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The Tragedy of MacBeth
by William Shakespeare
Act 1, Scene 3
Additional Information
- Year Published: 1607
- Language: English
- Country of Origin: England
- Source: Richard Grant White, ed. The Complete Works of William Shakespeare (New York: Sully and Kleinteich)
-
Readability:
- Flesch–Kincaid Level: 11.0
- Word Count: 1,282
- Genre: Tragedy
- Keywords: betrayal, envy, murder, power, revenge, tragedy
- ✎ Cite This
Downloads
SCENE. A heath near Forres.
(Thunder. Enter the three Witches)
First Witch
Where hast thou been, sister?
Second Witch
Killing swine.
Third Witch
Sister, where thou?
First Witch
A sailor's wife had chestnuts in her lap,
And munch'd, and munch'd, and munch'd:—
'Give me,' quoth I:
'Aroint thee, witch!' the rump-fed ronyon cries.

Second Witch
I'll give thee a wind.
First Witch
Thou'rt kind.
Third Witch
And I another.
First Witch
I myself have all the other,
And the very ports they blow,
All the quarters that they know
I' the shipman's card.
I will drain him dry as hay:
Sleep shall neither night nor day
Hang upon his pent-house lid;
He shall live a man forbid:
Weary se'nnights nine times nine
Shall he dwindle, peak and pine:
Though his bark cannot be lost,
Yet it shall be tempest-tost.
Look what I have.
Second Witch
Show me, show me.
First Witch
Here I have a pilot's thumb,
Wreck'd as homeward he did come.
(Drum within)
Third Witch
A drum, a drum!
Macbeth doth come.
ALL
The weird sisters, hand in hand,
Posters of the sea and land,
Thus do go about, about:
Thrice to thine and thrice to mine
And thrice again, to make up nine.
Peace! the charm's wound up.
(Enter MACBETH and BANQUO)
MACBETH
So foul and fair a day I have not seen.
BANQUO
How far is't call'd to Forres? What are these
So wither'd and so wild in their attire,
That look not like the inhabitants o' the earth,
And yet are on't? Live you? or are you aught
That man may question?
MACBETH
Speak, if you can: what are you?
First Witch
All hail, Macbeth! hail to thee, thane of Glamis!
Second Witch
All hail, Macbeth, hail to thee, thane of Cawdor!
Third Witch
All hail, Macbeth, thou shalt be king hereafter!
BANQUO
Good sir, why do you start; and seem to fear
Things that do sound so fair? I' the name of truth,
Are ye fantastical, or that indeed
Which outwardly ye show? My noble partner
You greet with present grace and great prediction
Of noble having and of royal hope,
That he seems rapt withal: to me you speak not.
If you can look into the seeds of time,
And say which grain will grow and which will not,
Speak then to me, who neither beg nor fear
Your favours nor your hate.
First Witch
Hail!
Second Witch
Hail!
Third Witch
Hail!
First Witch
Lesser than Macbeth, and greater.
Second Witch
Not so happy, yet much happier.
Third Witch
Thou shalt get kings, though thou be none:
So all hail, Macbeth and Banquo!
First Witch
Banquo and Macbeth, all hail!
MACBETH
Stay, you imperfect speakers, tell me more:
By Sinel's death I know I am thane of Glamis;
But how of Cawdor? the thane of Cawdor lives,
A prosperous gentleman; and to be king
Stands not within the prospect of belief,
No more than to be Cawdor. Say from whence
You owe this strange intelligence? or why
Upon this blasted heath you stop our way
With such prophetic greeting? Speak, I charge you.
(Witches vanish)
BANQUO
The earth hath bubbles, as the water has,
And these are of them. Whither are they vanish'd?
MACBETH
Into the air; and what seem'd corporal melted
As breath into the wind. Would they had stay'd!
BANQUO
Were such things here as we do speak about?
Or have we eaten on the insane root
That takes the reason prisoner?
MACBETH
Your children shall be kings.
BANQUO
You shall be king.
MACBETH
And thane of Cawdor too: went it not so?
BANQUO
To the selfsame tune and words. Who's here?
(Enter ROSS and ANGUS)
ROSS
The king hath happily received, Macbeth,
The news of thy success; and when he reads
Thy personal venture in the rebels' fight,
His wonders and his praises do contend
Which should be thine or his: silenced with that,
In viewing o'er the rest o' the selfsame day,
He finds thee in the stout Norweyan ranks,
Nothing afeard of what thyself didst make,
Strange images of death. As thick as hail
Came post with post; and every one did bear
Thy praises in his kingdom's great defence,
And pour'd them down before him.
ANGUS
We are sent
To give thee from our royal master thanks;
Only to herald thee into his sight,
Not pay thee.
ROSS
And, for an earnest of a greater honour,
He bade me, from him, call thee thane of Cawdor:
In which addition, hail, most worthy thane!
For it is thine.
BANQUO
What, can the devil speak true?
MACBETH
The thane of Cawdor lives: why do you dress me
In borrow'd robes?
ANGUS
Who was the thane lives yet;
But under heavy judgment bears that life
Which he deserves to lose. Whether he was combined
With those of Norway, or did line the rebel
With hidden help and vantage, or that with both
He labour'd in his country's wreck, I know not;
But treasons capital, confess'd and proved,
Have overthrown him.
MACBETH
[Aside] Glamis, and thane of Cawdor!
The greatest is behind.
[To ROSS and ANGUS]
Thanks for your pains.
[To BANQUO]
Do you not hope your children shall be kings,
When those that gave the thane of Cawdor to me
Promised no less to them?
BANQUO
That trusted home
Might yet enkindle you unto the crown,
Besides the thane of Cawdor. But 'tis strange:
And oftentimes, to win us to our harm,
The instruments of darkness tell us truths,
Win us with honest trifles, to betray's
In deepest consequence.
Cousins, a word, I pray you.
MACBETH
[Aside] Two truths are told,
As happy prologues to the swelling act
Of the imperial theme.—I thank you, gentlemen.
[Aside]
Cannot be ill, cannot be good: if ill,
Why hath it given me earnest of success,
Commencing in a truth? I am thane of Cawdor:
If good, why do I yield to that suggestion
Whose horrid image doth unfix my hair
And make my seated heart knock at my ribs,
Against the use of nature? Present fears
Are less than horrible imaginings:
My thought, whose murder yet is but fantastical,
Shakes so my single state of man that function
Is smother'd in surmise, and nothing is
But what is not.
BANQUO
Look, how our partner's rapt.
MACBETH
[Aside] If chance will have me king, why, chance may crown me,
Without my stir.
BANQUO
New horrors come upon him,
Like our strange garments, cleave not to their mould
But with the aid of use.
MACBETH
[Aside] Come what come may,
Time and the hour runs through the roughest day.

