightly older ring usually just means one of the three replicas for a subset of the partitions will be incorrect, which can be easily worked around.
The ring-builder also keeps its own builder file with the ring information and additional data required to build future rings. It is very important to keep multiple backup copies of these builder files. One option is to copy the builder files out to every server while copying the ring files themselves. Another is to upload the builder files into the cluster itself. Complete loss of a builder file will mean creating a new ring from scratch, nearly all partitions will end up assigned to different devices, and therefore nearly all data stored will have to be replicated to new locations. So, recovery from a builder file loss is possible, but data will definitely be unreachable for an extended time.
Ring Data Structure¶
The ring data structure consists of three top level fields: a list of devices in the cluster, a list of lists of device ids indicating partition to device assignments, and an integer indicating the number of bits to shift an MD5 hash to calculate the partition for the hash.
List of Devices¶
The list of devices is known internally to the Ring class as devs. Each item in the list of devices is a dictionary with the following keys:
| id | integer | The index into the list devices. |
| zone | integer | The zone the device resides in. |
| region | integer | The region the zone resides in. |
| weight | float | The relative weight of the device in comparison to other devices. This usually corresponds directly to the amount of disk space the device has compared to other devices. For instance a device with 1 terabyte of space might have a weight of 100.0 and another device with 2 terabytes of space might have a weight of 200.0. This weight can also be used to bring back into balance a device that has ended up with more or less data than desired over time. A good average weight of 100.0 allows flexibility in lowering the weight later if necessary. |
| ip | string | The IP address or hostname of the server containing the device. |
| port | int | The TCP port the listening server process uses that serves requests for the device. |
| device | string | The on disk name of the device on the server. For example: sdb1 |
| meta | string | A general-use field for storing additional information for the device. This information isn’t used directly by the server processes, but can be useful in debugging. For example, the date and time of installation and hardware manufacturer could be stored here. |
Note: The list of devices may contain holes, or indexes set to None, for
devices that have been removed from the cluster. However, device ids are
reused. Device ids are reused to avoid potentially running out of device id
slots when there are available slots (from prior removal of devices). A
consequence of this device id reuse is that the device id (integer value) does
not necessarily correspond with the chronology of when the device was added to
the ring. Also, some devices may be temporarily disabled by setting their
weight to 0.0. To obtain a list of active devices (for uptime polling, for
example) the Python code would look like: devices = list(self._iter_devs())
Partition Assignment List¶
This is a list of array(‘H’) of devices ids. The outermost list contains an array(‘H’) for each replica. Each array(‘H’) has a length equal to the partition count for the ring. Each integer in the array(‘H’) is an index into the above list of devices. The partition list is known internally to the Ring class as _replica2part2dev_id.
So, to create a list of device dictionaries assigned to a partition, the Python
code would look like: devices = [self.devs[part2dev_id[partition]] for
part2dev_id in self._replica2part2dev_id]
array(‘H’) is used for memory conservation as there may be millions of partitions.
Partition Shift Value¶
The partition shift value is known internally to the Ring class as _part_shift.
This value used to shift an MD5 hash to calculate the partition on which the
data for that hash should reside. Only the top four bytes of the hash is used
in this process. For example, to compute the partition for the path
/account/container/object the Python code might look like: partition =
unpack_from('>I', md5('/account/container/object').digest())[0] >>
self._part_shift
For a ring generated with part_power P, the partition shift value is 32 - P.
Fractional Replicas¶
A ring is not restricted to having an integer number of replicas. In order to support the gradual changing of replica counts, the ring is able to have a real number of replicas.
When the number of replicas is not an integer, then the last element of _replica2part2dev_id will have a length that is less than the partition count for the ring. This means that some partitions will have more replicas than others. For example, if a ring has 3.25 replicas, then 25% of its partitions will have four replicas, while the remaining 75% will have just three.
Dispersion¶
With each rebalance, the ring builder calculates a dispersion metric. This is the percentage of partitions in the ring that have too many replicas within a particular failure domain.
For example, if you have three servers in a cluster but two replicas for a partition get placed onto the same server, that partition will count towards the dispersion metric.
A lower dispersion value is better, and the value can be used to find the proper value for “overload”.
Overload¶
The ring builder tries to keep replicas as far apart as possible while still respecting device weights. When it can’t do both, the overload factor determines what happens. Each device will take some extra fraction of its desired partitions to allow for replica dispersion; once that extra fraction is exhausted, replicas will be placed closer together than optimal.
Essentially, the overload factor lets the operator trade off replica dispersion (durability) against data dispersion (uniform disk usage).
The default overload factor is 0, so device weights will be strictly followed.
With an overload factor of 0.1, each device will accept 10% more partitions than it otherwise would, but only if needed to maintain partition dispersion.
Example: Consider a 3-node cluster of machines with equal-size disks; let node A have 12 disks, node B have 12 disks, and node C have only 11 disks. Let the ring have an overload factor of 0.1 (10%).
Without the overload, some partitions would end up with replicas only on nodes A and B. However, with the overload, every device is willing to accept up to 10% more partitions for the sake of dispersion. The missing disk in C means there is one disk’s worth of partitions that would like to spread across the remaining 11 disks, which gives each disk in C an extra 9.09% load. Since this is less than the 10% overload, there is one replica of each partition on each node.
However, this does mean that the disks in node C will have more data on them than the disks in nodes A and B. If 80% full is the warning threshold for the cluster, node C’s disks will reach 80% full while A and B’s disks are only 72.7% full.
Partition & Replica Terminology¶
All descriptions of consistent hashing describe the process of breaking the keyspace up into multiple ranges (vnodes, buckets, etc.) - many more than the number of “nodes” to which keys in the keyspace must be assigned. Swift calls these ranges partitions - they are partitions of the total keyspace.
Each partition will have multiple replicas. Every replica of each partition must be assigned to a device in the ring. When a describing a specific replica of a partition (like when it’s assigned a device) it is described as a part-replica in that it is a specific replica of the specific partition. A single device may be assigned different replicas from many parts, but it may not be assigned multiple replicas of a single part.
The total number of partitions in a ring is calculated as 2 **
<part-power>
. The total number of part-replicas in a ring is calculated as
<replica-count> * 2 ** <part-power>
.
When considering a device’s weight it is useful to describe the number of
part-replicas it would like to be assigned. A single device regardless of
weight will never hold more than 2 ** <part-power>
part-replicas because
it can not have more than one replica of any part assigned. The number of
part-replicas a device can take by weights is calculated as it’s
parts_wanted. The true number of part-replicas assigned to a device can be
compared to it’s parts wanted similarly to a calculation of percentage error -
this deviation in the observed result from the idealized target is called a
devices balance.
When considering a device’s failure domain it is useful to describe the
number of part-replicas it would like to be assigned. The number of
part-replicas wanted in a failure domain of a tier is the sum of the
part-replicas wanted in the failure domains of it’s sub-tier. However,
collectively when the total number of part-replicas in a failure domain
exceeds or is equal to 2 ** <part-power>
it is most obvious that it’s no
longer sufficient to consider only the number of total part-replicas, but
rather the fraction of each replica’s partitions. Consider for example a ring
with 3
replicas and 3
servers, while it’s necessary for dispersion
that each server hold only 1/3
of the total part-replicas it is
additionally constrained to require 1.0
replica of each partition. It
would not be sufficient to satisfy dispersion if two devices on one of the
servers each held a replica of a single partition, while another server held
none. By considering a decimal fraction of one replica’s worth of parts in a
failure domain we can derive the total part-replicas wanted in a failure
domain (1.0 * 2 ** <part-power>
). Additionally we infer more about
which part-replicas must go in the failure domain. Consider a ring with
three replicas, and two zones, each with two servers (four servers total).
The three replicas worth of partitions will be assigned into two failure
domains at the zone tier. Each zone must hold more than one replica of some
parts. We represent this improper faction of a replica’s worth of partitions
in decimal form as 1.5
(3.0 / 2
). This tells us not only the number
of total parts (1.5 * 2 ** <part-power>
) but also that each partition
must have at least one replica in this failure domain (in fact 0.5
of
the partitions will have 2
replicas). Within each zone the two servers
will hold 0.75
of a replica’s worth of partitions - this is equal both to
“the fraction of a replica’s worth of partitions assigned to each zone
(1.5
) divided evenly among the number of failure domain’s in it’s sub-tier
