Words about the widget! Words about the widget! Words about the widget! Words about the widget! Words about the widget! Words about the widget! Words about the widget! Words about the widget! Words about the widget!
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Compare Widget to other products:
| Product | Quality | Speed | Strength | Price |
|---|---|---|---|---|
| Widget | Extremely High | 250,000 RPM | Withstands up to 2,000 tons per square inch | $10.00 |
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| 2009 Nissan Altima | 8.5 out of 10 | Up to 110 mph | No damage with collisions less than 1 mile per hour | $10,000 or more |
| Playbill | Cardstock | 0 | As strong as dry paper | Less than $0.50 |
| Brick | Good | Stationary | Holds up a building | $20.00 |
| Certificate of Deposit | Paper | 3 years | Dependent on the strength of the economy | As determined by the buyer |


|
App Engine Python SDK
v1.6.9 rev.445
The Python runtime is available as an experimental Preview feature.
|
Public Member Functions | |
| def | __init__ |
| def | __iter__ |
| def | from_json |
| def | to_json |
| def | split_input |
| def | validate |
| def | __str__ |
| Public Member Functions inherited from google.appengine.ext.mapreduce.input_readers.InputReader | |
| def | __iter__ |
| def | next |
| def | from_json |
| def | to_json |
| def | split_input |
| def | validate |
| Public Member Functions inherited from google.appengine.ext.mapreduce.json_util.JsonMixin | |
| def | to_json_str |
| def | from_json_str |
Static Public Attributes | |
| string | START_TIME_PARAM = "start_time" |
| string | END_TIME_PARAM = "end_time" |
| string | MINIMUM_LOG_LEVEL_PARAM = "minimum_log_level" |
| string | INCLUDE_INCOMPLETE_PARAM = "include_incomplete" |
| string | INCLUDE_APP_LOGS_PARAM = "include_app_logs" |
| string | VERSION_IDS_PARAM = "version_ids" |
| string | MODULE_VERSIONS_PARAM = "module_versions" |
| Static Public Attributes inherited from google.appengine.ext.mapreduce.input_readers.InputReader | |
| expand_parameters = False | |
| string | NAMESPACE_PARAM = "namespace" |
| string | NAMESPACES_PARAM = "namespaces" |
Input reader for a time range of logs via the Logs Reader API. The number of input shards may be specified by the SHARDS_PARAM mapper parameter. A starting and ending time (in seconds since the Unix epoch) are required to generate time ranges over which to shard the input.
| def google.appengine.ext.mapreduce.input_readers.LogInputReader.__init__ | ( | self, | |
start_time = None , |
|||
end_time = None , |
|||
minimum_log_level = None , |
|||
include_incomplete = False , |
|||
include_app_logs = False , |
|||
version_ids = None , |
|||
module_versions = None , |
|||
| kwargs | |||
| ) |
Constructor. Args: start_time: The earliest request completion or last-update time of logs that should be mapped over, in seconds since the Unix epoch. end_time: The latest request completion or last-update time that logs should be mapped over, in seconds since the Unix epoch. minimum_log_level: An application log level which serves as a filter on the requests mapped over--requests with no application log at or above the specified level will be omitted, even if include_app_logs is False. include_incomplete: Whether or not to include requests that have started but not yet finished, as a boolean. Defaults to False. include_app_logs: Whether or not to include application level logs in the mapped logs, as a boolean. Defaults to False. version_ids: A list of version ids whose logs should be read. This can not be used with module_versions module_versions: A list of tuples containing a module and version id whose logs should be read. This can not be used with version_ids **kwargs: A dictionary of keywords associated with this input reader.
| def google.appengine.ext.mapreduce.input_readers.LogInputReader.__iter__ | ( | self | ) |
Iterates over logs in a given range of time. Yields: A RequestLog containing all the information for a single request.
| def google.appengine.ext.mapreduce.input_readers.LogInputReader.__str__ | ( | self | ) |
Returns the string representation of this LogInputReader.
| def google.appengine.ext.mapreduce.input_readers.LogInputReader.from_json | ( | cls, | |
| json | |||
| ) |
Creates an instance of the InputReader for the given input shard's state. Args: json: The InputReader state as a dict-like object. Returns: An instance of the InputReader configured using the given JSON parameters.
| def google.appengine.ext.mapreduce.input_readers.LogInputReader.split_input | ( | cls, | |
| mapper_spec | |||
| ) |
Returns a list of input readers for the given input specification. Args: mapper_spec: The MapperSpec for this InputReader. Returns: A list of InputReaders.
| def google.appengine.ext.mapreduce.input_readers.LogInputReader.to_json | ( | self | ) |
Returns an input shard state for the remaining inputs. Returns: A JSON serializable version of the remaining input to read.
| def google.appengine.ext.mapreduce.input_readers.LogInputReader.validate | ( | cls, | |
| mapper_spec | |||
| ) |
Validates the mapper's specification and all necessary parameters. Args: mapper_spec: The MapperSpec to be used with this InputReader. Raises: BadReaderParamsError: If the user fails to specify both a starting time and an ending time, or if the starting time is later than the ending time.


Runtimes power the server-side processing of your application, and we can get you set up in one of several languages and frameworks. If you're looking to expose an HTTP API or interact with services like a database, choosing one here will hook that together for you.
{{runtime.description}}


Lost your keys? Tired of washing dishes but have a lot of shrink wrap for some odd reason? Are you slightly deaf and can't hear your phone play your favorite tunes? perhaps you have had one too many stale snickerdoodles? We have you covered here!
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Tired of losing your keys? Do this . Turn your nose ring into a keychain so you never have to worry about losing your keys again#LifeHackspic.twitter.com/32UUkWzVdR


SIUI is a self-initiated research project. SIUI stands for Spacially Independent User Interface, and deals with the concept of computer interfaces that float in mid-air, as seen mainly in Hollywood films like Iron Man and Minority Report. The aim of this research project is to conceptually explore what it would take to make something like this a technological reality.
5/25/2010 This evening I went to see Iron Man 2 with Ashley. It was an awesome film. Watching Tony Stark interact with the J.A.R.V.I.S. computer's interface inspired me to wonder, "how could such an interface work in real life?" It would have to be able to illuminate the air with out projection or screen. So how would it be possible?


|
Team 302 Swerve Robot
|
This applies a cubic profile to the input values. More...
#include <PiecewiseLinearProfile.h>
Public Member Functions | |
| PiecewiseLinearProfile () | |
| ~PiecewiseLinearProfile ()=default | |
| double | ApplyProfile (double inputVal) const override |
| : Apply the profile More... | |
This applies a cubic profile to the input values.
Definition at line 35 of file PiecewiseLinearProfile.h.
| PiecewiseLinearProfile::PiecewiseLinearProfile | ( | ) |
Definition at line 36 of file PiecewiseLinearProfile.cpp.
|
default |
|
overridevirtual |
: Apply the profile
Apply the profile.
| double | inputVal - value to be scaled (have profile applied to) |
| [in] | value | that needs the profile (scaling) applied |
Implements IProfile.
Definition at line 50 of file PiecewiseLinearProfile.cpp.


| DOSE: |
1.5 g |
smoked |
Cannabis |
(plant material) |
I'd like to start off by saying that I have never been into anything at all. I don't even like to drink. I guess the public idea on 'drugs' was working on me. I started reading various books and reading about spiritual healing or enlightenment. I am learning meditation on the chakras which is very rewarding especially when learning from sacred plants. I was going to try LSD or mushrooms first but after hearing about the revelations and strong effect of this herb I thought I should try it first.
I started out by thinking earlier that day on the goals and what I wanted to achieve. I then proceeded to pick up about 3 grams of some good herb. I packed up a homemade water pipe and a blanket and went down to the local park. I sat down and over the course of about 15 min. smoked two fairly large bowls. I was just about to pack up and go because I thought it wasn't going to work when it just hit me. I had an incredible body rush and a feeling of being inside my body, opposed to being a part of it.
I went down to a nice spot beside the water and sat down to think. I closed my eyes and just concentrated on the new state I was in. (Just to note I have been strongly questioning my religion lately) I saw a swirling tunnel and as it got clearer it appeared to be almost a conveyer belt at some sort of factory. I then saw that there were little statues of Jesus coming out of the conveyer belt. I immediately knew that this was illustrating the modern churches today. People today are only drawn to religion because of their fear of death. It is basically if you own a bible and attend church, you will be saved. It made me feel disgusted. I then thought that the Native American Church really has it right. They treat every natural thing around them as a gift from God and really trust it. I now believe the same thing.
I found myself thinking about Aldous Huxley's ideas about schizophrenia that goes something like: A person who has schizophrenia is like a person permanently under the influence of mescaline, and without warning is thrust into a world in which they are not holy enough to live in. That is enough to scare people into catatonia or violent outbreaks. I believe that is very much like the idea of heaven and hell. During your life you can chose to spiritually strengthen yourself so when the time of death comes you can readily accept the enlightenment. If you choose not to prepare it can be unexpected and turn into your worst nightmares. I suppose that is the point of the Tibetan Book of the Dead, to embrace the clear light.
After thinking for quite some time on the topics, I headed back to my house and laid down on my bed and threw on Dark Side of the Moon. I sat until the end of the great album, completely meditating to the music and exploring the new realm of consciousness. And by the time Eclipse was just ending right at the end where the song really picks up, felt like the happiest moment of my life.
That was pretty much the night and I drifted into sleep. The whole thing lasted about 3 hours. I woke up the next morning feeling very refreshed. I am very thankful for the lessons and wisdom of this teacher plant. I am eager to learn but not rushing it because I want to respect and take seriously the teachings of this world and keep them sacred.
I wish more people would take these sort of things more seriously and not hold onto things they canít keep. I encourage anyone to pick up a book by Timothy Leary or Terrance McKenna and really understand and think about what they are talking about.
Peace.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


{{ref improve|date=March 2013}} {{Infobox prepared food | name = Hot milk cake | image = | caption = | alternate_name = | country = United States | region = Mid-Atlantic States | creator = | course = | type = Cake | served = | main_ingredient = Flour, milk, eggs | variations = | calories = | other = }} Hot milk cake is a traditional two layer cake, possibly from the Mid-Atlantic States. It can be frosted with mocha icing.
It is served every year at the Anne Arundel County Historical Society annual Strawberry Festival at Baltimore-Washington International Airport.<ref>{{cite web | accessdate=August 24, 2005|title=Benson-Hammond House Opens its Doors for Annual Strawberry Festival|work=Press Releases|author=Tracy Newman|url=http://www.bwiairport.com/press_room/press_releases/117/ | archiveurl=http://web.archive.org/web/20060324055425/http://www.bwiairport.com/press_room/press_releases/117/ |archivedate=2006-03-24 }}</ref>
It is also a traditional quick one layer cake served in the Southern U.S., topped with fruit, powdered sugar icing, or boiled coconut topping.
Hot milk cake gets its distinctive flavor from the scalded milk that is the liquid component of the batter. It differs from traditional sponge cakes in that it does contain baking powder as leavening, and the eggs are beaten together whole instead of whipping the yolks and whites separately.
{{Reflist}}
{{Cookbook|Hot milk cake}} {{Cookbook|Mocha icing}}
{{Cakes}}
{{dessert-stub}}


