World Class
The physics world
Constructor
World
()
Item Index
Methods
- add deprecated
- addConstraint
- addContactMaterial
- addEventListener
- addMaterial
- clearForces
- collisionMatrixTick
- dispatchEvent
- getContactMaterial
- hasEventListener
- numObjects deprecated
- raycastAll
- raycastAny
- raycastClosest
- rayTest deprecated
- remove deprecated
- removeBody
- removeConstraint
- removeEventListener
- step
- step
Methods
addEventListener
-
type
-
listener
Add an event listener
Parameters:
-
type
String -
listener
Function
Returns:
The self object, for chainability.
clearForces
()
Sets all body forces in the world to zero.
collisionMatrixTick
()
Store old collision state info
dispatchEvent
-
event
Emit an event.
Parameters:
-
event
Object-
type
String
-
Returns:
The self object, for chainability.
getContactMaterial
-
m1
-
m2
Get the contact material between materials m1 and m2
Returns:
The contact material if it was found.
hasEventListener
-
type
-
listener
Check if an event listener is added
Parameters:
-
type
String -
listener
Function
Returns:
numObjects
()
Number
deprecated
Get number of objects in the world.
Returns:
raycastAll
-
from
-
to
-
options
-
callback
Ray cast against all bodies. The provided callback will be executed for each hit with a RaycastResult as single argument.
Parameters:
Returns:
True if any body was hit.
raycastAny
-
from
-
to
-
options
-
result
Ray cast, and stop at the first result. Note that the order is random - but the method is fast.
Parameters:
-
from
Vec3 -
to
Vec3 -
options
Object-
[collisionFilterMask=-1]
Number optional -
[collisionFilterGroup=-1]
Number optional -
[skipBackfaces=false]
Boolean optional -
[checkCollisionResponse=true]
Boolean optional
-
-
result
RaycastResult
Returns:
True if any body was hit.
raycastClosest
-
from
-
to
-
options
-
result
Ray cast, and return information of the closest hit.
Parameters:
-
from
Vec3 -
to
Vec3 -
options
Object-
[collisionFilterMask=-1]
Number optional -
[collisionFilterGroup=-1]
Number optional -
[skipBackfaces=false]
Boolean optional -
[checkCollisionResponse=true]
Boolean optional
-
-
result
RaycastResult
Returns:
True if any body was hit.
rayTest
-
from
-
to
-
result
Raycast test
Parameters:
-
from
Vec3 -
to
Vec3 -
result
Function | RaycastResult
removeEventListener
-
type
-
listener
Remove an event listener
Parameters:
-
type
String -
listener
Function
Returns:
The self object, for chainability.
step
-
dt
-
[timeSinceLastCalled]
-
[maxSubSteps=10]
Step the physics world forward in time.
There are two modes. The simple mode is fixed timestepping without interpolation. In this case you only use the first argument. The second case uses interpolation. In that you also provide the time since the function was last used, as well as the maximum fixed timesteps to take.
Parameters:
-
dt
NumberThe fixed time step size to use.
-
[timeSinceLastCalled]
Number optionalThe time elapsed since the function was last called.
-
[maxSubSteps=10]
Number optionalMaximum number of fixed steps to take per function call.
Example:
// fixed timestepping without interpolation
world.step(1/60);
step
-
dt
Step the simulation
Parameters:
-
dt
Number
Properties
allowSleep
Boolean
Makes bodies go to sleep when they've been inactive
bodies
Array
constraints
Array
contactmaterials
Array
contactMaterialTable
TupleDictionary
Used to look up a ContactMaterial given two instances of Material.
contacts
Array
All the current contacts (instances of ContactEquation) in the world.
defaultContactMaterial
ContactMaterial
This contact material is used if no suitable contactmaterial is found for a contact.
doProfiling
Boolean
dt
Number
Currently / last used timestep. Is set to -1 if not available. This value is updated before each internal step, which means that it is "fresh" inside event callbacks.
materials
Array
All added materials
profile
Object
quatNormalizeFast
Boolean
Set to true to use fast quaternion normalization. It is often enough accurate to use. If bodies tend to explode, set to false.
quatNormalizeSkip
Number
How often to normalize quaternions. Set to 0 for every step, 1 for every second etc.. A larger value increases performance. If bodies tend to explode, set to a smaller value (zero to be sure nothing can go wrong).
stepnumber
Number
Number of timesteps taken since start
subsystems
Array
time
Number
The wall-clock time since simulation start


Christopher Bennett
About
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Portfolio
Portfolio
Hangman
RPG Game
Trivia Game
Info Widget
Rock Paper Scissors


|
SoundFontInfoLib
2.21.6
Library for parsing and rendering SF2 files
|
Maintains a buffer of PCM samples which is used to save samples from an upstream node. More...
#include <InputBuffer.hpp>
Public Member Functions | |
| void | allocateBuffers (AVAudioFormat *format, AUAudioFrameCount maxFrames) |
| Set the format of the buffer to use. More... | |
| void | releaseBuffers () |
| Forget any allocated buffers. More... | |
| AUAudioUnitStatus | pullInput (AudioUnitRenderActionFlags *actionFlags, AudioTimeStamp const *timestamp, AVAudioFrameCount frameCount, NSInteger inputBusNumber, AURenderPullInputBlock pullInputBlock) |
| Obtain samples from an upstream node. More... | |
| void | prepareBufferList (AVAudioFrameCount frameCount) |
| Update the input buffer to reflect current format. More... | |
| AudioBufferList * | mutableAudioBufferList () const |
| Obtain a pointer to a mutable version of the internal channel buffers. More... | |
| BufferFacet & | bufferFacet () |
| Obtain the BufferFacet that manages the held AudioBufferList and provides a std::vector view of them. More... | |
| size_t | channelCount () const |
| Obtain the number of input channels. More... | |
| AUValue * | operator[] (size_t index) const |
| Obtain the channel buffer. More... | |
Maintains a buffer of PCM samples which is used to save samples from an upstream node.
Note that despite its name, there are multiple sample buffers held within, one for each channel of input.
|
inline |
Set the format of the buffer to use.
| format | the format of the samples |
| maxFrames | the maximum number of frames to be found in the upstream output |
References SF2::Render::BufferFacet::setBufferList().
|
inline |
Obtain the BufferFacet that manages the held AudioBufferList and provides a std::vector view of them.
|
inline |
Obtain the number of input channels.
References SF2::Render::BufferFacet::channelCount().
|
inline |
Obtain a pointer to a mutable version of the internal channel buffers.
|
inline |
Obtain the channel buffer.
|
inline |
Update the input buffer to reflect current format.
| frameCount | the number of frames to expect to place in the buffer |
References channel.
Referenced by pullInput().
|
inline |
Obtain samples from an upstream node.
Output is stored in internal buffer.
| actionFlags | render flags from the host |
| timestamp | the current transport time of the samples |
| frameCount | the number of frames to process |
| inputBusNumber | the bus to pull from |
| pullInputBlock | the function to call to do the pulling |
References prepareBufferList().
|
inline |
Forget any allocated buffers.
References SF2::Render::BufferFacet::release().


Omino
Omino is an algorithm experiment based on sentence's features.
It tries to understand the user's emotions when it types certain words.
The scenario could be applicable on Social media.
To give an idea it checks words like: LOL, ROTFL, ahah, haha, !!!"
or "I WANT MY MONEY BACK!!!!"
Your emoticon should be


--- layout: moviri-release title: Demos - Joined Model recline-deps: true root: ../../ ---
var dataset1 = new recline.Model.Dataset({ records:[ {country:'Italy', gender:"Female", age:5}, {country:'Italy', gender:"Male", age:13}, {country:'Spain', gender:"Male", age:14} ], fields:[ {id:'country', type:'string'}, {id:'gender', type:'string'}, {id:'age', type:'integer' } ] });
var joined1 = new recline.Model.JoinedDataset( { model: dataset1, join: [ { id: "ds1", model: dataset2, joinon:["country", "gender"]}, { id: "ds2", model: dataset3, joinon:["country", "gender"]} ], joinType: "left" });


MS:
1) Knowing the car’s exact location ; being able to perceive the car’s immediate environment ; making the correct driving decisions to get from A to B .
2) A variety of sensors feed real-time data into the on-board control system which makes the driving decisions. Provides the data for constructing a detailed picture of the immediate environment.
3) Three satellites ; signals’ traveling time ; Calculate the distance ; Satellites’ own coordinates ; Intersection point of three spheres ;
Discussions


Pigment
Programming Language, Designed
goals
Pigment is an experiment in programming language design. We're taking modern programming language research and putting it in a thoroughly designed, interactive environment in the browser.
follow
Participate in development on Github or follow @dino_joel for updates.
research
Pigment is built on the work of many mathematicians and computer scientists. Notably - the Epigram team, who built the original implementation; the dependent types community, who continue to hammer out the theory; and the larger functional programming community.


