| Methods' Summary |
| getUriReference |
returns the textual representation of the complete URI reference.
|
| isAbsolute |
returns whether this URI reference is absolute or relative.
|
| getScheme |
returns the scheme part of this (absolute) URI reference.
|
| getSchemeSpecificPart |
returns the scheme-specific part of this URI reference.
|
| isHierarchical |
returns whether this URI reference is hierarchical or opaque.
|
| hasAuthority |
returns whether this (hierarchical) URI reference has an authority part.
|
| getAuthority |
returns the authority part of this (hierarchical) URI reference.
|
| getPath |
returns the path part of this URI reference.
|
| hasRelativePath |
returns whether this (relative) URI reference has a relative path.
|
| getPathSegmentCount |
returns the number of path segments of this (hierarchical) URI reference.
|
| getPathSegment |
returns a given path segment of this (hierarchical) URI reference.
|
| hasQuery |
returns whether this (hierarchical) URI reference has a query part.
|
| getQuery |
returns the query part of this (hierarchical) URI reference.
|
| hasFragment |
returns whether this URI reference has a fragment part.
|
| getFragment |
returns the fragment part of this URI reference.
|
| setFragment |
sets the fragment part of this URI reference.
|
| clearFragment |
clears the fragment part of this URI reference.
|
| Methods' Details |
getUriReference
| string |
| getUriReference(); |
- Description
- returns the textual representation of the complete URI reference.
- Returns
- the textual representation of the complete URI reference. The exact
spelling of the URI reference is retained.
|
|
isAbsolute
- Description
- returns whether this URI reference is absolute or relative.
- Returns
- true if this URI reference is absolute, false if it is relative.
|
|
getScheme
- Description
- returns the scheme part of this (absolute) URI reference.
- Returns
- the textual representation of the scheme part (with the exact spelling
retained; without the delimiting “
: ”), if this
is an absolute URI reference; otherwise, an empty string is
returned.
|
|
getSchemeSpecificPart
| string |
| getSchemeSpecificPart(); |
- Description
- returns the scheme-specific part of this URI reference.
For an absolute URI reference, the scheme-specific part is everything
after the scheme part and the delimiting “: ”,
and before the optional “# ” and fragment part.
For a relative URI reference, the scheme-specific part is everything
before the optional “# ” and fragment part.
- Returns
- the textual representation of the scheme-specific part (with the exact
spelling retained).
|
|
isHierarchical
| boolean |
| isHierarchical(); |
- Description
- returns whether this URI reference is hierarchical or opaque.
An absolute URI reference is hierarchical if its scheme-specific part
starts with “/ ”. A relative URI reference is
always hierarchical.
- Returns
- true if this URI reference is hierarchical, false if it is opaque.
|
|
hasAuthority
- Description
- returns whether this (hierarchical) URI reference has an authority part.
- Returns
- true if this URI reference is hierarchical and has an authority part.
|
|
getAuthority
- Description
- returns the authority part of this (hierarchical) URI reference.
- Returns
- the textual representation of the authority part (with the exact spelling
retained), if this is a hierarchical URI reference that has an authority
part; otherwise, an empty
string is returned.
|
|
getPath
- Description
- returns the path part of this URI reference.
- Returns
- the textual representation of the path part (with the exact spelling
retained), if this is a hierarchical URI reference; for an opaque URI
reference, the scheme-specific part (with the exact spelling retained) is
returned.
|
|
hasRelativePath
| boolean |
| hasRelativePath(); |
- Description
- returns whether this (relative) URI reference has a relative path.
- Returns
- true if this URI reference is relative and has a relative path.
|
|
getPathSegmentCount
| long |
| getPathSegmentCount(); |
- Description
- returns the number of path segments of this (hierarchical) URI reference.
For an opaque URI reference, and for a hierarchical URI reference with
an empty path, the number of path segments is zero. For a hierarchical
URI reference with an absolute, non-empty path, the number of path
segments equals the number of “/ ” delimiters.
For a hierarchical URI reference with a relative, non-empty path, the
number of path segments equals the number of “/ ”
delimiters, plus one.
- Returns
- the number of path segments.
|
|
getPathSegment
| string |
| getPathSegment( |
[in] long |
index ); |
- Description
- returns a given path segment of this (hierarchical) URI reference.
- Parameter index
- the index of the path segment, starting at zero.
- Returns
- the textual representation of the given path segment (with the exact
spelling retained, without any delimiting “
/ ”),
if this URI reference is hierarchical and has that many path segments;
otherwise, and in particular if index is negative, an empty
string is returned.
|
|
hasQuery
- Description
- returns whether this (hierarchical) URI reference has a query part.
- Returns
- true if this URI reference is hierarchical and has a query part.
|
|
getQuery
- Description
- returns the query part of this (hierarchical) URI reference.
- Returns
- the textual representation of the query part (with the exact spelling
retained; without the delimiting “
? ”), if this
is a hierarchical URI reference that has a query part; otherwise, an
empty string is returned.
|
|
hasFragment
- Description
- returns whether this URI reference has a fragment part.
- Returns
- true if this URI reference has a fragment part.
|
|
getFragment
- Description
- returns the fragment part of this URI reference.
- Returns
- the textual representation of the fragment part (with the exact spelling
retained; without the delimiting “
# ”), if this
is a URI reference that has a fragment part; otherwise, an empty
string is returned.
|
|
setFragment
| void |
| setFragment( |
[in] string |
fragment ); |
- Description
- sets the fragment part of this URI reference.
- Parameter fragment
- the textual representation of the new fragment part. The exact spelling
will be preserved, and no escaping is performed.
|
|
clearFragment
- Description
- clears the fragment part of this URI reference.
|
|
Copyright © 2013, The Apache Software Foundation, Licensed under the Apache License, Version 2.0. Apache, the Apache feather logo, Apache OpenOffice and OpenOffice.org are trademarks of The Apache Software Foundation. Other names may be trademarks of their respective owners.


Turns a whole buffer into a base64 string.
Base-64 encoding is a way of taking binary data and turning it into a plain text. It is designed to carry data stored in binary format across the network channels. For example, you can use it to easily transfer images over the network.
| Box Name |
Type |
Description |
| Buffer Name |
String |
Name of the buffer |
| Variable |
String |
Variable to save the string value in |


Ayodhya Verdict: Will fulfil role of building Ram Mandir, says RSS chief Mohan Bhagwat
In its verdict on the Ayodhya land dispute case, the Supreme Court has ordered the Centre to form a trust, which will monitor the construction of the Ram temple, within three months
Rashtriya Swayamsevak Sangh (RSS) chief Mohan Bhagwat, on November 9, said that his organisation wholeheartedly welcomes the Supreme Court of India (SC)’s verdict in the Ayodhya land dispute case.
The Supreme Court, earlier in the day, had awarded the disputed land at Ayodhya to the Hindus party Ram Lalla Virajman, subject to certain conditions. It also ordered that an alternate plot of land must be awarded to the Sunni Waqf Board to construct a mosque.
In a press conference, after Chief Justice of India (CJI) Ranjan Gogoi read the unanimous verdict, Bhagwat said: "RSS welcomes the verdict. We want to thank all advocates. The people of India also deserve congratulations."
Also read: Judgement should not be seen as a win or loss for anybody, says PM Narendra Modi
While appealing to the people to express their "joy in a measured manner", Bhagwat told media persons, "We will all come together and fulfil our role for the construction of the Ram Mandir".
"This case was going on for decades and it has reached the right conclusion. This should not be seen as a win or loss. We also welcome everyone's efforts to maintain peace and harmony in society," the RSS chief added.
The Supreme Court has asked the Centre to form a trust, which will monitor the construction of the Ram temple, within three months.


It should be possible to invoke a Modal control on a trigger element (for example: button, datagrid row, etc). In this scenario you use a "data-modal" attribute on the Modal element that contains an ID selector that matches an existing piece of Modal markup. This configuration can be used for situations where the modal markup will be reused and reopened without too many resets/changes.


Bosnia: Lawmaker presents photos of alleged child abuse
by The Associated PressSARAJEVO, Bosnia — A Bosnian lawmaker has publicly shared shocking photos of children tied to beds and radiators in a public care home outside Sarajevo.
Sabina Cudic of the opposition Nasa Stranka party presented the photos ahead of a session of the parliament of one of the country’s two semi-autonomous parts, the Bosniak-Croat Federation.
Cudic said the photos were taken over the past year in the Pazaric care home for special needs children, and urged the parliament to discuss the issue.
Her initiative was rejected by the majority of lawmakers, but the parliament tasked one of its working groups to investigate the allegations and submit a report within a week.
Pazaric is already being investigated on suspicion of financial misconduct by the government-appointed management.
The Associated Press


Please note this does only factor the Offence-Defence, Independence-Interdependence, Irrationalism-Rationalism, and Actors-Structures axes.


{% extends "sentry/emails/security_base.html" %} {% block security_body %}
An authenticator has been removed from your Sentry account.


