Contextual Recommendation System
{% csrf_token %}
Would You like to get Contextual Recommendation?
Yes
No
Watching with your family?
Choose the Type of Device-:
Mobile
Tablet
TV/Laptop
Choose Your mood-:
Happy
Neutral
Sad
{% if movies_id %} {% for mov in movies_id %} {% endfor %} {% endif %}


| Cache:addFormattedMetadata (photos, names) |
Add formatted metadata to cache - note: photos may be different, caller of get-fmt-metadata beware. |
| Cache:addRawMetadata (photos, names) |
Add raw metadata to cache - note: photos may be different, caller of get-raw-metadata beware. |
| Cache:getFmtMeta () |
Get formatted metadata table - for legacy methods that still require separate, raw-meta and fmt-meta tables. |
| Cache:getFormattedMetadata (photo, name, acceptUncached, rejectNil) |
Get specified formatted metadata, hopefully from cache. |
| Cache:getRawMeta () |
Get raw metadata table - for legacy methods that still require separate, raw-meta and fmt-meta tables. |
| Cache:getRawMetadata (photo, name, acceptUncached, rejectNil) |
Get specified raw metadata, hopefully from cache. |
| Cache:loadFormattedMetadata (photos, names) |
Assure specified formatted metadata is in cache for short-term future use. |
| Cache:loadRawMetadata (photos, names) |
Cache specified raw metadata for short-term future use. |
| Cache:new (t) |
Constructor for new instance. |
| LrMetadata:createCache (t) |
Create metadata cache for local use. |
| LrMetadata:defineTokens (params) |
Display dialog box for defining tokens. |
| LrMetadata:getFmtGetPopupItems (params) |
Get gettable formatted items suitable for popup menu. |
| LrMetadata:getFormattedMetadata (photo, name, cache) |
Get specified formatted metadata, from cache if available. |
| LrMetadata:getHelpText (params) |
Get list of metadata items for printing or clipboard.. |
| LrMetadata:getPopupItems () |
Get gettable raw items suitable for popup menu. |
| LrMetadata:getRawGetPopupItems (params) |
Get gettable raw items suitable for popup menu. |
| LrMetadata:getRawMetadata (photo, name, cache) |
Get specified raw metadata, from cache if available. |
| LrMetadata:getRawSetPopupItems (params) |
Get settable raw items suitable for popup menu. |
| LrMetadata:init () |
Initialize data descriptors for getting/setting raw/formatted Lightroom metadata. |
| LrMetadata:isKnownKey (photo, name) |
Determine if key is known in formatted metadata. |
| LrMetadata:isKnownRawKey (photo, name) |
Determine if key is valid for reading raw metadata. |
| LrMetadata:isSettableRawKey (name) |
Determine if key is valid for setting raw metadata. |
| LrMetadata:new (t) |
Constructor for new instance. |
| LrMetadata:newClass (t) |
Constructor for extending class. |
| LrMetadata:transfer (params) |
Transfer metadata from photo (possibly missing) to photo (presumably file must exist, unless inclusions/exclusions carefully chosen). |
- Cache:addFormattedMetadata (photos, names)
-
Add formatted metadata to cache - note: photos may be different, caller of get-fmt-metadata beware.
Parameters:
- Cache:addRawMetadata (photos, names)
-
Add raw metadata to cache - note: photos may be different, caller of get-raw-metadata beware.
Parameters:
- Cache:getFmtMeta ()
-
Get formatted metadata table - for legacy methods that still require separate, raw-meta and fmt-meta tables.
- Cache:getFormattedMetadata (photo, name, acceptUncached, rejectNil)
-
Get specified formatted metadata, hopefully from cache.
Parameters:
-
photo
:
-
name
:
-
acceptUncached
:
-
rejectNil
:
Usage:
Enable advanced debugging for this module to see uncached metadata accesses.
- Cache:getRawMeta ()
-
Get raw metadata table - for legacy methods that still require separate, raw-meta and fmt-meta tables.
- Cache:getRawMetadata (photo, name, acceptUncached, rejectNil)
-
Get specified raw metadata, hopefully from cache.
Parameters:
-
photo
:
-
name
:
-
acceptUncached
:
-
rejectNil
:
Usage:
Enable advanced debugging for this module to see uncached metadata accesses.
- Cache:loadFormattedMetadata (photos, names)
-
Assure specified formatted metadata is in cache for short-term future use.
Parameters:
Usage:
clears any previous metadata from cache - use add-fmt-metadata to, well, add formatted metadata to the cache.
- Cache:loadRawMetadata (photos, names)
-
Cache specified raw metadata for short-term future use.
Parameters:
Usage:
clears any previous metadata from cache - use add-raw-metadata to, well, add raw metadata to the cache.
- Cache:new (t)
-
Constructor for new instance.
Parameters:
Usage:
presently no way to extend internal cache class.
if that changes, then provide new class constructor and go through object factory to create.
- LrMetadata:createCache (t)
-
Create metadata cache for local use.
Parameters:
-
t
: (table, optional) members: photos, rawIds, fmtIds, call. If provided, cache will be pre-loaded (and call used for caption while loading).
Usage:
equivalent to Lr catalog's batch get metadata functions, with the following conveniences:
You can add metadata to the cache, for same or different photos, after the fact.
When getting metadata via lr-meta methods, it will take from cache if available, else photo - thus no "attempt to index nil..." errors.
if data not in cache, debug message logged, so you can try passing an empty cache, and then based on what's logged learn how to fill it.
If you you know the cache variable exists, then there is no reason not to access directly, setting accept-cached as desired,
but if cache is being passed in, it's best to call lr-meta--get-raw/fmt instead, since it not only checks for cache, but accepts uncached.
- LrMetadata:defineTokens (params)
-
Display dialog box for defining tokens.
Parameters:
Usage:
asynchronous (optional callbacks).
params may include callbacks as defined in show-floating-dialog method.
if more than one simultaneous, pass unique titles, since they're used for guarding.
- LrMetadata:getFmtGetPopupItems (params)
-
Get gettable formatted items suitable for popup menu.
Parameters:
-
params
: optional parameter table, with members: simpleOnly (exclude table metadata), idOnly (item values to be id, not spec).
Return values:
- popup items - menu-compatible: titles are friendly, and values may be ids or raw-metadata specs (as seen in this module) depending on param.
- lookup - keys are ids, values are specs.
- LrMetadata:getFormattedMetadata (photo, name, cache)
-
Get specified formatted metadata, from cache if available.
Parameters:
Usage:
good for functions that can take advantage of a cache created externally, or not.
- LrMetadata:getHelpText (params)
-
Get list of metadata items for printing or clipboard..
Parameters:
-
params
: parameter table, with optional members: 'format' (idOnly, idPlusFriendly, friendlyOnly, friendlyPlusId)
Usage:
excludes custom (plugin) metadata
- LrMetadata:getPopupItems ()
-
Get gettable raw items suitable for popup menu. [[ *** on hold - needs more thought..
- LrMetadata:getRawGetPopupItems (params)
-
Get gettable raw items suitable for popup menu.
Parameters:
- LrMetadata:getRawMetadata (photo, name, cache)
-
Get specified raw metadata, from cache if available.
Parameters:
Usage:
good for functions that can take advantage of a cache created externally, or not.
- LrMetadata:getRawSetPopupItems (params)
-
Get settable raw items suitable for popup menu.
Parameters:
-
params
: optional parameter table, with members: simpleOnly (exclude table metadata), idOnly (item values to be id, not spec).
Return values:
- popup items - menu-compatible: titles are friendly, and values may be ids or raw-metadata specs (as seen in this module) depending on param.
- lookup - keys are ids, values are specs.
- LrMetadata:init ()
-
Initialize data descriptors for getting/setting raw/formatted Lightroom metadata.
Usage:
called automatically if need be, but feel free to call upon plugin init for faster initial on-demand response.
info is static, so only needs to be called once.
- LrMetadata:isKnownKey (photo, name)
-
Determine if key is known in formatted metadata.
Parameters:
- LrMetadata:isKnownRawKey (photo, name)
-
Determine if key is valid for reading raw metadata.
Parameters:
-
photo
: (LrPhoto, optional) test photo.
-
name
: (string, required) key.
- LrMetadata:isSettableRawKey (name)
-
Determine if key is valid for setting raw metadata.
Parameters:
- LrMetadata:new (t)
-
Constructor for new instance.
Parameters:
- LrMetadata:newClass (t)
-
Constructor for extending class.
Parameters:
- LrMetadata:transfer (params)
-
Transfer metadata from photo (possibly missing) to photo (presumably file must exist, unless inclusions/exclusions carefully chosen).
Parameters:
-
params
: (table) required. elements:
catUpdTitle (string, default="Transfer Lr Metadata") fromPhoto (LrPhoto, required) source of metadata (from catalog only). toPhoto (LrPhoto, required) target of metadata (catalog and maybe file too). inclusions (table, optional, but recommended) set (or array) of metadata names to include. exclusions (table, optional, usually omitted) set (or array) of metadata names to exclude. toIsVirginal (boolean, default = false) if true, blank from items will be ignored. exifToolSession (object, usually required) - in case included items will require exiftool to transfer. exifTool (object, fallback) - will be used if ets not provided, and et needed - @5/May/2014 18:00, I think it's safest to pass ets.
Usage:
Uses a combination of exiftool and sdk for both reading and writing.
Derived originally from NxToo's transferLrMetadata function.
Probably doesn't (wont/cant) transfer icc profile(?)
comment added 5/May/2014 18:01 - if metadata set via exiftool, I think a read-meta is required afterward so Lr gets the memo(?)
Initially used for transferring metadata from missing photo to recovered preview, also used in relative antics (selective mode).
This method may be preferred if target is photo in catalog, see also: Image:transferMetadata and Xmp:transferMetadata (in case target is file on disk).
incl/excl as passed - does not depend on prefs.


