Don’t panic
The best year-round temperature is a warm heart and a cool head
It could be better, but it’s good enough.
You will find a thing. It may be important
Your reality check about to bounce.
Two days from now, tomorrow will be yesterday.
When chosen for jury duty, tell judge fortune cookie say “guilty!”
Stop eating now. Food poisoning no fun.
You are cleverly disguised as responsible adult.
Drive like hell, you will get there.

Okay to look at past and future. Just don’t stare.
Soup was secret family recipe made from toad. Hope you liked!
You will soon have an out of money experience.
He who dies with most toys, still dies.
Person who rests on laurels gets thorn in backside.
Two can live as cheaply as one, for half as long.
Life is a sexually transmitted condition.
Give person fish, he eat for day. Teach person to fish, he always smell funny.

Look before you leap. Or wear a parachute.
The end is near, might as well have dessert.
This fortune no good. Try another.
Wise husband is one who thinks twice before saying nothing.
Marriage lets you annoy one special person for the rest of your life
Run
Make love, not bugs
You will read this and say “Geez! I could come up with better fortunes than that!”
I cannot help you, for I’m just a cookie
The fortune you seek, is in another cookie
Don’t eat any Chinese food today or you’ll be sick!
About time I got out of that cookie!
 Congratulations
Made in the USA


---
title: "Problem set 5"
linktitle: "PS 5"
date: "2020-10-26"
due_date: "2020-11-06"
due_time: "02:20 PM"
menu:
assignment:
parent: Problem Sets
weight: 5
type: docs
weight: 2
editor_options:
chunk_output_type: console
---
Exercises
- The following equation describes the median housing price in a community in terms of amount of pollution (\(nox\) for nitrous oxide) and the average number of rooms in houses in the community (\(rooms\)):
\(log(price) = \beta_0 = \beta_1log(nox) + \beta_2rooms + u\)
- What are the probable signs of \(\beta_1\) and \(\beta_2\)? What is the interpretation of \(\beta_1\)? Explain.
- Why might \(nox\) [or more precisely, \(log(nox)\)] and \(rooms\) be negatively correlated? If this is the case, does the simple regression of \(log(price)\) on \(log(nox)\) produce an upward or a downward biased estimator of \(\beta_1\)?
- Using data, the following equations were estimated:
\(\widehat{log(price)} = 11.71 - 1.043 log(nox)\), \(n = 506\), \(R^2 = 0.264\)
\(\widehat{log(price)} = 9.23 - 0.718 log(nox) + 0.306 rooms\), \(n = 506\), \(R^2 = 0.514\)
Is the relationship between the simple and multiple regression estimates of the elasticity of \(price\) with respect to \(nox\) what you would have predicted, given your answer in part (ii)? Does this mean that 0.718 is definitely closer to the true elasticity than 1.043?
- Read the box “The Return to Education and the Gender Gap” in Section 8.3.
- Consider a man with 16 years of education and 2 years of experience. Use the results from column (4) of Table 8.1 and the method in Key Concept 8.1 to estimate the expected change in the logarithm of average hourly earnings (AHE) associated with an additional year of experience.
- Explain why your answer to (a) does not depend on the region he is from.
- Repeat (a), assuming 10 years of experience.
- To answer this question, refer to Table 8.3: Nonlinear Regression Model of Test Scores in your textbook:
- A researcher suspects that the effect of % Eligible for subsidized lunch has a nonlinear effect on test scores. In particular, he conjectures that increases in this variable from 10% to 20% have little effect on test scores but that changes from 50% to 60% have a much larger effect.
i. Describe a nonlinear specification that can be used to model this form of nonlinearity.
ii. How would you test whether the researcher’s conjecture was better than the linear specification in column (7) of Table 8.3?
- A researcher suspects that the effect of income on test scores is different in districts with small classes than in districts with large classes.
i. Describe a nonlinear specification that can be used to model this form of nonlinearity.
- Labor economists studying the determinants of women’s earnings discovered a puzzling empirical result. Using randomly selected employed women, they regressed earnings on the women’s number of children and a set of control variables (age, education, occupation, and so forth). They found that women with more children had higher wages, controlling for these other factors. Explain how sample selection might be the cause of this result. (Hint: Notice that women who do not work outside the home are missing from the sample.) [This empirical puzzle motivated James Heckman’s research on sample selec-tion that led to his 2000 Nobel Prize in Economics. See Heckman (1974)]
- The demand for a commodity is given by \(Q = \beta_0 + \beta_1 P + u\), where \(Q\) denotes quantity, \(P\) denotes price, and \(u\) denotes factors other than price that determine demand. Supply for the commodity is given by \(Q = \gamma_0 + \gamma_1P + v\), where \(v\) denotes factors other than price that determine supply. Suppose \(u\) and \(v\) both have a mean of 0, have variances \(\sigma^2_u\) and \(\sigma^2_v\), and are mutually uncorrelated.
- Solve the two simultaneous equations to show how Q and P depend on u and v.
- Derive the means of P and Q.
- Derive the variance of P, the variance of Q, and the covariance between Q and P.
Revisit the box “The Return to Education and the Gender Gap” in Section 8.3. Discuss the internal and external validity of the estimated effect of education on earning
Complete Additional Empirical Exercise 8.2 using the dataset CollegeDistance.dta


---
# Feel free to add content and custom Front Matter to this file.
# To modify the layout, see https://jekyllrb.com/docs/themes/#overriding-theme-defaults
layout: default
---
{% include home/banner.html %}
{% include home/what.html %}
{% include home/mission.html %}
{% include home/how.html %}
{% include home/city.html %}
{% include home/can.html %}
{% include home/bio.html %}
{% include home/impact.html %}
{% include home/pillars.html %}
{% include home/commitment.html %}
{% include home/steps.html %}
{% include home/faq.html %}


- Educations
-
Iona College - New Rochelle, NY - 2014
Degree: M.B.A. Masters in Business Administration
College of the Holy Cross - Worcest, MA - 2006
Degree: Bachelor of Arts in Political Science
- Skills
-
Languages and Skills
Ruby, Ruby on Rails, PostgreSQL, Bash, JavaScript, JQuery, AWS S3
CSS, HTML, HAML, Bootstrap, Mustache, Heroku, Git, Slack, Trello
- Experience
-
The Iron Yard Jr Ruby on Rails Developer- 6/2017-11/2017
- Designed and built websites from scratch using Rails, HTML, CSS with Flexbox and JavaScript
- Built Muse, an online web app built with Rails and on a HAML template, that allows users to upload photos, comment, as well as like/dislike photos. Utilized AWS S3 for storing users’ photos after deployment to Heroku.
- GamePro, a video game review app I built on Rails. I modeled my app after an old video game magazine called, "GamePro." Users can upload pictures of their favorite video games and add reviews to their games and others. I used a Jquery rating system called "Raty," that allows users to give 1-5 stars to their games. It's similar to the start system on IMDB. I aslo implemented an average review method that takes all of the users reviews and averages them in a 5 star format and displays them when clicking on the game box art.
- RESTful API, Rails 5 was the first version of Rails that supported API only applications. I used this feature to generate an API-Centric framework via Rails 5. This RESTful Json API is Todo List that allows users to manage their todo lists and items. I intalled and utilized the RSPEC gem for testing the API
SUNLIGHT LEDInternational Account Manager - 4/2014-12/2016
- Helped launch Sunlight LED, the first industrial LED manufacturer in Central America
- Led the successful international market launch of Sunlight LED products
- Performed energy audits at clients’ facilities to create energy cost saving reports; tax incentives, maintenance savings, and energy output savings.
- Negotiated and Structured financing partnerships with local banks to decrease capital costs for clients.
- Sourced parts and materials in China, marinating weekly contact with suppliers to ensure the best possible quality and production.
ROCKLAND BAKERYRegional Manager - Nanuet, NY - 2007-2014
- Started as the New Jersey territory manager; quickly promoted to a
regional manager role in second year of employment.
- Opened 500+ new accounts, totalling $11.6 million in profitable new business,
which generated 20% operating margins.
- Assisted in growing Rockland’s largest food service clients; Sodexo, Aramark,
and Compass Group, annual sales from $30 million to $75 million.
- Expanded sales and distribution throughout the Northeast market New York, New Jersey, Connecticut, Pennsylvania, Delaware, and Massachusetts.
- Organized hiring of new staff and purchasing of trucks and equipment to service new routes in Massachusetts
- Assisted in the exponential expansion of the Philadelphia market; growing annual sales from $7.8 million to $13 million.
- Led the development and implementation of a second distribution center in Lehigh Valley, Pennsylvania.
Bank of NY Mellon Performance/Compliance Analyst - NY, NY - 2006-2007
- Analyzed daily equity, debt, and fund transactions within clients’ portfolios.
- Generated daily, monthly, and quarterly performance reports of clients holdings
- Worked with IT department to develop analytical platforms
- Generated monthly risk and volatility reports


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---
layout: game-page
redirect_from: /game/channel
title: Channel
year: 2019
semester: Fall
description: "Channel is a collective investigation of the varying nature of parent-child relationships. Divided into groups, the project resulted in three mini-games, each expressing a unique perspective about our day-to-day familial interactions. For the best experience, please tune in for all three channels!
For more in-depth information about the development of Channel, please visit the dev's blog at https://medium.com/@gzliu777"
tags: Singleplayer Windows Unity
# tag options: "Windows", "Mac", "Linux",
# "Singleplayer", "Multiplayer",
# "Controller-Compatible", "VR",
# "Game-Jam"
project_members: {
Bair in the Woods: "first",
Adrian Ma: Programming,
Adrian Mester: "Programming, Music and Sound",
Grace Li: Art,
Audrey Renouf: Art,
Door: "",
Grace Liu: "Art, Project Team Lead",
Jared Harkins: Programming,
Malek Anabtawi: "Narrative, Programming",
Chore: "",
Kalpa Anjur: Programming,
Sheenu You: "Programming, Art, Music and Sound"
}
stage_game_path: channel/
builds: {
Bair in the Woods (Windows): BairBuild.zip,
Door (Windows): DoorBuild.zip,
Chore (Windows): ChoreBuild.zip
}
thumbnail: channel_poster_banner2.png
top-img: channel_poster_banner2.png
screenshots: [
bair1.png,
bair2.png,
bair3.png,
door1.png,
door2.png,
door3.png,
chore1.png,
chore2.png,
chore3.png
]
# Optional
awards: [
]
gameplay-videos: [
player.vimeo.com/video/379918467
]
top-img-fit: cover
# top-img-fit options:
# "cover" - Cover the entire top area with the image, without squashing/stretching
# "fill" - Fit the FULL image into the top area, squashing/stretching as necessary
---


The Collaborative Information Portal proves that it is possible—yes, even at a huge government agency like NASA—to develop a large complex enterprise software system on time that successfully meets strict requirements for functionality, reliability, and robustness. The Mars rovers have far exceeded expectations, a testament of how well the hardware and the software, both on Mars and on Earth, were designed and built, and of the skills of the builders.
Unlike smaller programs, beauty for a large application is not necessarily found only in elegant algorithms. For CIP, beauty is in its implementation of a service-oriented architecture and in the numerous simple but well-chosen components—the nails that master software builders know just where to pound in.