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| THE INTERNET PLASMA PHYSICS EDUCATION EXPERIENCE | |
|
This site contains Interactive Plasma Physics Topics, ranging from electricity, magnetism, energy, and especially fusion. Please visit the "Virtual Tokamak" and our "Virtual Magnetic Stability Module" to learn about Plasma and Fusion Containment. You can even analyze actual data from past and current fusion experiments!
If you have any questions about fusion and plasma terminology, please visit our glossary of terms. If you have any questions or comments about this web site, please send a letter to our resident plasma physicist in our "Ask a Physicist" corner.
THE NATIONAL SPHERICAL TORUS EXPERIMENT View live streaming video from the PPPL campus! You can view live video from the NSTX control room as experiments are taking place. Click here for the control room feed, or click here to visit the NSTX site... [http://nstx.pppl.gov] View an interactive plasma stability walk-through! You can view actual data graphed with streaming video of stable and unstable plasmas. Click here for screen shots. [Flash plug-in required.]
The new site redesign is now online! Please email<EMAIL_ADDRESS>with questions / comments / concerns. **Best if viewed with Internet Explorer 5.0 and Greater** For certain pages at our Online Education Site, you may be required to have macromedia shockwave and flash installed, please click here for flash and/or shockwave.
Some of the awards our site has won for Science Education: |
|
|
home - about fusion - interactive physics - ask a physicist - virtual tokamak |
|
Copyright © 2001 IPPEX ONLINE
all rights reserved.
http://ippex-test.pppl.gov/ekaiser check out the Vulcan Interactive Plasma Display


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MoreToppingz™
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Which toppings would you like
Cheese.
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Supreme.
Pepperoni.
Fruit.
Bacon.
Artichoke.
Peanut Butter.
Number of Pizzas:
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Picking
Deliver
Process Order
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启蒙
To a very special teacher,Because you're always thought of
in a very special way, sure wouldn't
miss a chance like this to tell you so today, Happy Birthday!
献给豁达宽厚的老师， 因为在我的心里，您总是特别珍贵， 今天我能告诉您，
当然不错过机会。 祝您生日快乐!
成长
With love and the very warmest birthday, and because you're a wonderful teacher.
献上我对你的爱，祝你生日快乐充满温馨， 都因为你是最可爱的老师
歌颂
Roses, sweet and fragrant, sent to you to say, May each hour be
a happy one on this special day. Have a happy birthday!
送你一束甜蜜芬芳的玫瑰， 她对你说，今天的喜庆分外美妙，
每时每刻都同样幸福，令人陶醉。 祝你生日快乐!


Site Hound
{{current_user}}
arrow_drop_down
Change password
Log out
Workspace:
arrow_drop_down
Change workspace
Seeds
Model
Jobs
{% if is_admin %}
Users
{% endif %}


SubTrainer
FAQ's
Download Rikaikun Translator Chrome Extension
Drop a video locally or from your browser here.
Your browser doesn't support video. Please
upgrade your browser
to see the example.


Usage
The usage can be seen by running
processMeerKAT.py -h
the output of which is documented below.
Simple usage
-
To get things working, source
setup.sh
, which will add to your$PATH
and$PYTHONPATH
(add this to your~/.profile
, for future use)source /idia/software/pipelines/master/setup.sh
-
To build a config file, which the pipeline reads as input for how to process the data, run
processMeerKAT.py -B -C myconfig.txt -M mydata.ms
-
To run the pipeline, run
processMeerKAT.py -R -C myconfig.txt
This will create
submit_pipeline.sh
, which you can then run to submit all pipeline jobs to a SLURM queue:./submit_pipeline.sh
-
Display a summary of the submitted jobs
./summary.sh
-
Kill the submitted jobs
./killJobs.sh
-
If the pipeline crashes, or reports an error, find the error(s) by running (after the pipeline has run)
./findErrors.sh
-
Once the pipeline has completed, display the start and end times of each job by running
./displayTimes.sh
Detailed usage
-
Build config file using a custom SLURM configuration (nodes and tasks per node may be overwritten in your config file with something more appropriate by the end of the build step)
processMeerKAT.py -B -C myconfig.txt -M mydata.ms -p Test02 -N 10 -t 8 -D 4 -m 100 -T 06:00:00 -n run1_
-
Build config file using different MPI wrapper and container
processMeerKAT.py -B -C myconfig.txt -M mydata.ms --mpi_wrapper /path/to/another/mpi/wrapper --container /path/to/another/container
-
Build config file with different set of (python) scripts
processMeerKAT.py -B -C myconfig.txt -S /absolute/path/to/my/script.py False /absolute/path/to/container.simg -S partition.py True '' -S relative/path/to/my/script.py True relative/path/to/container.simg -S flag_round_1.py True '' -S script_in_bash_PATH.py False container_in_bash_PATH.simg -S setjy.py True ''
-
Run the pipeline immediately in verbose mode
processMeerKAT.py -R -v -s -C myconfig.txt
NOTE: All other command-line arguments passed into processMeerKAT.py
when using option [-R --run]
will have no effect, since the arguments are read from the config file at this point. Only options [-s --submit], [-v --verbose]
and [-C --config]
will have any effect at this point. Similarly, changing the [slurm]
section in your config file after using option [-R --run]
will have no effect unless you [-R --run]
again.
Command-line options
The command line help text is:
usage: /idia/software/pipelines/master/processMeerKAT/processMeerKAT.py [-h] [-M path] [-C path] [-N num] [-t num] [-D num] [-m num] [-p name] [-T time] [-S script threadsafe container] [-b script threadsafe container]
[-a script threadsafe container] [--modules [module [module ...]]] [-w path] [-c path] [-n unique] [-d list] [-e nodes] [-A group] [-r name] [-l] [-s]
[-v] [-q] [-P] [-2] [-I] [-x] [-j] (-B | -R | -V | -L)
Process MeerKAT data via CASA MeasurementSet. Version: 2.0
optional arguments:
-h, --help show this help message and exit
-M path, --MS path Path to MeasurementSet.
-C path, --config path
Relative (not absolute) path to config file.
-N num, --nodes num Use this number of nodes [default: 1; max: 79].
-t num, --ntasks-per-node num
Use this number of tasks (per node) [default: 16; max: 32].
-D num, --plane num Distribute tasks of this block size before moving onto next node [default: 1; max: ntasks-per-node].
-m num, --mem num Use this many GB of memory (per node) for threadsafe scripts [default: 232; max: 232].
-p name, --partition name
SLURM partition to use [default: 'Main'].
-T time, --time time Time limit to use for all jobs, in the form d-hh:mm:ss [default: '12:00:00'].
-S script threadsafe container, --scripts script threadsafe container
Run pipeline with these scripts, in this order, using these containers (3rd value - empty string to default to [-c --container]). Is it threadsafe (2nd value)?
-b script threadsafe container, --precal_scripts script threadsafe container
Same as [-S --scripts], but run before calibration.
-a script threadsafe container, --postcal_scripts script threadsafe container
Same as [-S --scripts], but run after calibration.
--modules [module [module ...]]
Load these modules within each sbatch script.
-w path, --mpi_wrapper path
Use this mpi wrapper when calling threadsafe scripts [default: 'mpirun'].
-c path, --container path
Use this container when calling scripts [default: '/idia/software/containers/casa-6.4.4-modular.simg'].
-n unique, --name unique
Unique name to give this pipeline run (e.g. 'run1_'), appended to the start of all job names. [default: ''].
-d list, --dependencies list
Comma-separated list (without spaces) of SLURM job dependencies (only used when nspw=1). [default: ''].
-e nodes, --exclude nodes
SLURM worker nodes to exclude [default: ''].
-A group, --account group
SLURM accounting group to use (e.g. 'b05-pipelines-ag' - check 'sacctmgr show user $USER cluster=ilifu-slurm20 -s format=account%30') [default: 'b03-idia-ag'].
-r name, --reservation name
SLURM reservation to use. [default: ''].
-l, --local Build config file locally (i.e. without calling srun) [default: False].
-s, --submit Submit jobs immediately to SLURM queue [default: False].
-v, --verbose Verbose output? [default: False].
-q, --quiet Activate quiet mode, with suppressed output [default: False].
-P, --dopol Perform polarization calibration in the pipeline [default: False].
-2, --do2GC Perform (2GC) self-calibration in the pipeline [default: False].
-I, --science_image Create a science image [default: False].
-x, --nofields Do not read the input MS to extract field IDs [default: False].
-j, --justrun Just run the pipeline, don't rebuild each job script if it exists [default: False].
-B, --build Build config file using input MS.
-R, --run Run pipeline with input config file.
-V, --version Display the version of this pipeline and quit.
-L, --license Display this program's license and quit.
Selecting MS and field IDs
As previously stated, to build a config file, run
processMeerKAT.py -B -C myconfig.txt -M mydata.ms
This calls CASA and adds a [data]
section to your config file, which points to your MS, and a [fields]
section, which points to the field IDs you want to process as bandpass, total flux and phase calibrators, and science target(s), as extracted from your input MS via their INTENT
labels. Only targets and extra fields may have multiple fields separated by a comma, and all extra calibrator fields are appended as “targets”, to allow for solutions to be applied to them, and quick-look images to be made of them (see v1.0 release notes).
The following is an example of what is appended to the bottom of your config file.
[data]
vis = '/idia/software/pipelines/test_data/mightee_cdfs_1350_1400mhz.ms'
[fields]
bpassfield = 'J1939-6342'
fluxfield = 'J1939-6342'
phasecalfield = 'J0240-2309'
targetfields = 'CDFS16'
extrafields = 'J0521+1638'
You can edit your config file and change the field IDs, as discussed in config files.


