-
.isDraggable
-
The "isDraggable" property specifies whether an AccDC Object is draggable.
-
Values: True or False (default)
Syntax
$A([
{
isDraggable: true,
...
}
]);
// Or
$A.reg.myObj.isDraggable = false;
Important
-
When "isDraggable" is changed programmatically, the change will take affect the next time the AccDC Object opens;
-
The ".setDrag()" or ".unsetDrag()" methods can be used to add or remove "drag" and "drop" event bindings at runtime;
-
.drag
-
The "drag" property configures the drag functionality for an AccDC Object.
-
Defaults
{ handle: null, minDistance: 0, maxX: null, maxY: null, persist: false, confineTo: null, init: null, override: null }
Definitions
-
handle(Optional)
-
A CSS Selector or DOM node that specifies a drag handle within an AccDC Object.
-
minDistance(Optional)
-
An integer value specifying a minimum range of pixels to move before dragging is activated.
-
maxX(Optional)
-
An integer value specifying the maximum horizontal drag range in pixels.
-
maxY(Optional)
-
An integer value specifying the maximum vertical drag range in pixels.
-
persist(Optional)
-
A boolean value specifying whether current coordinates will be saved/restored when a draggable AccDC Object is closed/opened.
-
confineTo(Optional)
-
A CSS Selector or DOM node that specifies a container element to use as the top/right/bottom/left boundaries where dragging is not permitted to pass.
-
init(Optional)
-
A function declaration that will override the initial event when dragging is first initialized by clicking the draggable AccDC Object.
drag: {
init: function(ev, dd, dc){
// Do something
},
...
}
-
override(Optional)
-
A function declaration that will override the default calculations so that custom dragging functionality is possible.
drag: {
override: function(ev, dd, dc){
// Do something with dd.offsetX and dd.offsetY
},
...
}
Syntax
$A([
{
drag: {
handle: '#dragImg',
confineTo: 'div.box',
persist: true,
init: function(ev, dd, dc){
// Do something
}
},
...
}
]);
// Or
$A.reg.myObj.drag.override = function(ev, dd, dc){
// Do something with dd.offsetX and dd.offsetY
};
Important
-
When "drag" properties/methods are changed programmatically, the change will take affect the next time the AccDC Object opens.
-
The ".setDrag()" or ".unsetDrag()" methods can be used to add or remove "drag" and "drop" event bindings at runtime;
-
dd(Drag Data)
-
The "dd" object is passed as an argument to all drag event handlers.
-
Properties
-
target (DOM Node)
-
The drag element to which the event handler has been bound. (Always the same as "this" within a drag event handler)
-
drag (DOM Node)
-
The dragged element to which the drag event has been bound.
-
proxy (DOM Node)
-
The dragged element which determines the drop target tolerance.
-
drop (Array)
-
An array of all active drop targets for the current drag instance.
-
available (Array)
-
An array of all available drop targets for the current instance.
-
update (Method)
-
Helper function that updates the locations of all available drop targets in the current drag instance.
-
startX (Number)
-
The horizontal location of the "mousedown" event.
-
startY (Number)
-
The vertical location of the "mousedown" event.
-
deltaX (Number)
-
The horizontal distance moved from "startX".
-
deltaY (Number)
-
The vertical distance moved from "startX".
-
originalX (Number)
-
The starting horizontal position of the dragged element.
-
originalY (Number)
-
The starting vertical position of the dragged element.
-
offsetX (Number)
-
The moved horizontal position of the dragged element.
-
offsetY (Number)
-
The moved vertical position of the dragged element.
-
.onDragStart()(Event)
-
The "onDragStart()" handler is fired when the mouse moves a minimum distance.
-
Return false to cancel dragging.
Syntax
$A([
{
onDragStart: function(ev, dd, dc){
// Do something
},
...
}
]);
// Or
$A.reg.myObj.onDragStart = function(ev, dd, dc){
// Do something
};
Required:
-
The "isDraggable" property must be set to True.
-
.onDrag()(Event)
-
The "onDrag()" handler is fired every time the mouse moves when dragging.
-
Return false to instantly fire "onDragEnd()".
Syntax
$A([
{
onDrag: function(ev, dd, dc){
// Do something
},
...
}
]);
// Or
$A.reg.myObj.onDrag = function(ev, dd, dc){
// Do something
};
Required:
-
The "isDraggable" property must be set to True.
-
.onDragEnd()(Event)
-
The "onDragEnd()" handler is fired after all other drag and drop handlers have fired.
-
Syntax
$A([
{
onDragEnd: function(ev, dd, dc){
// Do something
},
...
}
]);
// Or
$A.reg.myObj.onDragEnd = function(ev, dd, dc){
// Do something
};
Required:
-
The "isDraggable" property must be set to True.
-
.dropTarget
-
The ".dropTarget" property specifies one or more drop targets.
-
Values: CSS Selector or DOM node
Syntax
$A([
{
dropTarget: 'div.target',
...
}
]);
// Or
$A.reg.myObj.dropTarget = document.getElementById('target');
Required:
-
The "isDraggable" property must be set to True.
-
drop
-
The ".drop" object configures the drop functionality for an AccDC Object.
-
Options
-
mode (String) Default: "overlap"
-
The specified tolerance mode.
Accepted values: "fit", "intersect", "middle", "overlap"
-
tolerance (Method) Default: null
-
An optional override to use as a tolerance checker.
Must return True or False
-
delay (Number) Default: 20
-
The frequency in milliseconds to check for drop target tolerances.
(Executes the "tolerance()" method when an override is declared.)
Syntax
$A([
{
drop: {
mode: 'overlap'
},
...
}
]);
// Or
$A.reg.myObj.drop.delay = 30;
Required:
-
The "isDraggable" property must be set to True.
-
The "dropTarget" property must specify one or more drop zones.
-
.accDD
-
The ".accDD" property configures drag and drop functionality for screen reader and keyboard only users.
-
Options
-
on (Boolean) Default: false
-
Enable or disable drag and drop support for keyboard access.
-
dragText (String) Default: 'Move'
-
The action text that will be prepended to the AccDC Object's "role" property within a hidden drag link.
(The hidden drag link becomes temporarily visible to keyboard only users when tabbing through active elements.)
-
toText (String) Default: 'to'
-
The action text that will be appended to the AccDC Object's "role" property within a hidden drag link.
(The hidden drag link becomes temporarily visible to keyboard only users when tabbing through active elements.)
-
actionText (String) Default: 'Dragging'
-
The active state text that will be announced to screen reader users during a drag and drop action.
-
dragClassName (String) Default: ''
-
Optional class(s) that will be added to the hidden drag link when rendered for keyboard only users.
-
dragLinkStyle (Object) Default: {}
-
Optional CSS values to be added to the hidden drag link when rendered for keyboard only users.
-
returnFocusTo (String) Default: accDCObj
-
CSS Selector or DOM node that specifies an optional strategic focus point where programmatic focus will return after a drop action completes.
-
duration (Number) Default: 500
-
Time length in milliseconds that will be applied to the drag animation.
Syntax
$A([
{
accDD: {
on: true,
returnFocusTo: 'div.dropZone ol.drop'
},
...
}
]);
// Or
$A.reg.myObj.accDD.dragLinkStyle = {
backgroundColor: 'black',
color: 'white',
fontSize: '0.8em'
};
Required:
-
The "isDraggable" property must be set to True.
-
The "dropTarget" property must specify one or more drop zones.
-
The data-label attribute must be set on all dropTarget containers that match the "dropTarget" property, in order to set unique textual names for each drop zone for screen reader and keyboard only users.