Bug 1592026 R[Core:Graphics: WebRender]Make reftests work in the WR OS compositor configuration on macOS
Bug 1605861 R[Core:WebRTC: Networking]Only enable mDNS hostname obfuscation on Nightly
Bug 1605878 R[Firefox Build System:Lint and Formatting]TypeInference.cpp: Remove a nested redundant #if
Bug 1491989 R[Firefox for Android:Logins, Passwords and Form Fill]Autofill does not support LastPass's field classification
Bug 1604358 R[Release Engineering:Release Requests]Setup WNP for users coming from <72.0 and receiving the 72.0 release
Bug 1605544 R[WebExtensions:General]Intermittent toolkit/components/extensions/test/mochitest/test_ext_subframes_privileges.html | monitorConsole | messages left expected at least 1 got 0
###########
Changes to 6 bugs - 6 fixed.


CSS Shapes using div
The border-radius
property is used here to create these figures in combination with top
and bottom
.
The border-radius
property is used here to create these figures in combination with top
and bottom
.


Alexey Vasiliev, Railsware
Agile is terrible. Scrum is worse.
...the bottleneck is almost always the DOM mutation and not JS execution
React isn't popular because it's fast. It's popular because it's fun.
"Wallmart has moved to node.js" "Twitter has moved to Scala"
"Wallmart has moved to node.js"
"Twitter has moved to Scala"
Do we have same needs as Google, Facebook, Wallmart, Twitter?
Like "Best Practices" need context


Task Tracker
Input Tasks that have been completed below and keep track of the time when each item was added.


Grappling with change: Women's wrestling tones down razzmatazz in Riyadh
RIYADH: Dressed demurely in black leggings and unflattering baggy T-shirts, rather than their trademark low-cut bikini tops, WWE superstars Natalya and Lacey Evans starred in the first ever women's wrestling match in Saudi Arabia on Thursday (Oct 31), the latest unlikely event in the kingdom as it attempts to shrug off an ultra-conservative image.
As they arrived in the ring, with their flowing blonde hair uncovered, three teenagers laughed out loud having earlier in the evening been entranced by the spectacle served up by male, shirtless fighters.
"It's nonsense," said one to the other, struggling to be heard above the fireworks and rock 'n' roll music which blasted into the Riyadh night.
Evans, a former US Marine, and Natalya appeared at the King Fahd Stadium suitably dressed down for the occasion, their usual costumes left behind in the United States.
"Do you want them to be sent to jail?" said an expatriate fan who wished to remain anonymous when defending the dress code.
"Women's wrestling in Saudi Arabia, yes, but only if they dress like that, otherwise it would not be possible, even if it's a fact that the clothing is an integral part of the show," added a young fan wearing a black World Wrestling Entertainment (WWE) T-shirt, adorned with pictures of his favourite fighters.
Saudi Arabia is boosting entertainment that allows citizens to have fun, in what some see as an attempt to blunt public frustration over an economic downturn and high youth unemployment.
De facto leader Crown Prince Mohammed bin Salman has introduced reforms including allowing concerts, reopening cinemas, and lifting a prohibition on women driving as part of a modernisation drive.
However, when it comes to women's wrestling, it may be a long, hard road.
Last year, a broadcast during a men's wrestling match of a promotional video featuring scantily-clad female wrestlers sparked a scandal in the country, forcing the authorities concerned to apologise for the "indecent" images.
Ahmed, 24, who says he follows the sport from the kingdom, appeared disappointed with such furores.
"I was waiting for the women's match. Those who want to see such a spectacle should have the right to access it, and those who do not like don't have to come," he said.
Ali, 40, attended with his two children and said he wanted to support the social changes in progress in the country.
However, he thinks there should be "limits".
"These women's shows, honestly ...", said Ali, wearing his country's traditional all-white robe.
"That women drive, it's already a shock for me. I'm not against it but you have to get used to it."
Despite his discomfort, he said he had promised his daughter, pulling at his arm to show him her favourite wrestler, to teach her to drive when she is old enough.


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I am a Toronto front-end developer, graphic/UI/UX designer, copywriter and editor. I founded Mason Media to build beautiful, functional, and original web & print experiences. I co-think with clients to create unique and innovative products that balance beauty with function, scalability, and SEO. From interactive websites (custom coded, templates, and Wordpress), to copywriting, and graphic design, I create custom products with depth and originality.


{% load staticfiles %}
{% block title %} {% endblock %}
Autism Resource Database Alaska
Home
User Guide
Contact Us
Select Categories
Resource Types
Library
Online
Service
Event
Select Filters
Demographics
Male
Female
Age 1-3
Age 3-18
Age 18+
Disorders
Autism Spectrum
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Pervasive Development
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Cognitive Development
Behaviors
Sleep
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{% if error %} {% endif %}
{% block content %} {% endblock %}


We are interested in improving MindTrails and would like to learn about why you decided to stop the program. We appreciate your feedback!
What device(s) did you use to complete the program? Please check all that apply.
 Please check all that apply.
Of the sessions you did complete, where did you primarily complete the program? Please check all that apply.
During this program, did you change any medicine, therapy, or other intervention to help your anxiety? Please check all that apply.


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From time to time my hobbies differs whenever I'm hook with enthusiasm, for now I love to do website development, coding ( Specially ). I am satisfied whenever I do find it great, in look's and in backend layout. The more I see it the way it will gonna be, the more I am satisfied, specially when new knowledge comes and I cant find it way simply.
English - Professor Marigold Jean
HTML & CSS - Professor Gerard Arguelles
IT Fundamentals - Professor Ken Remaneses


class Insertion
The Insertion class inserts a value before or after another value in a list.
@example
Insertion.new([1, 2, 3], 4).before(3) # => [1, 2, 4, 3]
Public Class Methods
Creates an insertion object on a list with a value to be inserted. To finalize the insertion, call {#before} or {#after} on the object.
@param [Array] list the list to perform the insertion on @param [Object] value the value to insert
# File lib/yard/core_ext/insertion.rb, line 13 def initialize(list, value) @list = list @values = (Array === value ? value : [value]) end
Public Instance Methods
Inserts the value after val
.
@example If subsections are ignored
Insertion.new([1, [2], 3], :X).after(1) # => [1, [2], :X, 3]
@param [Object] val the object the value will be inserted after @param [Boolean] recursive look inside sublists
# File lib/yard/core_ext/insertion.rb, line 29 def after(val, recursive = false) insertion(val, 1, recursive) end
Alias for {#after} with recursive
set to true @since 0.6.0
# File lib/yard/core_ext/insertion.rb, line 37 def after_any(val) insertion(val, 1, true) end
Inserts the value before val
@param [Object] val the object
the value will be inserted before @param [Boolean] recursive look inside
sublists
# File lib/yard/core_ext/insertion.rb, line 21 def before(val, recursive = false) insertion(val, 0, recursive) end
Alias for {#before} with recursive
set to true @since 0.6.0
# File lib/yard/core_ext/insertion.rb, line 33 def before_any(val) insertion(val, 0, true) end
Private Instance Methods
This method performs the actual insertion
@param [Object] val the value to insert @param [Fixnum] rel the relative index (0 or 1) of where the object
should be placed
@param [Boolean] recursive look inside sublists @param [Array] list the list to place objects into
# File lib/yard/core_ext/insertion.rb, line 48 def insertion(val, rel, recursive = false, list = @list) if recursive list.each do |item| next unless item.is_a?(Array) tmp = item.dup insertion(val, rel, recursive, item) return(list) unless item == tmp end end index = list.index(val) list[index + rel, 0] = @values if index list end