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--- layout: post status: publish published: true title: VS2005 Hanging on XML Comments author: display_name: Tomas Restrepo login: tomasr email<EMAIL_ADDRESS>url: http://winterdom.com/ author_login: tomasr author_email<EMAIL_ADDRESS>author_url: http://winterdom.com/ wordpress_id: 450 wordpress_url: http://winterdom.com/2007/07/vs2005hangingonxmlcomments date: '2007-08-01 19:12:22 +0000' date_gmt: '2007-08-01 19:12:22 +0000' categories: - ".NET" tags: [] comments: - id: 316 author: lb author_email<EMAIL_ADDRESS>author_url: http://secretGeek.net date: '2007-08-01 00:43:23 +0000' date_gmt: '2007-08-01 00:43:23 +0000' content: | i just like that you're developing straight on the server ;-) vs2005 sure is flaky. - id: 317 author: BS author_email<EMAIL_ADDRESS>author_url: '' date: '2007-08-09 01:20:59 +0000' date_gmt: '2007-08-09 01:20:59 +0000' content: | Have you been able to sort out the trouble with VS2005 hanging when typing the '<' inside a CDATA tag? I'm experiencing the same problem, but have not so far figured out why this is happening, or how to solve it. Best regards BS - id: 318 author: Paul Huff author_email<EMAIL_ADDRESS>author_url: '' date: '2007-09-28 14:29:27 +0000' date_gmt: '2007-09-28 14:29:27 +0000' content: | Yes!! I just had that problem! Wouldn't that be the point of having CDATA available...to put xml that is supposed to come out as a string literal? I had to kill the process and lost some code. I've had WAY TOO MANY issues with VS 2005. 2003 wasn't near this bad. Hopefully 2008 fixes this stuff. An interesting point: should this worry us about using Microsoft's XML parser? ---
While working on my PipelineTesting library code, I'm running into a pretty annoying problem: Visual Studio will hang (with 100% processor usage) every time I try to type a '<' inside a section in an XML comment (specifically inside the
Has anyone else seen this before? This is VS2005 with SP1, btw, running on Windows Server 2003.


|
Quick Links: |
Provide value-semantic type and utilities for a BlazingMQ queue. More...
| bmqt::Uri | value-semantic type representing a URI |
| bmqt::UriParser | utility to parse a string into a URI |
| bmqt::UriBuilder | builder mechanism to create a URI |
bmqt::Uri
representing a URI for a BlazingMQ queue. A bmqt:Uri
can be built by parsing from a string representation, using the bmqt::UriParser
, or built using the bmqt::UriBuilder
. bmq://ts.trades.myapp/my.queue bmq://ts.trades.myapp.~bt/my.queue bmq://ts.trades.myapp/my.queue?id=foo
[-a-zA-Z0-9\\._]+
). The domain may be[-a-zA-Z0-9_~\\.]+
). The queue name must be less than bmqt::Uri::k_QUEUENAME_MAX_LENGTH
characters long. The URI may contain an optional query with a key-value pair. Currently supported keys are:
initialize
method of the UriParser
. This call is only needed one time; you can call it when your task starts. bmq
library takes care of that, so users of bmq
don't have to explicitly do it themselves. Then, parse a URI string created on the stack to populate a Uri
object. The parse function takes an optional error string which is populated with a short error message if the URI is not formatted correctly. bsl::string input = "bmq://my.domain/queue"; bmqt::Uri uri(allocator); bsl::string errorDescription; int rc = bmqt::UriParser::parse(&uri, &errorDescription, input); if (rc != 0) { BALL_LOG_ERROR << "Invalid URI [error: " << errorDescription << "]"; } assert(rc == 0); assert(error == ""); assert(uri.scheme() == "bmq"); assert(uri.domain() == "my.domain"); assert(uri.queue() == "queue");
Uri
object with a string representation of the URI and an allocator. bmqt::Uri uri("bmq://my.domain/queue", allocator); assert(uri.scheme() == "bmq"); assert(uri.domain() == "my.domain"); assert(uri.queue() == "queue");


Plain Select
Foobar
Normal Chosen Select
Foobar
Chosen Remote Source Select Minimal - Single Select
Foobar
Chosen Remote Source Select Minimal- Multiple Select
Foobar
Chosen Remote Source Select Kitchen Sink - Single Select
Foobar


The other night, I really wanted to smoke some weed, but I had none. So I went looking in my herbal cabinet. There was some yerba in there and I had read online that it's a decent high, so I packed a bowl, and lit up.
It took about 5-10 minuets to start to feel anything. The high was very similar to weed. I had that same feeling in my shoulders that I get when I smoke weed. Anyway, I was concerned because after about 5 minutes, I just kept getting higher, and higher for about 15 minutes. The only real difference between a weed high and the yerba high is that I can focus a little better, and my brain actually can function better, but I'm still really spaced out!
The next morning I still felt it! I guess this is my new back-up weed!
Overall, a good high, good up-time, and no withdrawls or crashes!
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.


|
Simply dummy text of the printing, typesetting
industry. Lorem Ipsum been the industry's
standard dummy text ever since the 1500s, when
an unknown printer took a gallery of type and
scrambled it to make a type specimen book. An
unknown printer took a gallery of type and
scrambled it to make.
|


Total Available Cash: $
Apples
Oranges
Bananas
Grapes
Price:
Price:
Price:
Price:
Buy Fruit
Buy Fruit
Buy Fruit
Buy Fruit
Average Purchase Price:
Average Purchase Price:
Average Purchase Price:
Average Purchase Price:
Sell Fruit
Sell Fruit
Sell Fruit
Sell Fruit


Time & date from minute.js here
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pip_services3_commons.refer.DependencyResolver module¶
pip_services3_commons.refer.DependencyResolver¶
Dependency resolver component implementation
| copyright: | Conceptual Vision Consulting LLC 2018-2019, see AUTHORS for more details. |
|---|---|
| license: | MIT, see LICENSE for more details. |
-
class
pip_services3_commons.refer.DependencyResolver.
DependencyResolver
(config=None, references=None)¶ Bases:
pip_services3_commons.config.IReconfigurable.IReconfigurable
,pip_services3_commons.refer.IReferenceable.IReferenceable
Helper class for resolving component dependencies. The resolver is configured to resolve named dependencies by specific locator. During deployment the dependency locator can be changed.
This mechanism can be used to clarify specific dependency among several alternatives. Typically components are configured to retrieve the first dependency that matches logical group, type and version. But if container contains more than one instance and resolution has to be specific about those instances, they can be given a unique name and dependency resolvers can be reconfigured to retrieve dependencies by their name.
Configuration parameters
- dependencies:
- [dependency name 1]: Dependency 1 locator (descriptor)
- …
- [dependency name N]: Dependency N locator (descriptor)
- References:
- References must match configured dependencies.
- Example:
- class MyComponent(IConfigurable, IReferenceable):
_dependencyResolver = None _persistence = None
- def __init__(self):
- self._dependencyResolver.put(“persistence”, new Descriptor(“mygroup”, “persistence”, “*”, “*”, “1.0”))
- def configure(self, config):
- self._dependencyResolver.configure(config)
- def set_references(self, references):
- self._dependencyResolver.setReferences(references) self._persistence = self._dependencyResolver.get_one_required(“persistence”)
component = MyComponent() component.configure(ConfigParams.from_tuples( “dependencies.persistence”, “mygroup:persistence:*:persistence2:1.0”))
component.setReferences(References.from_tuples(Descriptor(“mygroup”,”persistence”,”*”,”persistence1”,”1.0”), MyPersistence(), Descriptor(“mygroup”,”persistence”,”*”,”persistence2”,”1.0”), MyPersistence() // This dependency shall be set))
-
configure
(config)¶ Configures the component with specified parameters.
Parameters: config – configuration parameters to set.
-
find
(name, required)¶ Finds all matching dependencies by their name.
Parameters: - name – the dependency name to locate.
- required – true to raise an exception when no dependencies are found.
Returns: a list of found dependencies
-
static
from_tuples
(*tuples)¶ Creates a new DependencyResolver from a list of key-value pairs called tuples where key is dependency name and value the depedency locator (descriptor).
Parameters: tuples – a list of values where odd elements are dependency name and the following even elements are dependency locator (descriptor)
Returns: a newly created DependencyResolver.
-
get_one_optional
(name)¶ Gets one optional dependency by its name.
Parameters: name – the dependency name to locate. Returns: a dependency reference or null of the dependency was not found
-
get_one_required
(name)¶ Gets one required dependency by its name. At least one dependency must present. If the dependency was found it throws a [[ReferenceException]]
Parameters: name – the dependency name to locate. Returns: a dependency reference
-
get_optional
(name)¶ Gets all optional dependencies by their name.
Parameters: name – the dependency name to locate. Returns: a list with found dependencies or empty list of no dependencies was found.
-
get_required
(name)¶ Gets all required dependencies by their name. At least one dependency must be present. If no dependencies was found it throws a [[ReferenceException]]
Parameters: name – the dependency name to locate. Returns: a list with found dependencies.
-
put
(name, locator)¶ Adds a new dependency into this resolver.
Parameters: - name – the dependency’s name.
- locator – the locator to find the dependency by.
-
set_references
(references)¶ Sets the component references. References must match configured dependencies.
Parameters: references – references to set.


March 25
Therefore if any man be in Christ, he is a new creature: old things are passed away; behold, all things are become new.
2 Corinthians 5:17
Resurrection. What do you think of when you hear that word? Most people think of the past. Of a stone rolled away. An empty tomb. And a risen Lord.
Praise God, Jesus is alive today!
What we don't fully understand is this: He's not the only One who has been resurrected. We've been resurrected too!
We were spiritually resurrected the day we made the Lord Jesus Christ the Lord of our lives. That day we passed from death to life. The greater part of your resurrection has already happened!
Think about it. When you made Jesus Christ the Lord of your life, the Spirit of God hovered over you. The glory of the Lord came into your being. And that glory consumed the old, sinful man that you were. That old man died. And in his place a new creature was born.
Oh yes, there will be a day when the earthly body you live in will be raised and glorified--but you don't have to wait until then to be free from sin and from the sickness and poverty and failure that goes with this natural world. You're free from all that right now!
You may be sitting there thinking, "Well, if I'm so free, why can't I quit smoking? Why can't I lose this weight? Why am I always sick?"