(2
servers in each zone, i.e. 1.5 / 2
)” but also “the total number
of replicas (3.0
) divided evenly among the total number of failure domains
in the server tier (2
servers x 2
zones = 4
, i.e. 3.0 / 4
)”.
It is useful to consider that each server in this ring will hold only 0.75
of a replica’s worth of partitions which tells that any server should have at
most one replica of a given part assigned. In the interests of brevity, some
variable names will often refer to the concept representing the fraction of a
replica’s worth of partitions in decimal form as replicanths - this is meant
to invoke connotations similar to ordinal numbers as applied to fractions, but
generalized to a replica instead of four*th* or a fif*th*. The ‘n’ was
probably thrown in because of Blade Runner.
Building the Ring¶
First the ring builder calculates the replicanths wanted at each tier in the ring’s topology based on weight.
Then the ring builder calculates the replicanths wanted at each tier in the ring’s topology based on dispersion.
Then the ring calculates the maximum deviation on a single device between it’s weighted replicanths and wanted replicanths.
Next we interpolate between the two replicanth values (weighted & wanted) at each tier using the specified overload (up to the maximum required overload). It’s a linear interpolation, similar to solving for a point on a line between two points - we calculate the slope across the max required overload and then calculate the intersection of the line with the desired overload. This becomes the target.
From the target we calculate the minimum and maximum number of replicas any part may have in a tier. This becomes the replica_plan.
Finally, we calculate the number of partitions that should ideally be assigned to each device based the replica_plan.
On initial balance, the first time partitions are placed to generate a ring, we must assign each replica of each partition to the device that desires the most partitions excluding any devices that already have their maximum number of replicas of that part assigned to some parent tier of that device’s failure domain.
When building a new ring based on an old ring, the desired number of partitions each device wants is recalculated from the current replica_plan. Next the partitions to be reassigned are gathered up. Any removed devices have all their assigned partitions unassigned and added to the gathered list. Any partition replicas that (due to the addition of new devices) can be spread out for better durability are unassigned and added to the gathered list. Any devices that have more partitions than they now desire have random partitions unassigned from them and added to the gathered list. Lastly, the gathered partitions are then reassigned to devices using a similar method as in the initial assignment described above.
Whenever a partition has a replica reassigned, the time of the reassignment is recorded. This is taken into account when gathering partitions to reassign so that no partition is moved twice in a configurable amount of time. This configurable amount of time is known internally to the RingBuilder class as min_part_hours. This restriction is ignored for replicas of partitions on devices that have been removed, as removing a device only happens on device failure and there’s no choice but to make a reassignment.
The above processes don’t always perfectly rebalance a ring due to the random nature of gathering partitions for reassignment. To help reach a more balanced ring, the rebalance process is repeated a fixed number of times until the replica_plan is fulfilled or unable to be fulfilled (indicating we probably can’t get perfect balance due to too many partitions recently moved).
Ring Builder Analyzer¶
This is a tool for analyzing how well the ring builder performs its job in a particular scenario. It is intended to help developers quantify any improvements or regressions in the ring builder; it is probably not useful to others.
The ring builder analyzer takes a scenario file containing some initial parameters for a ring builder plus a certain number of rounds. In each round, some modifications are made to the builder, e.g. add a device, remove a device, change a device’s weight. Then, the builder is repeatedly rebalanced until it settles down. Data about that round is printed, and the next round begins.
Scenarios are specified in JSON. Example scenario for a gradual device addition:
{
"part_power": 12,
"replicas": 3,
"overload": 0.1,
"random_seed": 203488,
"rounds": [
[
["add", "r1z2-<IP_ADDRESS>:6200/sda", 8000],
["add", "r1z2-<IP_ADDRESS>:6200/sdb", 8000],
["add", "r1z2-<IP_ADDRESS>:6200/sdc", 8000],
["add", "r1z2-<IP_ADDRESS>:6200/sdd", 8000],
["add", "r1z2-<IP_ADDRESS>:6200/sda", 8000],
["add", "r1z2-<IP_ADDRESS>:6200/sdb", 8000],
["add", "r1z2-<IP_ADDRESS>:6200/sdc", 8000],
["add", "r1z2-<IP_ADDRESS>:6200/sdd", 8000],
["add", "r1z2-<IP_ADDRESS>:6200/sda", 8000],
["add", "r1z2-<IP_ADDRESS>:6200/sdb", 8000],
["add", "r1z2-<IP_ADDRESS>:6200/sdc", 8000],
["add", "r1z2-<IP_ADDRESS>:6200/sdd", 8000],
["add", "r1z2-<IP_ADDRESS>:6200/sda", 8000],
["add", "r1z2-<IP_ADDRESS>:6200/sdb", 8000],
["add", "r1z2-<IP_ADDRESS>:6200/sdc", 8000]
], [
["add", "r1z2-<IP_ADDRESS>:6200/sdd", 1000]
], [
["set_weight", 15, 2000]
], [
["remove", 3],
["set_weight", 15, 3000]
], [
["set_weight", 15, 4000]
], [
["set_weight", 15, 5000]
], [
["set_weight", 15, 6000]
], [
["set_weight", 15, 7000]
], [
["set_weight", 15, 8000]
]]
}
History¶
The ring code went through many iterations before arriving at what it is now and while it has largely been stable, the algorithm has seen a few tweaks or perhaps even fundamentally changed as new ideas emerge. This section will try to describe the previous ideas attempted and attempt to explain why they were discarded.
A “live ring” option was considered where each server could maintain its own copy of the ring and the servers would use a gossip protocol to communicate the changes they made. This was discarded as too complex and error prone to code correctly in the project time span available. One bug could easily gossip bad data out to the entire cluster and be difficult to recover from. Having an externally managed ring simplifies the process, allows full validation of data before it’s shipped out to the servers, and guarantees each server is using a ring from the same timeline. It also means that the servers themselves aren’t spending a lot of resources maintaining rings.
A couple of “ring server” options were considered. One was where all ring lookups would be done by calling a service on a separate server or set of servers, but this was discarded due to the latency involved. Another was much like the current process but where servers could submit change requests to the ring server to have a new ring built and shipped back out to the servers. This was discarded due to project time constraints and because ring changes are currently infrequent enough that manual control was sufficient. However, lack of quick automatic ring changes did mean that other parts of the system had to be coded to handle devices being unavailable for a period of hours until someone could manually update the ring.
The current ring process has each replica of a partition independently assigned to a device. A version of the ring that used a third of the memory was tried, where the first replica of a partition was directly assigned and the other two were determined by “walking” the ring until finding additional devices in other zones. This was discarded as control was lost as to how many replicas for a given partition moved at once. Keeping each replica independent allows for moving only one partition replica within a given time window (except due to device failures). Using the additional memory was deemed a good trade-off for moving data around the cluster much less often.
Another ring design was tried where the partition to device assignments weren’t stored in a big list in memory but instead each device was assigned a set of hashes, or anchors. The partition would be determined from the data item’s hash and the nearest device anchors would determine where the replicas should be stored. However, to get reasonable distribution of data each device had to have a lot of anchors and walking through those anchors to find replicas started to add up. In the end, the memory savings wasn’t that great and more processing power was used, so the idea was discarded.
A completely non-partitioned ring was also tried but discarded as the partitioning helps many other parts of the system, especially replication. Replication can be attempted and retried in a partition batch with the other replicas rather than each data item independently attempted and retried. Hashes of directory structures can be calculated and compared with other replicas to reduce directory walking and network traffic.
Partitioning and independently assigning partition replicas also allowed for the best balanced cluster. The best of the other strategies tended to give +-10% variance on device balance with devices of equal weight and +-15% with devices of varying weights. The current strategy allows us to get +-3% and +-8% respectively.
Various hashing algorithms were tried. SHA offers better security, but the ring doesn’t need to be cryptographically secure and SHA is slower. Murmur was much faster, but MD5 was built-in and hash computation is a small percentage of the overall request handling time. In all, once it was decided the servers wouldn’t be maintaining the rings themselves anyway and only doing hash lookups, MD5 was chosen for its general availability, good distribution, and adequate speed.
The placement algorithm has seen a number of behavioral changes for unbalanceable rings. The ring builder wants to keep replicas as far apart as possible while still respecting device weights. In most cases, the ring builder can achieve both, but sometimes they conflict. At first, the behavior was to keep the replicas far apart and ignore device weight, but that made it impossible to gradually go from one region to two, or from two to three. Then it was changed to favor device weight over dispersion, but that wasn’t so good for rings that were close to balanceable, like 3 machines with 60TB, 60TB, and 57TB of disk space; operators were expecting one replica per machine, but didn’t always get it. After that, overload was added to the ring builder so that operators could choose a balance between dispersion and device weights. In time the overload concept was improved and made more accurate.
For more background on consistent hashing rings, please see Building a Consistent Hashing Ring.