-
dd(Drop Data)
-
The "dd" object is passed as an argument to all drop event handlers.
-
Properties
-
target (DOM Node)
-
The drop element to which the event handler has been bound. (Always the same as "this" within an event handler)
-
drag (DOM Node)
-
The dragged element to which the drag event has been bound.
-
proxy (DOM Node)
-
The dragged element, which determines the drop target tolerance.
-
drop (Array)
-
Array of all active drop targets for the current drag instance.
-
available (Array)
-
Array of all available drop targets for the current drag instance.
-
update (Method)
-
Helper function that updates the locations of all available drop targets in the current drag instance.
-
startX (Number)
-
The horizontal location of the "mousedown" event.
-
startY (Number)
-
The vertical location of the "mousedown" event.
-
deltaX (Number)
-
The horizontal distance moved from "startX".
-
deltaY (Number)
-
The vertical distance moved from "startX".
-
originalX (Number)
-
The starting horizontal position of the dragged element.
-
originalY (Number)
-
The starting vertical position of the dragged element.
-
offsetX (Number)
-
The moved horizontal position of the dragged element.
-
offsetY (Number)
-
The moved vertical position of the dragged element.
-
.dropInit()(Event)
-
The ".dropInit" handler is fired after "drag.init()" when dragging first initiates.
-
Return false to make the drop target unavailable for the current drag action.
Syntax
$A([
{
dropInit: function(ev, dd, dc){
// Do something
},
...
}
]);
// Or
$A.reg.myObj.dropInit = function(ev, dd, dc){
// Do something
};
Required:
-
The "isDraggable" property must be set to True.
-
The "dropTarget" property must specify one or more drop zones.
-
.onDropStart()(Event)
-
The "onDropStart()" handler is fired when the dragged element moves within the tolerance of a drop target element.
-
Syntax
$A([
{
onDropStart: function(ev, dd, dc){
// Do something
},
...
}
]);
// Or
$A.reg.myObj.onDropStart = function(ev, dd, dc){
// Do something
};
Required:
-
The "isDraggable" property must be set to True.
-
The "dropTarget" property must specify one or more drop zones.
-
.onDrop()(Event)
-
The "onDrop()" handler is fired when the dragged element is dropped within the tolerance of a drop target element.
-
Syntax
$A([
{
onDrop: function(ev, dd, dc){
// Do something
},
...
}
]);
// Or
$A.reg.myObj.onDrop = function(ev, dd, dc){
// Do something
};
Required:
-
The "isDraggable" property must be set to True.
-
The "dropTarget" property must specify one or more drop zones.
-
.onDropEnd()(Event)
-
The "onDropEnd()" handler is fired when the dragged element moves out of the tolerance of a drop target element.
-
Syntax
$A([
{
onDropEnd: function(ev, dd, dc){
// Do something
},
...
}
]);
// Or
$A.reg.myObj.onDropEnd = function(ev, dd, dc){
// Do something
};
Required:
-
The "isDraggable" property must be set to True.
-
The "dropTarget" property must specify one or more drop zones.
-
.setDrag()
-
The ".setDrag()" method manually adds drag/drop bindings for an open AccDC Object.
-
Syntax
$A([
{
runAfter: function(dc){
dc.setDrag();
},
...
}
]);
// Or
$A.reg.myObj.setDrag();
Required:
-
The "isDraggable" property must be set to True;
-
The AccDC Object must be open when "setDrag()" is invoked.
-
.unsetDrag()
-
The ".unsetDrag()" method manually removes drag/drop bindings for an open AccDC Object.
-
Syntax
$A([
{
runAfter: function(dc){
dc.unsetDrag();
},
...
}
]);
// Or invoke unsetDrag; including all drop events as well
$A.reg.myObj.unsetDrag(true);
Required:
-
The "isDraggable" property must be set to True;
-
The AccDC Object must be open when "unsetDrag()" is invoked.
-
.cancel
-
The ".cancel" property can be used to cancel the opening of an AccDC Object.
-
Syntax
$A([
{
runBefore: function(dc){
// If condition
dc.cancel = true;
},
// Or
runDuring: function(dc){
// If condition
dc.cancel = true;
},
...
}
]);
-
.loading
-
The ".loading" property reflects the opening state of an AccDC Object.
-
Syntax
$A([
{
runBefore: function(dc){
alert(dc.loading); // False
},
runDuring: function(dc){
alert(dc.loading); // True
},
runAfter: function(dc){
alert(dc.loading); // False
},
...
}
]);
// Or
alert($A.reg.myObj.loading);
-
.loaded
-
The ".loaded" property reflects the open state of an AccDC Object.
-
Syntax
$A([
{
runAfter: function(dc){
alert(dc.loaded);
},
...
}
]);
// Or
alert($A.reg.myObj.loaded);
-
.closing
-
The ".closing" property reflects the closing state of an AccDC Object.
-
Syntax
alert($A.reg.myObj.closing);
-
.lock
-
The ".lock" property locks an AccDC Object in its current open/closed state.
-
Syntax
$A([
{
runAfter: function(dc){
dc.lock = true;
},
...
}
]);
// Or
$A.reg.myObj.lock = false;


Hello , Guys My Name is THAKUR ASHUTOSH SINGH
Today, inventions and mobile phone has become a great achievement in this respect. However, we can't ignore its fruitfulness but its misuses have been ignored. Following are the misuses of mobile phones: Corruption, Terrorism, Misusing of face book, Misuse in the examination, Data hacking, Chatting and wastage of time
If anyone who is having any problem related any thing they can contact us we are present to help you as soon as possible
Web Designer
CTO
Founder
DevOps
Software Engineer
UX Researcher
QA Engineer
System
Product Manager


Before you start
What you'll need
We'll ask for information about:
- income - how much you (or your partner) get from any jobs, pensions or benefits
- housing costs - what you (or your partner) pay for things like Council Tax and rent
If you or your partner get them, we may ask you to send us copies of:
- your payslips
- your latest Working Tax Credit award notice
- your latest Universal Credit award notice
Documents that could help
You may need:
- rent or mortgage statements
- latest Council Tax bill or Council Tax benefit letter
- pension details
- latest statement of benefits or award notice
- savings, investments and property details
Warning
It's important you know this information before you start. You can't save your application and come back to it later.


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Boeing drops automation system used to build 777 jets
NOVEMBER 14 — Boeing Co has abandoned a key automation system used to make fuselage sections for its 777 jetliners amid reports of reliability issues, and will instead partially switch back to mechanics, the planemaker said today.
The company began to build 777 fuselages in 2015 in an upright orientation, with robots drilling holes and installing fasteners, an initiative known as fuselage automated upright build (FAUB).
The world’s biggest planemaker said it had stopped using the system which, according to industry sources, caused problems with reliability and rework issues.
Boeing had faced delays last year when the FAUB machine was tried out on existing versions of the 777. (https://reut.rs/2KjsQtl)
Instead, the company will switch to “flex tracks” – an automated method to drill the holes along the circumference of the airplane that are then fastened manually.
The system was developed by Boeing Commercial Airplanes and has been tested in commercial and defence programs, company spokesman Paul Bergman said in an emailed statement.
Implementation of flex tracks for the 777 fuselage began in the second quarter and Boeing expects the transition to be complete by the year-end, Bergman said.
There are no planned changes in total staffing and the company continues to implement robotic systems on areas such as wing manufacturing for the 777X.
The setback highlights continuing pressure on the company’s management at a time it is trying to obtain approval to return its grounded 737 MAX jetliner to service before the end of this year.
The change in production strategy for the 777 was reported earlier by Bloomberg. — Reuters


Hello! I am Jason Starr. I am a .NET developer with experience in web, desktop, and mobile development. Most of my experience has centered on backend development, but I continuously explore new technologies and dedicate time towards maintaining my mobile and frontend skillsets.
Contact MeSkills
Web Development
Contributed to two, full-featured, multi-page web apps. Both leverage ASP.NET, and offer unique and responsive client features. More recently building SPAs with Angular and .NET Core.
Desktop Applications
Developed several applications with WPF and Windows Forms. Have experience building custom control libraries and writing backend services with WCF.
Android Mobile
Created android mobile application following the principles of modern Adnroid development (MAD). Utilizing JetPack libraries, MVVM architecture, and written 100% with Kotlin.


Aquaponics is a food production system that is a combination of hydroponics (growing plants in water) and aquaculture (raising aquatic animals such as fish).
Water from the fish tank is pumped into the plant bed which is then filtered back into the fish tank. The water used to nourish the plants has a number of nutrients found in the excretions from the fish. This is then broken down into nitrates and nitrites by nitrifying bacteria for the plants to absorb.
Our Aquaponics system makes it super easy to setup with an easy to follow guide on how to put everything together.
With the help of our mobile and web app, anyone can easily maintain our aquaponics system.
 :)
Want to know more about our system?


Preparation time
less than 30 mins
Cooking time
over 2 hours
Serves
Makes 1 x 25cm/10in round cake
Dietary
Try something different for your Christmas cake with this rich fruit cake recipe topped with homemade pecan marzipan.
Preheat the oven to 170C/335F/Gas 3 and line a 25cm/10in round, deep cake tin with non-stick paper.
Place the syrup, treacle, honey, sugar, cream and spices in a saucepan and bring to the boil. Pour the mixture into a large mixing bowl, add the butter in pieces and stir until melted, then add the orange and lemon extracts.
Beat in the eggs until smooth, then stir in the fruit. Mix the flour and soda together, then stir this through evenly.
Spoon into the tin and bake for about 2-2½ hours, or until a skewer inserted comes out clean. Leave to cool in the tin, then carefully remove from the tin.
When cold, spoon the top liberally with brandy, whisky or boiled orange juice, wrap well and leave in a cool, dark place for 3-4 days before icing.The cake will keep for up to 3 months and should be ‘fed’ (covered with brandy, whisky or boiled orange juice every 4-5 days).
For the pecan marzipan, combine the ground pecans and icing sugar in a bowl and mix together.
In a saucepan, whisk together the brown sugar, egg yolks, glucose, honey, glycerine, cinnamon and vanilla, then cook over a low heat whisking constantly until pale, light and piping hot.
Pour this over the pecan mixture and stir well to make a smooth paste. Leave to cool, then wrap in cling film.
To cover the cake in marzipan, first lightly knead the marzipan so it’s smooth then roll it out on a worktop dusted with icing sugar. Roll the marzipan into a disc about 1cm/½in thick and 1-2cm/½-1in wider than the diameter of your cake (check the marzipan isn’t sticking to the worktop by dusting underneath it again with icing sugar).
Brush the top of the cake with the sieved jam then leave a few minutes for it to set. Turn the cake upside down onto the marzipan and wiggle it gently so the top is stuck firmly.
Trim any excess marzipan leaving a 2cm/1in border. Using a knife, gently press up into the gap caused by the curve of the cake, then scrape it up smoothly so it is level with the side of the cake.
Carefully turn the cake the right way up and you should be left with a perfectly flat top surface and straight sides.
Wrap the cake in cling film and leave to dry in a cool, dark place for 4-5 days.
For the brandy butter icing, measure the icing sugar into a bowl, then melt the butter for a few seconds in the microwave or in a small pan over a low heat, taking care not to burn it.
Pour the melted butter with the cream and brandy into the sugar and mix until smooth.
Spread the icing onto the top of the cake and make small peaks using a knife. Set aside for a few hours, or until the icing has set.
Dust with icing sugar before serving.


