The results Wales need to qualify for Euro 2020 over the next four days and the back-up option that's now nearly certain
Here's how the picture looks ahead of Wales' games against Azerbaijan and Hungary
by Ian MitchelmoreWales face Azerbaijan in their penultimate Euro 2020 qualifier in Baku on Saturday before completing their campaign against Hungary on Tuesday.
They are the most important matches of Ryan Giggs' reign and this is what they need to qualify for the tournament.
What Wales need
If Wales beat Azerbaijan, they will qualify automatically if they win against Hungary and Slovakia drop points in either of their remaining games against Croatia and Azerbaijan.
If Wales draw with Azerbaijan, they can still qualify automatically, but they'd need to beat Hungary (claiming a better head-to-head record against them in the process) and hope Slovakia claim no more than two points from their remaining games against Croatia and Azerbaijan.
Wales can't qualify automatically if they lose to Azerbaijan.
The Red Dragons will also miss out if Slovakia win their remaining two games.
What about the Nations League?
To earn a Nations League play-off spot, Wales need one more of Austria, Sweden, Bosnia & Herzegovina or Denmark to qualify automatically given that Ukraine and Russia have already secured their place at next year's tournament. This is extremely likely to happen so the Nations League backstop is almost certainly there.
The play-offs take place in March next year.


Geodrill says two employees killed in Burkina Faso attack
(Reuters) - Geodrill Limited (GEO.TO) said on Thursday two of its employees were killed, after an ambush near a Canadian-owned mine in Burkina Faso killed at least 37.
The incident took place between Fada and Boungou in East Region of Burkina Faso on Wednesday. Dozens of people were feared still missing on Thursday.
Canadian gold miner Semafo (SMF.TO) said on Wednesday several people had been killed when a convoy transporting some of its workers was attacked on a road in eastern Burkina Faso.


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Bitcoin’s hashrate has seemingly been recovering in the last few months, after hitting a low of little over 32 million TH/s when miners were struggling to stay afloat because of the bear market. While the cryptocurrency’s price hasn’t yet fully recovered, it appears min...


With OpenAPI Generator you can generate Client and Server code of your API defined in an OpenAPI 2.0 or OpenAPI 3.0 yaml file.
Note: OpenAPI Generator is a community fork of Swagger Codegen.
The instructions below are also valid for Swagger Codegen 2.3.1 and 2.4.0 using swagger-codegen-maven-plugin
API defined in api-definition.yml
Frontend
Backend
The API Development process proposed here allows following the API First / Zalando RESTful API Guidelines principle and looks as follows:
Here, we explain the setup using the following technologies:
In order to use the helper scripts for swagger codegen provided by lsg-ext, you need install lsg-ext in your Backend Java Project, as we demonstrate the use together with the openapi-generator-maven-plugin
In your Spring Boot project folder, install lsg-ext:
For your convenience, add the following scripts to the package.json
:
Note: Per default the bundled API definition will be placed in a dist
folder right next to your src
folder.
If you want to change this, use the -d
parameter to set the location of the dist
folder when bundling the API definition.
The api-bundle
script from above would look like this if we wanted the API bundle to be placed in the admin
folder:
Define your API in
OpenAPI 2.0 Yaml File,
e.g. api-definition.yml
For your convencience, install the Swagger Plugin in IntelliJ. It helps you editing the OpenAPI yaml file.
The Zalando RESTful API Guidelines are a good resource for creating good APIs.
With the API First principle, you define and document your API in a first step, independent of the implementation.
You can start with the following content:
In order to move some
the content of your api-definition.yml
to separate files
in order to avoid having one huge file,
you can use the $ref: './models/Bank.yml'
property,
which simply inserts the content of the path referenced.
api-definition.yml
models/Bank.yml
In order to be able to copy the api-definition.yml
into e.g. Swagger Editor,
you can use the bundle
script of lsg-ext
as follows
As a shortcut, you can simply run
package.json
as described above.
This will generate a bundled file in src/main/resources/api/dist/api-definition.bundle.yml
Note: the $ref
references in the .yml
files need to be relative to the api-definition.yml
, starting with ./
Hint: if you want to maintain multiple API versions, simply use sub-folders for the versions. e.g. src/main/resources/api/v1/dist/api-definition.bundle.yml
and adapt the paths in the package.json
and pom.xml
accordingly.
Moreover, instead of having one huge API definition, you can also split it up into multiple different API definition files and put them in subfolders.
In the pom.xml
, you can adapt the path / package of the generated files to sub-packages.
In order to view your API definition in a swagger editor,
you can either paste the content of api-definition.bundle.yml
into Swagger Editor
or you can run
Important! Open http://localhost:5200 in Google Chrome, as Internet Explorer will cache the .yml file and API Responses, even though it should not!
In order to view an updated version of your
api-definition.bundle.yml
, run
In order to automatically re-generate the bundle as soon as you change your .yml file, run
and refresh the page to see the changes.
In order to generate the backend server / frontend client code, we use the openapi-generator-maven-plugin
Set up the following configuration in your pom.xml
in order to generate the code with maven:
Finally, run the following command:
In order to implement the backend API, simply create classes that implement the generated interfaces.
Note: It is important to copy the method signature including the annotations, otherwise path-parameters will not work correctly.
Also, add the @Override
annotation to prevent not-overriding the interface if the signature changes. Example:
In the angular frontend, simply import the ApiModule
and specify the api base path by providing the Configuration
as follows:
Finally, inject the generated service and use it in your component:
Sometimes it can be useful to constrain the allowed values of a parameter, e.g.


This tool gives you the ability to look behind-the-scenes of a blockchain. You can create transactions, mine blocks and see how they all work together. Go ahead, make some transactions, mine a block, tweak the settings and see the effects of your actions in real-time.
Source code - Based on my Python blockchain.


