In response to a year of persecution and the imminent passing of a law making the death sentence mandatory for all Muslim men who turn to Christ and life imprisonment for Muslim women who turn to Christ, Iranian church leaders are calling for prayer and fasting November 21 – 23rd 2008.
They know they have no influence in the courts of men – but they want to take their case to the courts of heaven.
And like Esther of old, the queen of Iran who told Mordecai to ask all the people of God to pray and fast for three days, so Iranian Christian leaders are asking the world-wide church to also set aside these three days for prayer and fasting.
If you are a prayer leader in your church, please contact other intercessors to be involved in these three days, and please approach your pastor to see if special prayers for Iran can be made at your church service on Sunday November 23rd.
The growing church in Iran is under attack. Since April there have been at least fifty three arrests of people whose only crime is their faith in Jesus Christ. The arrests are not localised, but have happened in all of Iran's major cities…Tehran, Mashhad, Isfahan, Shiraz, Kerman, and elsewhere. Sometimes people have been released the same day, others spent months in prison, some still remain behind bars. Many of them have had to pay exorbitant fees for bail and face frightening court cases. Some have suffered physically while in detention and it is believed that one elderly couple died as a result of being beaten up. These are only the arrests that get reported: it is likely there have been many more.
All of this has been happening against the ominous background of legislation going through the Iranian parliament that will make the death sentence mandatory for any man who leaves Islam and chooses another faith. Women will face life imprisonment for the same 'crime'. Click here to read more about this legislation.
Despite the persecution, the church in Iran continues to grow rapidly. The Word of God is reaching many in the country and many believers are determined to courageously share Christ with their countrymen. Christian leaders in Iran believe that the church will continue to grow very rapidly in the next five to ten years, such is the openness of Iranians to the Gospel.
Elam Ministries urges Christians, world wide to pray and fast on behalf of the church in Iran.
Pray against the law of apostasy. Pray that the severe mandatory punishments regarding apostasy in Iran's new penal code will not enter the statute book. Pray that many millions of Muslims will see the evil of this law and will hunger for spiritual truth and salvation.
April, Amol, Mazandaran: a Christian husband and his pregnant wife are arrested. The wife is released after three days, the husband not till the end of May and only when he had secured his bail with his home. He has to face charges in court.
May 11th, Shiraz: Homayon Gholamzadeh and his wife Fariba and Amir Hussein Anari, and his wife Fatemeh, were arrested at the airport and taken directly to jail. All were questioned about their faith and church involvement. The wives were released the same day, but Anari was not released till May 14th, and Gholamzadeh not till May 22nd. The same day Allaedin Hossein, his wife and three children were arrested, their home searched, and computers and books confiscated. All were released apart from the eldest son, Mujtaba Hussein, aged 21. He was kept in prison till June 3rd and then only released on $20,000 bail.
May 13th, Shiraz: Mahmood Matin and Arash Bandari, were arrested while walking in a park. Both were kept in solitary confinement till July 15th, when they were placed in a cell together.
May 31st, Tehran: Police arrest forty four year old Mohsen Namvar and confiscated his computer. Mohsen was in prison in 2007 when he was beaten so badly he could hardly walk. No reason was given for this second arrest. He was released on June 27th with high fever and shaking hands. He refuses to talk to his wife about his treatment. The family had to pay the security forces $43,000 for bail – and received no receipt. In early July they fled Iran as refugees.
June 3rd, Tehran: Christian couple, Tina Rad and Makan Arya were arrested and interrogated for holding Bible studies with Muslims. During their four day ordeal both were badly beaten up and the authorities threatened to put their four year old daughter into an institution. They had to raise a total of $50,000 to be released on bail.
July 12th, Tehran:. Mohsen Radfar arrested travelling to the city.
July 12th, Kerman: Twelve Christians are arrested at the airport on their way to a conference. While being questioned their homes are searched. They are released the same day.
July 17th, Isfahan: Sixteen Christians, including six women and two minors, arrested during a service. The elderly hosts of the meeting, Abbas Amiri and Sakineh Rahnama were so badly beaten that both later died: Abbas on July 30th, his wife on August 3rd.
Early August, Shiraz: Mahmood Matin Azad and Arash Basirat, imprisoned in Shiraz since May 13th, are formally charged with apostasy, which carries the death sentence.
August 8th, Kerman: A Christian couple, Dariush and Shireen, are arrested.
August 12th, Arak: Shahin Zanboori is arrested and suffered beatings while in prison as authorities attempted to find out the names of other believers. He was released on August 31st, but faces a court case.
Mid August, Mashad: A Christian, Iman Rashidi, is arrested.
August 21st, Mashad: Ramtin Soodmand, minister of the Evangelical Church, is imprisoned. Ramtin is the son of martyred Revd Hossein Soodmand who was hanged in 1990 for being an apostate from Islam. Ramtin's mother is blind.
September 22nd, Urumieh: Assyrian Evangelical Minister, Revd. S. Yadegar and another Christian man are arrested and held in prison charged with evangelizing.
September 23rd, Shiraz: All the charges against Mahmood Matin Azad and Arash Basirat are dropped and they are released.
September 28th, Urumieh: A Christian man, Sobhan, is arrested.
October 20th, Mashad: Fereshteh Dibaj and her husband Amir Montazami, who were arrested and held last year, are threatened again by the court that they could be imprisoned. Fereshteh Dibaj is the daughter of Mehdi Dibaj who was imprisoned for nine years for his Christian faith. He was sentenced to death for apostasy in 1993, but was released after international pressure, only to be murdered in the summer of 1994.
October 22nd, Mashad: Ramtin Soodmand freed.
This intimidation of Christians has been happening while parliament has been revising Iran's penal code whereby death for male converts will be mandatory. Articles 225-8 of the new code bluntly states that punishment for a male apostate is 'death' and for a female it is life imprisonment – unless she re-cants. In a similar way that Nazis argued over the definition of a Jew, so this code has special clauses for 'parental' and 'innate' apostates. The former have three days to recant; the latter none. Such details do nothing to hide the fundamental injustice of a law that seeks to ferociously punish its citizens for choosing their own religion.
Up to now the death sentence has been available as a punishment for apostasy from Islam in Iran, but individual judges could use their discretion. However the word used in this new legislation is 'hadd' which means this is a fixed punishment that cannot be changed, reduced, or annulled.
This proposed bill also introduces a new crime into Iran's statute book – 'establishing weblogs and sites promoting corruption, prostitution and apostasy' Those found guilty could be punished with death or the amputation of their arms and legs.
The new Penal Code was approved by the Iranian parliament by 196 – 7 votes on September 9th and is now being reviewed before it is sent back to parliament for another vote, and then to the Guardian Council for its final consent. It will then become law.
From the human perspective it is inevitable that this new penal code will become law, so threatening the lives not just of thousands of Christians from Muslim backgrounds, but any believer who wants to witness to the fact that Jesus Christ is the only Saviour, for this is 'promoting apostasy'.
Please start praying now, and put November 21st – 23rd in your diaries for praying and fasting.


