Bootstrap includes six predefined button styles, each serving its own semantic purpose.
Use a class .btn-outline-{color}
to quickly create a outline button.
Use .btn-flat-{color}
to create a flat button
use btn-gradient-{color}
create gradient buttons
Use .btn-relief-{color}
to create a relief button.
Use a class .round
with outline button class to create round outline button.
You can use .btn-icon
. you can create a rounded button by using
.rounded-circle
with .btn-icon
. You can only use .btn-icon
when you
only want icon in your button
Group a series of buttons together on a single line with the button group. Wrap a series of buttons with
.btn
in .btn-group
.
Add .btn-lg
or .btn-sm
for Fancy larger or smaller buttons size.
Add .btn-lg
or .btn-sm
with .btn-outline-*
for outline btn in
different sizes
Create block level buttons with a mix of our display and gap utilities.
The .btn
classes are designed to be used with the <button>
element. However,
you can also use these classes on <a>
or <input>
elements.


Lei Liu
Our rule of thumb is to increase the number of parallel downloads by using at least two, but no more than four hostnames. Once again, this underscores the number one rule for improving response times: reduce the number of components in the page.
Four stages in the front-end execution process are commonly noted:
Time To Title is the time elapsed from the moment a visitor’s browser requests your site to the moment that your site’s title appears in the tab of his or her browser.
Time To Title is largely dictated by your backend performance—that is, how fast your website’s content is delivered from your origin server to the visitor’s browser.
Time To Title is the first indication to the visitor that your site exists and is on the way. When users see the title appear promptly they are apt to be patient throughout the load process.
Time to Start Render is the time elapsed from the request to when the visitor sees actual website content appear on the page.
Nobody likes staring at a blank page. Assuring visitors that they are in the right place and will be soon seeing the content they expect will promote a good perception of your website.
Time To Display is the time elapsed from the request to when the browser has finished parsing the HTML page, constructed the Document Object Model (DOM), and displayed the HTML document.
This all means that the page will look like a web page, but there may be some images, interactive elements, and other media that haven’t fully loaded.
Time To Interact is the time elapsed from the request to the moment the user can interact with the page.
This does not mean that the page is fully loaded, as there may be scripts, trackers, and other assets that continue to load in the background. But it does mean that the almighty visitor can use the web page, and that’s an important moment. Many site owners choose Time To Interact as the principle index for overall web performance because of its relationship with user experience.


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The Arduino Wireless shield allows your Arduino board to communicate wirelessly using Zigbee. This documentation describes the use of the shield with the XBee 802.15.4 module (sometimes called "Series 1" to distinguish them from the Series 2 modules, although "Series 1" doesn't appear in the official name or product description).
You should be able to get two Arduino boards with Wireless shields talking to each other without any configuration, using just the standard Arduino serial commands (described in the reference).
To upload a sketch to an Arduino board with a Wireless shield, remove the Xbee. Then, you can upload a sketch normally from the Arduino environment. In this case, upload the Communication | Physical Pixel sketch to one of the boards. This sketch instructs the board to turn on the LED attached to pin 13 whenever it receives an 'H' over its serial connection, and turn the LED off when it gets an 'L'. You can test it by connecting to the board with the Arduino serial monitor (be sure it's set at 9600 baud), typing an H, and pressing enter (or clicking send). The LED should turn on. Send an L and the LED should turn off. If nothing happens, you may have an Arduino board that doesn't have a built-in LED on pin 13 (see the board index to check for sure), in this case you'll need to supply your own.
Once you've uploaded the Physical Pixel sketch and made sure that it's working, unplug the first Arduino board from the computer. Change the switch to the Micro setting. Now, you need to upload a sketch to the other board. Make sure its switch is in the USB setting. Then upload the following sketch to the board:
When it's finished uploading, you can check that it's working with the Arduino serial monitor. You should see H's and L's arriving one a second. Turn off the serial monitor and unplug the board. Change the switch to the Micro setting. Now connect both boards to power. After a few seconds, you should see the LED on the first board turn on and off, once a second. (This is the LED on the Arduino board itself, not the one on the Xbee shield, which conveys information about the state of the Xbee module.) If so, congratulations, your Arduino boards are communicating wirelessly.
You can use any of the standard Arduino serial commands with the Xbee shield. With the switch in the Micro position, the print and println commands will send data over the Xbee shield and the USB connection (i.e. to other Xbee shields and to the computer at the same time). In this configuration, however, the board will only receive data from the Xbee shield not from the USB connection.
The Xbee module on the shield is set up to work at 9600 baud by default, so unless you reconfigure it, you'll need to make sure you're passing 9600 to the Serial.begin() command in your sketch.
To allow your computer to communicate directly with the Xbee shield, connect it to an Arduino board whose microcontroller has been removed and place the switch in the USB configuration. Then you can send data to and receive data from the Xbee module from any terminal program. This allows you, for example, to see the data that the module is receiving from other Xbee shields (e.g. to collect sensor data wirelessly from a number of locations).
You can configure the Xbee module from code running on the Arduino board or from software on the computer. To configure it from the Arduino board, you'll need to have the switch in the Micro position. To configure it from the computer, you'll need to have the switch in the USB position and have removed the microncontroller from your Arduino board.
To get the module into configuration mode, you need to send it three plus signs: +++ and there needs to be at least one second before and after during which you send no other character to the module. Note that this includes newlines or carriage return characters. Thus, if you're trying to configure the module from the computer, you need to make sure your terminal software is configured to send characters as you type them, without waiting for you to press enter. Otherwise, it will send the plus signs immediately followed by a newline (i.e. you won't get the needed one second delay after the +++). If you successfully enter configuration mode, the module will send back the two characters 'OK', followed by a carriage return.
| Send Command | Expected Response |
+++
| OK <CR>
|
Once in configuration mode, you can send AT commands to the module. Command strings have the form ATxx (where xx is the name of a setting). To read the current value of the setting, send the command string followed by a carriage return. To write a new value to the setting, send the command string, immediately followed by the new setting (with no spaces or newlines in-between), followed by a carriage return. For example, to read the network ID of the module (which determines which other Xbee modules it will communicate with), use the 'ATID command:
| Send Command | Expected Response |
ATID <enter>
| 3332 <CR>
|
To change the network ID of the module:
| Send Command | Expected Response |
ATID3331 <enter>
| OK <CR>
|
Now, check that the setting has taken effect:
| Send Command | Expected Response |
ATID <enter>
| 3331 <CR>
|
Unless you tell the module to write the changes to non-volatile (long-term) memory, they will only be in effect until the module loses power. To save the changes permanently (until you explicitly modify them again), use the ATWR command:
| Send Command | Expected Response |
ATWR <enter>
| OK <CR>
|
To reset the module to the factory settings, use the ATRE command:
| Send Command | Expected Response |
ATRE <enter>
| OK <CR>
|
Note that like the other commands, the reset will not be permanent unless you follow it with the ATWR comamand.
For more information, see: the hardware page for the Xbee shield, and the Digi Xbee page. The text of the Arduino getting started guide is licensed under a Creative Commons Attribution-ShareAlike 3.0 License. Code samples in the guide are released into the public domain.


STRATUSCARE MILK OF MAGNESIA- magnesium hydroxide suspension
Stratus Pharamceuticals
Disclaimer: Most OTC drugs are not reviewed and approved by FDA, however they may be marketed if they comply with applicable regulations and policies. FDA has not evaluated whether this product complies.
Active ingredient (in each 15 mL tablespoon)
Magnesium hydroxide 1200mg
Uses
- relieves occasional constipation (irregularity)
- generally produces bowel movement in ½ to 6 hours
Warnings
Ask a doctor before use if you have
- kidney disease
- a magnesium-restricted diet
- stomach pain, nausea or vomiting
- a sudden change in bowel habits that last more than 2 weeks
Ask a doctor or pharmacist before use if you are taking any other drug. Take this product two or more hours before or after other drugs. Laxatives may affect how other drugs work.
Stop use and ask a doctor if
- you have rectal bleeding or no bowel movement after using this product. This may indicate a serious condition
- you need to use a laxative for more than 1 week.
If pregnant or breast-feeding, ask a health professional before use.
Keep out of reach of children. In case of overdose, get medical help or contact a Poison Control Center immediately.
Directions
- shake well before use
- do not exceed the maximum recommended daily dose in a 24 hour period
- dose may be taken once a day preferably at bedtime, in divided doses, or as directed by a doctor
- drink a full glass (8 oz) of liquid with each dose
- TBSP = tablespoonful
| adults and children 12 years and older |
2 to 4 TBSP |
| children 6 to 11 years |
1 to 2 TBSP |
| children under 6 years |
ask a doctor |
Other information
-
each tablespoon (15 mL) contains: magnesium 501mg and sodium 2mg
- Store at 20°C to 25°C (68°F to 77°F), excursions permitted between 15°C and 30°C (between 59°F and 86°F)
- keep tightly closed
Inactive ingredients
light mineral oil, peppermint oil, saccharin sodium, sodium hypochlorite, purified water
Questions or comments?
800-442-7882
Distributed by:
Stratus Pharmaceuticals Inc
12379 SW 130th Street
Miami, Florida 33186
PRINCIPAL DISPLAY PANEL - 355 mL Bottle Label
STRATUSCARE
Milk of Magnesia
NDC 58980-441-85
Magnesium Hydroxide /
Saline Laxative
- Effective overnight relief
- Stimulant & cramp free
- Low sodium
Distributed by:
STRATUS
PHARMACEUTICALS INC
Mint
12 FL OZ (355 mL)
Compare to Phillips'® Milk of Magnesia
active ingredient‡‡


