Based on Shereef's talk, I think that the DBC experience will be, in part, an excercise in normalizing vulnerability. It's challenging to say to other people, 'I don't get it' and it's hard not to internalize not understanding something. What I have noticed over the past week, however, is that I am relieved when I make the decision to ask for help. So, I'm just going to have to keep pushing myself to ask questions until it no longer feels uncomfortable (even if that never happens).
It was comforting to hear Shereef's San Francisco to Seattle analogy when comparing students' varying levels of experience. The analogy made the DBC experience feel less 'out of my league' and is a good indication of just how much more everyone will be learning in the coming 18 weeks.
Super excited to learn as much as I can from everyone!


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'Shocking' - Huddersfield fans have mixed feelings after Birmingham City stalemate
Latest Birmingham City news | Blues had to settle for a point in their Sky Bet Championship clash against the Terriers
by Mark WakefieldHuddersfield Town fans have been giving their verdict on the 1-1 draw with Birmingham City on Saturday.
Blues came from a goal behind to earn a point at the John Smith’s Stadium in their first game back after the November international break.
Fraizer Campbell opened the scoring for the Terriers before Marc Roberts equalised for Blues with just over 10 minutes left to play.
Blues now lie in 15th place in the Championship table going into Wednesday night’s trip to face Sheffield Wednesday at Hillsborough.
Here is what Huddersfield supporters had to say after the final whistle at the John Smith’s Stadium.
Daniel Peckett: “Lack of leaders on the pitch going forward once Campbell and Pritchard were subbed. O’Brien was a natural at left back!”
Mike Shackleton: “Good performance, should have won, but that’s football!”
Heather Whitehead: “Saw some beautiful football being played by the terriers, Hoggy, O'Brien and Pritchard were class. Hoggy is a machine.”
Birmingham City latest
This is your round up of all things Birmingham City; the one-stop shop that will keep you updated on the latest goings on at the club and beyond.
Transfers, injuries, match-days and managers, we’ve got you covered.
We’ll be bringing the very latest on the Blues throughout the week and around the clock.
Make sure you keep yourself updated with our handy daily catch up...
Must reads...
- 'My blood is boiling' - Former Birmingham City player accused of making vile slur
- Birmingham City's rampant starlets rated
- Pep Clotet explains that Birmingham City call - and who impressed him at Huddersfield
- Birmingham City player ratings as Jefferson Montero makes an impact at Huddersfield
- Garry Monk makes Birmingham City claim after Sheffield Wednesday charge
For all your latest BCFC news, opinion, analysis and transfer gossip, click here
You can follow our Blues reporter Brian Dick on Twitter, and his email address is<EMAIL_ADDRESS>Alan Alan Lee: “Not terrible performance or result but we definitely deserved to win this one today, Swansea is a must win imo!! UTT.”
Tim Johnson: “Keep believing who’d have said 1 loss in 9 a few months ago.”
Jay Laverick: “Shocking, we need a left winger and a good number 10.”
Craig Addy: “Two points dropped against poor opposition I’m afraid.”


Minimal function that returns an element's data attributes as an object.
This is logged in console if you want to check it out. Make sure you escape your attributes if they're not extremely simple.


| Parameter | Type | Description |
|---|---|---|
| value | Anything | Value use to bind into ngModel |
| ngModel | type of parameter value | Value send to parent component |
We can send different type of value to the slidepicker.
If we add or suppress a value with *ngIf in tag slidepicker-option, the component will change active or replace correctly the handle
If we want different size we just need to add class to slidepicker


DfE enquiries
Central newsdesk 020 7783 8300
General enquiries 0370 000 2288
Press release
Marden High School and John Spence Community High School to be rebuilt through the government’s flagship programme.
Pupils at 2 Tyne and Wear schools have celebrated the start of work to create schools fit for the 21st century through the government’s flagship rebuilding programme.
Marden High School and John Spence Community High School are among 31 schools across the North East to be rebuilt through the £4.4 billion priority school building programme ( PSBP ), which is transforming some of the most run-down schools in the country.
At Marden High School, more than £14 million of construction will deliver a new three-storey block and a playing field in what the head teacher described as “a new era” for the school.
With £13 million of construction, pupils and teachers at John Spence Community High School will also benefit from a new three-storey building, along with a refurbished sports hall and arts block.
Schools Minister Lord Nash said:
Our investment in school buildings across the country is transforming the learning environment for tens of thousands of pupils and their teachers.
The start of construction at Marden High School and John Spence Community High School are key milestones for the priority school building programme in the north east of England.
Ensuring all children have access to the best possible schools and facilities is just one part of our commitment to help all young people reach their potential regardless of their background. These buildings will provide modern, fit-for-purpose schools for pupils for many years to come.
Alison Jackson, head teacher of Marden High School, said:
Although actual building work on our new school started several months ago, today’s turf cutting ceremony officially recognises the launch of a new era for Marden High School and its stakeholders.
Thanks to the hard work and determination of our governing body over the last few years, Marden High School students and staff will have a brand new, state-of-the-art building at their disposal from September 2016. There has never been a more exciting time in the school’s history and I am very proud to be a part of it.
Jim Stephenson, head teacher of John Spence Community High School, said:
I am delighted that John Spence Community High School has been included in the priority school building programme and that we are to have a new school building up and running on site by this time next year. The new building will provide a fantastic working environment for our students and staff, with state of the art specialist science and technology facilities and new general purpose classrooms.
In retaining and refurbishing our existing sports hall and our purpose-built arts block alongside the new build we will be providing our students and the local community with an exciting, modern learning environment which is fit for the 21st century. John Spence is already an outstanding school. We continue to go from strength to strength and see the investment of millions of pounds in a new school building as yet another step forward for the school.
John Roper, Project Director for Sir Robert McAlpine, said:
We are proud to be delivering these schools as part of the Education Funding Agency’s priority school building programme. They will provide exciting opportunities for the local community in terms of improved education facilities and employment prospects and we look forward to the successful delivery of the schemes.
Both projects are scheduled for completion next year.
Thanks to the PSBP , school buildings are being rebuilt faster and cheaper than those built under the previous school building initiative - Building Schools for the Future (BSF). Under the BSF it took 3 years for construction work to begin. This was slashed to 1 year for the PSBP , with projects costing around a third less.
A total of 537 schools will benefit from construction through the 2 phases of the PSBP .
Central newsdesk 020 7783 8300
General enquiries 0370 000 2288
Published: 6 November 2015


Formation Control
Formation control is a network control algorithm which allows a collection of robots to form and maintain a particular shape in a distributed manner. This document provides a mathematical derivation and an implementation of sample code to implement formation control for the Robotarium. It summarizes the mathematics behind a decentralized formation control algorithm and highlights the transfer of the formal specification to the Robotarium’s MATLAB API. Additionally, this document contains experimental data from the Robotarium’s robots and a video.
Problem Statement
Consider a group of agents, where we define the state of each agent as . This particular algorithm models each agent with the single-integrator dynamics
where is the control input to agent . The goal of formation control is to drive the agents to a translationally independent formation that satisfies a set of given constraints. For this particular problem, the static communication topology is given by an undirected graph and a function that models the desired inter-agent distances. To achieve a particular formation specified by and , the communication topology enforced by must be rigid, a concept discussed in [1], [2], and [3]. For , the rigidity requirements to ensure a translationally independent formation are
\begin{equation} \dfrac{\text{car}(E)}{2} = 2N - 3 \label{eq:rigidity} \end{equation}
where represents the number of edges in an undirected graph (i.e., ). Intuitively, (\ref{eq:rigidity}) implies the removal of three degrees of freedom, which is required for translational independence in .
Solution
The proposed algorithm utilizes the edge tension energy described in [4]. The total edge tension energy of the system may be written as
where is the neighborhood set to agent induced by the graph topology . [4] shows that the control law
can be used to drive the agents to the desired configuration, with the proper choice of . This control law can be seen as a gradient descent on the edge tension energy of the agents. Let be defined as
where is the desired distance between two agents defined by , and is a gain. The gradient of this function is
substituting this result into the agent’s dynamics yields
which is a decentralized formation control law.
Implementation
Using the previously defined algorithm and the Robotarium’s provided MATLAB interface, we implemented the formation control algorithm described by (\ref{eq:formation-control-law}). The code snippet below demonstrates the transfer of (\ref{eq:formation-control-law}) into the Robotarium’s MATLAB API.
Deployment
We deployed this algorithm onto the Robotarium with agents and the formation specification
where each index is the distance constraint placed on edges and . Note that induces edges, which ensures rigidity by (\ref{eq:rigidity}). Figure 1 displays the communication topology and the trajectories of the robots during the experiment. Note that the agents achieve the desired rectangular formation. The erratic motion in some agents’ trajectories stems from the rigidity of the formation, which restricts the agents’ movements.
Fig 1. Physical robots’ trajectories (dashed) and communication topology (solid) during the deployment of the decentralized formation control algorithm onto the Robotarium
References
[1] R. Olfati-Saber and R. M. Murray, “Distributed structural stabilization and tracking for formations of dynamic multi-agents,” Proc. 41st IEEE Conf. Decision Control, vol. 1, pp. 209–215, Dec. 2002.
[2] R. W. Beard, J. R. Lawton, and F. Y. Hadaegh, “A coordination architecture for spacecraft formation control,” IEEE Trans. Control Syst. Technol., vol. 9, no. 6, pp. 777–790, Nov. 2001
[3] T. Eren, P. Belhumeur, B. Anderson, and A. Morse, “A framework for maintaining formations based on rigidity,” in Proc. 2002 IFAC Congr., pp. 2752–2757.
[4] M. Ji and M. Egerstedt. Distributed Coordination Control of Multi-Agent Systems While Preserving Connectedness. IEEE Transactions on Robotics, Vol. 23, No. 4, pp. 693-703, Aug. 2007.


