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J Sainsbury plc
Third Quarter Trading Statement for the 15 weeks to 7 January 2017
The announcement released by J Sainsbury plc entitled "Third Quarter Trading Statement for the 15 weeks to 7 January 2017" on 11 January 2017 at 7.00am incorrectly stated in Note 2 Sainsbury's Total Retail Sales (excluding the impact of the sale of Pharmacy business) including and excluding fuel. All other figures remain unchanged. The corrected figures are set out in Note 2 in the reissued announcement below:
Good Christmas performance as customers choose Sainsbury's for quality, choice and value
· Sainsbury's: Total Retail sales1 up 0.8 per cent (excl. fuel) and like-for-like Retail sales up 0.1 per cent (excl. fuel), with total volumes up and like-for-like volumes flat
· Argos: Total sales up 4.1 per cent and like-for-like sales up 4.0 per cent
· Combined Sainsbury's and Argos like-for-like sales up 1.0 per cent (excl. fuel)
Mike Coupe, Group Chief Executive, said: "Sainsbury's offered customers greater quality food, choice and value than ever before, across all channels. We had a record Christmas week, with over 30 million customer transactions at Sainsbury's and over £1 billion of sales across the Group. Thanks to the commitment of all our colleagues, we delivered an excellent shopping experience and helped our customers live well for less over the festive period.
"Our Groceries Online and Convenience channels performed well, achieving over nine and six per cent sales growth respectively and at Argos we saw record levels of online participation. Online sales made up 18 per cent of total Group sales in the quarter.
"Clothing and General Merchandise also had a very strong quarter, with Clothing sales up ten per cent and General Merchandise up three per cent.
"At Argos we delivered strong growth in the quarter, driven by the key Black Friday and Christmas trading periods. Our Argos digital stores in Sainsbury's supermarkets are performing well, as awareness of the convenience of shopping at both Sainsbury's and Argos under one roof grows among our customers.
"The market remains very competitive and the impact of the devaluation of sterling remains uncertain. However, we are well placed to navigate the external environment and remain focused on delivering our strategy."
Strategic and operational highlights
Our vision is to be the most trusted retailer where people love to work and shop. We are focused on delivering the five pillars of our strategy:
We know our customers better than anyone else
· Sainsbury's has removed the vast majority of multi-buy promotions and continues to implement its simpler pricing and promotional strategy
· Sainsbury's achieved like-for-like transaction growth across all channels, total volumes up and like-for-like volumes flat
Great products and services at fair prices
· We remain focused on offering both quality and value:
o This year customers paid 14 per cent less for a typical Christmas basket at Sainsbury's than they did two years ago2
o 25 per cent of Sainsbury's brand food was new or improved this year compared to two years ago, including our Taste the Difference party food range, where sales increased by 50 per cent year-on-year
o Our Blanc de Blanc Brut NV champagne and our Taste the Difference 18-month aged Cognac-laced Christmas puddings were both named Which? Best Buys this year
o Our turkeys were the best value on the market by 39 pence per kilo3; volumes were up over 30 per cent year-on- year across the range
· Sainsbury's Clothing sales grew by ten per cent and General Merchandise grew by three per cent
· Argos delivered strong sales growth in technology categories (wearable tech, mobile phones, computers, TV and audio), toys, sports and gifts
· Sainsbury's Bank performed well, with credit card new business more than doubling year-on-year, driven by an extended range of market leading products
There for our customers
· Argos had a strong online performance over the key Black Friday period, with 65 per cent of sales taken online and a quarter of a million Fast Track deliveries over that weekend. Over the third quarter, online sales grew by 13 per cent, accounting for 57 per cent of Argos sales
· There are now 30 Argos digital stores and three Habitat stores in Sainsbury's supermarkets and over 200 digital in-store collection points where customers can collect their Tu clothing, eBay purchases and DPD parcels
· Groceries Online achieved sales growth of over nine per cent and orders grew by 13 per cent. With a strong operational performance, the business had a record week in the quarter, delivering over 300,000 online orders
· Sainsbury's Convenience business grew six per cent and opened 15 new stores, including six trial franchise stores in Euro Garages' petrol forecourts
Colleagues making the difference
· Our colleagues provided excellent customer service over the Christmas period, when our stores are at their busiest
· Sainsbury's was named Grocer 33 Store of the Week for the 11th time this year4, the highest of any grocer this year
Our values make us different
· Sainsbury's brand Christmas advertisement had over 31 million views across social media and raised over £500k for Great Ormond Street Hospital
Investor Relations Enquiries Media Enquiries
James Collins +44 (0) 20 7695 0080 Louise Evans / Rebecca Reilly +44 (0) 20 7695 7295
1. All sales figures contained in this trading statement are stated including VAT5 and in accordance with IFRIC 13
2. Total Retail sales and like-for-like retail sales performances for Sainsbury's, Argos and the Group are set out in the tables below:
Sainsbury's Retail sales growth excluding fuel
Total (excl. impact of sale of Pharmacy business)
Sainsbury's Retail sales growth including fuel
Argos Retail sales growth
3. Sainsbury's store investment programme 2016/17
At the end of the quarter, Sainsbury's had 604 supermarkets and 796 convenience stores (including six franchise stores)
At the end of the quarter, Argos and Habitat store estate was as follows:
Argos Stores
Argos in Sainsbury's
Argos in Homebase
4. Argos' historic total and like-for-like sales performance is set out below. This reflects its pre-acquisition periods: FY2015/16 for the 52 weeks to 27 February 2016; Q1 for the 13 weeks to 28 May 2016; Q2 for the 13 weeks to 27 August 2016; and H1 for the 26 weeks to 27 August 2016
Argos sales growth (ex VAT)
5. Certain statements made in this announcement are forward-looking statements. Such statements are based on current expectations and are subject to a number of risks and uncertainties that could cause actual results to differ materially from any expected future events or results referred to in these forward-looking statements. Unless otherwise required by applicable law, regulation or accounting standard, we do not undertake any obligation to update or revise any forward-looking statements, whether as a result of new information, future developments or otherwise
6. Sainsbury's also released today its Third Quarter Corporate Responsibility & Sustainability update. This is available at www.j-sainsbury.co.uk/investor-centre/results-and-presentations/
7. A conference call will take place at 8:30am. To listen to the audio webcast we recommend that you register in advance. To do so please visit www.j-sainsbury.co.uk prior to the event and follow the on-screen instructions. To view the transcript of the conference call go to www.j-sainsbury.co.uk and follow the on-screen instructions in the third quarter trading statement section
8. The sale of our Pharmacy business to LloydsPharmacy completed on the 31 August 2016. The impact of this disposal is excluded from like-for-like sales for a period of one year from this date
9. Sainsbury's will announce its Fourth Quarter Trading Statement on 16 March 2017
(1) Sainsbury's total Retail sales excluding the impact of the sale of the Pharmacy business. Including the impact of the sale of the Pharmacy business, total Sainsbury's Retail sales were down 0.3 per cent (excl. fuel)
(2) Based on Sainsbury's internal data
(3) Based on midpoint of weight band for whole standard turkeys
(4) The Grocer 33 Service & Availability wins year-to-date since 18th June 2016
(5) Argos sales growth for pre-acquisition periods set out in note 4 excludes VAT
(6) Three Habitat stores, one Habitat store in Argos, three Habitat stores in Sainsbury's
(7) 36 collection points in Sainsbury's, one collection point in Habitat, four temporary Argos stores, one convenience store
*All intraday prices are subject to a delay of fifteen (15) minutes.
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JotForm is a free online form builder which helps you create online forms without writing a single line of code. No sign-up required.
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Can I set up a way to have all form responses forwarded to my email?Asked by signvisions on November 19, 2013 at 04:15 PM
Hey I am new at my company and taking over existing website management from our previous designer. They failed to even let me know that the forms on our website have just been piling up on our account here on JotForm. And I'd like to know if there's any way that I can set the form responses to automatically forward to a specified email address.
please disregard, I found my own answer. Didn't know where to look was all.
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subset: commoncrawl


