0.8 Release¶
Release 0.8.0¶
See also changes in the unreleased 0.7
Release summary¶
The main features of this release are several new time series models based on the statespace framework, multiple imputation using MICE as well as many other enhancements. The codebase also has been updated to be compatible with recent numpy and pandas releases.
Statsmodels is using now github to store the updated documentation which is available under http://www.statsmodels.org/stable for the last release, and http://www.statsmodels.org/devel/ for the development version.
This is the last release that supports Python 2.6.
Warning
API stability is not guaranteed for new features, although even in this case changes will be made in a backwards compatible way if possible. The stability of a new feature depends on how much time it was already in statsmodels master and how much usage it has already seen. If there are specific known problems or limitations, then they are mentioned in the docstrings.
The following major new features appear in this version.
Statespace Models¶
Building on the statespace framework and models added in 0.7, this release includes additional models that build on it. Authored by Chad Fulton largely during GSOC 2015
Kalman Smoother¶
The Kalman smoother (introduced in #2434) allows making inference on the unobserved state vector at each point in time using data from the entire sample. In addition to this improved inference, the Kalman smoother is required for future improvements such as simulation smoothing and the expectation maximization (EM) algorithm.
As a result of this improvement, all state space models now inherit a smooth method for producing results with smoothed state estimates. In addition, the fit method will return results with smoothed estimates at the maximum likelihood estimates.
Postestimation¶
Improved post-estimation output is now available to all state space models (introduced in #2566). This includes the new methods get_prediction and get_forecast, providing standard errors and confidence intervals as well as point estimates, simulate, providing simulation of time series following the given state space process, and impulse_responses, allowing computation of impulse responses due to innovations to the state vector.
Diagnostics¶
A number of general diagnostic tests on the residuals from state space estimation are now available to all state space models (introduced in #2431). These include:
- test_normality implements the Jarque-Bera test for normality of residuals
- test_heteroskedasticity implements a test for homoskedasticity of residuals similar to the Goldfeld-Quandt test
- test_serial_correlation implements the Ljung-Box (or Box-Pierce) test for serial correlation of residuals
These test statistics are also now included in the summary method output. In addition, a plot_diagnostics method is available which provides four plots to visually assess model fit.
Unobserved Components¶
The class of univariate Unobserved Components models (also known as structural time series models) are now available (introduced in #2432). This includes as special cases the local level model and local linear trend model. Generically it allows decomposing a time series into trend, cycle, seasonal, and irregular components, optionally with exogenous regressors and / or autoregressive errors.
Multivariate Models¶
Two standard multivariate econometric models - vector autoregressive moving-average model with exogenous regressors (VARMAX) and Dynamic Factors models - are now available (introduced in #2563). The first is a popular reduced form method of exploring the covariance in several time series, and the second is a popular reduced form method of extracting a small number of common factors from a large dataset of observed series.
Recursive least squares¶
A model for recursive least squares, also known as expanding-window OLS, is now available in statsmodels.regression (introduced in #2830).
Miscellaneous¶
Other improvements to the state space framework include:
- Improved missing data handling #2770, #2809
- Ongoing refactoring and bug fixes in fringes and corner cases
Time Series Analysis¶
Markov Switching Models¶
Markov switching dynamic regression and autoregression models are now available (introduced in #2980 by Chad Fulton). These models allow regression effects and / or autoregressive dynamics to differ depending on an unobserved “regime”; in Markov switching models, the regimes are assumed to transition according to a Markov process.
Statistics¶
- KPSS stationarity, unit root test #2775 (N-Wouda)
- The Brock Dechert Scheinkman (BDS) test for nonlinear dependence is now available (introduced in #934 by Chad Fulton)
- Augmented Engle/Granger cointegration test (refactor hidden function) #3146 (Josef Perktold)
New functionality in statistics¶
Contingency Tables #2418 (Kerby Shedden)
Local FDR, multiple testing #2297 (Kerby Shedden)
Mediation Analysis #2352 (Kerby Shedden)
Confidence intervals for multinomial proportions #3162 (Sebastien Lerique, Josef Perktold)
other:
- weighted quantiles in DescrStatsW #2707 (Kerby Shedden)
Duration¶
Kaplan Meier Survival Function #2614 (Kerby Shedden)
Cumulative incidence rate function #3016 (Kerby Shedden)
other:
- frequency weights in Kaplan-Meier #2992 (Kerby Shedden)
- entry times for Kaplan-Meier #3126 (Kerby Shedden)
- intercept handling for PHReg #3095 (Kerby Shedden)
Imputation¶
new subpackage in statsmodels.imputation
MICE #2076 (Frank Cheng GSOC 2014 and Kerby Shedden)
Imputation by regression on Order Statistic #3019 (Paul Hobson)
Penalized Estimation¶
Elastic net: fit_regularized with L1/L2 penalization has been added to OLS, GLM and PHReg (Kerby Shedden)
GLM¶
Tweedie is now available as new family #2872 (Peter Quackenbush, Josef Perktold)
other:
- frequency weights for GLM (currently without full support) #
- more flexible convergence options #2803 (Peter Quackenbush)
Multivariate¶
new subpackage that currently contains PCA
PCA was added in 0.7 to statsmodels.tools and is now in statsmodels.multivariate
Documentation¶
New doc build with latest jupyter and Python 3 compatibility (Tom Augspurger)
Other important improvements¶
several existing functions have received improvements
- seasonal_decompose: improved periodicity handling #2987 (ssktotoro ?)
- tools add_constant, add_trend: refactoring and pandas compatibility #2240 (Kevin Sheppard)
- acf, pacf, acovf: option for missing handling #3020 (joesnacks ?)
- acf, pacf plots: allow array of lags #2989 (Kevin Sheppard)
- pickling support for ARIMA #3412 (zaemyung)
- io SimpleTable (summary): allow names with special characters #3015 (tvanessa ?)
- tsa tools lagmat, lagmat2ds: pandas support #2310 #3042 (Kevin Sheppard)
- CompareMeans: from_data, summary methods #2754 (Valery Tyumen)
- API cleanup for robust, sandwich covariances #3162 (Josef Perktold)
- influence plot used swapped arguments (bug) #3158
Major Bugs fixed¶
- see github issues
While most bugs are usability problems, there is now a new label type-bug-wrong for bugs that cause that silently incorrect numbers are returned. https://github.com/statsmodels/statsmodels/issues?q=label%3Atype-bug-wrong+is%3Aclosed
Backwards incompatible changes and deprecations¶
- predict now returns a pandas Series if the exog argument is a DataFrame, including missing/NaN values
- PCA moved to multivariate compared to 0.7
Development summary and credits¶
Besides receiving contributions for new and improved features and for bugfixes, important contributions to general maintenance came from
- Kevin Sheppard
- Pierre Barbier de Reuille
- Tom Augsburger
and the general maintainer and code reviewer
- Josef Perktold
Additionally, many users contributed by participation in github issues and providing feedback.
Thanks to all of the contributors for the 0.8 release (based on git log):
Note
- Ashish
- Brendan
- Brendan Condon
- BrianLondon
- Chad Fulton
- Chris Fonnesbeck
- Christian Lorentzen
- Christoph T. Weidemann
- James Kerns
- Josef Perktold
- Kerby Shedden
- Kevin Sheppard
- Leoyzen
- Matthew Brett
- Niels Wouda
- Paul Hobson
- Pierre Barbier de Reuille
- Pietro Battiston
- Ralf Gommers
- Roman Ring
- Skipper Seabold
- Soren Fuglede Jorgensen
- Thomas Cokelaer
- Tom Augspurger
- ValeryTyumen
- Vanessa
- Yaroslav Halchenko
- dhpiyush
- joesnacks
- kokes
- matiumerca
- rlan
- ssktotoro
- thequackdaddy
- vegcev
Thanks to all of the contributors for the 0.7 release:
Note
- Alex Griffing
- Antony Lee
- Chad Fulton
- Christoph Deil
- Daniel Sullivan
- Hans-Martin von Gaudecker
- Jan Schulz
- Joey Stockermans
- Josef Perktold
- Kerby Shedden
- Kevin Sheppard
- Kiyoto Tamura
- Louis-Philippe Lemieux Perreault
- Padarn Wilson
- Ralf Gommers
- Saket Choudhary
- Skipper Seabold
- Tom Augspurger
- Trent Hauck
- Vincent Arel-Bundock
- chebee7i
- donbeo
- gliptak
- hlin117
- jerry dumblauskas
- jonahwilliams
- kiyoto
- neilsummers
- waynenilsen
These lists of names are automatically generated based on git log, and may not be complete.


| Title | {{row.Title === undefined ? '-' : row.Title}} | Company Name | {{row.company === undefined ? '-' : row.company}} | Location | {{row.Location === undefined ? '-' : row.Location}} | History | {{row.Job_Post_History === undefined ? '-' : row.Job_Post_History}} | URL | Link | Ratings | {{row.Ratings === undefined ? '-' : row.Ratings}} | Reviews | {{row.Reviews === undefined ? '-' : row.Reviews}} | Experience | {{row.Experience === undefined ? '-' : row.Experience}} | Salary | {{row.Salary === undefined ? '-' : row.Salary}} | Qualification | {{row.Qualification === undefined ? '-' : row.Qualification}} |
|---|


The design proposal must produce a functional light output. LED mood lights that only 'glow' will not be accepted.
2009
“You should design and develop an LED architectural light fitting. The design should be innovative either in the lighting effect it produces, its operation, its mounting arrangement, or in the way it fits into its surroundings.”
The idea was to use shapes and colors on the floor of London's city hall. The colors and shapes were intended to be used as a measure of the popularity of the politicians in the building at the time.
The first sketches involved mounting LED's on sliding rails that could move to create a shape. However, this first sketch provides no projection mechanism. The sketch above is a different concept that uses reflective fabric to project the light. The shapes are created by shaping the leading edge of the fabric with motors and small cables.
Sketches will only get you so far. To make sure this concept is valid, its important to make sure each of the individual components work. This is a simple piece of cardboard with aluminum foil taped to it. I used this prototype to verify I could project shaped light with a reflective surface.
I made the first prototype to verify the lighting effect was possible. I made this protoype to verify that I could shape the leading edge of a piece of fabric with cables.


