In 2014 N.J.Robinson celebrated its 50th year of supplying the fibreglass industry with quality Australian made spraying machinery. N.J.Robinson is the only Australian made spray machinery produced to date.
Neil Robinson saw a need in the Australian FRP industry to have a reliable, cost effective and simple spray machine, so he developed the Robo Mk1. It was to be a revolution to the industry for years.
Constant development and the changing needs of industry, have bred many designs of FRP Spray and Pouring gun designs to suit current trends, as well as general Fibreglass machines, N.J.Robinson has also earned a reputation as being able to design, change and adapt machinery to suit individual customer requirements.
On the back of the success in the FRP Machinery, N. J. Robinson in the 80’s branched out into plural component Epoxy, Poly Urethane, concrete etc and many very specialized machinery for Universities, Government and Defence. Robinson’s name has since become sin ominous with a safe handling, and accurate on demand mixing and dispensing of these chemicals. It has become a very large section of the Business.
N.J. Robinson has had excellent success with the overseas markets since the early 80’S with the first overseas sale to a large boat builder in Hong Kong, since that time, hundreds of machines have been sent around the world. Asia has become a major consumer for our Chopper guns and gelcoat spray equipment, due to the simplistic designs and ease of maintenance on the machines, fewer moving parts and unsurpassed reliability without the need for specialty maintenance staff.
Our network of supply agencies around Asia include Thailand, Hong Kong, Vietnam, Philippines.


DOE Datasets
U.S. Department of Energy Featured Datasets
ODE DRAFT 4/24/15
categories.json
datasets.json
View on GitHub


Purpose of the document: Describe the general functionalities of Eno.
Creation and update
| Version | Date | Contributors | Purpose of the update |
| 0.1 | 11/12/2017 | Heïdi Koumarianos | Creation |
Status: work in progress
Offer of services
Objectives: standardization, industrialization, reuse
How to get it?
How to use it?
Find more about it
Eno is a tool that generates survey questionnaires starting from their formal description, i.e. from metadata describing the questionnaire. Eno is used by Insee since 2015, to produce web questionnaires for business surveys, from their description in DDI 3.2. Nearly 15 surveys are already using Eno for their web questionnaires.
Due to its modular design, Eno can create questionnaires in different formats from the same DDI description. Currently, Eno generates XForms web questionnaires that can be executed on Orbeon Forms Runner. PDF questionnaires is under development.
The use of standard description in DDI provides structured information and consequently well structured questionnaire.
DDI description enables to identify clearly the different components of a questionnaire, such as sequences of questions, questions, instructions, different formats of response.
Common used response formats are available : simple text, number, date, single choice question, multiple choice question, grid question.
This type of questionnaire also allows us to incorporate dynamic layout : filters and questionnaire logic flow, loops, controls to check the format of the input fields, consistency between the different input fields and, where necessary, with previous collected data. Controls are emphasized by probing messages to invite respondent to correct or fulfill his response.
Labels can be customized with informations on the respondent, already known before data collection (from a register eg), as well as collected previously in the form.
Forms can be pre-filled with previously collected data as well.
The distinction between questionnaire's elements allows to show them in different ways and styles, and to create a coherent layout for questionnaires produced.
Eno is developped in an international perspective, codes and comments are in english. Data can be collected in any langage.
The development of one tool, based on standardised description in DDI leads to a standardized design. It ensures that questionnaires comply with standards and recommendations on survey design.
Display choices are shared between surveys within the NSI, improvements are available/profitable for every users at the same time.
Using a generator lightens the burden of work for the survey departments.
The generation of different data collection formats from the same questionnaire description supports unimode design for mixed mode surveys.
The questionnaire documentation can be stored and reused, in a global NSI context, or for a similar survey from year to year. Classifications are shared between different surveys teams.
Eno is a stakeholder in active metadata: the questionnaire description can be reused for dissemination or documentation of surveys.
Eno is published as open source on a GitHub repository. It is available under the MIT license, and contributions as well as suggestions for improvements are welcome.
How to use it?
Eno comes packaged in various ways: as a command-line tool, a REST web service and a Docker image.
Eno was built, tested and run on business surveys only at the moment. Future work will allow to perform significantly more surveys by providing new output formats for Eno (paper very soon) and a bigger functional coverage for household surveys (for example: more complex logic flows that can be found in household surveys).


Sign Up
  First Name
  Last Name
  Email id
Password
Gender
Male
Female
Birth Date:
Date:
1
2
Month:
January
February
Year:
1990
1991
Occupation
Student
Teacher


Example Applications for JAX-RS
This section provides an introduction to creating, deploying, and running your own JAX-RS applications. This section demonstrates the steps that are needed to create, build, deploy, and test a very simple web application that uses JAX-RS annotations.
A RESTful Web Service
This section explains how to use NetBeans IDE to create a RESTful web service. NetBeans IDE generates a skeleton for the application, and you simply need to implement the appropriate methods. If you do not use an IDE, try using one of the example applications that ship with Jersey as a template to modify.
You can find a version of this application at tut-install/examples/jaxrs/HelloWorldApplication/.
To Create a RESTful Web Service Using NetBeans IDE
- In NetBeans IDE, create a simple web application. This example creates a very
simple “Hello, World” web application.
- From the File menu, choose New Project.
- From Categories, select Java Web. From Projects, select Web Application. Click Next.
Note - For this step, you could also create a RESTful web service in a Maven web project by selecting Maven as the category and Maven Web Project as the project. The remaining steps would be the same.
- Type a project name, HelloWorldApplication, and click Next.
- Make sure that the Server is GlassFish Server (or similar wording).
- Click Finish.
The project is created. The file index.jsp appears in the Source pane.
- Right-click the project and select New; then select RESTful Web Services from Patterns.
- Select Simple Root Resource and click Next.
- Type a Resource Package name, such as helloWorld.
- Type helloworld in the Path field. Type HelloWorld in the Class Name field. For MIME Type, select text/html.
- Click Finish.
The REST Resources Configuration page appears.
- Click OK.
A new resource, HelloWorld.java, is added to the project and appears in the Source pane. This file provides a template for creating a RESTful web service.
- In HelloWorld.java, find the getHtml() method. Replace the //TODO comment and the exception
with the following text, so that the finished product resembles the following method.
Note - Because the MIME type produced is HTML, you can use HTML tags in your return statement.
/** * Retrieves representation of an instance of helloWorld.HelloWorld * @return an instance of java.lang.String */ @GET @Produces("text/html") public String getHtml() { return "
Hello, World!!
"; }
- Test the web service. To do this, right-click the project node and click
Test RESTful Web Services.
This step deploys the application and brings up a test client in the browser.
- When the test client appears, select the helloworld resource in the left pane,
and click the Test button in the right pane.
The words Hello, World!! appear in the Response window below.
- Set the Run Properties:
- Right-click the project node and select Properties.
- In the dialog, select the Run category.
- Set the Relative URL to the location of the RESTful web service relative to the Context Path, which for this example is resources/helloworld.
Tip - You can find the value for the Relative URL in the Test RESTful Web Services browser window. In the top of the right pane, after Resource, is the URL for the RESTful web service being tested. The part following the Context Path (http://localhost:8080/HelloWorldApp) is the Relative URL that needs to be entered here.
If you don’t set this property, the file index.jsp will appear by default when the application is run. As this file also contains Hello World as its default value, you might not notice that your RESTful web service isn’t running, so just be aware of this default and the need to set this property, or update index.jsp to provide a link to the RESTful web service.
- Right-click the project and select Deploy.
- Right-click the project and select Run.
A browser window opens and displays the return value of Hello, World!!
See Also
For other sample applications that demonstrate deploying and running JAX-RS applications using NetBeans IDE, see The rsvp Example Application and Your First Cup: An Introduction to the Java EE Platform at http://docs.oracle.com/javaee/6/firstcup/doc/. You may also look at the tutorials on the NetBeans IDE tutorial site, such as the one titled “Getting Started with RESTful Web Services” at http://www.netbeans.org/kb/docs/websvc/rest.html. This tutorial includes a section on creating a CRUD application from a database. Create, read, update, and delete (CRUD) are the four basic functions of persistent storage and relational databases.
The rsvp Example Application
The rsvp example application, located in the tut-install/examples/jaxrs/rsvp/ directory, allows invitees to an event to indicate whether they will attend. The events, people invited to the event, and the responses to the invite are stored in a Java DB database using the Java Persistence API. The JAX-RS resources in rsvp are exposed in a stateless session enterprise bean.
Components of the rsvp Example Application
The three enterprise beans in the rsvp example application are rsvp.ejb.ConfigBean, rsvp.ejb.StatusBean, and rsvp.ejb.ResponseBean.
ConfigBean is a singleton session bean that initializes the data in the database.
StatusBean exposes a JAX-RS resource for displaying the current status of all invitees to an event. The URI path template is declared as follows:
@Path("/status/{eventId}/")
The URI path variable eventId is a @PathParam variable in the getResponse method, which responds to HTTP GET requests and has been annotated with @GET. The eventId variable is used to look up all the current responses in the database for that particular event.
ResponseBean exposes a JAX-RS resource for setting an invitee's response to a particular event. The URI path template for ResponseBean is declared as follows:
@Path("/{eventId}/{inviteId}")
Two URI path variables are declared in the path template: eventId and inviteId. As in StatusBean, eventId is the unique ID for a particular event. Each invitee to that event has a unique ID for the invitation, and that is the inviteId. Both of these path variables are used in two JAX-RS methods in ResponseBean: getResponse and putResponse. The getResponse method responds to HTTP GET requests and displays the invitee's current response and a form to change the response.
An invitee who wants to change his or her response selects the new response and submits the form data, which is processed as an HTTP PUT request by the putResponse method. One of the parameters to the putResponse method, the userResponse string, is annotated with @FormParam("attendeeResponse"). The HTML form created by getResponse stores the changed response in the select list with an ID of attendeeResponse. The annotation @FormParam("attendeeResponse") indicates that the value of the select response is extracted from the HTTP PUT request and stored as the userResponse string. The putResponse method uses userResponse, eventId, and inviteId to update the invitee's response in the database.
The events, people, and responses in rsvp are encapsulated in Java Persistence API entities. The rsvp.entity.Event, rsvp.entity.Person, and rsvp.entity.Response entities respectively represent events, invitees, and responses to an event.
The rsvp.util.ResponseEnum class declares an enumerated type that represents all the possible response statuses an invitee may have.
Running the rsvp Example Application
Both NetBeans IDE and Ant can be used to deploy and run the rsvp example application.
To Run the rsvp Example Application in NetBeans IDE
- From the File menu, choose Open Project.
- In the Open Project dialog, navigate to:
tut-install/examples/jaxrs/
- Select the rsvp folder.
- Select the Open as Main Project check box.
- Click Open Project.
- Right-click the rsvp project in the left pane and select Run.
The project will be compiled, assembled, and deployed to GlassFish Server. A web browser window will open to http://localhost:8080/rsvp.
- In the web browser window, click the Event Status link for the Duke’s
Birthday event.
You’ll see the current invitees and their responses.
- Click on the name of one of the invitees, select a response,
and click Submit response; then click Back to event page.
The invitee’s new status should now be displayed in the table of invitees and their response statuses.
To Run the rsvp Example Application Using Ant
Before You Begin
You must have started the Java DB database before running rsvp.
- In a terminal window, go to:
tut-install/examples/jaxrs/rsvp/
- Type the following command:
ant all
This command builds, assembles, and deploys rsvp to GlassFish Server.
- Open a web browser window to http://localhost:8080/rsvp.
- In the web browser window, click the Event Status link for the Duke’s
Birthday event.
You’ll see the current invitees and their responses.
- Click on the name of one of the invitees, select a response,
and click Submit response, then click Back to event page.
The invitee’s new status should now be displayed in the table of invitees and their response statuses.
Real-World Examples
Most blog sites use RESTful web services. These sites involve downloading XML files, in RSS or Atom format, that contain lists of links to other resources. Other web sites and web applications that use REST-like developer interfaces to data include Twitter and Amazon S3 (Simple Storage Service). With Amazon S3, buckets and objects can be created, listed, and retrieved using either a REST-style HTTP interface or a SOAP interface. The examples that ship with Jersey include a storage service example with a RESTful interface. The tutorial at http://netbeans.org/kb/docs/websvc/twitter-swing.html uses NetBeans IDE to create a simple, graphical, REST-based client that displays Twitter public timeline messages and lets you view and update your Twitter status.


