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The new place of "Are we in space yet?" is found at AeroRust's community website - https://aerorust.org/catalogue.


This is the first time ever that a cross-cluster initiative has been organized by Arts x Makers. We have an exciting lineup of activities and merchandise for you on 27th February 2019, the day between Valentines & White Day.
 It's back again! This time, you can even pre-order the amount that you want beforehand. While stocks last!
Coming soon on Week 3.
I wonder what this is?
Walk-in only.
Can't decide what kind of gift to give to your peers or lovely gf during this special occassion? Fear not! Professional local clubs in designing services are available this season to help you out! P.S. The rates are way cheaper than outside :)
by Modern Visual Media Circle
Chibi is a cute Japanese art style originated from manga, that features characters with big heads and small bodies. MVMC members will provide paid service to ‘chibify’ interested students’ pictures. The pictures will be framed and turned into keychains.
by Everposter
Show your care and affection for your loved ones by pre-ordering a customised merchandise today!
Other than unique decoration bottles, check out special keychain designs in the order link!
These crafts are also hand-made by your own peers, but no pre-ordering required!
by NihonGo! Japanese Cultural Club
Ever thought that flowers are pretty but their beauty is fleeting? With NihonGo!, now you will be able to learn to make roses that will stay beautiful for as long as you take care of them! A great gift for anyone you care about.
Free of charge :)
by PADI
Gives great satisfaction when clicking it.
Only walk-in purchase.
Have lots of fun with team-based games!
by Ballroom Dancing Club
Taught by Nancy Low from Melvin Low Dance Studio. Take a step out of your comfort zone, and experience the joy of dance! Beginners are welcome to join in too! It will be a great experience for you and your friend/gf/bf! :D
just walk-in~
by NihonGo! Japanese Cultural Club
Remember Cultural Games Night last year? The drum challenge is back again! This time, you get to play in 2v2, 3v3 or even 4v4 format!
P.S. It will be on projecter and screen this time, as there is no TV available for us to loan, but it will still be lots of fun!!
Fill up this survey and stand a chance to win limited Forever edition of Line Plush Toys or other goodies!
SurveyContact us at<EMAIL_ADDRESS>for general enquiries.


Stinky Tofu Projects
contact
About Me
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Contact
Resume
1.555.555.5555
<EMAIL_ADDRESS>GitHub
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Rose ringed parakeet
Three to five white eggs are laid.
by Bruce MunroA scarce localised species, the nature of its introduction from India and China is unknown, but probably from escaped cage birds. Groups have established in Durban, near Sodwana Bay and central Gauteng since about 1970. These parakeets like woodland and adjacent cultivated lands. They are gregarious in flocks of up to 60 birds. Noisy when raiding croplands, they can do considerable damage. Holds food in its foot while nibbling with its bill. Fruit, seeds, grain, flowers and nectar are food preferences.
Their flight is swift and direct with fast wing beats. The call is a loud shrill kee – ak repeated slowly or fast several times. They also have a variety of whistles and chattering notes.
Breeding month is September. Their nest being a hole in a tree eight to 10m above the ground with the floor lined with bark chips. Three to five white eggs are laid. Incubation is 26 to 28 days and nestlings for six to seven weeks.
There is no tribal name for this bird and in Afrikaans die ringnekparkiet.
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But meowing by your bowl is not cutting it right now. How can we make those dumb humans understand what you want?


Variables
Const abort
Const animationEnd
Const animationIteration
Const animationStart
Const blur
Const canPlay
Const canPlayThrough
Const change
Const click
Const compositionEnd
Const compositionStart
Const compositionUpdate
Const contextMenu
Const copy
Const cut
Const doubleClick
Const drag
Const dragEnd
Const dragEnter
Const dragExit
Const dragLeave
Const dragOver
Const dragStart
Const drop
Const durationChange
Const emptied
Const encrypted
Const ended
Const error
Const focus
Const input
Const invalid
Const keyDown
Const keyPress
Const keyUp
Const load
Const loadStart
Const loadedData
Const loadedMetadata
Const mouseDown
Const mouseEnter
Const mouseLeave
Const mouseMove
Const mouseOut
Const mouseOver
Const mouseUp
Const paste
Const pause
Const play
Const playing
Const progress
Const rateChange
Const scroll
Const seeked
Const seeking
Const select
Const stalled
Const submit
Const suspend
Const timeUpdate
Const touchCancel
Const touchEnd
Const touchMove
Const touchStart
Const transitionEnd
Const volumeChange
Const waiting
Const wheel
Simulate an event dispatch on a DOM node with optional
eventData
event data.Simulate
has a method for every event that React understands.


--- layout: post title: FEDERATED cheats date: type: post published: false status: draft categories: - MySQL tags: [] meta: _edit_last: '2' author: login: shlomi email<EMAIL_ADDRESS>display_name: shlomi first_name: Shlomi last_name: Noach ---
We are actually using FEDERATED table at Outbrain, and they solve a difficult problem: ... fact/dimension.
My esteemed colleague Gabi Davis is ...
- LIMIT -- on clicnet side!
- Add indexes to FEDERATED that do not appear on server, to cheat FEDERATED into producing better plans!


My professional objective is to continually improve my software engineering and web development skills by implementing industry best practices and working on exciting far reaching projects as well as continuing to be a valued team member of a forward thinking web/software development company.
Position: Senior Software Engineer
Details: TBA
Position: Assistant Team Leader / Senior Developer, Software Architect
Projects:
Responsive Online Booking Engine
Example: https://secure.flightcentre.com.au
Technical lead developer in an agile team implementing the responsive redesign of the online booking engine for FCTG, built using Symfony2 PHP framework, Backbone+Marionette JavaScript MVC framework, Foundation responsive framework, we have begun a migration to ReactJS+Redux.
The responsive booking engine is on nine of FCTG's brands/sites such as: Flight Centre (Australia, New Zealand, Singapore, South Africa) Escape Travel (Australia), Student Flights (Australia, New Zealand), Travel Associates (Australia)
In order to achieve the various brands we had to implement a skinnable stylesheet system allowing developers to customize the look of the application across brands.
Contact me for reference contact details
Position: Installation, Support, Training & Development
Tasks: Installation, Support, Training & Development of a web application for use in the drug & alcohol treatment management industry.
Contact me for reference contact details
2002 - Diploma of Multimedia – Moreton Institute of TAFE
2000-2001 - Diploma of Information Technology (Software Development)
| Skill/Technology | Proficiency |
|---|---|
| JavaScript / Typescript | Advanced |
| ReactJS | Advanced |
| PHP | Advanced |
| SQL (MySQL) | Advanced |
| HTML | Advanced |
| CSS | Advanced |
| JavaScript | Advanced |
| Linux | Intermediate |
| Apache | Intermediate |
| Nginx | Intermediate |
| Redis | Basic |
| Unit Testing | Advanced |
| Git | Advanced |
| Redux | Advanced |
| Agile Methodologies | Advanced |
Contact me for details


For this week’s analysis, I’ve chosen a site that I have to use about once a month, and each time pains me greatly. I give you, the ORCA Card site:
https://orcacard.com/ERG-Seattle/welcomePage.do
Those who are not familiar with the site, the ORCA Card is a way to pay for your bus, train and Vanpool fare throughout the Puget Sound Area and is managed on the ORCA Card website. Users can create a login and order a card, add funds to an existing card, or even give their card a nickname. Seems harmless from their homepage, right? Just wait until you login and try to reload the thing. So far the only thing I’ve found to be more time consuming than that is running around flipping couch cushions or raiding your little brother’s piggy bank for loose change (which I of course would never do).
This week I’ve chosen a shorter list of criteria to use so I can dive deeper into each topic:
- Is the site easy to navigate? Are the navigational elements clear?
- Is the site intuitive?
- Is the site easy to learn?
- Are the site features easy to use?
Are the navigational elements clear? Is the site easy to navigate?
I would say that the navigational elements are clear for the most part. After logging in, the user is presented with a very clean and basic interface. The main menu is located to the left of the page with titles that do make sense such as ‘Order a Card’ or ‘Register a Card’.
However, the main reason for using this site after you’ve ordered and registered your card is to be able to reload it so you can keep using it for your travels. Looking at the page, it is really difficult to be able to tell where you might do that. I feel like the site’s users would really benefit from a simple menu link that says ‘Reload your card’ or ‘Add funds to your card’. There is a ‘Pay Vanpool fare’ link at the bottom of the ‘My ORCA’ section of the menu, I don’t see a reason why adding a reload option would be an issue.
Is the site intuitive?
I will continue with my previous point of trying to reload your card. On the homepage there is no link to clue a user in where they may be able to do that, or any sort of instruction they may follow. In order to add funds to the card, a user must either click ‘E-Purse transfer’ or click their card number (I blocked mine out for privacy purposes). In my opinion, I think the term ‘E-purse’ is not very clear and somewhat misleading, and I would not pick the card number as the first place I’d go. However on the next page after you click your card number, there is a different menu which has an ‘Add value’ option. This would be a helpful link to have on the main page so the user doesn’t have to go searching for it.
Is the site easy to learn?
This site may become easy for those who login frequently to re-up their card. I prefer to add money about once per month and use it until the balance gets low. Because of this I’ve found its easy to forget where to go to reload and end up clicking around until I end up at the right spot. Another option I discovered while clicking around the site is to ‘Autoload’ your card, so once you run low on funds it will reload your card automatically to an amount you’ve specified to your account. Although the site does have a FAQ section that will tell you different ways to load your card, I think it would be much more helpful to have ‘how-to’ type links on the homepage, or more section names.
Are the features easy to use?
In my opinion, somewhat. I found the initial setup to be a little frustrating, but once you have your ORCA card linked and your credit card information saved it becomes quite a bit easier. However I do think there is plenty of room for improvement to make for a better and more enjoyable user experience. I would start by adding clearer menu options to the homepage (‘Reload Your Card Here’, ‘Setup Autoload Here’, ‘Add funds’, etc.) and doing away with terms such as ‘E-purse’. There also seems to be several steps to add your funds, I would prefer to see as a more simple way to do so and would love to see an app one day and a more web-app type interface for the overall website to make things more convenient for commuters.