Search for your character in the top right!
Welcome to the fan-made Final Fantasy XIV character search! Begin by searching your character and selecting your server to pull your character's information.
Welcome to the fan-made Final Fantasy XIV character search! Begin by searching your character and selecting your server to pull your character's information.


Positioned at the enterance with 28ft height and 30ft width, the Stonecut Swagathgopura stands as magnificent welcome pillars to the town. These are considered to be one of biggest Stone made SwagathaGopura in the country.
| Project Type | Gopura |
| Client | Private |
| Completion Date | July 2016 |
| Location | Marnakatte |
This public park symbolizes the respect towards freedom fighters,martyrs of the nation. On public interest the park was designed and built on stone to presreve memory of the great soldiers. It is located at Karkala, Karnataka.
| Project Type | Theme Park |
| Client | Public Ogranization |
| Completion Date | January 2014 |
| Location | Karkala |
This temple was built as a tribute to Jarandhaya from the trust and the devotees, the shilamayi structure beautifies the slush architrcture of the temple. It is located in Kubeoor at Mulki.
| Project Type | Temple |
| Client | Devi Trust |
| Completion Date | April 2016 |
| Location | Mulki |
Phone:
+91 9880 191 020
+91 9482 098 221
Sri Laxminarayana Designers,Jarkala, Karkala
Udupi(D), Karnataka
E-mail:
nagarajthantri[at]gmail.com
Sri Laxminarayana Designers has estabilished itself as one of the greatest and prestigious providers of construction focused interior renovation services and building.


Video: Biden Says Graham Will ‘Regret’ Investigating His Family’s Ukraine Ties
Did the former vice president threaten a senator?
Democratic presidential candidate Joe Biden tried to do damage control against Sen. Lindsey Graham’s (R-S.C.) request for documents related to his son Hunter’s role on the board of Ukrainian energy company Burisma Holdings, saying he felt “embarrassed” for the senator.
During a CNN interview on Friday, Biden pushed back against Graham’s move, saying that Trump is “holding power over him.”
“I am disappointed. Quite frankly, I’m angered,” Biden said of Graham’s request. “He knows me. He knows my son. He knows there’s nothing to this. Trump is now essentially holding power over him that even the Ukrainians wouldn’t yield to. Ukrainians would not yield to, quote, ‘investigate Biden — there’s nothing to investigate about Biden or his son.'”
“Lindsey is about to go down in a way that I think he’s going to regret his whole life,” he added.
Graham had told Fox News Wednesday that he would request transcripts of phone calls between Biden and Burisma founder Mykola Zlochevsky, who was arrested earlier this week for money laundering.
“I want to know if there’s any transcript or readouts of the phone calls between the vice president and the president of the Ukraine in February after the raid on the gas company president’s house,” Graham said.
Ukrainian MP MP Alexander Dubinsky said during a Wednesday press conference that Hunter Biden had received $16.5 million through Burisma’s money laundering operation.
“The son of Vice-President Joe Biden was receiving payment for his services, with money raised through criminal means and money laundering,” Dubinsky said. “Biden received money that did not come from the company’s successful operation but rather from money stolen from citizens.”
President Trump’s lawyer Rudy Giuliani likened Biden’s remarks to a mafia threat.
Coup, Part Deux continues and even though the CIA’s Mockingbird Press is working overtime, Biden is going down.


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Doctor of Philosophy, Computing
School of Computing, Graphics and Visualization Track
University of Utah, Salt Lake City, UT
December 2019
GPA: 4.0
Bachelor of Science, Computer Science
Summa Cum Laude
Gannon University, Erie, PA
May 9, 2009
GPA: 4.0
Outstanding Teaching Assistant Award, University of Utah School of Computing, 2011
Archbishop John Mark Gannon Award for Academic Excellence, Gannon University, 2009
Leadership Scholarship Award, Gannon University, (2005-2009)
Academic Excellence Award, Gannon University, (2005-2009)
Dean's List Gannon University, 8 of 8 Semesters (2005-2009)
Phi Eta Sigma National Honor Society, Gannon University, 2006
American Chemical Society Outstanding Freshmen Chemist Award, Gannon University, 2006
Software Engineer
May 2019-Present
Recursion Pharmaceuticals
Part-Time Contractor
November 2017-August 2018
Go Nimbly
Research Intern
October 2014-September 2017
Idaho National Laboratory
Research Intern
May 2013-August 2013
Lawrence Livermore National Laboratory
Research Intern
May 2012-August 2012
Sandia National Laboratories
Research Assistant
January 2012-October 2014
University of Utah, School of Computing
Instructor
June 2011-August 2011
University of Utah, School of Computing
Programmer
May 2011-December 2011
University of Utah, Energy and Geoscience Institute
Programming Consultant
May 2010-May 2012
Total Systems Resources
Teaching Assistant
August 2009-December 2011
University of Utah, School of Computing
IT Co-op
September 2008-May 2009
GE Transportation
Programmer
May 2007-August 2008
ImmersiMap, LLC
IT Intern
May 2007-August 2007
Insight Technology, LLC
Student Aide
August 2006-May 2007
CAAP/ACT 101 Tutorial Services Program, Gannon University


Introspect
Personal web application that aids reflection on past and current relationships by analyzing and representing data in a way that reveals patterns and surfaces qualities most important to you. Introspect was built with Ruby on Rails, MongoDB, JavaScript, D3.js, and Bootstrap.
Our Reads
Classroom web application allowing students to recommend books to each other, fostering engagement and a love for reading. With further development, this app will also support student book discussions, allow teachers to upload their classroom libraries, and give classrooms a platform to share their classroom library book wish list. Originally, this app was built with Ruby, Sinatra and the Google Books API.
CSS Cheat Sheet
A resource created for my classmates in the first few weeks of Dev Bootcamp.


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Tools for maintaining and querying time data in PostgreSQL. It includes temporal data types, functions, operators, opclasses (for indexing), and triggers. Also includes documentation for best practices, examples, and useful queries.
The Temporal PostgreSQLproject is a PostgreSQL Community project that is a part of the pgFoundry.
The pgFoundry page for the project is at http://pgfoundry.org/projects/temporal, where you can find downloads, documentation, bug reports, mailing lists, and a whole lot more.


