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Home Editorial US Opinion and Editorial Death of a Naked Liberal
Death of a Naked Liberal
In 2010, Newsweek was sold for a dollar and it has been devalued since. Its corporate owners have called buying it a mistake and a fool's errand.
Around the same time last year, Newsweek marked a major milestone. The loss of 2.5 million readers in ten years. Since then it lost another million leaving it with about the reading population of a small city.
Meanwhile MSNBC isn't doing any better. It lost a fifth of its viewers since last year and it still can't decide if it's a network of angry idiots screaming at the camera (Chris Matthews, Al Sharpton, Ed Schultz and Lawrence O'Donnell) or snide aging college kids making wisecracks about Republicans (Rachel Maddow, Chris Hayes). Neither format is working all that well and at this rate MSNBC may want to look into bringing Keith Olbermann, who combines both demographics, back for another run.
Newsweek and MSNBC will both attribute their bleeding readership and viewership to the internet, but that doesn't explain why they're both doing badly there as well. MSNBC was caught hiring bots pretending to be young women to pump up hashtags for its hosts and Newsweek's fusion with the Daily Beast didn't save it either. Its final print issue carried a hashtag implying that the web had done it in, but the internet wasn't to blame.
Neither do Newsweek and MSNBC suffer from a surplus of class. Newsweek's desperate covers last year amounted to a formerly respected magazine descending into outright trolling. It was no longer possible to tell the difference between Newsweek covers and Newsweek parody covers. And certainly Tina Brown has never been accused of a surplus of restraint and good taste. On the MSNBC front, no news network which includes Al Sharpton trying to read from a teleprompter can be accused of betting on class.
MSNBC tried to be FOX News for liberals and Newsweek tried to be the Huffington Post with a print edition. They didn't outright fail at the job, but they couldn't succeed well enough either.
The dirty little secret of liberal media is that it doesn't work. Outlets that identify explicitly as liberal usually play to a very marginal audience. Mother Jones begs money from its readers in the same obnoxious way as PBS. NPR relies on donors. The New Republic is flailing. Liberal mags that succeed do it by focusing on a topic that overlaps with a liberal target audience and embeds their articles there.
It works for magazines like Rolling Stone and the New Yorker. Online sites like Huffington Post and Buzzfeed succeed by filling themselves with so much trash that the politics becomes a sideline. The liberal brand is fine when it's stuffed into culture, elitist or trashy. It doesn't however stand on its own two feet. It can't, because it has no real appeal.
Liberalism remains marginal. Gallup polls invariably show forty percent of Americans describing themselves as conservative and twenty percent or less identifying as liberal. Liberals dumped the liberal brand after conservatives effectively destroyed it back in the Reagan era. They emphasize policies and rhetoric over political identification because a liberal political identity is toxic.
The cultural dominance of the left did not come about because a majority of Americans knowingly identify with it, but because the left has succeeded in breaking up its agendas into tinier and tinier pieces and making them part of the national dialogue using seemingly agnostic media channels. These stealth tactics have been successful because they eschewed open identification. Liberal media doesn't work when it's transparently liberal. That's why even liberals mock NPR's news coverage.
Liberal media influence works when it isn't identified as such. And when it is identified as such then eighty percent of the country switches the channel and cancels its subscription. And then liberals realize that they are preaching to the choir and dump the whole thing as a bad business. MSNBC's overt identification with a liberal agenda allowed viewers to see how little of a difference there was between a liberal news channel and the "objective" mainstream news media.
MSNBC exposed millions of people to what actual media liberals sound like when they take off their disguises and begin talking about their agenda. It allowed a level of honesty that was rare in a media landscape where stealth liberalism is delivered using biased reporting that advocates for an agenda while claiming that there is no advocacy or agenda, only common sense solutions to problems that will never be repeated again.
It's the agenda that has always been the issue. What conservatives understand and most of the country does not, is that the issues being debated are not singular events. It's not just about an individual tax hike or gay marriage or background checks for gun owners. It's about a larger agenda being put into place piece by piece. And that agenda is the ultimate taboo topic. It's the thing we aren't supposed to talk about.
Watch a media report on any issue and there is never any identification or agenda to the left. Liberal activists are just activists. Often they are described as mothers or grandmothers. They don't have a larger plan. They would just like us to ban something dangerous, raise taxes, protect our oceans and make the country more equal. There is no policy platform. No larger set of demands hiding behind the ones being made right now. And most of the country accepts this deceptive coverage at face value.
MSNBC however churned out naked liberalism. It showed career radicals like Melissa Harris-Perry discoursing on just what the agenda is. And that's fine for Mother Jones, but it isn't something that liberals like to see out in the open. And it's not something that even many of them want to spend too much time thinking about because understanding what they have truly climbed on board with can be a troubling and alienating experience.
Naked liberalism makes even liberals uncomfortable. It's why they get uncomfortable hearing the self-righteous voices on NPR. It's too much like looking into a mirror and the things in the mirror are surprisingly unsettling. Hearing a Keith Olbermann or Jon Stewart tear into Republicans was one thing. Opposition is always safe ground. It's when the talk begins to turn to what you stand for that things begin to fall apart.
Newsweek and MSNBC had made the mistake of going "Full Liberal" and not only is there a much smaller liberal audience, but that audience doesn't really like naked liberalism. It would rather see its agenda dressed up in mainstream colors than see it for what it really is. It may occasionally dive into the partisan pool, but then it gets out again.
Conservative media outlets exist as alternatives to a dishonestly liberal media establishment. But what can liberal media outlets exist as alternatives to? All they can do is speak openly about the agenda that their big brothers choose to pass off as mainstream activism and when you already control the dialogue, there's not much of a percentage in sudden bouts of honesty.
The liberal agenda relies on manipulation and deception. It can sell quite well so long as no one knows what they're buying. But label the product with the liberal brand and it stays on the shelves. New media bastions of liberalism camouflage themselves with trash. They talk politics without letting on that they're talking about politics because that admission is the death knell of everything.
Liberalism's disproportionate influence depends on not being identified for what it is. That is why it is so panicked by right wing talk show hosts, not because of their rhetoric, but because they identify a clear political struggle between two political agendas and categorize both sides. And that forces the recognition that there are two sides, disrupting the illusion of anchormen and editors as objective observers and narrators of America.