text:
Department of Econometrics /
Sustainability (Switzerland) /
D.E. Allen (David) and M.J. McAleer (Michael)
Fake news and propaganda: Trump's democratic America and Hitler's national socialist (Nazi) Germany
Sustainability (Switzerland) , Volume 11 - Issue 19
This paper features an analysis of President Trump's two State of the Union addresses, which are analysed by means of various data mining techniques, including sentiment analysis. The intention is to explore the contents and sentiments of the messages contained, the degree to which they differ, and their potential implications for the national mood and state of the economy. We also apply Zipf and Mandelbrot's power law to assess the degree to which they differ from common language patterns. To provide a contrast and some parallel context, analyses are also undertaken of President Obama's last State of the Union address and Hitler's 1933 Berlin Proclamation. The structure of these four political addresses is remarkably similar. The three US Presidential speeches are more positive emotionally than is Hitler's relatively shorter address, which is characterised by a prevalence of negative emotions. Hitler's speech deviates the most from common speech, but all three appear to target their audiences by use of non-complex speech. However, it should be said that the economic circumstances in contemporary America and Germany in the 1930s are vastly different.
Keywords Emotional valence, Sentiment analysis, Text mining, Word cloud
JEL Econometric and Statistical Methods: Other (jel C19), Miscellaneous Mathematical Tools (jel C65), Analysis of Collective Decision-Making: Other (jel D79)
Persistent URL dx.doi.org/10.3390/su11195181, hdl.handle.net/1765/120380
Journal Sustainability (Switzerland)
Allen, D.E, & McAleer, M.J. (2019). Fake news and propaganda: Trump's democratic America and Hitler's national socialist (Nazi) Germany. Sustainability (Switzerland), 11(19). doi:10.3390/su11195181

redpajama_set_name: RedPajamaCommonCrawl


text:
Q: jQuery select all checkboxes within table row I have a table with multiple checkboxes in each row, and I created some jQuery to check all the chekboxes on a certain row by clicking another checkbox.
$('table').on('change', '.selectAll', function(e) {
      if(this.checked) {
          $(e.target).closest('tr').find(".aCheckbox").each(function() {
                $(this).attr('checked', true);
          });
      }
      else {
        $(e.target).closest('tr').find(".aCheckbox").each(function() {
                $(this).attr('checked', false);
          });
      }
});

But it will only work twice (i.e: you can check all the boxes, uncheck them, but then after that nothing will happen when I try to check them again)
When I'm clicking my .selectAll checkbox it is changing the input's html to checked='checked' successfully but no change is visible.
What is the problem here?
Thanks

A: You need to change the checked property, not the checked attribute. You also don't need to iterate, so I simplified the function for you:
$('table').on('change', '.selectAll', function (e) {
    $(this).closest('tr').find(".aCheckbox").prop('checked', this.checked);
});

redpajama_set_name: RedPajamaStackExchange


The third edition of AUSINDEX, the joint Naval exercises between India and Australia has started from Visakhapatnam on Tuesday with the arrival of HMAS Canberra, a landing helicopter dock; HMAS New Castle and HMAS Paramatta, both frigates; HMAS Collins, a conventional submarine and HMAS Success, a Durance-class multi-product replenishment oiler.
The First edition was held in September 2015 at Visakhapatnam and the second in Australia in June 2017, with the participation of ships of the Eastern Fleet of the Indian Navy and the ships, submarines belonging to Royal Australian Navy.
The main motive of this exercise is to strengthening the mutual cooperation and interoperability between the Indian Navy and the Royal Australian Navy, providing opportunities for interaction and exchange of professional views between the personnel of the two armed forces. A sign of the strengthening of bilateral and defence cooperation between the two countries as envisaged in the Framework for Security Cooperation (FSC) announced by the then Prime Ministers of Indian and Australia in 2014.
The third edition would involve exercises in all three dimensions with a focus on anti-submarine warfare (ASW). The number of units being fielded by both navies in the exercise is the highest till date. The increased scale of participation signifies the importance attached to the exercise by both countries while the enhanced complexity is indicative of the interoperability between the two navies. The exercise underscores India's vision of the SAGAR (Security and Growth for All in the Region) and shared objectives of the two countries towards ensuring good order in the maritime domain and solidarity with friendly and harmonious countries.


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text:
Tryphosella lowryi is een vlokreeftensoort uit de familie van de Lysianassidae. De wetenschappelijke naam van de soort is voor het eerst geldig gepubliceerd in 2006 door Kilgallen, Myers & McGrath.

Tryphosidae

redpajama_set_name: RedPajamaWikipedia


Only a few parts of wreckage have been found, such as this piece of a wing flap that washed up in the Indian Ocean.
FIVE witnesses could hold the key to finding the exact spot where missing flight MH370 crashed, an investigator claims.
Noel O'Gara, who has spent four years probing the world's greatest aviation mystery, believes the jet was shot down by mistake by the Malaysian military.
The Irish private sleuth has identified crucial accounts from people who say the saw the doomed plane's final moments, according to the The Daily Star Online.
He says this information can be used to locate the missing Boeing 777 - unless the Malaysian Government has already removed every trace to cover up their blunder.
"Most likely, MH370 is still lying on the sea bed in that area," Mr O'Gara said.
"Unless the Malaysian Government recovered it later.
"They would know exactly or within a few miles of where it had come down."
One of the witness accounts is said to come from New Zealand oil worker Mike McKay, who says he saw a plane on fire over his rig near Vietnam.
The aircraft was "ascending rapidly in the struggle for control of the plane" and appeared to fall again, Mr McKay claimed.
Malaysia Airlines flight MH370 took a mystery left turn an hour after takeoff, radar data showed. Marked here is the spot where a fisherman claims he saw it crash in the Malacca Strait.
Latife Dalelah was a passenger on another flight when she saw what she believed was a plane on the surface of the water "in the crucial place and at the crucial time".
The third witness is Katherine Tee, an English sailor who told the official Australian search organisation she saw a burning plane on her way to Phuket in Thailand.
"Tee saw a plane go down and two smaller planes high overhead heading off in that area and at that time," Mr O'Gara said.
It's claimed this could be evidence fighter jets downed the Boeing 777 - perhaps because of fears it had been hijacked.
Mr O'Gara's fourth and fifth witnesses are two Malaysian fishermen who say they saw the plane come down off Kota Bharu.
The Malaysia Airlines Boeing 777 vanished nearly five years ago with 239 on board.
Mr O'Gara claims the Malaysian Government may have covered up what happened and secretly removed the evidence from the sea bed.
Only small pieces of wreckage have been found since the Malaysia Airlines jet vanished over the Malacca Strait with 239 on board in March 2014.
It was heading from Kuala Lumpur to Beijing when radar showed it took an unexplained left turn back across the Malay Peninsula.
Satellite pings suggested it kept flying for another seven hours, leading official search teams to concentrate their efforts 1600 kilometres west of Australia.
A detailed sonar scan of the ocean floor found no trace it was ever there, giving rise to a raft of rival theories.
One aviation expert said it could have been brought down by a stowaway who stormed the cockpit in a 9/11-style hijacking.
Last week an amateur sleuth claimed he had evidence it landed in the jungle in Cambodia.
Fisherman Rusli Khusmin said he saw the crash and recorded the spot on a GPS device.


., the electric-car maker backed by , plans to list its battery business by 2022 to raise funds to expand as the global auto industry transitions away from the traditional combustion engine.
The listing will occur sometime by the end of 2022 and the company hasn't decided yet where the shares will be trading, Chairman Wang Chuanfu said in an interview with Bloomberg News Wednesday at its headquarters in Shenzhen.
BYD, which makes batteries for automobiles and mobile phones, is in the process of spinning off its vehicle-battery operations into a separate company before listing. It isn't clear yet whether the IPO will be for the car-battery business alone, or will also include other units.