@()(implicit user: models.user.User, session: play.api.db.slick.Config.driver.simple.Session)
@import controllers.organization.routes.OrganizationsController
@import com.artclod.play.s
@defining(user.courses) { courses =>
@mainWithStatus("EdTech Welcome Page")(None){
@viewsupport.ViewText.welcome
General Information
This site is a experiment using new software and theories about education to improve how people learn. You must be enrolled in a course to make use of the system.
If you are already enrolled please select a course from the list below.
If you have been given a code to join a course navigate to it by selecting the appropriate organization below.
We plan on opening up the system later but it is currently invite only, and there is no way to request access to courses inside the system.
Courses
@if(courses.isEmpty) {
You are not currently associated with any courses.
} else {
You are currently associated with the following course@s(courses):
@for(course <- courses) {- @tag.courseAccessLink(course)
}
}
Organizations
If you have a code you can navigate to the course by picking the correct organization in the list here
}
}


Ask Fuzzy: What's the difference between formula and breast milk?
by Jennifer JamesThere is much we don't understand about breast milk, particularly in terms of the complex interplay between different components and how they work together to achieve complete nutrition for infants and young children.
What we do know is that breast milk is a dynamic food that changes according to the needs of breastfed infants.
For example, breast milk produced by a mother of a premature infant is very different to the breast milk of a mother who gave birth to a baby born at 40 weeks, which is very different to the breast milk received by a six-month-old, or a 12-month-old or even a two-year-old child.
In stark contrast, formula is a static food that provides the basic nutrients required for infant growth.
Even as the scientific community develops an understanding of breast milk, the ability to mimic breast milk and its capacity to protect from disease, promote mental and physical growth or optimise development is unlikely to ever happen.
The physical act of breastfeeding provides opportunities for growth and development that is not available to the formula-fed infant.
The action of suckling at the breast versus sucking on a bottle teat shows clear differences in oral muscle activity and dental development.
Breast fed babies have been shown to have fewer speech and enunciation problems and the oral cavity is able to develop normal shape and functionality.
Even with the array of formula products available today, none can provide infants and children with the best possible start to life.
Response by: Jennifer James, senior lecturer in midwifery, breastfeeding, RMIT


--- title: Our team description: ---
At Sportsynergy we have humble roots. It all began on a cool autumn morning in 2001 when the Commodore Squash Club was looking for a way to make itself more convenient to its members. The small club was sparsely staffed on the weekends so members were not able to simply call in and make court reservations during this time; they had to physically go to the club. What’s more, when managing leagues, the club pro found himself keeping track of everything on scraps of paper.
Recognizing these problems, squash pro John O’Brien along with several other members of the Commodore devised a solution. The club members would have the ability to manage their own court reservations, not from just the club but from home and from work too. They would be able to have easy access to their fellow club members contact information to more conveniently arrange matches. Several months later the Commodore Squash Club went online with this system and Sportsynergy was born.
Sportsynergy is wholly owned by the founders and has no debts or investment. It is committed to sustainable organic growth by reinvesting profits from the sale of products and services with additional revenue from customization and consultancy work.


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Bayesian Inference¶
Mini-objectives:
- Review Probability
- Discuss Statistical Philosophies
- Repurpose Bayes’ rule for Distributions (and start callling it Bayes’ Theorem)
- Discuss Bayesian Inference
Probability Review¶
Recall that we have learned about three probability estimands
- Joint: \(Pr(A \cap B)\)
- Conditional: \(Pr(A | B)\)
- Marginal: \(Pr(A)\)
These concepts are reviewed here and some related practice problems are available here.
Note
EXERCISE
Specify the conditional probability in terms of joint and marginal probabilities.
Conditional probability¶
Recall the exercise from yesterday
Note
PREVIOUSLY
- Three types of fair coins are in an urn: HH, HT, and TT
- You pull a coin out of the urn, flip it, and it comes up H
- Q: what is the probability it comes up H if you flip it a second time?
Note
SOLUTION
The way you solved this problem yesterday was to list out the sample space and count the outcomes comprising the event of interest. But of course this problem can also be solved analytically. To do so we calculate
- \(Pr(F_1=H \cap F_2=H)\)
- \(Pr(F_1=H)\)
- \(Pr(F_2=H|F_1=H) = \frac{Pr(F_1=H, F_2=H)}{Pr(F_1=H)}\)
as
\(\begin{eqnarray}Pr(F_1=H \cap F_2=H) &=& \underset{c \in \{HH,HT,TT\}}{\sum}Pr(F_1=H \cap F_2=H | C=c) Pr(C=c)\\&=&1\times\frac{1}{3}+\frac{1}{4}\times\frac{1}{3}+0\times\frac{1}{3} = \frac{5}{12}\\\\\\Pr(F_1=H) &=& \underset{c \in \{HH,HT,TT\}}{\sum}Pr(F_1=H | C=c) Pr(C=c)\\&=&1\times\frac{1}{3}+\frac{1}{2}\times\frac{1}{3}+0\times\frac{1}{3} = \frac{1}{2}\\\\\\\Pr(F_2=H|F_1=H) &=& \frac{5/12}{1/2}=\frac{5}{6}\end{eqnarray}\)
So we first answered this question counting outcomes in events based on the sample space, and now we answered it using the law of total probability. But if you’re still skeptical about our answer, perhaps just simulating the experiment will help convince you:
Note
EXERCISE
Figure out what the following code does and try it out!
import random
import pandas as pd
coins = ['HH', 'HT', 'TT']
results = []
for i in range(10000):
coin = random.choice(coins)
results.append([random.choice(coin) for j in [1,2]])
df = pd.DataFrame(results, columns=['first', 'second']) == 'H'
# df.groupby('first').mean()
# 5./6
Simulation is a great way to confirm your answers to different problem. It’s a general purpose tool that you should always remember to keep at your disposal when you’re trying to figure out how something works. Just even the process of creating the simulation can be helpful to nail down your understanding of a problem.
If you are not familiar with pandas, here is another way of simulating the conditional probability.
import numpy as np
n = 10000
coins = ['HH', 'HT', 'TT']
coins_selected = np.random.choice(coins,n)
first_side_shown = np.array([c[np.random.random_integers(0,1,1)[0]] for c in coins_selected])
coins_with_heads = coins_selected[np.where(first_side_shown == 'H')[0]]
second_side_shown = np.array([c[np.random.random_integers(0,1,1)[0]] for c in coins_with_heads])
print("%s/%s"%(np.where(second_side_shown=='H')[0].size,second_side_shown.size))
print(np.where(second_side_shown=='H')[0].size/second_side_shown.size)
4096/4938
0.8295
More discussion about conditional probabilities can be found here.
Bayesian Inference¶
Bayesian inference is based on the idea that distributional parameters \(\theta\) can themselves be viewed as random variables with their own distributions. This is distinct from the Frequentist perspective which views parameters as known and fixed constants to be estimated. E.g., “If we measured everyone’s height instantaneously, at that moment there would be one true average height in the population.” Regardless of one’s philosophical perspective, both approaches have value in practice.
The key computational step in the Bayesian framework is deriving the posterior distribution, which is done using the a forumula we have already seen; namely Bayes’ theorem:
Bayes’ theorem is comprised of
- \(P(\theta|X)\) – the posterior distribution
- \(P(X|\theta)\) – the likelihood function
- \(P(\theta)\) – the prior distribution
- \(P(X)\) – the marginal likelihood
Just as the posterior distribution is the central estimand in Bayesian statistics, the likelihood function is the central piece of machinery in a Frequentist context. But as you can see from the formula, the posterior is simply a kind of “re-weighting” of the likelihood function (so Bayesian and frequentist inference must not be completely at odds – they agree on at least something). The re-weighting is accomplished by striking a balance between the likelihood function and the prior distribution. The prior distribution represents our belief about the parameter prior to seeing the data, while the likelihood function tells us what the data implies about the parameter – and then these two perspectives are reconciled. The marginal likelihood turns out to just be a constant which ensures that the posterior is a probability mass function or a probability density function (i.e., sums to one or has area one). As such, in many contexts the marginal likelihood simply represents a formality that is not crucial to the posterior calculation; however, sometimes it is useful (although it can be difficult to obtain). Interestingly, the marginal likelihood can be used for Bayesian model selection, so for some tasks it is an estimand of primary importance.
Statistical Paradigms¶
Bayesian inference works by updating the belief about the parameters \(\theta\) encoded in the prior distribution with the information contained in the observed data \(x\) about the parameters as quantified in the likelihood function. This updated belief – called the posterior distribution – can serve as the next “prior” for the subsequent collection of additional data, and can itself be updated, and so on. The updated belief is always encoded as a probability distribution, so statements of belief about parameters are made using probability statements. In contrast, Classical (or Frequentist) statistics instead focusses on characterizing uncertainty in parameter estimation procedures that results from random sampling variation. I.e., Frequentist statistics never makes statements about parameters, but instead makes statements about probabilities (long-run frequency rates) of estimation procedures.
Arguments for Bayesian Analysis¶
- Ease of Interpretation: making probability statements about parameters of interest is much simpler than trying to perform hypothesis testing by $interpreting p-values* and confidence intervals (*to be discussed later).
- No “Large Sample” Requirements: the accuracy of many Frequentist results rely upon asymptotic distributional results that require a “large sample size” – the actual quantity of which often remains unclear – whereas Bayesian analysis is a fully coherent probabilistic framework regardless of sample size.
- Integrated Probabilistic Framework: Bayesian analysis provides a hierarchical modeling framework that definitionally characterizes and propagates all the modeled uncertainty into parameter estimation.
- Ability to Utilize Prior Information: the Bayesian framework naturally provides a way to combine information, or learn; however, the ability to input (potentially arbitrary) information into analysis via the prior means objectivity can be sacrificed for subjectivity.
- Natural Framework for Regularization: the prior distribution of a Bayesian specification can be used to perform regularization, i.e., stabilize model fitting procedures so that they are less prone to overfitting data.
Complex Data Modeling: Bayesian analysis provides – via computational techniques – the ability to develop and use more complicated modeling specifications than can be evaluated and use with classical statistical techniques; however, such approaches can be computationally demanding.
In general, Bayesian computation is more expensive than Frequentist computation as there tends to be a lot of overhead. Also, complex models are not always preferable: (a) they require practitioners with more advanced skill sets, (b) they will be more difficult to implement correctly, and (c) simple solutions can outperform complex solutions at a fraction of total development and computational costs.
Occam’s razor says that the simplest answer is often correct one. And Murphy’s law says that if something can go wrong, it will go wrong. These are very good considerations to keep in my as you contruct your data analysis pipelines.
Note
CLASS DISCUSSION
What do you appreciate most about the Bayesian philosophy?
What do you appreciate about the Frequentist philosophy?