What media liberals fear most isn't the right, it's being exposed as the left. It's not so much what FOX News says, as its very existence that is threatening, because once viewers become aware that FOX represents the right, then, even if they don't agree with it, they have to come around to the conclusion that there is another side and that the media embodies that other side.
Liberalism is marginal, as is MSNBC's audience. Media outlets like Newsweek and MSNBC that go full liberal die. And that lesson has terrible implications for liberal power as a whole.
Daniel Greenfield, a Shillman Journalism Fellow at the Freedom Center, is a New York writer focusing on radical Islam. He is completing a book on the international challenges America faces in the 21st century. He blogs at Sultan Knish.
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Palmer Luckey: Oculus Rift's success depends on a 'virtual cycle'
admin February 11, 2016 3 min read
This is the year of virtual reality. The excitement is palpable from audience members at the VR/AR Vision Summit 2016 conference as they cheered at developer jargon and clapped enthusiastically for VR's rockstar, Palmer Luckey.
The creator of the soon-to-be-released Oculus Rift didn't give away anything particularly tantalizing during a short interview, but he did have a few personal insights on a vision of a future where virtual reality is the norm.
VR is quickly catching on and as headsets will begin shipping out this year, the tech will be even more accessible. Luckey pointed out that VR needs to work successfully for everyone in order to really stick. Specifically, he mentions a "virtual cycle" where developers create, consumers buy and hardware manufacturers continue to perfect their devices.
But it's hard to say just how well the tech will take off. Sure, techies and early adopters are all on board – we've been following these companies for awhile now eagerly awaiting to travel to distant lands from our couches, but who's to say the average family will be ready? Accessibility remains questionable as expensive PCs will need to be fitted with the proper innards for the high end headsets to run properly.
Read this: What filmmakers, storytellers and games devs think of VR
Oculus, along with HTC and Sony seem prepared for this. One whole selling point is around PC bundles where everything is outfitted without the need to install additional components. Oculus even released the required specs last year while HTC has detailed the necessary setup for its Vive Pre. As for Sony? Dr. Richard Marks, director of the PlayStation magic lab, stated during the conference how 36 million PS4's are perfectly "VR ready."
The amount of units Facebook and Oculus will move also don't define success for Luckey. Rather it's the dollars spent on content and "hours spent in content" that will truly show whether VR will remain. Luckey mentions the early days of consoles and peripherals that didn't work but says that in order for the Rift and VR to succeed, everyone must keep doing their part.
He adds that the more people using Rifts every day, the better it is for the ecosystem. The release of the Samsung Gear VR has been a good test run for this. Unfortunately Luckey wouldn't spill the beans on the numbers and only stated "we've shipped a lot of units." As we've seen with the music, film, art industries, it's apparent VR isn't simply for the gaming crowd and Luckey was pleased to find that many Gear VR users have been attracted to VR experiences as much as games.
Read this: Incredible upcoming Oculus Rift games for 2016
The amount of content for Gear VR has certainly grown and it doesn't seem to be stopping. Other mobile VR headsets that are more accessible, like Google Cardboard, also don't show signs of slowing down with Google launching a refined version later this year.
The Rift itself has gone through many iterations. Luckey points to higher resolutions, wider field-of-views and better ergonomics as improvements to look forward to as Rift and VR continue evolving. In that time, Luckey's belief that content creation will help fuel the virtual cycle is so strong, a four month trial of Unity Pro is now part of the Oculus Rift package. Of course it's probably a push for devs to use Unity as their main tool but it's nice to think that he believes the average consumer can also be the creator. So as long as developers continue to make good VR, people will keep buying which in turn helps along Luckey's proposed ecosystem and we all get to be part of a new era of technology.
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Posted in: 2000 Eyes, by Tom Keogh, Film Reviews
2000 Eyes: 102 Dalmatians
Written by Tom Keogh	 November 6, 2020 November 4, 2020 Leave a Comment on 2000 Eyes: 102 Dalmatians
[Written for Film.com]
Shortly before the end of a promotional screening of 102 Dalmatians, an anxious Disney publicist leaned into the press row where I sat and announced that a couple of the film's reels had been shown out of order. Did we critic types happen to notice, she asked?
Of course, reply my astute colleagues. I, however, keep my mouth shut. You could have shown me this shrill hunk of junk upside down and backwards, and I would have remained willingly obtuse.
A typical sequel from hell, 102 Dalmatians bashes sensitive souls into a self-defensive posture with its outsize presentation: screeching soundtrack, bullying storyline, manic performances. There is little reminiscent of the 1996 live-action version of 101 Dalmatians, an engaging love story that gradually added slapstick to achieve a certain comic lilt. That earlier movie's class is not on display in this follow-up, which arms itself with audacity and then charges at the audience.
Gone, too, are Joely Richardson, Jeff Daniels, and Joan Plowright, who brought a certain gloss and warmth to 101 Dalmatians. In their place are a couple of good but lesser-known actors in dull parts: Ioan Gruffudd (television's Poldark) and Alice Evans (10 Things I Hate About You) as a pair of dog-lovers who get in the way of Glenn Close's returning villainess, Cruella De Vil.
Banking almost entirely on the niche popularity of Close's hammy character, 102 Dalmatians has nowhere to go once the opening scenes make it obvious that Cruella (despite, or because of, radical psychiatric treatment) will soon blow a gasket and continue her wicked quest for a Dalmatian-skin coat. The rest of the movie is by-the-numbers: Cruella outsmarts everyone but her would-be prey, those cute and spotted pups who battle her in a cartoonish and gooey endgame. It's as redundant as pre-chewed kibble, and as annoying as watching Rover hump your leg incessantly. Disney amps up the film's un-pretty preposterousness with tacky support work by none other than Gerard Depardieu. (Does the House of Mouse own this big lug's soul, or what? As memory serves, his few American projects have been for the one studio.) As a fashion maven and Cruella ally, Depardieu's garish role is the low point of an already-hopeless enterprise.
Nominally directed by Kevin Lima (Tarzan), 102 Dalmatians is the flipside of a strategy that worked very well for Disney's Toy Story II: i.e., if a sequel isn't likely to be better than its predecessor, at least make it funnier or cooler or whatever. In this case, everything—including the blueprint for a valuable studio property made not once but twice (including the 1961 animated 101 Dalmatians)—was thrown out on a whim. The obnoxious result is deservedly forgotten.
Tags: 102 Dalmatians, 2000 Eyes, Alice Evans, Cruella De Vil, Gerard Depardieu, Glenn Close, Ioan Gruffudd, Kevin Lima
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Pacify is a new multiplayer horror coming to Steam in February 2019. It includes Coop, PVP and a single player mode. Players work for PAH Inc and are sent on a mission to investigate a haunted house.
Emily Wants to Play Too is now available through Steam.