See Release notes
Download, Install
Please browse
GOCDB Documentation Index on the EGI wiki.
First,
check known bugs and feature requests to see if this has not
already been reported.
If not, please raise a ticket against GOCDB in
GGUS.
Before you make any request, check this is not already integrated to our development plans, see
GOCDB Development Plans.
Any suggestion, new feature or improvement request should be submitted to the
RT requirements tracker.
Suggestions will be discussed within GOCDB developers, the OTAG, or any political
body involved before inclusion into development plans.
These bodies reserve the right to decline unsuitable requests.
For all other enquiries including general questions, temporary problems reports or support requests please submit a ticket in the GGUS system


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I am Associate Professor at the Department of Computer-Science and Software Engineering, Canada Research Chair (Tier II) on Big Data Infrastructures for Neuroinformatics, head of the Big Data Infrastructures for Neuroinformatics lab, and member of the PERFORM centre and Data Science Research Centre at Concordia University in Montreal. Before, I was Researcher at the French National Center for Scientific Research.
My research goal is to build platforms for the efficient and reproducible processing of Big Data. The main applications of my work are in medical image analysis, in particular neuroimaging.
Tristan Glatard
Faculty of Engineering and Computer Science
Department of Computer Science and Software Engineering
Concordia University
1455 De Maisonneuve Blvd. W., Montreal, Quebec, Canada H3G 1M8
Office: EV 6.225
tristan.glatard@concordia.ca


web & mobile interfaces
custom designs & hand lettering
infographics & logos
Graduating from Carnegie Mellon (Go Tartans!) in Civil Engineering, I took an unconventional route and became a consultant. Currently, I produce compelling designs for technology clients at Deloitte. No matter the context, I aim to tell a good story through my creations.
I work with clients in the federal sector, helping them build web application architecture and visualize messy data. Much of what I do involves communicating technical information to a non-technical audience. On the side, I've found opportunities to further my passion for design by creating infographics, designing user interfaces, and practicing graphic facilitation.
My favorite tools that I use to create things are Illustrator and its iPad companion Adobe Draw. While I have experience with wireframing tools and templates, I prefer a blank slate for the freedom to create. My ideas often start with pen and notebook, and end in digital.
When I'm not working, I enjoy getting lost in art museums, hiking in the great outdoors, working out a sweat, assembling Ikea furniture (only when all the pieces fit), and reading poetry in a newly discovered bookstore. I'm often listening to 99% Invisible, adopting a lifestyle of Minimalism, and following my design inspirations Jennet and Mimi. Check them out!


> Define all permissions used in your app in constant.
> For better performance, query for all permissions that your app will need on load.
> The following gives example of how to use the `av-has-permission` directive to hide a section based on whether or not user has permission. There should be only one button showing below.


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Capture The Flags
In computer security, Capture the Flag (CTF), a type of wargame, is a computer security competition. CTF contests are usually designed to serve as an educational exercise to give participants experience in securing a machine, as well as conducting and reacting to the sort of attacks found in the real world (i.e., bug bounty programs in professional settings). Reverse-engineering, network sniffing, protocol analysis, system administration, programming, and cryptanalysis are all skills which have been required by prior CTF contests at DEF CON.
There are three main styles of capture the flag competitions:
A few helpful resources to learn and practice CTF are: OverTheWire, Hacker101, PicoCTF, HackThisSite, HackTheBox, Vulnhub
Although, the only way to master CTF is via practice, there are not shortcuts but a few prerequisites to get used to CTF challenges.
There are three main styles of capture the flag competitions:
- Attack/Defense : In an attack/defense style competition, each team is given a machine (or a small network) to defend on an isolated network. Teams are scored on both their success in defending their assigned machine(s) and on their success in attacking the other team's machines. Depending on the nature of the particular CTF game, teams may either be attempting to take an opponent's flag from their machine or teams may be attempting to plant their own flag on their opponent's machine. Two of the more prominent attack/defense CTF's are held every year at DEF CON, the largest hacker conference, and the NYU-CSAW (Cyber Security Awareness Week), the largest student cyber-security contest.
- Hardware challenges : Hardware challenges usually involve getting an unknown piece of hardware and having to figure out how to bypass part of the security, e.g. using debugging ports or using a Side-channel attack. and
- Jeopardy : Jeopardy style competitions usually involve multiple categories of problems, each of which contains a variety of questions of different point values and difficulties. Teams attempt to earn the most points in the competition's time frame (for example 24 hours), but do not directly attack each other. Rather than a race, this style of game play encourages taking time to approach challenges and prioritizes quantity of correct submissions over the timing.
- KotH : There is a fourth type of CTF, most commonly referred to as King of the Hill (KotH). King of the Hill is similar to Attack/Defend, but instead of everyone having their own machine (or small network) to defend, there are only preconfigured ones, which require all teams to exploit them. Once a team has successfully taken over the machine, the focus shifts to defending the machine from other teams' attacks. Score is usually determined by a score reporting service on the machine, that reports a team token. When one team is able to gain access, they will remove the other team's token and insert their own, thus making them the King of the Hill.
A few helpful resources to learn and practice CTF are: OverTheWire, Hacker101, PicoCTF, HackThisSite, HackTheBox, Vulnhub
Although, the only way to master CTF is via practice, there are not shortcuts but a few prerequisites to get used to CTF challenges.
- Firstly you need to have "try harder" approach and offensive approach.
- Secondly, a strong knowledge of networking is required, How the OSI and TCP/IP models work? Client-Server interactions, Http headers, various web technologies like HTML/CSS, JS and PHP.
- Some familiarity with the linux filesystem will be helpfull.
- Though not mandatory, having knowledge of any scripting language like Bash/Python apart from any regular programming is a bonus.
- Also, try going through writeups on a daily basis. Remember at the end its all about understanding how things work and not being a "SCRIPT KIDDIE".


pragma solidity ^0.4.24;
import "zos-lib/contracts/Initializable.sol";
import "./ConditionalEscrow.sol";
/**
* @title RefundEscrow
* @dev Escrow that holds funds for a beneficiary, deposited from multiple parties.
* The primary account may close the deposit period, and allow for either withdrawal
* by the beneficiary, or refunds to the depositors.
*/
contract RefundEscrow is Initializable, ConditionalEscrow {
enum State { Active, Refunding, Closed }
event Closed();
event RefundsEnabled();
State private _state;
address private _beneficiary;
/**
* @dev Constructor.
* @param beneficiary The beneficiary of the deposits.
*/
function initialize(address beneficiary, address sender) public initializer {
ConditionalEscrow.initialize(sender);
require(beneficiary != address(0));
_beneficiary = beneficiary;
_state = State.Active;
}
/**
* @return the current state of the escrow.
*/
function state() public view returns (State) {
return _state;
}
/**
* @return the beneficiary of the escrow.
*/
function beneficiary() public view returns (address) {
return _beneficiary;
}
/**
* @dev Stores funds that may later be refunded.
* @param refundee The address funds will be sent to if a refund occurs.
*/
function deposit(address refundee) public payable {
require(_state == State.Active);
super.deposit(refundee);
}
/**
* @dev Allows for the beneficiary to withdraw their funds, rejecting
* further deposits.
*/
function close() public onlyPrimary {
require(_state == State.Active);
_state = State.Closed;
emit Closed();
}
/**
* @dev Allows for refunds to take place, rejecting further deposits.
*/
function enableRefunds() public onlyPrimary {
require(_state == State.Active);
_state = State.Refunding;
emit RefundsEnabled();
}
/**
* @dev Withdraws the beneficiary's funds.
*/
function beneficiaryWithdraw() public {
require(_state == State.Closed);
_beneficiary.transfer(address(this).balance);
}
/**
* @dev Returns whether refundees can withdraw their deposits (be refunded).
*/
function withdrawalAllowed(address payee) public view returns (bool) {
return _state == State.Refunding;
}
uint256[50] private ______gap;
}
|


This is the Wix App settings demo.
Please add a short description of your App + CTA for the main action.
Upgrade now to get more features and enjoy everything our app has to offer!
This is the Wix App settings demo.
Please add a short description of your App + CTA for the main action.
Upgrade now to get more features and enjoy everything our app has to offer!


Slide h1
This is a h2
All the Flow You'd Expect
Python knows the usual control flow statements that other
languages speak if, for, while and range -- with some
of its own twists, of course.
More control flow tools
var function(x) {};
Normal pre text.
Normal text.
This is some code.
All the Flow You'd Expect
Python knows the usual control flow statements that other
languages speak &emdash; if
, for
,
while
and range
&emdash; with some
of its own twists, of course.
More control flow tools
/


Founded in 2011 in a small 750 square foot space on 4th ave, Seapine has grown to produce some of the most consistent beers in the Pacific Northwest. In 2015, with production needs ramping up, Seapine relocated about a mile away from its first home to a new 6,000 square foot operation on Utah Ave, continuing to churn out some amazing brews. With a great space and friendly staff, this is definitely a spot to check out in Seattle.
Not satisfied with your current choice?


Ener then name of the burger you'd like to eat.
Technologies Used: HTML, CSS, Bootstrap, JavaScript, jQuery, Node Js, Express JS, MySql, Heroku
Keep track of your day with this easy to use scheduler.
Technologies Used: HTML, CSS, JavaScript, jQuery, Moments.js, Bootsrap
Check the weather from your computer and phone.
Technologies Used: HTML, CSS, JavaScript, JSON, Ajax, jQuery, Bootstrap, Moments
Property management all-in-one app!
Technologies Used: HTML, CSS, JavaScript, JSON, Ajax, jQuery, Materialize, Node.Js, Heroku, MySQL, API


Hi, my name is Nathalyn and I'm a product designer.
I like thinking of and creating ways that improve human experiences through digital design.
Marketing Page
This project shows the front page for a marketing website meant for a specif business I'm interested in.
Search Page
This project searches through a specific database to find information that the user is trying to look up.
Travel App
This project compares travel times based on different transportation methods and tells you the best one.
Map of Favorite Spots
This project uses mapping api's to plot points for my favorite spots in the city for a do-it-yourself walking tour.
Marketing Page
This project shows pictures from a recent trip to the viewer and allows them to easily navigate through photos.
Marketing Page
Someone can enter in the numbers they want and press the big blue button and get the result.
If you'd like to chat sometime or would like to know what I'm working on, send me a message!
Phone Number
Email Address


The goal of TOA API is to provide us, and potential outside users a way to query our databases.
The Base URL for accessing anything related to our API is http://theorangealliance.org/apiv2
In order to gain access to TOA API, you need to first gain access to an API key. You can apply for an API Key Here. Once you have that key, you must set two custom headers with every GET request. You must set X-Application-Origin
to the name of your application. Secondly, you must set X-TOA-Key
to your API key.
Level 0
Level 1
Level 2
Every URL parameter following the /api/ is considered a separate component (in the project they also have their own routing files). Without the X-Application-Origin and X-TOA-Key headers, TOA API will send a 403 forbidden access response. These are used for tracking.
Here are the following main components as well as their sub-components:
(Parameters are in bold and will vary)
* All data is returned in JSON format
{{ route.route }} - {{ route.route_desc }}
{{ route.example }}