- You’re a skilled programmer, but bugs still slip into your code. After a particularly difficult implementation of an algorithm, you decide to test your code on a trivial example. It passes. You test the code on a harder problem. It passes once again. And it passes the next, even more difficult, test too! You are starting to believe that there may be no bugs in this code...
- You’re a doctor who has some previous experience with the symptoms that are presenting for the current patient and you’ve diagnosed this sort of condition many times before...
Note
Are YOU SURE you’re a Bayesian?
Without looking...
Write Bayes’ theorem and describe the function of the different components that comprise the theorem, particularly with respect to parameters and evidence.
Further study¶
If you do actually want to be a Bayesian – fear not – you can! Programming in the Bayesian landscape has become incredibly easy via the advent of probabilistic programming. Here are several outstanding resources available that you can use to start learning more about Bayesian analysis:


Simple answer: because of minification issues.
Minification can cause modules to use each other as their arguments (unintentionally), if the developer isn’t careful.
If you look closely enough at the above, you’ll see the first IIFE is missing a semicolon at the end.
That means that when minified, it’ll look like this:
The broken code:
The problem is that now function a
is being called with function b
passed in as an argument. Interesting.
So, we just add a ;
to the beginning of the module, and to the end. This acts as a safeguard to ensure we don’t run into that problem when we minify.
So, when we try doing the above example with semicolons at the beginning and at the end, and you minify the code, you get this instead:
The working code:
The cool thing is, the above doesn’t throw any errors. In fact, JSHint won’t yell at you either.
Why is this? Check out the MDN article on empty
:
An empty statement is used to provide no statement, although the JavaScript syntax would expect one.
So those extra semicolons are not a syntax error, because a random semicolon anywhere in the code can be interpreted as an empty
statement. Cool, huh?


Rocks remember. You are the ghost of a dead archeologist, collect rocks to discover the history of the development of this game.
settings table
creation menu


--- layout: archive title: Zulip Chat Archive permalink: /stream/113489-new-members/topic/noncomputable.html ---
I'm trying
def to_complex (x : ℤ[ω]) : ℂ := x.re + x.im * (1 + I * real.sqrt 3) / 2
but getting definition 'to_complex' is noncomputable, it depends on 'complex.discrete_field'
.
Is there some import
or open
that will "deal" with this? What are the consequences of ignoring the noncomputability of sqrt?
It looks like an interesting exercise to make real.sqrt
computable (looks like there is a proof sketch in the comments of real.sqrt
's definition). Is that worth trying? Is it just a matter of constructing the Cauchy sequence that converges to sqrt(n)?
The real numbers as implemented in mathlib have no useful computational structure anyways (they are Cauchy sequences without any explicit rate of convergence). You should just put noncomputable theory
at the top of your file if you are going to use the reals a lot.
Thanks!
Are you saying that even if we complete the proof of sqrt_aux_converges
sqrt would still be "uncomputable"?
It would be computable in the sense that Lean wouldn't have the noncomputable
tag, but it would not be computable in any practical sense. There is no computable function real -> bool
for example, so there's basically nothing you can do with a "computable" function on the current implementation of the reals.
I think I see :)
Thanks again! (I must say I'm blown away by the support here...)
I tend to not put noncomputable theory
at the top of my files, and then every time Lean complains something is noncomputable I just write noncomputable
in front of it, so e.g. noncomputable def to_complex ...
would also remove the error.
Last updated: Apr 24 2020 at 19:02 UTC