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Ecumenical Vespers Service for the Feast of St. Anna
On July 25, 2012, at the invitation of His Excellency Archbishop Allen Vigneron (Roman-Catholic Archbishop of Detroit), His Eminence Metropolitan Nicholas attended the Vespers Service for the Feast of St. Anna at the Cathedral of the Most Blessed Sacrament in Detroit, MI. Metropolitan Nicholas was also invited to a private dinner at the residence of the Archbishop preceding the Vespers Service. Accompanying His Eminence at dinner were: Rev. William Bartz (Chancellor), Rev. Nicholas Pathenos (Ecumenical Liaison), Rev. Aristotle Damaskos (Proistamenos of Holy Trinity Cathedral in Toledo, OH) and Mr. Alex Radulescu (Assistant to the Metropolitan). His Eminence Metropolitan Nicholas delivered the sermon stressing the importance of good parenting taking as models Sts. Joachim and Anna. At the end of the service, Metropolitan Nicholas presented the Roman Catholic Cathedral with an icon of Sts. Joachim & Anna with Panagia receiving in return an icon of St. Anna from Archbishop Vigneron.


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Home About NEB News and Press Releases 15 Inspiring Scientists Receive Passion in Science Awards™
15 Inspiring Scientists Receive Passion in Science Awards™
New England Biolabs® Award Recognizes Artistic, Environmental, Humanitarian, and Leadership Achievements
IPSWICH, Mass., Oct. 13, 2014 – Launching a global initiative to treat and prevent diseases affecting the world's poorest billion people is not the typical scientist's day job. Or is it?
"It's incredibly inspiring how many scientists step outside the lab to do brilliant, creative things in the arts or for humanitarian causes," says Peter Jay Hotez, the Dean of the National School of Tropical Medicine at Baylor College of Medicine, Texas Children's Hospital Endowed Chair of Tropical Pediatrics, and President of the Sabin Vaccine Institute.
Hotez is an inspiration himself, developing new vaccines for neglected tropical diseases – the major diseases of the poor, while simultaneously working to provide access to essential medicines for the "bottom billion" affected by these conditions through two organizations he helped found: the Global Network for Neglected Tropical Diseases and a vaccine development partnership between the Sabin Vaccine Institute and Texas Children's Hospital.
He is one of the 15 recipients of the "Passion in Science" awards, funded by New England Biolabs (NEB®), which recognizes scientists for their inspirational work that crosses into the arts, humanitarian service, environmental stewardship and scientific leadership.
"We are very excited about the Passion in Science Awards. What better way to celebrate NEB's 40th anniversary than to celebrate our customers who share similar values to our own," states Don Comb, founder of New England Biolabs.
"I'm continually humbled and motivated by what other scientists dare to dream," says Sir Richard Roberts, who shared the Nobel Prize in Physiology or Medicine for the discovery of "split" genes, and is currently the Chief Scientific Officer at NEB. "Seeing the work of Peter Hotez and other Passion in Science awardees, such as Karl Booksh, who works with disabled students to foster a love of STEM subjects, provides a stirring reminder of the impact that scientists can have when they choose to help others."
The Passion in Science awardees, selected from more than 600 candidates, represent a diverse set of talents and contributions to society. Awardees include:
Massachusetts Institute of Technology synthetic biologist Tal Danino, who tessellated cancer cells and bacteria in collaboration with Brazilian artist Vik Muniz to raise money for research (see image 1);
Oxford Brookes University electron microscopist Louise Hughes, whose 3-D printed models of viruses and cells brings the microscopic world to the visually impaired (see image 2);
Xiamen University Professor Tonni Kurniawan, whose bacteria-based composting device is reducing health hazards and generating extra income for people in Indonesia; and
Baylor University Professor Lori Baker, who risks her personal safety to visit migrants' graves along the U.S.–Mexico border, test DNA, and use the results to bring closure to the migrants' families.
Videos and photos of the inspiring work by all of the Passion in Science Awardees are available at www.neb.com/passioninscience.
"Immense possibilities for good lie within each of us. As scientists, we often have unique opportunities to apply what we know to shine a light on local and global issues. We only need to find the energy and courage to make a difference," says Paul McDonald, a scientist at the Virginia Tech Carilion Research Institute who received a Passion in Science award for his research and policy recommendations to reduce incidents of suicide in the Army.
The Passion in Science award also recognizes contributions from younger scientists, including this TED Talk by Shelly Xie, now a medical student at the University of Texas Southwestern Medical Center. Shelly uses sand shadow art to convey the experiences of a mother and daughter infected with the parasitic disease schistosomiasis (see image 3).
"Emotions swell up when watching her performance. She is a shining example of the great potential of the next generation of scientists," says Florida International University Professor Kalai Mathee, who received a Passion in Science Award for her lab's research into antibiotic resistance to improve the quality of life for children and adults with cystic fibrosis.