Kiwi medical cannabis company breaks crowdfunding record
by Puro New ZealandKiwi medical cannabis company breaks crowdfunding record
Medical cannabis start-up Puro has already raised just under $2.4 million on PledgeMe, the highest amount ever raised in PledgeMe’s crowdfunding history.
Tim Aldridge, Puro’s managing director, says the response so far has been incredible.
“There’s a big appetite out there to become part of our journey and make a real difference to the lives of hundreds of thousands of New Zealanders,” says Aldridge.
“Before we went to PledgeMe we worked really hard to get all our ducks in row. We were the first medical cannabis company to undertake an equity crowdfunding campaign with a licence, we secured premium Marlborough land, built an expert team, and had buyers lined up”.
“The fact that so many kiwis are backing us feels like a real vote of confidence in what we’re doing. It’s also a sign that investors recognise this is a rapidly growing industry with enormous economic potential for New Zealand.”
Puro is running two simultaneous PledgeMe campaigns. They are seeking to raise $2 million in an equity crowdfunding campaign (minimum investment of $500) and another $2 million in a wholesale campaign (minimum investment of $50,000).
With 14 days still to go, they have raised $1,793,569 in their equity crowdfunding campaign and $600,000 in their wholesale campaign.
PledgeMe spokesman Tan Huynh says Puro has surpassed the $2.06 million raised by Behemoth Brewing, who also ran two simultaneous campaigns.
“We knew craft beer was an exciting for investors but Puro have taken medicinal cannabis to the next level.”
Huynh says by raising $2.4 million Puro have also eclipsed the Australian PledgeMe record of $2.15million AUD.
Aldridge says the maximum amount Puro can raise for each campaign is $2 million.
“It’s not too late to invest but time is running out,” says Aldridge. “We’re perfectly positioned to become New Zealand’s largest grower of premium medical cannabis, and every pledge helps us to get there.”
Money raised will be spent on building a research centre and initial growing facilities, site security and expansion into overseas markets.
Visit PledgeMe to view the campaign:
• Equity crowdfunding campaign: http://pldg.me/puro
•
• Wholesale campaign: http://pldg.me/purowholesale
•
•


Intro
Highly motivated and dedicated Computer Science student, eager to team up and excel.
Being a person who thoroughly enjoys working with other team players, I am looking for a creative, challenging and growth-oriented position in the field of software development.
Education
BSc Computer Science, Academic College of Tel-Aviv, Yaffo
- Participated in MTA-Hackthon in the year of 2019
- Participating in Red Hat - Open Source Pillars course(25 out of 77 students accepted)
- Relevant coursework:
Operating Systems, Algorithms, Data Structures, Design
Patterns, Data Bases, C# and .NET Framework, C, Advanced Prog in C++, Computer Communication, Open Source Pillars
Udemy Courses
- The Complete 2020 Web Development Bootcamp - In progress [50%]
- Complete Linux Training Course to Get Your Dream IT Job 2020 - In progress [27%]
- Complete Python Developer in 2020: Zero to Mastery - [100%]


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Storyboard FerrymansProblemManuel
initial situation:
Reachable State 1
Reachable State 2
Reachable State 3
Reachable State 4
Reachable State 5
Reachable State 6
Reachable State 7
Reachable State 8
Reachable State 9
Reachable State 10
Reachable State 11
Reachable State 12
Reachable State 13
Reachable State 14
Reachable State 15
Reachable State 16
Reachable State 17
Reachable State 18
Reachable State 19
Reachable State 20
Reachable State 21
Reachable State 22
Reachable State 23
Reachable State 24
Reachable State 25
Reachable State 26
Check: Number of Reachable States expected: 27 actual 27
large reachbility graph with embedded states:
Check: found a solution true


{
"@context": "http://schema.org",
"@type": "Person",
"name": "Eric Carlisle",
"givenName": "Eric",
"familyName": "Carlisle",
"email"<EMAIL_ADDRESS>"image": "http://www.ericcarlisle.comimg/global/eric-carlisle-800x800.png",
"jobTitle": "UI Developer, UX Designer",
"url": "http://www.ericcarlisle.com",
"sameAs" : [
"https://twitter.com/eric_carlisle",
"https://www.linkedin.com/in/ericcarlisle",
"https://github.com/ecarlisle",
"https://www.slideshare.net/ericcarlisle",
"https://medium.com/@eric_carlisle"
]
}

<meta name="keywords" content="yo-yo, axle, string, finger, play, gravity, exploit" />
<meta name="description"
content="A Yo-Yo is a toy with a string. You unroll, gravity happens and...
Was that 160 characters already?"/>

The Yo-Yo

A Yo-yo is a toy consisting of an axle connected to two disks, and a string looped
around the axle. It has some similarties to a slender spool. A Yo-yo is played by
holding the free end of the string known as the handle, allowing gravity to spin
the yo-yo and unwind the string. The player then allows the yo-yo to wind itself back
to the player's hand, exploiting its spin.

"Insanity is doing the same thing over and over again and expecting different results."
“It can scarcely be denied that the supreme goal of all theory is to make the irreducible basic elements as simple and as few as possible without having to surrender the adequate representation of a single datum of experience.”
Everything should be made as simple as possible, but not simpler.

Eric Carlisle's Logo

<meta itemprop="width" content="600">
<meta itemprop="height" content="100">

Eric Carlisle's Logo

<meta property="width" content="600">
<meta property="height" content="100">

Eric Carlisle's Logo

{
"@context": "http://schema.org",
"@type": "ImageObject",
"author": "Jane Doe",
"contentUrl": "http://www.ericcarlisle.comimg/logo.png",
"width": 600,
"height": 100,
"caption": "Eric Carlisle's Logo",
}
{
"@context": "http://schema.org",
"@type": "Person",
"name": "Eric Carlisle",
"givenName": "Eric",
"familyName": "Carlisle",
"email"<EMAIL_ADDRESS>"image": "http://www.ericcarlisle.comimg/global/eric-carlisle-800x800.png",
"jobTitle": "UI Developer, UX Designer",
"url": "http://www.ericcarlisle.com",
"sameAs" : [
"https://twitter.com/eric_carlisle",
"https://www.linkedin.com/in/ericcarlisle",
"https://github.com/ecarlisle",
"https://www.slideshare.net/ericcarlisle",
"https://medium.com/@eric_carlisle"
]
}


AMISTAD (1997) A Film Review by Ted Prigge Copyright 1998 Ted Prigge
Director: Steven Spielberg Writer: David H. Frinzoni (based on the book "Black Mutiny" by William Owens) Starring: Djimon Hounsou, Matthew McConaughey, Morgan Freeman, Anthony Hopkins, Stellan Skarsgård, Nigel Hawthorne, David Paymer, Pete Postlethwaite, Jeremy Northam, Xander Berkeley, Paul Guilfoyle, Geno Silva, John Ortiz, Peter Firth, Arliss Howard, Razaaq Adoti, Abu Bakaar Fofanah, Anna Paquin, Tomás Milián, Kevin J. O'Connor, Austin Pendleton
In 1839, the slaves on the Spanish Ship "La Amistad" revolted, killed all but two captors (two because none of them knew how to steer the ship), who proceeded to sail them to America instead of Africa like they said they would. Once there, a series of long, controversial hearings were heard, debating over their origin, which would decide if the slaves were legal (which means they are technically murders) or not (which means they were merely defending themselves, and hey, that's okay). It's a true story, and I didn't even know about it.
Upon learning about this and how undertold it is, Steven Spielberg thought it was high time someone made a big budget Dreamworks movie out of it, directed by him as his next "Schindler's List" (since he directed "The Lost World" this summer, he thought he'd try to do what he did in '93, otherwise known as "The Year of Spielberg"). The result? "Amistad." With a big vast cast of everyone from Anthony Hopkins to Anna Paquin to Austin freaking Pendleton, very impressive production designs, and lots of debate over freedom to stir everyone up into a pissed-off and emotionally moved frenzy.
In fact "Amistad" is so big that it's almost disappointing. "Amistad" not only wants to be Spilberg's next "Schindler's List," but it wants to be: a) as emotionally moving as that film; b) as monetarily successful as it; and c) the big winner in the Oscar race. It's hand-crafted so that everything about it is supposed to stir someone up, and filled with scenes of horror, beauty, and various other stuff that melts Oscar's heart. But why isn't it all this?
Well, there's a couple problems with the film. First off, the film limits the debate over slavery in a couple ways: first, making the film's outcome only affect a small group of slaves - no big grand debate here; and because it's only a trial. The film plays like this: a great 15 minute introduction where we see the bloody, gory, and charging in oh so many ways revolt; then 2 hours and 15 minutes of various courtrooms and talking, broken up sporadically with scenes like one where the unofficial slave leader and on-again-off-again protagonist, Cinqué (Djimon Hounsou), stands up in court to scream repeatedly "Give us free!" while John Williams' score pounds the emotion into our brains so that we don't have any other thoughts than "Guess the film wants me to cry now."
Another problem is lack of focus in some areas. Is it a film about slavery and its affects on man, or is it just a big debate by people who only know from second hand experience? For maximum effect, the film should have been about Cinqué and his experience as the leader of the alleged slaves. It is sometimes. But the film also decides to focus on other people, placing them in the foreground for awhile. The other main character is a real estate lawyer named Baldwin, played by Matthew McConaughey, which brings out deja vu since his character in this is only slightly different from the one he played in "A Time to Kill" (though admittingly he does it so well). He takes over the story sometimes, presenting a man who gets into the job thinking as the slaves as objects to debate over, and eventually thinking of them as people. It's too weakly shown, and perhaps it could have been tossed all together and had him get into the job to make sure they become free. But the film just shows it, and almost dumps him later on in the film, then picks him back up.
This goes with many of the characters, most of whom are underwritten (I suspect there's a big-ass director's cut somewhere, where everyone gets a chance to grow - but I'm sure there's not many people who want to see it). Take for instance Morgan Freeman's character, an ex-slave who's now a civilian/abolitionist (working with another abolitionist, played by the great Stellan Skarsgård, now of "Good Will Hunting" fame): he never grows throughout and the main reason he seems to be there, other than for historical accuracy perhaps, is so that there can be a few scenes where he remembers the pain of being a slave. That's it.
In fact, many characters can be summed up in either very short sentences or mere words. Nigel Hawthorne's current President Van Buren is sheepish, since he has to try and not create a Civil War and also hold a good contract with Spain (headed by young Queen Isabella, played by Anna Paquin who has a small monologue); Jeremy Northam's judge in the second trial is nervous but trying to appear confident; David Paymer's Secretary John Forsyth is ignorant; and Pete Postlethwaite's prosecuting attorney is stubborn. And for "comic relief," look to Austin Pendleton as a Professor who's forte is African languages, who stutters just as much as he usually does, and to the same effect (I love that guy).
As for Djumon Hounsou, he's very intense as Cinqué, showing him as sometimes pissed off, sometimes saddened, sometimes bewildered. Some say he should have received an Oscar nomination for his performance, but just remember that this year had so many strong performances that you can't acknowledge them all. Regardless, Hounsou has a strong film presence, one that attracts sympathy for his character.
But the one actor who REALLY walks away with his role is Anthony Hopkins, who DID get an Oscar nomination for his performance as the crotchety, somewhat bitter, and incredibly intelligent ex-President John Quincy Adams, who has the most characterization in the film, sometimes shown in scenes that he's not even in (one of my favorites was one where a bunch of Presidential advisors discussed how the only great thing about him was that his father was a great president). Hopkins not only emerges as a scene stealer in all of his scenes, but also gives one of the best courtroom speeches in any film. Sure, it goes on for 11 minutes, but it's so well done, so underempahsized by the music (the score is one of Williams' most overbearing), and so fascinating that I almost wanted to applaud afterwards. And I almost did.
What I really didn't feel like applauding after, or even really cheering over (though I did smile) was the final verdict. Sure, the music stirs up, people get pissed off, and many others dance in happiness (McConaughey jumps up and down like he was moshing), but for some odd reason I could not really feel that emotionally moved. Maybe it was because it was the third time this verdict had been read in the film. Maybe it was because the vedict wasn't monumental. It only affected a small group of people. In the beginning of the film, Van Buren replies to a message about the trial with a quick "There are over 100,000 slaves (or something) living in the U.S; why should I care about 40 (or so)?" Sure, he sounded cruel when he said it, but at least he was being honest.
Yet during the ending when they were showing close-ups of characters in the film and summing up their lives afterwards in short paragraphs, I couldn't help but feel moved for Cinqué when the title said that he returned to his land in Africa to find it destroyed and his family gone, maybe being captured into slavery. Why did it move me? Probably because it was personal. It affected one person. The film has a way of not getting to grand and not getting to personal with its message throughout. Maybe if it had picked one of these instead of lingering in moderation, it may have been great. Maybe it could have been almost as good as "Schindler's List."
Still, "Amistad" is educational, powerful, and intriguing throughout. The film's 2 1/2 hours are leisurely but never tedious, and there are so many great moments in the film...let me ammend that a bit: so many great real moments in the film, like clips of slaves been drowned on the slave ships by being tied to a bunch of rocks and pulled to the ocean floor, or a bunch of slaves in captivity and a newborn baby being held above them...things like this that make "Amistad" worth seeing. It suceeds on many levels, but doesn't suceed on being magnificent.
MY RATING (out of 4): ***
Homepage at: http://www.geocities.com/Hollywood/Hills/8335/
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
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Related links: index of all rec.arts.movies.reviews reviews