West Brom transfers: Three players linked with Albion ahead of January transfer window
Latest West Bromwich Albion transfer rumours | We take a look at the players who have been tipped to make a move to The Hawthorns in the new year
by Alex Dicken, https://www.facebook.com/alexdickenjournalist/?fref=ts, Chris Watson, Mark WakefieldThe 2020 January transfer window is just around the corner, and West Bromwich Albion look to be in a good place going into the New Year.
The Baggies are currently top of the Sky Bet Championship table, as they and the rest of the teams in the league enjoy a break thanks to the last round of internationals in the calendar year.
Slaven Bilic can feel pleased with the start he has made as Albion boss, but he, like most managers in the country, will also have one eye on the upcoming transfer window.
Could we see Albion dip into the transfer market and strengthen their squad to help secure a promotion push in the second half of the season?
That will no doubt change between now and January as Bilic, along with technical director Luke Dowling, irons out the areas he believes need strengthening.
Here are the players who have been linked with Albion so far...
West Brom latest
This is your round up of all things West Brom; the one-stop shop that will keep you updated on the latest goings on at the club and beyond.
Transfers, injuries, match-days and managers, we’ve got you covered.
We’ll be bringing the very latest on the Baggies throughout the week and around the clock.
Make sure you keep yourself updated with our handy daily catch up...
Must reads...
- Garry Monk can't believe Sheffield Wednesday lost to West Brom
- 'Not since February 23' - Albion roll on as Bilic faces dilemma
- 'I spoke to him' - Every word from Bilic after Baggies stay above Leeds
- Here's how Ahmed Hegazi played on his West Brom comeback
- Things you might have missed as West Brom marched on
- Player ratings as Baggies keep title push rolling
For all your latest WBA news, opinion, analysis and transfer gossip, click here
You can follow our West Brom reporter Joseph Chapman on Twitter, and his email address is<EMAIL_ADDRESS>Dwight Gayle
The Baggies continue to be linked with Newcastle United striker Dwight Gayle and are tipped to re-sign him in January.
Gayle's future is set to be decided in January and Albion are keen to re-sign the striker after his successful loan spell at The Hawthorns last season.
Gayle scored 24 goals in 42 Championship matches for the Baggies as they missed out on promotion to the Premier League.
Reports recently have suggested Albion made a play to sign Gayle on loan at the end of the summer transfer window but the striker would prefer a permanent transfer.
Ronald Sobowale
West Brom have been credited with an interest in young forward Ronald Sobowale - the cousin of Bayern Munich and Austria star David Alaba.
Sobowale, 22, was originally in the Chelsea academy, but was released at the age of 15 having lined up alongside the likes of Tammy Abraham and Dominic Solanke.
Trials with Cardiff City, Barnsley and Brentford wouldn’t bear any fruit.
In the meantime, Londoner Sobowale has been tearing it up in non-league to attract interest from the upper reaches of the English football ladder once more.
The Whyteleafe striker has also been on trial with Albion’s Championship rivals Middlesbrough, but Premier League pair Leicester City and Watford - as well as Fulham - are all monitoring him, according to the Daily Mail.
poll loading
Who has been your West Brom player of the season so far?
2000+ VOTES SO FAR
Romaine Sawyers Kyle Bartley Jake Livermore Matt Phillips Grady Diangana Matheus Pereira Semi Ajayi Darnell Furlong Hal Robson-Kanu Sam Johnstone Charlie Austin Kyle Edwards Nathan Ferguson Filip Krovinovic Kenneth Zohore Kieran Gibbs
Sam McCallum
Coventry City's 19-year-old full-back Sam McCallum is another player to have been linked with West Brom.
Young defender McCallum, who has recently turned 19, enjoyed a breakthrough into the Sky Blues first team last season but has featured more regularly from the off under Robins this term.
He signed a new contract in March which runs until the summer of 2022, but clubs in divisions above Coventry are already supposedly circling - including Albion.
Sky Blues boss Mark Robins insists McCallum won't be sold on the cheap though. He told CoventryLive: “There’s no interest or appetite to sell and I wouldn’t think it would be beneficial for him to go anywhere at this stage."


Usage:
DICOMClient [ -h ] [ -c ] [ -P patient_id ] [ -o output_file ] [ -3 ] [ -z ] [ -g ] inFile1 inFile2 ...
-h Show this help and then exit (without GUI)
-c Run in command line mode (without GUI)
-P Specify new patient ID for anonymization
-o Specify output file for anonymization (single file only, command line only)
-d Specify output directory for anonymization (can not be used with -o option)
-y Truncate all dates to just the year, eg: 19670225 -> 19670101
-3 Restrict generated XML to 32 character tag names, as required by the SAS software package
-t Show attribute tag details in text dump (effective in command line mode only)
-l preload.xml Preload UIDs for anonymization. This allows anonymizing to take place over multiple sessions.
-z Replace each control character in generated XML files that describe DICOM attributes with a blank. Required by SAS
-g Perform aggressive anonymization - anonymize fields that are not marked for
anonymization but contain strings found in fields that are marked for anonymization.


Files CCore/inc/gadget/MetaList.h CCore/src/gadget/MetaList.cpp
The namespace Meta contains a collection of meta-tools widely-used in CCore. They are enclosed in the namespace Meta. This particular file provides tools to work with type lists.
template <class T>
using EraseType = int ;
EraseType is a Meta-type. It maps any type to the type int.
template <int ... IList> struct IndexListBox;
IndexListBox is used to "box" a list of integer indexes.
template <int Base,class ... TT>
using IndexList = .... ;
IndexList<Base,T1,...,Tn> == IndexListBox<Base,Base+1,...,Base+n-1>
IndexListBox is a Meta-type. It creates a box of indexes IndexListBox<i,i+1,...,i+n-1>. The first index is Base, the length of the list is the length of the type list TT.
template <> struct TypeListBox<> { using Type = TypeListBox<> ; template <class ... SS> using Extend = TypeListBox<SS...> ; }; template <class T,class ... TT> struct TypeListBox<T,TT...> { using Type = TypeListBox<T,TT...> ; using FirstType = T ; template <class ... SS> using Extend = TypeListBox<T,TT...,SS...> ; }; TypeListBox<T1,...,Tn>::Extend<S1,...,Sm> == TypeListBox<T1,...,Tn,S1,...,Sm>
TypeListBox is another "box" type for a list of types. This box has three inner values:
Type is the self type.
FirstType is the first type of the list, if the list is not empty, otherwise it is not defined.
Extend is a Meta-function. This function extends the box by the provided list of types.
template <class Box1,class Box2>
using JoinTypeList = .... ;
JoinTypeList< TypeListBox<T1,...,Tn> , TypeListBox<S1,...,Sm> > == TypeListBox<T1,...,Tn,S1,...,Sm>
JoinTypeList is a Meta-type. It joins two type list boxes.
template <unsigned Index,class ... TT> requires ( Index <= sizeof ... (TT) ) struct SplitTypeList { using First = .... ; using Last = .... ; }; template <unsigned Index,class ... TT> struct SplitTypeListBox<Index,TypeListBox<TT...> > : SplitTypeList<Index,TT...> {}; SplitTypeList<Index,T0,...,Tn-1>::First == TypeListBox<T0,...,TIndex-1> SplitTypeList<Index,T0,...,Tn-1>::Last == TypeListBox<TIndex,...,Tn-1>
SplitTypeList splits the given type list on two parts. SplitTypeListBox uses a type list box as the argument.
template <unsigned Len,class ... TT> requires ( Len <= sizeof ... (TT) )
using PrefixTypeList = typename SplitTypeList<Len,TT...>::First ;
PrefixTypeList<Len,T0,...,Tn-1> == TypeListBox<T0,...,TLen-1>
PrefixTypeList is a Meta-type. It creates a prefix of the given type list with the given length.
template <unsigned Off,class ... TT> requires ( Off <= sizeof ... (TT) )
using PartTypeList = typename SplitTypeList<Off,TT...>::Last ;
PartTypeList<Off,T0,...,Tn-1> == TypeListBox<TOff,...,Tn-1>
PartTypeList is a Meta-type. It creates a suffix of the given type list from the given offset.
template <unsigned Off,unsigned Len,class ... TT> requires ( Off+Len <= sizeof ... (TT) )
using TypeSubList = typename SplitTypeListBox<Len,PartTypeList<Off,TT...> >::First ;
PartTypeList<Off,Len,T0,...,Tn-1> == TypeListBox<TOff,...,TOff+Len-1>
TypeSubList is a Meta-type. It creates a part of the given type list from the given offset and with the given length.
template <unsigned Index,class ... TT> requires ( Index < sizeof ... (TT) )
using SelectList = typename SplitTypeList<Index,TT...>::Last::FirstType ;
SelectList<Index,T0,...,Tn-1> == TIndex
SelectList is a Meta-type. It selects a type with the given index from the type list.
template <class T,class ... TT>
inline constexpr unsigned IndexOf = .... ;
IndexOf is a Meta-constant. It equals the 1-based index of the type T in the following type list TT.
template <class ... TT> requires ( sizeof ... (TT) > 0 )
struct PopTypeList
{
using Split = SplitTypeList<( sizeof ... (TT) - 1 ),TT...> ;
using Start = typename Split::First ;
using Last = typename Split::Last::FirstType ;
};
PopTypeList<T0,...,Tn-1>::Start == TypeListBox<T0,...,Tn-2>
PopTypeList<T0,...,Tn-1>::Last == Tn-1
PopTypeList is a Meta-function. Being applied to a non-empty type list it returns two values: Start is the length minus one prefix, and Last is the last type of the list.