In these lessons, I first implemented Assignment 12 which I had already made in TinkerCAD and is shown below.
The code is found here
Then in the next lesson, I was handed an ultrasonic distance sensor. However, I did not take a video of the result and thus only the coding is showed here.
I modified Assignment 12 and coded the Ultrasonic distance sensor so that when it detects if something is within 10 to 30cm away from the sensor that I can press the button and it will run Assignment 12.
After that, I implemented the same circuit but with an LM34 instead of an ultrasonic distance sensor. Both the video of it and the coding is shown below.
For this, I had also modified Assignment 12 so that when the temperature is below 27 degrees celcius, then it will run Assignment 12 but without the use of the pushbutton.


subtom_clean_motl¶
Cleans a given MOTL file based on distance and/or CC scores.
This MOTL manipulation script uses one MATLAB compiled scripts below:
Options¶
Directories¶
- scratch_dir
Absolute path to the folder with the input to be processed. Other paths are relative to this one.
- mcr_cache_dir
Absolute path to MCR directory for the processing.
- exec_dir
Directory for executables
Variables¶
- clean_motl_exec
Clean MOTLs executable
File Options¶
- input_motl_fn
Relative path and name of the input MOTL file to be cleaned.
- output_motl_fn
Relative path and name of the output MOTL file.
- output_stats_fn
Relative path and name of the optional output cleaning stats CSV file. If you do not want to write out the differences just leave this as “”.
The CSV format of the output statistics file for cleaning is a single row with the following columns:
Column |
Value |
|---|---|
1 |
Total Initial Number of Particles |
2 |
Number of Particles Removed in Edge Cleaning |
3 |
Number of Particles Removed in Cluster Cleaning |
4 |
Number of Particles Removed in Distance Cleaning |
5 |
Number of Particles Removed in CC Cleaning |
6 |
Total Remaining Number of Particles |
Clean Options¶
- tomo_row
Which row in the motl file contains the correct tomogram number. Usually row 5 and 7 both correspond to the correct value and can be used interchangeably, but there are instances when 5 contains a sequential ordered value starting from 1, while 7 contains the correct corresponding tomogram.
- do_ccclean
If the following is set to 1 then the MOTL will be cleaned by CCC either by CCC value or a fraction of the highest CCC values to keep. If it is set to 0 then CCC cleaning will be skipped.
- cc_fraction
If cleaning by CC then after edge, cluster, and distance cleaning, if any are selected, is completed. The MOTL will be sorted by CCC and then the top fraction as specified here will be kept with the rest discarded. For example if cc_fraction=0.7 the top 70% of the clean data will be kept and the bottom 30% of the cleaned data will be discarded. A value of 1 here means that data is not cleaned by CCC fraction.
- cc_cutoff
If cc_fraction is 1 and therefore not used then particles with a CCC below this cutoff will be removed from the output MOTL file. Values must be within -1 to 1, with -1 not removing any particles.
- do_distance
If the following is set to 1 then the MOTL will be cleaned by distance. If it is set to 0 distance cleaning will be skipped.
- distance_cutoff
Particles that are less than this distance in pixels from another particle will be cleaned with the particle with the highest CCC kept while the others are removed from the output MOTL file.
- do_cluster
If the following is set to 1 then the MOTL will be cleaned by a clustering criteria that enforces kept particles to exist as clusters. This can be useful when there is no lattice and clusters of particles makes a good indication that a true copy of the reference exists there. If it is set to 0 cluster cleaning will be skipped.
- cluster_distance
The following determines the radius that defines what is considered a cluster in cluster cleaning.
- cluster_size
The cluster size specifies how many particles must be found within cluster_distance for the particle to be considered part of a cluster. The particle with the highest CCC in the cluster will be selected as the representative particle for the cluster and the remaining clustered points will be removed.
- do_edge
If the following is set to 1 then the MOTL will be edge cleaned considering the dimensions of the tomogram in which the particles are contained. If any part of the particle exists outside of the tomogram it will be removed from the MOTL. If it is set to 0 edge cleaning will be skipped.
- tomogram_dir
Absolute path to the folder where the tomograms are stored. If you are not edge cleaning leave this set to “”.
- box_size
What is the box size of the particle that will be extracted from the tomogram, which is necessary to specify to be able to edge clean.
- write_stats
If the following is 1 then the details of how many particles were cleaned in each stage will be written out, if 0 then not.
Example¶
scratch_dir="${PWD}"
mcr_cache_dir="${scratch_dir}/mcr"
exec_dir="/net/dstore2/teraraid/dmorado/software/subTOM/bin"
clean_motl_exec="${exec_dir}/MOTL/subtom_clean_motl"
input_motl_fn="combinedmotl/allmotl_2.em"
output_motl_fn="combinedmotl/allmotl_cc0.1_dist4_cluster2d10_2.em"
output_stats_fn="combinedmotl/allmotl_cc0.1_dist4_cluster2d10_stats.csv"
tomo_row=7
do_ccclean=1
cc_fraction=1
cc_cutoff=0.1
do_distance=1
distance_cutoff=4
do_cluster=1
cluster_distance=10
cluster_size=2
do_edge=1
tomogram_dir="/net/dstore2/teraraid/dmorado/subTOM_tutorial/data/tomos/bin8"
box_size=36
write_stats=1


Hi again, Not sure if this is a bug or not but when you post in the forums, this post will show in the battlefeed which is ok, Is there any way not to show the start of the formatting text for the signature in the battlefeed?
Example: when i type "BBLOG is the best thing since sliced bread" it comes out as "BBLOG is the best thing since sliced bread [size9] (whatever the signature is).
Thanks again for all your work,
Marty
BrainFooLong
Administrator
This a bug by battlelog, the don't format BBCodes in Feeds. Hope they fix it in the next update.
Greetz
BrainFooLong
Administrator
PS: I don't fix it because all other users without bblog will also see the BBCodes.
So it simple must be done by Battlelog itself.


Your Python, Our Servers : What could possibly go wrong?
We've been brainstorming for products to build. What do you think of this one?
Python Interactive Console in the Browser
One idea is a CPython interactive console in the browser. Client is Javascript, which sends the user's Python to execute in a sandbox on our EC2 instances. Dirigible already has the infrastructure to support running our user's arbitrary Python in a sandbox across our grid - so we'd only need to strip the spreadsheet-UI off to expose this functionality to end-users.
Your console state is persistant - so you could start some investigation, or a long-running statement, then log off, and then reconnect to it later from another machine.
Since the Python runs on our servers, all the client needs is a working browser with Javascript. You could run code from any device - even funky things like iPads which don't traditionally make installing and running Python very easy. Your only hinderance would be the keyboard. Since our servers could be beefy, it would run substantially faster. We could help to support running in parallel across several servers.
We could provide multiple versions of Python - and keep them fully loaded with packages from PyPI - so you could use any combo without having to install anything locally.
There are already some examples of in-browser Python consoles like this, but none of them quite do what we'd hope to do.
We're also thinking of providing really simple tools so you could work on scripts or programs locally, and then run them in the cloud with a single command / button.
Generally we're thinking of running your stuff on our own EC2 servers. Other applications might involve executing stuff on your own servers, instead of ours, but thus far we haven't come up with applications of this that offer much over fabric or a combination of an SSH session and Unix program 'screen'.
Would you use this? What for? Do you think it's totally dumb? I'd love to hear about it.
Most interestingly, would you pay for it? We're thinking free for trivial uses, a few dollars for some advanced features (access to networking, persistance) and scale up to support teraflop computing.


Please watch your step through the garden and walk only over the furnished alleyways!
You hereby agree that the artists, developers, partners and sponsors of this application cannot be held responsible for any loss, damage, or injury, including but not limited to suffering and death, that may be sustained while using this
application.


VisualK allows to visualize the status and evolution
of the service provided by the
K-root name server
in near real-time.
K-root is pictured as a node-link graph where each node is an
anycast instance and each link implies topological
proximity between two instances. The size of each node reflects
the volume of traffic served by the corresponding instance.
Links become active when there are traffic migrations between instances.
VisualK was designed and implemented at the
RIPE NCC
in collaboration with
Roma
Tre University.
Read more
on CircleID


And the winner is...
Drumroll please...
The anticipation is killing me...
Me of course.
And the winner is...
Drumroll please...
The anticipation is killing me...
Me of course.
And the winner is...
Drumroll please...
The anticipation is killing me...
Me of course.
And the winner is...
Drumroll please... The anticipation is killing me... Me of course.


“Vihari apekkhaṁ idha vā huraṁ vā,
Yo vedagū samito yatatto;
Sabbesu dhammesu anūpalitto,
Lokassa jaññā udayabbayañcā”ti.
Itthaṁ sudaṁ āyasmā puṇṇamāso thero gāthaṁ abhāsitthāti.
vaggo paṭhamo.
Tassuddānaṁ
A knowledge master, peaceful and self-controlled,
is rid of concern for this world and the world beyond.
Unsullied among all things,
they’d know the arising and passing of the world.
It was thus that this verse was recited by the senior venerable Puṇṇamāsa.
Subhūti koṭṭhiko thero,
kaṅkhārevatasammato;
Mantāṇiputto dabbo ca,
sītavaniyo ca bhalliyo;
Vīro pilindavaccho ca,
puṇṇamāso tamonudoti.


