Event Location:
Kalamazoo Valley Community College
6767 West O Avenue
Kalamazoo, Michigan
Abstract:
Do you remember what it was like to fall in love? Wasn't it wonderful? Lately it just hasn't been the same. You've been stuck in the same old routine, doing the same old charts and tables. Maybe Reporting Services doesn’t tell you what’s wrong. Maybe you're even thinking about seeing other reporting products. Maybe you and RS just weren't meant to be together. In this session, Doug will re-ignite your passion for RS by showing you how to design for better performance, explaining what RS has been trying to tell you through logs (but you haven't been listening), and demonstrating some new -- and easy -- tricks you may not have known RS can do. After this session, you'll want to spend some time alone with your new old flame.
Speaker(s): Doug Lane,
Abstract:
Don’t let the “Intermediate” rating scare you “Beginners” away. This “Black Arts” session is for anyone that uses T-SQL. There are dozens of things we do in SQL that require some type of iteration. "Iteration" means "counters" and "loops" to most people and recursion to others. To those well versed in the techniques of "Set-based" programming, it means some form of a "Numbers" or "Tally" Table, instead. SQL Server MVP Jeff Moden takes the mystery out of how this wonderfully compact tool works and how it easily replaces many types of loops. This session has been updated to include additional information about what “Pseudo-Cursors” are and how they work as well discovering why “Recursive CTE’s” can be your worst enemy.
Speaker(s): Jeff Moden,
Abstract:
The Query Optimizer uses statistics to decide how to execute a query. If statistics are out of date, improperly sampled or simply don’t exist, then you could unintentionally deceive the Optimizer. Accurate statistics can help avoid poor query plans, so if you’re not familiar with how to read a histogram, the various options for updating statistics or want to know why sample size does matter, this session is for you! We will also delve into what happens when a value doesn’t exist in a statistic, discuss methods to manage statistics for volatile tables and examine the challenges that exist with statistics on partitioned tables. Expect a session filled with demos and real-world examples that will create a foundation of statistics knowledge.
Speaker(s): Erin Stellato,
Abstract:
Don’t let the “Intermediate” rating scare you “Beginners” away. This “Black Arts” session is for anyone that uses T-SQL. SQL Server MVP Jeff Moden demonstrates and explains simple methods for converting gobs of “vertical data” into horizontal numeric and textual data by date or other key using Cross Tabs and Pivots. This session includes the “Black Arts” method of “Pre-Aggregation” for incredibly high performance and how to dynamically and automatically produce reports based on a date. The methods learned in this session can be used to provide “dynamically pivoted” result sets to SSRS, Crystal Reports, and other reporting software.
Speaker(s): Jeff Moden,
Abstract:
The future of BI is self-service reporting and PowerPivot is the conduit to that goal. We will explore how to use the PowerPivot add-in for Excel 2010 to tie different data sources together and deliver analytics. In this session you will learn how to use PowerPivot (within the familiar interface of Excel) to combine different data sources such as Analysis Services cubes, TSQL queries, Stored Procedures, Excel spreadsheets, flat files and data from the web to create basic PivotTables and PivotCharts in Excel. The data these new spreadsheets overcomes the 1,048,576 row limitation in Excel 2007/2010, contains refreshable data sources and has excellent data compression and lighting fast speed thanks to the utilizati
Speaker(s): Scott Schommer,
Abstract:
Taking the periodic table of elements into consideration I've created The Periodic Table of Dynamic Management Objects as a reference tool for these functions and views that have become so critical for today's SQL Server DBA to performance tune and gain metadata insights into their various SQL instances. In navigating the table we will examine key DMVs and DMFs of interest: requests, sessions, wait stats, indexes, system information will all be covered. We will also delve into how these DMOs - just like their elemental counterparts - can be combined to yeild interesting insights into your servers. We will also look at how things can go awry as well! Like mixing vinegar and baking soda, sometimes combining DMOs can cause a big mess too!
Speaker(s): Tim Ford,
Abstract:
In this Lunch session see how BlueGranite – a Microsoft’s 2011 Partner of the Year award winner and top industry partner – has helped customers leverage the Microsoft BI platform to help increase profitability through deeper business analysis. Through an end-users eyes, learn how Microsoft Business Intelligence and SQL Server 2008 R2 can provide an up-to-the-minute view of the health of your business. See real world-examples and use cases from a live solution; including the use of SSAS OLAP cubes, Microsoft Excel, PerformancePoint Services, and mobile platforms.
Speaker(s): Matthew Mace,
Abstract:
Indexes make queries run faster, right? Not always, no. And finding the right indexes for your needs is often more of an Art than a Science. Attend this session as we take a visual tour of how indexes are laid out and the way data is accessed when indexes are utilized. We will discuss clustered indexes as well as non-clustered indexes and also when to use indexed views along with some other variations.
Speaker(s): Wendy Pastrick,
Abstract:
There are many ways to performance monitor your SQL Server environment. In this session we’ll review Extended Events, which is one of the newer SQL Server monitoring platforms. Learn the ins and outs of how to get detailed information on the errors and events that occur within SQL Server and how to dig into the information. With a few T-SQL statements, issues that could take weeks to research can be investigated in minutes.
Speaker(s): Jason Strate,
Abstract:
Issue a "SELECT {data} FROM {myTable}" statement and users need to trust the data returned is accurate. What happens when multiple processes access the same data? What happens further if one of those process is an UPDATE or even a DELETE statement? How about if both processes will be updating that data? Understanding Isolation in SQL Server is paramount in ensuring data integrity in your system. We will cover the different levels of isolation and how they impact what a user views when accessing the data at a given point-in-time.
Speaker(s): Wendy Pastrick,
Abstract:
Know those apps that need a complete rewrite from scratch, but management won't listen to you? Kendra Little has been there and she's figured out how to frame the big conversations. She'll give you seven strategies to improve scale and change application architecture, and explain concepts from sharding to caching along the way. You'll get a toolkit for each conversation: how to gather the right supporting data from the environment, who to talk to, and how to speak the right language to drive each change.
Speaker(s): Kendra Little,
Abstract:
A one hour session showing how SQL Server creates and manages indexes using a B-Tree. This will include discussions and demonstrations on clustered vs non-clustered indexes as well as how to build the best performing index solutions.
Speaker(s): Charles Otten,
Abstract:
Bad habits: we all have them. SELECT * is the obvious one; but in this session you will learn about various other habits and why they can be bad for performance or maintainability. Come learn how these habits develop, what kind of problems they can lead to, and how you can avoid them. Eliminating these habits will lead to more efficient code, a more productive work environment, and - in a lot of cases - both.
Speaker(s): Aaron Bertrand,
Abstract:
This session focuses on SQLServer-based BI solution delivery. Capabilities discussed will include Excel Services, PerformancePoint Services, Business Connectivity Services, Reporting Services Integrated Mode, and PowerPivot. This session will emphasize real-world best practices in technology selection, solution design, security, and deployment.
Speaker(s): Rob Kerr,
Abstract:
SQL Server "Denali" delivers many highly anticipated features that some feel are long overdue. In this session you will get a first-hand look at many of these new features relating to the engine (contained databases, AlwaysOn, and T-SQL enhancements), client tools (Management Studio, Books Online, and "Juneau"), and changes to setup and system requirements. You'll also learn about some of the features that will not be making it into Denali, and deprecated functionality that will stop working in this or the next release.
Speaker(s): Aaron Bertrand,
Abstract:
Change Tracking (the little sister to Change Data Capture CDC) will be demonstrated in detail in this session. This SQL server feature is available in Standard Editions of SQL server so everybody can use it. A complete example from server settings to each T-SQL statement will be explored.
Speaker(s): Tom Groszko,
Abstract:
There are many ways to solve problems with SQL Server, and the performance of the various solutions can vary dramatically. This session will focus on specific server settings and T-SQL practices to create efficient running solutions. We’ll discuss how functions can hurt and help performance, approaches to removing cursors in favor of set based approaches, tricks to find missing indexes, how to determine the actual cost of your queries and much more.
Speaker(s): Charles Otten,
Abstract:
Many database professional have little to no understanding about how to use wait events as part of an overall performance tuning process. And yet wait events are the secret sauce that many leading experts have been using for years. Attend this talk and you will gain an understanding of the SQLOS execution model, an understanding of how to use DMVs to find out what your queries are waiting for, and why using wait events could be the best thing to happen for your career as a DBA.
Speaker(s): Thomas LaRock,
Abstract:
Synchronous and asynchronous components, memory buffers, data type choices, Oh My! Tuning the data flow is all about choices. In this session we'll walk through some of the choices that can give you the biggest performance boosts in your ssis data flow. Together we'll work through the differences between synchronous and asynchronous components. We'll highlight components that should be avoided and explore alternates that can help us create the fastest data flow possible.
Speaker(s): Tim Costello,
Abstract:
Consultants work with technology, but they also deal with a lot of politics. Brent Ozar was a production DBA for years and sat through thousands of meetings. Now that he’s a consultant, he’s figured out how consultants handle political bombs during meetings, and he wants to share his favorite consulting lines with you. You’ll learn how to deal with dangerous developers, miserable managers, and cussing customers using simple lines that won’t blow up in your face.
Speaker(s): Brent Ozar,
Abstract:
Storage Area Networks are like a bad black box: we put data in, we get data out, but we have no idea what's going on inside. Why is everything so slow and yet so expensive? Is it a SAN problem or a SQL problem? Learn what's happening inside the black box from Brent Ozar, a Microsoft Certified Master and former SAN administrator, who will demystify storage.
Speaker(s): Brent Ozar,
Abstract:
The Policy-Based Management feature in SQL Server 2008 provides a great way to ensure your systems are configured consistently and correctly, but it can be tedious to implement on each server in your environment. PowerShell scripts allow you to automate the implementation of your policies so you can focus on more important problems. This session will walk you through how PBM works, how to define your policies in PowerShell, and how to set up Agent jobs to evaluate those policies regularly to let you know when you need to take action.
Speaker(s): Allen White,
Abstract:
When moving databases to a virtual environment the performance metrics DBAs typically use to troubleshoot performance issues such as O/S metrics, storage configurations, CPU allocation and more become unreliable. DBAs no longer have a clear, reliable view of the factors impacting database performance. Understanding the difference between the physical and virtual server environment adds a new dimension to the DBA tasks. This presentation describes the changes that DBAs need to make in their performance and monitoring practices.
Speaker(s): Thomas LaRock,
Abstract:
We often hear about the advantages of diversity in the workforce, but it can be difficult to relate to one another when we all have different backgrounds and experiences. Please join our panelists Kendra Little, Wendy Pastrick, Yanni Robel and Erin Stellato as they explore lessons learned as women working in information technology. They will discuss ways they have been able to leverage their differences to compliment a team and share communication techniques they’ve acquired from working in diverse environments. All attendees are welcome.
Speaker(s): Shelly Noll,
Abstract:
The days of hiding amongst rows of servers, focusing purely on operational tasks are quickly coming to an end. DBAs that want to hide in their foxhole, focusing purely on operational tasks are quickly being outsourced. This session will cover the steps to becoming a highly valued leader in your organization by building relationships, automating mundane tasks, standardizing processes, and making education a priority.
Speaker(s): David Levy,
Abstract:
Every SQL Server instance relies on the tempdb database. Whether through explicit use with #temp tables or @table variables, or implicit use through working space for many other operations, most tempdb databases get quite a workout. This session will dig into many of the otherwise-hidden issues that can kill server performance. After this session, you will be able to spot tempdb performance issues, drill into the causes, and take the steps necessary to solve them.
Speaker(s): Eddie Wuerch,
Abstract:
NoSQL (or, more correctly NoRel) is a moniker applied to a family of non-relational software systems for storing data that powers some of the largest sites on the Internet. Amazingly enough, non-relational database technology has been around a very long time. This session will include a high level discussion of some of the pros and cons of this technology compared to traditional systems like Oracle and SQL Server; as well as a survey of the most popular "NoSQL" platforms and who uses them. We will also cover a brief history of relational and non-relational databases as it is germane to the topic
Speaker(s): Craig Purnell,
Abstract:
In this “demo-tastic” presentation, SSIS trainer, author, and consultant Andy Leonard explains the what, why, and how of an SSIS framework that delivers metadata-driven package execution, connections management, and centralizes logging. Key takeaways: 1) Developers can migrate packages from Development, through their lifecycle, to Production without editing SSIS Connection Managers properties. 2) A metadata-driven approach to SSIS package execution. 3) Demonstration of a centralized logging reporting application.
Speaker(s): Andy Leonard,
Abstract:
Refactoring SQL is not like refactoring application code. This talk will cover proven SQL refactoring techniques that will help you identify where performance gains can be made, apply quick fixes, improve readability, and help you quickly locate places to make sweeping performance improvements. Jeremiah Peschka has years of hands on experience tuning SQL applications for performance, throughput, and concurrency.
Speaker(s): Jeremiah Peschka,
Abstract:
Do you know when your users are using the production login accounts from their workstations? Are you aware of changes being made to the development servers that may impact future deployments? Has the new Junior DBA start giving out access like candy? As DBAs, we are responsible for knowing and acting on all of this and much more. Fortunately, SQL Server provides a number of features that you can use to monitor and track user activity. In this session, we’ll look at these features and demonstrate how you can use them to the extent that your users find you creepy!
Speaker(s): Jason Strate,
Abstract:
Computing running totals, averages by state or group, and other complex aggregations are not easy to implement in many relational databases. Thankfully, many relational databases include support for window functions. Window functions are an extension to the ANSI SQL standard. More than just another part of SQL, window functions enable complex ranking, ordering, and other aggregations over a subset of rows in a query. Understanding the capabilities of window functions lets you extend application functionality, build rich and complex queries, and reduce overhead in the application tier.
Speaker(s): Jeremiah Peschka,
Abstract:
This highly-interactive, demo-intense presentation is for beginners and developers just getting started with SSIS. Attend and learn how to build SSIS packages from the ground up.
Speaker(s): Andy Leonard,
This is a list of speakers from the XML Guidebook records. The details and URLs were valid at the time of the event.
 Kendra fell in love with the challenge of deploying software to a complex database environment when she worked in a build operations team at a software startup. She went on to become a database administrator for performance critical databases at Microsoft Corporation. Since then, Kendra has worked internationally as a teacher and consultant, and founded the training site SQL Workbooks. She joined Redgate as a Product Evangelist in 2018.
LinkedIn: http://www.linkedin.com/in/sqlrockstar/
Contact: http://thomaslarock.com
Thomas LaRock is a Head Geek at SolarWinds and a Microsoft Certified Master, Data Platform MVP, VMware vExpert, and a Microsoft Certified Trainer. He has over 15 years’ experience in the IT industry in roles including programmer, developer, analyst, and database administrator.
With more than 51,000 posts and 39 mostly 5 star articles, Jeff Moden is a strong contributor on SQLServerCentral.com where he coined the term “RBAR” (Row By Agonizing Row) and helped make the "Tally Table" a household name. Jeff has more than 2 decades of experience with SQL Server and is mostly self-trained in what he calls the “Black Arts” of T-SQL. He’s known worldwide for his informative articles, high performance T-SQL coding methods, and methods of mentoring. His dedication to helping others earned him the MS SQL Server MVP award for nine years and the RedGate Exceptional DBA Award in 2011. His mantra is "Performance is in the code".
LinkedIn: http://www.linkedin.com/in/AndyLeonard
Contact: https://andyleonard.blog
Andy Leonard is founder and Chief Data Engineer at Enterprise Data Analytics, Microsoft Data Platform MVP, creator of the DILM (Data Integration Lifecycle Management) Suite, an SSIS trainer, consultant, developer, Business Intelligence Markup Language (Biml) developer and BimlHero, SQL Server database and data warehouse developer, community mentor, engineer, and farmer. He is a co-author of "The Biml Book and SQL Server Integration Services Design Patterns" and author of "Managing Geeks - A Journey of Leading by Doing", "Data Integration Lifecycle Management with SSIS", "Building Custom Tasks for SSIS", and the "Stairway to Integration Services". Andy blogs at andyleonard.blog where you can learn more on the About Andy page.
Contact: http://adventuresinsql.com
An IT Professional with more than 10 years experience, largely in a software development role. Exclusively a DBA for more than 3 years, recently joined Microsoft as a Premier Field Engineer specializing in SQL Server.
LinkedIn: https://www.linkedin.com/in/timothyford
Contact: http://thesqlagentman.com
Tim Ford is a Data Professional, Author and Community Leader whose technical passions lie in creative solutions for managing and presenting data. He#39;s been a healthcare DBA since 2000 and leads SQL Agent Man Consultancy and SQL Cruise. He takes 25 students and leaders in the SQL Community and places them on cruise ships for technical and professional development training without the distractions of the office and internet twice a year on SQL Cruises (www.sqlcruise.com). Currently Tim serves on the Board of Directors for PASS and is passionate about taking fellow Data Professionals to the next level in their careers. He enjoys telling stories with data.
Contact: http://brentozar.com
Jeremiah Peschka sees the magic in technology. He knows how to do things now, and he also knows how to think about possibilities. Jeremiah likes to imagine new kinds of indexes, new kinds of teams, new kinds of applications. This means that when you need to reinvent something, or get unblocked, you should talk to Jeremiah.
LinkedIn: http://www.linkedin.com/pub/allen-white-sql-server-mvp/5/784/b08/
Contact: http://dataperfpro.com/blog/
Allen White is a Data Platform consultant. He has been both a developer and an administrator, so he understands both perspectives towards database technology. He loves sharing his experiences and helping people learn how to use SQL Server. Allen has spent over 40 years in IT, using SQL Server since 1992, and has been awarded Microsoft’s MVP Award for the last 13 years. Allen was a PASS Director from 2016 - 2018.
LinkedIn: https://www.linkedin.com/in/brentozar
Contact: https://www.BrentOzar.com
Brent Ozar loves to make SQL Server faster. He created sp_Blitz and the SQL Server First Responder Kit. He shares what he's learned at BrentOzar.com.
LinkedIn: http://www.linkedin.com/in/erinstellato
Contact: http://www.sqlskills.com/blogs/erin
Erin Stellato is a Data Platform MVP and lives outside Cleveland, OH. She has almost 20 years of technology experience and has worked with SQL Server since 2003. Her areas of interest include performance tuning, Query Store, Extended Events, and helping accidental/involuntary DBAs understand how SQL Server works. Erin is an active member of the SQL Server community, has volunteered for PASS at the local and national level, and is a regular speaker at conferences including the PASS Summit, SQLIntersection, and SQLBits. Outside of time with family and friends, she enjoys running, spinning, movies, and all things chocolate.
Contact: http://sqlblog.com/blogs/aaron_bertrand/
Aaron is a senior consultant for SQL Sentry, makers of performance monitoring and event management software for SQL Server, Analysis Services, and Windows. He has been blogging at sqlblog.com since 2006, focusing on manageability, performance, and new features; has been an MVP since 1997-98; and speaks frequently at user group meetings and SQLSaturday events.
LinkedIn: http://www.linkedin.com/in/kerrrob/
Contact: http://www.robkerr.com
Rob is CTO with BlueGranite, is a Microsoft SQL Server MVP and holds top Microsoft certifications in both SQL Server Database Administration and BI Development. Rob has implemented data warehouse and business analytics systems for many Fortune 500 companies, and focuses on large-scale data warehousing, geospatial data analysis and mobile solutions. Rob is the lead contributor to msbiacademy.com, a site providing free on-demand training covering a variety of Microsoft BI topics.
LinkedIn: http://linkedin.com/in/craigpurnell
Contact: http://www.craigpurnell.com/
Craig Purnell is a career database professional, trainer, and community activist. He has spent over 10 years as the Database Administrator at a large Midwestern law firm. He has been in IT for 15 years and has spent his entire career working with enterprise databases and ERP systems. Craig is an active member of the Ohio North SQL Server User Group and has presented at many user groups, SQLSaturdays, and the PASS Summit in 2012 and 2013
Contact: http://wendyverse.blogspot.com
Wendy Pastrick is from Chicago, IL, and for the past 15 years has served as a Database Administrator supporting both development and production environments. Her many years of involvement with PASS include WIT Virtual Chapter and the Chicago Suburban User Group, serving as Regional Mentor, and as a PASS Board member since 2013. Wendy has organized several highly successful SQLSaturday events in Chicago.
Contact: http://sqlblog.com/blogs/aaron_bertrand/
Aaron is a senior consultant for SQL Sentry, makers of performance monitoring and event management software for SQL Server, Analysis Services, and Windows. He has been blogging at sqlblog.com since 2006, focusing on manageability, performance, and new features; has been an MVP since 1997-98; and speaks frequently at user group meetings and SQLSaturday events.
Charles has been working with SQL Server since 1999 and has assisted companies with database design, application development, data warehousing, enterprise reporting and performance tuning. He has successfully implemented multi-million dollar systems and system conversions throughout his career. At Dematic Corp he is involved in creating high performance solutions using SQL Server 2005/2008 for high volume (1000's trans/sec) applications requiring subsecond response times.
Doing proof of concept projects and pushing the limits of technology are the passions in my professional life. Many people do projects just because they are assigned to them, but I like to ask questions like "who, what, when, where, why, how and how often". Finding the answers to these simple inquiries saves not only me, but the people (and teams) around me time, money and resources. I also make spending time with my wife and 2 kids, attend a local PASS user group and enjoy life!
LinkedIn: http://www.linkedin.com/in/AndyLeonard
Contact: https://andyleonard.blog
Andy Leonard is founder and Chief Data Engineer at Enterprise Data Analytics, Microsoft Data Platform MVP, creator of the DILM (Data Integration Lifecycle Management) Suite, an SSIS trainer, consultant, developer, Business Intelligence Markup Language (Biml) developer and BimlHero, SQL Server database and data warehouse developer, community mentor, engineer, and farmer. He is a co-author of "The Biml Book and SQL Server Integration Services Design Patterns" and author of "Managing Geeks - A Journey of Leading by Doing", "Data Integration Lifecycle Management with SSIS", "Building Custom Tasks for SSIS", and the "Stairway to Integration Services". Andy blogs at andyleonard.blog where you can learn more on the About Andy page.
LinkedIn: https://www.linkedin.com/in/brentozar
Contact: https://www.BrentOzar.com
Brent Ozar loves to make SQL Server faster. He created sp_Blitz and the SQL Server First Responder Kit. He shares what he's learned at BrentOzar.com.
Contact: http://www.douglane.net
Doug Lane (MCITP, MCTS) is a consultant with Brent Ozar Unlimited and has over 14 years' experience with SQL Server. He blogs about SQL Server with emphasis on Reporting Services and professional development.
Shelly Noll is a .NET Developer and recovering DBA with over 15 years of IT experience. Currently serving as a Software Developer with Learning Care Group in Novi, MI, she is involved in the .NET developer community and serves as Vice-President for the Great Lakes Area .NET Users Group. Her education includes a BS in Psychology from Loyola University Chicago and a MS in Information Systems from Lawrence Technological University.
With more than 51,000 posts and 39 mostly 5 star articles, Jeff Moden is a strong contributor on SQLServerCentral.com where he coined the term “RBAR” (Row By Agonizing Row) and helped make the "Tally Table" a household name. Jeff has more than 2 decades of experience with SQL Server and is mostly self-trained in what he calls the “Black Arts” of T-SQL. He’s known worldwide for his informative articles, high performance T-SQL coding methods, and methods of mentoring. His dedication to helping others earned him the MS SQL Server MVP award for nine years and the RedGate Exceptional DBA Award in 2011. His mantra is "Performance is in the code".
LinkedIn: http://www.linkedin.com/in/jasonstrate/
Contact: http://www.jasonstrate.com/
Jason Strate is a SQL Server Solutions Architect with Pragmatic Works. He is also a Microsoft SQL Server MVP and MCM. He has over 15 years of experience developing, architecting, and managing data platforms. Jason writes, blogs, and presents on SQL Server.
I have been working with MS SQL since 2000 and prior to that with Oracle and Sybase SQL. I have been working with a variety of databases for many years. I also develop desktop applications with C++ and C#.
Contact: www.blue-granite.com
Matthew Mace, President/CEO - Matthew was a founder of BlueGranite, helping start the company 1996. Matthew is active in the technology and business community, serving as Chair of the Western Michigan University CIS Advisory Board, past President Vice-President of the Michigan Chapter of the International Association of Microsoft Certified Partners, and an instructor with Junior Achievement. Matthew was selected as one of the Top 40 Business Leaders Under 40 for West Michigan.
LinkedIn: http://www.linkedin.com/in/sqlrockstar/
Contact: http://thomaslarock.com
Thomas LaRock is a Head Geek at SolarWinds and a Microsoft Certified Master, Data Platform MVP, VMware vExpert, and a Microsoft Certified Trainer. He has over 15 years’ experience in the IT industry in roles including programmer, developer, analyst, and database administrator.
LinkedIn: http://www.linkedin.com/pub/tim-costello/8/b38/a02/
Contact: http://www.timcost.com
Tim Costello is an MCITP, MCTS specializing in etl and data analytics for Interworks Inc. Tim is an international speaker that is always looking for opportunities to share his passion for SQL Server, Tableau and data visualization. Tim is active in the SQL community and leads a data visualization focused user group in the Dallas area.
Contact: http://brentozar.com
Jeremiah Peschka sees the magic in technology. He knows how to do things now, and he also knows how to think about possibilities. Jeremiah likes to imagine new kinds of indexes, new kinds of teams, new kinds of applications. This means that when you need to reinvent something, or get unblocked, you should talk to Jeremiah.
Charles has been working with SQL Server since 1999 and has assisted companies with database design, application development, data warehousing, enterprise reporting and performance tuning. He has successfully implemented multi-million dollar systems and system conversions throughout his career. At Dematic Corp he is involved in creating high performance solutions using SQL Server 2005/2008 for high volume (1000's trans/sec) applications requiring subsecond response times.
LinkedIn: http://www.linkedin.com/in/eddiewuerch
Contact: http://www.indydba.com
Eddie Wuerch has 20 years of experience as a SQL Server specialist in a much-longer IT career. A Microsoft Certified Master, Eddie spends his days in the Salesforce Marketing Cloud, focusing on performance, scale, and uptime for the massive SQL Server backend. These SQL Servers churn billions of transactions daily against trillions of rows of data in a 24x7 continuously-available online system accessed by millions worldwide every day.
LinkedIn: http://www.linkedin.com/in/jasonstrate/
Contact: http://www.jasonstrate.com/
Jason Strate is a SQL Server Solutions Architect with Pragmatic Works. He is also a Microsoft SQL Server MVP and MCM. He has over 15 years of experience developing, architecting, and managing data platforms. Jason writes, blogs, and presents on SQL Server.
Contact: http://wendyverse.blogspot.com
Wendy Pastrick is from Chicago, IL, and for the past 15 years has served as a Database Administrator supporting both development and production environments. Her many years of involvement with PASS include WIT Virtual Chapter and the Chicago Suburban User Group, serving as Regional Mentor, and as a PASS Board member since 2013. Wendy has organized several highly successful SQLSaturday events in Chicago.
The following is a list of sponsors that helped fund the event.