Event Location:
Microsoft Malaysia
Level 26, Menara 3 Petronas, KLCC
Kuala Lumpur, Kuala Lumpur, Malaysia
Abstract:
Receiving imperfectly column-aligned data from applications is becoming a norm. However preparing this data for pre-defined relational structures using traditional methods is becoming significantly complex. Many implementations though, still handle this using traditional programming techniques - but isn't this still a database related task? And shouldn't the components of the Database Management Systems bear the responsibility of getting this done? With new features incorporated into modern database platforms, processing unstructured data is no longer a challenge, and can be performed easily. Let us take a sample data set and see how we do this the Microsoft way, of course using Microsoft SQL Server product suite including cloud offerings such as HDInsight.
Speaker(s): Dinesh Priyankara,
Abstract:
Extended events to aid in performance tuning and in day to day administration specially when you don't have any benchmarking data for troubleshooting issues. In this session, we will see how the Extended Events streaming API can be used to process events in a near real-time. We will demonstrate how this feature enables new possibilities to capture real time problems without enabling any third party tools or inbuilt SQL Server features to capture issues like blocking, deadlocks, high CPU and many more. Extended Events were introduced in SQL Server 2008 but by SQL Server 2016, it has enhanced significantly. After this session, hopefully you will start using extended event, if you haven't started using till now.
Speaker(s): Dharmendra Keshari,
Abstract:
"Why my database performance has been suddenly slow? Have my query plans changed? Which plans have regressed and since when? Is there any way I can control the plan change without changing the source code?" If you have encountered any of the above situations, then query store is your remedy. SQL Server Query store is one of the path breaking features released in SQL Server 2016. The presentation will showcase how query store is a boon in handling sudden performance degradations, plan changes and analyzing query performance patterns over a period of time. Presentation will also demonstrate the power of query store in forcing query plans and compare it against options available in earlier versions of SQL Server. Presentation will have interesting demos on tracking plan regressions and on scenarios the use force plans feature. At the end of the session, audience will have a clear understanding on how query store becomes their new important weapon in their arsenal, for performance
Speaker(s): Nagaraj Venkatesan,
Abstract:
Data acquisition becomes extremely easier and companies start using huge amount of data to analyse customer behaviours, and to provide customers with more tailored service. Data analytics is become progressively important in services organisations. Among various data processing approaches machine learning is predominantly imperative. According to user’s interests, automatically predict things that have the same feature to the users is also a crucial part of user personalised service. If sophisticated visual analyses generate immediate results presented in ways that shows patterns and allow exploration people across all levels to make effective decisions. This session will highlight on Microsoft’s Azure, Power BI tools to explore relevant data sources.
Speaker(s): Dr. J. Joshua Thomas,
Abstract:
The recent past has shown us how the business intelligence landscape is shifting away from an IT-led paradigm to a business-led paradigm. This paradigm attempts to put the power of data in the hands of users for self-service. Power BI is Microsoft's self-service business intelligence offering, and is now standing out as a leader in self-service business intelligence. Join this session to learn what Power BI is all about and its capabilities. We'll then move over to various usage scenarios and how Power BI helps save the day. We will also take a look at how Power BI fronts the capabilities of advanced analytics on Azure, and brings it down to the end user.
Speaker(s): Gogula Aryalingam,
Abstract:
Start gaining the benefits of going to the Cloud for your Business Intelligence needs right now! In this session we will explore how we can start implementing and using both Azure SQL and Power BI together. The idea is to develop a demo template that audience can take away and start building their own real-world solution. Heck, we may even implement some cool Azure SQL features like operational analytic if time permits. ;-)
Speaker(s): Ian Choy,
Abstract:
Microsoft recently launched SQL Server 2016, which, in addition to many other great features, offers in-database advanced analytics with R Services, allowing users to combine the power of SQL Server and Microsoft R Server (or Open Source R), without data leaving the database. With SQL Server R Services, users can develop analytic models in a local R IDE and it has it's own template as well for support different industry needs.
Speaker(s): Dinesh Asanka,
Abstract:
High availability doesn't have to mean slow SQL server performance. In this informative webinar, Jason Aw, from SIOS Technology Corp. will share his practical strategies for boosting performance in these IO-intensive environments. He will also discuss the benefits of combining leading high performance storage platforms and high availability solutions to deliver continuous availability and faster application response times in SQL Server environments.
Speaker(s): Jason Aw,
Abstract:
At this session, we will discuss about how SQL Server Database Backup works internally and why your database backup process takes long time to be completed! By attending this session, you will learn how to optimize SQL Server Database Backup process.
Speaker(s): Hamid J. Fard,
Abstract:
This session covers the top new features in SQL Server 2016
Speaker(s): Chiu Kiang Phua,
Abstract:
Innovative Strategies for SQL Server Disaster Recovery
Speaker(s): Virendra Kumar Yaduvanshi,
Abstract:
Step-by-step walkthrough on how to use Azure Machine Learning to build a prediction model and API for a beginner's multiclass classification problem with sample dataset.
Speaker(s): Juv Chan,
Abstract:
Ease of access and easy life is now possible with On-premises and hybrid cloud technology within SQL Server 2016. SQL 2016 Hyperscale technology gives us a huge relief in Backups, Disaster Recovery solutions, access resources no matter whether they are in on-premises, private or public cloud. New tools within SQL Server 2016 and Microsoft Azure has made every single DBA/Developers life much easier to scale to the cloud. This session will enable you to start working on scaling to the cloud and benefit from the SQL Server 2016's advanced new features.
Speaker(s): Dr. Subramani Paramasivam,
Abstract:
SQL server indexes need to be effective so that data could be manipulated with minimum resource consumption. Having too few indexes will result in scanning full tables and having too many indexes will result in incurring un-necessary costs in keeping the index up-to-date. Even if the number of indexes "seem" sufficient, de-fragmenting is only one side of the story. In this session, we will cover index creation best practices and demo sql cache based index tuning, duplicate indexes, and more.
Speaker(s): Manjot Kaur,
This is a list of speakers from the XML Guidebook records. The details and URLs were valid at the time of the event.
LinkedIn: https://sg.linkedin.com/in/dharmendra-keshari-a7043398
Contact: http://dharmendrakeshari.com/
Dharmendra Keshari has strong and in-depth experience in Database Management. Currently, working as Senior Database Administrator at Micron Technology in Singapore and handling one of the most critical databases which are being used by Singapore Public Hospitals, national specialty centres and polyclinics. Dharmendra is an avid, regular mentor on social media, helping several enthusiast in solving their problems related to Database management. he is co-leader and regular speaker at Singapore SQL Server Pass Chapter (User Group). He has done certification for “Microsoft SQL Server#174; 2008, Implementation” and “Maintenance amp; Administering Microsoft SQL Server 2012 Database”.
LinkedIn: http://uk.linkedin.com/in/dageop
Contact: http://www.yoursqlman.com/index.php/blogs
Dr.SubraMANI Paramasivam is a Microsoft MVP, PhD, Microsoft Certified Trainer and Head of Data AI at DAGEOP Ltd having 21 years of DB, BI, Analytics and AI experience. Mani has also spoken in various events like MS IGNITE, PASS Summit, MS Inspire, SQLBITS, Power Platform Summit, Global AI Bootcamp, Data BI Summit, SQLRelay, Power BI World Tour, Data Platform Summit, INSIDESQL UK, Global AI Nights, SQLServerGeeks Summit, MCT Global Summits, Data Day Events and various user group events. Mani also believes in Empowering Every Person in the planet and spreads the awareness on Global challenges via www.EmpoweringEveryPerson.com. He is also a co-owner of 1 Global AI Meetup and 3 Power BI PUG PASS local / user groups.
Darien has over 30 years of IT experience including former positions at TIBCO and Microsoft. Darien has worked across Australia and Southeast Asia including as Specialist Director at Microsoft Malaysia. An accomplished Cloud Computing seller and recognised best-practices global speaker, Darien is a believer in a future of Platform-as-a-Service-based cloud applications. His expertise includes establishing and embracing a customer's cloud journey and jointly developing a cloud technology roadmap incorporating some quick value-based wins up front. His current technologies and solutions expertise are too broad to mention here but include Linux and Windows virtual machines in the cloud, SAP on Microsoft Azure, SQL Server and BI, and many more.
Chiu Kiang is the principal of PCK Consulting, a provider for SQL Server and Microsoft .NET development and consulting services. He works with customers and partners on technologies covering data management, business intelligence, performance tuning and enterprise integration. He is currently in his 11th year in his role as a Microsoft MVP for SQL Server.
LinkedIn: http://lk.linkedin.com/in/dineshpriyankara/
Contact: http://dinesql.blogspot.com/
Dinesh is an experienced professional and database enthusiast with skills in database management systems and business intelligence. Possessing over 18 years of experience on data related technologies, he does training, consulting, and is a top contributor to the local SQL Server community. In recognition of his contributions and expertise he has demonstrated, he was awarded the Microsoft Most Valuable Professional (MVP) award for SQL Server for 13 consecutive years since 2006. He is a Subject Matter Expert on SQL Server exams and has contributed for SQL Server 2012, 2016, 2017 and Azure Data Engineering exam development and Job Task Analysis (JTA). Dinesh is the Founder/Principal Architect of dinesQL (Pvt) Ltd (http://dinesql.com). In his
I have been working with SQL server for over 10 years. I have been an internal DBA and a consultant. I am passionate about automation, cloud technologies, performance tuning and learning SQL internals.
LinkedIn: https://my.linkedin.com/pub/dehhui-chuan/1/271/a66
Deh Hui brings with her a breadth of marketing, business and technology experience on the data platform, having started off as a Microsoft Certified Professional on SQL Server early in her career, having done business analysis with data tools - SAS/ SPSS and now marketing the data platform stack - SQL Server, Power BI, Datazen, Revolution Analytics. She is well recognized having won accolades such as NextGen Marketing Leader, Leadership Development and Talent Acceleration programs.
LinkedIn: https://www.linkedin.com/in/virendrayaduvanshi
Contact: https://wikidba.net/
Competent, accomplished and result oriented information technology specialist with 20 years of experience, Dynamic leadership career, and demonstrated success in designing and implementing Database with emphasis on System Administration, Database Administration, Technologies deployment and technical analysis of multi-client operations, Innovative, result-driven leader with diverse IT experience emphasizing cross platform systems and network architecture, engineering, installation/implementation, integration, security and Administration for a VLDBs projects. MCTS, MCITP and ITIL - applies broad technical expertise to resolve complex systems and DBs issues associated with progressive growth/expansion.
LinkedIn: https://my.linkedin.com/in/juv-chan-6104a540
Microsoft Azure MVP https://mvp.microsoft.com/en-us/PublicProfile/5002031
LinkedIn: https://www.linkedin.com/in/awjason
Contact: http://www.sios-apac.com/
A passionate IT leader with over 20 years of experience in in technology, infrastructure, cloud environments particularly with high availability and disaster recovery solutions for different architectures including SQL database applications.
Ian Choy is Microsoft#39;s Technology Solution Professional for the data platform business, working with customers on Microsoft data platform adoption, architecture design decisions and best practices. His work and passion involves partner enablement on upcoming Microsoft technology and involvement community events. Prior experiences includes managing large scale data warehouse operations, business intelligence implementations and software development projects.
LinkedIn: https://lk.linkedin.com/in/dineshasanka
Contact: http://htttp://dbfriend.blogspot.com
Dinesh Asanka MVP for more than 8 years and has experience over 15 years with SQL Server different versions. He has spoken in Sri Lanka as well as out side conferences. Regular writer at SQL-Server-Performance.com and co-authored couple of books on SQL Server. Visiting Lecturer at Sri Lanka Institute of Information Technology (SLIIT), Sri Lanka on subjects such as Database Administration, Big Data Analytics, Data Security, Data warehousing amp; Data Mining at B.Sc and M.Sc level. Currently, reading for Mphil in the areas of data warehouse and fuzzy technology at University of Moratuwa, Sri Lanka.
LinkedIn: https://in.linkedin.com/in/nagaraj-venkatesan-b6958b6
Contact: http://strictlysql.blogspot.com
Nagaraj Venkatesan is a Data Platform MVP from Singapore and the leader of Singapore SQL PASS Chapter. As a SQL Server enthusiast, Nagaraj is a regular speaker in Asia Pacific region at Data Platform events like SQL Saturdays, SQL Server Geeks Summit, User group meetups etc. Nagaraj shares his technical expertise at strictlysql.blogspot.com. Nagaraj also runs a YouTube channel called "DataChannel", which contains technical interviews with top Microsoft Data Platform experts in the world.
LinkedIn: https://my.linkedin.com/in/hamidjfard
I am SQL Server Data BI Platform Expert with more than 9 years’ of professional experience, I am currently Microsoft Certified Master: SQL Server 2008, Microsoft Certified Solutions Master: Charter-Data Platform, Microsoft Data Platform MVP and CIW Database Design Specialist. After a few years of being a production database administrator I jumped into the role of Data Platform Expert. Being a consultant allows me to work directly with customers to help solve questions regarding database issues for SQL Server.
Dr. J. Joshua Thomas, MSc, Ph.D., is currently a senior lecturer in department of computing at the School of Engineering, Computing and Built Environment, KDU Penang University College. He received his PhD in Intelligent Systems Techniques from University Sains Malaysia. He is currently work with machine learning (Deep learning) problems in computer vision, cross industry standard process for data science/mining (CRISP-DM) targeting manufacturing sensor dataset modelling, evaluation and deployment, Big data visual analytics and its applications. He has published academic articles from his research domain as book chapters, journal articles and conference proceedings. He has experience in Microsoft PowerBI, Azure Machine Learning studio.
LinkedIn: http://www.linkedin.com/in/gogula
Contact: http://datamaul.wordpress.com
Gogula is a data analytics professional from Sri Lanka, with 14+ years on the Microsoft data platform. He has worked with many aspects of data analytics and BI solutions from architecting, designing, developing and consulting across various industries and verticals. He is Regional Mentor for PASS South Asia, Data Platform MVP, MCSE, former MCT, and MSc in IT. Gogula's passion revolves data analytics and BI; hence enjoys writing, teaching and speaking about the things he works with. He was also involved as an SME for Microsoft certification development. He currently juggles his full time job as Lead Architect while speaking at local and foreign events, along with regular stints at the Sri Lankan Data Community which he co-founded.
The following is a list of sponsors that helped fund the event.