The Three Musketeers is a marvelous journey and should be appreciated foremost for its engaging story. The techniques Dumas employed to such success in 1840-- particularly his mastery of the form of the Romance--still work today.
As we saw in the closing portions of the book, Dumas gives us a fully developed Romance within his historical framework. He starts with levity and confidence, and ends with moroseness and doubt. The ending, indeed, seems to question many of the books dearly held values. D'Artagnan becomes a lieutenant in the Musketeers, but his promotion comes from the Cardinal--the Cardinal whom he and his four friends had fought so valiantly against for the first half of the novel. In the epilogue, d'Artagnan befriends the Comte de Rochefort, a Cardinalist agent. Was all that earlier fighting really worth it, then? Or was there something futile in all the Musketeers' efforts? Both the possibility of futility and this return to the normal at the end of a great Quest, characterize the form of the Romance as much as do its lighter aspects. Dumas sees the form through.


saws: Small-Sample Adjustments for Wald tests Using Sandwich
Estimators
Tests coefficients with sandwich estimator of variance and with small samples. Regression types supported are gee, linear regression, and conditional logistic regression.
| Version: |
0.9-6.1 |
| Depends: |
R (≥ 2.6.0), gee, stats |
| Suggests: |
MASS |
| Published: |
2014-01-23 |
| Author: |
Michael P. Fay |
| Maintainer: |
Michael P. Fay <mfay at niaid.nih.gov> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
no |
| Citation: |
saws citation info |
| Materials: |
NEWS |
| In views: |
Survival |
| CRAN checks: |
saws results |
Downloads:
Reverse dependencies:
| Reverse depends: |
MOJOV |
| Reverse suggests: |
geex |
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=saws
to link to this page.


Record
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This website requires a laptop/desktop device with a mouse, and a sufficiently large screen. Try with another device?
I'm not afraid to click
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How this works


Counter for Sabarimala pilgrims at Kochi airport
by Special CorrespondentThe Travancore Devaswom Board has started a special counter at Cochin International Airport Ltd. to help Sabarimala pilgrims. N. Vasu, Devaswom Board president, inaugurated it on Wednesday.
The counter is functioning at the arrival zone of the domestic terminal. Dhanalakshmi Bank is also functioning in the airport for the Devaswom Board. Pilgrims can get the coupons for Sabarimala offerings from the bank counter.


H.B. Woodrose & Cannabis
| DOSE: T+ 0:00 |
5 seeds |
oral |
H.B. Woodrose |
(ground / crushed) |
| T+ 2:50 |
1 bowl |
smoked |
Cannabis |
(plant material) |
The other evening I took HBWR for the first time. I have taken MGs three times before, but only in low doses and never had an experience like this. The best experience with MGs was slight visual distortion. Aside from that, I have taken MDMA twice (enjoyed it immensely both times) and smoked weed lots in the last 2 years (every day for a year, although I'm smokin' less now). I decided to take HBWR as I am interested in psycadelic drugs, both as a novel experience and to understand myself and others better - enlightenment and wisdom.
I took them at home, with my g/f as a sitter, on a weekday evening. I was feeling happy, relaxed, and contented with life. At 5pm I crushed 5 seeds with pliers, after first removing the fuzzy coating. I put these on bread and ate it. At 6pm, I sat down and attempted to eat. No alteration of consciousness. A feeling of nausea had been building for the last hour. I had a few bites and found I could not eat due to feeling nausea. It did not feel too bad, I just felt full, altough I wasn't. I had had a portion of chips for lunch, and no food since then.
By seven o'clock the nausea was reaching it's peak. I never had to go to the bathroom, but if I'd have tried I could've vomited. I do not like being sick, and avoid it if I can. I went and sat in the bedroom by myself. Start feeling an altered consciousness coming on. Pupils start to get big. At 7.50 I have a gravity bong. I do this with the intent of bringing on the effects, and subsiding the nausea. Within ten minutes both effects have been acheaved. I felt profoundly altered, but I couldn't decribe how. The only thing I have to compare it to is MDMA, to which it felt similar, but with no euphoria and no energy rush. I feel happy 'cos I already felt happy.
I listen to some music - Aereogramme, Scottish indie rock. It sounds fantastic. I notice a slight increase in the vividness of colours. I listen to Boards Of Canada (warp-electronica). Sounds incredible! The artwork looks amazing too. I speak to my girlfriend, and tell her I feel great. We kiss, and I am surprised and delighted that I get an amazing vision with my eyes closed. While kissing her, first I see a still image of us, in two tones of grey, as if it was embossed in stone. Then it starts moving for a few seconds, and I am watching me and my g/f kiss from a 3rd person perspective! The wierdness of it makes me open my eyes. Then, when she stroked my arm, I see vivid blue elecricity, a moving zigzag line, 6-8 inches long, travel down her arm into my body. I interpret this as love.
G/f leaves to watch TV in the other room. I lay on the bed and close my eyes, and I can see amazing CEV's. I wrote some notes at this point, and I described it as 'like Nintendo-MTV'. I could see lots of little Yoshis dancing to the music! After five minutes of lying like this, I notice I can feel my breath on my chin. It feels like cold water is running across my chin when I breath out. I could still feel it when I started writing it down. My pupils are absolutely huge, approx 1mm of iris is visible.
After this the experience becomes more profound. This is the first time I have tripped like this. I close my eyes and listen to the music, and I see myself wake up in different places. The only way I can describe this is dreaming, but while being awake. Very different from daydreams. I can hear and see, but I can also feel things like the temperature etc. They only last for a few seconds at a time, and then I force myself to wake up, and I don't want to sleep or get stuck in an alternative dimension. I think I must be having a fear of ego-loss, so I let go of my fears, but I still can only remain in these places for very short times, long enough to only have a quick glimpse. The places I can remember best were on top of a mountain (very cold, white snow, beautiful blue sky) and being in some kind of tunnel. The tunnel is brown, with tentacles growing from the walls, and round doors lining it. It sounds a bit scary, but wasn't in the slightest.
Next, I open my eyes. Some slight visual distortions when I look at things, extremely vivid colours. When I look at the ceiling, I can see the posters on our wall in the periphery of my vision. We have the Kandinsky poster with 12 coloured circles that look like sweets. The colours start chnging very rapidly, and it looks like a light show - very inpressive! At the same time I can see the poster we have of a flower. The top of the flower grows toes and they start wiggling! This is very amusing! I see images from the past too, memories come back to me with ease. I also feel an intense love for my girlfriend.
I go into the lounge to speak to my g/f. By now it is nearly ten. The lounge is boring, TV is very disinteresting, even though it was a documentary about a subject I would normally enjoy. I warm up the food I couldn't eat earlier, but although I find it deliciious and am experiencing no nausea, I find it difficult to eat as I still feel full. Eat a spoonful of Ben & Jerry's icecream, which is very nice indeed, but that was all we had. I would've liked more of that. I have a very sweet tooth!
I go to bed with g/f as I become extremely tired. However I find it dificult to sleep, and I have to go for a wee 3 times in the next two hours. When I go upstairs, in the bathroom I notice that if I stare at the walls they start distorting - slowly moving/ melting. This is funny! The next day I feel fine, a bit spaced when I first get up, but later on no different from how I usually feel, maybe just a bit tired. No trouble going about my day to day life.
My experience was great fun, I enjoyed the visual fun and games, and felt very happy. My experience felt at times very profound, and I think I learnt things about myself I had not fully realised before. I am glad I did it. I plan to repeat this experiment after a suitable time has passed, at least one month.
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.


Split and Join Strings
A couple of common string operations include splitting and joining strings with a specific separator character. JavaScript supports these operations using strings and arrays of strings.
var stringList = "1, 2, 3, 4, 5"; var arrayList = stringList.split(", "); // ["1", "2", "3", "4", "5"] var backToString = arrayList.join(";"); // "1;2;3;4;5"


The [PartOf] attribute can be attached to any page element that can produce Css and Javascript assets. The [PartOf] attribute defines the namespace to use for these assets to ensure that names of Css classes and Javascript functions do not conflict.
Unless you are writing a very large application, you will likely use only one package for all of your application code.
If you are creating a reusable package for distribution to application developers then you must put all of your elements into packages so that the application developer can choose a namespace for each package and avoid naming conflicts between imported packages.
The [PartOf()] attribute has the following properties you can set.
The name of the Package that defines the namespace for assets belonging to this page element.
This is also used in name resolution for any attributes attached to this element. For example if this element refers to layouts, regions, components etc by name then these names will be resolved within the scope of the package. To refer to elements from other packages, prefix the element name with the namespace of the package and a colon.


22 These aren’t new blocks but they have a new feature: These accept two-item (x,y) lists as input, and have extended menus (also including other sprites): “Center” means the center of the stage, the point at (0,0). “Direction” is in the point in direction sense, the direction that would leave this sprite pointing toward another sprite, the mouse, or the center. “Ray length” is the distance from the center of this sprite to the nearest point on the other sprite, in the current direction. The stop block has two extra menu choices. Stop this block is used inside the deﬁnition of a custom block to stop just this invocation of this custom block and continue the script that called it. Stop all but this script is good at the end of a game to stop all the game pieces from moving around, but keep running this script to provide the user’s ﬁnal score. The last two menu choices add a tab at the bottom of the block because the current script can continue after it. The new “pen trails” option is true if the sprite is touching any drawn or stamped ink on the stage. Also, touching will not detect hidden sprites, but a hidden sprite can use it to detect visible sprites. The video block has a snap option that takes a snapshot and reports it as a costume. It is hyperized with respect to its second input. The “neg” option is a monadic negation operator, equivalent to . “lg” is log2. “id” is the identity function, which reports its input. “sign” reports 1 for positive input, 0 for zero input, or -1 for negative input. name changed to clarify that it’s different from + and × are variadic: they take two or more inputs. If you drop a list on the arrowheads, the block name changes to sum or product.