Exercise links
Click Handler
Key Handler
Event Current Target
Event Current Target without StopPropagation
Event Current Target without StopPropagation
Event Delegation
Event Delegation Another Approach
Drill 01 - Image Carousel
Drill 02 - FizzBuzz game
Drill 03 - Bulb Light


- Robert F. Kennedy


- Task - Class in logic.workstation
-
Class used to describe a task that needs to be performed in order to complete a car order.
- Task(CarPart) - Constructor for class logic.workstation.Task
-
Creates a task corresponding with the given car part.
- TaskOrder - Class in logic.car
-
A class holding the information about task orders.
- TaskOrder(TaskOrderDetails) - Constructor for class logic.car.TaskOrder
-
Creates a new task order by initializing the task order details with the given details.
- TaskOrderDetails - Class in logic.car
-
A class holding more information about task orders.
- TaskOrderDetails(CarPart, DateTime) - Constructor for class logic.car.TaskOrderDetails
-
Constructs a new task order's details by initializing the part and deadline of this
task order's detail with the given parameters.
- TaskOrderDetailsMaker - Class in logic.car
-
A class for building the task order's details.
- TaskOrderDetailsMaker() - Constructor for class logic.car.TaskOrderDetailsMaker
-
Creates a new task order detail by initializing the available types of tasks.
- testCustomShop() - Method in class tests.UserTest
-
Test the customs shop manager class.
- testDayOverflow() - Method in class tests.AssemblyLineTest
-
This test tests whether orders are correctly scheduled to the next day, when they can't be completed
on the first day anymore.
- testEqiDateTime() - Method in class tests.AssemblyLineTest
-
Tests the correctness of eqiDateTime(...)
- testEstimatesEasy() - Method in class tests.AssemblyLineTest
-
This test tests the correct propagation of estimated completion times.
- testIdleWorkstation() - Method in class tests.WorkStationTest
-
Test idle().
- testINValidEasy() - Method in class tests.OrderDetailsTests
-
Tests ModelA being set up incorrectly.
- testNegativeOvertime() - Method in class tests.AssemblyLineTest
-
Test the effect of negative overtime on the system.
- testOrdersValid() - Method in class tests.AssemblyLineTest
-
A quick test to check whether the builders defined above work.
- testOvertimeOver2Hours() - Method in class tests.AssemblyLineTest
-
Test the correct calculation of estimated completion times in case of overtime.
- testOvertimeOver2HoursPhase70() - Method in class tests.AssemblyLineTest
-
Test the correct calculation of estimated completion times in case of overtime.
- testPrioritySchedulingEasy() - Method in class tests.AssemblyLineTest
-
A basic test of the batch scheduling strategy.
- tests - package tests
-
- testSingleTasks() - Method in class tests.AssemblyLineTest
-
Test the correct estimated assemblytimes for TaskOrders.
- testSpecificPosts() - Method in class tests.WorkStationTest
-
Tests to simulate the workflow on the assembly line (without Assemblyline) With repetitions.
- testSportsBodyWithoutSpoiler() - Method in class tests.OrderDetailsTests
-
Tests a model with sports body without the mandatory spoiler
The details produced should be null.
- testSportsBodyWithSpoiler() - Method in class tests.OrderDetailsTests
-
Tests a model with sports body with mandatory spoiler
- testStat1() - Method in class tests.StatisticsTests
-
The main test.
- testTaskOrder() - Method in class tests.WorkStationTest
-
Test that taskorders are completed correctly by the workstations.
- testTaskOrderDetatilsMaker() - Method in class tests.OrderDetailsTests
-
Tests the builder of the task orders and the task details.
- testUniversalPost() - Method in class tests.WorkStationTest
-
Tests the correct functioning of one Workstations in tandem with the CarOrders they're working on.
- testValidEasy() - Method in class tests.OrderDetailsTests
-
Tests a simple testcase: ModelA set up propperly.
- toString() - Method in class logic.assemblyline.BatchSpecificationStrategy
-
Returns a string which represents this scheduling strategy.
- toString() - Method in class logic.assemblyline.FifoStrategy
-
Returns a string which represents this scheduling strategy.
- toString() - Method in class logic.assemblyline.SchedulingStrategy
-
Returns a string which represents this scheduling strategy.
- toString() - Method in class logic.assemblyline.Statistics
-
Returns a string representation of these statistics.
- toString() - Method in enum logic.car.CarModel
-
Returns a string representation of this car model.
- toString() - Method in class logic.car.CarOrder
-
Returns a string representation of this car order.
- toString() - Method in class logic.car.CarOrderDetails
-
Builds a string which is a representation of this detail's model and tasks.
- toString() - Method in enum logic.car.CarPart
-
Returns a string representation of this car part.
- toString() - Method in enum logic.car.CarPartType
-
Returns a string representation of this car part type.
- toString() - Method in class logic.car.TaskOrder
-
Returns a string representation for the estimated completion time for this task order.
- toString() - Method in class logic.workstation.AccessoriesPost
-
Returns a string representation of an accessories post.
- toString() - Method in class logic.workstation.CarBodyPost
-
Returns a string representation of a car body post.
- toString() - Method in class logic.workstation.DriveTrainPost
-
Returns a string representation of a drive train post.
- toString() - Method in class logic.workstation.Task
-
Returns the string representation of this task.
- tryMoveAssemblyLine(int) - Method in class logic.assemblyline.AssemblyLine
-
Returns true if the assembly line can be moved, false otherwise.
- type - Variable in enum logic.car.CarPart
-
The car part type of this car part.


Soldiers of Kaki!
Home
(current)
Kakista ulos!
(current)
Kaki!
Delicious.
Kaki!
Delicious.
Kaki!
Delicious.
Kaki!
Delicious.
Kaki!
Delicious.
Kaki!
Delicious.
Kaki!
Delicious.
Kaki!
Delicious.
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PyClaw tutorial: Solve the acoustics equations¶
PyClaw is designed to solve general systems of hyperbolic PDEs of the form
As an example, in this tutorial we’ll set up a simulation that solves the acoustics equations in one dimension:
The key to solving a particular system of equations with PyClaw or other similar codes is a Riemann solver. Riemann solvers for many systems are available as part of the clawpack/riemann package.
We’ll assume that you’ve already followed the Installing PyClaw instructions.
The following instructions show how to set up a problem step-by-step in an interactive shell. See acoustics_1d for the full source on which this is based.
The commands below should be typed at the Python prompt; we recommend using IPython.
>>> from clawpack import pyclaw
>>> from clawpack import riemann
The Solver¶
PyClaw includes various algorithms for solving hyperbolic PDEs; each is implemented in a Solver object. So the first step is to create a solver
>>> solver = pyclaw.ClawSolver1D(riemann.acoustics_1D)
Next we set the boundary conditions. We’ll use a wall (wall) condition at the left boundary and a non-wall (zero-order extrapolation) condition at the right boundary
>>> solver.bc_lower[0] = pyclaw.BC.wall
>>> solver.bc_upper[0] = pyclaw.BC.extrap
The domain¶
Next we need to set up the grid. We do so by defining the physical domain and the computational resolution. We’ll use the interval \((-1,1)\) and 200 grid cells:
>>> domain = pyclaw.Domain([-1.0], [1.0], [200])
Notice that the calling sequence is similar to numpy’s linspace command.
Finally, we set up a Solution object, which will hold the solution values:
>>> solution = pyclaw.Solution(solver.num_eqn, domain)
Initial condition¶
Now we will set the initial value of the solution
>>> state = solution.state
>>> xc = state.grid.p_centers[0] # Array containing the cell center coordinates
>>> from numpy import exp
>>> state.q[0,:] = exp(-100 * (xc-0.75)**2) # Pressure: Gaussian centered at x=0.75.
>>> state.q[1,:] = 0. # Velocity: zero.
Problem-specific parameters¶
The acoustics equations above have some coefficients – namely, the bulk modulus \(K\) and density \(\rho\) – that must be defined. Furthermore, checking the code for the Riemann solver we’ve chosen reveals that it expects us to provide values for the impedance \(Z\) and sound speed \(c\). These values are stored in a Python dictionary called problem_data that is a member of the State
>>> from math import sqrt
>>> rho = 1.0
>>> bulk = 1.0
>>> state.problem_data['rho'] = rho
>>> state.problem_data['bulk'] = bulk
>>> state.problem_data['zz'] = sqrt(rho*bulk)
>>> state.problem_data['cc'] = sqrt(bulk/rho)
The controller¶
The most convenient way to run a PyClaw simulation is by using a Controller object. The controller directs the solver in advancing the solution and handles output.
>>> controller = pyclaw.Controller()
>>> controller.solution = solution
>>> controller.solver = solver
>>> controller.tfinal = 1.0
At last everything is set up! Now run the simulation
>>> status = controller.run()
This should print out a few lines indicating the output times. It also prints the minimum and maximum tipe-step used, the number of steps required for the computation and the maximum CFL number. The simplest way to plot the solution is
>>> from clawpack.pyclaw import plot
>>> plot.interactive_plot()
That’s it! Your first PyClaw simulation. Of course, we’ve only scratched the surface of what PyClaw can do, and there are many important options that haven’t been discussed here. To get an idea, take a look through the pyclaw/examples directory and try running some other examples. It’s also a good idea to get more deeply acquainted with the main Understanding Pyclaw Classes.