Bafana ‘Can’t Be Happy, But…’
by Soccer LadumaA win is a win, as they say, but Thulani Hlatshwayo has admitted that Bafana Bafana aren’t completely happy with the fact that they only scored once against Sudan at the weekend.
Watch: Phiri’s Piledriver For Bafana
‘Tyson’ was at the heart of Bafana’s defence once again on Sunday afternoon as the captain led Molefi Ntseki’s troops out to battle against the Sudanese at Orlando Stadium, with Lebogang Phiri’s single goal proving to be the difference as South Africa picked up the first three points of their 2021 Africa Cup of Nations qualifying campaign.
Ntseki’s side had plenty of chances to put the game to bed over 90 minutes, and also had a goal disallowed – correctly – for offside in the final 10 minutes, but it was Phiri’s goal just before the stroke of half-time that gave them the victory.
Speaking to the media after the game, the Bafana skipper insisted that the win was the most important thing, saying, “The most important thing for us was to recover… Yes, we can’t be happy with the performance overall because we could have scored more goals, but we’re happy with the three points that we’ve got.
Meanwhile, when asked about a change of partner at centre back after Erick Mathoho replaced Buhle Mkhwanazi, Hlatshwayo added, “Everyone is important in the team… I’m happy for Tower to have come in, though the coach didn’t really explain why he took Buhle out, but it’s a country, everyone is putting their hands up.”
Read: SuperSport To Plan For Life After Furman?
Bafana now have a lengthy break before Ntseki will get to work with them again as they wait for March’s 2022 World Cup qualifiers, and they will be pleased to go into that period on the back of a win.
Download The Soccer Laduma Social Media App & Earn Airtime for Selfies!


--- layout: post status: publish published: true title: New & re-awared MVPs author: display_name: Tomas Restrepo login: tomasr email<EMAIL_ADDRESS>url: http://winterdom.com/ author_login: tomasr author_email<EMAIL_ADDRESS>author_url: http://winterdom.com/ wordpress_id: 405 wordpress_url: http://winterdom.com/2005/01/newreawaredmvps date: '2005-01-05 19:16:14 +0000' date_gmt: '2005-01-05 19:16:14 +0000' categories: - Personal tags: [] comments: [] ---
Congratulations are in order for Sam for getting re-awarded as an MVP; and most specially for Robert for getting awarded for the first time... most deserved, imho! Way to go, dudes!


Check to see if the specified object, left
, matches, and report the result in
the returned MatchResult
.
Check to see if the specified object, left
, matches, and report the result in
the returned MatchResult
. The parameter is named left
, because it is
usually the value to the left of a should
or must
invocation. For example,
in:
list should equal (List(1, 2, 3))
The equal (List(1, 2, 3))
expression results in a matcher that holds a reference to the
right value, List(1, 2, 3)
. The should
method invokes apply
on this matcher, passing in list
, which is therefore the "left
" value. The
matcher will compare the list
(the left
value) with List(1, 2, 3)
(the right
value), and report the result in the returned MatchResult
.
the value against which to match
the MatchResult
that represents the result of the match
Trait extended by objects that can match a value of the specified type. The value to match is passed to the matcher's
apply
method. The result is aMatchResult
. A matcher is, therefore, a function from the specified type,T
, to aMatchResult
.Creating custom matchers
If none of the built-in matcher syntax satisfy a particular need you have, you can create custom
Matcher
s that allow you to place your own syntax directly aftershould
ormust
. For example, classjava.io.File
has a methodexists
, which indicates whether a file of a certain path and name exists. Because theexists
method takes no parameters and returnsBoolean
, you can call it usingbe
with a symbol orBePropertyMatcher
, yielding assertions like:Although these expressions will achieve your goal of throwing a
TestFailedException
if the file does not exist, they don't produce the most readable code because the English is either incorrect or awkward. In this case, you might want to create a customMatcher[java.io.File]
namedexist
, which you could then use to write expressions like:One good way to organize custom matchers is to place them inside one or more traits that you can then mix into the suites or specs that need them. Here's an example:
Note: the
CustomMatchers
companion object exists to make it easy to bring the matchers defined in this trait into scope via importing, instead of mixing in the trait. The ability to import them is useful, for example, when you want to use the matchers defined in a trait in the Scala interpreter console.This trait contains one matcher class,
FileExistsMatcher
, and aval
namedexist
that refers to an instance ofFileExistsMatcher
. Because the class extendsMatcher[java.io.File]
, the compiler will only allow it be used to match against instances ofjava.io.File
. A matcher must declare anapply
method that takes the type decared inMatcher
's type parameter, in this casejava.io.File
. The apply method will return aMatchResult
whosematches
field will indicate whether the match succeeded. ThefailureMessage
field will provide a programmer-friendly error message indicating, in the event of a match failure, what caused the match to fail.The
FileExistsMatcher
matcher in this example determines success by callingexists
on the passedjava.io.File
. It does this in the first argument passed to theMatchResult
factory method:In other words, if the file exists, this matcher matches. The next argument to
MatchResult
's factory method produces the failure message string:If the passed
java.io.File
is a file (not a directory) and has the nametemp.txt
, for example, the failure message would be:For more information on the fields in a
MatchResult
, including the subsequent three fields that follow the failure message, please see the documentation forMatchResult
.Given the
CustomMatchers
trait as defined above, you can use theexist
syntax in any suite or spec in which you mix in the trait:Note that when you use custom
Matcher
s, you will need to put parentheses around the custom matcher when if followsnot
, as shown in the last assertion above:tempFile should not (exist)
.Matcher's variance
Matcher
is contravariant in its type parameter,T
, to make its use more flexible. As an example, consider the hierarchy:Given an orange:
The expression "
orange should
" will, via an implicit conversion inShouldMatchers
, result in an object that has ashould
method that takes aMatcher[Orange]
. If the static type of the matcher being passed toshould
isMatcher[Valencia]
it shouldn't (and won't) compile. The reason it shouldn't compile is that the left value is anOrange
, but not necessarily aValencia
, and aMatcher[Valencia]
only knows how to match against aValencia
. The reason it won't compile is given thatMatcher
is contravariant in its type parameter,T
, aMatcher[Valencia]
is not a subtype ofMatcher[Orange]
.By contrast, if the static type of the matcher being passed to
should
isMatcher[Fruit]
, it should (and will) compile. The reason it should compile is that given the left value is anOrange
, it is also aFruit
, and aMatcher[Fruit]
knows how to match againstFruit
s. The reason it will compile is that given thatMatcher
is contravariant in its type parameter,T
, aMatcher[Fruit]
is indeed a subtype ofMatcher[Orange]
.


The facet browser facilitates overview and explorative searching, by presenting a list of selected facets with tags derived from the search result.
A search for eventyr (fairy tales) could yield
Tags can be sorted according to popularity (e.g. the number of hits from the search result that had the given tag) or in normal alpha-numeric order.
A design criteria was complete facet browsing, which means that all hits from the search is used for creation of the overview. On a modern (by late 2006 standards) dual-processor machine, about 3 million hits can be processed per second.
The facet browser relies on a cache of the wanted facets, which takes some minutes to build for an index with a few million documents. An iterative approach to updating of the cache is on the drawing board.
The timestamp follows ISO standard notation: YYYMMDD-HHMMSS. The timestamps refers to creation time, not last update.


From:Chandler Bob To:Peng Gary ; Saunders James Sent:2017-01-11T04:37:10.0000000Z Subject:FW: TW-COGS
The attached spreadsheet shows the quarterly reclasses between O&M and COGS for Transwestern for the year 2000. As we discussed, we are very supportive of making this 2000 reclass in order to avoid having to explain large year to year variances caused only by the re-mapping. It will also conform Enron's reporting to TW's stand-alone GAAP reporting for 2000. Please call if you have any questions.
Thanks for helping us make this happen.
-----Original Message-----
From: Joe, Allen
Sent: Friday, October 12, 2001 11:05 AM
To: Chandler, Bob
Cc: Walters Jr., Harry; Dimacali, Aurora; Zahn, Gary
Subject: TW-COGS
Per your request. Proposed restatement of CY 2000 TW COGS to O&M
***********
EDRM Enron Email Data Set has been produced in EML, PST and NSF format by ZL Technologies, Inc. This Data Set is licensed under a Creative Commons Attribution 3.0 United States License <http://creativecommons.org/licenses/by/3.0/us/> . To provide attribution, please cite to "ZL Technologies, Inc. (http://www.zlti.com)."
***********
California


Get into a high plank position. Place your hand firlmy on the gorund, directly under shoulders. Ground your toes intothe floor to stabilize your lower half. Lower your body.  Don't let your butt dip or stick out at any point. Push back up. Exhale as you push back to the starting position.