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For the next three class periods, we will explore the use of population models to address conservation questions– a process known as population viability analysis (PVA)
PVA is essentially a set of practical approaches to problem-solving in conservation, and wildlife management via creative application of demographic theory, simulation models and statistics.
As much as possible we will use hands-on activities to explore the fundamentals of PVA. We will use InsightMaker- a free web-based systems modeling tool for running simulation models.
First we will build a PVA for the grizzly bears of Yellowstone National Park!
We will end this mini-course by building a PVA for the loggerhead turtle, Caretta caretta, which is based on a paper by Crowder et al 1994.
But even before any of that, let’s review some basic population ecology theory and mathematics which are the foundation of PVA!
From Krebs (1972):
“A group of organisms of the same species occupying a particular space at a particular time, with the potential to breed with each other”
From Cole (1957):
“A biological unit at the level of ecological integration where it is meaningful to speak of birth rate, death rate, sex ratios, and age structure in describing properties or parameters of the unit.”
From Gotelli (1998):
“A group of plants, animals, or other organisms, all of the same species, that live together and reproduce.”
From NOAA website:
“a group of individuals of the same species living in the same area at the same time and sharing a common gene pool; a group of potentially interbreeding organisms in a geographic area”
Defining a population is not always straightforward…. Spatial boundaries defining populations sometimes are easily defined, but more typically are vague and difficult to determine.
Population size, or abundance, is often represented as \(N\), and is the most basic measurement of a wild population.
Giant puffballs produce 7 trillion offspring in one reproductive event.
… If all of those individuals reached adulthood, the descendants from just two parent puffballs would weigh more than the entire planet in two generations!
The reason? Populations grow geometrically, in a process called exponential growth. This is the foundational concept of population ecology, and this simple model has enormous resonance across all of ecology and evolution.
“Mathematics seems to endow one with a new sense.”
- Charles Darwin
“Like most mathematicians, he takes the hopeful biologist to the edge of the pond, points out that a good swim will help his work, and then pushes him in and leaves him to drown.”
- Charles Elton, in reference to a work by Alfred Lotka
“The importance of the method is this: if we know certain variables, mostly desired by ecologists and in some cases already determined by them, we can predict certain results which would not normally be predictable or even expected by ecologists. The stage of verification of these mathematical predictions has hardly begun; but their importance cannot be under-estimated.”
- Charles Elton
First of all, we need a symbol to represent population size, or abundance. This is \(N\), for the \(N\)umber of individuals!
\(\Delta N\) represents the change in population size, \({N_{t+1}}-{N_t}\)
The famous “BIDE” equation is a way to break down \(\Delta N\) into components.
\(\Delta N = B + I - D - E \qquad \text{(Eq. 1)}\)
where \(B\) represents the number of births, \(I\) reprents the number of immigrants, \(D\) represents the number of deaths, and \(E\) represents the number of emigrants.
If we ignore immigration and emigration, then the BIDE equation simplifies to:
\(\Delta N = B - D \qquad \text{(Eq. 2)}\)
Now let’s focus on \(B\) and \(D\). The important thing to recognize is that the number of births and deaths in a population is not constant.
What does the number of births depend on?
What is more likely to be constant is the per-capita rate of producing offspring, or dying. Does this make sense? These per-capita rates are often expressed as lower case letters. So \(b\) represents per-capita births, and \(d\) represents per-capita deaths.
\(b = \frac {B_t}{N_t} \qquad \text{(Eq. 3)}\)
–or–
\(B_t = b \cdot N_t\)
The letter \(t\) of course represents time, which could be years, or minutes, or decades, or whatever! So the above equation could be described as follows: “the number of births at a given time is equal to the per-capita birth rate times the total population size at that time”
Similarly,
\(D_t = d \cdot N_t \qquad \text{(Eq. 4)}\)
Okay, we’re almost there.
If \(\Delta N = B - D \qquad \text{(Eq. 5)}\)
then
\(\Delta N = b \cdot N_t - d \cdot N_t\qquad \text{(Eq. 6)}\)
which is equal to
\(\Delta N = (b - d) \cdot N_t \qquad \text{(Eq. 7)}\)
which could also be written:
\(\Delta N = r \cdot N_t\qquad \text{(Eq. 8)}\)
Where \(r\) represents the difference between births and deaths. If \(r\) is positive, then births are greater than deaths and the population grows. If \(r\) is negative then deaths exceed births and the population declines.
We can use calculus notation to consider the instantaneous change in population size:
\(\frac{\partial N}{\partial t} = r \cdot N \qquad \text{(Eq. 9)}\)
This simple formula represents exponential growth and is probably the most fundamental equation of population ecology.
We will have time to explore this model in a few minutes!
A couple more quick notes:
The greek symbol lambda (\(\lambda\)), represents the finite rate of growth, or \(\frac {N_{t+1}}{N_t}\). Lambda is what you multiply the current population size by to compute the population size in the next time step.
\(N_{t+1}=N_t + B - D \qquad \text{(Eq. 11)}\)
\(N_{t+1}=N_t + b \cdot N_t - d \cdot N_t \qquad \text{(Eq. 12)}\)
\(N_{t+1}=N_t + (b - d) \cdot N_t \qquad \text{(Eq. 13)}\)
\(N_{t+1}=N_t + r \cdot N_t \qquad \text{(Eq. 14)}\)
\(N_{t+1}=N_t \cdot (1 + r) \qquad \text{(Eq. 15)}\)
\(N_{t+1}=\lambda \cdot N_t \qquad \text{(Eq. 16)}\)
Modern computers have reduced or eliminated many of the barriers to understanding how complex systems behave, and as a result specialized software and computer programming are a critical component to modern whole-systems analysis, including ecosystems analyses. Armed with basic facility with computer programming, ecologists and natural resource professionals can formalize their understanding of the natural systems in which they work, accounting for complex biological realities that may have been ignored if these tools were not available. In these three classes, we will learn to use computer simulations for understanding and managing natural populations.
InsightMaker is a web-based visual programming language for modeling the dynamics of inter-connected systems.
A dynamic system essentially consists of [Stocks] and [Flows].
A [Stock] represents a quantity of something. The [Stock] only changes over time ONLY via [Flows In] or [Flows Out].
A [Stock] of stuff increases over time via what [Flows] in. Imagine our stock represents Moose! Moose Births would then be the input [Flow] to the population of Moose over time.
A [Stock] of stuff decreases over time via what [Flows] out. For example, Moose Deaths could represent the [Flow] out of the population of Moose.
If the [Flow] in is larger than the [Flow] out then the [Stock] increases over time.
If the [Flow] out is larger than the [Flow] in then the [Stock] decreases over time.
If the [Flow] in equals the [Flow] out then the amount in the [Stock] will not change over time.
Open up InsightMaker. If you have never used it before you need to sign up first with a username and password. InsightMaker is free!
Create a new “Insight” and clear the demo model.
Right click in the center of the screen and select Create Stock from the pop-up. Notice that the name is New Stock and is selected. Type in a name for what this is an accumulation of (e.g., “Moose”!). Note the Configuration Panel on the right - where you can alter the settings for your [Stock]. In the configuration panel, set the Initial Value to 50. That is, there will be 50 moose at the start of the simulation!
Select [Flow] in the upper left corner of your screen under [Connections]. Now notice that when you mouse over the [Stock] a small right-arrow displays. Click on the right-arrow and drag a couple inches to the left of the [Stock] and release. This is how you create a [Flow] out of a [Stock]. To create a [Flow] into a [Stock] click the Reverse button in the Connections menu. Please do that now. You can name the [Flow] as you wish (e.g., “Births”!). Also in the Configuration Panel set Flow Rate equal to 1.
Now click Run Simulation and you have just finished your first simulation model!!
Can you figure out how to change the settings to run the model for 50 years? Try this and click Run Simulation.
Use the same methods as step 4 to create a [Flow Out], representing moose deaths. Set the death rate to 1 moose per year. Re-run the model. Is the population increasing or declining? Why?
Change the Configuration Panel for the [Stock] and for the [Flow In] and [Flow Out] so that “Show Value Slider” is set to “Yes”. You can change the model parameterization easily using these sliders. Try it a couple times, re-running the simulation after each change.
Q: Is this Moose model realistic? What is the first thing you would like to change to make the model more realistic?
Now let’s consider per-capita rates of birth and death in the population. This way, if the population is bigger, the total births will increase!
To create a variable to store per-capita vital rates (per-capita birth and death rate), right-click on the canvas and select Variable from the drop-down. While the [Variable] is still selected rename it (per-capita) birth rate. Open the [Equation] window for birth rate and set it to 0.5 (if you mouse over Stock or Flow a small [\(=\) Sign] will appear. If you click this it will open the Equation window where you can set values.
Now draw a [Link] from birth rate to the “Births” [Flow]. In InsightMaker, flow of information is represented by a [Link]. To create a [Link], click Link in the Connections part of the toolbar. When you mouse over the birth rate click on the right-arrow, drag to the [Flow] and release. You now have a [Link] on top of the [Flow]. Now hold the Shift Key and click in the middle of the [Link] and a little little green node will be created on the [Link]. You can select this node and drag it to make a visually pleasing curved line!
Your model should look something like this:
[Moose]*[Birth rate]
That is, the rate of inflow into the [Moose] stock is equal to the total number of moose multiplied by the per-capita birth rate.
For the [Moose], [Birth rate], and [Death rate], open the configuration panel and set “Show Value Slider” to “Yes”. Set the “Slider Max” to 100 for moose, and 1 for birth and death rate. Make sure the number of moose is set to 50, the birth rate is set to 0.5, and the death rate is set to 0.4.
Now click [Run Simulation]. How would you describe the results?
NOTE: If you are running into difficulties, you can always use this working model. Click on this link and then click “Clone Insight” in the top right corner of your screen. This will create a copy of the Insight that you can change as you wish!
Q: what happens if you set the birth rate equal to the death rate?
Q: what happens if you set the birth rate less than the death rate?
Q: is this model realistic? What is the next thing you would like to change in this model?
Which one of these figures is most likely to be from a real wildlife population??
OR
… And these fluctuations are often difficult to predict!
That is to say…
 We all know it intuitively. But what exactly do we mean by that? And how can we deal with it? How can we incorporate it into our models?
Q: if you were to re-run the basic population model you just made in InsightMaker ten times, how many different results would you get?
When a model outcome is the same every time (when starting with the same input values) we say that the model is deterministic.
BUT… ecological systems (e.g., dynamic populations) have inherent variability that is often not predictable.
We can’t predict with certainty whether or not an individual will mate, or die.
We can’t be certain whether next year or the year after that will be a good year or a bad year for offspring production or mortality!
The key is to embrace uncertainty. As population ecologists, we have some tricks to help us manage and account for unpredictable variation in our study systems:
When we incorporate random processes into models, the result can be different each time we run the model!
These are called stochastic models.
When we use stochastic models, we often want to run lots of replicates. Each replicate represents a possible future.
We can then interpret the cloud of possible futures rather than just the results from a single model run!
Here we see that the population went extinct in three replicates, out of a total of 50 replicates.
Q: What is the extinction risk for this population?
When it comes to projecting who lives and dies, who gives birth and who doesn’t, how many females are born to each individual in the population, we just can’t know that for sure.
In other words, we can’t know whether an individual will be “lucky” or “unlucky” so to speak!
In population ecology this is called demographic stochasticity.
We usually can’t predict whether next year or the year after will be a good one or a bad one for a population- that is, we don’t know whether the per-capita vital rates (e.g., \(b\), or \(d\)) will be more or less optimal year-to-year
In other words, we can’t know whether a population will be “lucky” or “unlucky”, so to speak!
In population ecology this is called environmental stochasticity.
To ensure that each model run (replicate) – or each year of each model run – is different from one another, we can include at least one random number generator in our models!
A random number generator is like a box of (potentially infinite) possible numbers – a lottery ball machine for example! Each time we want a new number we reach in and pull one out, record the number, put it back in and shake it up again.
Every random-number generator has a distribution. This is a way of defining what exactly is in the box. For example, the box might have 10 “ones”, 5 “twos”, and 2 “threes”. In this case the distribution looks like this (probability of each possibility):
A probability distribution can be pretty much anything you want it to be. However, there are several key distributions that come up again and again in nature, and we should know them, because they end up being major building blocks of PVA!
Consider the probability of flipping a coin 10 times and getting 4 heads. This quantity would follow a binomial distribution
Another discrete distribution we will use in this PVA mini-course is the Poisson distribution:
Q What population parameter might this distribution be useful for modeling?
In continuous distributions, there is an infinite set of possibilities in our random-number box between any upper and lower bound.
Let’s consider the uniform distribution:
lower = 0
upper = 10
curve(dunif(x,lower,upper),0,10,ylab="Probability (density)",xlab="Possibilities",main="Uniform distribution (continuous)",ylim=c(0,1)) # probability density
This isn’t a very intersting looking distribution. All possible numbers from 0 to 10 are equally probable.
Another continuous distribution you should know is called the Normal distribution. This distribution has a lower bound of \(-\infty\) and an upper bound of \(\infty\).
Q What population parameter might this distribution be useful for modeling?
mean = 7.1
stdev = 1.9
curve(dnorm(x,mean,stdev),0,15,ylab="Probability (density)",xlab="Possibilities",main="Normal distribution (continuous)") # probability density
Make sure your Population stock can NOT go negative (this is a setting in the configurations panel: Allow Negatives = “No”). Hit “Simulate”- you should see exponential growth!
To do this in InsightMaker, open the equation window for the Deaths flow, and use the following formula to define the total number of deaths in the population each year:
RandBinomial([Population], [Death rate])
For the total births, \(B\) we will use the Poisson distribution. The Poisson distribution is often use to represent births, because there could feasibly be more births than there are individuals currently in the population (e.g., if all individuals have two offspring!). This would not be possible with a binomial distribution! That is, the maximum number of “heads” (you can always think of binomial distributions as coin-flipping!) is the total number of individuals, period.
To do this in InsightMaker, use the following formula for the Births flow:
RandPoisson([Population]*[Birth rate])
If you’re having trouble, you can clone a working model here
Run the simulation. What does it look like?
Use the “Sensitivity Testing” tool (in the “Tools” menu, upper right corner) to run the model 50 times. Choose [Population] as the “Monitored Primitive”. View the results!
Change the initial abundance to 500 and re-run the “Sensitivity Testing” tool.
Change the initial abundance to 10 and re-run the “Sensitivity Testing” tool.
Q Is the effect of demographic stochasticity bigger at low or high abundances?
Q Is there any risk of extinction in this population?
Q In this model, did the population vital rates change at all? If not, why does it look different each time we run the model?
[Moose]*[Birth rate]
And do the same for Deaths!
[Moose]*[Death rate]
RandNormal(0.4, 0.4)
Similarly, use the following formula for the Death Rate variable:
RandNormal(0.3, 0.3)
Use the “Sensitivity Testing” tool (in the “Tools” menu, upper right corner) to run the model 50 times. Choose [Population] as the “Monitored Primitive”.
Change the initial abundance to 500 and re-run the “Sensitivity Testing” tool.
Note that the normal distribution CAN go below zero or above 1, which is often NOT biologically realistic! Let’s truncate the normal distribution to behave more realistically. That is, if the random number you draw comes out less than zero, just set it to zero!
For birth rate, this can be done like this:
Max(0,RandNormal(0.4, 0.4))
This forces birth rates to always be greater than or equal to zero.
For death rate, this can be done like this:
Min(1,Max(0,RandNormal(0.3, 0.3)))
This forces death rates to always be greater than or equal to zero.
Re-run the model with the modified/constrained random vital rates.
If you’re having trouble, you can clone a working model here
Q Is the effect of environmental stochasticity bigger at low or high abundances?
Q Under what circumstances can you envision small populations being more vulnerable to environmental stochasticity than large populations?
Before we move on do run some real PVA analysis, let’s return to the topic of this mini-course: PVA.
Population Viability Analysis (PVA) is the process of building and running a formal predictive population models for the purpose of gaining insight about present and future conservation status, or ranking alternative management options.
In general, we are interested in evaluating population-level risk under various scenarios. These scenarios could involve population size, different vital rates, or specific sources of mortality.
We are often interested in evaluating the factors that threaten the present or future viability of a population.
Just like population models, population threats can be classified as either deterministic or stochastic.
What is the population-level impact of the following?
What is the population-level impact of the following?
Q: which is more likely to cause a large population to become small: stochastic threas or deterministic threats?
Q: can you match the above concepts with the two paradigms of conservation biology: the small-population paradigm and the declining-population paradigm?
NOTE: The process of building a PVA model is iterative and non-linear.
For example – after running your model (step 4) you might realize that your results (step 5) are totally unrealistic. This might prompt you to go back and change your conceptual model of the life history (step 1), and re-parameterize your model (step 2).
How does your population work?
The first step is to conceptualize the life history for your species of interest. This can be done by visualized in a life history diagram (essentially and stock-and-flow diagram just like we have already been doing!), and think about the following questions:
Q: Why do most population models ignore males??
This is where you attach real numbers to the stocks and flows in your conceptual life history diagram!
If you want to ask spatial questions, your model needs to be spatially explicit, or at least consider spatial structure in some way. The kinds of questions you might think about include:
For the grizzly bear and loggerhead examples, we will not consider spatial structure!
You have already simulated simple population dynamics!
There are lots of options for simulation software- R, InsightMaker, Vortex, Ramas, and much more!
What scenarios do you want to test in order to test your original questions?
Finally, you need to make sense of all the simulations you just ran!
There are two types of data analysis tools that you will need to be able to use the simulation results to answer your questions: graphical visualization and statistical analysis.
Before we get into the PVA examples, let’s just step back and look at the final stage of the PVA process- visualizing results and making conclusions.
This is, after all, why we do PVA in the first place!!
To illustrate some of these concepts, let’s build ourselves a very simple PVA model in R.
For this demo I’m using the “R” programming language because of its flexible and powerful visualization tools. You can download R for yourself from this website:
For simplicity, let’s ignore age structure - that is, let’s build a scalar PVA model.
Also let’s ignore parameter uncertainty for now.
Here is the basic model parameterization:
####
# Basic simulation parameters
####
nyears <- 100 # number of years
nreps <- 500 # number of replicates
####
# Basic life history parameters
####
R_max <- 1.03 # Maximum rate of growth (max lambda)
Init_N <- 51 # Initial abundance
K <- 175 # Carrying capacity
####
# Environmental stochasticity
####
SD_lambda <- 0.11 # standard deviation of lambda
####
# Density-dependence (Ricker model)
####
Ricker <- function(prev_abund){ # this is a function for computing next-year abundance -- includes env stochasticity
prev_abund * exp(log(rnorm(1,R_max,SD_lambda))*(1-(prev_abund/K)))
}
####
# Catastrophe
####
Flood_prob <- 0.0 # 0% chance of major flood
Flood_lambda <- 0.25 # 25% of population can survive a flood, should it occur!
Now we can use these parameters to build a simple PVA model:
## Set up data structures to store simulation results!
PVAdemo <- function(nreps,nyears,Init_N,R_max,K,Flood_prob,Flood_lambda){
#browser()
PopArray2 <- array(0,dim=c((nyears+1),nreps))
## start looping through replicates
for(rep in 1:nreps){
# set initial abundance
PopArray2[1,rep] <- Init_N # initial abundance
### loop through years
for(y in 2:(nyears+1)){
### stochasticity and d-d
nextyear <- max(0,trunc(Ricker(PopArray2[y-1,rep])))
### catastrophe
if(runif(1)<Flood_prob) nextyear <- nextyear*Flood_lambda
PopArray2[y,rep] <- nextyear
}
}
return(PopArray2)
}
### Run the PVA!
Default <- PVAdemo(nreps,nyears,Init_N,R_max,K,Flood_prob,Flood_lambda)
There are several types of visualizations that you might want to use for your PVA models:
The first is to look at the “cloud” of abundance trajectories. This is the same type of figure we have seen in InsightMaker using the “Sensitivity testing” tool.
PlotCloud <- function(simdata){
plot(c(1:101),simdata[,1],col=gray(0.7),type="l",ylim=c(0,max(simdata)),xlab="Years",ylab="Abundance")
for(r in 2:ncol(simdata)){
lines(c(1:101),simdata[,r],col=gray(0.7),type="l")
}
}
PlotCloud(Default)
Okay, what do we learn from this? Really, it’s a mess!!!
If our question is about extinction risk, maybe we want to plot extinction risk by time…
Extinction_byyear <- function(simdata){
apply(simdata,1,function(t) length(which(t==0)))/ncol(simdata)
}
plot(c(1:101),Extinction_byyear(Default),type="l",lwd=2,xlab="year",ylab="extinction risk")
abline(h=0.05,col="red",lwd=2)
Maybe our question is about the probability of decline over 100 years …
In that case maybe we should present a histogram of final abundances…
hist(Default[nrow(Default),],xlab="Final abundance after 100 years",ylab="Number of replicates",main="")
abline(v=Init_N,col="green",lwd=2)
We could compute the probability of decline by computing \(\frac{number.declined}{total.simulations}\)
prob_decline <- round(length(which(Default[nrow(Default),]<Init_N))/ncol(Default),2)
cat("the probability of decline is: ", prob_decline)
## the probability of decline is: 0.15
What if our question is about the effect of flooding on extinction risk?
Let’s imagine that the probability of flooding is not expected to change with climate change, but that the intensity of the flood damage is likely to increase substantially!
Currently, floods generally result in a 10% population reduction. But climate change could increase this number to as much as 90%. Let’s look at how much this could increase extinction risk!
Flood_prob <- 0.1 # 10% chance of major flood
Exctinction_risk <- function(simdata){
length(which(simdata[nrow(simdata),]==0))/ncol(simdata)
}
flood_lambdas <- seq(0.9,0.1,by=-0.05)
all_scenarios <- numeric(length(flood_lambdas))
for(scenario in 1:length(flood_lambdas)){
PVA <- PVAdemo(nreps,nyears,Init_N,R_max,K,Flood_prob,flood_lambdas[scenario])
all_scenarios[scenario] <- Exctinction_risk(PVA)
}
plot(flood_lambdas,all_scenarios,type="p",cex=2,xlab="flood impact (lambda in flood year)",ylab="extinction risk")
abline(h=0.05,col="red",lwd=2)
We can present yearly fecundity and survival probabilities compactly in a projection matrix [A] which we use to project the population size year to year.
We all remember the finite-population-growth equation:
\(N_{t+1}=\lambda \cdot N_t \qquad \text{(Eq. 1)}\),
where \(N\) is abundance (as always), \(t\) is time, often in years but could be any time units, and \(\lambda\) is the multipicative growth rate over the time period \(t \rightarrow t+1\)
The matrix population growth equation looks pretty much the same!
\(\mathbf{N}_{t+1} = \mathbf{A} \cdot \mathbf{N}_{t} \qquad \text{(Eq. 2)}\),
where \(\mathbf{N}\) is a vector of abundances (abundance for all stages), and \(\mathbf{A}\) is the transition matrix, which we have seen before.
We can be more explicit about this if we re-write the above equation this way:
\(\begin{bmatrix}N_1\\ N_2\\N_3 \end{bmatrix}_{t+1}=\begin{bmatrix}0 & F_2 & F_3\\ P_{1 \rightarrow 2} & P_{2 \rightarrow 2} & 0\\ 0 & P_{2 \rightarrow 3} & P_{3 \rightarrow 3}\end{bmatrix} \cdot \begin{bmatrix}N_1\\ N_2\\N_3 \end{bmatrix}_{t} \qquad \text{(Eq. 3)}\)
Where \(P_{1 \rightarrow 2}\) is the probability of advancing from stage 1 to 2, and \(F_2\) is the fecundity of stage 2.
There are three important types of transitions.
NOTE: fecundity is NOT the same thing as birth rate, \(b\). What’s the difference?
Birth rate, \(b_t\), is the per-capita rate of offspring production for stage \(t\)
Fecundity, \(F_t\), is the _per-capita rate by which an individual of stage \(t\) contributes new offspring to the population at time \(t+1\). Sounds pretty similar, right? What’s the difference??
Fecundity also takes into account the survival rate from \(t\) to \(t+1\)!! For an adult of stage \(t\) to contribute to the next generation, it must both survive and reproduce!.
\(F_t = P_{1 \rightarrow 2} \cdot b_{t+1} \qquad \text{(Eq. 4)}\)
There is a lot we can do with matrix population models. The most obvious one is projection:
We have already seen the projection equation (Eq. 2, above). Here is how we can implement this in R:
Year1 <- projection_matrix %*% Abundance_year0 # matrix multiplication!
Let’s try it!:
First, let’s build a projection matrix:
projection_matrix <- matrix(
c(
0, 1.2, 3.1,
0.4, 0, 0,
0, 0.75, 0
)
,nrow=3,ncol=3,byrow=T
)
projection_matrix
## [,1] [,2] [,3]
## [1,] 0.0 1.20 3.1
## [2,] 0.4 0.00 0.0
## [3,] 0.0 0.75 0.0
Next, let’s build an initial abundance vector:
Abundance_year0 <- c(1000,0,0)
Abundance_year0
## [1] 1000 0 0
Now we can run the code for real!
Year1 <- projection_matrix %*% Abundance_year0 # matrix multiplication!
Year1
## [,1]
## [1,] 0
## [2,] 400
## [3,] 0
Now we have 300 individuals in stage 2!
Let’s project one more year:
Year2 <- projection_matrix %*% Year1 # matrix multiplication!
Year2
## [,1]
## [1,] 480
## [2,] 0
## [3,] 300
Here is some R code to project many years into the future!
nYears <- 20 # set the number of years to project
TMat <- projection_matrix # define the projection matrix
InitAbund <- Abundance_year0 # define the initial abundance
## NOTE: the code below can be re-used without modification:
allYears <- matrix(0,nrow=nrow(TMat),ncol=nYears+1) # build a storage array for all abundances!
allYears[,1] <- InitAbund # set the year 0 abundance
for(t in 2:(nYears+1)){ # loop through all years
allYears[,t] <- TMat %*% allYears[,t-1]
}
plot(1,1,pch="",ylim=c(0,max(allYears)),xlim=c(0,nYears+1),xlab="Years",ylab="Abundance",xaxt="n") # set up blank plot
cols <- rainbow(3) # set up colors to use
for(s in 1:3){
points(allYears[s,],col=cols[s],type="l",lwd=2) # plot out each life stage abundance, one at a time
}
axis(1,at=seq(1,nYears+1),labels = seq(0,nYears)) # label the axis
legend("topleft",col=cols,lwd=rep(2,3),legend=paste("Stage ",seq(1:nrow(TMat)))) # put a legend on the plot


