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Q: 'Execution target' list on KMM Android studio is empty I'm trying my hand at Kotlin Multiplatform Mobile, and am trying to run the demo app on an iPhone. I am able to run it easily on the Xcode simulation but can't simulate it on Android Studio, I'm not able to se 'Execution target' list enter image description here
I can do it on Xcode but No when I try directly on Android Studio, What can I do?
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I need to select 'Expectation target' but I can't see any option an the list

redpajama_set_name: RedPajamaStackExchange


text:
// This file is automatically generated.

package adila.db;

/*
 * Sugar Sugar
 *
 * DEVICE: s9121
 * MODEL: SUGAR
 */
final class s9121 {
    public static final String DATA = "Sugar|Sugar|";
}

redpajama_set_name: RedPajamaGithub


Ireland lost its first T20I due to the failure of crucial players and reluctance to the spin-attack of Indian bowlers. Some of the other flaws are, dropping Rohit Sharma twice and lack of planning to encounter Indian batsmen. Here are some of the reasons why Ireland lost to India in the first T20I.
The Irish bowlers failed to collapse the opening stand of Rohit Sharma and Shikhar Dhawan in the first 15 overs. This is a failure of fielding department as well. The poor performance of the bowlers and frequent deliveries outside the off-stump caused the opening partnership to continue upto 160 runs. The perfect combination of left-hand-right-hand batsmen for the opening stand made India make an impressive score of 208 runs off 20 overs.
Rohit Sharma slammed 97 runs in the first 15 overs after being dropped twice. The opening stand of Rohit Sharma and Shikhar Dhawan is one of the best in the World. They were in good form and thrashed the Irish bowlers with 160 runs. But unfortunately, Rohit Sharma lost his wicket and missed out his third T20I century with a difference of three runs. He scored 97 runs off 61 balls.
The players except James Shannon failed to establish good partnerships. James Shannon slammed 60 runs off 31 balls and the only highest partnership from Ireland was between Shannon and Andrew Balbirnie of 40 runs. Shannon fought a lone battle afterward and failed to support the team due to lack of a good hand to support him and rebuild the innings.
The key players like Paul Stirling and Kevin O Brien could not contribute to the victory of the team. Paul Stirling was dismissed at the score of one run in the first over itself and most of the crucial batsmen could not score more than 10 runs. Andrew Balbirnie is the only batsman to score 11 runs. The new comers like Stuart and Simi Singh also failed to score some impressive runs.
The spin-duo of India, Yuzwendra Chahal and Kuldeep Yadav managed to pick seven wickets together. Kuldeep Yadav picked 4 wickets and conceded 21 runs and Yuzwendra Chaha picked 3 wickets off 38 runs. Yuzwendra Chahal managed to pick the wickets of crucial batsmen like Kevin O Brien, and Gary Wilson. Kuldeep Yadav picked the wicket of James Shannon, the top scorer of the match. The spin duo is expecting to perform well keeping an eye on the long tour to England. It is exciting to see how can the Irish team encounter the leg spinners after learning a big lesson from their defeat in the first T20I.


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Review: Princess Diaries (2001)
Mia Thermopolis' (Anne Hathaway) main ambition in life is to be invisible. The 15 year old lives with her mother Helen and their cat Fat Louie in a renovated firehouse in San Francisco. She is very unpopular at her private school, with only two friends: her best friend Lily Moscovitz (Heather Matarazzo) and her brother Michael (Robert Schwartzman).
A few weeks before Mia turns 16, she is invited to meet her paternal grandmother for the first time in her life. When she arrives at the Genovian consulate, she gets the shock of her life: her grandmother is in fact Queen Clarisse Renaldi, Queen of Genovia. Queen Clarisse (Julie Andrews) explains that Mia is now the only heir to the Genovian throne. Mia refuses to acknowledge her position and runs away from the consulate to go fight with her mother for withholding life changing information. When Clarisse visits her at her house, it is explained to her that without her acceptance to her title, Genovia will have no future ruler. The three ladies come to an agreement that Mia will take Princess Lessons, and can decide her fate on the Genovian Independence Day ball. The queen appoints her head of security, Joe (Hecto Elizando) as Mia's personal bodyguard.
Mia's lessons start and she meets her grandmother each day after school. She has to frequently cancel her plans with her best friend, which leads to explosions from Lilly. She finally shares the news with her after an Italian hairdresser, Paulo transforms her image and Lilly accuses her of "trying to fit in". Lilly is obviously ecstatic, but things start going off again when Paulo leaks the information of a Princess schoolgirl to the press.
School becomes crazy for Mia, and she hides on the rooftop with Joe. But finally there seems to be some good things happening to her. Josh Bryant, a popular boy band lookalike, finally notices her, and asks her to the school beach party. There he kisses her as a publicity stunt, and Mia is further humiliated by school bully Lana Thomas (Mandy Moore) and her cronies. The Queen is furious after Mia appears in a newspaper in compromising photos. Joe points out to the Queen how unfair she was as the situation was out of control. Clarisse apologises to Mia, and their bond is stronger than before. Mia gets her revenge on Lana by messing ice cream on her cheerleader outfit at school, and the teachers are amused that Lana finally got some medicine of her own.
Mia realises that she must choose her destiny (rather difficult for a 15 year old) and plans to run away. She opens the diary her father left her for her 16th birthday, and misses the letter that falls out. Just as she wants to run away, she notices the letter Fat Louie is sitting on. Reading it, she realises she needs to become a princess. On her way to the consulate her car breaks down (in the rain) and it seems all hope is lost. Joe, who realised her intentions, saves her and takes her to the consulate to accept her position. Mia ends up with her friend Michael, who had a crush on her all along.
The story ends with Mia in an aeroplane, arriving in Genovia to take over her duties.
This movie is a serious contender to be a favourite film of all time to me. It really is a very sweet and fun film. This movie was Anne Hathaway's first movie, and it is obvious there that she was meant to become a star. She portrays the awkward Mia perfectly. I love the movie because it really is about a young girl making difficult decisions and about the importance of being who you are.
March 7, 2013 by Natasha Categories: Movies, ReviewsTags: Anne Hathaway, Julie Andrews, Movies, Princess Diaries, Reviews Leave a comment
Review: Fallen Star (Nora Roberts)

redpajama_set_name: RedPajamaCommonCrawl


WASD keys to move, J/K/L to attack and defend. combo1 : S-W-F , combo2 : S-D-J , combo3: secret.
Its recommended to bookmark this page if you like the game Thunder Devil game and want to play it later, in your free game bookmarks! just press the CTRL (control) and D key on your keyboard at the same time and your set.


When America entered World War I in 1917, chairman of the War Industries board Bernard Baruch asked women to take off their corsets to conserve steel. Some 28,000 tons was diverted, enough to build an entire battleship.
An outspoken Russian Jewish immigrant sold American women on the first undergarment that uplifted and conformed to their shape -- the brassiere.
An 18-year-old immigrant from Tsarist Russia in 1904, Ida Kaganovich held socialist ideals and believed in women's rights. After breaking with an aunt and uncle in Hoboken, New Jersey, strong-willed Ida Americanized her last name to "Cohen." Two years later, she married the beau she had followed to the U.S., William Rosenthal. Unwilling to work for others, Ida bought a Singer sewing machine on the installment plan, and hung out her shingle as a seamstress. William, plagued with poor health, took up sculpting.
Rosenthal's business grew during World War I, and by 1921, she opened a dress shop in Manhattan with a partner, Enid Bisset. William soon joined them. Jazz Age women were living through a cultural sea change; they won the right to vote and went to work in new jobs in factories, department stores, and offices as urban economies expanded. The Flapper look made women wrap their chests in bandeaux for a flat-chested "Boyish Form." Buxom Ida deplored the fashion. "Why fight nature?" she asked.
To make women look better in their dresses, Enid and William designed a built-in bandeau with cups that separated and supported the breasts. Customers loved the brassieres, and quickly demanded them separately. By 1922, the small dress shop had registered the name Maiden Form and hired a salesman. Word of mouth brought more success, and in 1925, at Ida's urging, the partners stopped dressmaking to focus on their hot product. In 1928, they sold 500,000 bras. The company survived the Great Depression and Enid's retirement, and by the end of the 1930s Maiden Form products were sold in department stores across the nation and around the world.
"I Dreamed... in My Maidenform Bra"
Ida became the management and marketing genius, with William her creative counterpart. William devised standard cup sizes, along with the first maternity and nursing bras. Ida managed the company's finances, manufacturing, and sales. She bought ads, negotiated with unions and introduced assembly-line production. They built loyalty by continuing old styles as they introduced new ones, and made sure a wide array of retailers carried their line. Most importantly, they built the brand name with racy ads that debuted in 1949, featuring photographs of women in bras. The "I dreamed... in my Maidenform bra" campaign ran successfully for 20 years. William died in 1958, but Ida remained at work until she suffered a stroke in 1966. She died of pneumonia in 1973, leaving the multimillion dollar family company to her daughter, Beatrice.