{% extends "base.html" %} {% block content %}
Date: {{ report.release_date }}
Comments: {{ report.comments }}
Project: {{ report.project }}
Client: {{ report.project.client }}
Edit


A smart accessory for your belongings - never leave anything behind.
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Only notifies you when you need it. Automatic muting in safe places such as your home or the office.
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Greek Metrics¶
The greek metrics are a collection of 26 short rhythms enumerated below. They are encoded in the fragments_db.db file in the databases directory. They are also provided as XML files in the fragments directory.
Name |
Quarter length list |
|---|---|
Spondee |
[2.0, 2.0] |
Iamb |
[1.0, 2.0] |
Trochee |
[2.0, 1.0] |
Anapest |
[1.0, 1.0, 2.0] |
Amphimacer |
[2.0, 1.0, 2.0] |
Amphibrach |
[1.0, 2.0, 1.0] |
Bacchius |
[1.0, 2.0, 2.0] |
Dactyl |
[2.0, 1.0, 1.0] |
5/16 |
[2.0, 2.0, 1.0] |
Choriamb |
[2.0, 1.0, 1.0, 2.0] |
Antipast |
[1.0, 2.0, 2.0, 1.0] |
Ionic Minor |
[1.0, 1.0, 2.0, 2.0] |
Ionic Major |
[2.0, 2.0, 1.0, 1.0] |
Peon I |
[2.0, 1.0, 1.0, 1.0] |
Peon II |
[1.0, 2.0, 1.0, 1.0] |
Peon III |
[1.0, 1.0, 2.0, 1.0] |
Peon IV |
[1.0, 1.0, 1.0, 2.0] |
Epitrite I |
[1.0, 2.0, 2.0, 2.0] |
Epitrite II |
[2.0, 1.0, 2.0, 2.0] |
Epitrite III |
[2.0, 2.0, 1.0, 2.0] |
Epitrite IV |
[2.0, 2.0, 2.0, 1.0] |
Adonic |
[2.0, 1.0, 1.0, 2.0, 1.0] |
Dochmius I |
[1.0, 2.0, 2.0, 1.0, 2.0] |
Dochmius II |
[2.0, 1.0, 2.0, 1.0, 2.0] |
Amphimacer+Anapest |
[2.0, 1.0, 2.0, 1.0, 1.0, 2.0] |
Dactyl+Antibacchius |
[2.0, 1.0, 1.0, 2.0, 2.0, 1.0] |


 Seth watched over his bags as much as he did his bus driver who also kept looking at him as he spoke to these very abnormal men who all had big bellies.  They were standing huddled in a semicircle some leaning on this huge pretty bus that surpassed the one Seth had arrived with which was a rainbow of different colors and parts. This bus was bigger and better in length and width with soft curves and grove, no sellotaped windows or shuttered rear indicators plus it had a uniform pearl-white color.
Everything and everyone in the congested terminus was foreign to Seth even the atmosphere people shouting, cars hooting hysterically, everyone seemed busy like bees on a honeycomb, some coming some leaving. Yet amidst all this hysteria Seth kept vigil over his bag just as his mother had instructed him, looking at the driver one by one all the men would take sneak peeks at Seth and pretend otherwise.
Now the talk started to drag as the other men were talking and it was Seth’s driver who now kept turning around now and again with anxious eyes. Seth with his bag stood erect and calm, he knew that when adults speak it is rude to listen or look so he found something to occupy his mind. He started looking around at all the busy people who also carried their luggage’s, these were families of different sizes, some had both parents along with their children, but others it was just the mother and child, some went solo. Some people carried fruit baskets and many other things that Seth knew not and all these were exchanged for the button without a hole and the one who receives the button always seemed happier than the one who would get the nourishment of an orange or banana.
This grieved Seth but he held steadfast to the hope of a Brighter Future. Seth noticed that these buses had a similar sound and smoke came out of them except for when they stopped, this he wondered why? Some juxtaposition was how the masses dresses compared to him, his mother’s vintage couture juxtaposed against the massed stood apart from the flamboyant array of colors textures and designs that people wore, from head to toe. Some even had different hair color and textures, unlike his natty afro.
Just as Seth was lost in his new world the bus driver came back to his rescue and told him to follow him to the next bus that would take him straight to his brothers.  “Hi, sir” replied the downtrodden young boy who had a lot on his plate to melt with fear of an old fat hippopotamus with a sagging belly. “My name is Zwelakhe and I will be your driver to Kimberly,” said the guy who robbed a chimpanzee’s face. “Nice to meet you, I am Seth the son of Mthimkhulu and Nolwandle.” respectful and uncompromising was his tone.
Well then son you can go in and sit here in front, your bags will be loaded on the trailer. “Pardon me, sir, I mean not to be rude but I would like to see and assure that my bags are loaded and safe in obedience my parent's command.” “Then so be it, young man, boys take all those and load them onto the trailer” decreed the fat bus driver and so it was done. Thank you, sir, you have been far too kind said Seth to his former bus driver as he took his tiny little body into the front seat and closed the door.
The men were all evidently shocked at this young boy’s assertive demeanor. While the drivers were awaiting their buses to be full Seth looked and the sun and saw it was lunch time, as usual, so he reached for his leather bag, opened his hatched lunch box made of cane strips.  Bit by bit passengers came in and the bus was full, the driver came to start the engine and left while passengers were filling the record book. This time Seth had boarded a minibus.
To be continued...
Listen To Our Audio


--- layout: photopost category: Photography title: "India Trip" subtitle: "A winter break tour of the subcontinent." date: 2015-01-22 12:00:00 author: "Rupert Deese" photoset:<PHONE_NUMBER>1212813 header-img: img/2015-01-22-bg.jpg ---
For three weeks starting in December, 2014, I visited India with a group of dear friends from college. We travelled down the western coast of the subcontinent, visiting New Delhi, Mumbai, Bangalore, Kovalam, Cochin, and Trivandrum. I shot the better part of two rolls there, whenever I had the foresight to choose my little Rollei B35 over my iPhone.


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IMMORTAL BELOVED A film review by Mark R. Leeper Copyright 1995 Mark R. Leeper
Capsule: Columbia's first Famous-Composer Bio-Mystery since AMADEUS is a speculation about the real-life mystery of to whom Ludwig van Beethoven addressed three unsent letters. He referred to the addressee only as his "Immortal Beloved." Gary Oldman is a good choice to play the genius who expresses his emotional torment through his music. Still somehow the story is less than compelling. Rating: high +1 (-4 to +4).
Well, to start with, there probably were three major amors in Beethoven's life. And one really was Giulietta Guicciardi; so far the filmmakers got that one right. The other two women were Giulietta's cousin Josephine von Brunsvik, to whom he proposed, and Therese Malfatti, the daughter of one of Beethoven's doctors. The film did show Josephine as a minor diversion and ignored Malfatti altogether. This is a rough biography of Ludwig Van Beethoven that takes some liberties to add some suspense.
There genuinely is a historical mystery, of course. After Beethoven's death three letters were found addressed to someone he called "Immortal Beloved." It is possible they were just a writing exercise, though the fact they range from poetic prose to complaints about his health and his discomfort makes that unlikely. If they were to a real person, nobody ever found out to whom the letters were addressed. The film suggests that Beethoven (here played by Gary Oldman), kept this love a secret, then illogically left a bequest to his "Immortal Beloved" without ever naming the intended recipient. Anton Schindler, a friend (played by Jeroen Krabbe) sets out, to solve the mystery. (The real Anton Schindler apparently was a junior acquaintance of the composer. Beethoven was born in 1770 and Schindler was the author of BIOGRAPHIE VON LUDWIG VAN BEETHOVEN--English title: BEETHOVEN AS I KNEW HIM--in 1860, some thirty-three years after Beethoven died. But Schindler might well have looked for the mysterious love, so to set up this mystery/biography is really not too much of a conceit. Though it is a bit absurd to assume that the composer would on one hand be so secretive about this love and on the other hand virtually to force this investigation by leaving her his fortune. And, of course, as with AMADEUS, any conclusions the film draws are purely speculation and should be considered as such.
The film opens with Oldman living up to his name and near death. (He looked much the same early in BRAM STOKER'S DRACULA, but there he was near death just on the other side.) Schindler finds the will and sets out with a list of leads to try to discover who this Immortal Beloved is. The structure is like that of CITIZEN KANE and as with CITIZEN KANE the story of the life is revealed as a mosaic of flashbacks and here even flashbacks-within-flashbacks, mostly covering the period from the onset of his deafness to his death. First Schindler visits the now-aging Countess Giulietta Guicciardi (Valeria Golino), whom Beethoven forcefully makes his pupil. She falls in love with him and wants to marry him, but she and her father discover a secret about Beethoven that he cannot bear them to know. The trail then leads to Anna Marie Erdody (Isabella Rossellini), a Hungarian noble who continues the story, and so forth. Much of the film concentrates on either on his women, his deafness, or his cruel battle for custody and control of his nephew.
Gary Oldman is one of the best and most versatile actors in film today. He gives us a very watchable impression of a great genius in constant struggle with himself and with his own personal demons. Krabbe's role is less demanding, calling for him to be little more than a good listener in period clothing. Galino and Rossellini are winning but are upstaged by the intensity of Oldman's performance. In fact the only other strong performance is by Johanna Ter Steege as the sister- in-law who fights Beethoven for custody of her own son. Direction is by Bernard Rose, director of the off-beat fantasy PAPERHOUSE and of the horror film CANDYMAN.
"It is the power of music to carry one into the mental state of the composer," according to Beethoven. And Rose seemingly uses this as the inspiration to score the film with whatever music Beethoven is composing at each point in time. Whether he was entirely accurate is unclear, but he does seem to proceed though the symphonies in chronological order. This means, of course, that the filmmakers get a glorious, evocative orchestral score simply by making selections. And certainly one cannot deny the power of scenes like Napoleon's shelling Vienna to the strains of the first movement of the Fifth Symphony in pure digital sound.
The fragmentation of the narration, using the patchwork narrative form, and bogging down of the story into a custody battle tend to rob IMMORTAL BELOVED of some of its power, but the music on a really good sound system and the crafty proposed solution to the central mystery make this one of the better musical biographies. Rating high +1 on the -4 to +4 scale.
Mark R. Leeper<EMAIL_ADDRESS>.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
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Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
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Related links: index of all rec.arts.movies.reviews reviews