Download my CV Here :Download CV
User experience encompasses all aspects of the end-user’s interaction with the company, its services, and its products
Moringa School | 2021 - 2022
Moringa School is a multi-disciplinary learning-accelerator committed to closing the skills gap in Africa’s job market by providing transformative tech-based learning.
Dedan Kimathi University Of Technology | 2021 - 2022
DeKUT is one of the most progressive University in Africa with keen focus on quality education, holistic development of students and production of relevant human resources and leaders to contribute to growth and development.
Tenwek High School | 2021 - 2022
Tenwek Boys High school was started in 1945 by the World Gospel missionaries as an intermediate school and is currently under the sponsorship of the African Gospel Church (AGC). Among those who went through the school when it was intermediate include the late Mr. Samwel Cheruiyot Langat (Former director of KLB).
I like the multiplayer video gaming as a team-building activity and as a way to de-stress. Be part of a tech team, gaming has become my personal interest and have prove its beneficial.
A reference to the sports I play on a regular basis can be a great way to enhance some of my soft skills including being a team player, being able to work well with others, or having leadership abilities.
I work in developing the
different web applications
I work in designing the
different applications
I work in developing the
different apps applications
I develop the content for bloggers
Thie photographic website was created for keeping different galleries of nature including wild animals, people & natural photos. The website was created basically using html and css
click Here to view the website
This project display the format page of a newspaper. It is created with the html and css.
click Here to view the website
This web project was created using basically html and css. The project is a bout the StreetFood website. It has the following parts which are Home ,About the site, Menu, Street Food , Catering, Reservation, Gallery and Contact.
click Here to view the website
This is an ERP system created for medical. It is specifically created for Dedan Kimathi University medical centre. The website was created basically using html for front end, php for backend and css
click Here to view the website
This is my web portfolio which showcases my work. It contains a list of different projects I have work on with a live link to GitHub, my background information, and my pictures. It is basically created using HTML and CSS
click Here to view the website
This is an environmental conservation awareness website.
It has the following features :
Home, Events, About Us, Members, Contacts and Partners pages.It is created with HTML and CSS
click Here to view the website


