text:
Coldplay Live
A Head Full of Dreams Tour (2015-2017)
2016: Promo & various appearances
[2016-03-16] Chris Martin on The Howard Stern Show
By grids,
March 16, 2016 in 2016: Promo & various appearances
alicjanna
And, of course they are going back to Europe in 2017! I'm starting to save the money, my goal is 2-3 gigs... Fingers crossed
Haven't watched this yet but Howard Stern is always rude and vulgar, I totally hate this guy.
Regrettably, Howard did not push him so much as during the last interview in the MX era. Such a shame...
Yeah, that's because MX is still good... The recent stuff again I really do enjoy but yes could have been better without Stargate.
Honorary Coldplayers
Don't think the "goodness" of AHFOD had anything to do with it :) as far as i kkow, howard stern never rated coldplay as a band in the past, except for during chris' interviews. but the Stargate thing is a whole other matter.
Granted, I haven't listened to this yet, but I have mixed feelings about Stern from the previous interview. While I hate that he makes Chris feel really uncomfortable, there were some cool things we got from it. :shrug:
Rickulus
Chris always looks like he doesn't know how to respond to Howard Stern haha. All the other interviewers are a bit too polite and try to not ask personal questions, while Stern just goes all out. I don't know how I feel, we get to know more, but Chris looks uncomfortable. But again, he did agree to come there (for the second time).
alisbe
I've just listened to it and I think Chris was more confident this time. Today he said no to the questions about his current relationship. Last time he was like "I don't feel comfortable talking about it but I don't know how to stop him". My favorite parts were the cover of life on Mars and Viva La Vida (my favorite song of all time)
How surprising that Apple and Moses named their "band" Birds Of Prey....Chris Martin's genes through and through
Listened to it entirely now. Howard Stern is still a disgusting guy to me (his vulgarity....) but at least he did really ask Chris in-depth about the songwriting process and didn't let him get away with vague answers like usual. Also, although it seems like he despised Stargate for the sole reason that they are from Scandinavia, which is a stupid thing to do, I think it was good that he critically questioned the power Coldplay gave them over their own music. I wish it would make Chris wake up to this.
diego_camargo
[MEDIA=twitter]710108487989239808[/MEDIA]
Mobile Link: https://twitter.com/ColdplayAtlas/status/710108487989239808
A BOMB!! :censored:
I'm thinking about this answer and trying to figure out and in my mind I came up with this: They are not breaking up or ending the band, they're still friends and will collaborate with each other sometimes. Coldplay will not make full LP's with big world tour and promotions around it anymore. That doesn't mean Coldplay will stop working with music, they could still release singles now and then, collaborate and produce for another artists but LP7 will be their last LP. Coldplay will exist but in another form. For me it's fair they probably miss their familys and friends after being so active the last couple of years and want to have time for their personal projects. It's artistically health for everyone of them too.
While I hope they go on extended hiatus to find a new artistic identity again, I hope they will eventually release more LPs. Don't want them to be gone forever
Me too. Maybe they will change their minds later, but for now it appears to be deadset for them. It will be interesting if Jonny and Will have another side project in mind. That would be pretty cool to see.
Guest diogo_sg
Just finished listening to this. It's a great interview. Really great. Very insightful. I've been learning so much from Chris regarding happiness, sadness and, well, life. He's such a smart person and I can only imagine what it would be like to have a 'serious' conversation with him. I haven't listened to the MX era interview with Howard Stern, but he didn't seem rude at all in this one. The questions were well put and the answers were very interesting - we really got to learn a large handful of new things about the band and Chris. By the way, the four performances were just superb! All of them! Amazing.
Kamili
Listen the old interview-MX era and you`ll see how rude he was. This new interview was a real transformation of Howard. Although I think that both interviews had a real quality.
I will when I have the time. I have a huge list of interviews and other stuff (Coldplay-related and not) that I have to watch, read, see, etc, but I don't have much free time to do so :)
Of course, just thought about the difference of Howard`s behaviour ;)
Does anyone know where I can buy the jacket he's wearing in the interview?


Using a manta or rebozo to 'mantear' the upper body. Lima, Peru 2014.
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vibhuthi which is of great religious/scientific value in its purest form.
this is a bulk pack that can be used for distribution / gifting in religious gatherings.
this is just pure bhaspam. a portion of the proceedings go towards helping goshalas.


text:
import { Module } from '@nestjs/common';
import { UsersService } from './users.service';

@Module({
  providers: [UsersService],
  exports: [UsersService],
})
export class UsersModule {}