"Young scientists reaffirm my commitment to research and teaching. They are the reasons why I look forward to every day," says Mathee. More than 100 scientists, from high schoolers to visiting professors, have passed through the Mathee Lab for 65 Roses. Her lab is named after a touching mondegreen by a 5-year old boy with cystic fibrosis, who heard "cystic fibrosis" as "65 roses".
The awards and accompanying charitable donations were funded by New England Biolabs, a molecular biology reagents company. NEB maintains a strong basic research program, which includes laboratories focused on neglected tropical diseases caused by filarial parasites.
The full list of awardees follows:
Category: Arts and Creativity
Shelly Xie, UT Southwestern Medical Center, Dallas, TX; educating about neglected tropical diseases through evocative sand art performances;
Tal Danino, MIT; micropatterning of cancer cells and bacteria with artist Vik Muniz to raise money for oncology research;
Alia Qatarneh, Harvard University; rapping about science to engage young scientists-to-be;
Louise Hughes, Oxford Brookes University, United Kingdom; generating 3-D printed models from electron microscopy to help the visually impaired experience the microscopic world.
Category: Environmental Stewardship
Andrew Markley, University of Wisconsin Madison; curbing Styrofoam pollution by founding a reuse and recycling program at the University of Wisconsin, Madison, and replicating it at two other universities;
Tonni Kurniawan, Xiamen University, Xiamen, PR China; improving the Takakura Home Composting method to reduce health hazards to and increase income of residents in Indonesia and other equatorial countries.
Category: Humanitarian Duty
Karl Booksh, University of Delaware; leading a mentorship program for students with disabilities to encourage and open up careers in science, technology, engineering, and mathematics (STEM);
Paul McDonald, Virginia Tech Carilion Research Institute; analyzing trends of high-risk behaviors and changing Army-wide policies to increase awareness, identification, and response to at-risk Soldiers as part of the Army Suicide Prevention Taskforce;
Lori Baker, Baylor University, Waco, TX; risking her personal safety to visit migrants' graves along the U.S.–Mexico border, test DNA, and use the results to bring closure to their families;
Peter Jay Hotez, Baylor College of Medicine, Houston, TX; helping to establish the modern framework of neglected tropical diseases and working relentlessly with governments, industry, and academics to develop new vaccines and raise awareness resources for vaccines and treatments.
Category: Inspiration in Science
Ite Laird-Offringa, Norris Cancer Center, University of Southern California; fighting lung cancer through novel tools that leverage patients' immune response for early detection and treatment;
Jason Furrer, University of Missouri; inspiring undergrads to join real scientific laboratory research, regardless of initial skill level, that aims to help people with Crohn's disease;
Laurie Doering, McMaster University, Ontario Canada; researching astrocyte-based factors that may be able to treat neurons of people with Fragile X and autism;
Kalai Mathee, Florida International University; mentoring trainees and researching bacterial (Pseudomonas aeruginosa) antibiotic resistance that can ultimately help children and adults with cystic fibrosis to have a longer and better quality of life;
Whitney Hagins, Massachusetts Biotechnology Education, Cambridge, MA; providing equipment grants, teacher professional development, and co-teaching programs to support first-rate high school science education.
About New England Biolabs
Established in the mid 1970's, New England Biolabs, Inc. is the industry leader in the discovery and production of enzymes for molecular biology applications and now offers the largest selection of recombinant and native enzymes for genomic research. NEB continues to expand its product offerings into areas related to PCR, gene expression, sample preparation for next generation sequencing, cellular analysis, epigenetics and RNA analysis. Additionally, NEB is focused on strengthening alliances that enable new technologies to reach key market sectors. New England Biolabs is a privately held company, headquartered in Ipswich, MA, and has extensive worldwide distribution through a network of exclusive distributors, agents and seven subsidiaries located in Canada, China, France, Germany, Japan, Singapore and the UK.
For more information about New England Biolabs visit www.neb.com.
Images 1 to 3: Left: Tal Danino at MIT developed methods to micropattern cervical cancer cells (HeLa) and collaborated with artist Vik Muniz to create art that raises money for research. Middle: Electronic microscopist Louise Hughes at Oxford Brookes University prints 3-D models of viruses, cells, and microorganisms so the visually impaired can experience microscopy. Right: In this TED Talk, medical student Shelly Xie at UT Southwestern Medical Center uses her hands to shape sand and convey the hardship of families in developing nations who battle parasitic infections.
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Catophoenissa fuenzalidai is een vlinder uit de familie van de spanners (Geometridae). De wetenschappelijke naam van de soort is voor het eerst geldig gepubliceerd in 1956 door Ureta.