ICJ: Russia must file counter-memorial on Ukraine's claim within one year
The court made the relevant decision on November 19.
The Hague-based International Court of Justice (ICJ), the principal judicial organ of the United Nations, has ruled the Russian Federation must file a counter-memorial in the case concerning application of the International Convention for the Suppression of the Financing of Terrorism and of the International Convention on the Elimination of All Forms of Racial Discrimination.
"By an Order dated November 8, 2019, the International Court of Justice, the principal judicial organ of the United Nations, has fixed December 8, 2020 as the time-limit for the filing of the Counter-Memorial of the Russian Federation in the case concerning Application of the International Convention for the Suppression of the Financing of Terrorism and of the International Convention on the Elimination of All Forms of Racial Discrimination (Ukraine v. Russian Federation)," the court said in a press release on November 19, 2019.
As UNIAN reported earlier, the ICJ published its November 8 Judgment on the preliminary objections raised by the Russian Federation in the case concerning Application of the International Convention for the Suppression of the Financing of Terrorism and of the International Convention on the Elimination of All Forms of Racial Discrimination (Ukraine v. Russian Federation).


{% extends 'layout.html' %} {% block main %}
3.1 Details of Outward Supplies and inward supplies liable to reverse charge
| Nature of Supplies | Total Taxable value | Integrated Tax | Central Tax | State/UT Tax |
|---|---|---|---|---|
| (a) Outward taxable supplies (other than zero rated, nil rated and exempted) | {{"%0.2f"%(data.table3_1.row_a.taxable_value)}} | {{"%0.2f"%(data.table3_1.row_a.igst)}} | {{"%0.2f"%(data.table3_1.row_a.cgst)}} | {{"%0.2f"%(data.table3_1.row_a.sgst)}} |
| (b) Outward taxable supplies (zero rated ) | {{"%0.2f"%(data.table3_1.row_b.taxable_value)}} | {{"%0.2f"%(data.table3_1.row_b.igst)}} | -- | -- |
| (c) Other outward supplies (Nil rated, exempted) | {{"%0.2f"%(data.table3_1.row_c.taxable_value)}} | -- | -- | -- |
| (d) Inward supplies (liable to reverse charge) | -- | -- | -- | -- |
| (e) Non-GST outward supplies | -- | -- | -- | -- |
3.2 Of the supplies shown in 3.1 (a), details of inter-state supplies made to unregistered persons, composition taxable person and UIN holders
| Supplies made to Unregistered Persons | ||
| Place of Supply (State/UT) | Total Taxable value | Integrated Tax |
|---|---|---|
| {{ row.pos }} | {{"%0.2f"%(row.taxable_value) }} | {{"%0.2f"%(row.igst) }} |
| Supplies made to Composition Taxable Persons | ||
| Place of Supply (State/UT) | Total Taxable value | Integrated Tax |
|---|---|---|
| {{ row.pos }} | {{"%0.2f"%(row.taxable_value) }} | {{"%0.2f"%(row.igst) }} |
| Supplies made to UIN Holders | ||
| Place of Supply (State/UT) | Total Taxable value | Integrated Tax |
|---|---|---|
| -- | -- | -- |
4. Eligible ITC
| Details | Integrated Tax | Central Tax | State/UT Tax |
|---|---|---|---|
| (A) ITC Available (whether in full or part) | |||
| (1) Import of goods | -- | -- | -- |
| (2) Import of services | -- | -- | -- |
| (3) Inward supplies liable to reverse charge (other than 1, 2 above) | -- | -- | -- |
| (4) Inward supplies from ISD | -- | -- | -- |
| (5) All other ITC | {{"%0.2f"%(data.table4.igst)}} | {{"%0.2f"%(data.table4.cgst)}} | {{"%0.2f"%(data.table4.sgst)}} |
5. Values of exempt, nil-rated and non-GST inward supplies
| Nature of Supplies | Inter-State Supplies | Intra-State Supplies |
|---|---|---|
| From a supplier under composition scheme, Exempt and Nil rated supply | {{"%0.2f"%(data.table5.inter_state_value)}} | {{"%0.2f"%(data.table5.intra_state_value)}} |
| Non GST supply | -- | -- |
6. Payment of tax
| Description | Tax payable | Integrated Tax | Central Tax | State/UT Tax | CESS | Tax/Cess Payable in cash |
|---|---|---|---|---|---|---|
| Integrated Tax | {{"%0.2f"%(data.table3_1.row_a.igst + data.table3_1.row_b.igst)}} | |||||
| Central Tax | {{"%0.2f"%(data.table3_1.row_a.cgst)}} | |||||
| State/UT Tax | {{"%0.2f"%(data.table3_1.row_a.sgst)}} |


Seattle, where I live, is a coffee obsessed city. No matter you live here in Seattle or elsewhere, if, when you hear the word “Java”, a computer programming language comes to mind before a cup of hot drink, count yourself in as a denizen of Geek-speaking land.
Geek Language Quiz - 1
In this “Geek Language Quiz” series, we’ll list some commonly asked questions about technical terms, especially for recruiting purposes, and their answers. Test and score yourself on your understanding of the Geek language. Have fun!
Job Description Review by Developers - iOS Mobile App Developer
iOS Developer (Seattle)
In this series, I invite a qualified engineer/developer with matching or related technical background to review a real job description. In these reviews, you’ll learn the unfiltered feedback and thoughts from the technical people who are the target readers of these job descriptions. Please note: each review reflects only the opinion of the specific reviewer.
Let’s Fix Technical Recruiting’s Image Problem
What‘s the first organic search result in Google when you type in “technical recruiting?”
For me, the answer was a blog titled, “Why are technical recruiters so clueless?”, by none other than the creator of Ruby on Rails web development framework - David Heinemeier Hansson of 37Signals, known in the software community as DHH.
What Is an SDET ?
If you are a software developer looking for a contract or full-time job with companies like Microsoft, Amazon, etc., you’ve probably been approached by enough recruiters that asked you if you’d be interested in working as an SDET. Your first reaction might have been - Testing? No way.
What Makes a Strong Recruiting Team
In order to attract top talent to your organization it is imperative that you have a top-notch recruiting team in place. I often wonder if organizations realize just how important recruiting is to the success of an organization. If an organization does not have the very best recruiting team in place, it can be at a severe competitive disadvantage. The recruiting function is the key driving force in ensuring the right hires made and less than desirable hires are avoided.
Job Description Review by Developers - QA Engineer
QA Engineer - Desktop Virtualization (Seattle)
In this series, I invite someone to review a real job description with matching or related technical background. In these reviews, you’ll learn the unfiltered feedback and thoughts from the technical people who are the target readers of these job descriptions. Please note: each review reflects only the opinion of the specific reviewer.
Developer Mind Reading 101
What Developers Look for in a Job
If you’re a technical recruiter, knowing what’s on your candidate’s mind helps tremendously at every step of your interaction with them. The better you know what the most important considerations are on their mind, the better chance you have to successfully recruit them. Here is a list of super power you’ll get when you can “read mind” -