The DC Universe (DCU) is the fictional shared universe where most stories in American comic book titles published by DC Comics take place. DC superheroes such as Superman, Batman, Wonder Woman, Martian Manhunter, The Flash, Green Lantern, Aquaman, and Booster Gold are from this universe, and it also contains well-known supervillains such as Lex Luthor, the Joker, Brainiac, Lady Shiva, Sinestro, Deathstroke, Cheetah, and Darkseid. In context, the term "DC Universe" usually refers to the main DC continuity. The term "DC Multiverse" refers to the collection of all continuities within DC Comics publications
Within the Multiverse, the main DC Universe has gone by many names, but in recent years has been referred to by "Prime Earth" (not to be confused with "Earth Prime") or "Earth 0". The main DC Universe, as well as the alternate realities related to it, began as the first shared universe in comic books and were quickly adapted to other media such as film serials or radio dramas. In subsequent decades, the continuity between all of these media became increasingly complex with certain storylines and events designed to simplify or streamline the more confusing aspects of characters' histories.


little-endian
`Prev `__
L
`Next `__
--------------
**little-endian**: adj.
Describes a computer architecture in which, within a given 16- or 32-bit
word, bytes at lower addresses have lower significance (the word is
stored ‘little-end-first’). The `*PDP-11* <../P/PDP-11.html>`__ and
`*VAX* <../V/VAX.html>`__ families of computers and Intel
microprocessors and a lot of communications and networking hardware are
little-endian. See `*big-endian* <../B/big-endian.html>`__,
`*middle-endian* <../M/middle-endian.html>`__, `*NUXI
problem* <../N/NUXI-problem.html>`__. The term is sometimes used to
describe the ordering of units other than bytes; most often, bits within
a byte.
--------------
+---------------------------------+----------------------------+-------------------------+
| `Prev `__ | `Up <../L.html>`__ | `Next `__ |
+---------------------------------+----------------------------+-------------------------+
| lithium lick | `Home <../index.html>`__ | live |
+---------------------------------+----------------------------+-------------------------+


Class: Aws::Proton::Types::CountsSummary
| Relationships & Source Files | |
| Super Chains via Extension / Inclusion / Inheritance | |
|
Class Chain:
self,
Struct
|
|
|
Instance Chain:
self,
::Aws::Structure ,
Struct
|
|
| Inherits: |
Struct
|
| Defined in: | gems/aws-sdk-proton/lib/aws-sdk-proton/types.rb |
Overview
Summary counts of each ::Aws::Proton
resource type.
Constant Summary
Instance Attribute Summary
-
#components ⇒ Types::ResourceCountsSummary
rw
The total number of components in the Amazon Web Services account.
-
#environment_templates ⇒ Types::ResourceCountsSummary
rw
The total number of environment templates in the Amazon Web Services account.
-
#environments ⇒ Types::ResourceCountsSummary
rw
The staleness counts for
::Aws::Proton
environments in the Amazon Web Services account. -
#pipelines ⇒ Types::ResourceCountsSummary
rw
The staleness counts for
::Aws::Proton
pipelines in the Amazon Web Services account. -
#service_instances ⇒ Types::ResourceCountsSummary
rw
The staleness counts for
::Aws::Proton
service instances in the Amazon Web Services account. -
#service_templates ⇒ Types::ResourceCountsSummary
rw
The total number of service templates in the Amazon Web Services account.
-
#services ⇒ Types::ResourceCountsSummary
rw
The staleness counts for
::Aws::Proton
services in the Amazon Web Services account.
Instance Method Summary
::Aws::Structure
- Included
| #to_hash | Alias for Structure#to_h. |
Instance Attribute Details
#components ⇒ Types::ResourceCountsSummary (rw)
The total number of components in the Amazon Web Services account.
The semantics of the components
field are different from the
semantics of results for other infrastructure-provisioning
resources. That's because at this time components don't have
associated templates, therefore they don't have the concept of
staleness. The components
object will only contain total
and
failed
members.
# File 'gems/aws-sdk-proton/lib/aws-sdk-proton/types.rb', line 504
class CountsSummary < Struct.new( :components, :environment_templates, :environments, :pipelines, :service_instances, :service_templates, :services) SENSITIVE = [] include Aws::Structure end
#environment_templates ⇒ Types::ResourceCountsSummary (rw)
The total number of environment templates in the Amazon Web Services
account. The environmentTemplates
object will only contain total
members.
# File 'gems/aws-sdk-proton/lib/aws-sdk-proton/types.rb', line 504
class CountsSummary < Struct.new( :components, :environment_templates, :environments, :pipelines, :service_instances, :service_templates, :services) SENSITIVE = [] include Aws::Structure end
#environments ⇒ Types::ResourceCountsSummary (rw)
The staleness counts for ::Aws::Proton
environments in the Amazon Web
Services account. The environments
object will only contain
total
members.
# File 'gems/aws-sdk-proton/lib/aws-sdk-proton/types.rb', line 504
class CountsSummary < Struct.new( :components, :environment_templates, :environments, :pipelines, :service_instances, :service_templates, :services) SENSITIVE = [] include Aws::Structure end
#pipelines ⇒ Types::ResourceCountsSummary (rw)
The staleness counts for ::Aws::Proton
pipelines in the Amazon Web Services
account.
# File 'gems/aws-sdk-proton/lib/aws-sdk-proton/types.rb', line 504
class CountsSummary < Struct.new( :components, :environment_templates, :environments, :pipelines, :service_instances, :service_templates, :services) SENSITIVE = [] include Aws::Structure end
#service_instances ⇒ Types::ResourceCountsSummary (rw)
The staleness counts for ::Aws::Proton
service instances in the Amazon Web
Services account.
# File 'gems/aws-sdk-proton/lib/aws-sdk-proton/types.rb', line 504
class CountsSummary < Struct.new( :components, :environment_templates, :environments, :pipelines, :service_instances, :service_templates, :services) SENSITIVE = [] include Aws::Structure end
#service_templates ⇒ Types::ResourceCountsSummary (rw)
The total number of service templates in the Amazon Web Services
account. The serviceTemplates
object will only contain total
members.
# File 'gems/aws-sdk-proton/lib/aws-sdk-proton/types.rb', line 504
class CountsSummary < Struct.new( :components, :environment_templates, :environments, :pipelines, :service_instances, :service_templates, :services) SENSITIVE = [] include Aws::Structure end
#services ⇒ Types::ResourceCountsSummary (rw)
The staleness counts for ::Aws::Proton
services in the Amazon Web Services
account.
# File 'gems/aws-sdk-proton/lib/aws-sdk-proton/types.rb', line 504
class CountsSummary < Struct.new( :components, :environment_templates, :environments, :pipelines, :service_instances, :service_templates, :services) SENSITIVE = [] include Aws::Structure end


| handler: null | ||
|---|---|---|
| Row 1 | Record 1 | Record 1 |
| Row 2 | Record 2 | Record 2 |
| Row 3 | Record 3 | Recrod 3 |
| Row 4 | Record 4 | Record 4 |
| Row 5 | Record 5 | Record 5 |
| handler: "td.sorter" | |||
|---|---|---|---|
| Row 1 | Record 1 | Record 1 | |
| Row 2 | Record 2 | Record 2 | |
| Row 3 | Record 3 | Recrod 3 | |
| Row 4 | Record 4 | Record 4 | |
| Row 5 | Record 5 | Record 5 | |
| handler: "span.sort-handler" | ||
|---|---|---|
| Row 1 | Record 1 | Record 1 |
| Row 2 | Record 2 | Record 2 |
| Row 3 | Record 3 | Recrod 3 |
| Row 4 | Record 4 | Record 4 |
| Row 5 | Record 5 | Record 5 |


Behind every mask there is a face, and behind that a story.
KICKASS
Download
SCORPION
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SUB-ZERO
Download
DEADPOOL
Download
STORMTROOPER
Download
DARTH-VADER
Download
DARTH-MAUL
Download
BOBA-FETT
Download
SPIDERMAN
Download
VENOM
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FALLOUT
Download
IRONMAN
Download


WITNESS LIST
Special Purpose Districts Committee
November 30, 2017 - 1:00 PM
#1 - Disaster Preparedness
On:
Burrer, Todd (Severn Trent)
Campbell, Augustus (West Houston Association)
Davis, Scott (Meyers Research LLC)
Duncan, Wendy (Self; Willow Fork Drainage District)
La Caille, Cari-Michel (TCEQ)
Norman, Scott (Texas Association of Builders)
Parks, Michael (Association of Water Board Directors)
Phinney, Chuck (Department of public safety, division of emergency management)
Sloan, Mark (Harris County)
Stuckey, Joshua (Harris County Engineering Department)
#2 - Bond Review
On:
Bartholomew, Jan (RW Baird & Co.)
Cohen, Howard (Schwartz, Page & Harding, LLP)
Kavanaugh, Cliff (FirstSouthwest, division of Hilltop securities)
Martin, Ross (Winstead PC)
Peak, Julie (FirstSouthwest)
Prihoda, Andrew (Office of the Attorney General)
Ulmann, Chris (TCEQ)
#3 - Dissolution
On:
Clegg, Steve (Self; Benbrook Library District)
Lary, Trey (Allen Boone Humphries Robinson LLP)
Lord, Clark (Montrose management district)
Mathew, Bryan (Texas Public Policy Foundation)
Stuckey, Joshua (Harris County Engineering Department)
Taylor, Andy (Self; 1620 Hawthorne Ltd.)
Ulmann, Chris (TCEQ)
1


Episode MAY 2018
It is a period of more and more customers coming to the Okta side of The Force, and want to customize their end-user experience. The battle to delight customers and cement Okta's market leadership is progressing, and the Okta's Empire is ahead of the competition.
Hor-Kan Chan (eng manager)
Santhosh Krishnan (eng)
Nikhil Venkatraman (eng)
Samer Fanek (eng)
Manuel Tanzi (eng)
Priya Kathirvel (QA)
Joël Franusic (TMM)
Lily Hsiao (Director Eng)
Matt Loughran (tech writing)
John Intrater (design)
Chris Barbara (eng)
Rocco Muscaritolo (eng)
Trevor Thompson (architect)
John Gronberg (PM)
Tom Abbott (PM DevEx)
Nate Barbettini (PM DevEx)
Ahmed Al-Bahar (PM)
Reman Child (DevEx architect)
Tom Britton (program manager)
Jing Hu (eng)
Frank Montanaro (eng)
Eric Carroll (eng)
Mauricio Silva (eng)
Daniel Lu (PMM)
Jade Feng (PM)