Helper class that resolves MongoDB connection and credential parameters, validates them and generates a connection URI.
More...
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| void | SetReferences (IReferences references) |
| | Sets references to dependent components. More...
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| |
| void | Configure (ConfigParams config) |
| | Configures component by passing configuration parameters. More...
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| |
| async Task< string > | ResolveAsync (string correlationId) |
| | Resolves MongoDB connection URI from connection and credential parameters. More...
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| |
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void | ValidateConnection (string correlationId, ConnectionParams connection) |
| |
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void | ValidateConnections (string correlationId, List< ConnectionParams > connections) |
| |
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string | ComposeUri (List< ConnectionParams > connections, CredentialParams credential) |
| |
Helper class that resolves MongoDB connection and credential parameters, validates them and generates a connection URI.
It is able to process multiple connections to MongoDB cluster nodes.
connection(s):
- discovery_key: (optional) a key to retrieve the connection from IDiscovery
- host: host name or IP address
- port: port number (default: 27017)
- database: database name
- uri: resource URI or connection string with all parameters in it
credential(s):
- store_key: (optional) a key to retrieve the credentials from ICredentialStore
- username: user name
- password: user password
- *:discovery:*:*:1.0 (optional) IDiscovery services
- *:credential-store:*:*:1.0 (optional) Credential stores to resolve credentials
◆ Configure()
| void PipServices3.MongoDb.Connect.MongoDbConnectionResolver.Configure |
( |
ConfigParams |
config | ) |
|
Configures component by passing configuration parameters.
- Parameters
-
| config | configuration parameters to be set. |
◆ ResolveAsync()
| async Task<string> PipServices3.MongoDb.Connect.MongoDbConnectionResolver.ResolveAsync |
( |
string |
correlationId | ) |
|
Resolves MongoDB connection URI from connection and credential parameters.
- Parameters
-
| correlationId | (optional) transaction id to trace execution through call chain. |
- Returns
- resolved URI.
◆ SetReferences()
| void PipServices3.MongoDb.Connect.MongoDbConnectionResolver.SetReferences |
( |
IReferences |
references | ) |
|
Sets references to dependent components.
- Parameters
-
| references | references to locate the component dependencies. |
◆ _connectionResolver
| ConnectionResolver PipServices3.MongoDb.Connect.MongoDbConnectionResolver._connectionResolver = new ConnectionResolver() |
|
protected |
The connections resolver.
◆ _credentialResolver
| CredentialResolver PipServices3.MongoDb.Connect.MongoDbConnectionResolver._credentialResolver = new CredentialResolver() |
|
protected |
The credentials resolver.
The documentation for this class was generated from the following file:
- src/Connect/MongoDbConnectionResolver.cs


I am a Full Stack Web Developer currently living in the Twin Cities. I have built up a solid foundation through a 20 week bootcamp at Prime Digital Academy. At the moment I am seeking to enter the software development industry while further developing my current skill set.
You only have one life to live, do not regret how you live it.


This tutorial will show how to use the Feed Grains open data source, provided by the USDA Economic Research Service to learn about grain production and historical effects. This tutorial will also explore grain prices in relation to production levels and determine whether there is evidence of some direct correlation, as people would expect based on supply and demand expectations.
Before we start the tutorial though, let's just give a simple introduction to the different grain types we'll be talking about!
Barley: Member of the grass family, a major cereal grain. First cultivated in Eurasia around 10,000 years ago. Versatile grain that can be grown in many climates globally. Nutlike flavor and chewy. Grown for human consumption, unlike oats, it's not usually grown for animal feed, but for beer.
Hay: Grass, legumes, or other assorted plants that have been cut, dried, and stored. Used as animal fodder for grazing animals like cows, horses, goats, sheep. Generally not used for human consumption, but some crazy people may eat it). One of, if not the most used feed for livestock. Easy to grow since basically anything can turn into hay.
Corn: Also known as maize, a large grain first domesticated in southern Mexico around 10,000 years ago. It is a very popular grain, one of the most widely grown foods in the world. People eat it, but also use it for a variety of other stuff like fuel.
Oats: Also known as the common oat, a cereal grain that is grown for its seed. Another popular grain that is widely grown. Although suitable for human consumption, in the form of oatmeal and rolled oats, typically it is grown for livestock feed.
Sorghum: A genus of flower plants, the majority of people have no idea what it is (I never heard of it until making this tutorial). Versatile crop that can be grown as a grain or sweet crop, supposedl one of the top 5 cereal crops in the world (probably not in the US though).
Now that you know what these grains are (not that it really matters), we can get started with the tutorial!
The following topics will be covered in this tutorial:
Before we start, first run the lines below the import the necessary libraries. numpy will be used for numerical calculations, pandas will be used to load the data and perform the majority of parsing and data processing, matplotlib will be the used to graph the data.
import numpy as np
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
Now that the necessary libraries are loaded, lets load the grain data. The data will be in csv format (comma separated values), which stores comma separated values for each cell element. No manual data reading or formatting is necessary as it can be easily parsed using pandas's method read_csv.
Download the FeedGrains.zip file from the USDA Economic Research Service website: https://www.ers.usda.gov/data-products/feed-grains-database/feed-grains-yearbook-tables.aspx. Unzip the FeedGrains.zip file so FeedGrains.csv is in a FeedGrains folder. There's no real reason to put it in a separate folder since it's just one file, but why not. Copy the foder into the same folder as this notebook and load the data using the below command.
df = pd.read_csv("FeedGrains/FeedGrains.csv")
df.head()
1 line, that's how easy it is to load a csv file using pandas! Next, we will be processing the data to make it easier to work with.
As you can see, the column names are odd and meaningless without prior knowledge of the dataset. To help with that, here is a list describing what each column represents:
| Column name | Description |
|---|---|
| SC_Group_ID | # ID of data group |
| SC_Group_Desc | description of data group |
| SC_GroupCommod_ID | # ID of commodity group |
| SC_GroupCommod_Desc | description of commodity group |
| SC_Geography_ID | # ID of data location |
| SortOrder | weighted sort order by country? unsure |
| SC_GeographyIndented_Desc | description of location |
| SC_Commodity_ID | # ID of specific commodity type |
| SC_Commodity_Desc | description of specific commodity type |
| SC_Attribute_ID | # ID of data's attribute |
| SC_Attribute_Desc | description of data's attribute |
| SC_Unit_ID | # ID of unit type |
| SC_Unit_Desc | description of unit type |
| Year_ID | year the data represents |
| SC_Frequency_ID | # ID of frequency data is collected |
| SC_Frequency_Desc | description of frequency data is collected |
| Timeperiod_ID | # ID of timeperiod the data represents |
| Timeperiod_Desc | description of timeperiod the data represents |
| Amount | amount of units describing the attribute for the given commodity type |
Note that 'commodity' is asynchronous to grain for the most part. Since the data includes products such as malted barley and alcohol, which aren't grains, we will use 'commodity'.
You probably realized that there are two columns describing each column (the ID and description). To make it easier to work with and shrink the width of the table, we will now delete all the 'duplicate' ID columns by using the code below.
del df['SC_Group_ID']
del df['SC_GroupCommod_ID']
del df['SortOrder']
del df['SC_Geography_ID']
del df['SC_Commodity_ID']
del df['SC_Attribute_ID']
del df['SC_Unit_ID']
del df['SC_Frequency_ID']
del df['Timeperiod_ID']
df.head()
You can see that the table is much cleaner, now that there are no more duplicate columns. Also note that you can only run the above code once on the dataframe. Running it more times will result in an error since the columns can't be found, as they have already been deleted.
Now that we have cleared the duplicate columns, lets rename the columns to be more descriptive and intuitive for our purposes. You can use the following line to manually change the column names.
df.columns = ['Group', 'Commod_Group', 'Location', 'Commod', 'Attribute', 'Unit', 'Year', 'Frequency', 'Time Period', 'Amount']
print(df.shape)
df.head()
This looks much more pleasing to look at than the initial table (in my opinion, you might think different, but at least the table is smaller).
You might've noticed that there's an extra line before the table above. This is the shape of the dataframe. It consists of a tuple (# rows, # columns). There is a huge amount of data totaling to over 400,000 rows. Computers are fast enough that now they can process that amount of data relatively quickly, but we will still be extracting only the data we need. It is a good habit since the dataframe will be easier to work with after clearing out unnecessary data, as well as if working with even larger datasets in the future, say trillions of values.
For the purposes of this tutorial, we will only be looking at the data for the US, so we can begin by extracting all the rows whose Location is United States. Run the following code to achieve this.
df_us = df[df.Location.isin(['United States'])]
print(df_us.shape)
You can see that now the number of rows has decreased from over 400,000 to just a little over 40,000.
We saved the new extracted dataframe into a new variable df_us. This way, if we still need to find something in the original dataset, we can easily reference it without having to load the data again.
There's multiple groups that the data is categorized in. Before we can look at them, let's first sort the dataframe and find a list of unique groups.
df_us = df_us.sort_values(by=['Group'])
names = df_us['Group'].unique().tolist()
names
We now have a list of unique groups in names. The next step before we can begin to analyze our data is to filter the dataframe again. We will achieve this by creating 6 different dataframes, one for each data group.
data = {}
for i in range(0,6):
data[names[i]] = df_us[df_us.Group.isin([names[i]])]
Now that we have separated the data into their respective groups, we can begin analyzing and visualizing it.
We will start by looking at the Supply and use data group. Let's start by looking at the corresponding data.
data['Supply and use'].head()
We can see that even within the data group, there are many other variables that we can use to try and analyze the data. Following, we will attempt to analyze and graph the data by the annual beginning stocks for grains.
To start, let's look at annual beginning stock of each commodity. Before we can begin looking at the data, once again, we need to filter and sort the data.
In the Attribute column, you can see that there are a variety of attributes. For this section, we will only be looking at Beginning stocks. First, lets extract only the rows whose attribute is Beginning stocks.
sau = data['Supply and use']
sau = sau[sau.Attribute.isin(['Beginning stocks'])]
You will notice that in the Frequency column, there are Annual and Quarterly data values. For simplicity, we will only be looking at annual values so we will extract only the rows with Annual.
sau = sau[sau.Frequency.isin(['Annual'])]
Now that we have the data we need, let's sort it by Year and take a look!
sau = sau.sort_values(by='Year')
sau.head()
Finally, we can start to graph and visualize the data! To begin, we will make line graphs for each commodity to view the change in the amount of beginning stock for each year. Hopefully we will find some relationship!
for i, group in sau.groupby('Commod_Group'):
plot = group.plot(x='Year', y='Amount', title=str(i))
y = 'Beginning Stocks (' + group.Unit.iloc[0] + ')'
plot.set(xlabel='Year', ylabel=y)
plt.show()
Personally, I would think that the beginning stock of grains each year would be increasing, or at least have an increasing trend, due to improvements in agricultural techniques. However, it is clear based on the graphs that something happened between 1986 and 1988. One event must have led to a massive surplus in 1986, while another event must have led to a huge (deficit?) in 1988. Through a quick search on "corn supply 1986" and "corn supply 1987", I managed to find 2 articles that explain the phenomena.
http://agfax.com/2016/11/29/grain-market-reminded-of-1986-king-daddy-year-of-corn-stocks-dtn/
The article in the link above describes how there were "four consecutive years of good crop weather" which led to not only the US, but the entire world to have excess grain supplies. Only about 66% of corn stock was used, explaining the massive surplus in the time period.
http://articles.latimes.com/1988-07-13/business/fi-5672_1_food-prices
This article compares the staggering grain production in 1988 compared to 1987.  As a result, the surplus that built up the past years must have been depleted in an instant, over the following years of bad weather.
Based on this, it seems that weather has a much greater effect on grain supply than agricultural techniques. However, this correlation can't be concluded without looking at weather data and trying to find a relation between the two datasets. We won't be looking at that today since this is a tutorial to get started in looking at grain data. Instead, we will explore more subsets of data in FeedGrains.csv, specifically prices!
Just looking at one correlation of data is no fun since finding a relation is so simple. Next, let's take a look at the prices of the grains above! We will begin by looking at annual grain prices and graph the data to see if we can find a basic visual correlation.
Prices won't be found in the Supply and use group, so we will be looking at the Prices data group for this part.
data['Prices'].head()
Similar to the Supply and use data group, Prices also has a variety of information. Once again, we will start by working to filter out unnecessary data.
Let's start by sorting the data by year and see where to go from there.
p = data['Prices']
p = p.sort_values(by='Year')
p.head()
Once again, we can see that there is detailed data for each quarter of the year or each month, but for simplicity, we will again, be looking at annual prices. This consistency with the annual grain stocks data will also allow us to easily perform a comparison. Let's now extract only the annual data...
p = p[p.Frequency.isin(['Annual'])]
p.head()
You may have noticed that there is some difference between the two datasets, the Prices dataset has a Hay group, while the Supply and use dataset has Feed grains.  Before we come to this conclusion, let's take a look at what groups are in the Prices datasets.
p['Commod_Group'].unique().tolist()
Just like the Supply and use dataset, there are 5 groups, so we will be assuming that Hay corresponds to Feed grains.
You probably also noticed that the commodities in Prices differs from the group, as compared to the Supply and use dataset. Although there are many different types of specific grains and farmers are paid different prices depending on the specific product being made from their produce, we will be looking at the grain groups as a whole so it will be easier to compare.
Next, we see that there are newer attributes in recent years, distinguishing between farmers' pay on the high end, low end, and average. We will take only the average pay rate in order to maximize the data we can use (early years don't distinguish between high and low end). We can extract only the average prices with:
p = p[p.Attribute.isin(['Prices received by farmers'])]
p.head()
After filtering some more data, we can see that there are some more issues with data consistency. Sorghum is listed under two types of units, Dollars per bushel and Dollars per cwt. We will only be looking at Dollars per bushel so next, we will remove those sets of data. The code below is slightly different from previous methods of extraction, because instead of extracting data with a certain value, we will extract data that doesn't contain a certain value, effectively removing the unwanted data.
p = p[p.Unit != 'Dollars per cwt']
p.head()
There doesn't seem to be any more data inconsistencies so we can finally begin to graph the data. We will be graphing based on Commod this time instead of Commod_Group since Commod is more consistent. Hopefully we can find some trends!
for i, group in p.groupby('Commod'):
if i == 'Corn' or i == 'Hay all (dry)' or i == 'Barley' or i == 'Oats' or i == 'Sorghum':
plot = group.plot(x='Year', y='Amount', title=str(i))
plot.set(xlabel='Year', ylabel=group.Unit.iloc[0])
plt.show()
We can see that there is inconsistency in the start years for the datasets, so we will set a x-limit so it will be easier to compare the datasets.
for i, group in p.groupby('Commod'):
if i == 'Corn' or i == 'Hay all (dry)' or i == 'Barley' or i == 'Oats' or i == 'Sorghum':
plot = group.plot(x='Year', y='Amount', title=str(i), xlim=(1975, 2017))
plot.set(xlabel='Year', ylabel=group.Unit.iloc[0])
plt.show()
Simply looking at the data, there appears to be no relation between stock and prices whatsoever. The most clear indicators are how there's a spike in grain stock around 1987, but there is no defined change in prices during that time period. Prices also spiked around 2012, but there appears to have been no change in average grain stock during that time period.
Through some research, it seems that since around 2010, there has been severe weather conditions such as droughts in the US causing a deficit in the supply (although it seems to look consistent based on the data). Supposedly this is the reason for a raise in price, despite the fact that the data on our grain supply seems to differ.
The resulting conclusion seems to imply that regardless of the weather and grain supply, it will not have a severe impact on the price of grain, at least in the short term. Although this seems trivial, this does impact virtually everyone. Whether there is another reason that prices are high despite our consistent supply, or demand has simply increased beyond past years, resulting in a higher necessary grain supply, numbers tell more truth than a news article.
Note: for grader
After coming this far, I could not think of a way to incorporate machine learning usefully into this dataset without either choosing a completely different dataset or different subset of data. I initially expected there to be data for other countries as well so a linear regression line would be useful in determining the global trend of price and supply and determine if there is a relation be comparing the regression lines, but the only data in the dataset is for the US.
This tutorial has looked at the changes in grain supply, as well as grain prices over the time period of 1975 to 2016. Through graphical evidence, there does not seem to be any evidence of a correlation between grain price and supply, no matter how much surplus or deficit there is. There may be a correlation with the economy or weather between the two datasets, but that was not explored in this tutorial.
In conclusion, there are many things that data science can accomplish in any field. New patterns or unexpected trends may be found that were unseen before. With these patterns and unexpected trends, further research and data application can be applied to determine correlations between data. Although correlation does not imply causation, new discoveries may be found that initiate new ideas, especially considering the sheer amount of data, even for something (seemingly simple) like grains.
Data source: https://www.ers.usda.gov/data-products/feed-grains-database/feed-grains-yearbook-tables.aspx