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Shohei Ohtani - the unanimous AL MVP, and well-deserved. Among other awards - the Historic Achievement Award, Player Of The Year, etc. We witnessed possibly the greatest season of any athlete, albeit a baseball player. Well, at least a baseball player. If Linsanity was not unfairly targeted against / kicked out from prejudices in that so-called sport, then it'll rank among it. Shohei is still very young, and still can improve / get better. And you know it.
And now from Shohei - 'Sho' Me The Wins! haha. Team improvement is the next step. Looking forward to next season fo 'Sho'.
'Sho' us the home runs! And Shohei certainly does with power. Number 45 and counting. Imagine how much more if mofos didn't intentionally walk him and whatnot.
Happy 40th, Shohei! No, not a birthday but homeruns haha. He had a stellar pitching the same game as well. As the song goes, he's "simply the best, better than all the rest" haha.
How embarrasing would it be, to be a victim to a Shohei power home run on one's birthday, sort of like being "posterized" haha - "Happy Birthday, Mr. Pitcher. Your wishes have come true!!" haha.
Congratulations for another Player Of The Month award for July - two consecutive months. It's not just the power homers, but everything else - pitching, RBI's, base steals, etc. It's unreasonable to expect Shohei to hit a homer every game or frequently - but we can only hope. We also have to acknowledge or notice his other contributions as mentioned, which are also highly valuable. Unfortunately, the Angels roster or bullpen as they say, is much left to be desired or is not a winning combo. Baseball fans would probably know what the team needs upgrades in.
37 HR's and counting. From the way fans and other media are describing The Big 'Sho', you can say that he might be the perfect athlete or specimen. Godly. The Total Package. Nah - everyone has flaws or has bad ones. But For 'Sho', he is the real deal and MVP.
I am not surprised that Shohe Ohtani jerseys can get pricey. But value equals talent for sure. And there really is no other athlete like The Big 'Sho'. Did his latest homer rival that of the one at the Tokyo Dome? Probably not, but close.
32 home runs and counting. They are not just average home runs, but they have distance / power. After watching the home run blasted into the roof of the Tokyo Dome years ago, I am not surprised. To all the haters, racists (typical media) against exceptional and talented Asian athletes - we'll gladly tell you where to stick it (*hint - where the sun don't shine).
Happy 27th! That's still hella young. I can imagine he hasn't reached his full potential yet. There is no need to go over what he is doing, since it is well-known now and is the talk of the town in the sports world (of course, in MLB in particular). Still - I'm sure he isn't fully satisfied. For any endeavor, there is always the desire to improve and get even better.
My favorite nicknames - The Big 'Sho', The 'Sho'-Stopper, 'Sho'-Tastic, etc. It appears endless haha.


text:
import { Component, Input, trigger, state, style, transition, animate, group } from '@angular/core'

@Component({
  selector: 'app-sensor',
  template: `
    {{_component.name}}: {{_component.controlState}}

      %
      °C

  `,
  animations: [
    trigger('growShrink', [
      state('in', style({ transform: 'scale(1)', opacity: 1 })),
      transition('void => *', [
        style({ transform: 'scale(0)', opacity: 0 }),
        group([
          animate('1.3s ease', style({ transform: 'scale(1)' })),
          animate('1.3s ease', style({ opacity: 1 })),
        ])
      ]),
      transition('* => void', [
        group([
          animate('1.3s ease', style({ transform: 'scale(0)' })),
          animate('1.3s ease', style({ opacity: 0 }))
        ])
      ])
    ])
  ],
})
export class SensorComponent {
  private _component: any

  @Input()
  set component(component: any) {
    this._component = component
  }

  constructor() { }

}


Shivling carved out of natural Tiger Eye gemstone.
Shivaling has three distinct parts which are considered as portions of Brahma,Vishnu and Shiva.The lower part represents Brahma, the middle Vishnu and the upper and the most prominent represents Shiva.Thus, Shivling represents all the three powers in one- as the Param Braham or Supreme Shiva.
Another interpretation considers Shivling to be divided in two parts – Shiva and Shakti.The top part is considered Shiva and the yoni is considered to be Shakti.
There is mysterious and indescribable power in Shivaling to induce the concentration of mind.It is like the crystal glazing, mind easily attains one-pointedness by looking at the Shivaling.This is the reason why ancient scholars and sages advocated the worship of Shivaling and its installations in temples.
Tiger Eye is primarily used as a personal talisman to attract wealth and property. It does increase devotion and aids in smoothing differences between life partners. It has strong energy to build leadership and authority.


AARHUS, Denmark & BELLEVUE, Wash. – August 2018 — TimeXtender, a recognized global software company enabling instant access to any type of data in the organization to support advanced analytics and artificial intelligence (AI), has announced new enhancements to its Discovery Hub® platform.
The latest release of TimeXtender's Discovery Hub® platform now allows users to seamlessly connect to more than 100 popular systems and data platform providers such as Microsoft Dynamics (365 and on-premises), SAP, Salesforce, Spark, MySQL and Amazon (Redshift, Athena, DynamoDB), among many others. These connectors are pre-built and included in Discovery Hub® requiring minimal configuration and allowing fast and reliable connections to data. In addition, support for JSON and XML files as well as REST based APIs have also been included. See the full list of available connectors here.
Furthermore, this release extends the already broad support for Microsoft Azure by including connectivity to Azure SQL Database Managed Instance (DBMI). Azure SQL DB Managed Instance is a new service in Azure, providing near 100% compatibility with SQL Server on-premises.
In short, the latest Discovery Hub® release provides better alignment with Microsoft Azure, supporting Azure SQL Database, Azure SQL Database Managed Instance, Azure Analysis Services, and Azure Data Lake. Discovery Hub® is also Azure certified and available in the Azure Marketplace.
"Discovery Hub® helps to address their growing customer demand for advanced analytics in a governed data environment. TimeXtender on Azure enables organizations to optimize their data without draining time or resources," stated Bharat Sandhu, Director of Product Marketing, Big Data and Analytics, Microsoft Corp.
Moreover, a recently published report by Microsoft entitled "TimeXtender streamlines and speeds up data discovery" details how Discovery Hub® can rapidly deliver tangible business benefit in the fast-moving Artificial Intelligence space. The case study can be found here.
And visit here, to find out more information about Discovery Hub® on the TimeXtender website.
TimeXtender is a recognized global software company enabling instant access to any type of data in the organization to support advanced analytics and artificial intelligence (AI). The company inspires quality business decisions with data, mind and heart and helps customers manage ever-changing data sources to realize the full potential of data through Discovery Hub®, a modern software platform that allows customers to build, deploy and manage an enterprise-grade, analytical architecture. Supporting the Microsoft Azure cloud platform, TimeXtender helps customers make the transformative journey to the cloud. The company serves its 2,700+ customers, from mid-sized companies to Fortune 500, through its global network of partners. TimeXtender was founded in 2006 and is privately owned, with headquarters in Denmark and the U.S. and regional offices and partners around the world.


Our Village Hall is in the middle of Witnesham on the B1077. Formerly the village school (built 1810), it became the village hall in the early 1950s, with later extensions and refurbishments.
It holds 115 seated (120 closely seated), 120 dancing.
Facilities: Servery, toilets and disabled toilet, car park (40 cars). Licensed for music and dancing.
Main hall, with side and store room. PA and hearing loop. Toilets and disabled toilet in main entrance hall, right.


Cell Care (formerly Tumor-X (le*) 1:4 | Hedley Enterprises Ltd.
• Works to help reduce the size of tumors and cysts.
• Purifies the circulatory system with the removal of toxins that cause chronic illness.
• Supplies body-building nutrients that help the body fight illness.
• Provides anti-inflammatory and analgesic properties that reduce pain.