{% load static %}
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer.
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer.
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer.
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Lorem Ipsum is simply dummy text of the printing and typesetting industry.Lorem Ipsum is simply dummy text of the printing and typesetting industry.
Lorem Ipsum is simply dummy text of the printing and typesetting industry.Lorem Ipsum is simply dummy text of the printing and typesetting industry.
Lorem Ipsum is simply dummy text of the printing and typesetting industry.Lorem Ipsum is simply dummy text of the printing and typesetting industry.
Lorem Ipsum is simply dummy text of the printing and typesetting industry.Lorem Ipsum is simply dummy text of the printing and typesetting industry.
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text and typesetting industry. Lorem Ipsum has been the industry's standard dummy ever since the 1500s,
Creativity itself doesn't care at all about results - the only thing it craves is the process. Learn to love the process and let whatever happens next happen, without fussing too much about it
Shree Dungarpuri Ji Ka Math Bhawan
Tankar Pada
Chohtan
Contact:<PHONE_NUMBER>


Affirmation and Stereotype Threat
Exploring my Values
When I think of the times in my life when I've been the happiest, the proudest, or the most satisfied, the following values come to mind:
Accomplishment Affection Challenge Close relationships Commitment Compassion Competence Confidence Cooperation Courage Creativity Credibility Economic security Fairness Faith Free time Freedom Friendships Growth Having a family Health Helping other people Honesty Inner harmony Insight Inspiration Integrity Knowledge Meaningful work Nature Order Peace Personal development Physical challenge Purity Quality Self-reliance Self-respect Spirituality Stability Truth Will-power Wisdom.
Having a family is on my list because It's at the center of what I choose to do with my life. Much of my happiness is tied into my wife, kids, and other family members. Their happiness is my happiness, so I try to serve them and grow closer to them. I also consider Personal development to be a key to my happiness. I've never felt satisfied with "business as usual" for very long. If I'm not learning something new, getting better at breaking bad habits and forming good ones, etc., then I start to feel anxious or down.
Do I feel I'm generally trying to live up to these values? Here's what I think on a scale of 1(disagree) to 5(agree):
- Accomplishment: 3
- Affection: 4
- Challenge: 3
- Close relationships: 4
- Commitment: 4
- Compassion: 5
- Competence: 4
- Confidence: 3
- Cooperation: 4
- Courage: 3
- Creativity: 3
- Credibility: 5
- Economic security: 4
- Fairness: 5
- Faith: 5
- Free time: 3
- Freedom: 4
- Friendships: 4
- Growth: 5
- Having a family: 5
- Health: 3
- Helping other people: 3
- Honesty: 5
- Inner harmony: 4
- Insight: 3
- Inspiration: 3
- Integrity: 5
- Knowledge: 4
- Meaningful work: 4
- Nature: 3
- Order: 4
- Peace: 5
- Personal development: 4
- Physical challenge: 3
- Purity: 5
- Quality: 4
- Self-reliance: 4
- Self-respect: 4
- Spirituality: 4
- Stability: 4
- Truth: 5
- Will-power: 4
- Wisdom: 4
Advice
The last topic someone asked me for advice on was about Meaningful work. She has been thinking about quitting her job in order to have time to figure out what she'd rather be doing. Perhaps she recognized that I value doing work that is meaningful, even in my present situation of trying to find lasting employment. I'm sure she believed I might have some advice that would help her, although since her scenario is still in progress we have yet to see.
Values and Stereotype Threat
When I think about my values, it brings to mind different challenges I've overcome and other positive experiences. I suppose reflecting on these values would help mediate stereotype threat if I recognize I feel it. Other exercises that I would turn to would be meditation/prayer, to find peace and move beyond the feelings.


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{% extends 'template-lab-4a.html' %} {% set mainClasses = 'nhsuk-u-padding-top-0' %} {% block pageTitle %} Symptoms - NHS {% endblock %} {% block beforeContent %} {% endblock %} {% block content %}
Bad breath (sometimes called halitosis) is very common. You can usually treat it yourself.
The best way of making sure you do not have bad breath is to keep your teeth, tongue and mouth clean.
gently brush your teeth and gums at least twice a day for 2 minutes
use a fluoride toothpaste
gently clean your tongue once a day using a tongue scraper or cleaner
clean between your teeth with interdental brushes or floss at least once a day
get regular dental check-ups
keep dentures clean and remove them at night
use sugar-free mints or chewing gum after having strong-smelling food and drinks
try using an antibacterial mouthwash or toothpaste
do not rinse your mouth with water straight after brushing your teeth
do not have lots of sugary foods and drinks
do not brush so hard your gums or tongue bleed
Causes of bad breath include:
Page last reviewed: 02 August 2019
Next review due: 02 August 2022