fuenzalidai

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THE HISTORIC FIVE DAYS P & T STRIKE OF 1960 – 2
2. P & T STRIKE OF 1946
The global economic crisis of 1929 -30 did not spare British India. In fact, it was much more severe. The recommendations of the Jahangir Committee, which was appointed to suggest remedial measures utterly failed in its task. The recommendations were completely anti-worker. Ban on recruitment, reduction of existing wages and posts, abolition of ED posts, denial of trade unions rights – all were part of the recommendations. The Emergency Reduction Rules – 1931 was issued on 8th December 1931.
½ Anna ( One Rupee = 16 anna) per rupee was reduced from the salary of those drawing up to Rs. 30/- . For those drawing from Rs. 30 to Rs. 83, one anna per rupee was reduced. Government snatched away more than Rs. 2.75 crore through this method. The pay scales of new entrants were also reduced.
Then existing unions organized agitational programmes against this attack, but government did not relent. Instead, it started victimization of workers. The Second World War (1939 – 45) worsened the situation. During 1943-44, more than 35 lakh people perished in Bengal alone due to famine. When the Director General P & T called the unions and sought support to the government's war efforts, the unions demanded that Dearness Allowance should be granted to meet the heavy increase in prices of essential commodities. Rationing system was introduced for the first time in the country.
The increase of Rs. 5 to 15 relief to employees recommended by the Adjudication Committee headed by High Court Judge Justice Rajyadhaksha was completely inadequate and did not satisfy the workers.
The II World War ended after Red Army of the USSR marched to Berlin defeating Hitler's invasion and Japan cities Hiroshima-Nagasaki bombed by USA killing lakhs of people, devastating both the cities through atom explosion. The axis allies Germany-Japan-Italy who started the war were utterly defeated. USA-USSR-British alliance won decisively. The world never has seen so much loss of lives and devastation as in II World War. The United Nations was formed on 24th October 1945 to maintain world peace and to avoid another world war.
It was at this stage that the (First) Pay Commission was appointed by Government of India with Federal Court Judge Sreenivas Baradacharya as Chairman. The intention was to temporarily satisfy the employees and delay settlement of the demands raised by the unions.
Appointment of Pay Commission was not sufficient to satisfy the meagerly paid Postmen & Class IV employees. The All India Postmen & Lower Grade Staff Union headed by V.G.Dalvi served notice to the government for going on indefinite strike w.e.f. 11th July 1946 with the following most important demands:
1. Pay of all officials in P & T should be revised
2. Existing leave rules should be abolished and pre-31 orders restored
3. All distinction on Leave and Pension Rules between superior and inferior servants in P & T should be abolished
4. Officials who acted in higher grade for one year should be confirmed in those grades
5. Posts reserved for promotion for Postmen should be increased from 20% to 50%
6. No retrenchment – Retrenched officials should be reinstated
7. P & T Holidays should be as in other central government departments
8. Work done on Sundays and Postal Holidays should be compensated by Over Time Allowance
9. Gratuity @ one month's pay for one year service should be granted to family of official dying before earning pension.
10. All distinction in the matter of pay, leave, DA & other allowances between A,B,C, areas should be abolished and all areas should be treated as A area
11. Medical examination for promotion should be abolished
12. Adequate leave reserve should be provided; temporary services should be counted for pension.
Other All India Unions did not serve strike notice on the ground that since Pay Commission has been appointed, there is no need for immediate strike.
The strike started on 11th July itself as given notice of. There was tremendous support for the strike from the people. The pitiable condition of the Postmen, who were delivering letters to them were known to all. Solidarity demonstrations were held with massive participation in Calcutta, Bombay, Madras etc.as per the call of AITUC. Pandit Jawaharlal Nehru demanded the British government to accept the genuine demands of the postal workers.
As the news of the strike reached beyond the big cities, postmen in rural areas also participated. At the initiative of leaders like B.N.Ghosh (Dada Ghosh) and K.G.Bose, the Postmen strike was converted to P & T Strike in Bengal with all the P &T unions giving call for strike. In many circles, this was repeated. The P & T services were at a standstill.
Government was compelled to discuss with V.G.Dalvi and other leaders. All the major 12 demands were agreed and the strike was called off on 3rd August 1946 after 23 days. It was a complete success for the workers.
Dada Ghosh, one of the leaders of the strike in Bengal ( who later became the first Secretary General of NFPTE), assessed the strike as follows:
"The strike was not any superimposed movement, but it was a natural outburst of the genuine hardship of the employees. In no civilized country could anyone think of stoppage of Postal, Telegraph and Telephone services for two or three weeks. The strike was a long drawn one because of the callous and unsympathetic attitude of the government. But even then, the public sympathy was a parting kick to the British imperialism in India. Just after a week of the withdrawal of the strike, the Congress formed the Interim Government with Pandit Jawaharlal Nehru as the Prime Minister of India. Future historians, I am sure, will have to admit it."
Like the Revolt of the Indian Navy ( Navy Mutiny) at the same time, the P & T Strike also is considered as part of the Independence Movement.
Although the Railway Unions had given strike notice earlier, they were withdrawn on the assurance that Pay Commission will be appointed. But the Railway Unions in South India went on Strike. They were severely punished. (To be continued).