[1]
Versatile, accurate; Inferior mounting system
[2]
Everything BUT THE MOUNTING SYSTEM; The mounting system


Monday - Saturday
10:00am - 7:00pm
Sunday
9:00am - 12:00pm
4688 Convoy St #106, San Diego, CA 92111
(858) 874-3030
Mon
10:00am to 7:00pm
Tue
10:00am to 7:00pm
Wed
10:00am to 7:00pm
Thu
10:00am to 7:00pm
Fri
10:00am to 7:00pm
Sat
10:00am to 7:00pm
Sun
9:00am to 12:00pm


Demonstrate how to:
<svg>
, and
This example is based on Mike Bostock's Brush & Zoom II Block. The original source with its supporting explanation can be found by following the link below.
Source: Brush & Zoom II Block.
The implementation is a straightforward Angular component without any inputs. Its template is an <svg>
element with fixed dimensions. The component renders the visualization using the d3
instance provided
by the injected D3Service
.
The D3 component can be embedded into a parent component using the following tag:
<app-brush-zoom-2></app-brush-zoom-2>
.
The source code for the D3 component can be found at:


The ever-astute Hooting Yard reader OutaSpaceman was much stirred by yesterday's item on the Silos Of Concern. When he had finished reproaching me for reading the Guardian – claiming it makes me “huffy”—he very helpfully wrote to tell me that it is possible to fry an egg in a silage pit. Naturally, I asked for further details, to which he replied as follows:
Choose your silage pit.
Dig down about 2 feet. (Deeper the hole quicker the frying time)
Crack egg into hole.
Wait and observe the egg, turning if necessary, till it is cooked to your taste.
Retrieve the fried egg and marvel.
ON NO ACCOUNT ATTEMPT TO EAT THE EGG.
It will probably be poisonous or, at least, shot through with rotting grass.
I read this with some consternation. Important questions were screaming in my head. What criteria should I use to make my choice of silage pit? Could I dig using any old spade or did he recommend a particular kind? Would I need a metal or plastic or wooden spatula to turn and retrieve my egg, or would any kind do? What did he suggest I do with the uneaten egg once I had stopped marvelling? Could it be fed safely to any barnyard animals? If so, which ones?
I am pleased to say that OutaSpaceman wrote back with commendable promptness. This is what he had to say:
1. Age is the primary criteria. The longer the pit has been filled and festering the better.
2. A peat cutter is probably the best implement to use as this will give the hole good clean corners and prevent side collapse. (On no account should a shovel be used because of the contamination risk i.e. I've never shovelled excrement with a spade)
3. My own preference is for a stainless steel spatula with a wooden handle. Hygiene being the prime advantage of this utensil and the opportunity for reuse after a comprehensive sterilisation. Wooden spatulas carry the risk of contamination from prior use and the very real threat of combustion. Plastic spatulas will melt.
4. The uneaten egg should be placed on a clay pigeon trap and shot at by an untutored, unsupervised ten year old child. Feeding animal protein to, in the majority, vegetarian creatures is an unnatural practice. That's how we got BSE.
If any other readers have any silage pit-related recipes, please send them in. We could have the makings of a Christmas bestseller.


Not Your Father's Football
Last Searched Team:
Go back to League Selection
Last game:
Upcoming game:
Top Recent World Soccer Highlights


| Methods' Details |
addTextListener
- Description
- registers a text event listener.
|
|
removeTextListener
- Description
- unregisters a text event listener.
|
|
setText
| [oneway] void |
| setText( |
[in] string |
aText ); |
- Description
- sets the text of the component.
|
|
insertText
| [oneway] void |
| insertText( |
[in] Selection |
Sel, |
| [in] string |
Text ); |
- Description
- inserts text at the specified position.
|
|
getText
- Description
- returns the text of the component.
|
|
getSelectedText
| string |
| getSelectedText(); |
- Description
- returns the currently selected text.
|
|
setSelection
| [oneway] void |
| setSelection( |
[in] Selection |
aSelection ); |
- Description
- sets the user selection.
|
|
getSelection
- Description
- returns the current user selection.
|
|
isEditable
- Description
- returns if the text is editable by the user.
|
|
setEditable
| [oneway] void |
| setEditable( |
[in] boolean |
bEditable ); |
- Description
- makes the text editable for the user or read-only.
|
|
setMaxTextLen
| [oneway] void |
| setMaxTextLen( |
[in] short |
nLen ); |
- Description
- sets the maximum text length.
|
|
getMaxTextLen
- Description
- returns the currently set maximum text length.
|
|
Copyright © 2013, The Apache Software Foundation, Licensed under the Apache License, Version 2.0. Apache, the Apache feather logo, Apache OpenOffice and OpenOffice.org are trademarks of The Apache Software Foundation. Other names may be trademarks of their respective owners.


