--- layout: archive title: Zulip Chat Archive permalink: /stream/113488-general/topic/uniform_add_group.20vs.20topological_add_group.html ---
We know that a topological additive abelian group is a uniform additive group, and that a uniform additive group is a topological additive group
but which one of them should be an instance? @Kevin Buzzard @Mario Carneiro
if they are equivalent, then they should be the same
(I have a preference for the topological terminology)
a topological additive group is based on a topological space and an additive group; a uniform additive group is based on a uniform space and an additive group
they can't be the same, right
A topological add group has a uniform structure
so it's both
but that would cause a loop in the inferrence
how?
I'm saying delete uniform add group and replace it with top add group
aha
now?
Actually I guess this is already how uniform_add_group is defined
so it's just a rename
well, currently we have:
class uniform_add_group (α : Type u) [uniform_space α] [add_group α] : Prop := (uniform_continuous_sub : uniform_continuous (λp:α×α, p.1 - p.2))
maybe you don't need uniform continuity
oh, it's a predicate
@Johannes Hölzl will object, but I want it to be a class
indeed it is Hoelzl who introduced uniform add groups, at least according to this
oh, wait we do need uniform continuity
Is the uniformity of a uniform add group uniquely defined?
Topological groups actually have two induced uniformities, the left and right uniformity
so topological add group and uniform add group aren't exactly the same
a uniform add group comes with a chosen uniformity, a top add group doesn't
so what should I do?
@Kevin Buzzard what do you think about this?
This is an implementation issue and I have no idea.
I will comment though that with something like the Haar measure on a locally compact Hausdorff topological group, there are two: a left Haar measure and a right Haar measure, but mathematicians often just talk about "the Haar measure" and they have just randomly chosen one of them.
But these are additive groups, which should always be abelian, and then the uniformities coincide.
No -- Haar measure doesn't need abelian. It's Pontrjagin duality which needs abelian
Sure, I know that. Infinite Galois groups have Haar measures...
So I think my point is: in the non-commutative case we don't want an instance from topological_group
to uniform_group
because in that case we want the user to explicitly say "Use the left uniformity" (or "use the left Haar measure", etc...). But in the commutative case, the left and right uniformity agree (just as with Haar measures), so it would make sense if the system could automatically pick one. But then we get diamond issues, and maybe it is just not worth it.
Oh I see! Sorry :-) What I'm suggesting is that we always use the left one.
I was also confused by uniform_add_group in the beginning, and wanted to get rid of it and keep topological add groups. But then I had this completion diamond issue, and Johannes fixed it by using more uniform_add_group...
@Patrick Massot @Kevin Buzzard the problem is that I'm cleaning up the perfectoid project in which you have an instance of topological add comm group -> uniform add group
which messes up everything
How much breaks if you remove that instance?
Everything about topological rings in the perfectoid project has been merged into mathlib, you can get rid of everything
I don't think it's everything
here's what is left of for_mathlib/uniform_space.lean
:
import analysis.topology.completion import analysis.topology.uniform_space namespace uniform_space variables {α : Type*} [uniform_space α] {β : Type*} [uniform_space β] {γ : Type*} [uniform_space γ] open Cauchy set def pure_cauchy₂ : α × β → Cauchy α × Cauchy β := λ x, (pure_cauchy x.1, pure_cauchy x.2) lemma pure_cauchy_dense₂ : ∀x : Cauchy α × Cauchy β, x ∈ closure (range (@pure_cauchy₂ α _ β _)) := begin intro x, dsimp[pure_cauchy₂], rw [←prod_range_range_eq, closure_prod_eq], simp[prod.ext_iff, pure_cauchy_dense], end namespace pure_cauchy lemma prod.de : dense_embedding (λ p : α × β, (pure_cauchy p.1, pure_cauchy p.2)) := dense_embedding.prod dense_embedding_pure_cauchy dense_embedding_pure_cauchy end pure_cauchy end uniform_space
Are those lemmas used elsewhere in the perfectoid project?
I don't know
You can remove this.
{% endraw %}Last updated: Apr 24 2020 at 19:02 UTC


Mahathir’s ruling party crushed in by-election in Johor
- Advertisement -
The opposition Barisan Nasional defeated the ruling Pakatan Harapan in a by-election in Johor, wrestling the parliamentary seat with a 15,000 majority.
The BN rep Wee Jeck Seng registered a whopping 25,466 votes to the PH’s candidate Karmaine Sardini’s 10,380 votes. PH won the seat last year but the incumbent MP succumbed to a heart attack last month.
The Tanjung Piai by-election is seen as a referendum on Prime Minister Dr Mahathir Mohamad’s leadership, said a former deputy president of Anwar Ibrahim’s party, Syed Husin Ali.
Anwar heads the PKR which stands for People’s Justice Party in English. The seat was contested by a member of Dr Mahathir’s party, the Bersatu.
- Advertisement -
Syed Husin Ali says the message is loud and clear and Dr M should step down because he has to take responsibility for the severe defeat.
“The results are clear. The people are disappointed and want to teach Harapan, especially Dr M (a lesson),” he tweeted after it became clear BN was headed for a landslide victory.
“He (Mahathir) knows what should be done with immediate effect. Don’t delay it any longer.
“A large number of the rakyat (people) are unhappy with Mahathir’s leadership which has slid to his and Umno’s old ways.”
He said the people expected changes but they are slow in coming and the people spoke at Tanjung Piai.
Tanjung Piai is one of the rare time Dr Mahathir campaigned personally in favour of PH candidate Karmaine.
The latter is a Muslim religious figure, and he was defeated by a Chinese from the Malaysian Chinese Association in a shift of votes in the constituency.
The irony is the Barisan candidate got the backing of the Islamists from the PAS who last year canvassed Muslim voters not to vote for non-Muslims in an election.
This time around, they said it was the duty of the Muslims to punish the PH and vote for an ethnic Chinese instead.
On top of that, ex-PM Najib Razak was also hot on the trails in the campaign supporting the BN candidate.
- Advertisement -


Detection of differentially included nodes¶
Congratulations if you have reached this point! This is the final step of the analysis :). To achieve the aim of determining the effect of bam mutation
you just need to run whippet with the following syntax.
julia {path_bin}/whippet-delta.jl -a sample1.psi.gz,sample1.psi.gz,sample1.psi.gz -b sample4.psi.gz,sample5.psi.gz,sample6.psi.gz -o {output_basename}
- Where:
{path_bin}
needs to be replaced by the path to find thewhippet-delta.jl
script.-a
/-b
are input a comma-separated list the.psi.gz
files obtained for each condition.{output_basename}
should be replaced by any desired output name.
Challenge 3
Run the this command over your samples!
Challenge 4
Find on Whippet’s documentation about the obtained results. Particularly focus on interpreting the last file obtained .diff.gz
file. According to this, answer the following questions:
How many differentially included nodes did you find? (See documentation to find recommendations from the authors)
How many of them might be biologically relevant based on DeltaPsi obtained values?
What type of alternative splicing node are the ones found significantly different and biologically relevant
bam mutation
?
Challenge 5
Important part of the job as bioinformatician is to inspect the obtained results using a genome browser. In this case, the one of the best way to assess the results is by visual inspection:
Use the IGV to generate sashimi plots that allow you to evaluate the changes if the changes in splicing after
bam mutation
looks convincing.According to the quantitative and qualitative results you have generated at this point, if you have to just choose one example to experimentally validate as AS event that is regulated during spermatogenesis, which one would you choose? Why?


Class ServiceProxy
Wrapper class that uses a Daemon to send and receive messages to other services
Inherited Members
Namespace: chia.dotnet
Assembly: chia-dotnet.dll
Syntax
public class ServiceProxy
Remarks
The lifetime of the daemon is not controlled by the proxy. It should be disposed outside of this class. Connect(CancellationToken)
Constructors
| Improve this Doc View SourceServiceProxy(Daemon, String)
ctor
Declaration
public ServiceProxy(Daemon daemon, string destinationService)
Parameters
| Type | Name | Description |
|---|---|---|
| Daemon | daemon | Daemon instance to use for rpc communication |
| String | destinationService |
Properties
| Improve this Doc View SourceDaemon
The Daemon used for underlying RPC
Declaration
public Daemon Daemon { get; set; }
Property Value
| Type | Description |
|---|---|
| Daemon |
DestinationService
Declaration
public string DestinationService { get; set; }
Property Value
| Type | Description |
|---|---|
| String |
Methods
| Improve this Doc View SourceCreateMessage(String, Object)
Constructs a Message instance with Destination and Origin set from DestinationService and OriginService
Declaration
protected Message CreateMessage(string command, dynamic data)
Parameters
| Type | Name | Description |
|---|---|---|
| String | command | The command to send |
| Object | data | Data to send with the command |
Returns
| Type | Description |
|---|---|
| Message |


{%extends 'base.html'%} {% load bootstrap3 %}
Location{{neighborhood.location}}
Count{{neighborhood.occupants_count}}


Please sideload your add-in to see app body.
Search By
Search Text
No case found!
Case Id
Subject
Send mail content to Appian
Send attachment(s) to Appian