Can GameSalad make a game similar to Uncharted — Welcome to the GameSalad forum!
When I say similar to Uncharted, that's just an example. I know GS is a 2D game maker and couldn't do anything close to that. But what about some of the simple stuff in the game? Could you make a player swing from ropes to get from one platform to another with GS? Or could you make a player jump from one platform and instead of landing on the other platform they grab onto it and pull themselves up? Is anything like that possible with GS?
Yes, there's nothing you mention that would be problematic in GameSalad.
You can look at the games on the arcade and featured on Gamesalad to see what it can do.
Your talking uncharted by Naughty Dog probably isn't the best example.
Im thinking Pitfall for rope swinging action. Can't think of a ledge climbing 2-D game at the moment.
Gamesalad does 2-D side scrolling platformers really well!!!!
@Toque Catching on ledges in 2D games, think of Prince of Persia.
GS is great for side scrollers. Building levels like that is going to take some time. Lots of fun and potential there. Find a good game illustrator to make your life easier.
The original Prince of Persia was so great, spent many hours playing that on my Mac LC II.
Thanks Liberdbell. I was having a design problem with a game concept but your question helped me with some great options!
@pHGhost - You just brought back a lot of memories with that one bud. Prince of Persia is the BEST analog side scroller ever created. Hands down! At least for a PC.


What Is The Best Life Insurance Policy To Buy?
That depends on you and your life insurance needs.
If you need for life insurance is to have protection for a period of 30 years or less, then a term life insurance policy may offer the best protection at an affordable price.
If you need guaranteed lifetime protection no matter how old you live to, then a permanent life insurance policy would be a better option.
Term life and permanent life are the two basic types of life insurance policies.
Term life is temporary protection for a period of 30 years or less with guaranteed level rates.
Permanent life insurance has level premiums and the protection is for your entire lifetime, as long as the premiums are paid on time.
Term life is pure life insurance protection, while permanent life insurance may build up some cash vale inside the policy over the years.
Term life has the lowest rates which means you can afford to buy more term life insurance than permanent life insurance.
Which Is Best Policy For Life Insurance?
The best life insurance policy for you will depend on your situation, and what goals you want your life insurance policy to accomplish.
For instance, some people buy life insurance to provide protection to help pay off their home loan in case they die before the mortgage is paid off.
In this instance, a level term life insurance policy of 20 or 30 years may fit your life insurance needs. It offers the most affordable protection for your family to fit the need.
If you have needs of 30 years or less, a term life plan may be good, while a permanent life insurance policy can provide lifetime coverage, but usually costs a lot more.
Here's an article with more information on finding the best life insurance to buy and explaining how the two basic types (Term and Permanent) of life insurance work.
When it comes to buying life insurance and choosing a plan, the best type of life insurance will depend on your own personal situation and needs.
Ask yourself - What do I want my life insurance policy to accomplish?
Your answer to this question will assist you in deciding which type of life insurance plan may be right for you.
For example, term life and permanent life insurance are the two basic types of life insurance.
A term life insurance plan may be a good idea if you need life insurance for 30 years or less. Since it is temporary, it costs a lot less than permanent life insurance, so you can get a lot more life insurance for your money, while you need the coverage.
On the other hand, a permanent life insurance plan may be a good idea if you need lifetime coverage, but not too much life insurance, since the rates are much higher than rates for term life insurance.
Or, you may decide to buy a smaller permanent life insurance plan to provide for your final expenses, and a much larger term life insurance policy for a period of 10, 15, 20 or 30 years, to provide more life insurance protection for your family.
Here's how you can learn more about the benefits of term life insurance vs permanent life insurance and compare rates online.


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Lower Fremont Glacier is east of the Continental Divide in the northern Wind River Range in the U.S. state of Wyoming. The glacier is in the Fitzpatrick Wilderness of Shoshone National Forest, and is among the largest grouping of glaciers in the American Rocky Mountains. Lower Fremont Glacier flows to the southeast and the rapid retreat of this glacier has left behind lateral moraines and a proglacial lake. Lower Fremont Glacier is separated from the Bull Lake Glacier by a moraine and from the Upper Fremont Glacier by cliffs.