redpajama_set_name: RedPajamaGithub


text:
Brian Beihl: That's really cool, man.
I love havin' Becca and Chu out.
Jim Scherer: Oh, man, check your phones.
male: We got some news.
Mike Weaver: We got a baby. male: We got a baby.
Mike: When you hear that whole word about "metastasized to the
bone," that's usually kind of a death sentence, isn't it?
Kim Beihl: It's very lonely.
It's very sad and devastating, and some marriages
don't make it through this.
When the light comes,
nothin' left to hide,
darkness runs away,
Kandice Weaver: I love field trips on the road.
Sometimes we know in advance if things are gonna be happening,
but then many days we wake up, and we're like,
"Oh, my goodness, we're 20 minutes from whatever,"
and then we pop over there.
Today we got to tour the McPherson Guitar Factory and be
there when Mike and the guys recorded a little session.
Mike: For a long time, I have just been so blessed by
the people at McPherson Guitars.
They just make some incredible instruments, and so we were
invited to come and actually play a couple songs, using some
brand-new guitars that they had made of carbon fiber, and I
jumped at the chance and really enjoyed getting to take
everybody else with me on that little part of the journey.
male: One, two, three, four.
Hangin' by a thread from the tree of this life.
I've been spinnin' round and round and round
inside my flesh cocoon.
An old, beat-up Pinto might be what I drive
for now, but I'll be drivin' a Cadillac soon
'cause you know, one day,
I will fly to my mansion in the sky.
I'll have no regrets
when I leave this place for good.
When I say my last farewells,
oh, please, don't forget to tell them
I'm not really dead.
I'm just changin' neighborhoods.
I'll be changing', ooh, yeah.
Ooh, you know, one day,
ooh, please, don't forget to tell them
You know I'm changin', ooh, changin'.
It won't be long till we'll all be
changin' neighborhoods.
Jim: Michael, man, that was awesome today at the McPherson
place when you guys did "Neighborhoods," acoustic,
and you know we talked about that in rehearsal.
Mike: We might need to put it back in the set, man.
Jay Weaver: I think it's time to bring the hoods back.
Mike: The strings add so much to that, you know?
It's, like--makes it a new song, to me.
It's like, kind of, it adds a new life to everything
in the set, man.
Brian: Yeah, it's really cool, man.
I love havin' Becca and Chu out. It's fun.
male: Yeah, that's my favorite, man.
Jim: It's like, man, it was just so different.
It sounds awesome.
\Oh, man, check your phones.
male: I don't even have my phone.
male: Mister, we got some news.
Mike: We got a baby.
Jim: They got a baby Redmon.
Aw.
Mike: Awesome, man.
Jeremy probably will just head over to the studio
with the baby.
The baby will be like--
Jay: Keep workin'--
Brian: For Jeremy and Anna,
I'm super-excited for them, and, you know, as a friend
and bandmate, brother.
You know, I wanna rejoice with them and be happy for them
in this moment 'cause it's something really truly special.
Mike: Life is a miracle, man, you know?
Jim: Yeah, man, it's awesome.
Mike: You know, as much as we've been through--and we've
seen the miracle of God sustaining us in that--we sure
have also, at the same time, seen God do so many things in
the lives of other people, man, enough that, really, it would
keep us going through the rough season that we've been through.
Mike: Before we went through the more recent difficult times,
man, previously, there were just some of the most incredible
things I've ever heard at, just, kind of, breaking loose at the
shows, and then God is the one doing all of these things.
A song can't, you know, make cancer go away.
But God can, and we have seen him do that on more occasions
than I can count now.
Jay: Man, to see him show up on a night-to-night basis--music
is fun, and it's a good reason to go, but it gets old.
Seein' Jesus come and turn on the lights in somebody's eyes,
make their leg grow out, make whatever is ailing better, that
doesn't get old, yeah, and so, each night, we love the sitting
and just watch what he does.
Jim: And then there was that lady who was driving down
to the gulf.
I believe it was to--she was gonna end her life, and then she
heard "Redeemed" on the radio and said, "Mm, that's not what
I need to hear right now," and so she changes the station,
and there's "Redeemed" on the other side station.
Mike: On the other station?
Jim: She's just like, "I think somebody's tryin' to give
me a message."
Brian: That reminds me of the guy with
the three kidneys, you know?
I mean, it's just like, "What in the world?"
Mike: Who had even heard of someone having--
Jay: A third kidney.
Mike: Three kidneys, yeah, a third kidney surgically
implanted?
And then the Lord healed his kidneys, and he--
Jay: Yeah, man, that was my favorite line from that one.
Man, God took me from the transplant list and put me
on the donor list, yeah.
Mike: And that's unbelievable.
Jim: When you begin to hear these stories for the first time
of what's happening, through the music or in a concert, it really
is amazing, and then, as it starts to happen again and again
and again, you start to have an expectation.
It's like, "What's the next thing?
What's going to happen next?"
and the horizons of what you think and dream
can be imaginable.
They're just vast compared to where we were before.
Brian: So cool how the Lord works in that, you know?
He's just so awesome.
Mike: Praise God. That's awesome.
Joe Shirk: So the story on this bus, this is the first bus
we've had as Big Daddy Weave, and we bought it back in 2004,
and all of us guys were talkin' about that.
It's like, "You know what?
It'd really be awesome if one of us got our CDL, and I just love
to drive so much, I was like, "You know what?
I don't mind doin' that."
And, just, middle of '06, before you know it, it's like,
'07, '08, '09.
I think in the nine years, it was calculated somewhere
at 500.000 miles in nine years.
I've been across all 50 states.
Joe: Well, yeah, definitely, I hear in this kind of cold.
male: Well, if there's any change with it, I'll definitely
get back with you on it.
Joe: I'll see you later.
male: What's up, brother? We'll see ya, man.
Mike: Bro, I need to ask you, man, what'd you hear
from the doc last time, man?
male: I was out west, drivin' rock and roll stuff and
wasn't feelin' right, and somebody suggested that probably
because of my age and in my 50s that I probably had low T, so
went to get checked, and my PSA was like 1.400, which it should
be zero to four, and they were like, "We need to do a biopsy,"
and the biopsy came back positive with aggressive
stage 4 cancer.
It was all through the skeleton.
And I didn't hear him, but the urologist told my wife
probably two years.
male: The latest scan is even clearer than before.
Mike: Praise God, dude.
male: Dude, absolutely.
Mike: You're a living miracle, dude.
"Dave, the miracle."
male: I feel he's got a plan for me.
I don't know what it is yet, but he's got one.
Mike: When you hear that ole word about "metastasized to
the bone," that's usually kind of a death sentence, isn't it?
Yeah. Dude--
male: The cancer had eroded my femur, my left femur, to the
point to where it was ready to snap, so they had to put a metal
rod in my leg, and I had just had that surgery, and I was
going, "Well, I'mma go check out the show," you know?
And I went down there, and it was, like, sittin' there after a
few songs, I was--man, it was hurtin' bad, and I was thinkin',
"Now I made a mistake comin' to the show.
I should've stayed in my room," but then you guys got to that
point in the show where you're sayin', "Look, if anybody has
any problems, any infirmities or mental issues they need
to be prayed for, we'd like to pray for you."
Well, I didn't get up 'cause I'm part of the crew.
I just sat where I'm at.
And you guys prayed over everybody, and I didn't pay
much attention to it.
Then, when you started singin' again, I'm thinkin',
"Wait a minute, man.
That's not--something's bad.
That's not hurting. That's not--" you know?
And I got up and moved around.
I'm like, "Wow, this is--" you know?
So that's when I called my brother, and I'm like,
"Dude, this is freakin' me out."
And he's like, "Don't freak out."
You know, he said, "Look, you've just been--you've
been healed, man."
And it has not bothered me since then.
Mike: Come on. male: It has not.
male: Shortly after, that's when, I think, when I went back
and we did the second bone scan, right after that,
and it came back clear.
You know, I just, kind of, came to the realization that the Lord
was talkin' to me, and I better start listenin', and I said,
"I'm not sure exactly what it is."
I got a funny feelin' that he has plans for me.
I don't know what they are, but I'm in, "in for a penny,
in for a pound."
You know, if you're gonna snatch me from the jaws of death,
then I'm gonna do what he tells me to do.
Mike: That's so good.
When I--when you texted me the scan, dude, the picture of the
scans, and, like, this side is just like black, it's just,
like, riddled with cancer, and this side is just like white,
it's like just this stark difference, man.
Bro, I don't even know if I ever told you this, but in that
time-- 'cause it's like we had just lost my dad, you know,
that--earlier, just at Christmas right before that, and we were
just in this low point, man.
We were just hurtin', and, dude, the story of what God did in
your life, man, carried me for a whole long way, man.
It just really was a shot in the arm to just keep believin' and
keep trusting, and hangin' in there with the Lord, man, you
know, even in the face of the disappointment that my family
had been through, you know?
We sure are proud of you, and we're proud for you,
and we love you, man.
male: Love you, man. Mike: You too, brother.
Mike: We've seen God do so many miracles that I can't even
remember all of 'em, but at the same time, some of the ones who
are the closest to us, even in our own family, you know, we're
praying for these miracles that we have yet to see.
My brother, who I've literally seen pray for hundreds and
hundreds of people, just personally himself, and heard of
so many miracles of what Jesus has done in the lives of people,
and then his diabetes and the whole situation that he's been
through, and to not see that breakthrough before, literally,
he even had to have his feet amputated, oh, that was so
painful, as almost as painful as the physical act was
the disappointment of being like, "God, I don't understand
these things."
Emily Weaver: I remember when Jay--the day he went to the
hospital, and our girls were at their last day of school, and I
called them, and I told them that it was gonna be easier,
"Daddy was gonna be better."
And when people are watching us and how we interact, and you put
up a--almost like a front of "everything is good because God
is good," but if you're real, it's not always good.
And it's hard, but God is so good."
Mike: To see God, you know, as, you know, as hope in the
middle of what looks hopeless, as light in the middle of
darkness, man, that's somethin' that you can't just conjure up,
That's, really, that's a whole different kind of faith,
The same thing for Brian and Kim.
To see them deal with disappointment, to see them deal
with, you know, not necessarily seeing today what they had asked
for, but to see what comes out on the other side of that,
because of walking through what they've walked through with
Jesus, that's a whole different kind of miracle.
Jay: How 'bout checkin' my leg here for something, please,
ma'am, if there's somethin' in my shoe?
Emily: Okay, and the whole--the leg part?
Jay: No, just in the shoe itself, I think.
So did you know that Jeremy and Anna's little baby girl was
here, Miss Addie?
She made it.
Emily: Aw. That's cool.
Jay: It's awesome to see that for them.
I'm super-excited, but it just hurts me for B.B.
and Kim 'cause, I mean, he hasn't--B.B.'s handling
it like a champ.
Just hurts, man, just to watch them have to suffer through all
this, knowing they want it so bad, and we've all prayed
for it so hard.
Jay: We're obviously so excited for the Redmon household
to now have to switch from man to man to zone defense with the
birth of a third child, you know, but at the same time,
you can't help but hurt with Brian and Kim.
You know, I mean, they are still strugglin' today, you know, with
that, and it's not for lack of prayin'.
It's not for lack of askin'.
Emily: Yeah, I remember, like, even, like, when we were
pregnant with Nathan and just being, like, "No, I want this
for Kim."
Jay: Yeah, you kind of almost wanna hide the fact that, this
bundle of joy is coming, 'cause you're just so hurtin' for them.
I don't have the answer to that one.
It's the same thing we went through, prayin' for my feet,
and you're sittin' here literally adjusting my fake
foot, you know?
We prayed for my real feet to stay with me, you know, but not
how it went down.
Emily: I think it's all in your mind-set of what
the miracle is.
Like, sure, you had to lose your feet, and that's going against
what people were praying for, but you have your legs.
Jay: I didn't die.
Emily: And didn't die.
The miracle is now that we're all here.
Jay: That's true.
Well, we'll just keep prayin' for B.B.
and Kim, you know, just keep asking Jesus to have theirs turn
out the way they're asking.
For more info, go to bigdaddyweave.com, or listen
wherever you listen to music.
Kim: I remember, one time, me breaking down, being really
upset, and someone hugging me, and I remember, after that, that
I don't think anyone's hugged me in a really long time.
People are scared.
They don't know how to react.
They don't know what to say.
And even one time, if you respond back, they're really
scared to say anything to you afterwards.
I just want more education to be out there about how to help not
only the couples, but their families and their friends
alongside them to walk this journey with them and together
because it's very lonely.
It's very sad and devastating, and some marriages don't make it
through this.
And Brian and I are closer than we've ever been because of this.
Like, when you're gone and people, they either asked me one
of two things, like, "How's Brian?"
"Where's Brian? What's he doing?"
or they say, I think, "How are you, Kim?"
And it's not the "How are you, Kim?"
like, "What's going on in your life?"
It's the kind of "Poor you, Kim," like--and I
know people care.
Like, they wouldn't ask if they didn't care.
I know that, but I think this has consumed us so much that
it's all they know to ask us, and I think I'm getting tired of
people asking either what are we gonna do next--
"Are you gonna do IVF again?
Are you gonna do adoption and try that again?"
Like, "What's next?"
and I think I'm ready to not talk about it for a while with
people and try to have a life with you again.
I mean, you and I have not gone on, like, a vacation probably
since our honeymoon, and we're gonna be married
12 years this year.
Brian: I know it.
It's been so consuming over the last several years, anyway, but,
obviously, for the long time, but that just is our everyday
conversation and, just, what consumes us day in, day out.
Brian: Although I know that God can do the miraculous, we
have yet to see that miracle for us.
It's really hard.
It's such an emotional roller coaster to be on.
On the one hand, we're really happy for Jeremy and Anna, but
on the other hand, it just is a reminder, and it's like, "But
that's not where we are," and that's where we so want to be.
We want to be in that place to where we can experience that
experience, havin' a child and kind of starting our
family together.
It hasn't worked out that way for us, and, you know, it's just
this back and forth of really happy, but, yet really sad and
really hurt, you know?
So it's tryin' to juggle those two things can be a little
tricky at times.
Kim: What might be helpful is--and I don't know
where you're at with this but, like, pulling ourselves back and
saying, "Okay, who are--who's that pocket of people in our
life that we really, really trust and that we know, like,
sticks in it with us and, like, just--because we have to have
some kind of community around us, but, like, that's--those are
the people that we will still talk with, but I can't be "out
there" anymore with all this 'cause it's--
Brian: Oh, it's too draining.
Kim: It's consuming me, and I don't want it anymore.
Brian: I'm totally fine with that.
Just, we'll find that group of people that's just right around
us and just keep it in that.
For us, I think it is important that we just focus on having
time together and where our conversations aren't always
about the next step and all that.
Yeah, I totally agree with all that.
I think that's--it'll be a good thing for us.
Kim: I think so too.
Brian: Yeah.
Kim: Where do you wanna go on vacation?
Brian: What about Hawaii*?
Jim: Okay, so talk about set list.
Did you hear about add more songs to the set?
Mike: So they're talkin' about, like, wanting to get
something that kind of starts with a "bang."
That was the only thing.
It's like, so what do we find, like, without an intro?
Jim: Was it the only name?
That's a big sing-along, get everybody going.
Mike: "Love Come to Life," like, the newer arrangement,
"boom, boom, boom, boom"--
It's somethin' we see in the show that kind of
ends up working.
Jeremy: Hey, guys, sorry we're late.
all: Hey.
Mike: Oh, now, see, this is what I'm talkin' about.
That's what I'm--hey, baby.
Joe: This is a exciting day, for sure.
There's been so much goin' on in the Redmon's life, but the
anticipation of another child and--I mean, that's huge.
Projects will come and go, but our children, you know, that
opportunity is just so awesome.
Mike: Do they make that for dudes?
I don't know if they make that for dudes.
Jay: Uncle Jay dog.
Yeah, get 'em.
Jay: We've been through a season together.
We got to mourn different things together, but it's even better
when you get to have the season of rejoicing, you know, with
each other, and I'm so thankful to get to do that and to get to
see new life in the Redmon household and just do life in
Big Daddy Weave.
Jay: Hey, you.
male: Oh, yeah, I got a foot earlier, but--
male: Look at you.
Brian: You know, for Jeremy and Anna, I'm super-excited for
them and happy for them in this moment 'cause it's somethin'
really truly special.
Jeremy: That was a crazy season.
Really thankful for the guys' support.
So excited for Addie being here.
She's awesome.
The record is finished, and the band already has a natural break
right now, which is awesome, so this feels good.
Feels good to have some stuff behind us, and, you know, I'm
thankful for the guys celebrating with us,
rejoicing in this.
We've walked through the struggles together, and we're
gonna walk through the highs together, and so here's to the
male: Oh, I mean, you know, I got nothin'.
Mike: Hey, this is Mike from Big Daddy Weave, and we are
performing at the Kennedy Center in Washington, D.C., March 22,
of 2020, and want you to join us.
You can enjoy the experience from the audience or join us on
stage as part of the Kennedy Center Worship Choir.
Singers will enjoy a weekend of rehearsals and preparation for
the concert, while nonperforming friends and family will enjoy an
all-access pass to a behind-the-scenes experience.
Visit truenorthpresents.com/bdwdc