@*
* Copyright 2023 HM Revenue & Customs
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*@
@import uk.gov.hmrc.fhregistrationfrontend.models.businessregistration.BusinessRegistrationDetails
@import uk.gov.hmrc.fhregistrationfrontend.views.html.summary._
@import uk.gov.hmrc.fhregistrationfrontend.views.html.helpers._
@import uk.gov.hmrc.fhregistrationfrontend.forms.models.{LimitedCompanyApplication,SoleProprietorApplication,PartnershipApplication,BusinessEntityApplication}
@import uk.gov.hmrc.fhregistrationfrontend.views.Mode.ReadOnlyApplication
@(applicationData: BusinessEntityApplication, bpr: BusinessRegistrationDetails, verifiedEmail: String)(implicit messages: Messages)
@{
applicationData match {
case limitedCompanyApplication: LimitedCompanyApplication =>
Html(EmailAddress(verifiedEmail, ReadOnlyApplication).toString() +
ContactPerson(limitedCompanyApplication.contactPerson, bpr, ReadOnlyApplication).toString() +
MainBusinessAddress(limitedCompanyApplication.mainBusinessAddress, ReadOnlyApplication).toString() +
SummarySectionHead(heading = Messages("fh.summary.businessDetails")).toString() +
"
" +
CompanyRegistrationNumber(limitedCompanyApplication.companyRegistrationNumber, ReadOnlyApplication).toString() +
DateOfIncorporation(limitedCompanyApplication.dateOfIncorporation, ReadOnlyApplication).toString() +
TradingName(limitedCompanyApplication.tradingName, ReadOnlyApplication).toString() +
VATRegistrationNumber(limitedCompanyApplication.vatNumber, ReadOnlyApplication).toString() +
CompanyOfficers(limitedCompanyApplication.companyOfficers, ReadOnlyApplication).toString() +
"
" +
SummarySectionHead(heading = Messages("fh.summary.businessActivities")).toString() +
"" +
BusinessStatus(limitedCompanyApplication.businessStatus, ReadOnlyApplication).toString() +
ImportingActivities(limitedCompanyApplication.importingActivities, ReadOnlyApplication).toString() +
BusinessCustomers(limitedCompanyApplication.businessCustomers, ReadOnlyApplication).toString() +
OtherStoragePremises(limitedCompanyApplication.otherStoragePremises, ReadOnlyApplication).toString() +
"
"
)
case soleProprietorApplication: SoleProprietorApplication =>
Html(
EmailAddress(verifiedEmail, ReadOnlyApplication).toString() +
ContactPerson(soleProprietorApplication.contactPerson, bpr, ReadOnlyApplication).toString() +
MainBusinessAddress(soleProprietorApplication.mainBusinessAddress, ReadOnlyApplication).toString() +
SummarySectionHead(heading = Messages("fh.summary.businessDetails")).toString() +
"" +
NationalInsurance(soleProprietorApplication.nationalInsuranceNumber, ReadOnlyApplication).toString() +
TradingName(soleProprietorApplication.tradingName, ReadOnlyApplication).toString() +
VATRegistrationNumber(soleProprietorApplication.vatNumber, ReadOnlyApplication).toString() +
"
" +
SummarySectionHead(heading = Messages("fh.summary.businessActivities")).toString() +
"" +
BusinessStatus(soleProprietorApplication.businessStatus, ReadOnlyApplication).toString() +
ImportingActivities(soleProprietorApplication.importingActivities, ReadOnlyApplication).toString() +
BusinessCustomers(soleProprietorApplication.businessCustomers, ReadOnlyApplication).toString() +
OtherStoragePremises(soleProprietorApplication.otherStoragePremises, ReadOnlyApplication).toString() +
"
"
)
case partnershipApplication: PartnershipApplication =>
Html(
EmailAddress(verifiedEmail, ReadOnlyApplication).toString() +
ContactPerson(partnershipApplication.contactPerson, bpr, ReadOnlyApplication).toString() +
MainBusinessAddress(partnershipApplication.mainBusinessAddress, ReadOnlyApplication).toString() +
SummarySectionHead(heading = Messages("fh.summary.businessDetails")).toString() +
"" +
TradingName(partnershipApplication.tradingName, ReadOnlyApplication).toString() +
VATRegistrationNumber(partnershipApplication.vatNumber, ReadOnlyApplication).toString() +
BusinessPartners(partnershipApplication.businessPartners, ReadOnlyApplication).toString() +
"
" +
SummarySectionHead(heading = Messages("fh.summary.businessActivities")).toString() +
"" +
BusinessStatus(partnershipApplication.businessStatus, ReadOnlyApplication).toString() +
ImportingActivities(partnershipApplication.importingActivities, ReadOnlyApplication).toString() +
BusinessCustomers(partnershipApplication.businessCustomers, ReadOnlyApplication).toString() +
OtherStoragePremises(partnershipApplication.otherStoragePremises, ReadOnlyApplication) +
"
"
)
}
}


A restaurant or an eatery, is a business which prepares and serves food and drinks to customers in exchange for money. Meals are generally served and eaten on the premises, but many restaurants also offer take-out and food delivery services, and some offer only take-out and delivery. Restaurants vary greatly in appearance and offerings, including a wide variety of cuisines and service models ranging from inexpensive fast food restaurants and cafeterias to mid-priced family restaurants, to high-priced luxury establishments.


|
Elma
An event loop manager for embedded systems
|
A channel for sending double values to and from Process objects. More...
#include <channel.h>
Public Member Functions | |
| Channel (string name) | |
| Channel (string name, int capacity) | |
| Channel & | send (json) |
| Channel & | flush () |
| json | latest () |
| json | earliest () |
| int | size () |
| bool | empty () |
| bool | nonempty () |
| string | name () |
| int | capacity () |
A channel for sending double values to and from Process objects.
Here is an example that uses channels that enables a model of a car and a simple cruise controller to communicate.
|
inline |
|
inline |
|
inline |
| json elma::Channel::earliest | ( | ) |
Get the oldest value. Throws an error if the channel is empty.
Definition at line 38 of file channel.cc.
|
inline |
| Channel & elma::Channel::flush | ( | ) |
Clear the channel, deleting all values in it
Definition at line 20 of file channel.cc.
| json elma::Channel::latest | ( | ) |
Get the newest value. Throws an error if the channel is empty.
Definition at line 28 of file channel.cc.
|
inline |
|
inline |
| Channel & elma::Channel::send | ( | json | value | ) |
Send a value
| value | The value to send into the channel |
Definition at line 10 of file channel.cc.
|
inline |


  Retirement based on your age This will normally be your 60th Birthday. Early payment of deferred pension benefit. Early payment of deferred benefits are available to you at the age of: 50 – 60 if you joined the scheme between 01/04/2000 and 05/04/2006 and you had a break in service of less than 5 years 55 – 60 if joined the scheme on or after 06/04/2006 55 - 60 if you had a break in service of 5 years or more, then re-joined the scheme on or after 06/04/2006 Early payment of deferred benefits because of ill health You can only choose this option if you’re under 60 and your ill health application has been approved by the Scheme’s medical advisors Commuted early payment of pension benefits because of ill health You can only choose this option if: you’re under 60 and your ill health application has been approved by the Scheme’s medical advisors' joined the NHS Pension Scheme on or after 06/03/1995 you take this benefit as a lump sum If you don’t have this information available, you can return to your application summary and save your application for later. {% endblock %}
Claim your NHS Pension
This will normally be your 60th Birthday.
Early payment of deferred benefits are available to you at the age of:
You can only choose this option if you’re under 60 and your ill health application has been approved by the Scheme’s medical advisors
You can only choose this option if:
If you don’t have this information available, you can return to your application summary and save your application for later.


--- title: "Plants that Heal | Cancer Fighting Flora" layout: "default" ---
The active compound in many medicines were originally found in plants. Common practice is to name the medicine after the plant it comes from. Below are several examples of plants and the active compounds they contain that are used in cancer medicines.
When you visit the Medicinal Garden at Red Butte Garden, look for the grey plant identification signs located near the plants to learn more about these and other plants.
Common Name: Barberry
Active Compound: Berberine
Common Name: Gotu Kola
Active Compound: Asiaticoside
Common Name: Autumn Crocus
Active Compound: Colchicine
Common Name: Winter Jasmine
Active Compound: Methyl Jasmonate
Common Name: Mayapple
Active Compound: Podophyllin
Common Name: Pacific Yew and English Yew
Active Compound: Taxol and 10-deacetylbaccatine III
Common Name: Heart-leaved Moonseed
Active Compound: Tinosporin
Common Name: Ashwaganda
Active Compound: Withanolide and Withaferin
This website does not provide medical advice. This site is for information purposes only. Any medical information on this site is not intended to be a substitute for professional medical advice, diagnosis, or treatment. Always seek the advice of your physician or other qualified health provider with any questions you may have regarding a medical condition.


--- permalink: /about/ layout: default title: About pagetitle: 'About the author' ---
I'm currently studying for my master's degree at the Hasso Plattner Institute in the IT Systems Engineering program and am working my master's thesis.
My full name is Cornelia Rehbein. Born and raised in Frankfurt Oder, Germany, I graduated from the Hasso Plattner Institut with a B.Sc. degree and am now working towards a M.Sc. degree in IT Systems Engineering. My resume is available on LinkedIn.
I've worked as a research assistant on projects involving 3D Point Clouds, 3D Point Cloud Analysis and 3D Model Generalization at the institute. Between 2011 and 2012, I interned at SAP Labs in Palo Alto, California for a year where I developed applications for mobile devices. At the moment, I am working on a research project that involves natural language query processing.
In general, I am more interested in front-end development than backend, but I experienced both sites. I currently enjoy building mobile applications and user-facing web apps. Recently, I've also become interested in natural language processing. Most of my time is spent on personal projects, on github and on reddit and twitter.


A current–voltage characteristic or I–V curve (current–voltage curve) is a relationship, typically represented as a chart or graph, between the electric current through a circuit, device, or material, and the corresponding voltage, or potential difference across it.


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One of the famous proofs of modern mathematics is Georg Cantor's demonstration that the set of rational numbers is enumerable. The proof works by using an explicit enumeration of rational numbers as shown in the diagram below.
1/1 1/2 1/3 1/4 1/5 ... 2/1 2/2 2/3 2/4 3/1 3/2 3/3 4/1 4/2 5/1
In the above diagram, the first term is 1/1, the second term is 1/2, the third term is 2/1, the fourth term is 3/1, the fifth term is 2/2, and so on.
The input starts with a line containing a single integer t <= 20, the number of test cases. t test cases follow.
Then, it contains a single number per line.
You are to write a program that will read a list of numbers in the range from 1 to 10^7 and will print for each number the corresponding term in Cantor's enumeration as given below.
Input: 3 3 14 7 Output: TERM 3 IS 2/1 TERM 14 IS 2/4 TERM 7 IS 1/4


|
James Traficant, age 61, is now incarcerated at the Allenwood Federal Corrections Institution. Registered as Inmate Number 31213-060, he is scheduled for release on July 17, 2009. Persons wishing to write to Mr. Traficant should address their letters to: Mr. James Traficant #31213-060 F.C.I. Allenwood P.O. Box 1500 White Deer, Pennsylvania 17887 Phone:<PHONE_NUMBER> - Fax:<PHONE_NUMBER> |


Great Deal: Get the brand new Surface Pro 7 with Black Pro Type Cover for just $599
by PradeepMicrosoft generally will not sell its newest Surface products at discount for first few months. It looks like the new Surface Pro 7 device is an exception. Microsoft Store is now selling Platinum Surface Pro 7 + Black Pro Type Cover Bundle for just $599 ($280 discount). This bundle includes Surface Pro 7 device with 12.3-inch touch display, Intel Core i3-1005G1 processor and 4GB memory/128GB SSD.
Last month, Microsoft announced the new Surface Pro 7 device, powered by the 10th Generation Intel Core processors. In addition to the new processors for improved performance, the Surface Pro 7 now comes with an USB-C port and support for Fast Charging.
Find the deal here from Microsoft Store.


Invisible.JS is a text to binary conversion tool...
but, you can change the values for 1 and 0 to whatever you want. For
example, if you make 1 a SPACE
character and 0 a
TAB
character you can then encode your message and the
result will be invisible!
Try it out on this Haiku !