Acceleration
Acceleration With Gravity
Rotation
Orientation
Device Mode
Ambient Light
Geolocation
Velocity
"MozOrientation"


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{% import "_includes/forms" as forms %} {{ forms.lightswitchField({ id: 'expandSingles', name: 'expandSingles', label: 'Expand Singles' | t, on: settings.expandSingles, instructions: 'Expands the Singles link on the Entries page to list them like Channels and Structures.' | t }) }} {{ forms.lightswitchField({ id: 'redirectToEntry', name: 'redirectToEntry', label: 'Redirect to Entry' | t, on: settings.redirectToEntry, instructions: 'Automatically redirects to edit the Single Entry when clicking on the item in the sidebar.' | t }) }}


Free shipping on orders over 300,000
Free exchange and compensation for defective items
Customer consulting service 24/24
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Life
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| data Char |
To convert a Char to or from the corresponding Int value defined by Unicode, use Prelude.toEnum and Prelude.fromEnum from the Prelude.Enum class respectively (or equivalently ord and chr).
| instance Bounded Char |
| instance Enum Char |
| instance Eq Char |
| instance Ord Char |
| instance Read Char |
| instance Show Char |
| instance Ix Char |
| instance Storable Char |
| type String = [Char] |
Unicode characters are divided into letters, numbers, marks, punctuation, symbols, separators (including spaces) and others (including control characters).
| isControl :: Char -> Bool |
| isSpace :: Char -> Bool |
| isLower :: Char -> Bool |
| isUpper :: Char -> Bool |
| isAlpha :: Char -> Bool |
| isAlphaNum :: Char -> Bool |
Note that numeric digits outside the ASCII range are selected by this function but not by isDigit. Such digits may be part of identifiers but are not used by the printer and reader to represent numbers.
| isPrint :: Char -> Bool |
| isDigit :: Char -> Bool |
| isOctDigit :: Char -> Bool |
| isHexDigit :: Char -> Bool |
| isLetter :: Char -> Bool |
| isMark :: Char -> Bool |
| isNumber :: Char -> Bool |
| isPunctuation :: Char -> Bool |
| isSymbol :: Char -> Bool |
| isSeparator :: Char -> Bool |
| isAscii :: Char -> Bool |
| isLatin1 :: Char -> Bool |
| isAsciiUpper :: Char -> Bool |
| isAsciiLower :: Char -> Bool |
| data GeneralCategory |
| = | UppercaseLetter | Lu: Letter, Uppercase |
| | | LowercaseLetter | Ll: Letter, Lowercase |
| | | TitlecaseLetter | Lt: Letter, Titlecase |
| | | ModifierLetter | Lm: Letter, Modifier |
| | | OtherLetter | Lo: Letter, Other |
| | | NonSpacingMark | Mn: Mark, Non-Spacing |
| | | SpacingCombiningMark | Mc: Mark, Spacing Combining |
| | | EnclosingMark | Me: Mark, Enclosing |
| | | DecimalNumber | Nd: Number, Decimal |
| | | LetterNumber | Nl: Number, Letter |
| | | OtherNumber | No: Number, Other |
| | | ConnectorPunctuation | Pc: Punctuation, Connector |
| | | DashPunctuation | Pd: Punctuation, Dash |
| | | OpenPunctuation | Ps: Punctuation, Open |
| | | ClosePunctuation | Pe: Punctuation, Close |
| | | InitialQuote | Pi: Punctuation, Initial quote |
| | | FinalQuote | Pf: Punctuation, Final quote |
| | | OtherPunctuation | Po: Punctuation, Other |
| | | MathSymbol | Sm: Symbol, Math |
| | | CurrencySymbol | Sc: Symbol, Currency |
| | | ModifierSymbol | Sk: Symbol, Modifier |
| | | OtherSymbol | So: Symbol, Other |
| | | Space | Zs: Separator, Space |
| | | LineSeparator | Zl: Separator, Line |
| | | ParagraphSeparator | Zp: Separator, Paragraph |
| | | Control | Cc: Other, Control |
| | | Format | Cf: Other, Format |
| | | Surrogate | Cs: Other, Surrogate |
| | | PrivateUse | Co: Other, Private Use |
| | | NotAssigned | Cn: Other, Not Assigned |
Unicode General Categories (column 2 of the UnicodeData table) in the order they are listed in the Unicode standard.
| instance Bounded GeneralCategory |
| instance Enum GeneralCategory |
| instance Eq GeneralCategory |
| instance Ord GeneralCategory |
| instance Read GeneralCategory |
| instance Show GeneralCategory |
| instance Ix GeneralCategory |
| generalCategory :: Char -> GeneralCategory |
| toUpper :: Char -> Char |
| toLower :: Char -> Char |
| toTitle :: Char -> Char |
| digitToInt :: Char -> Int |
| intToDigit :: Int -> Char |
| ord :: Char -> Int |
| chr :: Int -> Char |
| showLitChar :: Char -> ShowS |
| lexLitChar :: ReadS String |
| readLitChar :: ReadS Char |


Q: Why?
Ans: BEANS.
Q: Is this real? (As in I can buy things)
Ans: OFC No, This is a joke made in like what? 15 mins? and hosted on github pages, what did you expect?


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{% extends "base_content.html" %} {% load engine_tags %} {% block headtitle %} Edit Data: {{ data.name }} {% endblock %} {% block content %}
Edit the data name
Replace content of stored file with this one. This does not change the name.
Edit uploaded text ( {{ form.input_text.field.max_length }} characters ).
Data type used to sub-select during analysis.
A detailed explanation of what is in the data collection (markdown OK).


| Day 1 | Glasgow arrival |
| Day 2 | Train to Glencoe |
| Day 3 | Second day in Glencoe |
| Day 4 | Train to Fort William and Glenfinnan |
| Day 5 | Boat ride through the Kyle of Lochalsh |
| Day 6 | Train to Loch Ness and Fort William |
| Day 7 | Free day |
| Day 8 | Trip to Aviemore and Pitlochry |
| Day 9 | Train to Edinburgh |
| Day 10 | Second day in Edinburgh |
| Day 11 | Third day in Edinburgh |
| Day 12 | Trip to Sterling |
| Day 13 | Train to Glasgow |
| Day 14 | Glasgow departure |


Guitars are so much more awesomer than kittens in bowties
See told you! Can you name the parts in the following image?
Heres some things I see:
- Bridge
- Sound Hole
- Head
I am now going to attempt to build a table, wish me luck
| Item type |
Item Count |
Electric or Acoustic |
| Bridge |
2 |
Both |
| Sound Hole |
1 |
Acoustic |
| Head |
2 |
Both |
| Pickup Selector |
1 |
Electric |
Anyone want to color guitars?
So, what do you think? Much, much better than kittens in bowties, right?


The appellant was assaulted by the assailant and in self-defense she quickly grabbed a nearby eggplant, which she used as an anticoagulant to staunch the flow of blood from her wounds. [G|D]
The gallant knight jubilantly strode onto the battlefield, implant firmly in place, and petulantly challenged the forces of evil to battle. [G|D]
As the rocket blasted off, the propellant provided a powerful stimulant to the sealed engine, whose exhaust was angled at a perfectly slanted trajectory. [G|D]
The vigilant doctor carefully transplanted the organ into the patient, successfully supplanting the failing organs, before the nurse flew volant across the room with joy at a successful procedure. [G|D]


VoltageClampSeries Current data from an intracellular voltage-clamp recording. A corresponding VoltageClampStimulusSeries (stored separately as a stimulus) is used to store the voltage injected.
| capacitance_fast |
(single) Fast capacitance, in farads. |
| capacitance_fast_unit |
(char) Unit of measurement for capacitance_fast, which is fixed to 'farads'. |
| capacitance_slow |
(single) Slow capacitance, in farads. |
| capacitance_slow_unit |
(char) Unit of measurement for capacitance_fast, which is fixed to 'farads'. |
| comments |
(char) Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information,
or descriptive information if the primary description field is populated with a computer-readable string.
|
| control |
(uint8) Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values.
If present, the length of this array should be the same size as the first dimension of data.
|
| control_description |
(char) Description of each control value. Must be present if control is present. If present, control_description[0] should
describe time points where control == 0.
|
| data |
REQUIRED (any) Data values. Data can be in 1-D, 2-D, 3-D, or 4-D. The first dimension should always represent time. This can
also be used to store binary data (e.g., image frames). This can also be a link to data stored in an external file.
|
| data_continuity |
(char) Optionally describe the continuity of the data. Can be "continuous", "instantaneous", or "step". For example, a voltage
trace would be "continuous", because samples are recorded from a continuous process. An array of lick times would be "instantaneous",
because the data represents distinct moments in time. Times of image presentations would be "step" because the picture remains
the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data.
It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable.
|
| data_conversion |
(single) Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition
system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the
data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16
range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then
the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.
|
| data_offset |
(single) Scalar to add to the data after scaling by 'conversion' to finalize its coercion to the specified 'unit'. Two common
examples of this include (a) data stored in an unsigned type that requires a shift after scaling to re-center the data, and
(b) specialized recording devices that naturally cause a scalar offset with respect to the true units.
|
| data_resolution |
(single) Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value
of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.
|
| data_unit |
(char) Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units.
To access the data in these units, multiply 'data' by 'conversion' and add 'offset'.
|
| description |
(char) Description of the time series. |
| electrode |
IntracellularElectrode |
| gain |
(single) Gain of the recording, in units Volt/Amp (v-clamp) or Volt/Volt (c-clamp). |
| resistance_comp_bandwidth |
(single) Resistance compensation bandwidth, in hertz. |
| resistance_comp_bandwidth_unit |
(char) Unit of measurement for resistance_comp_bandwidth, which is fixed to 'hertz'. |
| resistance_comp_correction |
(single) Resistance compensation correction, in percent. |
| resistance_comp_correction_unit |
(char) Unit of measurement for resistance_comp_correction, which is fixed to 'percent'. |
| resistance_comp_prediction |
(single) Resistance compensation prediction, in percent. |
| resistance_comp_prediction_unit |
(char) Unit of measurement for resistance_comp_prediction, which is fixed to 'percent'. |
| starting_time |
(double) Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample
can be specified and all subsequent ones calculated from the sampling rate attribute.
|
| starting_time_rate |
(single) Sampling rate, in Hz. |
| starting_time_unit |
(char) Unit of measurement for time, which is fixed to 'seconds'. |
| stimulus_description |
(char) Protocol/stimulus name for this patch-clamp dataset. |
| sweep_number |
(uint32) Sweep number, allows to group different PatchClampSeries together. |
| timestamps |
(double) Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. |
| timestamps_interval |
(int32) Value is '1' |
| timestamps_unit |
(char) Unit of measurement for timestamps, which is fixed to 'seconds'. |
| whole_cell_capacitance_comp |
(single) Whole cell capacitance compensation, in farads. |
| whole_cell_capacitance_comp_unit |
(char) Unit of measurement for whole_cell_capacitance_comp, which is fixed to 'farads'. |
| whole_cell_series_resistance_comp |
(single) Whole cell series resistance compensation, in ohms. |
| whole_cell_series_resistance_comp_unit |
(char) Unit of measurement for whole_cell_series_resistance_comp, which is fixed to 'ohms'. |
|
|
addlistener |
Add listener for event. |
|
|
delete |
Delete a handle object. |
|
|
eq |
== (EQ) Test handle equality. |
|
|
export |
|
|
|
findobj |
Find objects matching specified conditions. |
|
|
findprop |
Find property of MATLAB handle object. |
|
|
ge |
>= (GE) Greater than or equal relation for handles. |
|
|
gt |
> (GT) Greater than relation for handles. |
| Sealed
|
isvalid |
Test handle validity. |
|
|
le |
<= (LE) Less than or equal relation for handles. |
|
|
listener |
Add listener for event without binding the listener to the source object. |
|
|
loadAll |
|
|
|
lt |
< (LT) Less than relation for handles. |
|
|
ne |
~= (NE) Not equal relation for handles. |
|
|
notify |
Notify listeners of event. |
|
|
validate_capacitance_fast |
|
|
|
validate_capacitance_slow |
|
|
|
validate_comments |
|
|
|
validate_control |
|
|
|
validate_control_description |
|
|
|
validate_data |
|
|
|
validate_data_continuity |
|
|
|
validate_data_conversion |
|
|
|
validate_data_offset |
|
|
|
validate_data_resolution |
|
|
|
validate_data_unit |
|
|
|
validate_description |
|
|
|
validate_electrode |
|
|
|
validate_gain |
|
|
|
validate_resistance_comp_bandwidth |
|
|
|
validate_resistance_comp_correction |
|
|
|
validate_resistance_comp_prediction |
|
|
|
validate_starting_time |
|
|
|
validate_starting_time_rate |
|
|
|
validate_stimulus_description |
|
|
|
validate_sweep_number |
|
|
|
validate_timestamps |
|
|
|
validate_whole_cell_capacitance_comp |
|
|
|
validate_whole_cell_series_resistance_comp |
|