 Kind gentlemen, your pains
Are register'd where every day I turn
The leaf to read them. Let us toward the king.
Think upon what hath chanced, and, at more time,
The interim having weigh'd it, let us speak
Our free hearts each to other.
BANQUO
Very gladly.
MACBETH
Till then, enough. Come, friends.
(Exeunt)


See: Description
| Class | Description |
|---|---|
| Distribution |
This class can be utilized to track the distributions of values.
|
| DistributionAggregateFunction |
This abstract class represents a function that aggregates values from a frequency distribution
|
| DistributionAggregateFunction.DistributionAggregateFunctionArithmeticMean |
This class calculates the arithmetic mean for a given distribution.
|
| DistributionAggregateFunction.DistributionAggregateFunctionGeometricMean |
This class calculates the geometric mean for a given distribution.
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| DistributionAggregateFunction.DistributionAggregateFunctionInterval |
This class calculates the mode for a given distribution.
|
| DistributionAggregateFunction.DistributionAggregateFunctionMedian |
This class calculates the median for a given distribution.
|
| DistributionAggregateFunction.DistributionAggregateFunctionMode |
This class calculates the mode for a given distribution.
|
| DistributionIterator<T> |
An iterator over values of a distribution
|
| IntArrayDictionary |
A hash groupify operator.
|
| IntArrayDictionaryEntry |
Implements an entry.
|