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Tagged: Backstage Expert, audition tips, audition strategies, audition technique, actors, acting
acting, acting career advice, actor advice, actors mindset, following your dreams
Don't send me an email like this...
I used to have a massive crush on Jon Bon Jovi.
Who didn't?
That hair. The swagger. How his lips lingered on the microphone when he sang…
He was the ultimate heartthrob and he made me want to be a singer. Because then I had a chance of touring with him.
Why not dream big, right?
But what I really wanted to be was Little Orphan Annie and I thought I had a good shot. I had the hair and I loved the songs.
So I auditioned when the musical came to town.
Tagged: acting, acting career, actors life, actor goals
acting, actor advice, actors, actors mindset, auditioning
I got new headshots recently and I was terrified.
Headshots are one of those things that, as an actor, you KNOW you have to do but it's so freaking stressful because "what will I wear" and "how many looks do I need?" and "what if my hair doesn't cooperate?"
All the things that make you say no.
I'd actually needed new headshots for a while. But I kept putting it off.
Then...I started a trial run with a new manager and the first thing she asked me was whether or not I would consider new headshots.
Ugh. I believe in kismet, so I knew it was time.
So I booked it.
Tagged: actor advice, actors, actor mindset, acting, acting career, acting tips
It's getting personal...
I want to do something a bit different today and show you an example of what I call the shadow side of strengths.
For me, it's was when three of my top talents banded together in their very usual pattern, to hurt someone I care about.
Tagged: acting, actors life
acting, actor advice, goal setting, Backstage Expert
Busy doing nothing?
I walked by a house the other day that still had its Christmas lights up. I get it, those perpetually tangled strings are a complete pain in the butt to put up and take down every year.
But this house also had a giant snowman on the front porch, surrounded by fake presents and oversized ornaments. I didn't see a garage, which means the owners walk by these decorations every day.
And every day, they choose NOT to take them down.
It's all about choices.
And just like the owners of that house, you're making choices every second of every single day.
It's a bit heady to think of your acting career unfolding in a series of snap decisions, isn't it?
Tagged: actors, actor advice, acting, actor mindset, acting tips, Backstage Expert
acting, actor advice, actors, following your dreams, acting career advice
The #1 secret for making things happen
As humans, we need each other.
For companionship, for love, and definitely for goals.
Because we all have strengths and things we're good at, but we also have the things we're not so good at.
This could look like a person who has a million great ideas but never finishes one before she's off and running with the next thing.
Or it's the person that's who takes so long weighing all the pros and cons that they never make a decision.
I'm highly aware of what my talents are and also very aware of alllll the things I don't do well.
Enter strength-based partnerships.
Tagged: actor advice, acting, acting career, strengths partnerships, Dallas Travers, actor goals, goal setting for actors
life lessons, following your dreams, coaching, actors mindset, actor advice, University of Michigan, acting and rejection, Scandal ABC
Remember your why
If you read my blog post, "The power of being naive", several weeks back, then you know that I went to the University of Michigan and that I'm pretty much obsessed with it. #goblue.
I wish the Wolverines had won the NCAA tournament, but I was still blown away by the way the team played.
It was freaking impressive by all accounts.
But what I loved the most, was how the coach, John Beilein, responded to a reporter's question after their loss for the title. His words speak volumes about him as a coach and mentor for those young men. He said:
Tagged: Michigan, actors, acting, auditioning
acting, actors, actors mindset, cut through the noise, actor advice
Wanna cut through the noise? Do this.
I got a great question recently from an actor named Josh Berresford and wanted to highlight it here, because I think this is one that comes up for a lot of people... including me.
Here's what he asked:
How do we deal with all of the bloggers, educators etc. out there, and be able to extract what will help us most and not be inundated with so much and so many to choose from?
Here's my (very stream-of-consciousness) response:
Tagged: acting, actors, actor mindset, actor advice
acting, actors, auditioning, coaching, following your dreams, actors mindset, mindset
How Barre Class Reset My Self-Talk
I think we can all agree there's not enough time in a day.
So in an effort to "add more time" to my own day, I decided to get up at an hour earlier, at 5:45, to exercise. I know, I know, 5:45 a.m. is NOT that early...and especially since I spent 18 years getting up at 3:45am when I worked in the bond market. But, times change (no pun intended).
In the first few minutes of my 6:30 barre class, when I couldn't sustain a plank for a full minute, I got frustrated and started berating myself for not being as strong as I should be or letting the early morning get to me. My mind said, "You're better than this."
And then my heart said, "Hey! I woke up at 5 freaking 45 to be here. Isn't that kinda awesome? And even if I only get 80% of the benefit, isn't that better than not working out at all?
And slowly, my mindset shifted. And while I still didn't feel as strong as I normally do, I felt pretty dang proud of myself for being there at all.
Tagged: nerves in the audition room, self-talk, actor mindset, mindset, acting, auditioning, self-confidence, how to control audition room nerves, DaJuan Johnson, Think Bigger Coaching
acting, actors, auditioning, business, entrepreneurs
The Butter Cookie Breakthrough: How I Learned To Spike My Productivity
I'm new to the entrepreneur lifestyle and it has been a huge learning curve with many highs and many lows. And lots of 'what the hell have I dones'.
It has felt a bit like getting a ticket for a 2018 Simon & Garfunkel Nostalgia Tour (someone please make this happen) but then finding out it's in London and my passport won't be renewed in time.
I'm being dramatic but I had a recent wake-up call that turned my business on its head
Here's what happened.
Tagged: actors, entrepreneurs, acting
acting, actors, auditioning
The Real Reason Your Social Media is a Pain in the A$$
Social Media is kind of a pain in the ass.
You wish it was easier to use. You wish it was fun. You wish that attracting gobs of followers with your witty banter and interesting posts was a no-brainer.
You make excuses not to do it like, "I'm too old", or "I wouldn't know what to post", but deep down you're actually afraid that no one will like your stuff, follow you back, or that you might get blasted for saying something dumb, amiright?
And then a new kind of fear creeps in. It's called FOMO and it sounds like, "What's a meme?" or "Whose abs are they talking about?"
I know that's what you're thinking because I used to think it, too.
Tagged: actors, acting, social media for actors
acting, actors, coaching, auditioning
How Getting Really Pissed Off Helped Me Find My Groove
She doesn't know it (yet, because I just figured it out for myself) but my mom is the inspiration behind the Magnetic Actor Method.
But not in the, "Hi, it's me, your mom. I just called to say I have this great idea for a business you should start" kind of inspiration.
That's not even close. Here's the backstory.
Tagged: actors, acting, coaching
auditioning, actor advice
Promises, Promises + a Year of Bringing Back the Magic
I've been getting a lot of questions about my New Year's Resolutions.
The truth is, I don't make them. Never have. One year I tried to do something every day in lieu of giving something up (I chose sit-ups), but that didn't stick either. (Dangit.. just realized I could have given up situps and crushed my resolutions that year!)
So screw it! This year I'll unabashedly eat chocolate whenever I want, and may, or may not, work on my core.
But I do have goals. And plans...for you. BIG plans.
Tagged: magnetic actor method, acting, auditioning
acting, actors, auditioning, coaching
5 Ways To Supercharge Your Next Audition
I totally rocked an audition last week.
Everything went exactly as I had planned, and I knew I'd booked it.
As we all know, auditioning is scary. As an actor, you're putting yourself on the line in every audition, and most of the time, you hear crickets. It's easy to start getting in your head and questioning whether you've got what it takes.
I'm a firm believer in leveraging one's strengths in all facets of the business, and for me, that includes audition prep and the moment I walk into the casting room. That's what my Magnetic Actor Method is all about, and it has transformed the way I approach auditions. Here's what it might look like in the the audition room, and how it worked for me.
Tagged: audition, auditioning, actors, acting, coaching
entrepreneurs, coaching, auditioning, actors, acting
The Only Thing That Really Matters (P.S. It's Not Chocolate)
I know it's December, but I'm still thinking about Thanksgiving. And it's because of my brothers.
Yes, because I'm thankful for them, but there's more to it. It really comes down to that I don't see them enough.
We see each other every Thanksgiving which is pretty incredible for a family strewn across the country: My mom is in Hawaii, I'm in California, one brother is in Michigan and the other brother is in New York.
But about 5 years ago we made it a priority to see each other every Thanksgiving, because life is short. And family is what matters.
Tagged: family, acting
acting, actors, coaching
The 5 Non-Negotiables I Can't Live Without
I think we can all agree that our world feels out of control right now, and we have no idea what we're gonna wake up to.
But there is one thing I can count on every single day, no matter what (and it's not that I wake up and want chocolate*, although that happens!? #truth)...
Tagged: actors, acting, Cliftonstrength
actors, acting
How To Have More Free Time: My Day Of The Conscious Nope
I pride myself on knowing my greatest talents and strengths, yet they sometimes get me into trouble and it drives me absolutely insane.
I don't think I'm alone.
We all have strengths and talents that let us do incredible things, but there's also a "dark side". Our strengths can also get the best of us if left unguarded or misunderstood.
For me, it's my Responsibility and Harmony. I know what you're thinking, "Those seem like goodie two-shoes themes. How in the world do they get you in trouble?"
First of all, I don't mean TROUBLE, Trouble. I just mean they leave me cursing myself for my inability to reign it all in. So, maybe instead of the "dark side" of talent, I should call it, Talent Exuberance.
Tagged: actors, acting
acting, auditioning
How To Handle The Most Misunderstood Audition
Yippee! You have an audition!
Then, dread. It's a one-liner.
I know what you're thinking. How will I stand out? How will I let the CD know what a good actor I am and that I can cry on cue? What about my Meisner Training?
Throw it all out the window! (But not too far.. you'll need all of this when the guest star auditions roll in).
Tagged: auditioning, actors, acting
acting, auditioning, actors
3 Smart Strategies I Hope You Never Use
I just forgot to go to an audition. Seriously…who freaking does that?
Me! I did that, and my anger and shock were tearing me apart. Forgetting important auditions is not something I do.
How then, I asked myself, how for the love of dark chocolate, did this happen?
Tagged: actors, auditioning, acting
acting, actors
How We Can Turn Hollywood On Its Head
Let's Start a Revolution.
Who's with me? Wouldn't it be incredible if we could take the entertainment industry by storm and move it from a fear-based, nebulous entity to one where we all speak the same language – a language of strengths, self-certainty and positive growth?
That's the kind of revolution I'm talking about.
Tagged: hollywood, actors, auditioning, acting


Please complete the below information for the Monthly Parker who will be cancelled at the time of this request.
Note: Cancellations must be received 30 days in advance. Any requests not received 30 days in advance, will still be charged for the entirety of the current month, and the following month.
Example: If requested to cancel a card on 6/30, you will still be charged throughout the month of July and you card will be cancelled 7/30. If you request to cancel a card on 6/15, you will still be charged for the remainder of June, and July. You must cancel by the 1st of the month, to avoid charges in the next month.


Download the Windows installer from the POPFile Download Page, and run setup.exe and follow the instructions in there. You can launch POPFile from the Start Menu (Start→ Programs → POPFile → Run POPFile in Background), or reboot and it will start automatically. Important note: nothing will appear on your screen! To check if it's running correctly, read the "Accessing POPFile" section below.
You'll need several things to get started with POPFile.
POPFile itself occupies just over a megabyte. The word lists (called the corpus) used to classify your email will take some additional space depending on how much mail you use to train POPFile and how many buckets you create.


Now that the election and Inauguration are officially over, I feel like we can all breathe a bit. I proudly say that I attended my first protest, which was a very peaceful one. The Women's March on Washington had several different messages voiced through the signs carried throughout the city by all of the individual patrons. There was a large crowd, a very large crowd, and by the numbers reported, surpassed the attendance of the inauguration of our 45th President of the United States.
I am not writing this as a bash of either political party, I am simply here to express some thoughts that I personally feel as a citizen of this great nation. First and for most, we ALL are created equal, I do not care what color you are, if you speak another language aside from English, if we don't share the same religion, if we don't share the same politics, what your sexual orientation or identity is, etc.. If you treat me with respect, I will do the same in return.
This election divided our country so much, and created so much hate. I want to live in a country where we look out for one another, where we don't judge people, and especially are not trying to turn our country back 50 or 100 plus years, not after all of the work we have done. Of course, now that we have a new Commander in Chief, things are different, and based on the voice of President Trump's campaign, he has a different vision aside from what President Obama worked for over the past eight years. I am not intending to start any fight, or rude comments, simply my observations from his campaign messages.
I hope over the next four years, we see some progression, and keep our country safe, and not undo all of the work that President Obama worked so hard for. No President is perfect, and I will leave this post with this: Knowledge is Power.


Image Title: How To Install A Subway Tile Kitchen Backsplash Young House Love Throughout Plans 16. Post Title: Kitchen Subway Tile Backsplash. Filename: how-to-install-a-subway-tile-kitchen-backsplash-young-house-love-throughout-plans-16.jpg. Image Dimension: 650 x 969 pixels. Images Format: jpg/jpeg. Publisher/Author: Brandon Hand. Uploaded Date: Wednesday - January 30th. 2019 21:26:21 PM. Category: Architecture. Image Source: homedit.com. 25 Subway Tile Backsplash Ideas That Are Totally Timeless Within Kitchen Prepare 6. How To Install A Kitchen Backsplash The Best And Easiest Tutorial With Regard Subway Tile Designs 10. Kitchen Subway Tiles Are Back In Style 50 Inspiring Designs With Tile Backsplash Ideas 1. Kitchen Subway Tiles Are Back In Style 50 Inspiring Designs Pertaining To Tile Backsplash 8. White Granite Kitchen Countertops With Subway Tile Backsplash In Decor 11. White Kitchen Cabinets With Subway Tile Backsplash Beveled Intended For Ideas 3. How To Install A Subway Tile Kitchen Backsplash Young House Love Inside Inspirations 4. 11 Creative Subway Tile Backsplash Ideas HGTV With Kitchen Designs 18. Installing A Subway Tile Backsplash In Our Kitchen THE SWEETEST DIGS For Plan 7. These Kitchens Prove That Subway Tile Backsplashes Will Never Go Out Within Kitchen Backsplash Inspirations 5.


Did You Ever Wish For A Crystal Ball That Can Tell You When The Market Is Going Up Or Down? How About A Personal Trading Advisor That Can Recommend When To Enter A Trade? With Quant Trader You Get Both In One Easy To Use Software Package.
Though we have yet to evaluate your service, be assured that we have acknowledged your submission and will have it reviewed in a prompt and steadfast manner. Our team of highly qualified and enthusiastic writers spend countless hours searching the web for products and sites to review, and treat each entry with the same respect and deference. We sincerely hope our site will meet your needs.