Following collectible sneakers sold on eBay
More about this project
© Kat Chuang, Data Engineering Fellow Insight Data Science


{{ partial "head" . }}
We are a different kind of technology company. Above all, we believe in building exceptional products for our clients


Airplane “broke up in flight” before crashing and killing two from Salisbury last month
by David WhisenantSALISBURY, N.C. (WBTV) - A preliminary report by the National Transportation Safety Board (NTSB) indicates that a small plane broke up in flight before crashing into an Atlanta town home on October 30.
Two Salisbury businessmen, 59-year-old pilot Leslie Csanyi Jr. and 60-year-old Scott Robert Lowrie, were killed in the crash.
Csanyi was a frequent flier for business, vacations, even to deliver much needed supplies to Haiti after the 2010 earthquake.
The agency says shortly after takeoff from DeKalb-Peachtree Airport, the pilot reported losing the vacuum gauge in the Piper PA-28.
The report shows that Csanyi experienced trouble turning and maintaining his route, telling the controller over the radio that the plane had “...lost their vacuum gauge.”
The plane then turned briefly to the northeast before entering a right turn and rapidly descended to 3,700 feet.
According to the report, the controller told the pilot to maintain “wings level” at 4,000 feet, but there was no response from the pilot.
The controller tried to contact the pilot several times with instructions to maintain wings level, but received no response from the plane before radar contact was lost.
The final report from the agency is expected to take several months.


This tool, powered primarily with AngularJS, will help you design and generate an ORM CFC file and a corresponding ValidateThis (VT) validation file to manage both client-side and server-side validation.
Choose from the following option(s):
Generate a new ORM file and corresponding VT file.
You currently have no files from previous uses of this tool (every time you use the tool to generate files, all of the design data is stored in a timestamped JSON file which you can then load and use to make changes).
OR


Situated about 70nm south of the US/Mexico border. It is a popular cruise ship destination and tourist resort.
Position 31°51′N, 116°36′W.
This port is reported to be the simplest place on the Pacific coast of Mexico to make first entry into the country and secure your TIP paperwork. Officials are used to dealing with foreign yachts.
International Arrival Port Clearance for yachts is done all in one place, the big CIS office. It contains offices for Migracion, Aduana, Capitania, Agriculture, Navy, and you pay one fee by credit card. This is where you get your TIP. You do not need an agent.
Officials will only inspect your boat if there is some problem. They do not work at weekends.
Boats are either anchored inside the breakwater or taken to Pirates Pier, a marina offering a limited range of services.
If any crew member flies into Mexico and then wishes to sail out, they may experience difficulties in getting an exit stamp. See Noonsite report.
Last updated September 2014.
This is the most northerly Port of Entry on Mexico's Pacific coast. There are 3 full service marinas here. Two inside the harbour breakwaters and one just under 3 nm north of the town.
There are moorings by the sport fishing docks on the eastern side of the harbour. This is a popular port of call, and berths and anchorages can be in short supply.
As of 2007, anchoring is prohibited in the harbour. It is not known how long this restriction is expected to last.
Last updated April 2015.


public class LDASynParam
extends java.lang.Object
| Modifier and Type | Field and Description |
|---|---|
double |
_alpha |
double |
a |
double |
alpha |
double |
b |
double |
beta |
double |
c |
boolean |
directed |
int |
docLength |
double |
gamma |
boolean |
negEdge |
double |
nu |
int |
numBlocks |
int |
numDocs |
int |
numTopics |
int |
numVocab |
double |
sigma |
| Constructor and Description |
|---|
LDASynParam() |
public final double alpha
public final double _alpha
public final double beta
public final int numTopics
public final int numVocab
public final int numDocs
public final int docLength
public final double nu
public final boolean negEdge
public final double c
public final double sigma
public final boolean directed
public final double a
public final double b
public final double gamma
public final int numBlocks


public interface Traversal<S,E> extends Iterator<E>, Cloneable
| Modifier and Type | Interface and Description |
|---|---|
static class |
Traversal.Exceptions
A collection of
Exception types associated with Traversal execution. |
static interface |
Traversal.SideEffects |
| Modifier and Type | Field and Description |
|---|---|
static String |
OF
Used for reflection based access to the static "of" method of a Traversal.
|
| Modifier and Type | Method and Description |
|---|---|
default void |
addStart(Traverser<S> start)
Add a single
Traverser object to the head of the traversal. |
void |
addStarts(Iterator<Traverser<S>> starts)
Add an iterator of
Traverser objects to the head/start of the traversal. |
default <E2> Traversal<S,E2> |
addStep(Step<?,E2> step)
Add a
Step to the end of the traversal. |
void |
applyStrategies(TraversalEngine engine) |
Traversal<S,E> |
clone()
Cloning is used to duplicate the traversal typically in OLAP environments.
|
default <C extends Collection<E>> |
fill(C collection)
Add all the results of the traversal to the provided collection.
|
default <E2> void |
forEachRemaining(Class<E2> endType,
Consumer<E2> consumer)
A traversal can be rewritten such that its defined end type E may yield objects of a different type.
|
List<Step> |
getSteps()
Get the
Step instances associated with this traversal. |
boolean |
isLocked() |
default Traversal |
iterate()
Iterate all the
Traverser instances in the traversal. |
default List<E> |
next(int amount)
Get the next n-number of results from the traversal.
|
default void |
reset()
Call the
Step.reset() method on every step in the traversal. |
default Traversal<S,E> |
reverse()
|
Traversal.SideEffects |
sideEffects()
Get the
Traversal.SideEffects associated with the traversal. |
default Traversal<S,E> |
submit(GraphComputer computer)
Submit the traversal to a
GraphComputer for OLAP execution. |
default List<E> |
toList()
Put all the results into an
ArrayList . |
default Set<E> |
toSet()
Put all the results into a
HashSet . |
forEachRemaining, hasNext, next, remove
static final String OF
Traversal.SideEffects sideEffects()
Traversal.SideEffects
associated with the traversal.void addStarts(Iterator<Traverser<S>> starts)
Traverser
objects to the head/start of the traversal.
Users should typically not need to call this method. For dynamic inject of data, they should use InjectStep
.starts
- an iterators of traversersdefault void addStart(Traverser<S> start)
Traverser
object to the head of the traversal.
Users should typically not need to call this method. For dynamic inject of data, they should use InjectStep
.start
- a traverser to add to the traversalList<Step> getSteps()
Step
instances associated with this traversal.
The steps are ordered according to their linked list structure as defined by Step.getPreviousStep()
and Step.getNextStep()
.void applyStrategies(TraversalEngine engine)
boolean isLocked()
default <E2> Traversal<S,E2> addStep(Step<?,E2> step) throws IllegalStateException
Step
to the end of the traversal.
This method should automatically link the step accordingly. For example, see TraversalHelper.insertStep(com.tinkerpop.gremlin.process.Step, int, com.tinkerpop.gremlin.process.Traversal<?, ?>)
.
If the TraversalStrategies
have already been applied, then an IllegalStateException
is throw stating the traversal is locked.E2
- the output of the stepstep
- the step to addIllegalStateException
Traversal<S,E> clone()
default Traversal<S,E> submit(GraphComputer computer)
GraphComputer
for OLAP execution.
This method should apply the traversal strategies for TraversalEngine.COMPUTER
.
Then register and execute the traversal via TraversalVertexProgram
.
Then wrap the ComputerResult
in a new Traversal
containing a ComputerResultStep
.computer
- the GraphComputer to execute the traversal ondefault void reset()
Step.reset()
method on every step in the traversal.default Traversal<S,E> reverse() throws IllegalStateException
IllegalStateException
default List<E> next(int amount)
amount
- the number of results to getList
default List<E> toList()
ArrayList
.default <C extends Collection<E>> C fill(C collection)
collection
- the collection to filldefault Traversal iterate()
Traverser
instances in the traversal.
What is returned is the empty traversal.
It is assumed that what is desired from the computation is are the sideEffects yielded by the traversal.default <E2> void forEachRemaining(Class<E2> endType, Consumer<E2> consumer)
E2
- the known output type of the traversalendType
- the true output type of the traversalconsumer
- a Consumer
to process each outputCopyright © 2013–2014 TinkerPop. All rights reserved.


Sources from the location.hash and sinks into various javascript functions.
Sources from the raw location and sinsk into various javascript functions.
Various other sources and sinks: the first value represnets the DOM source, the second the JS sink.