{%extends 'base.html' %} {% block content %}
Enjoy the latest blogs and share your experiences with others.


This div has a special class on it!
Elements can have multiple classes and the class selector still works!
This is just a regular div.


public static interface SimplePool.PoolItemCallback<T>
| Modifier and Type | Method and Description |
|---|---|
T |
createForPool()
Called by the pool when a new instance is required to populate the pool.
|
boolean |
isStale(T item)
Called by the pool when an idle item is retrieved from the pool.
|
void |
removedFromPool(T item)
Called by the pool when an item is forcibly removed from the pool - for example
when the pool size is reduced.
|
T createForPool()
boolean isStale(T item)
item
- The item.void removedFromPool(T item)
item
- The item.


Class: SolidusSubscriptions::SubscriptionOrderPromotionRule
- Inherits:
-
Spree::PromotionRule
- Object
- Spree::PromotionRule
- SolidusSubscriptions::SubscriptionOrderPromotionRule
- Defined in:
- app/models/solidus_subscriptions/subscription_order_promotion_rule.rb
Instance Method Summary collapse
-
#applicable?(promotable) ⇒ Boolean
Promotion can be applied to an entire order.
-
#eligible?(order, **_options) ⇒ Boolean
An order is eligible if it fulfills a subscription Installment.
Instance Method Details
#applicable?(promotable) ⇒ Boolean
Promotion can be applied to an entire order. Will only be true for Spree::Order
10 11 12 |
# File 'app/models/solidus_subscriptions/subscription_order_promotion_rule.rb', line 10 def applicable?(promotable) promotable.is_a? Spree::Order end |
#eligible?(order, **_options) ⇒ Boolean
An order is eligible if it fulfills a subscription Installment. Will only return true if the order fulfills one or more Installments
21 22 23 |
# File 'app/models/solidus_subscriptions/subscription_order_promotion_rule.rb', line 21 def eligible?(order, **) order.subscription_order? end |


--- kind: carrier title: Gateway Health url: http://www.medicareassured.com agent_support: 1-888-871-0417 ---
Please download and complete the Agency Demographic Sheet to get started.
Return completed sheets to contracting@rubyim.com.


3D Twin stick shooter in development with Unity3D. Featuring 6 different enemies with unique AIs, 4 maps with unique traps and mechanics. Core mechanics are an endless wave system, a score/combo system and a set of power up that the player can buy with the game credits. Role: Lead programmer. Mechanics implemented: AIs with state machines, player aim and shoot system, power ups, score system.
Two days project done during the Global Game Jam 2017 in Politecnico di Milano with other 4 programmers and 5 artists. It consists in a two players local coop game that is based on communication. It features two totally different points of view (First person and Top down) that are rendered on two different screens.
Rogue-like Point to Survive RPG where an old videogamer tries to run away from the hospital. Featuring 4 different enemies, 6 consumables, 4 player skills, 3 statistics and various possible builds.
Noir.doc is an graphic adventure based on the crime news 'Il delitto della Cattolica'. It was made during the Hackathon organized from the 'Corriere della Sera' in Milan. This game has been realized in 48 hours by four programmers and two artists.
Three weeks project made with Construct 2 in the first months of my game programming course. Pow Meow is a 2D pixel art action shooter Metal Slug alike. It features four enemies including a boss, three weapons and granades.
Two days Jam Game done in Digital Bros Game Academy internal Game Jam. It consists in a puzzle/quiz game where the player is a soccer referee and has to decide if a series of situations are faulty or clean. It`s meant to be a mobile game and it won the "Most Innovative" Award.


We use graph layout algorithms to visualize Ekşi Sözlük data by means of entry counts, author counts,
and by detecting relationships between topics through the references given inbetween topics.
Our project consists of three major parts of work:
crawling through the website and getting entry, topic and author data
visualizing the network using graph layout algorithms
analyzing the network using social network analysis techniques


Facets of the website
Complaint registry:
The user can input his or her problem in the portal's complaint section.
The input will be in the form of a text, describing the problem he or she is facing and against whom.
This will give a more profound evidence of when, how, where and by whom the victim was bullied.
Ticket generation:
A ticket will be generated for every complaint. This ticket will possess a
unique ID. This will help the consultant and the user to uniquely identify the complaint and track down
the progress made by the officials in solving the issue.
Tags:
Complaints will be classified on the basis of tags. This allows the officials to search
for problems on the basis of tags.
This will include a certain level of flexibility to the search process and the officials as well since they
can now search for tags in their area of expertise.
Data analysis:
Data will be analyzed on a regular basis and shown in the analytics dashboard.
Analytical data will include the location(s) and the tag(s) associated with the complaint
This will help in identifying the areas which are infested with the heinous crime of cyberbullying
This will also bring into our notice the types of cyberbullying occuring in those areas, including the
frequency at which the complaints are addressed and solved by the authorities.
Messaging system:
Email/sms will be sent with third party modules.


--- layout: default title: CNRS-AIST JRL --- {%- include breadcrumbs.html breadcrumbs="News" title="News" -%}
| 15/03/2021 | Fumio Kanehiro was interviewed by XYZ |
| 31/05/2020 | The paper co-authored by Abderrahmane Kheddar, Stéphane Caron, Pierre Gergondet, Andrew Comport, Arnaud Tanguy, Christian Ott, Bernd Henze, George Mesesan, Johannes Englsberger, Máximo Roa, Pierre-Brice Wieber, François Chaumette, Fabien Spindler, Giuseppe Oriolo, Leonardo Lanari, Adrien Escande, Kévin Chappellet, Fumio Kanehiro, Patrice Rabate: Humanoid robots in aircraft manufacturing recevied the 2020 IEEE Robotics and Automation Magazine Best Paper Award. |
| 13/01/2020 | The paper co-authored by Masato Tsuru, Pierre Gergondet, Tomohiro Motoda, Adrien Escande, Eiichi Yoshida, Ixchel G. Ramirez-Alpizar, Weiwei Wan, Kensuke Harada: POMDP-based action planning for the recognition of occluded objects with Humanoid robots received the 2020 International Conference on Artificial Life and Robotics (ICAROB) Young Author Award. |
| 01/04/2020 | Ko Ayusawa has received the MEXT Award for Science and Technology for young scientists. |


Train
Dataset: data1
Elapsed time: 1000s
Training output
Test output
Metrics
Accuracy: 100%
Kappa: 0.00