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DISNEY/EVENT411
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BROCHURE REDESIGN
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UX/UI
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MOBILE FRIENDLY CUSTOMER EMAILS
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1. Researched & wrote first draft of Social Media Policy (engaging agencies to learn of competitor social policies) 2. Finalized Intranet layouts, navigation, coordination between IT/PR for kiosk launch 3. Overhauled all website graphics: designed new page graphics, composed and edited copy, and coordinated vendor site art (re-wrote descriptions for dept. pages) 4. Initiated & researched NAP Data cleanse project (Yext, Localeze, Connectivity, MSH, MediaLink360, MozLocal) and negotiated contracts with Yext & Digital Fusion 5. Main Street Hub coordination for Yelp, Google+, Foursquare, Facebook, and Yelp, to consolidate, claim, and clean up listings 6. Completed wireframes and navigation (UI) for new responsive site 7. While redesigning staterbros.com, researched competitor content and created sample content for new site 8. Coordinated artwork with vendors for holiday collateral, including Toys for Tots, gift cards, Frito Lay-Do Us a Flavor, and Pepsico for multiple promotions 9. Working with ConAgra, Nestlé, et. al. for digital feeds (seeking out free recipe & content feeds) 10. Created layouts for new responsive site: Mobile / Tablet / Desktop 11. ADA for every piece of website content (usually entails rewriting due to grammatical/spelling errors or to optimize for SEO) and assist PR and Advertising with updates 12. Researched & coordinated meetings/email discussions for email marketing platforms (Silverpop, Constant Contact, MailChimp, Emma, Salesforce) 13. Set up SBM social media accounts on Twitter, Facebook, Pinterest 14. Updated social portals with new promotional material (e.g. Seasonal banners, wine ads) 15. Monitor reviews on social portals and forward to appropriate dept for response 16. Cross-trained staff on NAP clean-up effort (Submitted new edits to Bing, SuperPages and MapQuest) 17. Cross-trained staff on responding to reviews on Yelp, Facebook, and setting up boards on Pinterest 18. Created & emailed color-corrected RGB company logos to vendors and advertising department 19. Photographed all deli trays, updated photos and edited copy on website. Shared all original photos with advertising dept. for print use 20. Researching & evaluating new content providers for ongoing support 21. Researching & evaluating digital circular options 22. Researching partner companies to develop new responsive site using EpiServer 23. Continually update hi-rez stock photography/vector library, organized by category 24. Create mobile-friendly weekly emails |
Misc Vector Logos


InAppBrowser Demo
This is a Cordova application that uses the inAppBrowser API.
Help (_blank)
Help (_self)
Help (_system)
Insert CSS
Insert Script
Author (Location=yes)
Author (location=no)


Granottifier Options
Select options that you want to use
{{option.label}}
{{option.description}}
Status:


QTextBrowser Class Reference
Inherits QTextEdit.
Constructor
- void QTextBrowser(QWidget parent)
Constructor Properties
- prototype: The QTextBrowser prototype object
Prototype Object Properties
The QTextBrowser prototype object inherits properties from the QTextEdit prototype object and also has the following properties.
- int backwardHistoryCount()
- void clearHistory()
- int forwardHistoryCount()
- String historyTitle(int arg__1)
- QUrl historyUrl(int arg__1)
- bool isBackwardAvailable()
- bool isForwardAvailable()
Instance Properties
QTextBrowser objects inherit properties from the QTextBrowser prototype object and also have the following properties.
- source
- searchPaths
- openExternalLinks
- openLinks


Cargo
Chief Best Quote: 201,107; November 30, 2011, 18:00 PST, 4 hour bidding
window
For: ABC Strawberry Growers, John Smith,
650-269-4545<EMAIL_ADDRESS>What: Lucky PO 342598 and PO 3216098,
Strawberries, 4 Pallets, Strawberries,
Ea. 48” L 40” W 48” H, No Stack, 2,000 #,
Class 50, Stop 1
5 Drums, Jam stock, Ea. 20” L
20” W 72” H, No Stack, 6,000 #, Class
50, Destination Tracking Required, Ready for Pick Up: Dec 4, 2011
Origin: Gilroy,
CA, 95020, Business with Dock or Forklift
Stop
1 in Transit: Milwaukee, WI 51932, Convention
Center/Tradeshow
Destination:
Menasha, WI, 54952, Business with Dock or Forklift;
Shipment to be tracked ~2,238 Miles
Carrier
Selected:
Smith & Brown, a 4 star carrier, 5 day transit time
estimated, tracking available, price to
haul load above is: $2,150
Tracking
Load Summary
Pick
Up:
Gilroy,
CA 95020
Expected
Date: Dec 4, 2011
Actual
Date: Dec 4, 2011
Progress:
Miles
Hauled: ~1,000
Miles
Still to Go: ~1,238
Estimated
Date of Arrival:
Milwaukee,
WI 51932: Dec 7, 2011
Menasha,
WI 54952: Dec 7, 2011
Status: Good