Powered by Sri Lanka Telecom
Find Out MoreSLIOT Challenge 2018 is a Competition which is organized by Computer Science and Engineering department of University of Moratuwa and Institute of Engineers Sri Lanka in collaboration with Sri Lanka Telecom PLC. This competition is organized to improve the awareness on the concept "Internet of Things" (IOT) and its usages among the Sri lankan community, it is mainly launched under two categories, University and Open category.
University category is focusing on the undergraduates of government and private universities of Sri Lanka. In Open category, organizers expect to evaluate IoT based solutions which are capable in providing solutions to general public according to Industrial level standards. By this Competition we hope to ignite imagination and creativity by providing a competitive background among each other. We will check your ideas in various aspects to determine its creativity, value, benefits, technologies etc. Winners will be chosen from the best ideas and event day performance of the applications.
Come up with any new IDEA, that help to solve any day to day life problem or come up with a totally new project that is based on Internet Of Things, and that’s all. You are ready to participate in the SLIOT Competition.*
* Undergraduate category team must consist with undergraduates from a recognized Sri Lankan University (Government or private).
*Open category proposals should be related IOT based applications which is either readily available or newly invented and has a business case. The proposals should be up to industrial level standards.
Stay tuned. Prizes will be unvailed soon.
Please don't hestitate to contact us for more information.


Overview
PaperParcel is an annotation processor that automatically generates the CREATOR
and writeToParcel(...)
implementations for you when writing Parcelable objects. PaperParcel fully supports both Java and Kotlin (including Kotlin Data Classes). Additionally, PaperParcel supports Google's AutoValue via an AutoValue Extension.
Out of the box, PaperParcel supports all of the types that are supported by the Parcel class, including a few minor additions (e.g. java.util.Set
). Support for any other types can be added using custom Type Adapters.
Usage
Using PaperParcel is easy, the API is extemely minimal. Let's look at an example:
@PaperParcel // (1)
public class User implements Parcelable {
public static final Creator<User> CREATOR = PaperParcelUser.CREATOR; // (2)
long id; // (3)
String firstName; // (3)
String lastName; // (3)
@Override public int describeContents() {
return 0;
}
@Override public void writeToParcel(Parcel dest, int flags) {
PaperParcelUser.writeToParcel(this, dest, flags); // (4)
}
}
I've annotated each important part with a comment and a number, let's look at each of these one by one:
- Annotating a class with
@PaperParcel
will automatically generate theCREATOR
andwriteToParcel(...)
implementations for that class at compile time. These implementations are generated into a java class (in the same package as your model) calledPaperParcel$CLASS_NAME$
- This is the first usage of the generated code — the generated
CREATOR
instance. - These are the fields that will be processed by PaperParcel.
- This is the second usage of the generated code — the generated
writeToParcel(...)
implementation.
The fields in this example are all package private, but that is absolutely not a necessity. See Model Conventions for detailed information on how you can structure your model classes.
Manually entering the CREATOR
and filling in the Parcelable
interface methods is fairly repetitive, so I like to use Intellij Live Templates to generate this code automatically.
Even Easier; Use The AutoValue Extension
If you are already using AutoValue, all you need to do is simply add implements Parcelable
to your AutoValue object and that's it:
@AutoValue
public abstract class User implements Parcelable {
public abstract long id();
public abstract String firstName();
public abstract String lastName();
public static User create(long id, String firstName, String lastName) {
return new AutoValue_User(id, firstName, lastName);
}
}
Kotlin
Usage is exactly the same as java:
@PaperParcel
data class User(
val id: Long,
val firstName: String,
val lastName: String
) : Parcelable {
companion object {
@JvmField val CREATOR = PaperParcelUser.CREATOR
}
override fun describeContents() = 0
override fun writeToParcel(dest: Parcel, flags: Int) {
PaperParcelUser.writeToParcel(this, dest, flags)
}
}
Optional: If you don't mind a minor amount of reflection, the paperparcel-kotlin
module provides PaperParcelable. PaperParcelable
is an interface with default implementations written for describeContents
and writeToParcel(...)
so you don't have to write them yourself, e.g.:
@PaperParcel
data class User(
val id: Long,
val firstName: String,
val lastName: String
) : PaperParcelable {
companion object {
@JvmField val CREATOR = PaperParcelUser.CREATOR
}
}
As mentioned in the Java Usage section, Intellij Live Templates can be a really useful tool when writing PaperParcel models. A quick tutorial for setting up Live Templates for PaperParcel in kotlin can be found here.
Migrating from PaperParcel 1.x
If you are a PaperParcel 1.x user and would like to move to 2.x, see Migrating from PaperParcel 1.x.
Type Adapters
PaperParcel keeps it built-in TypeAdapter
s list minimal to ensure the library is as small as possible. If you want to extend the type system, you can do this by registering your own custom TypeAdapter
. Defining a custom TypeAdapter
is simple, let's look at an example that adds support for the java.util.Date
class:
@RegisterAdapter // 1
public final class DateAdapter implements TypeAdapter<Date> {
public static final DateAdapter INSTANCE = new DateAdapter(); // 2
@NonNull @Override public Date readFromParcel(@NonNull Parcel source) {
return new Date(source.readLong());
}
@Override public void writeToParcel(@NonNull Date value, @NonNull Parcel dest, int flags) {
dest.writeLong(value.getTime());
}
}
I've annotated each important part with a comment and a number, let's look at each of these one by one:
- This is how you register your custom adapter with the compiler — just by annotating this class, generated code will now use
DateAdapter
when reading and writingDate
fields. Additionally,Date
fields can now be used inList
s,Map
s, Arrays, etc too. - This is a completely optional singleton instance. If PaperParcel notices your class is a singleton, it will use the singleton instance. This helps greatly in preventing unecessary allocations. For this reason, most of the built-in type adapters are singletons. Note for Kotlin users, this is equivalent to defining your Adapter as an
object
.
Many similar projects also use some variant of TypeAdapter
, however the PaperParcel implementation is slightly more flexible. PaperParcel allows TypeAdapter
s to be composable and generic. To see why this is useful, let's look at how PaperParcel's built-in SparseArrayAdapter is defined:
public final class SparseArrayAdapter<T> implements TypeAdapter<SparseArray<T>> {
private final TypeAdapter<T> itemAdapter;
public SparseArrayAdapter(TypeAdapter<T> itemAdapter) {
this.itemAdapter = itemAdapter;
}
...
}
As you can see, SparseArrayAdapter
has a dependency on another TypeAdapter
to handle the parcelling of its items, but the item type is not hard-coded (it is generic). This means we don't need to define a new adapter class each time we use a SparseArray
with a different item type, instead this single adapter will handle all item types.
A TypeAdapter
can list any number of TypeAdapter
or Class
dependencies as constructor parameters and PaperParcel will resolve them at compile time. You can take advantage of this power to easily add support for container types that don't come out of the box, e.g. RealmList
for Realm, various non-java Collection
and Tuple
types in Kotlin, or even ImmutableMap
for Guava.
Excluding Fields
By default, PaperParcel will exclude any static
or transient
fields from being included in the generated CREATOR
and writeToParcel(...)
implementations. If you have more complicated requirements for excluding fields, then you can customise this behaviour using the @PaperParcel.Options
API:
Exclude via modifiers
Let's say you wanted to exclude all transient
and static final
fields (therefore keeping any non-final static
field). You could achieve that like this:
@PaperParcel
@PaperParcel.Options(
excludeModifiers = {
Modifier.TRANSIENT,
Modifier.STATIC | Modifier.FINAL
}
)
public class Example implements Parcelable {
static final int field1 = 0; // Will not be parcelled
static int field2; // Will be parcelled
transient int field3; // Will not be parcelled
int field4; // Will be parcelled
...
}
Exclude via annotation
Another API available to you is excludeAnnotations
. This API lists all of the annotations that will be used to exclude fields. Let's see how this might look:
First we'll create an annotation and call it Exclude
:
@Retention(RetentionPolicy.SOURCE)
@Target(ElementType.FIELD)
public @interface Exclude {
}
Now we can use this annotation in any of our model classes to exclude fields like so:
@PaperParcel
@PaperParcel.Options(excludeAnnotations = Exclude.class)
public class Example implements Parcelable {
int field1; // Will be parcelled
@Exclude int field2; // Will not be parcelled
...
}
Opt-in field strategy
Lastly, PaperParcel can be configured to ignore all fields unless specified otherwise. This is useful in a style of programming where you want to explicitly specify all fields that should be considered for parcelling.
Like the previous example, we can define our own annotation:
@Retention(RetentionPolicy.SOURCE)
@Target(ElementType.FIELD)
public @interface Expose {
}
Then our @Expose
annotation can be used to include individual fields like so:
@PaperParcel
@PaperParcel.Options(
excludeNonExposedFields = true,
exposeAnnotations = Expose.class
)
public class Example implements Parcelable {
@Expose int field1; // Will be parcelled
int field2; // Will not be parcelled
...
}
Reusable exclusion rules
Applying exclusion rules in this manner can become tedius if you if you want to apply the same rules to many (or all) of your model objects. For a more reusable strategy, you may wish to create a custom annotation which will define all of the rules you wish to apply; then use your custom annotation on your @PaperParcel
classes instead. Here's an example of a custom annotation that has @PaperParcel.Options
applied to it:
@PaperParcel.Options(...) // Define your rules here
@Retention(RetentionPolicy.SOURCE)
@Target(ElementType.TYPE)
public @interface MyOptions {
}
After defining @MyOptions
(call it whatever you like), you can then apply it directly to any @PaperParcel
class to apply the rules:
@MyOptions
@PaperParcel
public class Example implements Parcelable {
...
}
Model Conventions
Note: this section is only relevant if you are using PaperParcel without the assitance of AutoValue or Kotlin's data classes.
By default, PaperParcel uses no reflection to access fields1. Because of that, all of the fields that PaperParcel is going to process need to follow a few loose conventions in order for PaperParcel to know how to read your fields and re-instantiate your models. Any failure to follow these conventions will result in a compile time error with a clear message informing you of what is wrong.
Reading Fields
The easiest way for PaperParcel to read a field is for it to be non-private. Because the generated code lies in the same package as the model itself, default
, protected
, or public
fields can be read directly.
However private fields are common practice and need to be supported. Therefore, if a field is private, PaperParcel will look for an accessor method (AKA a getter method) for that field. PaperParcel relies on the following conventions to find accessor methods:
- The method needs to return an assignable type to the field's type.
- The method needs to have no arguments.
- The method needs to have one of the following names:
$FIELD_NAME$
,get$FIELD_NAME$
, oris$FIELD_NAME$
. For example, if the field is namedfirstName
, then the set of valid accessor method names would containfirstName
,getFirstName
, andisFirstName
.
Writing Fields
The easiest way for PaperParcel to write a field is for it to be non-private and non-final. Because the generated code lies in the same package as the model itself, default
, protected
, or public
fields can be written directly.
As already mentioned, private fields to be supported. Therefore, if a field is private, PaperParcel will look for either a corresponding constructor arugment for the field, or a setter method for the field.
Constructor arugments are simple: they must have the same name as the field that it is assigning. In addition, the argument type must be assignable to the field type.
Setter methods are discovered using similar conventions to the aforementioned accessor method conventions:
- The method needs to have one argument.
- The argument type needs to be assignable to the field's type.
- The method needs to have one of the following names:
$FIELD_NAME$
, orset$FIELD_NAME$
. For example, if the field is namedfirstName
, then the set of valid setter method names would containfirstName
andsetFirstName
.
1: You can configure PaperParcel to access private fields via refelection using the PaperParcel.Options#reflectAnnotations() API. ↩
Download
Java:
dependencies {
compile 'nz.bradcampbell:paperparcel:2.0.0-beta1'
annotationProcessor 'nz.bradcampbell:paperparcel-compiler:2.0.0-beta1'
}
Kotlin:
PaperParcel requires kotlin 1.0.5
(or greater) and the 'kotlin-kapt'
Gradle plugin. Please note that the 'kotlin-kapt'
Gradle plugin is still experimental and may have issues.
apply plugin: 'kotlin-kapt'
dependencies {
compile 'nz.bradcampbell:paperparcel:2.0.0-beta1'
compile 'nz.bradcampbell:paperparcel-kotlin:2.0.0-beta1' // Optional
kapt 'nz.bradcampbell:paperparcel-compiler:2.0.0-beta1'
}
Development snapshots are available on JFrog OSS Artifactory.
Contributing
If you would like to contribute code you can do so by forking the repository and sending a pull request.
When submitting code, please make every effort to follow existing conventions and style in order to keep the code as readable as possible. Please also make sure your code compiles by running gradlew clean build
.
License
Copyright 2016 Bradley Campbell.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.