{% extends "base_map/base.html" %} {% block header_content %} {% endblock %} {% block content %}
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A channel to discuss trading. For useful links and more info click the pinned messages to the right.
100 messages
Before 05-Dec-19 12:00 AM
Caglio05-Mar-19 01:46 PM
It seems easiest to me to trade into tether
than buy again with tether
ComputerGenie 👴👴👴05-Mar-19 01:46 PM
tether is the 1 coin that I despise more than BTC
Caglio05-Mar-19 01:47 PM
Why, BTC is life
ComputerGenie 👴👴👴05-Mar-19 01:47 PM
Caglio05-Mar-19 01:48 PM
Oh I see
U love BCH right
U are actually roger ver
I thought u are Elon Musk
dukeleto05-Mar-19 01:48 PM
LTC up 12%, nothing fishy there
Caglio05-Mar-19 01:49 PM
LTC is cool coin
Everyone else will follow soon
siu - Chainmakers05-Mar-19 01:49 PM
please, all parents must take care of their children at all times
were are Caglio's parents?

Caglio05-Mar-19 01:56 PM
@siu - Chainmakers son do you think I should invest more money into KMD, or to buy some Verus Coin ?
siu - Chainmakers05-Mar-19 01:56 PM
i dont give investment advice
dukeleto05-Mar-19 01:56 PM
@Caglio kmd gives you 5% apr for clicking one button per month, not quite the same with vrsc, you have to have a "staking wallet" and hope for staking rewards based on your % ownership of total supply
this is also not investment advice, just the facts ma'am
Caglio05-Mar-19 01:58 PM
That is true, I already earned over 10 coins
dukeleto05-Mar-19 01:58 PM
neither of those apply if you keep it on an exchange, like a total newb
Caglio05-Mar-19 01:58 PM
Which is almost 10$ and I appreciate that
But I heard Verus Coin is gonna have a big pump soon, I joined some groups
Thats why I am asking
dukeleto05-Mar-19 01:59 PM
pump groups, oh my
Caglio05-Mar-19 01:59 PM
I thought about pawning my fiancees rings, and investing in that, so I can take her out for a cruise
dokrates05-Mar-19 01:59 PM
btc pumping
any news? bakkt or any
Caglio05-Mar-19 01:59 PM
But its kinda fishy right
dukeleto05-Mar-19 02:01 PM
i am amazed that people still spend money on paid pump+dump groups(edited)
this channel will tell you about your favorite shitcoin for free
Caglio05-Mar-19 02:02 PM
You think its a pump and dump scheme ?
@dukeleto i guess ur right tho
dukeleto05-Mar-19 02:03 PM
i think pump+dump groups are a scheme
Caglio05-Mar-19 02:04 PM
I never tried it, but I kinda understand how it works
dukeleto05-Mar-19 02:04 PM
I have been mining VRSC since almost it's genblock, it's a legit project if that is what you are asking. No idea what the pump+dump groups are trying to say about it, tho.
Caglio05-Mar-19 02:05 PM
I havent heard of it till yesterday tbh
siu - Chainmakers05-Mar-19 02:05 PM
so far looking like support retest
Caglio05-Mar-19 02:06 PM
I never understood those charts
Ppl drawing lines and what ?
dukeleto05-Mar-19 02:06 PM
it's called "math"
also "lying with statistics"
and "smoking hopium with numbers"
siu - Chainmakers05-Mar-19 02:07 PM
In this specific chart we only work with moving averages
40minutes of technical analysis on all major altcoins, stuff like that. And he manages funds for people, so he is getting paid to do this research, regardless. He doesn't shill anything in particular
Technical Analysis Insights from Brave New Coin. The coverage spans every aspect of the Cryptocurrency and Blockchain Ecosystem, including its impact on the greater FinTech and Payments space.
It would be nice if BTC would just hit 5K today and get it over with
1
Caglio05-Mar-19 02:46 PM
Haha yes
Cryptoon05-Mar-19 03:20 PM
Josh also said 33k btc by july 2018 tho :p
Anyway, I also like his analysis nonetheless
ComputerGenie 👴👴👴05-Mar-19 03:25 PM
kmd gives you 5% apr for clicking one button per monthgoes looking for the button to click in komodod that @dukeleto is talking about
Caglio05-Mar-19 03:38 PM
@ComputerGenie 👴👴👴 ur such a comedian
dukeleto05-Mar-19 03:47 PM
@ComputerGenie 👴👴👴 collecting interest is pretty annoying via the cli, especially if you have bajillions of utxos, the button you need to hit is slamming your head repeatedly into the closest wooden furniture
1
ComputerGenie 👴👴👴05-Mar-19 03:53 PM
I only consolidate 30-60 UTXOs a day, because I'm too poor to have bajillions


REFLECTOR OF ZANZIBAR'S BEAUTY
home
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» Tours
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EBD - Easton Bible DIctionary
Fury
FURY
"FURY "as attributed to God, is a figurative expression for dispensing afflictive judgments (
Leviticus 26:28
;
Job 20:23
;
Isaiah 63:3
;
Jeremiah 4:4
;
Ezekiel 5:13
;
Daniel 9:16
;
Zechariah 8:2
).
G
"FURY "as attributed to God, is a figurative expression for dispensing afflictive judgments (Leviticus 26:28; Job 20:23; Isaiah 63:3; Jeremiah 4:4; Ezekiel 5:13; Daniel 9:16; Zechariah 8:2).
G


The command line tools (obomerge, obo2obo, obo2flat, obodiff) do not use the same memory management settings as OBO-Edit. Their memory settings are configured independently by passing options directly to the Java interpreter.
This is done through the use of a .vmoptions file. Each command-line utility may have a file named <utility name>.vmoptions in the same directory as the utility. Each line of this file should contain a single option to be passed directly to the Java virtual machine. The last line of this file MUST BE BLANK! Otherwise the options file will not be read correctly.
To run obomerge with 1024M of memory, create a text file named obomerge.vmoptions in the same directory as the obomerge utility with the following contents:
-Xmx1024M
Note the blank line at the end of the file.


No issue selected
Activity
Lorem sdhgbaskdhģakhdakshdģak dsahgdahšķdģāksdhģa
Posted by: Aaaa
Date: 16.07.2019
Replies: 14
Is solved: false
Description:
Posted by: User
Date: 16.07.2019
Date: 16.07.2019
Activity
Posted by: Aaaa
Date: 16.07.2019
Replies: 14
Is solved: false


The image found in this paragraph has its bottom edge aligned with the baseline of the text in the paragraph.


Warning !
Best check yo self, you're not looking too good.
Oh snap! Change a few things up and try submitting again.
Well done! You successfully read this important alert message.
Heads up! This alert needs your attention, but it's not super important.


coordinatetransformation¶
Error message
No PROJ.4 translation for source SRS, coordinatetransformation initialization has failed. Fusion Warning: Invalid extents for raster product: nsew
Description
The data that you are attempting to process does not contain valid Projection information, or the extents of the data extend beyond 180 (or -180) degrees.
Resolution
To verify that data has a projection, run:
geinfo {sourcedatafile}
Use getranslate
to assign projection information to the data,
or gereproject
to give the data a projection that is readable
by GEE.


|
CoAP Protobuf RPC library
0.0.1
|
Server Handling for CoAP protocol. More...
#include "RpcServer.h"
Functions | |
| void | coappbrpc::return_handler (coap_context_t *ctx, struct coap_resource_t *resource, coap_session_t *session, coap_pdu_t *request, coap_binary_t *token, coap_string_t *query, coap_pdu_t *response) |
| Callback function that sets response data to be sent back to RPC client. More... | |
Server Handling for CoAP protocol.
| void coappbrpc::return_handler | ( | coap_context_t * | ctx, |
| struct coap_resource_t * | resource, | ||
| coap_session_t * | session, | ||
| coap_pdu_t * | request, | ||
| coap_binary_t * | token, | ||
| coap_string_t * | query, | ||
| coap_pdu_t * | response | ||
| ) |
Callback function that sets response data to be sent back to RPC client.
| ctx | Coap context variable reference of type struct coap_context_t. |
| resource | Coap resource referece. |
| session | Coap Session variable reference of type coap_session_t |
| request | CoAP PDU request received by server |
| token | CoAP unique token references |
| query | CoAP query reference |
| response | CoAP PDU response reference for storing data to be returned from Server |


--- title: Apply 1D conv with un-shared weights. type: docs repo: https://github.com/rstudio/keras menu: main: name: Apply 1D conv with un-shared weights. - keras parent: keras-reference aliases: - /reference/keras/k_local_conv1d.html - /keras/reference/k_local_conv1d.html - /guide/keras/reference/k_local_conv1d.html - /tools/tools/keras/reference/k_local_conv1d.html - /installation/keras/reference/k_local_conv1d.html - /tutorials/keras/reference/k_local_conv1d.html - /guide/tools/keras/reference/k_local_conv1d.html - /deploy/keras/reference/k_local_conv1d.html - /tools/keras/reference/k_local_conv1d.html - /tutorials/tools/keras/reference/k_local_conv1d.html ---
Apply 1D conv with un-shared weights.
k_local_conv1d(inputs, kernel, kernel_size, strides, data_format = NULL)
| inputs | 3D tensor with shape: (batch_size, steps, input_dim) |
| kernel | the unshared weight for convolution, with shape (output_length, feature_dim, filters) |
| kernel_size | a list of a single integer, specifying the length of the 1D convolution window |
| strides | a list of a single integer, specifying the stride length of the convolution |
| data_format | the data format, channels_first or channels_last |
the tensor after 1d conv with un-shared weights, with shape (batch_size, output_length, filters)
This function is part of a set of Keras backend functions that enable lower level access to the core operations of the backend tensor engine (e.g. TensorFlow, CNTK, Theano, etc.).
You can see a list of all available backend functions here: https://keras.rstudio.com/articles/backend.html#backend-functions.