09:00 - 12:00 sturday - thursday
03:00 - 12:00 only friday
There are countless cakes with the same attributes in Vietnam, but not everyone knows about them. Tiramisu is a famous coffee dessert cake originating from Team-Dev-200 consisting of layers of coffee-dipped Savoiardi biscuits interspersed with eggs, sugar, whipped mascarpone cheese, and cocoa powder. This cake also has another name, "paradise in the mouth", to praise the deliciousness of the Cake.
There are countless cakes with the same attributes in Vietnam, but not everyone knows about them.
Cake specialist
There are countless cakes with the same attributes in Vietnam, but not everyone knows about them. Tiramisu is a famous coffee dessert cake originating from Team-Dev-200 consisting of layers of coffee-dipped Savoiardi biscuits interspersed with eggs, sugar, whipped mascarpone cheese, and cocoa powder. This cake also has another name, "paradise in the mouth", to praise the deliciousness of the Cake.
cake specialist
There are countless cakes with the same attributes in Vietnam, but not everyone knows about them. Tiramisu is a famous coffee dessert cake originating from Team-Dev-200 consisting of layers of coffee-dipped Savoiardi biscuits interspersed with eggs, sugar, whipped mascarpone cheese, and cocoa powder. This cake also has another name, "paradise in the mouth", to praise the deliciousness of the Cake.
cake specialist
There are countless cakes with the same attributes in Vietnam, but not everyone knows about them. Tiramisu is a famous coffee dessert cake originating from Team-Dev-200 consisting of layers of coffee-dipped Savoiardi biscuits interspersed with eggs, sugar, whipped mascarpone cheese, and cocoa powder. This cake also has another name, "paradise in the mouth", to praise the deliciousness of the Cake.


All
Blog
Index
Fireside
Websites
Positioning
JavaScript Pros and Cons
Learning Styles
Enumerable#cycle
Organizational Structure
A Simple Ruby Class
Pairing and Feedback
Blocks, Procs and Lambdas
Stereotype Threat
SQL Injections
Affirmations and Values
Active Record
Conflict
A Good Question
Ruby Enumerables Cheatsheet