NiM helps you debug your code with style and grace by leveraging Chrome DevTools and Node.js' debugging tool, V8 Inspector. Further, the goal of this project is to improve the Node developer's experience to the greatest extent possible. To that effort, this DevTools panel will be used to facilitate even greater NiM functionality.
Got idea's about how to make this page useful? Tweet @june07t, share on Twitter, or email 667@june07.com.


| T# | Shooter | Avg | Prone | Sitting | Offhand | Total |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
| $HOME_MARKSMAN_TNUM | $HOME_MARKSMAN_NAME | $HOME_MARKSMAN_AVERAGE | $HOME_MARKSMAN_PRONE | $HOME_MARKSMAN_SITTING | $HOME_MARKSMAN_OFFHAND | $HOME_MARKSMAN_TOTAL |
|
| T# | Shooter | Avg | Prone | Sitting | Offhand | Total |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
| $AWAY_MARKSMAN_TNUM | $AWAY_MARKSMAN_NAME | $AWAY_MARKSMAN_AVERAGE | $AWAY_MARKSMAN_PRONE | $AWAY_MARKSMAN_SITTING | $AWAY_MARKSMAN_OFFHAND | $AWAY_MARKSMAN_TOTAL |
|
| Shooter | Score |
| 1 | $HOME_TOP_MARKSMAN | $HOME_TOP_SCORE |
| 2 | $HOME_TOP_MARKSMAN | $HOME_TOP_SCORE |
| 3 | $HOME_TOP_MARKSMAN | $HOME_TOP_SCORE |
| 4 | $HOME_TOP_MARKSMAN | $HOME_TOP_SCORE |
| 5 | $HOME_TOP_MARKSMAN | $HOME_TOP_SCORE |
| 6 | $HOME_TOP_MARKSMAN | $HOME_TOP_SCORE |
| Raw Score Total | $HOME_SCORE_TOTAL |
| Handicap | $HOME_SCORE_HANDICAP |
| Final Score Total | $HOME_SCORE_FINAL |
|
| Shooter | Score |
| 1 | $AWAY_TOP_MARKSMAN | $AWAY_TOP_SCORE |
| 2 | $AWAY_TOP_MARKSMAN | $AWAY_TOP_SCORE |
| 3 | $AWAY_TOP_MARKSMAN | $AWAY_TOP_SCORE |
| 4 | $AWAY_TOP_MARKSMAN | $AWAY_TOP_SCORE |
| 5 | $AWAY_TOP_MARKSMAN | $AWAY_TOP_SCORE |
| 6 | $AWAY_TOP_MARKSMAN | $AWAY_TOP_SCORE |
| Raw Score Total | $AWAY_SCORE_TOTAL |
| Handicap | $AWAY_SCORE_HANDICAP |
| Final Score Total | $AWAY_SCORE_FINAL |
|


#!/usr/bin/env python
# -*- coding: utf-8 -*-
from parapy.core import *
from parapy.geom import *
from primitives import LiftingSurface
from definitions import *
from user import MyColors
from directories import *
__author__ = ["Nelson Johnson"]
__all__ = ["HorizontalStabilizer"]
[docs]class HorizontalStabilizer(ExternalBody, LiftingSurface):
""" This script will generate the horizontal stabilizer using the lifting surface primitive with the required area
from the 'scissorplot.py' script. Also, the bounding box is made for the section of the HTP within the fuselage,
which is used to size the fuselage frames.
:returns: ParaPy Geometry of the Horizontal Tail Surface
:param planform_area: This is the Required Planfrom Area for the HT from the Scissor Plot in [m^2]
:type planform_area: float
:param aspect_ratio: This is the required Aspect Ratio of the HT Surface corresponding to the scissor plot value.
:type aspect_ratio: float
:param taper: This is the required Taper Ratio of the HT Surface.
:type taper: float
:param dihedral: This is the required Dihedral Angle of the HT Surface in degrees.
:type dihedral: float
:param twist: This is the required Twist Angle of the Tip Airfoil w.r.t the Root Airfoil in degrees.
:type twist: float
:param offset: This is the offset in the flow direction of the tip W.R.T. the root Leading Edge.
:type offset: float or NoneType
:param fuse_width_factor: This is the assumed factor of the semispan which the fuselage extends over the HT semispan
:type fuse_width_factor: float
:param color: Changes the color of the wing skin to the one defined in MyColors
:type color: tuple
:param airfoil_type: This is the name of the folder within the 'airfoils' folder. There are three options \
'cambered', 'reflexed' and 'symmetric'.
:type airfoil_type: str
:param airfoil_choice: This is the filename of the requested airfoil.
:type airfoil_choice: str
:param ply_number: Changes the number of ply's of carbon fiber pre-preg.
:type ply_number: int
"""
__icon__ = os.path.join(DIRS['ICON_DIR'], 'htail.png')
#: Below is the required tail surface area from the scissor plot.
planform_area = Input(0.8, validator=val.Positive())
#: Below is the required HT aspect ratio.
aspect_ratio = Input(5.0, validator=val.Positive())
#: Below is the required HT taper ratio.
taper = 1.0
#: Below is the tail dihedral angle.
dihedral = 0.0
#: Below is the tail wing twist angle.
twist = Input(0.0, validator=val.Range(-5.0, 5.0))
#: Below is the chosen trailing edge offset.
offset = Input(None)
#: Below is the assumed factor relating the part of the HT covered by fuse to semispan
fuse_width_factor = Input(0.025)
#: Changes the color of the wing skin to the one defined in MyColors
color = Input(MyColors.skin_color)
#: Below is the tail airfoil type. The input must correspond to an existing folder.
airfoil_type = Input('symmetric', validator=val.OneOf(['cambered', 'reflexed', 'symmetric']))
#: Below is the tail airfoil DAT file. The input must correspond to an existing filename.
airfoil_choice = Input('NACA0012')
#: Changes the number of ply's of carbon fiber http://www.ijera.com/papers/Vol4_issue5/Version%202/J45025355.pdf
ply_number = Input(4, validator=val.Instance(int))
@offset.on_slot_change
def sweep_validator(self):
""" Simple listener to validate the offset parameter """
if abs(self.le_sweep) >= 0.0 and self.offset is not None:
error_window('Currently adding sweep to the horizontal tail is not implemented')
setattr(self, 'offset', None)
return None
# Attributes ########--------------------------------------------------------------------------------------------------
[docs] @Attribute
def component_type(self):
""" This attribute names the component 'ht' for horizontal stabilizer.
:return: Name of HT
:rtype: str
"""
return 'ht'
[docs] @Attribute
def center_of_gravity(self):
""" This shows the COG which was found from one wing and translated to origin. This is because because the fused
shape does not exhibit a C.G.
:return: ParaPy Point of HT CG
:rtype: Point
"""
pos = Point(self.solid.cog.x, self.position.y, self.solid.cog.z)
return pos
[docs] @Attribute
def htwing_cut_loc(self):
""" This calculates the spanwise distance of the cut, inside of which, the HT is inside the fuselage. This
location is where the HT bbox to size the fuselage frame(s) ends in the spanwise direction. The height of this
bbox is the maximum thickness of the wing at this cut location.
:return: Spanwise distance from HT root chord to cut location
:rtype: float
"""
return self.semi_span*self.fuse_width_factor
[docs] @Attribute
def htright_cut_plane(self):
""" This makes a plane at the right HT span location where the fuselage is to end.
:return: ParaPy Plane to cut HT
:rtype: Plane
"""
return Plane(reference=translate(self.solid.position,
'y', self.htwing_cut_loc),
normal=Vector(0, 1, 0),
hidden=True)
[docs] @Attribute
def get_htfuse_bounds(self):
""" This attribute is obtaining (the dimensions of) a bounded box at a fuselage width factor of the semispan
which will be used to size the fuselage frames. These frames drive the shape of the fuselage.
:return: ParaPy Bounding Box
:rtype: bbox
"""
inner_part = PartitionedSolid(solid_in=self.solid,
tool=self.htright_cut_plane).solids[0].faces[1].wires[0]
# Above obtains a cross section of the wing, at the specified fuselage width factor.
mirrored_part = MirroredShape(shape_in=inner_part,
reference_point=self.solid.position,
vector1=Vector(1, 0, 0),
vector2=Vector(0, 0, 1))
# Above mirrors the cross section about the aircraft symmetry plane.
root = sorted(self.solid.faces, key=lambda f: f.cog.y)[0].edges[0]
first_iter = Fused(inner_part, root)
# Fusion of the three wing cross sections is done in 2 steps to avoid ParaPy errors.
second_iter = Fused(first_iter, mirrored_part)
bounds = second_iter.bbox
# Above gets the bounds of the wing fuselage bounding box for return.
return bounds
# Parts #####----------------------------------------------------------------------------------------------------------
[docs] @Part
def ht_mirror(self):
""" This is a mirrored shape of the right HT.
:return: HT left wing half
:rtype: MirroredShape
"""
return MirroredShape(shape_in=self.solid,
reference_point=self.solid.position,
vector1=Vector(1, 0, 0),
vector2=Vector(0, 0, 1))
[docs] @Part
def internal_shape(self):
""" This part creates the bounding box for the part of the HT within the fuselage.
:return: HT fuselage Sizing bbox
:rtype: Box
"""
return Box(width=self.get_htfuse_bounds.width,
height=self.get_htfuse_bounds.height,
length=self.get_htfuse_bounds.length,
position=Position(self.get_htfuse_bounds.center),
centered=True,
color=MyColors.cool_blue,
transparency=0.5,
hidden=True)
[docs] @Part
def external_shape(self):
""" This part is the external shape of the HT.
:return: Fused Shape of left and right HT surfaces
:rtype: Fused
"""
return Fused(self.solid, self.ht_mirror, hidden=True)
if __name__ == '__main__':
from parapy.gui import display
obj = HorizontalStabilizer()
display(obj)


This is an example of the default functionalities of Custom Element NavBar.
NavBar with 2 Items. Each item is with 50% width.
NavBar with 3 Items. Each item is with 33.33% width.
NavBar with 4 Items. Each item is with 25% width.
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NavBar with more than 5 Items. Items are displayed in 2 columns and each item is with 50% width.
NavBar with "columns" set to ['30%', '50%', '20%'].