----
000000
Description
Attributes
Category
IT/Digital ratio
Technology maturity
Market Skills avalability
TOTAL Skills avalability
Digital capabilities
Examples and resources
Examples
Resources
Avantages and limitations
Avantages
Limitiations
Linked technologies
Strong links
Weak links


‘Okada’ rider jailed 10 years for robbery
by Alex Ofori AgyekumNsawam (E/R), Nov. 15, GNA – The Nsawam Circuit Court has sentenced Eric Ahedor, a 24-year-old ‘Okada’ rider for 10 years imprisonment with hard labour for robbery.
The convict pleaded guilty for robbing Mr Isaac Apiadu Opare, a photographer.
Prosecuting, Police Chief Inspector Dodzi, told the court presided by Madam Andley Kocuvi-Tay that the complainant Mr Isaac Apiadu Opare is a resident at Adeiso, while the convict lives at Nsuobiri, near Danso both in the Eastern Region.
Inspector Dodzi said on September 11, this year, around 1600 hours, the complainant had a phone call from an unknown caller inviting him to cover a birthday party programme at Nsuobiri.
He said on the same day, the convict around 2030 hours came to the complainant’s house with his motorbike to identify himself that he was asked by the earlier caller to bring him to Nsuobiri to cover the programme.
The prosecution said on their way, the convict stopped and pulled a knife on the complainant and asked him (complainant) to surrender his mobile phone and his Cannon cameras used for taking pictures.
Inspector Dodzi said the convict inflicted knife wounds on the complainant and succeeded in taking his camera valued at GH¢1,600.00 and his Samsung mobile phone valued at GH¢500.00 all amounting to GH¢2,100.00.
He said the complainant reported the incident to the Adeiso police and Eric Ahedor was arrested and arraigned before the Nsawam Circuit Court.
GNA


SICStus Prolog streams are divided into two categories, those opened by
see/1
or tell/1
and those opened by open/[3,4]
. A stream
in the former group is referred to by its file specification,
while a stream in the latter case is referred to by its stream
object (see the figure “Categorization of Stream Handling Predicates”).
For further information about file specifications, see
ref-fdi. Stream objects are discussed in
ref-iou-sfh-sob. Reading the state of open streams is discussed
in ref-iou-sos.
Each operating system permits a different number of streams to be open.


s3io_read(bucket, key, readfun, ..., .localfile = tempfile(), .rm_localfile = TRUE, .get_object_args = list())
| bucket | [string] AWS S3 bucket name. |
|---|---|
| key | [string] AWS S3 object key. |
| readfun | [function] A read function where the first argument is a filepath.
The function's signature should look like |
| ... | Additional arguments forwarded on to |
| .localfile | [string] The local filepath of the downloaded file. |
| .rm_localfile | [boolean] Should the local filepath be deleted once it has been read?
If |
| .get_object_args | [list] Additional optional args passed on to |
The returned value from readfun
.
# NOT RUN { s3io_read("mybucket", "my/object/key.csv", readr::read_csv, col_names = TRUE) # }


Great job! Thanks for submitting a quote to WebDevlopr, you should be receiving an email soon.
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Before Change
Set up the Insteon local switch platform.
insteonhub = hass.data["insteon_local"]
conf_switches = load_json(hass.config.path(INSTEON_LOCAL_SWITCH_CONF))
if conf_switches:
for device_id in conf_switches:
setup_switch(
device_id, conf_switches[device_id], insteonhub, hass,
After Change
def setup_platform(hass, config, add_devices, discovery_info=None):
Set up the Insteon local switch platform.
insteonhub = hass.data["insteon_local"]
if discovery_info is None:
return
linked = discovery_info["linked"]
device_list = []
for device_id in linked:
if linked[device_id]["cat_type"] == "switch":
device = insteonhub.switch(device_id)
device_list.append(


If you have any query,suggestion or even complaint. Please submit this form and we will get back to you ASAP


Remember people want to know who you are, so be original, honest and open about yourself.
You can also tell some inspiring story from your life experiences. A story may possess more power to hold a reader’s attention than general information.
Don’t create very long About Me pages. The readers avoid the pages that hold long and detailed content. So the moment it starts to get boring and uninteresting, write the ending lines.


About Me
My name is Andrew Yen. I am currently a Full Stack Web Development student at the UCR Extension Center. I love dogs, sushi and above all video games.
My favorite types of video games are JRPGs (Japanese role-playing games), visual novels, and platformers. As a long time gamer who has seen all sorts of great and messy UIs, I hope to create clean, responsive websites in the future.


Tornado is a simple web framework...
...around a fast HTTP server...
...around a low-level event system.
It can be used for...
...building web apps...
...HTTP REST APIs...
...authentication frameworks...
...even custom TCP-based services.
from tornado.web import Application, RequestHandler
from tornado.ioloop import IOLoop
class HomeHandler(RequestHandler):
def get(self):
self.set_header("Content-type", "text/plain")
self.write("Hello, world!")
if __name__ == "__main__":
app = Application([("/", HomeHandler)])
app.listen(8080)
IOLoop.instance().start()
I'm going to talk through how Tornado works.
This means some libraries you might not use.
Tornado is actually very simple.
Tornado selects the best library for your platform.
For Linux, this means epoll.
For Mac, this means kqueue.
For Windows, this means old / boring select.
These are not the codes you are looking for.
The IOLoop abstracts those polling libraries away:
from tornado.ioloop import IOLoop
ioloop = IOLoop.instance()
# watch for events on a socket / file descriptor
ioloop.add_handler(sock.fileno(), callback, ioloop.READ)
# add a callback to run on the next "cycle"
ioloop.add_callback(callback)
# add a callback to run at (or after) a specific time
ioloop.add_timeout(time.time() + 60, callback)
Singletons -- great until they murder you
Use as default, but allow passing it in
class TCPServer(object):
def __init__(self, ioloop=None):
self._ioloop = ioloop or IOLoop.instance()
def send(self, message):
#...
All you need unless you're writing a TCP client / server.
Use these to split up blocking operations, defer tasks, etc.
# blocking operation...
results = DB.slow_find()
def parse_results(results):
for result in results:
# do something
# let other things work for a while
IOLoop.instance().add_callback(parse_results, results)
If you ARE writing a server, you need to:
# add a callback for a file descriptor on certain events
ioloop.add_handler(sock.fileno(), callback, ioloop.READ)
# update for new events
ioloop.update_handler(sock.fileno(), ioloop.WRITE)
# remove file descriptors when finished
ioloop.remove_handler(sock.fileno())
...but stayed tuned...
IOStream wraps sockets:
ioloop = IOLoop.instance()
sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
stream = IOStream(sock, io_loop=ioloop)
stream.connect(("google.com", 80), connect_callback)
stream.read_bytes(4096, read_callback)
# etc...
It provides plenty of helpers:
# read until exact string match
stream.read_until("\n\n", header_callback)
# read until a regular expression is matched
stream.read_until_regex("BYTES: \d+\s+", bytes_callback)
# read until the socket closes -- optional streaming
stream.read_until_close(finish_callback, streaming_callback)
# write out to the socket
stream.write("Foobar!", write_callback)
# if a socket is closed, call a callback
stream.set_close_callback(on_close)
stream.closed() or stream.reading() or stream.writing()
Use IOStream when someone else hasn't done it already.
(For instance, your favorite new NoSQL database.)
Don't use IOStream for HTTP clients -- that's coming up.
HTTPServer is (generally) invisible.
It leverages IOStream, etc. to support HTTP/1.1.
Runs implicitly when Application.listen() is called.
You probably won't need to touch it, but it's there.
Uses HTTPRequest.
HTTPRequest is used heavily in the request handlers.
It wraps information / helpers for client connections:
request.body # the request body string, if present
request.headers # dictionary of headers
request.cookies # dictionary of cookies
request.path # /foobar/path
request.query # ?key=value
request.remote_ip # actual request ip
request.scheme # actual request scheme (http[s])
tornado.web
contains the real meat of Tornado.
Most work (in web apps) is done here.
Encapsulates the "V" and "C" of "MVC"
from tornado.web import RequestHandler, Application
class Controller(RequestHandler):
# regex groups in route passed to method
def get(self, username):
ip = self.request.remote_ip # request on handler
# tornado includes its own templating system
self.render(
"template.html", ip=ip, username=username)
app = Application([
# routes are regex passed into Application
("/(\w+)", Controller)
])
{% extends "base.html" %}
{% block content %}

Hello, {{ username.uppercase() }}.

{# it's mostly just python. #}
{% if ip == "<IP_ADDRESS>" %}

You must still be working on this.

{% else %}

You are accessing us from {{ ip }}.

{% end if %}
{% end block %}
{# You can even... #}
{% import requests %}
{{ requests.get("http://www.google.com").text }}
{# ...but don't.  #}
It has just enough for what you need...
...with enough rope to hang yourself twice.
So be smart.
class Users(RequestHandler):
def post(self):
content = json.loads(self.request.body)
# application is available from the handler
id = self.application.settings["database"].save(content)
# a dictionary passed to write == JSON
self.write({
"id": "%s" % (id),
"name": content["name"]
})
app = Application([("/users", Users)],
debug=True, # for automatic reloading
database=pymongo.Connection()["mydatabase"])
from tornado.wsgi import WSGIApplication
app = WSGIApplication([("/", Handler)])
# for giggles...
server = gevent.pywsgi.WSGIServer(('', 8080), app)
server.serve_forever()
Can't do Tornado's async stuff, though.
class BaseHandler(RequestHandler):
@property
def db(self):
return self.application.settings["db"]
def get_current_user(self):
token = self.get_secure_cookie("token")
user = self.db.users.find_one({"token": token})
return user or None
class LoginHandler(BaseHandler):
def post(self):
if self.current_user:
self.redirect("/dashboard")
username = self.get_argument("username")
password = self.get_argument("password")
user = self.db.find_one({"username": username})
if not user or user.password != password:
return self.redirect("/login")
self.set_secure_cookie("token", user.token)
self.redirect("/dashboard")
class Dashboard(BaseHandler):
@tornado.web.authenticated
def get(self):
self.render("dashboard.htm", user=self.current_user)
class AsyncHandler(RequestHandler):
@tornado.web.asynchronous
def get(self):
service.fetch("/other/thing", callback=self._callback)
# request stays open...
def _callback(self, response):
if response:
self.write(response)
else:
raise HTTPError(500, "We couldn't find it.")
# without finish, the request never closes
self.finish()
There are lots of other helpers in the web stack.
(Websockets, error helpers, etc.)
Dig around in the documentation.
from tornado.httpclient import AsyncHTTPClient
def callback(response):
print response.code
print response.body
client = AsyncHTTPClient()
client.fetch("http://foo.com/some/resource", callback)
def fetch_callback(response):
print response.headers
print response.body
client = AsyncHTTPClient()
client.fetch("https://foo.com/some/resource",
method="POST", body=json.dumps({"key": "value"}),
headers={"Content-type": "application/json"},
auth_username="foo", auth_password="bar",
validate_cert=False, callback=fetch_callback)
You'll probably use this a lot.
It's especially useful when used with auth.
(seeggwwaaayyy...)
Tornado includes lots of third party auth.
This fits nicely with the async nature of Tornado.
Also, you can be lazy about your auth system.
from tornado.auth import TwitterMixin
class TwitterAuthHandler(RequestHandler, TwitterMixin):
@tornado.web.asynchronous
def get(self):
if self.get_argument("oauth_token", None):
return self.get_authenticated_user(self._on_auth)
self.authorize_redirect()
def _on_auth(self, user):
if not user:
raise HTTPError(500, "Couldn't auth.")
user = self.db.create({"username": user["username"]})
self.set_secure_cookie("token", user.token)
self.redirect("/dashboard")
Deployment
To Async or Not?
Testing
Libraries of Import
@joshmarshall on the Twitters.
@joshmarshall on the GitHub.