--- title: Flipping your Way to Freedom author: ~ date: '2020-05-05' slug: flipping-your-way-to-freedom categories: [] tags: [riddler, puzzles] subtitle: 'Simulations, logic, and some calculus!' summary: "" authors: [] lastmod: '2020-05-05T08:46:45-07:00' featured: no image: caption: '' focal_point: '' preview_only: yes projects: [] ---
In this post, we will solve a classic puzzle from the Riddler. We will use R to simulate the puzzle and build some intuition, and then use good old calculus to compute a closed form solution to the problem!
From Bart Wright comes a rhetorical question from a famed soliloquy, “To flip, or not to flip?”:
You are locked in the dungeon of a faraway castle with three fellow prisoners (i.e., there are four prisoners in total), each in a separate cell with no means of communication. But it just so happens that all of you are logicians (of course).
To entertain themselves, the guards have decided to give you all a single chance for immediate release. Each prisoner will be given a fair coin, which can either be fairly flipped one time or returned to the guards without being flipped. If all flipped coins come up heads, you will all be set free!
The only tools you and your fellow prisoners have to aid you are random number generators, which will give each prisoner a random number, uniformly and independently chosen between zero and one.
What are your chances of being released?
Extra credit: Instead of four prisoners, suppose there are N prisoners. Now what are your chances of being released?
This blog uses http://hypothes.is for enabling inline comments. You can highlight any line of text and click to annotate. You will need to sign up for an account with hypothes.is. You can also use this to take private notes! Let us first try to understand the state of policies available to the prisoners. Since the only mechanism available is a random number generator, any policy would have to depend on the number generated. Moreover, the prisoner would need to decide whether or not to flip a coin based on this number.
Without any loss of generality, we can assume that prisoner \(i\) decides to flip a coin if the random number generated is less than \(\theta_i\). Since the prisoners cannot communicate with each other, the only optimal policy that exists is \(\theta_1 = \theta_2 = ... \theta\).
We can now simulate the impact of this policy on the probability of freedom as a function of the number of prisoners, and the threshold \(\theta\).
simulate_policy <- function(theta = 0.5, nb_prisoners = 4) {
# Generate random numbers for all prisoners
x <- runif(nb_prisoners)
# Toss if x > theta: N = No Toss, H = Head, T = Tail
tosses <- ifelse(x < theta, "N", sample(c("H", "T"), nb_prisoners, replace = TRUE))
# Freedom: #H > 0 and #T == 0
sum(tosses == "H") > 0 && sum(tosses == "T") == 0
}
mean(replicate(1000, simulate_policy()))
#> [1] 0.246
Now that we have a function to simulate the policy, we can use it to compute the
outcome for a number of trials across different values of theta
and
nb_prisoners
. The easiest way to do this is to create a grid of values using
expand.grid
and apply the function simulate_policy
to compute the outcome of
the trial.
NB_TRIALS <- 10^4
simulations <- expand.grid(
id_trial = 1:NB_TRIALS,
theta = seq(0, 1, 0.01),
nb_prisoners = 4:10
) %>%
mutate(is_free = map2_lgl(theta, nb_prisoners, simulate_policy))
simulations
#> id_trial theta nb_prisoners is_free
#> 1 1 0 4 0
#> 2 2 0 4 0
#> 3 3 0 4 0
#> 4 4 0 4 0
#> 5 5 0 4 0
#> 6 6 0 4 0
We can summarize the simulated outcomes across theta
and nb_prisoners
and
plot them.
outcomes <- simulations %>%
group_by(theta, nb_prisoners) %>%
summarize(prob_free = mean(is_free))
outcomes %>%
mutate(nb_prisoners = factor(nb_prisoners)) %>%
ggplot(aes(x = theta, y = prob_free, color = nb_prisoners)) +
geom_smooth(se = FALSE, span = 0.2) +
geom_point(alpha = 0.5) +
geom_hline(yintercept = 0.25, linetype = "dashed", color = "gray20") +
guides(colour = guide_legend(nrow = 1)) +
labs(
title = "Probability of freedom",
subtitle = "",
x = "Probability of NOT flipping a coin",
y = "",
color = "Number of prisoners"
) +
theme(plot.title.position = "plot")
Note that I use geom_smooth
to plot the curve and overlay the points on top of
it. This provides a better approximation of behavior since we are only
simulating N = 10^4 trials.
😀 You can click on any of the plots to view an enlarged version!
We can now recover the approximate probabilities of freedom and plot it as a function of the number of prisoners. Note how the probabilities seem to be really close to each other and around 25%.
outcomes %>%
group_by(nb_prisoners) %>%
filter(prob_free == max(prob_free)) %>%
ungroup() %>%
ggplot(aes(x = nb_prisoners, y = prob_free)) +
geom_col(fill = "purple", color = NA) +
geom_hline(yintercept = 0.25, linetype = "dashed") +
labs(
title = "Probability of freedom",
subtitle = "",
x = "Number of prisoners",
y = ""
) +
theme(plot.title.position = "plot")
Maybe, we can solve this problem exactly without simulations. Let N denote the event that a prisoner does not flip the coin, and \(\theta\) be the probability of this event. The only scenario under which the prisoners end up being free is when none of them toss a tail, and all of them don’t end up NOT tossing. Hence, we can now compute the probability of freedom as:
\[ \begin{aligned} P(Freedom) &= P(T^cT^cT^c...T^c) - P(NNN...N) \\ &= \Big(\frac{1+\theta}{2}\Big)^n - \theta^n \end{aligned} \]
Now that we have a closed form expression for the probability of freedom, we can
turn this into an R function and use the optimize()
function to compute the
optimal values.
prob_freedom <- function(n = 4) {
function(theta) {
((1 + theta) / 2)^n - theta^n
}
}
optimize(prob_freedom(4), c(0, 1), maximum = TRUE)
#> $maximum
#> [1] 0.6579609
#>
#> $objective
#> [1] 0.2848424
We can extend this approach to compute the optimal probability of freedom across a range of values for the number of prisoners.
We use unnest_longer
to unpack the list of values returned by optimize()
.
The tidyr
package is full of such utility functions!
optimal_values <- data.frame(nb_prisoners = 1:30) %>%
mutate(prob_free = map(nb_prisoners, ~ {
optimize(prob_freedom(.x), c(0, 1), maximum = TRUE)
})) %>%
tidyr::unnest_longer(prob_free)
head(optimal_values)
#> # A tibble: 6 x 3
#> nb_prisoners prob_free prob_free_id
#> <int> <dbl> <chr>
#> 1 1 0.0000661 maximum
#> 2 1 0.500 objective
#> 3 2 0.333 maximum
#> 4 2 0.333 objective
#> 5 3 0.547 maximum
#> 6 3 0.299 objective
optimal_values %>%
ggplot(aes(x = nb_prisoners, y = prob_free, color = prob_free_id)) +
geom_line(size = 1.5) +
geom_hline(yintercept = c(0.25, 0.96), linetype = "dashed", color = "gray40") +
scale_color_discrete(
labels = c("Not Flipping Coin", "Freedom")
) +
labs(
title = "Probability of freedom",
subtitle = "",
x = "Number of prisoners",
y = "Probability",
color = ""
) +
theme(
plot.title.position = "plot"
)
It seems like the probabilities of freedom, and NOT flipping the coin converge asymptotically to the values 0.25 and 0.96 respectively. It would be interesting if we can prove this result mathematically!
Let us take the derivative of the probability function and see if we can derive a closed form expression for the optimal value of \(\theta\), by setting the derivative to zero. Let \(P(\theta)\) represent the probability of freedom. Recall that we can express it as:
\[ P(\theta) = \Big(\frac{1 + \theta}{2}\Big)^{n} - \theta^n \] The first derivative can be written down as:
\[ P^{'}(\theta) = 2^{-n} n(1 + \theta)^{n - 1} - n\theta^{n-1} \]
Solving for \(P^{'}(\theta) = 0\), we get
\[ \theta_{opt} = \Big[\exp\big(\frac{n\log(2)}{n - 1}\big) - 1\Big]^{-1} \]
Voila! That is a really beautiful result!! Plugging the optimal value of \(\theta\), we can write down the probability of freedom as:
\[ P(\theta_{opt}) = \Big[\exp\big(\frac{n\log(2)}{n - 1}\big) - 1\Big]^{-n} \]
I must admit that by the time I came to this part of the derivation, I got lazy and used WolframAlpha to compute the limits for me!
Computing the limit of this probability, as \(n \to \infty\), we get:
\[ \lim_{n \to \infty}\Big[\exp\big(\frac{n\log(2)}{n - 1}\big) - 1\Big]^{-n} = \frac{1}{4} \]
Let us now use this exact expression and plot the probabilities of freedom and not deciding to toss the coin.