Setup WiFi
Connect To Wifi Network
Create Wifi Network (AP)
Create and Connect to Wifi Network (AP/Term)
WiFi SSID:
WiFi Password:
Show Password
Save WiFi settings
Scan WiFi
RSSI (dBm)
Channel
Authorisation
Scan WiFi Networks


Firewatch and Dementia in gaming.
I've just finished up playing Firewatch and I loved it. I just wanted to thank Campo Santo for the game and for including dementia in it. I thought it gave an interesting edge to the story. I thought I'd share it here too:
This isn't a support request, I just wanted to reach out to you guys and this is the only email I could find. Thank you for making this game. I first found out about it maybe a year ago when someone posted up an Android homescreen using artwork from the game and it's been my background on my desktop, at work and on my phone. It's just so beautiful!
Then the game came out and the intro really hit me. My Grandad had dementia and before he went into a home I remember going round to visit. He greeted us at the door, my mum, my dad and as I stepped up to the door he turned and ask kindly "and who are you?". You should never have to introduce yourself as "Your grandson." It was so weird. I have no idea how it made him feel but I never saw him again after that. I couldn't deal with it and I didn't want to put him through the same thing again. The intro just brought all that back to me and I just wasn't expecting that kind of story in this game.
I just want to say thank you for including dementia in this game and getting it so spot on.
Thanks for the awesome game and I look forward to the next (and my photos)!
Regards,
Andy Burne


Copyright © 1999-2020 Member of the Open Biological Ontologies Foundry The Gene Ontology Consortium is supported by a P41 grant from the National Human Genome Research Institute (NHGRI) [grant U41 HG002273]


cake
The command-line processor for the CakePHP framework.
More information: home page
- Display basic information about the current app and available commands:
cake
- Display a list of available routes:
cake routes
- Clear configuration caches:
cake cache clear_all
- Build the metadata cache:
cake schema_cache build --connection connection
- Clear the metadata cache:
cake schema_cache clear
- Clear a single cache table:
cake schema_cache clear table_name
- Start a development web server (defaults to port 8765):
cake server
- Start a REPL (interactive shell):
cake console


Battling Stereotype Threats
Self-Affirmation
June 13th, 2015
Stereotype Threat by Claude M. Steele argues that minorities can protect themselves from stereotype threat by practicing self-affirmation. This can be done through deliberate focus on values and skills that are important to themselves. In this blog, I will practice self-affirmation in hope of combating stereotype threat during my stay at San Francisco.
Values that are important to me:
| Values | How well I do |
| Accomplishments | 4 |
| Dependability | 5 |
| Competence | 3 |
| Fairness | 4 |
| Coolness under fire | 2 |
| Personal Development | 3 |
Of all the values, dependability is one of the most important one to me. There's rarely occasions to question and distrust someone who is known for being dependable and reliable. When I say I will do something, you can rest assure that it'll be done and done well. In every day life, I show this by being punctual, getting errands done on time, and only accepting work and the volume of work that I'm comfortable with. My expectations of others are similar in that if they have committed to do something; I rely on them heavily to get it done. And I know others rely on me as well and I hate letting people down so I highly value dependability.
Recently a friend talked to me about fairness at work in a restaurant. The bartenders always seem to earn more in tip and the servers have to tip them out at the end of the night as well. I greatly value fairness in all environments. When she described the scenario though, I did not think it was all that unfair. We talked about the level of skills and training the bartenders must acquire in order to be competent enough to earn good tips. We also talked about the level of responsibility and duties that the bartenders must assume that are well above and beyond those of the servers'. At the end of the discussion, we mutually agreed that in terms of fairness, so long as she has an equal opportunity to train and work as a bartender then all is fair to her.
Through writing this blog, I feel like a made progress in defending myself against stereotype threats. I have to constantly remind myself of what values are important to me and how I can get better at living those values. Other exercises that I would recommend include being aware of the stereotypes that I maybe placing on others. I recommend looking for examples of people that are far from stereotypical and let them break our preconceived notions.
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Moist Muffins
Category: Desert
Today we're cooking moist muffins, a very delicious desert.Read more...
Choose the type of display:
Category: Desert
Today we're cooking moist muffins, a very delicious desert.Read more...
Category: Appetizer
Today we're cooking a very delicios appetizer suited for any occasion. Read more...
Category: Dinner
Today we're cooking pastas!Get ready to be amazed! Read more...
Category: Breakfast
Today we're cooking a very delicious, very easy-to-make healthy breakfast! Read more...


It looks like you're trying to install Elefant into a sub-folder.
Elefant's CMS was designed to run a complete website, and needs to be installed in the root of a site to function correctly. Please move Elefant to the root folder to continue, or use a sub-domain of your site to install it under.
Click here for instructions on configuring virtual hosts for development.
(Check your host for instructions on setting up sub-domains in production.)
{% else %}Welcome to the Elefant CMS installer.
This installer will guide you through the process of installing and configuring your new website.
If you have any trouble during the install process, please visit the Elefant project at the following link to report it, and we'll do our best to help:
http://github.com/jbroadway/elefant
Click "Next" to continue whenever you're ready. Thanks for using Elefant!
{% end %}


If one wants to summarise our knowledge of physics in the briefest possible terms, there are three really fundamental observations:
1. Spacetime is a pseudo-Riemannian manifold M, endowed with a metric tensor and governed by geometrical laws.
2. Over $M$ is a principle bundle $P_{G}$ with a non-abelian structure group $G$.
3. Fermions are sections of $(\hat{S}_{+}\otimes{}V_{R})\oplus(\hat{S}\_\otimes{}V_{\bar{R}})$ . $R$ and $\bar{R}$ are not isomorphic; their failure to be isomorphic explains why the light fermions are light.
All of this must be supplemented with the understanding that the geometrical laws obeyed by the metric tensor, the gauge fields, and the fermions are to be interpreted in quantum mechanical terms.


Xmla.Dataset Class
This class implements an XML/A multidimensional Dataset object.
You do not need to instantiate objects of this class yourself.
Rather, the Xmla
class will instantiate this class
to convey the result of the executeMultiDimensional
method
(see executeMultiDimensional()
),
and possibly the execute
method.
(Note that the execute()
instantiates either the
Xmla.Rowset
or the Xmla.Dataset
class
depending on the value of the Format
property in the options passed to the execute()
method.)
An instance of the Xmla.Dataset
class may be returned immediately as return value from these methods when doing a synchronous request.
In addition, the Xmla.Dataset
object is available in the eventdata passed to any registered listeners
(see addListener()
).
Constructor
Xmla.Dataset
-
doc
Parameters:
-
doc
DOMDocumentThe responseXML result returned by server in response to a
Execute
request.
Item Index
Methods
Properties
- AXIS_CHAPTERS static
- AXIS_COLUMNS static
- AXIS_PAGES static
- AXIS_ROWS static
- AXIS_SECTIONS static
- AXIS_SLICER static
Methods
axisCount
()
Int
Get the number of proper axes in this Dataset. This is the number of axes that appears in the SELECT
list, and excludes the slicer axis.
Returns:
cellOrdinalForTupleIndexes
-
A
Calculate the cellset ordinal for the argument tuple indexes.
This method accepts a variable number of tuple indexes. One integer argument must be passed for each proper axis (excluding the slicer axis). Each integer arguments represent the index of a tuple on the respective axis.
The arguments must be specified by descending axis order. So if the data set has two axes (a row and a column axis), this method expects the tuple index of a tuple on the row axis first, and after that, the tuple index on the column axis.
The method returns an integer that represents the ordinal of the cell identified by the tuples specified by the tuple index arguments.
One could use this ordinal as argument to the getByOrdinal()
method of this Dataset's Cellset
.
Instead of calling this method and passing the result into the Cellsets getByOrdinal()
method,
you can call the getByTupleIndexes()
method of this Dataset's Cellset
.
Parameters:
-
A
Intvariable number of integer tuple indexes. Tuple indexes should be passed in descending order of axes.
Returns:
The ordinal number that identifies the cell from this Dataset's Xmla.Dataset.Cellset
that belongs to the tuples identified by the arguments.
close
()
Cleanup this Dataset object.
fetchAsObject
()
Object
Gets all of the XML data into one JS object. The object consists of the following members:
axes
: An array of objects that represent the query axes (but not the slicer axis). Each axis has apositions
member which is an array of tuples, and ahierarchies
member, which is an array of hierarchies.slicerAxis
: An object that represents the slicer axis, or null if there is no slicer axis.cells
: An array of cell objects, representing the cellset.
Returns:
getAxis
-
nameOrIndex
Get the axis specified by the argument index or name.
If the axis does not exist, an INVALID_AXIS
exception is thrown.
To prevent an exception from being thrown, you should call the hasAxis()
method to determine if the axis exists.
Alternatively, you can call axisCount()
, and use an integer argument between zero (inclusive) and axis count (exclusive).
Parameters:
-
nameOrIndex
String | intFor int arguments, a value of 0 up to the number of axes. You can also use one of the
AXIS_xxx
constants. For string arguments, this method will match the name of the axis as it is returned in the XML/A response. These names are of the formAxisN
where N is an ordinal that identifies the axis.
Returns:
The Xmla.Dataset.Axis
object that corresponds to the argument.
getCellset
()
Xmla.Dataset.Cellset
Get the Cellset object.
Returns:
The Xmla.Dataset.Cellset
object.
getChapterAxis
()
Xmla.Dataset.Axis
Get the Chapter axis. This is the fifth axis, and has ordinal 4. If the chapter axis doesn't exist, an INVALID_AXIS
exception is thrown.
To prevent an exception from being thrown, you should call the hasChapterAxis()
method to determine if the axis exists.
Returns:
The chapter Xmla.Dataset.Axis
object.
getColumnAxis
()
Xmla.Dataset.Axis
Get the Column axis. This is the first axis, and has ordinal 0. If the column axis doesn't exist, an INVALID_AXIS
exception is thrown.
To prevent an exception from being thrown, you should call the hasColumnAxis()
method to determine if the axis exists.
Returns:
The column Xmla.Dataset.Axis
object.
getPageAxis
()
Xmla.Dataset.Axis
Get the Page axis. This is the third axis, and has ordinal 2. If the page axis doesn't exist, an INVALID_AXIS
exception is thrown.
To prevent an exception from being thrown, you should call the hasPageAxis()
method to determine if the axis exists.
Returns:
The page Xmla.Dataset.Axis
object.
getRowAxis
()
Xmla.Dataset.Axis
Get the Row axis. This is the second axis, and has ordinal 1. If the row axis doesn't exist, an INVALID_AXIS
exception is thrown.
To prevent an exception from being thrown, you should call the hasRowAxis()
method to determine if the axis exists.
Returns:
The row Xmla.Dataset.Axis
object.
getSectionAxis
()
Xmla.Dataset.Axis
Get the Section axis. This is the fourth axis, and has ordinal 3. If the section axis doesn't exist, an INVALID_AXIS
exception is thrown.
To prevent an exception from being thrown, you should call the hasSectionAxis()
method to determine if the axis exists.
Returns:
The section Xmla.Dataset.Axis
object.
getSlicerAxis
()
Xmla.Dataset.Axis
Get the Slicer axis. This is the axis that appears in the WHERE
clause of the MDX statement.
Returns:
The slicer Xmla.Dataset.Axis
object.
hasAxis
-
nameOrIndex
Determine if the axis specified by the argument exists.
Parameters:
-
nameOrIndex
String | intFor int arguments, a value of 0 up to the number of axes. You can also use one of the
AXIS_xxx
constants. For string arguments, this method will match the name of the axis as it is returned in the XML/A response. These names are of the formAxisN
where N is an ordinal that identifies the axis.
Returns:
true
if the specified axis exists, false
if it doesn't exist.
hasChapterAxis
()
Boolean
Determine if the chapter axis exists.
Returns:
true
if the chapter axis exists, false
if it doesn't exist.
hasColumnAxis
()
Boolean
Determine if the column axis exists.
Returns:
true
if the column axis exists, false
if it doesn't exist.
hasPageAxis
()
Boolean
Determine if the page axis exists.
Returns:
true
if the page axis exists, false
if it doesn't exist.
hasRowAxis
()
Boolean
Determine if the row axis exists.
Returns:
true
if the row axis exists, false
if it doesn't exist.
hasSectionAxis
()
Boolean
Determine if the section axis exists.
Returns:
true
if the section axis exists, false
if it doesn't exist.
hasSlicerAxis
()
Boolean
Determine if the slicer axis exists.
Returns:
true
if the slicer axis exists, false
if it doesn't exist.
Properties
AXIS_CHAPTERS
Int
final
static
Can be used as argument for getAxis()
to get the fifth axis (the chapters axis).
Alternatively you can simply call getChapterAxis()
Default: 4
AXIS_COLUMNS
Int
final
static
Can be used as argument for getAxis()
to get the first axis (the column axis).
Alternatively you can simply call getColumnAxis()
Default: 0
AXIS_PAGES
Int
final
static
Can be used as argument for getAxis()
to get the third axis (the page axis).
Alternatively you can simply call getPageAxis()
Default: 2
AXIS_ROWS
Int
final
static
Can be used as argument for getAxis()
to get the second axis (the row axis).
Alternatively you can simply call getRowAxis()
Default: 1
AXIS_SECTIONS
Int
final
static
Can be used as argument for getAxis()
to get the fourth axis (the section axis).
Alternatively you can simply call getSectionAxis()
Default: 3
AXIS_SLICER
String
final
static
Can be used as argument for getAxis()
to get the slicer axis
(the axis that appears in the WHERE
clause of an MDX-SELECT
statement).
Alternatively you can simply call getSlicerAxis()
Default: SlicerAxis