Syntax:
sinh number => result
cosh number => result
tanh number => result
asinh number => result
acosh number => result
atanh number => result
Arguments and Values:
number---a number.
result---a number.
Description:
These functions compute the hyperbolic sine, cosine, tangent, arc sine, arc cosine, and arc tangent functions, which are mathematically defined for an argument x as given in the next figure.
Function Definition Hyperbolic sine (e^x-e^-x)/2 Hyperbolic cosine (e^x+e^-x)/2 Hyperbolic tangent (e^x-e^-x)/(e^x+e^-x) Hyperbolic arc sine log (x+sqrt(1+x^2)) Hyperbolic arc cosine 2 log (sqrt((x+1)/2) + sqrt((x-1)/2)) Hyperbolic arc tangent (log (1+x) - log (1-x))/2
Figure 12-16. Mathematical definitions for hyperbolic functions
The following definition for the inverse hyperbolic cosine determines the range and branch cuts:
arccosh z = 2 log (sqrt((z+1)/2) + sqrt((z-1)/2)).
The branch cut for the inverse hyperbolic cosine function lies along the real axis to the left of 1 (inclusive), extending indefinitely along the negative real axis, continuous with quadrant II and (between 0 and 1) with quadrant I. The range is that half-strip of the complex plane containing numbers whose real part is non-negative and whose imaginary part is between -<PI> (exclusive) and <PI> (inclusive). A number with real part zero is in the range if its imaginary part is between zero (inclusive) and <PI> (inclusive).
The following definition for the inverse hyperbolic sine determines the range and branch cuts:
arcsinh z = log (z+sqrt(1+z^2)).
The branch cut for the inverse hyperbolic sine function is in two pieces: one along the positive imaginary axis above i (inclusive), continuous with quadrant I, and one along the negative imaginary axis below -i (inclusive), continuous with quadrant III. The range is that strip of the complex plane containing numbers whose imaginary part is between -<PI>/2 and <PI>/2. A number with imaginary part equal to -<PI>/2 is in the range if and only if its real part is non-positive; a number with imaginary part equal to <PI>/2 is in the range if and only if its imaginary part is non-negative.
The following definition for the inverse hyperbolic tangent determines the range and branch cuts:
arctanh z = log (1+z) - log (1-z)/2.
Note that:
i arctan z = arctanh iz.
The branch cut for the inverse hyperbolic tangent function is in two pieces: one along the negative real axis to the left of -1 (inclusive), continuous with quadrant III, and one along the positive real axis to the right of 1 (inclusive), continuous with quadrant I. The points -1 and 1 are excluded from the domain. The range is that strip of the complex plane containing numbers whose imaginary part is between -<PI>/2 and <PI>/2. A number with imaginary part equal to -<PI>/2 is in the range if and only if its real part is strictly negative; a number with imaginary part equal to <PI>/2 is in the range if and only if its imaginary part is strictly positive. Thus the range of the inverse hyperbolic tangent function is identical to that of the inverse hyperbolic sine function with the points -<PI>i/2 and <PI>i/2 excluded.
Examples:
(sinh 0) => 0.0 (cosh (complex 0 -1)) => #C(0.540302 -0.0)
Side Effects: None.
Affected By: None.
Exceptional Situations:
Should signal an error of type type-error if number is not a number. Might signal arithmetic-error.
See Also:
log, sqrt, Section <IP_ADDRESS> (Rule of Float Substitutability)
Notes:
The result of acosh may be a complex even if number is not a complex; this occurs when number is less than one. Also, the result of atanh may be a complex even if number is not a complex; this occurs when the absolute value of number is greater than one.
The branch cut formulae are mathematically correct, assuming completely accurate computation. Implementors should consult a good text on numerical analysis. The formulae given above are not necessarily the simplest ones for real-valued computations; they are chosen to define the branch cuts in desirable ways for the complex case.


This part prescribes policies and procedures for conducting market research to arrive at the most suitable approach to acquiring, distributing, and supporting supplies and services. This part implements the requirements of 41 U.S.C. 3306(a)(1), 41 U.S.C. 3307, 10 U.S.C. 2377, and 6 U.S.C. 796.
(a) Agencies shall—
(1) Ensure that legitimate needs are identified and trade-offs evaluated to acquire items that meet those needs;
(2) Conduct market research appropriate to the circumstances—
(i) Before developing new requirements documents for an acquisition by that agency;
(ii) Before soliciting offers for acquisitions with an estimated value in excess of the simplified acquisition threshold;
(iii) Before soliciting offers for acquisitions with an estimated value less than the simplified acquisition threshold when adequate information is not available and the circumstances justify its cost;
(iv) Before soliciting offers for acquisitions that could lead to consolidation or bundling (15 U.S.C. 644(e)(2)(A) and 15 U.S.C. 657q);
(v) Before awarding a task or delivery order under an indefinite-delivery/indefinite-quantity (ID/IQ) contract (e.g., GWACs, MACs) for a noncommercial item in excess of the simplified acquisition threshold (10 U.S.C. 2377(c)); and
(vi) On an ongoing basis, take advantage (to the maximum extent practicable) of commercially available market research methods in order to effectively identify the capabilities of small businesses and new entrants into Federal contracting that are available in the marketplace for meeting the requirements of the agency in furtherance of—
(A) A contingency operation or defense against or recovery from nuclear, biological, chemical, or radiological attack; and
(B) Disaster relief to include debris removal, distribution of supplies, reconstruction, and other disaster or emergency relief activities (see 26.205); and
(3) Use the results of market research to—
(i) Determine if sources capable of satisfying the agency’s requirements exist;
(ii) Determine if commercial items or, to the extent commercial items suitable to meet the agency’s needs are not available, nondevelopmental items are available that—
(A) Meet the agency’s requirements;
(B) Could be modified to meet the agency’s requirements; or
(C) Could meet the agency’s requirements if those requirements were modified to a reasonable extent;
(iii) Determine the extent to which commercial items or nondevelopmental items could be incorporated at the component level;
(iv) Determine the practices of firms engaged in producing, distributing, and supporting commercial items, such as type of contract, terms for warranties, buyer financing, maintenance and packaging, and marking;
(v) Ensure maximum practicable use of recovered materials (see Subpart 23.4) and promote energy conservation and efficiency;
(vi) Determine whether consolidation is necessary and justified (see 7.107-2) (15 U.S.C. 657q);
(vii) Determine whether bundling is necessary and justified (see 7.107-3) (15 U.S.C. 644(e)(2)(A)).
(viii) Assess the availability of electronic and information technology that meets all or part of the applicable accessibility standards issued by the Architectural and Transportation Barriers Compliance Board at 36 CFR Part 1194 (see Subpart 39.2).
(b) When conducting market research, agencies should not request potential sources to submit more than the minimum information necessary.
(c) If an agency contemplates consolidation or bundling, the agency—
(1) When performing market research, should consult with the agency small business specialist and the local Small Business Administration procurement center representative (PCR). If a PCR is not assigned, see 19.402(a); and
(2) Shall notify any affected incumbent small business concerns of the Government's intention to bundle the requirement and how small business concerns may contact the appropriate Small Business Administration procurement center representative (see 7.107-5(a))
(d) See 10.003 for the requirement for a prime contractor to perform market research in contracts in excess of $5.5 million for the procurement of items other than commercial items in accordance with section 826 of Public Law 110-181.
(a) Acquisitions begin with a description of the Government’s needs stated in terms sufficient to allow conduct of market research.
(b) Market research is then conducted to determine if commercial items or nondevelopmental items are available to meet the Government’s needs or could be modified to meet the Government’s needs.
(1) The extent of market research will vary, depending on such factors as urgency, estimated dollar value, complexity, and past experience. The contracting officer may use market research conducted within 18 months before the award of any task or delivery order if the information is still current, accurate, and relevant. Market research involves obtaining information specific to the item being acquired and should include—
(i) Whether the Government’s needs can be met by—
(A) Items of a type customarily available in the commercial marketplace;
(B) Items of a type customarily available in the commercial marketplace with modifications; or
(C) Items used exclusively for governmental purposes;
(ii) Customary practices regarding customizing, modifying or tailoring of items to meet customer needs and associated costs;
(iii) Customary practices, including warranty, buyer financing, discounts, contract type considering the nature and risk associated with the requirement, etc., under which commercial sales of the products or services are made;
(iv) The requirements of any laws and regulations unique to the item being acquired;
(v) The availability of items that contain recovered materials and items that are energy efficient;
(vi) The distribution and support capabilities of potential suppliers, including alternative arrangements and cost estimates; and
(vii) Size and status of potential sources (see Part 19).
(2) Techniques for conducting market research may include any or all of the following:
(i) Contacting knowledgeable individuals in Government and industry regarding market capabilities to meet requirements.
(ii) Reviewing the results of recent market research undertaken to meet similar or identical requirements.
(iii) Publishing formal requests for information in appropriate technical or scientific journals or business publications.
(iv) Querying the Governmentwide database of contracts and other procurement instruments intended for use by multiple agencies available at https://www.contractdirectory.gov/contractdirectory/ and other Government and commercial databases that provide information relevant to agency acquisitions.
(v) Participating in interactive, on-line communication among industry, acquisition personnel, and customers.
(vi) Obtaining source lists of similar items from other contracting activities or agencies, trade associations or other sources.
(vii) Reviewing catalogs and other generally available product literature published by manufacturers, distributors, and dealers or available on-line.
(viii) Conducting interchange meetings or holding presolicitation conferences to involve potential offerors early in the acquisition process.
(c) If market research indicates commercial or nondevelopmental items might not be available to satisfy agency needs, agencies shall reevaluate the need in accordance with 10.001(a)(3)(ii) and determine whether the need can be restated to permit commercial or nondevelopmental items to satisfy the agency’s needs.
(d)(1) If market research establishes that the Government’s need may be met by a type of item or service customarily available in the commercial marketplace that would meet the definition of a commercial item at Subpart 2.1, the contracting officer shall solicit and award any resultant contract using the policies and procedures in Part 12.
(2) If market research establishes that the Government’s need cannot be met by a type of item or service customarily available in the marketplace, Part 12 shall not be used. When publication of the notice at 5.201 is required, the contracting officer shall include a notice to prospective offerors that the Government does not intend to use Part 12 for the acquisition.
(e) Agencies should document the results of market research in a manner appropriate to the size and complexity of the acquisition.
The contracting officer shall insert the clause at 52.210-1, Market Research, in solicitations and contracts over $5.5 million for the procurement of items other than commercial items.