SWITCH A film review by Janet M. Lafler Copyright 1991 Janet M. Lafler
SWTICH is a sexual role-reversal comedy directed by Blake Edwards and starring Ellen Barkin which has funny and insightful moments, but also has a great many holes.
The premise is simple: Steve Brooks is an inveterate womanizer hated by women everywhere. After being killed by three former girlfriends he lands in Purgatory, where he is told that he is a borderline case; he has done enough good to be eligible for heaven, but has behaved so horribly to women that he's also a candidate for hell. To resolve the difficulty, he's sent back to earth to find one female who likes him. Thanks to a suggestion from the Devil, he goes back as a woman.
The bulk of the movie deals with Steve (in his female persona, Amanda) trying to get by as a woman for long enough to find a woman who likes him. As Amanda, Barkin turns in a great performance. Tottering on her high heels, tugging at her unfamiliar female finery, walking, talking and gesturing in masculine fashion, she performs just broadly enough to be funny without being ridiculous.
The movie deals with the various possibilities inherent in this switch with uneven success. Steve's reaction to his female body, including his persistent habit of acting as if it were someone else's body, is well-handled, and often quite funny. ("Did you get a look at my legs?" s/he asks best friend Walter, played by Jimmy Smits.) His sexual adjustment is also handled well; there is no easy way for him to slide into either lesbianism or heterosexuality as a woman.
There are problems, though. I found myself wondering whether a man who had just turned into a woman would dress like that. There's no reason that Steve/Amanda immediately has to put on four-inch stiletto heels. Then there's the question of just what's good about Steve Brooks.  All women. (Either his mother's dead or she hates him too; at any rate, she's never mentioned.) And there's at least one glaring continuity error. (Hint: I don't know anyone whose hair could grow eight inches in five months.)
On a more serious and subtle level, the movie-makers seem to be assuming that spending a few days or months as a woman can make a man really understand what it is like to be a woman, a premise I find unconvincing. (A similar transformation occurs in TOOTSIE.) Only a few days after the switch, Amanda complains about how an ad doesn't really reflect women's experience; in fact, once Steve becomes a woman he pretty quickly begins spouting feminist rhetoric. While I would like to believe that any man who woke up one day in a woman's body would become a feminist, there are limits to what makes sense. When Amanda starts holding forth on date rape, it doesn't ring true. In the end, the movie's feminist pieties strike me as rather cheap. As a comedy, this movies succeeds, but when it tries to get serious about the differences between men's and women's experiences, it's often frustrating and shallow.
SWITCH is an engaging movie, worth going to see simply for Barkin's performance. (Supporting performances are competent, but not exciting.) Pacing falters somewhat in the last third of the movie, but in general Barkin's energy keeps things moving.
Janet Lafler -- send mail to<EMAIL_ADDRESS>(In answer to your first question, Repnomar is a character in M.J. Engh's The Wheel of the Winds.) .
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


?N^WVOflKBOTANICAL
GARDEN
01497759""
Forestiera
segregata
(|acq.)
Krug-
&
Urb.
det.
Carol
J.
Brooks
The
University
of
Alabama
PLANTS
OF
THE
BAHAMA
ISLANDS
Oleaceae
Forestiera
segregata
(Jacquin)
Krug
&
Urban
shrub
3
m.
high;
flowers
yellow-green;
fruit
maturing
dark
red.
GRAND
BAHAMA
ISLAND:
Dead
Man's
Reef,
9
miles
E.S.E.
of
West
End.
edge
of
road
near
beach,
scrub.
Walter
H.
Lewis,
no.
7135
23
Dec.
1968
MISSOURI
BOTANICAL
GARDEN
HERBARIUM
01497759
Legend -
Level of confidence that token is an accurately-transcribed word
extremely low
very low
low
undetermined
medium
high
very high


About Me
I’m an applied scientist at Amazon Alexa. I was a postdoctoral research scientist at Digital Video and MultiMedia Lab at the Columbia University in the city of New York, supervised by Prof. Shih-Fu Chang. I obtained a Ph.D. from Tsinghua University, Beijing, China, in 2016, supervised by Prof. Shengjin Wang. My research interests include local feature detection and description, large scale image retrieval and image forensics. Here is my full resume.
News
Jun. 2020
I have one paper accepted by IEEE Journal of Selected Topics in Signal Processing
May. 2020
I'll be serving as a Special Session Chair in WIFS 2020
Feb. 2020
I'll be serving as an AC in ACMMM 2020
Sep. 2019
I have one paper accepted in WIFS 2019
Experience
Amazon Alexa
Cambridge, MA, USA
Applied Scientist
Nov. 2019 - Present
Columbia University
New York, New York, USA
Postdoctoral Research Scientist
July 2016 - Oct. 2019
Tencent, Inc.
Beijing, China
Research Intern
Nov. 2015 - May 2016
JD.com
Beijing, China
Research Intern
Aug. 2015 - Nov. 2015
Education
Tsinghua University
Beijing, China
Ph.D., Electrical Engineering
Sep. 2013 - Jul. 2016
Columbia University
New York, New York, USA
Visiting Scholar
Nov. 2014 - May 2015
Tsinghua University
Beijing, China
M.S., Electrical Engineering
Sep. 2010 - Jul. 2013
Tsinghua University
Beijing, China
B.S., Electronic Engineering
Sep. 2006 - Jul. 2010
Projects
Visual Political Literacy Project
Danesfield
Events
NYC Media Lab’s Annual Summit 2019
Brooklyn, NY
Sep. 2019
We will host a demo "Political Visual Literacy App"
CVPR 2019
Long Beach, CA
Jun. 2019
I co-organized the 2nd Landmark Recognition Workshop
CVPR 2018
Salt Lake City, UT
Jun. 2018
I co-organized the 1st Landmark Recognition Workshop
Selected Publication
Xu Zhang, Zhaohui H. Sun, Svebor Karaman, Shih-Fu Chang
Discovering Image Manipulation History byPairwise Relation and Forensics Tools
IEEE Journal of Selected Topics in Signal Processing
Xu Zhang, Svebor Karaman, Shih-Fu Chang
Detecting and Simulating Artifacts in GAN Fake Images
WIFS 2019
Mang Ye, Xu Zhang, Pong C. Yuen, and Shih-Fu Chang
Unsupervised Embedding Learning via Invariant and Spreading Instance Feature
CVPR 2019
Matthew J. Leotta, Chengjiang Long, Bastien Jacquet, Matthieu Zins, Dan Lipsa, Jie Shan, Bo Xu, Zhixin Li, Xu Zhang, Shih-Fu Chang, Matthew Purri, Jia Xue, Kristin Dana
Urban Semantic 3D Reconstruction From Multiview Satellite Imagery
CVPRW 2019. Best paper in the EarthVision 2019 Workshop
Xu Zhang, Felix X Yu, Sanjiv Kumar, Shih-Fu Chang
Learning Spread-out Local Feature Descriptors
ICCV 2017.


Performs a joint analysis of experiments with mixtures and random effects, taking on a process variable represented by a covariable.
| Version: | 1.0.2 |
| Depends: | MASS, lattice |
| Published: | 2018-07-03 |
| Author: | Marcelo Angelo Cirillo Paulo Cesar Ossani |
| Maintainer: | Paulo Cesar Ossani <ossanipc at hotmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| Citation: | Blendstat citation info |
| CRAN checks: | Blendstat results |
| Reference manual: | Blendstat.pdf |
| Package source: | Blendstat_1.0.2.tar.gz |
| Windows binaries: | r-devel: Blendstat_1.0.2.zip, r-release: Blendstat_1.0.2.zip, r-oldrel: Blendstat_1.0.2.zip |
| OS X binaries: | r-release: Blendstat_1.0.2.tgz, r-oldrel: Blendstat_1.0.2.tgz |
| Old sources: | Blendstat archive |
Please use the canonical form https://CRAN.R-project.org/package=Blendstat to link to this page.


Fifa 19 EDA
FIFA 19 is a football simulation video game developed by EA Vancouver as part of Electronic Arts' FIFA series. The objective of this notebook is to analyse the dataset and see various trends (EDA) using Python and its libraries.
We will load the dataset with all the players and also load libraries to do all the analysis. This kernel is easily understandable to the beginner like me. This verbosity tries to explain everything I could possibly know. Once you get through the notebook, you can find this useful and straightforward. I attempted to explain things as simple as possible. In this notebook, I extensively use plotly along with seaborn and matplotlib for data visualization and EDA on FIFA 19 dataset.
Used Libraries
- NumPy (Numerical Python)
- Pandas
- Matplotlib
- Missingno
- Plotly
We will use a dataset for FIFA 19 soccer game. Based on it we will tour through the process of data preparation, model assembly and model understanding. In each phase we show how to combine results from different methods of exploration. The main goal of this chapter is to show how different techniques complement each other. Some phases, like data preparation, are simplified in order to leave space for the method for visual exploration.
Top Teams based on Rating
The dataset contains the detailed attributes for every player registered in the latest edition of FIFA 19 database. Data scraped from sofifa
Changes and Improvement suggestions are welcome. Feel free to suggest any new additions that you think are useful or drop a PR on the github project.


These innovation areas have been chosen as your current areas of expertise. They will influence the types of competition you will be invited to assess. If you would like to amend them or add new ones please contact Innovate UK<EMAIL_ADDRESS>Please tell us about your main areas of expertise or any specialist skills you have. This will help us to assign you the most appropriate applications for assessment. For example; Solar Power, Genetics, Recycling
You can submit up to 4 pages in PDF format no larger than 1MB. This can describe your relevant skills, experience and work history.
No file currently uploaded
Please select your current area of work. If you are working in both please select the most dominant.


