@@include("../partials/head.html")
Get started with Dash-ui, Responsive Website Template for building responsive, mobile-first sites, with Bootstrap and a template starter page.
Be sure to have your docs set up with the latest design and development standards. That means using an HTML5 doctype and including a viewport meta tag for proper responsive behaviors. Put it all together and your docs should look like this:
That’s all you need for overall page requirements. Visit the Layout docs or our official examples to start laying out your site’s content and components.
Dash-ui employs a handful of important global styles and settings that you’ll need to be aware of when using it, all of which are almost exclusively geared towards the normalization of cross browser styles. Let’s dive in.
Dash-ui requires the use of the HTML5 doctype. Without it, you'll see some funky incomplete styling, but including it shouldn't cause any considerable hiccups.
Dash-ui is developed mobile first, a strategy in which we optimize code for mobile devices first and then scale up components as necessary using CSS media queries. To ensure proper rendering and touch zooming for all devices, add the responsive viewport meta tag to your .
You can see an example of this in action in the starter template.


This program takes in a String in postfix notation, and provides functionality to evaluate it.
The user can add to the postfix string by entering an integer or operator in the text field and pressing enter or pressing the "Add to Postfix String" button. The current postfix string will is shown in the "Current String" box. The string can be evaluated by pressing the Evaluate button or cleared with the Clear button.
A valid postfix string is assumed.
The PostfixEvaluatorGUI class creates the window and implements an ActionListener that is configured to listen for events from the Add to String, Evaluate, and Clear buttons as well as events from the top text field. The class also initializes a PostfixEvaluator object to store the postfix StringBuffer object and perform the evaluation.
The PostfixEvaluator performs the postfix evaluation by reading the StringBuffer from left to right. It pushes numbers to an integer stack, and when an operator is encountered, the top two values are popped from the stack and evaluated using that operator. The result is pushed back on the stack, and this continues until the end of the string is reached. The final value popped from the stack is the final result to be displayed in the Evaluation field.
The string is traversed character by character using spaces to separate both integers and operators from each other.


Flash Player plugin required
Execution of this tool demo requires an installed Flash Player plugin (version 10 or higher).


| Class | Description |
|---|---|
| Achievement |
A StarCraft 2 achievement.
|
| Achievements |
Class who contains player's
Achievement . |
| Campaign |
Payers campaign progression.
|
| Career |
Useful information about player's multiplayers career.
|
| Points |
Total and collections of obtain points by a player in this career.
|
| Portrait |
Picture used by a player.
|
| Profile |
Player's profile.
|
| Rewards |
All player's rewards.
|
| Season |
Season informations.
|
| Stats |
Statistics about palyer's game.
|
| SwarmLevel |
Player experience with one race.
|
| SwarmLevels |
Player experience of each Race.
|


« Previous Demo:
Animated Content Tabs with CSS3
Back to the Codrops Article
Rotating Words
with CSS Animations
Demo 1
Demo 2
Demo 3
Demo 4
Demo 5
Real poetry is like
creating beautiful butterflies
with a silent touch of
spice
colors
happiness
wonder
sugar
happiness
Real poetry is like creating beautiful butterflies with a silent touch of spice


{% extends 'outpost/base.html' %} {% block content %}
Welcome to the data management portal of the Medical University of Graz.
Official Website