> We tried 2 different sets of headphones.
> It's all static except for just barely hearing the sound from the .mp3 file.
> You can barely tell that there is a file playing, but you know it is.
> By the way, I wrote to the EBay seller with no response.
> I'm going to take Rocker's advise and start a dispute I guess.
> I found Iriver customer service info with google. I'll start that tomorrow.
> Thanks for your response's.
> >> hooked up to any computer when it was formatted.
> > I didn't know the iriver-firmware was able to do it.
> > firmware since it is not able to find any rockbox on the hard disk.
> > damaged and such ?
> > Would be a bummer having bought a faultive device.
> This is partially downloaded message.
> Choose 'Download' from menu to download entire message.
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Registration for South Sound Baseball is closed.
The Easton Ghost X 30/20 YBB18GX10 and LL18GHX 30/20 2 5/8" has been decertified by USA Baseball and is no longer an approved bat under the USABat Standard.
Our organization is an all-volunteer program that strives to promote a strong sense of community and self, while members have fun teaching and learning the fundamental skills of baseball. We assist the rookie player or the highly skilled, competitive player to develop into a good ball player and citizen. We strive to treat every player fairly and equally regardless of playing ability. We are proud of the fact that many players have competed in post high school baseball, including some who have gone on to play Major League Baseball as well as players who have returned to the program to pass on their knowledge and experience to the next generation of players.


Today I want to share 5 teas which will soon be making their way to The Tea Makers of London site. They're all Ceylon teas from tea gardens throughout Sri Lanka. Each one has a slightly different taste and richness depending on the growing conditions. I've never really taken the time to really look into a selection of teas like this. It's been interesting to learn about regions and how the location of the tea gardens and the surrounding climate really alters the tea.
You can find my cute tea strainer here.
In the foothills of Adam's Peak you'll find Maskeliya. Adam's Peak is a sacred mountain where people from all faiths climb to the top for worship. Maskeliya is surrounded by dense forest, lakes and mountains. It's a very scenic part of Sri Lanka. A quick Google had me longing to visit.
Ceylon Maskeliya BOP is a very dark and rich tea. I didn't find that there was much of a scent to it. It's a lovely and warming tea which works well black or with a little milk and honey.
Nuwara Eliya is also known as Little England because of the cooler weather, architecture and golf courses. It's one of the most popular tea-growing districts of Sri Lanka. They receive a moderate rainfall which makes for a particularly fine tea.
Ceylon Nuwara Eliya FBOP has more of a smokey scent that the other teas, it's quite unusual. It's generally a much lighter tea in colour and flavour. I enjoyed this tea black as it was the best way to really detect the very slight fruity flavour.
In the Central Province of Sri Lanka you'll find the Kenilworth Tea Garden. It's named after Kenilworth Castle in Warwickshire, England. The Kenilworth Tea Garden is renowned for making quality teas. The Tea Makers of London have selected this BOP which has a lovely coppery colour and a very smooth flavour.
Ceylon Kenilworth BOP is suggested to be a good alternative to breakfast tea. I personally found that the milk overpowered it a little and really enjoyed it black.
Bogawantalawa is a valley in the Central Province of Sri Lanka with 11 gardens. It's known locally as the 'Golden Valley'. Tea has been grown in this area for over 140 years. It's another stunning part of Sri Lanka, it seems most of these tea-growing areas are.
When I first opened up the packet I could detect a slight hint of rose. The tea is very fine and looked like a beautiful snow globe as it slipped through the tea strainer. Despite the fine leaves it's a dark and strong tea – one of my favourites.
Kandyan tea gardens are dotted across the mountains in Sri Lanka's central province. Many of the tea estates in Kandy are clustered together in valleys which shelters them from fierce winds. The flavour of the teas from the Kandyan valley change depending on the altitude of which the tea bushes are grown. The best teas from Kandy are harvested in the first quarter of the year when the weather is much more dry.
This tea has a mild and sweet scent and I could easily pick out notes of orange. It has a subtle flavour and worked well as a black tea in the afternoon.
Leave a comment below and let me know what types of teas you've been drinking recently?
Shop Formal Gowns, Leather Watches, Black Tees, White Lace Dresses and more. Get this widget.


text:
News, Music, Arts, and Culture
Jazz After Hours
RME Radio Hour
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Serenade/Sunday Concerts
Full Schedule - 90.3 FM
Full Schedule -105.7 FM/HD2
Heartland Politics
Rock Island Lines
Love Girls: The Podcast
Talking Art
Wellness Wake Up Call
River Way Stories
Midwest Week
The Great Quad Cities Listen
WVIK Artist Mug
Grant Funders
APRIS
Intelligent Conversations
WVIK Events
WVIK App
Live Stream Information
Public File & Station Governance
Host, Talking Art
Carolyn Martin joined WVIK as a host of Talking Art in September of 2017. A long-time fan of NPR programming with a love of storytelling and all art forms, she is thrilled to have the opportunity to speak with creative people about their work in the Quad Cities region.
Retiring as an Obstetrician/Gynecologist physician after nearly 25 years of practice in Davenport, she was looking for a meaningful way to navigate retirement. Thanks to Jay Pearce, the General Manager of WVIK, who despite her lack of previous radio experience was either insightful enough or crazy enough to let her embark on this adventure, she is giving voice to artists who beautify our community and make this a better place to live. She also gets more sleep now and doesn't have to work on weekends or holidays!
In addition to her volunteer work with WVIK, Carolyn is a board member of Quad City Arts, the foundation board of Quad Cities Cultural Trust, and Vera French Community Mental Health Center.
She lives in Bettendorf, Iowa with her husband Joseph.
Carolyn would like to recognize the late Bruce Carter, whose years of interviewing artists for WVIK on his program Art Talks inspired her to continue in his legacy.
'Talking Art' with Marion Meginnis
By Carolyn Martin • Nov 16, 2020
The Hamburg Historic District in Davenport, IA, affectionately known as the "Gold Coast," contains some of the widest variety of architectural styles in the Quad Cities. Built primarily by German immigrants in the 19th and early 20th century, the district lies between 5th and 9th Streets (south to north) and between Ripley and Vine (east to west).
'Talking Art' with Josh Graves of the Underground Economy
By Carolyn Martin • Nov 5, 2020
Situated on the second floor of the River Music Experience building in Davenport, IA, is The Underground Economy, a full-scale media and production house which bridges the gap between art and entrepreneurship. Containing a podcast studio, a recording studio, and a content editing station, the space is available to creatives via a variety of membership options, with the goal to become an incubator for the arts within the Quad Cities.
'Talking Art' with a local high school string quartet about "Beatles vs. Stones"
By Carolyn Martin • Oct 16, 2020
Justin Teitle
The national touring show Beatles vs. Stones - A Musical Showdown is coming to the Adler Theatre in Davenport on October 20, 2020. The tribute bands Satisfaction and Abbey Road, wearing period clothing and playing vintage instruments, will be accompanied onstage during seven of their songs by a string quartet composed of local high school musicians.
'Talking Art' with novelist John Shallman
By Carolyn Martin • Sep 28, 2020
Rock Island native John Shallman recently published his first novel, Return from Siberia.
'Talking Art' with Cecile Houel
The acclaimed artist Cecile Houel works in Ft. Madison, IA where she has been creating beautiful, realistic portraits of Nobel Peace Prize Laureates. Twenty of her large 4' x 4' works are currently on display in a variety of locations throughout the Quad Cities. Ten are at the Beréskin Gallery & Art Academy in Bettendorf as part of their "Peace Starts Within" exhibit; six are on display at Quad City Arts' airport gallery as part of their "A Portrait of Remarkable Women" show; and two portraits are at both the German American Heritage Center and in the River Center/Adler display cases. The portraits will be up through the end of October.
'Talking Art' with Hannah Holman about the Quad City Music Academy
The Quad City Music Academy is a new school for students pursuing their musical education in cello, violin, viola, or bass. Private lessons are offered with a variety of accomplished professional musicians, and specialized courses and workshops are also available. The Academy is the first of its kind in the Quad Cities. Due to the Covid-19 pandemic, the fall 2020 semester will be held online.
'Talking Art' with Gaye Shannon Burnett & Jonathan Burnett about Racial Inequity in the Arts
By Carolyn Martin • Jul 20, 2020
Racial inequity in the arts is well documented across all genres, from theatre, to film, literature, and the visual arts. The public outcry and protests that have occurred this year following the death of George Floyd and countless other people of color have resulted in a strong public reckoning regarding our own implicit biases regarding race. Those biases, in combination with existing economic disparities and entrenched institutional hierarchies affect what we see and view on screen, on stage, in museums, and read in books.
'Talking Art' with Alma Gaul about the late sculptor Beverly Pepper
By Carolyn Martin • Jun 11, 2020
Photo by Curtis Bill Pepper
The innovative sculptor Beverly Pepper was a resident artist with the Visiting Artist program in the Quad Cities in 1981. Over a dozen works were created during her time here. Four of them remain in the Quad Cities, of which three are available for the general public to view. Her sculptures, many of them monumental in size, have been exhibited in major museums throughout the world including the Metropolitan Museum of Art, the Brooklyn Museum, the Museum of Fine Arts in Boston, the Centre Pompidou in Paris, the Barcelona Museum of Contemporary Art, and in many locations throughout Italy where she resided for many decades.
Talking Art with Samantha Pauly
By Carolyn Martin • Jun 4, 2020
Originally from the Quad Cities, Samantha Pauly is an actor best known for originating the role of Katherine Howard in SIX the Musical on Broadway, and for her portrayal of Eva Perón in Jamie Lloyd's critically acclaimed London revival of Evita.
Talking Art with Amelia Bay
By Carolyn Martin • Apr 22, 2020
The freelance hairstylist, Amelia Bay, is originally from the Quad Cities and now works in television and on Broadway. She was in the midst of filming for the TV show Law & Order: Special Victims Unit when the entertainment industry was shuttered due to the COVID-19 pandemic.
© 2021 WVIK