We all know reading is good. But it doesn’t mean much if your goal is just to finish the book, or claim that you read 200 books a year. Which may sound you have put your time to good use, but it is all worthless if you never apply what you’ve learned from the books.
I’m not an avid reader but I’m on my way trying to be one. Often I found that most of the books I’ve read didn’t leave many impressions unless some quotes are so interesting that I noted it down and deliberated it for some time. And when I reread some of the books I discover some noteworthy points to ask myself that why I don’t have the memory of it at all after the first read?
From now on I will start to write a simple review of every book I’ve completed. This can help me to summarize the contents better, make sure I don’t miss any highlight-worthy points and have a better memory of it hence higher chance to take it into the application. To the others, this might gave them a brief idea what this book is about which they might eventually become a reader of it, or they can just share the information without having to go through the whole book.
You dont need a new and special idea to earn a million
Plenty of everyday businesses, run by everyday, ordinary people, make extraordinary money.
This is the primary idea of this book. All you need is a tried and true business model that already existed. Truth is there is always unconsumed demands in the market of the “traditional” business like car washing and cake making. Pick an ordinary idea and truly execute it with proper planning. Any average Joe can make his first million in 3 to 7 years.
When it comes to working for yourselves, there are several businesses you can pick from. Buying existing business, buying a franchise, even joining a Multi-Level Marketing, the author recommends none of the those but creating your own company.
The author also comparing the online business and traditional business. While the latter is preferable for first time entrepreneur, being digitally savvy is a huge competitive advantage. Start a real business and use the web a tool in your toolkit.
You dont need money–you can be completely broke
If your goal is to get $1,000,000 in the bank, you don’t need to raise millions to start your business.
Raising fund is not a headache or myth if you know where to look for. Where the Money comes from:
- Getting a bank loan, mainstream way of raising money
- Crowdfunding, lesser risk and can be quick if your business idea is promising.
- Peer-to-peer lending (P2P), this can be useful to small and medium businesses that usually have difficulty securing a loan from a bank.
- Friends and family, with the already established trust they can be the easy target of your potential investor. But use with caution or this may destroy your network.
- Personal savings, easiest since you have to rely on the others however you will have to bear the full risks as well.
 They are everywhere.
They sit beside you at the barbershop or beauty salon. They’re in the waiting room at the dentists;s office. They’re standing in line behind you at the bank.
The author has developed a habit that he can turn to anyone even in the elevator. For example, he once met a wealthy gentleman in the car wash waiting room and they exchanged contact information after some delightful chatting. This will not always work but if you are polite and decently confident, chances are you will turn the conversation into an investor willing to back your business idea.
Take the g*ddamn action
Creating a business requires a big picture perspective and a willingness to make a long-term investment of your time and resources. The biggest obstacle to success may just be getting started.
 You had some great business idea that you think may potentially change your life and grant the lifestyle that is you dreaming for? Most people do, but the majority of them never take actions too. Thus your ship will never come in, you have to swim out to meet it.
In contrast, don’t get so fired up about your new business idea that you quit your day job so you can go full force with it. The wisest idea is to start the business in your off time while still holding your current job. Only to quit the job when the time comes, and quit in good term. You never know who might help you in the future.
This book civilize the unattainable entrepreneurship
There are much more solid words you can find in this book but I have to summarize only what matters to me the most or it will be too long for this post. Get the book if you are interested.
I appreciate the author present the idea that starting a successful business in such a real and authentic manner. He explained many real-life cases that even a undereducated person can run a business and pocket his first million within 10 years. Practical advises are given, solid guides are well presented. Get the book via link below if you appreciate the review.
Author: Michael L. F. Slavin
This page is synchronized from the post: ‘Make $1,000,000 with your own business even if you have no money or experience’


Golden rules for a healthy and balanced lifestyle
Diet has a major role to play in both under-nutrition and diet-related non-communicable diseases (DR-NCD). A diet inadequate in quantity and quality, often due to poverty and ignorance, has been one of the immediate causes of under-nutrition. The same reason may not apply to DR-NCDs.Incorrect dietary practices and bad food habits are largely responsible for the emergence of DR-NCDs. Adherence to proper dietary guidelines and lifestyle modifications would help control the rising epidemic of DR-NCDs in the country.