See also
 List of glaciers in the United States

References

Glaciers of Fremont County, Wyoming
Shoshone National Forest
Glaciers of Wyoming


Ecoware clear disposable cups look and perform like traditional plastic, but are made from plants. Mind blown? Don't worry. You're not the only one. Made from Ingeo™ bioplastic, Stemless Wine EcoCups do not compromise on quality or performance, certified for commercial composting. 150mL pour line. Cold use only. Store below 40°C.


e rest of Europe), 2020 Toyota Verso will be made at the Turkish factory of the company.
Before restyling kompaktvena stands sharp teardrop headlamps, a thin grille falshradiatora, massive bumpers, memorable thanks to the huge air intake and fog spaced along the sides. Note the location and low front bumper – its edge almost touches the surface.
As if copying the front part of the feed has also received huge bumper, against which large marker lamps look quite moderate. The back door takes up almost the entire space of the stern, it is crowned with a spoiler.
Side view cling hardly at all, in addition to falling back stern and relatively high vyshtampovki. Wings more bloated as you get closer to the rear, large doorways were highly glazing line.
Overall impression of the exterior is satisfactory – a low-key, but with a claim to individuality.
Dimensions of the new 2020 Toyota Verso are as follows: length is 4440 mm, width – 1790 mm, height – 1620 mm. Indicators wheelbase and ground clearance is 145 mm, respectively 2780.
Dimensions protectors depends on the selected version of a complete set of auto – 205/60 R16, or 215/55 R17, coming from the alloy wheels.
Exterior color options are more than enough – a total of 11 provided that will allow everyone to choose the color of cars according to their own preferences. Note the two emerging new colors: 2 shades of blue and dazzling white.
All materials are of high quality interior finish, pleasant to the touch plastic, leather is clearly not the worst, and the tissue is very dense. The first series meets comfortable chair, getting heated, the controls are placed in the interior restyling cars are so ergonomically that getting used to the time it is not absolutely required. On the center console there was a place for the 6.1 multimedia screen (CD, MP3, AUX, USB, Bluetooth), below which is blochok climate control. Gear Shift Knob, which is located at the bottom of the console, three-spoke steering wheel lies comfortably in the hand, the original form of the dashboard is equipped with informative instruments at its center flaunts small computer monitor.
There are three complete cars, the basic version presupposes ABS, BAS, EBD (more expensive trim levels available for VSC system – Stability ), traction control (TRC), as well as an assistant at the start of the hill (HAC).
Most "pack" got cruise control, a large 6.1 inch screen Touch, by means of which the navigation control, and displays the picture with Smart Entry and Push Start back of the camera, keyless entry system, large panoramic roofs, and many others are not cheap enough options and system.
The second row was separate chairs that can be moved along the interior a very impressive distance – 195 mm, which provides all three passengers sufficient space.
Rear, third row capable of comfortably accommodate only children – the place is frankly not enough. Note that the interior restyling cars, regardless of the wishes of the owner, may be 5 or 7-seater, while the seven-seat car has a very tiny luggage compartment of 155 liters.
When folded back row boot capacity increases to 440 liters when folded second and third rows flat luggage compartment is obtained, which will accommodate bulky items up to 1.5 m.
Restyling touched not only the exterior and interior of the family car – the technical characteristics have also undergone significant changes. For example, we have been greatly improved drag coefficient and control cars, increased body rigidity. Due to the changes, 2020 Toyota Verso suspension (front – McPherson , rear – torsion beam) is much better absorbs any unevenness of road surface, and the control car has become much easier due to increased information content of the steering wheel. An updated version of a minivan equipped with two petrol and 3 diesel powertrains.
Ruler gasoline engines are 1.6-liter (132 hp) and 1.8 liter (147 hp) engines.
Diesel engines – 2.0 liter (126 hp) and 2.2 liters, which is dependent on the settings can produce 150 hp or 177 hp.
The youngest gasoline and diesel engines (volumes of 1.6 and 2.0 l) are aggregated with 6-speed manual stupas. The more powerful power units operate with a manual gearbox or 6-speed automatic transmission.
Sales restyled version of the family cars 2020 Toyota Verso in Russia began recently, the starting price of cars is 820 thousand rubles – for this amount available Comfort equipment with an initial 1.6 liter petrol engine, teamed with a 5-speed manual transmission. This equipment with a 1.8 liter engine, working together with the CVT, is estimated at 890 thousand rubles. A more advanced version of the 2020 Toyota Verso elegans (petrol engine of 1.8 liters, is aggregated with CVT) is 999.5 thousand rubles. The cost of the most elite version of the Prestige starts at 1 090 thousand rubles.


text:
Sia News
7 Celebs That Are At least 95% Vegan Just Like Beyoncé
Labrinth, Sia and Diplo Form New Supergroup LSD
Sia's 'Santa's Coming For Us' Video Is A '50s Hollywood Affair
Sia Celebrates Halloween With Christmas Song 'Santa's Coming For Us'
Sia Announces 'Everyday Is Christmas' Album
Zayn Is Back With the Incredible 'Dusk Till Dawn' Video Featuring Sia
Zayn and Sia's 'Dusk Till Dawn' Video Looks Like A Hollywood Blockbuster
Sia Has Signed A New Record Deal And Is Releasing A Christmas Album
Here Are All The Record Store Day 2017 Releases You Need To Grab
What You Missed In Music: Carpool Karaoke TV Series First Look, The Weeknd's New Video & More
Sia Under Attack From Azelia Banks After Defending Animal Rights
MTV's Most Played Videos 2016: Sia Tops The List With 'Cheap Thrills', But Who Else Is Up There?
New Music Out This Week: The xx, Olly Murs, Sia & More
Bastille Have Scored Their Second No. 1 Album With 'Wild World'
Sean Paul Tells Us Why Dancehall Is Still Relevant & How He Helped Bring It Into The Mainstream
This Week's Must-Hear New Music Round Up: Lady Gaga, Sia & Tove Lo
Era Istrefi On Being Rihanna & Sia's Lovechild: "I'll Take It!"
Maddie's Back In Sia/Kendrick Lamar's 'The Greatest' Video, Which Is A Tribute To The LGBT Community
Fifth Harmony & Beyonce Battle It Out For The Top Spot In MTV Hottest Summer Superstar
Find Out Who's Playing On The MTV Stage At This Year's V Festival
Sia Reached Out To Drake On Twitter And Sent Everyone Into Meltdown
Ariana Grande Scores First No. 1 Album & Drake Breaks Records With 'One Dance'
Sia Debuts Finding Dory Track 'Unforgettable' And We're Fully Obsessed
Sia's Carpool Karaoke Is A Perfect Example Of Why She Should Keep Every Song She Ever Writes