This checks whether or not we're in one of the following positions:
for (KEY in right); for (KEY;;);
This is because these spots allow VariableDeclarations AND normal expressions so we need to tell the path replacement that it's ok to replace this with an expression.
This checks whether we are swapping an arrow function's body between an expression and a block statement (or vice versa).
This is because arrow functions may implicitly return an expression, which is the same as containing a block statement.
Check whether the path node key
strict equals value
.
Walk the input node
and statically evaluate it.
Returns an object in the form { confident, value }
. confident
indicates
whether or not we had to drop out of evaluating the expression because of
hitting an unknown node that we couldn't confidently find the value of.
Example:
t.evaluate(parse("5 + 5")) // { confident: true, value: 10 } t.evaluate(parse("!true")) // { confident: true, value: false } t.evaluate(parse("foo + foo")) // { confident: false, value: undefined }
Walk the input node
and statically evaluate if it's truthy.
Returning true
when we're sure that the expression will evaluate to a
truthy value, false
if we're sure that it will evaluate to a falsy
value and undefined
if we aren't sure. Because of this please do not
rely on coercion when using this method and check with === if it's false.
Build an array of node paths containing the entire ancestry of the current node path.
NOTE: The current node path is included in this.
Get the parent function of the current path.
Get the source code associated with this node.
Walk up the tree until we hit a parent node path in a list.
Infer the type of the current NodePath
.
Check whether we have the input key
. If the key
references an array then we check
if the array has any items, otherwise we just check if it's falsy.
Hoist the current node to the highest scope possible and return a UID referencing it.
Alias of has
.
Check whether the current path references a completion record
Check the type against our stored internal type of the node. This is handy when a node has been removed yet we still internally know the type and need it to calculate node replacement.
Check whether or not the current key
allows either a single statement or block statement
so we can explode it if necessary.
Opposite of has
.
Match the current node if it matches the provided pattern
.
For example, given the match React.createClass
it would match the
parsed nodes of React.createClass
and React["createClass"]
.
Check if the currently assigned path references the importName
of moduleSource
.
Replace a node with an array of multiple. This method performs the following steps:
Parse a string as an expression and replace the current node with the result.
NOTE: This is typically not a good idea to use. Building source strings when transforming ASTs is an antipattern and SHOULD NOT be encouraged. Even if it's easier to use, your transforms will be extremely brittle.
Share comments amongst siblings.
Update all sibling node paths after fromIndex
by incrementBy
.
Check if the current path will maybe execute before another path
Generated using TypeDoc
Give node
comments
of the specifiedtype
.


Tech Comic
22 Feb 2018 © https://medium.freecodecamp.org/coding-explained-in-25-profound-comics-8847ea03819c


Those people who have built an LFS system may be aware of the general principles of downloading and unpacking software. Some of that information is repeated here for those new to building their own software.
Each set of installation instructions contains a URL from which you can download the package. The patches; however, are stored on the LFS servers and are available via HTTP. These are referenced as needed in the installation instructions.
While you can keep the source files anywhere you like, we assume that you have unpacked the package and changed into the directory created by the unpacking process (the 'build' directory). We also assume you have uncompressed any required patches and they are in the directory immediately above the 'build' directory.
We can not emphasize strongly enough that you should start from a
clean source tree each time.
This means that if you have had an error during configuration or
compilation, it's usually best to delete the source tree and
re-unpack it before trying
again. This obviously doesn't apply if you're an advanced user used
to hacking Makefile
s and C code, but if
in doubt, start from a clean tree.
The golden rule of Unix System Administration is to use your
superpowers only when necessary. Hence, BLFS recommends that you
build software as an unprivileged user and only become the
root
user when installing the
software. This philosophy is followed in all the packages in this
book. Unless otherwise specified, all instructions should be
executed as an unprivileged user. The book will advise you on
instructions that need root
privileges.
If a file is in .tar
format and
compressed, it is unpacked by running one of the following
commands:
tar -xvf filename.tar.gz tar -xvf filename.tgz tar -xvf filename.tar.Z tar -xvf filename.tar.bz2
You may omit using the v
parameter in
the commands shown above and below if you wish to suppress the
verbose listing of all the files in the archive as they are
extracted. This can help speed up the extraction as well as make
any errors produced during the extraction more obvious to you.
You can also use a slightly different method:
bzcat filename.tar.bz2 | tar -xv
Finally, you sometimes need to be able to unpack patches which are
generally not in .tar
format. The
best way to do this is to copy the patch file to the parent of the
'build' directory and then run one of the following commands
depending on whether the file is a .gz
or .bz2
file:
gunzip -v patchname.gz bunzip2 -v patchname.bz2
Generally, to verify that the downloaded file is genuine and
complete, many package maintainers also distribute md5sums of the
files. To verify the md5sum of the downloaded files, download both
the file and the corresponding md5sum file to the same directory
(preferably from different on-line locations), and (assuming
file.md5sum
is the md5sum file
downloaded) run the following command:
md5sum -c file.md5sum
If there are any errors, they will be reported. Note that the BLFS
book includes md5sums for all the source files also. To use the
BLFS supplied md5sums, you can create a file.md5sum
(place the md5sum data and the exact
name of the downloaded file on the same line of a file, separated
by white space) and run the command shown above. Alternately,
simply run the command shown below and compare the output to the
md5sum data shown in the BLFS book.
md5sum <name_of_downloaded_file>
For larger packages, it is convenient to create log files instead
of staring at the screen hoping to catch a particular error or
warning. Log files are also useful for debugging and keeping
records. The following command allows you to create an installation
log. Replace <command>
with the command
you intend to execute.
( <command>
2>&1 | tee compile.log && exit $PIPESTATUS )
2>&1
redirects error messages to
the same location as standard output. The tee command allows viewing of the
output while logging the results to a file. The parentheses around
the command run the entire command in a subshell and finally the
exit $PIPESTATUS
command ensures the result of the <command>
is returned as the
result and not the result of the tee command.
There are times when automating the building of a package can come
in handy. Everyone has their own reasons for wanting to automate
building, and everyone goes about it in their own way. Creating
Makefile
s, Bash scripts, Perl scripts or simply a list of commands used
to cut and paste are just some of the methods you can use to
automate building BLFS packages. Detailing how and providing
examples of the many ways you can automate the building of packages
is beyond the scope of this section. This section will expose you
to using file redirection and the yes command to help provide ideas
on how to automate your builds.
You will find times throughout your BLFS journey when you will come across a package that has a command prompting you for information. This information might be configuration details, a directory path, or a response to a license agreement. This can present a challenge to automate the building of that package. Occasionally, you will be prompted for different information in a series of questions. One method to automate this type of scenario requires putting the desired responses in a file and using redirection so that the program uses the data in the file as the answers to the questions.
Building the CUPS package is a good example of how redirecting a file as input to prompts can help you automate the build. If you run the test suite, you are asked to respond to a series of questions regarding the type of test to run and if you have any auxiliary programs the test can use. You can create a file with your responses, one response per line, and use a command similar to the one shown below to automate running the test suite:
make check < ../cups-1.1.23-testsuite_parms
This effectively makes the test suite use the responses in the file as the input to the questions. Occasionally you may end up doing a bit of trial and error determining the exact format of your input file for some things, but once figured out and documented you can use this to automate building the package.
Sometimes you will only need to provide one response, or provide the same response to many prompts. For these instances, the yes command works really well. The yes command can be used to provide a response (the same one) to one or more instances of questions. It can be used to simulate pressing just the Enter key, entering the Y key or entering a string of text. Perhaps the easiest way to show its use is in an example.
First, create a short Bash script by entering the following commands:
cat > blfs-yes-test1 << "EOF"
#!/bin/bash
echo -n -e "\n\nPlease type something (or nothing) and press Enter ---> "
read A_STRING
if test "$A_STRING" = ""; then A_STRING="Just the Enter key was pressed"
else A_STRING="You entered '$A_STRING'"
fi
echo -e "\n\n$A_STRING\n\n"
EOF
chmod 755 blfs-yes-test1
Now run the script by issuing ./blfs-yes-test1 from the command line. It will wait for a response, which can be anything (or nothing) followed by the Enter key. After entering something, the result will be echoed to the screen. Now use the yes command to automate the entering of a response:
yes | ./blfs-yes-test1
Notice that piping yes by itself to the script results in y being passed to the script. Now try it with a string of text:
yes 'This is some text' | ./blfs-yes-test1
The exact string was used as the response to the script. Finally, try it using an empty (null) string:
yes '' | ./blfs-yes-test1
Notice this results in passing just the press of the Enter key to the script. This is useful for times when the default answer to the prompt is sufficient. This syntax is used in the Net-tools instructions to accept all the defaults to the many prompts during the configuration step. You may now remove the test script, if desired.
In order to automate the building of some packages, especially those that require you to read a license agreement one page at a time, requires using a method that avoids having to press a key to display each page. Redirecting the output to a file can be used in these instances to assist with the automation. The previous section on this page touched on creating log files of the build output. The redirection method shown there used the tee command to redirect output to a file while also displaying the output to the screen. Here, the output will only be sent to a file.
Again, the easiest way to demonstrate the technique is to show an example. First, issue the command:
ls -l /usr/bin | more
Of course, you'll be required to view the output one page at a time
because the more
filter was used. Now try the same command, but this time redirect
the output to a file. The special file /dev/null
can be used instead of the filename
shown, but you will have no log file to examine:
ls -l /usr/bin | more > redirect_test.log 2>&1
Notice that this time the command immediately returned to the shell prompt without having to page through the output. You may now remove the log file.
The last example will use the yes command in combination with output redirection to bypass having to page through the output and then provide a y to a prompt. This technique could be used in instances when otherwise you would have to page through the output of a file (such as a license agreement) and then answer the question of “do you accept the above?”. For this example, another short Bash script is required:
cat > blfs-yes-test2 << "EOF"
#!/bin/bash
ls -l /usr/bin | more
echo -n -e "\n\nDid you enjoy reading this? (y,n) "
read A_STRING
if test "$A_STRING" = "y"; then A_STRING="You entered the 'y' key"
else A_STRING="You did NOT enter the 'y' key"
fi
echo -e "\n\n$A_STRING\n\n"
EOF
chmod 755 blfs-yes-test2
This script can be used to simulate a program that requires you to read a license agreement, then respond appropriately to accept the agreement before the program will install anything. First, run the script without any automation techniques by issuing ./blfs-yes-test2.
Now issue the following command which uses two automation techniques, making it suitable for use in an automated build script:
yes | ./blfs-yes-test2 > blfs-yes-test2.log 2>&1
If desired, issue tail blfs-yes-test2.log to see the end of the paged output, and confirmation that y was passed through to the script. Once satisfied that it works as it should, you may remove the script and log file.
Finally, keep in mind that there are many ways to automate and/or script the build commands. There is not a single “correct” way to do it. Your imagination is the only limit.
For each package described, BLFS lists the known dependencies. These are listed under several headings, whose meaning is as follows:
Required means that the target package cannot be correctly built without the dependency having first been installed.
Recommended means that BLFS strongly suggests this package is installed first for a clean and trouble-free build, that won't have issues either during the build process, or at run-time. The instructions in the book assume these packages are installed. Some changes or workarounds may be required if these packages are not installed.
Optional means that this package might be installed for added functionality. Often BLFS will describe the dependency to explain the added functionality that will result.
On occasion you may run into a situation in the book when a package will not build or work properly. Though the Editors attempt to ensure that every package in the book builds and works properly, sometimes a package has been overlooked or was not tested with this particular version of BLFS.
If you discover that a package will not build or work properly, you should see if there is a more current version of the package. Typically this means you go to the maintainer's web site and download the most current tarball and attempt to build the package. If you cannot determine the maintainer's web site by looking at the download URLs, use Google and query the package's name. For example, in the Google search bar type: 'package_name download' (omit the quotes) or something similar. Sometimes typing: 'package_name home page' will result in you finding the maintainer's web site.
In LFS, stripping of debugging symbols was discussed a couple of times. When building BLFS packages, there are generally no special instructions that discuss stripping again. It is probably not a good idea to strip an executable or a library while it is in use, so exiting any windowing environment is a good idea. Then you can do:
find /{,usr/}{bin,lib,sbin} -type f -exec strip --strip-unneeded {} \;
If you install programs in other directories such as /opt or /usr/local, you may want to strip the files there too.
For more information on stripping, see http://www.technovelty.org/linux/stripping-shared-libraries.html.
One of the side effects of packages that use Autotools, including libtool, is that they create many files with an .la extension. These files are not needed in an LFS environment. If there are conflicts with pkgconfig entries, they can actually prevent successful builds. You may want to consider removing these files periodically:
find /lib /usr/lib -not -path "*Image*" -a -name \*.la -delete
The above command removes all .la files with the exception of those that have "Image" as a part of the path. These .la files are used by the ImageMagick programs. There may be other exceptions by packages not in BLFS.
Last updated on 2014-08-24 10:00:46 -0700


