Thanks for visiting my website. I try my best to keep update my work and my personal projects here.
I can describe myself as an emotional person with the desire to live happily. I like to have challenges in my life and overcome them with the best results and always keep them done. My biggest challenge was moving from my home country to start a new journey by myself and learn everything from there. I love to work in a group environment with different people from different areas and grow my knowledge as a person. I believe that I will never get bored in this life and, that is why I like to try everything. Seriously, I have been in places that never in my 20s I thought I would be.
And well, I am just 23 years old
Creating amazing web pages for different clients ussing CSS, HTML, Javascript, PHP.
Design different arts for different clients using the different tools from Adobe Creative cloud.
Co-op term as a tech support for Fording River Operations. Involved in different projects with mobile applications deployments (Intune, CiscoVPN and DUO) and brought solutions to mine software issues. Collaborate with a complete team to support day to day problems.
Deploy and management software to all site. Management of different assets inside of the company to keep a control of the stocking. Provide remote tech support to other sites and helping engineers, environmentalists, accountants, and administrative staff.
Major courses completed: Data Structures, Mobile Development and Web Development, Computer Networks
Class 2020, graduation online sounds good
Bussiness courses completed: Accounting and economics
Requirements, hazards, equipment, industries, training and certification, investigations.
Graduation with honours from one of the best schools in my country.
Web design is probably where I spent hours in my free time. Designing and creating ideas for myself or for my friends.
I love branding. I have worked with people that know more about this but I have enough knowledge to create something amazing.
Analyze the market is a master key for business success. Thankfully, we have tools that simplify the analysis for us, such as Google Analytics or Facebook for business.
The fun part. Where the dreams come true. Implementing all the tools to create the best website
Knowledge of the marketing tools that are useful to boost a brand.
Experience with tech and application support for enterprises.
Have I mentioned that I know how to make good margaritas?


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BLAKE NISSEN
02.14.18
When Mike Laster talks to Zach Butler, the conversation carries weight to it.
Butler, a freshman guard, was supposed to join a roster behind former point guard Jaaron Simmons. Instead, Butler found himself playing behind another freshman, Teyvion Kirk.
So Laster talked to Butler and began to teach him some of the lessons he had learned himself — specifically, about work ethic and waiting for a turn to hit the floor. After all, Laster had been there before.
“I kind of tell him the struggles I went through,” Laster said. “I tell him all my experiences, kind of help them learn from what I’ve grew from at an early age. If I’m able to give them this advice early, they wouldn’t go through the same stuff that I went through. They’re going to do it a little better than I did.”
Even with his on-court product the best it has ever been, Laster’s key role has been the off-the-court work he put in when no one was watching, and the lessons he can provide from it.
Carl Fonticella | PHOTO EDITOR
Ohio senior guard Mike Laster (#24) puts up a three-point shot while being guarded by Buffalo junior guard CJ Massinburg (#5) during the second half of the Bobcats' 73-66 loss on Friday, January 26, 2018.
“The role that I’m playing right now, it’s really cool, for real,” Laster said. “I feel like a lot of people listen to me and take what I say and account for it.”
It’s the role that Laster has embraced, the team’s leader because of his on and off the floor habits. All of the work that he put in has culminated in a senior year that, team record aside, has gone about as well as it could for Laster.
“The difference between him and most people, in the world in general, is that he not only leads with his words, but he leads with his actions,” Kirk said. “(He’s) one of the best seniors you can have around.”
He’s not a vocal leader per se, but he doesn’t need to be. Everything he needs to say is nonverbal when he takes the floor with his injured left shoulder wrapped up. It’s a lead-by-example model, and it’s one that has worked for the Bobcats by their hardest-working player.
“The biggest thing you can do for me is be available,” coach Saul Phillips said. “(Freshmen) need to have somebody like that to look at to say, ‘OK, this is what a senior looks like. This is what I need to try and become.’ ”
Over the last few weeks, Laster has played through pain. Everyone knows it. Everyone can see it with each trip down the floor whenever his left arm held close to his stomach.
Just how much pain he has is a question difficult to answer. But it wouldn’t make much sense for Laster to talk openly about his left shoulder, which has come wrapped in a brace for the last few weeks.
Blake Nissen | PHOTO EDITOR
Mike Laster pushes up the court during Ohio's game against Bowling Green on January 30, 2017. The Bobcats lost 66-50.
At Eastern Michigan on Jan. 20, his shoulder popped out of place while going for a rebound. His arm got locked up going for the ball, and, for good measure, he landed on his left side, too. Laster had it set back into place and returned to the game.
Ten days later, it happened again at Bowling Green, and Laster went into the hallway, removed his jersey and had his shoulder put back into place by the training staff once more.
 “That’s probably a tough situation. He’s grinding it out, playing hard and producing for us with an injury.”
The shoulder can, according to Phillips, pop out of place at any second. He also said the injury has limited Laster in some ways, as he’s had to make variations to his game that have been restricting. Instead of driving to the rim like he normally would, he’s had to pull up short and shoot fadeaway jumpers.
Despite his injury, he leads a Bobcats team decimated by injuries elsewhere on the roster in minutes per game.
But for Laster, it’s not his style to complain or willingly sit out. It’s the first attribute his teammates will mention when asked about him. Laster’s work ethic has put him in a position that few, except for those who know him, thought possible for the first two and a half years of his college career.
Laster has forgotten about his last two seasons on purpose. But Laster’s minutes reduction from his sophomore to senior season has demonstrated his dedication to the Bobcats.
“It’s easy to come in the gym when you get 35 minutes a night and shoot,” senior forward Sam Frayer said. “But when you’re getting three or four minutes a night and the shots aren’t falling, that’s when it’s hard, that’s when you really test your character. Mike’s got good character.” - Sam Frayer, senior forward
He was Phillips’ first recruit at Ohio in 2014 out of Cass Technical High School in Detroit. Laster started 17 games his freshman year, but, over the next two seasons, he didn’t make one start.
“You can’t really think about stuff that happened before,” Laster said. “You’ve just got to keep moving forward.”
Laster averaged just 1.9 points per game his sophomore year in just 9.4 minutes after a strong start to his career. In his junior season, it looked to be more of the same. But then Antonio Campbell, Ohio’s best player out for the season, went down with an injury and was out for the season. The Bobcats needed minutes from elsewhere in the lineup. That’s where Laster, who continued to work throughout his minutes reduction, came into play.
He averaged 21.8 minutes per game in the 16 games without Campbell and pinned together a five-game stretch in which he reached double digit points. Even though he wasn’t starting, Laster had carved out a nice little niche for himself on the Bobcats. But the most impressive part of that isn’t the improved stat-line or the increased role. It’s the work that preceded it.
“It’s easy to come in the gym when you get 35 minutes a night and shoot,” senior forward Sam Frayer said. “But when you’re getting three or four minutes a night and the shots aren’t falling, that’s when it’s hard, that’s when you really test your character. Mike’s got good character.”
Laster kept working with long nights in The Convo, perfecting whatever he could for his eventual chance, whenever, and if ever, it would come.
 “He’s doing everything when no one is watching.”
Laster never made a problem about his lack of minutes. He just kept working. But to Laster, that’s the only way of doing things. He won’t brag about it, either. Yet, that doesn’t mean that no one else can for him.
“I sound like a broken record,” Phillips said. “There has not been one person that has put more sweat equity in this, even when they weren’t necessarily getting the returns they wanted, than Mike.”
At the outset of this season, Laster’s role still was in flux. His position as a starter still wasn’t sealed as the season drew closer.
Emilee Chinn | FOR THE POST
Ohio senior guard Mike Laster prepares to make a pass during Ohio’s 91-57 loss against Toledo on Jan. 16.
But over Ohio’s first few games, he established himself as not only a starter, but the go-to scorer when the Bobcats needed one. He scored double digit points for 12 games in a row from November to January and is the team’s second leading scorer (14.4 per game), just narrowly behind Kirk (15.1 per game).
And for Laster, his grind is something that can’t be seen by fans or casual viewers of Ohio basketball. It’s only something that can be found out by talking to his teammates and coaches. It’s not the on-court product that has been meaningful for the Bobcats — it’s the relationships he’s built off the floor, too.
“You never set an arrival date for a player, you just keep plugging away until they get to the point where they’re comfortable enough to make the plays they need to make,” Phillips said. “It has been a very rewarding year in terms of watching Mike Laster grow as a person, as a player, as a leader.”
Carl Fonticella | PHOTO EDITOR
Left image: Ohio sophomore guard Mike Laster goes in for a layup during the second half of the Bobcat’s 76-64 win over rivals Miami on Feb. 20, 2016. With the win, Ohio improved to 18-8 on the season.
Right image: Ohio senior guard Mike Laster (#24) puts up a floater in front of Iona graduate student forward TK Edogi (#13) in the second half of Ohio’s 93-88 loss to Iona on Tuesday, Nov. 28.
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--- redirect_from: /docs/1.0.10/classes/params.paramtype.html ---
properties will override the default methods and/or pattern in `ParamType`'s public interface.
properties will override the default methods and/or pattern in `ParamType`'s public interface.
A configuration object which contains the custom type definition. The object's
a new ParamType object
Dynamic flag
When dynamic
is true
, changes to the parameter value will not cause the state to be entered/exited.
Normally, if a parameter value changes, the state which declared that the parameter will be reloaded (entered/exited).
When a parameter is dynamic
, a transition still occurs, but it does not cause the state to exit/enter.
Default: false
Enables/disables inheriting of parameter values (of this type)
When a transition is run with TransitionOptions.inherit set to
true
, the current param values are inherited in the new transition.
However, parameters whose type has inherit: false
set will not be inherited.
The internal parameter type of hash
has inherit: false
.
This is used to disable inheriting of the hash value (#
) on subsequent transitions.
$state.go('home', { '#': 'inboxAnchor' });
...
// "#" is not inherited.
// The value of the "#" parameter will be `null`
// The url's hash will be cleared.
$state.go('home.nest');
See also TransitionOptions.inherit and ParamDeclaration.inherit
The name/id of the parameter type
A regular expression that matches the encoded parameter type
This regular expression is used to match an encoded parameter value in the URL.
For example, if your type encodes as a dash-separated numbers, match that here:
new RegExp("[0-9]+(?:-[0-9]+)*")
.
There are some limitations to these regexps:
(?: )
)/^foo$/
Disables url-encoding of parameter values
If a parameter type is declared raw
, it will not be url-encoded.
Custom encoding can still be applied in the encode function.
The decoding behavior of raw parameters is not defined. See: ParamDeclaration.raw for details
Wraps an existing custom ParamType as an array of ParamType, depending on 'mode'. e.g.:
mode
is "auto", thenWraps an existing custom ParamType as an array of ParamType, depending on 'mode'. e.g.:
mode
is "auto", thenGiven an encoded string, or a decoded object, returns a decoded object
Given an encoded string, or a decoded object, returns a decoded object
Decodes a parameter value string (from URL string or transition param) to a custom/native value.
Decodes a parameter value string (from URL string or transition param) to a custom/native value.
For example, if your type decodes to an array of ints, then decode the string as an array of ints here:
decode: (str) => str.split("-").map(str => parseInt(str, 10))
Note: in general, encode and decode should be symmetrical. That is, encode(decode(str)) === str
a custom representation of the URL parameter value.
Encodes a custom/native type value to a string that can be embedded in a URL.
Encodes a custom/native type value to a string that can be embedded in a URL.
Note that the return value does not need to be URL-safe (i.e. passed through encodeURIComponent()
).
It only needs to be a representation of val
that has been encoded as a string.
For example, if your custom type decodes to an array of ints, then encode the array of ints to a string here:
encode: (intarray) => intarray.join("-")
Note: in general, encode and decode should be symmetrical. That is, encode(decode(str)) === str
a string representation of val
that can be encoded in a URL.
Determines whether two decoded values are equivalent.
Determines whether two decoded values are equivalent.
For example, if your type decodes to an array of ints, then check if the arrays are equal:
equals: (a, b) => a.length === b.length && a.reduce((acc, x, idx) => acc && x === b[idx], true)
true
if the values are equivalent/equal, otherwise false
.
Tests if some object type is compatible with this parameter type
Tests if some object type is compatible with this parameter type
Detects whether some value is of this particular type.
Accepts a decoded value and determines whether it matches this ParamType
object.
If your custom type encodes the parameter to a specific type, check for that type here. For example, if your custom type decodes the URL parameter value as an array of ints, return true if the input is an array of ints:
is: (val) => Array.isArray(val) && array.reduce((acc, x) => acc && parseInt(val, 10) === val, true)
If your type decodes the URL parameter value to a custom string, check that the string matches
the pattern (don't use an arrow fn if you need this
): function (val) { return !!this.pattern.exec(val) }
Note: This method is not used to check if the URL matches. It's used to check if a decoded value is this type. Use pattern to check the encoded value in the URL.
this is the name of the parameter in which `val` is stored. Can be used for
meta-programming of `ParamType` objects.
true
if the value matches the type, otherwise false
.
Generated using TypeDoc
An internal class which implements ParamTypeDefinition.
A ParamTypeDefinition is a plain javascript object used to register custom parameter types. When a param type definition is registered, an instance of this class is created internally.
This class has naive implementations for all the ParamTypeDefinition methods.
Used by UrlMatcher when matching or formatting URLs, or comparing and validating parameter values.
Example:
var paramTypeDef = { decode: function(val) { return parseInt(val, 10); }, encode: function(val) { return val && val.toString(); }, equals: function(a, b) { return this.is(a) && a === b; }, is: function(val) { return angular.isNumber(val) && isFinite(val) && val % 1 === 0; }, pattern: /\d+/ } var paramType = new ParamType(paramTypeDef);