TELLab System Administrator's Manual
Table of Contents
TELLab Sysadmin Manual
1 What is TELLab?
1.1 History
2 Sysadmin tasks
2.1 Certificate renewal
2.2 DNS service
2.3 XSEDE hosting
2.4 AWS hosting
3 Installation
4 Cloud platforms
5 Installing software
6 Security
7 Background basics
8 Index and Cross-reference
TLindex
Next:
Introduction
, Up:
(dir)
TELLab Sysadmin Manual
This manual covers both legacy TELLab and TELLab2.
Introduction
: How to use this manual
Sysadmin tasks
: Everything a sysadmin needs to do
Installation
: How to set up a new installation from scratch
Cloud platforms
: Cloud providers used by the TELLab Team
Installing software
: How to install all of the required components
Security
: How to protect your systems from the bad guys
Background basics
: A crash course for newcomers to *NIX
Index and Cross-reference
: Complete index
TLindex
: Complete index


flow state needs an immediate feedback in order to be achieved: literary writing does not have that, but computer writing, with IDEs, linters, etc. does have immediate feedback (with execution speed, so i guess it changes over the years as well) (clemens)
from thought to practice: conceptual art aims at communicating concepts, ideas. experimental art don’t know what they aim at but are motivated by an aesthetic criteria. (richard gabriel, keynote science is not enough) maybe this connects to the tension between having to be understood by humans and understood by computers? [[table_of_contents#understanding code]]
the distance calculation in the interpreting step of programming language compilation to resolve a variable (i.e. scoping) and the fact that one uses shorter variable names based on inner scope, is such example of a connection between literary and architecture
chap 2 of sicp
rousset: forme et signification > L’art réside dans cette solidarité d’un univers mental et d’une construction sensible, d’une vision et d’une forme. Saisir des significations à travers des formes.
metaphors and the main problems of hermeneutics
the metaphorical process as cognition, imagination and feeling
MD system used in the visual search process
ontologies of computer programs
programming paradigms - van roy
linguistics and computational semantics - cantwell-smith
computational artefacts - peter suber
heisenberg - the meaning of beauty in the exact sciences
the programmer’s brain (preview) -> However, your brain does a lot more while you are reading the BASIC program. You are mentally trying to execute the code, to understand what is happening. That process is called tracing—the mental compiling and executing of code


Cosmia
“A monad is a monoid in the category of endofunctors.” Is there something similar for comonad? Hmm, say, comonoid? What does it looks like if there is?
I tried to flip the arrow of monoid, but it looks strange…
And I cannot find any law of it…
maybe … ?
But it’s nearly of no use…
I tried to flip the arrow of monoid, but it looks strange…
class Comonoid a where coidentity :: a -> () comultiple :: a -> (a, a)
And I cannot find any law of it…
maybe … ?
class Comonoid a where v :: a -> () p :: a -> a q :: a -> a forall x. ((p.p) x, (q.p) x , q x) = (p x, (p.q) x, (q.q) x) p x = x q x = x
But it’s nearly of no use…


In this chapter you will learn some techniques that will allow you to increase the security of your applications.
Helmet can help protect your app from some well-known web vulnerabilities by setting HTTP headers appropriately. Generally, Helmet is just a collection of 12 smaller middleware functions that set security-related HTTP headers (read more). Firstly, install the required package:
$ npm i --save helmet
Once the installation is completed, apply it as a global middleware.
import * as helmet from 'helmet';
// somewhere in your initialization file
app.use(helmet());
Cross-origin resource sharing (CORS) is a mechanism that allows resources to be requested from another domain. Under the
hood, Nest makes use of cors package, that provides
a bunch of options that you may customize based on your requirements. In order to enable CORS, you have to call enableCors()
method.
{{ enableCors }}
Also, you can pass a configuration object as a parameter of this function. The available properties are exhaustively described in the official cors repository. A different way is to use a Nest options object:
{{ enableCorsOptions }}
Instead of passing a boolean value, you can use a cors configuration object as well (read more).
Cross-site request forgery (known as CSRF or XSRF) is a type of malicious exploit of a website where unauthorized commands are transmitted from a user that the web application trusts. To mitigate this kind of attacks you can use the csurf package. Firstly, install the required package:
$ npm i --save csurf
Once the installation is completed, apply it as a global middleware.
import * as csurf from 'csurf';
// somewhere in your initialization file
app.use(csurf());
To protect your applications from brute-force attacks, you have to implement some kind of rate-limiting. Luckily, there is a bunch of various middleware available on the NPM already. One of them is express-rate-limit.
$ npm i --save express-rate-limit
Once the installation is completed, apply it as a global middleware.
{{ expressRateLimit }}
Hint
If you work with FastifyAdapter
, consider using fastify-rate-limit instead.