--- layout: default ---
I give the majority of his photos away for free on Unsplash & Flickr. I rely on your support to make this happen. Please donate what you can to show your support using the secure link below.


Grenade attack close to military training facility in Kabul leaves 5 wounded
by Khaama PressUnknown gunmen hurled hand grenades close to a military training facility in Kabul city earlier today which left at least five people wounded.
Nasrat Rahimi, a spokesman for the Ministry of Interior confirmed that the gunmen hurled two hand grenade close to Kabul Military Training Center at around 7:30 am local time.
Rahimi further added that the attack wounded five people including Afghan National Army personnel and a civilian.
No group individual or group including Taliban militants has so far claimed responsibility for the attack.
Author
-
The Khaama Press News Agency is the leading and largest English news service for Afghanistan with over 3 million hits a month. Independent authors/columnists and experts are welcomed to contribute stories, opinions and editorials. Send stories to news@khaama.com.


Cannot find that user account in the legacy system. Maybe try linking other provider?
This user account was already bound to identity in the new system. Maybe try linking other provider?
This user account was already tied to the new system.
Invalid migration code. Please start over.
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No email associated with that user ID. Please go to www.touchdevelop.com and set your email first.
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The code is invalid; please try again
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We need an activation code here, not user password.
The user account doesn't exist anymore.
This code has already been used.
We need an activation code here, not group code.
Group owner is out of activation credits.
This code cannot be entered here. Sorry.
This nickname is not allowed.
Cannot verify email - no such user.
Cannot verify email - invalid or expired code.
Thank you, your email was updated.


--- layout: default nav_bar_title: Home nav_bar_index: 1 ---
Hi! I'm Zach Kirsch, a senior at Tufts University pursuing degrees in Computer Science and Math.


Struts 1 (or just 'Struts') has been superseded by Struts 2 in recent years. There is still a huge community for Struts 1 web applications though.
To configure PicoContainer to handle the dependency injection of Struts actions, refer to the web.xml below.
PicoContainer-Web and Struts1 Webapp webapp-composer-class *your web app composer class name* picoFilter org.picocontainer.web.struts.PicoActionFactory$ServletFilter picoFilter *.do org.picocontainer.web.PicoServletContainerListener action org.apache.struts.action.ActionServlet config /WEB-INF/struts-config.xml 2 action *.do index.html
Things are different in the struts-config.xml file though - there is a PicoContainer enabled RequestProcessor:
With this design you can use Constructor Injection and three tier container scoping for Struts web applications. Make sure you make and configure your own WebappComposer implementation.
See downloads on how to download the struts module either using Maven or by downloading full distribution.
We have a sample application. It is a small form-style web-app that shows and list of cheeses, allows you to add and delete from the list. See the Maven2 source for it. Here is a screenshot of it running:
Download the war file for it (full Java source in WEB-INF/classes).