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FAITHLESS (TROLÖSA) A film review by Rachel Gordon Copyright 2001 filmcritic.com filmcritic.com
Liv Ullman may get the directing credit, but every line in Faithless is stamped Ingmar Bergman (who wrote the script). Between the immoral souls of the characters twitching with desires they can't control and the extended two and a half hours to endure, who else could it be? (Bergman's original Fanny and Alexander was close to five hours long, though the American version is two and a half).
Bergman showed a penchant for family drama with Fanny and Alexander and Wild Strawberries, among others.  This can lead to a deeper emotional entanglement with the characters; it's human nature to reflect and react based on internalized stimuli. Unfortunately for Faithless, Bergman is revisiting territory he excelled in some 40 years ago, without shedding any new light on his subjects.
This isn't the first film in which Bergman has written an old man getting close to the end and brooding with a fantasy companion about his wrongdoings. It's basically Wild Strawberries, only this time the crime is adultery instead of hubris. The main character is even sitting at a desk and writing constantly, again.
Bergman (the character, played by Erland Josephson) is an elderly gentleman who beckons Marianne (Lena Endre) to discuss her adulterous relationship with David. Marianne, an actress, and Markus (Thomas Hanzon), an orchestra prodigy, have been happily married. They have a young daughter, Isabelle (newcomer Michelle Gylemo), and David (Krister Henrikkson) is their best friend. David is a director and the stereotypical brooding, unhappy artist. One day David offhandedly suggested sleeping with Marianne, and when she went to Paris on a special project, he found reason to go as well, and their new relationship began.
Bergman and Marianne journey through the entire story of the relationship. Often the camera cuts from the tense face of him to the tear-strained eyes of her. Every once in a while these moments are punctuated with a flashback sequence. In fact, the experience feels more like a play than a film, as screen time is consumed with the two sitting in a room and chatting away. The circumstances that brought Bergman to be the repentant weakling he is today and Marianne as his mirage take a back seat. Multiple takes of a man feeling horrible and a woman crying do not a film make.
Not to say that Faithless is a complete waste of time. When scenes that reflect on Isabelle come along, her innocence and quiet intelligence are well drawn. Because she gets to underplay the situation she has no control over, her plight becomes more important than that of her parents. This young amateur remarkably carries more presence in her silence than Marianne does with her tears.
Another fascinating point in the film is how simple and suddenly adultery can come to pass between two old friends. No easy excuse is made for it -- "trouble in the marriage" -- and the subsequent actions of the characters involved are realistically complicated. The film sticks to its story without attempting to pander to a mainstream audience.
For those who have never seen Bergman's work, this is not the place to start. A predecessor by some 40 years, Wild Strawberries is a more interesting story (even if it was shot in black and white) because the characters are more active, both in imagination and real time. They don't just sit around and brood all day but instead reflect based on external cues in their environment. That is what made Strawberries emotionally engaging. Perhaps if Faithless was told from beginning to end instead of through glimpses into a past, driven by tears, it would have hit half the nerves it was striving to.