{% load static %}
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I'm Lewis McMahon, a Sheffield based Developer and Climber.
The main languages I work in are PHP, Python and Javascript. For code exmples see Github and NPM
I started using php in 2008 when I built my first website and once someone found out I could do websites I quickly ended up doing freelance work. Over the years I have built many websites and applications including gallery, custom event booking software, a system to automate generate print ready pfd’s for business cards, I advised the development team on a new online lottery site and many others.
My main specialty with php is security and implementing login systems using things like unique user salts, multi factor auth and authentication hashes.
I have been using python since 2013 for web crawling and general data analysis along with general devops scripting.
I mostly write 2.7 but have started to use 3.x in the last few years.
I have been using jquery and javascript since i started doing web design and develpment in 2008 but in recent years i have started to use NodeJS more and more and now maintain several plugins for the NodeBB project.
I have been a user of Amazon Web Services since 2011 initially just using EC2 but I now I have several projects using EC2, SES, S3, ECS, RDS, Route 53, Lambda and CloudWatch.
I have migrated several company's to AWS from traditional hosting, where we used things like custom CloudWatch metrics and S3 to cut their bills in half along with giving them more redundancy, fault tolerance and faster disaster recovery. Several of those migrations also included migration users from SVN to git and implementing a proper deployment pipeline such as AWS CodeDeploy, DeployHQ and Rocketeer.
I have been doing web design since 2008 and still create things for myself but I no longer take on pure design work.
I am an adventure climber for me the experience of climbing a spicy traditional route has so much more value than climbing a hard sport route. I climb mostly in and around the peak district but have my eyes on a few projects in the lakes this year and possibly one in scotland.
I am currently undertaking a Summer Mountain leader course, with a view to taking a Mountaineering Instructor Award course next year. This is mostly to broaden my skillset and give me some more confidence to take people on larger multi-pitch climbs


Design Principles
This isn't a real wiki, just a demonstration of what it would be like to use the parrot stylesheet in the wiki so when we change, for example, the button styling, the change would be shown here automatically.
The advantage is that it eliminates all the intermediate artifacts—wireframes, comps, etc.— so we have less stuff to create and maintain.
Layout & Navigation
Branding & Iconography
Color & Typography
Heading 1
Used for ...
Example
Body
Used for ...
Example
Animation
Controls
Buttons
Basic button
Used for ...
Small button
Used for ...
Dropdowns
Basic dropdown
Used for ...
Account dropdown
Used for ...


| Date | Nominal | Contact | Ref | Job | Type | Debit | Credit |
|---|---|---|---|---|---|---|---|
| {date}08/12/1980{/} | {nominal}Sales:Wholesale:Munster{/} | {contact}Tipperary Toppers{/} | {ref_no}3377046{/} | {job}Great Gifts Joseph Greensmith{/} | {type}invoice{/} | €{debit}1,056.91{/} | €{credit}0.00{/} |
| Closing balance after {count}29{/} records: | €1,056.91 | €0.00 | |||||
| Total for {nominal}Sales:Limerick{/nominal}: | €1,056.91 | €0.00 |


Data Access¶
This tutorial covers the basic EEG methods for data loading. DEEG data structures are based around the numpy array with (p, m, e) structure, where ‘p’ represents the trail number，’m’ represents the channel, and ‘e’ represents the EEG signal. We also provide reader functions for a wide variety of other data formats. DEEG also has APIs to several publicly available datasets, which DEEG can manage for you.
Available data formats
csv, edf, bdf, gdf, vhdr, fif, fif.gz, set, cnt, mff, nxe, hdr, mat, bin, data, sqd, con, ds, txt
Available datasets
Dataset |
format |
link |
|---|---|---|
DEEP |
.dat/.mat |
|
DREAMER |
.mat |
|
SEED |
.mat |
|
NeuroMarketing |
.txt |
https://drive.google.com/file/d/0B2T1rQUvyyWcSGVVaHZBZzRtTms/view |
We’ll start this tutorial by loading the NeuroMarketing dataset, which contains EEG data of 25 subjects when watching 42 photos of different products, along with the photos of 42 products. The deeg.load_NeuroMarketing()
function will automatically load NeuroMarketing dataset and convert the data to our standard (p, m, e) structure.
import deeg
import os
path = os.path.abspath('.') + '/Data-EEG-25-users-Neuromarketing/'
data, labels = deeg.load_NeuroMarketing(path)
print("Data shape: {}".format(data.shape))
Data shape: (1045, 14, 512)
To load DEEP, DREAMER, and SEED datasets, you need to first submit an application for the datasets. Once you get permission , you can download the datasets and load the datasets by deeg.load_DEEP()
, deeg.load_DREAMER()
, deeg.load_SEED()
respectively. These functions are similar as deeg.load_dataset()
, which we show above.
DEEG also supports users to load other data using deeg.load_data()
function. Here is an example of loading a csv data file.
import deeg
import os
path = os.path.abspath('.') + '/data.csv'
data = deeg.load_data(path)


2 Samuel 5:23
And when David inquired of the LORD, he said, Thou shalt not go up; but fetch a compass behind them, and come upon them over against the mulberry trees.