“Adhicetaso appamajjato,
Munino monapathesu sikkhato;
Sokā na bhavanti tādino,
Upasantassa sadā satīmato”ti.
… Ekudāniyo thero ….
A sage of higher consciousness, diligent,
training in the ways to sagacity:
there are no sorrows for such a one,
calm and ever mindful.


Download ttytter (command line twitter client):
# Get recent version of ttytter (old versions fail to auth)
wget http://www.floodgap.com/software/ttytter/ttytter.txt -O /usr/local/bin/ttytter && chmod +x /usr/local/bin/ttytter
Create the following script:
1 2 3 4 5 6 7 8 9 10 |
|
Btw. it is trivial to read the currently playing title from xbmc via curl as well to adapt to whatever one watches.


This site provides applications using data that has been modified for use from its original source, ida.ussc.gov, an official website of the U.S. Sentencing Commission. The U.S. Sentencing Commission makes no claims as to the content, accuracy, timeliness, or completeness of any of the data provided at this site. The data provided at this site is subject to change at any time. It is understood that the data provided at this site is being used at one’s own risk.


{foaf:familyName}, {foaf:givenName}
Personal
Contact
Occupational
Full Name
Nick Name
Birthday
Home Address
Telephone
Work Phone
Personal Phone
Email
Work Email
Personal Email
Accounts
Online Account
Account URL:
Account Type:
Select an account type
Callimachus Account
Job Title
Department
Company
Work Address
Save
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{%extends "base.html" %} {%block title%}Conference Email - {{conference}}{%endblock%} {%block content%}
Return to registration.


You can download the specterd file from the github releases page: https://github.com/cryptoadvance/specter-desktop/releases


Create new user for VW with authentication (must be logged in as authenticated user)
Note: This API call is intended to be used in a scripted environment
Route Parameters
None.
Request Parameters
userid: VW system user id
firstname: First name of user
lastname: Last name of user
email: Email address of user
password: Password of user (unencrypted)
address1: First line of address of user
address2: Second line of address of user
city: City of user's address
state: State of user address
zipcode: Zip code of address of user
tel_voice: User's voice telephone
tel_fax: User's fax telephone
country: User's address country
Examples:
params = {'userid':'tsmith','firstname':'Ted','lastname':'Smith','email':'tsmith@gmail.com','password':'pass1_2!T','address1':'12 Rose St.','address2':'University of Idaho','city':'Boise','state':'ID','zipcode':'78543-0001','tel_voice':'202-277-3622','tel_fax':'202-277-3614','country':'USA'}
Query Parameters
None
Response
The request returns a text string -- "User created:userid"


{# widget always knows its options and data for player use. #}
{# however ginormous joined objects are elided. Use APIs to #}
{# get them if you need them (TODO: consider ways of #}
{# whitelisting them for the inline JSON attributes) #}
{# This wrapper exists for editor.js to inject contextual widget insertion controls into,
since those are area level controls rather than widget level #}
{%- if data.widget._edit and data.options.edit != false -%}
{%- include 'widgetControls.html' -%}
{%- endif -%}
{{ data.output() | safe }}


Project I'm working on:
- [Project name goes here]
- [Competiton name goes here]
- [Competiton name goes here]
Competitions I've gone to:
Experience with Programming:
[Response goes here]
What I like to do:
[Response goes here]
BHS Programming Club
[Response goes here]
[Response goes here]


Our Pre-Breach services consist of Penetration-Testing, Incident-response Preparation, Physical Security Assessments, Employees Cybersecurity Training & Complete Security Audits.

We provide Incident response in Pre and Post Breach Services consisting of Preparation, Identification, Containment, Eradication, Recovery & Lessons Learned Application, which we think are the key factors.
Our Post-Breach Services contains Data Restoration, Damage Recovery, Stopping on-going attack, Defending All Networks, Investigation of Attacks & Disable services or Real-time patch.

Training is our most focused field, It contains Testing Employee/Staff for Social Engineering, Social Engineering Causes, Types, Identification, Defences & Reporting.
Awareness is an initiative by us where we will host seminars in every school, colleges containing education regarding Social-Media Scams, Career opportunities in Cybersecurity, Social Engineering awareness & many more.

We provide Complete Threat analysis, Security check, Security ratings, Physical/Technical Penetration Report & Security Score in our Risk Assessment Service by following all "OWASP Testing Guides" standard.


Configuration of web.xml
The source file can be found at src/webapp/WEB-INF/web.xml
Various webapp parameters can be configured:
- log-access: Whether requests should be logged (if enabled, then see
logs/access-cnode1.log
)
- workflow.not-live.most-recent-version: Display most recent version if workflow is configured but page is not live
- session-timeout: Session timeout (default is 30 minutes)
- detect-mobile-per-request: Whether mobile devices should be detected per request
- mobile-devices: List of mobile devices
In order to overwrite the default settings one should copy the original file to src/webapp/WEB-INF/local.web.xml
and the Yanel build process will use this local file.


[attributes] --- label: Decisions of the Convention on Biological Diversity relevant to the WDPA layout: template-news-stories-article target_page: categories: - Technical Resources is_published: true position: 47 [file image] Bocas del Toro, Panama_evan-kirby-52282-unsplash.jpg [file hero_image] Bocas del Toro, Panama_evan-kirby-52282-unsplash.jpg [date_not_null published_date] 2019-01-01 00:00:00 UTC [categories topics] [wysiwyg content]
The following is a list of the decisions by the Conference of Parties (COP) of the Convention on Biological Diversity (CBD) relevant to the WDPA.
COP VI/28, 2004 “Invites the World Conservation Monitoring Centre of the United Nations Environment Programme, working with international organizations, to further develop the World Database on Protected Areas in order to assist the monitoring towards the overall objective of the decision on protected areas, and urges Parties, other Governments and relevant organizations to provide up-to-date information for the database." [This is further elaborated in the annexed Programme of Work on Protected Areas].
COP VIII/24, 2006 “Notes the importance of the World Database on Protected Areas as a tool to assist the monitoring of progress towards achieving the targets of the Programme of Work on Protected Areas, and invites the World Conservation Monitoring Centre of the United Nations Environment Programme, the World Commission on Protected Areas of the International Union for Conservation of Nature, and their collaborators to further develop access to the database and information management including tools for data sharing and exchange."
COP IX/18, 2008 “Encourages Parties to develop national or regional data networks in order to facilitate the exchange of, and access to information..., including providing information to the WDPA"
COP X/31, 2010 “Encourages Parties to share and update relevant information on their protected areas system with the World Database on Protected Areas"
COP X/31, 2010 “The COP... invites Parties, taking into account the target for goal 1.4 of the programme of work, which calls for all protected areas to have effective management in existence by 2012 using participatory and science-based site planning processes with full and effective participation of stakeholders, and noting that to assess the effectiveness of the management, specific indicators may also be needed to: (a) Continue to expand and institutionalize management effectiveness assessments to work towards assessing 60 per cent of the total area of protected areas by 2015 using various national and regional tools and report the results into the global database on management effectiveness maintained by the World Conservation Monitoring Centre of the United Nations Environment Programme (UNEP WCMC)"
COP X1/24, 2012 “Invites the UNEP World Conservation Monitoring Centre and its partners, including the World Commission on Protected Areas of the International Union for Conservation of Nature (IUCN), to continue to report progress towards achieving Aichi Biodiversity Target 11 and related targets through the Protected Planet Report".
COP XIII/2, 2016 “Invites the International Union for Conservation of Nature and the World Conservation Monitoring Centre to work with Parties and other Governments to update the World Database on Protected Areas and also to contribute to the assessment of progress in the implementation of Aichi Biodiversity Target 11".