{#==========================================
Docs : "bootstrapping"
==========================================#}
Bootstrapping a Spincast application is very easy. Most of the time,
you start with the
Bootstrapping your app
spincast-default
Maven artifact in your
pom.xml
(or build.gradle
) :
<dependency>
<groupId>org.spincast</groupId>
<artifactId>spincast-default</artifactId>
<version>{{spincast.spincastCurrrentVersion}}</version>
</dependency>
Then, in the main(...)
method of your application,
you use the Spincast
class to initialize your application.
You can do this the "quick way", or use the Bootstrapper
to
have more options. Let see both of those approaches...
The quickest way to initialize a Spincast application is to call Spincast.init(args)
:
public class App { public static void main(String[] args) { Spincast.init(args); } // ... }
This will create a Guice context using all the default plugins,
will bind the current App
class itself in that context (as a singleton) and will load the
App
instance. You then simply
have to add an init method to your App
class to
define Routes, add some logic, and start the HTTP Server :
public class App { public static void main(String[] args) { Spincast.init(args); } @Inject protected void init(DefaultRouter router, Server server) { router.GET("/").handle(context -> context.response().sendHtml("
Hello World!
")); server.start(); } }
This is a simple, but totally functional Spincast application! There is a demo page for this very example. On that page, you can download the sources and run the application by yourself.
Finally, note that Spincast.init(args)
in fact creates a default Bootstrapper
under the hood. We will now see how you can configure this bootstrapper explicitly to have more control
over your application initialization...
In most cases, you need more control than simply calling Spincast.init(args)
.
You want to be able to add custom modules to the Guice context, to add extra plugins, etc.
You do so by using Spincast.configure()
instead of
Spincast.init(args)
. This starts a bootstrapper to help
configure your application before it is started. Let's see an example :
public static void main(String[] args) { Spincast.configure() .module(new AppModule()) .plugin(new SpincastHttpClientPlugin()) .requestContextImplementationClass(AppRequestContextDefault.class) .init(args); //.... }
Explanation :
.configure()
instead of .init(args)
!
.init(args)
so the Guice
context is created, the current class is bound and then loaded. We also use this method to bind
the arguments received in the main(...)
method to the Guice context.
Bootstapper's options :
Let's now see the bootstrapper's options (Note that none of them is mandatory,
except requestContextImplementationClass(...)
if you are using a
custom Request Context type and websocketContextImplementationClass(...)
if you are using a
custom WebSocket Context type).
module(...)
: Adds a Guice module.
It can be called multiple time to add more than one module. All the modules
added using this method are going to be combined together.
plugin(...)
: To register a plugin.
You can add multiple plugins (in addition to the default ones). They will
be applied in the order they are added to the bootstrapper.
disableAllDefaultPlugins()
: Disables all
the default plugins, including the core
one. If you think about
using this method, you should probably start
with the spincast-core artifact
instead of spincast-default
.
disableDefaultXXXXXXXPlugin()
: Disables
a default plugin. There is a version of this method for every
default plugin. If you disable a default plugin, you are responsible for
binding the required components the plugin was in charge of!
requestContextImplementationClass(...)
: Tells Spincast
that you are using a custom Request Context type.
You need to pass as a parameter the implementation class of your
custom Request Context type. Calling this method is mandatory if you are using
a custom Request Context type!
websocketContextImplementationClass(...)
: Tells Spincast
that you are using a custom WebSocket Context type.
You need to pass as a parameter the implementation class of your
custom WebSocket Context type. Calling this method is mandatory if you are using
a custom WebSocket Context type!
bindCurrentClass(...)
: By default,
the class in which the bootstrapper is created is automatically
bound in the Guice context (as a singleton) and its instance is loaded
when the context is ready. To disable this, you can call bindCurrentClass(false)
.
appClass(...)
: You can specify which class should be automatically
bound and loaded when the Guice context is ready. Calling this method will disable the
binding of the current class (as calling bindCurrentClass(false)
would do).
getDefaultModule(...)
: Allows you to get the Guice module
resulting from all the default plugin. You can use this (in association with
disableAllDefaultPlugins()
and module(...)
) to tweak the
Guice module generated by the default plugins.
App
class
extend SpincastConfigDefault
so you can override some default configurations right in that class!
Everything in Spincast is based on dependency injection so you can
easily replace/extend pretty much anything you want.
@Inject
annotation. Don't put everything in the App
class, except if
your application is very small.
spincast-core
directly
This is an advanced topic that most applications will never need.
If you need total control over how your application is built, you can decide to start without the default plugins and pick, one by one, which one to add.
By using "spincast-default"
you add the default plugins as
Maven artifact but also a lot of
transitive dependencies. For example, dependencies for some
Jackson artifacts
are added by the default
Spincast Jackson Json plugin. Those
dependencies may conflict with other dependencies you use in your application.
This is a situation where you may want to start without the default plugins.
To start a Spincast application from scratch, start with the "spincast-core"
Maven artifact instead
of "spincast-default"
:
<dependency> <groupId>org.spincast</groupId> <artifactId>spincast-core</artifactId> <version>{{spincast.spincastCurrrentVersion}}</version> </dependency>
Doing so, you start with the core
code but you need to provide an implementation
for all the required components, by yourself. You generaly provide those
implementations by choosing and installing
some plugins by yourself.
For example, to provide an implementation for the Server and for the TemplatingEngine components, you could use:
<dependency> <groupId>org.spincast</groupId> <artifactId>spincast-plugins-undertow</artifactId> <version>{{spincast.spincastCurrrentVersion}}</version> </dependency> <dependency> <groupId>org.spincast</groupId> <artifactId>spincast-plugins-pebble</artifactId> <version>{{spincast.spincastCurrrentVersion}}</version> </dependency> // ...
Note that by starting without spincast-default
, you don't
have access to the Bootstrapper!
You'll have to create the Guice context by yourself, using the modules provided by the
different plugins.
If you fail to provide an implementation for a component that would be bound by a default plugin, you will get this kind of error when trying to start your application :
> ERROR - No implementation for org.spincast.server.Server was bound.


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| Huy V. Vo INRIA, Valeo.ai, ENS |
Francis Bach INRIA |
Minsu Cho POSTECH |
Kai Han University of Oxford |
| Yann LeCun NYU |
Patrick Pérez Valeo.ai |
Jean Ponce INRIA |
Learning with complete or partial supervision is powerful but relies on ever-growing human annotation efforts. As a way to mitigate this serious problem, as well as to serve specific applications, unsupervised learning has emerged as an important field of research. In computer vision, unsupervised learning comes in various guises. We focus here on the unsupervised discovery and matching of object categories among images in a collection, following the work of Cho et al. 2015. We show that the original approach can be reformulated and solved as a proper optimization problem. Experiments on several benchmarks establish the merit of our approach. .
@inproceedings{Vo19UOD, title = {Unsupervised image matching and object discovery as optimization}, author = {Vo, Huy V. and Bach, Francis and Cho, Minsu and Han, Kai and LeCun, Yann and P{\'e}rez, Patrick and Ponce, Jean}, booktitle = {Proceedings of the IEEE/CVF Conference in Computer Vision and Pattern Recognition ({CVPR})}, year = {2019} }
This work was supported in part by the Inria/NYU collaboration agreement, the Louis Vuitton/ENS chair on artificial intellgence and the EPSRC Programme Grant Seebibyte EP/M013774/1.