Most SaaS (multi-tenant) applications have editions (packages) those have different features. Thus, they can provide different price and feature options to thier tenants (customers).
ASP.NET Boilerplate provides a feature system to make it easier. We can define features, check if a feature is enabled for a tenant and integrate feature system to other ASP.NET Boilerplate concepts (like authorization and navigation).
Feature system uses IFeatureValueStore to get values of features. While you can implement it in your own way, it's fully implemented in module-zero project. If it's not implemented, NullFeatureValueStore is used which returns null for all features (Default feature values are used in this case).
There are two fundamental feature types.
Can be "true" or "false". This type of a feature can be enabled or disabled (for an edition or for a tenant).
Can be an arbitrary value. While it's stored and retrieved a string, numbers also can be stored as strings.
For example, our application may be a task management application and we may have a limit for creating tasks in a month. Say that we have two different edition/package; one allows creating 1,000 tasks per month, while other allows creating 5,000 tasks per month. So, this feature should be stored as value, not simply true/false.
A feature should be defined before checking. A module can define it's own features by deriving from FeatureProvider class. Here, a very simple feature provider that defines 3 features:
public class AppFeatureProvider : FeatureProvider
{
public override void SetFeatures(IFeatureDefinitionContext context)
{
var sampleBooleanFeature = context.Create("SampleBooleanFeature", defaultValue: "false");
sampleBooleanFeature.CreateChildFeature("SampleNumericFeature", defaultValue: "10");
context.Create("SampleSelectionFeature", defaultValue: "B");
}
}
After creating a feature provider, we should register it in our module's PreInitialize method as shown below:
Configuration.Features.Providers.Add<AppFeatureProvider>();
A feature definition requires two properties at least:
Here, we defined a boolean feature named "SampleBooleanFeature" which's default value is "false" (not enabled). We also defined two value features (SampleNumericFeature is defined as child of SampleBooleanFeature).
Tip: Create a const string for a feature name and use it everywhere to prevent typing errors.
While unique name and default value properties are required, there are some optional properties for a detailed control.
Let's see more detailed definitions for the features above:
public class AppFeatureProvider : FeatureProvider
{
public override void SetFeatures(IFeatureDefinitionContext context)
{
var sampleBooleanFeature = context.Create(
AppFeatures.SampleBooleanFeature,
defaultValue: "false",
displayName: L("Sample boolean feature"),
inputType: new CheckboxInputType()
);
sampleBooleanFeature.CreateChildFeature(
AppFeatures.SampleNumericFeature,
defaultValue: "10",
displayName: L("Sample numeric feature"),
inputType: new SingleLineStringInputType(new NumericValueValidator(1, 1000000))
);
context.Create(
AppFeatures.SampleSelectionFeature,
defaultValue: "B",
displayName: L("Sample selection feature"),
inputType: new ComboboxInputType(
new StaticLocalizableComboboxItemSource(
new LocalizableComboboxItem("A", L("Selection A")),
new LocalizableComboboxItem("B", L("Selection B")),
new LocalizableComboboxItem("C", L("Selection C"))
)
)
);
}
private static ILocalizableString L(string name)
{
return new LocalizableString(name, AbpZeroTemplateConsts.LocalizationSourceName);
}
}
Note that: Input type definitions are not used by ASP.NET Boilerplate. They can be used by applications while creating inputs for features. ASP.NET Boilerplate just provides infrastructure to make it easier.
As shown in the sample feature providers, a feature can have child features. A Parent feature is generally defined as boolean feature. Child features will be available only if the parent enabled. ASP.NET Boilerplate does not enforces but suggests this. Applications should take care of it.
We define a feature to check it's value in the application to allow or block some application features per tenant. There are different ways of checking it.
We can use RequiredFeature attribute for a method or a class as shown below:
[RequiresFeature("ExportToExcel")] public async Task<FileDto> GetReportToExcel(...) { ... }
This method is executed only if "ExportToExcel" feature is enabled for the current tenant (current tenant is obtained from IAbpSession). If it's not enabled, an AbpAuthorizationException is thrown automatically.
Surely, RequiresFeature attribute should be used for boolean type features. Otherwise, you may get exceptions.
ASP.NET Boilerplate uses power of dynamic method interception for feature checking. So, there is some restrictions for the methods use RequiresFeature attribute.
Also,
We can inject and use IFeatureChecker to check a feature manually (it's automatically injected and directly usable for application services, MVC and Web API controllers).
Used to simply check if given feature is enabled or not. Example:
public async Task<FileDto> GetReportToExcel(...)
{
if (await FeatureChecker.IsEnabledAsync("ExportToExcel"))
{
throw new AbpAuthorizationException("You don't have this feature: ExportToExcel");
}
...
}
IsEnabledAsync and other methods have also sync versions.
Surely, IsEnabled method should be used for boolean type features. Otherwise, you may get exceptions.
If you just want to check a feature and throw exception as shown in the example, you can just use CheckEnabled method.
Used to get current value of a feature for value type features. Example:
var createdTaskCountInThisMonth = GetCreatedTaskCountInThisMonth();
if (createdTaskCountInThisMonth >= FeatureChecker.GetValue("MaxTaskCreationLimitPerMonth").To<int>())
{
throw new AbpAuthorizationException("You exceed task creation limit for this month, sorry :(");
}
FeatureChecker methods have also overrides to work features for a specified tenantId, not only for the current tenantId.
In the client side (javascript), we can use abp.features namespace to get current values of the features.
var isEnabled = abp.features.isEnabled('SampleBooleanFeature');
var value = abp.features.getValue('SampleNumericFeature');
If you need to definitions of features, you can inject and use IFeatureManager.
ASP.NET Boilerplate framework has not a built-in edition system because such a system requires a database (to store editions, edition features, tenant-edition mappings and so on...). Therefore, edition system is implemented in module zero. You can use it to easily have an edition system, or you can implement all yourself.


"SCYTHIAN" The Scythians consisted of “all the pastoral tribes who dwelt to the north of the Black Sea and the Caspian, and were scattered far away toward the east. Of this vast country but little was anciently known. Its modern representative is Russia, which, to a great extent, includes the same territories.” They were the descendants of Japheth (Genesis 9:27). It appears that in apostolic times there were some of this people that embraced Christianity (Colossians 3:11).
"SCYTHIAN" The Scythians consisted of “all the pastoral tribes who dwelt to the north of the Black Sea and the Caspian, and were scattered far away toward the east. Of this vast country but little was anciently known.
Its modern representative is Russia, which, to a great extent, includes the same territories.” They were the descendants of Japheth (Genesis 9:27). It appears that in apostolic times there were some of this people that embraced Christianity (Colossians 3:11).


Curious how this page was created?
The demo home page was set up using the theme’s
template builder tools
and strategically placed Custom Query Widgets inside the grid-powered dynamic
sidebars.
We have prepared a step-by-step tutorial that
deconstructs every component used in this page,
so you can reverse-engineer the process and create your own amazing landing
pages.


{{balance}} {{symbol}}
{{t 'deposit.confirmations' confirmations=confirmations}}
- To protect account security, withdrawal can only be made to a Mixin Messenger account.
- Get Mixin Messenger from the only official donwload page https://mixin.one.
- Find the the circle button at the bottom of the Mixin Messenger app, it's the QR code scanner.
- Click the button below will redirect you to the Mixin Messenger website.
- Scan the QR code with the Mixin Messenger QR code scanner.
- Allow the access of Ocean ONE to your Mixin profile.
The Mixin Messenger connection is permanent, you can't disconnect it later.
The withdrawal can only be made to your Mixin Messenger account, and your connected Mixin Messenger ID is {{me.mixin_id}}.
Enter the amount of {{symbol}} to withdrawal:


irc howto
irc and you
now what can it do?
A few of us hang out in the freenode
IRC network in the
#ulug
and ##uofu
channels. If you're new to IRC, but want to join us, read on.
IRC is a protocol for chat. With an IRC client, you log into a server where you can chat with other users on that server. People typically chat in rooms called channels, although you can message people directly.
Although other forms of instant communication have emerged and started to displace IRC, IRC still remains as a popular communication channel for open source communities.
irc clients
There are many
clients
available for IRC.
Some include:
Cross-platform
Mac
Terminal Fans
If you don't wish to install a client, there's always the web client for Freenode.
web quickstart
If you're using the web
web
client, simply enter your desired nickname,
make sure the channels listed are
#ulug
and ##uofu
,
fill in the captcha and hit connect.
register on freenode
Registering your IRC nick on freenode allows you to reserve that nick and use it for identification.
First make sure you have set your desired nick.
Next, message NickServ with the REGISTER
command.
Be sure to use an unique password as you may be authenticating over plaintext.
You'll need to use a valid email as you'll be sent a verification email which will be used to complete the registration. In the email will be a random string that you'll message to NickServ.
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| &.gg | Plot arithmetic |
| *.gg | Plot arithmetic |
| -.ggplot | Plot arithmetic |
| /.ggplot | Plot arithmetic |
| align_patches | Align plots across multiple pages |
| area | Specify a plotting area in a layout |
| get_dim | Align plots across multiple pages |
| get_max_dim | Align plots across multiple pages |
| guide_area | Add an area to hold collected guides |
| inset_element | Create an inset to be added on top of the previous plot |
| multipage_align | Align plots across multiple pages |
| plot_annotation | Annotate the final patchwork |
| plot_arithmetic | Plot arithmetic |
| plot_layout | Define the grid to compose plots in |
| plot_spacer | Add a completely blank area |
| set_dim | Align plots across multiple pages |
| wrap_elements | Wrap arbitrary graphics in a patchwork-compliant patch |
| wrap_ggplot_grob | Make a gtable created from a ggplot object patchwork compliant |
| wrap_plots | Wrap plots into a patchwork |
| |.ggplot | Plot arithmetic |


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Kojo Adams, Accounting Department, EcoBank. Cotonou, Attn my friend , I am Mr kojo Adams, Auditor, with Accounting Department,Ecobank here in Cotonou, Benin Republic. I got your very good name and e-mail address from the online classified posted on the net.I have decided to contact you purely on the personal conviction of trust andconfidence that we can co-operate with one another and do a very lucrative business for our mutual benefit.The Business I am proposing to you is in respect of the sum of US$11,183,000.00 (Eleven Million One Hundred and Eighty-Three Thousand United States Dollars Only) deposited in Dollar account with my bank which belonged to Mr Mohamed Saleh Ibrahim who died on 25th July,2000 in a plane crash, is an Engineering contractor.My bank has made several efforts at contacting the family of Mohamed Saleh Ibrahim or his relatives, but all have proved abortive as he had no identifiable kins men. This sum of US$11.183M has remained unclaimed ever since then and nobody has come forward as his next of kin. The management under the influence of our chairman and member of the board of directors has made an arrangement for the fund to be declared unclaimable and subsequently be turned to the reserve account of the bank. It is against the background of the foregoing,that two of my colleagues and myself in the bank have decided to contact you for assistance and partnership, for you to stand as the next of kin to Mr Mohamed Saleh Ibrahim. With your permission this fund will be transferred to your private account abroad as the beneficiary and next of kin to Mr Mohamed Saleh Ibrahim . All proof of claim and necessary documentation will be carefully worked out in your favour and we assure you of 100% risk free involvement and protection. consequently, if you find this proposal acceptable to you and you wish to assist us, I expect your urgent response and upon receipt of that,we shall discuss and agree on the disbursement and sharing ratio.Let me therefore expect your very urgent response through my phone,or e-mail addresses. Please endeavour to include your private phone and fax number and also your private e-mail where available. Please keep this proposal very secret and confidential. Thank you and best regards as I await your urgent response. yours Faithfully, Adams. +229-280-899 ------------------------------------------ Faites un voeu et puis Voila ! www.voila.fr


Energy demand around the globe is projected to increase by more than 50% over the next 35 years, and sustainable, low-carbon footprint energy resources are needed to meet this increasing energy demand. While electricity generation from renewable sources is expected to grow over the next 25 years, the viability of this form of energy generation is challenged by the uneven nature of electricity production from many renewable sources, such as wind or solar power, so energy storage solutions (such as the vanadium redox flow battery depicted below) are needed to capture this energy and provide it to the grid as needed.
Large-scale flow batteries are being developed to meet these energy storage needs. Additionally, energy generation technologies, such as reverse electrodialysis and capacitive mixing, that harness energy from salt concentration differences are being developed, and these technologies seek to produce electricity by taking advantage of the chemical energy contained in solutions of different concentration. These technologies rely on polymer membranes to regulate ion transport.
Membranes for energy technologies must be designed to function efficiently in ionic environments that are often very different from those encountered in natural water sources. Little is known about how different ions and complex ion mixtures influence polymer membrane transport properties, and our research seeks to understand fundamental relationships between ions and polymers that contribute to selectivity in energy applications. Improved membrane selectivity, achieved by optimizing polymer chemistry and structure, for energy applications will enable development of improved renewable energy storage and generation technologies.