redpajama_set_name: RedPajamaCommonCrawl


text:
Q: How can I vectorise a for loop This is part of deep learning where I have implementated the forward propagation with explicit loops, but I'm stuck as to how to do with only numpy vectorised operations.
def forward(self, input_t):
    output_t = np.zeros_like(input_t)
    for i in range(input_t.shape[0]):
        curr = input_t[i, :] - np.max(input_t[i, :])
        output_t[i, :] = np.exp(curr) / np.sum(np.exp(curr))
    self.store = output_t
    return output_t

A: How about smth like this:
import numpy as np

def forward_loop(input_t):
    output_t = np.zeros_like(input_t)
    for i in range(input_t.shape[0]):
        curr = input_t[i, :] - np.max(input_t[i, :])
        output_t[i, :] = np.exp(curr) / np.sum(np.exp(curr))
    store = output_t
    return output_t

def forward(input_t):
    output_t = np.zeros_like(input_t)
    curr = input_t - np.max(input_t, axis = 1).reshape(-1,1)
    output_t = np.exp(curr) / np.sum(np.exp(curr), axis = 1).reshape(-1,1)
    store = output_t
    return output_t

x = np.random.rand(3, 3)

print(f'x = \n{x}')
print(f'y_loop = \n{forward_loop(x)}')
print(f'y = \n{forward(x)}')

output:
x =
[[0.98055614 0.0364636  0.07754052]
 [0.14524677 0.53440358 0.33880981]
 [0.0406863  0.14387749 0.08279181]]
y_loop =
[[0.55729621 0.21680631 0.22589748]
 [0.27105399 0.40000412 0.32894188]
 [0.31728829 0.35177859 0.33093312]]
y =
[[0.55729621 0.21680631 0.22589748]
 [0.27105399 0.40000412 0.32894188]
 [0.31728829 0.35177859 0.33093312]]

redpajama_set_name: RedPajamaStackExchange


Anyone that grew up on the video games of the 1980s will find himself or herself flashing back to that time when playing Cosmic Fortune. This slot machine with a 80s video game feel to it boasts impressive features other slots don't, such as an unprecedented five jackpots attached to the game, three of which are progressive jackpots. Other features of Cosmic Fortune include avalanche, free fall and not one, but two, bonus games.
The regular symbols in the game are represented by four aliens who are red, orange and blue. The fourth alien is pink and was reportedly inspired by the classic Star Wars character Jabba the Hut. Other symbols in the game include one metallic partial moon and one metallic full moon as well as a spaceship. The game's distinctive wild symbol is a metallic sphere that has an engraving of the letter W. Other symbols in the game can be replaced by the wild symbol. The scatter symbol is also a metallic sphere, but this symbol has an engraving of the letter S. Getting at least three of the scatter symbols on the screen within one spin triggers the Free Falls Bonus. 10 free spins are then awarded to players and it is always possible to earn more free spins within the round. Every time a winning combination of symbols appears on the reels during the bonus round each symbol is converted into a marble which ends up at the bottom of the reels. Once all the marbles have been collected a spaceship comes down and picks them up. It then flies the length of the reels and launches the marbles into buckets. The more marbles end up in the buckets the more a player wins.
When a player gets three of their marbles into any one of these buckets they win that particular jackpot. The progressive jackpot feature is then over and players are returned to the regular game screen.
One last feature of Cosmic Fortune that many players enjoy is its cascading reels. Not only are these reels visually entertaining they provide players with greater opportunities to walk away from the game a winner. When a winning combination is achieved the symbols that comprised the winning combination go away and other symbols automatically drop into place.
With all these amazing features Cosmic Fortune is an exciting game that offers much more action and chances of winning money than other slot machine games do.


One of the main distinguishing features of a sit on top kayak is an open deck where the paddler sits. There is no closed cockpit, and the legs of the paddler are always exposed.
This open deck provides more comfort, especially for novice paddlers as they are less restricted in their movements. It is also safer in the event of a capsize as the paddler has no risk of being trapped inside*. Fatyak sit on top kayaks suit all ages as they come with built in foot braces for different leg lengths. (See image below).
There is also more room for storing your belongings, making it popular for fishing and touring.
Our sit on top kayaks from Fatyak are also virtually unsinkable. Not only do they have air between the outer and inner hulls making them really buoyant, they also have self-bailing scuppers which let any water back out straight away.
Other features of a sit on top kayak from Fatyak include the moulded in water-tight storage areas, carry handles and accessory attachment points. Fatyak kayaks are stackable for easy storage and are also very light. Thus making them really easy to carry to and from the waters edge and on to the top of the roof of your car.
Got any questions relating to our products? Give us a call, an email or use the live chat feature on the site.
We love hearing about your kayaking adventures. Tell us about them below in the comments!
*Note: For paddlers using the leg straps. Care must be taken to ensure that the paddler is happy slipping out of these in the event of a capsize. We advise paddlers to practice this beforehand in a safe environment.
Related articles: Choosing a kayak, Caring for your Fatyak, Transporting your Fatyak, Fatyak Stability… or look under our top menu to see all our paddling advice and product information.


text:
NIRA formal announcement likely soon
IANS | December 08, 2021 03:53 PM
NEW DELHI:The Ministry of Jal Shakti is likely to make official announcements of National Interlinking of Rivers Authority (NIRA) and Special Purpose Vehicle (SPV) for the Ken Betwa interlinking project.
The sub-committee for restructuring of the National Water Development Agency (NWDA) had last year suggested the formation of a NIRA like set up. After all, NWDA is an agency and with restructuring, an 'Authority' with powers is envisaged.
The NWDA would be subsumed in NIRA. We have moved the cabinet note from our side, " confirmed a senior official of the Ministry of Jal Shakti.
NIRA would be an overarching body, autonomous in functions for planning and would act as the nodal body for the projects related to interlinking of rivers across the country.
Implementation of the interlinking of rivers projects is happening with funding at the ratio of 90:10 (Centre: State). NIRA would be responsible for looking after and procuring finance from central and state governments, multi-lateral financial institutions such as World Bank, ADB, JICA, BRICS bank etc.
As announced earlier, there would be a special purpose vehicle (SPV) for each of the interlinking projects.
"For the SPV to materialise, agreements amongst the states involved is a must. As on date, we only have an agreement between Madhya Pradesh and Uttar Pradesh vis-A-vis Ken Betwa project, so in all likelihood, we will be announcing the SPV for Ken Betwa project soon, " the official said.
However, the official declined to put a date to it. Sources in the Ministry said, the announcement will be made before the Election Commission announced the dates for the Assembly elections in Uttar Pradesh as then the model code of conduct would kick in and no announcements would be possible. Polls are due in Uttar Pradesh early next year.
When asked if the SPV would be announced even before the project gets all the statutory clearances, the official said, "We are parallelly working on it too."
Mired in controversy for years, the Ken Betwa interlinking of rivers has still not received three major clearances. The environmental clearance was challenged and is pending at the National Green Tribunal (NGT). The stage II (final) Forest Clearance and subsequent state approval, in this case from the Madhya Pradesh government, is pending. And last, but never the least, the Central Empowered Committee, appointed by the Supreme Court, has submitted the report to the apex with its objections to the wildlife clearance, the court is yet to give its say on it.
'Reservation not at odds with merit': SC uphold OBC quota in medical courses
BSF foils bid to smuggle contraband in Amritsar sector
PM to unveil 216-ft 'Statue of Equality' in Hyd on Feb 5
BJP releases 1st list of 59 candidates for Uttarakhand Assembly polls
Rahul aide holds Twitter poll for Punjab CM, Channi comes first
Mamata again writes to PM flagging Centre's proposal to amend IAS cadre rules
German, Indian Navy chiefs discuss ways to strengthen cooperation
Rs 7,411 cr deposited in Telangana farmers' bank accounts


Cloud is becoming a vehicle for next-generation digital business. Many I&O organizations are adapting their strategies to leverage cloud capabilities and prepare for a future of integrated solutions, leading to AI, IoT and edge computing.
Take a deep dive into the cloud with extensive coverage on: migration tactics, vendor selection, optimization, multi-cloud environments, cloud security, data center outsourcing strategies, hybrid & digital infrastructures, cloud optimization, cloud computing, IaaS, PaaS, SaaS and more.
As spending shifts from traditional systems to cloud services, there is both great risk and opportunity. This Smarter with Gartner article, will discuss how the the shift to the Cloud will impact all IT markets.
Read Full Smarter with Gartner Article Now.
The cloud phenomenon continues to grow. As many companies have moved to a cloud first position, many others are finding they need advice in structuring their overall cloud journey. Join Gartner VP & Fellow Daryl Plummer as he discusses the state of cloud computing, major cloud strategy elements and way to ensure cloud success in this free on-demand webinar.
By 2022, 75% of infrastructure and operations (I&O) organizations will have self-organizing cloud platform engineering teams, which is an increase from less than 10% in 2017.
By 2020, more than 50% of enterprises will run mission-critical, containerized cloud-native applications in production, up from less than 5% today.