Pharmacy DoS Quality Payments
Use this service to check and update Directory of Service (DoS) records for your pharmacy.
You can either:
- confirm that the details are correct
- tell us what needs to be changed
You will need to know:
- the ODS (F) code for your pharmacy
- the address, postcode and telephone number
- the opening times for each of your pharmacy services
Many pharmacies will have multiple records on the DoS and you need to check all of them.
We expect this to take approximately 5–10 minutes per service.
Important dates
Opens:
2nd October 2017
Closes:
24th November 2017
Contact
DoS Profile Updater queries
<EMAIL_ADDRESS>0300 303 4034
Pharmacy DoS Quality Payments
england.communitypharmacy@nhs.net


Something I'm Good At By: Brett Eldredge
Wanna Be That Song By: Brett Eldredge
Lose My Mind By: Brett Eldredge
Going Away For A While By: Brett Eldredge
Change


'Avenue 5' Trailer: Hugh Laurie Captains a Luxury Space Cruise Gone Awry in HBO Comedy From 'Veep' Creator (Video)
New series from Armando Iannucci debuts in January
by Reid NakamuraHBO released the first trailer for “Avenue 5,” the new space comedy from “Veep” creator Armando Iannucci.
Set 40 years in the future, “Avenue 5” stars Hugh Laurie as Ryan Clark, the confident and suave captain of a space cruise ship that has luxury amenities like gourmet buffets, a spa, an observation deck and yoga classes. As shown in the trailer, however, things don’t go exactly according to plan.
Avenue 5’s eight-week journey around Saturn is interrupted when the ship suddenly encounters technical difficulties, and it’s up to Ryan and his crew to calm the disgruntled passengers and find a way to deal with unexpected events onboard – though they may or may not be equipped for the task.
Also Read:
In addition to “House” and “Veep” alum Laurie, the cast also includes Josh Gad, Zach Woods, Rebecca Front, Suzy Nakamura, Lenora Crichlow, Nikki Amuka-Bird and Ethan Phillips.
Iannucci created the series and co-wrote the series with Simon Blackwell and Tony Roche. Executive producers include Kevin Loader, Blackwell, Roche and Will Smith. Peter Fellows is co-executive producer and Steve Clark-Hall is producer.


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Checking this option will disable regular polling (cron) for changes in GitHub
and will try to create a GitHub hook. Creating a GitHub hook requires that the user
which is specified in the GitHub Pull Request Builder configuration has
admin rights to the specified repository.
If you want to create a hook manually set it for event types:
issue_comment
, pull_request
and url http://yourserver.com/jenkins/ghprbhook/
.
Your Jenkins server must be accessible from internet.


| Contents | Previous | Next |
Java Management Extensions Technology (JMX) became a standard part of the Java platform in the Java Platform Standard Edition (Java SE) 5.0. The JMX technology was developed through the Java Community Process (JCP) as two closely related Java Specification Requests (JSRs). The versions of the JSRs implemented in Java SE 5.0 are detailed in the following sections.
The Java SE 6 platform implements version 1.4 of the JMX Specification (Maintenance Release, October 2006). It incorporates the modifications listed in the errata provided with the download.
The Java SE 6 platform implements version 1.4 of the JMX Remote API Specification (Maintenance Release, October 2006).
In addition to standard RMI and RMI/IIOP connectors, JSR 160 also defines optional JMX Messaging Protocol (JMXMP) connectors based on TCP sockets. The Java SE platform does not include these optional connectors. However, you might want to use JMXMP connectors if, for example, you require a more advanced level of security.
If you want to use a JMXMP connector, download the
JSR 160 Reference Implementation from the download page specified
at the beginning of this section, and add the jmxremote_optional.jar
file to your classpath. You
will find examples of use of JMXMP connectors in the JMX Remote API
Tutorial included with the JSR 160 Reference Implementation.
| Contents | Previous | Next |


@import helper.CSRF @import uk.gov.hmrc.play.views.html.helpers._ @import config.FrontendAppConfig @()(implicit request: Request[_], messages: Messages) @contentHeader = {
Your application will be reviewed by HM Revenue and Customs.
The review process can take up to 14 days. You'll get an email when the decision has been made.
You'll need to sign in to this website to see the decision.
If you need to make a change to your application, email savings.audit@@hmrc.gsi.gov.uk.
}


"I can't tell you how many times I've bitten into a juicy hamburger and then realized it was Friday during Lent. Thanks Lent Alert!"
~ Pope Francis I
"I won't give up Lent Alert for Lent!"
~ Pope John Paul II
"If you don't want to eat meat, this can't be beat!"
~ Pope Benedict XVI
"Of all the mailing lists that alert you to not eat meat on Fridays during Lent, this one is the best."
~ Michael Squitieri, Creator of Lent Alert


{% load static %}
Good Read
Home
(current)
Run Model
{% verbatim %}
AI - Article Suggestions
{{a.title}}
{{a.summary}}
Read full article on source site →
Select Keywords
{{t.keyword}}
Go!
{% endverbatim %}


This is my super cool caption.
Last updated 3 mins ago
This is my kind of cool caption.
Last updated 5 mins ago


Green Room Booking
Booking Procedure:
The Green Screen Room (SA48) forming part of the School of Computing Science and Digital Media, Robert Gordon University is located in the Garthdee House annexe towards the west end of campus. The rooms general dimensions are 7.8 x 7.6 meters, providing a total floor area of 58 square meters (over 620 square feet). The room includes a cyc/infinity wall on three faces thereby assisting to get a high quality key from the recorded footage.
The room is secured by key and padlock code, both of which can be obtained from N425. Keys must be returned to N425 or School Office by 5pm. Students must also provide list of all other students undertaking filming with them in the room.
Lighting & Power:
All lighting has keyed to standard daylight temperatures. Fixed ceiling lighting provides both general room illumination and lighting on the primary green screen surfaces and are controlled from a touch screen panel. Additional lighting is supplied of a selection of Coolite 9 and Coolite 655’s providing the equivalent of over 6000 watts. The room is equipped with nine retractable four gang sockets mounted in the ceiling. Two pairs of double gang sockets may also be found above the motion capture railing infrastructure, close to ceiling level, on each of the primary green screen walls.
Motion Capture:
A large area of the room is given over to an Optitrack 12 camera Flex 13 Motion Capture system. This is mounted on a railing system at a height of 2.5 meters. A HP Z400 Workstation with a Core i7 processor & 24GB of RAM is used to capture the actors movements through the use of Optitrack’s Motive MoCap system. The installation occupies and area 7.5 x 6.2 meters amounting to 46 square meters or 500 square feet.
Libec Swift Jib 50:
You may also make use of a remotely operated Jib system, specifically the Libec Swift Jib 50 with T102B tripod and DL08 dolly. It also feature the REMO30, a remote tilt and pan head, supporting cameras up to five kilograms.
Terms & Conditions:
Damages & Breakages:
The student who books out the room is responsible for the rest of the group using the room, therefore they will be liable for any damages or breakages in the room. If you intend on using the room with a group of students, please ensure you have their full name and matric number when booking the room.


Programming language agnostic Software Engineer whose passion for programming comes from taking on a problem and overcoming every obstacle or technical challenge to solve it. This passion is equally matched with the desire to keep solutions as minimal and maintainable as possible, only introducing complexity necessary to solve a given problem without sacrificing reusability and best practices of Object Oriented Design, and testability. Lover of all things Javascript and admirer of anything front-end. Passionate learner and believer that programmers never stop educating themselves.
SKILLS
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Mac OSX, Windows (XP, Vista, 7, 8, 10)
Software Packages
Sublime Text, Eclipse, Atom, Photoshop, Dreamweaver
Programming Languages
Javascript, Ruby, Java, C++
Web Technologies
HTML, CSS, jQuery, Angular.js, Web Services, Ruby on Rails, Sass, RailsJS (in learning)
DataBases
SQLite3, Firebase
Other
Git, RESTful Practices, TDD, API systems, Radio Frequencies, IP, Digital Video Networks, Agile/ScrumOther


US military academy athletes can now delay service, go pro
by LOLITA C. BALDORWASHINGTON (AP) - Defense Secretary Mark Esper has issued new guidelines that will allow athletes attending the nation’s military academies to seek waivers to delay their service and play professional sports immediately upon their graduation.
A memo signed Friday by Esper requires athletes going pro to get approval from the defense secretary. It says they must eventually fulfill their military obligation or repay the cost of their college education.
The memo was obtained by The Associated Press. President Donald Trump directed the Pentagon in May to come up with a way to allow athletes to play professional sports immediately upon graduation.
TOP STORIES
Skeptics chuckle as climate activist Greta Thunberg sets sail for Europe on 'plastic yacht'
Reckoning coming for Adam Schiff for impeachment inquiry
Evangelist Franklin Graham calls impeachment hearing 'a day of shame for America'
The Pentagon in 2018 rescinded a policy allowing athletes from the service academies to go straight to the pros. Then-Defense Secretary Jim Mattis argued that the academies exist to train officers.
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Federated Stats implements basic statistical algorithms such as variance and regression in a federated fashion using HyFed API.
Federated Stats implements basic statistical algorithms such as variance and regression in a federated fashion using HyFed API.


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SOTTO COFFEE TABLE
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TRE I TABLE
BRANDON LOUNGE
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ISOLA LOUNGE
BRANDON SECTIONAL
DOUGLAS SECTIONAL
MITOSI SECTIONAL
NICHOLAS I SECTIONAL
NICHOLAS II SECTIONAL
SALON SECTIONAL
SHEA I SECTIONAL
TRE II SECTIONAL
BRANDON SOFA
CHICAGO I SOFA
CHICAGO II SOFA
COVE SOFA
PALMS LOVESEAT
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At the age of 4 years Bertie began dancing with Holt Morris. This early love of traditional music led to the desire to play an instrument himself. At the age of 6 he borrowed a melodeon and begun to learn from a fellow morris man. At 8 he wished for an instrument to call his own and busked at The Trowbridge Villiage Pump Festival, earning enough over three days to buy his very first Hohner Erica.
Whilst busking at the pump festival Bertie was approached by Tim Van Eyken and proceeded to be taught by him for the next year. Since then, Bertie has attended numerous workshops hosted by Andy Cutting, Jamie Huddlestone, Luke Daniels and Karen Tweed and has been taught since the age of 14 by Ruth Behan.
In April 2013 Bertie attended a melodeon building workshop led by Emmanual Pariselle to create a melodeon with a unique C#/G/Reversals layout. This has rapidly become his favourite instrument, allowing a diverse range not offered by his others. He is currently awaiting a custom D/G/acc. 18 bass Castagnari.
In addition to years of performance with Holt Morris, Bertie has played with bands Spill the Whisky, The Merv Grist Players and alongside guitarist Tim Webb - as well as solo performances at the The Bath Folk Festival and The Holt Music Festival.
If you would like to know more please get in touch below.