publications
Hope this list never ends😊
2020
- Combined burden and functional impact tests for cancer driver discovery using DriverPowerShimin Shuai, PCAWG Drivers and Functional Interpretation Working Group, Steven Gallinger, Lincoln Stein, and PCAWG ConsortiumNature communications (2020)
The discovery of driver mutations is one of the key motivations for cancer genome sequencing. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumour types, we describe DriverPower, a software package that uses mutational burden and functional impact evidence to identify driver mutations in coding and non-coding sites within cancer whole genomes. Using a total of 1373 genomic features derived from public sources, DriverPower’s background mutation model explains up to 93% of the regional variance in the mutation rate across multiple tumour types. By incorporating functional impact scores, we are able to further increase the accuracy of driver discovery. Testing across a collection of 2583 cancer genomes from the PCAWG project, DriverPower identifies 217 coding and 95 non-coding driver candidates. Comparing to six published methods used by the PCAWG Drivers and Functional Interpretation Working Group, DriverPower has the highest F1 score for both coding and non-coding driver discovery. This demonstrates that DriverPower is an effective framework for computational driver discovery.
- NatureAnalyses of non-coding somatic drivers in 2,658 cancer whole genomesEsther Rheinbay, Morten Muhlig Nielsen, Federico Abascal, Jeremiah A Wala, Ofer Shapira, Grace Tiao, Henrik Hornshøj, Julian M Hess, Randi Istrup Juul, Ziao Lin, Lars Feuerbach, Radhakrishnan Sabarinathan, Tobias Madsen, Jaegil Kim, Loris Mularoni, Shimin Shuai, Andrés Lanzós, Carl Herrmann, Yosef E Maruvka, Ciyue Shen, Samirkumar B Amin, Pratiti Bandopadhayay, Johanna Bertl, Keith A Boroevich, John Busanovich, Joana Carlevaro-Fita, Dimple Chakravarty, Calvin Wing Yiu Chan, David Craft, Priyanka Dhingra, Klev Diamanti, Nuno A Fonseca, Abel Gonzalez-Perez, Qianyun Guo, Mark P Hamilton, Nicholas J Haradhvala, Chen Hong, Keren Isaev, Todd A Johnson, Malene Juul, Andre Kahles, Abdullah Kahraman, Youngwook Kim, Jan Komorowski, Kiran Kumar, Sushant Kumar, Donghoon Lee, Kjong-Van Lehmann, Yilong Li, Eric Minwei Liu, Lucas Lochovsky, Keunchil Park, Oriol Pich, Nicola D Roberts, Gordon Saksena, Steven E Schumacher, Nikos Sidiropoulos, Lina Sieverling, Nasa Sinnott-Armstrong, Chip Stewart, David Tamborero, Jose M C Tubio, Husen M Umer, Liis Uusküla-Reimand, Claes Wadelius, Lina Wadi, Xiaotong Yao, Cheng-Zhong Zhang, Jing Zhang, James E Haber, Asger Hobolth, Marcin Imielinski, Manolis Kellis, Michael S Lawrence, Christian Mering, Hidewaki Nakagawa, Benjamin J Raphael, Mark A Rubin, Chris Sander, Lincoln D Stein, Joshua M Stuart, Tatsuhiko Tsunoda, David A Wheeler, Rory Johnson, Jüri Reimand, Mark Gerstein, Ekta Khurana, Peter J Campbell, Núria López-Bigas, PCAWG Drivers and Functional Interpretation Working Group, PCAWG Structural Variation Working Group, Joachim Weischenfeldt, Rameen Beroukhim, Iñigo Martincorena, Jakob Skou Pedersen, Gad Getz, and PCAWG ConsortiumNature (2020)
The discovery of drivers of cancer has traditionally focused on protein-coding genes1-4. Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658 genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium5 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers6,7, raise doubts about others and identify novel candidates, including point mutations in the 5’ region of TP53, in the 3’ untranslated regions of NFKBIZ and TOB1, focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that although point mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available.
- NaturePan-cancer analysis of whole genomesICGC/TCGA Pan-Cancer Analysis of Whole Genomes ConsortiumNature (2020)
Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1-3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10-18.
- Candidate Cancer Driver Mutations in Distal Regulatory Elements and Long-Range Chromatin Interaction NetworksHelen Zhu, Liis Uusküla-Reimand, Keren Isaev, Lina Wadi, Azad Alizada, Shimin Shuai, Vincent Huang, Dike Aduluso-Nwaobasi, Marta Paczkowska, Diala Abd-Rabbo, Oliver Ocsenas, Minggao Liang, J Drew Thompson, Yao Li, Luyao Ruan, Michal Krassowski, Irakli Dzneladze, Jared T Simpson, Mathieu Lupien, Lincoln D Stein, Paul C Boutros, Michael D Wilson, and Jüri ReimandMolecular cell (2020)
A comprehensive catalog of cancer driver mutations is essential for understanding tumorigenesis and developing therapies. Exome-sequencing studies have mapped many protein-coding drivers, yet few non-coding drivers are known because genome-wide discovery is challenging. We developed a driver discovery method, ActiveDriverWGS, and analyzed 120,788 cis-regulatory modules (CRMs) across 1,844 whole tumor genomes from the ICGC-TCGA PCAWG project. We found 30 CRMs with enriched SNVs and indels (FDR < 0.05). These frequently mutated regulatory elements (FMREs) were ubiquitously active in human tissues, showed long-range chromatin interactions and mRNA abundance associations with target genes, and were enriched in motif-rewiring mutations and structural variants. Genomic deletion of one FMRE in human cells caused proliferative deficiencies and transcriptional deregulation of cancer genes CCNB1IP1, CDH1, and CDKN2B, validating observations in FMRE-mutated tumors. Pathway analysis revealed further sub-significant FMREs at cancer genes and processes, indicating an unexplored landscape of infrequent driver mutations in the non-coding genome.
- Integrative pathway enrichment analysis of multivariate omics dataMarta Paczkowska, Jonathan Barenboim, Nardnisa Sintupisut, Natalie S Fox, Helen Zhu, Diala Abd-Rabbo, Miles W Mee, Paul C Boutros, PCAWG Drivers and Functional Interpretation Working Group, Jüri Reimand, and PCAWG ConsortiumNature communications (2020)
Multi-omics datasets represent distinct aspects of the central dogma of molecular biology. Such high-dimensional molecular profiles pose challenges to data interpretation and hypothesis generation. ActivePathways is an integrative method that discovers significantly enriched pathways across multiple datasets using statistical data fusion, rationalizes contributing evidence and highlights associated genes. As part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumor types, we integrated genes with coding and non-coding mutations and revealed frequently mutated pathways and additional cancer genes with infrequent mutations. We also analyzed prognostic molecular pathways by integrating genomic and transcriptomic features of 1780 breast cancers and highlighted associations with immune response and anti-apoptotic signaling. Integration of ChIP-seq and RNA-seq data for master regulators of the Hippo pathway across normal human tissues identified processes of tissue regeneration and stem cell regulation. ActivePathways is a versatile method that improves systems-level understanding of cellular organization in health and disease through integration of multiple molecular datasets and pathway annotations.
- Pathway and network analysis of more than 2500 whole cancer genomesMatthew A Reyna, David Haan, Marta Paczkowska, Lieven P C Verbeke, Miguel Vazquez, Abdullah Kahraman, Sergio Pulido-Tamayo, Jonathan Barenboim, Lina Wadi, Priyanka Dhingra, Raunak Shrestha, Gad Getz, Michael S Lawrence, Jakob Skou Pedersen, Mark A Rubin, David A Wheeler, Søren Brunak, Jose M G Izarzugaza, Ekta Khurana, Kathleen Marchal, Christian Mering, S Cenk Sahinalp, Alfonso Valencia, PCAWG Drivers and Functional Interpretation Working Group, Jüri Reimand, Joshua M Stuart, Benjamin J Raphael, and PCAWG ConsortiumNature communications (2020)
The catalog of cancer driver mutations in protein-coding genes has greatly expanded in the past decade. However, non-coding cancer driver mutations are less well-characterized and only a handful of recurrent non-coding mutations, most notably TERT promoter mutations, have been reported. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancer across 38 tumor types, we perform multi-faceted pathway and network analyses of non-coding mutations across 2583 whole cancer genomes from 27 tumor types compiled by the ICGC/TCGA PCAWG project that was motivated by the success of pathway and network analyses in prioritizing rare mutations in protein-coding genes. While few non-coding genomic elements are recurrently mutated in this cohort, we identify 93 genes harboring non-coding mutations that cluster into several modules of interacting proteins. Among these are promoter mutations associated with reduced mRNA expression in TP53, TLE4, and TCF4. We find that biological processes had variable proportions of coding and non-coding mutations, with chromatin remodeling and proliferation pathways altered primarily by coding mutations, while developmental pathways, including Wnt and Notch, altered by both coding and non-coding mutations. RNA splicing is primarily altered by non-coding mutations in this cohort, and samples containing non-coding mutations in well-known RNA splicing factors exhibit similar gene expression signatures as samples with coding mutations in these genes. These analyses contribute a new repertoire of possible cancer genes and mechanisms that are altered by non-coding mutations and offer insights into additional cancer vulnerabilities that can be investigated for potential therapeutic treatments.