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Docs > Functions
Functions are declared using `fn`. For example:
```
fn f(a, b, c) {
...
}
```
You can then call it using `f(a, b, c)` where `a`, `b`, and `c` are expressions. Whenever `f` is called, `...` will be run; the last value in it will be returned. Explicit return can be done with `return`:
```
fn f() {
return ...
}
```
Functions cannot modify outside scope, but they can
modify their arguments. Functions can be used as closures, since each keeps the scope they were defined in.
## Technical Details
- Every function runs in its own VM, but inherits scope from its caller.


Theorem Proving:
Enumeration, Computation, Deduction
Goals
Computer-Assisted proof components
Automated Deduction
Limits of Set theory and First-order Logic
Goals
- Goal: Use computers to greatly increase our ability to discover and prove
mathematical results across areas of mathematics.
- Why?
- How?
Learn to search for, construct and recognize useful mathematical objects.
What?
- There are infinitely many prime numbers.
- There are arbitrarily long arithmetic progressions all of whose elements are prime numbers.
- There are infinitely many natural numbers $n$ such $n$ and $n+2$ are both primes.
Computer-Assisted proof components
- Computers have been used in various ways to provide a component of a proof:
- Enumeration,
- Symbolic algebra,
- Exact real number arithmetic,
- Linear programming,
- SAT solvers.
- Some examples:
- Four colour theorem,
- Kepler conjecture,
- Boolean Pythagorean triples problem.
Formal proofs in Mathematics.
- A formal deduction system should giver rules that describe
- What are well-formed expressions, i.e., represent mathematical objects.
- How to deduce statements from other statements (more generally to make judgements).
- Axioms, which are well-formed propositions that we take to be proved.
- In the usual foundations of mathematics, the rules for forming expressions and making deductions are those of First-Order Logic, and the axioms are those of Set Theory.
First-order logic: languages
- A first-order language, which describes a domain of discourse (e.g. $\mathbb{N}$) has vocabulary consisting of
- Variables - can be taken to be a fixed countable set.
- Constants (e.g. $0$, $1$).
- Functions (e.g. $+$).
- Relations (e.g. $<$, $=$).
- Special symbols $\Rightarrow$, $\iff$, $\wedge$, $\vee$, $\forall$, $\exists$, ...
- We form two kinds of expressions from these, terms (e.g. $1+1$, $n + 3$)
and formulas (e.g. $n + 1 < 2$, $4 < 3$).
- Terms and formulas may depend on variables.
- Terms represent objects in the domain of discourse.
- Formulas are either true or false.
Deduction and theories
- We can deduce formulas from other formulas using the rules of deduction.
- The main deduction rule is Modus Ponens : given $P$ and $P\Rightarrow Q$ we deduce $Q$.
- A theory is a language together with a collection of formulas, called axioms in the language.
- A formula is deducible in a theory if it can be
obtained from the axioms by the rules of deduction.
Universal deducer?
- A universal deducer is a computable function (algorithm) which, given a proposition (formula),
returns a proof if it is deducible and otherwise returns failure.
- By results of Turing, there is no such algorithm.
- We can enumerate proofs and check if they prove either the given proposition or its negation.
This does not always work as there are statements that are true but not provable.
- Practically, we can conclude that there is no best deducer,
as any given proof can be found by some deducer but no deducer can find all proofs.
Robbins conjecture
- Robbins conjecture was a conjectural characterization of Boolean algebras in terms of
associativity and commutativity of $\vee$ and the Robbins equation
$\neg(\neg(a\vee b)\vee \neg(a \vee \neg b)) = a$.
- This was conjectured in the 1930s, and finally proved in 1996 using the
automated theorem prover EQP, which is a Resolution Theorem Prover with Paramodulation.
- So far, this seems to be the only major success of deductive theorem provers.
- First-order logic theorem provers are, however, used in interactive proof systems
(hammer tactics).
Real-life mathematics
- A proof in real-life mathematics consists of:
- definitions, axioms, assumptions, notation;
- assertions;
- hints about which assertions, definitions etc. are used in the proof of a given assertion.
- focussing attention on relevant objects and results.
- introducing variables,hypotheses etc. into a scope.
- The reader is expected to deduce all assertions based on the hints
(or at least believe that he/she can do so).
- In particular, there is no objective sense in which a proof is complete or correct.
“ Since the first half of the 20th century mathematics has been presented as a science based on
ZFC and ZFC was introduced as a particular theory in Predicate Logic.
“ Therefore someone who wanted to get to the bottom of things in mathematics had a simple
road to follow - learn what Predicate Logic is, then learn a particular theory called ZFC, then
learn how to translate propositions about a few basic mathematical concepts into formulas of
ZFC, and then learn to believe, through examples, that the rest of mathematics can be reduced
to these few basic concepts.”
Vladimir Voevodsky
Why better (new) foundations?
- In the usual foundations of mathematics, $sin(3)$ and $3(sin)$ are syntactically equally valid, i.e., the usual language of mathematics is an informal language.
- Statements and proofs formalized in first-order logic are verbose and opaque.
- Propositions and Proofs are not first class, i.e., cannot be arguments or values of functions, so not composable.
We instead have patterns of proof (such as induction).
- HoTT foundations are fully formal, yet much closer to working mathematics and with a syntax that actually describes valid objects. Further, introducing variables, hypothesis and assumptions as well as inductive proofs, are natural.
“ The roadblock that prevented generations of interested mathematicians and computer scientists
from solving the problem of computer verification of mathematical reasoning was the
unpreparedness of foundations of mathematics for the requirements of this task.”
“ Formulating mathematical reasoning in a language precise enough for a computer to follow
meant using a foundational system of mathematics not as a standard of consistency applied only
to establish a few fundamental theorems, but as a tool that can be employed in everyday
mathematical work. ”
Vladimir Voevodsky


Flireh1291.github.io
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|
Groovy 2.1.7 | |||||||
| PREV NEXT | FRAMES NO FRAMES |
| Interface Summary | |
|---|---|
| AdaptingMetaClass | An interface for MetaClass instances that "adapt" other MetaClass instances such as a proxy or delegating MetaClass. |
| Buildable | |
| ClosureInvokingMethod | An interface for MetaMethods that invoke closures to implements. |
| GroovyCallable | A special "marker" style interface allowing Groovy classes to implement both Runnable and Callable yet give preference to Runnable (for backwards compatibility) for APIs having both Runnable and Callable methods. |
| GroovyInterceptable | Marker interface used to notify that all methods should be intercepted through the invokeMethod mechanism
of GroovyObject . |
| GroovyObject | The interface implemented by all Groovy objects. |
| GroovyResourceLoader | Allows frameworks that integrate with Groovy to determine how Groovy files are resolved. |
| Interceptor | Implementers of this interface can be registered in the ProxyMetaClass for notifications about method calls for objects managed by the ProxyMetaClass. |
| MetaClass | A MetaClass within Groovy defines the behaviour of any given Groovy or Java class. |
| MetaClassRegistry | A MetaClassRegistry is an object that is responsible for managing the a cache of MetaClass instances. |
| MetaClassRegistryChangeEventListener | A listener called whenever a constant MetaClass is set, removed or replaced. |
| MetaObjectProtocol | |
| MutableMetaClass | An interface that defines methods that implementers of mutable Meta classes should specify. |
| PropertyAccessInterceptor | |
| Range | A Range represents the list of all items obtained by starting from a
from value and calling next() successively
until you reach the to value. |
| Writable | Represents an object which is capable of writing itself to a text stream in a more efficient format than just creating a toString() representation of itself. |
| Class Summary | |
|---|---|
| BenchmarkInterceptor | Interceptor that registers the timestamp of each method call before and after invocation. |
| Binding | Represents the variable bindings of a script which can be altered from outside the script object or created outside of a script and passed into it. |
| Closure | Represents any closure object in Groovy. |
| DelegatingMetaClass | @author John Wilson |
| EmptyRange | Constructing Ranges like 0..<0 |
| ExpandoMetaClass | ExpandoMetaClass is a MetaClass that behaves like an Expando, allowing the addition or replacement of methods, properties and constructors on the fly. |
| ExpandoMetaClass.ExpandoMetaConstructor | Handles the ability to use the left shift operator to append new constructors |
| ExpandoMetaClass.ExpandoMetaProperty | Instances of this class are returned when using the << left shift operator. |
| ExpandoMetaClassCreationHandle | |
| GString | Represents a String which contains embedded values such as "hello there ${user} how are you?" |
| GroovyClassLoader | A ClassLoader which can load Groovy classes. |
| GroovyClassLoader.ClassCollector | |
| GroovyClassLoader.InnerLoader | |
| GroovyCodeSource | CodeSource wrapper class that allows specific security policies to be associated with a class compiled from groovy source. |
| GroovyLogTestCase | Helper class to spoof log entries as produced by calling arbitrary code. |
| GroovyObjectSupport | A useful base class for Java objects wishing to be Groovy objects |
| GroovyShell | Represents a groovy shell capable of running arbitrary groovy scripts |
| GroovySystem | |
| IntRange | Represents a list of Integer objects from a specified int up (or down) to and including a given to. |
| ListWithDefault | A wrapper for List which automatically grows the list when either get(int) or
getAt(int) is called with an index greater than or equal to size() . |
| MapWithDefault | A wrapper for Map which allows a default value to be specified. |
| MetaArrayLengthProperty | Represents a property on a bean which may have a getter and/or a setter |
| MetaBeanProperty | Represents a property on a bean which may have a getter and/or a setter |
| MetaClassImpl | Allows methods to be dynamically added to existing classes at runtime |
| MetaClassImpl.Index | |
| MetaClassImpl.MetaConstructor | This is a helper method added in Groovy 2.1.0, which is used only by indy. |
| MetaClassRegistry.MetaClassCreationHandle | Class used as base for the creation of MetaClass implementations. |
| MetaClassRegistryChangeEvent | An event used to propagate meta class updates |
| MetaExpandoProperty | Represents a property in an Expando object |
| MetaMethod | Represents a Method on a Java object a little like Method except without using reflection to invoke the method |
| MetaProperty | Represents a property on a bean which may have a getter and/or a setter |
| NonEmptySequence | Represents a sequence of objects which represents one or many instances of of objects of a given type. |
| ObjectRange | Represents an inclusive list of objects from a value to a value using comparators. |
| ParameterArray | Distinguish a parameter array from Object[]. |
| PropertyValue | |
| ProxyMetaClass | As subclass of MetaClass, ProxyMetaClass manages calls from Groovy Objects to POJOs. |
| Reference | Represents a reference to a value |
| Script | This object represents a Groovy script |
| Sequence | Represents a sequence of objects which represents zero or many instances of of objects of a given type. |
| SpreadMap | Represents a spreadable map which extends java.util.HashMap. |
| TracingInterceptor | |
| Tuple | Represents a list of Integer objects from a specified int up to but not including a given and to. |
| Exception Summary | |
|---|---|
| ClosureException | An exception thrown by a closure invocation |
| DeprecationException | Use this exception to mark a method implementation as being deprecated. |
| GroovyRuntimeException | An exception thrown by the interpreter |
| IllegalPropertyAccessException | An exception occurred if a dynamic property dispatch fails with a field not accessible. |
| IncorrectClosureArgumentsException | An exception occurred when invoking a Closure with the wrong number and/or types of arguments |
| MissingClassException | An exception occurred if a dynamic method dispatch fails with an unknown class. |
| MissingFieldException | An exception occurred if a dynamic field dispatch fails with an unknown field. |
| MissingMethodException | An exception occurred if a dynamic method dispatch fails with an unknown method. |
| MissingPropertyException | An exception occurred if a dynamic property dispatch fails with an unknown property. |
| ReadOnlyPropertyException | This exception is thrown if an attempt is made to set a read only property |
| SpreadListEvaluatingException | |
| SpreadMapEvaluatingException | |
| StringWriterIOException | An IO exception occurred trying to append to a StringWriter which should never happen. |
| Annotation Type Summary | |
|---|---|
| Category | Transforms an instance-style Groovy class or interface to become a static-style conventional Groovy category. |
| Delegate | Field annotation to automatically delegate part of the functionality of an owner class to the annotated field. |
| DelegatesTo | This annotation can be used by API or DSL writers to document parameters which accept a closure. |
| DelegatesTo.Target | |
| Grab | Used to grab the referenced artifact and its dependencies and make it available on the Classpath. |
| GrabConfig | Used to modify the grape configuration for grab requests. |
| GrabExclude | Used to exclude an indirectly referenced artifact from the classpath. |
| GrabResolver | Used to add a repository for resolving Grape dependencies. |
| Grapes | Sometimes we will need more than one grab per class, but we can only add one annotation type per annotatable node. |
| Lazy | Field annotation to simplify lazy initialization. |
| Mixin | Provides a mechanism for mixing in methods into a class. |
| Newify | Annotation that supports writing constructor call expressions without the 'new' keyword. |
| Singleton | Class annotation to make class singleton. |
Copyright © 2003-2013 The Codehaus. All rights reserved.