I always like seeing deleted scenes. In part, I like reassuring myself that the edit team made the right cuts. But it's also good to see what the writing and production team originally planned--sometimes there are little nuances that add to my overall understanding of the characters/writing/direction. And the SV Season 5 deleted scenes are no exception.
Whee! These made me sooo squeeful. I've missed this show so much! Many thanks to the wonderful stir_of_echoes for her generosity!
Damn! I'm only halfway through this and I've got to go out. Expect more later.
Old habits die hard... even when you've been on holiday!
What a genius episode! I adored it.
Well, what can I say? This may be my shortest ep review ever.
I don't have long today so I'm just going to jot down the things I found most interesting about this ep and revisit it later.
This wasn't my favourite episode ever, but I did enjoy some aspects, and it moved the plot arcs of Season 5 along.
Oh joy! A fast torrent and a brilliant episode.
I am certainly Late to the Party this week but thanks to the lovely katetheother I was able to view this week's ep with only a day's delay, despite my DL capacity being maxed. Hopefully I'll be all back to normal very soon.
I've just finished watching Reckoning and the tears are streaming down my face. I am alone tonight. It's the first time I've ever watched a new Smallville episode without supacat who could not be here. I can't be sure how this changed my viewing but I suspect it made it closer and more intimate. I feel ripped apart with emotion right now. Everything I love about this show was in this episode. In the last twenty-four hours I rewatched Season 1 with a new viewer, who asked if the journey was worth it?
Finally! Scribbled thoughts on Lockdown, after 36 hours of trying to obtain ep and nearly passing out from heat-exhaustion, and just before dashing out again to meet a newly returned friend from overseas.
My review this week is somewhat hampered by being on painkillers and penicillin, as I had my wisdom teeth removed a couple of days ago. So it's going to be short and simple this week!
For me this was one of the most layered episodes of Season 5 so far. The direction and photography were beautifully controlled and Tom's acting was superb. I have a lot I want to unpack from this episode, but I'll start with one of the most powerful scenes.


Here's some new ones I snapped today! Hope you like it.
Last edited by hyperion667; 07-09-2014 at 09:05 PM.
I love how you work with the color of the image. Really cool!
WOW thats incredible. Love them!
Last edited by alshaikh85; 02-20-2015 at 12:00 PM.
Its a convertible maybach, I'll upload some more pictures when I'm home.
Last edited by jenz; 02-26-2015 at 02:18 PM.
After nine months of waiting to decorate, just lowered with new wheels. Thought I could grow out of it.
Great seeing everybody's cars! Makes it easier to configure when pictures are available.
Last edited by josephpampliega; 02-28-2015 at 02:16 AM.
Would you have problems with warranty repairs if you lower the car?


text:
Rick Perry, Your Trayvon Martin Tweet Doesn't Mean What You Think It Means
Texas Gov. Rick Perry is well known for loving guns and threatening vigilante violence, so it's pretty easy to guess what he'd think of Florida's Stand Your Ground law that has come under criticism after the Trayvon Martin shooting.
By Elspeth Reeve
Texas Gov. Rick Perry is well known for loving guns and threatening vigilante violence, so it's pretty easy to guess what he'd think of Florida's Stand Your Ground law that has come under criticism after the Trayvon Martin shooting. Not only did Perry sign Texas' version of Stand Your Ground in 2007, in 2010 he won the "highest honor" awarded by American Legislative Exchange Council, the group that successfully pushed almost two dozen states to adopt the law. Perry hasn't said anything about the Martin case, but it's pretty clear that he'd support ALEC against its current critics. Unless, of course, you read his sole Martin-related tweet.
The link there goes to a Washington Examiner story from Wednesday about the successful threats to boycott the companies like Coca-Cola and Walmart who are members of the Perry-honoring ALEC. So it seems Perry was trying to stick it to the gun-hating P.C. police by spending his hard-earned cash on Coke in Walmart. Take that you ALEC-haters! Except the headline of the Examiner's story is, "Coke caves in face of Democratic boycott threat." And as the story explains, "Coke was quick to react to the political boycott threat, pulling support from the targeted group just five hours after it was called. Walmart said that support for a group does not mean it backs every decision by those groups."
Coca-Cola said their statement, "We have a longstanding policy of not taking positions on issues that don't have a direct bearing on our company or on our industry." And Walmart told the Examiner that it didn't have a position on the issue at the center of the debate: "Our membership in any organization does not affirm our agreement with each policy created by the broader group."
So, if you're a friend of ALEC's now, you probably wouldn't be chugging Coke (Or Pepsi; they dropped their ALEC membership in January) while wandering a Walmart at the moment. We're not really sure what Perry meant in his tweet, so here are a few possible interpretations:
Perry is actually applauding Coca-Cola's decision to quit ALEC and does not want to see NRA-backed self-defense laws spread around the country. This seems unlikely, since he's long been a big supporter of the NRA and is always having his photo taken shooting stuff.
Perry thinks "cave" means something like, "to go even deeper" instead of "to capitulate." That would mean he thought the headline indicated Coke's more intense commitment to ALEC, which would be consisted with his past gun fetishism.
Perry is like a lot of people on the internet, and does not closely read the stories he links to on Twitter. We see this all the time from random Twitterers, but it seems especially foolish for a public figure to do with his official account. (Also, in our experience, even the laziest readers at least get through the headline.)
Some conservatives have waded into the Martin story in a way that suggests they think the unarmed teenager was a thug who had it coming. Perhaps Perry was trying to make the same case, but more subtly. We would have granted him a bonus tenth in his Conservative Outrage Score if that emoticon had been a winking smile. And he could have earned a whole extra point if he'd managed to read two words into the story he linked.


In the previous chapter we saw how to interact with Python. In this chapter we want to start using it to do interesting stuff, but before we'll spend some time improving our work environment.
First we'll introduce screen, a wonderful piece of software that will allow you to do many things at once within the terminal, without losing track of any; get used to screen, and you won't be able to be without it.
Once we understand screen we'll learn how to install Python packages.
By the end of the chapter you will know how to use screen to work in parallel workspaces within the terminal. You will have also learned how to find and install Python packages, and you'll know a bit more about system administration. You will have a rather nice Python environment set up, and we'll use it to take a mathematical detour that will give you a feeling of the many cool things you can do easily with Python once you know your way around. You may, of course, skip the last part if you don't care about math: read the first parts, were we talk about screen and Python packages, and move on.
It is good that you experiment with your work environment, and figure out how to tailor it to your needs. And not only for the obvious fact that you might spend many hours a day in front of your computer, and you'd rather be comfortable. The best work happens when the computer does not interfere between you and your task. The interface to the computer should be as transparent to your thought processes as possible, the interaction effortless and automatic. Only then your attention will be focused, and your work your best1.
It might be that one of the reasons that makes the UNIX work environment so compelling is that it lends itself so well to tuning and automating, leaving plenty of room for you to find your perfect setup. Most things can be done with keyboard shortcuts that can be learned until they become almost autonomous. When in Emacs, my fingers reach out for C-x C-s every now and then without me being fully aware of it; movement between applications happens with Command-TAB; the mouse is hardly every touched.
Because I think (and this is a strongly felt guess, but a guess nevertheless) that reaching for the mouse, and aiming at a place to click, imposes a much higher cognitive load on your brain than just letting your fingers press a fully automated chord in the keyboard. And I'd much rather have my brain working out the problem at hand than thinking about what it's doing with the mouse.
When you have been working at the terminal for a while there may be quite a bit of information in it. Its value is usually in the short term —whatever you want to store for the future you'll stash away in a file and save it— but it is important anyway. It is your command line history, environment variables you might have declared, a Python session in which you have defined a couple of helper functions, and have stored some values in variables that you are using to perform repetitive computations.
The time will come in which your work-flow will make you close valuable sessions. For example, you are working with the Python interpreter when you realize that you need to install a new package, and while you are at it you need to check if a library is installed. You'd rather not interrupt the interpreter, and you'd rather not leave your package installation to check the library out.
There's a simple solution: start a new terminal or, if in OS-X, open another window with Command-n (or another tab with Command-t). But it quickly becomes cumbersome, you end up with lots of terminal windows in your screen, and it's not the best way. The best solution is to have multiple workspaces within your terminal, which is what screen does for you. And it is the best because it works, it is based on easy-to-automate keyboard commands, you find it everywhere, and it affords you some measure of permanence between sessions.
echo "This is the starting bash"
echo "This is the first screen"
With C-a n you will go forward to the next workspace. Experiment circling between workspaces back and forth, making sure you recognize them.
and you'll be back, moving with C-a n and C-a p among workspaces that remember your previous work and the state your programs were in, as if you had never left.
When you are done with it, you close screen by leaving all the shells it is running. You close a shell by typing C-d (remember that C-d means end of file, and is also how you leave the Python interpreter). When you have closed all the shells within screen it will not have further reason to stay alive, and it will exit.
In a remote server screen becomes much more than a convenience. A remote server is, for example, the computer hosting your web pages. We'll talk about how to connect to another computer in a later chapter.
When you are working in a remote server it feels just like when you are working at the terminal in your computer, but slower. The main difference is that the computer who's answering your commands is your server, not yours.
The first thing you do after login in your server, before starting to work, is to run screen. This allows you to keep several tracks in parallel, creating workspaces as you need them. But then you have to disconnect from the server, and you don't want to stop what you are doing, because maybe one of the workspaces contains a long running program that has not finished, and in another you are editing a file.
So you just detach from your screen, C-a d, and exit the server. The next time you log in you'll reattach with screen -r, and it will be as if nothing had happened. You'll be back to your long running program, maybe finished by now, and to the file you are editing, and to whatever workspaces you left when you disconnected.
You can try something similar now: just exit your screen-running terminal. Open a terminal again, then do screen -r. If all has gone well you should be looking at the workspace where you were before you closed the terminal.
Another way in which you improve your work environment is by adding functionality to it. Python gives you an easy way to do it.
Say you are a programmer. You've been working on a cool problem, you've come up with a piece of software to solve it, and you decide to give it to the community.
You want to make it available to other programmers, who may want to contribute to your code. Luckily, you have been using git to keep track of your versions (more on git on a coming chapter), so you decide to store your software as a repository in Github. Once your software is there it is easy for other programmers to get copies, make improvements, and share them with you.
The chances are not low that there will be other programmers around who want to help, or who can take advantage of your software to help them solve other problems: there were 3.5 million users on Github on April 2013, and on December 2013 Github was hosting 10 million repositories.
You also want to make your software available to users, so you package it up in a way that makes it is easy for other people to install. In this section we'll be talking about these packages, and how to install them.
Say your hypothetical piece of software is a Python package. If you want to make it as easy as possible for your users to find it you'll go and register it at the Python Package Index, PyPI for short2. Once your package is listed there your users will be able to find it and install it using a program called pip.
If pip is installed which will tell you where it is. If it is not installed which will stay quiet.
Note that we are not running Python as we usually do: there is a sudo before the call to python. It is required because the installation procedure will need to write in locations of your computer that are protected.
On your day-to-day interaction with the computer you are a normal user: you can modify and delete files in your home directory (either /Users/your-login-name/ if you are in a Mac, or /home/your-login-name/ if you are in Linux), which is plenty enough for normal work and it does not put the integrity of the computer at risk.
But software is usually installed in places of the computer where all users will be able to run it, like /usr/local/bin/, and is usually protected so that normal users cannot remove it.
If you want to install something you will need to temporarily acquire the power to do so: you will need administrative privileges. This is what a sudo before a command does. It will ask for your password, and if you enter it correctly it will grant administrative privileges to the command that you are running. It will work if you are on the sudoers group; if you are not, you will be informed, and you will have to find somebody with administrative rights to your computer to do the installation for you.
you'll be asked for your password and, if you enter it correctly, you'll be giving administrative rights to python get-pip.py. If the person who wrote get-pip.py wanted to wipe out your computer, he could. If somebody intercepts it when you download it, on its way from the Github server where it resides to your computer, she could make it do anything she wanted. Which is kind of scary.
But you'll be all-right. There are many people making sure that get-pip.py does what it's supposed to do; and the address you'll be downloading get-pip.py from begins with https, which means that it will travel encrypted.
Python offers a mechanism that helps you avoid installing things in your machine for everybody. It is called virtualenv, and it makes a local installation of everything Python wherever you want. It is very convenient when you are developing Python packages, but unless you don't have administrative rights to your computer you don't need to worry about it now.
IPython is a great addition to your Python toolset. We are going to install and use it for the Python shell it provides, much nicer than the standard python you've been interacting with so far. But IPython does many more things: you might want to spend some time exploring it.
Command line completion is a big deal. It is much easier and quicker to interact with a program that's helping you write —as bash and Emacs do. Let's install IPython, and then we'll take a closer look at completion.
This should open the ipython shell.
This is an extremely convenient thing to have. If you want a quick glance of a module you just import it, then use command line completion to see its contents.
In the previous chapter we asked the computer to manipulate numbers. It is reasonably easy to convince Python to do simple operations, such as the ones we did, or even combinations of them, such as the average of a list of numbers.
How about a way to write a program that would perform algebraic manipulations in symbols such as the above, and maybe find the exact values of \(x\) for which the equation is true? It is actually quite straight forward if you have the right package installed.
quaternion algebra and 3D rotations.
And you are ready to start playing.
but here we are playing a trick. We'll be using sympy later on, and we don't want to use the full name every time we call one of its functions. By adding the as sp to the import we define sp as a synonym, so we can type sp wherever sympy was called for.
Note that you can explore it further simply by typing p., then tab: IPython will show you all the possible completions, which include subs and all the other functions defined in p.
Some familiarity with Python and sympy can do a lot for your appreciation of mathematics, and your ability to explore them.
Only then can you hope to enter what top athletes and many computer programmers call the flow, a state of mind in which you let your mind focus by itself, and in which you can spend many joyful hours feeling as if your work just happens.
There are 39361 packages available at PyPI as of 2014-01-14.


