|
| | buildLink ($originalPrefix, $outputPrefix, $action, $extension, $data, array &$extraParams) |
| |
◆ buildLink()
| buildLink |
( |
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$originalPrefix, |
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|
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$outputPrefix, |
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$action, |
|
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$extension, |
|
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$data, |
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array & |
$extraParams |
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) |
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Method to build a link to the specified page/action with the provided data and params.
Unhandled extra params will be turned into a query string after this function is called. If a param is handled by the core URL, it should be unset from the extra params list.
- Parameters
-
| string | $originalPrefix | Original prefix for the type of link to be generated; this is a known value, but shouldn't be displayed to the user |
| string | $outputPrefix | The configured output that means the same thing as the original prefix but is user configured |
| string | $action | Action to take on the data |
| string | $extension | Specified extension for the link |
| mixed | $data | Info about data to link to specifically (eg, info about a thread) |
| array | $extraParams | Extra params that modify how the link is built |
- Returns
- string|false Core link if handled, false otherwise
The documentation for this interface was generated from the following file:
- C:/Users/Michel/Desktop/test/xf/library/XenForo/Route/BuilderInterface.php


|
UQTk: Uncertainty Quantification Toolkit 3.1.3
|
#include <Object.h>
Public Member Functions | |
| Object () | |
| Construct a new reference counted object with a zero reference count. More... | |
| virtual | ~Object () |
| Destroy this object. More... | |
| long int | reference_count () const |
| Returns the number of references that are held to this object. More... | |
Protected Member Functions | |
| long int | reference_grab () const |
| long int | reference_release () const |
Private Attributes | |
| long int | refs_ |
Friends | |
| template<class T > | |
| class | RefPtr |
| template<class T > | |
| class | ConstRefPtr |
Base class for reference counted objects.
Part of the Particle Simulation Toolkit (pst)
The "friend" classes "RefPtr" and "ConstRefPtr" take care of the reference counting and garbage collection. This means that it should be safe to create an array of reference counted objects, as long as you do not assign a reference counted pointer to any at the entries in the array at any time.
|
inline |
Construct a new reference counted object with a zero reference count.
|
inlinevirtual |
Destroy this object.
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inline |
Returns the number of references that are held to this object.
|
inlineprotected |
Enables the friends of the class to increment and decrement the reference count.
|
inlineprotected |
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friend |
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friend |
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mutableprivate |


|
Boreal Engine
0.1
Simple game engine written in C++ using OpenGL
|
Namespace for all things related to Boreal Engine. More...
Classes | |
| class | Time |
| class | Camera |
| class | Debug |
| Allows user to log messages, as well as warnings and errors. Allows filtering for specific message types (log, warning, and error). More... | |
| class | IndexBuffer |
| Allows user to create and manage index buffers. More... | |
| class | Input |
| Allows user to handle user input. More... | |
| class | Model |
| Allows user to create and manage models. More... | |
| class | ShaderProgram |
| class | Texture |
| struct | Vertex |
| Structure that describes the components of a vertex. More... | |
| class | VertexBuffer |
| Allows user to create and manage vertex buffers. More... | |
| class | Window |
| Allows user to create and manage windows. More... | |
Typedefs | |
| typedef struct Boreal::Vertex | Vertex |
| Structure that describes the components of a vertex. | |
Functions | |
| void | Initialize () |
| Function to initialize everything needed to use Boreal Engine. | |
| void | Terminate () |
| Function to terminate Boreal Engine. | |
Namespace for all things related to Boreal Engine.


Graphs with mermaid
This is a sequence diagram generated by Mermaid which is integrated in the default layout :
Gantt
gantt
title Cleanup repositories roadmap
dateFormat YYYY-MM-DD
section CI
Skill up with GitHub actions :2022-09-25, 5d
section PHP
git-manager :a1, 2022-09-25, 2d
remote-git :after a1, 1d
section NodeJS
node-extract :2022-09-28, 1d
markdown-to-html :4d
Sequence diagram
sequenceDiagram
Alice ->> Bob: Hello Bob, how are you?
Bob-->>John: How about you John?
Bob--x Alice: I am good thanks!
Bob-x John: I am good thanks!
Note right of John: Bob thinks a long
long time, so long
that the text does
not fit on a row.
Bob-->Alice: Checking with John...
Alice->John: Yes... John, how are you?


Clubs and Communites in your University
Hackerspace
E-Cell
Debate Society
Team Aeolus - DBC (fixed wing) division
Trance
Pixels
Ninaada
CORI
Prakalpa
Samparpana
Nautanki
Maaya
Pulse
Aatmatrisha
PESU Super Smash Bros
Mastadon Basketball Women
UniFOSS
Swarantraka
PESU Shuttlers Men
CS Club
The AlCoding Club
ActionCut
Socioholics
CSR
Rotaract
Sanskriti
AIKYA
Abhinayaveethii
Aidra
Fantom
Hospitality and Tourism
QForest
Quotient Quiz Club
Team Aeolus - IARC (Robotics) division
TEDX
SAE
Paisa Vasool
MIT Event
Talk+
Team Haya Racing
ICare group
Impetus
PES Chronicles
Dsgnr
Samkaran
Kirik Party
Robotics
JEDI
Microsoft Innovation Lab
MUN Society
Ordell Ugo
Pes Talkies
Papyrus
ECLAT
Jhenkar
Pitch Please
Saarang
Ouroboros
Excelsior
Chef Club
Catalyst
Entropi
Team Haya Off Roading
The Music Club
IEEE-RAS
Developer Student Clubs
PESU Shuttlers Women
Mastadon Kabaddi
PESU Chess Mates
Masatdon Football Men
Mastadon Football Women
Mastadon Marauders
Mastadon Swimming
Mastadon Throwball
Mastdon Basketball Men
Rowing
Changemakers' Society
Through the Lens
Epsilon
Dhruva Club


Out of the box Boost QVM defines generic yet simple quat, vec and mat types. For example, the following snippet creates a quaternion object that rotates around the X axis:
#include <boost/qvm/quat.hpp> #include <boost/qvm/quat_operations.hpp> .... quat<float> rx=rotx_quat(3.14159f);
Similarly, a matrix that translates by a given vector can be created as follows:
#include <boost/qvm/mat.hpp> #include <boost/qvm/vec.hpp> #include <boost/qvm/map_vec_mat.hpp> .... vec<float,3> v={0,0,7}; mat<float,4,4> tr=translation_mat(v);
The usual quaternion, vector and matrix operations work on these Boost QVM types, however the operations are decoupled from any specific types: they work on any suitable type that has been registered by specializing the quat_traits, vec_traits and mat_traits templates.
For example, a user-defined 3D vector type float3 can be introduced to Boost QVM as follows:
#include <boost/qvm/vec_traits.hpp> struct float3 { float a[3]; }; namespace boost { namespace qvm { template <> struct vec_traits<float3> { static int const dim=3; typedef float scalar_type; template <int I> static inline scalar_type & write_element( float3 & v ) { return v.a[I]; } template <int I> static inline scalar_type read_element( float3 const & v ) { return v.a[I]; } static inline scalar_type & write_element_idx( int i, float3 & v ) { return v.a[i]; } //optional static inline scalar_type read_element_idx( int i, float3 const & v ) { return v.a[i]; } //optional }; } }
After a similar specialization of the mat_traits template for a user-defined 3x3 matrix type float33, the full range of vector and matrix operations defined by Boost QVM headers becomes available automatically:
float3 v; X(v) = 0; Y(v) = 0; Z(v) = 7; float vmag = mag(v); float33 m = rotx_mat<3>(3.14159f); float3 vrot = m * v;
User-defined quaternion types are similarly introduced to Boost QVM by specializing the quat_traits template.
Tutorial navigation: Quaternions, Vectors, Matrices | C Arrays | Views | Swizzling | Interoperability
See also: Boost QVM


Controls
Number to Visualise:
Pi
Phi
e
X-Side Length:
Y-Side Length:
Ball Radius:
Colours
Number
Colour
0
1
2
3
4
5
6
7
8
9


Item.
I've given my students a file which contains data on the number of predatory lending institutions in each county, as well as data on race, income, and education. Give me 10 problems which use correlation to help students uncover patterns in the data and how predatory lending institutions are distributed.in-context


new Controller(model, view)
Parameters:
| Name | Type | Description |
|---|---|---|
model |
object | The Model instance |
view |
object | The View instance |
- Source:
Members
_activeRoute
Store a reference to the active route, allowing us to re-filter todo
items as they are marked complete or incomplete.
- Source:
Methods
_filter(force)
Re-filters the todo items, based on the active route.
Parameters:
| Name | Type | Description |
|---|---|---|
force |
boolean | undefined | Force item re-filtering |
- Source:
_updateCount()
Updates the pieces of the page which change depending on the remaining number of todos.
- Source:
_updateFilterState(currentPage)
Simply updates routes in url
Parameters:
| Name | Type | Description |
|---|---|---|
currentPage |
string | '' || active || completed. |
- Source:
addItem(title)
An event to fire whenever you want to add an item. Simply pass in the event
object and it'll handle the DOM insertion and saving of the new item.
Parameters:
| Name | Type | Description |
|---|---|---|
title |
string | The title of the item to add |
- Source:
editItem(id)
Triggers the item editing mode.
Parameters:
| Name | Type | Description |
|---|---|---|
id |
number | ID of the new model to edit. |
- Source:
editItemCancel(id)
Cancels the item editing mode of the element.
Parameters:
| Name | Type | Description |
|---|---|---|
id |
number | ID of the model being edited. |
- Source:
editItemSave(id, title)
Finishes the item editing mode successfully.
Parameters:
| Name | Type | Description |
|---|---|---|
id |
number | ID of the edited model to save |
title |
string | The content of the todo. |
- Source:
removeCompletedItems()
Will remove all completed items from the DOM and storage.
- Source:
removeItem(id)
Removes an item from the list : By giving it an ID it'll find the DOM element matching that ID,
remove it from the DOM and also remove it from storage.
Parameters:
| Name | Type | Description |
|---|---|---|
id |
number | The ID of the item to remove from the DOM and storage |
- Source:
setView(locationHash)
Loads and initialises the View
Parameters:
| Name | Type | Description |
|---|---|---|
locationHash |
string | The hash of the actual page can have these values : '' | 'active' | 'completed' |
- Source:
showActive()
Renders all active tasks with the parameter completed: false.
- Source:
showAll()
An event to fire on load. Will get all items and display them in the
todo-list
- Source:
showCompleted()
Renders all completed tasks with the parameter completed: true.
- Source:
toggleAll(checkbox)
Will toggle ALL checkboxes' on/off state and completeness of models (Just pass in the event object).
Parameters:
| Name | Type | Description |
|---|---|---|
checkbox |
object | The checkbox to validate the status of the element. |
- Source:
toggleComplete(id, checkbox, silent)
Updates the display of items based on their status wich depend from the checkbox state
Parameters:
| Name | Type | Description |
|---|---|---|
id |
number | The ID of the element to complete or uncomplete |
checkbox |
object | The checkbox to check the state of complete or not. |
silent |
boolean | undefined | Prevent re-filtering the todo items |
- Source:


Most of the icons within Versions will display a text label when you point at them for a moment. In Browse view, you can widen the Data Status column (has three dots as the heading) to see the text labels for each status.
The numbers in the small badges next to the working copy bookmark show how many items have changes. A yellow badge indicates local changes in your working copy, while a blue badge indicates remote changes in the repository. Within the file listing, folders that contain changes are indicated by a yellow dot.
Added: File has been added to the working copy, but not committed to the repository.
Deleted: File has been deleted from the working copy, but not committed to the repository. It will be removed from the file listing once the change is committed.
Ignored: File has been explicitly marked as ignored in the working copy, or is ignored due to global-ignore setting in subversion config file.
Missing: File has been removed from the working copy outside of svn (e.g. deleted in the Finder).
Modified: File in the working copy has changes that have not been committed to the repository.