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50000 Quaoar
Facts
- 50000 Quaoar, provisional designation 2002 LM60, is a non-resonant trans-Neptunian object (cubewano) and a possible dwarf planet in the Kuiper belt, a region of icy planetesimals beyond Neptune.
- It measures approximately 1,100 km (680 mi) in diameter, which is about half the diameter of Pluto.
- A small amount of methane is present on its surface, which can only be retained by the largest Kuiper belt objects.
- In 2004, signs of crystalline ice were found on Quaoar, indicating that the temperature rose to at least 110 K (−163 °C) sometime in the last ten million years.
History
- Discovered by Chad Trujillo, Michael Brown.
- Discovered in 002 Jun 05 10:48:08.
- In February 2007, Weywot, a synchronous minor-planet moon in orbit around Quaoar, was discovered by Brown. Weywot is measured to be 80 km (50 mi) across. Both objects were named after mythological figures from the Native American Tongva people in Southern California. Quaoar is the Tongva creator deity and Weywot is his son.
- At the time of its discovery in 2002, Quaoar was the largest object found in the Solar System since the discovery of Pluto.
Highlights
- Satellites: Quaoar has one known moon, Weywot.
- Not that much things.
Precaution
- Life becomes quite difficult due to adverse conditions that occur during the transition of the seasons. There are special shelters for these situations.
- We offer a special sprey-product for scientists doing field studies outside the sterile area for safety.
- Don't forget your coat.