Taking responsibility for your salon's impact on the environment is not only good for the planet, it can be great for business. Many consumers seek out cruelty-free and environmentally friendly products and purchase them exclusively. Making this kind of change can give you a leg up on the competition and a point of emphasis for your marketing campaigns. Such a shift requires several steps.
Customer loyalty is the lifeblood of small businesses, especially those in the salon industry. Establishing a strong customer base and maximizing the revenue obtained through repeat customers is essential to stay afloat and prosper in an ultra-competitive and ever-changing industry. Building trust and a relationship with your customers takes work, and while your employees on the front lines are partly responsible for building these relationships, there are other ways to nurture them. Here we explore 5 perks you can offer your salon clients to help build customer loyalty.
When clients come to a salon they are paying just as much for the experience as they are for the services they are receiving. This makes the atmosphere of your boutique an integral piece in drawing in and retaining customers. Here we outline 7 ways to create the perfect salon atmosphere.
One of the best ways to increase revenue for your salon business is to upsell additional services to your customers. Offering new services may require hiring or training staff members, purchasing equipment and carrying new product lines. While the initial investment may be significant, the revenue and exposure gained from offering these services is well worth the risk. It also may be necessary in order for your salon to remain competitive. Here are just a few services to consider offering at your salon today.


text:
Q: Convert linked excel into embedded excel I have a ppt presentation with hundreds of charts that are all linked to the same .xls file. I want to send the presentation to the client and I want him to be able to access the data. However, I do not want him to open the entire xls file when he clicks on edit data.
So what I would like to do is to "convert" the linked charts to charts with an embedded excel that only contains the data concerning the specific chart.
(I am not sure if that's the right way to put it. I feel like the distinction between embedded and linked is not as clear cut anymore as it used to be in previous office versions)
I have found a macro for ppt 2003 that simply copies the old chart and does
Set oSh2 = oSl.Shapes.PasteSpecial(ppPasteOLEObject)(1)
but I think this does now longer work ( I am working with ppt 2013).
Any ideas on how to do this are highly appreciated. Many thanks

A: If you don't want to give him access to the entire original workbook/worksheet, you'll need to create multiple worksheets, each with just the data you DO want him to be able to get at and then either link or embed those into your PPT file.
If you create the charts using the old MS Graph mini-app (still included, if optionally, with Office) you can link data from an external Excel file into the graph datasheet. I'm almost certain that doing it this way will give others access to the graph datasheet (ie JUST the data used for the graph) but not to the linked source XL file.
I don't see a way of doing this with the new chart engine.


WOMEN AIRism SLEEVELESS TOP is rated 4.8 out of 5 by 32.
Rated 5 out of 5 by Maritza from Airism products Airism is a great an essential Part of any wardrobe. I really enjoy the softness and breathable fabric. The material is soft and cozy that feels part of you. They are hand or machine washable and no iron is needed. I bought long sleeves and now this sleeve less that are ideal for the spring. Airism under shirts keeps you warm and cool at the same time. They are a treat in you!
Rated 5 out of 5 by Ema L from Very comfortable I bought this recently for the warmer weather. I wear the heatech range in the winter. It's ideal to wear underneath Long sleeved tops. The product description is accurate. I bought a small which is slightly tight yet comfortable. I'm a size 10.
Rated 5 out of 5 by SD from so light comfortable and feel good everytime im wearing it.


text:
Augusto Osvaldo Pinochet Hiriart (26 de setembro de 1945) é um ex-militar e empresário chileno, filho do ditador Augusto Pinochet e Lucía Hiriart.

Biografia
Tem sido protagonista de diversos escândalos políticos e casos de corrupção no Chile, entre os quais estão o caso dos pinocheques, a receptação de veículos roubados e o caso Riggs, sendo apenas julgado por uma  pena remitida pelo segundo destes casos.

Família Pinochet
Filhos de líderes nacionais
Militares do Chile

redpajama_set_name: RedPajamaWikipedia


This is for papers and links to stellar metamorphosis.
This is for the Catholics in the house.
This is for those who want to read the book.
This is for those who want to read the article as it was written on wikipedia before it was deleted.
This is for those who like to bash free thinkers.
This is the locked thread on cosmoquest.
This is the best version, which covers other star/planet models as well that are ignored by establishment. Mr. Charles Chandler is the best!
This is the thread on Thunderbolts Project forum.
This is the deletion page of stellar metamorphosis off wikipedia.
This is for people who want to see the papers in an alternative science journal.
For my fellow conspiracy nuts.


Since February 2018, I've been listening and recording around Kingston and the town of Ulster; synthesizing interviews, bird song, passing cars, protests, conflict, unique perspectives and oral histories, meetings, optimisms, water, as part of a project called, Place Accumulation: Kingston/Ulster. Using the Dynamic Listening Instrument, an interactive sound sculpture which uses a venn-diagram of electromagnetic fields to allow sounds to be handled as a tactile entity and bended dynamically, sounds are arranged and dispersed back into different locations and events in Kingston. Using a sounding bucket, people in Kingston can listen in, re-arrange, explore, and play with sounds from their overlapping and opposed publics and environments.
My trajectories of enquiry started with a public scoping meeting about the company GlidePath's proposed fossil fuel plant to be built behind the Hudson Valley Mall, a "We Want a Dream Act Now!" demonstration on Broadway, and a Police Community relations forum at City Hall. These trajectories were followed and have led to intimate collaboration, opportunities for unique sonic exchange, and expanded enquiry and listening.
This project started as a way to use the Dynamic Listening Instrument for and with a place and community, to amplify, map, and transduce relationships between public space, ecology, and empathy. With collaborations, friendships, occupation of public space, attentive listening and open hanging out and deep listening, the Dynamic Listening Instrument introduces a new type of social feedback to a place and community.
Fish, Callan F., "Place Accumulation: Kingston/Ulster" (2018). Senior Projects Spring 2018. 363.