- ReactiveEditText - Class in com.reactivecascade.reactive.ui
-
An EditText
which can be manipulated and which in turn manipulates a supporting
ReactiveValue
which reflects the current on-screen value
FIXME The cursor position on screen is not maintained nicely when values update
Created by Paul Houghton on 12-03-2015.
- ReactiveEditText(Context) - Constructor for class com.reactivecascade.reactive.ui.ReactiveEditText
-
- ReactiveEditText(Context, ReactiveValue<String>) - Constructor for class com.reactivecascade.reactive.ui.ReactiveEditText
-
- ReactiveEditText(Context, AttributeSet) - Constructor for class com.reactivecascade.reactive.ui.ReactiveEditText
-
- ReactiveEditText(Context, AttributeSet, ReactiveValue<String>) - Constructor for class com.reactivecascade.reactive.ui.ReactiveEditText
-
- ReactiveEditText(Context, AttributeSet, int) - Constructor for class com.reactivecascade.reactive.ui.ReactiveEditText
-
- ReactiveEditText(Context, AttributeSet, int, ReactiveValue<String>) - Constructor for class com.reactivecascade.reactive.ui.ReactiveEditText
-
- ReactiveEditText(String, Context, AttributeSet, int, int) - Constructor for class com.reactivecascade.reactive.ui.ReactiveEditText
-
- ReactiveEditText(String, Context, AttributeSet, int, int, ReactiveValue<String>) - Constructor for class com.reactivecascade.reactive.ui.ReactiveEditText
-
- ReactiveImageView - Class in com.reactivecascade.reactive.ui
-
An ImageView which can be directly bound to change the screen when an up-chain value changes
- ReactiveImageView(Context) - Constructor for class com.reactivecascade.reactive.ui.ReactiveImageView
-
- ReactiveImageView(Context, AttributeSet) - Constructor for class com.reactivecascade.reactive.ui.ReactiveImageView
-
- ReactiveImageView(Context, AttributeSet, int) - Constructor for class com.reactivecascade.reactive.ui.ReactiveImageView
-
- ReactiveInteger - Class in com.reactivecascade.reactive
-
An Integer
which can be updated in an atomic, thread-safe manner.
- ReactiveInteger(String, int) - Constructor for class com.reactivecascade.reactive.ReactiveInteger
-
Create a new atomic integer
- ReactiveInteger(IThreadType, String, int, IActionOneR<Integer, Integer>, IOnErrorAction) - Constructor for class com.reactivecascade.reactive.ReactiveInteger
-
Create a new atomic integer
- ReactiveLong - Class in com.reactivecascade.reactive
-
A Long
which can be updated in an atomic, thread-safe manner.
- ReactiveLong(String, long) - Constructor for class com.reactivecascade.reactive.ReactiveLong
-
Create a new atomic long
- ReactiveLong(String, long, IThreadType, IActionOneR<Long, Long>, IOnErrorAction) - Constructor for class com.reactivecascade.reactive.ReactiveLong
-
Create a new atomic long
- reactiveTargets - Variable in class com.reactivecascade.reactive.Subscription
-
- ReactiveTextView - Class in com.reactivecascade.reactive.ui
-
Change the displayed value from any thread by calling view.bindable.set(String value)
- ReactiveTextView(Context) - Constructor for class com.reactivecascade.reactive.ui.ReactiveTextView
-
- ReactiveTextView(Context, AttributeSet) - Constructor for class com.reactivecascade.reactive.ui.ReactiveTextView
-
- ReactiveTextView(Context, AttributeSet, int) - Constructor for class com.reactivecascade.reactive.ui.ReactiveTextView
-
- ReactiveTextView(Context, AttributeSet, int, int) - Constructor for class com.reactivecascade.reactive.ui.ReactiveTextView
-
- ReactiveValue<T> - Class in com.reactivecascade.reactive
-
Thread-safe reactive display of a variable getValue.
- ReactiveValue(String, T) - Constructor for class com.reactivecascade.reactive.ReactiveValue
-
Create a new AtomicValue
- ReactiveValue(String, T, IThreadType, IActionOneR<T, T>, IOnErrorAction) - Constructor for class com.reactivecascade.reactive.ReactiveValue
-
Create a new AtomicValue
- reactiveValue - Variable in class com.reactivecascade.reactive.ui.ReactiveEditText
-
- read(String) - Method in class com.reactivecascade.util.FileUtil
-
- readAsync() - Method in class com.reactivecascade.util.FileUtil
-
- readAsync(String) - Method in class com.reactivecascade.util.FileUtil
-
- readIThreadType - Variable in class com.reactivecascade.rest.AbstractRESTService
-
- remove(Object) - Method in class com.reactivecascade.functional.DoubleQueue
-
- remove(KEY) - Method in class com.reactivecascade.rest.PrioritizedGettable
-
- removeAsync(T) - Method in class com.reactivecascade.reactive.ui.AltArrayAdapter
-
- replace(Integer, V, V) - Method in class com.reactivecascade.reactive.ui.MirrorArrayAdapter.MirrorDelegate
-
This onFireAction really is atomic because both the MirrorArrayAdapter and MirrorDelegate are limited
to the UI thread.
- replace(String, byte[], byte[]) - Method in class com.reactivecascade.rest.FileMirrorService
-
- replace(K, V, V) - Method in class com.reactivecascade.rest.MirrorService
-
Overriding services must call this in a super
- replace(String, String, String) - Method in class com.reactivecascade.rest.PreferencesMirrorService
-
- run() - Method in class com.reactivecascade.functional.AltFuture
-
The
ExecutorService
of this
AltFuture
s
IThreadType
will call this for you.
- RuntimeAssertionException - Exception in com.reactivecascade.util
-
This is a message indicating a functional chain or other assert statement has failed at
runtime.
- RuntimeAssertionException(String) - Constructor for exception com.reactivecascade.util.RuntimeAssertionException
-
- RuntimeAssertionException(String, Exception) - Constructor for exception com.reactivecascade.util.RuntimeAssertionException
-


| 063:006 Khan | : |
It is equal to them whether you (Muhammad SAW) ask forgiveness or ask not forgiveness for them. Verily, Allah guides not the people who are the Fasiqin (rebellious, disobedient to Allah). |
| 063:006 Maulana | : |
It is alike to them whether thou ask forgiveness for them or ask not forgiveness for them -- Allah will never forgive them. Surely Allah guides not the transgressing people. |
| 063:006 Pickthal | : |
Whether thou ask forgiveness for them or ask not forgiveness for them is all one for them; Allah will not forgive them. Lo! Allah guideth not the evil-living folk. |
| 063:006 Rashad | : |
It is the same for them, whether you pray for their forgiveness, or not pray for their forgiveness; GOD will not forgive them. For GOD does not guide the wicked people. |
| 063:006 Sarwar | : |
It is all the same whether you seek forgiveness for them or not; God will never forgive them. God does not guide the evil-doing people. |
| 063:006 Shakir | : |
It is alike to them whether you beg forgiveness for them or do not beg forgiveness for them; Allah will never forgive them; surely Allah does not guide the transgressing people. |
| 063:006 Sherali | : |
For them it is equal whether thou ask forgiveness for them, or ask not forgiveness for them. ALLAH will never forgive them. Surely, ALLAH guides not the rebellious people. |
| 063:006 Yusufali | : |
It is equal to them whether thou pray for their forgiveness or not. Allah will not forgive them. Truly Allah guides not rebellious transgressors. |
Concepts/Themes Covered: الإيمان > الإيمان بالله > الاستغفار Faith> Belief In Allah> Asking Allah for Forgiveness الإيمان > الإيمان بالله > النفاق Faith> Belief In Allah> Hypocrisy الإنسان والعلاقات الأخلاقية > الأخلاق الذميمة > الفسق Man and The Moral Relations>The Dispraised Morals>Impiety
This tool uses eight English parallel translations for the Holy Quran imported from Mr. Clay Smith. You can also visit Qurany Concepts for browsing the Quran themes or topics. If you want to search the Holy Quran for keywords, please visit Qurany Keywords.


Thank you for using TRInfoView!
This is a simple example:
- It's a standard html file (check readme.html)
- It uses some formatting (check the file styles.css)
- It uses a subtle background (noisy.png - found on subtlepatterns.com)
- You can include PNG images (like icons or screenshots)
- The html can contain links to websites or email-addresses
that will be opened in Safari or Mail.
So I can show you an icon of my app "SmarterContacts"
and ask you to check out the product's website
or to send me an email.
Question or Feedback?
If you have questions, find bugs or would like to request additional features, you can reach me by sending an email to info@smartersoftware.de.


Tyler Breeze becomes new UpUpDownDown Champion during Grubhub live stream
by WWE.comSurvivor Series Sunday featured two title changes before the show even started — all on an UpUpDownDown live stream, presented by Grubhub!
First, Cesaro retained his title after Team Cesaro, featuring the Swiss Cyborg’s drafted squad of Alexa Bliss, Gentleman Jack Gallagher and Rusev, defeated Team Kingston across a number of games. Kofi Kingston’s chosen squad consisted of Big E, The Miz and King Corbin.
Cesaro later put the title on the line again, however, and The Goddess of WWE unseated him through a win in “Brawlhalla” to become UpUpDownDown Champion.
But Little Miss Bliss’ title reign was short-lived. Initially disguised as a Grubhub delivery man, Tyler Breeze revealed himself and swooped in for an immediate shot at Bliss’ title in “Saturday Night Slam Masters,” emerging victorious as the new UpUpDownDown Champion.
You can rewatch all the action by viewing the live stream replay below.


Right story
Right Story is a google home APP, which can alternate the content of what smart speaker said to fit users’ preference.
-
Science
-
Male
-
Violence
“…
Snow White, he she discovers a tiny cottage powered by solar panel belonging to a group of seven Dwarfs. When the Dwarfs return home with the fox they huntedwith the fruits they found.
…”


Click on the PLAY square to start the game.
Click on a square to reveal parts of the picture or hold down the mouse button.
Enter what you see in the textbox and gain points for the most common answers.


Time.Date
Syntax
Time.Date : string
Description
The Time.Date function returns the current date and time as a string. The returned string in the format "dd mmm yy hh:mm:ss", where mmm is the first 3 characters of the month, e.g., "Apr". For example, if the date is Christmas 1989 at 9:02:37 in the morning, Time.Date will return "25 Dec 89 09:02:37". Twenty-four hour time is used, so eleven thirty at night the same day would return "25 Dec 89 23:30:00"
Example
This program greets you and tells you the date and time.
var theDateTime, theDate, theTime : string
theDateTime := Time.Date
theDate := theDateTime (1 .. 9)
theTime := theDateTime (11 .. *)
put "Greetings!! The date and time today is ", Time.Date
Details
Be warned that on some computers, such as IBM PC compatibles or Apple Macintoshes, the date may not be set correctly in the operating system; in that case, the Time.Date procedure will give incorrect results.
The string form of the date can be converted to a numeric form for comparison purposes using the Time.DateSec function. The numeric form can be converted to a string using the Time.SecDate function. The numeric form of the time can be obtained using the Time.Sec function.
Status
Exported qualified.
This means that you can only call the function by calling Time.Date, not by calling Date.
See also
Time.Sec, Time.DateSec and Time.SecDate functions.