| SIGPROCMASK(2) | Linux Programmer's Manual | SIGPROCMASK(2) |
/* Prototype for the glibc wrapper function */ int sigprocmask(int how, const sigset_t *set, sigset_t *oldset);
/* Prototype for the underlying system call */ int rt_sigprocmask(int how, const kernel_sigset_t *set, kernel_sigset_t *oldset, size_t sigsetsize);
/* Prototype for the legacy system call (deprecated) */ int sigprocmask(int how, const old_kernel_sigset_t *set, old_kernel_sigset_t *oldset);
Feature Test Macro Requirements for glibc (see feature_test_macros(7)):
sigprocmask(): _POSIX_C_SOURCE
The behavior of the call is dependent on the value of how, as follows.
If oldset is non-NULL, the previous value of the signal mask is stored in oldset.
If set is NULL, then the signal mask is unchanged (i.e., how is ignored), but the current value of the signal mask is nevertheless returned in oldset (if it is not NULL).
A set of functions for modifying and inspecting variables of type sigset_t ("signal sets") is described in sigsetops(3).
The use of sigprocmask() is unspecified in a multithreaded process; see pthread_sigmask(3).
Each of the threads in a process has its own signal mask.
A child created via fork(2) inherits a copy of its parent's signal mask; the signal mask is preserved across execve(2).
If SIGBUS, SIGFPE, SIGILL, or SIGSEGV are generated while they are blocked, the result is undefined, unless the signal was generated by kill(2), sigqueue(3), or raise(3).
See sigsetops(3) for details on manipulating signal sets.
Note that it is permissible (although not very useful) to specify both set and oldset as NULL.
The glibc wrapper function for sigprocmask() silently ignores attempts to block the two real-time signals that are used internally by the NPTL threading implementation. See nptl(7) for details.
The original Linux system call was named sigprocmask(). However, with the addition of real-time signals in Linux 2.2, the fixed-size, 32-bit sigset_t (referred to as old_kernel_sigset_t in this manual page) type supported by that system call was no longer fit for purpose. Consequently, a new system call, rt_sigprocmask(), was added to support an enlarged sigset_t type (referred to as kernel_sigset_t in this manual page). The new system call takes a fourth argument, size_t sigsetsize, which specifies the size in bytes of the signal sets in set and oldset. This argument is currently required to have a fixed architecture specific value (equal to sizeof(kernel_sigset_t)).
The glibc sigprocmask() wrapper function hides these details from us, transparently calling rt_sigprocmask() when the kernel provides it.
| 2017-09-15 | Linux |


Upcoming Trips
Send something on cheap rates. Use Daqya to find a messenger and send your parcel safely using our premium escrow service.
Send something on cheap rates. Use Daqya to find a messenger and send your parcel safely using our premium escrow service.


[
next
] [
prev
] [
prev-tail
] [
tail
] [
up
]
9
Magnetic surface averaging
9.1
Deﬁnition
9.2
Flux Surface Functions
[
next
] [
prev
] [
prev-tail
] [
front
] [
up
]


Logout
Track on Map
Search Patients
Filter Options
NIC
Contact Number
Patient ID
Search
Patient Infomation
NIC Number
Name
Age
Gender
Hometown
Contact Number


[gecode-users] Number of propagators
Mikael Zayenz Lagerkvist
zayenz at gmail.com
Wed May 24 11:03:45 CEST 2006
Just for completeness, committing a space to an alternative without
giving a branching-description will compute a fixpoint first before
doing the branching.
Cheers
Mikael
On 5/24/06, Christian Schulte <schulte at imit.kth.se> wrote:
> Actually, you are right: only propagators are considered. There is am major
> difference though compared to Oz in when stability is achieved: Only clone
> and status make a space stable, commit in particular does not compute a
> fixpoint (this is in order to support batch recomputation). So while
> propagation in Oz is eager, it is lazy in Gecode.
>
> Cheers
> Christian
>
> --
> Christian Schulte, http://www.imit.kth.se/~schulte/
>
> -----Original Message-----
> From: gustavo.ggutierrez at gmail.com [mailto:gustavo.ggutierrez at gmail.com] On
> Behalf Of Gustavo Gutierrez
> Sent: Tuesday, May 23, 2006 11:08 PM
> To: schulte at imit.kth.se
> Cc: users at gecode.org
> Subject: Re: [gecode-users] Number of propagators
>
>
> Hi Christian,
>
> First of all thanks for the answer and the addition.
>
> On 5/23/06, Christian Schulte <schulte at imit.kth.se> wrote:
> > I just added two functions propagators() and branchings() to the trunk
> > version that return the desired information but only if the space is
> > stable.
>
> I have a question about space stability and gecode. AFAIK, from mozart and
> your PhD thesis, a space is stable when there are no threads/propagators
> running. In the gecode case there are no threads but only propagators
> (right?), so a space becomes stable after performing propagation in it (i.e
> by calling the status method)? or are there others situations when this can
> happen?
>
>
> Thanks in advance,
>
> --
> Gustavo Gutierrez
>
>
> _______________________________________________
> Gecode users mailing list
> users at gecode.org
> https://www.gecode.org/mailman/listinfo/gecode-users
>
--
Mikael Zayenz Lagerkvist, http://www.ict.kth.se/~zayenz/
More information about the gecode-users
mailing list


Welcome to my single-page application demo, built with:
This demo is a simple web app to manage items you have at home and with who you have shared them. It is also to show you how to integrate entities managed by the LSG.GenericCrud with a frontend application. This sample include these entities:
| Entity type | Controller type | Implementation type | DTO |
|---|---|---|---|
| Contact | CrudController | Implemented | No |
| Item | CrudController | Implemented | Yes |
| Share | HistoricalCrudController | CustomService | No |
| Contributor | CrudController | Inherited | No |
| User | HistoricalCrudController | Inherited | Yes |
| BlogPost | HistoricalCrudController | Implemented | Yes |


Mastovoyeur
Public
local
federated
timeline of https://
Load newest statuses
time
account
content
Load more
Following discussion
time
account
content
Go back to timeline