See: Description
| Class | Description |
|---|---|
| Bv3fIntersection |
The bounding volume intersection describes the results of a bounding volume intersection test.
|
| BvMinMax3f |
The description of a 3D min-max volume.
|
| Line3f |
A class representing a line in 3D of single precision (the elements are represented by float values),
hence the name Line3f.
|
| PackageConstants |
Geometric computations for graphics are fraught with corner cases, particularly around vector normalization, matrix inversion
singularities, and ray intersection when the intersection is near the origin of the ray.
|
| Plane3f |
A class representing a plane in 3D of single precision (the components are represented by float values),
hence the name Plane3f.
|
| Plane3fIntersection |
A class representing a the intersection of a ray with a plane in 3D of single precision (the components are represented by
float values), hence the name Plane3fIntersection.
|
| Point3f |
A class representing a point in 3D of single precision (the components are represented by float values),
hence the name Point3f.
|
| Quadric3f |
A class representing a a family of quadrics centered at 0,0,0 in object space and with the Z axis being the primary axis
of the shape.
|
| Quadric3fIntersection |
The quadric intersection describes the results of a quadric intersection test.
|
| TestXfm3f | |
| Vector3f |
A class representing a vector in 3D of single precision (the components are represented by float values),
hence the name Vector3f.
|
| Xfm4x4f |
A class representing a
transformation (Xfm) in 3D of single precision (the components are represented by float values),
hence the name Xfm4x4f.
|
| Exception | Description |
|---|---|
| SingularMatrixException | |
| ZeroLengthVectorException |
The exception typically thrown in normalization functions when the vector being
normalized is so close to zero length (relative to floating point precision) that the
divide by length operation generates meaningless results or a floating point divide
by zero exception.
|
These are utility classes supporting 3D modeling, geometry, and rendering.


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CINDERELLA A film review by Adrian Preston Copyright 1996 Adrian Preston
The Brothers Grimm's fairy tales were a mish-mash of folk tales from around the world. Revisionists to the last, the Grimms traveled widely, collected tales and rewrote them to portray a Grimm version of the current socio-moral climate. Hans Christian Anderson did exactly the same thing. Rumplestiltskin is a prime example, the original version ( a Nordic folk tale I believe, but I could be wrong. ) had the heroine as a scheming shrew, who used her beauty to ensnare Rumplestiltskin into falling deeply in love with her, and who came to a very sticky end after she betrayed him and he snatched her first-born child away. The version we all know from childhood changes the focus of the story completely, so the ugly, un-socially-acceptible Rumplestilskin becomes the bogeyman. Revisionism in action.
The reason I'm mentioning this is that it draws an astonishing parallel with the Walt Disney of today, Pocahontas being the absolute definitive in this respect. However, Cinderella is the Walt Disney of the past and is Disney at it's best.
 Meeting a woman who claims to be her fairy godmother and transforms her into a vision of beauty, she attends the Prince's ball. The Prince falls deeply in love, but because Cinderella must leave at midnight, he only has a glass slipper with which to find her. A search ensues, Cinderella is found, they are married and live happily ever after. O.K., nothing earth shattering there, but Disney have managed to take all their stock effects and tie them into a lovely unified whole around the simple storyline.
As far as the plot goes ( we were talking about revisionism remember ), some liberties are taken.  At the end of the story, the stepmother and sisters as punishment had their eyes put out, and their tongues cut off, and were made to wander the streets as beggars. But really, you can't blame Disney for ommitting these little things. I doubt that an animated image of two women mutilating their feet would appeal to the younger audience. :)
The songs are simple and kept to a minimum. The comic relief characters ( the mice and the fairy-godmother ) are well-used througout the film and are tied in well with the plot, and the villain of the piece, the evil stepmother exudes a delicious air of evil. The weakest characters surprisingly are the ugly sisters, who are rather underutilised, and could have been depicted as more comic-evil than as they are portrayed, which is vindictive-nasty. One of the main criticisms one can make of the early Disney films is that the heroines were rather bland and ineffectual, witness Snow White, and Sleeping Beauty. With Cinderella, Disney give us a much more rounded character as a heroine, and the film hangs together around her, rather than the supporting characters.
The animation, as usual is excellent. Cinderella I suppose is a early to mid Disney piece, and is all clean lines and subtle shades, where the animative focus is on the characters rather than the background. It lacks both the realism of earlier and recent Disney work and the minimalism of mid-period, and is a sort of halfway-house between the two. It works though, and works very well. As personal preference goes, it is probably my favourite of the animation styles Disney have tinkered with so far.
Anyway, my son loves the film and so do I. (Probably for different reasons, I've always held a bit of a flame for Cinderella.) and I award the film:
**** (four stars) out of five.
-- Adi, Lecturer in ??????? Kingston University
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
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File generated from /home/antongml/offline_projects/potato_game/_build/test/lib/potatoserver/ebin/../src/farmer/farmer_server.erl by COVER 2018-10-27 at 23:14:36 **************************************************************************** | -module(farmer_server).