{% extends 'emails/base.html' %} {% block content %}
Hi there,
Hope you had a great SAC Fair! As a user of Penn Clubs, we’d love to hear some feedback from you on how we did transitioning this years Club Fair online!
If you have 5 minutes to fill out our short feedback survey here, that would be greatly appreciated. We plan on continuing to improve Penn Clubs based on input from our users like you.
Just as a reminder, officers of clubs cannot see your contact information if you have only bookmarked your club. They can, however, see your information if you have subscribed to their club. We also encourage you to check back on club pages in their "How to Get Involved" section of their pages for more information on applications, info sessions, and more.
Thanks for helping us expand our platform during the SAC Fair! We appreciate your patience as we transitioned. Please let us know if you have any questions or feedback.
Fill out our Survey! {% endblock %}


For help sending push notifications, join the Ionic Platform and check out Ionic Push. We also have other services available.


| Expedition Name: | ||
| Expedition Type: | ||
| Sponsor Organization: | Add New Organization to Database | |
| Description: | ||
| Dates: | Begin Date: End Date: | |
| Equipment: | Add New Equipment to Database | |
| Identifier: | ||
| Alternate Names: |
(Comma-separated list of alternative expedition names.)
|


Circuit Details
- Multi-channel light to digital processor
- High dynamic range requirements
- Noisy ambient and system environment – signal-path and substrate noise filtering required
- Precision, high-speed current-to-voltage front-end
- Multiple package options
- QFN for prototypes and development systems
- 9-bump WLCSP for high volume production
IP Blocks Utilized
- Programmable Gain Transimpedence Amplifier (TIA)
- Band Pass Filter
- Analog to Digital Conversion
- Combined Analog and Digital Automatic Gain Control (AGC)
- Bandgap, Precision Reference Network
- Envelope Detection
- External Diode Bias
- Power-on-Reset (POR)
- Watchdog


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This is my most recent experience with neurontin. I was going through opiate withdrawals because my script of D's ran out, and I was getting desperate. I called all my contacts & nobody had anything; not even a suboxone.
I have been on dilaudid for years from having chronic pain from multiple abdominal hernias and a ruptured colon that resulted in a colostomy (shit bag). I am prescribed only 100 8mg D's a month and go through them like candy. I never take them as prescribed. I almost always bang them or once in awhile, snort them.
Well, two days ago I ran out of my D's early because I had to get rid of some because I needed some extra money. I don't condone the selling or abusing of meds, but this is just what I do. So, I was withdrawing pretty bad yesterday morning and was running out of options. Thoughts of robbing the pharmacy was entering my mind, and that was out of the question.
Then, while I was laying in bed with terrible cold sweats and the shakes, I remembered that pain management gave me a script for neurontin with my last dilaudid script. The dr. told me that the neurontin would boost the effects of the dilaudid. Now, I've had neurontin before from a past surgery and had a decent experience from swallowing around 3000mg of the 600mg pills (not capsule form). These I had now were the 300mg dose. I took the script to the pharmacy and got them filled and immediately after returning to my car, emptied 6 capsules into my mouth and took a large drink of pepsi.
On my way home I was feeling absolutely nothing from the neuros. But the good thing was, they were beginning to ease my withdrawals. I was still shaking a lil, but my cold sweats had stopped after about 30 minutes of taking the neuros.
After about 2 hours, I was laying in bed and feeling ok. My withdrawals had been pretty much curbed by the neuros, so now I wanted to get bent. So I grabbed the bottle of neuros, took out 10 more, and swallowed the caps whole without taking the powder out first. Again, these are the 300mg ones, so altogether I've now taken 4800mg over a period of 2 1/2 hours.
I drank a bottle of pepsi to help with the absorption process, and decided to play some Guitar Hero Mettalica on the Wii. After around another hour or so, I was feeling no effects of the neurontins. Neither bad nor good. My prior experience with them had been better. My past experience had resulted in quite a boost in my mood and slight euphoria. This time I was feeling nothing other than my withdrawals being stopped.
After another 6 hours I was starting to feel a bit tired and it was getting close to bedtime anyway, so I laid down and was out in a matter of minutes. I woke up this morning with slight withdrawals from my opiate use, and swallowed another 8 neuros. After 30 minutes, my withdrawals had ceased, but no other effects.
So, as far as recreational use, I wouldn't recommend neurontin to anyone that has a high opiate tolerance that is looking for a good buzz. But, I would recommend it for opiate withdrawals. I was quite amazed at how well it was able to curb my withdrawals so well.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


mplus_compile.Rd
Creates a tidy dataset containing analyses from multiple Mplus objects. This can then be used in the mplus_apa_table()
function, or can be saved separately.
mplus_compile( Mplus_file, rounding = 2, param_header = NULL, parameter = NULL, display = "all", standardized = TRUE, converged = TRUE, define = FALSE )
| Mplus_file | An mplus object generated by the Mplus Automation package from Mplus output using the |
|---|---|
| rounding | A value between 0 and 3. Defaults to 2. |
| param_header | Parameter headers from the Mplus output. Exact parameter headers can be found using |
| parameter | Parameters in the Mplus output. These can be found using |
| display | How many columns should be displayed. Choose from "all", "minimal", "descriptives" or manually specify which columns should be displayed. Available columns can be found using |
| standardized | Whether standardized or unstandardized output should be used for univariate and bivariate models. Defaults to TRUE. |
| converged | If TRUE, removes non-converged models. |
| define | Displays a column containing information from the 'define' input in the Mplus file. Defaults to FALSE. |
A tibble containing specified variables and parameters from multiple Mplus models.


Entertainment
Tipperary trad fest attracts top musicians
Newport weekend sees gigs by Frankie Gavin and Noel Hill
by Tipperary Star reporterSome of the top names in trad music will be in Newport next month for the town’s Trad Fest, which runs from December 6 to 8.
Among those taking part will be fiddle player Frankie Gavin and concertina player Noel Hill.
They will be joined on stage at the Freigh Inn by Monica Brennan and Brian McGrath. Doors open open at 7.30pm and tickets cost €20.
The opening night will see an eclectic group gather for what is billed as the Electric Banquet in Newport church.
The free event, which kicks off at 7pm, will feature musicians from around Newport, including Brendan Mulholland, Deirdre Scanlon, Brian Shinners, Teresa Tuohey and Tova Byres. Also on the bill will be St Mary’s Secondary School choir and Newport College choir. There will be a bucket collection in aid of Crumlin Children’s Hospital.
Saturday will see plenty of workshops in the Community Hall from 11am to 2pm. Participation costs €20. There will be classes in tin whistle, concertina, fiddle and flute.


Spiced Academy Final Project Presentation
Samuel Rothen
04.12.2020
Project Introduction
Project Introduction
Project Goals
- Live Face Tracking
- Face Mask Detection
- Automated Camera-Mount that tracks People without Face Mask
Project Structure
Project Structure
Project Structure
Project Structure
Project Structure
Live Face Tracking
Face Mask Detection
Automated Camera-Mount
Complete System
Project Outlook
- Radar-Camera-Fusion
- Detect Oxidation on Steel Slab Surface
- Live Adjustment of the Radar-Configuration
Random Statistics
- 273 Lines of Python-Code
- 39 Lines of Arduino-Code
- 40 Commits to GitHub
- 4.515 Train/Test-Pictures
- 2.386.286 Neurons
- 6 Model-Layers
- 68 Epochs for Training
- 50 Minutes to train the Model