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I have a younger cousin who goes to the same high school as me. All she wears is cropped tops. We have different body types. I have always been naturally skinny and she always had some baby fat but it bugs me when she asks to borrow my clothes. She's always asking me every single day to let her borrow something. I already had to give her a couple of my blouses because she stretched them out. I feel bad telling her no but I feel like I have to. She knows she stretches out my tops. Plus people have noticed that she purposely lifts up her cropped top to show her stomach even more and I've told her (thinking I was helping her out). She has a muffin top meaning her stomach fat sticks out and it's bugging me.
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Indians on coast say cyclone evacuation saved them
Credit: The Associated Press
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PODAMPETTA, India — Her house in this seaside village was flattened by the cyclone that roared in from the Bay of Bengal with torrential rains and winds topping 200 kilometers (131 miles) per hour. But the fact that Agya Amma was still here to survey the pile of twisted wood and shredded thatch that had been her home proved this was a different kind of disaster for India.
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Fujii, Satoko Orchestra Nagoya
Pianist and composer Satoko Fujii's Nagoya band, comprised of younger Japanese players influenced by rock music, along with Natsuki Tamura, powerful eclectic and experimental jazz.
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Label: Bakamo
Catalog ID: 07
Squidco Product Code: 12144
Format: CD
Condition: New
Released: 2008
Country: Japan
Packaging: Jewel tray, not sealed.
Recorded September 4, 2007 by Nobuki Matsui at Tokuzo. Mixed and mastered by Yasuhiro Usui.
Satoko Fujii-conductor
Shinkgo Takeda-alto sax
Akihiko Yoshimaru-alto sax
Kenichi Matsumoto-tenor sax
Yoshihio Hanawa-tenor sax
Yoshiyuki Hirao-baritone sax
Natsuki Tamura-trumpet
Tsomutu Watanabe-trumpet
Takahiro Tsujita-trumpet
Misaki Ishiwata-trumpet
Tomoyuki Mihara-trombone
Toshinori Terukina-trombone, euphonium
Tatsuki Yoshino-tuba
Yasuhiro Usui-guitar
Atsutomo Ishigaki-bass
Hisamine Kondo-drums
Highlight an artist name or instrument above
and click here to Search
1. 五角 Gokaku 10:29
2. Eaves 8:30
3. Blueprint 8:58
4. 近藤スター Kondo Star 12:41
5. 暑月 Shogetu 8:08
6. 三角 Sankaku 8:37
7. 山嶺 Sanrei 10:42
Improvised Music
Staff Picks & Recommended Items
sample the album:
"In a recent interview in Cadence magazine, pianist and composer Satoko Fujii briefly discusses her four ongoing big bands - New York, Tokyo, Nagoya, and Kobe. Unlike the other three big bands, Orchestra Nagoya is comprised of younger Japanese players whose musical backgrounds and listening habits include a healthy dose of rock music. The band, conducted by Fujii, features electric guitarist Yasuhiro Usui who also produced, mixed, and mastered the CD, and wrote two of its seven pieces. Unlike Orchestra New York and Orchestra Tokyo (I haven't yet heard Orchestra Kobe), Fujii does not play the piano in Orchestra Nagoya. Her husband, trumpeter Natsuke Tamura is, however, a prominent soloist on "Sanrei," which also boasts two of his quirky, imaginative compositions, 'Gokaku' and 'Sankaku.' As one might expect, the music here is brash, boldly experimental, even startling.
Sanrei is unique amongst contemporary big band recordings in that its edgy, manic, streetwise energy is more about punk rock or alternative rock than it is a reflection of pioneering 60s and 70s avant-jazz big bands such as Globe Unity or the London Jazz Composers' Orchestra. The piano-less rhythm section is adept at playing bruising, punkish rock and intricate funky fusion. But this band can also swing hard, albeit not in a traditional fashion. At times, the brass and reed section work has a joyfully sloppy, off-kilter Sun Ra sort of sound to it. After a careful listen or two, it's quite apparent that this lack of precision is completely intentional (as it was in Sun Ra's various bands). Even more iconoclastic is the band's penchant for distorted guitar and bass sounds, collective brass and reed soloing, and spontaneous eruptions of vocal sounds - yodeling, scatting, howling, groaning, screaming, and even some pseudo-operatic singing. [...]
Sanrei is a bracing, high-intensity musical journey through the imaginations of some of Japan's most exciting and interesting musicians and composers. While it represents a definitive break from the typical 'avant garde big band' sound, it is probably too dark, intense, and rock-based for fans of traditional big band jazz. However, I totally enjoyed "Sanrei" from beginning to end. Fujii and her colleagues prove once again that the creative possibilities in a jazz ensemble of any given size are limitless."-Dave Wayne, JazzReview.com
Get additional information at JazzReview.com
Artist Biographies:
• Show Bio for Satoko Fujii
"Born on October 9, 1958 in Tokyo, Japan, Fujii began playing piano at four and received classical training until twenty, when she turned to jazz. From 1985-87, she studied at Boston's Berklee College of Music, where her teachers included Herb Pomeroy and Bill Pierce. She returned to Japan for six years before returning to the US to study at the New England Conservatory in Boston, where her teachers included George Russell, Cecil McBee, and Paul Bley, who appeared on her debut CD Something About Water (Libra, 1996).
Since then Fujii has been an innovative bandleader and soloist, a tireless seeker of new sounds, and a prolific recording artist in ensembles ranging from duos to big bands. She has showcased her astonishing range and ability approximately 80 CDs as leader or co-leader. With each new recording or new band, she explores new aspects of her art.
Regular collaborations include her New York trio with bassist Mark Dresser and drummer Jim Black, augmented by trumpeter/husband Natsuki Tamura to form the Satoki Fujii Four; her duo with Tamura; the Satoko Fujii Quartet featuring Tatsuya Yoshida of the Japanese avant-rock duo, The Ruins; Orchestra New York, which boasts the cream of New York's contemporary avant garde improvisers, including saxophonists Ellery Eskelin and Tony Malaby, trumpeters Herb Roberton and Steven Bernstein, and trombonist Curtis Hasselbring, among others; Orchestra Tokyo, drawing on that city's best improvisers; Orchestra Nagoya; Orchestra Kobe; the co-operative trio Junk Box with Tamura and percussionist John Hollenbeck; ma-do, a quartet including Tamura on trumpet, bassist Norikatsu Koreyasu, and Akira Horikoshi; the Min-Yoh Ensemble with Tamura, trombonist Hasselbring, and accordionist Andrea Parkins; the Satoko Fujii New Trio, featuring bassist Todd Nicholson and drummer Takashi Itani― plus countless engagements and collaborations with some of the world's most important improvisers."-Satoko Fujii Website (http://www.satokofujii.com/bio.html)
^ Hide Bio for Satoko Fujii
• Show Bio for Natsuki Tamura
"Japanese trumpeter and composer Natsuki Tamura is internationally recognized for a unique musical vocabulary that blends extended techniques with jazz lyricism. This unpredictable virtuoso's seemingly limitless creativity led François Couture in All Music Guide to declare that "... we can officially say there are two Natsuki Tamuras: The one playing angular jazz-rock or ferocious free improv... and the one writing simple melodies of stunning beauty... How the two of them live in the same body and breathe through the same trumpet might remain a mystery."
Born on July 26, 1951, in Otsu, Shiga, Japan, Tamura first picked up the trumpet while performing in his junior high brass band. He began his professional music career after he graduated from high school, playing in numerous bands including the World Sharps Orchestra, Consolation, Skyliners Orchestra, New Herd Orchestra, Music Magic Orchestra, and the Satoko Fujii Ensemble, as well as in his own ensemble. He was the trumpeter for numerous national television shows in Japan from 1973-1982, including The Best Ten, Music Fair, Kirameku Rhythm and many others.
In 1986, he came to the United States to study at Berklee College of Music. He then returned to his native Japan to perform and teach at the Yamaha Popular Music School and at private trumpet studios in Tokyo and Saitama, before coming back to the US to study at New England Conservatory. He made his debut recording as a leader in 1992 on Tobifudo.