--- layout: article article: true permalink: /blog/article/ipv6-ipv4 title: "ipv6-ipv4" cover: "ipv6-ipv4.jpg" description: "ipv6-ipv4?" time_reading_minutes: "30" categories: ["Software"] ---


Communication Protocols
Transfer of state via GET, PUT, PATCH, etc
Think in terms of actions using GET and PUT
Example
| Operation | RPC (operation) | REST (resource) |
|---|---|---|
| Signup | POST /signup | POST /persons |
| Read a person | GET /readPerson?personid=1234 | GET /persons/1234 |
| Read a person’s items list | GET /readUsersItemsList?userid=1234 | GET /persons/1234/items |
| Add an item to a person’s list | POST /addItemToUsersItemsList | POST /persons/1234/items |
| Update an item | POST /modifyItem | PUT /items/456 |
| Delete an item | POST /removeItem?itemId=456 | DELETE /items/456 |
Communicate Synchronously or Async
Spring's central class for synchronous client-side HTTP access. It simplifies communication with HTTP servers, and enforces RESTful principles.
Javascript callbacks, promises, etc
// Say "Hello."
console.log("Hello.");
// Say "Goodbye" two seconds from now.
setTimeout(function() {
console.log("Goodbye!");
}, 2000);
// Say "Hello again!"
console.log("Hello again!");
java.nio library, futures, threads, etc
CompletableFuture.supplyAsync(this::findReceiver)
.thenApply(this::sendMsg)
.thenAccept(this::notify);
We create a task and subscribe ourselves as observers to the success/failure/error etc of the task.
When the task ends, methods(onSuccess(), onError()) of registered observers are called.
for( i = 0; i < observers.Count; i++) {
observers[i].onSuccess("some data");
}
Blocking Call
// Obtains the feature at a given position.
rpc GetFeature(Point) returns (Feature) {}
Client
/**
* Blocking unary call example.
Calls getFeature and prints the response.
*/
public void getFeature(int lat, int lon) {
info("*** GetFeature: lat={0} lon={1}", lat, lon);
Point request = Point.newBuilder()
.setLatitude(lat)
.setLongitude(lon)
.build();
Feature feature = blockingStub.getFeature(request);
}
Server
receives an observer as if this was a non blocking call.
public void getFeature(Point Point, StreamObserver responseObserver) {
responseObserver.onNext(getFeatureFor(point));
responseObserver.onCompleted();
}
Networking Library ensures the call is blocking.
ListenableFuture responseFuture = futureUnaryCall(call, param);
while(!responseFuture.isDone()) {
try {
executor.waitAndDrain();
} catch (InterruptedException var8) {
Thread.currentThread().interrupt();
throw Status.CANCELLED.withDescription("Call was interrupted").withCause(var8).asRuntimeException();
}
}
return getUnchecked(responseFuture);
Streaming Async call
// Accepts a stream of Points on a route being traversed, returning a
// RouteSummary when traversal is completed.
rpc RecordRoute(stream Point) returns (RouteSummary) {}
Client
Send an observer for response
StreamObserver requestObserver = asyncStub.recordRoute(responseObserver);
Send points on the received observer
for (int i = 0; i < numPoints; ++i) {
int index = random.nextInt(features.size());
Point point = features.get(index).getLocation();
requestObserver.onNext(point);
// Sleep for a bit before sending the next one.
Thread.sleep(random.nextInt(1000) + 500);
}
Server
@Override
public StreamObserver recordRoute(final StreamObserver responseObserver) {
return new StreamObserver() {
int pointCount;
int distance;
Point previous;
final long startTime = System.nanoTime();
@Override
public void onNext(Point point) {
pointCount++;
// For each point after the first, add the incremental distance from the previous point to
// the total distance value.
if (previous != null) {
distance += calcDistance(previous, point);
}
previous = point;
}
@Override
public void onCompleted() {
long seconds = NANOSECONDS.toSeconds(System.nanoTime() - startTime);
responseObserver.onNext(RouteSummary.newBuilder().setPointCount(pointCount)
.setDistance(distance)
.setElapsedTime((int) seconds).build());
responseObserver.onCompleted();
}
};
}
We saw in previous examples that server received an observer which it calls methods on to send data/status/error
How can one machine calling methods on an object result to methods being called on another object sitting on another machine.
Or how is this observer java object shared?
gRPC uses netty under the hood.


Under the General tab, fill out the following information.
Name - class name to create, must be a valid Java name. Use camel-case for multipart names. This will then update other settings to match.
Display name - to show in UI, etc.
Plural - name used for many of these objects.
DB Name - table name.
Pkey Name - name of DB table primary key.
Display Property - this can be set to any property (or calc property) that is the default display for this class.
Sort Property - name of property to sort by default. It can also be a property that is flagged as a sequence property, which will automatically be numbered in the order it was last sorted.
Est Total - estimated total amount of objects that will be created. This is for documentation only.
Use DataSource - check if this should also exist in the database.
Local Only - if true, then changes to this object will not be communicated to other servers.
Add to Cache - if this is a local only object, then it can be choosen to be excluded from the OAObjectCache.
Pre-Select - if true, then all objcts will be selected during program startup.
Lookup - true if this object is used for a drop down type of selection.
Server Root - if true then this the object will be selected from database and included in the ServerRoot as a reference. The ServerRoot object is a top level object that will be sent to client applications during startup. If checked, then an editor will be displayed to define the query to use.
ClientRoot - similar to the ServerRoot, but this object is unique for each client that connects to the server.
Hide - if checked then this object should be hidden when the Model's display settings is set to hide hidden objects.
Hide Links - if checked then this object's links should be hidden when the Model's display settings is set to hide hidden links.
Flag - if true, then this object can be color coded.


Copyright (c) 2003 Chris Huntoon
This game is played on the following 8x8 square board:
|
| An example Blue's turn. The marked blue stone captures the marked red stone and wins in the next moves. Red cannot stop the a7 or a8 stones to reach his corner. |


Welcome!
Let's get some work done.
Parently was created to help children and parents keep track of household chores. It is recomended for
kids over 8 years old.
On Parently you can also keep track of your weekly PRIZES! It's easy to manage and fun to use. To get
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com.phunware.mapping.model
Interfaces
Recyclable
Classes
Building
Building
BuildingInfo
BuildingInfo
BuildingOptions
BuildingOptions
Floor
Floor
FloorOptions
FloorOptions
FloorResourceOptions
FloorResourceOptions
InternalSharedLocation
InternalSharedLocation
InternalSharedLocationArray
InternalSharedLocationArray
LandmarkManeuverOptions
LocationOptions
LocationOptions
OcclusionCalculator
OcclusionCalculator
PoiType
PoiType
PoiTypeOptions
PoiTypeOptions
Point
Point
PointOptions
PointOptions
PortalReferencePointOptions
PortalReferencePointOptions
ReferencePointOptions
ReferencePointOptions
Route
Route
RouteConfig
RouteConfig
RouteManeuver
RouteManeuver
RouteManeuverOptions
RouteManeuverOptions
RouteOptions
RouteOptions
RouteStep
RouteStep
RouteStepOptions
RouteStepOptions
SharedLocation
SharedLocation
VenueOptions
VenueOptions


Blue**** Consulting Services
We are a Blue**** Consulting Service, we supply the latest of Consulting offerings to the market.
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- As a company we offer planned, measured approaches to pro-active systems maintenance, security, backup and disaster recovery to reduce 'downtime'.
- Costs are budgeted, planned and controlled which result in very hard dollar savings for the company.
- I have the capability to adjust day-to-day technology support levels. This flexibility comes with ease and without effecting the livelihood or moral of employees.
- I have the best practices and comprehensive experiences around planning, implementing and maintaining such systems allow myself to successfully deliver these productivity improvements.
- I want to be competitive with my rivals and I have the technology tools that really help me to deliver.
Source - Top 10 Benefits of IT Consulting.


Due to massive loads on the server side, audio is disabled until there are more servers.
Furthermore, beware that audio is not working properly. There are many problems to solve.