Coverage report:
92%
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Returns an overview of available metadata for a given dataset.
nomis_overview(id, select = NULL)
| id | The ID of the particular dataset. Returns no data if not specified. |
|---|---|
| select | A string or character vector of one or more overview parts to
select, excluding all others. |
A tibble with two columns, one a character vector with the name of the metadata category, and the other a list column of values for each category.
General dataset information such as name, description, sub-description, mnemonic, restricted access and status
Shows the geographic coverage of the main geography dimension in this dataset (e.g. United Kingdom, England and Wales etc.)
The keywords allocated to the dataset
The units of measure supported by the dataset
The classifications allocated to this dataset
Information about the first release, last update and next update
Details for the point of contact for this dataset
Show the available analysis breakdowns of this dataset
Individual dimension information (e.g. sex, geography, date, etc.)
Allows a specific dimension to be selected (e.g. dimension-geography would allow information about geography dimension). This is not used if "Dimensions" is specified too.
Full list of selectable codes, excluding Geography, which as a list of Types instead. (Requires "Dimensions" to be selected too)
Full list of selectable codes for a specific dimension, excluding Geography, which as a list of Types instead. This is not used if "Codes" is specified too (Requires "Dimensions" or equivalent to be selected too)
Any available metadata attached at the dimensional level (Requires "Dimensions" or equivalent to be selected too)
Information about whether user defined codes can be created with the MAKE parameter when querying data (Requires "Dimensions" or equivalent to be selected too)
Metadata attached at the dataset level
#> #>#>#> #>#>#> #>#> Rows: 20 #> Columns: 2 #> $ name <chr> "analyses", "analysisname", "analysisnumber", "contact", "conte… #> $ value <list> [[<data.frame[3 x 3]>], "output data for a single date or rang…s <- nomis_overview("NM_1650_1", select = c("Units", "Keywords")) s %>% tidyr::unnest(name) %>% glimpse()#> Rows: 3 #> Columns: 2 #> $ name <chr> "id", "keywords", "units" #> $ value <list> ["NM_1650_1", "Year last worked", [["Persons"]]]# }


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With online piracy being such a big issue for people and companies who sell digital content, various attempts have been made by organisations and authorities to thwart the efforts of the perpetrators. This section contains resources that explore laws and legislations that address the issue of online piracy, the response of the public and their success in stopping online piracy.
The first resource chosen is a peer-reviewed journal article titled “Beyond Counterfeiting: The Expanding Battle Against Online Piracy”, written by Laurent Szuskin et al., and published in the Intellectual Property & Technology Law Journal in 2009. This article explores how countries around the world have tried to combat online piracy, and in particular how effective the French HADOPI law and other legislations from various countries have been to reduce online piracy.
The second resource chosen is a book titled “Chokepoints”, written by Natasha Tusikov and published in 2016. The book looks into the infamous Stop Online Piracy Act (SOPA), a bill introduced in the USA in 2012 to address online piracy and give intellectual property holders substantial power over the Internet. SOPA was withdrawn due to the large number of protests and opposition. However, its withdrawal was not the end for SOPA - the author details how much of SOPA has in fact been implemented via a series of secret agreements by a small group of corporations.
Title: Beyond Counterfeiting: The Expanding Battle Against Online Piracy
Authors: L. Szuskin, S. Fourques de Ruyter, & J. Doucleff
Published: 2009
Category: Peer-reviewed Journal Article
This article investigates the current development in laws against online piracy around the world. In particular, it focuses on the French HADOPI law, UK’s Copyright Designs and Patents Act (CDPA), and various strategies employed by the US. The authors present the motivation behind the legislations, their impact on society and whether or not they were successful in combating piracy.
The HADOPI law introduces a new approach in fighting against online piracy by focusing on the source - it holds internet users legally responsible for any activity that illegally harms digital content owners on their computers. However, the French Constitutional council ruled that "certain provisions of the new law did not comply with the French Constitution". The HADOPI law has since been revised to comply with the French Constitution, and no longer has the authority to order ISPs to suspend the Internet access of a subscriber. It aims to combat piracy by initiating a 'three strike' policy for the offending internet subscriber, which at the third stage could potentially send the offender to court.
The article also further discusses the CDPA from the UK and US copyright laws such as the Digital Millennium Copyright Act (DMCA). The authors contend that whilst there are many laws in place that address illegal distribution of copyrighted digital content, problems such as peer-to-peer copying is difficult to deal with because detection and enforcement is difficult and costly, making online piracy a challenging issue to defeat.
Read this article to find out more about the finer details of the various laws and legislations that have been put in place to battle online piracy, and whether such measures were able to reduce it.
Title: Chokepoints
Author: Natasha Tusikov
Published: 2016
Category: Book
"Chokepoints", written by Natasha Tusikov, is a book that explores the rise and fall of the Stop Online Piracy Act (SOPA), a bill first introduced in the US, and its lasting effects on the face of fighting against online piracy.
In January 2012, millions of internet uses participated in the “internet blackout” in protest against SOPA. It was believed that the bill would greatly endanger freedom of speech on the internet due to its potential for censorship. The general consensus was that SOPA was designed to favour rights holders, particularly large institutional copyright owners such as the movie and music industries, at the expense of Internet firms that provide essential online services as they would be required to do the work in enforcing SOPA by controlling access to suspected perpetrators.
SOPA never managed to pass and become law, but that wasn’t the end of what it served to bring to stop online piracy - the author discusses the actions and outcomes of several small corporations that constructed a regime through a series of unofficial agreements which allows “large internet firms to act as regulators for powerful intellectual property owners”. It goes to show that where the law has been unable to deliver, large corporations actually hold a lot of power - for something as large and global as the internet, this is an issue that will affect industries around the world.
Read this book to find out more about SOPA’s motivation and history, and the how effects of just a few corporations have made an impact in the world of online piracy.


$4599 per operative involved
Operatives:
Total price: $4599
$7599 per operative involved
Total price: $7599
$3199 per operative involved
Destination: Capital Suburbs Jungle
Total price: $3199


Happy Girls
问题描述 :
These days, Hunan TV host the big concert � Happy Girls.
Long1 and xinxin like it very much, they even use their cellphones to suppose the girl who they like most. This way is easy if you have enough money then you can make a contribution toward your lover.
But sometimes, it also causes the problem of injustice. Those who has a lot of money can support their lover in every second. So now, we make a rule to restrict them � every tel-number can just support once in one minute (i.e two messages should have difference bigger or equal 60s).
As an exerllent programer, your mission is to count every Happy girl’s result.
Long1 and xinxin like it very much, they even use their cellphones to suppose the girl who they like most. This way is easy if you have enough money then you can make a contribution toward your lover.
But sometimes, it also causes the problem of injustice. Those who has a lot of money can support their lover in every second. So now, we make a rule to restrict them � every tel-number can just support once in one minute (i.e two messages should have difference bigger or equal 60s).
As an exerllent programer, your mission is to count every Happy girl’s result.
输入:
There are many cases.
For every case:
For every case:
The first line gives N, represents there are N happy gilrs numbered form 1 to N（N<=10）
Then many lines follows(no more than 50000), each line gives the time one sent his/her message, the cellphone number and the number he/she support. They are sepatated by space.
The last line an message “#end”.
输出:
There are many cases.
For every case:
For every case:
The first line gives N, represents there are N happy gilrs numbered form 1 to N（N<=10）
Then many lines follows(no more than 50000), each line gives the time one sent his/her message, the cellphone number and the number he/she support. They are sepatated by space.
The last line an message “#end”.
样例输入:
4 0:12:25<PHONE_NUMBER>6 1 0:15:52<PHONE_NUMBER>5 2 0:15:56<PHONE_NUMBER>5 3 0:18:55<PHONE_NUMBER>7 2 11:12:2<PHONE_NUMBER>5 4 5:41:55<PHONE_NUMBER>7 2 #end
样例输出:
The result is : 01 : * 02 : *** 03 : 04 : *
刚开始用字典树写死活就是过不去。后来模拟的G++提交能AC，C++提交就wa。
#include<stdio.h> #include<string.h> #include<stdlib.h> #define N 50005 struct node { int x; __int64 tt; int id; }a[N],b[N]; int mark[15]; int fun(char *s) { int a,b,c; sscanf(s,"%d:%d:%d",&a,&b,&c); return a*3600+b*60+c; } int cmp(const void *a,const void *b) { node *c,*d; c=(node *)a;d=(node *)b; if(c->tt!=d->tt) return c->tt<d->tt?1:-1; else return c->x-d->x; } int main() { int n; while(scanf("%d",&n)!=EOF) { int i,j,k; j=0; char s[15]; while(scanf("%s",s),strcmp(s,"#end")!=0) { a[j].x=fun(s); scanf("%I64d%d",&a[j].tt,&a[j].id); j++; } qsort(a,j,sizeof(a[0]),cmp); k=1; b[0]=a[0]; for(i=1;i<j;i++) { if(a[i].tt!=a[i-1].tt||a[i].x-a[i-1].x>=60) b[k++]=a[i]; } memset(mark,0,sizeof(mark)); for(i=0;i<k;i++) mark[b[i].id]++; printf("The result is :\n"); for(i=1;i<=n;i++) { printf("%02d : ",i); for(j=1;j<=mark[i];j++) printf("*"); printf("\n"); } } return 0; }
参考：http://blog.csdn.net/zizaimengzhongyue/article/details/10040343
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显然是天象厅放科幻电影啦。右下的阴影是天象投影仪，去过天文馆的人都能认出来的。
终于明白了递归和dp的关系，多谢分享！
能不能说一下tmp数组和solve都是干嘛的？
赞一个！权限已更新:）
妈呀！这个Dijkstra模板好长OwQ！
printf这个函数在计算的时候是从右到左，打印是从左到右。
a是根先忽略掉，递归子树。剩下前缀bejkcfghid和后缀jkebfghicd，分拆的原则的是每个子树前缀和后缀的节点个数是一样的，根节点出现在前缀的第一个，后缀的最后一个。根节点b出现后缀的第四个位置，则第一部分为四个节点，前缀bejk，后缀jkeb，剩下的c出现在后缀的倒数第2个，就划分为cfghi和 fghic，第3部分就为c、c
这是研发的在线笔试题吗?发现很多C啊，阿里不是JAVA多么？
顺利测试通过了，多谢
Thanks for using the time to examine this, I truly feel strongly about it and enjoy finding out far more on this subject matter. If achievable, as you achieve knowledge
递归还真是一门学问，学习了
楼主放题时候没注意下？xxx定律见：
hdoj3782：http://acm.hdu.edu.cn/showproblem.php?pid=3782
感谢分享 学习了`(*∩_∩*)′
顶一个 赞一个
请问printAllCombination的时间复杂度怎么分析呢？