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| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | ||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Object org.catechis.JDOMSolution
public class JDOMSolution
| Field Summary | |
|---|---|
private org.jdom.Document |
doc
|
private EncodeString |
encoder
|
private java.lang.String |
file_name
|
private int |
index
|
private AllStatsHistory |
last_all_stats_history
This member saves the last statistics object to check it with the next one so that we dont put repeats in the histories list. |
private java.lang.String |
last_date
|
private java.lang.String |
last_word
|
private java.util.HashSet |
last_words
|
private java.lang.String |
level
|
private java.util.Vector |
log
This is our homegrown loggin system, because system outs dont come thru the JUnit and Ant setup. |
private java.lang.String |
org_level
|
private java.io.Reader |
reader
|
private Storage |
store
|
private java.util.Hashtable |
sub_elements
|
private java.util.Hashtable |
text_def_hash
|
private java.util.Hashtable |
word_levels
|
private java.util.Vector |
words
|
| Constructor Summary | |
|---|---|
JDOMSolution(org.jdom.Document _doc,
Storage _store)
This constructor was created for testing purposes. |
|
JDOMSolution(java.io.File file)
|
|
JDOMSolution(java.io.File _file,
Storage _store)
|
| Method Summary | |
|---|---|
void |
addHistory(AllStatsHistory all_stats_history)
We create a history element (in the most redundant way possbile) based on this xml schema: |
org.jdom.Element |
addHoweverManyToElement(org.jdom.Element elem,
java.util.Hashtable sub_elems)
(Note, This method also comes from the original CreateJDOMList in the com.businessglue.util. |
int |
addIds()
utility method to ad ids to old words |
void |
addSessionHistory(AllStatsHistory all_stats_history)
|
void |
addTestingOptiuons(java.lang.String word_id,
java.lang.String path,
java.lang.String encoding,
java.lang.String[] testing_options)
Add an array of options to the testing_options elment. |
private org.jdom.Element |
addTests(org.jdom.Element word,
Word word_obj)
// |
void |
addWord(Word word_obj)
We need to create word object to add to the file passed in at creation time. |
void |
addWTDKeys(java.lang.String wntd_file_key_r,
java.lang.String wntd_file_key_w,
long word_id)
Used to save a backup to test files for deletion later. |
private void |
adjustLevel(org.jdom.Element word,
java.lang.String type,
java.lang.String grade)
This method increments or decrements (using grade) the reading or writing level (using type) of a word element. |
void |
append(java.util.Vector v)
|
private void |
backupTests(java.util.List all_tests,
java.lang.String word_id,
java.lang.String user_id,
java.lang.String category_id)
|
void |
changeScore(java.lang.String date,
java.lang.String new_score)
Here we look in a test file to match the test date and then replace it with the new test score. |
java.lang.String |
changeWordLevel(WordTestMemory wtm,
WordTestResult wtr,
java.lang.String max_level)
This method changes the reading/writing level either up or down. |
private Word |
checkForNull(org.jdom.Element e)
|
int |
cleanAllTests()
CLEANING UTILITY |
int |
cleanAndBackupAllTests(java.lang.String user_id,
java.lang.String category_id)
Clean tests from words and back them up in individual word files. |
int |
cleanLevels()
CLEANING UTILITY |
int |
cleanLevels(int max_level)
CLEANING UTILITY |
void |
deleteWord(Word word_obj)
Delete word object |
void |
deleteWord1(Word word_obj)
Delete word object |
void |
editWord(Word old_word_obj,
Word new_word_obj)
Change a word object. |
void |
editWord2(Word old_word_obj,
Word new_word_obj,
java.lang.String path,
java.lang.String encoding)
Change a word object. |
private boolean |
filterWord(Word word,
WordFilter word_filter,
int index)
The actual filtering of word objects happens here. |
Word |
findWord(java.lang.String search_text)
Normal find word method. |
org.jdom.Element |
findWordElement(java.lang.String search_text)
Normal find word method. |
Word |
findWordFromDefinition(java.lang.String search_text)
Normal find word method. |
Word |
findWordFromId(java.lang.String search_id)
Find word by id. |
Word |
findWordWithoutTests(java.lang.String search_text)
Normal find word method. |
private java.lang.String |
getAdjustLevel(org.jdom.Element word,
java.lang.String type,
java.lang.String grade)
Copy of previous method except it returns the new level value |
private java.lang.String |
getAdjustLevel(org.jdom.Element word,
java.lang.String type,
java.lang.String grade,
java.lang.String test_level,
java.lang.String max_level,
java.lang.String original_level)
This is the third iteration of this method. |
java.lang.String |
getEarliestDate(java.lang.String date)
This method will return the date of the first test. |
java.util.Vector |
getFilteredWords(WordFilter word_filter)
This method, like its brother, gets the following from a Word object filtered/screened according to properties set in the WordFilter object passed in. |
java.util.Vector |
getHistory()
Unmarshall, unbind, get all the statistics history from an xml.hist file. |
private int |
getLevelMax(java.lang.String levels)
Helper method used in getFilteredWords. |
private int |
getLevelMin(java.lang.String levels)
Helper method used in getFilteredWords. |
java.util.Vector |
getLog()
|
java.util.Hashtable |
getOptionsHash()
This method reads a xml file with the format: option name=xxx value=xxx and returns these in a hastable. |
private boolean |
getRetiredElement(org.jdom.Element e)
This method is used in the getWordsForTest() method. |
java.util.Vector |
getSessionHistory()
Unmarshall, unbind, get all the statistics history from an xml.hist file. |
private Word |
getTestingOptions(Word word,
org.jdom.Element e)
|
java.util.Hashtable |
getWhateverHash(java.lang.String elements,
java.lang.String names,
java.lang.String values)
This method retrieves a list of option style elements from an xml file with the following format: |
java.util.Hashtable |
getWhateverKeyValHash(java.lang.String option,
java.lang.String _name,
java.lang.String _value)
This method takes an element name, two sub-elements names from which it constructs the key-value pairs stored in a hashtable. |
java.util.Vector |
getWords()
This methods retrieve the following from a Word object private String text; private String definition; private int writing_level; private int reading_level; date_of_entry test [] |
java.util.Vector |
getWordsForTest(java.lang.String category)
Same as above but with category/file name set. |
private Word |
isRetired(Word word,
org.jdom.Element e)
|
private boolean |
isUniqueHistory(AllStatsHistory all_stats_history)
|
java.lang.String |
recordWordScore(java.lang.String word,
java.lang.String grade,
java.lang.String test_file,
java.lang.String date,
java.lang.String type,
java.lang.String max_level,
java.lang.String org_level)
(Note, This method came from the original CreateJDOMList in the com.businessglue.util. |
java.lang.String |
recordWordScoreSearchById(long word_id,
java.lang.String word,
java.lang.String grade,
java.lang.String test_file,
java.lang.String date,
java.lang.String type,
java.lang.String max_level,
java.lang.String org_level)
Create a new "test" element with grade/file/date sub-elements. |
void |
replaceWord(java.lang.String original_text,
java.lang.String new_text,
java.lang.String new_def)
Replace word method replaces both word and definition properties. |
void |
replaceWordAndChangeTest(WordTestMemory wtm,
WordTestResult wtr)
Replace word method replaces both word and definition properties, and changes the reading/writing level either up or down. |
private void |
replaceWordLevel(org.jdom.Element word,
java.lang.String level,
java.lang.String type)
|
private java.lang.String |
updateWordLevel(org.jdom.Element word,
java.lang.String pass_fail,
java.lang.String word_text,
java.lang.String date,
java.lang.String type,
java.lang.String max_level,
java.lang.String org_level)
(Note, This method also comes from the original CreateJDOMList in the com.businessglue.util. |
private boolean |
wordIsAlreadyUpdated(java.lang.String word_text)
(Note, This method also comes from the original CreateJDOMList in the com.businessglue.util. |
void |
writeDocument(java.lang.String file_name)
Write document with no encoding. |
void |
writeDocument(java.lang.String file_name,
java.lang.String encoding)
Write document with encoding. |
| Methods inherited from class java.lang.Object |
|---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Field Detail |
|---|
private Storage store
private org.jdom.Document doc
private EncodeString encoder
private java.io.Reader reader
private java.util.Vector words
private java.util.Hashtable text_def_hash
private java.util.Hashtable sub_elements
private java.util.Hashtable word_levels
private java.lang.String last_date
private java.lang.String last_word
private java.util.HashSet last_words
private int index
private java.lang.String level
private java.lang.String org_level
private java.lang.String file_name
private AllStatsHistory last_all_stats_history
private java.util.Vector log
| Constructor Detail |
|---|
public JDOMSolution(org.jdom.Document _doc, Storage _store)
public JDOMSolution(java.io.File file)
public JDOMSolution(java.io.File _file, Storage _store)
| Method Detail |
|---|
public java.util.Hashtable getWhateverHash(java.lang.String elements, java.lang.String names, java.lang.String values)
This method retrieves a list of option style elements from an xml file with the following format:
elements ("word")
names content /names("text")
values content /values("definition")
/elements
THen is creates a Hash like this keys=names hash(key)=value.
public java.util.Hashtable getOptionsHash()
public java.util.Hashtable getWhateverKeyValHash(java.lang.String option, java.lang.String _name, java.lang.String _value)
public java.util.Vector getWords()
We had a problem when there was no reading or writing level present for some words, hence the two separate try blocks. This is a workaround, as the system should add these attributes, or make sure they are there in some other way.
private Word isRetired(Word word, org.jdom.Element e)
private Word getTestingOptions(Word word, org.jdom.Element e)
public java.util.Vector getWordsForTest(java.lang.String category)
private boolean getRetiredElement(org.jdom.Element e)
I remeber reading that using errors as a design feature was not a good idea. So should we add retired elements to every single word file when for a long time a word wont need it? Not sure about the performance trade offs when this class is bloated and horrible to begin with...
private int getLevelMin(java.lang.String levels)
Helper method used in getFilteredWords.
private int getLevelMax(java.lang.String levels)
Helper method used in getFilteredWords.
public java.util.Vector getFilteredWords(WordFilter word_filter)
IF any of the Word properties are null, then that property is set with a string saying null instead of risking a null object, or 0 if it is an int.
If filter properties are null, then it is assumed to be a default non-filtered property..
private boolean filterWord(Word word, WordFilter word_filter, int index)
Here are some of the properties we set in the WordFilter object.
word_filter.setStartIndex(0);
word_filter.setMinMaxRange("0-0");
word_filter.setType("reading");
word_filter.setCategory("october.xml");
If properties have not been set in the filter object, then they are skipped by using a try/catch block.
private Word checkForNull(org.jdom.Element e)
public void addHistory(AllStatsHistory all_stats_history)
We create a history element (in the most redundant way possbile) based on this xml schema:
This old version deosnt contain the last 24 hour period session information.
public void addSessionHistory(AllStatsHistory all_stats_history)
all_stats_history
- public java.util.Vector getHistory()
Unmarshall, unbind, get all the statistics history from an xml.hist file.
public java.util.Vector getSessionHistory()
Unmarshall, unbind, get all the statistics history from an xml.hist file.
public void replaceWord(java.lang.String original_text, java.lang.String new_text, java.lang.String new_def)
Replace word method replaces both word and definition properties.
Formerly we encoded the text and definitions here, but after commenting them out, it seemed to have no effect. Here is the code we used after the if (text.equals(original_text)) block: //String enc_name = encoder.encodeThis( name); //String enc_value = encoder.encodeThis(value);
public void replaceWordAndChangeTest(WordTestMemory wtm, WordTestResult wtr)
Replace word method replaces both word and definition properties, and changes the reading/writing level either up or down.
Just in case there are two different test with the same date and time (What are the chances of that, really? if the clock stops...?) we should really make sure the test name and not only the date match.
We have to enclose the test element checks in a try/catch block because the word may have no tests yet.
This method is not used right now, as we replace the word info and change the level in different methods, so that the user can choose to change the level, but not replace the text-definition, and vice versa.
public java.lang.String changeWordLevel(WordTestMemory wtm, WordTestResult wtr, java.lang.String max_level)
This method changes the reading/writing level either up or down.
The word test result must be changed from fail to pass to increment, and the opposite for decrements.
private void replaceWordLevel(org.jdom.Element word, java.lang.String level, java.lang.String type)
private java.lang.String getAdjustLevel(org.jdom.Element word, java.lang.String type, java.lang.String grade, java.lang.String test_level, java.lang.String max_level, java.lang.String original_level)
If the test is at level 0, it should only be incremented once.
If the test is 1 or higher, it gets incremented twice, once to bring it back to its pre-test level, and another to simulate a passed test.
private void adjustLevel(org.jdom.Element word, java.lang.String type, java.lang.String grade)
This method increments or decrements (using grade) the reading or writing level (using type) of a word element.
The level is incremented or decremented twice because if the user failed a test for a word at level 1, then the word is now at level 0, so to reverse the test we need to increment it up 2 to level 2. However, if the original level is only 0, then we only want to add 1, because words arnt allowed to go below 0.
If the original level was 0 or 1, then the current level would be the same: 0.
private java.lang.String getAdjustLevel(org.jdom.Element word, java.lang.String type, java.lang.String grade)
public Word findWord(java.lang.String search_text)
Normal find word method. The argument is the text child element of a word element.
public org.jdom.Element findWordElement(java.lang.String search_text)
Normal find word method. The argument is the text child element of a word element.
public java.lang.String getEarliestDate(java.lang.String date)
public Word findWordFromDefinition(java.lang.String search_text)
Normal find word method. The argument is the text child element of a word element.
public Word findWordFromId(java.lang.String search_id)
Find word by id.
public Word findWordWithoutTests(java.lang.String search_text)
Normal find word method. The argument is the text child element of a word element.
public void changeScore(java.lang.String date, java.lang.String new_score)
Were looking to change an element like this one:
Note the responisibilty for creating the new test score happens in the Struts Action class ChangeUpdateAction, where it knows how many words are in the test, and what the pass/fail of all the other words is.
public void addWord(Word word_obj)
The reading and writing levels are fixed at 0, but it would be easy to let the user dictate other leves, as well as other elements.
private org.jdom.Element addTests(org.jdom.Element word, Word word_obj)
public void editWord(Word old_word_obj, Word new_word_obj)
Change a word object.
This has been a persitently annoying error. When we first made this method over a year ago, if didnt work. Because content management is not the purpose of this package, we let is slide. But being able to edit words when it is most needed, such as after a test seems too necessary to avoid.
So we took another look and got the test in the FileStorageTest working.
However, the JDOMSolution test continued to fail.
Thats why the second method was created, to experiment with recording the document within the edit method.
public void editWord2(Word old_word_obj, Word new_word_obj, java.lang.String path, java.lang.String encoding)
Change a word object.
See editWord for more notes.
public void deleteWord1(Word word_obj)
Delete word object
public void deleteWord(Word word_obj)
Delete word object
public java.lang.String recordWordScore(java.lang.String word, java.lang.String grade, java.lang.String test_file, java.lang.String date, java.lang.String type, java.lang.String max_level, java.lang.String org_level)
(Note, This method came from the original CreateJDOMList in the com.businessglue.util. package.)
Here we create a new "test" element with grade/file/date sub-elements.
We also update each individual word level dependant on type.
Note: We cyclce thru the word list again here. It would be nice to merge this with the other previous cycle when the words are graded. Maybe this is not possible because what we use is a hashmap, no a reference to the xml file. Maybe we could bind an XPath reference to the key, or use and array...?
public java.lang.String recordWordScoreSearchById(long word_id, java.lang.String word, java.lang.String grade, java.lang.String test_file, java.lang.String date, java.lang.String type, java.lang.String max_level, java.lang.String org_level)
Create a new "test" element with grade/file/date sub-elements.
We also update each individual word level dependant on type.
Note: We cycle thru the word list again here. It would be nice to merge this with the other previous cycles when the words are graded. Maybe this is not possible because what we use is a hashmap, no a reference to the xml file. Maybe we could bind an XPath reference to the key, or use and array...?
public int addIds()
private java.lang.String updateWordLevel(org.jdom.Element word, java.lang.String pass_fail, java.lang.String word_text, java.lang.String date, java.lang.String type, java.lang.String max_level, java.lang.String org_level)
(Note, This method also comes from the original CreateJDOMList in the com.businessglue.util. package.)
This method changes the 'level' element in the words file and adds the result to the word_levels Hashmap for later retrieval.
Without the updateWordLevel method, we had the levels updated an arbitrary amount of times per test, when only once was desired. It's because the test results come in as a Hastable, and we cycle trhu that hashtable looking for those words in the xml file. So for each word, we have to cycle again thru the xml file looking for that word.
There must be a better way of doing this, so the updateWordLevel method is a workaround to get things started with correct behaviour.
private boolean wordIsAlreadyUpdated(java.lang.String word_text)
(Note, This method also comes from the original CreateJDOMList in the com.businessglue.util. package.)
Because we had the same words being updated numerous times, this method uses a Hashset whith the method.contains(word) to exclude further updates.
THis method should be considerd a workaround, as there is definately a better way.
public org.jdom.Element addHoweverManyToElement(org.jdom.Element elem, java.util.Hashtable sub_elems)
(Note, This method also comes from the original CreateJDOMList in the com.businessglue.util. package.)
This method adds an element with an arbitrary number of sub elements which are passed in as a hashtable or key-value pairs
public void addWTDKeys(java.lang.String wntd_file_key_r, java.lang.String wntd_file_key_w, long word_id)
wntd_file_key_r
- Word's Next Test Date file key in tests/lists directory.wntd_file_key_w
- word_id
- public void addTestingOptiuons(java.lang.String word_id, java.lang.String path, java.lang.String encoding, java.lang.String[] testing_options)
word_id
- path
- encoding
- testing_options
- public void writeDocument(java.lang.String file_name)
Write document with no encoding.
public void writeDocument(java.lang.String file_name, java.lang.String encoding)
Write document with encoding.
XMLOutputter(java.lang.String indent, boolean newlines, java.lang.String encoding)
public int cleanAllTests()
public int cleanAndBackupAllTests(java.lang.String user_id, java.lang.String category_id)
private void backupTests(java.util.List all_tests, java.lang.String word_id, java.lang.String user_id, java.lang.String category_id)
public int cleanLevels()
public int cleanLevels(int max_level)
private boolean isUniqueHistory(AllStatsHistory all_stats_history)
public void append(java.util.Vector v)
public java.util.Vector getLog()
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VASE is developed at the Centre for Molecular and Biomolecular Informatics (CMBI) department of Bioinformatics at the Radboud University in Nijmegen by C. Baakman<EMAIL_ADDRESS>and J. Black.
VASE uses the structures from the Protein Databank (PDB) where available. Alignment information is taken from the stockholm files at CMBI, whenever an official PDB structure is requested. For user-submitted structures, stockholm files are generated using CMBI's webservice.
VASE uses JMOL to create a 3D representation of protein structures.
VASE is open source and available for download at GitHub.