Some kind of patterns can not be captured with an ordinary feedfoward neuronal network. Take for example the function plotted below. Well it is not a function in mathematical sense, because the mapping $X \mapsto Y$ is ambiguous. So we can not use a function $X \mapsto Y$ to regress such a pattern.
Mixture Density Networks (MDN) model this pattern with a mixture of Gaussian distributions. The loss fucntion for this network can be derived from minimizing the negative log-likelihood of the data, w.r.t. the mixture of Gaussian distributions.
\begin{equation} \mathcal{L}(y,x) = - \log \Big[ \sum_{k=0}^{K} \Pi_k(x) \cdot \mathcal{N}\big(y | \mu_k(x), \sigma_k(x) \big) \Big] \end{equation}
We can benefit from implementations already provided in tf.contrib.distributions
for both, the categorical distribution $\Pi_k(x)$
tf.contrib.distributions.OneHotCategorical(probs= [0.1, 0.5, 0.4])
and the Gaussian parts $\mathcal{N}$ of the mixture
tf.contrib.distributions.Normal(loc= 0.0, scale= 1.0)
We use a neuronal network to regress the parameters of the distributions: We want $\pi$ to be a categorical distribution summing to one. This can be achieved by soft-max loss. The soft max loss for the logits $z$ of the mixture distribution $\pi$ is: \begin{equation} \pi_j = \sigma(z_j) = \frac{e^{z_j}}{\sum_{k=0}^{K} e^{z_k}} \end{equation}
For numerical stability reasons we do not regress $\pi$ directly with the network, but the probabilities in log-space $\log(\pi)$. This simplifies the soft-max as follows:
\begin{align} \forall_j: \; \log(\pi_j) = \log\big(\sigma(z_j)\big) & = \log\big(\frac{e^{z_j}}{\sum_{k=0}^{K} e^{z_k}} \big) \end{align}
\begin{align} = \log\big(e^{z_j} \big) - \log \big( \sum_{k=0}^{K} e^{z_k} \big) \end{align}
\begin{align} = z_j - \log \big( \sum_{k=0}^{K} e^{z_k} \big) \end{align}
The second part of the formula can be computed numerically stable with
tf.reduce_logsumexp(...)
Let’s see how the loss changes with these adaptions:
\begin{align} \mathcal{L}(y,x) & = - \log \Big[ \sum_{k=0}^{K} \Pi_k(x) \cdot \mathcal{N}\big(y | \mu_k(x), \sigma_k(x) \big) \Big] \end{align}
\begin{align} = - \log \Big[ \sum_{k=0}^{K} e^{\log\big(\pi_k(x) \big)} \cdot \mathcal{N}\big(y | \mu_k(x), \sigma_k(x) \big) \Big] \end{align}
\begin{align} = - \log \Big[ \sum_{k=0}^{K} e^{\log\big(\pi_k(x) \big) + \log \Big( \mathcal{N}\big(y | \mu_k(x), \sigma_k(x) \big) \Big) } \Big] \end{align}
The probability of the Gaussian in log-space simplifies to: \begin{align} \log \Big( \mathcal{N}\big(y | \mu_k(x), \sigma_k(x) \big) \Big) &= \log(\frac{1}{\sigma \sqrt{2\pi}}) + \log\Big(e^{- 0.5 \big( \frac{y - \mu_k}{\sigma} \big)^2} \Big) \end{align}
\begin{align} = \log(\frac{1}{\sigma \sqrt{2\pi}}) - 0.5 \big( \frac{y - \mu_k}{\sigma} \big)^2 \end{align}
\begin{align} = \log(\frac{1}{\sigma \sqrt{2\pi}}) - 0.5 \frac{ (y - \mu_k ) ^2 }{\sigma ^2} \end{align}
\begin{align} = \log(\frac{1}{\sigma \sqrt{2\pi}}) - 0.5 \frac{ (y - \mu_k ) ^2 }{e^{2 * \log(\sigma)}} \end{align}
\begin{align} = -log(\sigma) - \log(\sqrt{2\pi}) - 0.5 \frac{ (y - \mu_k ) ^2 }{e^{2 * \log(\sigma)}} \end{align}
The loss is now a function of $\log(\sigma), \log(\Pi)$ and $ \mu$ which we regress with the neural network.
Additionally we can add a temperature parameter $\tau$ to control the uncertainty of our learned model as you can see below.
If we cut a slice of the plot for $X=0$ we can see the learned mixture of Gaussians for the distribution $\mathcal{P}(Y)$ over outcomes $Y$ :


Shank doner capicola tenderloin sirloin jerky spare ribs frankfurter ground round beef corned beef. Corned beef shankle pork chop leberkas ball tip boudin. Venison pork loin pancetta, flank landjaeger doner pastrami brisket strip steak salami bresaola cow shoulder meatball jowl. Rump pork chop jowl doner beef ribs spare ribs biltong kielbasa prosciutto tri-tip cupim picanha filet mignon.  Tail bacon ham hock, turducken bresaola flank swine shankle pastrami kevin boudin leberkas pork chop tongue short loin. Tenderloin shoulder leberkas flank.
ouille pork belly spare ribs, leberkas ham meatball filet mignon jerky cupim frankfurter rump ball tip. Sausage tongue strip steak porchetta t-bone salami beef chicken, pork belly shank pastrami.
Eula Parker - CEO at Comp inc
Biltong frankfurter brisket pastrami ground round kielbasa turkey cupim pig. Jowl spare ribs chicken, pork loin short ribs beef ham cow frankfurter corned beef salami filet mignon meatball pancetta.  Fatback venison cupim rump.
Short loin tongue salami kevin, drumstick tenderloin pork. Picanha tri-tip sirloin, doner bacon filet mignon beef. Frankfurter pork belly leberkas, tri-tip corned beef t-bone tail. Capicola flank hamburger pork. Turducken tongue landjaeger ribeye, frankfurter ball tip flank biltong ground round strip steak prosciutto short loin pork belly beef ribs shankle.
Pork belly porchetta short loin shankle cow pork, leberkas sirloin corned beef shoulder. Hamburger pork loin porchetta, cow beef ribs salami biltong ham frankfurter meatloaf turducken venison. Shank frankfurter ball tip porchetta jowl tongue. Jerky meatloaf andouille swine salami, strip steak pork belly porchetta pork.
Tri-tip filet mignon ground round landjaeger, meatloaf t-bone venison hamburger pork loin pancetta sausage corned beef spare ribs short loin swine. Tail tongue corned beef turducken swine sausage prosciutto. Biltong drumstick pork chop, t-bone pancetta tail jerky beef ribs. Short ribs venison sirloin picanha leberkas cow filet mignon t-bone frankfurter shankle cupim


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My experience of working on Enterprise and Academic software projects; knowledge of collaborating with client, support and QA teams; have equipped me with the attributes and skills which can fuel my passion for Software Engineering and Computer Science.
My demonstrated ability to research and develop features in existing or new products, with a passion for providing quality solutions, has been expanding my horizons! I understand the need of continuous education and learning with the advancement of technologies to provide quality solutions.


Parth Samthaan on his rapport with co-star Erica Fernandes
by Priyanka BoruaParth Samthaan and Erica Fernandes’ professional relationship made headlines when many reported that the ‘Kasautii Zindagii Kay 2’ (Star Plus) stars were not cordial with each other. While speaking about his co-stars Samthaan said that work arguments happen but he and Fernandes are still good friends.
Samthaan revealed, “We are good friends and friendly even today. We are in a good space. We work together daily on our TV serial and things are smooth between us. At times, there are some arguments or differences of opinions at work, but this is normal. In fact, recently, the cast came over to my new house and we all chilled together. I am not even aware of most of these so-called rumours, so we don’t need to deal with it.”
‘Kasautii Zindagii Kay 2’ is produced by Ekta Kapoor.