2. Supervised learning: predicting an output variable from high-dimensional observations¶
The problem solved in supervised learning
Supervised learning consists in learning the link between two datasets: the observed data X, and an external variable y that we are trying to predict, usually called target or labels. Most often, y is a 1D array of length n_samples.
All supervised estimators in the scikit-learn implement a fit(X, y) method to fit the model, and a predict(X) method that, given unlabeled observations X, returns predicts the corresponding labels y.
Vocabulary: classification and regression
If the prediction task is to classify the observations in a set of finite labels, in other words to “name” the objects observed, the task is said to be a classification task. On the opposite, if the goal is to predict a continous target variable, it is said to be a regression task.
In the scikit-learn, for classification tasks, y is a vector of integers.
Note: See the Introduction to machine learning with Scikit-learn Tutorial for a quick run-through on the basic machine learning vocabulary used within Scikit-learn.
2.1. Nearest neighbor and the curse of dimensionality¶
Classifying irises:
The iris dataset is a classification task consisting in identifying 3 different types of irises (Setosa, Versicolour, and Virginica) from their petal and sepal length and width:
>>> import numpy as np
>>> from sklearn import datasets
>>> iris = datasets.load_iris()
>>> iris_X = iris.data
>>> iris_y = iris.target
>>> np.unique(iris_y)
array([0, 1, 2])
2.1.1. k-Nearest neighbors classifier¶
The simplest possible classifier is the nearest neighbor: given a new observation x_test, find in the training set (i.e. the data used to train the estimator) the observation with the closest feature vector. (Please see the Nearest Neighbors section of the online Scikit-learn documentation for more information about this type of classifier.)
Training set and testing set
When experimenting with learning algorithm, it is important not to test the prediction of an estimator on the data used to fit the estimator, as this would not be evaluating the performance of the estimator on new data. This is why datasets are often split into train and test data.
KNN (k nearest neighbors) classification example:
>>> # Split iris data in train and test data
>>> # A random permutation, to split the data randomly
>>> np.random.seed(0)
>>> indices = np.random.permutation(len(iris_X))
>>> iris_X_train = iris_X[indices[:-10]]
>>> iris_y_train = iris_y[indices[:-10]]
>>> iris_X_test = iris_X[indices[-10:]]
>>> iris_y_test = iris_y[indices[-10:]]
>>> # Create and fit a nearest-neighbor classifier
>>> from sklearn.neighbors import KNeighborsClassifier
>>> knn = KNeighborsClassifier()
>>> knn.fit(iris_X_train, iris_y_train)
KNeighborsClassifier(algorithm='auto', leaf_size=30, n_neighbors=5,
warn_on_equidistant=True, weights='uniform')
>>> knn.predict(iris_X_test)
array([1, 2, 1, 0, 0, 0, 2, 1, 2, 0])
>>> iris_y_test
array([1, 1, 1, 0, 0, 0, 2, 1, 2, 0])
2.1.2. The curse of dimensionality¶
If the data is only described by one feature, with values ranging from 0 to 1, with n train observations, new data will be no further away than 1/n and the nearest neighbor decision rule will be efficient as soon as 1/n is small compared to the scale of between-class feature variations.
If the number of features is p, the number of training samples to pave the [0, 1] space with a between-point distance of d, is 1/d**p. This number scales exponentialy p, the dimensionality of the problem.
In other words, the prediction problem becomes much harder for high-dimensional data. This is called the curse of dimensionality and is the core problem that machine learning addresses.
2.2. Linear model: from regression to sparsity¶
Diabetes dataset
The diabetes dataset consists of 10 physiological variables (age, sex, weight, blood pressure) measure on 442 patients, and an indication of disease progression after one year:
>>> diabetes = datasets.load_diabetes()
>>> diabetes_X_train = diabetes.data[:-20]
>>> diabetes_X_test = diabetes.data[-20:]
>>> diabetes_y_train = diabetes.target[:-20]
>>> diabetes_y_test = diabetes.target[-20:]
The task at hand is to predict disease prediction from physiological variables.
2.2.1. Linear regression¶
Linear regression, in it’s simplest form, fits a linear model to the data set by adjusting a set of parameters, in order to make the sum of the squared residuals of the model as small as possilbe.
Linear models:
- : data
- : target variable
- : Coefficients
- : Observation noise
>>> from sklearn import linear_model
>>> regr = linear_model.LinearRegression()
>>> regr.fit(diabetes_X_train, diabetes_y_train)
LinearRegression(copy_X=True, fit_intercept=True, normalize=False)
>>> print regr.coef_
[ 3.03499549e-01 -2.37639315e+02 5.10530605e+02 3.27736980e+02
-8.14131709e+02 4.92814588e+02 1.02848452e+02 1.84606489e+02
7.43519617e+02 7.60951722e+01]
>>> # The mean square error
>>> np.mean((regr.predict(diabetes_X_test) - diabetes_y_test)**2)
2004.5676026898223
>>> # Explained variance score: 1 is perfect prediction
>>> # and 0 means that there is no linear relationship
>>> # between X and Y.
>>> regr.score(diabetes_X_test, diabetes_y_test)
0.58507530226905713
2.2.2. Shrinkage¶
If there are few data points per dimension, noise in the observations induces high variance:
>>> X = np.c_[ .5, 1].T
>>> y = [.5, 1]
>>> test = np.c_[ 0, 2].T
>>> regr = linear_model.LinearRegression()
>>> import pylab as pl
>>> pl.figure()
>>> np.random.seed(0)
>>> for _ in range(6):
... this_X = .1*np.random.normal(size=(2, 1)) + X
... regr.fit(X, y)
... pl.plot(test, regr.predict(test))
... pl.scatter(this_X, y, s=3)
A solution, in high-dimensional statistical learning, is to shrink the regression coefficients to zero: any two randomly chosen set of observations are likely to be uncorrelated. This is called ridge regression:
>>> regr = linear_model.Ridge(alpha=.1)
>>> pl.figure()
>>> np.random.seed(0)
>>> for _ in range(6):
... this_X = .1*np.random.normal(size=(2, 1)) + X
... regr.fit(this_X, y)
... pl.plot(test, regr.predict(test))
... pl.scatter(this_X, y, s=3)
This is an example of bias/variance tradeoff: the larger the ridge alpha parameter, the higher the bias and the lower the variance.
We can choose alpha to minimize left out error, this time using the diabetes dataset, rather than our synthetic data:
>>> alphas = np.logspace(-4, -1, 6)
>>> print [regr._set_params(alpha=alpha
... ).fit(diabetes_X_train, diabetes_y_train,
... ).score(diabetes_X_test, diabetes_y_test) for alpha in alphas]
[0.58511106838835292, 0.58520730154446743, 0.58546775406984897, 0.58555120365039137, 0.58307170855541623, 0.570589994372801]
Note
Capturing in the fitted parameters noise that prevents the model to generalize to new data is called overfitting. The bias introduced by the ridge regression is called a regularization.
2.2.3. Sparsity¶
Fitting only features 1 and 2
Note
A representation of the full diabetes dataset would involve 11 dimensions (10 feature dimensions, and one of the target variable). It is hard to develop an intuition on such representation, but it may be useful to keep in mind that it would be a fairly empty space.
We can see that although feature 2 has a strong coefficient on the full model, it conveys little information on y when considered with feature 1.
To improve the conditioning of the problem (mitigate the The curse of dimensionality), it would be interesting to select only the informative features and set non-informative ones, like feature 2 to 0. Ridge regression will decrease their contribution, but not set them to zero. Another penalization approach, called Lasso (least absolute shrinkage and selection operator), can set some coefficients to zero. Such methods are called sparse method, and sparsity can be seen as an application of Occam’s razor: prefer simpler models.
>>> regr = linear_model.Lasso(alpha=.1)
>>> print [regr._set_params(alpha=alpha
... ).fit(diabetes_X_train, diabetes_y_train
... ).score(diabetes_X_test, diabetes_y_test)
... for alpha in alphas]
[0.5851191069162196, 0.58524713649060311, 0.58571895391793782, 0.58730094854527282, 0.5887622418309254, 0.58284500296816755]
>>> best_alpha = alphas[4]
>>> regr.alpha = best_alpha
>>> regr.fit(diabetes_X_train, diabetes_y_train)
Lasso(alpha=0.025118864315095794, copy_X=True, fit_intercept=True,
max_iter=1000, normalize=False, precompute='auto', tol=0.0001)
>>> print regr.coef_
[ 0. -212.43764548<PHONE_NUMBER>1<PHONE_NUMBER>2 -160.8303982 -0.
-187.19554705 69.38229038<PHONE_NUMBER>7 71.84239008]
Different algorithms for a same problem
Different algorithms can be used to solve the same mathematical problem. For instance the Lasso object in the scikit-learn solves the lasso regression using a coordinate decent method, that is efficient on large datasets. However, the scikit-learn also provides the linear_model.LassoLars object, using the LARS which is very efficient for problems in which the weight vector estimated is very sparse, that is problems with very few observations.
2.2.4. Classification¶
For classification, as in the labeling iris task, linear regression is not the right approach, as it will give too much weight to data far from the decision frontier. A linear approach is to fit a sigmoid function, or logistic function:
>>> logistic = linear_model.LogisticRegression(C=1e5)
>>> logistic.fit(iris_X_train, iris_y_train)
LogisticRegression(C=100000.0, dual=False, fit_intercept=True,
intercept_scaling=1, penalty='l2', tol=0.0001)
Multiclass classification
If you have several classes to predict, an option often used is to fit one-versus-all classifiers, and use a voting heuristic for the final decision.
Shrinkage and sparsity with logistic regression
The C parameter controls the amount of regularization in the LogisticRegression object, the bigger C, the less regularization. penalty=”l2” gives Shrinkage (i.e. non-sparse coefficients), while penalty=”l1” gives Sparsity.
Excercise
Try classifying the digits dataset with nearest neihbors and a linear model. Leave out the last 10% and test prediction performance on these observations.
2.3. Support vector machines (SVMs)¶
2.3.1. Linear SVMs¶
The SVM is a discrimant model: they try to find a combination of samples to build a plane maximizing the margin between the two classes. Regularization is set by the C parameter: the small the choice of C, means a stronger regularization, which means the margin will be caluculated using many, to all the observations around the separation line; a larger choice of C will thus have the margins computed on the observations that are close to the separating line.
| Unregularized SVM | Regularized SVM (default) |
|---|---|
SVMs can be used in regression –SVR (Support Vector Regression)–, or in classification –SVC (Support Vector Classification).
>>> from scikits.learn import svm
>>> svc = svm.SVC(kernel='linear')
>>> svc.fit(iris_X_train, iris_y_train)
SVC(C=1.0, cache_size=200, coef0=0.0, degree=3, gamma=0.0, kernel='linear',
probability=False, shrinking=True, tol=0.001)
Warning
Normalizing data
For many estimators, including the SVMs, having datasets with unit standard deviation for each feature is important to get good prediction.
2.3.2. Using kernels¶
Classes are not always separable in feature space. The solution is to build a decision function that is not linear but that may be for instance polynomial. This is done using the kernel trick that can be seen as creating an decision energy by positioning kernels on observations:
| Linear kernel | Polynomial kernel |
>>> svc = svm.SVC(kernel='linear')
|
>>> svc = svm.SVC(kernel='poly',
... degree=3)
>>> # degree: polynomial degree
|
| RBF kernel (Radial Basis Function) |
>>> svc = svm.SVC(kernel='rbf')
>>> # gamma: inverse of size of
>>> # radial kernel
|
Interactive example
See the SVM GUI to download svm_gui.py; add data points of both classes with right and left button, fit the model and change parameters and data.
Excercise
Try classifying classes 1 and 2 from the iris dataset with SVMs, with the 2 first features. Leave out 10% of each class and test prediction performance on these observations.
The solution is available below:
Warning: the classes are ordered, do not leave out the last 10%, you would be testing on only one class.
Hint: You can use the decision_function method on a grid to get intuitions.


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Summary
Stats comming soon...