Grand challenges in single-cell data science
Table of Contents
Introduction
Lähnemann et al. 2020 list 11 “grand challenges” in single cell data science. On first reading, the list of challenges struck me as reviewing areas where researchers have already made the fundamental contributions, rather than areas where fundamental contributions remain to be made. Here, I revisit the paper more carefully to try and identify areas where fundamental contributions could be made.
Recurring challenges
Varying levels of resolution. The discussion in this section is initially motivated by the problem of unsupervised learning of clusters in the context of scRNA-seq data, although the overarching questions are more general. The overarching questions (which remain unstated explicitly, but implicitly motivate which considerations are deemed “important”) are: (1) how can we identify subsets of cells that make sense to treat as coherent units, (2) how can we choose the “resolution” (degree of coherence on the axis of interest versus degree of heterogeneity elsewhere) for a particular scientific question of interest, and (3) how do we build representations of the data that facilitate extracting coherent subsets of cells at the desired resolution?
The highlighted example of PAGA (Wolf et al. 2019) is illustrative of the assumptions that went into the framing of the problem. The example suggests that the challenge should be addressed by building monolithic, hierarchical representations that capture multiple levels of resolution at once, such that exploratory analysis becomes trivial. However, other methods such as HSNE (Pezotti et al. 2016) or topic models (Dey et al. 2017, González-Blas et al. 2019) require a different approach, where higher resolution representations require both a human in the loop, and potentially substantial extra computation.
Building monolithic, hierarchical representations requires developing new statistical models with (likely) complicated inference algorithms. It is not immediately obvious whether such representations would be useful outside of biology, and if so in what way. In contrast, building high quality, efficient software implementations of relatively simple methods could be a much more feasible strategy to make exploratory data analysis at multiple levels of resolution easier. There are two potential objections to the latter strategy: (1) it allows researcher degrees of freedom (Gelman and Loken 2013), and (2) it is difficult to assess uncertainty in the estimated hierarchy. These can be countered by the fact that the methods are used for exploratory data analysis, not confirmatory data analysis (Tukey 1977), and that in many cases the estimated representations and hierarchies can be confirmed by external, independent data.
Quantifying uncertainty of measurements and analysis results. There are two issues: (1) the measurement noise in single cell assays is increased compared to bulk assays, making certain analyses harder/impossible; (2) common analyses have uncertainties that are often not propagated through typical analysis pipelines. The first issue is not properly appreciated in the field, but unfortunately, likely cannot be addressed through clever computation. For example, accurately estimating gene expression variance from scRNA-seq data appears generally not possible.
The second issue initially appears more difficult. What does a typical analysis pipeline actually do? (1) filter e.g., low quality cells, and uninformative genes, (2) estimate a low rank representation, which induces a visualization and a clustering, (3) identify genes that are informative about the clusters.
The robustness of downstream results to filtering choices is not systematically studied. However, one obvious area that does not appear to be adequately explored is using existing statistical methods for black box function optimization (e.g., Snoek et al. 2012, Li et al. 2017) in this setting, using metrics such as the Adjusted Rand index of the cluster labels, the hold-out prediction accuracy of cluster labels from gene expression, or the correlation of cluster “centroids” to known/previously identified cell types as the optimization criterion. (It is possible that some groups have tried these approaches and found they did not work well.)
Commonly used representations such as PCA have statistical models underlying them (e.g., Tipping and Bishop 1999), which could in principle be used to produce uncertainty in the representation. It is clear the propagating that uncertainty of certain methods is very difficult, especially when those methods do not have an explicit statistical model underlying them. However, propagating uncertainty is easy in generative models that simultaneously estimate low-dimensional representations and high-dimensional parameters of interest (e.g., differential expression analysis in a variational auto-encoder, as in Lopez et al. 2018). The drawback of such approaches is that they require either more complex inference algorithms, require solving more difficult optimization problems, or require more work to interpret the results.
Identifying genes that are informative about cluster labels while quantifying uncertainty in the identified genes is a variable selection problem, which is well-studied (e.g., Wang et al. 2020).
Scaling to higher dimensionalities: more cells, more features, and broader coverage. There are two fundamental questions: (1) do the software implementations of common models/methods run with reasonable computational budgets on time/space, and (2) do the models/methods support multiple types of measurements (either simultaneously on the same samples or not)?
The first issue requires concentrated effort in software engineering, as opposed to effort in new experimental protocols, data generation, statistical models, or likely even in inference algorithms. This area is one in which there are few major players (Seurat, scanpy), but they have the majority of resources, attention, adoption, and traction. The second issue requires the development of novel, linked statistical models in the case of simultaneous measurements, which in turn likely requires specialized software implementations. Further, there may be fundamental statistical problems in the case of “integrating” non-simultaneous measurements, in the form of un-correctable biases due to systematic technical differences between experiments.
Challenges in single-cell transcriptomics
Handling sparsity in single-cell RNA sequencing. This discussion is moot (Sarkar and Stephens 2020). “Dropouts” are not a problem, “imputation” does not make sense, and sparsity is a problem only for (space and time) efficient, robust software implementations. The only open research question here is whether denoising is just an interesting side-effect of fitting generative models for statistical tasks of true interest, or whether denoised estimates of true gene expression can be substituted for the data matrix in a modular approach for those tasks. There is some indication that for visualization, at least, there is interest in the denoised gene expression levels (e.g., Alquira-Hernandez and Powell 2021).
Defining flexible statistical frameworks for discovering complex differential patterns in gene expression. In what sense are current DE frameworks “inflexible”? The paper suggests two senses: (1) DE needs fixed assignments of samples to conditions, and (2) DE only considers mean shifts. The first issue matters only when the assignments come from some clustering algorithm, which generally has an uncertainty that is not computed. This issue could be easily resolved by a model-based clustering algorithm that assigns a posterior probability of cluster assignment. (It could also be replaced by a different problem, of assessing DE in a topic model.) The second issue relates to the general problem of detecting whether two distributions are different from each other in a statistically meaningful way, which seems to be a much harder problem, and one which has an unclear biological interpretation. There has been some work in linking the distribution of true gene expression levels to genetic (Yvert 2013) and environmental (Korthauer et al. 2016) perturbations. However, there are still fundamental disconnects between these ideas and e.g., theory of the kinetics of transcriptional regulation.
Mapping single cells to a reference atlas. The problems in this section boil down to the statistical problem of semi-supervised learning of cell clusters in new data sets, using reference data as labeled auxiliary data. This problem seems to run into a fundamental limitation, that there will be systematic differences in measurement error between new data sets and reference data sets. This limitation suggests that what is needed is not just labeled reference data, but a full generative model for the reference data which can be updated with the new data set. Existing methods have already begun to approach this idea (Wang et al. 2019, Lotfollahi et al. 2020).
On the one hand, distributing a full generative model could be easier than distributing a high-dimensional cell atlas (c.f., pre-trained Inception v3). On the other hand, it is unclear how to make this sort of framework widely accessible to non-experts, or even extensible by other expert researchers.
Generalizing trajectory inference. What is “trajectory inference”? The paper suggests a model in which cells undergoing some biological process move in a state space parameterized by transcriptome, proteome, epigenome, etc. Then, what would it mean to “generalize” trajectory inference? The paper never addresses this question, but instead discusses the problems of: (1) performing trajectory inference from different types of measurements, (2) performing (parallel) trajectory inference from different initial conditions, and (3) making rigorous statistical comparisons between estimated trajectories.
One goal of trajectory inference is to learn about critical points, characterized by specific changes in e.g., transcriptomes, in biological processes of interest. Such critical points might correspond to bifurcations of a relatively homogeneous population of cells responding to some stimulus (Lönnberg et al. 2017), or more general branching from an initial pluripotent state (Farrell et al. 2017).
It is unclear that trajectory inference from single cell epigenomic or proteomic data actually requires new statistical methods. However, this is in part because the generative models for these processes (in particular, the measurement error) have not been rigorously laid out. It is clear that trajectory inference from simultaneous measurements of transcriptome, proteome, etc. in each cell (e.g. CITE-Seq, Stoeckius et al. 2017) is principled, and would require (relatively) simple development of new, linked statistical models (in which different measurement models depend on a common latent variable model). The situation of integrating independent trajectories learned from transcriptome, etc. seems much more difficult (due to systematic differences between measurements), and potentially unsolvable.
One glaring omission in this discussion is the use of known time points of collection as prior information in trajectory inference. In general, cells do not proceed lock-step through responses to stimuli, and the use of multiple collections seems like the obvious choice to characterize temporal processes at single cell resolution. However, one could argue that such experimental designs are still unlikely to discover new biology, since the time points for collections are typically chosen based on prior knowledge. However, the statistical problems here seem much more tractable.
Finding patterns in spatially resolved measurements. The paper indicates that the fundamental question is assigning samples to cell types/compartments given gene expression and spatial coordinates. Why would this be an interesting thing to do? In the case of slide-based approaches, one issue is that measurement are not made at single-cell resolution, but at few-cell resolution, and so (unwanted) spatial variation in cell type abundance may lead to false positive discoveries of spatial patterns in gene expression (e.g., Cable et al. 2020, Kleschchevnikov et al. 2021).
My own list of fundamental questions in spatial measurements is very different: (1) what are the predominant patterns of spatial gene expression, (2) which spatial structures define (or are defined by) those patterns, and (3) which genes co-vary spatially? In my view, answering these questions are the first step towards understanding how (perturbations to) cell-level (molecular) phenotypes lead to (changes in) tissue-level phenotypes. I argue that understanding how cell-level phenotypes lead to tissue-level phenotypes is the next major hurdle in connecting disease-associated genetic variation to disease susceptibility/outcomes.
The paper also indicates that there are is also a problem of “resolution” in spatial coherence of cells. My idea to use convolutional neural nets to parameterize spatial expression models naturally handles this case, since stacked convolutions naturally encode spatial coherence at different scales.
Challenges in single-cell genomics
Dealing with errors and missing data in the identification of variation from single-cell DNA sequencing data.
Challenges in single-cell phylogenomics
Scaling phylogenetic models to many cells and many sites.
Integrating multiple types of variation into phylogenetic models.
Inferring population genetic parameters of tumor heterogeneity by model integration.
Overarching challenges
Integration of single-cell data across samples, experiments, and types of measurement.
Validating and benchmarking analysis tools for single-cell measurements.


this is text in #container1, now we must have a header
click me
link with no value
link with value 5
link 1
link 2
link
link
link
link
link
span
div
h1
link
link
link
link
link
CD3.Behaviors:Core


Responses are only recorded if Submit Response Button is clicked after chosing one of the provided Categories
You May also chose any custom tag you think may be helpful in categorizing these images.
Comments may include why you decided to classify the pair the way you did.
Deciding how to classify given two images
-
CLONE : If the pages have no perceptible changes in functionality or appearance, they are considered Clones
-
NEAR-DUPLICATES : If the changes between the pages are subtle and do not probably affect the functionality offered
-
Advertisements
-
Background Images
-
Minor Elements that were shown vs hidden because of user actions like hovering for example navigation lists that appears vs not
-
DIFFERENT : If the pages are very different and represent completely different functionality


The mission of Use My Tech Stuff™ is to connect people with the technology that they need.
Retail stores charge excessive prices for technology, often with very limited return policies.
Whether its for an emergency, business or personal use, we get the technology you need in your hands at a fraction of the cost. When you're done, you simply return it.
Renters create a profile and post pieces of technology that they would like to rent out.
Rentees can browse pieces of technology by category, distance, and price and communicate directly with renters about their postings.
With multiple payment options, pick-up scheduling and a verified review system, you'll never use anything else!


http://www.speakers-podium.com/susangranger.
Susan Granger's review of "MANSFIELD PARK" (Miramax Films)
In this provocative, revisionist adaptation of Jane Austen's third novel, Canadian writer-director Patricia Rozema gives her 19th century heroine, Fanny Price, much of Austen's own confidant, creative personality. Incorporating material from Austen's early journals and letters, Rozema recreates Fanny (Frances O'Connor) as a poor relation who is sent from Portsmouth to the magnificent mansion called Mansfield Park to live in emotional exile with her pompous uncle, starchy aunts, and privileged cousins. Her favorite cousin is the brooding Edmund (Jonny Lee Miller) who is destined to be a humble clergyman, much to the chagrin of the outspoken, ambitious young woman (Embeth Davidtz) who wants to marry him. Always made to feel inferior within the genteel, rigidly conventional British class system, she is considered more than a servant but less than an equal companion. Nevertheless, meek Fanny becomes an adept and witty writer who is courted by a charming, handsome rake (Allesandro Nivola) whom she does not trust. Australian actress Frances O'Connor does a splendid job as the plucky heroine and her complex performance is matched by playwright Harold Pinter, as her autocratic uncle, and Lindsay Duncan in dual roles - as both Fanny's desperate, impoverished mother and wealthy, opium-addicted aunt. Admittedly, Patricia Rozema's script tackles too many social issues, including the dark brutality of slavery on the Caribbean island of Antigua, an exploitive endeavor which supports this segment of England's landed gentry. And Rozema's willfully manipulative, pro-feminist characters seem far ahead of their time. On the Granger Movie Gauge of 1 to 10, Mansfield Park is a sensual, cinematic 7. It's a period drama that should appeal, primarily, to the art-house crowd.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Devesh Patel
On Pairing
Giving Feedback
July 18, 2015
Pairing is a key format to learning at DBC and is done with great frequency. This is a good thing as you are able to see how other people think and try to work together to solve a problem. After all two heads are better than one. One thing negative I found myself doing was over preparing which in some ways defeats the purpose of pairing. I learned not to do that as much to make the pairing session more rewarding. I learned this through receiving feedback.
Feedback can be difficult to get as it feels like criticism but ultimately helps you be a better pair. Feedback is also difficult to provide as it has to be actionable, specific, and kind. The most difficult thing about providing feedback is trying to find out what could be done better. As you pair more, you get a sense of how to pair and this becomes easier, but initially it is hard to give proper feedback.
I think pairing and getting feedback is good as it helps in both learning and working in a team environment. Coding is not necessarily a solo process and pairing helps to emphasize this.