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NAME
has-private-filename — Determine if a filename is “private” e.g. prefixed with a “_” (underscore.)
SYNOPSIS
var hasPrivateFilename = require('has-private-filename');
hasPrivateFilename(
str);
DESCRIPTION
The has-private-filename() extension takes a file base-name string representation and determines if it matches the common “private” file naming convention. In which private files are prefixed with an underscore “_” whereas standard files are not.
RETURN VALUES
Upon successful completion, the value of true is returned; otherwise the value false is returned to indicate the inverse.
EXAMPLES
The following demonstrates the expected return values.
´use strict';
var assert = require('assert');
var hasPrivateFilename = require('has-private-filename');
assert(hasPrivateFilename('_example.file') === true);
assert(hasPrivateFilename('example.file') === false);


FIXTPPS(1) FIXTPPS(1) NAME fixtpps - filter to fix Tpscript documents to work with PSUtils SYNOPSIS fixtpps < Tpscript.ps > Fixed.ps DESCRIPTION Fixtpps is a perl filter which "fixes" PostScript generated from the Troff Tpscript driver so that it works correctly with Angus Duggan's psu‐ tils package. AUTHOR Copyright (C) Angus J. C. Duggan 1991-1995 SEE ALSO psbook(1), psselect(1), pstops(1), epsffit(1), psnup(1), psresize(1), psmerge(1), fixscribeps(1), getafm(1), fixdlsrps(1), fixfmps(1), fixps‐ ditps(1), fixpspps(1), fixtpps(1), fixwfwps(1), fixwpps(1), fixwwps(1), extractres(1), includeres(1), showchar(1) TRADEMARKS PostScript is a trademark of Adobe Systems Incorporated. PSUtils Release 1 Patchlevel 17 FIXTPPS(1)


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 I filled a 36 Oz Emptied fruit bottle out, threw in the kava and the calea and some tea bags. Put in hot water and shook it up like mad. After an hour or so we drained the stuff out. Word had been going around that I had some herbs that gave you dreams and I had friends asking left and right for tea. I posted my first experience, and I'm going to give somewhat detailed experiences of my friends. (The 36 WRETCHEDLY tasting ounces went in a day in a half :)).
----------------------------------
Myself -
3 bowls smoked (Calea) - Vivid realistic dream that I mistook for reality the next day.
2 joints and a cup of my tea mixture - I had a dream of smoking out my dorm window and getting in trouble with authorities. Never happened yet I thought it did for a while the next day.
3 cups of my tea - Nothing on day one, I was somewhat euphoric and relaxed, I kept dropping objects and couldn't stop questioning reality, but the next day I had a hardcore dream with odd events, but I forgot what happened since I fell back a sleep after I woke up in the middle of the dream
----------------------------------
Participant 1 -
2 Joints (Calea) also with previous THC use - Noticed clearer thoughts, he had sex with his girlfriend in his dream, and when he woke up, stunned she wasn't next to him and then realized it was a dream, so realistic he ejaculated in his pants while sleeping.
About 2 Cups of the tea and some THC use - He became extremely hyper, took a tab and ended up never sleeping.
----------------------------------
Participant 2 -
1 Joint and a large cup of tea - We both noticed not being cold in cold weather for about 40 minutes. He slept, felt that he had a lot of dreaming but didn't remember anything.
----------------------------------
Participant 3 -
One cup of tea (mixed with Chocolate Milk to wash down, not bad) - Had a vivid dream that he could create a blue portal and teleport to any location he wanted to.
----------------------------------
Participant 4 -
A cup and a little more - Never mentioned anything to me about dreaming, but he actually liked the taste of Calea and Kava mixed!
----------------------------------
Participant 5 -
A little less than a cup - She claimed her dream to be very mind purifying. It consisted of her being back in Middle school in a sewer area with flowers everywhere. Her friend who had commited suicide in high school talked to her in the sewer.
----------------------------------
Participant 6 -
THC, a little alcohol, and my Tea - Nothing.
----------------------------------
Participant 7 -
Tea - Probably dreamt, but couldn't remember anything
----------------------------------
Participant 8 -
Tea - Just drank some
----------------------------------
Don't ask me what caused me to mix Kava and Calea, I had both herbs lying around and I was quite bored. Me and Part. 2 decided to make a bit of tea and we liked it. It made us feel warm in the cold, and relaxed. My friend's hip pain was completely unevident.
Overall, I liked the mix. I drank three cups over a period of three hours. I noticed my eyelids force closing after exerting my body, and I would drop stuff as if I had been up for a few days straight.
Music was noticably better, I was very relaxed. Later in the night I started going crazy, as if I was watching everything from a movie. I couldn't stop questioning reality. The night had been very wierd, and I couldn't help having thoughts like, maybe the world is all in my head, and since I drank the tea thats why everything is wierded out. I didn't feel too messed up, but when I woke up in the morning remembering the night before I noticed a bit of a change.
From what I noticed, the Kava might make it harder to sleep, but it may just be that anticipation of dreaming that keeps me up. But the relaxation of the Calea, and the Kava effects mix well for a night you don't have anything to do on. Almost like a tranquilizing effect. I also noticed it doesn't really matter how long you take the Calea before sleep to really make a difference. In fact, most of the best experiences came from drinking the tea earlier in the day.
I hope this sheds some light on this underated herb. I plan on buying a lot of Calea and running some somewhat proffesional tests on Calea, making sure no one mixes any other drugs with it, how long they wait to sleep etc.
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.