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Many elements have a natural block state or inline state. what does this mean?
Inline means that the items are in a line. They do not have padding, they display everything in the same line. They're agile, but they don't really have a border. They're like a speedster in a video game. You can have loads of them, but sometimes they just aren't appropriate for the elements. Haveing all the paragraphs inline wouldn't look so good, right?
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@misc{thouvenin2020parallel, title={Parallel faceted imaging in radio interferometry via proximal splitting (Faceted HyperSARA): when precision meets scalability}, author={Pierre-Antoine Thouvenin and Abdullah Abdulaziz and Ming Jiang and Arwa Dabbech and Audrey Repetti and Adrian Jackson and Jean-Philippe Thiran and Yves Wiaux}, year={2020}, eprint={2003.07358}, archivePrefix={arXiv}, primaryClass={astro-ph.IM} }


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--- title: "Panel Data and Fixed Effects" subtitle: "Our first steps in Panel Data and Fixed Effects with R" type: book weight: 5 output: blogdown:html_page: theme: journal highlight: tango df_print: paged toc: yes toc_float: collapsed: false ---
Welcome to our ninth tutorial for the Statistics II: Statistical Modeling & Causal Inference (with R) course.
During this week’s lecture you were introduced to Panel Data and Fixed Effects.
In this lab session we will:
janitor::tabyl()
ggplot2
lm()
and the de-meaning approach with plm()
)After all the very valuable output you have generated in the past weeks, you have become a sensation within the policy analysis world. You are hired as an outside consultant by the Organization of Economic Non-Cooperation for Development (OENCD), they are interested in studying the effect of a carbon tax on national carbon dioxide emissions per capita. You are provided with data for the twenty-members of the organization from 2009 to 2019. The data can be called a balanced panel based on the description given in the lecture (i.e. each panel member is observed every year)
# These are the libraries we will use today. Make sure to install them in your console in case you have not done so previously.
set.seed(42) #for consistent results
library(dplyr) # to wrangle our data
library(tidyr) # to wrangle our data - pivot_longer()
library(lubridate) # for working with dates-times in a more intuitive manner
library(ggplot2) # to render our graphs
library(readr) # for loading the .csv data
library(kableExtra) # to render better formatted tables
library(stargazer) # for formatting your model output
library(janitor) # for data management and tabyl()
library(lmtest) # to gather our clustered standard errors - coeftest()
library(plm) # to gather our clustered standard errors - vcovHC() and plm()
carbon_tax_df <- readr::read_csv("https://raw.githubusercontent.com/seramirezruiz/stats-ii-lab/master/Session%207/data/carbon_tax_df.csv") # simulated data
Our dataset carbon_tax_df, contains the following information:
country_name
: Name of the countrycountry_code
: Three-letter country codeyear
: Yeartax
: Dummy for whether the carbon tax was in placeincome_class
: Categorical variable with income label (Low to High)co2_per_capita
: carbon dioxide emissions per capita in metric tons (T)We can use what we have learned about the janitor::tabyl()
function to check how many observations we have for each of the countries:
carbon_tax_df %>%
janitor::tabyl(country_name) %>%
janitor::adorn_pct_formatting(digits = 1) %>%
knitr::kable(col.names = c("Country", "N", "Percent, %")) %>%
kableExtra::kable_styling()
| Country | N | Percent, % |
|---|---|---|
| Adjikistan | 11 | 8.3% |
| Borovia | 11 | 8.3% |
| Carpania | 11 | 8.3% |
| Corinthia | 11 | 8.3% |
| Freedonia | 11 | 8.3% |
| Glenraven | 11 | 8.3% |
| Khemed | 11 | 8.3% |
| Laurania | 11 | 8.3% |
| Parano | 11 | 8.3% |
| Ron | 11 | 8.3% |
| Rumekistan | 11 | 8.3% |
| Transia | 11 | 8.3% |
We can also explore how many countries had a tax
in place every year.
carbon_tax_df %>%
janitor::tabyl(tax, year) %>%
janitor::adorn_totals("row") %>%
janitor::adorn_percentages("col") %>%
janitor::adorn_pct_formatting(digits = 1) %>%
janitor::adorn_ns() %>%
knitr::kable() %>%
kableExtra::kable_styling() %>%
kableExtra::add_header_above(c("", "Year" = 11))
| tax | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 100.0% (12) | 100.0% (12) | 83.3% (10) | 75.0% (9) | 66.7% (8) | 66.7% (8) | 41.7% (5) | 33.3% (4) | 33.3% (4) | 33.3% (4) | 41.7% (5) |
| 1 | 0.0% (0) | 0.0% (0) | 16.7% (2) | 25.0% (3) | 33.3% (4) | 33.3% (4) | 58.3% (7) | 66.7% (8) | 66.7% (8) | 66.7% (8) | 58.3% (7) |
| Total | 100.0% (12) | 100.0% (12) | 100.0% (12) | 100.0% (12) | 100.0% (12) | 100.0% (12) | 100.0% (12) | 100.0% (12) | 100.0% (12) | 100.0% (12) | 100.0% (12) |
We can further explore how many countries had a tax
in place every year at the income_class
cluster:
carbon_tax_df %>%
janitor::tabyl(tax, year, income_class) %>%
janitor::adorn_percentages("col") %>%
janitor::adorn_pct_formatting(digits = 1) %>%
janitor::adorn_ns()
## $High
## tax 2009 2010 2011 2012 2013 2014 2015
## 0 100.0% (3) 100.0% (3) 66.7% (2) 66.7% (2) 33.3% (1) 33.3% (1) 33.3% (1)
## 1 0.0% (0) 0.0% (0) 33.3% (1) 33.3% (1) 66.7% (2) 66.7% (2) 66.7% (2)
## 2016 2017 2018 2019
## 33.3% (1) 33.3% (1) 33.3% (1) 33.3% (1)
## 66.7% (2) 66.7% (2) 66.7% (2) 66.7% (2)
##
## $`High-Middle`
## tax 2009 2010 2011 2012 2013 2014 2015
## 0 100.0% (3) 100.0% (3) 66.7% (2) 66.7% (2) 66.7% (2) 66.7% (2) 0.0% (0)
## 1 0.0% (0) 0.0% (0) 33.3% (1) 33.3% (1) 33.3% (1) 33.3% (1) 100.0% (3)
## 2016 2017 2018 2019
## 0.0% (0) 0.0% (0) 0.0% (0) 33.3% (1)
## 100.0% (3) 100.0% (3) 100.0% (3) 66.7% (2)
##
## $Low
## tax 2009 2010 2011 2012 2013 2014
## 0 100.0% (3) 100.0% (3) 100.0% (3) 100.0% (3) 100.0% (3) 100.0% (3)
## 1 0.0% (0) 0.0% (0) 0.0% (0) 0.0% (0) 0.0% (0) 0.0% (0)
## 2015 2016 2017 2018 2019
## 100.0% (3) 66.7% (2) 66.7% (2) 66.7% (2) 66.7% (2)
## 0.0% (0) 33.3% (1) 33.3% (1) 33.3% (1) 33.3% (1)
##
## $`Low-Middle`
## tax 2009 2010 2011 2012 2013 2014 2015
## 0 100.0% (3) 100.0% (3) 100.0% (3) 66.7% (2) 66.7% (2) 66.7% (2) 33.3% (1)
## 1 0.0% (0) 0.0% (0) 0.0% (0) 33.3% (1) 33.3% (1) 33.3% (1) 66.7% (2)
## 2016 2017 2018 2019
## 33.3% (1) 33.3% (1) 33.3% (1) 33.3% (1)
## 66.7% (2) 66.7% (2) 66.7% (2) 66.7% (2)
As we can see, the three-way table creates a list containing the different combinations which are accesible with the $
operator. We can do a little bit of code gymnastics to generate our nicely formated output by saving the janitor::tabyl()
output into an object and printing each of the tables individually.
three_way_tab <- carbon_tax_df %>%
janitor::tabyl(tax, year, income_class) %>%
janitor::adorn_percentages("col") %>%
janitor::adorn_pct_formatting(digits = 1) %>%
janitor::adorn_ns()
| tax | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 100.0% (3) | 100.0% (3) | 66.7% (2) | 66.7% (2) | 33.3% (1) | 33.3% (1) | 33.3% (1) | 33.3% (1) | 33.3% (1) | 33.3% (1) | 33.3% (1) |
| 1 | 0.0% (0) | 0.0% (0) | 33.3% (1) | 33.3% (1) | 66.7% (2) | 66.7% (2) | 66.7% (2) | 66.7% (2) | 66.7% (2) | 66.7% (2) | 66.7% (2) |
| tax | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 100.0% (3) | 100.0% (3) | 66.7% (2) | 66.7% (2) | 66.7% (2) | 66.7% (2) | 0.0% (0) | 0.0% (0) | 0.0% (0) | 0.0% (0) | 33.3% (1) |
| 1 | 0.0% (0) | 0.0% (0) | 33.3% (1) | 33.3% (1) | 33.3% (1) | 33.3% (1) | 100.0% (3) | 100.0% (3) | 100.0% (3) | 100.0% (3) | 66.7% (2) |
| tax | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 100.0% (3) | 100.0% (3) | 100.0% (3) | 66.7% (2) | 66.7% (2) | 66.7% (2) | 33.3% (1) | 33.3% (1) | 33.3% (1) | 33.3% (1) | 33.3% (1) |
| 1 | 0.0% (0) | 0.0% (0) | 0.0% (0) | 33.3% (1) | 33.3% (1) | 33.3% (1) | 66.7% (2) | 66.7% (2) | 66.7% (2) | 66.7% (2) | 66.7% (2) |
| tax | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 100.0% (3) | 100.0% (3) | 100.0% (3) | 100.0% (3) | 100.0% (3) | 100.0% (3) | 100.0% (3) | 66.7% (2) | 66.7% (2) | 66.7% (2) | 66.7% (2) |
| 1 | 0.0% (0) | 0.0% (0) | 0.0% (0) | 0.0% (0) | 0.0% (0) | 0.0% (0) | 0.0% (0) | 33.3% (1) | 33.3% (1) | 33.3% (1) | 33.3% (1) |
ggplot(carbon_tax_df, aes(x = factor(year),
y= co2_per_capita,
color = factor(tax))) +
geom_point() + #create scatterplot
labs(title = "Exploratory plot of CO2 emissions per capita",
x = "Year",
y = "CO2 emissions in metric tons (T)",
color = "Carbon tax") +
theme_minimal() +
theme(legend.position="bottom") + #move legend to the bottom
scale_color_manual(name = " ", # changes to fill dimension
values = c("#a7a8aa", "#cc0055"),
labels = c("Control", "Treatment"))
carbon_tax_df %>%
dplyr::mutate(year_as_date = lubridate::ymd(year, truncated = 2L), #turning numeric to date format
income_class = factor(carbon_tax_df$income_class,
levels = c("High", "High-Middle",
"Low-Middle", "Low"))) %>% #reordering the factors
ggplot(., aes(x = year_as_date,
y= co2_per_capita,
color = factor(tax))) +
geom_point() + #create scatterplot
geom_path(aes(group = 1)) + #to render consecutive lines disregarding the tax (you will likely use geom_line() for the assignment)
facet_wrap(country_name~income_class) + #to split plot into panels based on this dimension
scale_x_date(date_labels = "%Y") + #telling ggplot that we want the ticks to be the years in the dates
labs(title = "Exploratory plot of CO2 emissions per capita",
x = "Year",
y = "CO2 emissions in metric tons (T)",
color = "Carbon tax") +
theme_bw() +
scale_color_manual(name = " ", # changes to fill dimension
values = c("#a7a8aa", "#cc0055"),
labels = c("Control", "Treatment"))