No one can do everything, but everyone can do something
Contact us and tell us more about your story and ideas
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This post is dedicated to margin management in base R
.
It describes how to use the par
function to call the
mar
and oma
parameters: the 2 types of
margin.
There are 2 margin areas in base R
plots:
margin
and oma
. You can control their size
calling the par()
function before your plot and giving
the corresponding arguments:
mar()
for margin.oma()
for outer margin area.
For both arguments, you must give four values giving the desired
space in the bottom, left, top and right part of the chart
respectively. For instance, par(mar=c(4,0,0,0))
draws a
margin of size 4 only on the bottom of the chart.
You can use mai()
and omi()
if you want to
set the areas in inches and not in lines.
# Margins area
par(oma=c(3,3,3,3)) # all sides have 3 lines of space
par(mar=c(5,4,4,2) + 0.1)
# Plot
plot(0:10, 0:10, type="n", xlab="X", ylab="Y") # type="n" hides the points
# Place text in the plot and color everything plot-related red
text(5,5, "Plot", col="red", cex=2)
box(col="red")
# Place text in the margins and label the margins, all in forestgreen
mtext("Margins", side=3, line=2, cex=2, col="forestgreen")
mtext("par(mar=c(b,l,t,r))", side=3, line=1, cex=1, col="forestgreen")
mtext("Line 0", side=3, line=0, adj=1.0, cex=1, col="forestgreen")
mtext("Line 1", side=3, line=1, adj=1.0, cex=1, col="forestgreen")
mtext("Line 2", side=3, line=2, adj=1.0, cex=1, col="forestgreen")
mtext("Line 3", side=3, line=3, adj=1.0, cex=1, col="forestgreen")
box("figure", col="forestgreen")
# Label the outer margin area and color it blue
# Note the 'outer=TRUE' command moves us from the figure margins to the outer margins.
mtext("Outer Margin Area", side=1, line=1, cex=2, col="blue", outer=TRUE)
mtext("par(oma=c(b,l,t,r))", side=1, line=2, cex=1, col="blue", outer=TRUE)
mtext("Line 0", side=1, line=0, adj=0.0, cex=1, col="blue", outer=TRUE)
mtext("Line 1", side=1, line=1, adj=0.0, cex=1, col="blue", outer=TRUE)
mtext("Line 2", side=1, line=2, adj=0.0, cex=1, col="blue", outer=TRUE)
box("outer", col="blue")


|
Subor SDK API
0.9.3
|
A Game Manifest that includes patch information. More...
#include <RuyiNetGameManifest.h>
Classes | |
| struct | Patch |
| Represents a game patch. More... | |
Public Member Functions | |
| RuyiNetGameManifest () | |
| RuyiNetGameManifest (RuyiNetGetGameManifestResponse &response) | |
| Construction from a response More... | |
| void | GetDataFromGameManifestResponse (RuyiNetGetGameManifestResponse &response) |
| Get Data from JSON response class. More... | |
Public Attributes | |
| std::string | GameId |
| The Game ID this manifest represents. More... | |
| std::string | LatestVersion |
| The latest version of the game. More... | |
| std::vector< Patch > | PatchInfo |
| A list of patches for this game. More... | |
| int | Status |
| The status of the response data (compare to RuyiNetHttpStatus.OK). More... | |
A Game Manifest that includes patch information.
|
inline |
|
inline |
Construction from a response
| response | The response class to convert from. |
|
inline |
Get Data from JSON response class.
| other |
| std::string Ruyi::SDK::Online::RuyiNetGameManifest::GameId |
The Game ID this manifest represents.
| std::string Ruyi::SDK::Online::RuyiNetGameManifest::LatestVersion |
The latest version of the game.
| std::vector<Patch> Ruyi::SDK::Online::RuyiNetGameManifest::PatchInfo |
A list of patches for this game.
| int Ruyi::SDK::Online::RuyiNetGameManifest::Status |
The status of the response data (compare to RuyiNetHttpStatus.OK).


!Newbie Guide:
Select the one you seek below. Their location will be indicated on the radar.
[npc_%objectId%_NpcLocationInfo 30153|Warehouse Keeper Markius]
[npc_%objectId%_NpcLocationInfo 30152|Warehouse Keeper Julia]
[npc_%objectId%_NpcLocationInfo 30151|Warehouse Freightman Chad]
[npc_%objectId%_Link default/NPCloc/30599.htm|Back To The Main List]


HOANG QUOC CUONG
Hi, I'm
MSV<PHONE_NUMBER>0191
I am an IT student of Vinh university at fourth year
My home town is vinh city where i currently live and working
At this time, i'm dreaming to become front-end developer
This is not a easy way to go
but i will try my best.


Amelogenin signal peptide mutation: correlation between mutations in the amelogenin gene (AMGX) and manifestations of X-linked amelogenesis imperfecta.
Formation of tooth enamel is a poorly understood biological process. In this study we describe a 9-bp deletion in exon 2 of the amelogenin gene (AMGX) causing X-linked hypoplastic amelogenesis imperfecta, a disease characterized by defective enamel. The mutation results in the loss of 3 amino acids and exchange of 1 in the signal peptide of the amelogenin protein. This deletion in the signal peptide probably interferes with translocation of the amelogenin protein during synthesis, resulting in the thin enamel observed in affected members of the family. We compare this mutation to a previously reported mutation in the amelogenin gene that causes a different disease phenotype. The study illustrates that molecular analysis can help explain the various manifestations of a tooth disorder and thereby provide insights into the mechanisms of tooth enamel formation.


thinking, reading, collecting, designing, editing, writing,
making a playing around to make the Internet —most— awesome.
Hello World! Exactly those are the words I use when I start creating new sites. Yes, as a Front-End developer, every day I sit in front of my desk, take a sip of coffee and, limited only by my imagination, skill and creativity, I begin to create and transform blank pages into new worlds, opening infinite possibilities.
My name is Yoger, I am twenty-three years old, I am from Venezuela, my only vices are to program and good coffee; from the age of seventeen I have kept learning day by day, creating nice and functional websites for small businesses, developing a huge passion for big and bold problems, and an indescribable love for great ideas, projects with great purposes, and animations CSS.
While I'm not programming I love writing, designing, learning and creating great and beautiful moments with those I love, always focused on improving every day. Honestly, I am happy what I do and will do whatever it takes to keep growing in this amazing career.
I collaborate with clients and peers to nurture and transform ideas into well thought out design specs. After all, as Castelao said, "True heroism is transforming desires into realities and ideas into deeds".
I design in the browser with HTML5, the powerful CSS3 and a touch of JavaScript, specifically whit jQuery. I love coding things from scratch, but I can work with front-end frameworks like Bootstrap too.
Having a responsive layout means that your website fluidly resizes for optimal viewing regardless of the screen size or device (e.g. iPhone, iPad).
It's important to keep your brand consistent and recognizable across all platforms. Social media is an increasingly important tactic in companies’ marketing strategy.
While most of my attention is on developing websites, I create other wonderful things from time to time. This includes logo design, content writing, Excel templates, and some newsletter.
I'm currently accepting new projects and would love to hear about yours. Please take a few minutes to tell me about it.
CONTACT MEReady to start your next project with me? That's great! Send me a message or send me an email and I will get back to you as soon as possible!


Projects Due Monday, May 10
Project Suggestions
Last modified April 30, 2010
- Projects taken from the book -- you may also use other references!
- Summarize any one of the chapters: 8, 11, or 13 through 23.
- You may choose Ch. 12, but then you must discuss in some detail parts that we did not do in class, for example, the use of empirical pseudopotentials.
- The ``2n+1'' theorem (not widely known) shows that if the wavefunction is know to order $n$ in a perturbation expansion, the energy can be calculated to order 2n+1. Work out the details of the formulas in the book and do exercise 3.24.
- Work out the general form for ``special points'' to any order, and work Exercise 4.21.
- Exercises 14.23-24. This uses Harrison's tight-binding approach.
- Bands in nanotubes. See description below.
- Summarize the iterative methods in Appendix M and give a comparison the approaches used in at least two methods.
- Exercise 3.12 and 3.16 in the book. The first is very important for understanding the exchange energy, but it only be stated in class. The second is a very interesting feature of fermions and bosons.
- Give the expressions for Hartree-Fock approximation for bands in a metal and work exercises 5.9, 10, 11 in the book. These are important relations that illustrate the basic features of bands in metals and the problem in Hartree-Fock approximation. The integrals are somewhat tedious and you do not need to evaluate them in detail but you do need to show that they lead to a unphysical singularity at the Fermi energy.
- Describe the Green's function methods for calculation of phonon dispersion in Ch. 19. Contrast this with the "brute force" methods that require large "supercells".
- Describe two of the methods for constructing norm-conserving pseudopotentials.
- Work out Exercise 4.22. for bands in a one-dimensional crystal. This shows relations among the methods.
- Linear scaling "order N" methods. Summarize the general ideas and discuss methods. See Ch. 23..
- Theory of Atomic Sphere methods in solids. This is barely covered in class. A project could go further to show the usefulness of atomic sphere approximations to have simple calculations for solids.
- Theory of polarization in solids and Berry's phases.
- Theory of Wannier Functions: history and recent advances
- Bands in interesting systems
- Nanotubes. Report on one paper that describes the types of nanotubes formed by ``rolling'' graphene sheets to make tubes. Give the conditions for metallic tubes (with zero gap like graphene) or tubes with gaps. A possible paper is Hamada, et al., Phys. Rev. Lett. 6, 1579 (1992) or another paper.
- Bands for the copper oxide square lattices in the Hi-Tc superconductors. Describe in tight binding and discuss the way the second neighbor terms affects the Fermi surface. Show the results are different depending on the sign of these terms.
- Physical Properties
- Optical properties of materials. Give theory in terms of transitions between bands and discussion of results in cases with direct and indirect bands gaps.
- Phonons. Give theory in terms of forces and force constants and discuss comparison of theory and experiment for several cases.
- Elastic properties. Give theory in terms of constants and discuss comparison of theory and experiment for several cases.
- Magnetism. Two possibilities: Give theory in terms of magnetic moments and Weiss mean field theory, or in terms of Kohn-Sham calculations. In either case discuss magnetism in at least two materials.
- Report on various calculations of surface energies that have been reported. Give at lest 3 references (not in the book) with description of their conclusions.
- Density Functional Theory
- Describe the original derivation of the PBE functional (very nice arguments and construction) and give the form proposed.
- Theory and actual recent examples of GGAs
- Hybrid functionals. What are they? In what ways have they been used?
- Theory of van der Waals functional proposed in a recent papers and following ones
- Applications of the van der Waals functional, what are tested that have been done and uses for interesting problems.
You can discuss with Prof. Martin IN ADVANCE about other projects.


Choose “Import .Jar/.Aar package"
Choose File location (The ZDK .aar file)"
Choose “Module dependency"
Select the ZDK module and click “OK"


For five years, I studied Electrical and Electronic Engineering at JKUAT. The course covered the fields of power systems, electromagnetics, power electronics, telecommunications, microprocessors and embedded systems.
I have been at Moringa from 9th March 2020. Here I seek to build on my software development skills as I aim to merge my fields of expertise and develop innovative solutions for the energy industry.
Für zwei Jahren habe ich Deutsch am Goethe Institut gelernt. Das war nach B2 Niveau.
High school experience at Alliance High School was great. I got a holistic experience ranging from books to sports, music, and cultural diversity. I made many friends, most of whom I'm still very tight with.