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16 June, 2021
“Double your money in 7 days.”
Investing in the stock market can be quite a roller coaster ride if you start believing in ads like this or those widely-spread misconceptions about the stock market. When it comes to trading, you have to follow a lot of Dos and Don’ts if you want to earn high profits. This blog will talk about a few things that you must do and a few that you must not while investing in the stock market.
The Dos
1. Educate yourself before you start investing. There are a lot of learning resources available on the internet; be it videos or blogs. Make sure you understand the basic concepts before you make your first investment.
2. Start your investment journey as early as possible. This will increase your chances of accumulating greater wealth.
3.  If you invest a lot of money in the beginning without even knowing the technicalities, you might end up losing money. So, start with a small amount and then increase as and when you gain some experience and confidence.
4. Diversify your investments in multiple assets. Invest in stocks, mutual funds, derivatives, fixed deposits, gold, and many more so that if you end up losing money in one place, you will not lose all your money.
5. Consider the trading costs. Apart from the brokerage costs, there are other charges too including exchange charges, demat AMC, and more.
Here are a few more tips to invest in the stock market. Do take a look before you commence your investment journey.
The Don’ts
1. Do not make decisions only based on social media influencers or advice given by friends or family. Do your own research and consult professionals if the need arises.
2. Do not expect high returns in the short-term. Stock market is a game of patience and the one who is calm and composed ends up earning high profits in the long run.
3. Do not borrow money from anyone just because you want to start investing in the stock market. You can start investing with your surplus amount.
4. Do not consider investing as gambling. Stock market investment is not for you to make an addiction. It is for you to have patience, invest for the long-term and build wealth gradually.
5. Do not panic under any circumstances. Stock market is volatile and it keeps fluctuating. However, you must stay calm and make meaningful decisions.
Apart from the above mentioned points, there are a few more mistakes that you must avoid while investing in the stock market. Now that you are aware of some of the most important things to do and things to not do in stock market investment, get ready for your first investment. However, before investing, make sure you choose the right stock broker. Here are some of the few things you must consider before choosing your stock broker. Happy investing!
For any queries, drop us an email at<EMAIL_ADDRESS>or call us on<PHONE_NUMBER>0 / 68. To open an account, please click on the button below.


Last year, 64.5 million passengers traveled through Denver International Airport (DEN). That number is expected to continue growing, and when you account for the airport’s 35k employees, the daily population of the airport is somewhere around 200,000. This translates to big opportunities for terminal concessions.
DEN was recently named Best Airport in the U.S. by the Wall Street Journal, based on passenger ratings for value, convenience, and reliability. There’s an opportunity to build on this customer experience while continuing to grow DEN’s concessions business.
With this in mind, DEN wanted to explore a digital loyalty program that would boost traveler spending at DEN concessionaires. Taking into account existing constraints and business goals, the client requested that:
Densider is a loyalty program designed to incentivize concession spending, reward exploration of the terminals, and capture the fun, wacky spirit of DEN.
Change the airport mindset by incentivizing exploration.
Reward spending at concessions and automatically rack up points when you connect your credit card.
Status tiers invoke DEN's famously fun conspiracies and let travelers earn extra points to elevate their travel experience.
Geolocation-triggered notifications drive adoption and exploration based on seasonal offers.
A colorful, quirky campaign catches travelers' attention and embraces the seasonal rhythms of Colorado's outdoor lifestyle.
Here's how the project evolved ↴
Knowing we only had four days to design a solution, my team adapted the design sprint methodology to tackle this challenge. Because the deliverables included a pitch to the client, we developed the story and pitch deck alongside the concept beginning on day one.
Secondary Research
User Interviews
Paper Prototyping
Figma
Our first task was to understand. We sifted through research provided by the client, conducted competitive research, and drafted two proto-personas:
Next, we interviewed travelers who fit these personas. We asked them questions about their airport habits (“What’s your pre-flight routine at the airport?”) and their values (“What makes a rewards program worth it to you?”). After synthesizing the perspectives gathered in these conversations, along with the rest of our research, we prioritized three key insights:
Travelers hyper-focus on their destination and often fail to notice their environment as they move through the airport.
Travelers see DEN as a gateway to Colorado’s one-of-a-kind outdoor lifestyle and embrace the airport’s so-called conspiracy theories.
Travelers evaluate loyalty programs based on the choice and value afforded by the rewards.
Based on our new understanding of the problem, we formulated a “How Might We” statement and began storyboarding user journeys in order to quickly uncover opportunities and challenges in capturing loyalty.
Sketching and whiteboarding sessions were useful as my team brainstormed how our insights might translate into a rewards structure and accompanying app:
To make sure that the concept matched up with user needs and motivations, we performed some simple hallway tests and 2-minute user interviews using a couple of sketched app screens. We wanted to hear travelers’ impressions about earning points and redeeming them for rewards.
We also checked in with the account manager to make sure we were heading in a direction that was feasible and attractive to the client. We especially wanted to know (a) whether the rewards structure aligned with expectations, and (b) how comfortable DEN was leaning into the wacky side of its identity (think: Lizard People sightings and Illuminati rumors).
Based on feedback from user testing and client conversations, my team continued iterating on the concept and increasing the fidelity.
By eliminating the need to “check-in” and providing automatic point accrual via credit card link instead, one of the biggest barriers to participation can be removed.
The lore around Denver’s airport lends itself toward making DEN feel like a destination in its own right, and the airport was more than happy to lean into that identity. By bringing those conspiracy elements into the loyalty program’s status tiers, we can make loyalists feel like “insiders.”
We also incorporated some of the airports’ tall tales into the activation campaign, which includes floor decals for heavily trafficked areas as well as digital ads near security and escalators.
DEN plans to move ahead with a phased pilot program building on the work my team did during this 4-day sprint.
“I really appreciate the attention to detail and sensitivity to DEN’s constraints that the students showed in their solutions.” —SVP Marketing @ DEN
Beyond rewarding customers for their loyalty, DENSIDER is poised to impact DEN’s concessions business in four key ways:
Studies show that just a 5% increase in retention can lead to a 25–100% increase in profit.
Moving ahead with an app allows DEN to see how travelers move within DEN, identify spending patterns in key customer segments, and gauge lifetime customer value.
Translating steps to points shifts travelers into an exploratory mindset that helps them shed their travel blinders and discover more of DEN’s offerings.
It’s smart business to extend what already works. In DEN’s case, that’s the fun around its so-called conspiracy theories, which have landed DEN in the media, time and again, and its seasonal content strategy for offers and rewards.