text:
Hot Scrunchie News: Is this old faithful really back?
In the last few months, three fashionable A-Listers have been spotted in the love-it-or-hate-it object of our times; the hugely-divisive hair accessory that is, The Scrunchie. And, as the saying goes; three's a trend. So is this old faithful having a bit of a comeback or is The Scrunchie destined to languish in our bathrooms forever more as a quick-hair-fix in the shower?
By the mid '80s, Madonna had several No 1s under her Boy-Toy belt, and everybody and their sister wanted to recreate her style. Dark lengths, bleached-blonde highlights tied up with ribbons, bushy brows, red lips and that beauty mark became the look for fashion-forward material girls everywhere.
Well, for starters, let's look at the evidence. There's no denying that fashion is having more than a passing flirtation with all things 90s and on first appearances it would seem that much like spaghetti straps and crop tops, The Scrunchie is also having something of a renaissance.
Exhibit A: Selena Gomez' 90s-tastic high-rise plait - with added Scrunchie
For an appearance on Letterman, Selena proved her 90s fashion prowess with this high-rise 'do and big, bulky Scrunchie that even included tightly bound hair at the roots - very Sporty Spice circa Say You'll Be There - but we loved her fresh take on an old classic with that fishtail braid. So far, so good for The Scrunchie.
James Arthur's new music video stars Cressida Bonas. Yep, Prince Harry's ex.
Memorise this song asap, because everyone will be mumbling it in a minute
Exhibit B: Cressy's Glasto Scrunchie moment
We've got high fash-hopes for Cressida Bonas - she could be our new favourite royal, after all - and we loved her super-cool-in-the-vein-of-Cara-Delevingne-festival style at Worthy Farm this summer. Indeed, when she went to get a plate of chips, we completely ignored how tasty those fried golden rectangles of potato looked because her half-up-half-down scrunchie-d festival hairdo was that ace. 2-0 to The Scrunchie.
Exhibit C: Pixie Lott's polka-dot print Scrunchie
Another half-up-half-down 'do and as ever, Pixie Lott nails the trend. While we'd prefer a less "done" style, we like the whole just around the crown element of it - which in practise would make us feel less like we're at school and our mum had done our hair and more, pop star on a night out. In short, The Scrunchie is still riding high. However, try as we might to wax lyrical about all things Scrunchie, this much-maligned hair accessory has undoubtedly been getting a bad rep since it fell out of favour sometime in the mid-90s; just ask Hillary Clinton. The American politician has been championing The Scrunchie for years, showcasing one in 2011 on an official visit to Spain. Indeed, such is her commitment to the aforementioned hair adornment that she has since turned up to numerous events wearing one.
But for those who will forever associate The Scrunchie with the beginning of the end (read: basically the break-up) of Carrie's relationship with Berger in Sex And The City - well, they're might well be no coming back for this controversial accessory for you. And that's okay, too.
TREND: 90s Make-Up
Criminal is the new Netflix show you'll be hooked on
David Tennant is back.
Everything you need to know about Molly-Mae Hague, Love Island's new bombshell
Is she still in that hot tub?
This is what it's really like to be a gay asylum seeker


I realize that the way I rate a book is different than some other reviewers. It's not a bad thing, and I actually love seeing their different ideas, styles and opinions. I do feel I should clarify mine, though.
I am very much an emotional reader. I can forgive small technical issues with writing if the character or plot draws me in. I can even give five stars to a book with glaring grammatical issues- why? The characters were real to me, the story took me out of myself and I probably found myself either sobbing for, or screaming at, the main character.
Now, this does not give the author license to throw everything out the window (I'm looking at you, Winston Groom) for the sake of character development. If a book has too many errors- even ones that are meant to be there- it will be a huge turn off. If I even get through the book, it will have lost at least one star for that.
In the end, though, when I sit down to review a book I look it over with my heart more than my head. Great character development is worth two stars all on their own. In this area, I include snappy dialogue between characters because that helps me to get a feel for the characters.
Good characters- I want the characters to be alive to me. To take me over, as it were. I want to feel for you, enjoy your accomplishments and cry with you. Seriously- bonus if you can make me cry (sadly, it isn't hard). My perfect example of this is Eva Luna, by Isabel Allende. I have read this book- at least in parts- every year for eighteen years now. Eva has a distinctive voice, one that I immediately fell in love with. If the character had not been so perfect, I would not have loved the book half so much. Now, though, opening that book is like going to visit an old friend. I actually bought seven copies of this book in paper (giving to friends to read and never getting them back, or reading them until they were damaged) before finally getting my eBook.
A premise that grabs my attention- there are, after all, millions of books out there… why this one? An example here would be Learning To Swear in America by Katie Kennedy- it was brilliant and the second I read the review about it I could not rest until I owned that book. Seriously, I bought it immediately.
A good plot: I want a plot line, I want the book to be leading somewhere. I want it to be discernable and imaginative. I feel like the earlier Alex Cross books are especially good examples. It was fast paced and intense, but you always knew the plot and theme of the book. On the other hand, I read Winter's Tale before seeing the movie and I wanted my money back- not just my money, I wanted my time back. The author had attention deficit disorder, it seems, because what should have been one romance and a side story with an amazing horse became six love stories and a horse. You ended up feeling lost and confused, and not clicking with any one character because he didn't give any of them enough development; instead adding more and more.
Then there is the adult content scale. I was a bit precocious with my reading as a kid ( Shakespeare and Stephen King in fourth grade), so I can understand that even though a kid can be reading a book, it doesn't always mean they should. I rate books not just on the type of content- language, violence, sexual content, drugs and alcohol- but the amount. The Fault In Our Stars, for instance, had some language and sexual content- but it was so minor that I would give it a two on the scale and have no issue handing the book to a preteen. Fifty Shades of Grey, on the other hand, is a ten. Not for kiddies.
So that's what moves me as a reviewer, what moves you?


text:
\section{Introduction}
\label{sec:intro}

Text-editing methods \cite{EditNTS,malmi2019encode,awasthi2019parallel,mallinson2020felix}, that target monolingual sequence transduction tasks like sentence fusion, grammar correction, and text simplification, are typically more data-efficient than the traditional sequence-to-sequence methods, but they still require substantial amounts of parallel training examples to work well.
When parallel source--target training pairs are difficult to obtain, it is often still possible to collect non-parallel examples for the source and the target domain separately. For instance, negative and positive reviews can easily be collected based on the numerical review scores associated with them, which has led to a large body of work on unsupervised text style transfer, e.g., \cite{yang2018unsupervised,shen2017style,wu2019mask,li2018delete}.

The existing unsupervised style transfer methods aim at transforming a source text so that its style matches the target domain but its content stays otherwise unaltered. This is commonly achieved via text-editing performed in two steps: using one model to identify the tokens to delete and another model to infill the deleted text slots  \cite{li2018delete,xu2018unpaired,wu2019mask}. In contrast, we propose a more unified approach, showing that both of these steps can be completed using a single model, namely a \textit{masked language model} (MLM) \cite{devlin2019bert}.
MLM is a natural choice for infilling the deleted text spans, but we can also use it to identify the tokens to delete by finding the spans where MLMs trained on the source and the target domain disagree in terms of likelihood. This is inspired by the recent observation that MLMs are effective at estimating (pseudo) likelihoods of texts \cite{wang2019bert,salazar2019masked}.
Moreover, by using a \textit{padded} variant of MLM \cite{mallinson2020felix}, we avoid having to separately model the length of the infilled text span.

To evaluate the proposed approach, \textsc{Masker}{}, we apply it to two tasks: sentence fusion, which requires syntactic modifications, and sentiment transfer, which requires semantic modifications. In the former case, \textsc{Masker}{} improves the accuracy of state-of-the-art text-editing models by more than 10 percentage points in low-resource settings by providing silver data for pretraining, while in the latter, it yields a competitive performance compared to existing unsupervised style-transfer methods.

\section{Method}
\label{sec:method}

Our approach to unsupervised style transfer is to modify source texts to match the style of the target domain. To achieve this, we can typically keep most of the source tokens and only modify a fraction of them. To determine which tokens to edit and how to edit them, we propose the following three-step approach: \\
\textit{(1)} Train padded MLMs on source domain data ($\Theta_\textmd{source}$) and on target domain data ($\Theta_\textmd{target}$). (\S\ref{sec:what}) \\
\textit{(2)} Find the text spans where the models \textit{disagree} the most to determine the tokens to delete. (\S\ref{sec:where}) \\
\textit{(3)} Use $\Theta_\textmd{target}$ to replace the deleted spans with text that fits the target domain.

\subsection{Padded Masked Language Models}
\label{sec:what}

The original MLM objective in BERT~\cite{devlin2019bert} does not model the length of infilled token spans since each \textmd{\texttt{[MASK]}}{} token corresponds to one wordpiece token that needs to be predicted at a given position.
To model the length, it is possible to use an autoregressive decoder or a separate model~\cite{mansimov2019generalized}.
Instead, we use an efficient non-autoregressive \textit{padded MLM} approach by~\citet{mallinson2020felix} which enables BERT to predict \textmd{\texttt{[PAD]}}{} symbols when infilling a fixed-length spans of \ensuremath{n_p}{} \textmd{\texttt{[MASK]}}{} tokens.

When creating training data for this model, spans of zero to \ensuremath{n_p}{} tokens, corresponding to whole word(s), are masked out after which the mask sequences are padded to always have \ensuremath{n_p}{} \textmd{\texttt{[MASK]}}{} tokens. For example, if $\ensuremath{n_p} = 4$ and we have randomly decided to mask out tokens from $i$ to $j=i+2$ (inclusive)
from text $W$, the corresponding input sequence is:
\begin{equation*}
\begin{split}
W_{\backslash{i:j}} = ( & w_1, \ldots, w_{i-1}, \textmd{\texttt{[MASK]}}, \textmd{\texttt{[MASK]}}, \\
& \textmd{\texttt{[MASK]}}, \textmd{\texttt{[MASK]}}, w_{i+3}, \ldots, w_{|W|}).
\end{split}
\end{equation*}
The targets for the first three \textmd{\texttt{[MASK]}}{} tokens are the original masked out tokens, i.e. $w_{i}, w_{i+1}, w_{i+2}$, while for the remaining token the model is trained to output a special \textmd{\texttt{[PAD]}}{} token.