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--- layout: post status: publish published: true title: MVP Summit 2008 author: display_name: Tomas Restrepo login: tomasr email<EMAIL_ADDRESS>url: http://winterdom.com/ author_login: tomasr author_email<EMAIL_ADDRESS>author_url: http://winterdom.com/ wordpress_id: 961 wordpress_url: http://winterdom.com/2008/04/mvpsummit2008 date: '2008-04-11 05:36:41 +0000' date_gmt: '2008-04-11 05:36:41 +0000' categories: - Personal tags: [] comments: [] ---
Provided the American Airlines problems from this week get sorted out, I'll be attending the MVP Summit again this year. I'll be arriving Sunday pretty late but will be staying until Friday.
If anyone wants to meet, chat, or just say Hi, send me an email (tomas at winterdom.com) or ping me via twitter.


We've already explored a two-dimensional version of the divergence theorem. If I have some region-- so this is my region right over here. We'll call it R. And let's call the boundary of my region, let's call that C. And if I have some vector field in this region, so let me draw a vector field like this. If I draw a vector field just like that, our two-dimensional divergence theorem, which we really derived from Green's theorem, told us that the flux across our boundary of this region-- so let me write that out. The flux across the boundary, so the flux is essentially going to be the vector field. It's going to be our vector field F dotted with the normal outward-facing vector. So the normal vector at any point is this outward-facing vector, So our vector field, dotted with the normal-facing vector at our boundary times our little chunk of the boundary. If we were to sum them all up over the entire boundary-- let me write that a little bit neater-- that's the same thing as summing up over the entire region. So let's sum up over the entire region. So summing up over this entire region, each little chunk of area, dA-- we could call that dx dy if we wanted to if we're dealing in the xy domain right over here, but each little chunk of area times the divergence of F, which is really saying, how much is that vector field pulling apart? So it's times the divergence of F. And hopefully, it made intuitive sense. The way that I drew this vector field right over here, you see everything's kind of coming out. You could almost call this a source right here, where the vector field seems like it's popping out of there. This has positive divergence right over here. And so because of this, you actually see that the vector field at the boundary is actually going in the direction of the normal vector, pretty close to the direction of the normal vector, so it makes sense. You have positive divergence, and this is going to be a positive value. The vector field is going, for the most part, in the direction of the normal vector. So the larger this is, the larger that is. So hopefully, some intuitive sense. If you had another vector field-- so let me draw another region-- that looked like this, so I could draw a couple situations. So one where there's very limited divergence, maybe it's just a constant. The vector field doesn't really change as you go in any given direction. Over here you'll get positive fluxes. I don't know what the plural of flux is. You'll get positive fluxes, because the vector field seems to be going in roughly the same direction as our normal vector. But here, you'll get a negative flux. So stuff is coming in here. If you imagine your vector field is essentially some type of mass density times volume, and we've thought about that before, this is showing how much stuff is coming in, and then stuff is coming out. So your net flux will be close to zero. Stuff is coming in, and stuff is coming out. Here, you're just saying, hey, stuff is constantly coming out of this surface.  Here you have a high divergence, and you would have a high aggregate flux. I could draw another situation. So this is my region R. And let's say that we have negative divergence, or we could even call it convergence. Convergence isn't an actual technical term, but you could imagine if the vector field is converging within R, well, the divergence is going to be negative in this situation. It's actually converging, which is the opposite of diverging. So the divergence is negative in this situation. And also the flux across the boundary is going to be negative. Because as we see here, the way I drew it, across most of this boundary, the vector field is going in the opposite direction. It's going in the opposite direction as our normal vector at any point. So hopefully, this gives you a sense of why there's this connection between the divergence over the region and the flux across the boundary. |
Well, now we're just going to extend this to three dimensions, and it's the exact same reasoning. If we have a-- and I'll define it a little bit more precisely in future videos-- a simple, solid region. So let me just draw it. And I'm going to try to draw it in three dimensions. So let's say it looks something like that. And one way to think about it is this is going to be a region that doesn't bend back on itself. And if you have a region that bends back on itself-- well, we'll think about it in multiple ways. But out of all the volumes of three dimensions that you can imagine, these are the ones that don't bend back on themselves. And there are some that you might not be able to imagine that would also not make the case. But even if you had ones that bent back on themselves, you could separate them out into other ones that don't. So here is just a simple solid region over here. I'll make it look three dimensional. So maybe if it was transparent, you would see it like that.  So it's this kind of elliptical, circular, blob-looking thing. So that could be the back of it. And then if you go to the front, it could look something like that. So this is our simple solid region. I'll call it-- well, I'll call it R still. But we're dealing with a three dimensional. We are now dealing with a three-dimensional region. And now the boundary of this is no longer a line. We're now in three dimensions. The boundary is a surface. So I'll call that S. S is the boundary of R. |
And now let's throw on a vector field here. Now, this is a vector field in three dimensions. And now let's imagine that we actually have positive divergence of our vector field within this region right over here. So we have positive divergence. So you can imagine that it's kind of-- the vector field within the region, it's a source of the vector field, or the vector field is diverging out. That's just the case I drew right over here. And the other thing we want to say about vector field S, it's oriented in a way that its normal vector is outward facing, so outward normal vector. So the normal, it's oriented so that the surface-- the normal vector is like that. The other option is that you have an inward-facing normal vector. But we're assuming it's an outward-facing N. Well, then we just extrapolate this to three dimensions. |
We essentially say the flux across the surface.  So it's going to be a surface integral. So this is flux across the surface. It's going to be equal to-- if we were to sum up the divergence, if we were to sum up across the whole volume, so now if we're summing up things on every little chunk of volume over here in three dimensions, we're going to have to take integrals along each dimension. So it's going to be a triple integral over the region of the divergence of F. So we're going to say, how much is F? What is the divergence at F at each point? And then multiply it times the volume of that little chunk to sense of how much is it totally diverging in that volume.  That should be equal to the flux. It's completely analogous to what's here. Here we had a flux across the line. We had essentially a two-dimensional-- or I guess we could say it's a one-dimensional boundary, so flux across the curve. And here we have the flux across a surface. Here we were summing the divergence in the region. Here we're summing it in the volume. But it's the exact same logic. If you had a vector field like this that was fairly constant going through the surface, on one side you would have a negative flux. On the other side, you would have a positive flux, and they would roughly cancel out. And that makes sense, because there would be no diverging going on. If you had a converging vector field, where it's coming in, the flux would be negative, because it's going in the opposite direction of the normal vector. And so the divergence would be negative as well, because essentially the vector field would be converging. |
So hopefully this gives you an intuition of what the divergence theorem is actually saying something very, very, very, very-- almost common sense or intuitive. And now in the next few videos, we can do some worked examples, just so you feel comfortable computing or manipulating these integrals. And then we'll do a couple of proof videos, where we actually prove the divergence theorem.
|
Let's say we have a path in the xy plane. That's my y-axis, that is my x-axis, in my path will look like this. Let's say it looks like that; trying to draw a bit of an arbitrary path, and let's say we go in a counter clockwise direction like that along our path. And we could call this path-- so we're going in a counter clockwise direction --we could call that path c. And let's say we also have a vector field. And our vector field is going to be a little unusual; I'll call it p. p of xy. It only has an i component, or all of its vectors are only multiples of the i-unit vector. So it's capital P of xy times the unit vector i. There is no j component, so if you have to visualize this vector field, all of the vectors, they're all multiples of the i-unit vector. Or they could be negative multiples, so they could also go in that direction.  They all go left to right or right to left. That's what this vector field would look like. Now what I'm interested in doing is figuring out the line integral over a closed loop-- the closed loop c, or the closed path c --of p dot dr, which is just our standard kind of way of solving for a line integral. And we've seen what dr is in the past. dr is equal to dx times i plus dy times the j-unit vector. And you might say, isn't it dx, dt times dt? Let me write that can't dr be written as dx, dt times dti plus dy, dt times dtj? And it could, but if you imagine these differentials could cancel out, and you're just left with the dx and a dy, and we've seen that multiple times. And I'm going to leave it in this form because hopefully, if we're careful, we won't have to deal with the third parameter, t. So let's just look at it in this form right here with just the dx's and the dy's. So this integral can be rewritten as the line integral, the curve c-- actually let me do it over down here. The line integral over the path of the curve c of p dot dr. So we take the product of each of the coefficients, let's say the coefficient of the i component, so we get p-- I'll do that in green, actually do that purple color --so we get p of xy times dx plus-- well there's no 0 times j times dy; 0 times dy id just going to be 0 --so this our line integral simplified to this right here. This is equal to this original integral up here, so we're literally just taking the line integral around this path. Now I said that we play our cards right, we're not going to have to deal with the third variable, t; that we might be able just solve this integral only in terms of x. |
And so let's see if we can do that. So let's look at our minimum and maximum x points. That looks like our minimum x point. Let's call that a. Let's call that our maximum x point; let's call that b. What we could do is we can break up this curve into two functions of x. y is functions of x. So this bottom one right here we could call as y1 of x. This is just a standard curve; you know when we were just dealing with standard calculus, this is just you can imagine this is f of x and it's a function of x. And this is y2 of x. Just like that. So you can imagine two paths; one path defined by y1 of x-- let me do that in a different color; magenta --one path defined by y1 of x as we go from x is equal to a to x is equal to b, and then another path defined by y2 of x as we go from x is equal to b to x is equal to a. That is our curve. So what we could do is, we could rewrite this integral-- which is the same thing as that integral --as this is equal to the integral-- we'll first do this first path --of x going from a to b of p of x. And I could to say p of x and y, but we know along this path y is a function of x. So we say x and y1 of x. Wherever we see a y we substitute it with a y1 of x, dx. So that covers that first path; I'll do it in the same color. We could imagine this is c1. This is kind of the first half of our curve-- well it's not exactly the half --but that takes us right from that point to that point. And then we want to complete the circle. Maybe I'll do that, and I'll do that in yellow. That's going to be equal to-- sorry we're going to have to add these two --plus the integral from x is equal to b to x is equal to a of-- do it in that same color --of p of x. And now y is going to be y2 of x. Wherever you see a y, you can substitute with y2 of x along this curve. y2 of x, dx. |
This is already getting interesting and you might already see where I'm going with this. |
So this is the curve c2. too I think you appreciate if you take the union of c1 and c2, we've got our whole curve. |
So let's see if we can simplify this integral a little bit. Well one thing we want to do, we might want to make their end points the same. So if you swap a and b here, it just turns the integral negative. So you make this into a b, that into an a, and then make that plus sign into a minus sign. And now we can rewrite this whole thing as being equal to the integral from a to b of this thing, of p of x and y1 of x minus this thing, minus p of x and y2 of x, and then all of that times dx. I'll write it in a third color. Now, I'm going to do something a little bit arbitrary, but I think you'll appreciate why I did this by the end of this video, and it's just a very simple operation. What I'm going to do is I'm going to swap these two. So I'm essentially going to multiply this whole thing by negative 1, or essentially multiply and divide by negative 1. So I can multiply this by negative 1 and then multiply the outside by negative 1, and I will not have changed the integral; I'm multiplying by negative 1 twice. So if I swap these two things, if I multiply the inside times negative 1, so this is going to be equal to-- do the outside of the integral, a to b. If I multiply the inside-- I'll do a dx out here --if I multiply the inside of the integral by negative 1, these two guys switch. So it becomes p of x of y2 of x. And then you're going to have minus p of x and y1 of x. My handwriting's getting a little messy. But I can't just multiply just the inside by minus 1. I don't want to change the integral, so I multiplied the inside by minus 1, let me multiply the outside by minus 1. And since I multiplied by minus 1 twice, these two things are equivalent. Or you could say this is the negative of that. Either way, I think you appreciate that I haven't changed the integral at all, numerically. I multiplied the inside and the outside by minus 1. And now the next step I'm going to do, it might look a little bit foreign to you, but I think you'll appreciate it. It might be obvious to you if you've recently done some double integrals. So this thing can be rewritten as minus the integral from a to b of-- and let me do a new color --of the function p of x, y evaluated at y2 of x minus-- and let me make it very clear; this is y is equal to y2 of x --minus this function evaluated at y is equal to y1 of x. And of course all of that times dx. |
This statement and what we saw right here-- this statement right here --are completely identical. |
And then if we assume that a partial derivative of capital P with respect to y exists, hopefully you'll realize-- and I'll focus on this a little bit because I don't want to confuse you on this step. Let me write the outside of this integral. So this is going to be equal to-- and this is kind of a neat outcome, and we're starting to build up to a very neat outcome, which will probably have to take the next video to do --so we do the outside dx. If we assume that capital P has a partial derivative, this right here is the exact same thing. This right here is the exact same thing as the partial derivative of P with respect to y, dy, the antiderivative of that from y1 of x to y2 of x. I want to make you feel comfortable that these two things are equivalent. And to realize they're equivalent, you'll probably just have to start here and then go to that. We're used to seeing this; we're used to seeing a double integral like this, and then the very first step we say, OK to solve this double integral we start on the inside integral right there, and we say, OK let's take the antiderivative of this with respect to y. So if you take the antiderivative of the partial of p with respect to y, you're going to end up with p. And since this is a definite integral, the boundaries are going to be in terms of x, you're going to evaluate that from y is equal to y2 of x, and you're going to subtract from that y is equal to y1 of x. Normally we start with something like this, and we go to something like this. This is kind of unusual that we started, we kind of solved, we started with the solution of the definite integral, and then we slowly built back to the definite integral. So hopefully you realize that this is true, that this is just we're kind of going in a reverse direction than we normally do. And if you do realize that, then we've just established a pretty neat outcome. Because what is this right here? Let me go back, let me see if I can fit everything. |