| TEZ-1881 |
Setup initial test-patch script for TEZ-1313 |
Major |
. |
Hitesh Shah |
Hitesh Shah |
| TEZ-1889 |
Fix test-patch to provide correct findbugs report |
Critical |
. |
Hitesh Shah |
Hitesh Shah |
| TEZ-1844 |
Shouldn't invoke system.exit in local mode when AM is failed to start |
Major |
. |
Jeff Zhang |
Jeff Zhang |
| TEZ-1912 |
Merge exceptions are thrown when enabling tez.runtime.shuffle.memory-to-memory.enable && tez.runtime.shuffle.memory-to-memory.segments |
Major |
. |
Rajesh Balamohan |
Rajesh Balamohan |
| TEZ-1913 |
Reduce deserialize cost in ValuesIterator |
Major |
. |
Rajesh Balamohan |
Rajesh Balamohan |
| TEZ-1945 |
Remove 2 GB memlimit restriction in MergeManager |
Major |
. |
Rajesh Balamohan |
Rajesh Balamohan |
| TEZ-1661 |
LocalTaskScheduler hangs when shutdown |
Major |
. |
Oleg Zhurakousky |
Jeff Zhang |
| TEZ-1949 |
Whitelist TEZ_RUNTIME_OPTIMIZE_SHARED_FETCH for broadcast edges |
Critical |
. |
Gopal V |
Gopal V |
| TEZ-1593 |
Refactor PipelinedSorter to remove all MMAP based ByteBuffer references |
Major |
. |
Gopal V |
Rajesh Balamohan |
| TEZ-1963 |
Fix post memory merge to be > 2 GB |
Major |
. |
Rajesh Balamohan |
Rajesh Balamohan |
| TEZ-1982 |
TezChild setupUgi should not be using environment |
Major |
. |
Siddharth Seth |
Siddharth Seth |
| TEZ-1803 |
Support > 2gb sort buffer in pipelinedsorter |
Major |
. |
Rajesh Balamohan |
Rajesh Balamohan |
| TEZ-1997 |
Remove synchronization DefaultSorter::isRLENeeded() (Causes sorter to hang indefinitely in large jobs) |
Major |
. |
Rajesh Balamohan |
Rajesh Balamohan |
| TEZ-1995 |
Build failure against hadoop 2.2 |
Major |
. |
Hitesh Shah |
Rajesh Balamohan |
| TEZ-2000 |
Source vertex exists error during DAG submission |
Major |
. |
Rohini Palaniswamy |
Jeff Zhang |
| TEZ-1999 |
IndexOutOfBoundsException during merge |
Major |
. |
Rohini Palaniswamy |
Rajesh Balamohan |
| TEZ-2082 |
Race condition in TaskAttemptListenerImpTezDag.getTask() |
Major |
. |
Hitesh Shah |
Bikas Saha |
| TEZ-2075 |
Incompatible issue caused by TEZ-1233 that TezConfiguration.TEZ_SITE_XML is made private |
Critical |
. |
Jeff Zhang |
Jeff Zhang |
| TEZ-2095 |
master branch fails to compile against hadoop-2.4 |
Critical |
. |
Hitesh Shah |
Hitesh Shah |
| TEZ-1996 |
Update Website after 0.6.0 |
Major |
. |
Jonathan Eagles |
Jonathan Eagles |
| TEZ-2072 |
Add missing Private annotation to createDAG in the DAG API class |
Minor |
. |
Siddharth Seth |
Siddharth Seth |
| TEZ-2080 |
Localclient should be using tezconf in init instead of yarnconf |
Major |
. |
Prakash Ramachandran |
Siddharth Seth |
| TEZ-167 |
Create tests for MR Combiner |
Major |
. |
Hitesh Shah |
Devaraj K |
| TEZ-2085 |
PipelinedSorter should bail out (on BufferOverflowException) instead of retrying continuously |
Major |
. |
Rajesh Balamohan |
Rajesh Balamohan |
| TEZ-2009 |
Change license/copyright headers to 2015 |
Blocker |
. |
Hitesh Shah |
Hitesh Shah |
| TEZ-1935 |
Organization should be removed from http://tez.apache.org/team-list.html |
Major |
. |
Hitesh Shah |
Hitesh Shah |
| TEZ-2133 |
Secured Impersonation: Failed to delete tez scratch data dir |
Major |
. |
Johannes Zillmann |
Chang Li |
| TEZ-2070 |
Controller class of output should be committer rather than initializer in DAG's dot file |
Trivial |
. |
Jeff Zhang |
Jeff Zhang |
| TEZ-2170 |
Incorrect its in README.md |
Critical |
. |
Jakob Homan |
Jakob Homan |
| TEZ-2171 |
Remove unused metrics code |
Major |
. |
Prasanth Jayachandran |
Prasanth Jayachandran |
| TEZ-2178 |
YARN-3122 breaks tez compilation with hadoop 2.7.0 |
Major |
. |
Rajesh Balamohan |
Rajesh Balamohan |
| TEZ-1827 |
MiniTezCluster takes 10 minutes to shut down |
Minor |
. |
Ashutosh Chauhan |
Hitesh Shah |
| TEZ-2195 |
TestTezJobs::testInvalidQueueSubmission/testInvalidQueueSubmissionToSession fail with hadoop branch-2 |
Major |
. |
Hitesh Shah |
Hitesh Shah |
| TEZ-2059 |
Remove TaskEventHandler in TestDAGImpl |
Minor |
. |
Jeff Zhang |
Jeff Zhang |
| TEZ-2202 |
Fix LocalTaskExecutionThread ID to the standard thread numbering |
Major |
. |
Gopal V |
Gopal V |
| TEZ-2186 |
OOM with a simple scatter gather job with re-use |
Major |
. |
Siddharth Seth |
Rajesh Balamohan |
| TEZ-2204 |
TestAMRecovery increasingly flaky on jenkins builds. |
Major |
. |
Hitesh Shah |
Jeff Zhang |
| TEZ-2251 |
Race condition in VertexImpl & Edge causes DAG to hang |
Major |
. |
Rajesh Balamohan |
Rajesh Balamohan |
| TEZ-2265 |
All inputs/outputs in a task share the same counter object |
Major |
. |
Bikas Saha |
Bikas Saha |
| TEZ-2232 |
Allow setParallelism to be called multiple times before tasks get scheduled |
Major |
. |
Bikas Saha |
Bikas Saha |
| TEZ-1993 |
Implement a pluggable InputSizeEstimator for grouping fairly |
Major |
. |
Gopal V |
Gopal V |
| TEZ-2269 |
DAGAppMaster becomes unresponsive |
Major |
. |
Rajesh Balamohan |
|
| TEZ-2223 |
TestMockDAGAppMaster fails due to TEZ-2210 on mac |
Major |
. |
Jeff Zhang |
Hitesh Shah |
| TEZ-2293 |
When running in "mr" mode, always use MR config settings |
Major |
. |
Hitesh Shah |
Hitesh Shah |
| TEZ-2233 |
Allow EdgeProperty of an edge to be changed by VertexManager |
Major |
. |
Bikas Saha |
Bikas Saha |
| TEZ-2290 |
Scale memory for Default Sorter down to a max of 2047 MB if configured higher |
Blocker |
. |
Hitesh Shah |
Rajesh Balamohan |
| TEZ-2299 |
Invalid dag creation in MRRSleepJob post TEZ-2293 |
Major |
. |
Hitesh Shah |
Hitesh Shah |
| TEZ-2252 |
Tez UI: in graphical view some of the sinks are hidden as they overlap |
Major |
UI |
Rohini Palaniswamy |
Sreenath Somarajapuram |
| TEZ-2318 |
Tez UI: source and sink page is broken as they are not populated. |
Major |
UI |
Prakash Ramachandran |
Sreenath Somarajapuram |
| TEZ-2033 |
Update TestOrderedWordCount to add processor configs as history text and use MR configs correctly |
Minor |
. |
Hitesh Shah |
Hitesh Shah |
| TEZ-2323 |
Fix TestOrderedWordcount to use MR memory configs |
Major |
. |
Yesha Vora |
Hitesh Shah |
| TEZ-2310 |
Deadlock caused by StateChangeNotifier sending notifications on thread holding locks |
Major |
. |
Daniel Dai |
Bikas Saha |
| TEZ-2328 |
Add tez.runtime.sorter.class & rename tez.runtime.sort.threads to tez.runtime.pipelined.sorter.sort.threads |
Major |
. |
Rajesh Balamohan |
Hitesh Shah |
| TEZ-2313 |
Regression in handling obsolete events in ShuffleScheduler |
Blocker |
. |
Bikas Saha |
Rajesh Balamohan |
| TEZ-2224 |
EventQueue empty doesn't mean events are consumed in RecoveryService |
Major |
. |
Jeff Zhang |
Jeff Zhang |
| TEZ-2340 |
TestRecoveryParser fails |
Major |
. |
Jeff Zhang |
Jeff Zhang |
| TEZ-2261 |
Should add diagnostics in DAGAppMaster when recovery error happens |
Major |
. |
Jeff Zhang |
Jeff Zhang |
| TEZ-2357 |
Tez UI: misc.js.orig is committed by accident |
Major |
UI |
Jeff Zhang |
Prakash Ramachandran |
| TEZ-2341 |
TestMockDAGAppMaster.testBasicCounters fails on windows |
Minor |
. |
Jeff Zhang |
Jeff Zhang |
| TEZ-2248 |
VertexImpl/DAGImpl.checkForCompletion have too many termination cause checks |
Major |
. |
Bikas Saha |
Jeff Zhang |
| TEZ-2298 |
Ignore sending failure message, when TaskReporter$HeartbeatCallable is shutdown |
Major |
. |
Rajesh Balamohan |
Siddharth Seth |
| TEZ-2364 |
'joindatagen' AM picks wrong staging dir |
Major |
. |
Yesha Vora |
Siddharth Seth |
| TEZ-2362 |
State Change Notifier Thread should be stopped when dag is completed |
Major |
. |
Jeff Zhang |
Bikas Saha |
| TEZ-2342 |
TestFaultTolerance.testRandomFailingTasks fails due to timeout |
Minor |
. |
Jeff Zhang |
Jeff Zhang |
| TEZ-2358 |
Pipelined Shuffle: MergeManager assumptions about 1 merge per source-task |
Blocker |
. |
Gopal V |
Rajesh Balamohan |
| TEZ-2325 |
Route status update event directly to the attempt |
Major |
. |
Bikas Saha |
Prakash Ramachandran |
| TEZ-2314 |
Tez task attempt failures due to bad event serialization |
Blocker |
. |
Rohini Palaniswamy |
Bikas Saha |
| TEZ-2374 |
Fix build break against hadoop-2.2 due to TEZ-2325 |
Major |
. |
Hitesh Shah |
Hitesh Shah |
| TEZ-2305 |
MR compatibility sleep job fails with IOException: Undefined job output-path |
Critical |
. |
Tassapol Athiapinya |
Jeff Zhang |
| TEZ-2084 |
Tez UI: Stacktrace format info is lost in diagnostics |
Major |
UI |
Jeff Zhang |
Prakash Ramachandran |
| TEZ-2383 |
Cleanup input/output/processor contexts in LogicalIOProcessorRuntimeTask |
Major |
. |
Rajesh Balamohan |
Rajesh Balamohan |
| TEZ-1560 |
Invalid state machine handling for V_SOURCE_VERTEX_RECOVERED in recovery |
Critical |
. |
Jeff Zhang |
Jeff Zhang |
| TEZ-2221 |
VertexGroup name should be unqiue |
Major |
. |
Jeff Zhang |
Jeff Zhang |
| TEZ-2389 |
Tez UI: Sort by attempt-no is incorrect in attempts pages. |
Major |
. |
Sreenath Somarajapuram |
Sreenath Somarajapuram |
| TEZ-2363 |
Counters: off by 1 error for REDUCE_INPUT_GROUPS counter |
Minor |
. |
Gopal V |
Gopal V |
| TEZ-2360 |
per-io counters flag should generate both overall and per-edge counters |
Major |
. |
Hitesh Shah |
Prakash Ramachandran |
| TEZ-1988 |
Tez UI: does not work when using file:// in a browser |
Major |
UI |
Hitesh Shah |
Prakash Ramachandran |
| TEZ-2395 |
Tez UI: Minimum/Maximum Duration show a empty bracket next to 0 secs when you purposefully failed a job. |
Major |
UI |
Prakash Ramachandran |
Prakash Ramachandran |
| TEZ-2386 |
Tez UI: Inconsistent usage of icon colors |
Major |
UI |
Prakash Ramachandran |
Prakash Ramachandran |
| TEZ-2397 |
Translation of LocalResources via Tez plan serialization can be lossy |
Critical |
. |
Siddharth Seth |
Siddharth Seth |
| TEZ-2394 |
Issues when there is an error in VertexManager callbacks |
Critical |
. |
Bikas Saha |
Bikas Saha |
| TEZ-2405 |
PipelinedSorter can throw NPE with custom compartor |
Critical |
. |
Rajesh Balamohan |
Rajesh Balamohan |
| TEZ-2379 |
org.apache.hadoop.yarn.state.InvalidStateTransitonException: Invalid event: T_ATTEMPT_KILLED at KILLED |
Blocker |
. |
Rajesh Balamohan |
Hitesh Shah |
| TEZ-2237 |
Valid events should be sent out when an Output is not started |
Critical |
. |
Cyrille Chépélov |
Siddharth Seth |
| TEZ-2408 |
TestTaskAttempt fails to compile against hadoop-2.4 and hadoop-2.2 |
Minor |
. |
Hitesh Shah |
Hitesh Shah |
| TEZ-2401 |
Tez UI: All-dag page has duration keep counting for KILLED dag. |
Critical |
UI |
Tassapol Athiapinya |
Prakash Ramachandran |
| TEZ-2369 |
Add a few unit tests for RootInputInitializerManager |
Major |
. |
Siddharth Seth |
Siddharth Seth |
| TEZ-2415 |
PMC RDF needs to use asfext:pmc, not asfext:PMC |
Major |
. |
Sebb |
Hitesh Shah |
| TEZ-2406 |
Tez UI: Display per-io counter columns in task and attempt pages under vertex |
Major |
. |
Sreenath Somarajapuram |
Sreenath Somarajapuram |
| TEZ-2417 |
Tez UI: Counters are blank in the Attempts page if all attempts failed |
Major |
UI |
Sreenath Somarajapuram |
Prakash Ramachandran |
| TEZ-2396 |
pig-tez-tfile-parser pom is hard coded to depend on 0.6.0-SNAPSHOT version |
Major |
. |
Jonathan Eagles |
Rajesh Balamohan |
| TEZ-2366 |
Pig tez MiniTezCluster unit tests fail intermittently after TEZ-2333 |
Critical |
. |
Daniel Dai |
Prakash Ramachandran |
| TEZ-2416 |
Tez UI: Make tooltips display faster. |
Major |
. |
Sreenath Somarajapuram |
Sreenath Somarajapuram |
| TEZ-2423 |
Tez UI: Remove Attempt Index column from task->attempts page |
Major |
. |
Sreenath Somarajapuram |
Sreenath Somarajapuram |
| TEZ-2404 |
Handle DataMovementEvent before its TaskAttemptCompletedEvent |
Critical |
. |
Jeff Zhang |
Jeff Zhang |
| TEZ-2410 |
VertexGroupCommitFinishedEvent & VertexCommitStartedEvent is not logged correctly |
Blocker |
. |
Jeff Zhang |
Jeff Zhang |
| TEZ-2412 |
Should kill vertex in DAGImpl#VertexRerunWhileCommitting |
Blocker |
. |
Jeff Zhang |
Jeff Zhang |
| TEZ-2426 |
Ensure the eventRouter thread completes before switching to a new task and thread safety fixes in IPOContexts. |
Critical |
. |
Bikas Saha |
Siddharth Seth |
| TEZ-2445 |
Disable the object cleanup in local mode in LogicalIOProcessorRuntimeTask |
Blocker |
. |
Jeff Zhang |
Jeff Zhang |
| TEZ-2432 |
Syntax error in DOAP file release section |
Major |
. |
Sebb |
Hitesh Shah |
| TEZ-2057 |
tez-dag/pom.xml contains versions for dependencies |
Major |
. |
Hitesh Shah |
Jonathan Eagles |
| TEZ-2752 |
logUnsuccessful completion in Attempt should write original finish time to ATS |
Major |
. |
Bikas Saha |
Bikas Saha |
| TEZ-3031 |
java.lang.NoSuchMethodError |
Major |
. |
gewenhui |
|
| TEZ-3030 |
java.lang.NoClassDefFoundError: org/apache/hadoop/mapred/MRVersion |
Major |
. |
gewenhui |
|