Similar to \cite{wang2019bert,salazar2019masked}, we can compute the pseudo-likelihood ($\mathcal{L}$) of the original tokens $W_{i:j}$ according to:
\begin{align*}
   \pl{W_{i:j} \mid W_{\backslash{i:j}}; \Theta} = \prod_{t=i}^{j} \p{w_t \mid W_{\backslash{i:j}}; \Theta} \\
   \times \prod_{t=j+1}^{i + \ensuremath{n_p} - 1} \p{\textmd{\texttt{[PAD]}}_t \mid W_{\backslash{i:j}}; \Theta},
\end{align*}
where $\p{*_t \mid W_{\backslash{i:j}}; \Theta}$ denotes the probability of the random variable corresponding to the $t$-th token in $W_{\backslash{i:j}}$ taking value $w_t$ or \textmd{\texttt{[PAD]}}.
Furhermore, we can compute the maximum pseudo-likelihood infilled tokens $\widehat{W}_{i:j} = \arg \max_{W_{i:j}} \pl{W_{i:j} \mid W_{\backslash{i:j}}; \Theta}$ by taking the most likely insertion for each \textmd{\texttt{[MASK]}}{} independently, as done by the regular BERT. These maximum likelihood estimates are used both when deciding which spans to edit (as described in \S\ref{sec:where}) as well as when replacing the edited spans.

In practice, instead of training two separate models for the source and target domain, we train a single conditional model. Conditioning on a domain is achieved by prepending a special token (\texttt{[SOURCE]}{} or \texttt{[TARGET]}{}) to each token sequence fed to the model.\footnote{The motivation for using a joint model instead of two separate models is to share model weights to give more consistent likelihood estimates. An alternative way of conditioning the model would be to add a domain embedding to each token embedding as proposed by \citet{wu2019mask}.}
At inference time, padded MLM can decide to insert zero tokens (by predicting \textmd{\texttt{[PAD]}}{} for each mask) or up to \ensuremath{n_p}{} tokens based on the bidirectional context it observes.
In our experiments, we set $\ensuremath{n_p}=4$.\footnote{In early experiments, we also tested $\ensuremath{n_p}=8$, but this resulted in fewer grammatical predictions since each token is predicted independently. To improve the predictions, we could use SpanBERT~\cite{joshi2020spanbert}, which is designed to infill spans, or an autoregressive model like T5~\cite{raffel2019exploring}.}

\subsection{Where to edit?}
\label{sec:where}

Our approach to using MLMs to determine where to delete and insert tokens is to find text spans where the source and target model disagree the most. Here we introduce a scoring function to quantify the level of disagreement.

First, we note that any span of source tokens that has a low likelihood in the target domain is a candidate span to be replaced or deleted. That is, source tokens from index $i$ to $j$ should be more likely to be deleted the lower the likelihood $\pl{W_{i:j} \mid W_{\backslash{i:j}}; \Theta_\textmd{target}}$ is.
Moreover, if two spans have equally low likelihoods under the target model, but one of them has a higher maximum likelihood replacement $\widehat{W}_{i:j}^\textmd{target}$, then it is safer to replace the latter. For example, if a sentiment transfer model encounters a polarized word of the wrong sentiment and an arbitrary phone number, it might evaluate both of them as unlikely. However, the model will be more confident about how to replace the polarized word, so it should try to replace that rather than the phone number. Thus the first component of our scoring function is:
\[
\begin{split}
\tscore{i,j} = \; & \pl{\widehat{W}_{i:j}^\textmd{target} \mid W_{\backslash{i:j}}; \Theta_\textmd{target}} \\
   & - \pl{W_{i:j} \mid W_{\backslash{i:j}}; \Theta_\textmd{target}}.
\end{split}
\]
This function can be used on its own without having access to a source domain corpus, but in some cases, this leads to undesired replacements. The target model can be very confident that, e.g., a rarely mentioned entity should be replaced with a more common entity,
although this type of edit does not help with transferring the style of the source text toward the target domain. To address this issue, we introduce a second scoring component leveraging the source domain MLM:
\[
{\small
\begin{aligned}
  \sscore{i,j} = - \max \Big[ 0, \pl{\widehat{W}_{i:j}^\textmd{target} \mid W_{\backslash{i:j}}; \Theta_\textmd{source}} \\
  - \pl{W_{i:j} \mid W_{\backslash{i:j}}; \Theta_\textmd{source}} \Big]
\end{aligned}
}
\]
By adding this component to $\tscore{i,j}$, we can counter for edits that only increase the likelihood of a span under $\Theta_\textmd{target}$ but do not push the style closer to the target domain.\footnote{\sscore{i,j} is capped at zero to prevent it from dominating the overall score. Otherwise, we might obtain low-quality edits in cases where the likelihood of the source span $W_{i:j}$ is high under the source model and low under the target model but no good replacements exist according to the target model. Given the lack of good replacements, $\widehat{W}_{i:j}^\textmd{target}$ may end up being ungrammatical, pushing \sscore{i,j} close to $1$ and thus making it a likely edit, although \tscore{i,j} remains low.}

Our overall scoring function is given by:
\[
{\small
\score{i,j} = \tscore{i,j} + \sscore{i,j}.
}
\]
To determine the span to edit, we compute $\arg \max_{i,j} \score{i,j}$,
where $1 \leq i \leq |W| + 1$ and $i - 1 \leq j \leq i + \ensuremath{n_p} - 1$. The case $j = i-1$ denotes an empty source span, meaning that the model does not delete any source tokens but only adds text before the $i$-th source token.

The process for selecting the span to edit is illustrated in Figure~\ref{fig:scores}, where the source text corresponds to two sentences to be fused. The source MLM has been trained on unfused sentences and the target MLM on fused sentences from the DiscoFuse corpus~\cite{geva2019discofuse}. In this example, the target model is confident that either the boundary between the two sentences or the grammatical mistake ``\textit{in {\color{red}the} France}'' should be edited. However, also the source model is confident that the grammatical mistake should be edited, so the model correctly ends up editing the words ``\textit{. She}'' at the sentence boundary. The resulting fused sentence is: \textit{Marie Curie was born in Poland and died in the France .}

\begin{figure}[tb]
\centering
\includegraphics[width=\columnwidth]{score_plot_tiny.pdf}
\caption{\textsc{Masker}{} replaces span ``\textit{. She}'' by ``\textit{and \textmd{\texttt{[PAD]}}{} \textmd{\texttt{[PAD]}}{} \textmd{\texttt{[PAD]}}{}}'', resulting in the following fused sentence: \textit{Marie Curie was born in Poland and died in the France .}
}
\label{fig:scores}
\end{figure}

\paragraph{Efficiency.}
The above method is computationally expensive since producing a single edit requires $\mathcal{O}(|W| \times \ensuremath{n_p})$ BERT inference steps -- although these can be run in parallel. The model can be distilled into a much more efficient supervised student model without losing -- and even gaining -- accuracy as shown in our experiments.
This is done by applying \textsc{Masker}{} to the unaligned source and target examples to generate aligned silver data for training the student model.

\section{Experiments}
\label{sec:experiments}

We evaluate \textsc{Masker}{} on two different types of tasks: \textit{sentence fusion} and \textit{sentiment transfer}.
For both experiments, we only apply \textsc{Masker}{} once to edit a single span of at most four tokens, since the required edits are often local.\footnote{We tried running multiple iterations of \textsc{Masker}, but this somewhat decreased the accuracy of the method. When parallel development data is available, it could potentially be used to optimize a threshold of $\score{i, j}$ so that the model could be called repeatedly until the $\score{i, j}$ falls below the threshold. Alternatively, it would be interesting to explore methods for simultaneously identifying multiple, not necessarily adjacent, spans to edit.}

\subsection{Sentence Fusion}
\label{sec:fusion}

Sentence fusion is the task of fusing two (or more) incoherent input sentences into a single coherent sentence or paragraph, and DiscoFuse~\cite{geva2019discofuse} is a recent parallel dataset for sentence fusion. We study both a fully unsupervised setting as well as a low-resource setting.

\paragraph{Unsupervised.}
First, we remove the alignment between unfused and fused examples in the training set of 4.5 million examples and finetune \textsc{Masker}{} on the resulting, non-parallel source and target corpora. This model yields an Exact match accuracy (which is a standard metric for sentence fusion \cite{geva2019discofuse,rothe2019leveraging}) of 12.65 on the development set. This is already on par with the Exact score of 12.32 obtained by a supervised \textsc{LaserTagger~} model \cite{malmi2019encode} trained on 450 examples.
We also test ablating SourceScore{}, which results in a decreased Exact score of 2.14, attesting to the importance of using the source model.
Finally, we test our model on the reverse direction of going from a fused text to unfused sentences. Here, \textsc{Masker}{} yields a significantly higher Exact score of 23.18. This direction is typically easier since it does not involve predicting discourse markers, which would require modeling the semantic relation between two sentences. The predictions of the reverse model are used in the low-resource experiments.
The unsupervised results are summarized in Table~\ref{tab:unsupervised_discofuse}.

\begin{table}[tb]
\centering
{\small
\begin{tabular}{lc}
\toprule
\textbf{Method} & \textbf{Exact score} \\
\midrule
\textsc{Masker}{} (unfused $\rightarrow$ fused) & 12.65 \\
\quad \textit{ablating} SourceScore & 2.14 \\
\midrule
\textsc{Masker}{} (fused $\rightarrow$ unfused) & 23.18 \\
\bottomrule
\end{tabular}
}
\caption{\label{tab:unsupervised_discofuse} Unsupervised sentence fusion results.}
\end{table}

\paragraph{Low resource.}
We use \textsc{Masker}{} to generate noisy unfused sentences for 46K target fusions in the DiscoFuse development set. This silver data is used to pretrain three different model architectures, \textsc{LaserTagger~}~\cite{malmi2019encode}, \textsc{FelixInsert~}~\cite{mallinson2020felix}, and \textsc{Bert2Bert~}~\cite{rothe2019leveraging}, which have previously been used for training fusion models under low-resource settings.
The results on the test set (45K examples) without and with pretraining on \textsc{Masker}{} outputs are shown in Table~\ref{tab:discofuse}. On average, the silver data from \textsc{Masker}{} improves the Exact score by 13.37 when 450 parallel training examples are available and still by 2.01 when 45\,000 parallel examples are available.

\begin{table}[tb]
\centering
\resizebox{\columnwidth}{!}{%
\begin{tabular}{lcccc}
\toprule
\textbf{Method} & \multicolumn{4}{c}{\textbf{Parallel training examples}} \\
 & \textbf{0} & \textbf{450} & \textbf{4500} & \textbf{45000} \\
\midrule
\textsc{LaserTagger~} & 0.00 & 12.32 & 25.74 & 38.46 \\
+ \textsc{Masker}{} silver data & 19.61 &	25.97 &	34.20 &	42.41 \\
\midrule
\textsc{FelixInsert~} & 0.00 &	15.34 &	34.11 &	46.09 \\
+ \textsc{Masker}{} silver data & 18.22	& 25.23  & 38.43 & 47.21 \\
\midrule
\textsc{Bert2Bert~} &  0.00 &	0.00 &	3.35 &	42.07  \\
+ \textsc{Masker}{} silver data &  13.05 & 16.57 & 30.14 & 43.03 \\
\toprule
\textbf{Average improvement} & \textbf{16.96} &	\textbf{13.37} &	\textbf{13.19} &	\textbf{2.01} \\
\bottomrule
\end{tabular}
}
\caption{\label{tab:discofuse} Low-resource sentence fusion results.
Using the predictions of \textsc{Masker}{} as silver data to pretrain models improves the Exact score.
}
\end{table}

\subsection{Sentiment Transfer}
\label{sec:sentiment}

In sentiment transfer, the task is to change a text's sentiment from negative to positive or vice versa. We use a dataset of Yelp reviews \cite{li2018delete}, containing 450K training, 4K development, and 1K test examples. Half of the test reviews are positive and half negative, and human annotators have written a reference review of the opposite sentiment for each test review. We use the same automatic evaluation metrics used in previous work: \textit{BLEU} score
and \textit{accuracy} that a classifier trained to distinguish negative and positive reviews assigns to the modified reviews being of the target sentiment.