- Cancer LncRNA Census reveals evidence for deep functional conservation of long noncoding RNAs in tumorigenesisJoana Carlevaro-Fita, Andrés Lanzós, Lars Feuerbach, Chen Hong, David Mas-Ponte, Jakob Skou Pedersen, PCAWG Drivers and Functional Interpretation Group, Rory Johnson, and PCAWG ConsortiumCommunications biology (2020)
Long non-coding RNAs (lncRNAs) are a growing focus of cancer genomics studies, creating the need for a resource of lncRNAs with validated cancer roles. Furthermore, it remains debated whether mutated lncRNAs can drive tumorigenesis, and whether such functions could be conserved during evolution. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we introduce the Cancer LncRNA Census (CLC), a compilation of 122 GENCODE lncRNAs with causal roles in cancer phenotypes. In contrast to existing databases, CLC requires strong functional or genetic evidence. CLC genes are enriched amongst driver genes predicted from somatic mutations, and display characteristic genomic features. Strikingly, CLC genes are enriched for driver mutations from unbiased, genome-wide transposon-mutagenesis screens in mice. We identified 10 tumour-causing mutations in orthologues of 8 lncRNAs, including LINC-PINT and NEAT1, but not MALAT1. Thus CLC represents a dataset of high-confidence cancer lncRNAs. Mutagenesis maps are a novel means for identifying deeply-conserved roles of lncRNAs in tumorigenesis.
2019
- NatureThe U1 spliceosomal RNA is recurrently mutated in multiple cancersShimin Shuai, Hiromichi Suzuki, Ander Diaz-Navarro, Ferran Nadeu, Sachin A Kumar, Ana Gutierrez-Fernandez, Julio Delgado, Magda Pinyol, Carlos López-Otı́n, Xose S Puente, Michael D Taylor, Elı́as Campo, and Lincoln D SteinNature (2019)
Cancers are caused by genomic alterations known as drivers. Hundreds of drivers in coding genes are known but, to date, only a handful of noncoding drivers have been discovered-despite intensive searching1,2. Attention has recently shifted to the role of altered RNA splicing in cancer; driver mutations that lead to transcriptome-wide aberrant splicing have been identified in multiple types of cancer, although these mutations have only been found in protein-coding splicing factors such as splicing factor 3b subunit 1 (SF3B1)3-6. By contrast, cancer-related alterations in the noncoding component of the spliceosome-a series of small nuclear RNAs (snRNAs)-have barely been studied, owing to the combined challenges of characterizing noncoding cancer drivers and the repetitive nature of snRNA genes1,7,8. Here we report a highly recurrent A>C somatic mutation at the third base of U1 snRNA in several types of tumour. The primary function of U1 snRNA is to recognize the 5’ splice site via base-pairing. This mutation changes the preferential A-U base-pairing between U1 snRNA and the 5’ splice site to C-G base-pairing, and thus creates novel splice junctions and alters the splicing pattern of multiple genes-including known drivers of cancer. Clinically, the A>C mutation is associated with heavy alcohol use in patients with hepatocellular carcinoma, and with the aggressive subtype of chronic lymphocytic leukaemia with unmutated immunoglobulin heavy-chain variable regions. The mutation in U1 snRNA also independently confers an adverse prognosis to patients with chronic lymphocytic leukaemia. Our study demonstrates a noncoding driver in spliceosomal RNAs, reveals a mechanism of aberrant splicing in cancer and may represent a new target for treatment. Our findings also suggest that driver discovery should be extended to a wider range of genomic regions.
- NatureRecurrent noncoding U1 snRNA mutations drive cryptic splicing in SHH medulloblastomaHiromichi Suzuki, Sachin A Kumar, Shimin Shuai, Ander Diaz-Navarro, Ana Gutierrez-Fernandez, Pasqualino De Antonellis, Florence M G Cavalli, Kyle Juraschka, Hamza Farooq, Ichiyo Shibahara, Maria C Vladoiu, Jiao Zhang, Namal Abeysundara, David Przelicki, Patryk Skowron, Nicole Gauer, Betty Luu, Craig Daniels, Xiaochong Wu, Antoine Forget, Ali Momin, Jun Wang, Weifan Dong, Seung-Ki Kim, Wieslawa A Grajkowska, Anne Jouvet, Michelle Fèvre-Montange, Maria Luisa Garrè, Amulya A Nageswara Rao, Caterina Giannini, Johan M Kros, Pim J French, Nada Jabado, Ho-Keung Ng, Wai Sang Poon, Charles G Eberhart, Ian F Pollack, James M Olson, William A Weiss, Toshihiro Kumabe, Enrique López-Aguilar, Boleslaw Lach, Maura Massimino, Erwin G Van Meir, Joshua B Rubin, Rajeev Vibhakar, Lola B Chambless, Noriyuki Kijima, Almos Klekner, László Bognár, Jennifer A Chan, Claudia C Faria, Jiannis Ragoussis, Stefan M Pfister, Anna Goldenberg, Robert J Wechsler-Reya, Swneke D Bailey, Livia Garzia, A Sorana Morrissy, Marco A Marra, Xi Huang, David Malkin, Olivier Ayrault, Vijay Ramaswamy, Xose S Puente, John A Calarco, Lincoln Stein, and Michael D TaylorNature (2019)
In cancer, recurrent somatic single-nucleotide variants-which are rare in most paediatric cancers-are confined largely to protein-coding genes1-3. Here we report highly recurrent hotspot mutations (r.3A>G) of U1 spliceosomal small nuclear RNAs (snRNAs) in about 50% of Sonic hedgehog (SHH) medulloblastomas. These mutations were not present across other subgroups of medulloblastoma, and we identified these hotspot mutations in U1 snRNA in only <0.1% of 2,442 cancers, across 36 other tumour types. The mutations occur in 97% of adults (subtype SHHδ) and 25% of adolescents (subtype SHHα) with SHH medulloblastoma, but are largely absent from SHH medulloblastoma in infants. The U1 snRNA mutations occur in the 5’ splice-site binding region, and snRNA-mutant tumours have significantly disrupted RNA splicing and an excess of 5’ cryptic splicing events. Alternative splicing mediated by mutant U1 snRNA inactivates tumour-suppressor genes (PTCH1) and activates oncogenes (GLI2 and CCND2), and represents a target for therapy. These U1 snRNA mutations provide an example of highly recurrent and tissue-specific mutations of a non-protein-coding gene in cancer.
2017
- Recurrent noncoding regulatory mutations in pancreatic ductal adenocarcinomaMichael E Feigin, Tyler Garvin, Peter Bailey, Nicola Waddell, David K Chang, David R Kelley, Shimin Shuai, Steven Gallinger, John D McPherson, Sean M Grimmond, Ekta Khurana, Lincoln D Stein, Andrew V Biankin, Michael C Schatz, and David A TuvesonNature genetics (2017)
The contributions of coding mutations to tumorigenesis are relatively well known; however, little is known about somatic alterations in noncoding DNA. Here we describe GECCO (Genomic Enrichment Computational Clustering Operation) to analyze somatic noncoding alterations in 308 pancreatic ductal adenocarcinomas (PDAs) and identify commonly mutated regulatory regions. We find recurrent noncoding mutations to be enriched in PDA pathways, including axon guidance and cell adhesion, and newly identified processes, including transcription and homeobox genes. We identified mutations in protein binding sites correlating with differential expression of proximal genes and experimentally validated effects of mutations on expression. We developed an expression modulation score that quantifies the strength of gene regulation imposed by each class of regulatory elements, and found the strongest elements were most frequently mutated, suggesting a selective advantage. Our detailed single-cancer analysis of noncoding alterations identifies regulatory mutations as candidates for diagnostic and prognostic markers, and suggests new mechanisms for tumor evolution.


California's “Red Triangle” is the site of over 1/3 of great white shark attacks.
The danger zone begins around Bodega Bay and extends south about 50 miles west of San Fransisco.
The triangle juts out beyond the Farallon Islands and down to Big Sur south of Monterey.
9 attacks per year in the 1950s to 1.5 attacks per year in the last decade of the study.
In that time there were 13 recorded shark fatalities in California and only one near the San Francisco Bay.
read more