As an electronics engineering major, I initially thought of “embedding” as a kind of small sub-systems used as a small computer. Later, graph theory gives me another view of “embedding”:
Graph embedding of a graph on a surface is a representation of on in which points of are associated to vertices and simple arcs are associated to edges such that connectivity is preserved and there is no over-lapping between edges.
This view of “embedding” is more abstract, and somewhat more fun. I understand it as the act of “drawing” a graph onto another surface (or space). It is well known that any planar graph can be embedded on a 2D surface, and any graph can be embedded on a 3D “surface”. However, recently, the word “embedding” seems to mean something more concrete to a machine learning practitioner:
Embedding, as in “word embedding”, refers to a set of modeling and feature learning techniques that map structured tokens to vectors of real numbers.
I think embedding is dimensionality reduction or representation learning, just another different fancy name. Maybe, in the context of natural language processing and graph processing, we call dimensionality reduction embedding .
Background
There were many representation learning algorithms in the field of machine learning. One of the most famous method is Spectral Clustering in which the similarity of data is preserved while the dimensionality is reduced. More recently, the t-SNE algorithm is widely used for data visualization. The general objective of t-SNE is somewhat similar to Spectral Clustering. However, instead of dealing with large matrix computation, the authors solved the embedding problem by minimizing a loss function defined for the representations of each data point in two spaces (original data space and the embedding space). The result of t-SNE is a 2D or 3D representation of high dimensional data.
Similar to the t-SNE technique, DeepWalk was proposed by Perozzi et al at KDD’14. DeepWalk and other algorithms inspired by it were based on the Skipgram model proposed by Mikolov et al in 2013. By observing the similarity between the vertex frequencies distribution on random walks in a graph and the word frequency distribution in text, Perozzi et al proposed that we can use random walks on a graph to generate “sentences”, and then learn the node representation using the Skipgram model. The slide for my talk introducing DeepWalk at The University of Tokyo can be found here.
As mentioned above, Deepwalk is an algorithm that uses the word2vec software package on a generated artificial text. The “text” here is generated by performing random walks on graphs. Such idea is simple and effective.
The power law is observed in both domains. This observation can be the motivation for Deepwalk.
Denote a random walk starting from vertex is . The set containing all random walks is denoted with is the vertex set. Under this notations, the optimization problem is formulated in the same way as the skipgram model:
In the optimization problem above, is the mapping from a vertex to its vector representation. The probability is assumed to be able to factor as:
Demonstration of how Deepwalk works.
From here there are two problems need to be solved:
- How to construct the formula for .
- How to efficiently learn and compute the conditional probability.
For the first problem, two embedding matrices are introduced. The first matrix is - the context matrix storing the embedding of the centered vertices (). The second matrix is - the embedding matrix storing surround vertices’ embedding vectors. These two matrices are jointly-learned as the algorithm scans the corpus.
There are two popular solutions for the second problem: hierarchical softmax and negative sampling (my personal favorite learning algorithm). Hierarchical softmax is a decomposition technique that computes the conditional probability using a binary tree. In this technique, we first organize the words (in our context they are graph vertices) into the leaves of a binary tree. Then, the conditional probability is given by the probability of a random walk starts at the root node and ends at the leave node representing . The probability of turning left or right is computed with vector for and vectors associated with the intermediate binary tree nodes. We can compute the probability as:
where is a condition evaluation operator that returns 1 if true and -1 otherwise and is the sigmoid function. The detail of this function is explained in Stanford’s CS224n course. I highly recommend reading the material provided there. Their lecture notes are extremely well-written (thank you Stanford! ).
This picture is an attempt to visualize how hierarchical softmax works. At the first step of the algorithm, tokens (words or vertices) are assigned to the leaves of a binary tree. This assignment can utilize Huffman coding for minimum path length (frequent tokens get shorter paths from root). The root node and leave nodes of the binary tree are just placeholder. The algorithm keeps two sets of learn-able vectors: 1. The embedding vectors associated with each token (not on the tree), and 2. The vectors associated with the internal nodes of the binary tree (blue nodes in the figure above). When we need to compute a conditional probability, say , the embedding vector of and the internal node vectors will be used. For each internal node, we take the inner-product of and its associated vector then apply the sigmoid function to the scalar result. The output of the sigmoid functions are interpreted as the probability of going left from that node. Finally, the conditional probability equals the probability of going from root node to leaf node . Note that due to the property of binary trees, the probability is naturally normalized (P(going left) + P(going right) = 1).
Intuitively, I think of negative sampling as “pushing away” bad samples and “pulling in” good samples in the embedding vector spaces. When the algorithm “sees” a pair of vertices that are supposed to be close to each other, it updates the vectors to maximize the inner product. On the other hand, when the algorithm is given a pair of negative samples which is generated from some distribution, it tries to minimize the inner product. Under the hood, this algorithm optimize a objective that discriminate “true” samples (samples from our dataset) against “negative” samples (samples generated from some distribution). Negative sampling rises from a technique named Noise Contrastive Estimation. NCE deals with the intractable normalization term in unnormalized parametric statistical models. Instead of computing the normalization term directly, NCE views the normalization term as a learn-able variable. Then, the problem of learning the model parameters and the normalization term is posed as a linear regression to discriminate true data samples and generated (negative) data samples. Such technique shows great time-performance trade-off.
Our method
Having introduced the background of representation learning for nodes in graphs based on word2vec, I will introduce our insight and attempt to improve Deepwalk. First, some analogues:
| Text | Graph | |
|---|---|---|
| Element | Word | Vertex |
| (Semi) Structure | Sentences, grammar | Connections, subgraphs (motifs) |
| Distribution | Power law (frequency) | Power law (degree) |
It is a common knowledge that “friends of friends are friends”. In network science, this phenomenon can be captured by the statistic of a subgraph in the shape of a triangle.
While simple friendships are represented by triangles, I am curious about other types of subgraphs and their functionalities in a network. More specifically, I am interested in how communities are formed. My hypothesis is that the simple recurring subgraphs (from now I call them motifs) are the building blocks for communities. Then, I investigated the z-scores for each directed size-3 motifs on a benchmark network dataset.
For each motifs in the vertical axis, I first compute its z-score for the whole network. Then, I exacted three sub-networks: Intra communities (2 networks for each label) and inter-communities (contains only inter-community links). The z-scores for each networks is reported in the figure above. We are particularly interested in motifs that has high z-scores for intra-communities, but low z-scores for inter-communities. These motifs are likely to be the patterns that build communities.
From this insight, we propose motifwalk. Our method aims to improve the result of DeepWalk through context manipulation. More conretely, instead of only perform random walk, we propose the concept of biased walk for context generation.
Definition: biased walk - A random walk in which the next vertices is chosen based on a pre-defined probability distribution.
Keeping the same learning process as DeepWalk, we propose to generate the artificial context that favor a certain motifs. In such way, nodes within a community are more likely to be closer in the embedding space. The motifs pattern for the biased random walk are selected based on some knowledge about the network or the z-score. Motif selection is so far the weakest point of my proposed model as I have not come up with a concrete method of motif selection.
Experiments
I conducted experiment on several benchmark networks. The f1-macro score for Blogcatalog3 and Cora is presented here:
The random walk on blogcatalog is the triangle motif, while on cora it is the bi-fan motif (size-4). The embedding is learned by a word2vec model implemented using tensorflow.