We finetune the MLMs on the training set and apply the resulting \textsc{Masker}{} model to the test set. Additionally, we apply the \textsc{Masker}{} model to the non-parallel training set to create parallel silver data and train a \textsc{LaserTagger~} model. Interestingly, the latter setup outperforms \textsc{Masker}{} alone (15.3 vs. 14.5 BLEU score; 49.6 vs. 40.9 sentiment accuracy). We think this happens because \textsc{LaserTagger~} employs a restricted vocabulary of 500 most frequently inserted phrases, which prevents the model from reproducing every spurious infilling that the padded MLM may have produced, effectively regularizing \textsc{Masker}{}. In Table~\ref{tab:yelp}, we report these results along with baseline methods developed specifically for the sentiment transfer task by \citet{li2018delete} and \citet{wu2019mask}. Overall, \textsc{Masker}{} yields a competitive performance although \textsc{AC-MLM} w/ attention-based \cite{wu2019mask} slightly outperforms it.

\begin{table}[tb]
\centering
\resizebox{\columnwidth}{!}{%
\begin{tabular}{lcc}
\toprule
\textbf{Method} & \textbf{BLEU} & \textbf{ACC (\%)} \\
\midrule
\textsc{DeleteAndRetrieval} &	8.5 & \textbf{87.9} \\
\midrule
\textsc{AC-MLM} w/ frequency-ratio &	13.2 & 37.9 \\
\textsc{AC-MLM} w/ attention-based &	\textbf{15.7} & 53.4 \\
\textsc{AC-MLM} w/ fusion-method &	15.3 & 40.9 \\
\midrule
\textsc{Masker}{} &	14.5 & 40.9 \\
\textsc{LaserTagger~} w/ \textsc{Masker}{} silver data &	15.3 & 49.6 \\
\bottomrule
\hline
\end{tabular}
}
\caption{\label{tab:yelp} Yelp review sentiment transfer results.}
\end{table}

\section{Related Work}

Section~\ref{sec:intro} provides a high-level overview of the related work. Closest to this work is the \textsc{AC-MLM} sentiment transfer method by \citet{wu2019mask}.
This method first identifies the tokens to edit based on $n$-gram frequencies in the source vs. target domain (as proposed by \citet{li2018delete}) and based on LSTM attention scores (as proposed by \citet{xu2018unpaired}). Then it replaces the edited tokens using a conditional MLM. In contrast to their work, our approach leverages the same MLM for both identifying the (possibly empty) span of tokens to edit and for infilling the deleted span. Moreover, our padded MLM determines the number of tokens to insert without having to pre-specify it. In that sense, it is similar to the recently proposed Blank Language Model \cite{shen2020blank}.

In addition to the two applications studied in this work, it would be interesting to evaluate \textsc{Masker}{} on other style transfer tasks. Tasks for which unsupervised methods have recently been developed include formality transfer \cite{rao2018dear,luo2019dual}, lyrics style transfer \cite{nikolov2020conditional,lee2019neural}, text simplification \cite{paetzold2016unsupervised,surya2019unsupervised}, and sarcasm generation \cite{mishra2019modular,chakrabarty2020r}.

\section{Conclusions}

We have introduced a novel way of using masked language models for text-editing tasks where no parallel data is available. The method is based on training an MLM for source and target domains, identifying the tokens to delete by finding the spans where the two models disagree in terms of likelihood, and infilling more appropriate text with the target MLM. This approach yields a competitive performance in fully unsupervised settings and substantially improves over previous works in low-resource settings.

\bibliographystyle{acl_natbib}

redpajama_set_name: RedPajamaArXiv


text:
//
//  UISearchBar+LinkBlock.h
//  LinkBlockProgram
//
//  Created by NOVO on 17/5/8.
//  Copyright © 2017年 NOVO. All rights reserved.
//

#import "LinkBlockDefine.h"

#define UISearchBarNew ([UISearchBar new])

@interface NSObject(UISearchBarLinkBlock)
@property LB_BK       UISearchBar* (^searchBarText)(NSString* text);
@property LB_BK       UISearchBar* (^searchBarPlaceholder)(NSString* placeholder);
@property LB_BK       UISearchBar* (^searchBarDelegate)(id<UISearchBarDelegate> delegate);
@property LB_BK       UISearchBar* (^searchBarShowsBookmarkButton)(BOOL showsBookmarkButton);
@property LB_BK       UISearchBar* (^searchBarShowsCancelButton)(BOOL showsCancelButton);
@property LB_BK       UISearchBar* (^searchBarShowsSearchResultsButton)(BOOL showsSearchResultsButton);
@property LB_BK       UISearchBar* (^searchBarBackgroundImage)(UIImage* backgroundImage);

#pragma mark - LinkBlock

/** Get TextField from search bar  */
@property LB_BK       UITextField* (^searchBarSearchField)(void);
/** Use to modify border color of searchBar  */
@property LB_BK       UISearchBar* (^searchBarBackgroundImageColor)(UIColor* color);
@property LB_BK       UISearchBar* (^searchBarPlaceholderColor)(UIColor* color);
@end


Events at Setley Pond: The Scale Section annually holds two steering competitions for the Richard Graham Trophy and the Solent Cup. Places are determined by the number of times a competitor touches buoys or other components of the course (with the lowest number of touches winning!). Where two competitors have the same number of "touches" the one achieving that score in the fastest time is favoured. Most competitions consist of two rounds with the competitors best round being counted. The competitions are light-hearted. The Club's first Navy Day was held in 2008. There is an onshore display of warship models and fleet manoeuvres on the pond!
Supporting the RNLI: Over the years the SRCMBC supported various Lifeboat Days with Model Boat Displays, these included Calshot, Hythe Raft Race, and Lymington. Unfortunately many of these events are outdoors and the models are at the mercy of the weather. Calshot is particularly exposed and in 2009 strong winds overturned a table causing severe damage to some models. The Club continued to support Lymington Lifeboat Day where the models were displayed in the Lifeboat Station boat house. However participation ended in 2013 when the Boat House was required for other displays.
Charity Exhibitions The Club still supports the RNLI and also other charities through two annual exhibitions. The Highcliffe Show, which started in 1988, is held during the spring and in many years has been jointly arranged with the Highcliffe Branch of the RNLI supporters. With the Club participation in fewer Lifeboat days it was decided to start holding an autumn exhibition, the first being held in the Masonic Hall, Lymington, in 2010. This Exhibition moved to All Saints' Church Hall in Milford-on-Sea in 2013. The 2015 Milford Show was the most successful yet and, aided by sponsorship from Wightlink and HSBC, over £1000 was raised for charity. More information on some of the Charities supported by the Club can be found on our "Charities page".
Social Events: As well as raising funds for good causes, the annual Highcliffe Show and autumn Charity Exhibition serve as social occasions for Club members to meet. The Scale Section has an annual "Christmas Lunch", and occasional BBQs have been held.
Other Events: For many years the SRCMBC participated in the Romsey/Chandlers Ford "Model World" Exhibition and also in the Marwell Zoo Exhibition organised by Eastleigh and District Model Boat Club. More recently, Club members David McNair-Taylor and David Reith have displayed their warship models as members of the Surface Warship Association. Venues have included the Historic Dockyard in Portsmouth and Bursledon Brickworks.


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Q: How can I achieve a single mySQL row answer? How can I achieve a single mySQL row answer?
I have two tables given:
Table Flats
idFlat INT(11)
Street VARCHAR(45)

Table Tenants
id Tenant INT(11)
Flats_idFlat INT(11)
Surname VARCHAR(45)
Firstname VARCHAR(45)

My query
SELECT
    Flats.idFlat,
    Flats.Street,
    Tenants.Surname,
    Tenants.Firstname
FROM
    Flats
        LEFT JOIN
    Tenants ON Flats.idFlat = Tenants.Flats_idFlat
WHERE
    Tenants.Flats_idFlat IS NOT NULL

turns out with the following result because John and Peggy are living in the same flat:
idFlat    Street        Surname        Firstname
1          Taft Ave     John               Miller
1          Taft Ave     Peggy             Ballot

I'm looking for a result like this:
idFlat    Street        Surname        Firstname
1           Taft Ave    John/Peggy    Miller/Ballot

I tried some CONCAT_WS queries like
CONCAT_WS('/', Tenants.Surname, Tenants.Firstname) AS Tenants

but it always results in multiple output of the flat.

A: Try using GROUP_CONCAT with a custom ordering and separator:
SELECT
    f.idFlat,
    f.Street,
    GROUP_CONCAT(t.Surname   ORDER BY t.Surname SEPARATOR '/') AS Surname,
    GROUP_CONCAT(t.Firstname ORDER BY t.Surname SEPARATOR '/') AS Firstname
FROM Flats f
INNER JOIN Tenants t
    ON f.idFlat = t.Flats_idFlat
GROUP BY
    f.idFlat,
    f.Street

Note that your current left join probably can be reduced to an inner join given the logic in the where clause.