MG Creations starts work with Curtiss Wright Nuclear outage & fuel management solutions division.
Curtiss Wright Nuclear is a worldwide leader for custom designed products and services for safety and critical path outages in nuclear power plants. MG Creations role is to develop a strategy and provide enhance performance for online target marketing.


It's almost time. Jeremy Puglia is 4 days away from his Bellator MMA fight at The Nassau Coliseum! We're so looking forward to this fight. We like watching Jeremy fight anywhere but this Saturday Jeremy gets to fight in Long Island's premier professional sports arena. We have had the honor and pleasure of providing Jeremy's strength and conditioning training for this fight and several others. We have, literally and figuratively, had a ringside seat to Jeremy's growth as a fighter and development as an athlete. We have witnessed his hard work ethic, an ethic that we have not seen matched by too many athletes. Jeremy is quiet, not very expressive, and he doesn't get rattled. In the cage is a different story. That's when Jeremy becomes very expressive, not verbally, but physically. His ring persona belies his real-life persona. It's nearly shocking but oh so entertaining if you're a fight fan. There's one thing that I and all of Jeremy's coaches (Alex Vamos from Vamos Brazilian Jiu-Jitsu and MMA, Joe Scioli from Vamos BJJ and MMA and Rick Schaefer from No Limits Kickboxing & Fitness) know that everyone else will soon find out: Jeremy is ready and prepared to do battle. He is prepared to win. What we are looking forward to most is watching Jeremy make all the hard work and long hours of training pay off in the cage. Good luck Jeremy!


Lunch and Learn is a monthly (September to June) lunch gathering in which individuals bring their own lunch and desert is provided. Lunch and Learn meets from 11:30am-1:00pm usually on the third Thursday. Along with lunch there is always an interesting speaker. Come join us! The schedule is shown in the document below. You can make reservations below the schedule or by calling the church office, 248-644-2040.
Click here for the schedule for 2019!


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Franchise Awards 2020
Franchise Awards 2020 9 Dec20407 Integrating the best in web, social and print media marketing, Towne Post Network embraces the vast nature of publishing to pioneer the future of community magazines. Driven by a mission 'to be relevant and engaging throughout the month, not just the day they arrive in mailboxes', the Towne Post franchise has created an online community that complements its print magazines. We find out more about the Towne Post journey so far. Headquartered in Fishers, Indiana, with eighteen franchised territories across the state and into Kentucky, Towne Post Network is a hyper-local community magazine franchise system that is dedicated to spreading 'good news' through monthly print magazines, digital platforms, and social media channels. Integrating the three primary media channels together across local communities, Towne Post is disrupting the magazine industry through a franchise system unlike any other. 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Its an exciting move that will see current sales strategies of selling print and backing into digital social switched in a progressive approach that is typical of Tom and the Towne Post team. Never ones to shy away from risky concepts, the firm is constantly trying out new ideas, which don't always necessarily work but are always excellent learning experiences for future innovation. Ultimately, the forward-thinking approach of Towne Post is driven by a genuine desire to serve its franchisees effectively. Even before the pandemic, Zoom calls were a regular occurrence between Towne Post and its contingents, maintaining open channels of communication for developments, promotions and feedback. 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Contact: Tom Britt Website: https://townepost.com/ Headquartered in Fishers, Indiana, with eighteen franchised territories across the state and into Kentucky, Towne Post Network is a hyper-local community magazine franchise system that is dedicated to spreading 'good news' through monthly print magazines, digital platforms, and social media channels.
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Coming to the completion of my firm's own first holiday home, I am creating a series of some of the homes that inspire me.
Holiday homes are the place where clients want to play a little. There's less pressure on domestic bliss and more freedom to explore messy ways of living. And there is almost always an automatic conversation about how the interior of the house works with the land, with nature. Of course, the larger conversation for us all is WHY AREN'T ALL HOUSES CASUAL AND ABOUT CONTEMPLATION OF THE LAND. I'll leave that for another time. For now just enjoy Christensen & Co Architects holiday home in Asserbo, Denmark. The simple shape, canted roof/ceiling, clapboard ceiling, deep overhang, and big deck. We don't claim to be original.