Harms Lab
University of Oregon
How does evolution assemble such an amazing diversity of proteins?
We use ancestral sequence reconstruction to trace the evolution of proteins
We use ancestral sequence reconstruction to trace the evolution of proteins
We use ancestral sequence reconstruction to trace the evolution of proteins
We use ancestral sequence reconstruction to trace the evolution of proteins
We use ancestral sequence reconstruction to trace the evolution of proteins
We use ancestral sequence reconstruction to trace the evolution of proteins
We use ancestral sequence reconstruction to trace the evolution of proteins
Some Questions:
- How does this blind process put together integrated, complicated machines?
- Are there common mechanisms of evolutionary change at the molecular level (and what are they)?
- Is protein evolution predictable?
- Practically: how can we effectively navigate sequence space to new protein functions?
(Partial) answers to these questions lie at the interface of biochemistry and evolution
(Partial) answers to these questions lie at the interface of biochemistry and evolution
(Partial) answers to these questions lie at the interface of biochemistry and evolution
How should we think about this relationship?
Sequence space: how does the word RAGE evolve into COST?
English shapes possible trajectories
Smith JM (1970), Nature (doi:10.1038/225563a0)
Sequence space: how does the word RAGE evolve into COST?
English shapes possible trajectories
Smith JM (1970), Nature (doi:10.1038/225563a0)
Sequence space: how does the word RAGE evolve into COST?
English shapes possible trajectories
Smith JM (1970), Nature (doi:10.1038/225563a0)
Biochemistry determines the distribution of function in sequence space
Evolutionary processes determine moves through the space
Lab approaches:
- Trace historical changes in protein function.
- Study sequence space itself.
Today: describe two projects
Luke Wheeler: Promiscuity and specificity in the evolution of S100 proteins
Zach Sailer: High-order epistasis in genotype-phenotype maps
S100 proteins are small, $Ca^{2+}$ binding proteins: the lab workhorses!
S100 proteins bind short peptide regions of target proteins.
PDB: 1K9P, 2JTT
Otterbein et al. (2002) Structure 10: 557-567
Lee et al. (2008) Biochemistry 47: 10921-10932
S100 proteins bind short peptide regions of target proteins.
PDB: 1K9P, 2JTT
Otterbein et al. (2002) Structure 10: 557-567
Lee et al. (2008) Biochemistry 47: 10921-10932
Peptide binding occurs in a $Ca^{2+}$-dependent manner
The S100 protein family has expanded radically across the vertebrates
Different S100 proteins have evolved a huge variety of functions:
- Regulation of cell motility and proliferation
- Metal transport/sequestration
- Direct antimicrobial activity
- Pro-inflammatory signaling
- Substrate transport
S100A5 and S100A6 have different functions
S100A6 promotes cell motility and proliferation
- Inhibits p53 tetramerization
- Binds to proteins (annexins, calponin, tropomyosin), triggering cell motility
- Is a marker for metastasis and malignancy
S100A5 is involved in olfaction
- One identified target (a $Na/Ca^{2+}$ transporter)
- Massive increase in expression in olfactory sensory neurons upon olfactory stimulation
S100A5 and S100A6 arose by gene duplication in the ancestor of amniotes
S100A5 and S100A6 bind to different targets
Liriano (2012), Streicher et al. (2009) Biochemistry 48(12):2788
Modern orthologs share common binding specificity
How did their target specficity evolve?
- What changed with respect to specificity?
- What mutations were involved?
- How did these mutations exert their effect?
We reconstructed ancA5/A6, the last common ancestor of S100A5 and S100A6
Ancestor folds and responds to $Ca^{2+}$
Peptide target binding is strictly $Ca^{2+}$-dependent
What was the ancestral binding specificity?
Ancestor (apparently) binds to more targets than modern S100A5 and S100A6
Maybe this is an example of a protein that went from promiscuity to specificity?
- New interactions often start as promiscuous interactions that are refined
- Subfunctionalization of a promiscuous ancestor could lead to two more specific descendences
- Proteins need fewer specificty "rules" to "parse" less chemically complex past environments
But is this really an example of ancestral promiscuity?
Just how should we measure promiscuity, anyway?
Measuring changes in ancestral binding requires an unbiased sample of targets
Measuring changes in ancestral binding requires an unbiased sample of targets
Measuring changes in ancestral binding requires an unbiased sample of targets
Measuring changes in ancestral binding requires an unbiased sample of targets
Strategy: use phage display to measure an unbiased sample of peptide targets
Human S100A5 and S100A6 both bind to a large number of partners, many of them shared
Human S100A5 and S100A6 both bind to a large number of partners, many of them shared
The ancestor is much more similar to human S100A6 than S100A5
Binding set of human S100A5 has both shrunk and shifted from the ancestral state
Promiscuity to specificity on one lineage, ancestral promiscuity on the other.
Remaining questions:
- What are the genetic and biochemical bases for the altered specificity on the S100A5 lineage?
- Do we see the same picture if we limit our binding set to "biological" peptides?
- Can we mine new biological targets from our phylogenetically-informed, high-throughput data?
Conclusions:
- S100A5 and S100A6 have generally low peptide binding specificity
- Human S100A6 has preserved ancestral promiscuity
- Largest change has happened on the S100A5 lineage: increased specificity, altered set of targets
- A low-resolution experiment with known peptides gives a different answer than an unbiased, high-throughput measurement
Luke Wheeler: Promiscuity and specificity in the evolution of S100 proteins
Zach Sailer: High-order epistasis in genotype-phenotype maps
How does the distribution of function in sequence space shape evolutionary outcomes?
Epistasis (non-additivity between mutations) is a critical factor shaping evolution
The case of oseltamivir resistance in H1N1 influenza
- In 1991, the H274Y mutation to an influenza protein was shown to compromise viral fitness
- In 2008, H274Y entered the H1N1 population and conferred resistance to the drug oseltamivir
- Between 1991 and 2008, mutations accumulated that offset the deleterious effect of H274Y.
- Epistasis between these mutations opened a new evolutionary path
Bloom et al. (2010) Science 328:1272
Epistasis can have many effects:
- Limits evolutionary trajectories (making evolution follow predictable trajectories).
Weinreich et al (2006) Science 312(7):111
- Stochastically opens evolutionary trajectories (making evolution contingent on the past).
Harms & Thornton (2014) Nature 512:203
- "Entrenches" evolutionary trajectories (making evolution irreversible).
Shah et al. (2015) PNAS 112(25):E3226
But what if we expand sequence space?
Wright (1932) Proceedings of the Sixth International Congress of Genetics 356
Epistasis can be characterized through double mutant cycles
Epistasis can be characterized through double mutant cycles
Larger sequence spaces could (in principle) give higher-order epistasis
What we (naively) expected:
Some questions
Does appreciable high-order epistasis exist?
How would high-order alter evolutionary outcomes?
Where does it come from?
Some questions
Does appreciable high-order epistasis exist?
How would high-order alter evolutionary outcomes?
Where does it come from?
Approach: measure high-order epistasis in published sequence spaces
| Num. sites |
Num. sequences |
Genotype |
Phenotype |
Reference |
| 5 |
$32\ (2^{5})$ |
Enzyme point mutations |
Bacterial fitness |
Weinreich (2006) |
| 5 |
$128\ (2^{3} \times 4^{2})$ |
Protein/DNA point mutations |
Protein/DNA affinity |
Anderson (2015) |
| 5 |
$32\ (2^{5})$ |
Enzyme point mutants |
Bacterial fitness |
Chou (2011) |
| 5 |
$32\ (2^{5})$ |
Random genomic mutations |
Fungual fitness |
de Visser (2009) |
| 6 |
$64\ (2^{6})$ |
Combinations of enzyme alleles |
Yeast halploid growth rate |
Hall (2004) |
| 6 |
$64\ (2^{6})$ |
Combinations of enzyme alleles |
Yeast diploid growth rate |
Hall (2004) |
| 6 |
$64\ (2^{6})$ |
Combinations of enzyme alleles |
Yeast mating efficiency |
Hall (2004) |
Sequence spaces have very different genotypes and phenotypes
We detect statistically-significant high-order epistasis
Extract epistatic coefficients using the high-order model
$\vec{\beta} = \mathbf{X}^{-1} \vec{f}$
High-order interactions are seen across all datasets investigated
High order epistasis exists in all datasets
In general, the magnitude of epistasis does not decay with increasing order.
Some questions
Does appreciable high-order epistasis exist?
Does high-order epistasis matter?
Where does it come from?
Some questions
Does appreciable high-order epistasis exist?
Does high-order epistasis matter?
Where does it come from?
Can high-order epistasis can shape evolutionary trajectories?
Relative fitness of bacteria expressing $\beta$-lactamase variants
Weinriech (2006) Science, 10.1126/science.1123539
Knock out epistasis and see how it changes accessible trajectories
Knock out epistasis and see how it changes accessible trajectories
Removing high-order interactions expands the number of accessible trajectories
We can even see high-order epistasis just by staring at the sequence space
High-order epistasis creates order-dependence in evolution.
Some questions
Does appreciable high-order epistasis exist?
Does high-order epistasis matter?
Where does it come from?
Some questions
Does appreciable high-order epistasis exist?
Does high-order epistasis matter?
Where does it come from?
Do we expect this to be a general phenomenon?
Study high-order epistasis with simple protein computational model
- Pairwise-only (second order) interactions
- Can exhaustively sample thermodynamic ensembles across sequence space
Implementation from: Bloom et al. (2006). PNAS 103(15):5869-5874
Strategy
- Generate a 6-site ($2^{6} = 64$ protein) sequence space
- Generate full thermodynamic ensembles for each sequence
- Calculate $\Delta G_{native}$ for each ensemble
- Fit the high-order epistasis model to these data
Lattice model sequence space exhibits high-order epistasis
Where does this come from in a simple pairwise model?
$$\Delta G_{A} = E_{A} - RTln \Big (Q - e^{-E_{A}/RT} \Big )$$
For an ensemble with only states $A$ and $B$:
$$\Delta G_{A} = E_{A} - E_{B}$$
A two-state model should not exhibit high-order epistasis
Two-state lattice model does not exhibit high-order epistasis
If we add a third state, we expect high-order epistasis
$$\Delta G_{A} = E_{A} - RTln \Big (e^{-E_{B}/RT} + e^{-E_{C}/RT} \Big )$$
Three-state simulation: high-order epistasis
High-order epistasis arises from nonlinearity in system
- Each mutation affects more than one conformation
- The system thus responds nonlinearly to mutations.
- The linear model accounts for this with high-order terms
What about other sorts of nonlinearity?
Saturation:
Simulate a completely additive dataset, but apply a saturation curve
Periodic, high-order epitasis appears
Some questions
Does appreciable high-order epistasis exist?
Does high-order epistasis matter?
Where does it come from?
- From nonlinearity in the genotype-phenotype map
Conclusions:
- Biological phenotypes are generally non-linear
- Genotype space is fundamentally linear
- This mismatch means that high-order epistasis is "baked" into sequence space
- High-order epistasis leads to a profound "memory" in evolution: the effect of a mutation depends on all mutations that preceded it.
- Historical contingency, entrenchment, irreversibility, locally predictable evolutionary paths are the rule.
People
Luke Wheeler
Andrea Loes
Zach Sailer
Joseph Harman
Jamie Bridgham
Prof. Jim Prell
Undergraduates: Bram Ricketts, Ran Shi, Hiranmayi Duvvuri, Sarina Pollat, Abigal Tamil, Jaclyn Smith
Funding
What does high-order epistasis do to estimates of low-order terms?
(can we just ignore it?)
Strategy
- Generate sequence space with 10th-order epistasis
- Regress low-ordered models against that space
- Measure two values:
- $R^{2}$ between the model and the data
- $R^{2}$ between the output and input model parameters
Low-order models fit the phenotypes well...
...but low order models scramble the input parameters!
Low-order models fit the phenotypes well...
...but low order models scramble the input parameters!
The apparent interaction between residue 1 and 2 fluctuates wildly at low order
The apparent interaction between residue 1 and 2 fluctuates wildly at low order
The apparent interaction between residue 1 and 2 fluctuates wildly at low order
The apparent interaction between residue 1 and 2 fluctuates wildly at low order
The apparent interaction between residue 1 and 2 fluctuates wildly at low order
The apparent interaction between residue 1 and 2 fluctuates wildly at low order
Parameter flipping occurs in experimental datasets as well
Some questions
Does appreciable high-order epistasis exist?
Does high-order epistasis matter?
- Shapes evolutionary trajectories
- "Scrambles" low-order terms
Where does it come from?
There is no simple trend of specificity for these proteins
There is no simple trend of specificity for these proteins
Observations
- S100A5 and S100A6 bind to a huge variety of peptide targets
- In contrast, the number of peptides specific to S100A5 and S100A6 is small
- The evolution of their modern specificity was complicated
Unanswered questions:
- What happened to the total binding sets of AncA5, AncA6, and AncA5/A6?
- What is the physical mechanism by which historical mutations altered specificity?
Proteins only as specific as they need to be
Phage populations enrich in a calcium-dependent manner.
Questions
- What are the sizes of the total binding sets of proteins?
- Do proteins become more specific over time?
- What, physically, drives these changes?
S100 proteins are Ca2+ sensors
S100 proteins are Ca2+ sensors
S100 proteins are Ca2+ sensors


The Jesus Cares Campaign is the next evolution in the same strategy. Scripture says that His kindness leads us to repentance, but most people don’t believe He is kind and loving. They see Jesus as angry and judgmental. By saturating the media (TV, Radio, Billboard, Outdoor, Social Media) with the message that Jesus Cares, we are seeing hearts open to the offers of Jesus and we are seeing lives transformed..
When people are in a crisis, where they are considering taking their own lives, it's critical that they reach out to a resource such as a suicide hotline. However, many people are scared of calling a suicide hotline as they aren't sure what will happen if they do call. This fear might keep some people away. Understanding what happens when you call a suicide hotline can help ease your worries and make reaching out to one easier.
The helpline, similar to others, is a line dedicated to giving 24/7 support to those with deep, unanswerable questions about their religion. Steve Harrington, the executive director of the International Association of Peer Specialists, has noticed a rise in similar groups.
Do you not know? Have you not heard? The LORD is the everlasting God, the Creator of the ends of the earth. He will not grow tired or weary, and his understanding no one can fathom. He gives strength to the weary and increases the power of the weak. Even youths grow tired and weary, and young men stumble and fall; but those who hope in the LORDwill renew their strength.  - Isaiah 40:28-31
This site is intended to act as guidence for anyone who is not sure where to start their study, or just enjoys reading different scriptures throughout what is a busy life for most of us, without having to pull out their own bible.