class: inverse, center, middle #The Maillard Reaction A key complex of chemical reactions ##\#CaffeinatedTraining ##\#OilSlickCoffee
@michael.c.wright
youtube.com/c/MichaelCWright
OilSlickCoffee
Presented: June 12th, 2018 Host:
5758 Coffee Lab
Location: Bandung, Indonesia .footnote[ Press "h" for keyboard shortcuts for this presentation] --- # What is it? (40,000-foot view) * Critical, chemical reaction in coffee roasting * Occurs in many other foods as well * Browning of foods such as bread, meat, etc --- # What is it? (better description, but still not great) * Complex reaction of reactions * Occurs at room temperature, but very slowly * Occurs rapidly/readily at ≥ 140° - 165°C (280°-300°F) * Produces **hundreds** of aromatics and flavonoids * Produces caramel and melanoidins * Higher temps = higher reaction velocity * Higher reaction velocity = increased melanoidin production * More sugars over amino acids also increase reaction rate .footnote[ *Melanoidins Formed by Maillard Reaction in Food and Their Biological Activity, Food Eng Rev (2012) 4:203–223, ISSN 1866-7910] ??? Primarily why second phase, starting at 300° is also referred to as the Maillard phase Without the Maillard reaction, we aren’t roasting coffee --- # Maillard Reaction ## The plot thickens * Browning (caramel and melanoidin production) is the last step of the reaction
1
* Therefore it is a useful indication of a phase-change in roasting process * Removing chemically-free water is necessary in order to exceed 100°C/212°F (boiling point of water)
2
* "The Maillard reaction will not cause browning in foods cooked with moist heat (boiling, steaming, poaching, stewing) because water cannot be heated above 212°F/100°C unless it is under pressure."
3
* Water is a heatsink (large heat capacity) * Fermentation of coffee may contribute amine-containing precursors for the Maillard reaction
2
.footnote[
1
Melanoidins Formed by Maillard Reaction in Food and Their Biological Activity, Food Eng Rev (2012) 4:203–223, ISSN 1866-7910
2
http://luckypeach.com/opusculum-maillard-reactions/
3
https://www.quora.com/Why-is-coffee-brown/answer/Peter-Baskerville#] ??? If fermentation creates precursors for MR, this could expand our understanding of natural VS fully washed VS MR and flavor --- # Melanoidins * Brown, fibrous polymers with a high molecular weight * Largely responsible for a coffee’s body or mouthfeel * “[I]ntimately associated in consumers’ minds with a high-grade product of desirable texture and flavour.”
1
* Increasingly, studies indicate antioxidant effect
1
* Also antimicrobial effects against pathogenic microorgs
1
.footnote[
1
1 Melanoidins produced by the Maillard reaction: Structure and biological activity, Volume 128, Issue 3, Pages 573-822 (1 October 2011) ] --- class: pic, center, middle # Not all that glitters is gold ![pyrite](/images/pyrite.jpg) .footnote[
Pyrite (Fools Gold)
by pnjunction2007 from SENDAY/MIYAGI/JAPAN, Japan
[CC BY 2.0 (https://creativecommons.org/licenses/by/2.0)], via Wikimedia Commons] --- # Not all that glitters is gold Maillard reaction also produces the following * Furfural (toxin) * 5- hydroxymethylfurfural (possible carcinogen) * Furans (possible carcinogen) * Aldehyde (possible carcinogen) Maillard reaction causes the loss of some nutrients (but we don’t drink coffee for its nutritional benefits) **The dose determines the poison** .footnote[ Melanoidins Formed by Maillard Reaction in Food and Their Biological Activity, Food Eng Rev (2012) 4:203–223, ISSN 1866-7910] ??? California & Proposition 65 --- class: center, middle # Coffee is safe to drink Coffee drinking “shows reduction in cancers in certain humans, has not been shown to increase any cancers, and is particularly rich in cancer-chemo-preventive compounds.” **(But is not *medicinal*)** .footnote[ Joseph R. Landolph, Ph. D., https://oehha.ca.gov/media/downloads/crnr/coffeepeerreviewcomments091118.pdf] --- exclude: true class: middle # Quick Review * What is the critical temperature where the Maillard Reaction really gets going? * Why is the MR even important to coffee roasters? * How does the MR impact a coffee’s body/mouth-feel? ??? Occurs rapidly ≥ 140° - 165°C (280°-300°F) Produces hundreds of aromatics and flavonoids and produces melanoidins melanoidins have HMW = body/mouth feel --- # Leveraging the Maillard Reaction Tracking the reaction * It effectively starts at 140° - 165°C (280°-300°F) * (coincides with the beginning of yellowing) * The last step is browning via formation of caramel and melanoidins * sugar caramelization occurs around 198°C/390°F Therefore most of what happens after the MR is the creation of roasted flavors ![maillard flavor wheel](/images/roasted-flavor-wheel.jpg) .footnote[ https://sca.coffee/research/coffee-tasters-flavor-wheel/] --- class: image, center, middle #Maillard Flavors & Aromas
.footnote[ https://sca.coffee/research/coffee-tasters-flavor-wheel/] ??? Knowing what flavors are caused and when empowers the roaster. There is absolutely nothing wrong with darker roasts. Second crack is not a bad word. There are coffees that do very well when roasted to a darker degree. There are many customers who will prefer a darker roast. To develop or avoid flavors, we need to know how and when they are formed. --- # Put simply Longer Maillard reaction = greater number of bi-products = higher complexity + higher body Not all that glitters is gold! The price to pay for higher complexity and higher body = lower clarity ??? Clarity is probably a bad term to use here. Complex, full-bodied coffees can be clear in what they are, i.e., they can have clarity. --- # Maillard Reaction Cheat Sheet 1. The Maillard phase consumes sugars and amino acids 2. ...to produce melanoidins, which contribute to brownness of the roasted beans as well as the body of brewed or extracted coffee. 3. A higher rate of heat application increases the reaction rate. 4. The dominate flavors produced by the reaction are nutty, caramelly, chocolatey, malty flavors. 5. If temps are equal, a longer reaction time = greater number of byproducts = higher complexity + higher body. --- class: center, middle ## Value 4 Value If you found this content useful, please consider [supporting my work](https://oilslickcoffee.com/support/?utm_source=caffeinated-training&utm_medium=blog&utm_campaign=support). I charge no set fee or price for providing this. You can help keep information like this openly accessible by matching the value you received in the content; value 4 value. [Ko-fi](https://ko-fi.com/Z8Z8LX14) **/** Bitcoin Wallet: 32SW9kcAsJdZvQKBazhLUZBSD9YS8DDqe8
Learn more
--- class: center, middle End of presentation


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qml-ar
|
This class is a wrapper around QMLAR object which is placed at a separate thread and controlled by this object. More...
#include <threadedqmlar.h>
Public Slots | |
| void | setCameraId (int camera_id=-1) |
| Initialize from camera id (default value -1) | |
| void | setImageFilename (QString filename) |
| Initialize from image. | |
| void | setImageWidth (int new_width) |
| Set width of the image to process (on startup) | |
| void | startCamera () |
| Start camera if required. | |
| void | setFilterAlpha (double alpha) |
| Set filtering alpha. | |
| void | setBlobs (QVariantList that) |
| Set blobs (internal) | |
| void | setMarkers (QVariantList that) |
| Set markers (internal) | |
| void | setMVPMatrix (QMatrix4x4) |
| Set MVP matrix (internal) | |
| void | setMVMatrix (QMatrix4x4) |
| Set MV matrix (internal) | |
| void | setPMatrix (QMatrix4x4) |
| Set P matrix (internal) | |
| void | setRunning (bool) |
| Set running/paused. | |
| void | setShowShader (bool value) |
| Show shader output on top-left of input frame? Only for Android API >= 26. More... | |
Signals | |
| void | newMVPMatrix (QMatrix4x4) |
| Notify QML part when new matrix is available. | |
| void | newMVMatrix (QMatrix4x4) |
| Notify QML part when new matrix is available. | |
| void | newPMatrix (QMatrix4x4) |
| Notify QML part when new matrix is available. | |
| void | imageUpdated () |
| Notify about new image. | |
| void | newBlobs (QVariantList) |
| On new blobs from detector. | |
| void | newMarkers (QVariantList) |
| On new markers. | |
| void | setCameraIdSignal (int camera_id=-1) |
| Initialize from camera id (default value -1) | |
| void | setImageFilenameSignal (QString filename) |
| Initialize from image. | |
| void | setImageWidthSignal (int new_width) |
| Set width of the image to process (on startup) | |
| void | startCameraSignal () |
| Start camera if required. | |
| void | setFilterAlphaSignal (double alpha) |
| Set filtering alpha. | |
Public Member Functions | |
| ThreadedQMLAR () | |
| Empty constructor. | |
| int | getCameraId () |
| Get camera ID. | |
| QString | getImageFilename () |
| Get path to the image. | |
| QMatrix4x4 | getMVPMatrix () |
| Get ModelViewProjection matrix. | |
| QMatrix4x4 | getMVMatrix () |
| Get ModelView matrix. | |
| QMatrix4x4 | getPMatrix () |
| Get projection matrix. | |
| int | getImageWidth () |
| Get width of the image in the pipeline. | |
| QQuickImageProvider * | getImageProvider () |
| Get current image provider. | |
| QObject * | getCamera () |
| Get QCamera media object, if available. | |
| QVariantList | getBlobs () |
| Return list of blobs on markers. | |
| QVariantList | getMarkers () |
| Return list of detected markers. | |
| double | getFPSMean () |
| FPS: mean. | |
| double | getFPSStd () |
| FPS: std. | |
| double | getLatencyMean () |
| Latency (ms): mean. | |
| double | getLatencyStd () |
| Latency (ms): std. | |
| bool | markers_visible () |
| At least one marker present. | |
| double | getFilterAlpha () |
| Filtering coefficient. | |
| bool | poseValid () |
| Is pose valid? | |
| double | getFrameDrop () |
| Framedrop fraction. | |
| int | getFrameDelay () |
| Returns delay in frames. | |
| bool | getRunning () |
| Is QMLAR currently active? | |
| bool | getShowShader () |
| Show shader output (Android API >= 26) More... | |
Properties | |
| int | camera_id |
| Number of the camera to use. If set, using camera input. | |
| QString | image_filename |
| Path to the image to use. If set, will use image input. | |
| QObject | camera |
| QCamera mediaobject for Viewfinder (if available) | |
| QMatrix4x4 | mvp_matrix |
| OpenGL ModelViewProjection matrix from the pipeline. More... | |
| QMatrix4x4 | mv_matrix |
| OpenGL ModelView matrix from the pipeline. | |
| QMatrix4x4 | p_matrix |
| OpenGL Projection matrix from the pipeline. | |
| int | image_width |
| The width of the image to be used inside the pipeline. | |
| QVariantList | blobs |
| The list of blobs on detected markers (QVector2D as element) | |
| QVariantList | markers |
| The list of detected markers, each containing an array of marker corners. | |
| double | FPSMean |
| The mean FPS value at this moment. | |
| double | FPSStd |
| The std FPS value at this moment. | |
| double | LatencyMean |
| The mean Latency value at this moment. | |
| double | LatencyStd |
| The std Latency value at this moment. | |
| bool | markers_visible |
| Are markers visible right now? | |
| bool | pose_valid |
| Is the pose (MVP/MV matrix) valid at this moment? | |
| double | filter_alpha |
| Filtering coefficient for the pose. More... | |
| double | framedrop |
| The current percentage of dropped frames at this moment. | |
| int | frame_delay |
| Current delay in frames from capture to computed pose. | |
| int | running |
| Pause/stop QMLAR. | |
| bool | show_shader_output |
| Show shader output on top-left of the input frame? Android API >= 26 only. | |
This class is a wrapper around QMLAR object which is placed at a separate thread and controlled by this object.
|
inline |
Show shader output (Android API >= 26)
|
slot |
Show shader output on top-left of input frame? Only for Android API >= 26.
| value | Show or not |
|
readwrite |
Filtering coefficient for the pose.
Cached alpha filter.
|
read |
OpenGL ModelViewProjection matrix from the pipeline.
MVP matrix buffer.