Apache Drill 1.10.0 Release Notes
Release date: March 15, 2017
Today, we’re happy to announce the availability of Drill 1.10.0. You can download it here.
New Features and Improvements
This release of Drill provides the following new features and improvements:
- Support for the CREATE TEMPORARY TABLE AS (CTTAS) command.
- A JDBC connection option that improves fault tolerance when connecting directly to a Drill node from a client.
- The Web UI displays the Drill version and additional query profile statistics.
- Drill implicitly interprets the INT96 timestamp data type in Parquet files.
- Support for Kerberos authentication between the client and drillbit.
The following sections list additional bug fixes and improvements:
Sub-task
- [DRILL-4272] - When sort runs out of memory and query fails, resources are seemingly not freed
- [DRILL-4301] - OOM : Unable to allocate sv2 for 1000 records, and not enough batchGroups to spill.
- [DRILL-4730] - Update JDBC DatabaseMetaData implementation to use new Metadata APIs
- [DRILL-5008] - Refactor, document and simplify ExternalSortBatch
- [DRILL-5011] - External Sort Batch memory use depends on record width
- [DRILL-5014] - ExternalSortBatch cache size, spill count differs from config setting
- [DRILL-5017] - Config param drill.exec.sort.external.batch.size is not used
- [DRILL-5019] - ExternalSortBatch spills all batches to disk even if even one spills
- [DRILL-5020] - ExternalSortBatch has inconsistent notions of the memory limit
- [DRILL-5022] - ExternalSortBatch sets two different limits for "copier" memory
- [DRILL-5023] - ExternalSortBatch does not spill fully, throws off spill calculations
- [DRILL-5025] - ExternalSortBatch provides weak control over spill file size
- [DRILL-5026] - ExternalSortBatch uses two memory allocators; one will do
- [DRILL-5027] - ExternalSortBatch is inefficient: rewrites data unnecessarily
- [DRILL-5055] - External Sort does not delete spill file if error occurs during close
- [DRILL-5062] - External sort refers to the deprecated HDFS fs.default.name param
- [DRILL-5066] - External sort attempts to retry sv2 memory alloc, even if can never succeed
- [DRILL-5210] - External Sort BatchGroup leaks memory if an OOM occurs during read
- [DRILL-5262] - NPE in managed external sort while spilling to disk
- [DRILL-5264] - Managed External Sort fails with OOM
- [DRILL-5267] - Managed external sort spills too often with Parquet data
- [DRILL-5285] - Provide detailed, accurate estimate of size consumed by a record batch
- [DRILL-5294] - Managed External Sort throws an OOM during the merge and spill phase
Bug
- [DRILL-1808] - Large compilation unit tests fails due to high memory allocation
- [DRILL-2293] - CTAS does not clean up when it fails
- [DRILL-3562] - Query fails when using flatten on JSON data where some documents have an empty array
- [DRILL-4578] - "children" missing from results of full scan over JSON data
- [DRILL-4764] - Parquet file with INT_16, etc. logical types not supported by simple SELECT
- [DRILL-4812] - Wildcard queries fail on Windows
- [DRILL-4850] - TPCDS Query 33 failed in the second and 3rd runs, but succeeded in the 1st run
- [DRILL-4872] - NPE from CTAS partitioned by a projected casted null
- [DRILL-4919] - Fix select count(1) / count(*) on csv with header
- [DRILL-4938] - Report UserException when constant expression reduction fails
- [DRILL-4963] - Issues when overloading Drill native functions with dynamic UDFs
- [DRILL-4982] - Hive Queries degrade when queries switch between different formats
- [DRILL-4994] - Prepared statement stopped working between 1.8.0 client and < 1.8.0 server
- [DRILL-4995] - Allow lazy init when dynamic UDF support is disabled
- [DRILL-4996] - Parquet Date auto-correction is not working in auto-partitioned parquet files generated by drill-1.6
- [DRILL-5005] - Potential issues with external sort info in query profile
- [DRILL-5015] - As per documentation, when issuing a list of drillbits in the connection string, we always attempt to connect only to the first one
- [DRILL-5032] - Drill query on hive parquet table failed with OutOfMemoryError: Java heap space
- [DRILL-5034] - Select timestamp from hive generated parquet always return in UTC
- [DRILL-5039] - NPE - CTAS PARTITION BY (<char-type-column>)
- [DRILL-5040] - Interrupted CTAS should not succeed & should not create physical file on disk
- [DRILL-5044] - Fix retry logic to handle VersionMismatchException by not deleting jars in remote UDFs area
- [DRILL-5048] - Fix type mismatch error in case statement with null timestamp
- [DRILL-5050] - C++ client library has symbol resolution issues when loaded by a process that already uses boost::asio
- [DRILL-5051] - DRILL-5051: Fix incorrect result returned in nest query with offset specified
- [DRILL-5070] - Code gen: create methods in fixed order to allow test verification
- [DRILL-5081] - Excessive info level logging introduced in DRILL-4203
- [DRILL-5086] - ClassCastException when filter pushdown is used with a bigint or float column and metadata caching.
- [DRILL-5088] - Error when reading DBRef column
- [DRILL-5091] - JDBC unit test fail on Java 8
- [DRILL-5094] - Assure Comparator to be transitive
- [DRILL-5097] - Using store.parquet.reader.int96_as_timestamp gives IOOB whereas convert_from works
- [DRILL-5104] - Foreman sets external sort memory allocation even for a physical plan
- [DRILL-5112] - Unit tests derived from PopUnitTestBase fail in IDE due to config errors
- [DRILL-5113] - Upgrade Maven RAT plugin to avoid annoying XML errors
- [DRILL-5117] - Compile error when query a json file with 1000+columns
- [DRILL-5119] - Update MapR version to <IP_ADDRESS>963-mapr
- [DRILL-5121] - A memory leak is observed when exact case is not specified for a column in a filter condition
- [DRILL-5127] - Revert the fix for DRILL-4831
- [DRILL-5157] - Multiple Snappy versions on class path; causes unit test failures
- [DRILL-5159] - ProjectMergeRule in Drill should operate on RelNodes with same convention trait.
- [DRILL-5164] - Equi-join query results in CompileException when inputs have large number of columns
- [DRILL-5167] - C++ connector does not set escape string for metadata search pattern
- [DRILL-5190] - Display planning and queued time for a query in its profile page
- [DRILL-5196] - Could not run a single MongoDB unit test case through command line or IDE
- [DRILL-5207] - Improve Parquet scan pipelining
- [DRILL-5208] - Finding path to java executable should be deterministic
- [DRILL-5218] - Support Disabling Heartbeats in C++ Client
- [DRILL-5224] - CTTAS: fix errors connected with system path delimiters (Windows)
- [DRILL-5230] - Translation of millisecond duration into hours is incorrect
- [DRILL-5238] - CTTAS: unable to resolve temporary table if workspace is indicated without schema
- [DRILL-5242] - The UI breaks when trying to render profiles having unknown metrics
- [DRILL-5243] - Fix TestContextFunctions.sessionIdUDFWithinSameSession unit test
- [DRILL-5252] - A condition returns always true
- [DRILL-5263] - Prevent left NLJoin with non scalar subqueries
- [DRILL-5266] - Parquet Reader produces "low density" record batches - bits vs. bytes
- [DRILL-5273] - CompliantTextReader exhausts 4 GB memory when reading 5000 small files
- [DRILL-5274] - Exception thrown in Drillbit shutdown in UDF cleanup code
- [DRILL-5275] - Sort spill serialization is slow due to repeated buffer allocations
- [DRILL-5284] - Roll-up of final fixes for managed sort
- [DRILL-5287] - Provide option to skip updates of ephemeral state changes in Zookeeper
- [DRILL-5293] - Poor performance of Hash Table due to same hash value as distribution below
- [DRILL-5304] - Queries fail intermittently when there is skew in data distribution
- [DRILL-5313] - C++ client build failure on linux
- [DRILL-5326] - Unit tests failures related to the SERVER_METADTA
Improvement
- [DRILL-4217] - Query parquet file treat INT_16 & INT_8 as INT32
- [DRILL-4280] - Kerberos Authentication
- [DRILL-4373] - Drill and Hive have incompatible timestamp representations in parquet
- [DRILL-4604] - Generate warning on Web UI if drillbits version mismatch is detected
- [DRILL-4864] - Add ANSI format for date/time functions
- [DRILL-4956] - Temporary tables support
- [DRILL-4980] - Upgrading of the approach of parquet date correctness status detection
- [DRILL-4987] - Use ImpersonationUtil in RemoteFunctionRegistry
- [DRILL-5043] - Function that returns a unique id per session/connection similar to MySQL's CONNECTION_ID()
- [DRILL-5052] - Option to debug generated Java code using an IDE
- [DRILL-5056] - UserException does not write full message to log
- [DRILL-5065] - Optimize count(*) queries on MapR-DB JSON Tables
- [DRILL-5080] - Create a memory-managed version of the External Sort operator
- [DRILL-5085] - Add / update description for dynamic UDFs directories in drill-env.sh and drill-module.conf
- [DRILL-5098] - Improving fault tolerance for connection between client and foreman node.
- [DRILL-5108] - Reduce output from Maven git-commit-id-plugin
- [DRILL-5116] - Enable generated code debugging in each Drill operator
- [DRILL-5123] - Write query profile after sending final response to client to improve latency
- [DRILL-5126] - Provide simplified, unified "cluster fixture" for tests
- [DRILL-5172] - Display elapsed time for queries in the UI
- [DRILL-5195] - Publish Operator and MajorFragment Stats in Profile page
- [DRILL-5215] - CTTAS: disallow temp tables in view expansion logic
- [DRILL-5221] - cancel message is delayed until queryid or data is received
- [DRILL-5254] - Enhance default reduction factors in optimizer
- [DRILL-5255] - Unit tests fail due to CTTAS temporary name space checks
- [DRILL-5257] - Provide option to save query profiles sync, async or not at all
- [DRILL-5258] - Allow "extended" mock tables access from SQL queries
- [DRILL-5259] - Allow listing a user-defined number of profiles
- [DRILL-5260] - Refinements to new "Cluster Fixture" test framework
- [DRILL-5290] - Provide an option to build operator table once for built-in static functions and reuse it across queries.
- [DRILL-5301] - Add server metadata API
New Feature
- [DRILL-4935] - Allow drillbits to advertise a configurable host address to Zookeeper
- [DRILL-4979] - Make dataport configurable
Task
- [DRILL-5354] - Create CTTAS Documentaion


This is the landing page of the (to be built) Spotify App. Somehow, It will use the Spotify API to give you all your playlists & relted information as a CSV.
A good use case would be to uncouple your Spotify and Facebook accounts. Currently, you're forced to create a new account if you want to uncouple Spotify and Facebook, if you've created your Spotify Account using Facebook, which is the same mistake I made.
The downside if you delete your spotify account is, you'll lose all your playlists and saved music. So, besides giving you a .csv file of your playlists for your pleasure and convenience, this ncie little website / webapp will allow you to download all your playlists and upload them to your newly created user account.