{-# OPTIONS --without-K --safe #-}
module Data.Unit where
import Relation.Binary.PropositionalEquality as PropEq
open import Data.Unit.Base public
open import Data.Unit.Properties public
using (_≟_; _≤?_)
setoid = Data.Unit.Properties.≡-setoid
{-# WARNING_ON_USAGE setoid
"Warning: setoid was deprecated in v1.1.
Please use ≡-setoid from Data.Unit.Properties instead."
#-}
decSetoid = Data.Unit.Properties.≡-decSetoid
{-# WARNING_ON_USAGE decSetoid
"Warning: decSetoid was deprecated in v1.1.
Please use ≡-decSetoid from Data.Unit.Properties instead."
#-}
total = Data.Unit.Properties.≡-total
{-# WARNING_ON_USAGE total
"Warning: total was deprecated in v1.1.
Please use ≡-total from Data.Unit.Properties instead"
#-}
poset = Data.Unit.Properties.≡-poset
{-# WARNING_ON_USAGE poset
"Warning: poset was deprecated in v1.1.
Please use ≡-poset from Data.Unit.Properties instead."
#-}
decTotalOrder = Data.Unit.Properties.≡-decTotalOrder
{-# WARNING_ON_USAGE decTotalOrder
"Warning: decTotalOrder was deprecated in v1.1.
Please use ≡-decTotalOrder from Data.Unit.Properties instead."
#-}
preorder = PropEq.preorder ⊤
{-# WARNING_ON_USAGE decTotalOrder
"Warning: preorder was deprecated in v1.1.
Please use ≡-preorder from Data.Unit.Properties instead."
#-}


Data loading¶
To start any analysis we will need to populate our database. Here we will detail how to connect to a database, create projects, populate those projects with subjects, add experiments, and add *.fcs files.
Connecting to the database¶
If the database is hosted locally, then connecting is simple. We use the global_init function at the beginning of our analysis (whether this is in a script or in a notebook). All we have to do is pass the name of our database into this function, for example this will connect to the database called “CytoPy”:
from cytopy.data.mongo_setup import global_init
global_init('CytoPy')
If the database does not yet exist, it will automatically be generated.
If you’re connecting to a remote database, you can pass other arguments such as host name and port as keyword arguments. These are passed to a call to mongoengine.connection.register_connection. Please see the mongoengine documentaiton for details.
Currently CytoPy does not support connection to multiple databases. All connections default to the alias “core”.
Projects & Subjects¶
Inside CytoPy all data is contained within MongoDB documents. We start by defining a Project. We create a project like so:
from cytopy.data.project import Project
# Create a project for the PD data
pd_project = Project(project_id='Peritonitis', owner='ross')
pd_project.save()
We then retrieve this project using the get function and the relevant query:
pd_project = Project.objects(project_id='Peritonitis').get()
We use the Project document to access all the data within our analysis. A Project will have connections to one or more Subject’s. A Subject can be associated to more than one Project.
A Subject contains all the metadata related to one individual patient/mouse/cell-line (some biological ‘subject’). The Subject document is dynamic, that is, we can add any variables we like. In addition to this, there are special embedded documents that can be added to a Subject. Multiple embedded documents can be added for each:
Bug - each Bug document details a single microbiological isolate related to the associated subject e.g. if a patient had bacterial pneumonia and Pseudomonas aeroginosa had been isolated, you can add a Bug document detailing this event (see cytopy.data.subject.Bug)
Drug - each Drug document details the name of a drug administrated, the initiation data, and the end date (see cytopy.data.subject.Drug)
Biology - each Biology document details some biological measurement (see cytopy.data.subject.Biology)
The purpose of these embedded documents is that some metadata is complicated; a subject can have multiple bacterial isolates, many drugs administrated, or many other biological measurements taken. To be able to suitably associate this metadata to our single cell data in exploratory analysis, we must account for this.
An example of creating a Subject with two bacterial isolates and some biology:
from cytopy.data.subject import Subject, Bug, Biology, Drug
bugs = [Bug(org_name='staph', gram_status='positive'),
Bug(org_name='e.coli', gram_status='negative')]
biology = [Biology(test='white_cell_count', result=8000, units='cubic millimeter')]
patient = Subject(subject_id='patient_001', peritonitis=True, infection_data=bugs, patient_biology=biology, age=50, gender=1)
patient.save()
Notice that we added a field called ‘peritonitis’. This is pretty specific to this project. This doesn’t matter because Subject is a dynamic document. This means you can add whatever fields you want ad hoc.
We now save the Subject and add it to our Project:
from cytopy.data.project import Project
pd_project = Project.objects(project_id='Peritonitis').get()
pd_project.subjects.append(patient)
pd_project.save()
Always remember to save your documents!
Adding Cytometry data¶
To add Cytometry data we have to add a FCSExperiment to our project. Before we do that however, we must create a Panel.
Cytometry Panels¶
Cytometry data can be related according to some staining profile/panel used to describe the cellular contents of a biological sample. In CytoPy, an FCSExperiment must be created for each set of staining conditions. The staining conditions are described by a Panel document.
The Panel document is special because it standardises the input of cytometry data at the point of entry. What do I mean by this? Well imagine a user has collected 10 samples, all stained for the same markers, but each time they collected their data they labelled the metadata in their *.fcs file differently. E.g. in the first sample CXCR3 was labelled “CXCR3”, but in the next it was “CXCR 3”, then “CXCR-3” and then “cxcr-3” and so on. You can see how this could be an issue when it comes to analysing our data.
To overcome this problem, we introduce the Panel document. It contains a description of the expected marker and channel names, the marker and channel names that should be set as standard, and then a regular expression used to match markers and channels to their appropriate standard. If you haven’t heard of regular expression before, you can find info here:
To create a Panel we first prepare an Excel template. You can get a blank template here: https://github.com/burtonrj/CytoPy/tree/master/cytopy/assets
The template Excel spreadsheet contains two sheets:
Mappings - these are the channel/marker mappings and names of the channels and markers that should be used as standard. The channels and markers will appear with these names throughout your analysis as every file will be standardised accordingly.
nomenclature - this sheet details, for each channel and each marker standard, a regular expression search term, a list of possible “permutations” and whether the search should be case sensitive. This sheet is used to search each *.fcs file and match the marker/channel to the appropriate standard name
Below is an example of the mappings sheet for one staining panel in the Peritonitis study detailed in our manuscript:
An example of the nomenclature sheet:
This study spanned over 2 years and so there was a vast array of naming conventions used within the cytometry files provided. Using regular expression and a list of known permutations, we can match the channels and markers to the correct standard.
Templates can be made manually by editing the default template. A useful resource for testing regular expressions is https://regexr.com/
Some convenience functions for exploring the range of channel mappings and creating templates are:
cytopy.flow.read_write.explore_channel_mappings - given the path to a directory containing one or more *.fcs files, returns a list of dictionaries for all unique channel/marker names
cytopy.flow.read_write.fcs_mappings - given the path to a single *.fcs file, return the channel/marker names
cytopy.data.panel.create_template - given a list of channel mappings e.g. [{‘channel: ‘FITC’, ‘marker’: ‘CD3’}, {‘channel’: ‘PE’, ‘marker’:’CD4’}] generates a Excel template with template regular expression statements. This should then be checked and edited prior to use.
Once we have our template ready, we can create out Panel document:
from cytopy.data.panel import Panel
n_panel = Panel(panel_name='PD_N_Panel')
n_panel.create_from_excel('path/to/template.xlsx')
n_panel.save()
Creating FCSExperiments¶
As explained above, for each staining condition we are going to create an FCSExperiment. It is the FCSExperiment that will be used later on to access single cell data. To create a new FCSExperiment we use the add_experiment method of Project:
from cytopy.data.project import Project
pd_project = Project.objects(project_id='Peritonitis').get()
pd_project.add_experiment('PD_N_Panel', panel_name='PD_N_Panel')
As shown, this takes as input, the name of the experiment (‘N_panel’) and the name of the panel we want to associate to the experiment.
To load an experiment from our Project we use the load_experiment method:
experiment = pd_project.load_experiment('PD_N_Panel')
Adding *.fcs files¶
*.fcs files are stored within something called a FileGroup. Within a FileGroup there should be one primary file and then any other *.fcs files attributed to controls. We refer to this group of related files as one biological sample. So for example if I had three different mice (a, b, and c) and I stained for CD4 and CD8 but had an isotype control for CD4 and CD8 in each, then each mouse would have one FileGroup and within each FileGroup would be 3 files: the primary staining and two isotype controls.
We add the files for a biological sample like so:
experiment.add_new_sample(sample_id='patient_001_N', file_path='path/to/primary_staining.fcs', controls=[{'control_id': 'CD27', 'path': 'path/to/CD27_FMO.fcs'}], subject_id='patient_001')
In the method call above we provided the following:
sample_id: this is the ID we will use to retrieve data from this sample
file_path: this is the file path to the primary fcs file
controls (optional): a list of dictionaries, the dictionaries should contain a key value pair for the ‘control_id’ and for the ‘path’ where the control file is located
subject_id (optional): the Subject this sample should be referenced too. This will allow metadata to be pulled and associated at a later date


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Putin honours 'hero' pilots for Russian cornfield landing
MOSCOW: Russian President Vladimir Putin on Thursday (Nov 21) bestowed the country's top state honour on two pilots who safely landed a plane carrying more than 230 people in a cornfield after a bird strike.
At a ceremony in the Kremlin, Putin handed pilot Damir Yusupov and co-pilot Georgy Murzin the Hero of Russia awards, praising the crew's courage and professionalism.
"They were able to land the plane literally in an empty field and saved dozens of lives," Putin said.
In August, the Ural Airlines Airbus A321 flying to Crimea hit a flock of seagulls shortly after take-off from Moscow's Zhukovsky airport.

The aircraft, carrying 226 passengers and seven crew, was evacuated using inflatable ramps.
Russian media called the landing a "miracle" and drew comparisons with US pilot Chesley "Sully" Sullenberger's 2009 landing of a US Airways airliner in the Hudson River after a bird strike.


Time: 2:00pm*
Address:
All Saints Church
Manorhouse Lane, Great Bookham, KT23 4EL
*please arrive half an hour before the ceremony
Lost your invitation? Want to wish the couple well? Need to ask a question?
Get in touch with James and Olivia by filling out the form below. They would love to hear from you


{% extends "imagersite/base.html" %} {% block title %}
Here are some photos people took.
{{ photo.description }}


Libgloss is a library for all the details that usually get glossed over.
This library refers to things like startup code, and usually I/O support
for gcc
and C library
. The C library used through out
this manual is newlib
. Newlib is a ANSI conforming C library
developed by Cygnus Support. Libgloss could easily be made to
support other C libraries, and it can be used standalone as well. The
standalone configuration is typically used when bringing up new
hardware, or on small systems.
For a long time, these details were part of newlib. This approach worked well when a complete tool chain only had to support one system. A tool chain refers to the series of compiler passes required to produce a binary file that will run on an embedded system. For C, the passes are cpp, gcc, gas, ld. Cpp is the preprocessor, which process all the header files and macros. Gcc is the compiler, which produces assembler from the processed C files. Gas assembles the code into object files, and then ld combines the object files and binds the code to addresses and produces the final executable image.
Most of the time a tool chain does only have to support one target
execution environment. An example of this would be a tool chain for the
AMD 29k processor family. All of the execution environments for this
processor have the same interface, the same memory map, and the same
I/O code. In this case all of the support code is under newlib/libc/sys.
Libgloss's creation was forced initially because of the cpu32
processor family. There are many different execution environments for
this line, and they vary wildly. newlib itself has only a few
dependencies that it needs for each target. These are explained later in
this doc. The hardware dependent part of newlib was reorganized into a
separate directory structure within newlib called the stub dirs. It was
initially called this because most of the routines newlib needs for a
target were simple stubs that do nothing, but return a value to the
application. They only exist so the linker can produce a final
executable image. This work was done during the early part of 1993.
After a while it became apparent that this approach of isolating the hardware and systems files together made sense. Around this same time the stub dirs were made to run standalone, mostly so it could also be used to support GDB's remote debugging needs. At this time it was decided to move the stub dirs out of newlib and into it's own separate library so it could be used standalone, and be included in various other GNU tools without having to bring in all of newlib, which is large. The new library is called Libgloss, for Gnu Low-level OS support.


| Overview | Module | Use | Devguide | Index |
| uses of typedef PropertyValues |
back to typedef PropertyValues |
| Uses as Return Type |
| ::com::sun::star::style::XAutoStyle::getProperties() |
| Uses as Data Type |
| ::com::sun::star::i18n::LineBreakHyphenationOptions::aHyphenationOptions ::com::sun::star::text::Text::EndRedline ::com::sun::star::graphic::MediaProperties::FilterData ::com::sun::star::text::RedlinePortion::RedlineSuccessorData ::com::sun::star::text::Text::StartRedline |
| References in Developers Guide |
| Text - Indexes and Index Marks - Indexes OfficeDev - Implementing a New Locale - XLocaleData |
Copyright © 2013, The Apache Software Foundation, Licensed under the Apache License, Version 2.0. Apache, the Apache feather logo, Apache OpenOffice and OpenOffice.org are trademarks of The Apache Software Foundation. Other names may be trademarks of their respective owners.