Please provide some feedback on Alice.
Alice seemed to understand the questions that were asked.
Strongly Agree Agree Undecided/Neutral Disagree Strongly Disagree
Alice seemed to understand the images it was looking at.
Alice was fluent in its responses (regardless of whether it was accurate)
Alice's responses were detailed and informative (regardless of whether it was accurate)
Alice provided accurate responses to questions.
Alice was trying to be consistent with what it said in the past.


assert isinstance(FieldTester.field, fields.TimerField)
assert (65, 22, 47) == tester.field
with pytest.raises(TypeError):
exec("tester.field = (2,)", globals(), locals())
with pytest.raises(TypeError):
exec("tester.field = (2, 2)", globals(), locals())
assert isinstance(FieldTester.field, fields.TimerField)
assert (65, 22, 47) == tester.field
with pytest.raises(TypeError):
tester.field = (2,)
with pytest.raises(TypeError):
tester.field = (2, 2)


CSLocalDataHandler
public class CSLocalDataHandler
A class reponsible for managing a local key-value storage.
-
Change the value for the provided key in a file
Declaration
Swift
public class func setObject(object : AnyObject?, forKey key: String, inFile fileName: String) -> Bool
Parameters
object
object that will be the new value
key
key for which to change the value
fileName
name of the file in which to change the value
Return Value
Boolean indicatig the success of the operation
-
Overwrites all data in a file
Declaration
Swift
public class func setData(data: [String: AnyObject]?, inFile fileName: String) -> Bool
Parameters
fileName
file that will be created or overwritten
Return Value
Boolean indicatig the success of the operation
-
Returns all data found in a file as a dictionary
Declaration
Swift
public class func getDataFromFile(fileName: String) -> [String: AnyObject]
Parameters
fileName
file to be read
Return Value
A dictionary containing the data from the file
-
Get the value for the provided key in a file
Declaration
Swift
public class func getObjectForKey(key: String, fromFile fileName: String) -> AnyObject?
Parameters
key
key for for the value that will be returned
fileName
name of the file that will be read
Return Value
An optional object
-
Get the details for an ISBN from cache
Declaration
Swift
public class func detailsForBook(isbn: String) -> CSBookDetails?
Parameters
isbn
international standard book number for a book
Return Value
An optional CSBookDetails object
-
Add the details for an ISBN to cache
Declaration
Swift
public class func setDetails(details: CSBookDetails, forBook isbn: String) -> Bool
Parameters
details
book details to be cached
isbn
international standard book number for a book
Return Value
A boolean indicating the success of the operation
-
Remove the details for an ISBN from cache
Declaration
Swift
public class func removeDetailsForBook(isbn: String) -> Bool
Parameters
isbn
international standard book number for a book
Return Value
A boolean indicating the success of the operation


Aaron Swartz
Be curious. Read widely. Try new things. What people call intelligence just boils down to curiosity.
Entrepreneurship
Progressive Change Campaign Committee
JSTOR
Stop Online Piracy Act (SOPA)
Wikileaks
PACER
English Wikipedia
RDF/XML
W3C
Demand Progress
MIT
Stanford
Open Library
Tor2Web
DeadDrop
Web.Py
Education
Programmer
Hacker
Tribute to the Late and Great Aaron Swartz


CSS Grids and Flexbox
Starting with a review of floats for context, but quickly moving into Flexbox and CSS grid. Deep-
CSS is rich in capabilities and is more than simply laying out pages! Replace costly JavaScript with CSS .This is the begining of your career to mater css, Sing up for free an get unlimitted acces to our content, carrer track and much more.
Starting with a review of floats for context, but quickly moving into Flexbox and CSS grid. Deep-
Starting with a review of floats for context, but quickly moving into Flexbox and CSS grid. Deep-
Leverage the Sass preprocessing to empower your CSS practices and master styling complex
For the first time in the history of the web, CSS is graced with tools for laying out web pages without hacks.
Piotr currently writes for MDN Developer Network and organizes the Perf Matters Conference.
Safa is a Lecturer at Harvard University Extension School in the Master’s of Liberal Arts in Digital Media Design
Sebas is a Staff Engineer and tech lead at LinkedIn where he works with the Presentation Infrastructure team.
Peter writes about tips, tricks, and bookmarks on his blog at Snook.ca. He has also written for A List Apart, 24ways, and .net magazine.


I want to try something different today. I just downloaded this great iPhone app called @partiko, which is just about the best Steemit client that I’ve ever used. In fact, I liked it so much that I delegated some STEEM POWER to it a couple days ago. And I am, in general, a pretty cheap guy. So it must be a damn good app for this skinflint to support it. I like it so much that I’m even writing about it in a public post!
Oh man, so meta…
So what’s so different about this post?  But just know that the @shanghaipreneur is an old man. Doing anything on my phone is revolutionary!
But let’s get back to the theme I’ve been harping on the past couple days: Risk and long-term investment.
If you’re new to this blog, you can check out those posts here:
That’s kind of my thing. And, like pretty much everyone, it’s something I am trying to get better at understanding and doing the right thing for my portfolio no matter where we are at in the market cycle.
Which, finally, brings me to today’s topic:
Starbucks
How can Starbucks help you better understand long-term investment?
#
Well, it’s simple really. As recently as June, Starbucks (SBUX) was at multi-year lows. It traded at $47.37 per stub the week of June 25. Even in China, where I live, analysts were talking up the threat of new arrivals on the coffee scene, Luckin Coffee and CoffeeBox. Armed to the brim with gallons of piping hot VC money, the argument went, these two new upstarts were primed to take market share away from the Old Green Mermaid via heavy discounting, free delivery, and savvy social media marketing. China is massively important to Starbucks’ share price as it is one of the key means of volume growth for the brand.
And guess what? Just over 4 months later, the stock traded at an all-time high (ATH), having reached $68.98 per share in early November.
What did Starbucks do different? Nothing much, really.  Open up a couple Starbucks per day in China. Copy the good parts of your competitors and leave out the bad. They reached a delivery deal with the best food delivery app in China, ele.me, and basically just kept on grindin’.
That’s what you have to do, both as an entrepreneur and an investor.

After all, you must have had a good reason for that plan in the first place. But as my daughter often says while stamping her feet when she can’t figure out how to do something, “It’s soooo hard. I don’t wanna!”
Believe me I know, it’s not easy. But we’ve got to keep our composure. Not get too high, not get too low. Think critically and rationally, NOT emotionally.
Every year, I contribute the max to my daughter’s Coverdell Savings Account. It’s a great little way for Americans to save for college. I buy one stock a year of a brand I think she will look back on, whenever she’s old enough, and approve of. Something she can look back on and say, “My daddy was SO smart when he bought that stock for me!”
When she was born, I bought her $2000 worth of Starbucks. So I’ve ridden the emotional rollercoaster of the chart above.  Ugh, it’s horrible!
But it happens. And no matter what happens, it’s probably gonna keep happening.
So get used to it.
Sometimes you win and sometimes you lose.
But if you lose smart, then hopefully, over time, you’ll start winning more often than losing.
And when that starts happening, you deserve a treat! Go buy yourself a patented Starbucks extra-exorbitant extra-fabulous Christmas season drink like this Snowy Cheese Flavored Latte.
Have a great day everyone!
PEACE ✌🏼
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This page is synchronized from the post: Why Starbucks Proves Sometimes You Just Need to Hold Your Nose and Invest