Dexie.Syncable
Enables two-way synchronization with a remote server of any kind.
If you are looking for a batteries-included sync solution, check out the following npm packages:
These are built upon Dexie.Syncable but also implements ISyncProtocol and the backend.
Dependency Tree
- Dexie.Syncable.js
- Dexie.Observable.js
- An implementation of ISyncProtocol
Tutorial
1. Include Required Sources
Install over npm
npm install dexie
npm install dexie-observable
npm install dexie-syncable
Make sure to include dexie.js, dexie-observable.js, dexie-syncable.js and an implementation of ISyncProtocol.
import Dexie from 'dexie';
import 'dexie-observable';
import 'dexie-syncable';
import 'your-sync-protocol-implementation';
Or if using plain html:
<html>
<head>
<script src="dexie.js"></script>
<script src="dexie-observable.min.js"></script>
<script src="dexie-syncable.min.js"></script>
<!-- Example implementation of ISyncProtocol -->
<script src="WebSocketSyncProtocol.js"></script>
...
</head>
<body></body>
</html>
Usage with existing DB
In case you want to use Dexie.Syncable with your existing database, but do not want to use UUID based Primary Keys as described below, you will have to do a schema upgrade. Without it Dexie.Syncable will not be able to properly work.
import Dexie from 'dexie';
import 'dexie-observable';
import 'dexie-syncable';
import 'your-sync-protocol-implementation';
var db = new Dexie('myExistingDb');
db.version(1).stores(... existing schema ...);
// Now, add another version, just to trigger an upgrade for Dexie.Syncable
db.version(2).stores({}); // No need to add / remove tables. This is just to allow the addon to install its tables.
2. Use UUID based Primary Keys ($$)
Two way replication requires not to use auto-incremented keys if any sync node should be able to create objects no matter offline or online. Dexie.Syncable comes with a new syntax when defining your store schemas: the double-dollar prefix ($$). Similar to the ++ prefix in Dexie (meaning auto-incremented primary key), the double-dollar prefix means that the key will be given a universally unique identifier (UUID), in string format (For example “9cc6768c-358b-4d21-ac4d-58cc0fddd2d6”).
var db = new Dexie("MySyncedDB");
db.version(1).stores({
friends: "$$oid,name,shoeSize",
pets: "$$oid,name,kind"
});
3. Connect to Server
You must specify the URL of the server you want to keep in-sync with. This has to be done once in the entire database life-time, but doing it on every startup is ok as well, since it wont affect already connected URLs.
// This example uses the WebSocketSyncProtocol included in earlier steps.
db.syncable.connect ("websocket", "https://syncserver.com/sync");
db.syncable.on('statusChanged', function (newStatus, url) {
console.log ("Sync Status changed: " + Dexie.Syncable.StatusTexts[newStatus]);
});
4. Use Your Database
Query and modify your database as if it was a simple Dexie instance. Any changes will be replicated to server and and change on server or other window will replicate back to you.
db.transaction('rw', db.friends, function (friends) {
friends.add({name: "Arne", shoeSize: 47});
friends.where(shoeSize).above(40).each(function (friend) {
console.log("Friend with shoeSize over 40: " + friend.name);
});
});
NOTE: Transactions only provide the Atomicity part of the ACID properties when using 2-way syncronization. This is due to that the syncronization phase may result in that another change could override the changes. However, it’s still meaningfull to use the transaction() since method for atomicity. Atomicity is guaranteed not only locally but also when synced to the server, meaning that a part of the changes will never commit on the server until all changes from the transaction has been synced. In practice, you cannot increment a counter in the database (for example) and expect it to be consistent, but you can be guaranteed that if you add a sequence of objects, all or none of them will replicate.
API Reference
Static Members
Dexie.Syncable.registerSyncProtocol (name, protocolInstance)
Define how to replicate changes with your type of server.
Dexie.Syncable.Statuses
Enum of possible sync statuses, such as OFFLINE, CONNECTING, ONLINE and ERROR.
Dexie.Syncable.StatusTexts
Text lookup for status numbers
Non-Static Methods and Events
db.syncable.connect (protocol, url, options)
Create a presistend a two-way sync connection with given URL.
db.syncable.disconnect (url)
Stop syncing with given URL but keep revision states until next connect.
db.syncable.delete(url)
Delete all states and change queue for given URL
db.syncable.list()
List the URLs of each remote node we have a state saved for.
db.syncable.on(‘statusChanged’)
Event triggered when sync status changes.
db.syncable.getStatus (url)
Get sync status for given URL.
db.syncable.getOptions (url)
Get the options object for the given URL.
Source
Description
Dexie.Syncable enables syncronization with a remote database (of almost any kind). It has it’s own API ISyncProtocol. The ISyncProtocol is pretty straight-forward to implement. The implementation of that API defines how client- and server- changes are transported between local and remote nodes. The API support both poll-patterns (such as ajax calls) and direct reaction pattern (such as WebSocket or long-polling methods). See samples below for each pattern.
Sample ISyncProtocol Implementations
Sample Sync Servers
Table of Contents
- API Reference
- Best Practices
- Building Addons
- Collection
- Collection.and()
- Collection.clone()
- Collection.count()
- Collection.delete()
- Collection.desc()
- Collection.distinct()
- Collection.each()
- Collection.eachKey()
- Collection.eachPrimaryKey()
- Collection.eachUniqueKey()
- Collection.filter()
- Collection.first()
- Collection.keys()
- Collection.last()
- Collection.limit()
- Collection.modify()
- Collection.offset()
- Collection.or()
- Collection.primaryKeys()
- Collection.raw()
- Collection.reverse()
- Collection.sortBy()
- Collection.toArray()
- Collection.uniqueKeys()
- Collection.until()
- Compound Index
- Consuming Dexie as a module
- Deprecations
- Derived Work
- Design
- Dexie
- Dexie.AbortError
- Dexie.BulkError
- Dexie.ConstraintError
- Dexie.DataCloneError
- Dexie.DataError
- Dexie.DatabaseClosedError
- Dexie.IncompatiblePromiseError
- Dexie.InternalError
- Dexie.InvalidAccessError
- Dexie.InvalidArgumentError
- Dexie.InvalidStateError
- Dexie.InvalidTableError
- Dexie.MissingAPIError
- Dexie.ModifyError
- Dexie.NoSuchDatabaseErrorError
- Dexie.NotFoundError
- Dexie.Observable
- Dexie.Observable.DatabaseChange
- Dexie.OpenFailedError
- Dexie.PrematureCommitError
- Dexie.QuotaExceededError
- Dexie.ReadOnlyError
- Dexie.SchemaError
- Dexie.SubTransactionError
- Dexie.Syncable
- Dexie.Syncable.IDatabaseChange
- Dexie.Syncable.IPersistentContext
- Dexie.Syncable.ISyncProtocol
- Dexie.Syncable.StatusTexts
- Dexie.Syncable.Statuses
- Dexie.Syncable.registerSyncProtocol()
- Dexie.TimeoutError
- Dexie.TransactionInactiveError
- Dexie.UnknownError
- Dexie.UnsupportedError
- Dexie.UpgradeError()
- Dexie.VersionChangeError
- Dexie.VersionError
- Dexie.[table]
- Dexie.addons
- Dexie.async()
- Dexie.backendDB()
- Dexie.close()
- Dexie.currentTransaction
- Dexie.debug
- Dexie.deepClone()
- Dexie.defineClass()
- Dexie.delByKeyPath()
- Dexie.delete()
- Dexie.derive()
- Dexie.events()
- Dexie.exists()
- Dexie.extend()
- Dexie.fakeAutoComplete()
- Dexie.getByKeyPath()
- Dexie.getDatabaseNames()
- Dexie.hasFailed()
- Dexie.ignoreTransaction()
- Dexie.isOpen()
- Dexie.js
- Dexie.name
- Dexie.on()
- Dexie.on.blocked
- Dexie.on.error
- Dexie.on.populate
- Dexie.on.populate-(old-version)
- Dexie.on.ready
- Dexie.on.versionchange
- Dexie.open()
- Dexie.override()
- Dexie.semVer
- Dexie.setByKeyPath()
- Dexie.shallowClone()
- Dexie.spawn()
- Dexie.table()
- Dexie.tables
- Dexie.transaction()
- Dexie.transaction()-(old-version)
- Dexie.verno
- Dexie.version
- Dexie.version()
- Dexie.vip()
- Dexie.waitFor()
- DexieError
- Docs Home
- Download
- Export and Import Database
- Getting Started
- Hello World
- How To Use the StorageManager API
- Inbound
- IndexSpec
- Indexable Type
- IndexedDB on Safari
- Migrating existing DB to Dexie
- MultiEntry Index
- Promise
- Promise.PSD
- Promise.catch()
- Promise.finally()
- Promise.on.error
- Promise.onuncatched
- Questions and Answers
- Releasing Dexie
- Samples
- Simplify with yield
- Table
- Table Schema
- Table.add()
- Table.bulkAdd()
- Table.bulkDelete()
- Table.bulkGet()
- Table.bulkPut()
- Table.clear()
- Table.count()
- Table.defineClass()
- Table.delete()
- Table.each()
- Table.filter()
- Table.get()
- Table.hook('creating')
- Table.hook('deleting')
- Table.hook('reading')
- Table.hook('updating')
- Table.limit()
- Table.mapToClass()
- Table.name
- Table.offset()
- Table.orderBy()
- Table.put()
- Table.reverse()
- Table.schema
- Table.toArray()
- Table.toCollection()
- Table.update()
- Table.where()
- The three main limitations of IndexedDB
- Transaction
- Transaction.abort()
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- Transaction.table()
- Tutorial
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- Version
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- WhereClause.below()
- WhereClause.belowOrEqual()
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- WhereClause.inAnyRange()
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- db.syncable.connect()
- db.syncable.delete()
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- db.syncable.getOptions()
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- db.syncable.on('statusChanged')
- db.syncable.setFilter()
- unhandledrejection-event