When working with time-series data (or any dataset with 1 distinct y-value for each x), there often arises a practical need to develop & optimize a transformation. For example, moving average is used in a wide variety of settings ranging from Daily COVID hospitalizations to financial technical analysis. Such metrics have enormous potential public and/or business implications. This warrants extensive testing prior to implementing a transformation used to generate metric of interest.
Whether it’s due to cost or time, the lack of real-world data is a probable challenge in this setting - necessitating the generation of simulated data. However, it might not be feasible or cost-effective to develop a rigorous model fully characterizing the phenomenon of interest. Any coordinates following an arbitrary (yet continuous) trajectory might be sufficient to test and optimize a transformation. meandr
is designed to fulfill this need.
Each call to meandr()
outputs coordinates from a continuously-differentiable-piecewise-polynomial. In other words: a 2nd-order spline.
You can supply arguments if you wish to change default curve behavior. These are discussed in the next section.
meandr(
n_nodes = 100L, # number of inflection points (more nodes -> more intricate curve)
wt = c(1, -1), # values used to generate 2nd derivative (these are sampled with replacement)
gain = 0.75, # controls sensitivity of wt sampling
n_points = 100L, # number of coordinates (aka resolution)
scale = 1, # scales all f(t) values so that max(f(t)) == scale
seed = NULL # for reproducibility
)
In general, modulating n_nodes
should provide sufficient control. Here, the nodes correspond to inflection points.
Holding seed
constant at 2
, observe that increasing n_nodes
allows below function to meander into new territory. In other words, df2
is just an augmented variation of df1
.
Each call to meandr
first constructs a piecewise step-function by sampling elements from input wt
. The resulting step-function serves as the 2nd derivative, \(f''(t)\), which meandr
integrates twice to obtain final result.
This complete procedure is shown below:
The wt
sampling forming \(f''(t)\) utilizes a special algorithm that strives for alternating positive & negative values. This is to prevent meandr
from generating “boring” curves.
Increasing input gain
will increase the sensitivity of the wt
sampling algorithm, ultimately resulting in a curve with greater local variation. Note, however, that the local effects of changing gain
will cascade with increasing \(t\), resulting in an altogether different curve for the same seed
.
gain1 <- meandr(n_points = 200,
n_nodes = 50,
gain = 0.75, # default
seed = 1010)
gain2 <- meandr(n_points = 200,
n_nodes = 50,
gain = 2, # increase, this will inject more variance into 2nd derivative
seed = 1010)
The default value of wt
, c(1, -1)
, is appropriate for lower levels of gain
near 0.75
. However, gain2
curve above looks slightly unnatural, as one can clearly tell this is simply a series of pure quadratic polynomials chained together. We can avoid this effect by adjusting wt
.
custom_wt <- meandr(n_points = 200,
n_nodes = 50,
wt = seq(-1, 1, by = 0.01), # more variety in 2nd derivative values
gain = 2,
seed = 1010)
Beware! The wt
algorithm passes gain
to exp()
, so you won’t observe much difference as \(e^{gain} \rightarrow \infty\). I recommend starting at the default value of 0.75
and making incremental adjustments as needed.
gain3 <- meandr(gain = 1000) # 1000 doesn't work because exp(1000) returns Inf
#> Error in sample.int(length(x), size, replace, prob): NA in probability vector
Use n_points
to adjust output resolution. This does not affect underlying calculus driving curve shape. Example below uses same seed 2
as before.
meandr
will adjust output so that \(max(f) = scale\).
library(purrr)
scale <- map_dfr(1:5, ~ {
meandr(n_points = 100,
n_nodes = 20,
wt = c(1, -1),
scale = .x,
seed = 20) %>%
mutate(scale = .x)
})
This is useful if you want to supplement meandr
curve with additional noise. In example below, relative amplitude of noise is consistent across different meandr
curves because we use fixed scale
.


--- layout: post status: publish published: true title: Episode 5.06 - "Jarlos Samarmol" author: display_name: Corey Fineran login: Corey email<EMAIL_ADDRESS>url: '' author_login: Corey author_email<EMAIL_ADDRESS>wordpress_id: 8451 wordpress_url: http://ivyenvy.com/?p=8451 date: '2013-04-30 22:29:50 +0000' date_gmt: '2013-05-01 03:29:50 +0000' categories: - Podcast tags: - Kevin Gregg - Jorge Soler - Luis Valbuena - Cody Ransom comments: [] ---
We are a little over a month away from Episode #200 and we're inviting you to celebrate with us. Details can be found at http://ivyenvy.com/200. RSVP on our Facebook event or email<EMAIL_ADDRESS>if you are planning on coming or would like more information.
On this episode, we talk about the unexpected rise of Kevin Gregg. In six appearances, Gregg has a 0.00 ERA and 4 saves. I think you'll notice that we're not quite sure how to process this situation.
We catch up on Ian Stewart and his progress in his rehab stint in Iowa. He's batting .100 with 4 errors in 12 games. The Cubs have added Cody Ransom at 3rd base and after a few games, he is playing well enough that he and Valbuena might be enough to keep Stewart away from the Cubs forever.
Jorge Soler is benched for not hustling by the Daytona manager. We talk about this discipline and consider the Soler red flags.
We then dive into a discussion that a lot of fans of bad teams probably have. Should we find solace in the losses knowing that it ensures a better draft pick?
We answer a few listener submitted questions, Kurt gives us the Scary Stat of the Week and we pick a winner for this week's photo caption contest.
If you enjoy the podcast, we'd really appreciate your rating and review in iTunes. Just click on the image below.


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If everything is working normally, you should automatically connected to nodes soon, please wait.
Version: {{peer.version}} -- Height: {{peer.tipHeight}}
If you want to contribute to the network by becoming a public node, please open the above TCP port and forward it to your local computer IP address.
Ban until: {{peer.banUntil | date:'dd-MM-yyyy HH:mm'}} -- {{peer.banReason}}
Network Height (Chain Tip)
Consensus Height
Blockstore Height
Wallet Height
Uptime
External Address
Network
{{status.relayFee}}
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Wallet Creation Date


|
Fred and Rosemary WestThe couple that slays together, stays together. A bit cliche, but how can you resist such a perfect phrase to describe the most perfectly insidious couple ever to grace the planet Earth. Also applicable would be "The couple that rapes together, stays together," "The couple that molests their children together, stays together," and of course the ever popular "The couple that ties young women up in the basement, performs sado-masochistic Pagan rituals on them, removes the toe bones and sells them to a local coven, and then buries the body in the garden together, stays together."Fred and Rosemary were both abused as children. Rosemary was turning tricks at the age of 14 so she could buy a ticket away from her sexually abusive father.   Rosemary was not Fred's first wife. His first wife was a prostitute named Rena, who he married in 1967. For their honeymoon, Fred splurged on some British rail tickets for himself and his new bride. Along the way between Gloucester and Glasgow, they met up with Ann McFall, an 18-year-old scot who Fred lured into bed. The threesome traveled between Wales and Scotland by train for a few months, stopping off in local towns to do sexy things in hotels. Eventually, Ann got pregnant.  But as soon as Ann entered her third trimester, Fred couldn't slip her the weasel without harming the baby. So, he killed Ann and buried her in a field near his boyhood home.  He then buried her near Ann. By this time, Rena had given birth to Charmaine, a prematurely born daughter with severe birth defects. Her mother was disease ridden and a constant drunkard, and these transgressions did not make for a healthy child. But happy father Fred did not seem to blame his daughter for these shortcomings.   Rosemary got pregnant real quick. Fred obviously hadn't heard of condoms. Around this time, Fred was picked up for larceny and served a short jail sentence. While he was gone, Rosemary evidently grew weary of Charmaine's constant need for attention. She euthanized the child and buried her body in the yard. Sometimes fate is cruel. Sometimes it is kind. Sometimes it is both things at the same time. For Fred West, fate was very friendly. For his daughters, it was not. Fred loved little girls. Couldn't get enough of them. So it is perhaps ironic that the only children Fred ever fathered were female. It was only proper for daddy to break them in! Fred's daughters (The one's that lived anyway) were a constant source of amusement for both daddy and mum. All six were sexually abused as soon as they could walk. But the West's didn't limit themselves to incest. They moved into a cottage at 25 Cromwell Street in Gloucester and redecorated the place in an early Roman style. That is, the style of an early Roman brothel. The basement was adorned with whips, racks, chains, and cages.  The John rooms were rigged for video and audio surveillance. Fred liked to watch. Boarders seemed to come and go quite quickly from the West household. Fred charged nominal rents, and often found his home playing host to poor pregnant mothers and lonely college girls. Of course, when these boarders discovered that they were expected to pay their rent with their pussies, most moved out and left town.  In 1992, authorities began to wonder what had happened to Fred's daughter Heather. The standard line was that she had run off with some dyke at the age of 16. The five remaining West girls, however, giggled and spoke about their sister being buried under the garden path "six across, nine down," her grave marked by cobblestones. When Fred and Rose's explanations weren't satisfactory, the police began digging up the yard. When they started finding thigh bones, the jig was up. One cop said "She hadn't got three legs!" Fred confessed to accidentally killing his daughter Heather, but remained speechless on the other killings. When they got him in jail in 1994, he finally confessed to nine separate murders, though around 14 dead women are commonly attributed to he and Rose. On New Year's Day 1995, Fred hanged himself in his cell. Rosemary was charged with nine counts of first degree murder and remains in jail to this day. A great deal of time has been spent trying to explain why most of West's victims were found missing toe, finger, knee, and collar bones. The common explanation is that the Wests were selling bits and pieces to a local coven of witches. This has never been proved. But none of the some odd 300 missing toe and finger bones have been found, despite the police spending nearly a year searching the West home for more evidence of their disturbing work. If the Wests were selling bones to a coven, it was a strange group of witches to say the least. Neither of the Wests were ever seen to be practicing Pagans, and no one who lived in the neighborhood could remember hearing the daughters talk about witches or magic. Of course, those same neighbors didn't seem to notice the tortured screams coming from the basement, or the constant influx of new dirt piles in the backyard. Whatever the Wests were doing with all those bones will likely never be known. Rosemary doesn't talk much in jail, and Fred's hanging keeps him from speaking to the press. |


I am a chemical engineer turned programmer. I have extensive experience in troubleshooting, logic-based problem solving and root cause analysis. I have successfully managed many complex projects with budgets up to $3MM. I am passionate about finding creative solutions to challenging problems to increase the efficiency of any given process. I am new to the world of coding but I am eager to utilize my engineering training and experience into the medium of software and web development.
If you would like to learn about some of my personal interests, I have included some fun facts.
Email me at: JSyvino@gmail.com


todos
TodoMVC offline
Auto-refresh once we're back online
Take it easy, while network-gnomes fix the issue
Look important
Start Todoing after we're back online


I'm Kelsey
I am a freelance writer in Salt Lake City who specializes in technology, home, and parenting—and the areas where all those subjects intersect. My work has been featured on publications including Realtor Magazine, TechSpective, and Working Mother. Follow me on Twitter @kladown23.
Get in TouchWhat I Write
Technology | Home Automation
Manta | 4 Smart-Home Routines That Will Transform Your Home Office
Z-Wave | How to Create a Smart Home Theater
Who I Write For
Lazy Mom Letter
Enter your email address to subscribe for a weekly(ish) reminder that it's okay to be a less-than-perfect mom.