So, today I want you to begin considering yourself alive! Begin thinking of yourself as one who already has the life of God instead of an earthly being who's waiting for the resurrection. Consider yourself dead to sin and alive to the power of Jesus. You'll find yourself living a whole new life today!
Scripture Reading: Romans 8:1-14


My biggest hobby is video games. I'm also a passionate web integrator who love learning computing programmation especially front-end development. I prefer Javascript language
I love front-end development
You can contact me in: my Github for CodeSchool


Weasel coffee, also known as Weasel dung coffee, is a specialty coffee that is considered the world's rarest beverage. This coffee is widely grown in Indonesia, particularly on the islands of Sumatra, Java, and Sulawesi. The term "Kopi Luwak" refers to a sort of nut produced by a spotted civet that consumes coffee berries before excreting, drying, and processing them. The term Kopi Luwak is derived from the Indonesian word kopi, which signifies coffee. Luwak is the name of a region in the Indonesian island of Java, as well as a civet that lives there. Spotted civets may be found across Southeast Asia, including Indonesia, the Philippines, Vietnam, and southern China. Civets are raised in Vietnam to create this unique coffee.
"It has an earthy flavor, a moldy fragrance, is calming and syrupy, rich as if conveying the sound of the jungle and chocolate", John Cleese stated


| DOSE: T+ 0:00 |
6.25 mg |
oral |
4-Acetoxy-MiPT |
(powder / crystals) |
| T+ 0:30 |
6.25 mg |
oral |
4-Acetoxy-MiPT |
(powder / crystals) |
| T+ 1:10 |
6.25 mg |
oral |
4-Acetoxy-MiPT |
(powder / crystals) |
| T+ 2:00 |
6.25 mg |
oral |
4-Acetoxy-MiPT |
(powder / crystals) |
I recently ordered some 4-ACO-MiPT fumarate after hearing that its action was very similar to psilocybin, and that it was relatively mild. It seemed like a good RC to start with (my only other RC experience was a poor AMT experience a couple years ago). I received the package tonight and eyeballed (spare me, I know it's not very reliable) the 100mg order into 8 piles (each 12.5mg). At 8:15 MDT (10 minutes ago) I ingested 1/2 of one of the piles, approximately 6.25mg (6.25 to be safe).
t+0:00 - Parachuted 6.25 4-ACO-MiPT on a fairly empty stomach (last ate 3 hours ago). I am in my dorm room and since it's thanksgiving break nobody is around. I feel excited and jittery, but this is par for the course when trying new drugs.
t+0:30 - Definitely some threshold effects, muscle rubberiness and tingling on turns, slight heartburn, slight nausea, general threshold-type effects. Ingesting 6.25mg more slightly ahead of schedule because I think I can see the nature of the substance now and 6.25 should be safe.
t+0:50 - effects becoming more prominent now and it is difficult to communicate the exact nature of them, but I feel very 'spaced out,' the rubberiness of muscles has increased and sounds are altered, for certain. Though open eye visuals are almost non-existent I'm displaying an almost child-like fascination in such simple phenomena as the fact that when I turn off a light switch the light in the room changes. Very positive so far, will keep posted.
t+1:10 took another 6.25 because reports indicate that 13-20 is common dose and I'm feeling confident with the effects thus far that I can handle whatever this drug can throw at me (and that I would like to have the opportunity to handle it). Effects have scaled up since last post, motor control is at a minus and I'm starting to see definite colors in my vision, things are vibrating and vocalizing/putting into words of my thoughts is becoming difficult (apologies for the stream of consciousness like post, will try to compose myself next time). Very good body high going right now, just pleasant euphoria (would probably apply similar terms to the mental high, a type of euphoric fuzziness).
t+1:50 - Effects very significant at this point, went for a walk down the hall and the sides were subtly warping into concavity and convexity. Everything with shadows seems to be suspect to this brand of visual disturbance, with evenly lit areas less prone. Orgasm is very possible and occured in what appears as a stop-frame sequence in retrospect (in my memory).
Also memories take the flavor of whatever I am currently looking at, for instance the banner ad at the top of this page is in watercolor so all my memories are remembered with a faintly watercolored hue. Again this is mental and not overtly visual (so far there is nothing of that).
Conversation at this point seems impossible but while walking through the hallway stop and spoke to my RA (a swell guy) wished him a happy thanksgiving and was 100% fine, must just be a mental aversion.
Eating chips is lackluster, very ignorable. I think I might like to see some bright lights and that I might go for a walk outside. I will post a report later.
t+2:00 – another 6.25mg dose was taken at this point.
t+2:00-2:45: I walked down a way until I found some random rock that i decided to sit on and stared up at the sky. to my NE and NW were street lamps that when I looked up seemed to project their light into the sky building a warping and transforming red and blue and black light show, the pine trees assumed the shape of essential cones and projected contours of inverse cones directly over their termination points.
I borrowed a friend's mp3 player. briefly my taste in music is electronic so I was just bouncing around his bad (to me ) playlist when I saw 'wyclef'. I like Wyclef Jean so I decided to listen to whatever track this was. It was 'Hips Don't Lie' by Shakira (featuring Wyclef only), it's the stupidest song but there is a (I think?) trumpet part in it that was just the most beautiful melody I have ever heard, that sort of catapulted me (as though the conical projections didn't give you a clue) into this empatheogen-like thing where all I could do (can do) is smile.
My roommate came back and I tried to talk to him but couldn't really get my thoughts together and just ended up saying 'good' 5-20 times.
Mentally: since I had borrowed my friend's MP3 player I was extremely concerned (but not in a way that hurt my experience) with its wellbeing and the all-in-all way I composed myself, I felt mentally the equivalent (this is exceedingly hard to describe) of the narrator's voice's attitude in the chapter of Ulysses entitled 'Ithaca.' For those who have not read the book the chapter is phrased in catechism format and details the return of the main character to his home after a long day in Dublin, the descriptions of the scenery are among some of the greatest in English literature and I felt like that entire description was somehow (sort of) happening at that very moment.
t+3:00 -- closed eye visuals are amazing, geometrics with flashes of multi-colored lightning along the geometric lines in time with the music I'm listening to. Apparently the drug's effects work with music worth a damn, too--Herbie Hancock's Chameleon is a great piece of work sober, and it's soul-vibratingly good now.
best way to describe body high: opiate with tics and tremors (largely uncontrollable, minorly as a result of the music).
t+4:00 decrease in effects but still feeling much of the body high and some of the mental, no desire to experience closed-eye visuals. Nausea that was present through the entire trip still is, but nothing to write home about. Looking back on the last four hours is like staring out across a landscape of colors and shapes which remain to be charted (in other words, I'm still pretty high and I think I'm going to wait until tomorrow and do an objective writeup of effects). I will continue to post any relevant effects, though I think the drug has run its course.
t+8:20 (psychedelic-induced insomnia update)
I feel like I finally have the wherewithal to give at least a cursory retrospective summary, I can't sleep an definitely don't feel totally sober, but I definitely feel like I've come down substantially from my last update.
I want to make an observation before I go into detail on the entire trip. The last part of the trip was spent in bed, in the dark (between approximately 1:30 and 3:00 is the pertinent time period). During that time period most of the more subtle mental effects of the drug came out (and if you'll look at the timing of the trip this must have been after the first two doses had either finished up or were almost finished). I had what I would consider somewhat profound changes in thought processing, and it sort of hinted at what the potential of this drug is, the portion of the trip prior I remember as a haze of disconnected pictures sensations and actions, but the ending part gave me enough time and calmness to see that this drug has potential.
In short, I didn't do it right tonight. I jumped in headfirst with a large dose and it gave me a fast-paced tour of the drug, but in between doses and going out and about on whatever whim was in my mind, I didn't really gain anything from the experience.
I think that this drug has potential. I think that it can enhance creativity, break traditional thought patterns and be a euphoric experience, but tonight (last night) was only the lattermost. I also think this drug has combination potential--I think marijuana might cause a breakthrough if smoked on the peak of effects (I didn't have a true 'peak' because of my dosage scheme)
I want to take a second shot, this time, I'll dose properly (30mg in one shot) and smoke on the peak. I think it might be significant this way, instead of just a throwaway evening of euphoria.
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.


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Established in South Australia in 2003. We provide a number of IT related services. We have developed web and mobile applications for startUps, companies and government.
Our latest project is an innovation of our own. TKiEE (www.TKiEE.com) has recently received funding to move to the commercialisation phase and was selected in the IBM Global Entrepreneur Program and microsoft bizspark program.
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A CSS Primer
Cascading Style Sheets were actually invented a long time ago when HTML was in it infancy. But it not well understood and other methods of formatting web content had already been popularized and were dominating the market. It took many years and several popular books to get CSS to be recognized as a superior method for formatting webpages.
To fully understand how CSS works, there are several concepts that you have to learn and practice until they become second nature.
The Box Model
The first concept concerns what has come to be known as "the box model". Browsers reads HTML code, interpret its structure and formatting, and then display the webpage. CSS does its work by stepping between HTML and the browser, redefining how each element should be rendered. It imposes an imaginary box around each element and then enables you to format almost every aspect of how that box and its contents are displayed.
CSS permits you to specify fonts, line spacing, colors, borders, background shading and graphics, margins, and padding, among other things. In most instances these boxes are invisible, and although CSS gives you the ability to format them, it does not require you to do so.
CSS defines each HTML element into one of three basic categories: Block, inline or hidden.
Block elements by default:
- Occupy the full width of the screen or their parent element, unless an alternative width is specified.
- Stack on top of other block elements, regardless of their width.
- Dimensions are calculated by adding up width, height, padding, borders and margins.
- Will expand vertically to the height of its content, plus any padding.
- Include div, h1-h6, p, li, among others.
Inline elements by default:
- Appear within the body of another element
- Are only as wide as its content.
- Do not honor width or height specifications.
- Do honor left and right padding and margin specifications.
- Do not honor top and bottom padding or margin specifications.
- Include span, em, strong among others.
Hidden elements by default
- Do not appear in the browser
- Take up no space
- Do not affect the flow or appearance of other elements
- Include head, meta, script, style among others.
Cascade Theory
The cascade theory describes how the order and placement of rules in the style sheet or on the page affects the application of styling. In other words, if two rules conflict, which one wins out? The basic concept is that the rule closest to the element wins. Webpages often contain multiple style sheets and these may contain duplicative styling. Many companies do this on purpose, especially when they have multiple departments or divisions. Corporate headquarters will supply a "main" style sheet and allow the separate divisions to override these settings by inserting their own style sheets afterwards.
Cascade in Practice
The styles affecting each element are usually applied (when present) in the following order, the last being the most powerful:
- Browser default style sheet
- User preferences
- Author preferences
- Inline styling
- !Important declarations (Author)
- !Important declarations (User)
Inheritance Theory
The inheritance theory describes how one rule can be affected by one or more previously declared rules. Inheritance can affect rules of the same name as well as rules that format parent elements or elements that nest one inside another. Inheritance is tricky. It is not an all or nothing proposition. If a generic rule applies a color or size to one or more elements, this specification can be inherited if that element is not styled by a more specific default setting or targetted rule.
Inheritance in Practice
The styles affecting each element are usually applied (when present) in the following order, the last being the most powerful:
- Browser default style sheet
- User preferences
- Linked or embedded style sheets
- General styles
- Specific styles
Descendant Theory
CSS formatting can be very confusing for designers coming from the print world. These designers are accustomed to applying styles directly to text and objects one at a time. If you copy the text and paste it elsewhere, the formatting comes along. In some cases, styles can be based on one another, but this relationship is intentional.
On the other hand, CSS formatting of one element can overlap or influence another unintentionally via inheritance. When one element is inserted within another, it can adopt some aspects of its parent's styling. In fact, the descendant theory describes how formatting can be targetted to a particular element based on its position relative to other elements.
By constructing a selector using multiple elements in sequence, in conjunction with ID and class attributes, you can formatting specific instances of text or other content as it appears within your webpage. It may be helpful to think of it as the elements formatting themselves. Using CSS in this way changes the way we fundamentally think of formatting in general. Styling is no long intrinsic to the element itself, but to the entire page and the way the code is structured. You don’t apply the formatting to the element, per se, as much as the elements adopt styling from their position within the code.
Specificity
Specificity describes how browsers determine what formatting to apply when two or more rules conflict. Some refer to this as weight—giving certain rules more priority based on order (cascade), proximity, inheritance, and descendant relationships. Such conflicts are the bane of most web designers’ existence and can waste hours of time in troubleshooting errors in CSS formatting. Let’s take a look at how specificity affects the weight of some sample rules.
One technique that designers use to determine which rule is more specific than another is by giving numeric values to each part of the selector. Each HTML tag gets 1 point, each class gets 10 points, each ID gets 100 points and inline style attributes get 1000 points. Then, by adding up the component values of the selector its specificity can be calculated and compared to other rules.
Examples:
* (wildcard) { } 0 + 0 + 0 + 0 = 0 points h1 { } 0 + 0 + 0 + 1 = 1 point a:hover { } 0 + 0 + 0 + 2 = 2 points ul li { } 0 + 0 + 0 + 1 = 2 points .class { } 0 + 0 + 10 + 0 = 10 points .class h1 { } 0 + 0 + 10 + 1 = 11 points #id { } 0 + 100 + 0 + 0 = 100 points #id.class { } 0 + 100 + 10 + 0 = 110 points #id.class h1 { } 0 + 100 + 10 + 1 = 111 points style=" " { } 1000 + 0 + 0 + 0 = 1000 points