Artificial Intelligence | Introduction to Robotics
Instructor: Khatib, Oussama
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The purpose of this course is to introduce you to basics of modeling, design, planning, and control of robot systems. In essence, the material treated in this course is a brief survey of relevant results from geometry, kinematics, statics, dynamics, and control.
The course is presented in a standard format of lectures, readings and problem sets. There will be an in-class midterm and final examination. These examinations will be open book. Lectures will be based mainly, but not exclusively, on material in the Lecture Notes book. Lectures will follow roughly the same sequence as the material presented in the book, so it can be read in anticipation of the lectures
Topics: robotics foundations in kinematics, dynamics, control, motion planning, trajectory generation, programming and design.
Prerequisites: matrix algebra. |
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| Oussama Khatib |
| Khatib's current research is in human-centered robotics, human-friendly robot design, dynamic simulations, and haptic interactions. His exploration in this research ranges from the autonomous ability of a robot to cooperate with a human to the haptic interaction of a user with an animated character or a surgical instrument. His research in human-centered robotics builds on a large body of studies he pursued over the past 25 years and published in over 200 contributions in the robotics field.
Prof. Khatib was the Program Chair of ICRA2000 (San Francisco) and Editor of ``The Robotics Review'' (MIT Press). He has served as the Director of the Stanford Computer Forum, an industry affiliate program. He is currently the President of the International Foundation of Robotics Research, IFRR, and Editor of STAR, Springer Tracts in Advanced Robotics. Prof. Khatib is IEEE fellow, Distinguished Lecturer of IEEE, and recipient of the JARA Award. |
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On 6 December 2016, the Ministry of Health (MoH) in Madagascar alerted WHO of a suspected plague outbreak in Befotaka district, Atsimo Atsinanana region in the south-eastern part of the country. The district is outside the area known to be endemic area in Madagascar. No plague cases have been reported in this area since 1950.
As of 27 December 2016, 62 cases (6 confirmed, 5 probable, 51 suspected) including 26 deaths (case fatality rate of 42%) have been reported in two adjacent districts in two neighbouring regions of the country. 28 cases, including 10 deaths have been reported from Befotaka District in Atsimo-Atsinanana Region and 34 cases including 16 deaths have been reported from Iakora district in Ihorombe Region.
Of the 11 samples tested, 5 were positive for plague on rapid diagnostic test and 6 are now confirmed at Institut Pasteur laboratory. Of the total reported cases, 5 are classified as pneumonic plague cases and the remaining as bubonic plague.
Retrospective investigations carried out in those two districts showed that it is possible that the outbreak might have started in mid-August 2016. The investigation in neighbouring villages is still ongoing. On 29 December, an investigation carried out within 25 km of the initial foci in Befotaka district has reported three deaths and is being investigated further for possible linkage to the outbreak.
The affected zone is located in a very remote and hard to reach and highly insecure area (classified as red zone due to local banditry). Despite arrangements made with the local authorities, insecurity slows down the investigations and response activities. In addition, a helicopter has been made available but its use has been limited due to bad weather and financial limitations.
On 6 December, a 15 member multidisciplinary team from MoH, Institute Pasteur including public health professional, epidemiologist, entomologist and laboratory professional visited the affected area for epidemiological investigation and response activities.
Key response activities already implemented include:
Based on the available information to date, the risk of international spread appears unlikely, especially as it is occurring in very remote area. However, the difficulty to reach the affected area hampered prompt investigation and therefore at this stage the real magnitude of the outbreak is still to be defined and the risk of further spread in the area and sustained transmission cannot be formally ruled out. WHO continues supporting ongoing investigation and response activities.
Further ecological investigations will be needed to understand the occurrence of a plague outbreak in an area which has not reported any cases of plague since 1950 in order to adapt long term surveillance and control measures.
The outbreak impacts rural communities which have already suffered from remoteness and inadequate access to health services. Staff from MoH are supported by Pasteur Institute of Madagascar, who are all experienced on control measures. However, local conditions make their implementation complex.
Due to the remoteness of the affected area and the conditions for getting infected by the disease, the current outbreak does not represent a significant risk for travellers.