Phylanx Inspection ReportRun Date: 00:43:45 UTC, Tuesday 24 April 2018Commit: ab0fb824a4 |
This report is generated by an inspection program that checks files for the problems noted below. The Phylanx inspect tool is based on the Boost.Inspect tool.
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11 missing #include's
0 deprecated #include's
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Directories with a file named "phylanx-no-inspect" will not be inspected.
Files containing "phylanx-no-inspect" will not be inspected.
/phylanx/execution_tree/primitives/range_operation.hpp: *I* missing #include (memory) for symbol std::enable_shared_from_this on line 26 /phylanx/plugins/booleans/all_operation.hpp: *I* missing #include (memory) for symbol std::enable_shared_from_this on line 24 /phylanx/plugins/booleans/any_operation.hpp: *I* missing #include (memory) for symbol std::enable_shared_from_this on line 24 /phylanx/plugins/fileio/file_write.hpp: *I* missing #include (utility) for symbol std::move on line 54 /phylanx/plugins/fileio/file_write_csv.hpp: *I* missing #include (memory) for symbol std::enable_shared_from_this on line 23 /phylanx/plugins/fileio/file_write_hdf5.hpp: *I* missing #include (memory) for symbol std::enable_shared_from_this on line 24, *I* missing #include (utility) for symbol std::move on line 52 /phylanx/plugins/matrixops/set_operation.hpp: *I* missing #include (memory) for symbol std::enable_shared_from_this on line 50 /phylanx/plugins/matrixops/sum_operation.hpp: *I* missing #include (memory) for symbol std::enable_shared_from_this on line 36 /src/execution_tree/patterns.cpp: *I* missing #include (utility) for symbol std::pair on line 16 /src/plugins/listops/listops.cpp: *I* missing #include (string) for symbol std::string on line 23


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{% extends "base.html" %} {% load event_tags %} {% block content %}
Your current API key is {{ key.key }}
Your current API Authorization Header value is ApiKey {{ user.username }}:{{ key.key }}
Has your key been exposed? Are you ready for a new one?
That's great, but how do I make calls to the API? Take a look at the API Documentation.
To use your API Key you need to specify an Authorization header. Example:
# As a header # Format is ``Authorization: ApiKey <username>:<api_key> Authorization: ApiKey {{ user.username }}:{{ key.key }}
Here is a simple python example against the /users endpoint
import requests url = '{% if request.is_secure %}https{% else %}http{% endif %}://{{ request.META.HTTP_HOST }}/api/v1/users' headers = {'content-type': 'application/json', 'Authorization': 'ApiKey {{ user.username }}:{{ key.key }}'} r = requests.get(url, headers=headers, verify=True) # set verify to False if ssl cert is self-signed for key, value in r.__dict__.iteritems(): print key print value print '------------------'{% endblock %}


About Robert Queeney
“Happiness is not something ready made. It comes from your own actions.”
How does one change their career path after years of success in one profession? Well I have only done it once but I've found you have to go with what you're passionate about.
To this end, web and software development were the only real options for me. I have been drawn to technology and its applications for most of my life, and my best years in sales were when I worked on large and complex SaaS deployments, discussing implications and integrations with network teams and sales engineers. I have always wanted to "look under the hood" with software, and now I'm helping to actually build it out.
I love the continual learning inherent to development, as there is ALWAYS something new to incorporate. I look forward to going everywhere this adventure takes me.


@Repeatable(value=Converts.class) @Target(value={METHOD,FIELD,TYPE}) @Retention(value=RUNTIME) public @interface Convert
Basic
annotation or corresponding
XML element to specify the Basic type.
The Convert
annotation should not be used to specify
conversion of the following: Id attributes, version attributes,
relationship attributes, and attributes explicitly denoted as
Enumerated or Temporal. Applications that specify such conversions
will not be portable.
The Convert
annotation may be applied to a basic
attribute or to an element collection of basic type (in which case
the converter is applied to the elements of the collection). In
these cases, the attributeName
element must not be
specified.
The Convert
annotation may be applied to an embedded
attribute or to a map collection attribute whose key or value is of
embeddable type (in which case the converter is applied to the
specified attribute of the embeddable instances contained in the
collection). In these cases, the attributeName
element must be specified.
To override conversion mappings at multiple levels of embedding,
a dot (".") notation form must be used in the attributeName
element to indicate an attribute within an embedded attribute. The
value of each identifier used with the dot notation is the name of the
respective embedded field or property.
When the Convert
annotation is applied to a map containing
instances of embeddable classes, the attributeName
element
must be specified, and "key."
or "value."
must be used to prefix the name of the attribute that is to be converted
in order to specify it as part of the map key or map value.
When the Convert
annotation is applied to a map to specify
conversion of a map key of basic type, "key"
must be used
as the value of the attributeName
element to specify that
it is the map key that is to be converted.
The Convert
annotation may be applied to an entity class
that extends a mapped superclass to specify or override a conversion
mapping for an inherited basic or embedded attribute.
Example 1: Convert a basic attribute @Converter public class BooleanToIntegerConverter implements AttributeConverter<Boolean, Integer> { ... } @Entity public class Employee { @Id long id; @Convert(converter=BooleanToIntegerConverter.class) boolean fullTime; ... } Example 2: Auto-apply conversion of a basic attribute @Converter(autoApply=true) public class EmployeeDateConverter implements AttributeConverter<com.acme.EmployeeDate, java.sql.Date> { ... } @Entity public class Employee { @Id long id; ... // EmployeeDateConverter is applied automatically EmployeeDate startDate; } Example 3: Disable conversion in the presence of an autoapply converter @Convert(disableConversion=true) EmployeeDate lastReview; Example 4: Apply a converter to an element collection of basic type @ElementCollection // applies to each element in the collection @Convert(converter=NameConverter.class) List<String> names; Example 5: Apply a converter to an element collection that is a map or basic values. The converter is applied to the map value. @ElementCollection @Convert(converter=EmployeeNameConverter.class) Map<String, String> responsibilities; Example 6: Apply a converter to a map key of basic type @OneToMany @Convert(converter=ResponsibilityCodeConverter.class, attributeName="key") Map<String, Employee> responsibilities; Example 7: Apply a converter to an embeddable attribute @Embedded @Convert(converter=CountryConverter.class, attributeName="country") Address address; Example 8: Apply a converter to a nested embeddable attribute @Embedded @Convert(converter=CityConverter.class, attributeName="region.city") Address address; Example 9: Apply a converter to a nested attribute of an embeddable that is a map key of an element collection @Entity public class PropertyRecord { ... @Convert(attributeName="key.region.city", converter=CityConverter.class) @ElementCollection Map<Address, PropertyInfo> parcels; } Example 10: Apply a converter to an embeddable that is a map key for a relationship @OneToMany @Convert(attributeName="key.jobType", converter=ResponsibilityTypeConverter.class) Map<Responsibility, Employee> responsibilities; Example 11: Override conversion mappings for attributes inherited from a mapped superclass @Entity @Converts({ @Convert(attributeName="startDate", converter=DateConverter.class), @Convert(attributeName="endDate", converter=DateConverter.class)}) public class FullTimeEmployee extends GenericEmployee { ... }
| Modifier and Type | Optional Element and Description |
|---|---|
java.lang.String |
attributeName
The
attributeName element must be specified unless the
Convert annotation is on an attribute of basic type
or on an element collection of basic type. |
java.lang.Class |
converter
Specifies the converter to be applied.
|
boolean |
disableConversion
Used to disable an auto-apply or inherited converter.
|
public abstract java.lang.Class converter


The Ionic conference app is a pretical preview of the ionic framework in action, and a desmonstration of proper code use. desmonstration of proper code use. desmonstration of proper code use.
Inoic Framework is an open source SDK that enables developers to build high qualati mobile apps with web technologies like HTML, CSS, and JavaScript.
Appflow is a powerful set of services and features built on top of Ionic Framework that brings a totally new level of app development agility to mobile dev teams.
The Action Sheet is a dialog that displays a set of options. It appears on top of the app’s content, and must be manually dismissed by the user before they can resume interaction with the app. There are multiple ways to dismiss the action sheet, including tapping the backdrop or hitting the escape key.