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White Christmas at Temple Buell Theatre - Northwest - Denver, CO
3 Reviews of White Christmas at Temple Buell Theatre "I love the theatre, and I love the Buell in particular. This musical play is an adaptation of the Berlin scored .
http://www.yelp.com/biz/white-christmas-at-temple-buell-theatre-denver
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Colorado wakes up to a white Christmas and ... - The Denver Post
Dec 25, 2012 . A winter storm that blanketed the metro area in snow had cleared out by late Tuesday morning, leaving behind freezing temperatures and a .
http://www.denverpost.com/breakingnews/ci_22258188/colorado-wakes-up-white-christmas-and-freezing-temps
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Irving Berlin's White Christmas plays Denver for the holidays ...
Nov 29, 2012 . It's Christmas Eve, 1944, and Captain Bob Wallace (Tom Galan. . Irving Berlin's White Christmas plays Denver for the holidays (Photos) . Pollution could be shrinking otter penises, according to new study t.co/bCKUqnJJlv .
http://www.examiner.com/review/irving-berlin-s-white-christmas-plays-denver-for-the-holidays
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WHITE CHRISTMAS - Denver Center for the Performing Arts
APPLAUSE denvercenter.org . On White Christmas the Denver Center Theatre Company's Production Staff is . components of DCTC's successful Colorado .
http://www.denvercenter.org/Libraries/Applause_April_2012_forward/White_Christmas_Program.sflb.ashx
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Snow storm brings White Christmas to Colorado - Denver News ...
Dec 22, 2012 . DENVER -- Dreams of a White Christmas look on track this year. Snow will develop during the evening hours across Colorado and Denver .
http://kdvr.com/2012/12/22/mild-start-to-winter-snow-expected-christmas-eve/
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Denver Center Presents White Christmas » Catchcarri.com
Dec 14, 2012 . In celebration of the holiday season, The Denver Center Theatre Company is lighting up the stage with White Christmas. Hear the classic tunes .
http://catchcarri.com/denver-center-presents-white-christmas/
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White Christmas Denver Tickets 12/22/12 (Denver) tickets|eBay
Buy and Sell White Christmas Denver tickets Temple Buell Theatre - Denver tickets - 2012-12-22 tickets for Dec 22 at Temple Buell Theatre in Denver, CO at .
http://www.ebay.com/tickets/White-Christmas-Denver-Tickets-12-22-12-Denver/117615213
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No need for dreaming: Denver area expected to get white Christmas ...
Dec 24, 2012 . While Denverites may dream of a white Christmas, a very real northeast . The past six years of snowfall on Christmas in Denver averaged 5.5 . Brush, CO Weather Forecast for Monday, March 4 - Sunday, March 10, 2013.
http://www.brushnewstribune.com/ci_22253879/no-need-dreaming-denver-area-expected-get-white
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Denver Center for the Performing Arts
The official source of ticket to Broadway touring shows in Denver. The Official presenter ticketing website for The Denver Center for the Performing Arts. Tickets .
http://www.denvercenter.org/
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White Christmas Denver Tickets 12/11/12 (Denver) tickets|eBay
Buy and Sell White Christmas Denver tickets Temple Buell Theatre - Denver tickets - 2012-12-11 tickets for Dec 11 at Temple Buell Theatre in Denver, CO at .
http://www.ebay.com/tickets/White-Christmas-Denver-Tickets-12-11-12-Denver/117595220
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Denver Center Theatre Company Irving Berlin's White Christmas ...
Dec 1, 2012 . Denver Center Theatre Company Irving Berlin's White Christmas. Temple Buell Theater, Denver CO November 25, 2012. By Jane Elliot.
http://www.danceinforma.com/USA_magazine/2012/12/01/denver-center-theatre-company-irving-berlins-white-christmas/
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'White Christmas' Is Coming Back To The Buell Theater « CBS Denver
Nov 21, 2012 . DENVER (CBS4) It's a classic song that's part of two classic holiday movies, and now . The song 'White Christmas,' sung by Bing Crosby, is considered the best selling single in . Philadelphia Union v Colorado Rapids .
http://denver.cbslocal.com/2012/11/21/white-christmas-is-coming-back-to-the-buell-theater/
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Denver Center coupons - RetailMeNot
Discounts average $16 off with a Denver Center promo code or coupon. 12 Denver Center coupons now . JULYXMAS. Denver Center: 50% off White Christmas, select dates. Expires 7/31/12 . Colorado Symphony Orchestra · Ticketmaster .
http://www.retailmenot.com/view/denvercenter.org
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White Christmas for Rockies, Denver, Salt Lake City
Throughout the states of Utah and Colorado, colder temperatures moved in . Climatologically, a White Christmas is not as common in Denver as one may think.
http://www.accuweather.com/en/weather-news/white-christmas-for-rockies-de/3110912
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Denver's white Christmas history: Snow on the holiday not as ...
Dec 22, 2012. on the ground. Here in Denver we historically enjoy a better chance of. . One more mild day as Colorado prepares for a white Christmas » .
http://www.thorntonweather.com/blog/climatology/denvers-white-christmas-history-snow-on-the-holiday-not-as-common-as-you-might-think/
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Colorado weather forecast: White Christmas for high country, little to ...
Colorado weather forecast: White Christmas for high country, little to no snow for Denver. 3:15 PM, Dec 21, 2010 | comments. Tweet; Share. Facebook · Twitter .
http://www.9news.com/rss/story.aspx?storyid=170505
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White Christmas Denver Tickets 12/02/12 (Denver) tickets|eBay
Buy and Sell White Christmas Denver tickets Temple Buell Theatre - Denver tickets - 2012-12-2 tickets for Dec 2 at Temple Buell Theatre in Denver, CO at eBay.
http://www.ebay.com/tickets/White-Christmas-Denver-Tickets-12-02-12-Denver/117526164
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White Christmas Denver Tickets 12/18/12 (Denver) tickets|eBay
Buy and Sell White Christmas Denver tickets Temple Buell Theatre - Denver tickets - 2012-12-18 tickets for Dec 18 at Temple Buell Theatre in Denver, CO at .
http://www.ebay.com/tickets/White-Christmas-Denver-Tickets-12-18-12-Denver/117558969
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White Christmas (weather) - Wikipedia, the free encyclopedia
A white Christmas refers to the presence of snow on Christmas; either Christmas Eve or Christmas Day depending on local tradition. . Denver, Colorado, 50% .
http://en.wikipedia.org/wiki/White_Christmas_(weather)
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White Christmas Denver Tickets 12/01/12 (Denver) tickets|eBay
Buy and Sell White Christmas Denver tickets Temple Buell Theatre - Denver tickets - 2012-12-1 tickets for Dec 1 at Temple Buell Theatre in Denver, CO at eBay.
http://www.ebay.com/tickets/White-Christmas-Denver-Tickets-12-01-12-Denver/117554432


LMOs
The LMO-Unique Identifiers (LMO-UIds) Registry provides summary information on all living
modified organisms registered in the BCH including transformation events, genetic
modifications, and the unique identification code (if available) for each record.
Links to all decisions and Risk assessment reports that refer to these organisms are
accessible through the registry.
The BCH modalities of operation require the BCH to make use of existing unique
identification systems for living modified organisms, as appropriate, to facilitate
searching and retrieval of information.


Enjoy!
An artist that I enjoy listen to Vera, a character I've created Toon Me Challenge A very colourfull portrait of me A study of light & colour I've made A Draw This In My Style ChallengeIn this video, it is demonstrated what the convection LightBox offers to people. This event is extremelly important and well known, because it brings not only new artists to the mercat, but also some very well-knowned ones as, for example, in 2019:


{% extends "base.html" %} {% block body_class %}default-container{% endblock %} {% block content %}
{% trans "Sorry, you are having trouble accessing this feature! Due to a temporary technical issue, log in and registrations are not available for now. We're working hard to get this problem resolved. Thank you." %}


Item classes These pages provides a summary of the ComplexItem classes supplied with the Slate. For more details in these items, go to the class documentation. Warning: this page is out of date. Pseudo-3D items Box-and-arrow items Graphing items Labeled items
Warning: this page is out of date.


MY GIANT RATING: 6 / 10 --> Barely recommendable
Review Date: April 18, 1998 Director: Michael Lehmann Writer: David Seltzer Producers: Billy Crystal and Peter Schindler Actors: Billy Crystal as Sammy Kanin Gheorghe Muresan as Max Kathleen Quinlan as Serena Kanin Genre: Comedy Year of Release: 1998
Michael Lehmann's follow-up to the funny and touching THE TRUTH ABOUT CATS AND DOGS (7.5/10) doesn't come close to that film, or his directorial debut of HEATHERS (8/10), one of JoBlo's personal favourites. Crystal is also credited as one of the people who came up with the "story" for this film.
PLOT: Fast-talking agent from New York (Crystal) gets his life saved by a gigantic man in Romania (Muresan) and decides to bring him back to America for a shot at success in the world of entertainment.
CRITIQUE: This film is anything but a comedy. Yes, it does have some funny scenes. Yes, it does feature Billy Crystal, the successful host of the Oscars, cracking us up from year to year. But no, unfortunately for all those going into this film expecting a yuck-fest...'tis not to be, my friends. This film is rooted in sentimentality and the manipulation of emotions (in its characters and for the audience). Most of the film involved a sub-plot about the "giant" coming to America to find his long-lost love (nothing funny about that), and the fact that he may have some health problems (nothing funny about that either).
As a general film, it does work on some emotional levels, but as a comedy, it is definitely not something you would recommend to your friends for a "good laugh". Muresan is excellent as the puppy-eyed "giant" who doesn't want nor need much out of life. Crystal is generic as usual, and does little to distinguish his character from every other neurotic, wise-cracking Jewish yuppie that he's played over the years (Did I just describe Crystal as a "person" or his "character"? Too close to call. I guess the man's acting abilities don't necessarily stretch from his own persona). Funny at times, overly sentimental at others.
Overall, the movie doesn't deliver many laughs (one unique scene featuring the real Steven Seagal is pretty cool, and pretty big on Seagal's part, as the scene essentially makes fun of him-word on the street is that Seagal originally turned the part down, but after hearing that Van Damme might take it, he curiously reconsidered), has a disappointing ending, and seems to use Muresan's pure innocence and naiveté to garner emotional attachment from the audience (worked a little bit, but after a while....). The good points, well, not too many, but I guess I was never really bored or angry during the entire screening, so that's a plus. A flaccid recommendation indeed.
Little Known Facts: The film is dedicated to Andre. That's "Andre the Giant" to the laymen.
A scene featuring Mr. Muresan having to drink wine to get "tipsy", and being hauled onto a horse by a crane, is based on an actual occurence during the filming of Rob Reiner's PRINCESS BRIDE (8/10), when Andre the Giant also ran into some problems attempting to mount a horse. Billy Crystal stands 5"8, while Muresan towers at 7"7. Muresan's mom was 5"7 and his dad was only 5"9. He wears a size 19 shoe, and plays professional basketball in the NBA with the Washington Wizards. Billy Crystal once studied film and television direction at NYU, partially under the tutelage of filmmaker Martin Scorsese (TAXI DRIVER 8/10, GOODFELLAS 9/10 ).
(c) 1998 Berge Garabedian
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Year-end could see return to North Korea 'provocations,' says U.S. envoy
WASHINGTON (Reuters) - U.S. Special Representative for North Korea Stephen Biegun said on Wednesday a year-end deadline North Korea has set for Washington to show more flexibility in nuclear talks was an artificial one, but could mean a return to “provocative” steps that preceded the past two years of diplomacy.
North Korea has been demanding that Washington lift sanctions hobbling its economy, and its leader Kim Jong Un set the deadline for Washington to show more flexibility in April, raising concerns that he could resume nuclear and long-range missile testing suspended since 2017.
“I can imagine that we could see a possibility of going back to some of the more provocative steps that preceded the start of this diplomacy to begin with; I think that would be a huge mistake and a missed opportunity by the Democratic People’s Republic of Korea,” Biegun told the Senate Foreign Relations Committee in his nomination hearing for the State Department’s No. 2 post.


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January 01, 2003
Britain mulled ethnic cleansing in Northern Ireland
Globe and Mail | Submitted by: optional
In 1972, the British government explored the possibility of exiling hundreds of thousands of its own citizens, as an attempt to extinguish the war in Northern Ireland. The scheme would have involved orchestrating forced emigration for Catholics to the Irish Republic (in the south). The plan was ultimately rejected because officials could not figure out how to handle the negative publicity which would inevitably be generated "by expelling large numbers of its own citizens and doing so on a religious basis."
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Read article...
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Congressman wants to bring back the draft
New York Times | Submitted by: Ducky
Charles Rangel (Democrat, New York) has announced in an op-ed piece that he will seek to revive military conscription. The reason? Rangel is upset because only one member of Congress who voted in favor of war with Iraq currently has a child serving in the military. He feels that the men and women of the House and Senate would have exhibited "more caution and a greater willingness to work with the international community." [If that's true, then shouldn't Rangel have simply sponsored a bill requiring the children of elected officials to sign up for military service? Why lay this on the rest of the country? Also consider the 1863 Draft Riots -- it took a full week for the New York authorities to regain order.]
|
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Read article... and
This article...
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Hardcore Arab-Israeli sex video
channels.netscape.com | Submitted by: PETE
"Yussuf and Fatima" is being advertised in Israel as "the first Israeli-Arab porno." The 60-minute film evidently features a Palestinian man named Amir copulating with an Israeli "38-year-old mother of eight" named Amal Kusha. Was pornstar Jenna Jameson busy with some other project? Apparently both stars have been beaten by angry mobs since the video was produced.
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Read article...
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Happy New Year, I'm gonna kill myself.
 "I'm in my underwear, I'm in my own house and three people rush in and point guns at me," said Goldstein, who was in another room of the mansion. "First I'm thinking home invasion, then I realize they're cops, and they say to me, ‘Where's Katherine?' "
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Hint: look at the bowls on the lecterns (podium stands) in front of Kirsten to see the lights. You can see them in the first minute and from min 9 on the left edge of the view.
Travel the world to teach companies how to make APIs that don't make developers cry
Teaching developer to use APIs without crying.