|
KratosMultiphysics
KRATOS Multiphysics (Kratos) is a framework for building parallel, multi-disciplinary simulation software, aiming at modularity, extensibility, and high performance. Kratos is written in C++, and counts with an extensive Python interface.
|
A set of functions to compute quantities of interest for turbulent flows. More...
#include <vorticity_utilities.h>
Public Member Functions | |
Life Cycle | |
| VorticityUtilities ()=delete | |
| VorticityUtilities (VorticityUtilities const &rOther)=delete | |
| Deleted copy constructor. More... | |
| ~VorticityUtilities () | |
| Destructor. More... | |
Operators | |
| VorticityUtilities & | operator= (VorticityUtilities const &rOther)=delete |
| Deleted assignment operator. More... | |
Static Public Member Functions | |
Operations | |
| static void | CalculateQValue (const Geometry< Node > &rGeometry, const ShapeFunctionDerivativesArrayType &rShapeFunctionsGradients, std::vector< double > &rQValues) |
| static void | CalculateVorticityMagnitude (const Geometry< Node > &rGeometry, const ShapeFunctionDerivativesArrayType &rShapeFunctionsGradients, std::vector< double > &rVorticityMagnitudes) |
| static void | CalculateVorticityVector (const Geometry< Node > &rGeometry, const ShapeFunctionDerivativesArrayType &rShapeFunctionsGradients, std::vector< array_1d< double, 3 >> &rVorticities) |
Type Definitions | |
| typedef Geometry< Node >::ShapeFunctionsGradientsType | ShapeFunctionDerivativesArrayType |
| Type for an array of shape function gradient matrices. More... | |
| KRATOS_CLASS_POINTER_DEFINITION (VorticityUtilities) | |
| Pointer definition of VorticityUtilities. More... | |
A set of functions to compute quantities of interest for turbulent flows.
| typedef Geometry< Node >::ShapeFunctionsGradientsType Kratos::VorticityUtilities< TDim >::ShapeFunctionDerivativesArrayType |
Type for an array of shape function gradient matrices.
|
delete |
|
delete |
Deleted copy constructor.
| Kratos::VorticityUtilities< TDim >::~VorticityUtilities |
Destructor.
|
static |
|
static |
|
static |
| Kratos::VorticityUtilities< TDim >::KRATOS_CLASS_POINTER_DEFINITION | ( | VorticityUtilities< TDim > | ) |
Pointer definition of VorticityUtilities.
|
delete |
Deleted assignment operator.