Kanglong Wu
Oops, looks like you have come to the wrong place!
Note
如果您是本站以前的博客文章访客，我已将博客转移到以下子页面： Blog。
If you are a previous visitor to a blog post on this site, I have moved the my blogs (in Chinese) to the following sub-page: Blog.


class: center, middle, inverse, title-slide #
Getting Started in R
an introduction to data analysis and visualisation
## Welcome! ### Réka Solymosi & Sam Langton & Emily Buehler ### 1 July 2019 --- class: inverse, center, middle # Welcome! --- ## About us  @r_solymosi  @sh_langton  @emily_buehler --- ## About you --- ## About the course **Schedule** | | Slot | Module | |:--------|:-------|:------------------------------------------------------| | **1** | Mon pm | Intro | | **2.1** | Tue am | Basics | | **2.2** | Tue pm | Import data | | **3.1** | Wed am | Tidy data | | **3.2** | Wed pm | Transform data | | **4.1** | Thu am | Visualise data | | **4.2** | Thu pm | Model data | | **5** | Fri am | Reporting data |
 --- ## About the course By the end of the week you will be able to: - be able to read and write basic R code - read your data into R Studio - tidy (prep) your data for analysis - filter and subset data - summarise and create new variables - visualise your data - model your data - presenting results in a report --- ## Why R? - growing popularity - reproducable - learn to code - diverse - open source - community driven --- ## Growing popularity  source: http://r4stats.com/articles/popularity/ --- ## Growing popularity  source: http://r4stats.com/articles/popularity/ --- ## Growing popularity  source: http://r4stats.com/articles/popularity/ --- ## Reproducible  --- ## Reproducible  --- ## Reproducible: the point - People are very opinionated about it - Replication and transparency is a key debate in research - The need for replication is blind to research discipline - One day we might not have a choice in the matter - Either way, it will make your life a lot easier! --- ## Diverse: Inferential stats ```r library(stats) ``` ```r mean() sd() chisq.test() t.test() aov() glm() ``` --- ## Diverse: Plots ```r plot(cars$speed, cars$dist) ```  --- ## Diverse: Plots ```r library(ggplot2) ```  --- ## Diverse: Plots ```r library(waffle) ```  --- ## Diverse: Maps ```r library(ggplot2) ; library(sf) ```  --- ## Diverse: Stylised Maps ```r library(ggplot2) ; library(sf) # + open code ```  --- ## Diverse: Sequence analysis ```r library(TraMineR) ```  --- ## Diverse: Spatial autocorrelation ```r library(spdep) ```  --- ## Diverse: Aoristic analysis ```r library(aoristic) ```  --- ## Diverse: Social network analyis ```r library(igraph) ```  --- ## Diverse: Text mining ```r library(tidytext) ; library(geniusR) ```  --- ## Diverse: Text analysis ```r library(tidytext) ; library(geniusR) ``` ![](https://i2.wp.com/www.johnmackintosh.com/img/2018-01-28-album-word-correlations-original.png?w=456&ssl=1) [Source: John MacKintosh on R bloggers](https://www.r-bloggers.com/hardwired-for-tidy-text/) --- ## Diverse: Text analysis ```r library(tidytext) ```  [Source: Jakub Glinka on R bloggers](https://www.r-bloggers.com/sentiment-analysis-of-the-lord-of-the-rings-with-tidytext/) --- ## Diverse: interactive maps ```r library(tmap) ``` ![](img/ME_gif.gif) --- ## Diverse: Shiny apps to visualise voting  --- ## Open tools  --- ## Open source  --- ## Open source  --- ## Community driven  --- ## Community driven  --- ## Community driven  --- ## Community driven  --- ## Community driven  --- ## Community driven  --- ## Community driven  --- ## Community driven  --- ## Community driven Top resources: - Stack Overflow - RPubs - R4DS - Twitter --- ## Community driven  --- ## Join the community  --- ## After coffee - get to know R Studio - learn about packages - open, edit and run an R script - save the output


Alex Brown
Web Developer & Designer
Personal Profile
I am originally from Seattle but I have lived in Utah for the past 8 years. I worked to put myself through school and, while working for a marketing group in SEO, I found that I was more drawn to the technology aspect of my work.
I enrolled in a coding bootcamp through Coding Campus and graduated from both there and BYU at the same time. Almost immediately after graduation, I transfered from my SEO Marketing job and started working with a custom development shop called Lift Media as a combination Web Developer/ Front-end Designer. I work with clients to help them develop and design websites that fit their needs. I think of myself as a developer first with a passion for design (in fact, I enjoyed designing so much that I started my own clothing shop called Wolf & Co where I design & sell my own T-Shirts).
I love creating beautiful and functional websites. If you do too, then we'll make a great team.
Skills
Development Specialties
- HTML5
- CSS
- javaScript
- jQuery
- Mobile Responsiveness
- Bootstrap
- Git
- WordPress
- Shopify
- Instructional Development
- Google Analytics
- Google Development API
Development Experience
- PHP
- MySQL
- AngularJS
- Python
- Django
Design Specialties
- Adobe Photoshop
- Adobe Illustrator
- Responsive Web Design
- Branding
- Logo Design
- Clothing Design
Design Experience
- UI/UX
Portfolio
Development
-
UACTE Website
-
Purple Shopify Website
-
Ward Bros Website
-
Windsor Manor Website
-
iTOVi Website
-
Dr. Allen Website
-
RoomChoice Web App
-
Multipage Dentist Website Template
-
Single Page Dentist Website Template
-
RoomChoice Online Sales Tool
-
eLearning Quiz for Versado Training
-
Box of Love Website Mockup
-
Perfect Website Mockup
Design
-
Websites
-
Logos
-
Clothing


Data
Which dataset do you want to use?
Features
Click anywhere to edit.
Weight/Bias is 0.2.
Showing Output for Variable: Facebook Friends
Test loss
Training loss
Colors shows data, neuron and weight values.


The use of COBOL cripples the mind; its teaching should, therefore, be regarded as a criminal offense. -- Edsgar Dijkstra [source]


Across: 5. Aspire to admiration! (6) 8. Natural flair shown by 100 in fashionable period (8) 9. Viper is slithering round toilets! (7) 10. Quick, nobody is faster than you initially! (5) 11. Look after rings and belt (9) 13. Ran to get job with journalist (8) 14. Frisk doctor in prison (6) 17. 100 not out! (3) 19. She may change (3) 20. Rude antics on boat provoke threats (6) 23.  (8) 26. May be necessary for aerobics to end in next shake-up (9) 28. Supporter at home may be hit on the head! (5) 29. Exercises in Hut 99 can inhibit blood flow (7) 30. Artist comes out of Tate, grim! (8) 31. Climbed up and removed coat (6) Down: 1. Writer carrying on with me is somewhat artificial (6) 2. Remains by car in Kentish Town (7) 3. Do these men work in London out of convenience? (4 5) 4. Cries uncontrollably about note to writer (6) 5. Frantically grip a mad model! (8) 6. Granville's heart is made of iron! (5) 7. Framework keels over on to heavyweight (8) 12. Fuss about one party! (3) 15. After one year, boy takes Ruby out to town (9) 16. High-minded cox quit! I go to pieces! (8) 18. May be calcified if dose is wrong (8) 21. Desperate for judo grade? (3) 22. Rats sit in passages (7) 24. River-master (6) 25. Nailed disgraceful lion-tamer! (6) 27. Throw out part of a box of Perspex pellets (5)


Next: undefined-function, Previous: control-error, Up: Data and Control Flow Dictionary
program-error, error, serious-condition, condition, t
The type program-error consists of error conditions related to incorrect program syntax. The errors that result from naming a go tag or a block tag that is not lexically apparent are of type program-error.


This dialog is very similar to the dialogs you fill out when configuring your e-mail program.
This dialog shows the settings when using a Yahoo account.
Click Next when you are done to test your settings.
< Back Next: Email Diagnostics >


recommended movies
Iron Man
Iron Man 3
Iron Man 2
Guardians of the Galaxy
Captain America: The Winter Soldier
Captain America: Civil War
The Avengers
Captain America: The First Avenger
Green Lantern
The Core
The Man from U.N.C.L.E.
Ransom
Ant-Man
Cradle 2 the Grave
I Am Legend
Rio 2
Journey to the Center of the Earth
Men in Black II
Planet 51


What is a private key?
Every account is defined by a pair of keys: (1) a private key and (2) a public key. Each account has an address that is derived from the public key by using the last 20 bytes of information. The private key is the secret half of your address/public key.
The private key consists of 64 hexadecimal characters that should look like this:
56f759ece75f0ab1b783893cbe390288978d4d4ff24dd233245b4285fcc31cf6
If you misspell any portion of the private key, you will be attempting to access a different wallet. Without your private key you cannot access your funds.
The private key is an unencrypted private key. Anyone with access to your private key can control your wallet. If you do not have your private key, you do not own your wallet. We advise you to not backup using your private key, but instead use your mnemonic to securely backup your wallet.
Remember: We do not save your password, once forgotten, it cannot be recovered.


ITV This Morning's Holly Willoughby fans immediately start googling for skirt
Many thought it was the perfect skirt for winter
by Rebecca KoncienzcyFans of TV presenter Holly Willoughby have already been googling where to get hold of her new winter skirt.
The 38-year-old posted a snap of her outfit on Instagram ahead of today's edition of This Morning, showing off her tartan fashion choice.
Her followers loved the look, many wanting to know how they could get their hands on the skirt for themselves.
One, laura__k said: "Love that skirt. *immediately starts googling*"
Another, joanneswift23 said: "I need this outfit."
A third, bethmcfarlane547 said: "Love your skirt."
Holly's skirt is from Hobbs London and is priced at £99. Available in two colours, the Elea wool garment is dry clean only and available in sizes 8 to 18.
She paired it with a simple cream knitted jumper from Pure PR London who Are a client-based beauty, wellbeing and interior design company.
Completing her 'perfect' winter look, Holly wore black tights and black boots from Whistles.
The mum-of-three has been sporting some classic seasonal looks recently, including at the European premier of Frozen 2 at the BFI Southbank in London last night.