Filament Group
Apartment Criteria
Max Rent ($):
Min bedrooms:
Min baths:
Amenity Preferences
Subway access:
Not important
Somewhat important
Pretty Important
Must have
Water views:
Not important
Somewhat important
Pretty Important
Must have
Walking paths:
Not important
Somewhat important
Pretty Important
Must have


Flanked by the Arabian Sea in the West, the towering Western Ghats in the East and networked by 44 interconnected rivers, Kerala is blessed with a unique set of geographical features that have made it one of the most sought after tourist destinations in Asia. A long shoreline with serene beaches, tranquil stretches of emerald backwaters, lush hill stations and exotic wildlife, are just a few of the wonders that await you once you crossover to the other side. And what's more, each of these charming destinations is only a two hour drive from the other - a singular advantage no other place on the planet can offer. Kerala prides itself for being the flag bearer for not just how a culture can respect its past but also march forward with growth & progress as well. Hundred percent literacy, world-class health care systems, India's lowest infant mortality and highest life expectancy rates are among a few of the milestones that the people of the state are extremely proud of.


This article will give you a high-level explanation about virtual hosting
In general, virtual hosting is the practice of serving multiple websites or mini websites from a single web server. There are two major options to differentiate sites:
1. Using a different path as part of the URI. Let's call it path style.
2. Using different subdomain. Let's call it virtual hosting.
An ordinary Amazon S3 REST request specifies a bucket by using the first slash-delimited component of the Request-URI path.
Alternatively, you can use virtual hosting can be used to address a bucket in a REST API call by using the HTTP Host header. In practice, Amazon S3 interprets Host as meaning that most buckets are automatically accessible (for limited types of requests) at http://bucketname.s3.amazonaws.com.
Example Path Style Method
This example uses testbucket as the bucket name and test.jpg as the key name.
The URL is as follows:
http://s3.mypublicservice.com/testbucket/test.jpg
The request is as follows:
GET /testbucket/test.jpg HTTP/1.1
Host: s3.mypublicservice.com
Example Virtual Hosted–Style Method
This example uses testbucket as the bucket name and test.jpg as the key name.
The URL is as follows:
http://testbucket.s3.mypublicservice.com/test.jpg
The request is as follows:
GET /test.jpg HTTP/1.1
Host: testbucket.s3.mypublicservice.com
The virtual hosted–style method requires the bucket name to be DNS-compliant.
Part of the applications use only the virtual hosting approach and don't allow a configuration for path style, although the AWS SDK allows that.
In order to achieve similar behavior with NooBaa, a virtual hosting must be configured in NooBaa.
Starting from V2.4.2, virtual hosting is enabled automatically after setting DNS name for your NooBaa system. Check https://noobaa.desk.com/customer/portal/articles/2866032-set-system-dns-name-
Earlier versions require manual configuration, please contact<EMAIL_ADDRESS>The second and most important part is to register the DNS resolution of every bucket used by such applications.
You can automate this process by creating a trigger for bucket creation that will run your code to provision this DNS resolution.


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¡
9
The
New
York
copyright
reserved
Botanical
Garden
S||
Flora
of
St.
John,
U.S.
Virgin
Islands
OLEA
NO:
5257
Forestiera
eggersii
Krug
&
Urb.
LOCALITY:
Reef
Bay
Quarter;
road
to
Fish
Bay.
HABITAT:
Open,
recently
disturbed
roadside.
DESCRIPTION:
Shrub,
2
m
tall;
flowers
yellowish.
COLL:
P.
Acevedo-Rdgz.
DATE:
15
Feb
1993
Supported
by
funds
from
the
Smithsonian
Institution
and
the
Homeland
Foundation
SMITHSONIAN
INSTITUTION
From
THE
UNITED
STATES
NATIONAL
HERBARIUM
IMAGED
BOTANICAL
GARDE**,
00843160
Legend -
Level of confidence that token is an accurately-transcribed word
extremely low
very low
low
undetermined
medium
high
very high


avoidance2 package¶
Submodules¶
avoidance2.features module¶
Created on Mon Mar 25 18:51:16 2019
@author: bikash
-
class
avoidance2.features.
AnalyzeDataFrameFeatures
(input_file=None, utr=None, positions=None, ncrna_file=None, length=None, multiprocess=True)¶ Bases:
object
Calculates features for sequences in a dataframe
-
features
()¶ Calculates all features for given sequences
-
mean_and_sd
()¶ Calculates mean and standard deviation of features in a dataframe
-
-
class
avoidance2.features.
AnalyzeSequenceFeatures
(seq)¶ Bases:
object
Analyze sequence features
-
access_calc
(length=None, utr=None)¶ Sequence accessibility
-
avoidance
(ncrna_file=None)¶ This cats ncrnas and computes interaction for single mrna so is a single process
-
cai
()¶ Codon adaptation index
-
gc_cont
()¶ G+C content
-
sec_str
(utr=None, positions=None)¶ Secondary structure of specified position in sequence. Default position is -30 to 30 with 0 as start codon
-
avoidance2.functions module¶
Created on Sat Mar 23 11:30:45 2019
@author: bikash
-
avoidance2.functions.
accession_gen
()¶ Random accession numbers
-
avoidance2.functions.
csv_reader
(file)¶ Read csv and returns sequences in uppercase
-
avoidance2.functions.
fasta_reader
(file)¶ Converts .fasta to a pandas dataframe with accession as index and sequence in a column ‘sequence’
-
avoidance2.functions.
file_check
(file)¶ Check wether we are given a proper file or not and parse that file accordingly.
-
avoidance2.functions.
interaction_calc
(seq)¶ Runs RNAup and returns its output.
-
avoidance2.functions.
parallelize_df
(df, func)¶ parallelizes operations on a dataframe by splitting it to chunks
-
avoidance2.functions.
progress
(iteration, total, message=None)¶ Simple progressbar
-
avoidance2.functions.
rand_background
(seq, num=1000)¶ Random background
-
avoidance2.functions.
rms_check
(seq_df, rms=None)¶ Restriction modification sites checking.
-
avoidance2.functions.
rnaup_result_parser
(raw_result_list, mrna_dataframe=None)¶ Returns parsed interaction and a dataframe of all interactions as a tuple, first element is the parsed scores only, second is full table of results with sequences accession and RNAup output. You will rarely need the second element. It is mainly for debug purposes. note: this function is for one mrna vs one or multiple ncrna
-
avoidance2.functions.
sequence_df_features
(utr=None, positions=None, ncrna_file=None, length=None, input_df=None)¶ Calculates all features of sequences in a dataframe.
-
avoidance2.functions.
sequence_length
(seq)¶ Returns length of sequence in multiple of 3 by chopping extra positions
-
avoidance2.functions.
splitter
(seq, length=None)¶ Split sequence to codons
-
avoidance2.functions.
substitute_codon
(seq, num_of_subst=10)¶ randomly substitute codons along the sequence at random positions
-
avoidance2.functions.
syn_background
(seq, n=1000)¶ Randon synonymous background
avoidance2.markov module¶
Created on Sun Mar 24 12:49:12 2019
@author: bikash
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class
avoidance2.markov.
MarkovModel
(input_file=None, nostartstop=True, length=32)¶ Bases:
object
This is used to train a Markov model using the input sequence. By default, we train for length 32 codons. The start codon and stop codon are stripped by default, but if your sequences are already free from them, you can use nostartstop=False.
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codons_to_df
()¶ Returns a dataframe of codons in given sequences. position is column and sequence number is index.
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generate
(sequence, model=None, num_seq=10000)¶ Generate synonymous sequences to a given sequence using a Markov model
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static
get_probs
(possible_codons, index, prob_df)¶ Tries to extract probabilities of possible codons for substitution at given index(position along the sequence) using a probability table. First a lookup at that position is done, if that fails, we lookup to ‘codon_prob’ column which is the overall probability of that codon in the training sequence (priors). If that fails, we return a random probability using 1D Dirichlet distribution.
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train
()¶ Uses the codon dataframe to calculate probabilities codon name is the index and column number is the position of codon along the sequence.
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static
validate_model
(model)¶ Checks if the given Markov model is usable.
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avoidance2.optimization module¶
Created on Fri Mar 29 13:47:59 2019
@author: bikash
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class
avoidance2.optimization.
Optimizer
(seq=None, rf_model=None)¶ Bases:
object
Optimizes the sequence using simulated annealing
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background_features
()¶ Calculates features for background sequences. Currently, the background is random synonymous sequences.
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cost_function
¶ Calculates z scores of a given sequence based upon a group of sequences given to Optimizer class.
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cost_function_old
¶ Calculates z scores of a given sequence based upon a group of sequences given to Optimizer class.
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simulated_anneal
(itr=100)¶ preforms a simulated annealing
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static
validate_model
(model)¶ Checks if the given random forest classifier is usable.
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avoidance2.score module¶
Created on Mon Mar 25 21:06:17 2019
@author: bikash
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class
avoidance2.score.
Score
(input_file=None)¶ Bases:
object
Scores sequences based on their features using a random forest model.
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score_seq
(rf=None)¶ Scores sequence based on random forest classifier
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select_seq
(num=None)¶ Selects high scoring sequences based on classifier scores num specifies number of high scoring sequences to select
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static
validate_model
(model)¶ Checks if the given random forest classifier is usable.
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Supreme Court temporarily halts court order that demands Trump turn over his tax returns
by Rob BeschizzaCNBC reports that the Supreme Court has temporarily halted a lower court order requiring accountants to turn over President Donald Trump's tax returns to congress.
Steven Portnoy: "The DC Circuit Court's mandate is stayed pending a response due at 3pm Thursday afternoon."