Untidy happens
It’s not always possible to store everything in a tidy
but humongous data store. So, we have things like SQL foreign keys.
Unfortunately, the database may not have been set up with future tidy
in mind. Or, database access is only provided through CSV files.
Here’s an example of what can happen. We begin with some basic information, as tidy
as we could wish with not too much effort.
> patients %>% select(KEY, AGE, ADULT, GENDER, SURVIVED)
# A tibble: 3,065 x 5
KEY AGE ADULT GENDER SURVIVED
<int> <int> <lgl> <chr> <lgl>
1 238916 59 TRUE Male TRUE
2 193078 37 TRUE Male TRUE
3 580164 29 TRUE Female TRUE
4 917895 82 TRUE Female TRUE
5 376887 58 TRUE Female TRUE
6 508153 35 TRUE Male TRUE
7 415059 21 TRUE Male TRUE
8 184182 24 TRUE Female TRUE
9 318438 20 TRUE Male TRUE
10 508148 64 TRUE Male TRUE
# … with 3,055 more rows
A separate file contains variables of interest
> assessment
# A tibble: 25,371 x 2
KEY ASSESS
<int> <dbl>
1 284827 922.
2 284827 867
3 284827 835
4 284827 509.
5 284827 508.
6 284827 508.
7 284827 506.
8 4383 925.
9 4383 919
10 4383 901
# … with 25,361 more rows
This is the dreaded duplicate row problem.
The ASSESS
field in the larger tibble is the untidy
result of “oh, I have a new observation of a medical condition; let me record it along with the related patient,” as opposed to “I have a patient with a new condition, let’s add the condition.”
Fortunately, the conditions are binary: a patient either has been diagnosed or not. This allows a some simple logic, after skipping over the addition of other data as shown in the source code.
We know we have an order of magnitude more records than subjects. Using an object, injury
that has accumulated all this excess, we can do something about it.
dedup_injury <- injury %>% group_by(KEY) %>% summarize_all(mean)
injury <- dedup_injury %>% group_by(KEY) %>% mutate_if(is.double, as.logical)
In the first line we are taking the mean values of all columns with the same key. A male patient who is, say, 29, will have a mean AGE
of 29, a logical mean of 1, meaning TRUE, for GENDER
, etc.
The second line is a bit trickier, but not much. Our hypothetical patient may have multiple diagnoses, which evaluate to true, and multiple diagnoses which evaluate to false. Each diagnosis has it’s own column. If they are all false, the mean will be zero, or false. If the mean is one or greater, the mean will be one or more, true. Since we don’t have a Boolean notion of how true, all that’s needed is to coerce the result to a logical.
The following code puts the solution in context. It’s mainly concerned with assembling relevant data from sources with different layout. I am grateful that I didn’t have to construct an SQL query to reach the same results.
Code
# preprocess: consolidate medical records from multiple files
# some of which have multiple entries per patient for a single
# observation type
# The data derive from the National Trauma Data Bank and have
# been scrambled to disguise the original content. The fabricated
# data used here relates solely to processing datasets containing
# duplicate rows
# Richard Careaga
# 2019-05-07
# MIT License
# import libraries
library(dplyr)
library(magrittr)
library(stringr)
library(tibble)
library(tidyr)
'%out%' <- Negate('%in%') # operator to exclude list members with filter
# search patterns
surv_pattern = "Deceased|Expired"
unk_pattern = "UNK" # MUST CENSOR ASOCIATED KEY FROM ALL FILES
# Get patient demographics
patients <- as_tibble(read.csv("survey.csv",
stringsAsFactors = FALSE)
)
# censor GENDER for unk
censor_unk_gender <- patients %>%
filter(str_detect(GENDER,unk_pattern)) %>%
select(KEY) # 1 patient
patients <- patients %>% filter(KEY %out% censor_unk_gender$KEY) # remove the non-binary
# identify the patients younger than 0 and add them to a list of KEYs to be
# eliminated from subsequent files
censor_age_list <- patients %>% filter(AGE < -0.01) %>% select(KEY)
patients <- patients %>% filter(KEY %out% censor_age_list$KEY) # remove the unaged
# Divide gender into t/f columns (to facilitate later collapse)
patients <- patients %>%
mutate(FEMALE = ifelse(GENDER == "Female", TRUE, FALSE),
MALE = ifelse(GENDER == "Male", TRUE, FALSE),
ADULT = ifelse(AGE > 17, TRUE, FALSE)) %>%
select(KEY, AGE, GENDER, MALE, FEMALE, ADULT)
# Get discharge status
discharges <- as_tibble(read.csv("DISCHARGE.csv",
stringsAsFactors = FALSE)) %>%
select(KEY,DISCHARGE)
# censor negative age patients
discharges <- discharges %>% filter(KEY %out% censor_age_list$KEY )
# identify patients coded unk
censor_unk_list <- discharges %>%
filter(str_detect(DISCHARGE,unk_pattern)) %>%
select(KEY)
# remove unk
discharges <- discharges %>% filter(KEY %out% censor_unk_list$KEY)
patients <- patients %>% filter(KEY %out% censor_unk_list$KEY)
# classify mortality
discharges <- discharges %>% mutate(SURVIVED =
ifelse(str_detect(DISCHARGE, surv_pattern), "FALSE","TRUE")) %>%
mutate(SURVIVED = as.logical(SURVIVED)) %>%
select(-DISCHARGE)
# patients remaining after application of age and unk filters
patient_list <- discharges %>% select(KEY) %>% distinct()
# Procedure codes
procedures <- as_tibble(read.csv("PROCEDURES.csv",
stringsAsFactors = FALSE)
)
# remove unneeded variables
procedures <- procedures %>% select(KEY, PROCEDURES)
# censor negative age patients
procedures <- procedures %>% filter(KEY %out% censor_age_list$KEY )
# censor unk patients
procedures <- procedures %>% filter(KEY %out% censor_unk_list$KEY )
# remove negative PROCEDURES -1 and -2
procedures <- procedures %>% filter(PROCEDURES > 0)
# patients who had surgery
proc_list <- procedures %>% select(KEY) %>% distinct()
# patients who had no surgery
no_surgery_patients <- setdiff(patient_list, proc_list)
# procedures of interest
PROCEDURES_in_list <- c(22.79, 22.81, 22.82, 22.83, 22.84, 22.85, 22.87, 22.88, 22.89, 22.93)
# all other procedures
PROCEDURES_other <- setdiff(procedures$PROCEDURES, PROCEDURES_in_list)
pancreas_surgery <- procedures %>% mutate(PANCREAS_SURG = ifelse(PROCEDURES %in% PROCEDURES_in_list, TRUE, FALSE)) %>% select(-PROCEDURES) %>% distinct()
# remove FALSE
pancreas_surgery <- pancreas_surgery %>% filter(PANCREAS_SURG == TRUE) %>% distinct()
# all other procedures
non_pancreas <- procedures %>% filter(PROCEDURES %in% PROCEDURES_other) %>% distinct()
other_surgery <- non_pancreas %>% mutate(NON_PANCREAS_SURG = ifelse(PROCEDURES %in% PROCEDURES_other, TRUE, FALSE)) %>%
select(KEY, NON_PANCREAS_SURG) %>%
distinct()
# remove FALSE
other_surgery <- other_surgery %>% filter(NON_PANCREAS_SURG == TRUE) %>% distinct()
# patients who had no procedure
no_surgery <- no_surgery_patients %>% mutate(NULL_SURGERY = TRUE) %>% distinct()
# Diagnostic codes
assessment <- as_tibble(read.csv("ASSESS.csv",
stringsAsFactors = FALSE))
assessment <- assessment %>% select(KEY, ASSESS)
assessment <- assessment %>% distinct()
# apply censor filters for age, unk and non-targeted procedures
assessment <- assessment %>% filter(KEY %out% censor_age_list$KEY )
assessment <- assessment %>% filter(KEY %out% censor_unk_list$KEY )
injurylist <- c("508", "508.0", "508.00", "508.1", "508.2", "508.3",
"508.4", "508.41", "508.42", "508.43", "508.49", "508.5",
"508.51", "508.52", "508.53", "508.59", "508.8", "508.9")
injurytype <- assessment %>% filter(ASSESS %in% injurylist)
injury <- injurytype %>%
mutate(
"F_508.0" = ifelse(ASSESS == "508" | ASSESS == "F_508.0"|
ASSESS == "508.00", TRUE, FALSE),
"F_508.1" = ifelse(ASSESS == "508.1", TRUE, FALSE),
"F_508.2" = ifelse(ASSESS == "508.2", TRUE, FALSE),
"F_508.3" = ifelse(ASSESS == "508.3", TRUE, FALSE),
"F_508.4" = ifelse(ASSESS == "508.4", TRUE, FALSE),
"F_508.41" = ifelse(ASSESS == "508.41", TRUE, FALSE),
"F_508.42" = ifelse(ASSESS == "508.42", TRUE, FALSE),
"F_508.43" = ifelse(ASSESS == "508.43", TRUE, FALSE),
"F_508.49" = ifelse(ASSESS == "508.49", TRUE, FALSE),
"F_508.5" = ifelse(ASSESS == "508.5", TRUE, FALSE),
"F_508.51" = ifelse(ASSESS == "508.51", TRUE, FALSE),
"F_508.52" = ifelse(ASSESS == "508.52", TRUE, FALSE),
"F_508.53" = ifelse(ASSESS == "508.53", TRUE, FALSE),
"F_508.59" = ifelse(ASSESS == "508.59", TRUE, FALSE),
"F_508.8" = ifelse(ASSESS == "508.8", TRUE, FALSE),
"F_508.9" = ifelse(ASSESS == "508.9", TRUE, FALSE)
)
injury <- injury %>% select(-ASSESS) %>% distinct()
# check if any patients with injury of interest received no treatment
mean(no_surgery$KEY %in% injury$KEY)
# deduplicate
dedup_injury <- injury %>% group_by(KEY) %>% summarize_all(mean)
injury <- dedup_injury %>% group_by(KEY) %>% mutate_if(is.double, as.logical)
# nodup_injury %>% ungroup()
non508 <- setdiff(assessment$KEY, injury$KEY)
injury_non508 <- assessment %>%
filter(KEY %in% non508) %>%
mutate("NON_508" = TRUE) %>%
select(-ASSESS) %>%
distinct()
# check for untreated non508 injury
mean(no_surgery$KEY %in% non508)
# Open or closed pancreas injury
# censorship has aleady been run on assessment
closed_inj <- assessment %>%
mutate("F_576.0" = ifelse(ASSESS == "576.0", TRUE, FALSE)) %>%
select(-ASSESS)
closed_inj <- closed_inj %>% distinct()
open_inj <- assessment %>%
mutate("F_576.1" = ifelse(ASSESS == "576.1", TRUE, FALSE)) %>%
select(-ASSESS)
open_inj <- open_inj %>% distinct()
p_injury <- left_join(closed_inj,open_inj)
p_injury <- p_injury %>% distinct()
# eliminate duplicates
pancreas_injury <- p_injury %>%
mutate(RETENTION = ifelse(`F_576.0` + `F_576.1` == 0, "delete", "retain")) %>%
filter(RETENTION == "retain") %>%
select(-RETENTION)
# patients who had no procedure
no_surgery <- no_surgery_patients %>% mutate(NULL_SURGERY = TRUE) %>% distinct()
# censor negative age patients
no_surgery<-no_surgery %>% filter(KEY %out% censor_age_list$KEY )
# censor unk patients
no_surgery <- no_surgery %>% filter(KEY %out% censor_unk_list$KEY )
# join pieces
patients <- left_join(patients, discharges)
patients <- patients %>% distinct()
patients <- left_join(patients, injury)
patients <- patients %>% distinct()
patients <- left_join(patients, pancreas_injury)
patients <- patients %>% distinct()
patients <- left_join(patients, pancreas_surgery)
patients <- patients %>% distinct()
patients <- left_join(patients, other_surgery)
patients <- patients %>% distinct()
patients <- left_join(patients, no_surgery)
patients <- patients %>% distinct()
# remove NAs from logical variables
patients <- patients %>%
replace_na(list("F_508.0" = FALSE, "F_508.1" = FALSE,
"F_508.2" = FALSE, "F_508.3" = FALSE,
"F_508.4" = FALSE, "F_508.41" = FALSE,
"F_508.42" = FALSE, "F_508.43" = FALSE,
"F_508.49" = FALSE, "F_508.5" = FALSE,
"F_508.51" = FALSE, "F_508.52" = FALSE,
"F_508.53" = FALSE, "F_508.59" = FALSE,
"F_508.8" = FALSE, "F_508.9" = FALSE,
"F_576.0" = FALSE, "F_576.1" = FALSE,
"PANCREAS_SURG" = FALSE, "NON_PANCREAS_SURG" = FALSE,
"NULL_SURGERY" = FALSE))
# Reorder variable names
patients <- patients %>% select("KEY","AGE","ADULT","GENDER", "SURVIVED","PANCREAS_SURG",
"NON_PANCREAS_SURG", "NULL_SURGERY","F_508.0","F_508.1",
"F_508.2","F_508.3","F_508.4","F_508.41", "F_508.42",
"F_508.43","F_508.49", "F_508.5", "F_508.51","F_508.52",
"F_508.53", "F_508.59","F_508.8", "F_508.9", "F_576.0",
"F_576.1")


Polls open in Uruguay's presidential election runoff
Conservative Luis Lacalle Pou has led opinion polls against rival Daniel Martinez after striking key coalition deals.
Voters in Uruguay are heading to the polls in a presidential election that appears likely to sweep the right-leaning opposition into power and end the centre-left's 15-year rule.
In the lead-up to Sunday's vote, conservative opposition candidate Luis Lacalle Pou led the opinion polls against ruling party candidate Daniel Martinez after striking key coalition deals following a first-round vote in October.
More:
Those alliances with mostly conservative parties might prove key - Lacalle Pou came second in the October 27 poll with around 29 percent of the vote, behind Martinez's Broad Front with 39 percent.
The polling stations will open at 8am (11:00 GMT) and close at 19:30 (22:30 GMT). Some 2.6 million voters are eligible to vote.
The next president will take office in March for five years.
Progressive government
The Broad Front, a coalition of leftist movements, can point to a record of progressive government since it broke a decades-long conservative stranglehold in 2005.
Uruguay stood out on the international stage by approving abortion and gay marriage, as well as pioneering the legalisation of cannabis in 2013.
But Lacalle Pau has tapped in to voter concerns over the country's high tax rates, promising to look elsewhere to raise the $900m needed to reduce the public deficit, nearly five percent of GDP.
"Uruguay can't bear any more taxes," he told supporters.
Security has also declined, with a sharp rise in some violent crimes reported last year.
In 2018, South America's second-smallest country registered a record 414 murders, up 45 percent on the year before.
"Lacalle is the president who can improve the country, change what Broad Front did wrong economically and especially security," said Mariela Barcia, a 51-year-old teacher who voted for the conservative candidate in October.