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PWARC Celebrates Third Anniversary
No one went home hungry when the Pueblo West Amateur
Radio Club held its Third Anniversary Party on Wednesday, August 22,
at Pueblo West Library. The covered dish supper drew 20 hungry
members, spouses and guests.
PWARC President Jane Ewing was caught with two plates,
but she said one was for husband Bill. HI HI
Photo by Bill Fortune, KD0RPD |
|
|
Photo by Paul Sipes, KB0JIT |
PWARC Presents Elmer Award to WA0KAQ
Neal Tew (L), KD0MBL, presented Bill Ewing, WA0KAQ,
with an ARRL Elmer Award at the club's August 11, 2012 meeting. Neal
stated the award was being presented to the club's founder, although
he is grateful for everyone's assistance through the last two years
and for the fun he has had during that time.
Bill thanked Neal and told the members that he is
proud of every one of them. "Almost every day I hear how nice
the members are and how helpful the members have been to other hams,
whether or not they are members. This is a great bunch of hams we
have here. I'm proud of all of you for what you've done." |
|
Photos by Neal Tew, KD0MBL |
449.275 Repeater Node
K0JSC installed a UHF repeater node in Pueblo West on
August 6, 2012. The node links to Canon City and Pueblo and can be
linked to other repeaters in the area. |
|
|
KY6YYY Presents WA0KAQ With "Memory Book"
David Yeater, KY6YYY (seated right) presented Bill
Ewing, WA0KAQ, with a beautiful "Memory Book" at the July
14 PWARC meeting.
David included photos of Bill & Jane, PWARC
members, family members, friends awards received, events Bill
attended, and other club activities. The book is very much appreciated.
Photo by Paul Sipes, KB0JIT |
|
Mishelle Oakley Receives
First PWARC Scholarship
It gives Pueblo West Amateur Radio Club great pleasure
to present its first annual scholarship in the amount of $250 to
Michelle Oakley.
Michelle is a 2012 graduate of Pueblo West High School
and will attend Pueblo Community College, majoring in Biology and
minoring in Education.
Michelle won many honors and academic awards in math,
science and band during her time in high school.
In her application, Michelle stated, "My dream is
to become a teacher! I can not wait for the moments ahead when I
achieve this. Once I start teaching Biology in high school, I plan to
make science fun for my students." |
|
|


Scarborough Road, London, N9
Guide Price £600,000 - £625,000. Having been recently fully refurbished this Edwardian 3 bedroom (easily converted to the original 4 bedroom) semi detached family home within walking distance of Mottingham Rail Station is perfect for those needing daily access to London for their commute. Fully rewired and with a completely new plumbing system, the property now comprises of a large reception, beautiful fitted kitchen, shower room and dining room downstairs, and upstairs three double bedrooms (of which 2 are very large double rooms) and a family bathroom. The property also benefits from a new boiler, under floor heating in both bathrooms and the kitchen, Cat6 data cabling to all rooms, double glazing, a 76" rear garden and off street parking to the front.
ENTRANCE HALL
RECEPTION ROOM 13' 11" x 12' 3" (4.24m x 3.73m)
KITCHEN 11' 3" x 10' 4" (3.43m x 3.15m)
DINING ROOM 17' 4" x 11' 7" (5.28m x 3.53m)
SHOWER ROOM
LANDING
BEDROOM 1 16' 8" x 11' 5" (5.08m x 3.48m)
BEDROOM 2 17' 2" x 11' 8" (5.23m x 3.56m)
BEDROOM 3 11' 4" x 10' 3" (3.45m x 3.12m)
BATHROOM
GARDEN 76' x 24' 9" (23.16m x 7.54m)
STORE
IMPORTANT NOTE Please note that all measurements are approximate. We have not tested any services or appliances at this property. We strongly recommend that all the information which we provide is verified by yourself on inspection, by your Surveyor and also your Conveyancer.


{% extends 'wildlifecompliance/emails/base_email.html' %} {% block content %}
The address for an organisation you are linked to has been updated by {{address_updated_by.get_full_name}} ({{address_updated_by.email}}).
Organisation: {{ organisation.name }}
ABN: {{ organisation.abn }}
Address: {{ organisation.postal_address.line1 }}, {{ organisation.postal_address.locality }}, {{ organisation.postal_address.state }}, {{ organisation.postal_address.postcode}}, {{ organisation.postal_address.country}}
{% endblock %}


The JSON output from different Server APIs can range from simple to highly nested and complex. The examples on this page attempt to illustrate how the JSON Data Set treats specific formats, and gives examples of the different constructor options that allow the user to tweak its behavior. See our JSON Primer for more information.
Be sure to check out the "What's Not Supported" section.
If the JSON data describes an array, and each element of that array is of a basic type (number, string, boolean, or null):
[ 100, 500, 300, 200, 400 ]
the JSON DataSet will create a row for each element in the JSON array, and store its value in a column named "column0".
var dsExample1 = new Spry.Data.JSONDataSet("../../data/json/array-01.js"); ...
 Values from array: {column0}

Here is a live example:
If the JSON data describes an array, and each element of that array is an object:
[ { color: "red", value: "#f00" }, { color: "green", value: "#0f0" }, { color: "blue", value: "#00f" }, { color: "cyan", value: "#0ff" }, { color: "magenta", value: "#f0f" }, { color: "yellow", value: "#ff0" }, { color: "black", value: "#000" } ]
the JSON Data Set will create a row for each object in the array, and each property on the object will become a column.
var dsExample2 = new Spry.Data.JSONDataSet("../../data/json/array-02.js");
...
 Values from array: {color}({value})

Here's a live example:
If the JSON data describes an object:
{ color: "red", value: "#f00" }
the JSON Data Set will create a single row for the object, and each property on the object will become a column. The data set will only contain one row of data.
var dsExample3 = new Spry.Data.JSONDataSet("../../data/json/array-03.js");
...
 Values from object: {color}({value})

Here is a live example:
The objects returned from most Server APIs are highly nested:
{ "id": "0001", "type": "donut", "name": "Cake", "ppu": 0.55, "batters": { "batter": [ { "id": "1001", "type": "Regular" }, { "id": "1002", "type": "Chocolate" }, { "id": "1003", "type": "Blueberry" }, { "id": "1004", "type": "Devil's Food" } ] }, "topping": [ { "id": "5001", "type": "None" }, { "id": "5002", "type": "Glazed" }, { "id": "5005", "type": "Sugar" }, { "id": "5007", "type": "Powdered Sugar" }, { "id": "5006", "type": "Chocolate with Sprinkles" }, { "id": "5003", "type": "Chocolate" }, { "id": "5004", "type": "Maple" } ] }
If the data you want to extract out is not at the top-level of the JSON object, you can tell the JSON data set where to find it by using the "path" constructor option. In this example, we want to extract out all of the "batter" data:
var dsExample4 = new Spry.Data.JSONDataSet("../../data/json/object-02.js", { path: "batters.batter" }); ...

Batters:

{type} ({id})

The path is simply the set of properties used to traverse the object's structure, separated by dots. Here's a live example:
Batters:
In the case where you have an array of highly nested objects:
[ { "id": "0001", "type": "donut", "name": "Cake", "ppu": 0.55, "batters": { "batter": [ { "id": "1001", "type": "Regular" }, { "id": "1002", "type": "Chocolate" }, { "id": "1003", "type": "Blueberry" }, { "id": "1004", "type": "Devil's Food" } ] }, "topping": [ { "id": "5001", "type": "None" }, { "id": "5002", "type": "Glazed" }, { "id": "5005", "type": "Sugar" }, { "id": "5007", "type": "Powdered Sugar" }, { "id": "5006", "type": "Chocolate with Sprinkles" }, { "id": "5003", "type": "Chocolate" }, { "id": "5004", "type": "Maple" } ] }, { "id": "0002", "type": "donut", "name": "Raised", "ppu": 0.55, "batters": { "batter": [ { "id": "1001", "type": "Regular" } ] }, "topping": [ { "id": "5001", "type": "None" }, { "id": "5002", "type": "Glazed" }, { "id": "5005", "type": "Sugar" }, { "id": "5003", "type": "Chocolate" }, { "id": "5004", "type": "Maple" } ] }, { "id": "0003", "type": "donut", "name": "Old Fashioned", "ppu": 0.55, "batters": { "batter": [ { "id": "1001", "type": "Regular" }, { "id": "1002", "type": "Chocolate" } ] }, "topping": [ { "id": "5001", "type": "None" }, { "id": "5002", "type": "Glazed" }, { "id": "5003", "type": "Chocolate" }, { "id": "5004", "type": "Maple" } ] } ]
the JSON data set uses the "path" constructor option to extract the matching data out from each object in the array. Each match then becomes a row in the data set. In this example, we want the data set to select all of the "batter" objects and flatten them into rows:
var dsExample5 = new Spry.Data.JSONDataSet("../../data/json/array-03.js", { path: "batters.batter" });
...