| CUB Model Approximation {cubfits} | R Documentation |
This function provides codon usage bias approximation with observed ORFs but without any expressions.
cubappr(reu13.df.obs, phi.pred.Init, y, n, nIter = 1000, b.Init = NULL, init.b.Scale = .CF.CONF$init.b.Scale, b.DrawScale = .CF.CONF$b.DrawScale, b.RInit = NULL, p.Init = NULL, p.nclass = .CF.CONF$p.nclass, p.DrawScale = .CF.CONF$p.DrawScale, phi.pred.DrawScale = .CF.CONF$phi.pred.DrawScale, model = .CF.CT$model[1], model.Phi = .CF.CT$model.Phi[1], adaptive = .CF.CT$adaptive[1], verbose = .CF.DP$verbose, iterThin = .CF.DP$iterThin, report = .CF.DP$report)
reu13.df.obs |
a |
phi.pred.Init |
a |
y |
a |
n |
a |
nIter |
number of iterations after burn-in iterations. |
b.Init |
initial values for parameters |
init.b.Scale |
for initial |
b.DrawScale |
scaling factor for adaptive MCMC with random walks
when drawing new |
b.RInit |
initial values (in a list) for |
p.Init |
initial values for hyper-parameters. |
p.nclass |
number of components for |
p.DrawScale |
scaling factor for adaptive MCMC with random walks
when drawing new |
phi.pred.DrawScale |
scaling factor for adaptive MCMC with random walks when drawing new Phi of predicted set. |
model |
model to be fitted, currently "roc" only. |
model.Phi |
prior model for Phi, currently "lognormal". |
adaptive |
adaptive method of MCMC for proposing new |
verbose |
print iteration messages. |
iterThin |
thinning iterations. |
report |
number of iterations to report more information. |
Total number of MCMC iterations is nIter + 1
, but the
outputs may be thinned to nIter / iterThin + 1
iterations.
Temporary result dumping may be controlled by .CF.DP
.
A list contains three big lists of MCMC traces including:
b.Mat
for mutation and selection coefficients of b
,
p.Mat
for hyper-parameters, and
phi.Mat
for expected expression values Phi.
All lists are of length nIter / iterThin + 1
and
each element contains the output of each iteration.
All lists also can be binded as trace matrices, such as via
do.call("rbind", b.Mat)
yielding a matrix of dimension number of
iterations by number of parameters. Then, those traces can be analyzed
further via other MCMC packages such as coda.
Note that phi.pred.Init
need to be normalized to mean 1.
p.DrawScale
may cause scaling prior if adaptive MCMC is used, and
it can result in non-exits of equilibrium distribution.
Wei-Chen Chen<EMAIL_ADDRESS>https://github.com/snoweye/cubfits/
DataIO, DataConverting,
cubfits()
and cubpred()
.
## Not run: suppressMessages(library(cubfits, quietly = TRUE)) demo(roc.appr, 'cubfits', ask = F, echo = F) ## End(Not run)


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This is a vibrant resort town on the southern tip on the Sinai peninsula. Diving activities abound here due to the proximity of the many spectacular reefs in the Red Sea.
The port, in Sharem-al-Maya bay, has became the city's main yacht and service port. This is a commercial port and not very comfortable for yachts. Mooring fees are very high.
Travco Marina is only for Egyptian boats.
Last updated February 2011.


The value specified for this option must be a colon-separated list of
pathnames that determines where sendmail looks for the per-user forwarding
file when delivering email. The variables $z for the user's home
directory and $w for the system hostname can be used in the path.


Computation of an estimation of the long-memory parameters and the long-run covariance matrix using a multivariate model (Lobato (1999) <doi:10.1016/S0304-4076(98)00038-4>; Shimotsu (2007) <doi:10.1016/j.jeconom.2006.01.003>). Two semi-parametric methods are implemented: a Fourier based approach (Shimotsu (2007) <doi:10.1016/j.jeconom.2006.01.003>) and a wavelet based approach (Achard and Gannaz (2016) <doi:10.1111/jtsa.12170>).
| Version: | 1.2 |
| Published: | 2016-11-24 |
| Author: | Sophie Achard [aut, cre], Irene Gannaz [aut] |
| Maintainer: | Sophie Achard <sophie.achard at gipsa-lab.fr> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | multiwave results |
| Reference manual: | multiwave.pdf |
| Package source: | multiwave_1.2.tar.gz |
| Windows binaries: | r-devel: multiwave_1.2.zip, r-release: multiwave_1.2.zip, r-oldrel: multiwave_1.2.zip |
| OS X binaries: | r-release: multiwave_1.2.tgz, r-oldrel: multiwave_1.2.tgz |
| Old sources: | multiwave archive |
Please use the canonical form https://CRAN.R-project.org/package=multiwave to link to this page.


Snap Scrip
Saint Joan of Arc School
Giftcards
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Checkout
SNAPSCRIP@gmail.com


As the main developer, tester, and architect of the Ultilab Project, I worked with Java, Android Studio, XCode, Swift, MongoDB, JavaScript, and JQuery to create a mobile testing tool that would allow a tester to run a manual test on a single phone and have the same test run on many other phones simultaneously. The purpose of this tool is to allow fast, internal, cross-OS, cross-manufacturer mobile tests to occur.
At HackMIT 2016, I worked with a team of 3 to build a fun reminder app to help you rest your eyes according to the 20-20-20 rule. The Windows version, written in Java, comes as a nonobtrusive notification that dims the screen for 20 seconds when the user accepts. The Mac version, written in Python and integrated with the Mac OS notification system, also gives the user the choice to snooze, in which case a fun fact and/or GIF is displayed.
NavTalent is a meta start-up; it's a start-up that recruits for other start-ups. Specifically, we are addressing the needs of high-quality start-ups that must hire talented engineers without taking valuable time from the core team; and we are addressing the needs of high-caliber engineers who want to work for good start-ups but cannot find them or filter them from the lower-quality ones.
As an Associate and one of the members of the founding team at MIT, my role is to connect with smart engineers here at MIT and ensure that they are able to choose from high-quality start-ups as they transition into industry.
In 2015, I did research in the Space Propulsion Lab, which designs ion-spray thrusters for miniature satellite (cubesat) propulsion. Besides performing chemistry experiments to determine which materials work best for our thrusters, I designed algorithms for our in-house laser to make it more efficient and reduce operating costs.
In January 2015, I led a team of 4 to victory in a competition which required building, augmenting, and programming an EMG-controlled robotic arm within two weeks. Besides managing the team as a whole, I was personally responsible for designing and machining the robotic arm augmentations and tools in a machine shop, operating the robot, and presenting our project to sponsoring companies.
This project involved designing a modular, bluetooth-controlled bicycle lock to enable a shared-bicycle system that would be controlled by smartphone. Using Computer Aided Design (CAD) software, such as Solidworks, I designed the bicycle lock retainer and made improvements to the existing bicycle lock design. I also machined the lock, and ran user tests on the entire mechanical system.


20th Century Physicists
Albert Einstein
Marie Curie
Niels Bohr
Henri Becquerel
Max PLanck
Thank you
...keep visiting for more.


Filter by Categories Applies additive filters to a generic collection of content items. Download (GitHub)


EUR/USD Technical Analysis: Flirting with daily tops, around 1.1075 region
by Haresh Menghani- EUR/USD regains some traction and recovers a part of the post-NFP slide.
- The upside is likely to remain capped ahead of the FOMC on Wednesday.
The EUR/USD pair built on its intraday positive move and is currently placed near the top end of its daily trading range, around the 1.1075 region. The post-NFP slide showed some resilience below the 200-hour SMA, with some renewed USD selling bias helping the pair to regain some positive traction on the first day of a new trading week.
A sustained move back above 38.2% Fibonacci level of the 1.0981-1.1116 recent positive move was seen as a key trigger for intraday bullish traders. Any subsequent move beyond the 1.1085 area (23.6% Fibo.) has the potential to lift the pair further beyond the 1.1100 handle, back towards testing last week's swing high – around the 1.1115 region.
Meanwhile, technical indicators on the daily chart maintained their bullish bias and have again started gaining positive momentum on hourly charts, supporting prospects for additional gains. However, further gains are likely to remain capped ahead of this week's key event risk – the highly anticipated FOMC monetary policy update on Wednesday.
On the downside, the 50% Fibo. level, around mid-1.1000s, now seems to have emerged as immediate support. Failure to defend the mentioned support might negate the constructive outlook and prompt some aggressive technical selling, which might accelerate the slide and drag the pair back towards challenging the key 1.10 psychological mark.
EUR/USD 1-hourly chart
EUR/USD
| Overview | |
|---|---|
| Today last price | 1.1074 |
| Today Daily Change | 0.0014 |
| Today Daily Change % | 0.13 |
| Today daily open | 1.106 |
| Trends | |
|---|---|
| Daily SMA20 | 1.1045 |
| Daily SMA50 | 1.1053 |
| Daily SMA100 | 1.1068 |
| Daily SMA200 | 1.1159 |
| Levels | |
|---|---|
| Previous Daily High | 1.1112 |
| Previous Daily Low | 1.104 |
| Previous Weekly High | 1.1116 |
| Previous Weekly Low | 1.1002 |
| Previous Monthly High | 1.1176 |
| Previous Monthly Low | 1.0981 |
| Daily Fibonacci 38.2% | 1.1067 |
| Daily Fibonacci 61.8% | 1.1084 |
| Daily Pivot Point S1 | 1.1029 |
| Daily Pivot Point S2 | 1.0998 |
| Daily Pivot Point S3 | 1.0957 |
| Daily Pivot Point R1 | 1.1101 |
| Daily Pivot Point R2 | 1.1142 |
| Daily Pivot Point R3 | 1.1173 |


Search by city to get the 5 day forecast for any US city. Or select from your prior search history.


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[Updated October 17, 2014]
How much would it cost to make every public two- and four-year college and university in the United States tuition-free for all students? Much less than you think.
According to our estimate, after stripping off the amount that the government already spends to subsidize higher education — including at predatory for-profit institutions — the total amount of new money necessary would be as little as $15 billion a year. Fifteen billion is a lot of money, to be sure, but within the scope of the federal budget it is a fraction of one percent of yearly spending — merely a rounding error.
Here’s how we arrived at that astonishing figure.
In the 2012-2013 academic year, students spent $61.8 billion on tuition for public colleges and universities (source, page 7). That’s our starting point. But, as we said above, the government is already subsidizing that figure via various programs which would no longer be needed if tuition were simply free. Additionally, predatory for-profit colleges receive billions in federal subsidies which simply channel taxpayer money straight into the pockets of Wall Street investors while saddling students with worthless degrees and a crushing debt load.
In 2012-2013 the government spent $32.3 billion in Pell Grants (source, page 3). How much of that went to shady for-profit schools? As much as 21% — more than $6.7 billion (source, table 18) — and a large chunk was swallowed up by Corinthian Colleges, the notorious institution now being sued by the CFPB, SEC, and numerous state attorneys-general for its predatory practices. In addition, for-profit schools (Corinthian foremost among them [source, page 4]) specifically target veterans for enrollment, and so they took in roughly $1.7 billion in GI Bill monies in 2012-2013 (source, page i).
There is no reason to squander even a penny of public money on these fraudulent operations. These combined savings would amount to $8.4 billion, which, subtracted from that $61.8 billion figure above, would give us a remaining cost of $53.4 billion for 2012-2013.
But that’s not all. Bob Samuels, in his exhaustive research on public education financing, identifies tens of billions in additional savings from current subsidies and tax exemptions:
- student loan interest rate exemption: $1.7 billion (source, page 207)
- exclusion of employer-provided educational assistance: $0.8 billion (ibid.)
- exclusion of interest on student-loan bonds: $0.6 billion (ibid.)
- exclusion of scholarship and fellowship income: $3 billion (ibid.)
- exclusion of tax on earnings of qualified tuition programs including savings account programs: $1.8 billion (ibid.)
- Lifetime Learning tax credit: $1.7 billion (ibid.)
- parental personal exemption for students age 19 or over: $5.3 billion (ibid.)
- state prepaid tuition plans: $1.8 billion (source)
- American Opportunity Tax Credit (which is set to expire in Dec 2017): $21.7 billion (source)
TOTAL SAVINGS FROM TAX CREDITS = $38.4 billion.
So, in the final accounting:
- $38.4 billion in tax expenditures
- $6.7 billion in Pell Grants to for-profit schools
- $1.7 billion in GI Bill money to for-profit schools
TOTAL SAVINGS = $46.8 billion.
This means that tuition-free education at all public two- and four-year colleges could be achieved for just $15 billion in new spending. The outcome would be a drastic reduction in the vast student debt burden (approaching $1.3 trillion) — the single most significant step we could take to minimize the scale of the crisis.
Some will say this is a utopian proposition. But virtually every other industrialized nation (and many a developing country) has managed to offer free public higher education for decades. Even in this era of fiscal austerity, governments in countries as disparate as Germany and Chile have recently announced they are eliminating tuition costs altogether. In the U.S. we cannot continue to mortgage the lifetime earnings of students without severely limiting their opportunities and damaging the fabric of our democratic life.
When you hear elected officials and political interest groups agonizing over the intractability of the student debt crisis, while protecting a status quo that funnels money to Wall Street banks and other higher ed profiteers, ask them where their priorities really are.
$15 billion is no more than a line item in the military budget — a 2011 GAO audit found $70 billion had been wasted by the Defence Department in just two years. $15 billion is also much less money than the federal government currently spends on an array of pointless programs. For example, the discredited War on Drugs is costing U.S. taxpayers $51 billion per year, much of which comes from state budgets that have drastically cut state appropriations for higher education. Redirecting this worthless funding stream into a free education system would restore some credibility to the nation’s fiscal priorities.The “Robin Hood Tax,” a proposal to impose a less than ½ of 1% tax on Wall Street transactions, could generate an estimated $300 billion a year. Those billions, which currently line the pockets of bankers and hedge fund managers, could be used to pay off all existing student debt in about four years.
Federal tax subsidies for corporations add up to $100 billion per year in uncollected taxes (source). Ensuring that companies pay their fair share of taxation could guarantee fair labor conditions for the 1.3 million contingent faculty members — over 75% of the university teaching force — who make an average salary of $25,000 per year. Doubling their salaries to match the current median pay for a full-time professor would still only cost $61.75 billion per year (source, page 6).
These are only a handful of alternative funding sources. If you look around, you’ll have little trouble locating that $15 billion — a small price to pay for the universal, tuition-free public higher education that more and more of the world’s citizenry are demanding of twenty-first century democracies.
It’s simply a matter of priorities.
Researchers interested in learning more are encouraged to read Bob Samuels’ 2013 book, Why Public Higher Education Should Be Free, as well as Mike Konczal’s article, “Could We Redirect Tax Subsidies to Pay for Free College?”