In 1997 he released the duo album How Many? with pianist Satoko Fujii, who is also his wife. It marked the beginning of an artistic collaboration that continues up to the present. The duo has made a total of five CDs over the years, including 2012's Muku. "Muku contains some truly stunning, spine-tingling music...its sheer beauty and elegance is what lingers most," wrote Dave Wayne in All About Jazz. "Fujii's orchestral technique, clear chromatic lines and "prepared piano" devices contrast effectively with Tamura's arsenal of extended techniques which he executes with a warm, vocalized tone throughout the trumpet's full range," Ted Panken said in his four-star DownBeat review. Tamura's collaborations with Fujii reveal an intense musical empathy, and have garnered wide popular and critical acclaim. Jim Santella in All About Jazz described their synergy well in his glowing review of the couple's 2006 Not Two disc, In Krakow, In November: "... the creative couple forcefully demonstrates what can happen when you let your musical ideas run free... Similarly, Tamura's mournful trumpet can fly high or low in search of his next surprise. Oftentimes, they both issue plaintive moans that sing like angels on high." Their sixth duet album is due out in 2017.
In 1998, Tamura began recording his unaccompanied solo performances. The stunning solo trumpet debut release, A Song for Jyaki earned a Writers Choice 1998 in Coda magazine, and Andy Bartlett wrote in Coda, "A fabulous set of hiccuping leaps, drones and post-bop trumpet hi-jinx. Tamura goes from growling lows to fluid, free solo runs and echoes not only Don Cherry's slurring anti-virtuosic chops but also Kenny Wheeler's piercing highwire fullness." He followed it up in 2003 with KoKoKoKe, which Jon Davis described in Exposé as "Buddhist chants from an alien planet." Grego Applegate Edwards explains that on Tamura's most recent solo album, 2013's Dragon Nat, "he pares down to focus on simple unwinding melodic material, the sound of his trumpet as a sensuous thing, a periodicity. Taken as a whole it is a kind of environmental tone poem for the moment Natsuki is in now."
2003 was a breakout year for Tamura as a bandleader, with the release of Hada Hada, featuring his free jazz-avant rock quartet with Fujii on synthesizer. Peter Marsh of the BBC had this to say about the high voltage CD: "Imagine Don Cherry woke up one morning, found he'd joined an avant goth-rock band and was booked to score an Italian horror movie. It might be an unlikely scenario, but it goes some way to describing this magnificent sprawl of a record." The quartet's 2004 Quartet release Exit was deemed "...a brilliantly executed set with a neon glow," by Dan McClenaghan in All About Jazz.
In 2005, Tamura made a 180-degree turn in his music with the debut of his all acoustic Gato Libre quartet. Focusing on the intersection of European folk music and sound abstraction, the quartet featured Fujii on accordion, Kazuhiko Tsumura on guitar, and Norikatsu Koreyasu on bass. The quartet's poetic, quietly surreal performances have been praised for their "surprisingly soft and lyrical beauty that at times borders on flat-out impressionism," by Rick Anderson in CD Hotlist. Dan McClenaghan in All About Jazz described their fourth CD, Shiro, as "intimate, something true to the simple beauty of the folk tradition...Tamura's career has largely been about dissolving musical boundaries. With Gato Libre and Shiro, the trumpeter extends his reach even deeper into the prettiest, most accessible of his endeavors." After the unexpected passing of Norikatsu in 2012, Tamura added trombonist Yasuko Kaneko to the group. The new configuration has toured Europe and Japan and released its debut recording, DuDu, in 2014. "DuDu follows the winning formula of its predecessors but, as with the other discs, eschews the formulaic. The result is another sublimely satisfying, elegant record that brims with raw excitement and a reflective nostalgia," writes Hrayr Attarian in All About Jazz. With the tragic death of guitarist Kazuhiko Tsumura, Gato Libre is now a trio. They will release a CD and LP in 2017.
In 2010, Tamura debuted a new electric quartet, First Meeting, featuring Fujii, drummer Tatsuhisa Yamamoto and electric guitarist Kelly Churko. Their first release, Cut the Rope, is "is a noisy, free, impatient album, and ranks among Fujii and Tamura's most accomplished," according to Steve Greenlee in the Boston Globe.
While fronting groups and recording as a leader, Tamura has also played an integral role in nearly all of Satoko Fujii's many projects. He is featured on all of the CDs by Satoko Fujii's various orchestras (NY, Tokyo, Nagoya, Kobe, and Berlin) and has contributed original compositions and arrangements to each of their 19 critically celebrated albums. In addition, he was a featured soloist in the Satoko Fujii Quartet, her avant-rock free jazz group that also included Tatsuya Yoshida of The Ruins. Of his work on the quartet's 2003 release Minerva, Mark Keresman wrote in JazzReview.com, "Natsuki Tamura's trumpet has some of the stark, melancholy lyricism of Miles, the bristling rage of late 60s Freddie Hubbard and a dollop of the extended techniques of Wadada Leo Smith and Lester Bowie."
Tamura is a vital member of Fujii's Min-Yo Ensemble as well. "Tamura tempers his avant-garde antics with an innate lyricism," wrote Steve Smith of Time Out New York in his review of Fujin Raijin, the intimate acoustic quartet's debut CD. He's also been singled out for his contributions to Fujii's ma do ensemble. "With Tamura's brash and glowing lines, the band incorporates mesmeric ostinatos and thrusting opuses into the grand schema," Glenn Astarita wrote in Ejazznews about their first CD, Desert Ship.
Collaborative groups also play an important role in Tamura's career. Most recently, Tamura joined Fujii and two French musicians, trumpeter Christian Pruvost and drummer Peter Orins, to form Kaze, which made their recording debut in 2011. In 2015, they released their third album, Uminari, which Jazz Magazine (France) called, "a compelling example of free jazz today. Compositions are perfectly scripted, with a well-oiled interaction and playing of beautiful power..." The collaborative trio Junk Box, which he co-founded in 2006 along with pianist Fujii and drummer John Hollenbeck, plays Fujii's "composed improvisations," graphic scores that take "ensemble dynamics to great creative heights," says Kevin Le Gendre in Jazzwise. Their music "is full of bluster and agitation that nonetheless retains moments of great melodic beauty, usually by way of concise, pertly pretty motifs that trumpeter Tamura plays in between bursts of withering roars that often dissolve into austere overtones." Their premiere CD, Fragment, appeared in 2006. As Daniel Spicer wrote of Fragment in JazzWise, "Tamura spits out gloriously rude Lester-Bowie-like snorts, lows like a herd of robotic cattle or makes like a wheezy howler monkey... Cool and clever." Glenn Astarita of All About Jazz declared it "Required listening."
Along the way, there have been one-off cooperative groups and sideman appearances for Tamura as well. In the Tank, an ad hoc quartet with Fujii and electric guitarists Takayuki Kato and Elliott Sharp, is a "triumphant electro-acoustic adventure" according to Daniel Spicer of Jazzwise. "Think AMM meets blues guitar meets 1970s Miles Davis and you get some idea of the disc's flavor: a slow-moving panorama for the ears, where sounds are systematically added, repeated, refined, and replaced in turn," wrote Nate Dorward in Cadence. Tamura and Fujii were one of two piano/trumpet duos featured on the Double Duo Crossword Puzzle CD, a live recording with Dutch trumpeter Angelo Verploegen and pianist Misha Mengelberg. Tamura has also toured and recorded with saxophonist Larry Ochs' Sax and Drumming Core, and appeared on albums by drummer Jimmy Weinstein, saxophonist Raymond McDonald, and CDs by Japanese free-jazz pioneers trumpeter Itaru Oki and pianist Masahiko Sato. In 2014 he released Nax, a duet album with bassist Alexander Frangenheim. Tamua has toured throughout Japan, North America, and Europe, appearing at major jazz festivals, concert halls, and clubs."-Natsuki Tamura Website (http://www.natsukitamura.com/bio)
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text: Hey everybody. My name is Clint. I work full-time currently but I am starting a lawn mowing business up this spring on the side (nights/weekends). My goal is to one day be independent and be able to quit my job. I'd like to find some jobs aerating and fertilizing in the spring and fall, leaf pickup, shrub/tree trimming, and snow plowing. Eventually maybe landscaping/hardscaping could be a part as well. I've been reading the threads here for over a month already but just signed up. I'm sure I'll have some threads popping up around here soon.