-
addFlag(flag)
-
Adds the given flag to the Flag System.
Parameters:
| Name |
Type |
Description |
flag |
String
|
name of the flag, preferrably in captial letters |
- Source:
-
countFlag(flag)
-
Returns the amount this flag occurs in the Flag System.
Parameters:
| Name |
Type |
Description |
flag |
String
|
name of the flag, preferrably in captial letters |
- Source:
Returns:
int
-
endTalk()
-
Manually ends the active talk
- Source:
-
isFlag(flag)
-
Returns the state of the given flag.
Parameters:
| Name |
Type |
Description |
flag |
String
|
name of the flag, preferrably in captial letters |
- Source:
Returns:
boolean
-
matches(flags)
-
Checks if the given flag expression is matching
Parameters:
| Name |
Type |
Description |
flags |
String
|
flag expression to be matched against |
- Source:
Returns:
boolean
-
removeFlag(flag, all)
-
Removes the given flag from the Flag System.
Parameters:
| Name |
Type |
Description |
flag |
String
|
name of the flag, preferrably in captial letters |
all |
boolean
|
if set all occurences of this flag will be removed, not just one |
- Source:
-
setFlag(flag)
-
Sets the given flag in the Flag System if it has not been set yet.
Parameters:
| Name |
Type |
Description |
flag |
String
|
name of the flag, preferrably in captial letters |
- Source:
-
talk(entity)
-
Manually triggers the talk of the given entity
Parameters:
| Name |
Type |
Description |
entity |
Entity
|
int
|
Entity (-UID) whose talk will be started |
- Source:
-
teleport(e, x, y, bumpPos)
-
Teleports the given entity to a given location on the active map
Parameters:
| Name |
Type |
Description |
e |
Entity
|
int
|
Entity (-UID) to teleport |
x |
int
|
new X Position |
y |
int
|
new Y Position |
bumpPos |
boolean
|
if position should be set for bumpRectangle or for top-left Corner of e |
- Source:
-
teleportMap(x, y, map, bumpPos)
-
Teleports the player to a given location on a different map
Parameters:
| Name |
Type |
Description |
x |
int
|
new X Position |
y |
int
|
new Y Position |
map |
String
|
name of new map |
bumpPos |
boolean
|
if position should be set for bumpRectangle or for top-left Corner of e |
- Source:


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I've taken this chemical a few times at varying doses (20 mg -> 70 mg) and have found the only difference to be the duration of the trip, while the perceived intensity and effects remain pretty much the same.
Orally dosed, the effects are felt with a unique speed: come up 15-20 minutes after ingestion, peaking at 30 minutes after. The peak lasts around 20 minutes, with a sharp comedown of 5 or 10 minutes. Minor residual feelings linger for another hour or so. (All in all, 2 hours from ingestion to return to baseline.)
5-MeO-DALT has a very strong 'body load' that's associated with many psychedelics. I get the feeling that I'm about to 'break through' (colors start to dance a little, patterns seem to start forming) but it never actually happens, seemingly regardless of dose.
The body load is fairly heavy and rather uncomfortable, though not terrible. I get the general feeling that my brain is being tickled, which affects the rest of my body accordingly.
There is a moderate sense of time dilation, but since the chemical's effects are so brief, I never seemed to get lost in time at all.
I did not experience mydriasis, change in heartrate, or any other physical side effects. My perception of heat and cold is moderately altered, with cold temperatures feeling somewhat warmer, and warm temperatures feeling somewhat cooler. Repeated dosing (same day, or several times within a week) did not seem to build tolerance or change the effect profile.
All in all I can't recommend anyone taking this chemical recreationally, but it is moderately interesting, albeit unpleasant. The only use I can think for this would be for someone who wants to experience the negative physical side effects of RC psychedelics.
I, and everyone else on BlueLight and other discussion forums, have found Alexander Shulgin's report on 5-MeO-DALT to be completely different from what anyone else has experienced. Either his synthesis contained some impurities, or the current manufacturers are synthesizing it incorrectly. I haven't seen any sort of chemical verification, though I would suspect the RC samples are fairly pure.
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.


Sippe
This page contains an index of all the individuals in the database with the surname of Sippe. Selecting the person’s name will take you to that person’s individual page.
| Given Name | Birth | Death | Partner | Parents |
|---|---|---|---|---|
| Arthur Henry | 1st Qtr 1878 | Sippe, Charles Henry Thornton, Elizabeth Jane | ||
| Caroline Harriet.“Carrie” | 2nd Qtr 1885 | Morley, ??? | Sippe, Charles Henry Thornton, Elizabeth Jane | |
| Charles Blackburn | 2nd Qtr 1876 | Chambers, Emma Mary Isabel | Sippe, Charles Henry Thornton, Elizabeth Jane | |
| Charles Henry | c1842 | 1924-08-14 | Thornton, Elizabeth Jane | Sippe, Robert D. & Sophia |
| Clive M. | 1904 | Sippe, Charles Blackburn Chambers, Emma Mary Isabel | ||
| Dora Charlotte | 4th Qtr 1883 | Sippe, Charles Henry Thornton, Elizabeth Jane | ||
| Esther S. | 1896 | Weaver, ??? | Sippe, Charles Henry Thornton, Elizabeth Jane | |
| Frederick A. C. | 1899 | Sippe, Charles Blackburn Chambers, Emma Mary Isabel | ||
| George McDonald | 1874 | Sippe, Charles Henry Thornton, Elizabeth Jane | ||
| Robert D. & Sophia | ||||
| Robert Thornton | 3rd Qtr 1879 | 1902 | Horsley, Annie I. | Sippe, Charles Henry Thornton, Elizabeth Jane |
| Robin | 1903 | Sippe, Robert Thornton Horsley, Annie I. | ||
| Ruth Mary | 1908 | Kenny, John Harper | Sippe, Charles Blackburn Chambers, Emma Mary Isabel | |
| Sydney Vincent | 2nd Qtr 1889 | D'Arcy, Mabel Frances | Sippe, Charles Henry Thornton, Elizabeth Jane | |
| [Living] | Sippe, Charles Blackburn Chambers, Emma Mary Isabel |


04-Sep-2017 | Milku
That calls for ice cream...
My humans are just deciding what to do on the last day of the school holidays. The little humans just want to vegetate in front of computer screens really, but that's so boring. Their Mum isn't putting up with that.
They had hoped to find a film they wanted to see at the cinema...but one of the little humans had already seen Despicable Me 3 and the reviews of the Emoji Movie put them off...
They contemplated a walk along the promenade. Blackpool Illuminations were switched on last Friday so, if they timed it right, my humans would see a spectacular light show. But they'll need to be in bed early ready for school in the morning so perhaps they should go to see the lights at the weekend. Plus, it's looking a bit dull and feels autumnal today and that's putting them off walking out...not even the lure of the ice cream vendors on the prom is going to tempt them.
Thank goodness for the Internet otherwise I'd have been stuck with them all day. They want to visit Tootsie's ice cream parlour at Botany Bay. They're supposed to have over 150 ice cream flavours to choose from...it might be some time before I see them again...


| HTTP Response Code | No of Calls | No of Calls per Path | ||||
|---|---|---|---|---|---|---|
| response code (or "total") | count calls |
Details...
|
| Path | No of Calls |
|---|---|
| response code (or "total") | count calls |
| Proxied Service API | API User | Request Method | Path | Metric | HTTP Response Status | Count |
|---|---|---|---|---|---|---|


 But I can't give you this case, it don't belong to me.
The path of the righteous man is beset on all sides by the iniquities of the selfish and the tyranny of evil men. Blessed is he who, in the name of charity and good will, shepherds the weak through the valley of darkness, for he is truly his brother's keeper and the finder of lost children.  And you will know My name is the Lord when I lay My vengeance upon thee.
You think water moves fast? You should see ice. It moves like it has a mind. Like it knows it killed the world once and got a taste for murder. After the avalanche, it took us a week to climb out. Now, I don't know exactly when we turned on each other, but I know that seven of us survived the slide... and only five made it out. Now we took an oath, that I'm breaking now. We said we'd say it was the snow that killed the other two, but it wasn't. Nature is lethal but it doesn't hold a candle to man.
 But I can't give you this case, it don't belong to me.
This script is just for Firefox right now, but I'll iron out the kinks for Chrome soon too, hokay?
Get this at Github: https://github.com/polygonix/RDBL


 The Ministry of Health is committed to ensuring that during end of life, for patients who wish to stay at home, BC Palliative Care support and benefits are delivered as efficiently as possible. Unfortunately, administrative inefficiencies throughout the system were impacting the timely receipt of support and benefits for Palliative Care patients, causing undue stress and, at times, financial hardships.
By carrying out a collaborative Lean Kaizen workshop amongst stakeholders, the ministry was able to illuminate and address root causes of these process inefficiencies, such as the amount of time spent by all parties on processing and reprocessing enrollment forms.
Contact<EMAIL_ADDRESS>> Impact
A Lean approach resulted in the Province’s physicians saving 300,000 hours annually and HIBC reclaiming 70 processing hours annually. Most importantly, palliative care patients and their families, receive the timely benefits and medical supplies they need to be comfortable in their own homes, during the final days of life.
> Partner(s)
BC Pharmacare, Health Insurance BC (HIBC), Health Authorities and physicians
> Resouces Used
LEAN BC Toolkit
> Tags
#lean #voiceofthecustomer
> Code
N/A


Click Here
for project history


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This is my css
<Cascading Style Sheets (CSS) is a style sheet language used for describing the presentation of a document written in a markup language like HTML.[1] CSS is a cornerstone technology of the World Wide Web, alongside HTML and JavaScript.[2]>


Tasks
Generate Approx Pareto-front
Remove the repeated and non-dominated solutions from Pareto-front for all problems and instances
Generate


COMPATIBILTY SCORE
Languages:
Compare the 5 most used languages of each user.
Creativity:
Analysis of your creativity potential through every commits.
Faithfulness:
"- Who's this b*tch ?"
"- She's just one of my contributors. You have nothing to worry about..."
Size Matters:
How big is your total number of lines of code ?
RESULTS DETAILS