Note: The exploratory data analysis portions of our scripts will not transfer directly to this week’s assignment; however, they will be very useful for the extension portion of your final replication paper. Summarizing, graphing, and exploring your data will be critical to discover patterns, to spot anomalies, and to check assumptions
We have seen during the lecture that balanced panel data can help us decompose the error term. With a balanced panel we can capture all unobserved, unit- and time-specific factors.
In the example at hand, we can think of unit-specific factors as characteristics of individual countries that are constant over time (e.g. a country that just loves big pick-up trucks). We can also think about time-specific factors that affect all countries (e.g. global economic shocks).
We can formulate this as:
\[Y_{it} = β_0 + β_1D_{it} + \theta_{i} + \delta_t + \upsilon_{it}\]
where \(\theta_i\) reflects the time-invariant traits of the units, \(\delta_t\) reflects the time-specific factors that affect everyone and \(\upsilon_{it}\) is the idiosyncratic error
We will move forward by creating three models:
co2_per_capita
on tax
.naive_carbon <- lm(co2_per_capita ~ tax, data = carbon_tax_df)
pooled_naive_carbon <- plm(co2_per_capita ~ tax, data = carbon_tax_df, model = "pooling")
stargazer::stargazer(naive_carbon, type = "text")
##
## ===============================================
## Dependent variable:
## ---------------------------
## co2_per_capita
## -----------------------------------------------
## tax -6.261***
## (0.566)
##
## Constant 10.627***
## (0.352)
##
## -----------------------------------------------
## Observations 132
## R2 0.485
## Adjusted R2 0.481
## Residual Std. Error 3.166 (df = 130)
## F Statistic 122.394*** (df = 1; 130)
## ===============================================
## Note: *p<0.1; **p<0.05; ***p<0.01
stargazer::stargazer(pooled_naive_carbon, type = "text")
##
## ========================================
## Dependent variable:
## ---------------------------
## co2_per_capita
## ----------------------------------------
## tax -6.261***
## (0.566)
##
## Constant 10.627***
## (0.352)
##
## ----------------------------------------
## Observations 132
## R2 0.485
## Adjusted R2 0.481
## F Statistic 122.394*** (df = 1; 130)
## ========================================
## Note: *p<0.1; **p<0.05; ***p<0.01
What do we see here?
This model is telling us that on average, the \(CO_2\) emmissions per capita are reduced by 6.2 metric tons when a carbon tax is put in place. Still, after all the work we have done throughout the semester, we understand that there may be a plethora of factors that could be skewing the results of this bivariate regression.
We will learn two ways of gathering unit- and time-fixed effects in R:
First, we will perform Least Squares Dummy Variables (LSDV) estimation with lm(), where we essentially get an individual estimate for each unit.
Second, we will run our model with plm(), which will do the same mechanics, yet it will not estimate each of the units intercepts (because it relies on the “de-meaning” approach).
lsdv_unit_fe <- lm(co2_per_capita ~ tax + country_name, data = carbon_tax_df)
unit_fe <- plm(co2_per_capita ~ tax,
data = carbon_tax_df,
index = c("country_name"), # unit
effect = "individual",
model = "within")
stargazer::stargazer(lsdv_unit_fe, type = "text")
##
## ==================================================
## Dependent variable:
## ---------------------------
## co2_per_capita
## --------------------------------------------------
## tax -4.436***
## (0.474)
##
## country_nameBorovia 1.507
## (0.912)
##
## country_nameCarpania 5.106***
## (0.912)
##
## country_nameCorinthia 6.434***
## (0.887)
##
## country_nameFreedonia 6.120***
## (0.903)
##
## country_nameGlenraven 0.372
## (0.951)
##
## country_nameKhemed -0.672
## (0.951)
##
## country_nameLaurania 1.533
## (0.937)
##
## country_nameParano 3.693***
## (0.887)
##
## country_nameRon 2.715***
## (0.912)
##
## country_nameRumekistan 7.431***
## (0.887)
##
## country_nameTransia 1.883*
## (0.968)
##
## Constant 6.912***
## (0.627)
##
## --------------------------------------------------
## Observations 132
## R2 0.797
## Adjusted R2 0.776
## Residual Std. Error 2.079 (df = 119)
## F Statistic 38.844*** (df = 12; 119)
## ==================================================
## Note: *p<0.1; **p<0.05; ***p<0.01
stargazer::stargazer(unit_fe, type = "text")
##
## ========================================
## Dependent variable:
## ---------------------------
## co2_per_capita
## ----------------------------------------
## tax -4.436***
## (0.474)
##
## ----------------------------------------
## Observations 132
## R2 0.424
## Adjusted R2 0.366
## F Statistic 87.716*** (df = 1; 119)
## ========================================
## Note: *p<0.1; **p<0.05; ***p<0.01
What do we see here?
Adding unit-level fixed effects to the model, i.e. accounting for unobserved, time-invariant characteristics of countries and only focusing on within-state variation, an increase in the imposition of a carbon tax reduces \(CO_2\) per capita emissions by 4.44 metric tons. Once we have captured the variation between countries, we can see that our results from the naive model were substantially biased. We can still try to capture the time-specific portion of the error.
The results from the Least Squares Dummy Variables (LSDV) estimation are read in reference to a baseline. In this case, the constant is representing the intercept for Adjikistan. We can utilize the individual slopes for each country to say that Freedonians emit on average 6.12 more metric tons of \(CO_2\) per capita than Adjikistanians.
We will perform our regressions with Least Squares Dummy Variables (LSDV) estimation with lm() and our simplified way with plm().
lsdv_unit_time_fe <- lm(co2_per_capita ~ tax + country_name + factor(year),
data = carbon_tax_df)
unit_time_fe <- plm(co2_per_capita ~ tax,
data = carbon_tax_df,
index = c("country_name", "year"), # unit and time
model = "within",
effect = "twoways")
stargazer::stargazer(lsdv_unit_time_fe, type = "text")
##
## ==================================================
## Dependent variable:
## ---------------------------
## co2_per_capita
## --------------------------------------------------
## tax -3.908***
## (0.280)
##
## country_nameBorovia 1.267***
## (0.418)
##
## country_nameCarpania 4.866***
## (0.418)
##
## country_nameCorinthia 6.434***
## (0.398)
##
## country_nameFreedonia 5.928***
## (0.410)
##
## country_nameGlenraven -0.012
## (0.447)
##
## country_nameKhemed -1.056**
## (0.447)
##
## country_nameLaurania 1.196***
## (0.436)
##
## country_nameParano 3.693***
## (0.398)
##
## country_nameRon 2.474***
## (0.418)
##
## country_nameRumekistan 7.431***
## (0.398)
##
## country_nameTransia 1.450***
## (0.459)
##
## factor(year)2010 -4.697***
## (0.381)
##
## factor(year)2011 1.890***
## (0.384)
##
## factor(year)2012 -3.061***
## (0.387)
##
## factor(year)2013 0.106
## (0.392)
##
## factor(year)2014 -1.878***
## (0.392)
##
## factor(year)2015 -3.018***
## (0.414)
##
## factor(year)2016 -3.292***
## (0.424)
##
## factor(year)2017 -0.963**
## (0.424)
##
## factor(year)2018 -2.488***
## (0.424)
##
## factor(year)2019 -1.399***
## (0.414)
##
## Constant 8.621***
## (0.396)
##
## --------------------------------------------------
## Observations 132
## R2 0.963
## Adjusted R2 0.955
## Residual Std. Error 0.933 (df = 109)
## F Statistic 127.305*** (df = 22; 109)
## ==================================================
## Note: *p<0.1; **p<0.05; ***p<0.01
stargazer::stargazer(unit_time_fe, type = "text")
##
## ========================================
## Dependent variable:
## ---------------------------
## co2_per_capita
## ----------------------------------------
## tax -3.908***
## (0.280)
##
## ----------------------------------------
## Observations 132
## R2 0.641
## Adjusted R2 0.568
## F Statistic 194.229*** (df = 1; 109)
## ========================================
## Note: *p<0.1; **p<0.05; ***p<0.01
What do we see here?
Now in addition to adding unit-level fixed effects to the model, we control for time-specific factors that affect the global per capita \(CO_2\) emissions. The results suggest that the effect of a carbon-tax leads to a decrease \(CO_2\) emissions of 3.91 metric tons per capita.
In our models our assumption for the errors is \(υ_{it} ∼ iid(0, σ_υ^{2})\).
With longer panels, serial correlation between errors is a problem:
\(Cor(υ_{it}, υ_i(t−1))≠0\).
We can test for serial correlation in our time and unit FE specification model, as such:
pbgtest(unit_time_fe, order = 2)
##
## Breusch-Godfrey/Wooldridge test for serial correlation in panel models
##
## data: co2_per_capita ~ tax
## chisq = 0.25101, df = 2, p-value = 0.8821
## alternative hypothesis: serial correlation in idiosyncratic errors
In here, the null hypothesis is there is serial correlation of any order up to 2 (i.e., first- and second-order). In this case, we do not find any serial correlation, so we do not need to correct our standard errors manually. If we were to find serial correlation, we could introduce robust standard errors with a similar syntax to the one used last week for clustered standard errors:
model_with_robust_se <- coeftest(unit_time_fe, vcov=vcovHC(unit_time_fe, type = "sss"))
You report back to the Organization of Economic Non-Cooperation for Development (OENCD). Based on your analysis of the data at hand, you suggest that the implementation of a carbon tax does have an effect on national carbon dioxide emissions per capita. Your results show that a carbon tax reduces \(CO_2\) emissions by 3.91 metric tons per capita.
Your results are welcomed internationally and all states move forward with the measure.