Pavlich Law is conveniently located in the heart of Orange County, California. This location allows us to serve our clients' needs across a region of Southern California that includes Orange County, San Diego County, Los Angeles County, and Riverside County.
With the experience and knowledge gained from his representation in more than 300 cases, Mr. Pavlich has developed a keen ability to give unbiased, and thorough legal advice, and to provide zealous representation of clients in resolving their legal issues.


In the United States, an estimated 67,774 wildfires burned approximately 9,326,238 acres in 2012 alone.* To mitigate this number, teams of specialists country-wide -- from pilots of air tankers and helicopters to ground personnel such as Hot Shots and Smoke Jumpers -- are called to tame destructive fires that can destroy property and take lives.
To prepare, hundreds of firefighters assess the situation and coordinate responsibilities with various crews using maps. However, the role in which information is relayed has changed slightly through digital means, enabling information of a quickly changing wildfire to be shared with those in its path.
Still a fairly new concept for some, Banke and his team were introduced to Avenza Maps only a few years ago, allowing them to access maps and familiarize themselves with landmarks and fire breaks long before they arrive at a base camp. Once the Incident Management Team's GIS Specialists create the initial map with a QR Code (Quick Response Code), an incident-specific website is assigned, and firefighters can download the latest maps to the Avenza Maps app and receive the most updated version. "We used to get our first look of the fire during the morning briefing when the paper maps were handed out, but now both air and ground personnel come to the briefing more prepared knowing what they're up against," Banke shared.
While acting as a guide to water tankers and other ground personnel, Banke's job also includes being cognizant of areas near water or where retardant drops could be harmful to certain species. With the use of Avenza Maps, Banke can easily record a 1,800 gallon fire retardant drop with a simple touch of a pinpoint and include a picture and noted details to send back to biologists and GIS specialists monitoring the area. With ease, Banke can also quickly email copies of his findings back to base camp so that incident management personnel is aware of any wildfire shifts while Banke is airborne.
Every year, air tactical workshops are conducted where people like Banke receive a refresher course on rules, regulations and training of new techniques and technology. Avenza Maps is now included in the training on important apps used out in the field.


The reseller server evergreen.nocdirect.com is performing a raid array verification process which is resource intensive and may cause slower performance than normal. The process is 52% completed. We will keep the thread updated as it progresses.
Last edited by JPC-Jacob; 04-20-2017 at 10:19 PM.
The raid array verification process is 53% complete. Updates will follow.
The raid array verification process is 54% complete. Updates will follow.
The raid array verification process is 63% complete. Updates will follow.
RAID array verification has 66% completed. More updates to follow.
Server went unresponsive due to high I/O wait so we had no choice but to reboot it. Server is back online but the RAID verification has been started from scratch. We have stopped the cPanel services to control the load and expedite the verification process.
We apologize for the inconvenience and appreciate your cooperation. More updates will follow.
RAID array verification has 3% completed. More updates to follow.
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Aventura is just one of many neighborhoods in Miami that are worth exploring, and, you will need an automobile to check out everything there is to do in this city. Buses or metro, while cheap, may not take you to exactly where you need to go. Ridesharing is convenient, but small towns may not have timely service. Plus, if you plan to go all over Aventura and the surrounding areas, the cost can add up.
If you want convenience for a great price, then you're in the right place. We work with some of the top companies in the world. The first car rental business to be located in an airport, Avis has over seventy years of providing rentals to visitors from all over. With over five-thousand locations all over the world and a diverse fleet of autos, Avis is sure to provide you a great experience from pick-up to drop-off.
How do I get an Aventura Avis car rental at a great rate?
What should I have with me when I get my car rental in Aventura?
Avis's minimum age to rent a car is 21. Some rentals, especially higher category vehicles (luxury, SUVs, etc.), may have an additional fee if you are under 25. Make sure to review Avis's policy to find out if there is an additional cost before you book.
Is there a particular vehicle I should get for my trip to Aventura?
When cruising through Aventura or the rest of the U.S.A., you will need insurance. Avis requires that you show proof of insurance before you pick up your vehicle. Most countries require the driver to have insurance. You might be able to purchase additional insurance through Avis for your trip, if you think your insurance won't cover you while traveling through the U.S. of A. Additionally, as a United States citizen, you can also add on Collision Damage Coverage through CarRentals.com at checkout.
Although many major card issuers, like MasterCard or Visa, give some insurance, there are usually restrictions. For example, they may not cover your rental car if you reserve a luxury or larger vehicle. Make sure to check Avis's policy before you decide.
Avis, like several other rental car companies, requires a deposit when you make your reservation. The amount can vary greatly based on the type of automobile. Furthermore, be sure you have enough on your credit card to make the deposit.
Avis and most other suppliers give you a full to full tank policy. At CarRentals.com, we advise returning the car filled up. To avoid any added expenses, it is best to find a filling station before bringing the car rental to Avis.
Why should I get unlimited miles in Aventura?
Many suppliers will offer unlimited miles, but you want to ensure it's part of the bundle that you are purchasing. It's helpful to know how much you want to drive so you can plan your trip in advance. Although most rental car providers offer unlimited mileage, if it isn't part of your package, you could face additional cost. You may need to get unlimited miles if you're thinking of taking some road trips to discover what else Miami has to offer, or even the United States.
What is there to do around Aventura?
Once you've checked out Aventura, you'll be happy that you have your own car. Not sure where to start your trip? If you have a set of clubs, it may be worthwhile to pack them. Head to Turnberry Isle Resort & Club for day on the greens.
Once you've explored the must-do activities in Miami, having your own car will allow you to see what else Florida offers. When you are ready to explore more of the United States, you can drive wherever you like, without having to coordinate a rideshare or hanging out a stop waiting for the bus.
Before you head out of town, book your Avis Aventura rental car and zip off to take in all the must-do activities at your leisure. Book through CarRentals.com and hit the roads in Miami, Florida.


Dilation and Curettage (D&C): This procedure involves opening the cervix (dilation) and then scraping along the internal surface of the uterus (curettage). This can be performed for the evaluation or treatment of abnormal bleeding or for the surgical management of a miscarriage.
Hysteroscopy: A procedure used to diagnose abnormal bleeding or bleeding after menopause or infertility or to remove fibroids or polyps. A small scope is passed through the cervical opening and then the uterine cavity is filled with gas or fluid so the internal surface of the uterus (endometrial cavity) can be seen. This can be used to identify fibroids or polyps in the uterus and to direct their removal if needed. Hysteroscopy can be done with a D&C.
Hysterectomy: Removal of the uterus. A total hysterectomy also includes removal of the cervix. A subtotal hysterectomy leaves the cervix intact.
Laparoscopy: A small scope is passed into the abdominal cavity and the cavity is then filled with gas so the inside of the abdominal cavity can be seen. This allows the outside surface of the uterus, fallopian tubes, and ovaries to be visualized. Laparoscopy can be used to remove ovarian masses, perform tubal ligation, and evaluate pelvic pain. Some larger surgeries such as hysterectomies can also be performed partially or totally with laparoscopy.
LEEP: A thin wire loop with an electrical current that cuts like a scalpel to remove a piece of the cervix due to abnormal cells.
Salpingectomy: Removal of the fallopian tube. This can be done with laparoscopy or with an abdominal incision (open).
Total abdominal hysterectomy bilateral salpingo-oophorectomy (TAH BSO): Removal of the uterus, cervix, tubes, and ovaries through an abdominal incision.
Total vaginal hysterectomy (TVH): Removal of the uterus and cervix through a vaginal incision.
Pelvic Reconstruction: To resupport vaginal and bladder tissue.
Urinary Incontinence Procedures: Our physicians perform several different types of surgeries to correct urine leakage. The decision to have surgery and to determine what type of surgery must be based on an accurate diagnosis and consideration of all treatment possibilities.
Vulvar Biopsy: A small sample (usually less than 5 millimeters) taken from the external genitalia for evaluation of abnormal color, inflammation, or concern of cancer.