*This Morning is on ITV1 weekdays from 10:30am


| 036:077 Khan | : |
Does not man see that We have created him from Nutfah (mixed male and female discharge semen drops). Yet behold! He (stands forth) as an open opponent. |
| 036:077 Maulana | : |
Does not man see that We have created him from the small life-germ? Then lo! he is an open disputant. |
| 036:077 Pickthal | : |
Hath not man seen that We have created him from a drop of seed? Yet lo! he is an open opponent. |
| 036:077 Rashad | : |
Does the human being not see that we created him from a tiny drop, then he turns into an ardent enemy? |
| 036:077 Sarwar | : |
Has the human being not considered that We have created him from a drop of fluid. He is openly quarrelsome. |
| 036:077 Shakir | : |
Does not man see that We have created him from the small seed? Then lo! he is an open disputant. |
| 036:077 Sherali | : |
Does not man see that WE have created him from a mere sperm-drop? Then lo ! he is an open quarreler ! |
| 036:077 Yusufali | : |
Doth not man see that it is We Who created him from sperm? yet behold! he (stands forth) as an open adversary! |
Concepts/Themes Covered: أركان الإسلام > التوحيد > توحيد الله تعالي > وحدانيته Pillars of Islam> Islamic> Oneness of Allah> Singularity and Being Unique الإنسان والعلاقات الاجتماعية > الإنسان > أحواله وأوصافه Man and The Social Relations>Man>His Cirumstances and his Specifications الإنسان والعلاقات الاجتماعية > الإنسان > شرفه ودنوه Man and The Social Relations>Man>When Honourable and When Unhonourable الإنسان والعلاقات الاجتماعية > الرجل والمرأة Man and The Social Relations>Man and Woman
This tool uses eight English parallel translations for the Holy Quran imported from Mr. Clay Smith. You can also visit Qurany Concepts for browsing the Quran themes or topics. If you want to search the Holy Quran for keywords, please visit Qurany Keywords.


Semester Project Update #1 February 5th, 2021
Journal 2 February 5th, 2021
Journal 3 February 5th, 2021


| Age |
Reported sex |
| Injury type |
Type of collision |
| Time of day |
Year of collision |
| ◉ – Fatality | ◉ – Severe injury |
| ◉ – Visible injury | ◉ – Other injury |


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Adam Cotter | 09 Dec 2017 |
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Pauline Noble | 26 Jan 2018 |
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Sherilyn Metzel | 27 Jan 2018 |
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Terrie Boaler | 20 Jan 2018 |
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Rutter Pude | 13 Jan 2018 |
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Clifford Benjamin | 25 Jan 2018 |
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Thedric Romans | 12 Jan 2018 |
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Haily Carthew | 27 Jan 2018 |
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Dorothea Joicey | 12 Dec 2017 |
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Mikaela Pinel | 10 Dec 2017 |
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Donnell Farries | 03 Dec 2017 |
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Letizia Puncher | 09 Dec 2017 |
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A responsive site is one which adjusts it layout based on the size of the screen which the user is viewing it on. Responsive sites are important in this day and age because we view web pages on many different screen sizes and the users experience is very important for repeat visits.
A mobile first design is one which caters to the mobile user first. It is built with the mobile user in mind, then additional elements and features are added later.
Frameworks provide the developer with a foundation to use. This foundation of code saves the developer time and money. The down side of using this is that the developer is less likely to fully understand the code and when it comes to making changes they may come up short. The developer can also be limited by the framework itself and options available to build within it.
A wireframe is a 'blueprint' drawing of a web page. It provides the designer with a clearer picture of what the web page will look like and makes it easier for them to see the overall layout of the page before diving in to design.
Well I've had difficulty with most of the implementation, but it has been a good learning curve. I have had alot of HTML and CSS practice this week. The main difficulties I had was adding a nav bar and then changing the size of some font, but not all of it. This involved alot of adjustments. My next mission is to make my menu bar responsive and align the images below..


December 18, 2017
Admissions
Please visit the offical admissions for undergraduates course
Courses
ATM1001 Global Environment and Atmospheric Sciences
Scientific understanding of global environmental problems such as global warming, destruction of the ozone layer, air pollution, desertification, El Nino/ La Nino severe weather, etc. and related research areas and methodologies in atmospheric sciences.
ATM2101 Climate and Global Change
Understanding global-scale changes such as global warming, destruction of the ozone layer, desertification in terms of climate system including the atmosphere, oceans and terrestrial ecosystems.
ATM2102 Atmospheric Environment
Basic properties of the atmosphere such as its structure, physical and chemical properties, motions and circulations; atmospheric environmental problems associated with changes in atmospheric quality such as urban air pollution and long-range transport, photochemical smog, and acid rain.
ATM2103 Broadcasting Meteorology
Understanding the process of weather forecasting in the media including TV and radio broadcast script writing and practice, and discussion on related issues.
ATM3103, 4101 Atmospheric Dynamics I, II
Description of atmospheric motions based on fluid dynamics and thermodynamics: geostrophic motions, hydrostatic equation, vorticity and circulation, planetary boundary layer, synoptic motion, atmospheric oscillation, baroclinic instability, mesoscale circulation, and atmospheric general circulation.
ATM3104, 3108 Atmospheric Physics I, II
Atmospheric thermodynamics, cloud physics and precipitation processes, solar radiation and radiative transfer in the planetary atmosphere, atmospheric optical aerosol, and atmospheric electromagnetic theory.
ATM3105 Micrometeorology
Physical processes governing the wind, temperature and moisture in the surface layer, components of radiative interaction, heat transfer in the surface layer, turbulent transport of energy and mass, Monin-Obukhov similarity theory, urban meteorology, evaporation, and agricultural and forest meteorology.
ATM3106 Atmospheric Measurements
Methods and principles of meteorological observations, instrumentations in the surface layer, upper air and radiosonde measurements, meteorological satellites, experimental design, principles of field operation and management, data analysis, and field trip.
ATM3107 Atmospheric Chemistry
Atmospheric pollutants, chemical reactions of atmospheric pollutants, photochemistry of the ozone and other minor gases, atmospheric constituents and climate change, chemical analysis of urban atmosphere, removal processes.
ATM3109 Atmospheric Analysis
Analysis of meteorological codes, synoptic analyses (isobaric analysis and vertical sounding), air mass analysis, analyses of radar and satellite data, and production of climatic data.
ATM3110 Satellite Meteorology
Orbital and instrumental characteristics of meteorological satellites, measurements of meteorological variables by infrared, visible and microwave, radiative equilibrium and albedo, satellite measurements of surface temperature, atmospheric thermal structure, cloud heights and morphology, atmospheric secondary components, aerosols and precipitation, winds, etc.
ATM3111 Physical Oceanography
Physical understanding of oceanic motions, atmosphere-ocean interactions, balance of heat and salinity, Ekman layer, upwelling, oceanic general circulation, quasigeostrophic theory, surface gravity waves, Tsunami, ocean mixed layer, El Nino, and oceanic acoustics.
ATM3112 Upper Atmosphere
Physics and chemistry of the stratosphere, mesosphere and thermosphere, internal gravity waves, dynamics of equatorial oscillations and polar vortex, ozone budget, atmospheric tides, the earth’s magnetic field and its variations, and aurora.
ATM3113 Statistical Analysis in Meteorology
Statistical measures of meteorological variables (mean values, standard deviations, frequency distributions, correlation coefficients), spectral analysis of a simple time series, spectral and principal-component analyses of a space-time structure, correlations and statistical prediction, and rational verification of forecasting.
ATM3114 Aviation Meteorology
Understanding atmospheric phenomena relevant to aircraft operation, and its application to aviation weather forecast.
ATM4102 Fluid Dynamics
Equations of motion, continuity equation, streamlines, vorticity, dynamical similarity, inviscid flows, wave motions, boundary layer theory, rotating and stratified flows, buoyancy driven flows, turbulence, hydrodynamic instability, two-phase flows, and chaos.
ATM4103 Computational Fluid Dynamics
Numerical simulations and understanding of meteorological phenomena and climate change using computers, finite difference methods, finite element methods, spectral methods, numerical instability, numerical weather forecast, climate and typhoon simulation.
ATM4104 Air Pollution
Properties and measurements of air pollutants, effects of synoptic meteorological systems, mixed-layer dynamics, diffusion and transport of atmospheric pollutants, removal processes.


Lookin' for puppy love? Canadian photographer creates 'online dating profiles' for dogs on Instagram to help them get adopted by showcasing their unique personalities
by Erica Tempesta For Dailymail.com- Rachael Rodgers, 36, from Canmore, Alberta, takes dogs from shelters and foster homes and has outdoor photo shoots with them
- She posts the dogs' photos, videos, and personal bios on her Instagram account @trailsandbears in hopes of finding them loving homes
- Over the past two years, Rachael has photographed more than 200 dogs, and the feedback from the shelters has been positive
- Rachael's Instagram account now has more than 75,000 followers
A Canadian photographer is helping dogs get adopted by creating 'online dating profiles' for them complete with portraits on her popular Instagram account.
Rachael Rodgers, 36, from Canmore, Alberta, voluntarily takes dogs from shelters and foster homes and has outdoor photo shoots with them to show potential owners what they are like and hopefully find them the right match.
'That’s exactly what you want to do with the dog, is show them as you would an online dating profile,' she told NBC News of the posts shared on her account @trailsandbears, which boasts more than 75,000 followers.

Rachael said she came up with the idea after she posted a photo of her dog, Denali, sitting in a canoe in December 2016.
To her surprise, the scenic post got picked up by a dog Instagram account with millions of followers, prompting 6,000 people to start following her in return.
Wanting to make use of her newfound Instagram fame, she realized she could to some good by showing her dog-loving followers pictures of animals who need homes.
Rachael picks up the dogs from shelters herself, though some of the animals she is working with will get dropped off by their foster owners.
She admitted 'the behind-the-scenes is not glamorous at all,' explaining some of the shelters she works with are a three-hour drive away from her home.
As part of her project, she documents her day with the dogs with both photos and videos. Most of her posts feature at least one shot of the pups taken at eye level.
The footage is outdoorsy in nature, with plenty of snapshots of them frolicking in the snow or enjoying a kayak ride.
In order to get photos that show the dogs' true nature, she pets them and talks to them the whole time to get them to warm up.
Rachael takes hundreds of photos of each dog before narrowing them down to the ten or so she will edit and post on Instagram and Facebook.
The photos are accompanied by lengthy captions that detail their adventure and describe each pooch's personality.
'This is Zach. He’s a puppy. He doesn’t know what he wants to be yet when he grows up, but whatever it is, he wants to be the best one,' she captioned a post from April.
'Zach is a puppy rep for pups of four litters who were all born from moms who were living stray in Northern Saskatchewan. If you’re looking for a puppy, please remember that you can adopt a blank slate rather than ordering one up custom from a breeder.'
Over the past two years, Rachael has photographed more than 200 dogs, and the feedback from the shelters has been positive.
It's unclear exactly how many of the animals have been adopted because of her Instagram account, but the interaction she has had with people who given homes to the pups she has photographed indicates it's helpful.
'There’s just too many unwanted dogs,' she told NBC news. 'I guess my goal is to show how amazing just any random dog at a shelter is, [and] usually I take the dogs that are harder to adopt. But if those dogs are amazing, then why get a family pet from a breeder?'


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-at first enter the new application page and submit your application
-In the manage app page grab the hash code for your application
-using 'GET' you can access the complete information like the example below
-Using 'GET' you can check the user's version for sending it to server like the example below