This challenge allows you to practice the concepts and techniques learned over the past Sprint and apply them in a concrete project. This Sprint explored Advanced Web Applications, focusing on testing, client-side authentication, hosting web apps, and PUT and DELETE requests.
Read these instructions carefully. Understand exactly what is expected before starting this Sprint Challenge.
This is an individual assessment. All work must be your own. Your challenge score is a measure of your ability to work independently using the material covered through this sprint. You need to demonstrate proficiency in the concepts and objectives introduced and practiced in preceding days.
You are not allowed to collaborate during the Sprint Challenge. You must follow the twenty-minute rule before you seek support from your PM. You have three hours to complete this challenge. Plan your time accordingly.
Commit your code regularly and meaningfully. This helps both you (in case you ever need to return to old code for any number of reasons and your project manager).
In this project you will create a login page and request a token from the server that you’ll use to send all other requests to the server. You will then be able to fetch the color data array, update data, and delete data, and watch the fun happen!
Note You can use the sites like the following to get color hex codes:
Demonstrate your understanding of this Sprint’s concepts by answering the following free-form questions. Edit this document to include your answers after each question. Make sure to leave a blank line above and below your answer so it is clear and easy to read by your project manager.
Many services out in the wild require the client (our React app, for example) to provide proof that it’s authenticated with them. The server running these services can issue a JWT (JSON Web Token) as the authentication token, in exchange for correct login credentials.
[X] What steps can you take in your web apps to keep your data secure? As we build our web apps, we will most likely have some “protected” routes - routes that we only want to render if the user has logged in and been authenticated by our server. The way this normally works is we make a login request, sending the server the user’s username and password. The server will check those credentials against what is in the database, and if it can authenticate the user, it will return a token. Once we have this token, we can add two layers of protection to our app. One with protected routes, the other by sending an authentication header with our API calls (as we learned in the above objective).
[X] Describe how web servers work. The “world wide web” (which we’ll refer to as “the web”) is just a part of the internet - which is itself a network of interconnected computers. The web is just one way to share data over the internet. It consists of a body of information stored on web servers, ready to be shared across the world. The term “web server” can mean two things: – a computer that stores the code for a website – a program that runs on such a computer The physical computer device that we call a web server is connected to the internet, and stores the code for different websites to be shared across the world at all times. When we load the code for our websites, or web apps, on a server like this, we would say that the server is “hosting” our website/app.
[X] Which HTTP methods can be mapped to the CRUD acronym that we use when interfacing with APIs/Servers. Create, Read, Update, Delete
Follow these steps to set up and work on your project:
<firstName-lastName>
.
<firstName-lastName>
.
yarn install or npm install
at the root to retrieve all the dependencies for the node server. You will not need to create any react apps here nor will you need to install any other dependencies. You should have all you need in this repo.
server.js
. This file contains an API that you are going to be interfacing with. Below is documentation on how to interact with the API.
yarn start or npm start
to get your API up and running on http://localhost:5000
. This is the URL you’re going to need to use within your React app in order to make AJAX requests for data.
client
directory and notice it’s just a plain ol’ React App that we’ve built using create-react-app
.
client
and run yarn install or npm install
to retrieve the client side dependencies.
yarn start or npm start
to fire up your React application.
Follow these steps for completing your project:
The MVP of this project will be broken up between 2 stages. Follow each step.
Build a login form to authenticate your users.
axiosWithAuth
module to create an instance of axios with the authentication header
PrivateRoute
component and use it to protect a route that renders the BubblesPage
component
BubblePages
renders, make a GET request to fetch the color data for your bubbles.
ColorList.js
, complete the saveEdit
and deleteColor
functions to make AJAX requests to the API to edit/delete data
Bubbles.js
to see how this is built.
/api/login
: returns a token to be added to the header of all other requests. Pass in the following credentials as the body
of the request: { username: ‘Lambda School’, password: ‘i<3Lambd4’ }
/api/colors
: returns the list of colors and their hex codes.
/api/colors
: creates a new color object. Pass the color as the body
of the request (the second argument passed to axios.post
).
/api/colors/:id
: updates the color using the id
passed as part of the URL. Send the color object with the updated information as the body
of the request (the second argument passed to axios.put
).
/api/colors/123
: removes the color using the id
passed as part of the URL (123 in example).
HTTP/Axios Stretch Problems
ColorList.js
to add new colors to the colors data
Data Visualization
Bubbles.js
. Have fun with this! Try different components from the library, or see if you can add props to change the UI a bit.


|
Creed
|
|
|
Weathered
|
1.
Bullets
2. Freedom Fighter 3. Who's Got My Back? 4. Signs 5. One Last Breath 6. My Sacrifice 7. Stand Here With Me 8. Weathered 9. Hide 10. Don't Stop Dancing 11. Lullaby |
|
|
|
|
Human
Clay
|
1.
Are You Ready?
2. What If 3. Beautiful 4. Say I 5. Wrong Way 6. Faceless Man 7. Never Die 8. With Arms Wide Open 9. Higher 10. Wash Away Those Years 11. Inside Us All 12. Young Grow Old |
|
Voltar |