History
Created Saturday 10 July 2021
- The Human Past by Chris Scarre (ed.)
- How Humans Evolved by Boyd and Silk
- Why the West Rules, for Now by Ian Morris
- A History of Western Society by McKay, Hill and others
- A Little History of the World by Ernst Gombrich.
- Cities by John Reader
- Atlantic: Great Sea Battles, Heroic Discoveries, Titanic Storms, and a Vast Ocean of a Million Stories by Simon Winchester
- The Mediterranean in the Time of Philip the Second (Vol. 1) (Vol. 2) by Fernand Braudel.
- Empires of the Word by Nicholas Ostler.
- Energy in World History by Vaclav Smil.
- The Prize: The Epic Quest for Oil, Money & Power by Daniel Yergin.
- Pharaoh Triumphant: The Life and Times of Ramesses II by Kenneth Kitchen (1982).
- Caesar: Life of a Colossus by Adrian Goldsworthy (2006).
- Cleopatra: Beyond the Myth by Michel Chauveau, translated by David Lorton (2002).
- Arsinoë of Egypt and Macedon: A Royal Life by Elizabeth Donnelly Carney (2013).
- Nelson: A Dream of Glory and The Sword of Albion by John Sudgen (2004/2012).
- The Autobiography of a Seaman by Admiral Lord Thomas Cochrane
- Hugh Trevor-Roper: The Biography by Adam Sisman
- Leibniz: An Intellectual Biography by Maria Rosa Antognazza (2011).
- Descartes: An Intellectual Biography by Stephen Gaukroger
- McClellan's War: The Failure of Moderation in the Struggle for Union by Ethan Rafuse.
- The Triumph of the Moon: A History of Modern Pagan Witchcraft by Ronald Hutton
- Blood and Mistletoe: The History of the Druids in Britain by Ronald Hutton
- The Birth of the Modern World: Global Connections and Comparisons 1780-1914 by C.A. Bayly.
- The Red Flag: A History of Communism by David Priestland.
- The Global Cold War: Third World Interventions and the Making of Our Times by Odd Arne Westad.
- Inside Terrorism by Bruce Hoffman
- The Looming Tower by Lawrence Wright
- Bringing the War Home: The Weather Underground, the Red Army Faction and Revolutionary Violence in the Sixties and Seventies by Jeremy Varon
- The Structure of Scientific Revolutions
- Discovering Women's History, Deirdre Beddoe
- A Social History of Women in Ireland 1870-1970, Rosemary Cullen Owens
- Fighting Different Wars, Janet Watson
- Women's Letters: America from the Revolutionary War to the Present
- Gender and the politics of history by Joan W. Scott
- Ale, Beer and Brewsters: Women's Work in a Changing World, 1300-1600, Judith Bennett
- Soviet Women on the Frontline in the Second World War by Roger D. Marwick & Euridice Charon Cardona
- Why Stalin's Soldiers Fought: The Red Army's Military Effectiveness in World War II by Roger R. Reese
- Eichmann in Jerusalem: A Report on the Banality of Evil by Hannah Arendt.
- The Eichmann Trial by Deborah Lipstadt.
- Ordinary Men: Reserve Police Battalion 101 and the Final Solution in Poland by Christopher R. Browning.
- Hitler's Willing Executioners: Ordinary Germans and the Holocaust by Daniel Goldhagen
- An Uncompromising Generation: The Nazi Leadership of the Reich Security Main Office by Michael Wildt
- Hitler's Furies: German Women in the Nazi Killing Fields by Wendy Lower
- Denying the Holocaust: The Growing Assault on Truth and Memory by Deborah Lipstadt
- History on Trial: My Day in Court with David Irving. by Deborah Lipstadt
- Lying About Hitler: History, Holocaust, and the David Irving Trial by Richard J. Evans
- A Mosaic of Victims: Non-Jews Persecuted and Murdered by the Nazis. edited by Michael Berenbaum
- Between Resistance and Martyrdom: Jehovah's Witnesses in the Third Reich by Detlef Garbe
- Gypsies Under the Swastika by Donald Kenrick, Grattan Puxon
- The pink triangle. The persecution of homosexual males in concentration camps in Nazi Germany. by Rüdiger Lautmann
- For the Soul of Mankind: The United States, the Soviet Union, and the Cold War by Melvyn Leffler
- America's Cold War: The Politics of Insecurity by Campbell Craig and Fredrik Logevall.
- Strategies of Containment: A Critical Appraisal of American National Security Policy during the Cold War by John Lewis Gaddis.
- The Tragedy of American Diplomacy by William Appleman Williams
- Know Your Enemy: The Rise and Fall of America's Soviet Experts by David Engerman.
- Hong Kong and the Cold War: Anglo-American Relations
- The Last Colonial Massacre: Latin America in the Cold War by Greg Grandin.
- Neither Peace Nor Freedom: The Cultural Cold War in Latin America by Patrick Iber.
- That Infernal Little Cuban Republic: The United States and the Cuban Revolution by Lars Schoultz.
- The Institute of Pacific Relations: Asian Scholars and American Politics by John N. Thomas.
- Spying on the Bomb: American Nuclear Intelligence from Nazi Germany to Iran and North Korea by Jeffrey Richelson.
- Cold War Triumphalism: The Misuse of History after the Fall of Communism edited by Ellen Schrecker.
- How We Forgot the Cold War: A Historical Journey Across America by Jon Weiner.
- Uncertain Empire: American History and the Idea of the Cold War edited by Duncan Bell and Joel Isaac.
- Tombstone: The Great Chinese Famine 1958-1962 by Yang Jisheng; translated by Stacy Mosher and Guo Jian
- China Under Mao: A Revolution Derailed by Andrew G. Walder
- Mao’s Last Revolution by Roderick MacFarquhar and Michael Schoenhals
- Deng Xiaoping and the Transformation of China by Ezra F. Vogel
- Neither Gods nor Emperors: Students and the Struggle for Democracy in China by Craig J. Calhoun
- Freedom at Midnight by Larry Collins
- Kashmir's Contested Pasts: Narratives, Sacred Geographies, and the Historical Imagination by Chitralekha Zutshi
- The Myth of the Holy Cow by D.N. Jha
- Indian Fire Ritual by Musashi Tachikawa, Shrikant Bahulkar, and Madhavi Kolhatkar
Backlinks: Recommended Reading, Watching


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Travel
I have always loved travelling since I was young lad.
My family and I go on holiday most summers.
We usually go to France or Spain, but we have gone to England the past couple of years.
Spain
My first memory of going on holidays was to Barcelona, Spain when I was 5 years old with my family.
We mostly stayed in Barcelona and Salou when we went to Spain, but one year, we went to the Basque country.
I have seen a couple of soccer games whilst there, primarily Espanyol FC games (as Barcelona FC games are very expensive).
Another attraction in Barcelona/Salou is the Portaventura entertainment park, which we visited every time we went to the area.
The Basque country was also very interesting to visit, as it very different culturally from the rest of Spain, much like Catalonia, where Barcelona is located.
I managed to get to an Athletic Bilbao match while there, which was very entertaining.
France
France was where my family and I went on holidays the most.
We have been all around France, staying in a variety of caravan parks and camping sites.
I enjoyed these places the most, as I was given a lot of freedom of where I could go, that I didn't have at home.
We also visited Paris, and Disneyland, a couple of times.
I enjoyed visiting French historical sites and museums immensely, especially Medieval sites, due to my interest in history.
England
In the last few years, my family and I have started going to England for our holidays.
We usually go for city breaks, in cities such as Liverpool, Manchester and London.
We have also visited theme parks while in England, such as Alton Towers, near Stoke.
My brother and I also go to Premier League soccer games every year.
Since we support Spurs and Chelsea respectively, we try to get tickets for this match, though since it is a derby game, this isn't always possible.


An Essay on Typography by Eric Gill takes the reader back to the year 1930. The year when a conflict between two worlds came to its term. The machines of the industrial world finally took over the handicrafts.
The typography of this industrial age was no longer handcrafted. Mass production and profit became more important. Quantity mattered more than the quality. The books and printed works in general lost a part of its humanity. The typefaces were not produced by craftsmen anymore. It was the machines printing and tying the books together now. The craftsmen had to let go of their craft and became a cog in the process. An extension of the industrial machine.
But the victory of the industrialism didn’t mean that the craftsmen were completely extinct. The two worlds continued to coexist independently. Each recognising the good in the other — the power of industrialism and the humanity of craftsmanship. This was the second transition that would strip typography of a part of its humanity. We have to go 500 years back in time to meet the first one.
A similar conflict emerged after the invention of the first printing press in Europe. Johannes Gutenberg invented movable type and used it to produce different compositions. His workshop could print up to 240 impressions per hour. Until then, the books were being copied by hand. All the books were handwritten and decorated with hand drawn ornaments and figures. A process of copying a book was long but each book, even a copy, was a work of art.
The first printed books were, at first, perceived as inferior to the handwritten ones. They were smaller and cheaper to produce. Movable type provided the printers with flexibility that allowed them to print books in languages other than Latin. Gill describes the transition to industrialism as something that people needed and wanted. Something similar happened after the first printed books emerged. People wanted books in a language they understood and they wanted books they could take with them. They were hungry for knowledge and printed books satisfied this hunger.
But, through this transition, the book lost a large part of its humanity. The machine took over most of the process but craftsmanship was still a part of it. The typefaces were cut manually by the first punch cutters. The paper was made by hand. The illustrations and ornaments were still being hand drawn. These were the remains of the craftsmanship that went almost extinct in the times of Eric Gill.
The first transition took away a large part of humanity from written communication.  But it’s the third transition that stripped it naked. Typefaces are faceless these days. They’re just fonts on our computers. Hardly anyone knows their stories. Hardly anyone cares. Flicking through thousands of typefaces and finding the “right one” is a matter of minutes.
Typography is not about typefaces. It’s not about what looks best, it’s about what feels right. What communicates the message best. Typography, in its essence, is about the message. “Typographical design should perform optically what the speaker creates through voice and gesture of his thoughts.”, as El Lissitzky, a famous Russian typographer, put it.
Each transition took away a part of humanity from written language. Handwritten books being the most humane form and the digital typefaces being the least. Overuse of Helvetica is a good example. Messages are being told in a typeface just because it’s a safe option. It’s always there. Everyone knows it but yet, nobody knows it. Stop someone on the street and ask him what Helvetica is? Ask a designer the same question. Ask him where it came from, when, why and who designed it. Most of them will fail to answer these questions. Most of them used it in their precious projects but they still don’t spot it in the street.
Typefaces don’t look handmade these days. And that’s all right. They don’t have to. Industrialism took that away from them and we’re fine with it. We’ve traded that part of humanity for a process that produces more books that are easier to read. That can’t be bad. And it isn’t.
We’ve come close to “perfection” in the last five centuries. The letters are crisp and without rough edges. We print our compositions with high–precision printers on a high quality, machine made paper.
We lost a part of ourselves because of this chase after perfection. We forgot about the craftsmanship along the way. And the worst part is that we don’t care. The transition to the digital age made that clear. We choose typefaces like clueless zombies. There’s no meaning in our work. Type sizes, leading, margins… It’s all just a few clicks or lines of code. The message isn’t important anymore. There’s no more “why” behind the “what”.
Human beings aren’t perfect. Perfection is something that will always elude us. There will always be a small part of humanity in everything we do. No matter how small that part, we should make sure that it transcends the limits of the medium. We have to think about the message first. What typeface should we use and why? Does the typeface match the message and what we want to communicate with it? What will be the leading and why? Will there be more typefaces in our design? On what ground will they be combined? What makes our design unique and why? This is the part of humanity that is left in typography. It might be the last part. Are we really going to give it up?
We lost a part of ourselves because of this chase after perfection. We forgot about the craftsmanship along the way. And the worst part is that we don’t care. The transition to the digital age made that clear. We choose typefaces like clueless zombies. There’s no meaning in our work. Type sizes, leading, margins… It’s all just a few clicks or lines of code. The message isn’t important anymore. There’s no more “why” behind the “what”.
Human beings aren’t perfect. Perfection is something that will always elude us. There will always be a small part of humanity in everything we do. No matter how small that part, we should make sure that it transcends the limits of the medium. We have to think about the message first. What typeface should we use and why? Does the typeface match the message and what we want to communicate with it? What will be the leading and why? Will there be more typefaces in our design? On what ground will they be combined? What makes our design unique and why? This is the part of humanity that is left in typography. It might be the last part. Are we really going to give it up?