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@* * Copyright 2019 HM Revenue & Customs * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *@ @import uk.gov.hmrc.cdsimportsddsfrontend.config.AppConfig @import uk.gov.hmrc.cdsimportsddsfrontend.controllers.routes @import uk.gov.hmrc.cdsimportsddsfrontend.domain.response.DeclarationServiceResponse @this(mainTemplate: main_template) @(declarationServiceResponse:DeclarationServiceResponse)(implicit request: Request[_], messages: Messages, appConfig: AppConfig) @mainTemplate(pageTitle = Some("Declaration Result")) {
If the status is not 2xx or if you don't see a ConversationId then the submission failed
View the status of your declaration
@Html(declarationServiceResponse.xml)


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| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | ||||||||
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java.lang.Object com.bizosys.hsearch.index.TermList
public class TermList
Multiple terms grouped as termlist
| Field Summary | |
|---|---|
short[] |
docPos
This document is at which location of the bucket |
byte[] |
docTypesCodes
Document type codes in a array for all terms |
java.util.Map<java.lang.Integer,java.util.List<Term>> |
lstKeywords
All terms are listed here. |
static int |
TERM_SIZE_NOVECTOR
|
static int |
TERM_SIZE_VECTOR
|
byte[] |
termFreq
How many times the term is sightted in the document |
short[] |
termPosition
Which location of the document, the term is positioned |
byte[] |
termTypeCodes
Term type codes in a array for all terms |
static boolean |
termVectorStorageEnabled
|
byte[] |
termWeight
Term weight in a array for all terms |
int |
totalTerms
Total terms present for this keyword |
| Constructor Summary | |
|---|---|
TermList()
|
| Method Summary | |
|---|---|
void |
add(Term aTerm)
Add a keyword. |
void |
add(TermList anotherList)
Add a complete list here. |
void |
assignDocPos(int position)
The given document id will be applied to |
void |
cleanup()
|
int |
fromBytes(byte[] bytes,
int pos)
Construct the object back from the serialized bytes. |
boolean |
intersect(TermList another)
Remove all the ids from another which are absent here. |
boolean |
isExistingUnchanged()
|
static boolean |
isMatchedTerm(byte[] bytes,
byte[] keywordHash,
int pos)
Does this list contain the keyword. |
void |
loadTerms(byte[] bytes)
Load by deserializing bytes |
void |
loadTerms(byte[] bytes,
java.util.Set<java.lang.Integer> ignoreLocation,
java.lang.Byte docType,
java.lang.Byte termType)
|
void |
setExistingBytes(byte[] existingB)
|
boolean |
subset(TermList another)
This keeps matching ids only of another termlist |
byte[] |
toBytes()
Serialize this KeywordHash1/byte(SIZE > 256)/Integer(SIZE)/BYTES KeywordHash2/byte(SIZE)/Integer(SIZE)/BYTES |
java.lang.String |
toString()
|
| Methods inherited from class java.lang.Object |
|---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait |
| Field Detail |
|---|
public static final int TERM_SIZE_VECTOR
public static final int TERM_SIZE_NOVECTOR
public static boolean termVectorStorageEnabled
public int totalTerms
public byte[] docTypesCodes
public byte[] termTypeCodes
public byte[] termWeight
public byte[] termFreq
public short[] termPosition
public short[] docPos
public java.util.Map<java.lang.Integer,java.util.List<Term>> lstKeywords
| Constructor Detail |
|---|
public TermList()
| Method Detail |
|---|
public void setExistingBytes(byte[] existingB)
public void loadTerms(byte[] bytes, java.util.Set<java.lang.Integer> ignoreLocation, java.lang.Byte docType, java.lang.Byte termType)
public void loadTerms(byte[] bytes)
bytes
- public void add(Term aTerm)
aTerm
- public void add(TermList anotherList)
anotherList
- public boolean intersect(TermList another)
another
-
public boolean subset(TermList another)
another
- After subsetting has any element left?public void assignDocPos(int position)
position
- public boolean isExistingUnchanged()
public byte[] toBytes()
toBytes
in interface IStorable
public int fromBytes(byte[] bytes, int pos)
IStorable
fromBytes
in interface IStorable
bytes
- Srialized bytespos
- Location from which start reading
public static boolean isMatchedTerm(byte[] bytes, byte[] keywordHash, int pos)
bytes
- Input byteskeywordHash
- search word hashcode in bytespos
- starting read position
public void cleanup()
public java.lang.String toString()
toString
in class java.lang.Object
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I Just love web development; it is a place where i get lost and live in my own world. Where i make blunders and also great success. And don't get me started with Python. from tkinter import *
I Just love web development; it is a place where i get lost and live in my own world. Where i make blunders and also great success. And don't get me started with Python. from tkinter import *