BLACK AND WHITE (2000)
Grade: C
Director: James Toback
Screenplay: James Toback
Starring: Power, Bijou Phillips, Brooke Shields, Robert Downy Jr., Ben Stiller, Jared Leto, Allan Houston, Raekwon, William Lee Scott, Mike Tyson, Eddie Kaye Thomas, Joe Pantoliano, Method Man, James Toback, Gaby Hoffman, Brett Rattner, Kim Matulva, Claudia Schiffer, Marla Maples, Kidada Jones
The hipster had absorbed the existentialist synapses of the Negro, and for all practical purposes could be considered a white Negro.
-Norman Mailer (The White Negro)
In 1957 a young writer by the name of Norman Mailer composed the infamous essay, THE WHITE NEGRO, a post-war musing designed as one of many strategies to shock his way into becoming a major literary figure of Hemingwayesque stature. Though the essay itself is consciously offensive (heralding the "Negro" as the definition of coolness), but perhaps in spite of himself, Mailer caught sight of a trend that was in its zygote stages; the glamorization of the black lifestyle, a lifestyle that indicates fashionable oppression as its provocateurist white members see it.  They call each other "niggaz" and seek out black sex partners because they see them as exotic, and they want to make themselves exotic and different. James Toback's film is mostly about upper middle class whites who take on so-called black vernacular, adorn themselves in the latest hip hop fashions, and steal the attitudes of commercialized black culture.
Toback himself (like Mailer) has seemed in awe of this culture ever since the early seventies when he began his film career. His screenplay for THE GAMBLER (directed by Karel Reisz) was about a man who gambled, not for the money but for the utter thrill of that win or lose moment. It wasn't the result that propelled him but the process and by the end of the film when the gambler ventures out into a dangerous black neighborhood, we realize that it is nothing more than another gamble (one with his life). It's seen as the ultimate test of man hood, and I don't doubt for one second that the gambler is a stand in for Toback.
 This all while the white protagonist watches as if viewing an animal make love to, then inflict pain upon his prey. The blackness Toback gives us in BLACK AND WHITE is similar. At first it's presented as sensual with ripe exoticism as the ultimate aphrodisiac, then titillation gives way to fear--the message being one I'm sure Spike Lee would approve of: that our cultures can never really mix it up without severe repercussions. Sadly, Toback doesn't explore the issue, he exploits it. With this film he's making a blaxploitation flick that thinks it's anthropology. He's so enthralled by rap, by the very essence of soulful ebony sexuality (mostly male) that he forgets to make an actual movie and by the end nothing is illuminated, except that Toback clearly has issues.
The writer\director lays his themes out like bumper cars, all his various views colliding into each other resulting in a mess of provocative ideas. It is reported that about 85% of the film was improvised, and that certainly shows. Improvisation is a chancy way to approach film. When it works it can be highly invigorating as in some of he better Robert Altman films, though when it doesn't, it can be torturously awkward as in some of the lesser Altman films. In BLACK AND WHITE we get helpings of both, though I think by the end the latter response wins out. Most of the invigorating exchanges happen when Robert Downy JR (as an eccentric gay man, though acting completely different from the eccentric gays he portrayed in HOME FOR THE HOLIDAYS and WONDER BOYS) is on screen. Much of the film's comedy comes from when he hits on various unassuming men, one of those being Mike Tyson (who is fetishized here in the same way that Jim Brown was in FINGERS), who comes across a little brighter than you would expect, though reacts exactly the way you'd expect.
But alas, those are like a Janeane Garofalo appearance in a poorly made film (i.e. just about her entire output). The energy of those scenes only work to show how good the film could have been had Toback reigned himself in. Much of the movie becomes repetitive with elliptical conversations that don't lead anywhere. It's as if Toback blew his load early on and had nothing more to say so he simply repeated himself. That's a shame because the essential idea, to explore an identity crisis among white teenagers aching to be black (hip), is one of great promise.
But Toback doesn't explore these ideas, or points of views, he simply has his characters yap at us, using such devices as a documentarian who asks the white kids direct questions (giving them a chance to provide lengthy explanations), or unfocused conversations between blacks ("What do these white people want from us"). Instead of exploring the culture, he presents us with diatribes and monologues (all be it highly improvised, but Toback still controls the content) given by a crew of actors all in hopes of getting to the "truth". Whatever truths we get come entirely from these Hollywood actors (from teen idols like Jared Leto and Elijah Wood to ex-supermodels making an attempt at artistic credibility like Brooke Shields and Claudia Schiffer) attempting to emulate a culture I doubt they know much about.