I am an assistant professor in the School of Computing at KAIST. Before joining KAIST, I was a research scientist at Adobe Research. I received my Ph.D. from Stanford University, advised by Leonidas Guibas, and received M.S. and B.S. degrees from KAIST. My research focuses on 3D deep learning and geometry processing.
I am looking for new graduate students to join my group. Please reach out to me via email if you are interested in.
Research Statement (Presented at SIGGRAPH 2019 Doctoral Consortium)


The quote author is {{quote.author}}
This quote was added by {{quote.name}}.
Added {{quote.creationDate|timeCount}} days ago.


Beyond Engagement- JeffreyZeldman
Lack on engagement may be a good thing, if people spend less time on a site may not be a bad thing, it may mean that they got to your site and find the answer and got out
If a customer spends 30 min on our site was she engaged ... or frustrated ?
Speed if usefulness
Contnet performance quotient Design Cpq
A measurement the shortest distance between problem & solution. On a perfect website the user would get to a website and exactly find what they came for How quickly can you solve the customer’s problem? A new goal to iterate against. A new way to deliver value. A new way to evaluate success.
CPQ
The time it takes your customer to get the information she came for. Why do we need this ? Compare to your goals Every design is intentional
Add content where is natural in addition that your website don't limit your content to just website
Slide for this conference Talk -1 Beyond Engagement


Tesla’s new Cybertruck looks like a Mars Rover
by Jamie RobinsonThe sci-fi vibes are strong with Tesla’s futuristic new Cybertruck, which looks more like it’s built for exploring the surface of Mars than terrestrial adventures.
Tesla’s angular Cybertruck combines the functions of a truck with the speed of a sports car, reaching 60mph in 2.9 seconds. Built for on and off-road driving, it has an Ultra-Hard 30X cold-rolled stainless steel shell, can seat six, tow up to 14k, and features ‘ armour glass’ windows (which promptly smashed at the truck’s unveiling at the Los Angeles Auto Show. Oops.)
The robotic-looking Cybertuck is accepting preorders, and while it doesn’t have an official launch date, it is expected to complete production in late 2021 or late 2022. It is available in three versions: the single motor rear-wheel-drive model sets you back $39,900 while the dual-motor, all-wheel-drive is $49,900 and the tri-motor all-wheel-drive model $69,900.
Read next: Las Vegas nightclub filled with Damien Hirst artworks closes after just 7 months


Planned working day, work on the result, in the team mutual understanding and support. A serious company.
Corporate culture is on top, the authorities have always conducted training on improving skills in a given position.


Florent Vain
Développeur logiciel / Technicien informatiqueExperiences
Feb 2019Jan 2020
Hypermarket Versatile Worker
Auchan La Couronne La Couronne, France- Goods shelving, inventories, use of pallet truck, early shifts (3am, sometimes midnight)
- Worked alongside my scholarships during holidays and weekend
Dec 2017Sep 2018
- Goods shelving, inventories, use of pallet truck, early shifts (3am, sometimes midnight)
- Worked alongside my scholarships during holidays and weekend
Apr 2017Jun 2017
Intern Developer in a Research Lab
LaBRI Bordeaux, France- Designed and developed a front end application from top to bottom with state of the art technologies while discovering computer graphic's programmation (OpenGL/WebGL2/GLSL)
- Working under technical constraints (realtime and web based application) and alongside backend engineers
Education
20182020
Master's degree in games and interacive digital media
CNAM-ENJMIN Angoulême, France- Introduction to all aspects involved in game conception and production
- Programming courses focused on game development specific problematics
20172018
Bachelor in Computer Science
University of Bordeaux Bordeaux, France- General purpose programming courses focused on theoretical content
20152017
Technical degree in Computer Science
University Institutes of Technology of Bordeaux Bordeaux, France- System administration (Linux), Software achitecture and development (UML/C++/Java/C#), Web development (Frontend/Backend)
OTHERS
2019
Student's Office Vice President
CNAM-ENJMIN Angoulême, France
2016


Choose which message categories to show as inbox tabs. Other messages will appear in the Primary tab.
Deselect all categories to go back to your old inbox.


CV
Who I am
I am a developer mostly focused on dynamic languages like Ruby, but with knowledge of PHP, C# & Java. I also have a big foundation in networking due to my first jobs into the IT area.
I am a self-taught, pragmatic person, very much into the craft of building applications. I really enjoy what I do, and I wouldnít trade it for nothing.
If I am in a position of choosing a development methodology, Iíll choose to follow the Agile model.
What I am doing now
Software Developer at Red Intercable Digital Buenos Aires 2007-Present Day I am currently working on an application for a telecommunications company. The purpose of the app is to integrate the functionality of a CRM and a Network Provisioning service in order to concentrate the business information at one place only, and also to decrease the human error on network configuration tasks. This project is now in the final stages. I am also managing and developing several projects, most of them internal, all based on rails. The main project at this moment its a billing application that integrates all the corporate network clients in one place, provides a clean interface for billing, and helps dealing with the the current AFIP regulation. *Software Developer as Freelancer: 2008-Present Day* I am working on a big community site. We are hoping to release it pretty soon, probably by the end of the year. Other projects I have been involved in: * "Suipit":http://www.suipit.com/ Project management tool in spanish. * "Che Cupcakes Website":http://www.checupcakes.com.ar/ CMS-like, with some CRM features. * "Justo al Caer Website":http://www.justoalcaer.com.ar/ CMS-like, for my Rock&Pop band. h2. What I did before h3. Virtualizar Development Buenos Aires, 2006-Early 2008 I co-owned a development firm with Pedro Visintín. We worked on projects built with Ruby & Rails, using also mongrel, capistrano, rmagick, rspec, resource controller, git/svn and many more Open Source components. BackOffice (Network Provisioning System & CRM) * BackOffice (Network Provisioning System & CRM) * InfoMultas ("Callcenter":http://www.infomultas.com.ar/) * ... to name a few. h3. Developer at Banco Galicia de Buenos Aires Buenos Aires, 2006-2007 I performed two jobs in one. I worked programming applications for different targets: A search engine for the source control used at the software factory (java-console app), and 3 to 4 medium size websites for a small group of users inside the corporation (java-struts, hibernate, spring). I also worked as a SCM (Rational ClearCase) Administrator, providing support to 300 developers. h3. Network Administrator at e-volution Buenos Aires, 2003-2005 I performed tasks of analysis, configuration, and tuning of the inter-networking infrastructure of the corporation. I also maintain all the windows and linux based servers. At the same time I developed a tool for managing the updates of many projects to ease the complexity of the deployment task (the primary business of e-volution is web development). Datacenter Specialist at iplan networks Buenos Aires, 2004 I worked building, configuring and deploying Linux servers for iplan telecommunications. My main task was to tune the Calling Card platform based on MySQL-TCL/TK-PHP. h2. Education * Instituto Tecnológico ORT Nro. 2 ó Computer analyst - 2006. * Nacional of San Isidro - Bachiller. h2. Languages Spanish, English h2. Skills & Miscellaneous * Programming with different languages, including Ruby, PHP, C#, Pascal, Java, Bash. * Web Design with HTML and CSS. * MySQL, SQL Server and basic knowledge of Oracle. * Administration of Linux Servers (redhat, debian & gentoo). * Virtualization based on the Xen/Linux platform. * Configuration & Maintenance of network services like Apache, Ngynx, postfix, bind, monit, MySql, NFS, SVN, Tomcat. * Administration of Active Directory Network Services, and also Exchange Server, SQL server and Sharepoint Server. * Microsoft Certified Professional in Windows Server 2000, Active Directory Design and Analysis (2002). h2. Talks * 60 minutos On Rails. It was an introduction dictated on the CafeConf 2006, which is a conference focused on promoting Open Source. The talk was co-hosted with Pedro Visintin. * Ruby On Rails, brief introduction. Prior to the CafeConf talk, we gave a practical workshop about the features provided in rails version 1.1. * I regularly write in the RoR community site: http://blogs.onrails.com.ar/ about Ruby and Rails.Newer: Nuevo Hogar / Nuevo Blog


identity
password
PIN is 4 or 8 digits
APN
HTTP Proxy Host
HTTP Proxy Port
MMS Proxy
MMS Port
MMSC
SSID
encryption
Volume
Brightness level


Create the template url for your video by positioning the presentation and the presenter on the backdrop.
Cloudinary Cloud Name
Presenter Image
Presenter height
width
Presenter X offset
Y offset
Presentation Image
Presentation height
width
Presentation X offset
Y offset
background Image
background height
width


Language:
Substream1
- Disabled (the main stream frame rate of 31~60 frames, will disable Substream)
- Encoding Type:
- FPS:
- [5-30]
- GOP:
- [5-300]
- Bitrate(kbit):
- [32-32000]
- Encoded Size:
- H.264 Level:
- Bitrate Control:
- TS URL:
- HLS URL:
- FLV URL:
- RTSP URL:
- RTMP URL:
- RTMP/RTMPS/RTSP PUSH URL:
- Multicast IP:
- Multicast Port:
- [1-65535]