Batters:

{type} ({id})

Here's a live example:
Batters:
Some JSON formats use nested structures to simply group data together. An example of this would be the "image" and "thumbnail" properties in the following example:
{ "id": "0001", "type": "donut", "name": "Cake", "image": { "url": "images/0001.jpg", "width": 200, "height": 200 }, "thumbnail": { "url": "images/thumbnails/0001.jpg", "width": 32, "height": 32 } }
It is sometimes desirable to flatten these structures so they are also available as columns in the data set. You can use the "subPaths" constructor option to tell the JSON Data Set to include these nested structures when it flattens the top-level JSON object, or the data selected by the "path" constructor option. In this particular example, because we have not specified a "path" constructor option, the JSON data set will attempt to flatten the top-level object. Since we want to also include the data from the "image" nested structure, we specify the path to the data which is simply "image".
var dsExample6 = new Spry.Data.JSONDataSet("../../data/json/object-03.js", { subPaths: "image" }); ...

 id	 type	 name	 image.width	 image.height	 image.url

 {id}	 {type}	 {name}	 {image.width}	 {image.height}	 {image.url}

The properties within the nested "image" structure are now accessible from within the data set. Notice that the names of the columns are all prefixed by "image.". Here's a live example:
| id | type | name | image.width | image.height | image.url |
|---|---|---|---|---|---|
| {id} | {type} | {name} | {image.width} | {image.height} | {image.url} |
You can specify multiple paths in the "subPaths" constructor option. So if you wanted to include both "image" and "thumbnail" in the flattening process, you simply pass an array of strings:
var dsExample7 = new Spry.Data.JSONDataSet("../../data/json/object-03.js", { subPaths: [ "image", "thumbnail" ] }); ...

 id	 type	 name	 image.width	 image.height	 image.url	 thumbnail.width	 thumbnail.height	 thumbnail.url

 {id}	 {type}	 {name}	 {image.width}	 {image.height}	 {image.url}	 {thumbnail.width}	 {thumbnail.height}	 {thumbnail.url}

Here is a live example:
| id | type | name | image.width | image.height | image.url | thumbnail.width | thumbnail.height | thumbnail.url |
|---|---|---|---|---|---|---|---|---|
| {id} | {type} | {name} | {image.width} | {image.height} | {image.url} | {thumbnail.width} | {thumbnail.height} | {thumbnail.url} |
This example shows the use of the "path" constructor option to extract out the data items. This is nothing different from some of the previous examples, but we will build on this in the next example. An abbreviated version of the JSON data is included here for reference. You can see the full JSON data used by this example here.
{
"items":
{
"item":
[
{
"id": "0001",
"type": "donut",
"name": "Cake",
"ppu": 0.55,
"batters":
{
"batter":
[
{ "id": "1001", "type": "Regular" },
{ "id": "1002", "type": "Chocolate" },
{ "id": "1003", "type": "Blueberry" },
{ "id": "1004", "type": "Devil's Food" }
]
},
"topping":
[
{ "id": "5001", "type": "None" },
{ "id": "5002", "type": "Glazed" },
{ "id": "5005", "type": "Sugar" },
{ "id": "5007", "type": "Powdered Sugar" },
{ "id": "5006", "type": "Chocolate with Sprinkles" },
{ "id": "5003", "type": "Chocolate" },
{ "id": "5004", "type": "Maple" }
]
},
...
]
}
}
In this example, we are simply going to list the types of items in our JSON object. We are going to use the "path" constructor option to select out all of the "item" objects, and then display the info we get in a table:
var dsExample8 = new Spry.Data.JSONDataSet("../../data/json/donuts.js", { path: "items.item" }); ...

 id	 type	 name

 {id}	 {type}	 {name}

Using the path "items.item" will result in a data set that has the following columns defined for each row:
| ds_RowID | id | type | name | ppu |
|---|
Here is a live example:
| id | type | name |
|---|---|---|
| {id} | {type} | {name} |
This example builds on Example 8 to show what happens when you select a set of repeating structures with the "subPaths" constructor option.
{
"items":
{
"item":
[
{
"id": "0001",
"type": "donut",
"name": "Cake",
"ppu": 0.55,
"batters":
{
"batter":
[
{ "id": "1001", "type": "Regular" },
{ "id": "1002", "type": "Chocolate" },
{ "id": "1003", "type": "Blueberry" },
{ "id": "1004", "type": "Devil's Food" }
]
},
"topping":
[
{ "id": "5001", "type": "None" },
{ "id": "5002", "type": "Glazed" },
{ "id": "5005", "type": "Sugar" },
{ "id": "5007", "type": "Powdered Sugar" },
{ "id": "5006", "type": "Chocolate with Sprinkles" },
{ "id": "5003", "type": "Chocolate" },
{ "id": "5004", "type": "Maple" }
]
},
...
]
}
}
In this example, we are going to also select the "batter" objects with our "subPaths" constructor option, then display all of our data set rows in a table.
var dsExample9 = new Spry.Data.JSONDataSet("../../data/json/donuts.js", { path: "items.item", subPaths: "batters.batter" }); ...

 id	 type	 name	 batter

 {id}	 {type}	 {name}	 {batters.batter.type}

Using the path "items.item" and subPath "batters.batter" will result in a data set that has the following columns defined for each row:
| ds_RowID | id | type | name | ppu | batters.batter.id | batters.batter.type |
|---|
Here is a live example:
| id | type | name | batter |
|---|---|---|---|
| {id} | {type} | {name} | {batters.batter.type} |
If you compare the results above against what you see in Example 8, the first thing you will notice is that we now have more rows then we used to. What is basically happening here is that each top-level object matched by the "path" constructor option is merged with any objects that were matched by the paths in the "subPaths" constructor option. If more than one object is matched below a given top-level object, a row is created for every object matched so that its data can be accommodated.
This example builds on Example 9 to show what happens when you select another set of repeating structures with the "subPaths" constructor option.
9{ "items": { "item": [ { "id": "0001", "type": "donut", "name": "Cake", "ppu": 0.55, "batters": { "batter": [ { "id": "1001", "type": "Regular" }, { "id": "1002", "type": "Chocolate" }, { "id": "1003", "type": "Blueberry" }, { "id": "1004", "type": "Devil's Food" } ] }, "topping": [ { "id": "5001", "type": "None" }, { "id": "5002", "type": "Glazed" }, { "id": "5005", "type": "Sugar" }, { "id": "5007", "type": "Powdered Sugar" }, { "id": "5006", "type": "Chocolate with Sprinkles" }, { "id": "5003", "type": "Chocolate" }, { "id": "5004", "type": "Maple" } ] }, ... ] } }
In this example, we are going to also select the "topping" objects with our "subPaths" constructor option, then display all of our data set rows in a table.
var dsExample10 = new Spry.Data.JSONDataSet("../../data/json/donuts.js", { path: "items.item", subPaths: [ "batters.batter", "topping" ] }); ...

 id	 type	 name	 batter	 topping

 {id}	 {type}	 {name}	 {batters.batter.type}	 {topping.type}

Using the path "items.item" and sub paths "batters.batter" and "topping", will result in a data set that has the following columns defined for each row:
| ds_RowID | id | type | name | ppu | batters.batter.id | batters.batter.type | topping.id | topping.type |
|---|
Here is a live example:
| id | type | name | batter | topping |
|---|---|---|---|---|
| {id} | {type} | {name} | {batters.batter.type} | {topping.type} |
We get even more rows than we had in Example 9 because the "topping" path also selected multiple objects in some cases. So for every top-level object matched by the "paths" constructor option, we get 'm*n' rows, where 'm' is the number of matches by the "batters.batter" sub path, and 'n' is the number of matches by the "topping" sub path.
Sometimes you want to work with nested structures, but you don't want to deal with the explosion of rows as shown in Example 10. Imagine you want to show a list of the different types of items, and under each item, you also want to list the different types of batters and toppings available. Doing that with the data set used in Example 10 would require some JavaScript logic embedded in spry attribute conditionals to control when things showed up. A simpler approach would be to use NestedJSONDataSets.
In this example we use the same JSON data used in Example 10, but we will use 2 nested JSON data sets to track the "batter" and "topping" data. Nested data sets are special data sets that stay in sync with the current row of their parent data set. As the current row of the parent data set changes, so does the data inside of the nested data set.
var dsExample11_Items = new Spry.Data.JSONDataSet("../../data/json/donuts.js", { path: "items.item" }); var dsExample11_Batters = new Spry.Data.NestedJSONDataSet(dsExample11_Items, "batters.batter"); var dsExample11_Toppings = new Spry.Data.NestedJSONDataSet(dsExample11_Items, "topping"); ...

 {dsExample11_Items::name}

Batters:

{dsExample11_Batters::type}

 Toppings:

{dsExample11_Toppings::type}

The other interesting thing about nested data sets is that if their parent data set is used in a spry:repeat or spry:repeatchildren context, any data references from the nested data set are kept in sync with whatever the current row is that is being processed by the loop.
Here is a live example.
Although you can use nested data sets to produce a table that looks like the one in Example 9, there's an important difference. Nested data sets can only sort and filter within groups constrained by the parent's row it is associated with. It is easier to illustrate this with an example. In this example, we have a table that looks like the one in Example 9 on the left side, and on the right side, we have the same data presented as a set of nested lists.
var dsExample12_Items = new Spry.Data.JSONDataSet("../../data/json/donuts.js", { path: "items.item" }); var dsExample12_Batters = new Spry.Data.NestedJSONDataSet(dsExample12_Items, "batters.batter"); ...

 id	 type	 name	 batter

 {dsExample12_Items::id}	 {dsExample12_Items::type}	 {dsExample12_Items::name}	 {dsExample12_Batters::type}

 {dsExample12_Items::name}

Batters:

{dsExample12_Batters::type}

Here's the live example:
|
|
Notice that when you sort any column associated with the parent data set, all of the rows in the table shift around, whereas when you click on the batter column, it seems as if only the data in the batter column is moving around. If you look at what happens in the list on the right as you sort, it becomes more apparent what is happening.