| gamm {mgcv} | R Documentation |
Fits the specified generalized additive mixed model (GAMM) to
data, by a call to lme
in the normal errors identity link case, or by
a call to gammPQL
(a modification of glmmPQL
from the MASS
library) otherwise.
In the latter case estimates are only approximately MLEs. The routine is typically
slower than gam
, and not quite as numerically robust.
To use lme4
in place of nlme
as the underlying fitting engine,
see gamm4
from package gamm4
.
Smooths are specified as in a call to gam
as part of the fixed
effects model formula, but the wiggly components of the smooth are treated as
random effects. The random effects structures and correlation structures
availabale for lme
are used to specify other random effects and
correlations.
It is assumed that the random effects and correlation structures are employed primarily to model residual correlation in the data and that the prime interest is in inference about the terms in the fixed effects model formula including the smooths. For this reason the routine calculates a posterior covariance matrix for the coefficients of all the terms in the fixed effects formula, including the smooths.
To use this function effectively it helps to be quite familiar with the use of
gam
and lme
.
gamm(formula,random=NULL,correlation=NULL,family=gaussian(), data=list(),weights=NULL,subset=NULL,na.action,knots=NULL, control=list(niterEM=0,optimMethod="L-BFGS-B"), niterPQL=20,verbosePQL=TRUE,method="ML",drop.unused.levels=TRUE,...)
formula |
A GAM formula (see also |
random |
The (optional) random effects structure as specified in a call to
|
correlation |
An optional |
family |
A |
data |
A data frame or list containing the model response variable and
covariates required by the formula. By default the variables are taken
from |
weights |
In the generalized case, weights with the same meaning as
|
subset |
an optional vector specifying a subset of observations to be used in the fitting process. |
na.action |
a function which indicates what should happen when the data contain ‘NA’s. The default is set by the ‘na.action’ setting of ‘options’, and is ‘na.fail’ if that is unset. The “factory-fresh” default is ‘na.omit’. |
knots |
this is an optional list containing user specified knot values to be used for basis construction. Different terms can use different numbers of knots, unless they share a covariate. |
control |
A list of fit control parameters for |
niterPQL |
Maximum number of PQL iterations (if any). |
verbosePQL |
Should PQL report its progress as it goes along? |
method |
Which of |
drop.unused.levels |
by default unused levels are dropped from factors before fitting. For some smooths involving factor variables you might want to turn this off. Only do so if you know what you are doing. |
... |
further arguments for passing on e.g. to |
The Bayesian model of spline smoothing introduced by Wahba (1983) and Silverman (1985) opens
up the possibility of estimating the degree of smoothness of terms in a generalized additive model
as variances of the wiggly components of the smooth terms treated as random effects. Several authors
have recognised this (see Wang 1998; Ruppert, Wand and Carroll, 2003) and in the normal errors,
identity link case estimation can
be performed using general linear mixed effects modelling software such as lme
. In the generalized case only
approximate inference is so far available, for example using the Penalized Quasi-Likelihood approach of Breslow
and Clayton (1993) as implemented in glmmPQL
by Venables and Ripley (2002).
One advantage of this approach is that it allows correlated errors to be dealt with via random effects
or the correlation structures available in the nlme
library (using correlation structures beyond the
strictly additive case amounts to using a GEE approach to fitting).
Some details of how GAMs are represented as mixed models and estimated using
lme
or gammPQL
in gamm
can be found in Wood (2004 ,2006a,b). In addition gamm
obtains a posterior covariance matrix for the parameters of all the fixed effects and the smooth terms. The approach is similar to that described in Lin & Zhang (1999) - the covariance matrix of the data (or pseudodata in the generalized case) implied by the weights, correlation and random effects structure is obtained, based on the estimates of the parameters of these terms and this is used to obtain the posterior covariance matrix of the fixed and smooth effects.
The bases used to represent smooth terms are the same as those used in gam
, although adaptive
smoothing bases are not available. Prediction from the returned gam
object is straightforward using predict.gam
, but this will set the random effects to zero. If you want to predict with random effects set to their predicted values then you can adapt the prediction code given in the examples below.
In the event of lme
convergence failures, consider
modifying options(mgcv.vc.logrange)
: reducing it helps to remove
indefiniteness in the likelihood, if that is the problem, but too large a
reduction can force over or undersmoothing. See notExp2
for more
information on this option. Failing that, you can try increasing the
niterEM
option in control
: this will perturb the starting values
used in fitting, but usually to values with lower likelihood! Note that this
version of gamm
works best with R 2.2.0 or above and nlme
, 3.1-62 and above,
since these use an improved optimizer.
Returns a list with two items:
gam |
an object of class |
lme |
the fitted model object returned by |
gamm
was a somewhat different argument list to gam
,
gam
arguments such as gamma
supplied to gamm
will
just be ignored.
gamm
performs poorly with binary data, since it uses PQL. It is
better to use gam
with s(...,bs="re")
terms, or gamm4
.
gamm
assumes that you know what you are doing! For example, unlike
glmmPQL
from MASS
it will return the complete lme
object
from the working model at convergence of the PQL iteration, including the 'log
likelihood', even though this is not the likelihood of the fitted GAMM.
The routine will be very slow and memory intensive if correlation structures are used for the very large groups of data. e.g. attempting to run the spatial example in the examples section with many 1000's of data is definitely not recommended: often the correlations should only apply within clusters that can be defined by a grouping factor, and provided these clusters do not get too huge then fitting is usually possible.
Models must contain at least one random effect: either a smooth with non-zero
smoothing parameter, or a random effect specified in argument random
.
gamm
is not as numerically stable as gam
: an lme
call
will occasionally fail. See details section for suggestions, or try the
‘gamm4’ package.
gamm
is usually much slower than gam
, and on some platforms you may need to
increase the memory available to R in order to use it with large data sets
(see memory.limit
).
Note that the weights returned in the fitted GAM object are dummy, and not those used by the PQL iteration: this makes partial residual plots look odd.
Note that the gam
object part of the returned object is not complete in
the sense of having all the elements defined in gamObject
and
does not inherit from glm
: hence e.g. multi-model anova
calls will not work.
It is also based on the working model when PQL is used.
The parameterization used for the smoothing parameters in gamm
, bounds
them above and below by an effective infinity and effective zero. See
notExp2
for details of how to change this.
Linked smoothing parameters and adaptive smoothing are not supported.
Simon N. Wood<EMAIL_ADDRESS>Breslow, N. E. and Clayton, D. G. (1993) Approximate inference in generalized linear mixed models. Journal of the American Statistical Association 88, 9-25.
Lin, X and Zhang, D. (1999) Inference in generalized additive mixed models by using smoothing splines. JRSSB. 55(2):381-400
Pinheiro J.C. and Bates, D.M. (2000) Mixed effects Models in S and S-PLUS. Springer
Ruppert, D., Wand, M.P. and Carroll, R.J. (2003) Semiparametric Regression. Cambridge
Silverman, B.W. (1985) Some aspects of the spline smoothing approach to nonparametric regression. JRSSB 47:1-52
Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.
Wahba, G. (1983) Bayesian confidence intervals for the cross validated smoothing spline. JRSSB 45:133-150
Wood, S.N. (2004) Stable and efficient multiple smoothing parameter estimation for generalized additive models. Journal of the American Statistical Association. 99:673-686
Wood, S.N. (2003) Thin plate regression splines. J.R.Statist.Soc.B 65(1):95-114
Wood, S.N. (2006a) Low rank scale invariant tensor product smooths for generalized additive mixed models. Biometrics 62(4):1025-1036
Wood S.N. (2006b) Generalized Additive Models: An Introduction with R. Chapman and Hall/CRC Press.
Wang, Y. (1998) Mixed effects smoothing spline analysis of variance. J.R. Statist. Soc. B 60, 159-174
http://www.maths.bris.ac.uk/~sw15190/
magic
for an alternative for correlated data,
te
, s
,
predict.gam
,
plot.gam
, summary.gam
, negbin
,
vis.gam
,pdTens
, gamm4
(
https://cran.r-project.org/package=gamm4)
library(mgcv) ## simple examples using gamm as alternative to gam set.seed(0) dat <- gamSim(1,n=200,scale=2) b <- gamm(y~s(x0)+s(x1)+s(x2)+s(x3),data=dat) plot(b$gam,pages=1) summary(b$lme) # details of underlying lme fit summary(b$gam) # gam style summary of fitted model anova(b$gam) gam.check(b$gam) # simple checking plots b <- gamm(y~te(x0,x1)+s(x2)+s(x3),data=dat) op <- par(mfrow=c(2,2)) plot(b$gam) par(op) rm(dat) ## Add a factor to the linear predictor, to be modelled as random dat <- gamSim(6,n=200,scale=.2,dist="poisson") b2 <- gamm(y~s(x0)+s(x1)+s(x2),family=poisson, data=dat,random=list(fac=~1)) plot(b2$gam,pages=1) fac <- dat$fac rm(dat) vis.gam(b2$gam) ## In the generalized case the 'gam' object is based on the working ## model used in the PQL fitting. Residuals for this are not ## that useful on their own as the following illustrates... gam.check(b2$gam) ## But more useful residuals are easy to produce on a model ## by model basis. For example... fv <- exp(fitted(b2$lme)) ## predicted values (including re) rsd <- (b2$gam$y - fv)/sqrt(fv) ## Pearson residuals (Poisson case) op <- par(mfrow=c(1,2)) qqnorm(rsd);plot(fv^.5,rsd) par(op) ## now an example with autocorrelated errors.... n <- 200;sig <- 2 x <- 0:(n-1)/(n-1) f <- 0.2*x^11*(10*(1-x))^6+10*(10*x)^3*(1-x)^10 e <- rnorm(n,0,sig) for (i in 2:n) e[i] <- 0.6*e[i-1] + e[i] y <- f + e op <- par(mfrow=c(2,2)) ## Fit model with AR1 residuals b <- gamm(y~s(x,k=20),correlation=corAR1()) plot(b$gam);lines(x,f-mean(f),col=2) ## Raw residuals still show correlation, of course... acf(residuals(b$gam),main="raw residual ACF") ## But standardized are now fine... acf(residuals(b$lme,type="normalized"),main="standardized residual ACF") ## compare with model without AR component... b <- gam(y~s(x,k=20)) plot(b);lines(x,f-mean(f),col=2) ## more complicated autocorrelation example - AR errors ## only within groups defined by `fac' e <- rnorm(n,0,sig) for (i in 2:n) e[i] <- 0.6*e[i-1]*(fac[i-1]==fac[i]) + e[i] y <- f + e b <- gamm(y~s(x,k=20),correlation=corAR1(form=~1|fac)) plot(b$gam);lines(x,f-mean(f),col=2) par(op) ## more complex situation with nested random effects and within ## group correlation set.seed(0) n.g <- 10 n<-n.g*10*4 ## simulate smooth part... dat <- gamSim(1,n=n,scale=2) f <- dat$f ## simulate nested random effects.... fa <- as.factor(rep(1:10,rep(4*n.g,10))) ra <- rep(rnorm(10),rep(4*n.g,10)) fb <- as.factor(rep(rep(1:4,rep(n.g,4)),10)) rb <- rep(rnorm(4),rep(n.g,4)) for (i in 1:9) rb <- c(rb,rep(rnorm(4),rep(n.g,4))) ## simulate auto-correlated errors within groups e<-array(0,0) for (i in 1:40) { eg <- rnorm(n.g, 0, sig) for (j in 2:n.g) eg[j] <- eg[j-1]*0.6+ eg[j] e<-c(e,eg) } dat$y <- f + ra + rb + e dat$fa <- fa;dat$fb <- fb ## fit model .... b <- gamm(y~s(x0,bs="cr")+s(x1,bs="cr")+s(x2,bs="cr")+ s(x3,bs="cr"),data=dat,random=list(fa=~1,fb=~1), correlation=corAR1()) plot(b$gam,pages=1) summary(b$gam) vis.gam(b$gam) ## Prediction from gam object, optionally adding ## in random effects. ## Extract random effects and make names more convenient... refa <- ranef(b$lme,level=5) rownames(refa) <- substr(rownames(refa),start=9,stop=20) refb <- ranef(b$lme,level=6) rownames(refb) <- substr(rownames(refb),start=9,stop=20) ## make a prediction, with random effects zero... p0 <- predict(b$gam,data.frame(x0=.3,x1=.6,x2=.98,x3=.77)) ## add in effect for fa = "2" and fb="2/4"... p <- p0 + refa["2",1] + refb["2/4",1] ## and a "spatial" example... library(nlme);set.seed(1);n <- 100 dat <- gamSim(2,n=n,scale=0) ## standard example attach(dat) old.par<-par(mfrow=c(2,2)) contour(truth$x,truth$z,truth$f) ## true function f <- data$f ## true expected response ## Now simulate correlated errors... cstr <- corGaus(.1,form = ~x+z) cstr <- Initialize(cstr,data.frame(x=data$x,z=data$z)) V <- corMatrix(cstr) ## correlation matrix for data Cv <- chol(V) e <- t(Cv) %*% rnorm(n)*0.05 # correlated errors ## next add correlated simulated errors to expected values data$y <- f + e ## ... to produce response b<- gamm(y~s(x,z,k=50),correlation=corGaus(.1,form=~x+z), data=data) plot(b$gam) # gamm fit accounting for correlation # overfits when correlation ignored..... b1 <- gamm(y~s(x,z,k=50),data=data);plot(b1$gam) b2 <- gam(y~s(x,z,k=50),data=data);plot(b2) par(old.par)