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Tako Luka (たこルカ) is an officially recognized derivative of Megurine Luka, and the result of creativity of imagining Luka's hair in the form of an octopus, in the same manner as Hachune Miku. This octopus had a very important involvement in Vocaloid fandom, most notably in the Japanese community. Both Tako Luka and Hachune Miku are seen as mascots side by side with their source characters. The word "Tako" means Octopus, meaning that her English name is rendered as "Octopus Luka". The term "Derivative" is used here to describe a fanmade Vocaloid character that is based on an already existing character.
Connection with All-StarsEdit
Tako Luka appears in the moveset of Hatsune Miku as one of her attacks. Tako Luka will be thrown and will cling onto the enemy making them slow down, but don't drop AP orbs like Sackbot.


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|Publication number
|Publication type
|Application number
|Publication date
|Aug 9, 2011
|Filing date
|Oct 29, 2004
|Priority date
|Oct 30, 2003
|Fee status
|Also published as
|Publication number
|Michiel A. U. Bacchiani, Sameer Raj Maskey, Brian E. Roark, Richard William Sproat
|Original Assignee
|At&T Intellectual Property Ii, L.P.
|Export Citation
|BiBTeX, EndNote, RefMan
|Patent Citations (12), Non-Patent Citations (2), Referenced by (12), Classifications (12), Legal Events (4)
|External Links: USPTO, USPTO Assignment, Espacenet
The present application claims priority to U.S. provisional Application No. 60/515,896 filed on Oct. 30, 2003, the contents of which are incorporated herein by reference. The present application is related to Ser. No. 10/976,378, filed on Oct. 29, 2004, the contents of which are incorporated herein by reference.
1. Field of the Invention
The present invention relates to spoken dialog systems and more specifically to using meta-data for language models to improve speech processing by speech modules such as an automatic speech recognition module.
2. Introduction
Spoken dialog systems are becoming more prevalent in society. Technology is improving to enable users to have a good experience in speaking to a dialog system and receive useful information. The basic components of a typically spoken dialog system are shown in
One of the challenges of spoken dialog systems is dealing with names. A transcription system that requires accurate general name recognition and transcription may be faced with covering a large number of names that it will encounter. When developing a spoken dialog system, language models are trained using expected words and phrases to help the system interact with the user according to an expected "domain." For example, a spoken dialog system for a bank will have a set of expectations regarding user requests. Having a known domain helps designers prepare the spoken dialog system to achieve a recognition accuracy that is acceptable. In a banking domain, words and phrases such as "account balance", "checking", "savings", "transfer funds" are expected and may be part of a finite grouping.
However, without prior knowledge of the names of people, a spoken dialog system will require a large increase in the size and complexity of the system due to the expansion of the lexicon. Furthermore, this increase will adversely affect the system performance due to the increased possibility of confusion when trying to recognize different names. One example of a system that must have accurate name transcription by its ASR module is a directory assistance and name dialer system. Building such a system is complex due to the very large number of different names it may encounter. An additional complicating factor is the pronunciation of names which can vary significantly among speakers. As a result, ASR research on name recognition has received a fair amount of attention. The feasibility of a directory assistance application with as many as 1.5 million names has been investigated and it has been shown that recognition accuracy drops approximately logarithmically with increasing vocabulary size. A significant degradation in performance with increasing lexicon size has also been shown. Larger lexicons that allow more diverse pronunciations can be beneficial. Most efforts have focused on soliciting more detailed speech input from the user in the form of spelling, and have shown that this improves the system performance. Neural networks have also been shown to focus the search on the most discriminative segments in a multi-pass approach. One attempt has shown improvement in name recognition accuracy by incorporating confidence scores into the decision process.
Common among all previous work is that the coverage issue was addressed by increasing the vocabulary size. The increased confusability introduced by that increase is then addressed by more complex search and acoustic modeling, which is more costly. Therefore, what is needed in the art is an improved system and method for recognizing names or other similarly situated words or phrases in a spoken dialog. The improved system and method should be less costly and time consuming.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The features and advantages of the invention may be realized and obtained by means of the instruments and combinations particularly pointed out in the appended claims. These and other features of the present invention will become more fully apparent from the following description and appended claims, or may be learned by the practice of the invention as set forth herein.
Something that has not been taken into account in the modeling approaches discussed above is the prior probability distribution across names. Indeed, if no additional information is available, a uniform (or context independent frequency weighted) distribution across names is a reasonable estimate. However, in most contexts, a very small subset of the possible names will account for most of the true probability mass. In other words, the distribution of names seen in the speech of a particular speaker is very unlikely to be distributed uniformly across the large list of possible names. If the subset of names that are most likely to occur in a given context are known, the system accuracy can be increased with a decrease in complexity.
One embodiment of the invention is a method of generating a language model. Such a model may be used in an automatic speech recognition module or may be used in one of the modules within a spoken dialog system. The method comprises building a class-based language model, generating at least one sequence network and replacing class labels in the class-based language model with the at least one sequence network. In this manner, placeholders or tokens associated with classes can be inserted into the models at training time and word/phone networks can be built based on meta-data information at test time. Finally, the placeholder token can be replaced with the word/phone networks at run time to improve recognition of difficult words such as proper names.
Other embodiments of the invention include at least (1) an automatic speech recognition module using a language model generated according to the principles set forth herein, (2) a system such as a spoken dialog system or another type of computing device that may utilize at least one language processing module (e.g., ASR, LG, TTS, etc.) that requires a language model generated according to the principles set forth herein, and (3) a computer-readable medium that stores instructions for controlling a computing device.
In order to describe the manner in which the above-recited and other advantages and features of the invention can be obtained, a more particular description of the invention briefly described above will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings. Understanding that these drawings depict only typical embodiments of the invention and are not therefore to be considered to be limiting of its scope, the invention will be described and explained with additional specificity and detail through the use of the accompanying drawings in which:
Various embodiments of the invention are discussed in detail below. While specific implementations are discussed, it should be understood that this is done for illustration purposes only. A person skilled in the relevant art will recognize that other components and configurations may be used without parting from the spirit and scope of the invention.
Disclosed will be a system, method and computer-readable media for improving the performance of a language-related module that may be used in a spoken dialog system or some other application. A preferable use of the invention is to improve the ASR module's recognition accuracy for words such as names. The main aspects of the invention will be discussed with reference to the ASR module of a spoken dialog system. However, the basic principles of the invention are applicable to any component or module within a spoken dialog system. Furthermore, a language module (such as an ASR module) or language-processing function may also be used in any kind of computing device independent of a full spoken dialog system. For example, some kind of home appliance or vehicle feature may include an ASR module that receives an utterance from a user and takes an action, such as calling a particular person or turning on the television.
For many speech applications, information in addition to the speech that is to be recognized is available. For example, a voicemail has a mailbox, with an associated user name. A caller usually has an associated caller ID string. This additional information will be referred to as meta-data. The basic concept of the present invention is to build language models such as the speech recognition model, to include the relevant meta-data, and hence can recognize names when a name is spoken, or other words that are difficult to recognize. This can provide a tremendous benefit. One costly way to do this is to build new models for every message. However, the method proposed below provides a more economical approach to recognizing names or other difficult words. It is noted that most of the examples provided herein will relate to recognizing names. However, the principles are not limited to names. Other examples of how this invention may apply include such areas as news or technology. For example, if meta-data includes a word such as "Internet" then the method may be applied to identify other words that mean the same ("World-wide-web", "the 'Net", "the blogosphere" and so forth) such that the speech processing module, when the invention is applied to such words, may be able to utilize an improved language model.
As an introduction to this invention, it relates to a rapid construction of sub-networks based on given information external to a speech signal for inclusion in large previously constructed networks. Information external to the speech signal (referred to herein as meta-data) may be any information such as a name received from caller-ID or an e-mail address or URL associated with a voice over IP communication. The information external to the speech signal can be quickly integrated with the language models to improve recognition accuracy. Certain kinds of terms such as proper names are a problem for speech recognition because they often fall out of vocabulary. If the vocabulary is extended to include many, many names, the complexity of the system increases to a problematic level. Therefore, the present invention shows how external information can alleviate this issue by using side information has not been previously investigated in the language modeling community.
The method embodiment of the invention uses meta-data available at runtime to ensure better name coverage without significantly increasing the system complexity. The approach has been tested on a voicemail transcription task and assumed meta-data to be available in the form of a caller ID string (as it would show up on a caller ID enabled phone) and the name of the mailbox owner. Networks representing possible spoken realization of those names are generated at runtime and included in network of the decoder. The decoder network is built preferably at training time using a class-dependent language model, with caller and mailbox name instances modeled as class tokens. While the use of names as class tokens is preferable, class tokens may also relate to classes of information different from a person or company's name. The class tokens are replaced at test time with the name networks built from the meta-data. This method showed via testing a reduction in the error rate of name tokens of 22.1%.
The present inventors have focused on name recognition in a voicemail transcription task and assume context information or meta-data is available in the form of the name of the mailbox owner and the caller ID string from the incoming call leaving the voicemail message. Caller identification information is typically provided by phone companies. In a Voice Over IP context, name, email address, or other types of meta-data information may also be available. For example, an agenda for a business meeting, flyers, websites, and so forth may provide identifiable data such as company name or names of people attending the meeting.
There is a natural class of names of people or names of companies that tend to occur similarly in a speech signal. In a voicemail database, an example may be, "Hey, Jon, I am just calling to say hello." The caller ID for this call may provide further information: Jonathan Smith. In this way, a name-class can be defined in the language that is being produced. Since these proper names occur or are announced in similar ways and in similar contexts. One can take the specific instance that is being modeled and insert it into a grammar that improves the language model to recognize that particular proper name.
One aspect of the invention involves receiving the text of a proper name (or other type of meta-data) and identifying its orthographic representation and mapping it to phonological realizations of the name. For example, taking the name John Smith, likely nicknames and variations include Johnny, Jonathan, Mr. Smith, and so forth. Therefore, the issue of how to map from orthographic realization provided to something to be included in an ASR transducer or other spoken dialog system module is described herein. As noted above, another aspect of the invention is outside the use of names but to other words that may also have companion words or other phonological representations of the word.
A voicemail database used in experiments for the present invention is described next, followed by a description of how the meta-data is used to condition the spoken dialog system. Experimental results obtained using the invention then are presented with a discussion of the results.
Transcription experiments were conducted on a 100 hour corpus of voicemail messages collected from the voicemail boxes of 140 people. This corpus, named ScanMail, contains approximately 10,000 messages from approximately 2500 speakers. The corpus is approximately gender balanced and approximately 12% of the messages are from non-native speakers (as assessed by the labeler from listening to the speech). The mean duration of the messages is 36.4 seconds, the median is 30.0 seconds. The messages were manually transcribed and those parts of the transcripts that identify the caller and mailbox owner were bracketed. The identifications usually occur in the beginning of the message such as:
A two hour test set was chosen by randomly selecting 238 messages from the corpus. The remaining speech was used as the training set to build the acoustic and language models. In this test set, there were 317 word tokens corresponding to caller names and 219 word tokens corresponding to mailbox owner names.
The approach to including the name meta-data into the spoken dialog system (such as for the ASR module) uses a class-based language model, built preferably at training time. This language model represents name occurrences by class tokens. Then, preferably at test time, the name meta-data is used to produce a name network that gives possible, probability weighted spoken realizations of the meta-data defined names. That name network is then included in the recognition network by a network replacement step.
The method aspect of the invention is shown by way of illustration in
Next, a name network is generated (404). This involves building a word/phone network based on the given information preferably at testing time. For each voicemail message in the test set, the name of the mailbox owner was provided, and the name of the caller, if it was available, which it was for 71 percent of the test messages. For each provided name, e.g. Jeremy Jones, there are a variety of ways in which the name could be realized, e.g. Jerry Jones, Mister Jones, Jeremy, etc. This variation is the result of two random processes: first, the sequence of title, first name and last name can vary; next there can be many possible forms of the first name. From the training corpus, the probability of different realizations of the sequence of title was estimated, for each name class, first name (regardless of form) and last name.
For the probabilities of forms of first names, the inventors use a directory listing having the full name and optional nicknames for 40,000 people. For a given first name, the inventors counted each nickname for people with that name, and used the maximum likelihood estimate based on these counts for the nickname given the name. If no nickname was listed, it was counted as though the full form of the name was the nickname. In order to always allow for the full form of the name, if every observation with the name has a nickname, the full form can be given one count. For a particular caller ID, the <first.name> and <last.name> tokens in the graph in
With reference again to
The ScanMail voicemail system uses an optimized recognition network, which combines the pronunciation lexicon L and the grammar G into a single optimized finite-state transducer through off-line composition, determinization and minimization. As used herein, the terms grammar and language model or class-based language model typically mean the same thing. This network composition and optimization can be quite costly in space and time and is generally done once and the result treated as a static model.
In the current scenario, this resource cannot be static, since each message can have a different mailbox and caller ID. Composing and optimizing the entire network for each message is impractical. To avoid this, each name class label is provided with a special phone symbol in the lexicon, which allows the system to produce an optimized L∘G for the class-based G. For each message, L∘G is produced by composing the name network G′ with the lexicon and optimizing. Every transition in the original class-based L∘G with a name class label (i.e. (mname) or (cname)) as the output label (and hence the special phone symbol as the L∘G input label) is then replaced with the L∘G′ for that name class, and the weights are combined appropriately. The overhead of producing the very small L∘G′ and replacement in the large L∘G is relatively low.
The algorithm was evaluated on the 238 message ScanMail test set. This test set was drawn from the ScanMail corpus by random selection of messages. This means that for most test messages, there will be messages in the training set that were received in the same mailbox. The number of training messages received at a particular mailbox varied from 1 to 11 with an average of 3 messages per mailbox. The overlap in mailbox recipients results in an experimental setup that is likely to provide a lower error rate, especially on names, than a scenario where the test data is from mailboxes never seen in the training data. To normalize for this effect, the experiment used a different language model for each test message. The language models were constructed by excluding training messages from the same mailbox as the test message.
For the 238 test messages, the (mname) meta-data value was known for all messages but the (cname) meta-data was available for only 169 messages. For the messages that did not have the (cname) meta-data available, the inventors used a system that only used the (mname) class.
To evaluate the performance of the algorithm, in addition to Word Error Rates (WER) the inventors measured the error rate on the name tokens corresponding to the (mname) and (cname) class tokens. Using the alignments produced in computing the WER, the Name Error Rate (NER) is computed as the percentage of name tokens that were labeled as an error (either a deletion or a substitution) in that alignment.
The baseline system using no name replacements had a WER of 26.6% (7233 tokens). Using the proposed algorithm replacing only (mname) tokens, the WER dropped to 26.3% (7147 tokens). When replacing both (mname) and (cname) tokens, the WER rate dropped to 26.0% (7066 tokens).
WER and NER
Word Error
Name Error
(mname) + (cname)
The performance of the algorithm is summarized in Table 1. Among the 219 name tokens corresponding to (mname) class tokens, there were 128 errors in the baseline transcripts. Using the system that did (mname) replacements, this dropped to 68 errors. Among the 317 (cname) tokens, 177 were misrecognized in the baseline recognizer output. Using the (mname) and (cname) replacement system this error rate dropped to 119 errors. The total number of misrecognized name tokens in the baseline was 305 corresponding to a 56.9% NER. Using the (mname) and (cname) replacement system, the name token error rate dropped to 187 or 34.8% NER. This is an absolute NER reduction of 22.1%.
The word error rate improvement of the of the (mname) replacement system in terms of the number of tokens was 86 which is higher than the number of corrections among (mname) tokens (60) showing that the replacement had a small beneficial effect on the words surrounding the name tokens. Similarly, for the (mname) and (cname) replacement system, the number of corrected tokens in the WER computation exceeds the number of corrected (mname) and (cname) tokens by 49 showing the same small beneficial effect.
Out of the 536 name tokens corresponding to the (mname) and (cname) class tokens, 35 were out of vocabulary (OOV) word tokens. The (mname) and (cname) replacement system correctly recognized 24 (69%) of those.
The runtime overhead was computed on a 30 message, randomly selected from the test set. The average real time factor processing the messages with the baseline system was 3.8. The runtime of the (mname) replacement experiment increased this factor to 4.3 (a 13% increase). For the (mname) and (cname) replacement experiment, the average real-time factor was 4.6, a 20% increase compared to the baseline.
Although the decrease in overall WER was not large, names are of particular importance, so that the large reduction in name error rate is critical to both the perception and use of the system. ScanMail users have expressed a strong desire for the system to recognize these tokens correctly.
The results show that the proposed algorithm is not only useful for addressing errors that arise from OOV tokens but also improves on in-vocabulary name recognition. Where in a static system, the distribution across names may be fairly flat, the meta-data dependent system effectively provides a relatively peaked distribution for those names that correspond to allowed realizations of the given names.
Unlike previous efforts, the use of meta-data allows for the design of a system with good name coverage without a significant increase in system complexity. Although, unlike other systems, the use of meta-data incurs a run-time overhead at test time, this overhead is possibly smaller than the additional overhead incurred by a significant increase in complexity.
In contrast to systems with a static name inventory, the proposed algorithm avoids the need for manual system design when it is moved to new environment. Where a static system will likely incur an increase in the OOV rate, the proposed algorithm automatically adapts due to the run-time network generation.
Embodiments within the scope of the present invention may also include computer-readable media for carrying or having computer-executable instructions or data structures stored thereon. Such computer-readable media can be any available media that can be accessed by a general purpose or special purpose computer. By way of example, and not limitation, such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to carry or store desired program code means in the form of computer-executable instructions or data structures. When information is transferred or provided over a network or another communications connection (either hardwired, wireless, or combination thereof) to a computer, the computer properly views the connection as a computer-readable medium. Thus, any such connection is properly termed a computer-readable medium. Combinations of the above should also be included within the scope of the computer-readable media.
Computer-executable instructions include, for example, instructions and data which cause a general purpose computer, special purpose computer, or special purpose processing device to perform a certain function or group of functions. Computer-executable instructions also include program modules that are executed by computers in stand-alone or network environments. Generally, program modules include routines, programs, objects, components, and data structures, etc. that perform particular tasks or implement particular abstract data types. Computer-executable instructions, associated data structures, and program modules represent examples of the program code means for executing steps of the methods disclosed herein. The particular sequence of such executable instructions or associated data structures represents examples of corresponding acts for implementing the functions described in such steps.
Those of skill in the art will appreciate that other embodiments of the invention may be practiced in network computing environments with many types of computer system configurations, including personal computers, hand-held devices, multi-processor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, and the like. Embodiments may also be practiced in distributed computing environments where tasks are performed by local and remote processing devices that are linked (either by hardwired links, wireless links, or by a combination thereof) through a communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.
Although the above description may contain specific details, they should not be construed as limiting the claims in any way. Other configurations of the described embodiments of the invention are part of the scope of this invention. For example, the invention may be used as a method for building language models or a spoken dialog system using language models built according to the steps set forth above. A language model built according to this method may be used in any module such as an ASR module in any type of application besides a full spoken dialog system as well. Further, using methods described above, new models could be built from scratch for each utterance. Accordingly, the appended claims and their legal equivalents should only define the invention, rather than any specific examples given.
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|Maskey, et al. "Improved Name Recognition with Meta-Data Dependent Name Networks", Acoustics, Speech and Signal Processing, 2004 Proceedings, (ICASSP '04), IEEE International Conference on Montreal, Quebec, Canada, May 17-21, 2004, Piscataway, N.J. USA, IEEE, vol. 1, May 17, 2004, pp. 789-792.
|Ye-Yi Wang, "A Unified Context-Free Grammar and N-Gram Model for Spoken Language Processing", 2000 IEEE International Conference on Acoustics, Speech,, and Signal Processing, vol. 3, Jun. 5, 2000-Jun. 9, 2000, pp. 1639-1642.
|Citing Patent
|Filing date
|Publication date
|Dec 14, 2010
|Dec 10, 2013
|Nuance Communications, Inc.
|Multi-pass speech recognition
|Feb 22, 2013
|Jun 2, 2015
|Google Inc.
|Character and word level language models for out-of-vocabulary text input
|Apr 18, 2013
|Sep 27, 2016
|Google Inc.
|Gesture keyboard input of non-dictionary character strings
|Oct 28, 2014
|Nov 22, 2016
|Google Inc.
|Dynamically biasing language models
|Sep 30, 2015
|May 23, 2017
|International Business Machines Corporation
|Semi-supervised learning of word embeddings
|May 8, 2015
|Jun 6, 2017
|International Business Machines Corporation
|Semi-supervised learning of word embeddings
|Feb 16, 2011
|Aug 16, 2012
|International Business Machines Corporation
|Translated sentence quality estimation
|Feb 22, 2013
|Jul 31, 2014
|Google Inc.
|Character and word level language models for out-of-vocabulary text input
|Jun 28, 2012
|Sep 17, 2015
|Nuance Communications, Inc.
|Meta-data inputs to front end processing for automatic speech recognition
|Sep 30, 2015
|Nov 10, 2016
|International Business Machines Corporation
|Semi-supervised learning of word embeddings
|May 8, 2015
|Nov 10, 2016
|International Business Machines Corporation
|Semi-supervised learning of word embeddings
|Feb 21, 2017
|Jun 8, 2017
|International Business Machines Corporation
|Semi-supervised learning of word embeddings
|U.S. Classification
|International Classification
|Cooperative Classification
|European Classification
|Jul 15, 2011
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You bought your E-250 Econoline Club Wagon because its dependability and long-lasting quality struck a chord inside you; so why would you settle for second best when it comes to superior quality auto parts? Ford automobile owners have grown accustomed to a certain level of dependability when driving their E-250 Econoline Club Wagon around town. While it's not hard to find replacement parts for Ford vehicles, these days only the highest quality are required to maintain your automobile. It's not all the time that you discover you need a replacement A/C Compressor for your vehicle.
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HOTS for ICTs
How we engage our students to use HOTs through the use of ICTs
Tonia Lassmanon 21 September 2010
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Transcript of HOTS for ICTs
We've got the hots for Icts Nouns Verbs PEdagogy HOTS: Higher Order Thinking Understanding Comprehending Applying Analysing Synthesising Evaluating ENGAGEMENT PowerPoint MovieMaker Digital Pedagogy Animoto Wavepad ABCya Internet http://www.abc.net.au/innovation/gallipoli/gallipoli2.htm http://www.anzacs.net/AnzacStory.htm ReflectionFull transcript