text:
Le mot "cabanassiez" (24 points) est valide au SCRABBLE
Anagrammes du mot cabanassiez
cabanassiez (24 points)
canassiez (20 points) cabanasse (13 points) cabinasse (13 points)
cabaniez (21 points) abaissez (19 points) basaniez (19 points) bassinez (19 points) cabanais (12 points) acensais (10 points) aisances (10 points) basanais (10 points) encaissa (10 points) sesbania (10 points)
cabanez (20 points) cabinez (20 points) baissez (18 points) basanez (18 points) bizness (18 points) cassiez (18 points) naissez (16 points) cabanai (11 points) cabanas (11 points) cabanés (11 points) cabinas (11 points) cabines (11 points) abaissa (9 points) abaisse (9 points) abasies (9 points) acensai (9 points) acensas (9 points) aisance (9 points) basanai (9 points) basanas (9 points) basanés (9 points) bassina (9 points) bassiné (9 points) binasse (9 points) canasse (9 points) canisse (9 points) cassine (9 points) sabines (9 points) assénai (7 points)
baisez (17 points) banzai (17 points) basiez (17 points) bazins (17 points) bissez (17 points) caniez (17 points) casiez (17 points) cassez (17 points) nazcas (17 points) anisez (15 points) nazies (15 points) sanzas (15 points) abacas (10 points) basics (10 points) bissac (10 points) cabana (10 points) cabané (10 points) cabans (10 points) cabina (10 points) cabine (10 points) abasie (8 points) acensa (8 points) anabas (8 points) baines (8 points) baisas (8 points) baisés (8 points) baissa (8 points) baissé (8 points) basais (8 points) basana (8 points) basané (8 points) basies (8 points) basins (8 points) bassin (8 points) caisse (8 points) canais (8 points) casais (8 points) cassai (8 points) cassie (8 points) cassin (8 points) cessai (8 points) sabine (8 points) sabins (8 points) anisas (6 points) anisés (6 points) asanas (6 points) asines (6 points) asséna (6 points) naisse (6 points) niasse (6 points) saines (6 points) sanies (6 points)
basez (16 points) bazin (16 points) binez (16 points) bisez (16 points) canez (16 points) casez (16 points) nazca (16 points) sciez (16 points) zincs (16 points) assez (14 points) nazes (14 points) nazie (14 points) nazis (14 points) sanza (14 points) zains (14 points) zanis (14 points) abaca (9 points) abces (9 points) bancs (9 points) basic (9 points) caban (9 points) cabas (9 points) abies (7 points) acais (7 points) acnes (7 points) asics (7 points) assec (7 points) baies (7 points) baine (7 points) bains (7 points) baisa (7 points) baisé (7 points) basai (7 points) basas (7 points) basés (7 points) basie (7 points) basin (7 points) basis (7 points) bassa (7 points) basse (7 points) béais (7 points) bénis (7 points) besas (7 points) biens (7 points) binas (7 points) binés (7 points) bisas (7 points) bisés (7 points) bissa (7 points) bissé (7 points) canai (7 points) canas (7 points) canes (7 points) casai (7 points) casas (7 points) casés (7 points) cassa (7 points) cassé (7 points) céans (7 points) ceins (7 points) cessa (7 points) cinés (7 points) encas (7 points) incas (7 points) isbas (7 points) nabis (7 points) sabin (7 points) scans (7 points) scias (7 points) sciés (7 points) aînés (5 points) aisés (5 points) anisa (5 points) anisé (5 points) ansés (5 points) asana (5 points) asine (5 points) asins (5 points) assai (5 points) essai (5 points) naias (5 points) nases (5 points) nasse (5 points) saies (5 points) saine (5 points) sains (5 points) sanas (5 points) sanie (5 points) seins (5 points) sensa (5 points) siens (5 points)
binz (15 points) zecs (15 points) zinc (15 points) naze (13 points) nazi (13 points) niez (13 points) zain (13 points) zani (13 points) zens (13 points) bacs (8 points) banc (8 points) becs (8 points) bics (8 points) cabs (8 points) acai (6 points) aces (6 points) acne (6 points) asic (6 points) baes (6 points) baie (6 points) bain (6 points) bais (6 points) bani (6 points) bans (6 points) basa (6 points) basé (6 points) basi (6 points) béai (6 points) béas (6 points) béni (6 points) bens (6 points) bien (6 points) bina (6 points) biné (6 points) bisa (6 points) bisé (6 points) cana (6 points) cané (6 points) casa (6 points) casé (6 points) cens (6 points) ciné (6 points) ibns (6 points) inca (6 points) isba (6 points) nabi (6 points) nacs (6 points) sacs (6 points) scan (6 points) scia (6 points) scié (6 points) secs (6 points) aies (4 points) aîné (4 points) aisé (4 points) anas (4 points) ânes (4 points) anis (4 points) ansé (4 points) ases (4 points) asin (4 points) asse (4 points) issa (4 points) nais (4 points) nase (4 points) nias (4 points) niés (4 points) saie (4 points) sain (4 points) saïs (4 points) sana (4 points) sans (4 points) sein (4 points) sens (4 points) sien (4 points) sise (4 points)
zec (14 points) nez (12 points) zen (12 points) bac (7 points) bec (7 points) bic (7 points) cab (7 points) ace (5 points) bai (5 points) ban (5 points) bas (5 points) béa (5 points) ben (5 points) bis (5 points) cas (5 points) ces (5 points) cis (5 points) ibn (5 points) nac (5 points) nib (5 points) sac (5 points) sec (5 points) sic (5 points) aas (3 points) aie (3 points) aïs (3 points) ana (3 points) âne (3 points) ani (3 points) ans (3 points) asa (3 points) ase (3 points) nés (3 points) nia (3 points) nié (3 points) saï (3 points) sas (3 points) sen (3 points) ses (3 points) sis (3 points)
ba (4 points) be (4 points) bi (4 points) çà (4 points) ce (4 points) ci (4 points) aa (2 points) aï (2 points) an (2 points) as (2 points) en (2 points) ès (2 points) in (2 points) na (2 points) né (2 points) ni (2 points) sa (2 points) se (2 points) si (2 points)
cabanassiez en script json


Can I just say I am over the wind and the cold?! Needless to say it was a blustery morning but not so bad we couldn't take it.
After that was the Burpee Waterfall: I started with 10 Burpees and while I completed those, the PAX did the ab choice I call out. The next person goes and they choose an ab exercise, and so on until everyone completes their 10 burpees.
20 Supermans/20 Fish Swims (I have no idea..I made it up Ha! Stomach position and move your arms and legs like you are swimming.


text:
require "google/cloud/env"
require "google/cloud/errors"
require "google/cloud/bigquery/service"
require "google/cloud/bigquery/credentials"
require "google/cloud/bigquery/dataset"
require "google/cloud/bigquery/job"
require "google/cloud/bigquery/query_data"
require "google/cloud/bigquery/project/list"
require "google/cloud/bigquery/time"

module Google
  module Cloud
    module Bigquery
      ##
      # # Project
      #
      # Projects are top-level containers in Google Cloud Platform. They store
      # information about billing and authorized users, and they contain
      # BigQuery data. Each project has a friendly name and a unique ID.
      #
      # Google::Cloud::Bigquery::Project is the main object for interacting with
      # Google BigQuery. {Google::Cloud::Bigquery::Dataset} objects are created,
      # accessed, and deleted by Google::Cloud::Bigquery::Project.
      #
      # See {Google::Cloud#bigquery}.
      #
      # @attr_reader [String, nil] name The descriptive name of the project.
      #   Can only be present if the project was retrieved with {#projects}.
      # @attr_reader [Integer, nil] numeric_id The numeric ID of the project.
      #   Can only be present if the project was retrieved with {#projects}.
      #
      # @example
      #   require "google/cloud/bigquery"
      #
      #   bigquery = Google::Cloud::Bigquery.new
      #   dataset = bigquery.dataset "my_dataset"
      #   table = dataset.table "my_table"
      #
      class Project
        ##
        # @private The Service object.
        attr_accessor :service

        attr_reader :name, :numeric_id

        ##
        # Creates a new Service instance.
        #
        # See {Google::Cloud.bigquery}
        def initialize service
          @service = service
        end

        ##
        # The BigQuery project connected to.
        #
        # @example
        #   require "google/cloud/bigquery"
        #
        #   bigquery = Google::Cloud::Bigquery.new(
        #     project: "my-project-id",
        #     keyfile: "/path/to/keyfile.json"
        #   )
        #
        #   bigquery.project #=> "my-project-id"
        #
        def project
          service.project
        end

        ##
        # @private Default project.
        def self.default_project
          ENV["BIGQUERY_PROJECT"] ||
            ENV["GOOGLE_CLOUD_PROJECT"] ||
            ENV["GCLOUD_PROJECT"] ||
            Google::Cloud.env.project_id
        end

        ##
        # Queries data using the [asynchronous
        # method](https://cloud.google.com/bigquery/querying-data).
        #
        # When using standard SQL and passing arguments using `params`, Ruby
        # types are mapped to BigQuery types as follows:
        #
        # | BigQuery    | Ruby           | Notes  |
        # |-------------|----------------|---|
        # | `BOOL`      | `true`/`false` | |
        # | `INT64`     | `Integer`      | |
        # | `FLOAT64`   | `Float`        | |
        # | `STRING`    | `STRING`       | |
        # | `DATETIME`  | `DateTime`  | `DATETIME` does not support time zone. |
        # | `DATE`      | `Date`         | |
        # | `TIMESTAMP` | `Time`         | |
        # | `TIME`      | `Google::Cloud::BigQuery::Time` | |
        # | `BYTES`     | `File`, `IO`, `StringIO`, or similar | |
        # | `ARRAY` | `Array` | Nested arrays, `nil` values are not supported. |
        # | `STRUCT`    | `Hash`        | Hash keys may be strings or symbols. |
        #
        # See [Data Types](https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types)
        # for an overview of each BigQuery data type, including allowed values.
        #
        # @param [String] query A query string, following the BigQuery [query
        #   syntax](https://cloud.google.com/bigquery/query-reference), of the
        #   query to execute. Example: "SELECT count(f1) FROM
        #   [myProjectId:myDatasetId.myTableId]".
        # @param [Array, Hash] params Standard SQL only. Used to pass query
        #   arguments when the `query` string contains either positional (`?`)
        #   or named (`@myparam`) query parameters. If value passed is an array
        #   `["foo"]`, the query must use positional query parameters. If value
        #   passed is a hash `{ myparam: "foo" }`, the query must use named
        #   query parameters. When set, `legacy_sql` will automatically be set
        #   to false and `standard_sql` to true.
        # @param [String] priority Specifies a priority for the query. Possible
        #   values include `INTERACTIVE` and `BATCH`. The default value is
        #   `INTERACTIVE`.
        # @param [Boolean] cache Whether to look for the result in the query
        #   cache. The query cache is a best-effort cache that will be flushed
        #   whenever tables in the query are modified. The default value is
        #   true. For more information, see [query
        #   caching](https://developers.google.com/bigquery/querying-data).
        # @param [Table] table The destination table where the query results
        #   should be stored. If not present, a new table will be created to
        #   store the results.
        # @param [String] create Specifies whether the job is allowed to create
        #   new tables. The default value is `needed`.
        #
        #   The following values are supported:
        #
        #   * `needed` - Create the table if it does not exist.
        #   * `never` - The table must already exist. A 'notFound' error is
        #     raised if the table does not exist.
        # @param [String] write Specifies the action that occurs if the
        #   destination table already exists. The default value is `empty`.
        #
        #   The following values are supported:
        #
        #   * `truncate` - BigQuery overwrites the table data.
        #   * `append` - BigQuery appends the data to the table.
        #   * `empty` - A 'duplicate' error is returned in the job result if the
        #     table exists and contains data.
        # @param [Dataset, String] dataset The default dataset to use for
        #   unqualified table names in the query. Optional.
        # @param [Boolean] large_results If `true`, allows the query to produce
        #   arbitrarily large result tables at a slight cost in performance.
        #   Requires `table` parameter to be set.
        # @param [Boolean] standard_sql Specifies whether to use BigQuery's
        #   [standard
        #   SQL](https://cloud.google.com/bigquery/docs/reference/standard-sql/)
        #   dialect for this query. If set to true, the query will use standard
        #   SQL rather than the [legacy
        #   SQL](https://cloud.google.com/bigquery/docs/reference/legacy-sql)
        #   dialect. Optional. The default value is true.
        # @param [Boolean] legacy_sql Specifies whether to use BigQuery's
        #   [legacy
        #   SQL](https://cloud.google.com/bigquery/docs/reference/legacy-sql)
        #   dialect for this query. If set to false, the query will use
        #   BigQuery's [standard
        #   SQL](https://cloud.google.com/bigquery/docs/reference/standard-sql/)
        #   dialect. Optional. The default value is false.
        # @param [Boolean] large_results This option is specific to Legacy SQL.
        #   If `true`, allows the query to produce arbitrarily large result
        #   tables at a slight cost in performance. Requires `table` parameter
        #   to be set.
        # @param [Boolean] flatten This option is specific to Legacy SQL.
        #   Flattens all nested and repeated fields in the query results. The
        #   default value is `true`. `large_results` parameter must be `true` if
        #   this is set to `false`.
        # @param [Integer] maximum_billing_tier Limits the billing tier for this
        #   job. Queries that have resource usage beyond this tier will fail
        #   (without incurring a charge). Optional. If unspecified, this will be
        #   set to your project default. For more information, see [High-Compute
        #   queries](https://cloud.google.com/bigquery/pricing#high-compute).
        # @param [Integer] maximum_bytes_billed Limits the bytes billed for this
        #   job. Queries that will have bytes billed beyond this limit will fail
        #   (without incurring a charge). Optional. If unspecified, this will be
        #   set to your project default.
        #
        # @return [Google::Cloud::Bigquery::QueryJob]
        #
        # @example Query using standard SQL:
        #   require "google/cloud/bigquery"
        #
        #   bigquery = Google::Cloud::Bigquery.new
        #
        #   job = bigquery.query_job "SELECT name FROM " \
        #                            "`my_project.my_dataset.my_table`"
        #
        #   job.wait_until_done!
        #   if !job.failed?
        #     job.query_results.each do |row|
        #       puts row[:name]
        #     end
        #   end
        #
        # @example Query using legacy SQL:
        #   require "google/cloud/bigquery"
        #
        #   bigquery = Google::Cloud::Bigquery.new
        #
        #   job = bigquery.query_job "SELECT name FROM " \
        #                            "[my_project:my_dataset.my_table]",
        #                            legacy_sql: true
        #
        #   job.wait_until_done!
        #   if !job.failed?
        #     job.query_results.each do |row|
        #       puts row[:name]
        #     end
        #   end
        #
        # @example Query using positional query parameters:
        #   require "google/cloud/bigquery"
        #
        #   bigquery = Google::Cloud::Bigquery.new
        #
        #   job = bigquery.query_job "SELECT name FROM " \
        #                            "`my_dataset.my_table`" \
        #                            " WHERE id = ?",
        #                            params: [1]
        #
        #   job.wait_until_done!
        #   if !job.failed?
        #     job.query_results.each do |row|
        #       puts row[:name]
        #     end
        #   end
        #
        # @example Query using named query parameters:
        #   require "google/cloud/bigquery"
        #
        #   bigquery = Google::Cloud::Bigquery.new
        #
        #   job = bigquery.query_job "SELECT name FROM " \
        #                            "`my_dataset.my_table`" \
        #                            " WHERE id = @id",
        #                            params: { id: 1 }
        #
        #   job.wait_until_done!
        #   if !job.failed?
        #     job.query_results.each do |row|
        #       puts row[:name]
        #     end
        #   end
        #
        def query_job query, params: nil, priority: "INTERACTIVE", cache: true,
                      table: nil, create: nil, write: nil, dataset: nil,
                      standard_sql: nil, legacy_sql: nil, large_results: nil,
                      flatten: nil, maximum_billing_tier: nil,
                      maximum_bytes_billed: nil
          ensure_service!
          options = { priority: priority, cache: cache, table: table,
                      create: create, write: write,
                      large_results: large_results, flatten: flatten,
                      dataset: dataset, legacy_sql: legacy_sql,
                      standard_sql: standard_sql,
                      maximum_billing_tier: maximum_billing_tier,
                      maximum_bytes_billed: maximum_bytes_billed,
                      params: params }
          gapi = service.query_job query, options
          Job.from_gapi gapi, service
        end