Adrian Rybicki and Laura Palmer.
An enterprising Melton man has used his enthusiasm for dogs to inspire the creation of a new business.
Adrian Rybicki has set up Build a Bond Dog Training and will hold regular classes at Melton's Cattle Market, in Scalford Road.
He also offers training advice on a one-to-one basis around the Melton area.
He said: "I have been working with dogs for more than 10 years and have worked with a variety dogs and owners and know most of the common behavioural problems develop due to lack of education or aversive training methods.
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text:
Judgment ESRB Rating Hints at Rewards for Drinking and Bare Bottoms
Brianna ReevesFriday, February 15, 2019
In news surprising no one, the ESRB has rated Sega's Judgment, formally known as Project Judge, with an "M" for Mature. As expected, the newest title from the Yakuza studio features violence, foul language, and the like. Specifically, the ESRB's content descriptors list the following as the reasons for Judgment's "M" rating: "Blood, Intense Violence, Partial Nudity, Sexual Content, Strong Language, Use of Alcohol." The alcohol and sexual content descriptors are most interesting, especially considering how the ESRB's summary depicts their placement in the game.
While exploring Kamurocho, Japan, players will be able to wander into bars for alcoholic beverages. When doing so, experience points are rewarded. Naturally, too much alcohol results in inebriation, which causes the player character's movement and perception to become impaired.
On the sexual content side of things, the ESRB noted that a few situations in the game explore sexual themes. For instance, players will see a man groping a woman. That's in addition to another gentleman being depicted bare-bottomed. Spicy stuff, indeed.
The ESRB's complete ratings summary can be read in the text featured below.
This is an action game in which players assume the role of a detective (Takayuki Yagami) searching for a serial killer in the town of Kamurocho, Japan. From a third-person perspective, players explore the town, interact with characters, and engage in fights with human enemies (e.g., thugs, yakuza). Characters mostly punch and kick each other until opponents' life meters have drained; players can also use melee weapons (e.g., bats, bicycles, street signs) to inflict heavier damage. Some sequences depict slow-motion pummeling and enemies' deaths, accompanied by large blood-splatter effects.
Cutscenes also depict intense acts of violence: a captive shot in the head; characters beaten until severely bloody; a man repeatedly shot by a crowd; A handful of missions/environments contain sexual themes and content: a man groping a woman's buttocks; a clerk (Men's Entertainment store) asking, "Are you ready to witness the honkiest hooter experience you've ever had…?"; one mission depicts a man with his buttocks fully exposed. During the course of the game, players' character can enter bars/restaurants and drink alcohol, which is rewarded in the form of experience points; players' character has an alcohol-tolerance gauge, resulting in impaired movement and/or access to drunken attacks. The words "f**k," "sh*t," and "a*shole" appear in the dialogue.
Judgment, named Judge Eyes in Japan, hit Japan's store shelves in early December 2018. Prior to its launch, a couple of demos were released, and allowed players to transfer their save progress to the full game. Whether or not Western audiences will receive similar treatment remains to be seen.
Judgment will hit the PlayStation 4 in North America and Europe on an unspecified date in summer 2019.
[Source: ESRB]
Tags: Judgment, Ryu Ga Gotoku Studio, Sega


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The Centre for History in Public Health (CHiPH) was established in 2003, with its origins in the AIDS Social History Programme at LSHTM in the late 1980s. Its location within a multidisciplinary public health institution is unique and keeps it firmly in the forefront of historical research into public health and health services. Historical understanding is of central relevance to an understanding of public health in the present. Current developments cannot be understood without a knowledge of the past.
The Centre reaches across the School in all its activities and many are conducted jointly with other Centres in the School. We are for instance, closely involved in the work of the Antimicrobial Resistance Centre and are building links with new groups such as the MRC Unit in The Gambia.
The Centre has a core team of researchers who span the School Faculties and a wide ranging group of members together with PhD students and honorary staff from an international range of institutions.
The Centre attracts research funding from a number of providers, with the Wellcome Trust preeminent among them.
Our research covers both public health and health services within high, middle and low income countries. Key programmes currently under way include Dr Alex Mold's Investigator Award Placing the Public in Public Health and Prof Martin Gorsky's Investigator Award Health Systems in History: Ideas, Comparisons, Policies.
Our teaching is both to in-house Masters students and on the distance learning programme. A free online course (MOOC) on the history of public health in post-war Britain, is now also available and runs three times a year.
We have an active programme of public engagement with a variety of walks, films and seminars available to staff students and the general public. Policy engagement is part of this activity and we utilise our location in a leading School of public health to interact with policy makers.
The Centre currently holds two Medical Humanities Investigator Awards from the Wellcome Trust. We have also held a programme grant and two five year awards from the Wellcome Trust, along with a variety of other awards, including University Awards, Research Fellowships and small grants. We are also supported by the Institutional Strategic Support Fund (ISSF).
Other funding has come from, among others, the Economic and Social Research Council; Alcohol Research UK; the Health Protection Agency; NICE; the Department of Health and the EU.


text:
package monitorx.controller.api;

import monitorx.domain.Node;
import monitorx.plugins.Status;
import monitorx.service.NodeService;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.PathVariable;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RequestMethod;
import org.springframework.web.bind.annotation.RestController;

@RestController
@RequestMapping("/api/status")
public class StatusController {

    Logger logger = LoggerFactory.getLogger(getClass());

    @Autowired
    NodeService nodeService;

    @RequestMapping(value = "/{node}/", method = RequestMethod.GET)
    public String queryStatus(@PathVariable("node") String nodeCode) {
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        if (node == null) {
            return "Invalid node";
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        Status nodeStatus = node.getStatus();
        if (nodeStatus != null) {
            status = nodeStatus.getStatus();
        }
        return status;
    }
}