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Bewitched: Season 1
Handling Time:1 business day
Returns: Accepted
Condition: New
Elizabeth Montgomery stars as Samantha Stephens, a pretty, typical American housewife who just happens to be a witch in this beloved comedy classic. Included in this magical DVD collection is the Emmy (r) Award-winning series' entire first season- 36 episodes that introduce one of the funniest ensemble casts in TV history. Dick York as Samantha's mortal husband Darrin, Agnes Moorehead as his witch-of- a-mother-in-law Endora. Alice Pearce as nosey neighbor Gladys Kravitz, George Tobias as her oblivious husband Abner and Marion Lorne as dotty Aunt Clara. Join them and a who's who of '60s pop icon guest stars- Adam West, Raquel Welch, Peggy Lipton and Arte Johnson- in this enchanting, charming, and hysterically funny look at the suburban lifestyles of the witch and famous.
Brand: Columbia Tri Star
Manufacturer Part Number: 96753


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Mike Pruitt
I am a classically trained engineer and MBA in a modern world. My career has been in the printing and petroleum industries with a focus on the prime label, airlines, point of sale, financial transaction and oil and gas exploration markets. All this took me to all parts of the world where I lived in more than 15 countries. Inquisitive by nature and always ready to solve market needs. U Texas and U Chicago diplomas and advanced degree from the School of Life, College of Hard Knocks.