pyfos_brocade_media
- PyFOS module to provide REST support for port sfp-rdp media.¶
The pyfos_brocade_media
module provides REST support for port sfp-rdp media.
-
class
pyfos_brocade_media.
media_rdp
(dictvalues={})¶ Class of Media rdp
Important Class Members:
Attribute Name Description Frequently Used Methods name The name of the port. peek_name()
identifier The media identifier. peek_identifier()
connector The connector type of the media. peek_connector()
media-speed-capability/speed The speed capability list supported by the media. peek_media_speed_capability_speed()
media-distance/distance The distance list supported by the media. peek_media_distance_distance()
encoding The encoding type of the media. peek_encoding()
vendor-oui The vendor OUI for the media. peek_vendor_oui()
part-number The part number of the media. peek_part_number()
serial-number The serial number of the media. peek_serial_number()
vendor-name The vendor name of the media. peek_vendor_name()
vendor-revision The vendor revision of the media. peek_vendor_revision()
date-code Manufacturing date of the media. peek_date_code()
temperature The temperature of the media. peek_temperature()
rx-power The rx power of the media. peek_rx_power()
tx-power The tx power of the media. peek_tx_power()
current The media current. peek_current()
voltage The media voltage. peek_voltage()
wavelength The media wavelength. peek_wavelength()
power-on-time The media power-on time. peek_power_on_time()
remote-identifier The remote media identifier. peek_remote_identifier()
remote-laser-type The remote media laser type. peek_remote_laser_type()
remote-media-speed-capability/ speed The speed capability list supported by the remote media. peek_remote_media_speed_capability_speed()
remote-media-temperature The remote media temperature. peek_remote_media_temperature()
remote-media-rx-power The remote media rx power. peek_remote_media_rx_power()
remote-media-tx-power The remote media tx power. peek_remote_media_tx_power()
remote-media-current The remote media current. peek_remote_media_current()
remote-media-voltage The remote media voltage. peek_remote_media_voltage()
remote-optical-product-data/ part-number Media part number in the remote optical product data group. peek_remote_optical_product_data_part_number()
remote-optical-product-data/ serial-number - Media serial number in the remote
- optical product data group.
peek_remote_optical_product_data_serial_number()
- remote-optical-product-data/
- vendor-name
Media vendor name in the remote optical product data group. peek_remote_optical_product_data_vendor_name()
remote-optical-product-data/ | Media vendor revision in the vendor-revision | remote optical product data group. peek_remote_optical_product_data_vendor_revision()
- remote-optical-product-data/
- date-code
Manufacturing date in the remote optical product data group. peek_remote_optical_product_data_date_code()
- remote-media-voltage-alert/
- high-alarm
High alarm in the remote media voltage alert group. peek_remote_media_voltage_alert_high_alarm()
- remote-media-voltage-alert/
- low-alarm
Low alarm in the remote media voltage alert group. peek_remote_media_voltage_alert_low_alarm()
- remote-media-voltage-alert/
- high-warning
High warning in the remote media voltage alert group. peek_remote_media_voltage_alert_high_warning()
- remote-media-voltage-alert/
- low-warning
Low warning in the remote media voltage alert group. peek_remote_media_voltage_alert_low_warning()
- remote-media-temperature-alert/
- high-alarm
High alarm in the remote media temperature alert group. peek_remote_media_temperature_alert_high_alarm()
- remote-media-temperature-alert/
- low-alarm
Low alarm in the remote media temperature alert group. peek_remote_media_temperature_alert_low_alarm()
- remote-media-temperature-alert/
- high-warning
High warning in the remote media temperature alert group. peek_remote_media_temperature_alert_high_warning()
- remote-media-temperature-alert/
- low-warning
Low warning in the remote media temperature alert group. peek_remote_media_temperature_alert_low_warning()
- remote-media-tx-bias-alert/
- high-alarm
High alarm in the remote media tx bias alert group. peek_remote_media_tx_bias_alert_high_alarm()
- remote-media-tx-bias-alert/
- low-alarm
Low alarm in the remote media tx bias alert group. peek_remote_media_tx_bias_alert_low_alarm()
- remote-media-tx-bias-alert/
- high-warning
High warning in the remote media tx bias alert group. peek_remote_media_tx_bias_alert_high_warning()
- remote-media-tx-bias-alert/
- low-warning
Low warning in the remote media tx bias alert group. peek_remote_media_tx_bias_alert_low_warning()
- remote-media-tx-power-alert/
- high-alarm
High alarm in the remote media tx power alert group. peek_remote_media_tx_power_alert_high_alarm()
- remote-media-tx-power-alert/
- low-alarm
Low alarm in the remote media tx power alert group. peek_remote_media_tx_power_alert_low_alarm()
- remote-media-tx-power-alert/
- high-warning
High warning in the remote media tx power alert group. peek_remote_media_tx_power_alert_high_warning()
- remote-media-tx-power-alert/
- low-warning
Low warning in the remote media tx power alert group. peek_remote_media_tx_power_alert_low_warning()
- remote-media-rx-power-alert/
- high-alarm
High alarm in the remote media rx power alert group. peek_remote_media_rx_power_alert_high_alarm()
- remote-media-rx-power-alert/
- low-alarm
Low alarm in the remote media rx power alert group. peek_remote_media_rx_power_alert_low_alarm()
- remote-media-rx-power-alert/
- high-warning
High warning in the remote media rx power alert group. peek_remote_media_rx_power_alert_high_warning()
- remote-media-rx-power-alert/
- low-warning
Low warning in the remote media rx power alert group. peek_remote_media_rx_power_alert_low_warning()
Object Methods
-
get
(session, name=None)¶ Returns a
media_rdp
object or a list of objects with the attributes gathered from port media. If an optional name is given, returns either an object matching the name of the port or an empty object with the corresponding error if no match is found.Each object can be printed using
pyfos_util.response_print()
, and individual attributes can be accessed through peek methods.Parameters: - session – The session handler returned by
pyfos_auth.login()
. - name – The interface slot port details in the format of interface/slot/port.
Return type: A
media_rdp
object if the name is provided or a list of objects if there is more than one.- session – The session handler returned by
Attribute Methods
-
peek_name
()¶ Reads the port name in the object.
Return type: None or the port name.
-
peek_identifier
()¶ Reads the media identifier.
Return type: None or the identifier.
-
peek_connector
()¶ Reads the connector type of the media.
Return type: None or the connector type.
-
peek_media_speed_capability_speed
()¶ Reads a list of supported speed capabilities of the media.
Return type: None or a list of speeds.
-
peek_media_distance_distance
()¶ Reads a list of distance media support.
Return type: None or a list of distance media.
-
peek_encoding
()¶ Reads the supported encoding type of the media.
Return type: None or the encoding type.
-
peek_vendor_oui
()¶ Reads the vendor OUI of the media.
Return type: None or the vendor OUI.
-
peek_part_number
()¶ Reads the part number of the media.
Return type: None or the part number.
-
peek_serial_number
()¶ Reads the serial number of the media.
Return type: None or the serial number.
-
peek_vendor_name
()¶ Reads the vendor name of the media.
Return type: None or the vendor name.
-
peek_vendor_revision
()¶ Reads the vendor revision of the media.
Return type: None or the vendor revision.
-
peek_date_code
()¶ Reads the manufacturing date of the media.
Return type: None or the manufacturing date code.
-
peek_temperature
()¶ Reads the temperature of the media.
Return type: None or the temperature.
-
peek_tx_power
()¶ Reads the tx power of the media.
Return type: None or the tx power.
-
peek_rx_power
()¶ Reads the rx power of the media.
Return type: None or the rx power.
-
peek_current
()¶ Reads the media current.
Return type: None or the current.
-
peek_voltage
()¶ Reads the media voltage.
Return type: None or the voltage.
-
peek_wavelength
()¶ Reads the media wavelength.
Return type: None or the wavelength.
-
peek_power_on_time
()¶ Reads the media power on time.
Return type: None or the power on time.
-
peek_remote_identifier
()¶ Reads the remote media identifier.
Return type: None or the remote identifier.
-
peek_remote_laser_type
()¶ Reads the remote media laser type.
Return type: None or the laser type.
-
peek_remote_media_speed_capability_speed
()¶ Reads a list of remote media capable speeds.
Return type: None or the laser type.
-
peek_remote_media_temperature
()¶ Reads the remote media temperature.
Return type: None or the temperature.
-
peek_remote_media_tx_power
()¶ Reads the tx power of the remote media.
Return type: None or the tx power.
-
peek_remote_media_rx_power
()¶ Reads the rx power of the remote media.
Return type: None or the rx power.
-
peek_remote_media_current
()¶ Reads the remote media current.
Return type: None or the current.
-
peek_remote_media_voltage
()¶ Reads the remote media voltage.
Return type: None or the voltage.
-
peek_remote_optical_product_data_part_number
()¶ Reads the remote media part number.
Return type: None or the part number.
-
peek_remote_optical_product_data_serial_number
()¶ Reads the remote media serial number.
Return type: None or the serial number.
-
peek_remote_optical_product_data_vendor_name
()¶ Reads the remote media vendor name.
Return type: None or the vendor name.
-
peek_remote_optical_product_data_vendor_revision
()¶ Reads the remote media vendor revision.
Return type: None or the vendor revision.
-
peek_remote_optical_product_data_date_code
()¶ Reads the remote media manufacturing date.
Return type: None or the date code.
-
peek_remote_media_voltage_alert_high_alarm
()¶ Reads the high alarm in the voltage alert object.
Return type: None or the high alarm.
-
peek_remote_media_voltage_alert_low_alarm
()¶ Reads the low alarm in the voltage alert object.
Return type: None or the low alarm.
-
peek_remote_media_voltage_alert_high_warning
()¶ Reads the high warning in the voltage alert object.
Return type: None or the high warning.
-
peek_remote_media_voltage_alert_low_warning
()¶ Reads the low warning in the voltage alert object.
Return type: None or the low warning.
-
peek_remote_media_temperature_alert_high_alarm
()¶ Reads the high alarm in the temperature alert object.
Return type: None or the high alarm.
-
peek_remote_media_temperature_alert_low_alarm
()¶ Reads the low alarm in the temperature alert object.
Return type: None or the low alarm.
-
peek_remote_media_temperature_alert_high_warning
()¶ Reads the high warning in the temperature alert object.
Return type: None or the high warning.
-
peek_remote_media_temperature_alert_low_warning
()¶ Reads the low warning in the temperature alert object.
Return type: None or the low warning.
-
peek_remote_media_tx_bias_alert_high_alarm
()¶ Reads the high alarm in the tx bias alert object.
Return type: None or the high alarm
-
peek_remote_media_tx_bias_alert_low_alarm
()¶ Reads the low alarm in the tx bias alert object.
Return type: None or the low alarm.
-
peek_remote_media_tx_bias_alert_high_warning
()¶ Reads the high warning in the tx bias alert object.
Return type: None or the high warning.
-
peek_remote_media_tx_bias_alert_low_warning
()¶ Reads the low warning in the tx bias alert object.
Return type: None or the low warning.
-
peek_remote_media_tx_power_alert_high_alarm
()¶ Reads the high alarm in the tx power alert object.
Return type: None or the high alarm.
-
peek_remote_media_tx_power_alert_low_alarm
()¶ Reads the low alarm in the tx power alert object.
Return type: None or the low alarm.
-
peek_remote_media_tx_power_alert_high_warning
()¶ Reads the high warning in the tx power alert object.
Return type: None or the high warning.
-
peek_remote_media_tx_power_alert_low_warning
()¶ Reads the low warning in the tx power alert object.
Return type: None or the low warning.
-
peek_remote_media_rx_power_alert_high_alarm
()¶ Reads the high alarm in the rx power alert object.
Return type: None or the high alarm.
-
peek_remote_media_rx_power_alert_low_alarm
()¶ Reads the low alarm in the rx power alert object.
Return type: None or the low alarm.
-
peek_remote_media_rx_power_alert_high_warning
()¶ Reads the high warning in the rx power alert object.
Return type: None or the high warning.
-
peek_remote_media_rx_power_alert_low_warning
()¶ Reads the low warning in the rx power alert object.
Return type: None or the low warning.
See also
Module pyfos_auth


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