Pre Production
This environment is the central point for data migration, data entry and parallel testing. The data present in this environment, should not be used for testing and should be treated as live data.
Testing
This environment is dedicated to testing scenarios of varying complexity, to determine if the system can handle these phenomenons as well as, testing new features of the system, post periodic system updates.
Training
This environment is dedicated for user training. All new users will be given access to this environment for their respective training sessions. These training sessions will cover all core modules; HR, Payroll and Self-Service.
Reporting Servers
This report server will provide access to customized reports not utilized in the MyHr+ system. Access to customized reports are limited as testing and updates are done regulary to ensure accuracy and stability of the environment.
MoFPs - Migration and Testing
This environment is dedicated to MOF Migration.Not all users are given access to this environment, as scripts are tested continuously during validation exercises and data is often modified
TAJ - Migration and Testing
This environment is dedicated to TAJ Migration.Not all users are given access to this environment, as scripts are tested continuously during validation exercises and data is often modified
JCA - Migration and Testing
This environment is dedicated to JCA Migration.Not all users are given access to this environment, as scripts are tested continuously during validation exercises and data is often modified
NHT - Migration and Testing
This environment is dedicated to JCA Migration.Not all users are given access to this environment, as scripts are tested continuously during validation exercises and data is often modified
In keeping with the need to address issues of fiscal and debt sustainability as necessary conditions for macroeconomic stability and economic growth, the Government of Jamaica (GOJ) has embarked on a comprehensive fiscal consolidation program.
Eliminating the fiscal deficit is imperative to reducing the debt burden, restoring fiscal sustainability, and facilitating growth. It is also essential to improve public sector efficiency and service delivery in the current environment of spending cuts and austerity measures and so enable the public sector to respond effectively to the changing needs of the citizenry now and in the future. 2.3 In support of its commitment to improve the overall public sector deficit, and in particular, to increase efficiency and reduce administrative costs, the Government of Jamaica with the assistance of the Inter-American Development Bank, (IDB) has developed the Public Sector Efficiency Program (PSEP) (JA-L1046 and JAX1007).
The PSEP Program is designed to improve government efficiency and effectiveness in the areas of: (i) human resources management (HRM) (ii) information and communication technologies management (ICTM); and (iii) public sector control systems and accountability mechanisms. 2.5 The PSEP program is also to support initiatives included in the External Fund Facility (EFF) with the International Monetary Fund (IMF), specifically, the implementation of a HCMES and Shared Corporate Services, which will utilize the HCMES.
Under this Programme, the HRM component will address issues of HRM governance in the Jamaican public sector which has been fragmented for many years with dispersed responsibilities among central agencies, and limited enforcement capacity over ministries, departments, and agencies (MDAs) and, in particular, in over 200 existing public bodies.
The GOJ needs to increase the efficiency of its human resource (HR) processes across the public sector, ensure the accuracy of its payroll and maximize the human capital present in the administration. Having an integrated HCMES solution used by all MDAs will allow for this and should realize significant savings in the annual wage bill.
To address this, the GOJ will implement a commercial off the shelf (COTS) software solution with a centrally hosted database for the entire public sector.


Adds one or more mechanical properties to the Coldfire calculation set.
int jmpSetMechanicalProperty (int propertyToAdd);
propertyToAdd [input]
Integer that specifies the property (or set of properties) you wish to include in the list of mechanical properties to be calculated when running Coldfire. This parameter can take one or any combination of the following values:
JMP_MECHANICAL_PROPERTY_YIELD_STRESS |
To include yield stress in the calculation set. |
JMP_MECHANICAL_PROPERTY_TENSILE_STRESS |
To include tensile stress in the calculation set. |
JMP_MECHANICAL_PROPERTY_HARDNESS |
To include Vickers hardness in the calculation set. |
JMP_MECHANICAL_PROPERTY_HALL_PETCH |
To include Hall-Petch coefficient in the calculation set. |
JMP_STATUS_OK |
Request has been successfully completed. |
JMP_STATUS_ERROR |
An error has occurred. |
jmpSetMechanicalProperty (JMP_MECHANICAL_PROPERTY_HARDNESS | JMP_MECHANICAL_PROPERTY_HALL_PETCH);
JMP_MECHANICAL_PROPERTY_ALL
is also defined, and may be used as a shorthand to add all properties at once.| Headers | jmpcore.h jmpcoldfire.h |
| Library | jmpcoldfire.lib /jmpcoldfire_x64.lib |
| DLL | jmpcoldfire.dll /jmpcoldfire_x64.dll |


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Raptors’ Kyle Lowry to appear as cannon doll in ‘The Nutcracker’
by Sportsnet StaffSix months ago, the 2019 NBA season culminated in the first championship of Kyle Lowry‘s career as the Toronto Raptors captured the Larry O’Brien Trophy.
The veteran point guard will wrap up the year with another first: his debut as a cannon doll in the National Ballet’s performance of “The Nutcracker” in Toronto on Dec. 19.
Lowry will be joined as a celebrity cannon doll by Canadian Paralympians Cody Caldwell and Mike Whitehead, Team Ontario wheelchair rugby and wheelchair tennis athletes Gillian Cruz and Anne-Marie Dolinar, Stars lead singer Torquil Campbell, co-founder of WE Marc Kielburger, soprano Measha Brueggergosman, comedian Candy Palmater, author Jesse Thistle and host of “Mary’s Kitchen Crush” Mary Berg.
Lowry and the other celebrity walk-ons will be dressed as colourfully costumed Russian Petrouchka dolls, who fire a cannon into the audience in act one of the play.
Last year, fellow athletes Mitch Marner and Auston Matthews of the Toronto Maple Leafs took on the role.


mcc -o DetectHandGestureADIToF -W 'WinMain:DetectHandGestureADIToF,version=1.0' -T link:exe -d 'C:\Users\shiremat\OneDrive - MathWorks\Shared with Everyone\2020\ADI ToF Demo\DetectHandGestureToFproject\for_testing' -v 'C:\Users\shiremat\OneDrive - MathWorks\Shared with Everyone\2020\ADI ToF Demo\ToFrunloop.m' -a 'C:\Users\shiremat\OneDrive - MathWorks\Shared with Everyone\2020\ADI ToF Demo\ToFrunloop.m' -r 'C:\Program Files\MATLAB\R2019b\toolbox\compiler\Resources\default_icon.ico' Compiler version: 7.1 (R2019b) Dependency analysis by REQUIREMENTS. Parsing file "C:\Users\shiremat\OneDrive - MathWorks\Shared with Everyone\2020\ADI ToF Demo\ToFrunloop.m" (referenced from command line). Generating file "C:\Users\shiremat\OneDrive - MathWorks\Shared with Everyone\2020\ADI ToF Demo\DetectHandGestureToFproject\for_testing\readme.txt". Packaging... Creating the bundle... Creating the install agent URL file... Web based installer created at C:\Users\shiremat\OneDrive - MathWorks\Shared with Everyone\2020\ADI ToF Demo\DetectHandGestureToFproject\for_redistribution\RockPaperScissors_web.exe. Packaging complete. Elapsed packaging time was: 24 seconds.


A couple of years ago, Zeljko Filipin was trying to get me to start a Watir podcast. He was telling me how to do it and why it is so important. I asked him why he didn’t he do it himself? He said he didn’t speak good enough English. Nonsense. At that time I had never met Zeljko but had spoken with him over Skype several times.
Zeljko speaks Global English, whereas I speak American English. I told Zeljko that English is a second language for most Watir users, so his dialect, which is a simplified version that is known around world, would actually be more suitable for a podcast than mine. I agreed to do the first podcast, and from there Zeljko hasn’t stopped.
Watir developers come from all over the world as well. We last met in Austin in 2009. We are making plans to meet in April in San Francisco and I am looking into making a trip to Europe this summer to meet Watir developers and users there.
I got to meet Zeljko for the first time in the Austin meeting. He also got to record several podcasts with other attendees. Zeljko traveled from his home in Zagreb, Croatia, and paid for his own travel. So did other watir developers, travelling from as far as Australia and Norway.
Face-to-face meetings like this are critical to the ongoing collaboration. We first met members of the OperaWatir team then too, resulting in the recent release of OperaWatir to the general public.
We regularly communicate using email, IRC, and skype, but there is nothing like an occasional face-to-face meeting to develop personal connections and trust.
Your contributions to the Watir project will help defray the travel costs that the Watir development team incur to meet each other. We are planning a separate Watir day the Selenium Conference. We were just quoted $450 for a room for one day. Many of our overseas contributors have already booked their tickets.  You can click the Donate button on this page to pay with PayPal (via Pledgie). If you would like to make a contribution in another way, please send me email (bret at pettichord.com).


this is maths calculation which i think scriptsabit is simpler i hope we should reallyy like are you with me
cool to be abit mathematical might be seen simple but what is inside there no joke
A triangle having all the three sides of equal length is an equilateral triangle. Since all sides are equal, all angles are equal too
The two most common triangular forms used in architecture are equilateral and isosceles. Triangles are effective tools for architecture and are used in the design of buildings and other structures as they provide strength and stability. This is why many residential homes have A-frames; it provides a sturdy structure.