Site Map
- Home Page
- About the Website
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- 201901 Belgium, Paris, and Barcelona
- Chapter 11: Adios? Welcome to Europe (Brussels, Belgium)
- Chapter 12: (Paris, France)
- Chapter 13: Santiago, and Adios? (Barcelona, Spain)
- 201812 Latin America Exploration
- Chapter 0: Before the Exploration Starts
- Chapter 1: Flying aross the Oceans (Taipei - Lima)
- Chapter 2: Former Capital of Empire's Colony (Lima, Peru)
- Chapter 3: Capital of the Ancient Empire (Cusco, Peru)
- Chapter 4: March by Our Dreams (Cusco - Aguas Calientes)
- Chapter 5: Lost City of the Incas (Machu Picchu)
- Chapter 6: the Strike (Cusco - La Paz)
- Chapter 7: Witches's Market. (La Paz, Bolivia)
- Chapter 8: Mirror of the sky - Uyuni (Uyuni, Bolivia)
- Chapter 9: the Desert - San Pedro de Atacama (San Pedro de Atacama, Chile)
- Chapter 10: Santiago, and Adios? (Santiago, Chile)


vignettes/articles/cnsl_find_marker.Rmd
cnsl_find_marker.Rmd
This section comes together with the previous section Differential Expression. The basic strategy singleCellTK (SCTK) uses to find biomarkers is to iteratively identify the significantly up-regulated features of each group of cells against all the other cells. This means, the function we have (findMarkerDiffExp()
) is a wrapper of functions that do differential expression (DE) analysis, which would be called in a loop. For the detail of the functions we have for DE analysis, please refer to runDEAnalysis()
and the documentation linked to above.
The methods we have for marker detection are listed below.
| Method | Citation |
|---|---|
| wilcox | Aaron Lun and Jonathan Griffiths, 2016. |
| MAST | Greg Finak and et al., 2015 |
| Limma | Gordon Smyth and et al., 2004 |
| DESeq2 | Michael Love and et al., 2014 |
| ANOVA | Jeffrey T. Leek and et al., 2020 |
As per SCTK’s strategy, the primary input is limited to an SingleCellExperiment (SCE) object, which has been through preprocessing steps with cluster labels annotated. While the iteration is a fixed pattern, the parameters needed are rather simple:
sce <- findMarkerDiffExp(inSCE = sce,
useAssay = "logcounts",
method = "MAST",
cluster = "cluster",
covariates = NULL,
log2fcThreshold = 0.25,
fdrThreshold = 0.05)
Here all arguments execpt the input SCE object (inSCE
) are set by default. method
can only be chosen from the table above. cluster
and covariates
should be given a single string which is present in names(colData(inSCE))
. cluster
is required for grouping cells, while covariates
is optional for DE detection. log2fcThreshold
and fdrThreshold
are numeric and has to be set in plausible range. log2fcThrshold
has to be positive and fdrThreshold
has to be greater than zero and less than one.
The returned SCE object will contain the updated information of the markers identified in its metadata
slot.
To demonstrate a simple and clear example, here we use the “PBMC-3k” dataset from “10X” which can be easily imported with SCTK functions. The preprocessing only includes necessary steps to get cluster labels (i.e. QC and filtering are excluded).
library(singleCellTK)
pbmc3k <- importExampleData("pbmc3k")
pbmc3k <- scaterlogNormCounts(pbmc3k, "logcounts")
# Go through the Seurat curated workflow to get basic clusters
pbmc3k <- seuratNormalizeData(inSCE = pbmc3k, useAssay = "counts")
pbmc3k <- seuratFindHVG(inSCE = pbmc3k, useAssay = "seuratNormData")
pbmc3k <- seuratScaleData(inSCE = pbmc3k, useAssay = "seuratNormData")
pbmc3k <- seuratPCA(inSCE = pbmc3k, useAssay = "seuratScaledData")
pbmc3k <- seuratRunUMAP(pbmc3k)
pbmc3k <- seuratFindClusters(inSCE = pbmc3k, useAssay = "seuratScaledData")
# Optional visualization
plotSCEDimReduceColData(inSCE = pbmc3k,
colorBy = "Seurat_louvain_Resolution0.8",
conditionClass = "factor",
reducedDimName = "seuratUMAP")
Then we call findMarkerDiffExp()
on the clustered data, with the cluster annotation just attached, which by default named with "Seurat_louvain_Resolution0.8"
.
pbmc3k <- findMarkerDiffExp(inSCE = pbmc3k,
method = "Limma", # Runs fastest
useAssay = "logcounts",
cluster = "Seurat_louvain_Resolution0.8")
After this, the marker genes, together with their statistics, of each cluster will be concatenated in one table. This table can be extracted with:
markerTable <- metadata(pbmc3k)$findMarker
head(markerTable)
| Gene | Log2_FC | Pvalue | FDR | Seurat_louvain_Resolution0.8 | clusterExprPerc | ControlExprPerc | clusterAveExpr | |
|---|---|---|---|---|---|---|---|---|
| 74 | NOSIP | 0.5152459 | 0 | 0 | 0 | 0.6709091 | 0.3641860 | 1.0032117 |
| 121 | IL7R | 0.4715791 | 0 | 0 | 0 | 0.6418182 | 0.3404651 | 0.9947208 |
| 126 | CD7 | 0.4285577 | 0 | 0 | 0 | 0.6200000 | 0.3018605 | 0.8756739 |
| 410 | IL7R | 0.7250848 | 0 | 0 | 1 | 0.7448560 | 0.3265583 | 1.2137737 |
| 7 | CD2 | 0.5424127 | 0 | 0 | 1 | 0.6502058 | 0.2439024 | 0.8673990 |
| 601 | LCK | 0.3528016 | 0 | 0 | 1 | 0.6090535 | 0.3044264 | 0.7560978 |
Similarly to the Differential Expression section, we also provide a automated and organized heatmap plotting for the markers:
plotMarkerDiffExp(pbmc3k)
Note that when plotting the heatmap, the genes that are identified as up-regulated in multiple clusters will be considered only for the one cluster with the highest fold-change, while all of them are still kept in the table in metadata
.


$0600-$06FF/1536-1791: Buffer 3 ROM-Reference: STA $0600 : $C8C8 STA $0601 : $C8CD STA $0602 : $C8D2 Previous Page / Next Page


Jackky Bhagnani Brings DJ Super Sako’s Arabic Song ‘Mi Gna’ To India
The original version had released in 2016 and was a chartbuster.
by IANSActor-producer Jackky Bhagnani has acquired rights to create the Indian adaptation of the Arabic song, “Mi Gna” by Armenian-American DJ Super Sako.
“Super Sako’s voice and talent are inimitable and ‘Mi Gna’ is a song that had me hooked to it from the moment I heard it. Meeting him in Los Angeles was the universe conspiring to make this collaboration happen. I’m very excited to be working with him,” said Jackky.
This is for his music label Jjust Music.
Super Sako is looking forward to collaborating with the label. “When I met Jackky in Los Angeles, his vision for music and his openness to creating new experiences inspired me and I knew at that instant that he would be the best person to create the Indian adaptation of my song,” he said.
The original version had released in 2016 and was a chartbuster.
The new version of the track will be joining the list of other songs like “Prada” and “Choodiyan” released under Jackky’s label.


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---
# This file is licensed under the MIT License (MIT) available on
# http://opensource.org/licenses/MIT.
layout: development-sidebar
id: development
breadcrumbs:
- bitcoin
- bcc
- bcc contribute
- Code
---
{% translate involvetxt1 development %}
{% translate involvetxt2 development %}
{% capture markdown %}
*To report an issue, please see the [bug reporting][bcc contribute issues] page.*
## Code Review
Bitcoin Core is security software that helps protect assets worth
billions of dollars, so every code change needs to be reviewed by
experienced developers.
It can take a long time for other developers to review your pull
requests. Remember that all reviewers are taking time away from their
own projects to review your pull requests, so be patient and respectful
of their time.
Please also consider helping to review other people's pull requests. You
don't need to be an expert in Bitcoin, the Bitcoin Core codebase, or C++
(although all these things help). There are almost always [open pull
requests][bcc pulls] that any programmer can review.
## Starter Projects
Do you want to begin coding for Bitcoin Core but don't have a specific
improvement in mind? Here are a few ideas:
- **Fix existing issues:** the [issue tracker][bcc issues] is the
best place to find a useful way to contribute to Bitcoin Core.
Before starting to write any patches for issues you find, you may
want to comment on the issue to make sure nobody else is already
working on it.
- **Write tests:** Bitcoin Core is covered by many tests, but patches
that improve test coverage are always welcome and are a great way to
build familiarity with the codebase. See the documentation about
[automated testing][bcc automated testing].
{% include references.md %}
{% endcapture %}
{% if page.lang == 'en' %}
{{ markdown | markdownify }}
{% endif %}
{% translate devcommunities %}
{% translate devcommunitiesintro %}
- {% translate ircjoin %}
- {% translate slack %}
- {% translate stackexchange %}
- {% translate bitcointalkdev %}
{% translate contributors %}
{% translate contributorsorder %}
{% for c in site.corecontributors %}
{% endfor %}
{% translate more %}
{% case page.lang %}
{% when 'da' or 'es' or 'fr' or 'pl' or 'ro' or 'sl' or 'sv' or 'tr' or 'el' or 'bg' or 'ru' or 'uk' or 'ar' or 'fa' or 'hi' or 'ko' or 'zh_TW' %}
{% else %}
Want to contribute to a different project?
{% endcase %}
- Armory - A wallet with enhanced security features, written in C++.
- BFGMiner - A modular miner, written in C.
- Bitcoin Wallet - A SPV wallet for Android, written in Java.
- bitcoinj - A library for SPV wallets, written in Java.
- btcd - A full node, written in Go.
- btcwallet - A hierarchical deterministic wallet daemon, written in Go.
- ckpool - A fast mining pool server application, written in C.
- Electrum - A fast server-trusting wallet, written in Python.
- Eloipool - A fast mining pool server application, written in Python.
- Haskoin - An implementation of the Bitcoin protocol, written in Haskell.
- Libbitcoin - A cross-platform development toolkit, written in C++.
- Libbitcoin Server - A full node and query server, built on libbitcoin.
- Libbitcoin Explorer - A command line tool, built on libbitcoin.
- Libblkmaker - A client library for the getblocktemplate mining protocol, written in C.
- NBitcoin - A cross-platform library, written in C#.
- picocoin - A tiny library with lightweight client and utilities, written in C.
- python-bitcoinlib - A library for structures and protocols, written in Python.
- Python Blkmaker - A client library for the getblocktemplate mining protocol, written in Python.
- {% translate moremore %}
{% if page.lang == 'en' %}
{% endif %}