Node and Edge Selection
Graph nodes or edges can be selected with these functions. This is useful because some of the Graph Modification functions (ending with "_ws") and all of the Graph Traversal functions can make use of the stored selections.
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select_nodes()
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Select nodes in a graph |
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select_nodes_by_id()
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Select nodes in a graph by their ID values |
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select_nodes_by_degree()
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Select nodes in the graph based on their degree values |
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select_nodes_in_neighborhood()
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Select nodes based on a walk distance from a specified node |
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select_last_nodes_created()
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Select the last set of nodes created in a graph |
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select_edges()
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Select edges in a graph |
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select_edges_by_node_id()
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Select edges in a graph using node ID values |
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select_edges_by_edge_id()
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Select edges in a graph using edge ID values |
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select_last_edges_created()
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Select the last set of edges created in a graph |
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get_selection()
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Get the current selection available in a graph object |
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deselect_nodes()
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Deselect any selected nodes in a graph |
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deselect_edges()
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Deselect any selected edges in a graph |
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invert_selection()
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Invert selection of nodes or edges in a graph |
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clear_selection()
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Clear an active selection of nodes or edges |
Graph Modification
These functions make changes to the graph. We can change many aspects of the graph: the graph representation itself (e.g., adding or removing nodes and edges), or, the attributes of the nodes and edges (in terms of associated data and aesthetics).
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add_node()
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Add a node to an existing graph object |
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add_n_nodes()
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Add one or several unconnected nodes to the graph |
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add_n_nodes_ws()
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Add a multiple of new nodes with edges to or from one or more selected nodes |
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add_node_df()
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Add nodes from a node data frame to an existing graph object |
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add_n_node_clones()
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Add one or several clones of an existing node to the graph |
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add_node_clones_ws()
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Add clones of a selection of nodes |
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add_nodes_from_table()
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Add nodes and attributes to graph from a table |
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add_nodes_from_df_cols()
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Add nodes from distinct values in data frame columns |
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add_edge()
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Add an edge between nodes in a graph object |
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add_edge_df()
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Add edges from an edge data frame to an existing graph object |
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add_edges_w_string()
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Add one or more edges using a text string |
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add_edge_clone()
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Add a clone of an existing edge to the graph |
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add_forward_edges_ws()
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Add new edges with identical definitions as with a selection of edges |
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add_reverse_edges_ws()
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Add new edges in the opposite directions of a selection of edges |
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fully_connect_nodes_ws()
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Fully connect all nodes in a selection of nodes |
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add_edges_from_table()
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Add edges and attributes to graph from a table |
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add_path()
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Add a path of nodes to the graph |
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add_cycle()
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Add a cycle of nodes to the graph |
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add_balanced_tree()
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Add a balanced tree to the graph |
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add_star()
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Add a star of nodes to the graph |
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add_prism()
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Add a prism of nodes to the graph |
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add_full_graph()
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Add a fully connected graph |
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add_grid_2d()
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Add a 2D grid of nodes to the graph |
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add_grid_3d()
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Add a 3D grid of nodes to the graph |
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add_gnm_graph()
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Add a G(n, m) Erdos-Renyi graph |
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add_gnp_graph()
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Add a G(n, p) Erdos-Renyi graph |
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add_pa_graph()
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Add a preferential attachment graph |
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add_growing_graph()
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Create a random growing graph with m edges added per step |
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add_smallworld_graph()
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Add a Watts-Strogatz small-world graph |
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add_islands_graph()
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Create a random islands graph with edges between the islands |
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delete_node()
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Delete a node from an existing graph object |
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delete_nodes_ws()
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Delete all nodes in a node selection |
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delete_edge()
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Delete an edge from an existing graph object |
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delete_edges_ws()
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Delete all selected edges in an edge selection |
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delete_loop_edges_ws()
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Delete all loop edges associated with a selection of nodes |
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fully_disconnect_nodes_ws()
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Fully disconnect all nodes in a selection of nodes |
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rev_edge_dir()
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Reverse the direction of all edges in a graph |
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rev_edge_dir_ws()
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Reverse the direction of selected edges in a graph using an edge selection |
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set_node_attrs()
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Set node attribute values |
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set_node_attrs_ws()
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Set node attributes with a node selection |
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join_node_attrs()
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Join new node attribute values using a data frame |
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rescale_node_attrs()
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Rescale numeric node attribute values |
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copy_node_attrs()
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Copy a node attribute column and set the name |
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rename_node_attrs()
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Rename a node attribute |
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drop_node_attrs()
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Drop a node attribute column |
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mutate_node_attrs()
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Mutate a set of node attribute values |
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mutate_node_attrs_ws()
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Mutate node attribute values for a selection of nodes |
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colorize_node_attrs()
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Apply colors based on node attribute values |
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recode_node_attrs()
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Recode a set of node attribute values |
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set_df_as_node_attr()
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Set a data frame as a node attribute |
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set_node_position()
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Apply a layout position to a single node |
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layout_nodes_w_string()
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Layout nodes using a text-based schematic |
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nudge_node_positions_ws()
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Move layout positions of a selection of nodes |
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set_node_attr_w_fcn()
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Set node attribute values with a graph function |
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set_edge_attrs()
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Set edge attribute values |
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set_edge_attrs_ws()
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Set edge attributes with an edge selection |
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join_edge_attrs()
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Join new edge attribute values using a data frame |
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rescale_edge_attrs()
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Rescale numeric edge attribute values |
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copy_edge_attrs()
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Copy an edge attribute column and set the name |
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rename_edge_attrs()
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Rename an edge attribute |
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drop_edge_attrs()
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Drop an edge attribute column |
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mutate_edge_attrs()
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Mutate a set of edge attribute values |
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mutate_edge_attrs_ws()
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Mutate edge attribute values for a selection of edges |
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colorize_edge_attrs()
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Apply colors based on edge attribute values |
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recode_edge_attrs()
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Recode a set of edge attribute values |
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set_df_as_edge_attr()
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Set a data frame as an edge attribute |
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node_data()
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Insert node data attributes during node creation |
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node_aes()
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Insert node aesthetic attributes during node creation |
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edge_data()
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Insert edge data attributes during edge creation |
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edge_aes()
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Insert edge aesthetic attributes during edge creation |
Graph Inspection
Sometimes, you’ll need to gather information about the working graph. This collection of functions allows for extraction of graph components (e.g., ndfs and edfs), attribute information, counts, node and edge properties, and more.
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get_node_df()
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Get a node data frame from a graph |
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get_node_df_ws()
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Get the graph's ndf filtered by a selection of nodes |
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get_node_info()
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Get detailed information on nodes |
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get_last_nodes_created()
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Get the last set of nodes created in a graph |
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get_node_attrs()
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Get node attribute values |
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get_node_attrs_ws()
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Get node attribute values from a selection of nodes |
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get_degree_distribution()
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Get total degree distribution data for a graph |
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get_degree_histogram()
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Get histogram data for a graph's degree frequency |
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get_edge_df()
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Get an edge data frame from a graph |
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get_edge_df_ws()
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Get the graph's edf filtered by a selection of edges |
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get_edge_info()
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Get detailed information on edges |
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get_last_edges_created()
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Get the last set of edges created in a graph |
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get_edge_attrs()
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Get edge attribute values |
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get_edge_attrs_ws()
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Get edge attribute values from a selection of edges |
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get_node_ids()
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Get a vector of node ID values |
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get_nbrs()
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Get all neighbors of one or more nodes |
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get_common_nbrs()
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Get all common neighbors between two or more nodes |
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get_non_nbrs()
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Get non-neighbors of a node in a graph |
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get_similar_nbrs()
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Get neighboring nodes based on node attribute similarity |
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get_predecessors()
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Get node IDs for predecessor nodes to the specified node |
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get_successors()
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Get node IDs for successor nodes to the specified node |
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get_all_connected_nodes()
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Get all nodes connected to a specified node |
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get_articulation_points()
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Get articulation points |
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get_periphery()
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Get nodes that form the graph periphery |
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get_edge_ids()
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Get a vector of edge ID values |
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get_edges()
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Get node IDs associated with edges |
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get_paths()
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Get paths from a specified node in a directed graph |
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do_dfs()
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Use the depth-first search (dfs) algorithm |
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do_bfs()
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Use the breadth-first search (bfs) algorithm |
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get_attr_dfs()
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Get data frames bound to node attributes |
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count_nodes()
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Get a count of all nodes |
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count_edges()
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Get a count of all edges |
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count_loop_edges()
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Get count of all loop edges |
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count_mutual_node_pairs()
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Get the number of mutually-connected node pairs |
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count_asymmetric_node_pairs()
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Get the number of asymmetrically-connected node pairs |
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count_automorphisms()
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Get the number of automorphisms |
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count_unconnected_nodes()
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Get count of all unconnected nodes |
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count_unconnected_node_pairs()
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Get the number of unconnected node pairs |
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count_w_connected_cmpts()
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Get the number of weakly-connected components |
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count_s_connected_cmpts()
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Get the number of strongly-connected components |
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get_multiedge_count()
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Get the count of multiple edges |
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get_edge_count_w_multiedge()
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Get count of edge definitions where multiple edges occur |
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get_agg_degree_in()
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Get an aggregate value from the indegree of nodes |
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get_agg_degree_out()
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Get an aggregate value from the outdegree of nodes |
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get_agg_degree_total()
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Get an aggregate value from the total degree of nodes |
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get_mean_distance()
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Get the mean distance |
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get_min_eccentricity()
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Get the minimum graph eccentricity |
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get_max_eccentricity()
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Get the maximum graph eccentricity |
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get_reciprocity()
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Get the graph reciprocity |
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get_girth()
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Get the graph girth |
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get_adhesion()
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Get graph adhesion |
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get_min_cut_between()
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Get the minimum cut between source and sink nodes |
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get_degree_in()
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Get indegree values for all nodes |
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get_degree_out()
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Get outdegree values for all nodes |
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get_degree_total()
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Get total degree values for all nodes |
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get_betweenness()
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Get betweenness centrality scores |
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get_closeness()
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Get closeness centrality values |
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get_pagerank()
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Get the PageRank values for all nodes |
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get_alpha_centrality()
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Get the alpha centrality for all nodes |
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get_eigen_centrality()
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Get the eigen centrality for all nodes |
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get_authority_centrality()
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Get the authority scores for all nodes |
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get_leverage_centrality()
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Get leverage centrality |
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get_radiality()
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Get radiality centrality scores |
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get_eccentricity()
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Get node eccentricities |
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get_coreness()
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Get coreness values for graph nodes |
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get_constraint()
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Get constraint scores for one or more graph nodes |
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get_closeness_vitality()
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Get closeness vitality |
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get_bridging()
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Get bridging scores |
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get_dice_similarity()
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Get Dice similarity coefficient scores |
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get_jaccard_similarity()
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Get Jaccard similarity coefficient scores |
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get_w_connected_cmpts()
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Get all nodes associated with connected components |
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get_s_connected_cmpts()
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Get nodes within strongly connected components |
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get_cmty_edge_btwns()
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Get community membership by edge betweenness |
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get_cmty_walktrap()
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Get community membership using the Walktrap method |
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get_cmty_louvain()
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Get community membership by Louvain optimization |
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get_cmty_l_eigenvec()
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Get community membership by leading eigenvector |
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get_cmty_fast_greedy()
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Get community membership by modularity optimization |
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is_node_present()
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Determine whether a specified node is present |
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is_edge_present()
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Determine whether a specified edge is present |
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is_edge_loop()
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Is the edge a loop edge? |
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is_edge_multiple()
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Is the edge a multiple edge? |
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is_edge_mutual()
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Is the edge mutual with another edge? |
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is_graph_empty()
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Is the graph empty? |
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is_graph_directed()
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Is the graph a directed graph? |
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is_graph_undirected()
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Is the graph an undirected graph? |
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is_graph_simple()
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Is the graph a simple graph? |
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is_graph_weighted()
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Is the graph a weighted graph? |
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is_graph_connected()
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Is the graph a connected graph? |
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is_graph_dag()
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Is the graph a directed acyclic graph? |
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is_property_graph()
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Is the graph a property graph? |
Graph Traversal
Traversing the graph is useful if you have a defined graph model and you’d like to explore the connections and relationships between nodes and edges. Traversals effectively modify a selection of nodes or edges. With the modified selection, we can extract related attributes and work with them.
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trav_out()
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Traverse from one or more selected nodes onto adjacent, outward nodes |
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trav_in()
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Traverse from one or more selected nodes onto adjacent, inward nodes |
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trav_both()
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Traverse from one or more selected nodes onto neighboring nodes |
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trav_out_edge()
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Traverse from one or more selected nodes onto adjacent, outward edges |
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trav_in_edge()
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Traverse from one or more selected nodes onto adjacent, inward edges |
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trav_both_edge()
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Traverse from one or more selected nodes onto adjacent edges |
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trav_out_node()
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Traverse from one or more selected edges onto adjacent, outward nodes |
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trav_in_node()
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Traverse from one or more selected edges onto adjacent, inward nodes |
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trav_out_until()
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Traverse outward node-by-node until stopping conditions are met |
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trav_in_until()
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Traverse inward node-by-node until stopping conditions are met |
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trav_reverse_edge()
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Traverse to any reverse edges |


New Profile
Personal Data
First Name:
Last Name:
Select City
Brest
Vitebsk
Gomel
Grodno
Minsk
Gender
Male
Female
Authorization Data
Email:
Password:
How did you know about us?
From friends
From the Google, Yandex...
Social networks
Other


There are many mobile applications on the market to help you with your Bmw/Mini, but those who use ProTool never look back...
ProTool was designed with 2 things in mind: make it powerful enough for professionals, and simple enough for enthusiasts. With advanced diagnostics, full-scale coding abilities, and a simple interface it easily becomes the most valuable tool in your toolbox.
You have the Amazon and Ebay stuff, and then you have BimmerGeeks...
Whether you are using our personally developed software or the others on the web, your going to need hardware. When it comes from us, it's stronger, faster, more reliable or simply put...better
Free software is always nice. While they may not be the best, hopefully they get you on the right track.
We've taken the most popular software out there compatible with our hardware and made some modifications for you. Easily installed, hand translated, and best of all...free.
We understand learning these tools and cars can be a lot to take in, but we've got you covered...
All of our staff own Bmw's, work on them, and understand them. Not only do we extend our support out to you, we come with a social community of over 5000 users that have your back as well.