        ##
        # Queries data using the [synchronous
        # method](https://cloud.google.com/bigquery/querying-data).
        #
        # When using standard SQL and passing arguments using `params`, Ruby
        # types are mapped to BigQuery types as follows:
        #
        # | BigQuery    | Ruby           | Notes  |
        # |-------------|----------------|---|
        # | `BOOL`      | `true`/`false` | |
        # | `INT64`     | `Integer`      | |
        # | `FLOAT64`   | `Float`        | |
        # | `STRING`    | `STRING`       | |
        # | `DATETIME`  | `DateTime`  | `DATETIME` does not support time zone. |
        # | `DATE`      | `Date`         | |
        # | `TIMESTAMP` | `Time`         | |
        # | `TIME`      | `Google::Cloud::BigQuery::Time` | |
        # | `BYTES`     | `File`, `IO`, `StringIO`, or similar | |
        # | `ARRAY` | `Array` | Nested arrays, `nil` values are not supported. |
        # | `STRUCT`    | `Hash`        | Hash keys may be strings or symbols. |
        #
        # See [Data Types](https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types)
        # for an overview of each BigQuery data type, including allowed values.
        #
        # @param [String] query A query string, following the BigQuery [query
        #   syntax](https://cloud.google.com/bigquery/query-reference), of the
        #   query to execute. Example: "SELECT count(f1) FROM
        #   [myProjectId:myDatasetId.myTableId]".
        # @param [Array, Hash] params Standard SQL only. Used to pass query
        #   arguments when the `query` string contains either positional (`?`)
        #   or named (`@myparam`) query parameters. If value passed is an array
        #   `["foo"]`, the query must use positional query parameters. If value
        #   passed is a hash `{ myparam: "foo" }`, the query must use named
        #   query parameters. When set, `legacy_sql` will automatically be set
        #   to false and `standard_sql` to true.
        # @param [Integer] max The maximum number of rows of data to return per
        #   page of results. Setting this flag to a small value such as 1000 and
        #   then paging through results might improve reliability when the query
        #   result set is large. In addition to this limit, responses are also
        #   limited to 10 MB. By default, there is no maximum row count, and
        #   only the byte limit applies.
        # @param [Integer] timeout How long to wait for the query to complete,
        #   in milliseconds, before the request times out and returns. Note that
        #   this is only a timeout for the request, not the query. If the query
        #   takes longer to run than the timeout value, the call returns without
        #   any results and with QueryData#complete? set to false. The default
        #   value is 10000 milliseconds (10 seconds).
        # @param [Boolean] dryrun If set to `true`, BigQuery doesn't run the
        #   job. Instead, if the query is valid, BigQuery returns statistics
        #   about the job such as how many bytes would be processed. If the
        #   query is invalid, an error returns. The default value is `false`.
        # @param [Boolean] cache Whether to look for the result in the query
        #   cache. The query cache is a best-effort cache that will be flushed
        #   whenever tables in the query are modified. The default value is
        #   true. For more information, see [query
        #   caching](https://developers.google.com/bigquery/querying-data).
        # @param [String] dataset Specifies the default datasetId and projectId
        #   to assume for any unqualified table names in the query. If not set,
        #   all table names in the query string must be qualified in the format
        #   'datasetId.tableId'.
        # @param [String] project Specifies the default projectId to assume for
        #   any unqualified table names in the query. Only used if `dataset`
        #   option is set.
        # @param [Boolean] standard_sql Specifies whether to use BigQuery's
        #   [standard
        #   SQL](https://cloud.google.com/bigquery/docs/reference/standard-sql/)
        #   dialect for this query. If set to true, the query will use standard
        #   SQL rather than the [legacy
        #   SQL](https://cloud.google.com/bigquery/docs/reference/legacy-sql)
        #   dialect. When set to true, the values of `large_results` and
        #   `flatten` are ignored; the query will be run as if `large_results`
        #   is true and `flatten` is false. Optional. The default value is
        #   true.
        # @param [Boolean] legacy_sql Specifies whether to use BigQuery's
        #   [legacy
        #   SQL](https://cloud.google.com/bigquery/docs/reference/legacy-sql)
        #   dialect for this query. If set to false, the query will use
        #   BigQuery's [standard
        #   SQL](https://cloud.google.com/bigquery/docs/reference/standard-sql/)
        #   When set to false, the values of `large_results` and `flatten` are
        #   ignored; the query will be run as if `large_results` is true and
        #   `flatten` is false. Optional. The default value is false.
        #
        # @return [Google::Cloud::Bigquery::QueryData]
        #
        # @example Query using standard SQL:
        #   require "google/cloud/bigquery"
        #
        #   bigquery = Google::Cloud::Bigquery.new
        #
        #   sql = "SELECT name FROM `my_project.my_dataset.my_table`"
        #   data = bigquery.query sql
        #
        #   data.each do |row|
        #     puts row[:name]
        #   end
        #
        # @example Query using legacy SQL:
        #   require "google/cloud/bigquery"
        #
        #   bigquery = Google::Cloud::Bigquery.new
        #
        #   sql = "SELECT name FROM [my_project:my_dataset.my_table]"
        #   data = bigquery.query sql, legacy_sql: true
        #
        #   data.each do |row|
        #     puts row[:name]
        #   end
        #
        # @example Retrieve all rows: (See {QueryData#all})
        #   require "google/cloud/bigquery"
        #
        #   bigquery = Google::Cloud::Bigquery.new
        #
        #   data = bigquery.query "SELECT name FROM `my_dataset.my_table`"
        #
        #   data.all do |row|
        #     puts row[:name]
        #   end
        #
        # @example Query using positional query parameters:
        #   require "google/cloud/bigquery"
        #
        #   bigquery = Google::Cloud::Bigquery.new
        #
        #   data = bigquery.query "SELECT name " \
        #                         "FROM `my_dataset.my_table`" \
        #                         "WHERE id = ?",
        #                         params: [1]
        #
        #   data.each do |row|
        #     puts row[:name]
        #   end
        #
        # @example Query using named query parameters:
        #   require "google/cloud/bigquery"
        #
        #   bigquery = Google::Cloud::Bigquery.new
        #
        #   data = bigquery.query "SELECT name " \
        #                         "FROM `my_dataset.my_table`" \
        #                         "WHERE id = @id",
        #                         params: { id: 1 }
        #
        #   data.each do |row|
        #     puts row[:name]
        #   end
        #
        def query query, params: nil, max: nil, timeout: 10000, dryrun: nil,
                  cache: true, dataset: nil, project: nil, standard_sql: nil,
                  legacy_sql: nil
          ensure_service!
          options = { max: max, timeout: timeout, dryrun: dryrun, cache: cache,
                      dataset: dataset, project: project,
                      legacy_sql: legacy_sql, standard_sql: standard_sql,
                      params: params }
          gapi = service.query query, options
          QueryData.from_gapi gapi, service
        end

        ##
        # Retrieves an existing dataset by ID.
        #
        # @param [String] dataset_id The ID of a dataset.
        #
        # @return [Google::Cloud::Bigquery::Dataset, nil] Returns `nil` if the
        #   dataset does not exist.
        #
        # @example
        #   require "google/cloud/bigquery"
        #
        #   bigquery = Google::Cloud::Bigquery.new
        #
        #   dataset = bigquery.dataset "my_dataset"
        #   puts dataset.name
        #
        def dataset dataset_id
          ensure_service!
          gapi = service.get_dataset dataset_id
          Dataset.from_gapi gapi, service
        rescue Google::Cloud::NotFoundError
          nil
        end