White to play 41
pips White=166 Black=148
(CorrectAnswer= 0/0, ErrorScore= 0)
1. Bar/24 8/4 eq: -0.355 42.56% (G:10.49% B:0.56%) 57.44% (G:20.23% B:0.99%) 2. Bar/20 eq: -0.478 (-0.123) 40.52% (G: 8.75% B:0.40%) 59.48% (G:21.29% B:1.01%) 3. Bar/24 13/9 eq: -0.511 (-0.156) 41.05% (G: 9.36% B:0.47%) 58.95% (G:26.59% B:1.68%) 4. Bar/24 6/2 eq: -0.576 (-0.221) 37.97% (G: 8.29% B:0.35%) 62.03% (G:25.26% B:1.50%) 5. Bar/24 7/3 eq: -0.908 (-0.553) 34.53% (G: 6.82% B:0.34%) 65.47% (G:31.54% B:2.27%)


Frozen 2 Box Office Day 3 Advance Booking Trends: Another Jump On Cards
The animation film by Disney surprised everyone by collecting 10.5 crores approx in the first two days.
by Koimoi.com TeamFrozen 2 Box Office: Latest Hollywood release Frozen 2 is taking benefit of the new Bollywood film Pagalpanti’s underperformance. The animation film by Disney surprised everyone by collecting 10.5 crores approx in the first two days.
The growth on 2nd day was 100% for the film as the collections went from 3.5 crores to 7 crores. Now on Sunday, the film is looking set for another jump as the advance booking trends for the day are rocking. Have a look at how some of the major cities are performing as of now in different formats of Frozen 2’s release-
Mumbai
English 2D Almost full
English IMAX 2D Almost all shows are free
English IMAX 3D 50%
English 4DX 3D 75%
English MX 4D 100%
Hindi 3D 40-45%
Hindi 2D 50%
Hindi 4DX 3D 100%
Hindi IMAX 3D 100%
NCR
Hindi 3D 40-45%
English 3D 25-30%
English 2D 100%
Hindi 2D 40-45%
English IMAX 3D 65-70%
English 4DX 3D 70-75%
Hindi 4DX 3D 85-90%
Hindi IMAX 3D 100%
Bengaluru
Hindi 3D 70-75%
English 3D 50-55%
English IMAX 3D 75%
English 4DX 3D 85-90%
Hindi 4DX3D 100%
Hyderabad
English 2D 30-35%
English 3D Almost all shows are free
Hindi 3D Almost all shows are free
Hindi 2D Almost all shows are free
English 4DX 3D 80-85%
Ahmedabad
English 4DX 3D 100%
English 3D 15-20%
English 2D 50%
Chennai
English 2D 100%
English 3D 70-75%
Hindi 2D 35-40%
Hindi 3D 40-45%
English IMAX 3D 80-85%
Kolkata
English IMAX 3D 75%
English 3D 55-60%
English 2D 100%
Hindi 3D 30-35%
Frozen 2 is all set to have another big day at the Box Office and a very good weekend number is on cards.


A community-driven project for a de facto "standard" library for Fortran. The stdlib project is both a specification and a reference implementation, developed in cooperation with the Fortran Standards Committee. Find out more on GitHub.
{% include img_cached.html src="//img.shields.io/github/stars/fortran-lang/stdlib?style=social" %} {% include img_cached.html src="//img.shields.io/github/forks/fortran-lang/stdlib?style=social&label=Fork" %} {% include img_cached.html src="//img.shields.io/github/last-commit/fortran-lang/stdlib?color=blue" %} {% include img_cached.html src="//img.shields.io/github/issues/fortran-lang/stdlib" %}A prototype project to develop a common build system for Fortran packages and their dependencies. Find out more on GitHub.
{% include img_cached.html src="//img.shields.io/github/stars/fortran-lang/fpm?style=social" %} {% include img_cached.html src="//img.shields.io/github/forks/fortran-lang/fpm?style=social&label=Fork" %} {% include img_cached.html src="//img.shields.io/github/last-commit/fortran-lang/fpm?color=blue" %} {% include img_cached.html src="//img.shields.io/github/issues/fortran-lang/fpm" %}This website is open source and contributions are welcome! Find out more on GitHub.
{% include img_cached.html src="//img.shields.io/github/stars/fortran-lang/fortran-lang.github.io?style=social" %} {% include img_cached.html src="//img.shields.io/github/forks/fortran-lang/fortran-lang.github.io?style=social&label=Fork" %} {% include img_cached.html src="//img.shields.io/github/last-commit/fortran-lang/fortran-lang.github.io?color=blue" %} {% include img_cached.html src="//img.shields.io/github/issues/fortran-lang/fortran-lang.github.io" %}{{ sitePage.description }}


Type function Library apprever.* Revision Current Public Release (2013.2076) Keywords AppRever, ads, banner ads Sample code See also
Serve an AppRever banner ad.
You can set the x, y location, height and width, animate the ad, and include an optional message.
apprever.requestBannerAds( options )
Table. Short description goes here. See Format for options below.
options
The options
table contains the following properties:
Number. x location of top left of banner ad
Number. y location of top left banner ad
Number. width of banner ad
Number. height of banner ad
String. Message associated with banner ad (stored in the AppRever database)
Number. a=1 for animaited ads, a=0 to turn off banner ad animation
``````lua
-- You can set the width and height of banner ads to any size you like. To keep them
-- proportionate to the original 960x100 size, use the following code for landscape mode.
-- They are automatically scaled down proprtionally for portrait mode on each ad request.
-- So for a perfect fit on any device:
-- Calculate your actual device width
local width = math.round((display.contentWidth-2*display.screenOriginX) / display.contentScaleX)
-- Now scale proportionally to the 960x100 ad units currently used by AppRever
local height = (width/960)*100
apprever.requestBannerAds( {x=0, y = 0, w=width, h=height, m="beat level 10", a=1} )
For banner ads at the bottom of your landscape-mode App, just add in a calculation to
determine your actual device height, and for the y location of the ad, just subtract
off the height of the ad itself:
local width = math.round((display.contentWidth-2*display.screenOriginX) / display.contentScaleX)
-- this scales proportionally to the 960x100 ad units currently used by AppRever
local height = (width/960)*100
local actualScreenHeight = math.round((display.contentHeight-2*display.screenOriginY) / display.contentScaleY)
apprever.requestBannerAds( {x=0, y = actualScreenHeight-height, w=width, h=height, m="beat level 10", a=1} )
``````


webmachine
getting started quickly with Webmachine
Make sure that you have a working Erlang/OTP release, R12B5 or later.
Get the webmachine code:
hg clone http://bitbucket.org/justin/webmachine/ webmachine-read-only
Build webmachine:
cd webmachine-read-only make
Create, build, and start the skeleton resource:
./scripts/new_webmachine.erl mywebdemo /tmp cd /tmp/mywebdemo make ./start.sh
Take a look! Point a web browser at http://localhost:8000/
To make this resource handle URI paths other than /, add more dispatch terms in /tmp/mywebdemo/priv/dispatch.conf; to make that resource to more interesting things, modify the resource itself at /tmp/mywebdemo/src/mywebdemo_resource.erl.
To learn how to do more interesting things, check out some examples or read more documentation.