Call of Duty: Modern Warfare Update 1.09 Nerfs Already-Nerfed 725 Shotgun
by Marco CocomelloCall of Duty: Modern Warfare is facing a shotgun issue at the moment. If you got killed by someone on the other side of the map, it could be two things, a sniper or the 725 shotgun which has an insane amount of range. Activision and Infinity Ward are working hard to balance the gun and the latest update attempts just that. Keep in mind that the 725 was nerfed just last week but clearly it was not enough.
RELATED: The Game Awards 2019 Nominee List Revealed as Voting Opens
The Call of Duty: Modern Warfare 1.09 update release notes highlight the changes to not only the 725 shotgun but a range of other weapons too. This patch marks the third nerf for the shotgun to date.
Take a look at the full Call of Duty: Modern Warfare update 1.09 patch notes below;
Call of Duty: Modern Warfare Update 1.09
General Fixes
- Special Operations: Fix for an issue where a player would see no objective after retrying a mission after spectating (Operation Paladin)
- CDL: Fix for rulesets in Search and Destroy where Field Upgrades were disabled
- Fix for an exploit where players could duplicate their killstreaks (“Fix for various exploits”)
- Fix for the “Blue V” Optic challenge not displaying the proper text description
- Fix misspelling of “trophy”
Ground War:
- Fixed a bug that could cause the filter on the respawn selection screen to stay on screen when spawning back in
- Fix for an issue where the Select Loadout screen would keep reappearing after already selecting a loadout and attempting to spawn back in
Missions/Challenges:
The following challenges have been fixed in
- “Infiltrator”
- “Warrior’s Code”
- “Aggression”
- “Dominator”
- “Munitions”
- Officer progression “Launch Destroys”
- Officer progression “Heartbreaker”
- Officer progression ”Precision Airstrike”
- Officer progression: “Karma”
- Officer progression “Close and Personal”
Call of Duty: Modern Warfare Weapons:
AUG 5.56 Caliber conversion
- Increasing close range damage
- Increasing mid damage range and reduced chest multiplier
725
- Small reduction to base weapon damage range
- Significantly reduced the damage range added by attachments
- Small hips spread increase
- Reduced effective damage at the hip
Model 680
- Slight reduction of damage range with all range-extending attachments
Be sure to check out our full Modern Warfare review here.


Arduino is typically programmed with Arduino IDE with a set of C/C++ functions. The canonical blink sketch which turns a led on/off every 1 second looks like:
void setup() {
pinMode(13, OUTPUT); // initialize digital pin 13 as an output
}
void loop() {
digitalWrite(13, HIGH); // turn the LED on (HIGH is the voltage level)
delay(1000); // wait for a second
digitalWrite(13, LOW); // turn the LED off by making the voltage LOW
delay(1000); // wait for a second
}
pinMode
, digitalWrite
and delay
functions are defined by the Arduino
standard library. For the most part this works pretty well, and there are plenty
of libraries and example sketches.
For the sake of getting close to the metal, let’s write the above sketch in assembly instead. Before we do that we need to install couple depedencies. Assuming you’re on OSX and you have brew install you’ll need to do:
brew tap osx-cross/avr
brew install avr-libc avrdude
Here’s an example from
here.
Save it as simple_led_blink.s
.equ RAMEND, 0x8ff
.equ SREG, 0x3f
.equ SPL, 0x3d
.equ SPH, 0x3e
.equ PORTB, 0x05
.equ DDRB, 0x04
.equ PINB, 0x03
.org 0
rjmp main
main:
ldi r16,0 ; reset system status
out SREG,r16 ; init stack pointer
ldi r16,lo8(RAMEND)
out SPL,r16
ldi r16,hi8(RAMEND)
out SPH,r16
ldi r16,0x20 ; set port bits to output mode
out DDRB,r16
clr r17
mainloop:
eor r17,r16 ; invert output bit
out PORTB,r17 ; write to port
call wait ; wait some time
rjmp mainloop ; loop forever
wait:
push r16
push r17
push r18
ldi r16,0x40 ; loop 0x400000 times
ldi r17,0x00 ; ~12 million cycles
ldi r18,0x00 ; ~0.7s at 16Mhz
_w0:
dec r18
brne _w0
dec r17
brne _w0
dec r16
brne _w0
pop r18
pop r17
pop r16
ret
Explaining what the above assembly code does is out of scope of this small blog post.
Now connect your Arduino to your computer with usb and run the following commands from your terminal:
avr-as -g -mmcu=atmega328p -o simple_led_blink.o simple_led_blink.s
avr-ld -o simple_led_blink.elf simple_led_blink.o
avr-objcopy -O ihex -R .eeprom simple_led_blink.elf simple_led_blink.hex
avrdude -p atmega328p -c arduino -P /dev/tty.usbmodem14221 -b 115200 -D -U flash:w:simple_led_blink.hex:i
You’ll most likely need to change /dev/tty.usbmodem14221
to whatever usb port
your Arduino is connected to. To find which one run ls /deve/tty.*
and pick
the one without Bluetooth
in the file name.
Most of the above instructions are from here, frankly without it this process would’ve been much longer and way more tedious.


Retopology for Level Design (low-poly)
by Simon Gangl25games writes:
Hey pixels.
How do you create your levels for game dev? I guess there are many ways to do 3d level design. However, there will be a blocking in the beginning before you start with your detailed mesh. You need to plan the structure of your level and test it - again and again!
When you are finished with the blocking, it is time to start with the detailed mesh modeling... This is my personal method to do an retopology for an low-poly level design (organic structure).
Maybe there will be something which will help you as well :)
Cheers!


LENINGRAD COWBOYS GO AMERICA A film review by Lons Ponschock Copyright 1995 Lons Ponschock
A film by Aki Kaurismaki Stars a truly International Cast (1989) PG-13, 80 mins. Cameos Jim Jarmusch, Duke Robillard
It's got accordions in it. There's cool points for that. And subtitles but not many and ... what else? Oh yeah, the hair. The hair is really good. And the shoes are excellent: just the right touch.
LENINGRAD COWBOYS is a hoot.
If Richard Lester (A HARD DAY'S NIGHT, HELP!) were Finnish, he'd be Aki Kaurismaki. And remember, we have a lot of Finnish brethren and sistren around here. I run into the Valmet folks all the time. Here is an example of Finnish humor at it's most deadpan farcical best: a Monty Python meets the Flying Burrito Brothers.

Trust me, LENINGRAD COWBOYS is a lot of fun ... a road movie with music and Jim Jarmusch (MYSTERY TRAIN, A NIGHT ON EARTH) in a used car lot. The band goes from Russia to New York, New Orleans, Texas and finally Mexico where the accordions and all that come in handy again. I have tried to explain my love of accordions often whether it be Conjunto, Zydeco or Oompah music, but alas, accordions are apparently for discriminating tastes.
I usually watch these vids by myself. The sign of a good vid is if you can pop your fingers and laugh out loud by yourself. A really good film like this one will remove all the inhibitions associated with self-entertainment. ;-)
Well-directed with a style bordering ... no, right *in* the country of the absurd LENINGRAD COWBOYS GO AMERICA could be a modern classic if somebody saw it besides me. I guess it's the kind of show that is not recognized by the slackers because it is too low brow and not appreciated by the "film buffs" because ... well ... no one else saw it *before* them.
So have I given you enough reason to go rent this piece?
I hope so.
You can watch it and then amaze your friends with your subtle cool taste and international erudition. But mostly it's just plain good fun.
-- lon
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