redpajama_set_name: RedPajamaGithub


text:
19 December 2018 / Community
Using Sentence Embeddings to Automate Customer Support, Part One
Most of your company's customer support questions have already been asked and answered.
You're not alone, either. Amazon recently reported that up to 70% of their customer support responses were directly related to previous support answers.
But there's hope yet — neural networks can be trained to identify semantic similarity among text, which you can directly apply to your customer support workflow. Imagine this:
Introducing your new AI-assisted customer support workflow
In this two-part blog post, we'll develop a customer support workflow that can respond to incoming queries with a group of similar questions, making things a bit easier for your customer support agents.
Along the way, we'll be diving headfirst into the world of embeddings. This post will introduce basic embedding concepts, including one-hot encodings and word embeddings. The second post will dig into the more recent concept of Universal Sentence Embeddings (USE) — and that's also where we'll put it all together with our demo customer support project.
Ready? Set. Embed.
A primer on embeddings
A core part of the deep learning approach to Natural Language Processing (NLP) tasks is the concept of an embedding.
In the context of NLP, when we're talking about embeddings, what we are really talking about is vectors. And what's a vector, Victor? A vector is just a set of real numbers:
# v = [v1, v2, v3, .... ,vn]
# Where v1...vn are the real numbers or components of vector v
# For example:
v = [1, 3, 100, -30]
Importantly, we can use this set of real numbers to represent objects and phenomena in the world – such as a word or a sentence or even classical music.
What makes vectors different from a single real number is that they can also have a direction, which is a convenient feature that we'll exploit later on, when we start to identify similar vectors.
Why then have a different word for vector and embedding?
Well, an embedding refers to something that's been translated into a vector. This numerical representation as an array of numbers is useful because it facilitates a wide variety of mathematical operations.
For example, once we've created an embedding, we can locate this vector in something called a vector space. A vector space may sound like a difficult concept to grasp, but it's simply a method to locate points in space. Here is an example:
Vector spaces help us identify similar patterns more easily
In our illustration above, we're plotting four points that represent four different two dimensional (2D) vectors along two dimensions. This vector space probably looks quite familiar to you – it resembles the traditional Cartesian X-Y plane.
Visualizing embeddings in a vector space helps us identify related entities. Let me explain. Let's assume that the vectors on the graph: P, Q, U and V each represent different sentence embeddings. We can easily see that Q, U and V are closely clustered together, whereas P is in an entirely different quadrant.
Notice that Q, U, V are clustered together, whereas P stands alone.
This simple form of visual clustering can be used to identify patterns and similar entities when we encode something as an embedding.
This approach does become more difficult at higher dimensions, but there are techniques which we can use to reduce the dimensions to 2 or 3 dimensions so that it becomes easier to identify these aspects.
Thus, embeddings facilitate our ability to perform mathematical operations on non-numeric things – and thereby enabled much of NLP.
But how we make an embedding? How many dimensions do we need? And how do we set the values for each dimension?
Excellent questions. Let's work through a simple example together, using a reduced vocabulary of only four words: king, queen, man, woman.
One-hot encoding: our first embedding technique
To recap, we want to create an embedding for each of the four words in our vocabulary – that is, we want to represent each word as a unique vector.
We'll use the technique called "one hot" encoding to embed our words into vectors. With one hot encoding, we'll identify a unique word in our vocabulary via one dimension (also known as a feature) of a vector. The size of each vector will be the total number of entities in our vocabulary.
Let's take a look at a "one hot" encoding of our four-word reduced vocabulary:
King dimension 1 0 0 0
Queen dimension 0 1 0 0
Man dimension 0 0 1 0
Woman dimension 0 0 0 1
Each column is an embedding, and each embedding has four dimensions (represented by the rows in this grid). You'll notice that each embedding only has one dimension that contains a 1 – the rest of its dimensions are 0.
Using the word King, you'll see that it has a 1 for the"King dimension" and a 0 for the rest. We can now use the vector [1,0,0,0] to in place of the word King.
We should also be able to see that we can expand this approach to any number of words by simply adding a new dimension for each new word in our vocabulary.
King dimension 1 0 0 0 0
Queen dimension 0 1 0 0 0
Man dimension 0 0 1 0 0
Woman dimension 0 0 0 1 0
Joker dimension 0 0 0 0 1
However, even without a deep understanding of vectors, we can probably already see see that this approach is wasteful. There will be lots of 0's in our embeddings and the dimensionality will be very large. To use a more technical term in the industry, our embeddings will be very "sparsely" populated.
More importantly, our "one-hot" encoded embeddings tell us nothing about the relationships between the words in our reduced vocabulary set
As humans, we can easily discern that there is some connection between these words. "King" and "Queen" are both royal terms. "Man" and "Woman" are gender terms. But there is also a relationship between these pairs of terms. A "King" is traditionally associated with the word "Man" and a "Queen" is often associated with the word "Woman." Our one-hot encoding captures none of this relationship, however.
Visually representing embeddings
The easiest way to see these relationships is visually. In the previous section, our embeddings were only two dimensions in size, so it was easy to visually inspect them in a 2D vector space. But now we have four dimensional embeddings, so visual inspection becomes a bit more difficult. In the real world, we'll be dealing with hundreds of dimensions for our embeddings, so it's important to know how we can represent these visually in reduced dimensions.
To do this, we'll use a technique called Principal Component Analysis (PCA).
PCA is a way to identify the key information carrying parts of your embedding. It is trying to find out what is different and unique about each embedding, and will discard anything they have in common. PCA is a dimensional reduction technique (there are others such as T-SNE) which is used to highlight the important information in an embedding. We could spend much more time on PCA, but, for now, it is enough to just understand it is something we can use to reduce the dimensions of our embeddings.
Here's how we can plot our vocabulary using PCA using some basic Python machine learning libraries:
# Import the libraries
# Use PCA to reduce the dimensions of the embedding
def pca_transform(arr1, arr2, arr3, arr4, dim):
vectors = np.vstack((arr1, arr2, arr3, arr4))
# Set the number of dimensions PCA will reduce to
pca = PCA(n_components=dim)
pca.fit(vectors)
new_pca = pca.transform(vectors)
print("original shape:   ", vectors.shape)
print("transformed shape:", new_pca.shape)
return(new_pca)
# Draw a 2d graph with the new dimensions
def two_d_graph(reduced_dims):
colors = ("red", "green", "blue", "orange")
groups = ("King", "Queen", "Man", "Woman")
# Create plot
fig = plt.figure()
ax = fig.gca()
for data, color, group in zip(reduced_dims, colors, groups):
x, y = data
ax.scatter(x, y, alpha=0.8, c=color, edgecolors='none', s=30, label=group)
plt.title('Reduced vocab set')
plt.legend(loc=1)
# Transform the 4 dimensions to 2 via PCA
def vectors(a, b, c, d):
emba = np.array(a)
embb = np.array(b)
embc = np.array(c)
embd = np.array(d)
new_dim = pca_transform(emba, embb, embc, embd, 2)
two_d_graph(new_dim)
vectors([1,0,0,0], [0,1,0,0], [0,0,1,0], [0,0,0,1])
Our reduced vocabulary does not appear to have any clustering
If you're struggling to find any clustering in this chart, that's totally expected! None of the points are clearly located together in terms of the other points. And this makes sense, if you think about it. Our embeddings carry no information about how words relate to each other. Since we can just keep arbitrarily adding dimensions for new words in vocabulary, there's nothing to tell us that one is closer to the other.
Nevertheless, "one hot" encoding is a valid embedding technique, since we've found a way to represent a word as a vector. But, clearly, we want to do more – and capture some of the connection between the words in our embeddings.
It's a useful exercise now to think about another set of words where one-hot encoding wouldn't capture some important context. Take a minute and think about it.
Okay, got one? Here's mine:
Can you see the connection? "Dublin", "London" and "Washington D.C" are all in the "set" of capital cities, but they are also related to their respective countries. If we one-hot encode these all of this context will be lost.
We need to find some way to capture this context, and that is exactly what was achieved in 2013 with word embeddings.
Word embeddings: the power of context
Word2vec burst onto the scene in 2013 and entirely changed the NLP landscape, demonstrating that deep learning methods could yield incredible results when applied to NLP tasks such as translation, classification, and semantic parsing.
Word2vec, and similar approaches such as GloVe, showed that vector representations of words could be used to discover semantic meaning without requiring domain specific knowledge.
The key to these advances was finding a way to capture contextual information within an embedding. As we've seen, one-hot encoding makes it difficult to understand the relationship between words.
The British linguist J.R Firth believed that we could discover the features of a word by looking at the words around it. Or, as he more eloquently put it:
"You shall know a word by the company it keeps"
Essentially, you don't need to know all the rules of grammar or even the dictionary definition of a word to understand it. Instead, you just need to see what other words it is used with. Then you can know whether it is similar to other words, since they may share the same "company," as our old friend J.R. Firth would say.
King and Man He was a good King
King and Royalty The King always wears a crown
King and Man He lives like a King
Queen, King, Man, Woman A Queen is the wife or widow of a King
Queen, Royalty and Woman She was crowned Queen of England
Queen, King and Royalty This is the palace the King and Queen live in.
We can see from the table that the words "King", "Queen", "Man" and "Woman" are related since they often appear in the same sentences. While we might not explicitly use "Man" or "Woman" we get the context with words like "he" or "she" or "wife" and "husband". All of this context provides clues as to how each word is related to each other.
Word2vec uses this idea to learn the context of words via deep learning. There are different forms of word2vec but the basic idea is that we train a neural network to learn the context of words. We feed it a lot of data (such as 1 million most commonly used words from 6 billion words in Google news corpus) and the network learns what words appear next to each other more frequently.
To store this context, the network creates vectors with slightly more dimensions than our earlier example. In most cases, there are around 300 dimensions (or features) to each embedding. They then use these word embeddings to identify similar groups or clusters of words.
In the original Mikolov paper, they use the example of capital cities to show how this context has been learned.
Word embeddings can"learn" that capital cities are related, and also the countries to which they are related
From the graph, we can see that all of the countries are clustered on the left while cities are on the right. So there seems to be a correlation between the words representing countries and, separately, a correlation between the words representing cities. But we also see that there is a correlation between each country and its capital city via a horizontal transformation, i.e. if we traverse the graph horizontally via the arrows we end up close to that country's capital city and vice versa.
This did not happen by accident. We can imagine sentences in this dataset such as "Beijing is the capital of China" where these two words are commonly used together. And "Beijing has a population of X while Moscow has a population of Y". Or "The top five most populated cities are …"
Normally, in order to learn this context, we would need to manually label all this data to train a network. We would manually tag a sentence to indicate it contains words for a capital city or a country for example. Then train the network with lots of examples.
But there are a number of problems with this approach:
Firstly, the sheer volume of tagged data we would need would make it impractical.
Secondly, how would we even know the tags to use for each word? Take a sentence like "Beijing is the capital of China". We could tag it with "country" and "city" or "capital city". We could also tag it as containing "geographic" related words. Or what about "location" or "municipality"? And this is a relatively simple collection of words in a short sentence. Tagging every word in a large corpus would be extremely difficult.