I have some function-- and I'm assuming that the partial of P with respect to y exists --but I have some function defined over the xy plane. You know, you could imagine we're dealing in three dimensions now. We'll draw a little bit neater. So that's y, that's x, that's z, so this, you could imagine, is some surface; it just happens to be the partial of P with respect to x. So it's some surface on the xy plane like that. And what are we doing? We're taking the double integral under that surface, around this region. The region's boundaries in terms of y are defined by y2 and y1 of x. So you literally have that curve. That's y2 on top, y1 on the bottom. And so we're essentially taking the volume above. So if you imagine with the base is-- the whole floor of this is going to be the area inside of this curve, and then the height is going to be the function partial of P with respect to y. It's going to be a little hard for me to draw, but this is essentially some type of a volume, if you want to visualize it that way. |
But the really neat outcome here is if you call this region r, we've just simplified this line integral. And this was a special one. It only had an x-component, the vector field, but we've just simplified this line integral to being equivalent to-- maybe I should write this line integral because that's what's the really neat outcome. We've just established that this thing right here, which is the same as our original one, so let me write that. The closed line integral around the curve c of p of xy, dx, we've just established that that's the same thing as the double integral over the region r-- this is the region r --of the partial of P with respect to y. And we could write dy, dx, or we could write da, whatever you want to write, but this is the double integral over that region. The neat thing here is using a vector field that only had an x-component, we were able to connect its line integral to the double integral over region-- oh, and I forgot something very important. |
We had a negative sign out here. So this was a minus sign out here. Or we could even put the minus in here, but I think you get the general idea. |
In the next video, I'm going to do the same exact thing with the vector field that only has vectors in the y-direction. |
And then we'll connect the two and we'll end up with Green's theorem.
|
Let's take the derivative with respect to x of x to the n plus 1-th power over n plus 1 plus some constant c. And we're going to assume here, because we want this expression to be defined, we're going to assume that n does not equal negative 1. If it equaled negative 1, we'd be dividing by 0, and we haven't defined what that means. So let's take the derivative here. So this is going to be equal to-- well, the derivative of x to the n plus 1 over n plus 1, we can just use the power rule over here. So our exponent is n plus 1. We can bring it out front. So it's going to be n plus 1 times x to the-- I want to use that same color. Colors are the hard part-- times x to the-- instead of n plus 1, we subtract 1 from the exponent. This is just the power rule. So n plus 1 minus 1 is going to be n. And then we can't forget that we were dividing by this n plus 1. So we have divided by n plus 1. And then we have plus c. The derivative of a constant with respect to x-- a constant does not change as x changes, so it is just going to be 0, so plus 0. And since n is not equal to negative 1, we know that this is going to be defined. This is just going to be something divided by itself, which is just going to be 1. And this whole thing simplifies to x to the n. So the derivative of this thing-- and this is a very general terms-- is equal to x to the n. So given that, what is the antiderivative-- let me switch colors here. What is the antiderivative of x to the n? And remember, this is just the kind of strange-looking notation we use. It'll make more sense when we start doing definite integrals. But what is the antiderivative of x to the n? And we could say the antiderivative with respect to x, if we want to. And another way of calling this is the indefinite integral. Well, we know this is saying x to the n is the derivative of what? Well, we just figured it out. It's the derivative of this thing, and we've written it in very general terms. We're actually encapsulating multiple constants here. We could have x to the n plus 1 over n plus 1 plus 0, plus 1, plus 2, plus pi, plus a billion. So this is going to be equal to x to the n plus 1 over n plus 1 plus c. So this is pretty powerful. You can kind of view this as the reverse power rule. And it applies for any n, as long as n does not equal negative 1. Let me make that very clear. n does not equal negative 1. Once again, this thing would be undefined if n were equal to negative 1. So let's do a couple of examples just to apply this-- you could call it the reverse power rule if you want, or the anti-power rule. So let's take the antiderivative of x to the fifth power. What is the antiderivative of x to the fifth? Well, all we have to say is, well, look, the 5 is equal to the n. We just have to increment the exponent by 1. So this is going to be equal to x to the 5 plus 1 power. And then we divide by that same value. Whatever the exponent was when you increment it by 1, we divide by that same value, divided by 5 plus 1. And of course, we want to encapsulate all of the possible antiderivatives, so you put the c right over there. So this is going to be equal to x to the sixth over 6 plus c. And you can verify. Take the derivative of this using the power rule, you indeed get x to the fifth. Let's try another one. Let's try-- now we'll do it in blue. Let's try the antiderivative of-- let's make it interesting. Let's make it 5 times x to the negative 2 power dx. |
So how would we evaluate this? Well, one simplification you can do-- and I haven't rigorously proven it to you just yet-- but we know that scalars can go in and out of the derivative operator when you're multiplying by a scalar. |
So this is, indeed, equal to 5 times the antiderivative of x to the negative 2 power, dx. And now we can just use, I guess we could call it this anti-power rule, so this is going to be equal to 5 times x to the negative 2 power plus 1 over the negative 2 power plus 1 plus some constant right over here.  And this is equal to 5 times negative x to the negative 1 plus some constant. And then if we want, we can distribute the 5. So this is equal to negative 5x to the negative 1. Now, we could write plus 5 times some constant, but this is just an arbitrary constant. So this is still just an arbitrary constant. So maybe we could [INAUDIBLE] this. If you want it to show that it's a different constant, you could say this is c1, c1, c1. You multiply 5 times c1, you get another constant. We could just call that c, which is equal to 5 times c1. But there you have it. Negative 5x to the negative 1 plus c. |
And once again, all of these, try to evaluate the derivative, and you will see that you get this business, right over there.
|
We want to find the derivative with respect to x of all of this business right over here. And you might guess-- and this is definitely a function of x. x is one of the boundaries of integration for this definite integral. And you might say, well, it looks like the fundamental theorem of calculus might apply, but I'm used to seeing the x, or the function x, as the upper bound, not as the lower bound. How do I deal with this? And the key realization is to realize what happens when you switch bounds for a definite integral. |
And I'll do a little bit of an aside to review that. |
So if I'm taking the definite integral from a to b of f of t, dt, we know that this is capital F, the antiderivative of f, evaluated at b minus the antiderivative of F evaluated at a. This is corollary to the fundamental theorem, or it's the fundamental theorem part two, or the second fundamental theorem of calculus. This is how we evaluate definite integrals. Now, let's think about what the negative of this is. So the negative of that-- of a to b of f of t, dt, is just going to be equal to the negative of this, which is equal to-- so it's the negative of f of b minus f of a, which is equal to capital F of a minus capital F of b. All I did is distribute the negative sign and then switch the two terms. But this right over here is equal to the definite integral from, instead of a to b, but from b to a of f of t, dt. |
So notice, when you put a negative, that's just like switching the signs or switching the boundaries. Or if you switch the boundaries, they are the negatives of each other. |
So we can go back to our original problem. |
We can rewrite this as being equal to the derivative with respect to x of-- instead of this, it'll be the negative of the same definite integral but with the boundaries switched-- the negative of x with the upper boundary is x, the lower bound is 3 of the square root of the absolute value of cosine t, dt, which is equal to-- we can take the negative out front-- negative times the derivative with respect to x of all of this business. I should just copy and paste that, so I'll just copy and paste. Let me-- and paste it. So times the derivative with respect to x of all that, and now the fundamental theorem of calculus directly applies. This is going to be equal to-- we deserve a drum roll now. This is going to be equal to the negative-- can't forget the negative. And the fundamental theorem of calculus tells us that that's just going to be this function as a function of x. So it's going to be negative square root of the absolute value of cosine of not t anymore, but x. |
And we are done. |
|
Let's say I have some function f that is continuous on an interval between a and b. And I have these brackets here, so it also includes a and b in the interval. So let me graph this just so we get a sense of what I'm talking about. So that's my vertical axis. This is my horizontal axis. I'm going to label my horizontal axis t so we can save x for later. I can still make this y right over there. And let me graph. This right over here is the graph of y is equal to f of t. Now our lower endpoint is a, so that's a right over there. Our upper boundary is b. Let me make that clear. And actually just to show that we're including that endpoint, let me make them bold lines, filled in lines. So lower boundary, a, upper boundary, b. We're just saying and I've drawn it this way that f is continuous on that. Now let's define some new function. Let's define some new function that's the area under the curve between a and some point that's in our interval. Let me pick this right over here, x. So let's define some new function to capture the area under the curve between a and x. Well, how do we denote the area under the curve between two endpoints? Well, we just use our definite integral. That's our Riemann integral. It's really that right now before we come up with the conclusion of this video, it really just represents the area under the curve between two endpoints. So this right over here, we can say is the definite integral from a to x of f of t dt. Now this right over here is going to be a function of x-- and let me make it clear-- where x is in the interval between a and b. This thing right over here is going to be another function of x. This value is going to depend on what x we actually choose. So let's define this as a function of x. So I'm going to say that this is equal to uppercase F of x. So all fair and good. Uppercase F of x is a function. If you give me an x value that's between a and b, it'll tell you the area under lowercase f of t between a and x. Now the cool part, the fundamental theorem of calculus. The fundamental theorem of calculus tells us-- let me write this down because this is a big deal. Fundamental theorem-- that's not an abbreviation-- theorem of calculus tells us that if we were to take the derivative of our capital F, so the derivative-- let me make sure I have enough space here. So if I were to take the derivative of capital F with respect to x, which is the same thing as taking the derivative of this with respect to x, which is equal to the derivative of all of this business-- let me copy this. So copy and then paste, which is the same thing. I've defined capital F as this stuff. So if I'm taking the derivative of the left hand side, it's the same thing as taking the derivative of the right hand side. The fundamental theorem of calculus tells us that this is going to be equal to lowercase f of x. Now why is this a big deal? Why does it get such an important title as the fundamental theorem of calculus? Well, it tells us that for any continuous function f, if I define a function, that is, the area under the curve between a and x right over here, that the derivative of that function is going to be f. So let me make it clear. Every continuous function, every continuous f, has an antiderivative capital F of x. |
That by itself is a cool thing. But the other really cool thing-- or I guess these are somewhat related. |
Remember, coming into this, all we did, we just viewed the definite integral as symbolizing as the area under the curve between two points. That's where that Riemann definition of integration comes from. But now we see a connection between that and derivatives. When you're taking the definite integral, one way of thinking, especially if you're taking a definite integral between a lower boundary and an x, one way to think about it is you're essentially taking an antiderivative. So we now see a connection-- and this is why it is the fundamental theorem of calculus. It connects differential calculus and integral calculus-- connection between derivatives, or maybe I should say antiderivatives, derivatives and integration. Which before this video, we just viewed integration as area under curve. Now we see it has a connection to derivatives. Well, how would you actually use the fundamental theorem of calculus? Well, maybe in the context of a calculus class. |
And we'll do the intuition for why this happens or why this is true and maybe a proof in later videos. |
But how would you actually apply this right over here? Well, let's say someone told you that they want to find the derivative. Let me do this in a new color just to show this is an example. Let's say someone wanted to find the derivative with respect to x of the integral from-- I don't know. I'll pick some random number here. So pi 2x-- I'll put something crazy here-- cosine squared of t over the natural log of t minus the square root of t dt. So they want you take the derivative with respect to x of this crazy thing. Remember, this thing in the parentheses is a function of x. Its value, it's going to have a value that is dependent on x. If you give it a different x, it's going to have a different value. So what's the derivative of this with respect to x? Well, the fundamental theorem of calculus tells us it can be very simple. We essentially-- and you can even pattern match up here. And we'll get more intuition of why this is true in future videos. But essentially, everywhere where you see this right over here is an f of t. Everywhere you see a t, replace it with an x and it becomes an f of x. So this is going to be equal to cosine squared of x over the natural log of x minus the square root of x. You take the derivative of the indefinite integral where the upper boundary is x right over here. It just becomes whatever you were taking the integral of, that as a function instaed of t, that is now a function x. So it can really simplify sometimes taking a derivative. And sometimes you'll see on exams these trick problems where you had this really hairy thing that you need to take a definite integral of and then take the derivative, and you just have to remember the fundamental theorem of calculus, the thing that ties it all together, connects derivatives and integration, that you can just simplify it by realizing that this is just going to be instead of a function lowercase f of t, it's going to be lowercase f of x. Let me make it clear. In this example right over here, this right over here was lowercase f of t. And now it became lowercase f of x. This right over here was our a. And notice, it doesn't matter what the lower boundary of a actually is. You don't have anything on the right hand side that is in some way dependent on a. Anyway, hope you enjoyed that. And in the next few videos, we'll think about the intuition and do more examples making use of the fundamental theorem of calculus.