public class ExtendedInstruction extends Instruction
description, exampleFormat, INSTRUCTION_LENGTH, INSTRUCTION_LENGTH_BITS, mnemonic, operandMask, tokenList
| Constructor | Description |
|---|---|
ExtendedInstruction(java.lang.String example,
java.lang.String translation) |
Constructor for ExtendedInstruction, where no instruction description or
compact translation is provided.
|
ExtendedInstruction(java.lang.String example,
java.lang.String translation,
java.lang.String description) |
Constructor for ExtendedInstruction.
|
ExtendedInstruction(java.lang.String example,
java.lang.String translation,
java.lang.String compactTranslation,
java.lang.String description) |
Constructor for ExtendedInstruction.
|
| Modifier and Type | Method | Description |
|---|---|---|
java.util.ArrayList |
getBasicIntructionTemplateList() |
Get ArrayList of Strings that represent list of templates for
basic instructions generated by this extended instruction.
|
java.util.ArrayList |
getCompactBasicIntructionTemplateList() |
Get ArrayList of Strings that represent list of templates for
basic instructions generated by the "compact" or 16-bit version
of this extended instruction.
|
int |
getCompactInstructionLength() |
Get length in bytes that this extended instruction requires in its
binary form if it includes an alternative expansion for compact
memory (16 bit addressing) configuration.
|
int |
getInstructionLength() |
Get length in bytes that this extended instruction requires in its
binary form.
|
boolean |
hasCompactTranslation() |
Determine whether or not this pseudo-instruction has a second
translation optimized for 16 bit address space: a compact version.
|
static java.lang.String |
makeTemplateSubstitutions(RISCVprogram program,
java.lang.String template,
TokenList theTokenList) |
Given a basic instruction template and the list of tokens from an extended
instruction statement, substitute operands from the token list appropriately into the
template to generate the basic statement.
|
java.lang.Number[] |
returnOperands(int instructionCode) |
Given an instruction code, extracts from it the operands and retrieves the array.
|
computeOperands, createExampleTokenList, extractOperator, getDescription, getExampleFormat, getName, getTokenList
public ExtendedInstruction(java.lang.String example, java.lang.String translation, java.lang.String compactTranslation, java.lang.String description)
example
- A String containing example use of the MIPS extended instruction.translation
- Specifications for translating this instruction into a sequence
of one or more MIPS basic instructions.compactTranslation
- Alternative translation that can be used if running under
a compact (16 bit) memory configuration.description
- a helpful description to be included on help requests
The presence of an alternative "compact translation" can optimize code generation
by assuming that data label addresses are 16 bits instead of 32public ExtendedInstruction(java.lang.String example, java.lang.String translation, java.lang.String description)
example
- A String containing example use of the MIPS extended instruction.translation
- Specifications for translating this instruction into a sequence
of one or more MIPS basic instructions.description
- a helpful description to be included on help requestspublic ExtendedInstruction(java.lang.String example, java.lang.String translation)
example
- A String containing example use of the MIPS extended instruction.translation
- Specifications for translating this instruction into a sequence
of one or more MIPS basic instructions.public int getInstructionLength()
getInstructionLength
in class Instruction
public java.util.ArrayList getBasicIntructionTemplateList()
public int getCompactInstructionLength()
public boolean hasCompactTranslation()
public java.util.ArrayList getCompactBasicIntructionTemplateList()
public static java.lang.String makeTemplateSubstitutions(RISCVprogram program, java.lang.String template, TokenList theTokenList)
template
- a String containing template for basic statement.theTokenList
- a TokenList containing tokens from extended instruction.public java.lang.Number[] returnOperands(int instructionCode)
Instruction
returnOperands
in class Instruction
instructionCode
- an instruction code.


Network Diagram
Mia Ba
Shaoyun Xu
Friend 1
Friend 2
Friend 3
Friend 4
Friend 5
Friend 6
Friend 7
Yunshu Gao
Friend 1
Friend 2
Friend 3


HSL=> Hue Saturation Lightness
In HTML, a color can be specified using hue, saturation, and lightness (HSL) in the form:
hsl(hue, saturation, lightness)
Hue is a degree on the color wheel from 0 to 360. 0 is red, 120 is green, and 240 is blue.
Saturation is a percentage value, 0% means a shade of gray, and 100% is the full color.
Lightness is also a percentage, 0% is black, 50% is neither light or dark, 100% is white
Red with full saturation and half light
Green With full saturation and Half light
Blue with full saturation and half light
Red with null saturation and half light
Green with null saturation and half light
Blue with null saturation and half light
Red with half saturation and half light
Green with half saturation and half light
Blue with half saturation and half light
Red with full saturation and full light
Green with full saturation and full light
Blue with full saturation and full light


awesome..
awesomeness..
Hello there, awesome person! Here's a list of cool stuff...
github
This is a link to GitHub!
discord
This is a link to discord!
twitch
This is a link to twitch!


Hello World
Hello and Welcome to my site. I will be updating with my current projects in the next couple of days. In the mean time, I have a quick python script for you.
It is a magic eight-ball program. If you don't remember the magic eight-ball, it was a fortune teller toy where you would ask it a question and it will give you a prediction. Check it out.
import random
def compute():
messages = ['It is certain',
'It is decidedly so',
'Yes definitely',
'Reply hazy try again',
'Ask again later',
'Concentrate and ask again',
'My reply is no',
'Outlook not so good',
'Very doubtful']
return (messages[random.randint(0, len(messages)-1)])
if __name__ == "__main__":
print(compute())
#=> prints a random prediction to terminal.


Prosperity
Myself and Pastor Benny Hinn taken Gods de....
Behind the scene
Pastor Chris leaves for...
Healing
Experience Gods healing...
Events/p>
A Trip Around the world


tournament?.teamSize),
'team-not-full-color': (teamsMemberMap[team.name]?.length <= tournament?.teamSize)}">
({{teamsMemberMap[team.name]?.length}} / {{tournament?.teamSize}})
tournament?.teamSize"
class="fa fa-exclamation-triangle" pTooltip="Exceeded TeamSize">


After reading extensively about the substance I threw caution into the wind and gave it a go myself. I don't have a scale and convincing myself what the dosage was took alot of comparison against known substances like table salt. It was reported that a grain of table salt is approx. 1/10th of a milligram. So by simply approximating 10 grains of salt to 1 milligram I was able to crudely eyeball 12mg of 5-meo-mipt. This was very precarious because I was all by myself. I don't recommend this method of measuring but what am I gonna do when I don't have a scale.
I tried to mix a bit in water but it didn't seem to dissolve so decided to empty a cap of coral calcium and use the empty cap as a delivery.
9:15 PM is about the time I dropped the cap and waited patiently to feel something. This was a little worrisome because many thoughts went through my head about if I took too little or worse too much. But what ever the outcome it's too late to change it now.
10PM I was on the phone with my wife when I began to feel the effects. I had somewhat of a body load but it was minimal and I began to feel a little tense. I had to hang up with her because I didn't want to deal with her issues and the substance at the same time. Worrying if I had taken too much, I drank water and ate some food to try to dilute it. This turned out to either work or not be necessary because the overall experience was O.K. (I'll get there later)
10:45 PM If I had to describe the feeling at this point it would be something like a slight body buzz and noticable sound differnces. It was like I could hear myself at a slightly lower tone than normal. I would rate it at a +++ because I couldn't shut it down if I wanted to. And thank God I didn't want to. To take advantage of the auditory effects I threw on some Sasha and Digweed to really pull the sounds out and turned on my visualizations on windows media player to just see if any visual effects where lurking around the bend. Unfortunately, I didn't see anything unusual but it was fun to watch.
11:45 PM I think I peaked about this time because I had a great body buzz and the sounds were coming in real clear. I really enjoyed listening to the music during this experience because it provided a level of comfort in the unknown. I ventured away from my bed to the computer to see what porn would do because of the level of eroticism I was experiencing. (too bad I was alone on this one). I found that getting off to porn seemed pretty easy and enjoyable, unlike other substances (MDMA, AMPHETAMINES,) I can see how a couple could have alot of fun with this.
12:45 AM At this point I'm comfortable with the substance and I don't anticipate any surprises. It seems the peak is behind and I am feeling the trailing effects but it isn't a cracked out feeling at all.
1:45 AM I'm just about done with the experience, the effects have just about worn off. I don't know if there will be a part two to this, because I read on another experience that a mental trip began when the body buzz wore off but I'm ready if it happens.
2:45 AM I think everything is done now. I'm feeling tired which gives me hope that I will sleep peacfully for the the rest of the night. But before I go to sleep I would like to give an overall report of this substance.
Great care should be taken with this substance if a scale isn't available. Because of the low doses needed, (4-12mg orally reported, with 25mg causing 'freakout' episodes) it's very very difficult to 'eye' a correct amount without going into overdose territory. Since this substance doesn't seem to dissolve in water easily, the liquid measure method may not be an option either. It is suggested that precise measurements are taken before using this. With that said, I think this substance has a lot of positive qualities. For one, there seemed to be no nausea even though I took it with food in my stomach. Secondly, the duration seemed reasonable, 3-5 hours. Third, sexually speaking, the experienced seemed to heighten pleasure and created a base for more sexual exploration. On the down side, the possibility of an overdose is the real scare here.
I would rate this to be a 7 on a scale of 1 to 10. I probably would do it again if the atmosphere was right. The experience is one that I'm glad I had. I hope people curious about this substance will use it responsibly and come out of it with a positive experience like I did.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


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Wishing you all a very very Belated Happy Diwali..may the coming year brings you lots of happiness, good health and love. I had a great Diwali, decorated my house, made rangoli and burnt very few crackers and almost became deaf for few minutes.
I wore the NYX powder blush this Diwali and was surprised that I haven't swatched it here before, Definitely more on the light pink side than peach, so the shade name is a misnomer, don't fall for it. As the NYX powder blush in Silky Rose(Reviewed here) this one is also a matte shade which is very soft and easy to blend. Average stay power of around 4-5 hours on me.This one is strictly for fairer skin, dusky beauties will find it ash like and will totally wash them out.
NYX powder blushes are a good place to start and experiment with colors, only if we could get them for US prices in India. Why everything has to quadruple before selling in India... thats certainly not fair.
Which is your favorite peach blush....?? mine has to be from Colorbar(Reviewed here)


Breakout EDU - 3/31/2018
Breakout EDU has taken the world by storm, but how do we ensure the experience is successful? Read more about my experience and tips for keeping kids engaged and having a fantastic experience!
Read More...Breakout EDU has taken the world by storm, but how do we ensure the experience is successful? Read more about my experience and tips for keeping kids engaged and having a fantastic experience!
Read More...This past fall I took on an adventure I wasn’t sure either I or my kids would be ready for. I started a club for electronics and programming using an Arduino in middle school. I had many questions about whether middle school students could figure out an arduino, and the answer is YES!
Read More...Google sheets is a powerful tool and is very easy to use, once you are familiar with its syntax. This post will focus on how you can use 3 different statements, which should give a good starting point from which to grow. We will focus on =COUNTIF, COUNTIFS, and =QUERY. With these 3 statements you can begin to create powerful tools to quickly analyze and create meaningful data sets.


kosher has a tremendous amount of documentation and help content at its Github Pages site: https://cbush06.github.io/kosher/
Anyone is welcome to report bugs and request new features at kosher's Github Repository. Simply navigate to https://github.com/cbush06/kosher and click the Issues tab.