Great Forest [aq25], forest, in Mandoria, peasants: 163
Last updated Turn #144
Great Forest [aq25], forest, in Mandoria, peasants: 163
------------------------------------------------------------------------
28: It has become quite windy.
30: It has stopped raining.
30: The population grows by one peasant.
Routes leaving Great Forest:
North, forest, to Great Forest [ap25], 8 days
Garrison [ht9y], garrison, uncontrolled, with two peasants
East, forest, to Great Forest [aq26], 8 days
Garrison [bn3g], garrison, Mandor Confederacy, with ten workers
South, mountain, to Mandor Mountains [ar25], 10 days
West, mountain, to Mandor Mountains [aq24], 10 days
It is windy.
Seen here:
Garrison [ck6m], garrison, uncontrolled, with four peasants


This document describes the general architecture of Pythonwin. It describes the general design and interface to MFC.
After reading this, you should read the document and view architecture documentation.
For each MFC object created, there are usually 3 "objects" floating around. Although this may initially seem confusing, it does provide significant flexibility.
In general this complexity is hidden from view. The programmer usually only ever deals with a single object, and this object manages all others. However, an understanding if the implementation will assist in advanced programming techniques.
There is a quick example which shows all this in action.
For every window, toolbar, document etc. that exists in Pythonwin, there is a C++ object. In some cases this object may be a standard MFC object, as found in the MFC DLL's. In other cases, the C++ object will be derived from a standard MFC object, and can be found in win32ui.pyd.
Often, these C++ objects will not be aware that there is Python support behind them.
The win32ui module provides a large number of types, each one usually associated with an MFC C++ object.. The naming conventions for these objects is of the form "Py{MFC_Name}" - eg, PyCDocument provides the functionality of an MFC CDocument, PyCDialog for a CDialog.
There is a form of inheritance used for these objects. Each object provides methods from its derived class. A PyCDialog is derived from a PyCWnd, and therefore has all PyCWnd methods available. However, this is as far as the inheritance extends, as Python types are more restrictive than Python classes.
Each method that a win32ui type provides is generally just code for extracting Python arguments and making the call to the associated C++ object.
These objects and methods are defined in Pythonwin.hlp (available from the Pythonwin help menu.)
In object.py, there is a base class "Object". This provides 2 key functions.
The end result of this is that a class derived from "Object" looks just like a win32ui object, and can be used as such. In fact, there is rarely a reason to use the underlying object directly.
If you like you can skip this, and jump straight to the example below. It makes more sense in action!
Pythonwin provides support for many "virtual" functions. A "virtual" function is defined as a virtual C++ MFC function which has deferred its implementation to a Python object. To explain, I will use the example of a document.
In Python, it is possible to create a PyCDialog object by using win32ui.CreateDialog(). This will create both a PyCDialog object, and a C++ CDialog object. For dialogs to be useful to a programmer, it must be possible to define a method to be called when the dialog initialises (i.e., when the C++ OnInitDialog virtual method is called). Normally, a programmer would initialise the values of controls etc. at this time. To support this, the C++ OnInitDialog implementation calls Python to handle the call. In this example, OnInitDialog is a "virtual" function.
Each win32ui type supports being "attached" to a Python class instance. When a virtual function is called, the Python class instance associated with the object is checked to see if it has a method with the same name. If so, the method is called.
More details on this can be found in the document and view architecture documentation.
>>> import win32ui # import the base win32ui module.
>>> import dialog # import dialog.py
>>> d=dialog.Dialog(win32ui.IDD_SIMPLE_INPUT)
>>> d
<Dialog instance at 886c78>
This creates an instance of class Dialog, defined in dialog.py. Dialog is derived from Object (via Wnd). To see the underlying win32ui type:
>>> d._obj_
object 'PyCDialog' - assoc is 002F3278, vf=True, ch=0, mh=2, kh=0
>>>
This output shows the C++ CDialog object is at address 0x002F3278
, that there is a virtual function handler (i.e., the class instance "d"), that 2 messages have hooks, and no command or keyboard handlers are installed.
Even though the DoModal() method is implemented in the underlying win32ui type, the class object can be used just like the win32ui object. Thus:
>>> d.DoModal()
1
>>>
To see virtual functions in action
>>> class MyDialog(dialog.Dialog):
... def OnInitDialog(self, msg):
... self.GetDlgItem(win32ui.IDC_PROMPT1).SetWindowText("Hello")
... return 1
...
>>> d=MyDialog(win32ui.IDD_SIMPLE_INPUT)
>>> d.DoModal()
1
Note the prompt on the dialog box is now "Hello".


--- layout: example categories: example/v1.0.0 version: v1.0.0 title: Reorder marker list based on proximity description: Drag the primary marker on the map to re-order the menu listing based on proximity. tags: - ui ---


Top 3 jobs
The release of Apple Silicon-based Macs at the end of last year generated a flurry of news coverage and
some surprises at the machine’s performance. This post details some background information on the
experience of porting Firefox to run natively on these CPUs.
We’ll start with some background on the Mac transition and give an overview of Firefox internals that
needed to know about the new architecture, before moving on to the concept of Universal Binaries.
We’ll then explain how DRM/EME works on the new platform, talk about our experience with macOS Big Sur,
and discuss various updater problems we had to deal with. We’ll conclude with the release and an
overview of various other improvements that are in the pipeline.


| public | ParsingLog() |
| public | ParsingLog(int maxLineLength_) |
| public virtual | ~ParsingLog() |
| public abstract void | DecIndent() |
| public abstract void | IncIndent() |
| public virtual int | MaxLineLength() const |
| public abstract void | WriteBeginRule(const String<uchar>& ruleName) |
| public abstract void | WriteEndRule(const String<uchar>& ruleName) |
| public abstract void | WriteFail() |
| public abstract void | WriteSuccess(const String<uchar>& match) |
| public abstract void | WriteTry(const String<uchar>& s) |
| private int | maxLineLength |


CP
Section: User Commands (1)Updated: June 2012
Index Return to Main Contents
NAME
cp - copy files and directoriesSYNOPSIS
cp [OPTION]... [-T] SOURCE DESTcp [OPTION]... SOURCE... DIRECTORY
cp [OPTION]... -t DIRECTORY SOURCE...
DESCRIPTION
Copy SOURCE to DEST, or multiple SOURCE(s) to DIRECTORY.
Mandatory arguments to long options are mandatory for short options too.
- -a, --archive
- same as -dR --preserve=all
- --backup[=CONTROL]
- make a backup of each existing destination file
- -b
- like --backup but does not accept an argument
- --copy-contents
- copy contents of special files when recursive
- -d
- same as --no-dereference --preserve=links
- -f, --force
- if an existing destination file cannot be opened, remove it and try again (redundant if the -n option is used)
- -i, --interactive
- prompt before overwrite (overrides a previous -n option)
- -H
- follow command-line symbolic links in SOURCE
- -l, --link
- link files instead of copying
- -L, --dereference
- always follow symbolic links in SOURCE
- -n, --no-clobber
- do not overwrite an existing file (overrides a previous -i option)
- -P, --no-dereference
- never follow symbolic links in SOURCE
- -p
- same as --preserve=mode,ownership,timestamps
- --preserve[=ATTR_LIST]
- preserve the specified attributes (default: mode,ownership,timestamps), if possible additional attributes: context, links, xattr, all
- -c
- same as --preserve=context
- --no-preserve=ATTR_LIST
- don't preserve the specified attributes
- --parents
- use full source file name under DIRECTORY
- -R, -r, --recursive
- copy directories recursively
- --reflink[=WHEN]
- control clone/CoW copies. See below.
- --remove-destination
- remove each existing destination file before attempting to open it (contrast with --force)
- --sparse=WHEN
- control creation of sparse files. See below.
- --strip-trailing-slashes
- remove any trailing slashes from each SOURCE argument
- -s, --symbolic-link
- make symbolic links instead of copying
- -S, --suffix=SUFFIX
- override the usual backup suffix
- -t, --target-directory=DIRECTORY
- copy all SOURCE arguments into DIRECTORY
- -T, --no-target-directory
- treat DEST as a normal file
- -u, --update
- copy only when the SOURCE file is newer than the destination file or when the destination file is missing
- -v, --verbose
- explain what is being done
- -x, --one-file-system
- stay on this file system
- -Z, --context=CONTEXT
- set security context of copy to CONTEXT
- --help
- display this help and exit
- --version
- output version information and exit
By default, sparse SOURCE files are detected by a crude heuristic and the corresponding DEST file is made sparse as well. That is the behavior selected by --sparse=auto. Specify --sparse=always to create a sparse DEST file whenever the SOURCE file contains a long enough sequence of zero bytes. Use --sparse=never to inhibit creation of sparse files.
When --reflink[=always] is specified, perform a lightweight copy, where the data blocks are copied only when modified. If this is not possible the copy fails, or if --reflink=auto is specified, fall back to a standard copy.
The backup suffix is `~', unless set with --suffix or SIMPLE_BACKUP_SUFFIX. The version control method may be selected via the --backup option or through the VERSION_CONTROL environment variable. Here are the values:
- none, off
- never make backups (even if --backup is given)
- numbered, t
- make numbered backups
- existing, nil
- numbered if numbered backups exist, simple otherwise
- simple, never
- always make simple backups
As a special case, cp makes a backup of SOURCE when the force and backup options are given and SOURCE and DEST are the same name for an existing, regular file.
AUTHOR
Written by Torbjorn Granlund, David MacKenzie, and Jim Meyering.REPORTING BUGS
Report cp bugs to<EMAIL_ADDRESS>coreutils home page: <http://www.gnu.org/software/coreutils/>
General help using GNU software: <http://www.gnu.org/gethelp/>
Report cp translation bugs to <http://translationproject.org/team/>
COPYRIGHT
Copyright © 2010 Free Software Foundation, Inc. License GPLv3+: GNU GPL version 3 or later <http://gnu.org/licenses/gpl.html>.This is free software: you are free to change and redistribute it. There is NO WARRANTY, to the extent permitted by law.
SEE ALSO
The full documentation for cp is maintained as a Texinfo manual. If the info and cp programs are properly installed at your site, the command- info coreutils aqcp invocationaq
should give you access to the complete manual.
Index
This document was created by man2html, using the manual pages.
Time: 05:29:02 GMT, December 24, 2015