|
So let's see if we can take the derivative of this expression right over here, if we can find capital F prime of x. And once again, it looks like you might be able to use the fundamental theorem of calculus. A big giveaway is that you're taking the derivative of a definite integral that gives you a function of x. But here I have x on both the upper and the lower boundary, and the fundamental theorem of calculus, is at least from what we've seen, is when we have x's only on the upper boundary. And then, of course, it's an x squared, but we've seen examples of that already when we used the chain rule to do it. But how can we break this up and put this in a form that's a little bit closer to what we're familiar with when we apply the fundamental theorem of calculus? And to realize that, we really just have to attempt to graph what this is representing. |
So let's say that this is our lowercase f of x, or I should say f of t. So let's call this lowercase f of t. And let's graph it over the interval between x and x squared. So let's say this is my y-axis. This is my t-axis. And let's say that this right over here is y is equal to f of t. I'm drawing it generally. I don't know what this exactly looks like. And we're going to talk about the interval between x and x squared. So if we're going to talk about the interval between x, which is right over here, it's the lower bound, so x and x squared. It's the lower bound, at least for this definite integral. We don't know for sure. It depends on what x you choose on which one is actually smaller. But let's just say that for the sake of visualizing, we'll draw x right over here, and we will draw x squared right over here. |
So this whole expression, this entire definite integral, is essentially asking for, is essentially representing this entire area, the entire area under the curve. |
But what we could do is introduce a constant that's someplace in between x and x squared. Let's say that constant is c, and break this area into two different areas with c as the divider. So that same exact whole area we can now write it as two separate integrals. So one integral that represents this area right over here, and then another integral that represents this area right over there, and where we just say c is some constant between x and x squared. Well, how can we denote this area in purple? Well, that's going to be-- So this thing is going to be equal to the sum of these two areas. The purple area we can show is the definite integral from x to c of our function of t, cosine t over t dt. And then to that we're going to add the green area. And then we'll get the original area. So for the green area, our lower bound of integration is now our constant c, and our upper bound of integration is x squared, and it's going to be of cosine t over t dt. And this is a form where, if we know how to apply the chain rule, we can apply the fundamental theorem of calculus. And this is almost in a form. We're used to seeing it where the x is the upper bound. And, well, we already know what happens. We can swap these two bounds, but it'll just be the negative of that integral. So this is going to be equal to-- let me rewrite it-- the negative of the definite integral from c to x of cosine t over t dt. And then we have plus the definite integral that goes from c to x squared of cosine t over t dt. |
So all we've done is we've rewritten this thing in a way that we're used to applying the fundamental theorem of calculus. So if we want to find F prime of x, well, applying the derivative operator over here, we're going to have a negative out front. It's going to be equal to negative cosine x over x. Once again, just the fundamental theorem of calculus. And then plus-- we're first going to take the derivative of this thing with respect to x squared, and that's going to give you cosine of x squared over x squared. Wherever you saw t, you replace it with an x squared. And then you're going to multiply that times the derivative of x squared with respect to x. So that's just going to be-- derivative of x squared with respect to x is just 2x. And we're done. We just need to simplify this thing. So all of this is going to be equal to negative cosine x over x plus-- well, this is going to cancel out with just one of those-- plus 2 cosine x squared over x. And I guess we could simplify it even more as being equal to-- and we can swap these-- everything over x 2 cosine of x squared minus cosine of x. And we are done.
|
I thought I would do a few more examples of taking antiderivatives, just so we feel comfortable taking antiderivatives of all of the basic functions that we know how to take the derivatives of. And on top of that, I just want to make it clear that it doesn't always have to be functions of x. Here we have a function of t, and we're taking the antiderivative with respect to t. And so you would not write a dx here. |
That is not the notation. |
You'll see why when we focus on definite integrals. |
So what's the antiderivative of this business right over here? Well, it's going to be the same thing as the antiderivative of sine of t, or the indefinite integral of sine of t, plus the indefinite integral, or the antiderivative, of cosine of t. So let's think about what these antiderivatives are. And we already know a little bit about taking the derivatives of trig functions. We know that the derivative with respect to t of cosine of t is equal to negative sine of t. So if we want a sine of t here, we would just have to take the derivative of negative cosine t. If we take the derivative of negative cosine t, then we get positive sine of t. The derivative with respect to t of cosine t is negative sine of t. We have the negative out front. It becomes positive sine of t. So the antiderivative of sine of t is negative cosine of t. So this is going to be equal to negative cosine of t. And then what's the antiderivative of cosine of t? Well, we already know that the derivative with respect to t of sine of t is equal to cosine of t. So cosine of t's antiderivative is just sine of t-- so plus sine of t. And we're done. We've found the antiderivative. Now let's tackle this. Now we don't have a t. We're taking the indefinite integral with respect to-- actually, this is a mistake. This should be with respect to a. Let me clean this up. This should be a da. If we were taking this with respect to t, then we would treat all of these things as just constants. But I don't want to confuse you right now. Let me make it clear. This is going to be da. That's what we are integrating or taking the antiderivative with respect to. |
So what is this going to be equal to? Well once again, we can rewrite it as the sum of integrals. This is the indefinite integral of e to the a da, so this one right over here-- a d I'll do it in green-- plus the indefinite integral, or the antiderivative, of 1/a da. |
Now, what is the antiderivative of e to the a? Well, we already know a little bit about exponentials. The derivative with respect to x of e to the x is equal to e to the x. That's one of the reasons why e in the exponential function in general is so amazing. And if we just replaced a with x or x with a, you get the derivative with respect to a of e to the a is equal to e to the a. So the antiderivative here, the derivative of e to the a, the antiderivative is going to be e to the a. |
And maybe you can shift it by some type of a constant. Oh, and let me not forget, I have to put my constant right over here. I could have a constant factor. So let me-- always important. Remember the constant. So you have a constant factor right over here. Never forget that. |
I almost did. |
So once again, over here, what's the antiderivative of e to the a? It is e to the a. What's the antiderivative of 1/a? Well, we've seen that in the last video. |
It is going to be the natural log of the absolute value of a. |
And then we want to have the most general antiderivative, so there could be a constant factor out here as well. And we are done. We found the antiderivative of both of these expressions. |
|
Let's say that we have capital F of x as being equal to the definite integral from pi to x of cotangent squared of t dt. And what we're curious about finding is the derivative of this business. We want to figure out what F prime of x is equal to. Well this is a direct application of the fundamental theorem of calculus. This is just going to be the derivative with respect to x of all of this craziness. So let me just copy and paste that. So it's just going to be the derivative with respect to that. And the fundamental theorem of calculus tells us that this is going to be equal to just this function, but it's not going to be a function of t anymore. It's going to be a function of x. So it's going to be equal to cotangent squared of x. And you'll often see problems like this if you go to calculus competitions or things like that and, or maybe certain exams. |
And It's like, oh my god, I have to take the antiderivative of all of this business, evaluate it at the different boundaries, and then I got to take the derivative. |
No. |
You just apply the fundamental theorem of calculus, and it's actually a very straightforward and a very fast thing to do. |
Now let's mix it up a little bit. Let's say that you had the expression the definite integral from pi-- instead of from pi to x, let's say it's from pi to x squared-- and let me write that x squared in a different color just to make it clear what I'm doing-- from pi to x squared of cotangent squared of t dt. |
And you wanted to take the derivative of this business. So you want to take the derivative with respect to x of this business. How would you do it? Well the recognition here is that this is capital-- capital F of x was defined as this. Now instead of an x, you have an x squared. So this is the exact same thing as taking the derivative with respect to x of capital F of-- not x. That would be this. Instead, we have capital F of x squared. Where we had an x here before, we now have an x squared. You can verify. If you had capital F of x squared, every place where you saw the x here would be an x squared. So it would look exactly like this. And so we just have to apply the chain rule. So this is going to be equal to the derivative of F with respect to x squared. And this is just straight out of the chain rule. It's going to be F prime of x squared times the derivative with respect to x of x squared. This is the derivative of F with respect to x squared and then times the derivative of x squared with respect to x. This is just the chain rule right over here. So what's F prime of x squared-- the derivative of F with respect to x squared? Well, if you evaluate F prime at x squared, instead of just being cotangent squared of x, it's going to be cotangent squared of x squared. So this part right over here, this business right over here, is going to be cotangent squared of x squared. So this is the derivative of all of this business with respect to x squared, and then you have to multiply that times the derivative of x squared with respect to x, which is just 2x. So there you have it. The derivative of this, all this craziness, is equal to 2x cotangent squared of x squared. |
|
So, our goal in this video is to take the antiderivative of this fairly crazy looking expression. Or another way of saying it is to find the indefinite integral of this crazy looking expression.  And the indefinite integral of the entire expression is going to be equal to the indefinite integral of each of the terms. So this is going to be equal to, we could look at this term right over here and just take the indefinite, take the indefinite integral of that. x to the 3rd dx. And then from that we can subtract the indefinite integral of this thing. So we can say this is, and then minus. The indefinite integral of 5 times the square root of x d x. And then we can look at this one right over here. So then we can say plus the indefinite integral of 18 square root of x. Square roots of x over x to the third, dx and then finally, and I'm running out of colors here. Finally, I need more colors in my thing. |
We can take the anti derivative of this. So plus the anti derivative of x to the negative 40th power dx. So, I've just rewritten this and color coded things. So, let's take the anti derivative of each of these and you'll see that'll we'll be able to do it. Using our whatever we wanna call the inverse of the power rule or the anti power rule. Whatever you might wanna call it. So lets look at the first one. So we have, we have, what I'm gonna do is I'm just gonna find the anti derivative without the constant and just add the constant at the end for the sake of this. So we just make sure we get the most general anti derivative. |
So here the exponent is a 3. |
So we can increase it by 1. |
So it's going to be x to the 4th. It's gonna be that same purple color. Or that pink color. It's going to be x to the 4th. And we're gonna divide x to the 4th. So it's x to the 4th over 4 is the antiderivative of x to the 3rd, and you just had this scaling quantity. The 7 out front. So we can still just have 7 out front. So we get 7x to the 4th over 4. |
Fair enough. |
From that, we're going to subtract the antiderivative of this. |
Now, at first, this might not be obvious that this, you could use our inverse power rule or anti-power rule here. |
But then you just need to realize that 5 times the principal root of x is the same thing as. So, this is the same thing as 5 x X to the 1 half power. And, so, once again, the exponent here is one half, we can increment it by 1. This is going to be X to the 3 halves. And then, divide by the incremented exponent. So, divide by. Three halves and of course we had this five out front so we still want to have the five out front. Now this next expression looks even wackier but once again we can simplify a little bit. This is the same thing. Let me do it right over here. This is the same thing as 18 times x to the one half times x to the negative three power. X to the third in the denominator is the same thing as x to the negative three. We have the same base, we can just add the exponent so this is going to be equal to 18 times x to the 2 and a half power, and a half power or another way of thinking about it, this is the same thing as 18 times x, 18 times x to the 5 halves power. Two the 5 halves power. Did I do that right? Yeah, negative 3, oh sorry, this is negative 2 and a half let me make this very clear and this is going to be the negative 5 half power. X to the negative 3 is the same thing as x to the negative 6 halves, negative six halves plus 1 half is negative 5 halves. So once again we just have to increment this exponent. So negative 5 halves, plus 1 is going to be negative 3 halves. So you're going to have x, x to the negative 3 halves, and then you divide by what your exponent is when you increment, so divide it by negative, divide it by negative 3 halves. And then you have the 18 out front. And we obviously are going to have to simplify this. And then finally, our exponent in this term, let me not use that purple any more, the exponent, in this term right over here is negative 40, if we increment we get x to the negative 39 power, all of that over negative 39. And now we can add our constant. Now we can add our constant C, and all we need to do is simplify all of this craziness. So the first one is fairly simplified. We can write it as seven fourths. X to the 4th. Now this term right over here is essentially 5 divided by 3 halves, so 5 over three halves is equal 5 times two thirds, which is equal to 10 over 3. So this thing right over here simplifies to negative 10 over 3X to the three halves. And then we have all of this craziness. Now 18 divided by negative three halves. divided by negative 3 halves is equal to 18 times. Negative two thirds, which is equal to, well, we can, we can simplify this a little bit. This is the same thing as 6. This is the same thing as 6 times negative 2 which is equal to negative 12. So, this expression right over here, is negative 12 x to the negative 3 halves. And then finally this one right over here, we can just rewrite it as. If we want, we could, well, we could just write negative one thirty-ninths x to the negative 39. |
Plus, plus C, and we're done. |
We found the indefinite integral of all of this craziness. |
And I encourage you to take the derivative of this, and you can do it using really just the power rule, to take the derivative of this and verify that it does indeed equal this expression that we took, that we took the anti-derivative of.
|