See Table
- ActionScript for Flash MX Pocket Reference: Quick Reference for Flash MX Programmers
-- Colin Moock
- Adobe Integrated Runtime (AIR) for JavaScript Developers Pocket Guide
-- Mike Chambers
- AI for Game Developers
-- David M. Bourg
- America (The Book): A Citizen's Guide to Democracy Inaction
-- Jon Stewart
- America (The Book): A Citizen's Guide to Democracy Inaction (Teacher's Edition)
-- Jon Stewart
- An Imaginary Tale: The Story of "I" [The Square Root of Minus One]
-- Paul J. Nahin
- An Introduction to Numerical Analysis
-- Kendall E. Atkinson
- Apache Pocket Reference
-- Andrew Ford
- AppleScript in a Nutshell
-- Bruce W. Perry
- Approximation Algorithms
-- Vijay V. Vazirani
- Assembly Language Programming and the IBM 360 and 370 Computers
-- Walter G. Rudd
- Black Hat Python: Python Programming for Hackers and Pentesters
-- Justin Seitz
- Building Wireless Community Networks
-- Rob Flickenger
- C, A Software Engineering Approach
-- Peter A. Darnell
- Communication Complexity
-- Eyal Kushilevitz
- Computer Ethics
-- Tom Forester
- Computer Networks: A Systems Approach
-- Larry L. Peterson
- Computer Systems: A Programmer's Perspective
-- Randal E. Bryant
- Computing Concepts With C++ Essentials
-- Cay S. Horstmann
- CSS Pocket Reference
-- Eric A. Meyer
- CSS: The Definitive Guide
-- Eric A. Meyer
- CVS Pocket Reference
-- Gregor N. Purdy
- Cyberethics: Morality and Law in Cyberspace
-- Richard A. Spinello
- Data Structures and Algorithm Analysis in Java
-- Mark Allen Weiss
- Database System Concepts
-- Abraham Silberschatz
- Designing Embedded Hardware
-- John Catsoulis
- Digital Integrated Circuits: A Design Perspective
-- Jan M. Rabaey
- Essential System Administration
-- AEleen Frisch
- Exploring Expect: A Tcl-based Toolkit for Automating Interactive Programs
-- Don Libes
- Fermat's Enigma: The Epic Quest to Solve the World's Greatest Mathematical Problem
-- Simon Singh
- From Alchemy to Quarks
-- Sheldon L. Glashow
- Getting Started with Dwarf Fortress: Learn to Play the Most Complex Video Game Ever Made
-- Peter Tyson
- Getting Started with Flex 3: An Adobe Developer Library Pocket Guide for Developers
-- Jack Herrington
- Gimp Pocket Reference
-- Sven Neumann
- Global Catastrophic Risks
-- Nick Bostrom
- GNU Emacs Pocket Reference
-- Debra Cameron
- Hacking Exposed: Network Security Secrets & Solutions, Fourth Edition (Hacking Exposed)
-- Stuart McClure
- Head First Design Patterns
-- Eric Freeman
- Head First Object-Oriented Analysis and Design: A Brain Friendly Guide to OOA&D
-- Brett D. McLaughlin
- HTML5: Up and Running
-- Mark Pilgrim
- Implementing Mathematics with the Nuprl Proof Development System
-- Robert L. Constable
- In Search of Clusters: The Coming Battle in Lowly Parallel Computing
-- Gregory F. Pfister
- Intellectual Property in the New Technological Age: 2008 Case and Statutory Supplement
-- Robert Merges
- Introduction to Algorithms
-- Thomas H. Cormen
- Introduction to Electric Circuits [With CDROM]
-- Richard C. Dorf
- Introduction to Very Large Scale Integration Systems
-- Carver A. Mead
- Introductory circuit analysis
-- Robert L. Boylestad
- iPod and iTunes Hacks
-- Hadley Stern
- JavaScript Pocket Reference
-- David Flanagan
- JavaScript: The Definitive Guide
-- David Flanagan
- JavaScript: The Good Parts
-- Douglas Crockford
- JavaServer Pages Pocket Reference
-- Hans Bergsten
- jQuery Cookbook: Solutions & Examples for jQuery Developers
-- Cody Lindley
- Knoppix Pocket Reference
-- Kyle Rankin
- Latex: A Document Preparation System
-- Leslie Lamport
- LDAP System Administration
-- Gerald Carter
- Learn You a Haskell for Great Good!: A Beginner's Guide
-- Miran LipovaÃ°Ã°a
- Learning C#
-- Jesse Liberty
- Learning GNU Emacs
-- Debra Cameron
- Learning the vi Editor
-- Arnold Robbins
- Lego Mindstorms NXT 2.0: The King's Treasure
-- James Floyd Kelly
- Lex & Yacc
-- John R. Levine
- Lie Groups for Pedestrians
-- Harry J. Lipkin
- LINQ Pocket Reference (Pocket Reference (O'Reilly))
-- Joseph Albahari
- Mac OS X Snow Leopard Pocket Guide: The Ultimate Quick Guide to Mac OS X
-- Chris Seibold
- Machine Vision: Theory, Algorithms, Practicalities
-- E.R. Davies
- Managing IMAP
-- Dianna Mullet
- Managing Projects with Make
-- Andrew Oram
- Mastering Algorithms with Perl
-- Jon Orwant
- Mastering Regular Expressions: Powerful Techniques for Perl and Other Tools
-- Jeffrey E.F. Friedl
- Mathematical Go: Chilling Gets the Last Point
-- Elwyn R. Berlekamp
- Mathematical Perspectives on Neural Networks
-- Smolensky
- Measuring the Software Process: A Practical Guide to Functional Measurements
-- David Herron
- mod_perl Pocket Reference: Extending Apache
-- Andrew Ford
- Modern Information Retrieval
-- Ricardo Baeza-Yates
- MP3: The Definitive Guide: The Definitive Guide
-- Scot Hacker
- Online Computation And Competitive Analysis
-- Allan Borodin
- Operating Systems
-- Stuart E. Madnick
- Optimality Theory
-- Rene Kager
- Oracle PL/SQL Language Pocket Reference: A guide to Oracle's PL/SQL language fundamentals
-- Steven Feuerstein
- Oracle SQL*Plus Pocket Reference
-- Jonathan Gennick
- Perl & LWP
-- Sean M. Burke
- Perl 5 Desktop Reference
-- Johan Vromans
- Perl 5 Pocket Reference: Programming Tools
-- Johan Vromans
- Perl 6 Essentials
-- Allison Randal
- Perl Best Practices
-- Damian Conway
- Perl Debugger Pocket Reference
-- Richard Foley
- Perl for System Administration: Managing multi-platform environments with Perl
-- David N. Blank-Edelman
- Perl Pocket Reference
-- Johan Vromans
- PHP Pocket Reference
-- Rasmus Lerdorf
- PNG: The Definitive Guide: The Definitive Guide
-- Greg Roelofs
- Postfix: The Definitive Guide: The Definitive Guide
-- Kyle D. Dent
- Practical PostgreSQL. A Hardened, Robust, Open Source Database.
-- John C. Worsley
- Principles of Functional Programming
-- Hugh Glaser
- Probability And Statistics For Engineering And The Sciences
-- Jay L. DeVore
- Programming Amazon Web Services: S3, EC2, SQS, FPS, and SimpleDB
-- James Murty
- Programming Embedded Systems in C and C++
-- Michael Barr
- Programming in D: Tutorial and Reference
-- Ali Ã°Ã°ehreli
- Programming iOS 5: Fundamentals of iPhone, iPad, and iPod touch Development
-- Matt Neuburg
- Programming Perl
-- Tom Christiansen
- Programming PHP
-- Rasmus Lerdorf
- Programming Python [with CD]
-- Mark Lutz
- Programming Ruby: The Pragmatic Programmers' Guide
-- Dave Thomas
- Programming Scala: Scalability = Functional Programming + Objects
-- Dean Wampler
- Programming the Perl DBI
-- Tim Bunce
- Python Pocket Reference
-- Mark Lutz
- Quick Calculus: A Self-Teaching Guide
-- Daniel Kleppner
- Rails Recipes
-- Chad Fowler
- Security and Quality of Service in Ad Hoc Wireless Networks
-- Amitabh Mishra
- sed & awk
-- Dale Dougherty
- Seeing: The Computational Approach to Biological Vision
-- John P. Frisby
- Selfish Routing and the Price of Anarchy
-- Tim Roughgarden
- sendmail Desktop Reference
-- Bryan Costales
- SmallTalk by Example: The Developer's Guide to VisualWorks, with Disk
-- Alec Sharp
- SQL in a Nutshell
-- Kevin E. Kline
- SQL Pocket Guide
-- Jonathan Gennick
- Squeak: Open Personal Computing and Multimedia
-- Mark J. Guzdial
- Svg Essentials
-- J. David Eisenberg
- TCL/TK in a Nutshell
-- Paul Raines
- TCL/TK Pocket Reference
-- Paul Raines
- TCP/IP Network Administration
-- Craig Hunt
- Technical Communication
-- Mike Markel
- The Art of Computer Programming, Volume 1: Fundamental Algorithms
-- Donald Ervin Knuth
- The Art of Computer Programming, Volume 2: Seminumerical Algorithms
-- Donald Ervin Knuth
- The C Programming Language
-- Brian W. Kernighan
- The Elements Of Logic
-- Stephen F. Barker
- The Elements of Programming Style
-- Brian W. Kernighan
- The Hacker Diaries: Confessions of Teenage Hackers
-- Dan Verton
- The LEGO MINDSTORMS NXT 2.0 Discovery Book: A Beginner's Guide to Building and Programming Robots
-- Laurens Valk
- The Little MLer
-- Matthias Felleisen
- The Millennium Problems
-- Keith J. Devlin
- The Mythical Man-Month: Essays on Software Engineering
-- Frederick P. Brooks Jr.
- The Norton Anthology of Short Fiction
-- Richard Bausch
- The Unicode Standard: Version 4. 0
-- The Unicode Consortium
- Time Management for System Administrators
-- Thomas A. Limoncelli
- UML 2.0 in a Nutshell (In a Nutshell (O'Reilly))
-- Dan Pilone
- Understanding Operating Systems
-- Ann McIver McHoes
- Using C on the Unix System
-- Dave Curry
- VBScript Pocket Reference
-- Paul Lomax
- Windows 2000 Commands Pocket Reference
-- AEleen Frisch
- Windows XP Pocket Reference
-- David A. Karp
- Wireless and Mobile All-IP Networks
-- Yi-Bing Lin
- Wireless and Mobile Network Architectures
-- Imrich Chlamtac
- Wireless Security and Privacy: Best Practices and Design Techniques
-- Tara M. Swaminatha
- Wireless Sensor Networks: An Information Processing Approach
-- Leonidas Guibas
- Wizards and Their Wonders: Portraits in Computing
-- Christopher Morgan
- Word Pocket Guide
-- Walter Glenn
- Writing GNU Emacs Extensions
-- Bob Glickstein
- XML in a Nutshell: A Desktop Quick Reference
-- Elliotte Rusty Harold
- XML Pocket Reference
-- Michael Fitzgerald
- XML Pocket Reference: Extensible Markup Language
-- Robert Eckstein


http://www.vulnerabilityassessment.co.uk/Penetration%20Test.html
http://www.pentest-standard.org/index.php/Main_Page
http://projects.webappsec.org/w/page/13246978/Threat-Classification
http://www.owasp.org/index.php/Category:OWASP_Top_Ten_Project
http://www.social-engineer.org/


The Music Achievement Council is an organization of music leaders dedicated to developing and retaining instrumental music students and teachers.
The Music Achievement Council is an organization of music leaders dedicated to developing and retaining instrumental music students and teachers.
The Music Achievement Council is an organization of music leaders dedicated to developing and retaining instrumental music students and teachers.
The Music Achievement Council is an organization of music leaders dedicated to developing and retaining instrumental music students and teachers.
The Music Achievement Council is an organization of music leaders dedicated to developing and retaining instrumental music students and teachers.
The Music Achievement Council is an organization of music leaders dedicated to developing and retaining instrumental music students and teachers.
The Music Achievement Council is an organization of music leaders dedicated to developing and retaining instrumental music students and teachers.