| name-repair-superseded {tibble} | R Documentation |
tidy_names()
, set_tidy_names()
, and repair_names()
were early efforts
to facilitate post hoc name repair in tibble, given that tibble()
and
as_tibble()
did not do this.
From tibble v2.0.0, the .name_repair
argument gives direct access to three
specific levels of name repair: minimal
, unique
, and universal
.
See vctrs::vec_as_names()
for the implementation of the underlying logic.
tidy_names(name, syntactic = FALSE, quiet = FALSE) set_tidy_names(x, syntactic = FALSE, quiet = FALSE) repair_names(x, prefix = "V", sep = "")
name |
A |
syntactic |
Should names be made syntactically valid? If |
quiet |
Whether to suppress messages about name repair. |
x |
A vector. |
prefix |
A string, the prefix to use for new column names. |
sep |
A string inserted between the column name and de-duplicating number. |
x
with repaired names or a repaired version of name
.
These functions are superseded. The repair_names()
logic
will also remain available in vctrs::vec_as_names_legacy()
.
tibble(..., `.name_repair = "unique"`) ## is preferred to df <- tibble(...) set_tidy_names(df, syntactic = FALSE) tibble(..., `.name_repair = "universal"`) ## is preferred to df <- tibble(...) set_tidy_names(df, syntactic = TRUE)


The last episode of Russi Taylor voicing The Simpson’s Martin Prince is ‘epic'
Russi Taylor, the voice actor behind The Simpson’s Martin Prince passed away earlier this year, and the final episode of her voicing the character is set to air on Sunday.
The Simpsons’ executive producer Matt Selman confirmed that the final episode will air on Sunday, telling fans: ‘This Sunday’s episode of @TheSimpsons features the last vocal appearance of the wonderful, hilarious Russi Taylor as Martin Prince.
‘It turned out to be an epic farewell, one Russi would have loved.’
Despite it being the last episode voiced by Russi, the character of Martin will live on, and will be voiced by Grey DeLisle-Griffin, who is best known for voicing Daphne in Scooby Doo and Vicky on Nickelodeon’s The Fairly OddParents.
As well as her role as Martin Prince, Russi also was the voice of Minnie Mouse in several Mickey Mouse movies, and Huey, Dewey, Louie and Webby in DuckTales.
Advertisement Advertisement
She passed away from colon cancer in July 2019 at the age of 75, and had voice acted on 193 episodes of The Simpsons between 1989 and 2019.
While there’s no word on what her final appearance as Martin Prince will entail, fans of The Simpsons will be able to find out on Sunday.
The episode, entitled Thanksgiving of Horror in homage to the Treehouse of Horror series, will also be the longest single Simpsons episode ever at 25 minutes.
According to Entertainment Weekly: ‘The Simpsons face various Thanksgiving nightmares, including the first Thanksgiving, an A.I. mishap and a dangerous space mission complicated by a sentient cranberry sauce. ‘
Matt Selman added: ‘Russi’s Martin goes out in memorable style.’
Martin Prince has been a staple of Springfield’s cast of characters, being a bit of an overachiever and Nelson Muntz’s favourite target to bully.
As well as Martin, Russi was also the voice behind several other characters including twins Sherri and Terri, Uter Zorker and Dr. Hibbert’s daughter.
Got a showbiz story?
If you've got a story, video or pictures get in touch with the Metro.co.uk Entertainment team by emailing us<EMAIL_ADDRESS>calling 020 3615 2145 or by visiting our Submit Stuff page - we'd love to hear from you.


The cultivation of the ToorDhall (Pigeon Pea) goes back at least 3,500 years. The centre of origin is the eastern part of peninsular India. Pigeon peas contain high levels of protein and the important amino acids methionine, lysine, and tryptophan. In contrast to the mature seeds, the immature seeds are generally lower in all nutritional values, however they contain a significant amount of vitamin C (39 mg per 100 g serving) and have a slightly higher fat content. Research has shown that the protein content of the immature seeds is of a higher quality./
Our Company possess rich expertise in offering our Toor Dhal which are highly appreciated by our clients became for their special and unique quality, hygiene, taste, freshness and reasonable prices. Toor Dhal are husked and spilt in half. Pale yellow in color. It is slightly sweet, having earthly subtle nuttle flavor and soft texture. Toor Dhal that we offer are clean and comprise essential nutrients and vitamins. It is good source of protein, dietary fiber, amino acids, iron, calcium, carbohydrates and potassium. It’s calorific value is 237 Kcal / 100 gram dry weight. Toor dal is also sometimes referred to as lentils or split pigeon peas. This traditional Indian dish is often served with rich spices over rice, and is a staple in many Indian restaurants and households. Toor dal is a member of the legume family, and this meal is not only delicious, it also has a number of health benefits.
Toor dal contains folic acid, an important vitamin for all women, especially those planning to become pregnant. Folic acid is essential for fetal development and can help to prevent neural tube birth defects such as spina bifida. Getting adequate amounts of folic acid in your diet can help to reduce specific brain and spinal cord birth defects by more than 70 percent, according to the New York State Department of Health.
The United States Department of Agriculture notes that beans and peas such as toor dal can be counted in both the protein and vegetable subgroups of the government's healthy eating plan. This is because legumes such as toor dal are an excellent source of nutrients and plant protein, and they also contain dietary fiber. In essence, legumes are nutritionally similar to poultry, meat and fish, though they represent a low-fat and low-cholesterol alternative. Legumes such as toor dal provide essential nutrients, fiber and protein for vegetarians as well as those who wish to merely limit their meat consumption.
Toor dal is also an excellent source of carbohydrates, which your body needs for energy. When you eat food containing carbohydrates, your body breaks them down into glucose, or blood sugar. Blood sugar is then used to provide energy to your brain, body and nervous system. Unlike simple carbohydrates, which contain processed and refined sugars with little nutrition, legumes such as toor dal contain complex carbohydrates. Complex carbohydrates are recommended over simple carbohydrates because of their increased nutritional value.