Deep learning neural networks help us identify features that we humans cannot see. While manual tagging would be better than one-hot encoding it would still be very limiting since we would need to identify all the features in advance. To address this problem word2vec used two approaches: skip-gram and Continuous Bag of Words (CBOW).
Skip-gram and CBOW enabled word2vec models to be trained without requiring any labelling of data. The key to both approaches is to use the context of the words in a sentence to train the network. The diagram shows the input and output for each method.
Using the middle word to predict surrounding words
For skip-gram the input is a middle word in a sequence. The network then tries to predict the surrounding words
Using surrounding words to predict the middle word
In CBOWs the input is the surrounding words and the network tries to predict the middle word. If the prediction is incorrect this is fed back to the network and the weights and bias are tweaked and the process continues until it can accurately predict the target word(s).
In this way, it uses the context of the words to train the network to recognize what words are commonly used together. If words appear together often, then they are likely to be related and the network will create embeddings which capture this information.
These embeddings will be far more advanced than our simple reduced vocabulary set. By visually inspecting them, as we did with our simple examples, we can begin to comprehend some of the magic hidden in our new embeddings.
A better King and Queen?
Earlier we created some embeddings using one-hot encoding and a vocabulary of four words. We saw that there was not much information contained in those embeddings. We did not learn anything new from those embeddings.
One of the surprising outcomes of the word2vec approach was that the generated embeddings encapsulated more information in the form of context than anyone thought possible. This was discovered by performing basic mathematical operations such as addition and subtraction on the generated embeddings.
The famous example used in the one of the early papers by Mikolov et al. was to manipulate the word embedding for "King" using algebra to generate an embedding close to "Queen", i.e. King - Man + Woman = vector close to Queen.
4 separate embeddings
Subtract Man from Woman
Add it to King
And the closest word embedding is Queen
This was interesting since it provided some insight into what features may be represented by the dimensions of the embeddings. Being able to perform these types of operations implies that there are latent, hidden features of the embeddings which capture information relating to royalty and gender. For example, the dimensions might look something like:
This is different from our one-hot embeddings in a number of key ways:
The values in the dimensions are not binary, they range from 0 to 1.
Each word can have a value in more than one dimension
The embeddings are not sparsely populated, there are very few 0's.
If the dimensions of word embeddings contained something similar to the above table then the mathematical operations make sense. By subtracting the columns from each other we get transform the vectors to be close to other words in our vocabulary. Remember, this required no labelling of data in order to generate these embeddings. The neural network learned this context simply by looking at what words frequently appeared together or in close proximity in the data.
In this way, we can say that word embeddings are comprehensible – we can conceive of reasons why they work as they do.
Motivation for sentence embeddings
If word embeddings are so good at recognizing context, then why do we need sentence embeddings at all?
It's a good question – and one that is open to significant debate. In short, we could use word embeddings as a proxy for a sentence embedding approach.
One simple way you could do this is by generating a word embedding for each word in a sentence, adding up all the embeddings and divide by the number of words in the sentence to get an "average" embedding for the sentence.
Alternatively, you could use a more advanced method which attempts to add a weighting function to word embeddings which down-weights common words. This latter approach is known as Smooth Inverse Frequency (SIF).
These methods can be used as a successful proxy for sentence embeddings. However, this "success" depends on the dataset being used and the task you want to execute. So for some tasks these methods could be good enough
However, there are a number of issues with any of these types of approaches:
They ignore word ordering. So your product is easy to use, I do not need any help is identical to I do need help, your product is not easy to use. This is obviously problematic.
It's difficult to capture the semantic meaning of a sentence. The word crash can be used in multiple contexts, e.g. I crashed a party, the stock market crashed, or I crashed my car. It's difficult to capture this change of context in a word embedding.
Sentence length becomes problematic. With sentences we can chain them together to create a long sentence without saying very much, The Philadelphia Eagles won the Super Bowl, The Washington Post reported that the Philadelphia Eagles won the Super Bowl, The politician claimed it was fake news when the Washington Post reported that the Philadelphia Eagles won the Super Bowl, and so on. All these sentences are essentially saying the same thing but if we just use word embeddings, it can be difficult to discover if they are similar.
They introduce extra complexity. When using word embeddings as a proxy for sentence embeddings we often need to take extra steps in conjunction with the base model. For example, we need to remove stop words, get averages, measure sentence length and so on.
Preview of part two: sentence embeddings
Can sentence embeddings address these shortcomings and provide an easy to use method for identifying sentence similarity?
In part two, we'll investigate how much information we can pack into a single embedding. What happens when there are small changes in a sentence structure such as ordering or minor word changes? If sentence embeddings are such a new technology, can we know enough about them to put them into production?
To do this, we'll evaluate sentence embeddings against a baseline of sentences from a Quora question database and build a simple customer support recommender system to show how they could be used in a typical customer support workflow.
Let's move on part two!
This is part one of a two-part blog series by Cathal Horan on sentence embeddings.
Cathal is interested in the intersection of philosophy and technology. Specifically how technologies such as deep learning can help augment and improve human decision making. He recently completed an MSc in Business Analytics. His primary degree is in electrical and electronic engineering. He also has a degree in philosophy and a MPhil in psychoanalytic studies. He currently works at Intercom. Cathal is also a FloydHub AI Writer.
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I've discovered a new meal planning website that I think I am in love with. It's called Say Mmm. I've been looking for a site similar to this for over 6-months now, and there are a lot out there! They all have their pros and cons, but this is the first one that I have found that I am willing to try more than once, and would actually consider paying for the upgraded features. If you know me at all, you know that's saying a lot. But even without the upgrades, the site has a lot of things that I like -- FOR FREE! YAY for FREE!
Say Mmm has a website that is easy to use and access from your computer at home, and a website that is designed for your smart phone - so all of your recipes and shopping lists are right at your finger tips, even when you are on the go. I had a great time wandering through the grocery aisles with my shopping list in hand (on my smart phone), and crossing off items as I added them to the cart.
I love being able to save my own recipes to the website. You can type them in, or if they are already on your computer, just copy and paste. If the recipe is on another website, you can just include a link to it, and the ingredients will still be added to your shopping list!
I love the "link" option if I am in a hurry, but ideally, I prefer to copy the recipe into Save Mmm. It's more work at the beginning, of course, but in the end I think it is easier because you don't need to click over to another website -- everything you need is right there, within a single website. This especially comes in handy if you are at the grocery store and need to double-check the recipe on your smart phone. Some websites are not designed for smart phone use, so again, I just think it's easier. Try it and see what you think!
It's easy to add your own recipes, because you are able to type into a large text box. I've used other sites where you have to type each ingredient into it's own little box, with a separate little box for the measurement, and it's T.E.D.I.O.U.S. This is MUCH easier! Once you've typed it in (or copy and pasted it), you are able to preview how the ingredients will be added to your shopping list, immediately below your recipe.
Your shopping list is divided into two categories: "Get" and "Check". You will find that some items (primarily spices) are automatically added to the "Check" list. These items are likely items that you already have on hand, so rather than being added to the "Get" category, they are separated out so you can check the list quickly before you run to the store and then move any items that you need over to your actual shopping list.
TIP: The website tends to organize your shopping list in alphabetical order (even within categories like Meat or Dairy), so I edit the items in my shopping list to read slightly different then they might read in the actual recipe. For example, the recipe might say 6 oz. Shredded Mozzarella Cheese. I will change it in my shopping list to read Mozzarella Cheese - Shredded. You could even change it to say Cheese - Mozzarella, Shredded. Then when it is added to your shopping list, it is actually alphabetized by the item, rather than the "description" of the item. I don't know - maybe it wont' bother you at all, but I found it easier to put the description/type of item at the end... just felt like it made it easier to deal with the shopping list in the store.
TIP: This goes along with the above tip, but when you first enter a recipe, double check your shopping list. I just added a recipe that calls for Cream of Broccoli soup, but when it was added to the shopping list it told me that I needed "Cream - 1 Can". Totally different items! So I changed it on the shopping list to read "Soup - Cream of Broccoli [1 can]" - and it will be accurate (and in alphabetical order) from now on!
Also, double-check the measurements in the shopping list too. My recipe called for 1/4 cup of green onions, but the shopping list said 1 ounce of green onions. I just edited it back to 1/4 cup of green onions (because that is a lot easier for me to visualize), and again, it will be accurate from here on out. Keep in mind that this is not always a bad thing -- for example, it's nice that "2 cups of Sour Cream" in the list of ingredients gets changed to "16 ounces of Sour Cream" on the shopping list. Sometimes I do want the program to do the math for me!
There is a fun sharing feature on this site. I'm still learning how it works, but feel free to add me as a friend. My username is utahmommy.
I need to run for now, but I'll try to come back to add some more tips as I discover them. If you decide to give this site a try, let me know what you think!
Added more information at 10:45 am (MDT) on 12/29/11 - more to come!
Have you seen Lilo & Stitch? I'm guessing you have. Remember this scene? When Lilo illustrates Stitch's "badness level"? She determines that it's "unusually high for someone [his] size."
This is me. This is my stress level. I have determined that it's unusually high. Even for someone my size.
This is rather embarrassing to admit, but I need some help.
How do you create a schedule and how do you stick to it?
I feel like life just keeps happening all around me and I can't keep up. I get side-tracked or bored, or it seems like everything happens ALL AT ONCE - and when that happens, what do you do first?
I am feeling very overwhelmed and I need to change that. Surely someone has some suggestions... don't you?
My Mom discovered a feature in her genealogy program that makes poster-sized genealogical charts. Her favorite is the hourglass chart; a chart that shows both the ancestors and descendants of a particular person. After the poster is printed, we spend hours scanning in photos, resizing photos, and ultimately attaching the photos to the poster.
A few months ago, I helped my Mom make one for my Dad.
The school that my children attend requires them to complete a Personal Exploration Project during their 4th, 5th and 6th grade years. It's a fairly intense research project, spread out through the entire school year.
Sara's topic was "Cat's Bodies and How They Work". It's been a year of reading about cats, and Sara, quite frankly, is tired of it. I am glad that the end is in sight!
That said, Sara did get her act together and worked very hard on the "creative" aspect of the project. She chose to create an Alphabet Book and I think it turned out pretty cute.
As for me, I'm just glad that this research project is almost finished! One year down, Two to go. And then I get to start over again with Rebecca!