| Package | Description |
|---|---|
| org.bitcoinj.crypto |
The crypto package contains classes that work with key derivation algorithms like scrypt (passwords to AES keys),
BIP 32 hierarchies (chains of keys from a root seed), X.509 utilities for the payment protocol and other general
cryptography tasks.
|
| org.bitcoinj.wallet |
Classes that support the
Wallet , which knows how to find and save transactions relevant to
a set of keys or scripts, calculate balances, and spend money: the wallet has many features and can be extended
in various ways, please refer to the website for documentation on how to use it. |
| Modifier and Type | Method and Description |
|---|---|
static DeterministicKey |
HDKeyDerivation.createMasterPrivateKey(byte[] seed)
Generates a new deterministic key from the given seed, which can be any arbitrary byte array.
|
static DeterministicKey |
HDKeyDerivation.createMasterPrivKeyFromBytes(byte[] privKeyBytes,
byte[] chainCode) |
static DeterministicKey |
HDKeyDerivation.createMasterPubKeyFromBytes(byte[] pubKeyBytes,
byte[] chainCode) |
DeterministicKey |
DeterministicKey.decrypt(KeyCrypter keyCrypter,
org.spongycastle.crypto.params.KeyParameter aesKey) |
DeterministicKey |
DeterministicKey.decrypt(org.spongycastle.crypto.params.KeyParameter aesKey) |
DeterministicKey |
DeterministicKey.derive(int child)
Derives a child at the given index using hardened derivation.
|
DeterministicKey |
DeterministicHierarchy.deriveChild(List<ChildNumber> parentPath,
boolean relative,
boolean createParent,
ChildNumber createChildNumber)
Extends the tree by calculating the requested child for the given path.
|
static DeterministicKey |
HDKeyDerivation.deriveChildKey(DeterministicKey parent,
ChildNumber childNumber) |
static DeterministicKey |
HDKeyDerivation.deriveChildKey(DeterministicKey parent,
int childNumber)
Derives a key given the "extended" child number, ie.
|
DeterministicKey |
DeterministicHierarchy.deriveNextChild(com.google.common.collect.ImmutableList<ChildNumber> parentPath,
boolean relative,
boolean createParent,
boolean privateDerivation)
Extends the tree by calculating the next key that hangs off the given parent path.
|
static DeterministicKey |
HDKeyDerivation.deriveThisOrNextChildKey(DeterministicKey parent,
int childNumber)
Derives a key of the "extended" child number, ie.
|
static DeterministicKey |
DeterministicKey.deserialize(NetworkParameters params,
byte[] serializedKey)
Deserialize an HD Key with no parent
|
static DeterministicKey |
DeterministicKey.deserialize(NetworkParameters params,
byte[] serializedKey,
DeterministicKey parent)
Deserialize an HD Key.
|
static DeterministicKey |
DeterministicKey.deserializeB58(DeterministicKey parent,
String base58,
NetworkParameters params)
Deserialize a base-58-encoded HD Key.
|
static DeterministicKey |
DeterministicKey.deserializeB58(String base58,
NetworkParameters params)
Deserialize a base-58-encoded HD Key with no parent
|
DeterministicKey |
DeterministicKey.dropParent()
Returns the same key with the parent pointer removed (it still knows its own path and the parent fingerprint).
|
DeterministicKey |
DeterministicKey.dropPrivateBytes()
Returns the same key with the private bytes removed.
|
DeterministicKey |
DeterministicKey.encrypt(KeyCrypter keyCrypter,
org.spongycastle.crypto.params.KeyParameter aesKey) |
DeterministicKey |
DeterministicKey.encrypt(KeyCrypter keyCrypter,
org.spongycastle.crypto.params.KeyParameter aesKey,
DeterministicKey newParent) |
DeterministicKey |
DeterministicHierarchy.get(List<ChildNumber> path,
boolean relativePath,
boolean create)
Returns a key for the given path, optionally creating it.
|
DeterministicKey |
DeterministicKey.getParent() |
DeterministicKey |
DeterministicHierarchy.getRootKey()
Returns the root key that the
DeterministicHierarchy was created with. |
| Modifier and Type | Method and Description |
|---|---|
static DeterministicKey |
HDKeyDerivation.deriveChildKey(DeterministicKey parent,
ChildNumber childNumber) |
static DeterministicKey |
HDKeyDerivation.deriveChildKey(DeterministicKey parent,
int childNumber)
Derives a key given the "extended" child number, ie.
|
static HDKeyDerivation.RawKeyBytes |
HDKeyDerivation.deriveChildKeyBytesFromPrivate(DeterministicKey parent,
ChildNumber childNumber) |
static HDKeyDerivation.RawKeyBytes |
HDKeyDerivation.deriveChildKeyBytesFromPublic(DeterministicKey parent,
ChildNumber childNumber,
HDKeyDerivation.PublicDeriveMode mode) |
static DeterministicKey |
HDKeyDerivation.deriveThisOrNextChildKey(DeterministicKey parent,
int childNumber)
Derives a key of the "extended" child number, ie.
|
static DeterministicKey |
DeterministicKey.deserialize(NetworkParameters params,
byte[] serializedKey,
DeterministicKey parent)
Deserialize an HD Key.
|
static DeterministicKey |
DeterministicKey.deserializeB58(DeterministicKey parent,
String base58,
NetworkParameters params)
Deserialize a base-58-encoded HD Key.
|
DeterministicKey |
DeterministicKey.encrypt(KeyCrypter keyCrypter,
org.spongycastle.crypto.params.KeyParameter aesKey,
DeterministicKey newParent) |
void |
DeterministicHierarchy.putKey(DeterministicKey key)
Inserts a key into the heirarchy.
|
| Constructor and Description |
|---|
DeterministicHierarchy(DeterministicKey rootKey)
Constructs a new hierarchy rooted at the given key.
|
DeterministicKey(DeterministicKey keyToClone,
DeterministicKey newParent)
Clones the key
|
DeterministicKey(com.google.common.collect.ImmutableList<ChildNumber> childNumberPath,
byte[] chainCode,
BigInteger priv,
DeterministicKey parent)
Constructs a key from its components.
|
DeterministicKey(com.google.common.collect.ImmutableList<ChildNumber> childNumberPath,
byte[] chainCode,
org.spongycastle.math.ec.ECPoint publicAsPoint,
BigInteger priv,
DeterministicKey parent) |
DeterministicKey(com.google.common.collect.ImmutableList<ChildNumber> childNumberPath,
byte[] chainCode,
KeyCrypter crypter,
LazyECPoint pub,
EncryptedData priv,
DeterministicKey parent)
Constructs a key from its components.
|
DeterministicKey(com.google.common.collect.ImmutableList<ChildNumber> childNumberPath,
byte[] chainCode,
LazyECPoint publicAsPoint,
BigInteger priv,
DeterministicKey parent)
Constructs a key from its components.
|
| Modifier and Type | Field and Description |
|---|---|
protected DeterministicKey |
DeterministicKeyChain.Builder.watchingKey |
| Modifier and Type | Method and Description |
|---|---|
DeterministicKey |
Wallet.currentKey(KeyChain.KeyPurpose purpose)
Returns a key that hasn't been seen in a transaction yet, and which is suitable for displaying in a wallet
user interface as "a convenient key to receive funds on" when the purpose parameter is
KeyChain.KeyPurpose.RECEIVE_FUNDS . |
DeterministicKey |
KeyChainGroup.currentKey(KeyChain.KeyPurpose purpose)
Returns a key that hasn't been seen in a transaction yet, and which is suitable for displaying in a wallet
user interface as "a convenient key to receive funds on" when the purpose parameter is
KeyChain.KeyPurpose.RECEIVE_FUNDS . |
DeterministicKey |
Wallet.currentReceiveKey()
An alias for calling
Wallet.currentKey(org.bitcoinj.wallet.KeyChain.KeyPurpose) with
KeyChain.KeyPurpose.RECEIVE_FUNDS as the parameter. |
DeterministicKey |
DeterministicKeyChain.findKeyFromPubHash(byte[] pubkeyHash) |
DeterministicKey |
DeterministicKeyChain.findKeyFromPubKey(byte[] pubkey) |
DeterministicKey |
Wallet.freshKey(KeyChain.KeyPurpose purpose)
Returns a key that has not been returned by this method before (fresh).
|
DeterministicKey |
KeyChainGroup.freshKey(KeyChain.KeyPurpose purpose)
Returns a key that has not been returned by this method before (fresh).
|
DeterministicKey |
Wallet.freshReceiveKey()
An alias for calling
Wallet.freshKey(org.bitcoinj.wallet.KeyChain.KeyPurpose) with
KeyChain.KeyPurpose.RECEIVE_FUNDS as the parameter. |
DeterministicKey |
DeterministicKeyChain.getKey(KeyChain.KeyPurpose purpose)
Returns a freshly derived key that has not been returned by this method before.
|
protected DeterministicKey |
DeterministicKeyChain.getKeyByPath(ChildNumber... path)
Returns the deterministic key for the given absolute path in the hierarchy.
|
DeterministicKey |
Wallet.getKeyByPath(List<ChildNumber> path)
Returns a key for the given HD path, assuming it's already been derived.
|
protected DeterministicKey |
DeterministicKeyChain.getKeyByPath(List<ChildNumber> path)
Returns the deterministic key for the given absolute path in the hierarchy.
|
DeterministicKey |
DeterministicKeyChain.getKeyByPath(List<ChildNumber> path,
boolean create)
Returns the deterministic key for the given absolute path in the hierarchy, optionally creating it
|
DeterministicKey |
Wallet.getWatchingKey()
Returns a public-only DeterministicKey that can be used to set up a watching wallet: that is, a wallet that
can import transactions from the block chain just as the normal wallet can, but which cannot spend.
|
DeterministicKey |
DeterministicKeyChain.getWatchingKey()
An alias for
getKeyByPath(getAccountPath()) . |
DeterministicKey |
DeterministicKeyChain.markKeyAsUsed(DeterministicKey k)
Mark the DeterministicKey as used.
|
DeterministicKey |
DeterministicKeyChain.markPubHashAsUsed(byte[] pubkeyHash)
Mark the DeterministicKeys as used, if they match the pubkeyHash
See
DeterministicKeyChain.markKeyAsUsed(DeterministicKey) for more info on this. |
DeterministicKey |
DeterministicKeyChain.markPubKeyAsUsed(byte[] pubkey)
Mark the DeterministicKeys as used, if they match the pubkey
See
DeterministicKeyChain.markKeyAsUsed(DeterministicKey) for more info on this. |
| Modifier and Type | Method and Description |
|---|---|
List<DeterministicKey> |
Wallet.freshKeys(KeyChain.KeyPurpose purpose,
int numberOfKeys)
Returns a key/s that has not been returned by this method before (fresh).
|
List<DeterministicKey> |
KeyChainGroup.freshKeys(KeyChain.KeyPurpose purpose,
int numberOfKeys)
Returns a key/s that have not been returned by this method before (fresh).
|
List<DeterministicKey> |
DeterministicKeyChain.getKeys(KeyChain.KeyPurpose purpose,
int numberOfKeys)
Returns freshly derived key/s that have not been returned by this method before.
|
List<DeterministicKey> |
DeterministicKeyChain.getLeafKeys()
Returns leaf keys issued by this chain (including lookahead zone)
|
| Modifier and Type | Method and Description |
|---|---|
T |
MarriedKeyChain.Builder.followingKeys(DeterministicKey followingKey,
DeterministicKey... followingKeys) |
T |
MarriedKeyChain.Builder.followingKeys(DeterministicKey followingKey,
DeterministicKey... followingKeys) |
static Wallet |
Wallet.fromWatchingKey(NetworkParameters params,
DeterministicKey watchKey)
Creates a wallet that tracks payments to and from the HD key hierarchy rooted by the given watching key.
|
RedeemData |
MarriedKeyChain.getRedeemData(DeterministicKey followedKey)
Get the redeem data for a key in this married chain
|
RedeemData |
DeterministicKeyChain.getRedeemData(DeterministicKey followedKey)
Get redeem data for a key.
|
DeterministicKeyChain |
KeyChainFactory.makeWatchingKeyChain(Protos.Key key,
Protos.Key firstSubKey,
DeterministicKey accountKey,
boolean isFollowingKey,
boolean isMarried)
Make a watching keychain.
|
DeterministicKeyChain |
DefaultKeyChainFactory.makeWatchingKeyChain(Protos.Key key,
Protos.Key firstSubKey,
DeterministicKey accountKey,
boolean isFollowingKey,
boolean isMarried) |
DeterministicKey |
DeterministicKeyChain.markKeyAsUsed(DeterministicKey k)
Mark the DeterministicKey as used.
|
static DeterministicKeyChain |
DeterministicKeyChain.watch(DeterministicKey accountKey)
Creates a key chain that watches the given account key.
|
static DeterministicKeyChain |
DeterministicKeyChain.watchAndFollow(DeterministicKey watchKey)
Creates a deterministic key chain with the given watch key and that follows some other keychain.
|
T |
DeterministicKeyChain.Builder.watchingKey(DeterministicKey watchingKey) |
| Modifier and Type | Method and Description |
|---|---|
T |
MarriedKeyChain.Builder.followingKeys(List<DeterministicKey> followingKeys) |
| Constructor and Description |
|---|
DeterministicKeyChain(DeterministicKey watchingKey)
Creates a deterministic key chain that watches the given (public only) root key.
|
DeterministicKeyChain(DeterministicKey watchKey,
boolean isFollowing)
Creates a deterministic key chain with the given watch key.
|
KeyChainGroup(NetworkParameters params,
DeterministicKey watchKey)
Creates a keychain group with no basic chain, and an HD chain that is watching the given watching key.
|
Copyright © 2022. All rights reserved.