In this post I am giving a quick overview of how to create editable plots in PowerPoint from R. These plots are comprised of simple vector-based shapes and thus allow you to change labels, colours, or text position in seconds. Your project managers will love it!
R allows us to create great visualisations, but in most data science settings these need to be presented to key stakeholders and decision makers in presentations or “slideuments”. Having to make small changes to previously compiled slots can be time consuming and frustrating. A solution to this common problem is to keep your plots and graphs editable as a group of vector shapes in PowerPoint. This way project managers or data scientists themselves can make small changes without having to re-execute a single line of code.
We will use a tidyverse approach for creating the plot. Furthermore, the
officer
package enables us to smoothly interact with PowerPoint, and the rvg
package is required to save our plots as editable vector graphs.
R
library(tidyverse)
library(officer)
library(rvg)
For demonstration purposes, let’s create a plot using the diamonds dataset.
NB: I am saving the ggplot object to a variable name, but also displaying the
plot when executing the lines by appending the ; ggp
at the end.
R
# Using diamonds dataset which is shipped with R
ggp <- diamonds %>%
# Let's simplify things by only considering natural number carats
mutate(carat = floor(carat)) %>%
group_by(carat, cut, clarity, color) %>%
summarise(price = mean(price)) %>%
# Create a plot of price by carat, colour, cut, and clarity
ggplot(aes(x = carat, y = price, fill = color)) +
geom_bar(stat = 'identity') +
facet_grid(cut ~ clarity) +
# Simplify the plot layout a little
theme_bw() +
guides(fill = FALSE) +
theme(panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank()); ggp
Now we can use officer
to create a new PowerPoint document and
rvg::ph_with_vg
to drop our ggplot object in there.
```R # Create a new powerpoint document doc <- read_pptx() doc <- add_slide(doc, ‘Title and Content’, ‘Office Theme’)
doc <- ph_with_vg(doc, ggobj = ggp, type = ‘body’)
print(doc, target = ‘plot.pptx’) ```
Now open the document in PowerPoint. Right-click and ungroup the plot. Voila! You should be able to select individual elements, for example the data bars in the plot, change their colour, move them around, change the text in labels, and much more. Have a look at the plot below. A cookie for you if you can find all ten edits that I made in the example.
As always, hope this is helpful. And FYI, I am still looking for a way to
achieve the same result using Python
. If you know one, collect some bounty
here


@* * Copyright 2017 HM Revenue & Customs * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *@ @import uk.gov.hmrc.play.views.html.helpers.form @import helpers._ @import controllers.propertyLinking._ @(model: UploadEvidenceVM)(implicit request: Request[_], messages: Messages) @main_template(title = Messages("uploadEvidence.show.title"), bottomBackLink = true, topBackLink = true) { @form(model.call, 'enctype -> "multipart/form-data") {
@Messages("uploadEvidence.p.1")
@Messages("uploadEvidence.evidenceTypes")
@Messages("uploadFile.allowedTypes.mustbe")


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|
Halo PC End User Editing Kit Development Team:
Tutorials and Documentation:
-
Matthew Armstrong
-
David Mertz
-
Marc Tardif
Programming:
-
Shawn Green
-
Steve Jones
-
Charles Kostick
-
Sean Reardon
-
Jimmy Sieben
-
Scott Velasquez
Original Halo Tools
Programming:
- Mat Noguchi
and the Bungie Halo Programming team
Additional
Contributions:
The halo.bungie.net web
development team (background images and web graphics)
Special Thanks:
- Roger Wolfson - Test
Lead
- Microsoft Corporation
and Microsoft Game Studios
- Bungie Studios
- Gearbox Software Team
- All of the Halo fans
|


Welcome To Maruti Car Store!
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ansible.executor.process package¶
Submodules¶
ansible.executor.process.result module¶
ansible.executor.process.worker module¶
-
class
ansible.executor.process.worker.
WorkerProcess
(rslt_q, task_vars, host, task, play_context, loader, variable_manager, shared_loader_obj)[source]¶ Bases:
multiprocessing.process.Process
The worker thread class, which uses TaskExecutor to run tasks read from a job queue and pushes results into a results queue for reading later.


Bioengineering 148/248 is a bioengineering elective which consists of roughly half undergraduate and half graduate students. The course focuses on synthetic biology and its current applications in industry and consists of industry speakers, lectures, and design challenges. There are about seven lectures given by the professor which cover the topics listed below. There are also approximately seven or eight industry speakers from local SynBio companies. Each student has to write a reflection following the talk. There were four design challenges and one final design challenge. Design challenges are group projects in which groups need to provide solutions to a proposed question facing the synthetic biology industry/world today. After each project, a few randomly selected groups present their solutions to the class. Each student writes a post-presentations report analyzing their own solution as well as the solutions of the other groups.
CHEM 3A (required); BIOE 103 or equivalent (listed as required).
BIOE 11 was sufficient without BIOE 103 or other Bio or BioE experience.
3 hours of lecture per week. Approximately 30 minutes to an hour for each report (~1 per week), approximately 4-5 hours for each project (~1 every three weeks).
The course is only offered in the Fall. The undergraduates in the course are predominantly juniors and seniors, as it is an upper-division elective. The course is not too time-intensive, so it can be taken with any course load.
The course is an upper division elective. It is unique and does not directly serve as a prerequisite for a class, but it is a useful class to gain insight into synthetic biology in industry and synthetic biology topics.
The course will not be offered in Fall 2019, since the professor will be on sabbatical.
The name of the course may change as well, since the course no longer focuses on bioenergy. The content of the course is constantly evolving and depends on the current topics of the bioengineering industry. The professor is also receptive to feedback, so content and requirements are adjusted as well year to year.
Written by: Samantha Marinkovich
Last edited: Fall 2018


TRP
A broad group of eukaryotic six-transmembrane cation channels that are classified by sequence homology because their functional involvement with SENSATION is varied. They have only weak voltage sensitivity and ion selectivity. They are named after a DROSOPHILA mutant that displayed transient receptor potentials in response to light. A 25-amino-acid motif containing a TRP box (EWKFAR) just C-terminal to S6 is found in TRPC, TRPV and TRPM subgroups. ANKYRIN REPEATS are found in TRPC, TRPV & TRPN subgroups. Some are functionally associated with TYROSINE KINASE or TYPE C PHOSPHOLIPASES.
(mesh:D050051)
Cross-references
Synonyms
None available.
Incoming Relations
Outgoing Relations


Speaker- SANGAM BIRADAR and Hire Me!
Golang Series by Sangam Biradar
Tested Infrastructure
| Platform | Number of Instance | Reading Time |
|---|---|---|
| Play with GO | 1 | 5 min |
Open [PWG] Platform on your browser
Chapter 1.Programming in Go
Lets Start With First Hello world - Golang
Getting Start with Golang
package main
import "fmt"
func main() {
fmt.Println("Hello world!")
}
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func main() { … }
Program execution begins by initializing the main package and then invoking the function main. When that function invocation returns, the program exits. It does not wait for other (non-main) goroutines to complete.
Go: Meaning of the ‘fmt’ package acronym fmt is short for format. Package fmt implements formatted I/O with functions analogous to C’s printf and scanf. The format ‘verbs’ are derived from C’s but are simpler.
1. Numeral Systems (Decimal) - Programming in GO
package main
import "fmt"
func main() {
fmt.Println(42)
}
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2. Numeral Systems (binary) - Programming in GO
package main
import "fmt"
func main() {
fmt.printf("%d - %b \n", 42, 42)
}
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%b base 2
%c the character represented by the corresponding Unicode code point
%d base 10
%o base 8
%q a single-quoted character literal safely escaped with Go syntax.
%x base 16, with lower-case letters for a-f
%X base 16, with upper-case letters for A-F
%U Unicode format: U+1234; same as "U+%04X"
package main
import "fmt"
func main() {
// fmt.Printf("%d - %b - %x \n", 42, 42, 42)
// fmt.Printf("%d - %b - %#x \n", 42, 42, 42)
// fmt.Printf("%d - %b - %#X \n", 42, 42, 42)
fmt.Printf("%d \t %b \t %#X \n", 42, 42, 42)
}
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%x base 16, with lower-case letters for a-f
%x base 16, with upper-case letters for a-f
in above program the annotation verb %x formats a number in hexadecimal Ex:- which represent 0X2A ( base 16 format)
package main
import "fmt"
func main() {
for i := 1; i < 16; i++ {
fmt.Printf("%d \t %b \t %x \n", i, i, i)
}
}
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if your new to loop in go so lets see some detailing of for loop in go:
go has only one looping construct, the for loop.
the init statement: executed before the first iteration
the condition expression: evaluated before every iteration
the post statement: executed at the end of every iteration. the init statement will often be a short variable declaration, and the variables declared there are visible only in the scope of the for statement.
the loop will stop iterating once the boolean condition evaluates to false.
note: unlike other languages like c, java, or javascript there are no parentheses surrounding the three components of the for statement and the braces { } are always required.
as we seen decimal,binary and hexadecimal programs in go , in this above program using loop you can print n number that convert number to any numeral system ( refer integer cheatsheet fmt) to convert number into different fmt format.quick using simple go program.
5. numeral systems(UTF-8)- Programming in GO
UTF 8 = Unicode Transformation Format – 8-bit UTF8 is a character encoding where is assigns 1,112,064 characters a binary number that is from 1 byte (8 bits) to 4 bytes (32 bits) long.
Why is it necessary? Well, our computers use binary to store data. So inside a computer information is a sequence of 0’s and 1’s. When you are writing a text file on your computer the computer needs to store that in binary code (in 0’s and 1’s). But what would the character 'a' represent in binary? Short answer is whatever you want it to be. That is why we have UTF8 (and ASCII before it), it provides a standard that says the letter 'a' will take the value of 01100010 in binary. It allows us to say this file is stored with the UTF8 encoding,so the binary code must be interpreted with that in mind.
package main
import "fmt"
func main() {
for i := 60; i < 122; i++ {
fmt.Printf("%d \t %b \t %x \t %q \n", i, i, i, i)
}
}
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as we seen decimal,binary and hexadecimal programs in Go , in this above UTF-8 program annotaition %q is used for UTF-8 character in coding. Note:-UTF-8 has been the dominant character encoding for the World Wide Web since 2009, and as of March 2018 accounts for 91.0% of all Web pages. The Internet Mail Consortium(IMC) recommended that all e-mail programs be able to display and create mail using UTF-8, and the W3C recommends UTF-8 as the default encoding in XML and HTML
Chapter 2.Programming in Go - starting date 2 feb 19
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| B_02_barchart.table {lattice} | R Documentation |
Contingency tables are often displayed using bar charts and dot plots. These methods operate directly on tables, bypassing the need to convert them to data frames for use with the formula interface. Matrices and arrays are also supported, by coercing them to tables.
## S3 method for class 'table' barchart(x, data, groups = TRUE, origin = 0, stack = TRUE, ..., horizontal = TRUE) ## S3 method for class 'array' barchart(x, data, ...) ## S3 method for class 'matrix' barchart(x, data, ...) ## S3 method for class 'table' dotplot(x, data, groups = TRUE, ..., horizontal = TRUE) ## S3 method for class 'array' dotplot(x, data, ...) ## S3 method for class 'matrix' dotplot(x, data, ...)
x |
A |
data |
Should not be specified. If specified, will be ignored with a warning. |
groups |
A logical flag, indicating whether to use the last dimension as a grouping variable in the display. |
origin, stack |
Arguments to |
horizontal |
Logical flag, indicating whether the plot should be horizontal (with the categorical variable on the y-axis) or vertical. |
... |
Other arguments, passed to the underlying |
The first dimension is used as the variable on the categorical axis.
The last dimension is optionally used as a grouping variable (to
produce stacked barcharts by default). All other dimensions are used
as conditioning variables. The order of these variables cannot be
altered (except by permuting the original argument beforehand using
t
or aperm
). For more flexibility, use
the formula method after converting the table to a data frame using
the relevant as.data.frame
method.
An object of class "trellis"
. The
update
method can be used to
update components of the object and the
print
method (usually called by
default) will plot it on an appropriate plotting device.
Deepayan Sarkar<EMAIL_ADDRESS>barchart
, t
, aperm
,
table
, panel.barchart
,
Lattice
barchart(Titanic, scales = list(x = "free"), auto.key = list(title = "Survived"))


SDCC allows the use of in-line assembler with a few restriction as regards labels. All labels defined within inline assembler code HAS TO BE of the form nnnnn$ where nnnn is a number less than 100 (which implies a limit of utmost 100 inline assembler labels per function). It is strongly recommended that each assembly instruction (including labels) be placed in a separate line ( as the example shows). When the --peep-asm command line option is used, the inline assembler code will be passed through the peephole optimizer, this might cause some unexpected changes in the inline assembler code, please go throught the peephole optimizer rules defined in file 'SDCCpeeph.def' carefully before using this option.
eg_asm mov b,#10 00001$: djnz b,00001$ _endasm ;
The inline assembler code can contain any valid code understood by the assembler (this includes any assembler directives and comment lines ) . The compiler does not do any validation of the code within the _asm ... _endasm; keyword pair.
Inline assembler code cannot reference any C-Labels however it can reference labels defined by the inline assembler.
egfoo() { ... /* some c code */ _asm ; some assembler code ljmp $0003 _endasm ; ... /* some more c code */ clabel: /* inline assembler cannot reference this label */ _asm $0003: ;label (can be reference by inline assembler only) _endasm ; ... }
In other words inline assembly code can access labels defined in inline assembly. The same goes the other way, ie. labels defines in inline assembly CANNOT be accessed by C statements.


This is my old website and portfolio through late 2020. For the new website, visit https://wlandau.github.io/. I do Statistics and write software in the life sciences industry, and I am the creator and maintainer of the drake R package.
drake


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In this demo we are trying to do a new take on the classical "How was your experience" boards that you sometimes see in toilets, shops etc.
How to:
Use a Thumbs Up to register your experience as being good
Or a Thumbs Down to register it as being a bad experience


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