--- title: "Nested index page" description: "Should process index.html correctly" --- {% extends "_layout" %} {% block content %}
{{description}}
lorem ipsum


---
layout: static1
title: Saving Time With User-Centered Design
permalink: /cw-assessment
---
The Challenge
Background: Each year, the Cadet Wing (CW) assesses the over 4,000 cadets at the US Air Force Academy. Two components of this—the personal appearance inspection and cadet interview—had been carried out on paper or used a survey tool to log interview responses.
Goal: Cut down on the number of hours required to collect and analyze the data by developing a user-friendly, digital tool that will store the data in one location.
My Role: Interaction designer, usability tester, and trainer.
The Iterative Design Process
User Research
The CW conducted the user research on the two main user-groups: assessors and data analysts. From their research, I formed the following insights
- For the assessors:
- They're time crunched: they do not have much time to learn a new tool or tools, and assessments need to be completed efficiently.
- They exhibit a spectrum of comfort and abilities with technology: the product needs to be easy to use and intuitive.
- They feel pressure to have their squadron receive high marks.
- For the data analysts:
- They wanted granularity in the data: they needed to be able to track comments, which interview questions were asked, and how many points were given for each category.
- They were concerned about the integrity of the data.
- They needed one-stop access to data: data for both assessments needs to be stored in one location.
- They had more familiarity and comfort with technology than most assessors.
I added a third user to consider: the cadet. For cadet's, the main need was the ability to see their scores, and whether they passed, after the assessment was over.
UX Methods
The main UX skills used in this project were:
- Defining the Problem: We were initially approached with
We want to use the LMS for cadet assessment
. Through careful questioning and listening I was able to craft concrete goals for the project and identify constraints.
- Ideation and Journey Mapping: While ideating for possible solutions, I created journey maps for viable solutions, such as the one below.
These journey maps helped explain the pro's and con's of the two viable solutions that came out of the ideation phase.
- Prototyping: Because we have limited control over the user interface, I went straight to prototyping possible solutions in the LMS, focusing on the cleanest and simplest interactions with the LMS.
- Usability Testing and Iterating: Given the short lifespan of this project, I opted to adapt an agile framework. I quickly produced mockups of ideas and conducted usability testing at regularly scheduled meetings, then made revisions in light of the feedback from testing.
Interaction Design Decisions
One of the initial decision was whether the LMS could be leveraged to achieve the goal. After defining the problem, it was clear that it could. We then had to make the following decisions during the design and development of the rubrics.
Choosing the Best Tool
Of 6 assessment tools in the LMS, I chose 2 that were best suited to achieve our goal: the tests tool and the rubric tool. I created some mockups of each to showcase the functionality.
The appearance inspection as a test.
The appearance inspection as a rubric.
Previous
Next
We settled on the rubric for the following reasons:
- The workflow for the assessor was simplified but also more robust.
- Data retrieval with a rubric would be cleaner than a test.
- It would be easy to track changes in and verify the data.
Grouping the Cadets
Rubrics have to be housed within a course in the LMS. So, we had to decide how many courses to create. The four main considerations for making this decision were:
- Page Load Times: fewer courses would put more cadets in a course, meaning a longer load time.
- Ease of Finding Cadet: more courses would act as a filter when trying to find a cadet to assess.
- Double Roles: some cadets would need to be both assessed and assess other cadets.
- Data Collection: fewer courses would make data collection easier.
Ultimately, we chose one course per class year, or 4 courses total for the following reasons:
- We needed at least two courses to accommodate the double roles.
- We could easily create filters within a course to make it easy to find a cadet.
- Courses would load quickly enough with a little over 1,000 cadets enrolled.
- Data collection would not take too much longer than using one course.
- Creating one course per class year is a natural way for users to divide up the student population.
Accessing the Rubrics
The appearance assessment had different two rubrics that could be used. We had to decide when an assessor would choose the appropriate rubric: after launching the rubric window or before. The two workflows would be
- Launch the rubric window > choose the rubric > complete the rubric > save and submit the rubric.
- Choose the rubric > launch the rubric window > complete the rubric > save and submit the rubric.
After testing, we chose the second option because it was simpler to the assessors and reduced the chance of errors. The first option made some assessors mistakenly believe they were not done after filling in one rubric (note the 1 of 2
text). There was no confusion that you were done with the second option. This meant an extra column of data, fewer errors inputting data was worth the extra column.
Assigning Points
The rubrics had to calculate scores correctly. For the interview I leveraged the weighting function of the rubric, assigning a 0% weight to those rows and non-zero weight to the rest. This allowed us to track which questions were asked by selecting the appropriate question within the rubric and reserve the points for the rest of the rows.
For the uniform inspection rubric, I presented two ways the rubric could calculate points:
- Each category could be seen as an opportunity to gain points (i.e. a cadet started with a low score and worked his or her way to a higher score);
- Each category could be seen as an opportunity to lose points (i.e. they started with a high score and lost points for infractions).
On behalf of the cadets, I advocated for the first option, but the leadership chose the second option.
Descriptions for Categories
Given the length of the rubric and the fact that the Levels of Achievement row could not be frozen, I wanted to give assessors an easy way to reference which column corresponded to which level of achievement. The options I presented were to show, in each cell, the verbal description or the verbal description and the level of achievement (using ALL CAPS to distinguish the two).
In testing, including both the description and level of achievement increased the speed and accuracy of the assessments and reduced the cognitive load of the assessor; so that's what we adopted for the final product.
Assigning a Grade
Our final decision was how assessment grades were displayed in the course. Keeping the cadet in mind, I suggested adding a feature that would display a pass or fail grade (along with appropriate color coding) in addition to the score received on each assessment. The leadership liked this feature, so we added it.
Results
- Saved over 915 hours of annual work collecting and analyzing assessment data.
- Overwhelmingly positive feedback, including a letter of commendation from the Vice Commandant of Cadets noting how
Dr. Padgett’s innovative placement of the Personal Appearance Inspection (PAI) into Blackboard is a game changer for us
.
- Over 200 assessors who are happy to use the rubrics for Cadet Assessment.
- Full committment from the CW to adopt the LMS for all training and assessment programs.


TimeSearcher data file format
Harry
Hochheiser<EMAIL_ADDRESS>TimeSearcher HomePage: http://www.cs.umd.edu/hcil/timesearcher
1 October Feb 2002<EMAIL_ADDRESS>This document provides a quick overview of the .tqd data file format
used to store data for use in TimeSearcher. Essentially a flat-file
augmented with descriptive data, this format was developed for ease of
use and parsing. Ideally, a more descriptive format using a more
modern notations such as XML would be used instead, but development of
such a format is not particularly interesting from a research
viewpoint.
Each line in a TimeSearcher data file is either a data line or a
comment line. Comment lines are those that start with the pound ('#')
character: these lines are purely for human reference, and are ignored
by the parser.
Header MetaData
Each file consists of several pieces of meta data, each contained on a
separate line, and all specified in a set order. Specifically, the
following lines are required:
- 1. Title - a title for the data set.
- 2. Static (unchanging) attributes for each item in a data set. These
are the attributes of each item in the data set that do _not_ change
over time. Static attributes are provided in the form: "attribute
name, attribute type; attribute name, attribute type." Possible Types
are String, Float, and Int (for integer). Thus, for example, the line
"Name,String;Country,String" implies two static variables, Name and
Country, both having type "string".
Name,String
- 3. Dynamic attributes - those that do change over time, and therefore
might be appropriate for searching using TimeSearcher. Thes attributes
are specified in the same format used for static attributes, but
allowable value types are limited to Float and Int.
Low,Float;High,Float
- 4. The number of time points for each item in the database. Each item
must have the same number of measurements.
- 5. The number of items in the data set.
- 6. Labels for the time points. There must be one value provided for
each of the time points specified in example 6. These labels may be
integers establishing a numeric order (1,2,3, etc.), floats, or strings
(april,may,june,...).
Data Items
The individual data items are found immediately after the header
information. Each data item is specified on a single line, with fields
delimited by commas. The number of data item lines should be equal to
the value given in metadata line (5), as described above.
The first items are the static attributes of the data item, in the
order specified by the "static attribute" meta data line. Thus, given
the example of "name,country" given above, a possible start to a data
item might be "Hochheiser,US,".
The dynamic attributes are found immediately after the static
attributes. If the number of dynamic attributes (specified in line 3,
above) is n, this line will contain all n values (in the order
specified in line 3) for the first time point, followed by the values
for the second time point, etc., up until the number of time points
specified in item 4. For example:
AIRBORNE FREIGHT CORP,20.81,21.75,21.38,22.44,....
In this example, there are two values for each time point - Low, and
High, as desciribed in item #3 above. Thus, 20.81 is the low
value at the first time point, 21.75 is the high value at that
timepoint, 21.38 is the low value for the second time point,
etc.
An example of the metadata and the first data line are given
below. Several example files are given in the "data" directory
in the TimeSearcher distribution:
13 Months of High and Low prices
# static attributes
Name,String
# Dynamic atts
Low,Float;High,Float
# of time points=n
13
# of records k
223
# time point labels
September,October,November,December,January,February,March,April,May,June,July,August,September
#stat1, dynamic @ t1, dynamic @t2, ....,dynamic @tn
# each dynamic are the v1, v2, ..vk @ time tj.
AIRBORNE FREIGHT CORP,20.81,21.75,21.38,22.44,.....