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Nicolas Trembley
Wade Guyton at Le Consortium
September 23rd, 2016 in Exhibitions Comments Off on Wade Guyton at Le Consortium
Artist: Wade Guyton
Venue: Le Consortium, Dijon
Curated by: Nicolas Trembley
Date: June 25 – September 25, 2016
Full gallery of images and link available after the jump.
Tags: Dijon, France, Institution, Le Consortium, Nicolas Trembley, Wade Guyton
"Looking Back" at White Columns
February 17th, 2013 in Exhibitions No Comments
Artist: Yuji Agematsu, Julie Ault / James Benning, Lutz Bacher, Martin Beck, Kaucyila Brooke, Moyra Davey, Disband, Fat Lava / Nicolas Trembley, Peter Fend, Liam Gillick and Henry Bond, David Grubbs and Susan Howe, Lawrence Abu Hamdan, Alex Israel, Gareth James, Rockwell Kent, Alexander Kluge, Chris Kraus, Zoe Leonard, Sam Lewitt, Tan Lin, Chris Marker, Bjarne Melgaard, Alice Neel, Henrik Olesen, Alfred T. Palmer, Sam Pulitzer and Bill Hayden, Sabine Reitmaier, Helke Sander, Amy Sillman, Jason Simon, Harry Smith
Venue: White Columns
Exhibition Title: Looking Back / The White Columns Annual
Date: January 10 – February 23, 2013
Full gallery of images, videos, press release and link available after the jump.
Tags: Alex Israel, Alexander Kluge, Alfred T. Palmer, Alice Neel, Amy Sillman, Bill Hayden, Bjarne Melgaard, Chris Kraus, Chris Marker, David Grubbs, David Grubbs and Susan Howe, Disband, Fat Lava, Gareth James, Group Show, Harry Smith, Helke Sander, Henrik Olesen, Henry Bond, James Benning, Jason Simon, Julie Ault, Kaucyila Brooke, Lawrence Abu Hamdan, Liam Gillick, Lutz Bacher, Martin Beck, Moyra Davey, Nicolas Trembley, Peter Fend, Rockwell Kent, Sabine Reitmaier, Sam Lewitt, Sam Pulitzer, Susan Howe, Tan Lin, Yuji Agematsu, Zoe Leonard
Contemporary Art Venues
Sponsored Listings


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Orçamento $20-100 USD
I want a header of Textile industry with very nice design. First i want see a sample of textile industry header. Plz snd me PMB asap.
I can pay Max $40 for this. NO Flash Neded.
32 freelancers estão ofertando em média $38 para este trabalho
We wish to introduce iNavigators as an Information Technology arm of Rungta Enterprises, a multimillion-dollar conglomerate that was conceived with a singular charter to provide quality software solutions and to cater Mais
Hello, I'm interested in working on your project.Part of my portofolio is avaiable here http://agoni.go.ro Best Regards, Dorin Frunzete
Hi, I'm a professional Graphic Designer 'n' look forward to work with you. I 'll come up with the design soon. Thanks Shailza
Please have a look at the headers we made recently for our client . The URL is http://www.i4consultant.com/headers.html Please have a look at some of our urls http://public.gatebee.ch/ http://www.2engineer.com h Mais
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Becoming energy efficient isn't as easy as turning off a light switch – OK, maybe it can be. However, to truly decrease energy consumption, you're going to have to make some conscious efforts in your daily routine. In the hour or two before you leave for work, consider the following ways to increase energy efficiency in the morning to help decrease your carbon footprint.
• Take a shorter, cooler shower
No one can resist a hot shower, but did you know water heating can account for 12 percent of your utility bill? Try cutting your shower time in half. A shorter shower will equal less energy usage, and in turn, can reduce your heating bill. If you lower the temperature on your water heater to 120oF, you could save around 3 percent off your bill as well.
• Don't let your water run
When you brush your teeth, it's a good idea to be diligent and take your time. It's not a good idea to let the water run the entire time, though. Only let the water run when you need it, and not when your toothbrush is nowhere near the faucet.
• Be mindful of outlets
If you blow dry your hair, use a curling iron, use an actual iron or anything that plugs into the wall, then be mindful of how long you have your device plugged in. It's ideal to use a power strip; that way when you're done with your morning routine, you can simply flip a single switch instead of unplugging many electronics. If you keep appliances plugged in, even if they're turned off, they could still be using small amounts of power that, if continuously plugged in, could eventually consume a great deal of energy.
• Open your blinds and switch to LEDs
If you have windows that allow light inside your home, use them to your advantage. Lighting takes up about 14% of utility bills, and by cutting down on the time spent with lights on, the less you'll end up paying at the end of the month. Natural light is perfect for getting dressed and cooking breakfast. For the rooms where you don't have a lot of sunlight, switch out your incandescent bulbs with CFLs or LEDs.
• Use the bathroom fan
After a shower you'll notice extra humidity or heat in your bathroom. Turn on the vent or fan in your bathroom to relieve the area of excess humidity that could cause a rise in temperature. By using a fan, you'll help maintain your home's temperature and keep your air conditioning from turning on when you don't want it to. Be sure to turn it off, however, before you leave the house.
There are tons of ways to cut back on energy consumption in the mornings, so feel free to do your own research and find even more ways to save energy. Take the first step and use less electricity. Only you can control your carbon footprint at home.