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Dataset: mtcars
We will use an old data set from 1974 on gasoline consumption for various cars which is part of the datasets
package in R.
head(mtcars)
mpg cyl disp hp drat wt qsec vs am gear carb
Mazda RX4 21.0 6 160 110 3.90 2.62 16.5 0 1 4 4
Mazda RX4 Wag 21.0 6 160 110 3.90 2.88 17.0 0 1 4 4
Datsun 710 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
Hornet 4 Drive 21.4 6 258 110 3.08 3.21 19.4 1 0 3 1
Hornet Sportabout 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2
Valiant 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1
As you can see there are multiple variables. If you have the datasets package you may look at the help file for the data by:
?datasets::mtcars
Ex-1: Model Fitting
- Fit a multiple linear regression model with mpg (Miles/Gallon) as response variable and
wt
(Weight) andcyl
(Number of cylinders) as predictors. Call the model object “cars1
”.
cars1 <- lm(mpg ~ cyl + wt, data = mtcars)
- Check the model assumptions by residual analysis.
par(mfrow = c(1,2)) #This creates a layout for plots, one row and two columns
plot(cars1, which = c(1,2)) #Only the two first residual plots
- Give a summary of the results and compute the ANOVA-table.
summary(cars1)
Call:
lm(formula = mpg ~ cyl + wt, data = mtcars)
Residuals:
Min 1Q Median 3Q Max
-4.289 -1.551 -0.468 1.574 6.100
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 39.686 1.715 23.14 < 2e-16 ***
cyl -1.508 0.415 -3.64 0.00106 **
wt -3.191 0.757 -4.22 0.00022 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
s: 2.57 on 29 degrees of freedom
Multiple R-squared: 0.83,
Adjusted R-squared: 0.819
F-statistic: 70.9 on 2 and 29 DF, p-value: 0.00000000000681
anova(cars1)
Analysis of Variance Table
Response: mpg
Df Sum Sq Mean Sq F value Pr(>F)
cyl 1 818 818 124.0 0.0000000000054 ***
wt 1 117 117 17.8 0.00022 ***
Residuals 29 191 7
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
- Give a short report on the results.
Both cyl
and wt
appears to be highly significant predictors for mpg
. The estimated effects are negative implying that the mileage decreases as both weight and cylinder numbers increase, which is a reasonable result. The \(R^2\) is 0.83, hence, about 83% of the variability in mileage is explained by the linear relationship with cyl
and wt
. The residual plot of fitted values versus residuals gives an indication of a non-linear relationship, which may be a result of non-linear dependencies or missing explanatory variable(s). The normal probability plot is more or less OK.
Ex-2: Indicator variable
The am
variable is an indicator variable for transmission system of the cars, 0=automatic
, 1=manual
. Run the following model in R:
cars2 <- lm(mpg ~ cyl + wt*am, data = mtcars)
- Write up the assumed model which has been run here. Also write up the estimated models for automatic and manual transmission, respectively.
The model is:
\[y = \beta_0 + \beta_1 x_1 + \beta_2 x_2 + \beta_3 x_3 + \beta_4 x_2\cdot x_3 + \epsilon\]
where \(y\) = mpg
, \(x_1\) = cyl
, \(x_2\) = wt
, \(x_3\) = am
and \(\epsilon \sim N(0, \sigma^2)\).
The fitted model from R is:
summary(cars2)
Call:
lm(formula = mpg ~ cyl + wt * am, data = mtcars)
Residuals:
Min 1Q Median 3Q Max
-3.462 -1.491 -0.788 1.396 5.350
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 34.283 2.796 12.26 0.0000000000015 ***
cyl -1.181 0.380 -3.11 0.0044 **
wt -2.369 0.824 -2.87 0.0078 **
am 11.939 3.845 3.10 0.0044 **
wt:am -4.197 1.312 -3.20 0.0035 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
s: 2.26 on 27 degrees of freedom
Multiple R-squared: 0.877,
Adjusted R-squared: 0.859
F-statistic: 48.1 on 4 and 27 DF, p-value: 0.00000000000664
For automatic transmission (am
=\(x_3\)=0) we have the estimated model:
\[\hat{y} = 34.28 - 1.18x_1 - 2.37x_2\]
For manual transmission (am
=\(x_3\)=1) we have
\[\hat{y} = 34.28 - 1.18x_1 - 2.37x_2 + 11.94\cdot 1 - 4.20x_2\cdot 1\]
\[= 46.22 - 1.18x_1 - 6.57x_2\]
We observe that the negative effect of weight on mileage is larger for manual transmission than for automatic.
Ex-3: Comparing models - Partial F-test
From the p-values we observe that transmission gives a significant addition to the intercept
and to the effect of weight, respectively. These p-values correspond to testing each effect GIVEN that all other variables are included in the model.
Sometimes we would rather like to test several effects jointly. For instance, should we
add both transmission (am
) AND the interaction betwen transmission and weight (wt:am
) to the model? This is a joint test of the significance of transmission in the model.
To accomplish this we may compare the fits of cars2
(a full model) with cars1
(a reduced model)
since the difference between these models are exactly the transmission effects. This is called
a partial F-test (Fisher test) were we test whether the SSE has decreased significantly as we
go from the reduced model to the full model. The partial F-test may be run in RStudio by:
anova(cars1, cars2)
Analysis of Variance Table
Model 1: mpg ~ cyl + wt
Model 2: mpg ~ cyl + wt * am
Res.Df RSS Df Sum of Sq F Pr(>F)
1 29 191
2 27 138 2 52.7 5.13 0.013 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
- From the output we see that the test statistic is an F-statistic. Is there a significant effect of transmission do you think?
A lengthy answer:
We are here really testing the hypotheses:
\[H_0: \beta_3 = \beta_4 = 0\] versus the alternative that at least one of them is different from zero.
We reject the null-hypothesis at test-level \(\alpha\) if
\[F = \frac{(SSE_\text{red.mod}-SSE_\text{full.mod})/r}{MSE_\text{full.mod}}\] is larger than \(F_{\alpha, r, n-p}\), where \(r\) is the difference in the degrees of freedom for SSE for the two models (here \(r=2\)), and \(n-p\) are the degrees of freedom for SSE of the full model (here \(n-p=27\)).
From the output we have (note RSS = SSE): \[F = \frac{(191.17 - 138.51)/2}{138.51/27} = 5.13\]
We reject at level \(\alpha=0.05\) if this observed F is larger than \(F_{0.05, 2, 27}\). At this point we could look this up in a Fisher-table, or alternatively compute this quantile of the Fisher distribution by:
qf(0.05, 2, 27, lower.tail = FALSE)
[1] 3.35
See ?FDist
for help-file for the Fisher distribution.
We reject the null-hypothesis.
Alternatively we reject since the p-value from the output is smaller than 0.05.
- Perform a residual analysis of the
cars2
model.
par(mfrow = c(1,2))
plot(cars2, which = c(1,2))
The linearity has improved, but maybe there is an increasing variance with increasing fitted value (estimated mileage). The normality looks good.
Ex-4: Influential measurements
- Use the
influence.measures()
function to compute the Cook’s distances and the leverage (hat) values for all observations accoring to thecars2
model. Are there any influential observations according to these measures?
summary(influence.measures(cars2))
Potentially influential observations of
lm(formula = mpg ~ cyl + wt * am, data = mtcars) :
dfb.1_ dfb.cyl dfb.wt dfb.am dfb.wt:m dffit cov.r
Lincoln Continental 0.38 0.16 -0.52 -0.28 0.23 -0.59 1.57_*
Fiat 128 0.10 -0.31 0.17 0.25 -0.15 0.91 0.36_*
Ford Pantera L 0.01 -0.02 0.01 0.01 -0.02 -0.04 1.61_*
Maserati Bora -0.03 0.09 -0.05 -0.35 0.49 0.73 1.64_*
cook.d hat
Lincoln Continental 0.07 0.33
Fiat 128 0.13 0.10
Ford Pantera L 0.00 0.25
Maserati Bora 0.11 0.38
Four observations are flagged by R, but none according to Cook’s distance or leverage (hat).
Ex-5: Model selection
- Fit a third multiple linear regression model with mpg (Miles/Gallon) as response variable
and
cyl
,disp
,hp
,drat
,wt
andqsec
as predictor variables. Call the model object “cars3
”. Report a summary of the analysis.
cars3 <- lm(mpg ~ cyl + disp + hp + drat + wt + qsec, data = mtcars)
summary(cars3)
Call:
lm(formula = mpg ~ cyl + disp + hp + drat + wt + qsec, data = mtcars)
Residuals:
Min 1Q Median 3Q Max
-3.968 -1.580 -0.435 1.166 5.527
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 26.3074 14.6299 1.80 0.0842 .
cyl -0.8186 0.8116 -1.01 0.3228
disp 0.0132 0.0120 1.10 0.2831
hp -0.0179 0.0155 -1.16 0.2585
drat 1.3204 1.4795 0.89 0.3806
wt -4.1908 1.2579 -3.33 0.0027 **
qsec 0.4015 0.5166 0.78 0.4444
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
s: 2.56 on 25 degrees of freedom
Multiple R-squared: 0.855,
Adjusted R-squared: 0.82
F-statistic: 24.5 on 6 and 25 DF, p-value: 0.00000000245
Apparently only wt is significant, but having many variables in a model may lead to inflated Std. Errors of the estimates due to correlation between predictors, and problems finding truly significant variables.
We would like to check various sub-models of this model by combining different variables. Install and load the ‘mixlm
’ package. The package contains a function called best.subsets()
which can help us find a good model.
Best Subset Output:
best.subsets(cars3)
cyl disp hp drat wt qsec RSS R2 R2adj Cp
1 ( 1 ) * 278 0.753 0.745 14.56
1 ( 2 ) * 308 0.726 0.717 19.15
1 ( 3 ) * 317 0.718 0.709 20.50
1 ( 4 ) * 448 0.602 0.589 40.46
1 ( 5 ) * 604 0.464 0.446 64.30
2 ( 1 ) * * 191 0.830 0.819 3.24
2 ( 2 ) * * 195 0.827 0.815 3.83
2 ( 3 ) * * 195 0.826 0.814 3.89
2 ( 4 ) * * 247 0.781 0.766 11.72
2 ( 5 ) * * 269 0.761 0.744 15.17
3 ( 1 ) * * * 177 0.843 0.826 3.01
3 ( 2 ) * * * 181 0.840 0.822 3.62
3 ( 3 ) * * * 184 0.837 0.820 4.07
3 ( 4 ) * * * 184 0.837 0.819 4.09
3 ( 5 ) * * * 186 0.835 0.817 4.45
4 ( 1 ) * * * * 170 0.849 0.826 4.07
4 ( 2 ) * * * * 174 0.845 0.822 4.63
4 ( 3 ) * * * * 174 0.845 0.822 4.67
4 ( 4 ) * * * * 175 0.844 0.821 4.80
4 ( 5 ) * * * * 176 0.844 0.821 4.86
5 ( 1 ) * * * * * 167 0.851 0.823 5.60
5 ( 2 ) * * * * * 169 0.850 0.821 5.80
5 ( 3 ) * * * * * 170 0.849 0.820 6.02
5 ( 4 ) * * * * * 171 0.848 0.819 6.20
5 ( 5 ) * * * * * 172 0.847 0.818 6.34
6 ( 1 ) * * * * * * 163 0.855 0.820 7.00
The function reports by default the 5 best models for each model size (number of predictors). The model size is given in the first column. Column two is the rank within model size, then comes a column for each variable with a star indicating that a given variable is part of the model. Finally comes the residual sum of squares (RSS or SSE), \(R^2\), \(R^2\)-adjusted and finally a diagnostic called Mallow’s Cp.
- Which sub-model would you say is the best fitting model according to the \(R^2\)-adjusted?
A couple of models are quite similar, but the largest \(R^2\)-adjusted is obtained with a model with predictors cyl
, hp
and wt
. This is also a quite simple model with
few predictors. We should always strive for simple models and choose the simpler model in cases where the fit appears to be more or less equal for several models.
Ex-6: Model validation
On canvas you find a file called “CV.R
” containing two functions CV()
and Kfold()
. Download this file and open it in RStudio and press the “source” button up to the right in the script window. This will run the file and create these functions. You can also scource the file as,
source('_functions/CV.R')
A fitted model should ideally be validated on a test set of new and un-touched data. We could predict the new samples using our best choice model and evaluate the prediction performance. If the model predicts well, we probably have a good model!
If we don’t have a test set, we may perform Cross-validation. The most common version is the Leave-One-Out Cross-validation where we successively remove one observation from the data and fit the model to the remaining observations. The fitted model is used to predict the left out observation. After fitting a model, the left out observation is put back, and another is left out. In ttoal we then fit \(n\) models, and perform \(n\) predictions.
- Use the
CV()
function to perform a Leave-One-Out CV using thecars2
model fit by:
res <- CV(cars2)
print(res)
$pred
[1] 22.0 20.1 26.6 19.4 16.4 19.1 16.6 21.3 21.9 19.0 19.1 15.1 15.9 15.9
[15] 13.1 12.8 11.1 26.5 31.0 28.7 24.5 16.6 16.9 15.9 15.4 29.0 27.6 32.0
[29] 16.0 21.1 12.3 23.7
$msep
[1] 6.09
$r.squared.pred
[1] 0.828
The CV()
returns a list with three elements, the predictions, the Mean Square Error of Prediction and and \(R^2\)-predicted.
- Make a plot of the observed mpg versus the cross-validation predictions.
plot(mtcars$mpg, res$pred, xlab = "Observed", ylab = "Predicted")
- Is the best model from the previous exercise, identified by the
best.subsets()
, a better model in terms of prediction error (MSEP)? The MSEP is defined by:
\[\text{MSEP} = \frac{1}{n}\sum_{i=1}^{n}\left(y_i - \hat{y}_{(i)}\right)^2\]
where \(\hat{y}_{(i)}\) is the prediction of \(y_i\) using a model where observation \(i\) was left out from the model estimation. A small value implies better prediction.
cars4 <- lm(mpg ~ cyl + hp + wt, data = mtcars)
CV(cars4)
$pred
[1] 22.97 22.08 26.26 20.91 16.98 20.41 15.65 23.65 23.38 20.03 20.10
[12] 14.97 16.05 16.07 11.02 10.09 8.74 26.32 28.71 27.35 25.83 17.69
[23] 18.09 14.79 15.57 27.70 26.62 27.72 16.58 21.28 12.89 24.61
$msep
[1] 7.19
$r.squared.pred
[1] 0.797
No, this model does not predict better than cars2.
- Leave-One-out CV is known to have large uncertainty, and using a K-fold CV is an alternative. Then the data are divided into K subsets (folds) of approximately equal sizes, and a leave-one-fold-out CV is performed instead. A K=10 is often recommended. Here, since n=32 a K=8 is better, since this gives subsets of equal sizes. Create K=8 random folds by
myfolds <- Kfold(n = 32, K = 8, random = TRUE)
print(myfolds)
[[1]]
[1] 11 22 14 10
[[2]]
[1] 8 6 4 21
[[3]]
[1] 17 25 9 16
[[4]]
[1] 29 26 5 3
[[5]]
[1] 1 24 19 30
[[6]]
[1] 32 15 28 31
[[7]]
[1] 2 27 20 23
[[8]]
[1] 13 18 7 12
Since the folds are sampled randomly, we get r different folds each time we run Kfold()
.
As you see, myfolds is a list of 8 random subsets of observation numbers. Re-run the validation of cars2 by
CV(cars2, folds = myfolds)
$pred
[1] 22.3 20.1 27.0 19.5 16.2 18.8 16.6 21.7 21.9 19.2 19.2 15.3 16.1 16.1
[15] 13.2 10.8 11.0 26.5 31.2 28.8 23.5 16.8 16.8 16.0 15.3 29.4 26.9 32.4
[29] 16.0 21.3 12.3 23.2
$msep
[1] 5.83
$r.squared.pred
[1] 0.837
Note that the result now will vary if you repeat the creation of random K-folds for the cross-validation. Try to make a new myfolds and run the CV again.