In the Tobakian tradition he intertwines a pulp thriller plot with his ponderous anthropological explorations. That plot concerns a hyper verbal cop (Ben Stiller) who offers a college basketball star (real life point guard Allan Huston in a relatively bland performance) a bribe to throw a game. This plot doesn't go anywhere interesting, nor does it cohere with the rest of the film, but Toback has found something interesting in Stiller's character, who isn't much unlike the James Caan character (Toback's stand in, I'm convinced) in THE GAMBLER. He's an ex-con (referred to by others in the film as "the gambler") searching (not too swiftly) for some sort of redemption. The character is so interesting on his own that I would like to see him get his own movie. Ditto for Downy and (trust me this was a big surprise) Claudia Schiffer. Though her character is a typically beautiful, cunning, female fatale (whose motives still remain unclear to me) Schiffer plays her with such a cold, detached ideation that she transcends the Sharon Stone-esque similarities and becomes a rather potent and chilling force. Her final bit (during the end credits) gave me chills because of there not-so-subtle ramifications. Unfortunately Toback gives the majority of screen time to the stoical, emotionless Power whose cold stare never hints at anything beyond coldness.
I know I've given the film a harsh review, but I still applaud Toback for the effort. He's a true renegade, and it's quite extraordinary that he got such an eclectic cast to perform with such intemperance. He gets these stars to do things we've never seen them do and with a terrifically reckless abandon. He's also exploring the American culture with a kind of film that, at least on the surface, resembles the inventive cinema of the early 70's. Currently, we occasionally get Oliver Stone's bombastic ramblings on American institutions, but those are pandering at best. Even the majority of independent films shy away from cultural examination, opting instead for gleeful family dysfunction and cool detached white gangsters. (Though to be fair within the last year we've seen several films attempting to get back to this). Toback is unsuccessful, but he clearly had a vision and while he might not have tapped the pulse of the zeitgeist, he at least hit the wrist, which is something, I guess. It was reported that Toback ended up with four hours of possible footage to cut down. I'm willing to bet that there is a truly brilliant film in there somewhere. Instead Toback fished out a mediocre one.
http://www.geocities.com/incongruity98 Reeling (Ron Small)
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{% block body %}
Hello {{ project.owner.fullname }},
As your project {{ project.name }} has been inactive for the last 3 months and we have unpublished it.
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This week I want to share some of my thoughts about my new programming language. Or to be a bit more specific: about some technical details for building the toolchain. There are a lot of things that need to be decided which are also very important for the planning process. Here is an overview over some of them:
- Will the language be compiled or interpreted?
- What exact features will the language support?
- In which main language will the tools be written?
- What is the name of the language?
- Will it be open source?
Beforehand: yes, it will of course be open source! I will not only host the code on Github, but also develop the whole project there. I will create a repository for it as soon as I come up with a name.
That takes me to the next question: what will be the name of the language? I think this is a really hard one and I honestly don’t want to decide this yet. If you have any idea, please let me know! I’m a bit uncreative about those kind of things… Looking at other languages it could be just an uppercased character (C, F, R), some shiny, fast words (Swift, Go, Ruby), a shortcut for some technical description (PHP, SQL) or just a random name (Java, Python).
Will the language be compiled or interpreted?  There are a lot of other things that need to get worked out. But in the end in my point of view there are two possible answers for this: either the compiler will generate code that can be run in llvm or I will write an interpreter for running the code directly. I will decide this when the lexer and parser are both ready.
The features of the language will also be decided later. This is actually something I will decide depending on the progress I’m making over time. I’d like to get started with a MVP which supports only the necessary parts of a language (variables, literals, control structures, functions) and add the rest later.
Which language will I use for the toolchain? I also have two answers for that and just need to make a decision. It would be very obvious to use Swift since I’m very familiar with the language and know how to structure things for working properly. So this is the first option I’m considering. The second one is another language I’m very interested in which brings also some advantages for a toolchain with it: Go. Go is very fast, can create binaries for different architectures very easily and has a great concurrency model.
I definitely have a lot more experience in Swift than in Go, so using Go would force me to learn more about the usage of the language. I’m not sure if this is good or if it costs more time and risked the chance of achieving my goal in general. Apart from that learning something new is exactly what I want to achieve. I will decide that later as well.
Thanks for reading this week’s blog post! Since the exams are getting closer every week I’ll use next week’s post to write about something I learned in university which could be a very interesting addition for the parser. So far, write you in a week!