        ##
        # Creates a new dataset.
        #
        # @param [String] dataset_id A unique ID for this dataset, without the
        #   project name. The ID must contain only letters (a-z, A-Z), numbers
        #   (0-9), or underscores (_). The maximum length is 1,024 characters.
        # @param [String] name A descriptive name for the dataset.
        # @param [String] description A user-friendly description of the
        #   dataset.
        # @param [Integer] expiration The default lifetime of all tables in the
        #   dataset, in milliseconds. The minimum value is 3600000 milliseconds
        #   (one hour).
        # @param [String] location The geographic location where the dataset
        #   should reside. Possible values include `EU` and `US`. The default
        #   value is `US`.
        # @yield [access] a block for setting rules
        # @yieldparam [Google::Cloud::Bigquery::Dataset] access the object
        #   accepting rules
        #
        # @return [Google::Cloud::Bigquery::Dataset]
        #
        # @example
        #   require "google/cloud/bigquery"
        #
        #   bigquery = Google::Cloud::Bigquery.new
        #
        #   dataset = bigquery.create_dataset "my_dataset"
        #
        # @example A name and description can be provided:
        #   require "google/cloud/bigquery"
        #
        #   bigquery = Google::Cloud::Bigquery.new
        #
        #   dataset = bigquery.create_dataset "my_dataset",
        #                                     name: "My Dataset",
        #                                     description: "This is my Dataset"
        #
        # @example Or, configure access with a block: (See {Dataset::Access})
        #   require "google/cloud/bigquery"
        #
        #   bigquery = Google::Cloud::Bigquery.new
        #
        #   dataset = bigquery.create_dataset "my_dataset" do |dataset|
        #     dataset.access.add_writer_user "writers@example.com"
        #   end
        #
        def create_dataset dataset_id, name: nil, description: nil,
                           expiration: nil, location: nil
          ensure_service!

          new_ds = Google::Apis::BigqueryV2::Dataset.new(
            dataset_reference: Google::Apis::BigqueryV2::DatasetReference.new(
              project_id: project, dataset_id: dataset_id))

          # Can set location only on creation, no Dataset#location method
          new_ds.update! location: location unless location.nil?

          updater = Dataset::Updater.new(new_ds).tap do |b|
            b.name = name unless name.nil?
            b.description = description unless description.nil?
            b.default_expiration = expiration unless expiration.nil?
          end

          if block_given?
            yield updater
            updater.check_for_mutated_access!
          end

          gapi = service.insert_dataset new_ds
          Dataset.from_gapi gapi, service
        end

        ##
        # Retrieves the list of datasets belonging to the project.
        #
        # @param [Boolean] all Whether to list all datasets, including hidden
        #   ones. The default is `false`.
        # @param [String] token A previously-returned page token representing
        #   part of the larger set of results to view.
        # @param [Integer] max Maximum number of datasets to return.
        #
        # @return [Array<Google::Cloud::Bigquery::Dataset>] (See
        #   {Google::Cloud::Bigquery::Dataset::List})
        #
        # @example
        #   require "google/cloud/bigquery"
        #
        #   bigquery = Google::Cloud::Bigquery.new
        #
        #   datasets = bigquery.datasets
        #   datasets.each do |dataset|
        #     puts dataset.name
        #   end
        #
        # @example Retrieve hidden datasets with the `all` optional arg:
        #   require "google/cloud/bigquery"
        #
        #   bigquery = Google::Cloud::Bigquery.new
        #
        #   all_datasets = bigquery.datasets all: true
        #
        # @example Retrieve all datasets: (See {Dataset::List#all})
        #   require "google/cloud/bigquery"
        #
        #   bigquery = Google::Cloud::Bigquery.new
        #
        #   datasets = bigquery.datasets
        #   datasets.all do |dataset|
        #     puts dataset.name
        #   end
        #
        def datasets all: nil, token: nil, max: nil
          ensure_service!
          options = { all: all, token: token, max: max }
          gapi = service.list_datasets options
          Dataset::List.from_gapi gapi, service, all, max
        end

        ##
        # Retrieves an existing job by ID.
        #
        # @param [String] job_id The ID of a job.
        #
        # @return [Google::Cloud::Bigquery::Job, nil] Returns `nil` if the job
        #   does not exist.
        #
        # @example
        #   require "google/cloud/bigquery"
        #
        #   bigquery = Google::Cloud::Bigquery.new
        #
        #   job = bigquery.job "my_job"
        #
        def job job_id
          ensure_service!
          gapi = service.get_job job_id
          Job.from_gapi gapi, service
        rescue Google::Cloud::NotFoundError
          nil
        end

        ##
        # Retrieves the list of jobs belonging to the project.
        #
        # @param [Boolean] all Whether to display jobs owned by all users in the
        #   project. The default is `false`.
        # @param [String] token A previously-returned page token representing
        #   part of the larger set of results to view.
        # @param [Integer] max Maximum number of jobs to return.
        # @param [String] filter A filter for job state.
        #
        #   Acceptable values are:
        #
        #   * `done` - Finished jobs
        #   * `pending` - Pending jobs
        #   * `running` - Running jobs
        #
        # @return [Array<Google::Cloud::Bigquery::Job>] (See
        #   {Google::Cloud::Bigquery::Job::List})
        #
        # @example
        #   require "google/cloud/bigquery"
        #
        #   bigquery = Google::Cloud::Bigquery.new
        #
        #   jobs = bigquery.jobs
        #   jobs.each do |job|
        #     # process job
        #   end
        #
        # @example Retrieve only running jobs using the `filter` optional arg:
        #   require "google/cloud/bigquery"
        #
        #   bigquery = Google::Cloud::Bigquery.new
        #
        #   running_jobs = bigquery.jobs filter: "running"
        #   running_jobs.each do |job|
        #     # process job
        #   end
        #
        # @example Retrieve all jobs: (See {Job::List#all})
        #   require "google/cloud/bigquery"
        #
        #   bigquery = Google::Cloud::Bigquery.new
        #
        #   jobs = bigquery.jobs
        #   jobs.all do |job|
        #     # process job
        #   end
        #
        def jobs all: nil, token: nil, max: nil, filter: nil
          ensure_service!
          options = { all: all, token: token, max: max, filter: filter }
          gapi = service.list_jobs options
          Job::List.from_gapi gapi, service, all, max, filter
        end

        ##
        # Retrieves the list of all projects for which the currently authorized
        # account has been granted any project role. The returned project
        # instances share the same credentials as the project used to retrieve
        # them, but lazily create a new API connection for interactions with the
        # BigQuery service.
        #
        # @param [String] token A previously-returned page token representing
        #   part of the larger set of results to view.
        # @param [Integer] max Maximum number of projects to return.
        #
        # @return [Array<Google::Cloud::Bigquery::Project>] (See
        #   {Google::Cloud::Bigquery::Project::List})
        #
        # @example
        #   require "google/cloud/bigquery"
        #
        #   bigquery = Google::Cloud::Bigquery.new
        #
        #   projects = bigquery.projects
        #   projects.each do |project|
        #     puts project.name
        #     project.datasets.all.each do |dataset|
        #       puts dataset.name
        #     end
        #   end
        #
        # @example Retrieve all projects: (See {Project::List#all})
        #   require "google/cloud/bigquery"
        #
        #   bigquery = Google::Cloud::Bigquery.new
        #
        #   projects = bigquery.projects
        #
        #   projects.all do |project|
        #     puts project.name
        #     project.datasets.all.each do |dataset|
        #       puts dataset.name
        #     end
        #   end
        #
        def projects token: nil, max: nil
          ensure_service!
          options = { token: token, max: max }
          gapi = service.list_projects options
          Project::List.from_gapi gapi, service, max
        end

        ##
        # Creates a Bigquery::Time object to represent a time, independent of a
        # specific date.
        #
        # @param [Integer] hour Hour, valid values from 0 to 23.
        # @param [Integer] minute Minute, valid values from 0 to 59.
        # @param [Integer, Float] second Second, valid values from 0 to 59. Can
        #   contain microsecond precision.
        #
        # @return [Bigquery::Time]
        #
        # @example
        #   require "google/cloud/bigquery"
        #
        #   bigquery = Google::Cloud::Bigquery.new
        #
        #   fourpm = bigquery.time 16, 0, 0
        #   data = bigquery.query "SELECT name " \
        #                         "FROM `my_dataset.my_table`" \
        #                         "WHERE time_of_date = @time",
        #                         params: { time: fourpm }
        #
        #   data.each do |row|
        #     puts row[:name]
        #   end
        #
        # @example Create Time with fractional seconds:
        #   require "google/cloud/bigquery"
        #
        #   bigquery = Google::Cloud::Bigquery.new
        #
        #   precise_time = bigquery.time 16, 35, 15.376541
        #   data = bigquery.query "SELECT name " \
        #                         "FROM `my_dataset.my_table`" \
        #                         "WHERE time_of_date >= @time",
        #                         params: { time: precise_time }
        #
        #   data.each do |row|
        #     puts row[:name]
        #   end
        #
        def time hour, minute, second
          Bigquery::Time.new "#{hour}:#{minute}:#{second}"
        end

        ##
        # @private New Project from a Google API Client object, using the
        # same Credentials as this project.
        def self.from_gapi gapi, service
          project_service = Service.new gapi.project_reference.project_id,
                                        service.credentials,
                                        retries: service.retries,
                                        timeout: service.timeout
          new(project_service).tap do |p|
            p.instance_variable_set :@name, gapi.friendly_name