I developed for Slickdeal's
Price Tracker
tool to alert users when a price drops on a tracked item across a variety of stores.
I regularly performed maintenance on price scrapers for supported retailers to keep item information and prices updated.
Aside from working on Price Tracker, I bugfixed issues from different areas of the website and integrated new features using PHP, SQL, Javascript, and jQuery while using HTML5 and CSS3 to convert designs into functional web pages.


SitePen can provide a number of support packages to help you with Ajax/DWR development.
The three primary benefits of our support packages include:
For information about commercial support, please contact us. If you have questions about DWR please don't send them to the authors directly. There are far more people that can help on the mailing lists, so you'll get a faster response that way.
Most of these mailing lists are hosted by java.net. You can join Java.net by registering here, and then you can subscribe. However, you should not need to subscribe to take part - web interfaces are available.
The users mailing list is where the vast majority of discussion about DWR takes place. You can send email to the list directly using: [users at dwr.dev.java.net], or you can access the list on the web:
The idea behind the dwr-security mailing list is that we should have a way to discuss DWR security while minimizing the dangers associated with wide public dissemination. The list is not about keeping problems secret forever, but it is about responsible disclosure.
Just to be clear: dwr-security is NOT another option for getting support when something doesn't work.
Membership rules: Since dwr-security is about responsible disclosure, we would like to know who the members are. Almost everyone wants to subscribe from a gmail or similar web-based address. That's OK, but we want to link web addresses to some type of corporate address OR have some other way of positively identifying you.
Applications to join can be made using Google Groups. BUT the majority of applications to dwr-security are rejected because the applicant has not read the section above properly. Understanding it is not optional.
Anyone can post to the list using the address: [dwr-security at googlegroups.com]. You don't need to be a member to post to the list, but it does increase your spam score, so if you don't receive a fast answer you should try alerting [users at dwr.dev.java.net] to the fact that there is moderation that needs to happen.
Discussion list for DWR development. Currently most discussion takes place on the users mailing list, however this list may become more used in the future. The email address for the list is: [dev at dwr.dev.java.net], or, on the web:
This list contains announcements of new releases and other major project events. There is a better source of DWR news however in Joe's blog.


Net.TokenAvailable
Syntax
Net.TokenAvailable (netStream : int) : boolean
Description
Returns true if a line of input is waiting to be read from the net stream specified by the netStream parameter. If Net.TokenAvailable returns true, then a single token (character surrounded by whitespace) can be read from the stream without blocking.
Details
The Net module requires a TCP/IP stack to be installed and operating in order to function. It does not communicate using any other protocols
It is possible for Firewalls to interfere with the actions of the Net module, preventing connections from taking place.
Example
The following program fragment reads a character from netStream only if there is one waiting to be read.
if Net.TokenAvailable (netStream) then
var token : string
get : netStream, token
put token
end if
Status
Exported qualified.
This means that you can only call the function by calling Net.TokenAvailable, not by calling TokenAvailable.
See also
Net.BytesAvailable, Net.CharAvailable, and Net.LineAvailable.