Plant Parenthood
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Cora Krynick
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Preparation time
less than 30 mins
Cooking time
10 to 30 mins
Serves
Serves 4
Purple sprouting broccoli can be a cheap and cheerful ingredient for early spring dinners and goes brilliantly with anchovy and chilli.
Put a large pan of water on to boil with a little salt. Trim the outer leaves and woody stalks from the broccoli. Wash the good bits and chop into 1cm/½in sections. Cut the chilli in half lengthways and scrape out the seeds and the attached pith. Chop the chilli flesh, the garlic and the anchovies finely.
In another large pan warm four tablespoons of olive oil over a medium flame and add the chilli, garlic and anchovies. Gently fry these for a minute or so and add the broccoli, season with a little salt and pepper, then continue to cook gently while the pasta boils.
Drop the pasta in the boiling water and stir immediately. Cook until just tender with a little bit of resistance to the bite (al dente). This could take anything between 7 and 12 minutes depending on the type of pasta you choose.
When the pasta has nearly finished cooking, transfer a small ladle of the cooking water to the broccoli and continue to cook over a high heat until tender.
When cooked, drain the pasta. Add another two tablespoons of oil and the cheese to the broccoli. Toss with the drained pasta and serve immediately.


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{% extends "free_software.html" %} {% block logo %} {% endblock %} {% block software %}
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title: Proposal-array-find-from-last stage: 2 contributors: Wenlu Wang, Daniel Rosenwasser
_predicate_ should be a function that accepts three arguments and returns a value that is coercible to a Boolean value. `findLast` calls _predicate_ once for each element of the array, in descending order, until it finds one where _predicate_ returns *true*. If such an element is found, `findLast` immediately returns that element value. Otherwise, `findLast` returns *undefined*.
If a _thisArg_ parameter is provided, it will be used as the *this* value for each invocation of _predicate_. If it is not provided, *undefined* is used instead.
_predicate_ is called with three arguments: the value of the element, the index of the element, and the object being traversed.
`findLast` does not directly mutate the object on which it is called but the object may be mutated by the calls to _predicate_.
The range of elements processed by `findLast` is set before the first call to _predicate_. Elements that are appended to the array after the call to `findLast` begins will not be visited by _predicate_. If existing elements of the array are changed, their value as passed to _predicate_ will be the value at the time that `findLast` visits them.
When the `findLast` method is called, the following steps are taken:
The `findLast` function is intentionally generic; it does not require that its *this* value be an Array object. Therefore it can be transferred to other kinds of objects for use as a method.
_predicate_ should be a function that accepts three arguments and returns a value that is coercible to a Boolean value. `findLastIndex` calls _predicate_ once for each element of the array, in descending order, until it finds one where _predicate_ returns *true*. If such an element is found, `findLastIndex` immediately returns the index of that element value. Otherwise, `findLastIndex` returns -1.
If a _thisArg_ parameter is provided, it will be used as the *this* value for each invocation of _predicate_. If it is not provided, *undefined* is used instead.
_predicate_ is called with three arguments: the value of the element, the index of the element, and the object being traversed.
`findLastIndex` does not directly mutate the object on which it is called but the object may be mutated by the calls to _predicate_.
The range of elements processed by `findLastIndex` is set before the first call to _predicate_. Elements that are appended to the array after the call to `findLastIndex` begins will not be visited by _predicate_. If existing elements of the array are changed, their value as passed to _predicate_ will be the value at the time that `findLastIndex` visits them.
When the `findLastIndex` method is called, the following steps are taken:
The `findLastIndex` function is intentionally generic; it does not require that its *this* value be an Array object. Therefore it can be transferred to other kinds of objects for use as a method.
The initial value of the @@unscopables
This property has the attributes { [[Writable]]: *false*, [[Enumerable]]: *false*, [[Configurable]]: *true* }.
%TypedArray%`.prototype.findLast` is a distinct function that implements the same algorithm as `Array.prototype.findLast` as defined in
This function is not generic. ValidateTypedArray is applied to the *this* value prior to evaluating the algorithm. If its result is an abrupt completion that exception is thrown instead of evaluating the algorithm.
%TypedArray%`.prototype.findLastIndex` is a distinct function that implements the same algorithm as `Array.prototype.findLastIndex` as defined in
This function is not generic. ValidateTypedArray is applied to the *this* value prior to evaluating the algorithm. If its result is an abrupt completion that exception is thrown instead of evaluating the algorithm.


After calculating infectiousness and susceptibility of each individual on the
network, it creates an nlevels
by nlevels
matrix indicating the
number of individuals that lie within each cell, and draws a heatmap.
plot_infectsuscep(graph, toa, t0 = NULL, normalize = TRUE, K = 1L, r = 0.5, expdiscount = FALSE, bins = 20, nlevels = round(bins/2), h = NULL, logscale = TRUE, main = "Distribution of Infectiousness and\nSusceptibility", xlab = "Infectiousness of ego", ylab = "Susceptibility of ego", sub = ifelse(logscale, "(in log-scale)", NA), color.palette = function(n) viridisLite::viridis(n), include.grid = TRUE, exclude.zeros = FALSE, valued = getOption("diffnet.valued", FALSE), ...)
| graph | A dynamic graph (see |
|---|---|
| toa | Integer vector of length \(n\) with the times of adoption. |
| t0 | Integer scalar. See |
| normalize | Logical scalar. Passed to infection/susceptibility. |
| K | Integer scalar. Passed to infection/susceptibility. |
| r | Numeric scalar. Passed to infection/susceptibility. |
| expdiscount | Logical scalar. Passed to infection/susceptibility. |
| bins | Integer scalar. Size of the grid (\(n\)). |
| nlevels | Integer scalar. Number of levels to plot (see |
| h | Numeric vector of length 2. Passed to |
| logscale | Logical scalar. When TRUE the axis of the plot will be presented in log-scale. |
| main | Character scalar. Title of the graph. |
| xlab | Character scalar. Title of the x-axis. |
| ylab | Character scalar. Title of the y-axis. |
| sub | Character scalar. Subtitle of the graph. |
| color.palette | a color palette function to be used to assign colors in the plot (see |
| include.grid | Logical scalar. When TRUE, the grid of the graph is drawn. |
| exclude.zeros | Logical scalar. When TRUE, observations with zero values |
| valued | Logical scalar. When FALSE non-zero values in the adjmat are set to one.
in infect or suscept are excluded from the graph. This is done explicitly when |
| ... | Additional parameters to be passed to |
A list with three elements:
A numeric vector of size \(n\) with infectiousness levels
A numeric vector of size \(n\) with susceptibility levels
A list containing the class marks and counts used to draw the
plot via filled.contour
(see grid_distribution
)
A logical vector with TRUE
when the case was included in
the plot. (this is relevant whenever logscale=TRUE
)
This plotting function was inspired by Aral, S., & Walker, D. (2012).
By default the function will try to apply a kernel smooth function via
kde2d
. If not possible (because not enought data points), then
the user should try changing the parameter h
or set it equal to zero.
toa
is passed to infection/susceptibility
.
Aral, S., & Walker, D. (2012). "Identifying Influential and Susceptible Members of Social Networks". Science, 337(6092), 337–341. http://doi.org/10.1126/science.1215842
Infectiousness and susceptibility are computed via infection
and
susceptibility
.
Other visualizations: dgr
,
diffusionMap
, drawColorKey
,
grid_distribution
,
hazard_rate
, plot_adopters
,
plot_diffnet2
, plot_diffnet
,
plot_threshold
,
rescale_vertex_igraph
# Generating a random graph ------------------------------------------------- set.seed(1234) n <- 100 nper <- 20 graph <- rgraph_er(n,nper, p=.2, undirected = FALSE) toa <- sample(1:(1+nper-1), n, TRUE) # Visualizing distribution of suscep/infect out <- plot_infectsuscep(graph, toa, K=3, logscale = FALSE)