| ncvar_put {pbdNCDF4} | R Documentation |
Writes data to an existing netCDF file. The variable to be written to
must already exist on disk (i.e., you must call either
nc_create
or nc_open
before calling this function).
ncvar_put( nc, varid, vals, start=NA, count=NA, verbose=FALSE )
nc |
An object of class |
varid |
What variable to write the data to. Can be a string with the name
of the variable or an object of class |
vals |
The values to be written. |
start |
A vector of indices indicating where to start writing the passed values (starting at 1). The length of this vector must equal the number of dimensions the variable has. Order is X-Y-Z-T (i.e., the time dimension is last). If not specified, writing starts at the beginning of the file (1,1,1,...). |
count |
A vector of integers indicating the count of values to write along each dimension (order is X-Y-Z-T). The length of this vector must equal the number of dimensions the variable has. If not specified and the variable does NOT have an unlimited dimension, the entire variable is written. If the variable has an unlimited dimension, this argument must be specified. As a special case, the value "-1" indicates that all entries along that dimension should be written. |
verbose |
If true, prints information while executing. |
This routine writes data values to a variable in a netCDF file. The file
should have either been created with nc_create
, or
opened with nc_open
called with parameter write=TRUE
.
Note that the data type (i.e., precision) of the values written to the file is determined when the variable is created; in particular, it does not matter what type you pass to this function to be written. In other words, if the variable was created with type 'integer', passing double precision values to this routine will still result in integer values being written to disk.
Values of "NA" are supported; they are converted to the netCDF variable's
missing value attribute before being written. See ncvar_change_missval
for more information.
Data in a netCDF file is conceived as being a multi-dimensional array. The number and length of dimensions is determined when the variable is created. The 'start' and 'count' indices that this routine takes indicate where the writing starts along each dimension, and the count of values along each dimension to write.
David W. Pierce<EMAIL_ADDRESS>http://dwpierce.com/software
ncdim_def
,
nc_create
,
nc_open
,
ncvar_get
.
## Not run: #-------------------------------- # Make a few dimensions we can use #-------------------------------- nx <- 3 ny <- 4 nt <- 5 xvals <- (1:nx)*100. dimX <- ncdim_def( "X", "meters", xvals ) dimY <- ncdim_def( "Y", "meters", (1:ny)*100. ) dimT <- ncdim_def( "Time", "seconds", (1:nt)/100., unlim=TRUE ) #------------------------------------------------------------------- # Make varables of various dimensionality, for illustration purposes #------------------------------------------------------------------- mv <- 1.e30 # missing value to use var1d <- ncvar_def( "var1d", "units", dimX, mv ) var2d <- ncvar_def( "var2d", "units", list(dimX,dimY), mv ) var3d <- ncvar_def( "var3d", "units", list(dimX,dimY,dimT), mv ) #--------------------- # Create the test file #--------------------- nc <- nc_create( "writevals.nc", list(var1d,var2d,var3d) ) #---------------------------- # Write some data to the file #---------------------------- data1d <- runif(nx) ncvar_put( nc, var1d, data1d ) # no start or count: write all values ncvar_put( nc, var1d, 27.5, start=3, count=1 ) # Write a value to the third slot data2d <- runif(nx*ny) ncvar_put( nc, var2d, data2d ) # no start or count: write all values #-------------------------------- # Write a 1-d slice to the 2d var #-------------------------------- ncvar_put( nc, var2d, data1d, start=c(1,2), count=c(nx,1) ) #-------------------------------------------------------------- # Note how "-1" in the count means "the whole dimension length", # which equals nx in this case #-------------------------------------------------------------- ncvar_put( nc, var2d, data1d, start=c(1,3), count=c(-1,1) ) #------------------------------------------------------------------------------- # The 3-d variable has an unlimited dimension. We will loop over the timesteps, # writing one 2-d slice per timestep. #------------------------------------------------------------------------------- for( i in 1:nt) ncvar_put( nc, var3d, data2d, start=c(1,1,i), count=c(-1,-1,1) ) nc_close(nc) #---------------------------------------------------------------------- # Illustrate creating a character type variable #---------------------------------------------------------------------- cnames <- c("red", "orange", "green", "yellow", "puce", "colorwithverylongname" ) nstrings <- length(cnames) #-------------------------------------------------------------- # Make dimensions. Setting "dimnchar" to have a length of 12 # means that the maximum color name # length can be 12. Longer names will be truncated to this. # We don't need dimvars for this example. #-------------------------------------------------------------- dimnchar <- ncdim_def("nchar", "", 1:12, create_dimvar=FALSE ) dimcolorno <- ncdim_def("colorno", "", 1:nstrings, create_dimvar=FALSE ) #------------------------------------------------------------------------ # NOTE in the following call that units is set to the empty string (""), # which suppresses creation of a units attribute, and the missing value # is entirely omitted, which suppresses creation of the missing value att #------------------------------------------------------------------------ varcolors <- ncvar_def("colors", "", list(dimnchar, dimcolorno), prec="char" ) ncid <- nc_create( "colornames.nc", list(varcolors) ) ncvar_put( ncid, "colors", cnames, verbose=TRUE ) nc_close( ncid ) ## End(Not run)


Idea Saver | {{ editModeLabel }} Idea | {{ wizardModeLabel }} Mode
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workbox-cacheable-response. CacheableResponse
Use this plugin to cache responses with certain HTTP status codes or header values.
Defining both status codes and headers will cache requests with a matching status code and a matching header.
Constructor
CacheableResponse
new CacheableResponse(input)
Creates a new Plugin
instance, which stores configuration and logic to determine whether a Response
object is cacheable or not.
If multiple criteria are present (e.g. both statuses
and headers
), then the Response
needs to meet all of the criteria to be cacheable.
Parameter |
|||||||
|---|---|---|---|---|---|---|---|
|
input |
Object Values in
|
Example
new workbox.cacheableResponse.CacheableResponse({
statuses: [0, 200, 404],
headers: {
'Example-Header-1': 'Header-Value-1'
'Example-Header-2': 'Header-Value-2'
}
})
Method
isResponseCacheable
isResponseCacheable(input) returns boolean
Checks a response to see whether it's cacheable or not, based on the configuration of this object.
Parameter |
|||||||
|---|---|---|---|---|---|---|---|
|
input |
Object Values in
|
- Returns
-
boolean
true
if theResponse
is cacheable, based on the configuration of this object, andfalse
otherwise.