In this project, we propose an application framework to perform high quality upsampling and completion on noisy depth maps. Our framework targets a complementary system setup which consists of a depth camera coupled with an RGB camera. Inspired by a recent work that uses a nonlocal structure regularization, we regularize depth maps in order to maintain fine details and structures. We extend this regularization by combining the additional high-resolution RGB input when upsampling a lowresolution depth map together with a weighting scheme that favors structure details. Our technique is also able to repair large holes in a depth map with consideration of structures and discontinuities by utilizing edge information from the RGB input. Quantitative and qualitative results show that our method outperforms existing approaches for depth map upsampling and completion. We describe the complete process for this system, including device calibration, scene warping for input alignment, and even how our framework can be extended for video depthmap completion with consideration of temporal coherence.
Jaesik Park, Hyeongwoo Kim, Yu-Wing Tai, Michael S. Brown, and In-So Kweon
IEEE Transactions of Image Processing (TIP)
@article{Park_High_TIP_2014,
Title={High Quality Depth Map Upsampling and Completion for RGB-D Cameras},
Author={Jaesik Park and Hyeongwoo Kim and Yu-Wing Tai and Michael S. Brown and In-So Kweon},
Journal={IEEE Transactions of Image Processing (TIP)},
Year={2014}
}
Jaesik Park, Hyeongwoo Kim*, Yu-Wing Tai, Michael S. Brown, and In-So Kweon
The 13th International Conference on Computer Vision (ICCV)
*The firrst and the second authors provided equal contributions to this work.
Paper Supplement Poster Executable Data BibTeX
@inproceedings{Park_High_ICCV_2011,
Title={High Quality Depth Map Upsampling for 3D-TOF Cameras},
Author={Jaesik Park and Hyeongwoo Kim and Yu-Wing Tai and Michael S. Brown and In-So Kweon},
Booktitle={Proceedings of the The 13th International Conference on Computer Vision (ICCV)},
Year={2011}
}


Copy this file to your /Home directory and modify it. This version is the default. Cd;Dir; Cd("::/Demo");Dir; Cd("::/Demo/Graphics");Dir; Cd("::/Demo/Snd");Dir; Cd("::/Demo/DolDoc");Dir; Cd("::/Demo/Games");Dir; Cd("::/Demo/MultiCore");Dir; Cd("::/Demo/Asm");Dir; Cd("::/Doc");Dir; Cd("::/Demo/Lectures");Dir; Cd("::/Apps");Dir; Run TOSStdIns() if you wish to use the official staff /Home files. Cd("::/Demo/AcctExample");Dir; Make all with BootHDIns(). Cd("::/Kernel");Dir; Cd("::/Compiler");Dir; The ::/StartOS.HC file is compiled every time you boot. Cd("::/Adam");Dir; Welcome Help & Index Demo Index FastReboot Take Tour Key Map Fun Games Titanium/* Graphics Not Rendered in HTML */ Diamond/* Graphics Not Rendered in HTML */ Bat/* Graphics Not Rendered in HTML */ Varoom/* Graphics Not Rendered in HTML */ FlatTops/* Graphics Not Rendered in HTML */ Golf /* Graphics Not Rendered in HTML */ KeepAway/* Graphics Not Rendered in HTML */ RawHide/* Graphics Not Rendered in HTML */ X-Caliber/* Graphics Not Rendered in HTML */ Wenceslas/* Graphics Not Rendered in HTML */ Lines/* Graphics Not Rendered in HTML */ Unfun Games Talons/* Graphics Not Rendered in HTML */ Frankenstein/* Graphics Not Rendered in HTML */ ZoneOut/* Graphics Not Rendered in HTML */ ToTheFront/* Graphics Not Rendered in HTML */ Span /* Graphics Not Rendered in HTML */ Checkers/* Graphics Not Rendered in HTML */ Digits/* Graphics Not Rendered in HTML */ Code Scraps Strut/* Graphics Not Rendered in HTML */ BigGuns/* Graphics Not Rendered in HTML */ TheDead/* Graphics Not Rendered in HTML */ DunGen/* Graphics Not Rendered in HTML */ Models/* Graphics Not Rendered in HTML */ Nongames JukeBox/* Graphics Not Rendered in HTML */ Psalmody/* Graphics Not Rendered in HTML */ Budget/* Graphics Not Rendered in HTML */ Logic/* Graphics Not Rendered in HTML */ Vocab/* Graphics Not Rendered in HTML */ List all syms in alpabetic order List all syms in numeric order


Table of Contents - rest-client-1.6.7 Documentation
Pages
README
REST Client – simple DSL for accessing HTTP and REST resources
Usage: Raw URL
Multipart
Usage: ActiveResource-Style
Usage: Resource Nesting
Exceptions (see
www.w3.org/Protocols/rfc2616/rfc2616-sec10.html
)
Result handling
Non-normalized URIs.
Lower-level access
Shell
Logging
Proxy
Query parameters
Cookies
SSL Client Certificates
Hook
More
Meta
Classes/Modules
RestClient
RestClient::AbstractResponse
RestClient::Exception
RestClient::ExceptionWithResponse
RestClient::Exceptions
RestClient::MaxRedirectsReached
RestClient::Payload
RestClient::Payload::Base
RestClient::Payload::Multipart
RestClient::Payload::Streamed
RestClient::Payload::UrlEncoded
RestClient::RawResponse
RestClient::Redirect
RestClient::Request
RestClient::Request::Redirect
RestClient::Request::RequestFailed
RestClient::RequestFailed
RestClient::Resource
RestClient::Response
RestClient::ResponseForException
RestClient::SSLCertificateNotVerified
RestClient::ServerBrokeConnection
Net
Net::HTTP
Net::HTTP::Patch
Net::HTTP::Protocol
MIME
MIME::Types
Methods
::add_before_execution_proc — RestClient
::beautify_headers — RestClient::AbstractResponse
::create — RestClient::Response
::create_log — RestClient
::decode — RestClient::Request
::delete — RestClient
::execute — RestClient::Request
::get — RestClient
::head — RestClient
::log= — RestClient
::new — RestClient::Request
::new — RestClient::Exception
::new — RestClient::RawResponse
::new — RestClient::Redirect
::new — RestClient::Resource
::new — RestClient::ServerBrokeConnection
::new — RestClient::SSLCertificateNotVerified
::new — RestClient::Payload::Base
::new — RestClient::Redirect
::options — RestClient
::patch — RestClient
::post — RestClient
::put — RestClient
::reset_before_execution_procs — RestClient
::type_for_extension — MIME::Types
::version — RestClient
#<< — RestClient
#[] — RestClient::Resource
#__request__ — Net::HTTP
#boundary — RestClient::Payload::Multipart
#build_stream — RestClient::Payload::UrlEncoded
#build_stream — RestClient::Payload::Multipart
#build_stream — RestClient::Payload::Base
#build_stream — RestClient::Payload::Streamed
#close — RestClient::Payload::Multipart
#close — RestClient::Payload::Base
#code — RestClient::AbstractResponse
#cookies — RestClient::AbstractResponse
#create_file_field — RestClient::Payload::Multipart
#create_regular_field — RestClient::Payload::Multipart
#default_headers — RestClient::Request
#delete — RestClient::Resource
#description — RestClient::AbstractResponse
#execute — RestClient::Request
#fetch_body — RestClient::Request
#flatten_params — RestClient::Payload::Base
#flatten_params_array — RestClient::Payload::Base
#follow_redirection — RestClient::AbstractResponse
#generate — RestClient::Payload
#get — RestClient::Resource
#handle_key — RestClient::Payload::Multipart
#handle_key — RestClient::Payload::UrlEncoded
#has_file? — RestClient::Payload
#has_file_array? — RestClient::Payload
#head — RestClient::Resource
#headers — RestClient::Payload::Multipart
#headers — RestClient::AbstractResponse
#headers — RestClient::Payload::UrlEncoded
#headers — RestClient::Resource
#headers — RestClient::Payload::Base
#http_body — RestClient::Exception
#http_code — RestClient::Exception
#inspect — RestClient::Payload::Base
#inspect — RestClient::Exception
#length — RestClient::Payload::Streamed
#length — RestClient::Payload::Base
#log_request — RestClient::Request
#log_response — RestClient::Request
#make_headers — RestClient::Request
#message — RestClient::Exception
#message — RestClient::RequestFailed
#message — RestClient::RequestFailed
#method_missing — RestClient::ResponseForException
#mime_for — RestClient::Payload::Multipart
#net_http_class — RestClient::Request
#net_http_request_class — RestClient::Request
#open_timeout — RestClient::Resource
#parse_url — RestClient::Request
#parse_url_with_auth — RestClient::Request
#password — RestClient::Resource
#patch — RestClient::Resource
#patch — Net::HTTP::Protocol
#post — RestClient::Resource
#process_payload — RestClient::Request
#process_result — RestClient::Request
#process_url_params — RestClient::Request
#put — RestClient::Resource
#raw_headers — RestClient::AbstractResponse
#read — RestClient::Payload::Base
#request — Net::HTTP
#return! — RestClient::AbstractResponse
#send_entity — Net::HTTP::Protocol
#setup_credentials — RestClient::Request
#short_inspect — RestClient::Payload::Base
#size — RestClient::Payload::Base
#size — RestClient::RawResponse
#size — RestClient::Payload::Streamed
#stringify_headers — RestClient::Request
#timeout — RestClient::Resource
#to_i — RestClient::AbstractResponse
#to_s — RestClient::Exception
#to_s — RestClient::RequestFailed
#to_s — RestClient::RawResponse
#to_s — RestClient::Payload::Base
#to_s — RestClient::Resource
#to_s — RestClient::RequestFailed
#transmit — RestClient::Request
#type_for_extension — MIME::Types
#user — RestClient::Resource


is a partnership between the Evangelical Methodist Church in El Salvador and United Methodist Volunteers in Mission in the United States whose purpose is to improve the spiritual and physical lives of economically disadvantaged people living in El Salvador. SMP uses volunteers and funds provided by Evangelical Methodist Churches in El Salvador and United Methodist Churches in the US to build and repair church buildings, build and staff medical clinics, provide food for the hungry and build homes for people who do not have sufficient financial resources to obtain a home through any other program.