1 Theory¶
1.0 Introduction¶
The package DifferentialForms
(in file dform.spad
) builds on the
domain DeRhamComplex
. In the following section we give a brief overview
of the functions that are going to be implemented. The focus is on precise
definitions of the notions, since those may be varying in the literature.
In section (2) we will describe the exported functions and how they work,
in section (3) some short implementation notes will be given and finally
the last section is devoted to some examples.
1.1 Definitions¶
Let \(\mathcal{M}\) be a n-dimensional manifold (sufficiently smooth and orientable). To each point \(P \in \mathcal{M}\) there is a neighborhood which can be diffeomorphically mapped to some region in \(\mathbb{R}^n\), with coordinates
for all \(P' \in \mathcal{U} (P) \subset \mathcal{M}\). The tangent space \(T_{P'} (\mathcal{M})\) at the point \(P'\) is a vector space, that is spanned by the basis
which also is often denoted by
A tangent vector \(v\) has the form
The cotangent space \(T_{P'}^{} (\mathcal{M})^{\star}\) is the vector space of linear functionals
spanned by the basis \(e^1 (P'), \ldots, e^n (P')\) which (corresponding to the basis \(\partial_j\)) is also denoted by
The latter notation indicates the dependency on the moving point \(P'\). The dual basis is by definition comprised of those linear functionals such that
Therefore we have
where \(\alpha = \sum_{j = 1}^n \alpha_j e^j\).
1.1.1 Inner product of differential forms (dot)¶
Let \(g_x\) be a symmetric \(n \times n\) matrix which is nondegenerate (i.e. \(\det (g_x) \neq 0\)). The index x indicates that this matrix depends on the coordinates \(x_1 (P), \ldots, x_n (P)\) and may be varying from point to point. If this dependency is smooth (enough) we speak of a (pseudo-) Riemannian metric (locally). This way we get an isomorphism between tangent vectors and 1-forms (= covectors):
Clearly, \(\sum_k g^{j k} g_{k l} = \delta^j_l\), in other words \((g^{j k})\) is the inverse of g. The metric g defines an inner product of vectors
and by duality also on 1-forms:
Now, this inner product is extended to arbitrary p-forms by
and linearity.
1.1.2. The volume form \(\eta\) (volumeForm)¶
The Riemannian volume form \(\eta\) is (by definition) given by the n-form
This definition makes sense because by a (orientation preserving) change of coordinates \(\sqrt{\mathrm{det} g}\) transforms like the component of a n-form.
1.1.3. Hodge dual (hodgeStar)¶
The Hodge dual of a differential p-form \(\beta\) is the (n - p)-form \(\star \beta\) such that
holds, for all p-forms \(\alpha\). The linear operator \((\star)\) is called the Hodge star operator. By the Riesz representation theorem the Hodge dual is uniquely defined by the expression above.
Warning
Flanders [4] defines the Hodge dual by the equality
where \(\lambda\) is a p-form and \(\mu\) a (n - p)-form. This can result in different signs (actually \(\star_F = s(g)\star\), where \(s(g)\) is the sign of the determinant of \(g\)).
The generally adopted definition (2016) is the one given at the beginning of this subsection.
The components of \(\star \beta\) are
what is equal to
1.1.4 Interior product (interiorProduct)¶
The interior product of a vectorfield \(v\) and a p-form \(\alpha\) is a (p -1)-form \(i_v (\alpha)\) such that
holds, for all vectorfields \(v_1, \ldots, v_{p - 1}\). Therefore, the components of \(i_v (\alpha)\) are
One can express the interior product by using the \(\star\)-operator. Let \(\alpha\) be the 1-form defined by the equation
That means in components: \(\alpha_j = g_{j k} v^k\), thus we have
Clearly, the interior product is independent of any metric, whereas the Hodge operator is not! So, usually one should not use the Hodge operator to compute the interior product.
We will use the fact that the interior product is an antiderivation, which allows a recursive implementation.
1.1.5 The Lie derivative (lieDerivative)¶
The Lie derivative with respect to a vector field \(v\) can be calculated (and defined) using Cartan’s formula:
There are other ways to define \(\mathcal{L}_v \alpha\), however, it is convenient to compute it this way when \(d\) and \(i_v\) are already at hand.
1.1.6 The CoDifferential \(\delta\) (codifferential)¶
The codifferential \(\delta\) is defined on a p-form as follows:
where \(g\) is the metric and \(s(g)\) is related to the signature of \(s(g)\) as described next.
1.1.7 The sign of a metric \(s(g)\) (s)¶
The signature of a metric \(g\) is defined as the difference of the number of positive (p) and negative (q) eigenvalues, i.e:
and the sign functions s is defined as:
Since, as we always assume, \(g\) is non-degenerate, we have \(p+q=n\), and consequently:
1.1.8 The inverse Hodge star \(\star^{-1}\) (invHodgeStar)¶
Applying the Hodge star operator twice on a p-form twice we get the identity up to sign:
Therefore
1.1.9 The Hodge-Laplacian \(\Delta_g\) (hodgeLaplacian)¶
The Hodge-Laplacian also known as Laplace-de Rham operator is defined on any manifold equipped with a (pseudo-) Riemannian metric \(g\) and is given by
Note that in the Euclidean case \(\Delta_g = - \Delta\), where latter is the ordinary Laplacian.
Bibliography¶
References
| [1] | Ralph Abraham, Jerrold E.Marsden and Tudor Ratiu.Manifolds, Tensor Analysis, and Applications. Springer, Auflage: 2nd Corrected ed. 1988. Corr. 2nd printing 1993 edition. |
| [2] | Henri Cartan. Di erential Forms. Dover Pubn Inc, Au age: Tra edition. |
| [3] | Herbert Federer. Geometric Measure Theory. Springer, Au age: Reprint of the 1st ed. Berlin, Heidelberg, New York 1969 edition. |
| [4] | Harley Flanders and Mathematics. Differential Forms with Applications to the Physical Sciences. Dover Pubn Inc, Auflage: Revised. edition. |
| [5] | L. A. Lambe and D. E. Radford. Introduction to the Quantum Yang-Baxter Equation and Quantum Groups:An Algebraic Approach. Springer, Auflage: 1997 edition. |
| [6] | Walter Rudin and RudinWalter. Principles ofMathematicalAnalysis.Mcgraw Hill Book Co, Au age: Revised. edition. |
| [7] | Hassler Whitney. Geometric Integration Theory: Princeton Mathematical Series, No. 21. Literary Licensing, LLC. |


Ravan
Ravan is a JavaScript Distributed Computing system that uses HTML5 WebWorkers to perform brute force attacks on salted hashes in background JavaScript threads across a farm of workers.
Salted and plain versions of the following hashing algorithms are currently supported:
MD5
SHA1
SHA256
SHA512
Try it online Description
JS-Recon
JS-Recon a HTML5 based JavaScript Network Reconnaissance tool. It uses HTML5 features like CrossOriginRequests and WebSockets to perform network and port scanning from the browser.
Current functionality:
Port Scanning
Network Scanning
Detecting Internal IP Address
Try it online Description
Shell of the Future
Shell of the Future is a Reverse Web Shell handler. It can be used to hijack sessions where JavaScript can be injected using Cross-site Scripting or through the browser's address bar. It makes use of HTML5's Cross Origin Requests and can bypass anti-session hijacking measures like Http-Only cookies and IP address-Session ID binding.
It can be used to:
Demonstrate the severity of XSS and JavaScript injection attacks
Create POCs for XSS vulnerabilities in Penetration test reports
Run automated scans on internal websites from outside by tunneling the traffc through an internal browser
Download UserGuide Video Source Code
DSer
This is a plugin template for Burp Proxy that is used for penetration testing of JAVA Serialzied Objects passed in POST data. It was part of the demo presented at BlackHat Europe 2010.
The plug-in provides the following:
Deserialized the JAVA Object from the captured POST data
Injects a (J)IRB shell within Burp Proxy
Provides helper methods to access private varialbles and other useful stuff
Download Video
Imposter
Imposter is a flexible framework to perform Browser Phishing attacks.
The lists of attacks performed are:
Steal cookies
Set cookies
Steal Local Shared Objects
Steal stored passwords from FireFox
Steal cached files
Poison browser cache
Steal files from the victim's local file system through Internet Explorer
Run SQL queries on the victim's Google Gears database and transfer the results
Create ResourceStore and Managed ResourceStore on the victim's Google Gears LocalServer
Download UserGuide Videos
Sniff-n-Spit
During Penetration testing it can be seen that thick-clients sometimes communicate with a server whose IP address is hardcoded in to it. The HTTP communication between such client and server is harder to intercept and test. Sniff-n-Snip is a very useful utility in such scenarios. It sniffs for HTTP packets from the client to server and forwards them to your favorite proxy (Burp, WebScarab , Paros etc).
Download User Guide


Spark files and keeping track of your ideas, concepts & thoughts
For those that don't know what a Spark file is:
It's basically a file (be it in Evernote, Google Keep, or in my case: a MarkDown text file, stored in Dropbox for safekeeping) to dump random ideas in. Once those ideas are dumped, you can look at them at a later date to see if there's any merit to them.
Because every time you've got a new idea, it's the best idea in the world! The problem is that you've hyped yourself up with your own idea ("don't get high on your own supply") and you might not be able to see what may be wrong with it, so writing it down to look at it on a later date is the perfect way to self-critique.
Now, here's how I control my ideas:
If I'm behind my PC, where I have access to my several *.spark.md files, I'll just access them directly.
If I'm on the move, I'll just either mail myself the idea, or dump it in Google Keep (on my phone), where I can move later it into the correct text file.
Why are they *.spark.md? So I can easily find them with Everything. I've got a shortcut (Alt+Z, under Options > General > Keyboard -> Toggle window Hotkey) to toggle the window and the setting to close the window once I've opened a file (Options > General > Results -> Close Window on execute).
I open the file with Visual Studio Code because of the amazing Extension support it has. I'm using markdownlint (for keeping a consistent MarkDown file), Markdown Preview Enhanced (to see how the file compiles) and English Support for LanguageTool (as an alternative for Grammarly, since they : 1. Don't support anything else other than English, and 2. Have no extension for vscode). It's a neato combo!
The things that I place in my spark files are usually about programming (little features that I want to add to this project that I've got in my head for the last… 5 years now? Ever since 2014, I believe.   It literally means "held back" and if you think that's a 'naughty no-no word', you're retarded too.  Can't spill them here, because I want to eventually make money with them. :^)
Anyway, I just wanted to share this with you because this process really helped me keep my ideas on paper in a somewhat structural way. I hope it will help you too.
PS: The Spark File is a blog post, originally from 2012: Medium/The Spark File (if that link ever dies: It's also available on web.archive.org), which is the source of this idea.


Welcome to ArBlog Builder, a user-friendly interface for designing and deploying blog posts on Arweave. Absolutely no programming knowledge is necessary to publish your blog post - all that is required is an idea! As an added bonus, once the application deploys your blog post, it will storage forever ! Happy ArBlogging :)
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2 Corinthians 6:17
Wherefore come out from among them, and be ye separate, saith the Lord, and touch not the unclean thing; and I will receive you.


This application shows the display picture of a fb profile in full resolution even if the user has enforced privacy settings and chosen not to make profile photo public.
This application is for EDUCATIONAL purpose ONLY. The owner is in no way responsible for any misuse of the information provided. There are no intentions to breach the privacy of users. You are responsibe for any damages caused by this application.
This application exploits a flaw in Facebook CDN. This application is just an effort to bring in to notice that social networks are unreliable and why it's a bad idea to keep personal information on such sites.
This application might break if there are updates from Facebook. In case if it is not working write to - shivamd001 at gmail dot com