            # TODO: remove `Integer` and set normally after migrating to Gax or
            # to google-api-client 0.10 (See google/google-api-ruby-client#439)
            if gapi.numeric_id
              p.instance_variable_set :@numeric_id, Integer(gapi.numeric_id)
            end
          end
        end

        protected

        ##
        # Raise an error unless an active service is available.
        def ensure_service!
          fail "Must have active connection" unless service
        end
      end
    end
  end
end


text:
Nutanix ropes in senior AWS exec to head India operations
Photo Credit: Photo Credit: 123RF.com
Tanmay Tiwary	19 Jun, 2019
Cloud computing software specialist Nutanix has appointed Anantharaman Balakrishnan as its new vice president and managing director of sales in India.
Balakrishnan joins from cloud computing giant Amazon Web Services (AWS), where he was the head of the financial services and manufacturing verticals for the large enterprise business in India.
US-headquartered Nutanix said that Balakrishnan's knowledge and insight of the market, enterprise landscape and personalities, as well as a track record for rapidly growing business make him ideally placed to redefine the company's business in India and drive the enterprise cloud firm's efforts as it expands its focus to India's larger enterprises.
"We are all delighted to have Bala add his focus, structure, and direction to our cutting-edge solutions here in India," said Neville Vincent, vice president, South Asia Pacific at Nutanix.
Nutanix further said that hyperconverged infrastructure (HCI) and hybrid cloud will be key to keeping the country's enterprises relevant and competitive in the digital era.
"The battle lines are being drawn as public and private clouds converge. True success will lie with the companies that can drive innovation and value for their customers," said Balakrishnan, whose 25 years of managerial experience in the IT industry includes eight years at Dell EMC
In an interview with TechCircle last month, Vincent had spoken about the significance of hyperconverged infrastructure.
HCI is a type of software-defined data centre architecture that virtualises the elements of traditional "hardware-defined" systems. Its single-system approach offers more flexibility as compared to legacy systems.
Also in May, the company had announced a suite of offerings in the public and private cloud.
Nutanix AWS Anantharaman Balakrishnan Neville Vincent HCI cloud computing cloud software Hybrid cloud
Inside the SonyLiv app transformation journey


There's no denying it, for those of us living in the Northern Hemisphere, summer is well and truly underway. For us Speedhunters the summer brings lots of excitement, and with it, plenty of work. While most people are on vacation living the easy life our schedule becomes more crammed than ever which means back-to-back weekend events for months on end.
Over the years as an automotive journalist I've become accustomed to this insane schedule which begins with the Formula D kickoff in April and ends sometime in November just after SEMA. It's a distorted concept of summer, but it's the only one I know. No matter how used to it I think I am, there are always those times when the going gets extra weird.
No more than a day after returning to LA, haphazardly unpacking my things from my euro trip and hastily nursing a newly acquired cold, I was back on yet another airplane headed for another racing circuit. Before I knew it I was standing in the dark in the paddock of Mid Ohio, seemingly starring in a strange Speedhunting themed episode of the Twilight Zone.
Exactly one week prior I was at Spa, running through what was essentially exactly the same schedule, only halfway around the globe. Just like it did in Belgium, my weekend at Ohio actually began on a Thursday and the first order of business was a photoshoot on the track.
Despite not really knowing where or who I was, I think the shoot went quite well and you'll have to keep your eyes peeled for the feature coming soon. The call time was 5AM and fortunately for me, my mind, and more importantly, body, was still set to European time; so getting up for the shoot wasn't a problem.
No it would be staying awake that would prove the challenge. Try as I might there was little that my now-sore-throat-and-dizzy-sickened-body could do to fight off the jet lag, so I gave in and retired to the hotel to catch up on some rest. The next day I woke up around 4AM, like clockwork, and finished another story before heading the track where I found the team working on the car.
When I first walked out of the hotel the sun was hanging low in the sky and I froze and stood still for a moment while my mind tried to reason with a sense of time and place. I spent nearly a minute trying to decide whether it was dusk or dawn, a sure fire sign that I really "am the Speedhunter." Fortunately the time was 9:30AM and I was in good shape to witness qualifying.
Coming into this event there was a lot to be excited about. For Falken this would be a homecoming of sorts as it was at this very event one year ago where the team scored their first victory in the American Le Mans Series. For me it would be the return to the very first circuit I ever visited, which in turn sparked my interest in motorsport, some twenty odd years ago.
Not surprisingly the circuit didn't very much resemble the minor tidbits stored away in the depths of my brain. What I quickly learned was that while this course may seem short and simple on paper, it's actually extremely demanding and complex. The twistier bits are anything but straight forward and a fast lap here requires a calm head and smooth inputs.
The undulating course is daunting and seemingly easy to overdrive, not to mention very taxing on tires. When you take into consideration the disgusting combination of heat and humidity it seems that having a race car that handles properly is a non-possibility. At the end of the fifteen minute qualifying session the top eight cars in GT were separated by less than a second, unfortunately for Falken they were relegated to the ninth position on the grid and nearly two seconds off pole.
I returned to the paddock after the qualifying session to a very busy Falken pit bustling with fans. As luck would have it I had gotten back just in time for one of the ALMS' "tech talks". One of my favorite things about the ALMS is how they engage their fans and make them a very real part of the race weekend.
For tech talks race fans are encouraged to come to team's pit, this time Falken's, and ask virtually any question they can think of to be answered by the team. Here we see Kevin Jones answering one fan's question about how the team would adjust in the event of rain.
Stickers, of course! While it sounds funny to say, in racing stickers really are serious business. Since much of the race can and will be broadcast from on board the cars, it's important for teams to have branding in places that can be picked up by the cameras and absorbed into the subconscious of the viewers.
Even the smallest sticker can be considered prime real estate when it comes to television. Alex is carefully placing two decals, Falken and Porsche, for the rearward facing camera pod sticking through the roof.
The next morning I was back at the track bright and early for a mandatory photography meeting and before my body had time to wake up, cars were cuing for the warm up session. With the early morning sun beating down on the ground I made my way to the circuit where could hear the cars firing up in the distance. Before long they appeared.
To my surprise it seemed as though some of the minor changes from the day before had taken affect on the car. Moving through the trickier sections of the track, the car appeared to be very stable and quick compared to previous sessions. When I returned after the session I found out that the car seemed to have found its legs and was now within the coveted one second bracket.
While the team ran though last minute check lists the drivers were busy meeting and greeting with the fans. I always joke that this must be the hardest part of the weekend for the drivers, as it would be quite obnoxious to me, but Wolf and Bryan never seem to mind!
It never ceases to amaze me how popular Falken is in the paddock, particularly for a team of their size. Relatively speaking Falken is essentially a privateer in the scope of professional racing, which might seem strange to those that know them to be the big dogs in the drift scene. While they might not have the largest budget or team, they certainly do have one of the largest lines outside their hauler!
Just after what would have been lunch time, if Speedhunters had time to waste partake in such things, the GT cars were pulled into the pit lane for a few final adjustments prior to the race.
In addition to topping up on fuel, the boys removed the taxi-way wheel and tire combination and replaced it with race rubber and the car was ready to go.
Before the start of the race it is customary for all the cars to be pulled onto the grid in their respective qualifying positions. Many times, particularly with larger races, the grid is then opened up to the fans to come and inspect the cars up close.
At this point it was getting really hot and muggy out and I was seriously beginning to wonder if I could last until the end of the race. The look on Bryan's face is one of a man in misery, although I'm sure he'd never admit it. I feel so bad for the drivers at this stage, I could barely stay conscious outside in a tee-shirt – I can only imagine how agonizing it must be sitting in a hot race car all suited up with a balaclava and helmet on to boot!
Fortunately there are usually some kind words from colleges to help power through it. Here Porsche Factory works driver Marco Holzer sneaks in to wish Sellers some good luck.
In fact even our own Tommy Milner stopped by to say hello. Hi Tommy!
With sweat thoroughly soaking my entire body I made one last photograph of the team all lined up and trudged off to shoot the start of the race.
Here's what the last corner looked like on the first lap; a complete freight train, the likes of which have become synonymous with the ALMS GT class. As you can see Bryan was stuck in the thick of it with his work cut out for him on a track that is very difficult to execute passes on.
Although not the fastest car on the track, the number seventeen certainly was consistent and Sellers was doing a great job of keeping the car in one piece. By saving the tires and staying out of other people's accidents the car soon found itself moving forward in position.
And that's exactly how Bryan would spend the next hour, meticulously sawing his way through the field. By the time he handed the car over to Wolf on lap twenty six the car had found itself all the way up into the fourth spot. With fresh tires and a Porsche Factory driver in the car the outlook on the weekend was quite good.
When the car rejoined the field under yellow, Wolf came back out in seventh place and wasted no time pushing back towards the front. Fighting hard during his stint Henzler would overtake two cars putting Falken into fifth place before handing the car back over to Sellers for the home stretch.
With a cool head Bryan was able to bring the car home unscathed and managed to pass another car on the way to the checkered flag, narrowly missing out on a podium by just less than a second. Although it wasn't the repeat victory they had hoped for, it was a good display of teamwork with the pit crew credited for the finishing position.
And like that, just as quickly as it began, my weekend was over. As I watched the car being loaded onto the vehicle hauler I couldn't help but think "haven't I done this before", in a strange pseudo groundhog day way. Whether this weekend actually happened or is just a figment of my imagination I can't really be sure, but I do know it won't be the last. See you guys at Road Atlanta!
Will there be anyone covering the September race at VIR?
y'all are planning some more coverage on the new viper, yes? i see it lurking in one of the photos there.
As always, great coverage! That's the best team to follow!
No fan walk was a let down :(. It's awesome to see the little local track I've been going to for 10+ years on SpeedHunters.
Sean, since you've seen them both in person, which is wider and more 'aggressive' looking.... RWB cars or the Falken RSR?
@EricSeanDelaney To be honest considering how tight the schedule was due to all the other series also running during the weekend, it makes complete sense that there wasn't a fan walk. You need at least an hour just to let everyone in and get them back off the grid prior to the start of the race, and that isn't even taking rubber necking and photo taking into account.
@twincamRob That's a tough question to answer... They're both absurdly wide and aggressive, but if I had to differentiate I'd say the RSR appears more purpose built and therefore isn't quite as "scary" as the RWB, if that makes any sense. The RWB just looks like a crazy street sweeper. I like them both, but they're really hard to compare.
Yea that's what I figured, the IRL top 6 took forever it seemed. And those stickers went to good use!
Glad to hear it! Take some pictures and tag them in instagram!
@sean klingelhoefer Yea Yea I guess haha.
yes, but more? i <3 pictures and to me the new viper is worthy of more picture love.
That's all we have planned at the moment. The guys from Riley Technologies weren't too excited about me taking pictures of their cars.
@sean klingelhoefer Will you be covering Petit Le mans this year?
@JohnPhillips2 If everything goes according to plan, yes I will.
@NolanBjorn sorry you missed it! No idea about plans for next year at this point, but I'd love to go back.
Speedhunters has changed alot, I kind of miss "the old" Speedhunters. It was much more exciting, starting of with a little longer text and then just one row of text commenting/discussing the car/photo under each photo. I liked Speedhunters because of that but dont take me wrong, I still love the work you guys put in.


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