--- layout: post title: How to mount Google Drive on your Linux(Ubuntu) system date: 2015-06-04 15:02:47.000000000 +02:00 type: post parent_id: '0' published: true password: '' status: publish categories: - Bash - Linux - Ubuntu tags: [] meta: _publicize_done_external: a:1:{s:8:"facebook";a:1:{i:3508581;s:38:"https://facebook.com/10205226754283377";}} _rest_api_published: '1' _rest_api_client_id: "-1" geo_latitude: "-33.942849" geo_longitude: '18.489235' geo_address: Oude Molen Village, Cape Town, South Africa geo_public: '1' _publicize_job_id: '11328555960' _publicize_done_3700952: '1' _wpas_done_3508581: '1' _edit_last: '49460244' _wpas_skip_3508581: '1' _oembed_f1b82bc4f9d81b467434a31f18d70fe9: "{{unknown}}" _oembed_339df8d4964e65efb3a40c01f7880f51: "{{unknown}}" _oembed_a44d611370cc9cce406340bea3dc408e: "{{unknown}}" _oembed_a1d639412ded1c9962b161398ebb258c: "{{unknown}}" author: login: mpho112 email<EMAIL_ADDRESS>display_name: Mpho first_name: '' last_name: '' ---
I have always been a fan of cloud storage as anything can happen on my mechanical harddrive, but now that I have completely migrated to Ubuntu and having to realise that the is no support whatsoever for Google drive applications, I was on a quest to find a working and reliable on. Then I stumbled upon Google Drive Ocamlfuse which is a FUSE filesystem backend for Google Drive which you can use to mount your Google Drive under Linux.
Link: https://github.com/astrada/google-drive-ocamlfuse
Installation
[sourcecode language="bash"]
sudo add-apt-repository ppa:alessandro-strada/ppa
sudo apt-get update
sudo apt-get install google-drive-ocamlfuse
[/sourcecode]
Usage
run:
[sourcecode language="bash"]
google-drive-ocamlfuse
[/sourcecode]
Make sure you are connected to the internet as this will open your browser and require access to your Google Drive. Click "Allow" and this will give the application access to your files.
Mounting
Now we mount GDrive to your system.
run:
[sourcecode language="bash"]
mkdir -p ~/Google_Drive
google-drive-ocamlfuse ~/Google_Drive
[/sourcecode]
That's about it, unless you want to be heroic and modify changes in the configuration file which is here:
[sourcecode language="bash"]
~/.gdfuse/default/config
[/sourcecode]
Automount
To mount Google Drive upon startup, run:
[sourcecode language="bash"]
crontab -e
[/sourcecode]
and insert
[sourcecode language="bash"]
@reboot google-drive-ocamlfuse ~/Google_Drive
[/sourcecode]
Or go here: https://github.com/astrada/google-drive-ocamlfuse/wiki/Automounting
Done!!!


Sourukirā is a game development company with roughly around 100 members on our team. We are the designers behind games like Zack and Zack's Rebirth. We are located in Montreal Canada. We serve by our goal: For the gamers, by the gamers and only create games for gamers, for non-gamers, for everyone. We promise games that will revolutionize the gaming industry!
Sourukirā's loose translation is Soul Killer, which was Adriaan Rossouw's first gamertag in the olden days. The love for anime and Japanese culture was the reason behind the Japanese translated Soul Killer. The team agreed that the game company should stick to it's roots by creating games close to the CEO's heart since Sourukirā is a game development company that creates games for the people and not for the money
Sourukira was found by Adriaan Rossouw in 2026 when he invested most of his earnings in a building that would later become the HQ of the game Developement company, Sourukira. Sourukirā formerly had the name Rogue Game Development but when the company grew bigger, the company decided together that the rebrand name would be Sourukirā.


Still a "Student".
I <3 Git.
I <3 Github.
Big Repos !<3 Git.
Google, Facebook, etc.
!Large Files
Good one, and supported, Haskell.
Yeah, its Ruby!
Github uses this.
Umm, yeah.
OO Read/Write Access to Git.
Use it for Git Repo Access for anything.
Large Repos, {5-6 GB+}
But Developers work only on some.
Grit+git-media+Cloud FTW!


| DOSE: |
6 hits |
smoked |
Cannabis |
(plant material) |
Having never smoked weed before I didn't really know what to expect. I acted as if I'd done it quite a few times before in front of the other guys because I was embarressed to say its my first time. I am 16. This is how it went, me & 2 other guys began taking hits from the bong at 9:45pm. I was surprised how well I coped with the smoke, I was afraid I would cough & choke. The supplier warned us that it was rather potent weed than most, I don't know what the effects of normal weed are but I think this stuff was really strong. 15 minutes went by & I wasn't really noticing anything. I started to wonder if maybe I'm not as affected by weed as others, because it seemed like the other 2 had already got a bit stoned, as they were acting really slow & their conversation didn't make a lot of sense. But I was very wrong.
It did kick in somewhere around 10pm & it hit me hard. I remember not being able to get much breath in. The world around me went very slow. I could no longer move or talk without huge effort. When I forced myself to talk my own voice seemed distant and unfamiliar. My entire body gradually became numb & tingly. It seemed my eyes could only focus on 1 small area at a time, to move my eyes & look somewhere else took a lot of effort. Nothing really made any sense by this stage. I had a pleasant feeling all over but at the same time I felt very worried, partly because I wasn't sure if was breathing anymore!
During this time 2 girls arrived, I don't remember who they were I think they were friends of 1 of the guys. Shortly after that a group of about 5 guys arrived, I didn't know any of them, plus they were all drunk. I remember each of the new people that arrived introduced themselves to me & I tried my best not to be rude, but I just wanted to ignore them because just to say 'hey' was a tremendous effort. I managed to get out a half-hearted 'hi' to most of them I think. I was quite disappointed because I really wanted to talk to the girls because I remember them looking at me, but I couldn't bring myself to talk & I couldn't think what to say.
Throughout the entire period there was a dull, repetitive music being played which had a trance-like effect & gave me an overwhelming feeling to move to the beat. But I eventually gave up because I couldn't move fast enough. My friend and I had to leave at some point around 11ish, so up we got & I was trying desperately to control myself, but I remember walking like I was very drunk, which worried me because I was afraid I might knock something over in the room. As we left I attempted to say 'later guys' and 'cheers'(for the weed), but it probably came out in an incomprehendable murmur.
The moment we started walking away and down the street back to my friend's place I started feeling less stoned. I was able to talk & walk straight again. Although I was afraid that my friend's mum would know we're stoned because our clothes had a strong stench of weed-smoke and I couldn't talk much. But we got home & luckily she was in bed. We washed our mouths out with mouthwash and sprayed all our clothing in deodorant. Getting to sleep was easy. It felt really nice to lye in bed & snuggle under the warm covers. The next day I expected to be totally back to normal. I was still stoned for most of that next day! Not much, though enough that I could notice it. It seemed to come & go throughout the day. It felt really good though. I think I'll do it again in a week or so.
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.


WITNESS LIST Natural Resources Committee March 16, 1999-2:00P SB 513 FOR: Cornelius, Lester (Optical Technology Corporation - President), Oyster Bay, NY Gutierrez, Amador (Goodland Co. - Owner), Brownsville Judge, Patricia (Recharger Magazine - Executive Editor), Las Vegas, NV Nobles, Warren (Quality Business Solutions - Owner), Mesquite Wendt, Mike (Texas Association of Cartridge Remanufacturers - President), El Paso AGAINST: Kunz, Richard (Lexmark International, Inc. - Counsel), Lexington, KY Schmidt, Thomas (Lexmark International, Inc. - General Manager - Juarez plant), El Paso ON: Treadway, Tom (General Services Commission - Executive Director), Austin Registering, but not testifying: For: Cowman, Robert (TonerPlus, Inc. - Marketing Director), Austin Font, Rosette (Lasertone, Owner), Houston Fulmer, Mark (Alpha Laser Recharge, Inc. - President), Houston Gordon, Ronald (Gordon's Office Service - Owner), Bryan Graesser, David (Full Service Toner Supply, Inc. - President), Katy Jessup, Charles (Alpha Laser's / Texas Association Cartridge Remanufacturers), Meadows Place Nobles, Cynthia (Quality Business Solutions - Owner), Mesquite Thompson, Rickey (Southwestern Laser - President), Houston Wendt, Judy (Laser Tech, Owner), El Paso Against: Lang, Betsy (Lexmark International - GM Worldwide Supplies Marketing), Lexington, KY On: Schlimper, Paul (General Services Commission - Special Projects Manager), Austin SB 707 FOR: Glacken, Pamela (Association of Electric Companies of Texas - Member Company), Dallas ON: MacRae, J. Rollin (Texas Parks & Wildlife Department - Wetlands Conservation), Austin Shinkawa, Paul (Texas Parks & Wildlife Department - counsel), Austin Registering, but not testifying: For: Grover, Jim (Sprint - Regulatory Manager), Austin SB 873 FOR: Baker, Pamela (Environmental Defense Fund - Fisheries Biologist), Austin Lowerre, Richard (Aransas County and Texas Shrimp Association), Austin Turner, Franklin (Coalition for the Protection of Copano Bay - Chairman), Rockport ON: Hubert, Martin (Department of Agriculture - Deputy Commissioner), Austin Registering, but not testifying: For: Alvarez, Raul (Sierra Club - Lone Star Chapter), Austin Ingram, Dick (Coastal Conservation Association - Attorney), Austin On: King, Jack (Texas Parks & Wildlife Department), Austin Ray, Michael (Texas Parks & Wildlife Department), Austin Silcox, Raenell (Texas Parks & Wildlife Department - attorney), Austin Weber, Tom (TNRCC - Manager/Standards & Assessment), Austin SB 874 ON: Patton, Daniel (Texas Parks & Wildlife Department - Infrastructure Division), Austin Registering, but not testifying: On: Doran, Judith (Texas Parks & Wildlife Dept. - Attorney), Austin


Several of the resources in Congress has a /stream-endpoint which allows for connection through a Websocket connection. Below you will find a curl example for listening in on data on the selected application. To make it work you'd need to provide an API key with the correct permissions which can be created under the API management tab.


Excalidraw Libraries
A directory of public libraries that you can easily add to Excalidraw.
Follow the instructions if you want to add your own library into this list.
All the following libraries are under MIT License.
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