ObjectStreamContext
The interface {@link net.jini.io.ObjectStreamContext} may be
implemented by an object serialization stream class (a subclass of
{@link java.io.ObjectOutputStream} or {@link
java.io.ObjectInputStream}) to provide each object being serialized or
deserialized with access to context information relevant to the
overall serialization or deserialization operation. The class of an
object that is being serialized or deserialized can test (in its
private writeObject(ObjectOutputStream)
or
readObject(ObjectInputStream)
method) if the object
stream being used is an instance of ObjectStreamContext
.
If the stream class does implement that interface, the class can then
retrieve the context information (as a {@link java.util.Collection
Collection} of context objects) by invoking the stream's
getObjectStreamContext
method. The context information
available from a given element of the collection is determined by that
element's type. Examples of types that a context object might
implement include {@link net.jini.io.context.ClientHost} and {@link
net.jini.io.context.ClientSubject}.
MarshalOutputStream
and MarshalInputStream
The classes {@link net.jini.io.MarshalOutputStream} and {@link
net.jini.io.MarshalInputStream} extend the object serialization stream
classes {@link java.io.ObjectOutputStream} and {@link
java.io.ObjectInputStream} to implement the dynamic class loading
semantics of RMI argument and result marshalling and unmarshalling.
MarshalOutputStream
and MarshalInputStream
use {@link java.rmi.server.RMIClassLoader} to get class annotations
for marshalling and to resolve codebase annotations to {@link
java.lang.Class} objects for unmarshalling.
MarshalInputStream
supports optional verification that
the codebase annotation URLs used to resolve classes provide content
integrity (see {@link
net.jini.security.Security#verifyCodebaseIntegrity
Security.verifyCodebaseIntegrity}). MarshalOutputStream
and MarshalInputStream
may be extended (in concert) to
communicate class annotations in a way other than in the streams' own
data. Both MarshalOutputStream
and
MarshalInputStream
implement
ObjectStreamContext
.
MarshalledInstance
A {@link net.jini.io.MarshalledInstance} contains an object in
serialized form. A MarshalledInstance
can be
unmarshalled on demand, allowing an object to be sent in such a way
that the receiver can control when and in what context the object is
unmarshalled. MarshalledInstance
provides functionality
similar to {@link java.rmi.MarshalledObject}, but it additionally
supports use of object stream contexts and optional verification that
the codebase annotation URLs used to resolve classes provide content
integrity. A convenience constructor and method are provided for
converting between MarshalledObject
and
MarshalledInstance
instances.
@since 2.0
@version 2.0


Wave module¶
The wave
module contains a set of functions to
calculate quantities of interest for wave energy converters (WEC).
The wave module contains the following submodules:
io
: Loads data from standard formatsresource
: Computes resource metrics such as spectra and significant wave heightperformance
: Computes performance metrics such as capture length matrix and mean annual energy productiongraphics
: Generates graphics
Data formats and IO¶
As with other modules in the MHKiT Matlab package, the MHKit Python modules are used within the wave module. The wave module uses wave elevation and spectra data.
Wave elevation data is time-series data stored as an array which is converted to a pandas DataFrame with a time index. The column names describe the type of data in each column.
Spectra data can be stored in a structure with frequency, type, and spectrum field names or converted to a pandas DataFrame where the index is a descriptor and columns are frequency. The descriptor(type)/frequency can be time (in seconds or a DateTime index), or some other information that defines each row of the spectra data. For example, if spectra data is computed using the JONSWAP method, the index or type is a string that includes the significant wave height and peak period used to compute the spectra in each row.
File IO¶
The io
submodule contains the following function to load National Data Buoy Center (NDBC)
data file into a pandas DataFrame, including real time and historical data.
Wave resource¶
The resource
submodule contains methods to compute wave energy spectra and various metrics from the spectra.


Z3 contains an extension called muZ with fixed-point constraints. This tutorial includes some examples that demonstrate features of this engine. The following papers μZ - An Efficient Engine for Fixed-Points with Constraints. (CAV 2011) and Generalized Property Directed Reachability (SAT 2012) describe some of the main features of the engine. Be sure to follow along with the examples by clicking the "edit" link in the corner. See what the tool says, try your own formulas, and experiment! Please send feedback, comments and/or corrections to<EMAIL_ADDRESS>This tutorial covers some of the fixedpoint utilities available with Z3. The main features are a basic Datalog engine, an engine with relational algebra and an engine based on a generalization of the Property Directed Reachability algorithm, as well as the Duality engine.
The default fixed-point engine is a bottom-up Datalog engine. It works with finite relations and uses finite table representations as hash tables as the default way to represent finite relations.
(declare-rel a ())declares a 0-ary relation a.
(rule (=> b a))Create the rule that a follows from b. In general you can create a rule with multiple premises and a name using the format
(rule (=> (and b c) a) name)The name is optional. It is used for tracking the rule in derivation proofs. Continuing with the example, a is false unless b is established.
(query r)Asks if relation a can be derived. The rules so far say that a follows if b is established and that b follows if c is established. But nothing establishes c and b is also not established, so a cannot be derived.
(rule c)Now it is the case that a can be derived.
Relations can take arguments. We illustrate relations with arguments using edges and paths in a graph.
The example uses the declaration(declare-var a s)to instrument the fixed-point engine that a should be treated as a variable appearing in rules.
McCarthy's 91 function illustrates a procedure that calls itself recursively twice. The Horn clauses below encode the recursive function:
mc(x) = if x > 100 then x - 10 else mc(mc(x+11))The general scheme for encoding recursive procedures is by creating a predicate for each procedure and adding an additional output variable to the predicate.  The PDR engine produces the same proof of unsatisfiability. The proof is an inductive invariant for each recursive predicate.
A self-contained example that exercises the .NET API over C# is provided as a separate download.
Three different text-based input formats are accepted.
Files with suffix .datalog are parsed using the BDDBDDB format. The format can be used for comparing benchmarks with the BDDBDDB tool.
We use an artificial program to illustrate the basic Datalog format that complies to the format used by BDDBDDB.
Z 64 P0(x: Z) input Gt0(x : Z, y : Z) input R(x : Z) printtuples S(x : Z) printtuples Gt(x : Z, y : Z) printtuples Gt(x,y) :- Gt0(x,y). Gt(x,y) :- Gt(x,z), Gt(z,y). R(x) :- Gt(x,_). S(x) :- Gt(x,x0), Gt0(x,y), Gt0(y,z), P0(z). Gt0("a","b"). Gt0("b","c"). Gt0("c","d"). Gt0("a1","b"). Gt0("b","a1"). Gt0("d","d1"). Gt0("d1","d"). P0("a1").
(set-logic HORN) (declare-fun mc (Int Int) Bool) (assert (forall ((m Int)) (=> (> m 100) (mc m (- m 10))))) (assert (forall ((m Int) (n Int) (p Int)) (=> (and (<= m 100) (mc (+ m 11) p) (mc p n)) (mc m n)))) (assert (forall ((m Int) (n Int)) (=> (and (mc m n) (<= m 101)) (= n 91)))) (check-sat) (get-model)Note the following:
You can interact with muZ over the programmatic API from Python, C, OCaml, Java, and .NET. The APIs support adding rules and posing queries.


hello,
i've been using openemon for a while now, using an emonpi, and 2 emontx v2 nodes that forward to my own cms server.
took a while to get it all working but it's great and i love it!
i'm setting up a new similar set for a friend, but when using the new emonSD-17Jun2015.img image. on first, and any subsiquent boot the mysqld service won't start. i can't start it by hand either.
i have tried a number of SD cards, both 4G and larger, but all with the same effect. It's really odd!
when i use the emonpi-28May2015.img older image it still fails
having searched the forums, no one else mentions this, which makes me thing it's something specific to my setup.
but its the virgin image that fails...
i have also tried running the firmware updater, which runs fine. But the mysqld still fails to start post reboot.
running on a pi b 256mb - tried it another model and i fails
but runs on a 512mb ok
i had nothing like this problem last time, just install and go
there is nothing in the docs about this limitation is there?
many thanks,
Stephen.
Re: new emonpi build using emonSD-17Jun2015.img mysqld fails to start
I think you may be running out of RAM, the fact it runs on 512 but not 256 sort of confirms this theory, The "emonPi SDcard" images will require a bit more than the previous images as it is also running a mqtt broker and various other services for the wifi monitoring, mqtt in emoncms, the logging and configuration pages etc.
The pre emonPi images are probably more likely to run on a 256mB Pi but to be honest I think even the older image needs the 512mB for some headroom, it is running SQL, redis and apache2 servers without any memory caching (read-only mode) all the logs are written to RAM and emonhub runs an in memory buffer which is normally very minimal but any network issues will cause emonHub to stack data up in RAM and could choke the Pi. From memory I think mySQL 5.5 has 128mB in-memory cache and then there is redis in-memory buffer too.
IMO a 256mb Pi should only run as a forwarder, the 'rock solid gateway' style using emonHub only (no emoncms etc), 512mb min for a full "pre-emon-pi" emonhub + emoncms and the latest "emonPi" images should ideally only be used on a 1gb Pi unless emoncms is disabled or some restraint is applied.
The previous image you tried is still the emonPi type, the pre-emonPi images are still supported although a little harder to track down, the OLD: Raspberry Pi 2 pre-built SD card image (emonSD-13-03-15.img) BETA thread has links
Paul
Re: new emonpi build using emonSD-17Jun2015.img mysqld fails to start
hello Paul,
thanks for the information and confirmation.
is there a recipe / method to take the "emonsd" image and make it into that rock solid gateway with emon hub?
i know that i could just stop the mysqld service and apache service, not sure what other dependencies rely on this though.
i assume that the emon hub config is a text file somewhere, and that it isn't dependent of apache or anything else?
Thanks again,
Stephen.
Re: new emonpi build using emonSD-17Jun2015.img mysqld fails to start
The links to the guides are broken due to the github branch being renamed
"Using the pre-built image: https://github.com/emoncms/emoncms/blob/bufferedwrite/docs/setup.md"
should link to https://github.com/emoncms/emoncms/blob/low-write/docs/setup.md
"Technical overview and image build guide: https://github.com/emoncms/emoncms/blob/bufferedwrite/readme.md"
should link to https://github.com/emoncms/emoncms/blob/low-write/readme.md
most of the info you need will be on https://github.com/emoncms/emoncms/blob/low-write/docs/install.md
attached is a changelog for the pre emonPi image and it looks like the last versions did not have emoncms enabled so should "just work out of the box"
Paul