Creates a new standard or FIFO queue or returns the URL of an existing queue. You can pass one or more attributes in the request. Keep the following caveats in mind:
Note
You can't change the queue type after you create it and you can't convert an existing standard queue into a FIFO queue. You must either create a new FIFO queue for your application or delete your existing standard queue and recreate it as a FIFO queue. For more information, see Moving From a Standard Queue to a FIFO Queue in the Amazon SQS Developer Guide .
To successfully create a new queue, you must provide a queue name that adheres to the limits related to queues and is unique within the scope of your queues.
To get the queue URL, use the `` get-queue-url `` action. `` get-queue-url `` requires only the QueueName parameter. be aware of existing queue names:
Note
Some actions take lists of parameters. These lists are specified using the param.n notation. Values of n are integers starting from 1. For example, a parameter list with two elements looks like this:
Attribute.1=this
Attribute.2=that
See also: AWS API Documentation
create-queue
--queue-name <value>
[--attributes <value>]
[--cli-input-json <value>]
[--generate-cli-skeleton <value>]
The name of the new queue. The following limits apply to this name:
- A queue name can have up to 80 characters.
- Valid values: alphanumeric characters, hyphens (- ), and underscores (_ ).
- A FIFO queue name must end with the .fifo suffix.
Queue names are case-sensitive.
A map of attributes with their corresponding values.
The following lists the names, descriptions, and values of the special request parameters that the create-queue action uses:
- DelaySeconds - The number of seconds for which the delivery of all messages in the queue is delayed. Valid values: An integer from 0 to 900 seconds (15 minutes). The default is 0 (zero).
- MaximumMessageSize - The limit of how many bytes a message can contain before Amazon SQS rejects it. Valid values: An integer from 1,024 bytes (1 KiB) to 262,144 bytes (256 KiB). The default is 262,144 (256 KiB).
- MessageRetentionPeriod - The number of seconds for which Amazon SQS retains a message. Valid values: An integer from 60 seconds (1 minute) to 1,209,600 seconds (14 days). The default is 345,600 (4 days).
- Policy - The queue's policy. A valid AWS policy. For more information about policy structure, see Overview of AWS IAM Policies in the Amazon IAM User Guide .
- ReceiveMessageWaitTimeSeconds - The number of seconds for which a `` receive-message `` action waits for a message to arrive. Valid values: An integer from 0 to 20 (seconds). The default is 0 (zero).
- RedrivePolicy - The parameters for the dead letter queue functionality of the source queue. For more information about the redrive policy and dead letter queues, see Using Amazon SQS Dead Letter Queues in the Amazon SQS Developer Guide .
Note
The dead letter queue of a FIFO queue must also be a FIFO queue. Similarly, the dead letter queue of a standard queue must also be a standard queue.
- VisibilityTimeout - The visibility timeout for the queue. Valid values: An integer from 0 to 43,200 (12 hours). The default is 30. For more information about the visibility timeout, see Visibility Timeout in the Amazon SQS Developer Guide .
The following attributes apply only to FIFO (first-in-first-out) queues :
- FifoQueue - Designates a queue as FIFO. You can provide this attribute only during queue creation. You can't change it for an existing queue. When you set this attribute, you must provide a MessageGroupId explicitly. For more information, see FIFO Queue Logic in the Amazon SQS Developer Guide .
- ContentBasedDeduplication - Enables content-based deduplication. For more information, see Exactly-Once Processing in the Amazon SQS Developer Guide .
- Every message must have a unique MessageDeduplicationId ,
- You may provide a MessageDeduplicationId explicitly.
- If you aren't able to provide a MessageDeduplicationId and you enable ContentBasedDeduplication for your queue, Amazon SQS uses a SHA-256 hash to generate the MessageDeduplicationId using the body of the message (but not the attributes of the message).
- If you don't provide a MessageDeduplicationId and the queue doesn't have ContentBasedDeduplication set, the action fails with an error.
- If the queue has ContentBasedDeduplication set, your MessageDeduplicationId overrides the generated one.
- When ContentBasedDeduplication is in effect, messages with identical content sent within the deduplication interval are treated as duplicates and only one copy of the message is delivered.
- You can also use ContentBasedDeduplication for messages with identical content to be treated as duplicates.
- If you send one message with ContentBasedDeduplication enabled and then another message with a MessageDeduplicationId that is the same as the one generated for the first MessageDeduplicationId , the two messages are treated as duplicates and only one copy of the message is delivered.
Any other valid special request parameters (such as the following) are ignored:
- ApproximateNumberOfMessages
- ApproximateNumberOfMessagesDelayed
- ApproximateNumberOfMessagesNotVisible
- CreatedTimestamp
- LastModifiedTimestamp
- QueueArn
Shorthand Syntax:
KeyName1=string,KeyName2=string
Where valid key names are:
All
Policy
VisibilityTimeout
MaximumMessageSize
MessageRetentionPeriod
ApproximateNumberOfMessages
ApproximateNumberOfMessagesNotVisible
CreatedTimestamp
LastModifiedTimestamp
QueueArn
ApproximateNumberOfMessagesDelayed
DelaySeconds
ReceiveMessageWaitTimeSeconds
RedrivePolicy
FifoQueue
ContentBasedDeduplication
JSON Syntax:
{"All"|"Policy"|"VisibilityTimeout"|"MaximumMessageSize"|"MessageRetentionPeriod"|"ApproximateNumberOfMessages"|"ApproximateNumberOfMessagesNotVisible"|"CreatedTimestamp"|"LastModifiedTimestamp"|"QueueArn"|"ApproximateNumberOfMessagesDelayed"|"DelaySeconds"|"ReceiveMessageWaitTimeSeconds"|"RedrivePolicy"|"FifoQueue"|"ContentBasedDeduplication": "string"
...}
--cli-input-json (string) Performs service operation based on the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, the CLI values will override the JSON-provided values.
--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command.
To create a queue
This example creates a queue with the specified name, sets the message retention period to 3 days (3 days * 24 hours * 60 minutes * 60 seconds), and sets the queue's dead letter queue to the specified queue with a maximum receive count of 1,000 messages.
Command:
aws sqs create-queue --queue-name MyQueue --attributes file://create-queue.json
Input file (create-queue.json):
{
"RedrivePolicy": "{\"deadLetterTargetArn\":\"arn:aws:sqs:us-east-1:80398EXAMPLE:MyDeadLetterQueue\",\"maxReceiveCount\":\"1000\"}",
"MessageRetentionPeriod": "259200"
}
Output:
{
"QueueUrl": "https://queue.amazonaws.com/80398EXAMPLE/MyQueue"
}


Jeff Sessions Calls on Pelosi to Bring Impeachment Inquiry to a 'Conclusion' | Breitbart
by Trent BakerIn a Monday interview with “Fox & Friends,” former U.S. Attorney General Jeff Sessions called on House Speaker Nancy Pelosi (D-CA) to bring the impeachment inquiry to a “conclusion.”
Sessions, a candidate for his old U.S. Senate seat in Alabama, said the impeachment probe is “not well-founded,” adding Pelosi is “wrong” to threaten President Donald Trump if he criticizes the Ukraine whistleblower’s identity remaining a secret.
“I think [Pelosi] needs to bring this thing to a conclusion,” Sessions stated. “It’s not well-founded to begin with, but just to pick fights with the president and try to make those kind of threats I think is wrong at this time for sure.”
The former attorney general went on to say it is “unthinkable” that the whistleblower’s name remains a secret if that person is indeed a witness.
“Of course that person eventually would have to be made public, and asking for that is not harassment or not kind of threatening a witness, that’s for sure,” outlined Sessions.
He added, “I truly believe it’s not close to impeachment, it’s not the right way to proceed with this … but to convert a normal political disagreement into an impeachment matter is really a dangerous thing.”
Follow Trent Baker on Twitter @MagnifiTrent


ARKANSAS
AR
The state of Arkansas views cannabis as a criminal substance, prosecuting all who are caught with it and offering no legal means of access for citizens with medical needs.
Simple Possession Consequences:
Under 4 oz
Results in a Misdemeanor,
Up to 1 Year Jail Time
Over 4 oz
Results in a Felony,
Up to 6 Years Jail Time
Over 10 lb
Results in a felony,
Up to 10 Years Jail Time
Sale/Cultivation Consequences:
Sale,
Over 14g
Results in a Felony, Up to 1 Year Jail Time
Cultivation,
Any Amount
May be treated as either possession or sale
Trafficking,
Over 500 lb
Results in a Felony, 10 to 40 Years Jail Time


On June 30, 2016, 5:18pm, a temporary budget was passed.
Governor Rauner’s office announced he’s signed a temporary, patchwork-of-a-budget into law. It’s 11 months, 30 days, 17 hours, 18 minutes late.
At midnight July 1st, it would have been one year. Maybe Gov. Rauner and Democratic leadership in the legislature just didn’t want to face those headlines in the morning. Whatever the sudden source of urgency after so many months—here’s to hoping this will bring some relief to those who have been suffering through this game of chicken.
Here’s the thing, y’all. Yes, K-12 education is funded for a year. And you’ll be happy to know state legislators will likely be paid. But social services are still only 65% funded through the end of the year. What will fall into the 35% gulf?
And what will happen at the end of the year? What can we expect for funding the rest of 2017, and then 2018? Is this just how Illinois State government will (not) function, from now on?
With the budget punted until after the Nov 8 election, state legislators will now take this problem on the campaign trail. Let’s make sure they know we’ll be thinking of that other 35% in the voting booth.
You can find more about the stop-gap budget on some of the sites where we’ve been following the budget impasse this year:
To everyone who has provided information and help on this project, thank you.
Kristi Leach, Cathy Deng & Derek Eder
Chi Hack Night


Ruby: Understanding Enumerable#group_by
June 12, 2015
We have learned about Array and Hash, but it's just half way. Each of them have own methods for adding, deleting and accessing data.  Enumerable gives us lots of useful ways of doing something to every element of a collection object(array, hash) Let's look at the method #group_by: Groups the collection by result of the block. Returns a hash where the keys are the evaluated result from the block and the values are arrays of elements in the collection that correspond to the key. If no block is given an enumerator is returned.
Enumerable#group_by and Arrays
names = ["Julia", "Maxim", "Kate", "Natascha", "Oleg"]
=> ["Julia", "Maxim", "Kate", "Natascha", "Oleg"]
names.group_by {|name| name.length}
=> {5=>["Julia", "Maxim"], 4=>["Kate", "Oleg"], 8=>["Natascha"]}
Explanations
Each name is passed to the block. The result of block is the length of names, and this result is the group into which the name will go.
Enumerable#group_by and Hashes
food = {"Julia" => "fish", "Oleg" => "beef", "Anton" => "pasta", "Nata" => "fish", "Dima" => "chiken", "Kate" => "pasta"}
=> {"Julia"=>"fish", "Oleg"=>"beef", "Anton"=>"pasta", "Nata"=>"fish", "Dima"=>"chiken", "Kate"=>"pasta"}
food.group_by {|key, value| value}
=> {"fish"=>[["Julia", "fish"], ["Nata", "fish"]], "beef"=>[["Oleg", "beef"]], "pasta"=>[["Anton", "pasta"], ["Kate", "pasta"]], "chiken"=>[["Dima", "chiken"]]}
Explanations
In this example we group the people by the food


Buffalo Plains [aw65], plain, in Imperia, peasants: 100
Last updated Turn #103
Buffalo Plains [aw65], plain, in Imperia, peasants: 100
------------------------------------------------------------------------
10: Stefano [t8e], Imperial Empire, the High Priest of the Church of
10: Halon [157], with ten angels, 45 nazgul, arrived from the east,
10: accompanied by:
10: Lord Rodrigo Bane [c8b], Imperial Empire, Bishop of the Church of
10: Dol [153], with five angels, 40 hvy. xbowmen, six nazgul
11: Stefano [t8e], Imperial Empire, the High Priest of the Church of
11: Halon [157], with ten angels, 45 nazgul, went west, accompanied by:
11: Lord Rodrigo Bane [c8b], Imperial Empire, Bishop of the Church of
11: Dol [153], with five angels, 40 hvy. xbowmen, six nazgul
14: Pack of wolves [gq1f], wolves, number: 5, arrived from the west.
16: Pack of wolves [gq1f], wolves, number: 5, went east.
16: Band of thieves [cw4e], bandits, number: 33, arrived from the west.
20: Stack of giants [hf0d] loots the countryside.
23: Temuchin [k8z], refugee, with one worker, one skirmisher, arrived from
23: the east.
26: Band of thieves [cw4e], bandits, number: 33, went east.
27: Temuchin [k8z], refugee, with one worker, one skirmisher, went west.
30: Ronjar [e8y], refugee, with one riding horse, arrived from the west.
30: Faery hill [ba1q] appears here.
Routes leaving Buffalo Plains:
North, plain, to Buffalo Plains [av65], 7 days
East, plain, to Buffalo Plains [aw66], 7 days
South, to Ocean [ax65], Crystal Sea, 2 days
West, plain, to Buffalo Plains [aw64], 7 days
Inner locations:
Faery hill [ba1q], faery hill, 1 day
Seen here:
Stack of nazgul [dk2i], nazgul, number: 3
Stack of giants [hf0d], giants, number: 12
Band of thieves [cw4e], bandits, number: 32
Temuchin [k8z], refugee, with one worker, one skirmisher
Ronjar [e8y], refugee, with one riding horse