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Born out of love for fashion, Pixie Mood is a company that designs on-trend accessories that are at the same time vegan-friendly. With a keen eye for up and coming trends, we are quick to bring fresh designs inspired by the runway straight to those who love fashion.
Why Cruelty-free / Vegan-friendly?
The Pixie Mood team loves animals and believe that fashion would be even more awesome without harming any of our furry friends! Fashion is a form of self-expression, and Pixie Mood's mission is to offer a fashionable alternative for people to express themselves without harming any animals. We believe that there is always room for great fashion with compassion, for vegans and non-vegans alike!
Thank you for making the world beautiful by choosing cruelty-free products.
Our Style?
Pixie Mood is all about colours, fun patterns, and unique shapes and textures that will bring a smile to your face!
Vegan Leather
The type of vegan leather that we use is called Poly urethane (PU-leather), which is different from lower grade synthetic leathers such as vinyl or PVC. PU-leather has much less harmful impact on the planet than vinyl or PVC, it is a lot softer and does not crack in the harsh winter weather like other synthetic leathers would. Other than vegan leather, we are always on the hunt for new and innovative materials to be used in our designs.
Kelvin & Chloe – the couple behind Pixie Mood
Like most, the couple both worked at a 9 – 5 job before they started Pixie Mood. Chloe loves everything about fashion. Her love for art, colour, textiles has led her to pursue her dream of having her own handbag brand. She gathers ideas and design inspiration from around the world, from the unlikeliest of places, and put them into actuality. Kelvin, who graduated from Ryerson University with a Business Management major, has always dreamed of being an entrepreneur running his own company. After a couple years at their 9 -5 jobs, they took a leap of faith to bring each other's dream into reality. From then on, they have never looked back!


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Thamarai 25-01-2016 Tamil show special on Episode 362 of Thamarai Sun TV show of this day's Thamarai 25.01.16 Produced by Radaan Media view now Sun TV Serial Thamarai 25/01/16 Sun TV program Thamarai 25-01-16 Radaan Media Presents Thamarai January 25th 2016 Episode.
Source 1 – Click on the image below to watch. (Use Google Chrome or Firefox)
Source 2 – Click on the image below to watch.


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Free Inspiring Interview, Today, 4/7/09, 4pm PDT
- Dear Friends,
This is very inspirational.
The ideas discussed by Howard Martin, in my experience, have the greatest potential for personal and planetary transformation that I have yet found.
You can listen to a free interview with Howard Martin by my friend Jennifer McLean Today, Tuesday, April 7, 2009, 4pm Pacific Daylight Time.
There is an opportunity to ask questions.
Here is the webcast link:
http://instantTeleseminar.com/?eventid=6376890If you are interested in hearing the remaining free interviews, please click on this link to register:
Howard Martin is the author of The HeartMath Solution and the Executive Vice President of HeartMath.
HeartMath measures the rhythms and electromagnetic energies of the heart. The HeartMath Institute teaches individuals how to foster heart coherence to enhance their life.
The HeartMath Institute is part of the Global Coherence Initiative, which manages the research being done on individual heart coherence and its relationship with global level coherence.
Howard Martin cites research by Dean Radin which shows changes in the earth's electromagnetic field on and after September 11, 2001.
The HeartMath Institute's most recent endeavor is the Global Coherence Project, which is establishing a network of 100 centers around the world.
The Global Coherence Project will expand the HeartMath Institute's research to study the relationship between individuals changing their heart coherence and the earth's electromagnetic field.
In this interview, you will learn how you can break free from stress, maintain emotional clarity in the midst of chaos, raise levels of anti-aging hormones, and immediately lower stress hormones.
'The key to understanding our emotions is not in the brain, but in the heart.'
Howard Martinhttp://www.glcoherence.org/about-us/about.html
For an Introduction to the HeartMath Institute:
For more information about the HeartMath Institute:
For more information about the Global Coherence Initiative, go to:
For more information about the Global Coherence Project:
Howard Martin's call will be accessible, after it is connected, for 48 hours after the call by going to this link:
(be sure to refresh the page to access the link. If you are having problems with the audio, sometimes the cache in your browser needs to be cleared in order to hear it.)
This is part of a long series of interviews with leaders of transformation on the planet.
If you would like lifetime access to all the interviews in the series, please follow the links on the registration page to purchase:
http://tinyurl.com/healingmasters3To listen to a free audio recording of the interview until 4pm, April 9, 2009, please click on this link:www.healingwiththemasters.com/audio.htm
To register for remaining free interviews, please click on this link.
For lifetime access to the whole series of interviews, please follow the links from the registration page to purchase. Start with this link:
I hope that you enjoy the interview.
Happiness, Health and Abundance for All!
Many Blessings,
Pamela Melcher


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My unique gift is my ability to make personal growth not only sustainable, but deeply enriching, rewarding and fun. I have mentored with some amazing teachers, who have supported me to consistently look deeper into each situation or challenge with greater awareness along with the willingness to learn and grow through every opportunity.
After many years of personal growth and mentoring of others, I have found that breathing is a key component to holistic healing and transformation. Understanding and logic can only take one so far, until it becomes essential to use the immense intelligence of the body and conscious breath to carry us through limitations to new levels of conscious awareness and integration.


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In CPA firms, we often find that we have more people who want and need a mentor than we have qualified mentors to counsel them.
Should this stop the firm from having a successful mentoring program? No way. Try using Mentoring Circles where an experienced mentor leads discussion groups and guides several mentees at one time.
The old traditional way of mentoring has changed drastically from the days when the Baby Boomers were beginning their career.
Experiment with these ideas in your firm:
Old Rule: Mentors and mentees should have a lot in common. New Rule: The best matches are mis-matches.
Old Rule: Look for your mentor higher-up on the food chain. New Rule: A good mentor is anyone from whom you can learn.
Old Rule: Mentoring is one-on-one. New Rule: Mentoring works best when you mix and match.
Old Rule: Mentors pick their mentees. New Rule: Mentees pick their mentors.
Old Rule: You are either a mentor or a mentee. New Rule: Everyone needs mentors.


text: Radio personalities "Template:Infobox actor Graham William Walker (born 4 April 1963 in Dublin, Ireland) is an Irish... Graham Norton Pages in category "Radio personalities" This category contains only the following page. N Graham Norton Retrieved from "http://lgbt.wikia.com/wiki/Category:Radio_personalities?oldid=34105" Ad blocker interference detected! Wikia is a free-to-use site that makes money from advertising. We have a modified experience for viewers using ad blockers Wikia is not accessible if you've made further modifications. Remove the custom ad blocker rule(s) and the page will load as expected. Categories: Media Add category Cancel Save


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Would you voluntarily get tasered? These people did.
Somehow, photographer Patrick Hall got a bunch of willing people together who agreed to get tasered for his photo shoot. What's more, he got their significant others to pull the trigger.
He's either a super smooth talker with great persuasion skills or he got in touch with some real crazy, adventurous and brave bunch of people. Hall filmed them and the results, beautiful in a macabre way, will leave you cringing.
And oh, he wanted to record both of their reactions and so he did a longer version of the video as well. You can watch it here.


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- Description
Stylish chrome legs accent this contemporary futon and matching chair. Both quickly fold down to make a comfortable bed, or easily fold down the chair and arrange as a chaise.Includes
1 FutonDimensions
Sofa, 73 1/2" x 34" x 35 1/4"H
Bed, 73 1/2" x 47" x 19"H
Seat Ht, 19"
Seat Dp, 21.5"
More from this collection: Maybelle
- Additional Information
Additional Information
SKU 13701940 MPN CM2908 GTIN UPC 847289043874 Brand Furniture of America Collection Maybelle Assemble Length 73 1/2 Assemble Width 34 Assemble Height 35 1/4 Assembly Required Yes Material Fabric Color Chocolate Styles Contemporary Shipping Time 1-2 Weeks Free Shipping No
- Reviews
Disclaimer: Pictures displayed may include optional products not included in the price. Computer monitors often display color variations. Color swatches are shown if alternative colors are available. Please call us or email us if you have any questions!


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Hello, could anyone help me on the subject of making a gumpaste Champagne glass? I've looked under every search engine I could think of, including tutorials and comin up blank !! I just need to get a head start on what to do...........Help please !! Thanx, thanx thanx brendabaker
0 replies