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Imogen Hermes Gowar studied Archaeology, Anthropology and Art History before going on to work in museums. She began to write fiction inspired by the artefacts she worked with, and in 2013 won the Malcolm Bradbury Memorial Scholarship to study for an MA in Creative Writing at UEA. Her first novel The Mermaid and Mrs Hancock has been widely praised and has generated a queue of curious customers.
1. Who were your literary influences as you were growing up?
I particularly liked Joan Aiken because she used lots of words I didn’t know, and Gerald Durrell because of the way he could move from lyrical, beautifully-observed descriptions to comedy.
My most direct literary influence, though, was probably Jill Murphy. I wrote many of my own homages to The Worst Witch. I wanted to go to Cackle’s Academy very badly.
2. The Mermaid and Mrs Hancock was published in late January. Can you set the scene a bit for us so we know what to expect?
It’s September 1785 and in Deptford a humble merchant, Mr Hancock, is waiting for his ship to return. What he doesn’t know is that it’s not coming back; his captain has traded it in for a hideous little mermaid, which he’ll have to put on display to recoup his costs. Meanwhile, in Soho, the courtesan Angelica Neal is contemplating her next step now that her old keeper has died.
I’d say this is historical fiction with a superstitious edge to it, rather than full-on fantasy. On the magic scale, it sits somewhere between Jonathan Strange & Mr Norrell, and The Essex Serpent.
3. What attracted you to setting your book in the 1780s?
I’ve enjoyed the period as a reader for years, partly because of its liveliness and humour, but also because it’s a time of extreme social change and revision.
People had been shocked by the revolution in America, and the same philosophies that informed that were stirring up unrest in France and guiding the emancipation movement. The dawning industrial revolution was making new fortunes and challenging ideas of class and inheritance – a lot of people must have felt that the world as they knew it was vanishing. It’s such an energetic era, I think I’ll be interested in it forever.
4. What were your feelings when you started writing it? Did the characters find a ‘voice’ quickly?
As soon as I had the initial idea, Angelica and Mr Hancock were there in my head. I didn’t have to do any searching for them; Angelica in particular had a very strong, insistent voice from the word go.
What was strongest, though, was the narratorial voice. I wanted to get lots of singular period language in there. As for my feelings, I didn’t take it seriously for a long time: I actually wrote it as a fun distraction from the very dour novel I was working on at the time. It had so much fun and levity in it I couldn’t believe it was worth doing. I know now that you have to write to please yourself before trying to please anybody else.
5. What is your writing routine?
I usually start the day with reading or research over breakfast, and move on to writing with the second cup of tea.
I used to sit down and write until I’d hit my word count – when I was writing The Mermaid and Mrs Hancock it was at least a thousand a day – but that can lead to a lot of self-flagellation on bad days. Now I find writing for a set period with great concentration, and then allowing myself to go and do other things, to be much healthier.
Everyone’s different, but I think the key is to avoid beating yourself up at all costs. This is meant to be enjoyable, not another chore.
6. Is there anything you can share about your latest ‘work in progress’?
It’s also set in London, but in a very different time period. It’ll be quite different from The Mermaid and Mrs Hancock, but I hope it will appeal to the same readers.
7. Do you have a message for your readers in Suffolk Libraries?
Libraries are marvellous; celebrate yours every chance you get.
8. Can you tell us one thing that your readers may not know about you?
My landladies are nuns! I live on the top floor of an old convent, with the kitchen under the bell tower.


Welcome to Workflow!
Workflow is a library meant to handle complex user flows in iOS applications.
Table of Contents:
- Insallation
- Why DynamicWorkflow?
- Getting Started
- Testing Your Workflows
- Advanced
- Developer Documentation
- FAQ
The problem DynamicWorkflow was built to solve:
When developing for iOS one view controller has to know about the one following it in order to pass along data. Imagine a workflow for a fast food app.
Pick a location -> Pickup or Delivery -> Catering Menu or Normal Menu -> Choose Food -> Review Order -> Submit payment
Now imagine if a users location is known via GPS. You may be able to skip the first screen and assume the nearest location knowing they can edit it on the review screen. Pickup or Delivery may or may not need to show up depending on what the location they picked supports, Same with catering menu vs normal menu
Finally the review screen would be really nice if it gave a way to edit. This spells a nightmare for you if you utilize UIStoryboardSegue to help. You’ll have to use many of them, and if the design of this user flow changes you’re in for a bit of an annoying time changing them around.
The solution
DynamicWorkflow lets you specify once what the whole workflow looks like, then each view controller defines whether it should show up or not, so to solve the above problem you’d use something like this.
let workflow = Workflow()
.thenPresent(LocationsViewController.self)
.thenPresent(PickupOrDeliveryViewController.self)
.thenPresent(MenuChooserViewController.self)
.thenPresent(FoodChooserViewController.self)
.thenPresent(ReviewOrderViewController.self)
.thenPresent(SubmitPaymentViewController.self)
//from wherever this flow is launched
launchInto(workflow)
If you ever want to re-order these you simply move their position in the chain. Your ViewControllers will be naturally start to become defined in a way where they can be injected into any kind of workflow and so if for scheduled orders you want screens to show up in a different order, you just define a new Workflow
.


Simple step for sending a RocketChat message to specified channel.
Use the advanced settings to override the RocketChat Plugin global configuration to include: channel
.
Please see the RocketChat Plugin global configuration for more details on the fields.
Usage Example:
rocketSend "Build Started - ${env.JOB_NAME} ${env.BUILD_NUMBER} (<${env.BUILD_URL}|Open>)"


String literals should be written with single quotes unless using double quotes would save on escape characters.
Bad: double quotes
content: "hello";
Good: single quotes
content: 'hello';
Good: double quotes prevent the need for escaping single quotes
content: "'hello'";
Single quotes are easier to type by virtue of not requiring the Shift
key on
most popular keyboard layouts.
| Configuration Option | Description |
|---|---|
style |
single_quotes or double_quotes (default single_quotes ) |


Preparation time
less than 30 mins
Cooking time
10 to 30 mins
Serves
Serves 4
Crunchy chicken and prawns in soft tacos are livened up with a spicy tomato sauce, zesty mango salsa and cooling avocado.
Preheat the oven to 180C/160C Fan/Gas 4. To make the tomato mole, heat the oil in a saucepan over a high heat. Add the onion, chillies, garlic and sweetcorn and cook for 5 minutes, until soft. Add the tomatoes, season and stir. Reduce to a simmer and cook for 20 minutes. Blend until smooth.
Meanwhile, cut the chicken into finger-sized strips. Mix together the crème fraîche and egg and roll the chicken and prawns in the mixture. Crush the corn chips inside their bag. Drop the coated chicken and prawns into the bag and rustle it around so each piece is coated in corn chip crumbs. Leave for 5 minutes, so the corn chips go a little soggy.
Heat a little oil in a frying pan over a medium heat and cook the chicken and prawns, in batches, for 2 minutes on each side. Transfer to a baking tray and bake for 10 minutes or until the chicken is cooked through and the coating is brown and crisp.
In separate bowls, mix together the ingredients for the quick slaw and for the mango salsa.
Cut the avocados in half lengthways and remove the seeds.  Mash the flesh very well with a fork and then mix in the juices, Tabasco and season.
To serve, divide the smashed avocado between the tacos. Add the chicken and prawns and top with the tomato mole, quick slaw and mango salsa.


You could export the mermaid markdown and try to render the diagram on
your own. (search for: "mermaid cli")
In the meantime we are working to fix the issue.
{{ alert.rawData | json }}
Report it here: https://github.com/R0tenur/visualization/issues


This file contains a sample of ways Privly links may be displayed on host pages. Privly extensions must pass all these test cases before deployment.
Privly link https://priv.ly/posts/2#privlyInject1
Privly link without SSL http://priv.ly/posts/2#privlyInject1
Privly link https://priv.ly/posts/2#privlyInject1
Privly link without SSL http://priv.ly/posts/2#privlyInject1
Privly link forms all the body contents of the anchor, but the href points to a tracking server
Privly link https://priv.ly/posts/2#privlyInject1
Privly link without SSL http://priv.ly/posts/2#privlyInject1
Privly link is in the body of the anchor with other text, but the href points to a tracking server
Privly link Our link is surrounded by other text https://priv.ly/posts/2#privlyInject1 yes it is.
Privly link without SSL Our link is surrounded by other text http://priv.ly/posts/2#privlyInject1 yes it is.
Privly link is on an attribute other than the href
Privly link Link body does not contain Privly href
Privly link without SSL Link body does not contain Privly href


Want feedback on your assignment?
Feel free to DM us on any of our platforms here: Instagram , Discord , or LinkedIn. Alternatively, you may shoot us an email at<EMAIL_ADDRESS>and we will process your inquiry as quick as we can.