The season starts early in your home or in your garage or wherever the car is parked and after thinking about it since the end of the previous season you have made a commitment. You have decided to chase the 2016 points tittle for the upcoming season. The past season you received the RMLRA championship trophy. You now hope that you are placed among the top drivers in the local area. Maybe I should go see my shrink after this decision. The race car or cars that I have in the garage are excellent race cars and I have a pit crew that is on top of it to keep the car at the front during a race. Living in Colorado or Wyoming you need the support of enough drivers in your class to receive the maximum points every night in your division that you are racing in. Traveling to Gering, Nebraska to race on a Friday evening you hope that five cars in your class will be there. Legend race car teams have not been real strong fielding race cars to race this far from Denver, Colorado where many teams are located. Breaking this down, you need five cars in your division racing every night to receive one hundred points per night. The thought is to race at least nineteen races and come up with nineteen hundred points to put you in contention for the championship award. Many drivers throughout the country may race up to forty-fifty races or more chasing this championship. Living in the western part of the United States you have to travel many miles to race. Whereas a car racing on the east coast may be able to race several times a week without a lot of travel to and from races. A former RMLRA driver Terry Plummer went traveling during the 2005-2007 season and won the Golden Masters Award.
may be days before he finds out what the final outcome will be on his quest for the championship.
and later that night you go to bed with all kinds of possibilities that might come your way. The wait for USLCI to make an announcement is going to make for a few sleepless evenings possibly.
On Wednesday morning I happened to go to the US Legends web page and read the article on the Legends Asphalt Nationals. Although Scotty did not race the feature race his qualifying and a heat race victory, plus a second place finish in the second heat race gave him the points for a second place finish at the Nationals. The top two drivers ended up as follows.
Do take time to check the final results as several of our drivers did very well this season.
L. Scotty Scott did not start racing as a youngster but his family while living in the Cheyenne, Wyoming area was attracted to race cars at an early age. He spent a lot of time at Big Country Speedway watching his Dad and his uncle race modified and late models. We go back many years, when the modified's traveled to race on many area tracks in the states of Wyoming, Nebraska and Colorado and possibly a few more states not mentioned. Scotty has said many times that he thanks his family for the opportunity to race his Legend car.


text:
Video shows Illinois officer, highway worker save man from jumping off bridge
Watch Illinois deputy, highway worker save man's life
An Illinois deputy was awarded a letter of commendation for her efforts to save a man as he tried to jump off a bridge.
Dramatic video captured by a dashcam in Massac County, Illinois, shows the moment a sheriff's deputy and a highway worker saved a man as he tried to jump off a bridge.
Massac County Sheriff Chad Kaylor said on May 23, Deputy Summer Dixon responded to a bridge overpass on Interstate 24, where an Illinois Department of Transportation worker had encountered a man having "medical complications."
While Dixon was talking with the man, he suddenly tried to jump over the bridge railing. Dixon and the IDOT worker sprung into action and caught him before he dropped to the ground. They struggled to keep him from falling but they were eventually able to pull him back over the railing.
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The man was taken to a local hospital for evaluation, and Dixon received a letter of commendation from the sheriff.
If you or a loved one is feeling distressed, call the National Suicide Prevention Lifeline. The crisis center provides free and confidential emotional support 24 hours a day, 7 days a week to civilians and veterans. Call the National Suicide Prevention Lifeline at 1-800-273-8255. Or text HOME to 741-741 (Crisis Text Line).