--- title: A first pass at Latent Profile Analysis using MCLUST (in R) author: ~ date: '2017-08-22' slug: lpa-in-r-using-mclust categories: [r, r-package] tags: [tidyLPA, mixture-models] description: Desc ---
Since writing this post, I have worked with colleagues to release an R package to carry out the analysis. The package is tidyLPA and is described in the following sections, through the “Original Post” header below which is the beginning of the original post.
Latent Profile Analysis (LPA) is a statistical modeling approach for estimating distinct profiles, or groups, of variables. In the social sciences and in educational research, these profiles could represent, for example, how different youth experience dimensions of being engaged (i.e., cognitively, behaviorally, and affectively) at the same time.
tidyLPA provides the functionality to carry out LPA. LPA is a statistical modeling approach for estimating parameters (i.e., the means, variances, and covariances) for profiles. Note that tidyLPA is still at the beta stage! Please report any bugs at https://github.com/jrosen48/tidyLPA or send an email to<EMAIL_ADDRESS>You can install tidyLPA from CRAN with:
install.packages("tidyLPA")
You can also install the in-development version of tidyLPA from GitHub with:
install.packages("devtools")
devtools::install_github("jrosen48/tidyLPA")
Here is a brief example using the built-in pisaUSA15
dataset and variables for broad interest, enjoyment, and self-efficacy. Note that we first type the name of the data frame, followed by the unquoted names of the variables used to create the profiles. We also specify the number of profiles and the model. See ?estimate_profiles
for more details.
library(tidyLPA)
## Note that an update to tidyLPA is forthcoming; see vignette('introduction-to-major-changes') for details!
d <- pisaUSA15[1:100, ]
m3 <- estimate_profiles(d,
broad_interest, enjoyment, self_efficacy,
n_profiles = 3)
## Fit Equal variances and covariances fixed to 0 (model 1) model with 3 profiles.
## LogLik is 283.991
## BIC is 631.589
## Entropy is 0.914
plot_profiles(m3, to_center = TRUE)
To learn more:
As tidyLPA is at an early stage of its development, issues should be expected. If you have any questions or feedback, please do not hesitate to get in touch:
Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.
This post is a first attempt about carrying out LPA using MCLUST in R. MCLUST does model-based clustering, as or as the authors describe it, Gaussian Mixture Modeling, since LPA can be seen as one way to do mixture modeling through general latent variable modeling software. Another post will focus on OpenMx (and MPlus), both of which do that.
When carrying out LPA, we can fit an unconstrained model, in which not only the measured variables’ means, but also their variance and covariances, are different, or freely-estimated, across profiles, or mixture components. However, we also sometimes estimate commonly-specified models that are more constrained as part of a model-building process.
Namely, we are commonly interested in those in which the residual variances are constrained (to be the same across components) or freely-estimated (to be different across components) and the covariances are fixed (to be zero, i.e. the covariance matrix is diagonal, in that only the cells on the diagonal, or the variances, are estimated) or freely-estimated.
Let’s get started.
Here is a first pass, using the iris data, which is built into R.
First, let’s explore fit indices for each of the three models with between one and six mixture components. Like MCLUST does in its built-in function, we can plot these values of the Bayesian Information Criteria (BIC).
library(tidyverse, warn.conflicts = FALSE)
library(mclust)
library(hrbrthemes)
data(iris)
df <- select(iris, -Species)
explore_model_fit <- function(df, n_profiles_range = 1:9, model_names = c("EII", "VVI", "EEE", "VVV")) {
x <- mclustBIC(df, G = n_profiles_range, modelNames = model_names)
y <- x %>%
as.data.frame.matrix() %>%
rownames_to_column("n_profiles") %>%
rename(`Constrained variance, fixed covariance` = EII,
`Freed variance, fixed covariance` = VVI,
`Constrained variance, constrained covariance` = EEE,
`Freed variance, freed covariance` = VVV)
y
}
fit_output <- explore_model_fit(df, n_profiles_range = 1:6)
to_plot <- fit_output %>%
gather(`Covariance matrix structure`, val, -n_profiles) %>%
mutate(`Covariance matrix structure` = as.factor(`Covariance matrix structure`),
val = abs(val)) # this is to make the BIC values positive (to align with more common formula / interpretation of BIC)
library(forcats)
to_plot$`Covariance matrix structure` <- fct_relevel(to_plot$`Covariance matrix structure`,
"Constrained variance, fixed covariance",
"Freed variance, fixed covariance",
"Constrained variance, constrained covariance",
"Freed variance, freed covariance")
ggplot(to_plot, aes(x = n_profiles, y = val, color = `Covariance matrix structure`, group = `Covariance matrix structure`)) +
geom_line() +
geom_point() +
ylab("BIC (smaller value is better)") +
theme_ipsum_rc()
From red to purple, the models become less constrained (more free). It appears that a two or three profile (mixture component) model with freely-estimated residual variances and covariances, or a four profile model with constrained residual covariances and variances, fit best (based on interpreting the BIC).
Given this, we can fit (and inspect) a model, say, the three profile model with freely-estimated residual variance and covariances.
create_profiles_mclust <- function(df,
n_profiles,
variance_structure = "freed",
covariance_structure = "freed"){
if (variance_structure == "constrained" & covariance_structure == "fixed") {
model_name <- "EEI"
} else if (variance_structure == "freed" & covariance_structure == "fixed") {
model_name <- "VVI"
} else if (variance_structure == "constrained" & covariance_structure == "constrained") {
model_name <- "EEE"
} else if (variance_structure == "freed" & covariance_structure == "freed") {
model_name <- "VVV"
} else if (variance_structure == "fixed") {
stop("variance_structure cannot equal 'fixed' using this function; change this to 'constrained' or 'freed' or try one of the models from mclust::Mclust()")
}
x <- Mclust(df, G = n_profiles, modelNames = model_name)
print(summary(x))
dff <- bind_cols(df, classification = x$classification)
proc_df <- dff %>%
mutate_at(vars(-classification), scale) %>%
group_by(classification) %>%
summarize_all(funs(mean)) %>%
mutate(classification = paste0("Profile ", 1:n_profiles)) %>%
mutate_at(vars(-classification), function(x) round(x, 3)) %>%
rename(profile = classification)
return(proc_df)
}
m3 <- create_profiles_mclust(df, 3, variance_structure = "freed", covariance_structure = "freed")
We can then plot the mean values for the variables used to estimate the model for each of the two profiles. Of course, there are other models that we may want to inspect with different covariance matrix structures or profile numbers.
m3 %>%
gather(key, val, -profile) %>%
ggplot(aes(x = profile, y = val, fill = key, group = key)) +
geom_col(position = "dodge") +
ylab("Z-score") +
xlab("") +
scale_fill_discrete("") +
theme_ipsum_rc()
Please send me a message if you have any comments.
A big thank you to my colleagues You-Kyung Lee and Kristy Robinson for helping me begin to understand LPA.


--- layout: page title: Solutions --- {% for solution in site.data.opensource-solutions %}
Description: {{solution.description}}


Groupies, take heed: Marrying a musician may ultimately benefit your lawyer more than it will you. That's the message of ``Why Do Fools Fall In Love?'' about the three-way battle for the estate of singer Frankie Lymon, who died at the age of 25 in 1968 from a heroin overdose.
In his wake, Lymon left behind a trio of women all claiming to be his legitimate widow: Zola Taylor (Halle Berry), a singer with the Platters; Elizabeth Waters (Vivica A. Fox), a good girl gone wrong; and Emira Eagle (Lela Rochon), a strait-laced schoolteacher from Georgia. Certainly, considering what each lady had to put up with while being around the former teen idol, each was entitled to some kind of monetary compensation.
The picture ``Fools'' paints of Lymon is woefully incomplete - writer Tina Andrews can't seem to put her finger on exactly what led to Lymon's heroin addiction, for instance - but what's shown is unflattering and sad. An overnight success with his racially mixed group The Teenagers in the late 1950s, the sweet-voiced Lymon fell out of favor with the public almost as quickly, thanks to his forbidden dance with a white girl on national TV and his ill-fated attempt to go solo. Like many teen idols, he was effectively washed-up before age 20.
In what can only be read as an attempt to spice up his otherwise dreary life, Lymon first romanced Taylor, then married Waters before setting his sights on wholesome Eagle. All were won over by Lymon's charm and attentiveness. Taylor and Waters would later suffer greatly for their association with him. While Lymon once sang ``I'm Not A Juvenile Delinquent,'' offstage he was a junkie, a thief and a user.
Berry, Rochon and Fox are all far more believable as young women than they are in the sequences set in the mid-1980s in which director Gregory Nava allows each to ham it up disconcertingly. As Lymon, Larenz Tate capably handles a difficult character whose behavior ranges from beguiling to bizarre, but the true highlight of the cast is the incomparable Little Richard, playing himself with panache.
``Fools'' turns up the occasional insight into how this irresponsible man wormed his way into the hearts of three very different women, but more often than not Andrews' screenplay can't decide if it's a cautionary tale about the perils of marrying a has-been or a rowdy ``you go, girl'' celebration of sisterhood. The movie's timeline is pitifully tangled from the very start, when Waters hears Diana Ross' ``new'' cover of the Lymon-penned ``Why Do Fools Fall In Love?'' in 1985 - four years after the record went gold. In a scene set in 1964, Waters and Lymon listen to Otis Redding's ``Try A Little Tenderness'' on the radio; an astonishing feat considering the song wasn't recorded until 1966.
When it comes to recreating the Alan Freed rock-n-roll shows of the 1950s and the deliciously tacky go-go look of TV's ``Hullabaloo,'' the movie scores. But the courtroom battle that forms the dramatic centerpiece of the film is not exactly a nail-biter; it's a clear case of ``Smart-Mouthed Women, Foolish Choices.''
James Sanford
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
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Related links: index of all rec.arts.movies.reviews reviews


In the past two months I have taken varying amounts of brugmansia tea of different strengths several times. I have no plans to take it again, but I might some day. I have an Angels Trumpet growing in my backyard so it is easy enough for me to get some whenever I want.
My first experience I took two flowers and two leaves, placed them in about 700mL of water and boiled it for 25 minutes down to 400-420 mL. I strained the plant material out, squished it to squeeze all the liquid out, then placed the liquid in the freezer to cool down. In twenty minutes it was luke warm, so I added ice cubes to it, and drank 380mL of it, and threw the rest of it out.
I drank this over 10 minutes while on the phone to my (at the time) girlfriend. While on the phone we had a small fight and this put me in a bad mood, and I was worried it would ruin my trip. After about 30 minutes my body felt strange. My arms were heavy and walking became difficult. I managed to do everything normal for the next few hours, then went to bed.
Laying in bed I felt nothing while I was still and after a while I fell asleep. After this first lot of sleep I kept 'waking up' (I'm not sure if i woke up because I dont know if i was asleep, more like regained focus) and I saw people. Seeing as it was so long ago I can't remember who I saw first, but I know somewhere in there I saw my girlfriend two or three times, and she would be sitting on the end of my bed, and I'd reach out to touch her and she would disappear.