1 instantiation of PSSecurityException
System.Management.Automation (1)
engine\SecurityManagerBase.cs (1)
139
PSSecurityException securityException = new
PSSecurityException
(message, authorizationManagerException);
11 references to PSSecurityException
Microsoft.PowerShell.Commands.Utility (1)
commands\utility\ShowCommand\ShowCommandCommandInfo.cs (1)
46
catch (
PSSecurityException
)
System.Management.Automation (10)
engine\CommandDiscovery.cs (2)
538
/// <exception cref="System.Management.Automation.
PSSecurityException
">
642
catch (
PSSecurityException
reason)
engine\GetCommandCommand.cs (1)
1347
catch (
PSSecurityException
)
engine\Modules\ExportModuleMemberCommand.cs (1)
170
var
se = new PSSecurityException(Modules.CannotExportMembersAccrossLanguageBoundaries);
engine\remoting\fanin\InitialSessionStateProvider.cs (1)
1734
catch (
PSSecurityException
e)
engine\SecurityManagerBase.cs (3)
71
/// <exception cref="System.Management.Automation.
PSSecurityException
">
127
if (authorizationManagerException is
PSSecurityException
)
139
PSSecurityException
securityException = new PSSecurityException(message, authorizationManagerException);
engine\TypeTable.cs (1)
4619
catch (
PSSecurityException
reason)
FormatAndOutput\common\DisplayDatabase\XmlLoaderBase.cs (1)
635
catch (
PSSecurityException
reason)


In today's user interfaces there will be more ways to initiate a certain action. For instance a save action might be triggered by a toolbar button, a context menu or a keyboard shortcut. If you have a significant number of actions in your interfaces it becomes increasingly difficult to manage the actions and elements that invoke these actions.
Suppose that the previously mentioned save action should be enabled only when certain data is changed. Ideally you'll want to disable the toolbar button and context menu item too. This easily can lead to pages of spaghetti code.
An action list can provide a solution in this case. Instead of linking the interface elements with the action handlers directly you store the actions in a central repository: the action list. And the elements that should invoke the actions are registered at the action list. The action list knows how it should manipulate the state of interface elements and prevents access to disabled actions. Thus when an action is disabled, all interface elements that trigger the action are disabled too. It somehow the action is triggered anyway the action list will ultimately prevent it.
In the example box a typical example is given. It is a small interface to three actions: to popup three different boxes, pretty useless but actions nonetheless. The three actions can be triggered by toolbar buttons and a popup menu. The 'alert' action can also be triggered by a button.
If you check the 'disable alert' check box the 'alert' action will be disabled and the interface responds immediately by disabling the 'alert' button on the toolbar and the 'alert' menu option.
Apparently the big 'Show alert' button is still active. That is because it was not registered at the action list, but it still uses the action list's action. So when clicking the button the action list will prevent action execution.
There is also another benefit of using an action list. The toolbar buttons and menu items have icons and (hover) texts. These are arguably not properties of these interface elements but rather properties of the actions. By using an action list you can define icons and descriptive texts at the action level and let the user interface elements use this data (unless redefined/overridden).


Typer
{{mminutes || "00"}}:{{sseconds || "00"}}
{{t.wpm}}
WPM
Add Text!
Finished!
Spacebar to restart.


That’s some text with a footnote 1 and another 2 and another 3.
This is not a footnote.
And that’s the footnote. This is second sentence (same paragraph).
This is the very long one.
That’s the second paragraph.
And that’s the footnote.
That’s the second paragraph of the footnote.


|
||||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
Object realtimeweb.redditservice.util.Util
public class Util
Contains several functions that seriously should have been added to Java core. Or maybe I should have used Guava.
| Constructor Summary | |
|---|---|
Util()
|
| Method Summary | |
|---|---|
static double |
formatDecimals(double d,
int mantissa)
Change the precision of a double value, according to the new mantissa. |
static String |
get(String url,
HashMap<String,String> query_args)
|
static String |
hashRequest(String url,
Map<String,String> query_arguments)
|
static String |
join(List objects)
Concatenate a list of objects into a single string (using their "toString" method), joining them with a ",". |
static String |
join(String glue,
List objects)
Concatenate a list of objects into a single string (using their "toString" method), joining them with a specified glue string. |
static String |
post(String url,
Map<String,String> body_args)
|
static String |
slurp(InputStream is,
int bufferSize)
Convert an InputStream to a string. |
| Methods inherited from class Object |
|---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Constructor Detail |
|---|
public Util()
| Method Detail |
|---|
public static String join(List objects)
objects
- A list of objects to concatenate.
public static String join(String glue, List objects)
glue
- A string to use to join the objects.objects
- A list of objects to concatenate.
public static double formatDecimals(double d, int mantissa)
d
- The double value you want re-precisioned.mantissa
- The number of digits after the decimal place.
public static String slurp(InputStream is, int bufferSize) throws IOException
is
- bufferSize
-
IOException
public static String get(String url, HashMap<String,String> query_args) throws IllegalStateException, IOException, URISyntaxException
IllegalStateException
IOException
URISyntaxException
public static String post(String url, Map<String,String> body_args) throws IllegalStateException, IOException, URISyntaxException
IllegalStateException
IOException
URISyntaxException
public static String hashRequest(String url, Map<String,String> query_arguments)
|
||||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |


It is a global network, which connects all the computer and non-computer equipments around the world. The primary goal behind these connections is communication.
The Internet Corporation for Assigned Names and Numbers (ICANN) is a non-profit responsible for keeping the Internet secured, stable, and interoperable.
Domain name is the address put into the browser URL bar to reach a website.
An Internet Protocol Address (IP Address) is a unique string of character, which works as an identifier for a computer device.
Packets are small sets of data sent through a network with a destination.
The process of Routing serves the purpose of selecting a traffic route in a network or between multiple networks.
The Domain Name System (DNS) acts like a phone directory. It provides a way to match website names or addresses.
HTTP and HTTPS are both hypertext transfer protocol that enable the web data to be presented on screen as requested. While they are very similar, the one thing that sets them apart is HTTPS is more advanced as well as more secured.
World Wide Web Consortium (W3C) is an organization led by Tim Berners-Lee. The primary goal of this organization is to help a World Wide Web reach its full potential by creating protocols and guidelines for a long-term growth.
HTML and CSS are the two significant programming languages used for building a website.


This program plots the map with strike and dip symbols for planes and arrows for linears. The map is drawn either with geographic coordinates, Gauss-Krueger, or UTM-coordinates. In the menu "Margins of the map" The frame of the map can be increased or decreased, or the coordinates of the margin can be redefined. The purpose of the latter is to overlay a map, a digital elevation model, or a satellite image. Fill in the coordinates of the margins of this image to make sure that the image will not be distorted. Overlay is done in the menu "Diagram" either from clipboard or from a file. In the same menu the new map may be saved and/or printed.


DPM: Seven states won’t ban child marriage
by BY AZRIL ANNUARKUALA LUMPUR, Nov 19 — The federal government cannot enforce a ban on child marriages nationwide as seven states are not cooperating, Datuk Seri Dr Wan Azizah Wan Ismail revealed in Parliament today.
The deputy prime minister told Dewan Rakyat during the Minister’s Question Time only Selangor has successfully amended its laws on child marriages.
“Amending the enactment/legal ordinance on minimum age for marriages can only happen if the states agreed with the proposed amendments. Only Selangor has amended the enactment while the Federal Territories is in the process of amending it.
“Five other states that have agreed to amend (the law) are Penang, Sabah, Johor, Melaka and Perak.
“There are still seven states that disagreed with the legal amendment, which are Sarawak, Pahang, Terengganu, Perlis, Negri Sembilan, Kedah and Kelantan,” she said in her reply to Ledang (PH) MP Syed Ibrahim Syed Noh.
The women, family and community development minister also said her ministry is finalising the National Strategic Plan to Overcome the Reason of Underage Marriage.
The plan has programmes or actions involving 61 federal and state agencies and is expected to be presented to the Cabinet at the end of the year.

“In this issue, criminal elements cannot be proven. There are no evidence of the communication can be traced and it is also protected by the Personal Data Protection Act while their relationship has obtained the approval of the child and the child’s parents.
“Another problem is after grooming, they marry the child and many of parents feel that it is good for the child to be married off. It is very difficult to determine the sexual crime,” said Dr Wan Azizah.
Rantau Panjang (PAS) MP Datuk Siti Zailah Mohd Yusof then asked if the ministry has data on the divorce rate of child marriages, after noting that the divorce rate among those who are below 25 years of age has been spiking recently.
Dr Wan Azizah said it did not.


--- title: Importing Crystal Orientations sidebar: documentation_sidebar permalink: OrientationImport.html folder: documentation toc: false ---
In order to import orientation data from a text file we first need to defined the corresponding crystal symmetry, e.g. by a cif file
{% highlight matlab %} cs = crystalSymmetry.load('quartz.cif') {% endhighlight %} {% highlight plaintext %} cs = crystalSymmetry mineral : Quartz symmetry : 321 elements : 6 a, b, c : 4.9, 4.9, 5.4 reference frame: X||a*, Y||b, Z||c* {% endhighlight %}In the second step we may use the command orientation.load
to load the data. This function requires that one specifies the meaning of the column of the import file by the option columnNames
.
This creates a variable of type orientation which can be used for further analysis, e.g. to plot pole figures
{% highlight matlab %} plotPDF(ori,Miller({0,0,0,1},{1,0,-1,0},cs)) {% endhighlight %}


{% extends 'base.html' %} {% block content %}
This application helps you keep track of the evolution of the elements of your playlists.
Channel {{ channel.title }}
{{ playlist.title }}
See details


This page makes use of amp form for the form and amp bind to set some text and css classes when the form submits


--- layout: page title: Lean Prover Zulip Chat Archive permalink: archive/113488general/43086strictlymonotone.html ---
We have def monotone (f : α → β) := ∀⦃a b⦄, a ≤ b → f a ≤ f b
, but is there a version with < ... <
?
oh, it's strict_mono
in a different place
I think there's a PR about this
Perhaps it should move to order/
This is one of the infinitely many PR's coming from the perfectoid project :D
{% endraw %}