--- layout: stats title: Dylan Minarik Statistics permalink: "/stats/players/dylan-minarik.html" ---
| Year | Team | Finish | G | 10 | -5 | Pts | PPG |
|---|---|---|---|---|---|---|---|
| 2014 | Northwestern | 21 | 19 | 105 | 40 | 850 | 44.74 |
| 2015 | Northwestern | 18 | 18 | 134 | 36 | 1160 | 64.44 |
| 2016 | Northwestern | 24 | 16 | 69 | 18 | 600 | 37.50 |
| 2017 | Northwestern | 11 | 15 | 59 | 13 | 525 | 35.00 |
| Year | Round | Player | Team | Opponent | Result | 10 | -5 | Pts | Packet |
|---|---|---|---|---|---|---|---|---|---|
| 2014 | 1 (Prelims) | Dylan Minarik | Northwestern | Michigan A | Loss | 3 | 3 | 15 | Dartmouth |
| 2014 | 2 (Prelims) | Dylan Minarik | Northwestern | Virginia A | Loss | 0 | 1 | -5 | Chicago A + Chicago C |
| 2014 | 3 (Prelims) | Dylan Minarik | Northwestern | Truman State | Win | 5 | 2 | 40 | Illinois + USC |
| 2014 | 4 (Prelims) | Dylan Minarik | Northwestern | Hunter College | Win | 5 | 1 | 45 | Ohio State |
| 2014 | 5 (Prelims) | Dylan Minarik | Northwestern | Carleton | Win | 8 | 1 | 75 | Penn A |
| 2014 | 6 (Prelims) | Dylan Minarik | Northwestern | Rutgers | Loss | 3 | 3 | 15 | Michigan State |
| 2014 | 7 (Prelims) | Dylan Minarik | Northwestern | North Carolina | Loss | 6 | 2 | 50 | Yale |
| 2014 | 8 (Prelims) | Dylan Minarik | Northwestern | William and Mary | Win | 3 | 3 | 15 | Virginia |
| 2014 | 9 (Prelims) | Dylan Minarik | Northwestern | Stanford A | Loss | 4 | 3 | 25 | Harvard |
| 2014 | 10 (Prelims) | Dylan Minarik | Northwestern | Harvard A | Loss | 3 | 2 | 20 | UW + Alberta + Chicago B |
| 2014 | 11 (Prelims) | Dylan Minarik | Northwestern | Chicago B | Win | 9 | 1 | 85 | Alabama + Columbia A + B |
| 2014 | 13 (Playoffs) | Dylan Minarik | Northwestern | Ohio State | Win | 9 | 1 | 85 | No Packet Recorded |
| 2014 | 14 (Playoffs) | Dylan Minarik | Northwestern | WUSTL | Loss | 4 | 2 | 30 | No Packet Recorded |
| 2014 | 15 (Playoffs) | Dylan Minarik | Northwestern | Berkeley A | Loss | 3 | 3 | 15 | No Packet Recorded |
| 2014 | 16 (Playoffs) | Dylan Minarik | Northwestern | Maryland B | Win | 7 | 2 | 60 | No Packet Recorded |
| 2014 | 17 (Playoffs) | Dylan Minarik | Northwestern | Notre Dame A | Win | 11 | 1 | 105 | No Packet Recorded |
| 2014 | 18 (Playoffs) | Dylan Minarik | Northwestern | Berkeley B | Loss | 7 | 2 | 60 | No Packet Recorded |
| 2014 | 19 (Playoffs) | Dylan Minarik | Northwestern | Columbia B | Win | 7 | 3 | 55 | No Packet Recorded |
| 2014 | 20 (Playoffs) | Dylan Minarik | Northwestern | Michigan State | Loss | 8 | 4 | 60 | No Packet Recorded |
| Year | Round | Player | Team | Opponent | Result | 10 | -5 | Pts | Packet |
|---|---|---|---|---|---|---|---|---|---|
| 2015 | 1 (Prelims) | Dylan Minarik | Northwestern | Notre Dame A | Win | 11 | 1 | 105 | MIT A + Alberta |
| 2015 | 2 (Prelims) | Dylan Minarik | Northwestern | Rice | Win | 8 | 4 | 60 | Minnesota + Washington |
| 2015 | 3 (Prelims) | Dylan Minarik | Northwestern | Penn B | Win | 8 | 2 | 70 | Chicago A |
| 2015 | 5 (Prelims) | Dylan Minarik | Northwestern | Chicago A | Loss | 6 | 1 | 55 | Rice + Illinois + W+M |
| 2015 | 6 (Prelims) | Dylan Minarik | Northwestern | McMaster A | Win | 11 | 1 | 105 | Michigan + Toronto |
| 2015 | 7 (Prelims) | Dylan Minarik | Northwestern | Rutgers | Win | 10 | 2 | 90 | Stanford B + Columbia |
| 2015 | 8 (Prelims) | Dylan Minarik | Northwestern | RIT | Win | 12 | 1 | 115 | Maryland + NYU |
| 2015 | 9 (Prelims) | Dylan Minarik | Northwestern | Alberta | Loss | 6 | 1 | 55 | McGill + WUSTL |
| 2015 | 10 (Prelims) | Dylan Minarik | Northwestern | Michigan A | Loss | 3 | 2 | 20 | Stanford A |
| 2015 | 11 (Prelims) | Dylan Minarik | Northwestern | Minnesota A | Loss | 8 | 2 | 70 | Ottawa + Harvard |
| 2015 | 12 (Prelims) | Dylan Minarik | Northwestern | MIT B | Win | 8 | 0 | 80 | UCSD A |
| 2015 | 14 (Playoffs) | Dylan Minarik | Northwestern | Yale A | Win | 7 | 2 | 60 | Editors 1 |
| 2015 | 15 (Playoffs) | Dylan Minarik | Northwestern | WUSTL | Loss | 5 | 4 | 30 | Editors 2 |
| 2015 | 16 (Playoffs) | Dylan Minarik | Northwestern | Harvard A | Loss | 5 | 3 | 35 | Editors 3 |
| 2015 | 17 (Playoffs) | Dylan Minarik | Northwestern | Berkeley B | Win | 10 | 2 | 90 | Dartmouth |
| 2015 | 18 (Playoffs) | Dylan Minarik | Northwestern | William and Mary | Loss | 4 | 5 | 15 | Editors 4 |
| 2015 | 19 (Playoffs) | Dylan Minarik | Northwestern | Berkeley A | Loss | 5 | 2 | 40 | Editors 5 |
| 2015 | 21 (Playoffs) | Dylan Minarik | Northwestern | MIT B | Win | 7 | 1 | 65 | VCU and Berkeley |
| Year | Round | Player | Team | Opponent | Result | 10 | -5 | Pts | Packet |
|---|---|---|---|---|---|---|---|---|---|
| 2016 | 1 (Prelims) | Dylan Minarik | Northwestern | William and Mary | Win | 3 | 2 | 20 | Georgia Tech |
| 2016 | 2 (Prelims) | Dylan Minarik | Northwestern | Harvard A | Loss | 3 | 2 | 20 | Michigan B + Chicago C + Illinois |
| 2016 | 3 (Prelims) | Dylan Minarik | Northwestern | Berkeley A | Loss | 1 | 2 | 0 | MIT B + Stanford B |
| 2016 | 4 (Prelims) | Dylan Minarik | Northwestern | UCSD A | Win | 8 | 2 | 70 | Stanford A + Louisville |
| 2016 | 5 (Prelims) | Dylan Minarik | Northwestern | Penn A | Win | 6 | 0 | 60 | Maryland A + McGill |
| 2016 | 6 (Prelims) | Dylan Minarik | Northwestern | Minnesota A | Loss | 3 | 2 | 20 | WUSTL + Virginia |
| 2016 | 8 (Prelims) | Dylan Minarik | Northwestern | Michigan A | Loss | 4 | 0 | 40 | Columbia A + Columbia B |
| 2016 | 9 (Prelims) | Dylan Minarik | Northwestern | New College of Florida | Win | 5 | 2 | 40 | MIT A |
| 2016 | 10 (Prelims) | Dylan Minarik | Northwestern | Chicago C | Win | 6 | 1 | 55 | Michigan A |
| 2016 | 11 (Prelims) | Dylan Minarik | Northwestern | Columbia B | Loss | 3 | 0 | 30 | Berkeley A |
| 2016 | 13 (Playoffs) | Dylan Minarik | Northwestern | McGill | Win | 5 | 1 | 45 | Editors 1 |
| 2016 | 14 (Playoffs) | Dylan Minarik | Northwestern | Georgia | Win | 3 | 2 | 20 | Editors 2 |
| 2016 | 15 (Playoffs) | Dylan Minarik | Northwestern | Georgia Tech | Loss | 1 | 0 | 10 | VCU + Virginia + Oxford |
| 2016 | 16 (Playoffs) | Dylan Minarik | Northwestern | Chicago B | Loss | 3 | 0 | 30 | Editors 3 |
| 2016 | 17 (Playoffs) | Dylan Minarik | Northwestern | Princeton | Win | 6 | 1 | 55 | Editors 4 |
| 2016 | 18 (Playoffs) | Dylan Minarik | Northwestern | Maryland B | Win | 9 | 1 | 85 | Editors 5 |
| Year | Round | Player | Team | Opponent | Result | 10 | -5 | Pts | Packet |
|---|---|---|---|---|---|---|---|---|---|
| 2017 | 2 (Prelims) | Dylan Minarik | Northwestern | Harvard A | Win | 4 | 1 | 35 | Chicago A + JHU |
| 2017 | 3 (Prelims) | Dylan Minarik | Northwestern | Ottawa | Win | 4 | 1 | 35 | Minnesota + MIT A |
| 2017 | 4 (Prelims) | Dylan Minarik | Northwestern | Toronto B | Win | 3 | 0 | 30 | Ohio St + Cambridge + Oxford B |
| 2017 | 5 (Prelims) | Dylan Minarik | Northwestern | Johns Hopkins | Win | 5 | 0 | 50 | Stanford + Harvard |
| 2017 | 6 (Prelims) | Dylan Minarik | Northwestern | Princeton | Loss | 2 | 0 | 20 | WUSTL + UVA + Toronto + Penn |
| 2017 | 7 (Prelims) | Dylan Minarik | Northwestern | Berkeley B | Loss | 4 | 1 | 35 | Yale A + Duke |
| 2017 | 8 (Prelims) | Dylan Minarik | Northwestern | Yale A | Loss | 4 | 3 | 25 | Maryland |
| 2017 | 10 (Playoffs) | Dylan Minarik | Northwestern | WUSTL | Loss | 3 | 1 | 25 | Editors 1 |
| 2017 | 11 (Playoffs) | Dylan Minarik | Northwestern | Duke | Win | 1 | 1 | 5 | Editors 2 |
| 2017 | 12 (Playoffs) | Dylan Minarik | Northwestern | Rutgers | Win | 6 | 0 | 60 | Editors 3 |
| 2017 | 13 (Playoffs) | Dylan Minarik | Northwestern | Minnesota A | Win | 3 | 0 | 30 | Editors 4 |
| 2017 | 14 (Playoffs) | Dylan Minarik | Northwestern | Toronto A | Win | 3 | 3 | 15 | Editors 5 |
| 2017 | 15 (Playoffs) | Dylan Minarik | Northwestern | Chicago B | Win | 6 | 1 | 55 | Editors 6 |
| 2017 | 16 (Playoffs) | Dylan Minarik | Northwestern | Oxford B | Win | 7 | 0 | 70 | Editors 7 |
| 2017 | 17 (Playoffs) | Dylan Minarik | Northwestern | Chicago C | Win | 4 | 1 | 35 | Editors 8 |