|
KratosMultiphysics
KRATOS Multiphysics (Kratos) is a framework for building parallel, multi-disciplinary simulation software, aiming at modularity, extensibility, and high performance. Kratos is written in C++, and counts with an extensive Python interface.
|
Remove Mesh Nodes Process for 2D and 3D cases. More...
#include <remove_nodes_mesher_process.hpp>
Public Member Functions | |
Life Cycle | |
| RemoveNodesMesherProcess (ModelPart &rModelPart, MesherUtilities::MeshingParameters &rRemeshingParameters, int EchoLevel) | |
| Default constructor. More... | |
| virtual | ~RemoveNodesMesherProcess () |
| Destructor. More... | |
Operators | |
| void | operator() () |
| This operator is provided to call the process as a function and simply calls the Execute method. More... | |
Operations | |
| void | Execute () override |
| Execute method is used to execute the Process algorithms. More... | |
Input and output | |
| std::string | Info () const override |
| Turn back information as a string. More... | |
| void | PrintInfo (std::ostream &rOStream) const override |
| Print information about this object. More... | |
| void | PrintData (std::ostream &rOStream) const override |
| Print object's data. More... | |
| Public Member Functions inherited from Kratos::MesherProcess | |
| KRATOS_CLASS_POINTER_DEFINITION (MesherProcess) | |
| Pointer definition of MesherProcess. More... | |
| MesherProcess () | |
| Default constructor. More... | |
| MesherProcess (Flags options) | |
| Constructor. More... | |
| virtual | ~MesherProcess () |
| Destructor. More... | |
| void | operator() () |
| This operator is provided to call the process as a function and simply calls the Execute method. More... | |
| void | ExecuteInitialize () final override |
| void | ExecuteBeforeSolutionLoop () final override |
| void | ExecuteInitializeSolutionStep () final override |
| this function will be executed at every time step BEFORE performing the solve phase More... | |
| void | ExecuteFinalizeSolutionStep () final override |
| this function will be executed at every time step AFTER performing the solve phase More... | |
| void | ExecuteBeforeOutputStep () final override |
| this function will be executed at every time step BEFORE writing the output More... | |
| void | ExecuteAfterOutputStep () final override |
| this function will be executed at every time step AFTER writing the output More... | |
| void | ExecuteFinalize () final override |
| std::string | Info () const override |
| Turn back information as a string. More... | |
| void | PrintInfo (std::ostream &rOStream) const override |
| Print information about this object. More... | |
| void | PrintData (std::ostream &rOStream) const override |
| Print object's data. More... | |
| Public Member Functions inherited from Kratos::Process | |
| KRATOS_CLASS_POINTER_DEFINITION (Process) | |
| Pointer definition of Process. More... | |
| Process () | |
| Default constructor. More... | |
| Process (const Flags options) | |
| ~Process () override | |
| Destructor. More... | |
| void | operator() () |
| This operator is provided to call the process as a function and simply calls the Execute method. More... | |
| virtual Process::Pointer | Create (Model &rModel, Parameters ThisParameters) |
| This method creates an pointer of the process. More... | |
| virtual int | Check () |
| This function is designed for being called after ExecuteInitialize ONCE to verify that the input is correct. More... | |
| virtual void | Clear () |
| This method clears the assignation of the conditions. More... | |
| virtual const Parameters | GetDefaultParameters () const |
| This method provides the defaults parameters to avoid conflicts between the different constructors. More... | |
| std::string | Info () const override |
| Turn back information as a string. More... | |
| void | PrintInfo (std::ostream &rOStream) const override |
| Print information about this object. More... | |
| void | PrintData (std::ostream &rOStream) const override |
| Print object's data. More... | |
Protected Member Functions | |
Protected Operations | |
| void | CleanRemovedNodes (ModelPart &rModelPart) |
| virtual bool | RemoveNodesOnDistance (ModelPart &rModelPart, unsigned int &inside_nodes_removed, unsigned int &boundary_nodes_removed, bool &any_condition_removed) |
| virtual bool | CheckEngagedNode (Node &rNode, std::vector< Node::Pointer > &rNeighbours, std::vector< double > &rNeighbourDistances, unsigned int &rn_points_in_radius) |
| virtual bool | RemoveNodesOnError (ModelPart &rModelPart, unsigned int &error_removed_nodes) |
| virtual bool | RemoveNodesOnContact (ModelPart &rModelPart, unsigned int &inside_nodes_removed, unsigned int &boundary_nodes_removed, bool &any_condition_removed) |
| bool | RebuildBoundary (ModelPart &rModelPart) |
| Protected Member Functions inherited from Kratos::MesherProcess | |
| MesherProcess (MesherProcess const &rOther) | |
| Copy constructor. More... | |
Protected Attributes | |
Protected member Variables | |
| ModelPart & | mrModelPart |
| MesherUtilities::MeshingParameters & | mrRemesh |
| MesherUtilities | mMesherUtilities |
| int | mEchoLevel |
Type Definitions | |
| typedef ModelPart::ConditionType | ConditionType |
| typedef ModelPart::PropertiesType | PropertiesType |
| typedef ConditionType::GeometryType | GeometryType |
| typedef Bucket< 3, Node, std::vector< Node::Pointer >, Node::Pointer, std::vector< Node::Pointer >::iterator, std::vector< double >::iterator > | BucketType |
| typedef Tree< KDTreePartition< BucketType > > | KdtreeType |
| typedef ModelPart::MeshType::GeometryType::PointsArrayType | PointsArrayType |
| typedef GlobalPointersVector< Node > | NodeWeakPtrVectorType |
| typedef GlobalPointersVector< Element > | ElementWeakPtrVectorType |
| typedef GlobalPointersVector< Condition > | ConditionWeakPtrVectorType |
| KRATOS_CLASS_POINTER_DEFINITION (RemoveNodesMesherProcess) | |
| Pointer definition of Process. More... | |
Remove Mesh Nodes Process for 2D and 3D cases.
The process labels the nodes to be erased (TO_ERASE) if they are too close (mRemoveOnDistance == true) if the error of the patch they belong is very small (REMOVE_NODES_ON_ERROR) In the interior of the domain or in the boundary (REMOVE_BOUNDARY_NODES) ...
Additional treatment of the nonconvex boundaries is also going to erase nodes.
At the end of the execution nodes are cleaned (only in the current mesh) If boundary nodes are removed, conditions must be build again (new conditions are build in the current mesh) NOTE: as kratos uses shared pointers, the main list of nodes can be changed. the element contains the geometry which has pointers to nodes, so that nodes are kept in memory and their information can be recovered. that means also that if the element information is needed it is kept until the end when new elements are created and replace the old ones.
| typedef Bucket<3, Node, std::vector<Node::Pointer>, Node::Pointer, std::vector<Node::Pointer>::iterator, std::vector<double>::iterator > Kratos::RemoveNodesMesherProcess::BucketType |
| typedef ModelPart::ConditionType Kratos::RemoveNodesMesherProcess::ConditionType |
| typedef GlobalPointersVector<Condition> Kratos::RemoveNodesMesherProcess::ConditionWeakPtrVectorType |
| typedef ModelPart::MeshType::GeometryType::PointsArrayType Kratos::RemoveNodesMesherProcess::PointsArrayType |
| typedef ModelPart::PropertiesType Kratos::RemoveNodesMesherProcess::PropertiesType |
|
inline |
Default constructor.
|
inlinevirtual |
Destructor.
|
inlineprotectedvirtual |
|
inlineprotected |
|
inlineoverridevirtual |
Execute method is used to execute the Process algorithms.
Reimplemented from Kratos::MesherProcess.
|
inlineoverride |
Turn back information as a string.
| Kratos::RemoveNodesMesherProcess::KRATOS_CLASS_POINTER_DEFINITION | ( | RemoveNodesMesherProcess | ) |
Pointer definition of Process.
|
inline |
This operator is provided to call the process as a function and simply calls the Execute method.
|
inlineoverride |
Print object's data.
|
inlineoverride |
Print information about this object.
|
inlineprotectedvirtual |
|
inlineprotectedvirtual |
Reimplemented in Kratos::RemoveFluidNodesMesherProcess.
|
inlineprotectedvirtual |
|
protected |
|
protected |
|
protected |
|
protected |


We sell networks!
- orchestrate distributed technologies
- transform integrated partnerships
- syndicate integrated channels
- productize leading-edge functionalities
- iterate mission-critical web-readiness
- scale impactful e-services
- deploy B2C systems
- streamline scalable initiatives
- synergize dot-com networks
- monetize dynamic deliverables
- morph out-of-the-box bandwidth
- maximize user-centric users
- enable dynamic bandwidth


JOY - compiled at 16:57:51 on Mar 17 2003 (BDW) Copyright 2001 by Manfred von Thun usrlib is loaded inilib is loaded agglib is loaded agglib is already loaded agglib is already loaded numlib is loaded agglib is already loaded seqlib is loaded symlib is loaded agglib is already loaded seqlib is already loaded numlib is already loaded lsplib is loaded lazlib is loaded seqlib is already loaded numlib is already loaded mtrlib is loaded numlib is loaded agglib is already loaded seqlib is loaded MTRLIB m-print mm-2bin-m mm-mul-m mm-add-m mm-bin-m ms-cbin-m ms-bin-m sm-bin-m m-transpose-m mm-horcat-m mm-vercat-m mm-samedimensions mm-conformable m-dimensions vv-bin-m v-e-diag-m v-zdiag-m v-1col-m v-1row-m vv-2bin-s vv-bin-v vv-comformable vs-cbin-v vs-bin-v v-invert-v sv-bin-v v-negate-v n-e-vector vv-samesize TUTLIB toc-do-sec0-loop toc-repeat-sections toc-do-section toc-ask-for-section toc-do-section0 toc-one-heading toc-of-tutorial toc-all-headings put-stats ini-stats expecting-from expecting get-quote get-list get-integer praise pausing pause LAZLIB Squares Ones Powers-of-2 Odds Evens Positives Naturals Filter Map From-by From-to-by From-to From Take Size N-th Drop Third Second Cons Uncons Rest First Null LSPLIB lisp l-prompt y RECFOLDR tern l2 l1 FOLDR2 FOLDL bin ini lis FOLDR lib0 LIST NULL ATOM EQ CONS CDR CAR apply DEFUN DEF IF CLOSURE LAMBDA eval SYMLIB Min2Inf Min2Tre Min2Rev Min2Cam Min2Pol Inf2Tre Inf2Rev Inf2Cam Inf2Pol Cam2Inf Cam2Tre Cam2Rev Cam2Pol Rev2Tre Rev2Inf Rev2Cam Rev2Pol Pol2Tre Pol2Inf Pol2Cam Pol2Rev M42C M32C M22C M12C bin3ops M42T bin2ops M32T bin1ops M22T M12T new-infra X2Y R2I R2T R2C P2I P2T binops P2C I2T I2C C2R C2P C2I QUOTE unops C2T SEQLIB treesample treemap treefilter treestrip treereverse treeflatten treeshunt orlistfilter orlist cartproduct transpose delete insert-old insert merge1 merge mk_qsort qsort1 qsort1-1 qsort permlist insertlist powerlist2 powerlist1 subseqlist frontlist frontlist1 scalarproduct product restlist flatten reversestring reverselist reverse putlist NUMLIB cube-root use-newton newton deriv qroots tandeg cosdeg sindeg radians e pi celsius fahrenheit gcd fib fact prime odd even negative positive AGGLIB variance average sum interleave2list interleave2 foldr2 mapr2 fold2 stepr2 mapr pairstep from-to-string from-to-set from-to-list from-to zip unswons2 swons2 uncons2 cons2 null2 thirdd secondd restd firstd unswonsd unconsd swonsd consd nulld foldr set2string elements shunt string2set fifth fourth third second unpair pairlist pairstring pairset unitlist unitstring unitset INILIB all-libload special-libload basic-libload libload verbose forever repeat nullary2 i2 call dip3 dip2 dipd sequand negate disjoin conjoin show-todaynow now today localtime-strings months weekdays swoncat numerical sequor boolean to-lower to-upper falsity truth newstack pop2 dup2 ask putstrings bell space putln newline USRLIB standard-setting unix find-in edit escape editor dir terminal control-eof vms returned RAWJOY1 quit abort include putchars putch put get argc argv getenv system gc setecho setundeferror setautoput manual helpdetail help treegenrec treerec treestep all some split filter primrec infra times map fold step condlinrec genrec binrec tailrec linrec while cond iffile iffloat iflist ifstring ifset iflogical ifchar ifinteger ifte branch cleave ternary binary app4 app3 app2 unary4 unary3 unary2 unary nullary construct app12 app11 app1 dip x i file float user leaf list string set logical char integer in has equal = != < <= > >= small null body intern name enconcat concat take drop unswons uncons case opcase size of at compare rest first swons cons unstack ftell fseek fputstring fputchars fputch fput frename fremove fwrite fread fopen fgets fgetch fflush ferror feof fclose min max succ pred srand formatf format strtod strtol strftime mktime gmtime localtime trunc tanh tan sqrt sinh sin pow modf log10 log ldexp frexp floor exp cosh cos ceil atan2 atan asin acos abs chr ord neg sign div rem / * - + not and xor or choice pop rotated rolldownd rollupd swapd dupd popd rotate rolldown rollup swap dup id stderr stdout stdin rand time clock echo undefs undeferror autoput conts stack setsize maxint true false file type float type list type string type set type integer type character type truth value type


{{dayTime}}
{{trainer_first_name}} {{trainer_last_name}}
{{trainer_institution}}
Institute
{{numberOfPatients}}
Patients
Your patients
{{patient.first_name}} {{patient.last_name}}
{{current_patient.first_name}} {{current_patient.last_name}}
up to: {{dateOfLastMeasure}}
{{current_patient.weight}}
{{current_patient.visceral_fat}}
{{current_patient.fat_percentage}}
{{current_patient.mass_weight}}
{{current_patient.body_water}}
{{current_patient.bmr}}
{{current_patient.metabolic_age}}
{{current_patient.physique_rating}}
You don't have any patients yet!
Add patients and you will see their measurements and statistics
Choose charts:
Fitness
Calories and Body Measurement
Calories Charts
Calories burnt
Income Calories
Selected Table: {{selectedCaloriesTable}}
Body Measurements - 28 Last days
Workouts Statistics per Week
Workouts - 28 Last days


CompTIA Network+
ITIL Certified
Videography
Web Services
Performance Tuning
B2B
Penetration Testing
Network Security
C#
Windows Azure
mac
CompTIA Security+
Server 2000-2008
Skydiving
High Availability Architecture
PKI
Kerberos
Mercurial
skyd
High Performance Computing
Web Hosting
Ethical Hacking