|
Standard Reference Data Program |
Data Gateway |
Chemistry WebBook |
Go To: Top, Constants of diatomic molecules, References, Notes / Error Report
Data compilation copyright by the U.S. Secretary of Commerce on behalf of the U.S.A. All rights reserved.
Data compiled as indicated in comments:
LLK - S.G. Lias, R.D. Levin, and S.A. Kafafi
RDSH - H.M. Rosenstock, K. Draxl, B.W. Steiner, and J.T. Herron
View reactions leading to AlCl+ (ion structure unspecified)
| IE (eV) | Method | Reference | Comment |
|---|---|---|---|
| 9.4 | PE | Hildenbrand, 1977 | LLK |
| 9.5 ± 0.3 | EI | Hildenbrand, 1970 | RDSH |
| 9.4 ± 0.4 | EI | Hildenbrand and Theard, 1969 | RDSH |
Go To: Top, Gas phase ion energetics data, References, Notes / Error Report
Data compilation copyright by the U.S. Secretary of Commerce on behalf of the U.S.A. All rights reserved.
Data compiled by: K.P. Huber and G. Herzberg
| State | Te | ωe | ωexe | ωeye | Be | αe | γe | De | βe | re | Trans. | ν00 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Fragments of additional systems in the region 48200 - 54900 cm-1. | ||||||||||||
| Reddy and Rao, 1957 | ||||||||||||
| b (3Σ) | (43591) | (350) 1 | [0.226] 2 | [2.21] | b → a R | 18847.40 HQ | ||||||
| missing citation | ||||||||||||
| R | 18911 (Z) | |||||||||||
| missing citation | ||||||||||||
| R | 19895.00 HQ | |||||||||||
| missing citation | ||||||||||||
| State | Te | ωe | ωexe | ωeye | Be | αe | γe | De | βe | re | Trans. | ν00 |
| A 1Π | 38254.0 | 449.96 HQ | 4.37 3 | -0.216 | 0.259 4 | 0.006 | 2.067 | A ↔ X RV | 38237.7 HQ | |||
| missing citation; Mahanti, 1934; missing citation; Miescher, 1935 | ||||||||||||
| a 3Πr | 24658 | 524.35 HQ | 2.175 | 0.250 5 | 0.002 | 2.10 | a → X V | 24680 (Z) | ||||
| missing citation | ||||||||||||
| 24593.84 | 524.35 HQ | 2.175 | 0.250 5 | 0.002 | 2.10 | a → X V | 24615.31 HQ | |||||
| missing citation | ||||||||||||
| 24528 | 524.35 HQ | 2.175 | 0.250 5 | 0.002 | 2.10 | a → X V | 24541.65 HP | |||||
| missing citation | ||||||||||||
| State | Te | ωe | ωexe | ωeye | Be | αe | γe | De | βe | re | Trans. | ν00 |
| X 1Σ+ | 0 | 481.3 HQ | 1.95 | 0.24393012 | 0.00161113 6 | 2.5027E-07 7 | -0.0053E-7 | 2.130113 8 9 | ||||
| Lide, 1965; Wyse and Gordy, 1972 |
| 1 | Estimated from observed isotope shifts. |
| 2 | v > 0 probably predissociated. |
| 3 | This state may have a potential hump of ~ 0.26 eV. Barrow, 1954, Barrow, 1960 |
| 4 | Predissociation in v=10 missing citation. |
| 5 | Estimated from P and Q head separations. |
| 6 | αv= +4.697E-6(v+1/2)2 - 5.7E-9(v+1/2)3. |
| 7 | He= -4.456E-14. |
| 8 | From the corrected Be = 0.24394229. |
| 9 | Microwave sp. 11 |
| 10 | Thermochemical value [see Appendix of Hildenbrand and Theard, 1969] See also Barrow, 1960. |
| 11 | μel = 1 to 2 D Lide, 1965. Values of eqQ in Lide, 1965, Hoeft, Torring, et al., 1973. |
Go To: Top, Gas phase ion energetics data, Constants of diatomic molecules, Notes / Error Report
Data compilation copyright by the U.S. Secretary of Commerce on behalf of the U.S.A. All rights reserved.
Hildenbrand, 1977
Hildenbrand, D.L.,
Dissociation energies of CaBr, SrBr, BaBr, and BaCl from mass spectrometric studies of gaseous equilibria,
J. Chem. Phys., 1977, 66, 3526. [all data]
Hildenbrand, 1970
Hildenbrand, D.L.,
Dissociation energies and chemical bonding in the alkaline-earth chlorides from mass spectrometric studies,
J. Chem. Phys., 1970, 52, 5751. [all data]
Hildenbrand and Theard, 1969
Hildenbrand, D.L.; Theard, L.P.,
Mass spectrometric measurement of the dissociation energies of BeCi and BeCl2,
J. Chem. Phys., 1969, 50, 5350. [all data]
Reddy and Rao, 1957
Reddy, S.P.; Rao, P.T.,
The emission spectrum of aluminum monochloride in the vacuum ultraviolet,
Can. J. Phys., 1957, 35, 912. [all data]
Mahanti, 1934
Mahanti, P.C.,
Das bandenspektrum des aluminiumchlorids,
Z. Phys., 1934, 88, 550. [all data]
Miescher, 1935
Miescher, E.,
Bandenspektren von bor- und aluminium-halogeniden,
Helv. Phys. Acta, 1935, 8, 279. [all data]
Lide, 1965
Lide, D.R., Jr.,
High-temperature microwave spectroscopy: AlF and AlCl,
J. Chem. Phys., 1965, 42, 1013. [all data]
Wyse and Gordy, 1972
Wyse, F.C.; Gordy, W.,
Millimeter wave rotational spectra of AlCl, AlBr, and AlI,
J. Chem. Phys., 1972, 56, 2130. [all data]
Barrow, 1954
Barrow, R.F.,
Maxima in the potential energy-distance functions of diatomic molecules,
J. Chem. Phys., 1954, 22, 573. [all data]
Barrow, 1960
Barrow, R.F.,
Dissociation energies of the gaseous monohalides of boron, aluminium, gallium, indium, and thallium,
Trans. Faraday Soc., 1960, 56, 952. [all data]
Hoeft, Torring, et al., 1973
Hoeft, J.; Torring, T.; Tiemann, E.,
Hyperfeinstruktur von AlCl und AlBr,
Z. Naturforsch. A, 1973, 28, 1066. [all data]
Go To: Top, Gas phase ion energetics data, Constants of diatomic molecules, References
Copyright for NIST Standard Reference Data is governed by the Standard Reference Data Act.
|
Standard Reference Data Program |
Data Gateway |
Chemistry WebBook |
If you have comments or questions about this site, please contact us.


Use Left and Right arrow keys to navigate! |
You have reached the end of this module. You will now be redirected to your home page.
If you want to retake the module, simply click on the module name again. Or, proceed to take the quiz.
Remember to finish the quiz before the deadline.


The summary accrual import tool allows users to upload a file with protocol enrollments and
subsequently import those enrollments in
OnCore as summary accruals. This summary accrual import process only applies to protocols that are
eligible to record summary data
(see Protocol Eligibility below).
Protocol Eligibility:
- The protocol is configured for summary accrual
- The protocol does not have clinical services occurring in a UF Health location (e.g. blood
draws, labs, EKG’s).
- The protocol will not use an OnCore calendar.
- Import tool users must be listed as protocol staff for the protocol in OnCore.
Note: the login credentials are the same as OnCore login credentials


Menu component is designed to be used as overlay control. It can be very helpful when you need controls on top of the map, images, some text/code editor, etc.
Plain Links
Dropdowns
Dropdown can be position on left, center or right of the menu item. It also can be scrollable.
On Top Of Map


Total cases worldwide
Active cases worldwide
New cases worldwide
Total deaths worldwide
New deaths worldwide
Total recovered worldwide
Total cases
Active cases
New cases
Total deaths
New deaths
Total recovered
Coronavirus disease 2019 (COVID-19), also known as the coronavirus, or COVID, is a contagious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The first known case was identified in Wuhan, China, in December 2019. The disease has since spread worldwide, leading to an ongoing pandemic.
Most people infected with the COVID-19 virus will experience mild to moderate respiratory illness and recover without requiring special treatment. Older people, and those with underlying medical problems like cardiovascular disease, diabetes, chronic respiratory disease, and cancer are more likely to develop serious illness.
The best way to prevent and slow down transmission is to be well informed about the COVID-19 virus, the disease it causes and how it spreads. Protect yourself and others from infection by washing your hands or using an alcohol based rub frequently and not touching your face.