This first night was by far the strongest experience I've had on brugmansia tea, because at around four in the morning the TV was still on, and I 'woke up' and there was one of those TV Evangelists on, and she was talking to ME. I thought she was having a conversation just with me, and I talked to her for a full hour. She even said 'come over to the prayer chair' and I walked over to the TV and stood there waiting for her to give me a seat. Through the whole thing I just wanted to roll over and ignore her, but I couldn't cos I thought she would get angry and I had no idea she was just the TV.
In the morning I woke up and walked to the shower, wondered where my girlfriend had gone, walked back to my room, then remember I was in my house and she wasn't here.
My second experience went pretty much the same, same dosage as well. Drinking the tea went down pretty easy. Again three hours for the full hallucinatory effects to kick in. This time I drank it before going to my aunties for dinner. Nothing too bad happened, and I didn't really notice the drymouth and smooth hands, but the worst thing I did was ask my nan where my bag was.  Then I asked my aunty where nan went and she gave me a strange look so I didn't say anything for the rest of the night.
After these two first tries, the plant had stopped flowering and I had to make my brew out of the leaves instead. This is now my preferred way to do it, because even though it tastes worse, you have to drink less. When making it from the leaves I use 8 leaves in 2 1/2 cups of water, boil it for about half hour, until there is less than 1 cup of water left, then use that however I am taking it. I had only ever drank it straight after letting it cool down, but one of my friends was the first to try his in normal tea. Since then I've tried mine in coffee, but it doesn't mask the taste.
I never once had a 'bad trip', but I've always (except that time at my aunty's house) done it at home, and tripped while laying in bed. I always get a smooth experience of drifting in and out of 'sleep' while focusing on objects and people. The only bad trip I've ever seen is my friend that tried it in his tea. He ended up laying on the ground, unable to move, yelling at all the spiders. And looking for band aids for no reason. He had never done any drug before and this experience scared him off alcohol for like a month.
The most common effects/experiences during my trips are:
-Worst dry mouth ever (my body stops excreting liquid so that means no saliva and no sweat)
-Smooth hands (from no sweat)
-Bodily discomfort (only while moving, it feels strange. Sitting still it will go unnoticed)
-Inability to read (very very blurry, can't focus)
-Seeing people
-Seeing objects
-Not being able to find things (because i 'saw' it somewhere when it was really somewhere else)
All these effects only last me the night, but my friend that had the bad trip, he couldn't read for two days.
I think seeing somebody has a lot to do with my knowledge of them, who they are and how they react to certain things. The first time I used the tea, I only saw people for a little bit then they would disappear, but the TV had the most effect on me because it had a voice, so I didn't have to create the conversation in my head. Later after I had gotten used to the effects of the tea the people became a lot more interactive, and they would be just like they really were because I was creating them in my head. I actually had to tell a few people that they weren't real and I didn't care, I would talk to them just for the fun of it.
I grew used to whispering to communicate with these people, because talking out loud would wake me up more and I'd realise what I was doing, so i had to whisper to stop them from disappearing. One night when I was seeing people, they couldn't talk (every other time they had so far). So I'd be there reading there lips, telling them I'd gone deaf for some reason, then when they wouldn't respond, I'd speak out loud and my voice would sound really weird. For the few days after this experience I didn't like talking because my voice sounded unfamiliar and I didn't like it.
Long term effects:
While these may not be actual 'effects', they are something that has occured from using the tea for a long time.
-Occasionally once or twice a week I'll say something after not talking for a while, and my voice will be unfamiliar again.
-I also have a bottle that I just drink water out of, so I've always got cold water. After using this during so many of my trips, I can't drink out of it anymore because whenever I do I imagine the taste of the tea. This has stopped me from drinking all cold water. I took a big gulp, and it almost made me throw up (this was while i was sober)
-Last week was the last time I had my tea, and all week I felt sick. This was also when the 'not drinking cold water' kicked in, so doing that made it a lot worse. I'm guessing this was from the build up of doing the tea for so long, because I never felt sick any other time.

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Javascript alternative to our iframe Widget


(Mobilpymes)has 13 repositories available. Follow their code on GitHub.
has 13 repositories available. Follow their code on GitHub.


public class ShootContext
extends java.lang.Object
| Modifier and Type | Field and Description |
|---|---|
static java.lang.String |
SPECIAL_VAR_LAST_SELECTED |
static java.lang.String |
SPECIAL_VAR_PREVIOUSLY_SELECTED |
| Constructor and Description |
|---|
ShootContext(Game game,
View view,
PlayerColor shooterColor,
UndoInfo undoInfo,
ShootInteraction shootInteraction) |
| Modifier and Type | Method and Description |
|---|---|
Board |
getBoard() |
Game |
getGame() |
ShootInteraction |
getInteraction() |
java.util.Set<Player> |
getPlayers() |
java.util.concurrent.BlockingQueue<Request> |
getRequestQueue() |
Player |
getShooter() |
PlayerColor |
getShooterColor() |
Position |
getShooterPosition() |
UndoInfo |
getUndoInfo() |
Expression |
getVar(java.lang.String name) |
View |
getView() |
void |
setVar(java.lang.String name,
Expression value) |
public static final java.lang.String SPECIAL_VAR_LAST_SELECTED
public static final java.lang.String SPECIAL_VAR_PREVIOUSLY_SELECTED
public ShootContext(Game game, View view, PlayerColor shooterColor, UndoInfo undoInfo, ShootInteraction shootInteraction)
public Board getBoard()
public java.util.Set<Player> getPlayers()
public PlayerColor getShooterColor()
public Player getShooter()
public Position getShooterPosition()
public View getView()
public Game getGame()
public ShootInteraction getInteraction()
public java.util.concurrent.BlockingQueue<Request> getRequestQueue()
public UndoInfo getUndoInfo()
public Expression getVar(java.lang.String name)
public void setVar(java.lang.String name, Expression value)


This was group project one for the Full Stack program at Georgia Tech. Here is a link to the GitHub repo.
This was a Project 2 assignment created for the Full Stack program at Georgia Tech. Here is a link to the GitHub repo.
This was a Homework assignment created for the Full Stack program at Georgia Tech. Here is a link to the GitHub repo.
This was a homework assignment created for the Full Stack program at Georgia Tech. Here is a link to the GitHub repo.


These control the delay time of each {_envelope Envelope 2} generator, up to over two seconds. The highest twelve settings instead allow it to be triggered by something other than the key press:
| release | The envelope is triggered when the key is released. | |
| release sustain | The envelope is triggered when the key and sustain footswitch are released, whichever happens last. | |
| mono multiple | All voices share a common envelope computed by the virtual {_instrument}, and that envelope is retriggered on any key press. | |
| mono single | All voices share a common envelope computed by the virtual {_instrument}, and that envelope is triggered when the number of held keys goes from zero to one. This can be useful for simulating the percussion envelope of a Hammond organ. | |
| envelope 1A\nenvelope 1B | These trigger the envelope when either Envelope 1 starts its decay phase. Obviously, that is only useful if the Envelope 1 attack time is set to something other than "instant". | |
| sweep A\nsweep B | These trigger the envelope at the start of each sweep cycle, and release it (unless the sustain footswitch is held) in the middle of the cycle. | |
| \-sweep A\n\-sweep B | These trigger the envelope in the middle of each sweep cycle, and release it (unless the sustain footswitch is held) at the start of the cycle. | |
| \+sweep A\n\+sweep B | These trigger the envelope at the start of each sweep cycle, and again in the middle. |
These are contained in the {Envelope_trigger_cluster Envelope trigger clusters} within the {Envelope_sections Envelope 2 section}.
These are contained in the ENVELOPE 2 section of the right panel, under the following parameter number:
| {sw-19.png height=48} |
These appear in the display as Env2 Trigger.
These are accessed via the following {_NRPN NRPNs}:
| A | 1,23 | |
| B | 2,23 |
| MIDI | display | ||
| 0 | off | (default) | |
| 1 | 20ms | ||
| \b\n\b\n\b | \b\n\b\n\b | ||
| 115 | 2.3s | ||
| 116 | release | ||
| 117 | release sustain | ||
| 118 | mono multiple | ||
| 119 | mono single | ||
| 120 | envelope 1A | ||
| 121 | envelope 1B | ||
| 122 | sweep A | ||
| 123 | sweep B | ||
| 124 | \-sweep A | ||
| 125 | \-sweep B | ||
| 126 | \+sweep A | ||
| 127 | \+sweep B |


Monitoring standard or measures allowed for {{returntype}}
| Method | Method code | Description |
|---|---|---|
| C | ETS | Method from the guidelines for the monitoring and reporting of greenhouse gas emissions under the Emission Trading Scheme |
| C | IPCC | Method from the IPCC guidelines |
| C | MAB | Mass balance method approved by EA |
| C | NRB | National or regional binding calculation method prescribed by legal act for the substance and facility concerned |
| C | OTH | Other calculation method |
| C | PER | Calculation method prescribed by us in an operating permit or licence for the facility |
| C | SSC | European sector-specific calculation method |
| C | UNECE/EMEP | Method from the EMEP/CORINAIR atmospheric emission inventory guidebook |
| M | ALT | Alternative measurement method in accordance with existing CEN/ISO measurement standards |
| M | CRM | Measurement method demonstrated by means of certified reference materials and approved by us |
| M | NRB | National or regional binding measurement method prescribed by legal act for the substance and facility concerned |
| M | OTH | Other measurement method |
| M | PER | Measurement method prescribed by EA in an operating permit or licence for the facility |
| C | Calculation | |
| E | Estimation | |
| M | Weighing |


Seatrips Pool
{{title}}
Delegate: {{delegate.username}}
Rank:
{{delegate.rank}}
Productivity:
{{delegate.productivity}}
Approval:
{{delegate.approval}}
Last payout:
{{lastpayout|date}}
Next payout:
{{nextpayout|date}}
Sharing:
35%
Address
Paid
Pending
{{acc.address}}
{{acc.received|number:4}}
{{acc.pending|number:4}}


marrychToday at 2:24 AM
It would be nice to talk about dpow here
However, dpow requires a hardfork to reverse the blockchain at prior checkpoint level. Im not a dpow expert,if sm knows about dpow it would be nice to talk
Immutability is our priority
a.s.Today at 2:32 AM
Just answered there, that if there is an interest in our community, we will try to get both side together for further discussions
phyroToday at 2:34 AM
We wont be reverting
marrychToday at 2:35 AM
@phyro you mean that we don't want to be reverting or that dpow wont be reverting?
phyroToday at 2:37 AM
we won't be reverting the chain for any reason
marrychToday at 2:38 AM
So they can just explain us how dpow works,and if there is a possibility not to revert
phyroToday at 2:38 AM
i'm not really familiar with it yet


Orbital Optimization
- Optimizing orbitals and CI coefficients
- Orbitals are now optimal for a set of configurations rather than one
- i.e. multireference
- CASSCF
$$
\ket{\boldsymbol{\kappa},\textbf{C}} =
\text{exp}(-\hat{\kappa})
\sum_i C_i \ket{i}
\quad\quad \text{solve for } C_i \text{ and } \kappa
$$
- We can use HCI to solve for \(\{ C_i \}\)
| Variational
|
vHCISCF |
| Variational + PT |
HCISCF |