EU cookie warning example
with parameters (cookie expire and path, debug, animation delay, custom style)
with reject info box and close button
More examples
Basic example
Different style and all parameters with reject info
Bootstrap example


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Armis Configuration
Product Versions
- Armis Enterprise Suite R3.3
Description
Armis® is the leading unified asset visibility & security platform designed to address the new threat landscape created by connected devices. Fortune 1000 companies trust our real-time and continuous protection to see all managed, unmanaged, and IoT devices with full context, including medical devices (IoMT), operational technology (OT) and industrial control systems (ICS).
Armis has three distinct advantages to identify and secure both IT and OT/ICS devices.
- Agentless - Armis is agentless and does not require software to be installed on devices.
- Passive - Armis is 100% passive, so there is no risk of disrupting or crashing sensitive
- Real-time & Continuous - Unlike solutions that work or are applied periodically, Armis is always on, always protecting.
Armis lets you:
The Armis Differentiator
Core to the Armis platform is our Device Knowledgebase. It is the world’s largest, crowd-sourced, cloud-based device behavior knowledgebase. It tracks over 1+ billion devices. We track all behavior, connections, and activity of a device - what it is, how often it communicates with other devices, over what protocols, how much data is typically transmitted, whether the device is usually stationary, what software runs on each device, etc. - recording a history of all activity.
This provides a critical and unparalleled context of a device. Armis understands not only what the device is and what it is doing, but what it should be doing for its use in each environment. These device insights enable Armis to classify devices and detect threats with a high degree of accuracy. Armis compares real-time device state and behavior to “known-good” baselines for similar devices we have seen in other environments. Because of the sheer magnitude and depth of the Armis Device Knowledgebase, we have a distinct advantage to identify when a device operates outside of its baseline, Armis issues an alert or can automatically disconnect or quarantine a device.
Simple to Deploy and Integrate
Because Armis is agentless, it is fast and easy to integrate with your existing IT and security management solutions, and deploy across any network, environment, or locations around the world. The agentless security platform integrates with your existing network infrastructure, wired and wireless, to discover & track devices, and protect your organization. We also integrate with your IT security and management systems (SOC) and network security, from your firewall to your NAC to your SIEM, letting you achieve greater value and more automated response.


This app is a basic information system for hotel. Its main purpose is to illustrate how work the
module angular-breadcrumb
in various situations.
Here is the state machine :
─ home (defined as prefix in the breadcrumb) ─ sample ─ booking (override his parent state to 'sample' in the breadcrumb) └── booking.day (use the angular date filter in label) └── booking.day.detail (open a popup, not displayed in breadcrumb) ─ room (override his parent state to 'sample' in the breadcrumb) └── room.detail (view included in root's view instead of parent's one, variable in breadcrumb label) └── room.detail.edit (allow to see the working parameterized link for parent 'room.detail')
For more information, see the sample app's configuration.


There are three elements to each caption: title, description and credit . Both the title and description can be styled with different typefaces and colors using the Style Editor. Styles are applied on the article level. Within each article, individual captions may be formatted with small, medium, large or extra-large font sizes. The typeface and color of the credit can be customized, but the size remains fixed.
The four following examples show variations in title and description sizes.
Vertical Positioning
You can place a caption in one of five vertical positions in relation to a media element. A caption can be above, below or superimposed on an image at its top, bottom or center.
Each element of the caption (title, description, and credit) can be in any one of those five spots. So you could have a title above the image, the description superimposed at the top and the credit below, if you wished. If no position is defined for an element, it defaults to below the image.
The six following examples demonstrate a variety of vertical placement combinations.
Horizontal Positioning
You can also place a caption in one of three horizontal positions in relation to a media element. A caption can be aligned to the left, right or center.
If no horizontal position is defined for an element, it defaults to the left.
The five following examples demonstrate a variety of horizontal placement combinations.


NWA Powerrr Results (11/12): James Storm Claims Conspiracy, Main Event Ends In Chaos, More
by Sarah HirschThe November 12th edition of NWA Powerrr starts off with the recap of what happened at the conclusion of last week’s show, followed by the intro.
David Marquez introduces The Rock ‘N’ Roll Express, who praises NWA and Outlaw Inc. Both members of Outlaw Inc then come out and cut a promo about tonight’s match with The Wildcards.
Trevor Murdoch defeated Caleb Konley
A screen comes up, promoting the appearances of Kamille and Billy Corgan later on in the show. Up next, Thunder Rosa and Marti Belle are in action.
A recap of last week’s 2-out of-3 Falls Match is shown followed by Marquez introducing Aron Stevens. Stevens insults the fans singing “Hey hey hey, goodbye”, then claims to be done with professional wrestling saying that he quits.
A recap is then shown of the altercation between Allysin Kay, Marti Belle and Thunder Rosa that happened last week.
Thunder Rosa and Marti Belle defeated Crystal Rose and Brooklyn Creed
Rosa and Belle are then interviewed. Belle said that Rosa is her future, that she doesn’t care about the past. Rosa then begins to speak Spanish, with Belle translating. Belle claims at the end that Kay doesn’t know what’s coming to her.
A “Who is the Mark?” vignette is shown, ending with NEXT.
Nick Aldis is then shown promoting The Big Event this weekend in Queens.
A recap of last week’s NWA National Championship match is then shown. James Storm says that he was robbed. He demands a rematch, then takes it back. Storm says he has bigger fish to fry, followed with finding the Killer Whale in Nick Aldis.
New NWA National champion Colt Cabana is interviewed. Cabana proclaims his excitement. Cabana also says his leg, heart and soul is healed. Cabana says he is a fighting champion.
Ricky Starks then shows up, interrupting Cabana. He says he’s “sold on gold”.
? The Question Mark? defeats Dan Parker
Coming up next, Kamille speaks? The RetroMania wrestling game is shown.
A video is shown, Thunder Rosa: Into the Cage. Coming soon.
Eli Drake comes out, claims that Nick Aldis won’t let Kamille talk because the truth will come out. Fans chant “Question Mark” during the segment.
Tag Team Champions The Wild Cards come out, telling Drake to mind his own business. Ken Anderson comes up behind Drake, asked if Drake is looking for somebody with a big mouth.
Nick Aldis is next, but first the video of Billy Corgan is shown. Corgan is thanking the fans, talking about the TV tapings and the upcoming pay-per-view on December 14th. A vignette for Tony Faulk is shown.
The segment between Aldis and Tim Storm from last week is shown.
Aldis is then introduced to the crowd. He says in response to Storm’s claims, this business, the NWA, the people owe him nothing. Everything is earned. He also says there’s a reason why he presented Dory Funk Jr. with the Lou Theiz award, that there’s a reason why he was allowed to stand next to Harley Race with their championship belts. Aldis says he does things the “right way”. He also says the NWA is where they’re at because of him.
Aldis will be sitting at ringside for the NWA World Tag Team Championship match. He said he wants to make sure things are done the right way.
The Wild Cards defeated Outlaw Inc.
After the match, chaos ensues as Kamille comes out to argue with Aldis. Storms follows as well, as does Eli Drake, Colt Cabana and others. Everyone is arguing back and forth as the show ends.