{% comment %}@overview Generates the AIA detailed results row for a question or sub-question{% endcomment %}{% comment %}@param answerType {String} Form field used for the answer (e.g., "checkbox", "radio"). comment %}@param parentQuestionNumber {String} (Optional. Required for type = "checkbox"). Number of the parent question (e.g., "1" when "1a" and "1b" are checkboxes).{% endcomment %}{% comment %}@param questionNumber {String} Number of the question or sub-question (e.g., "4.1").{% endcomment %}{% comment %}@param questionDisplayNumber {String} (Optional, defaults to the value for questionNumber) Number to display for the question or sub-question if it is different than questionNumber (in the case where the question points to retrieve are different than the question number to display).{% endcomment %}{% comment %}@param hidden {Boolean} (Defaults to false) Whether the row should be hidden initially.{% endcomment %}{% comment %}@param nonScoringResult {Boolean} (Defaults to false) Whether the row is excluded from scoring.{% endcomment %}{% comment %}@return {String} Results row for the question or sub-question.{% endcomment %}{% if include.questionDisplayNumber %}{% assign questionDisplayNumber = include.questionDisplayNumber %}{% else %}{% assign questionDisplayNumber = include.questionNumber %}{% endif %}{% assign questionId = include.questionNumber | replace: ".", "-" %}


Let's get Started...
Scratch has some selected components and utilities for you.
COMPONENTS
UTILITIES
EFFECTS
Now let's see how to use em .
Download the CSS file.
Download the CSS file by clicking on the download button given below:
Your download will begin in a few seconds ...
Linking Scratch's CSS stylesheet to your HTML file.
Copy-paste the stylesheet link given below into your <head> before all other stylesheets.
< link rel="stylesheet" href="scratch-main.css" >
That's it !! Now you can use add all the Scratch's components and utilities in your website.


Assesments
S.no
Question
Response
1
Reason for Choosing the Hospital
Reachability
Recommendation
No Other Facility
2
Mode of Transportation & Time
Walk
Public Transport
Own Vehicle
3
Attender Details
Yes
No
4
Food and Transport Proivded by Hopsital?
Yes
No
5
Additional Thumb impression Requested
Yes
No


INTRODUCTION TO THE
RCBASIC PROGRAMMING LANGUAGE
First I would like to say thank you
for taking an interest in RCBASIC ( I use all caps because I think it looks
more retro that way). RCBASIC is a variant of the BASIC programming
language. It consist of a compiler, interpreter, and a code
editor. This version of BASIC was mostly influenced by sdlBasic and
QBasic. My main reason for writing this software was just to have fun
and challenge myself. This language is not as full featured as C++ or
Java but you can still create some awesome stuff with it. I hope you
have as much fun using this software as I had making it.
Rodney Cunningham (aka. n00b)


弹幕发射器🚀 Premium
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The entire Danmu infrastructure is proundly open-sourced on Charleo85/danmu


{% extends "base_forms.html" %} {% load crispy_forms_tags %} {% block logo %} {% include "includes/logo.html" %} {% endblock %} {% block content %}
Please fill out this form to request a centrally organised Carpentries workshop. We will ask you about dates, location and workshop type, so please plan to have this information available. If you would like more information about our workshops before scheduling, please request workshop information. If you are a Member Organisation or Instructor who is coordinating a self-organised workshop please use this form to register your workshop.
{% crispy form %} {% endblock %}


@* * This template is called from the `index` template. This template * handles the rendering of the page header and body tags. It takes * two arguments, a `String` for the title of the page and an `Html` * object to insert into the body of the page. *@ @(title: String)(content: Html) @pagejs = { }
@* Here's where we render the page title `String`. *@


--- layout: page title: M1ave description: Woodward 1 Ave. Apparel ---
Company: M1ave
Breif: M1ave celebrates Woodward as Michigans first course for racing. A premier place for automtive enthusiasts to show off their hard working custom built cars. M1ave comes to provide apperal for those that are at the track or just want to be part of the culture. Built on shopify.
Deliverables:Website Design
Website: M1ave


Before Change
if tf.executing_eagerly():
raise RuntimeError("Attention-based RNN decoder are currently not compatible "
"with eager execution")
initial_cell_state = super(AttentionalRNNDecoder, self)._get_initial_state(
batch_size, dtype, initial_state=initial_state)
attention_mechanism = self.attention_mechanism_class(
self.cell.output_size,
self.memory,
memory_sequence_length=self.memory_sequence_length,
After Change
self.memory,
memory_sequence_length=self.memory_sequence_length)
decoder_state = self.cell.get_initial_state(batch_size=batch_size, dtype=dtype)
if initial_state is not None:
if self.first_layer_attention:
cell_state = list(decoder_state)
cell_state[0] = decoder_state[0].cell_state
cell_state = self.bridge(initial_state, cell_state)
cell_state[0] = decoder_state[0].clone(cell_state=cell_state[0])
decoder_state = tuple(cell_state)
else:
cell_state = self.bridge(initial_state, decoder_state.cell_state)
decoder_state = decoder_state.clone(cell_state=cell_state)
return decoder_state
def step(self,
inputs,


This example demonstrates how to retrieve a structure from Marvin JS editor, using extra export options.
JChem Webservices (the web service implementation provided by ChemAxon) can accept special export options . The exportStructure() API function of Marvin JS gives the chance to specify export parameters for the molExport service.
In this example, +H export option (adding explicit Hydrogens to the structure) is passed to the molExport service. If the extra option has been specified, the exportStructure passes the request directly to the remote service instead of evaluating it on client side. If the location of the service has not been specified, an error message is thrown.
Please, take care that Marvin JS does not check whether the extra export options passed to WS are valid or not.
When the Get mol button is pressed, the current molecule is retrieved from the editor in mol format and the result is displayed in the textbox.
By unchecking the webservice checkbox, you can switch off the molExport web service. After this, pressing the Get mol button results in an error message, saying: "Unsupported format mol:+H".
var marvinSketcherInstance;
$(document).ready(function handleDocumentReady (e) {
var p = MarvinJSUtil.getEditor("#sketch");
p.then(function (sketcherInstance) {
marvinSketcherInstance = sketcherInstance;
initControl();
}, function (error) {
alert("Cannot retrieve sketcher instance from iframe:"+error);
});
});
function initControl () {
// get mol button
$("#btn-getmol").on("click", function (e) {
marvinSketcherInstance.exportStructure("mol", {"extra": "+H"}).then(function(source) {
$("#molsource").text(source);
}, function(error) {
alert("Molecule export failed:"+error);
});
});
var molconvertws_value = getDefaultServices()["molconvertws"]
$("#btn-service").change(function(e) {
var services = {
"molconvertws" : (e.target['checked']) ? molconvertws_value : null
};
marvinSketcherInstance.setServices(services);
});
}


WSConnectionUpgradeFactory
public class WSConnectionUpgradeFactory: ConnectionUpgradeFactory
The implementation of the ConnectionUpgradeFactory protocol for the WebSocket protocol. Participates in the HTTP protocol upgrade process when upgarding to the WebSocket protocol.
-
The name of the protocol supported by this
ConnectionUpgradeFactory
.Declaration
Swift
public let name = "websocket"
-
Upgrade
a connection to the WebSocket protocol. Invoked by the KituraNet.ConnectionUpgrader when an upgrade request is being handled.Declaration
Swift
public func upgrade(handler: IncomingSocketHandler, request: ServerRequest, response: ServerResponse) -> (IncomingSocketProcessor?, String?)