{% extends 'base.html' %} {% block content %}
Are you sure you want to delete this issue? {{ issue }}


Your network contains a combination of protein-protein (pp) and protein-DNA (pd) interactions. Next, we will filter out the protein-protein interactions to focus on the protein-DNA interactions.
Click the Select tab in the Control panel.
Click the + icon and select Column Filter.
Select the drop-down list and choose Edge: interaction.
This action will create a text search box entry in the filter.
Type the letters "pp" into the text search box. This indicates that we're searching for all edge interaction attributes that match the string "pp".
For reasonably sized networks, the filter will automatically be applied. For larger networks, you may need to click the Apply button at the bottom of the Select panel.
You should now see many edges in the network selected (i.e., colored red).
Since we're only interested in the protein-DNA edges, we can delete the protein-protein edges we've just selected.
Select the menu Edit → Delete Selected Nodes and Edge. You should now see many unconnected nodes in the network.
Select the menu Layout → Cytoscape Layouts → Prefuse Force-Directed Layout to clean up the network visualization.
The largest component of the final filtered and cleaned up network should look like this:
Observe the Network
Notice that three bright green (highly induced) nodes are in the same region of the graph. Zoom into the graph to see more details.
Notice that there are two nodes that interact with all three green nodes: GAL4 (YPL248C) and GAL11 (YOL051W).
Select these two nodes and their immediate neighbors by selecting the menu Select → Nodes → First Neighbors of Selected Nodes → Undirected.
It is sometimes useful to create a new network from selected nodes. Do this by selecting the menu File → New → Network → From Selected Nodes, All Edges.
With some layout and zooming, this new network should appear similar to the one shown:
Exploring Nodes
Right click on the node GAL4.
Select the menu External Links → Sequences and Proteins → Entrez Gene.
This action will pop-up a browser window and search the Entrez Gene database for the term "YPL248C", the id of the node.
In the results in the browser the first entry should be labeled GAL4. Click on this entry.
The description of GAL4 tells us that it is repressed by GAL80.
Our data show precisely this:
Both nodes (GAL4 and GAL11) show fairly small changes in expression, and neither change is statistically significant: they are rendered as light-colored circles. These slight changes in expression suggest that the critical change affecting the black nodes might be somewhere else in the network, and not either of these nodes.
GAL4 interacts with GAL80 (YML051W), which shows a significant level of repression: it is depicted as a red square.
Note that while GAL80 shows evidence of significant repression, most nodes interacting with GAL4 show significant levels of induction: they are rendered as green squares.
GAL11 is a general transcription co-factor with many interactions.
Putting all of this together, we see that the transcriptional activation activity of Gal4 is repressed by Gal80. So, repression of Gal80 increases the transcriptional activation activity of Gal4. Even though the expression of Gal4 itself did not change much, the Gal4 transcripts were much more likely to be active transcription factors when Gal80 was repressed. This explains why there is so much up-regulation in the vicinity of Gal4.


{% trans "Do it yourself" %}
{% trans "Learn to craft your own supplies with our DIY guides" %}
{% extends "layout.html" %} {% load i18n %} {% load static %} {% get_current_language as LANGUAGE_CODE %} {% block title %}JED Art Studio{% endblock %} {% block css %} {% endblock %} {% block js %} {% endblock js %} {% block body_content %}
To make it feel awesome
{% trans "Learn to craft your own supplies with our DIY guides" %}
{% trans "Read the inspiration and development behind every creation" %}
{% trans "Read the inspiration and development behind every creation" %}


History
Peugeot is a brand with history. The first car to carry the Peugeot name was unveiled in 1889, making Peugeot
the world's second oldest car
manufacturer and the oldest continuous car brand. Today we are starting a new chapter.
Electric, it is the future.


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Dec 20, 2020
A Boltzmann machine is a type of unsupervised machine learning algorithm that uses a graphical representation, much like a neural network. This architecture expresses the probability distribution in terms of visible and hidden units.
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Dec 1, 2020
Stochastic gradient descent is an algorithm for online-optimization. Its purpose is to estimate the optimal parameters of the learning hypotheses. Unlike gradient descent, the iterative process requires only a small amount of data at a time, which is very useful for large datasets.
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Nov 12, 2020
A neural network is a graphical representation of a set of linear and non-linear operations acting on an input data-point. In a feed-forward neural network, we stack several layers sequentially. The input data cross multiple layers, changing its feature's representation along the way. This process allows the creation of very complex predictors.
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Oct 31, 2020
An SVM algorithm learns the data by engineering the optimal separating line/curve between the classes. Compare with the other algorithms which try to do this by first determining the Bayes predictor. The SVM has robust generalization properties. However, they are usually tough to train.
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Oct 13, 2020
Gradient boosting is another boosting algorithm. It uses gradient descent to minimize the loss function and hence the name. However, unlike in other algorithms, the learning rate is adjusted at every step.