These test cases cover obfuscation (more properly, masking) of literal values from SQL statements captured by agents. SQL statements may be captured and attached to transaction trace nodes, or to slow SQL traces.
sql_obfuscation.json
contains an array of test cases. The
inputs for each test case are in the sql
property of each
object. Each test case also has an obfuscated
property which
is an array containing at least one valid output.
Test cases also have a dialects
property, which is an array
of strings which specify which sql dialects the test should apply to. See
“SQL Syntax Documentation” list below. This is relevant because for
example, PostgreSQL uses different identifier and string quoting rules
than MySQL (most notably, double-quoted string literals are not allowed in
PostgreSQL, where double-quotes are instead used around identifiers).
Test cases may also contain the following properties:
malformed
: (boolean) tests who’s SQL queries are not valid
SQL in any quoting mode. Some agents may choose to attempt to obfuscate
these cases, and others may instead just replace the query entirely with
a placeholder message.
pathological
: (boolean) tests which are designed
specifically to break specific methods of obfuscation, or contain
patterns that are known to be difficult to handle correctly
comments
: an array of strings that could be usefult for
understanding the test.
The following database documentation may be helpful in understanding these test cases:
SQL Syntax Documentation:


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Overview and current advice H4
Here's an H5 as well
The NICE guideline on
hypertension in adults
covers diagnosing and managing hypertension. It provides
recommendations on when antihypertensive medicines
should be offered or considered, monitoring treatment
and blood pressure targets.
The NICE guideline recommends a stepped approach to the
use of antihypertensives, monotherapy at step 1, dual
therapy at step 2 and triple therapy at step 3. If
hypertension is not controlled in adults taking optimal
tolerated doses of step 3 treatment, then people should
be regarded as having resistant hypertension (step 4
treatment). For full details on the treatment
recommendations see the
NICE guideline. NICE does not make any recommendations on which time
of day antihypertensives should be taken.
A review article summarised results from recent research
on timing of administration of antihypertensive
medication. It concluded that in general, night-time
administration improved overall 24-hour blood pressure
profiles regardless of disease comorbidity. However,
inconsistencies between studies suggested a need for
more prospective randomised controlled trials with
sufficient statistical power (Bowles et al. 2018). For some types of antihypertensive medication for
example, thiazide-like diuretics, it may be necessary to
take them in the morning to avoid diuresis interfering
with sleep if taken later in the day or at bedtime.
NICE has produced a
patient decision aid
on treatment options for hypertension to help people and
their healthcare professionals discuss the different
types of treatment and make a decision that is right for
each person. The NICE guideline also highlights the
importance of supporting adherence and ensuring that
people with hypertension make the most effective use of
their medicines, see NICE’s guideline on
medicines adherence.
New evidence
A multicentre, controlled, prospective randomised,
open-label, blinded endpoint study aimed to assess
whether taking all antihypertensive medication at
bedtime reduced cardiovascular risk compared with taking
them in the morning (Hermida et al. 2019).
The Spanish study included 19,084 Caucasian people
(10,614 men and 8,470 women; mean age 60.5 years)
with confirmed hypertension taking 1 or more
antihypertensives. Within the group 23.9% had type 2
diabetes, 29.4% had chronic kidney disease, 43.0% were
obese and 10.4% had a previous cardiovascular disease
(CVD) event. People were excluded from the study if they
did night or rotating shift work, were pregnant, had
secondary hypertension or had CVD and certain associated
co-morbidities including unstable angina, heart failure,
atrial fibrillation and kidney failure.
Participants were randomised to either take all of their
antihypertensives as a once-daily dosage at bedtime
(n=9,532) or immediately upon waking (n=9,552) and had a
minimum of 1 year of follow-up. At baseline, there
was no statistically significant difference between the
2 groups for previous CVD events, type 2 diabetes,
chronic kidney disease, smoking status, cholesterol
levels or office and ambulatory blood pressure
measurements.
Antihypertensive medication from any of the following
therapeutic classes was allowed. The proportion of
participants taking a drug from each of the therapeutic
classes at the end of the study in the upon waking and
bedtime groups respectively was:
-
angiotensin II receptor blockers: 53.1% in both groups
-
angiotensin converting enzyme inhibitors: 25.3% and
23.4%
-
calcium channel blockers: 32.7% and 36.8%
-
beta-blockers: 22.0% and 17.5%
- diuretics: 46.5% and 39.5%.
Dual and triple treatment regimens, where available,
were prescribed as single-tablet fixed combinations.
Over a median follow-up of 6.3 years, 1,752 (9.2%)
participants had a CVD event listed in the combined
primary outcome (myocardial infarction, coronary
revascularisation, heart failure, ischaemic stroke,
haemorrhagic stroke and CVD death). Participants in the
bedtime administration group had a
statistically significant
lower risk of the primary CVD outcome compared with
those in the upon waking group (adjusted
hazard ratio
0.55, 95%
confidence interval
0.50 to 0.61, p<0.001; adjusted for baseline
characteristics such as age, sex and
co-morbidities).There was also a statistically
significant lower risk of all of these outcomes
individually in the bedtime compared with upon waking
group. Throughout the study, 48-hour ambulatory blood
pressure was recorded at least annually. There was no
statistically significant difference between the 2
groups for mean awake systolic or diastolic blood
pressure, but there was a statistically significant
lower mean asleep systolic and diastolic blood pressure
in the bedtime administration group.
There was no statistically significant difference in the
frequency of adverse effects (reported by 6.7% and 6.0%
of the upon waking and bedtime administration groups
respectively, p=0.061), or poor adherence to the
allocated treatment schedule (2.8% and 2.9%
respectively, p=0.813). The study only reported overall
incidence of adverse events and did not report on
specific adverse events such as falls. In addition,
adverse events were only recorded if spontaneously
reported by participants or revealed through non-direct
questioning and physical examination. There was no
statistically significant difference between the 2
groups for sleep time hypotension (0.3% of all
participants).
This was a large study with a long duration of
follow-up. However, the study authors have highlighted
some study limitations. The study population was
Caucasian, therefore validation of the results for other
ethnic groups is needed. Also, the study did not
allocate participants to specific antihypertensive
medication therapeutic classes or set medication within
each class as treatment was chosen by each participating
clinician. For diuretics for instance, at the end of the
study, there were more participants taking them in the
upon waking group (46.5%) compared with the bedtime
administration group (39.5%, p<0.001). Finally, the
method by which adverse events were assessed is open to
recall bias.
Commentary provided by Dr Mark Shapley, member of NICE
hypertension in adults guideline committee and retired
General Practitioner
This large prospective trial aimed to answer a simple
question directly relevant to general practice where
there is a lack of good quality evidence. This new
evidence suggests that taking the total daily dose of
antihypertensive medication at bedtime, compared with in
the morning, reduces cardiovascular events and mortality
over a mean of 6.3 years. A major clinically
significant result - but there are caveats.
The study included a non-UK (Spanish), Caucasian
population and therefore, the findings may not apply to
other populations with different sleeping patterns
(although participants were encouraged not to sleep in
the day) or people with different family origins. The
mean age of the cohort was 60.5 years and therefore
results may not apply to older cohorts.
As is common in many trials of antihypertensive therapy,
patient centred adverse events were poorly reported
(sleep disturbance due to nocturia, falls and dizzy
episodes due to postural hypotension). These were only
collated via spontaneous reports which relies on people
remembering to report such events. Assessing this by
active questioning would have been preferable.
The classes of drugs prescribed were not blinded and
there were differences between the 2 study groups
with those who took a morning dose more likely to be on
diuretics and beta-blockers.
Broadly the clinicians appeared to prescribe classes of
drugs in the manner of the NICE guidance but the
criteria for diagnosing hypertension differed by using
not only ambulatory blood pressure monitoring whilst
awake but also allowed recruitment of those with raised
blood pressure diagnosed using ambulatory blood pressure
monitoring whilst asleep. The monitoring period for
ambulatory blood pressure in the study was also 48
hours.
The NICE guidance makes no recommendation as to when to
take antihypertensive medication and it was a question
that the development group did not consider.
In conclusion, and despite the limitations discussed
above, there may be a potential health gain in switching
to a regimen of taking a total daily dose of
antihypertensive medication at bedtime. This seems
reasonable to do but we should be cautious if
considering this in older people, in those at risk of
falls and in those in whom such a change may reduce
concordance with medication (for example, those taking
antihypertensives which may not be suitable for bedtime
administration such as diuretics).
Declaration of interests: Dr Mark Shapley declared no
interests.
Study sponsorship
The randomised controlled trial was funded by the Hygia
Project, an independent investigator-promoted research
network supported by unrestricted grants from several
Spanish Government and European Regional Development
Funds.
References
Bowles NP, Thosar SS, Herzig MX, et al (2018)
Chronotherapy for hypertension. Current Hypertension Reports 20: 97
Hermida RC, Crespo JJ, Dominguez-Sardina M et al (2019)
Bedtime hypertension treatment improves
cardiovascular risk reduction: the Hygia Chronotherapy
Trial. European Heart Journal 0: 1–12


** Copyright (c) 2006, Oliver Schoenborn ** Distributed under the BSD Software License (see accompanying ** LICENSE_IOF_1_0.txt in root folder of library for complete ** terms and conditions).
#include <string>
Include dependency graph for validity.hpp:
Go to the source code of this file.
Namespaces | |
| namespace | iof |
Classes | |
| struct | iof::validity |
| Represents the validity state of a stream. More... |


--- layout: default ---
An open-source workflow to enable the exchange of electronic invoices in a structured, machine-readable format. Supports Factur-X, ZUGFeRD 1.0 and 2.0, UBL and EN 16931.
Every year billions of invoices are exchanged. The majority is emailed in an unstructured PDF format, which means only humans can read and process it.
Invoice-x is a collection of open source applications and libraries aimed at automating the invoicing- and accounting workflow for businesses. Currently we offer tools to extract structured data from legacy PDF invoices, as well as embedding and editing structured XML-representations in hybrid invoices.
invoice2data is a Python library and command line tool to extract structured data from PDF invoices using regex templates and (optionally) OCR.
Factur-X NG (ZUGFeRD 2.0) is a container standard for embedding a XML representation (UBL, EN 16931 or another standard) of the invoice data.
InvoiceX-GUI is a desktop application allowing you to edit hybrid invoices on your desktop. Available for Windows, macOS and Linux.