Majority of the units taken up at the Orchard Road condo were four-bedroom units priced at over $10 million each.
Boulevard 88, a freehold luxury residential development along Orchard Road, sold 20 of the 25 units released during its private preview at an average selling price of $3,550 psf.
City Developments Limited (CDL) and its joint venture partners, Hong Leong Holdings and Lea Investments revealed that the previews, which started on 8 March, were by appointments only.
Directly accessible via Cuscaden Road and Orchard Boulevard, the 154-unit project is a short walk to Orchard MRT station and the future Orchard Boulevard station.
Prices for a two-bedroom plus study unit start from $4.4 million, $6 million for a three-bedder, and $9.6 million for a four-bedder.
Majority of the units taken up were four-bedroom units priced at over $10 million each, while the rest were three-bedders and two-bedroom plus study units.
Singaporeans accounted for around 60 percent of the buyers, while the rest were Singapore permanent residents and foreigners mainly from China, Indonesia and the US.
"We are very encouraged by the positive response for Boulevard 88. For an ultra-luxury development, achieving a sales value of over $160 million in less than two weeks of exclusive private previews is commendable in the current market," said CDL's group general manager Chia Ngiang Hong.
Aside from these, he noted that buyers were drawn to the project's attractive pricing.
"We are confident that Boulevard 88 will continue to attract savvy buyers looking for luxury living in the heart of town with good investment potential," he noted.


Ride with The Last Songwriters! Hotwalker Christmas Deals from The Borderland! Next record News! Art and Insanity!
If there is any doubt Jesse Winchester is one of the last of the truly great singer-songwriters, this performance should convince you. He's the Master who can break your heart. Remind yourself of why you love great songwriting.
110,000 have seen Jimmy Webb sing his Wichita Lineman on Jools Holland: The Link: http://www.youtube.com/watch?v=GlEpKhSHTyQ Jimmy has written the great ones: By the Time I Get to Phoenix, The Moon's a Harsh Mistress, Galveston, MacArthur Park and dozens more. He's a legend of song.
These four writer performers will be on the "Masters of American Song Train"…your chance to ride with them up close and personal: a package that includes concerts, workshops, hotels, meals, a beat tour of San Francisco…and more. Coming in January! Treat yourself to the ultimate Christmas package and our most affordable train ride, with the Masters. Click on www.rootsontherails.com for details and email trains@sover.net or call toll free 888-484-3669. A few seats remain.
GIFT IDEAS! The Ultimate Stocking Stuffer and Gift! (for those 18 and over): Hotwalker! Borderland! Two of the Tom Russell Classics, along with a personally signed art card from Tom. The whole 3-piece package is available for $20 from www.villagerecords.com limited offer.
The Rainbow Man in Santa Fe now has a new stock of Tom Russell art. You don't need to buy anything to check out the gallery show. Click on the link: www.rainbowman.com and then Tom Russell Art…..Includes: Crazy Horse, Bob Dylan, Gallo del Cielo, and others. Rainbow Man also features the famous Edward Curtis Native American prints…..and great folk art.
www.yarddog.com in Austin has some paintings left from the Tom Russell "Beats and Boxers" show, including Ferlinghetti, Burroughs in Tangier, and Roberto Duran plus Bob Dylan prints. Drop by the link….always an interesting site and store.
New Record in the works! Tom has recorded five new songs with Calexico in Tucson; also five songs in Nashville with Barry Walsh, Gretchen Peters, Viktor Krauss and Fats Kaplin; also two songs in L.A. with Thad Beckman, Van Dyke Parks, Don Heffington and Bob Glaub and one song in San Antonio with Augie Meyers and Joel Guzman. This one is really building into something…on a grand scale. Rumor has it that Tom also cut a Dylan song with Calexico…..
The great Filmmaker Eric Temple (A Voice in the Wilderness – Edward Abbey) is working on a Tom Russell Documentary; out next year. This one has some incredible vintage band footage…a Don't Look Back type approach. Check out Eric at: www.canyonproductions.com Eric also has DVDs of the Tom Russell/Ian Tyson songwriting workshop.
Buy yourself the Bob Dylan Christmas album, make a bowl of mulled wine and enjoy the holiday season….be safe. The Tom Russell Office. On the Frontier.


I intend to show a shell script for Jetty 8 server which is installed in /opt/jetty-distribution-8.1.0.RC2/ (path on my virtual server). The script checks the process id of the running Jetty server, kills it if it was found and restarts the server with the command "nohup java -jar start.jar".
I have released a new 0.3 version of the Maven plugin for web resource optimization. As I mentioned in the last posts this plugin was created as a part of the PrimeFaces Extensions project. It produces better compression results than YUI Compressor and has some nice features. The current release fixes only one issue. Release notes are here. The plugin is available in the Maven central repository.
If you have any questions regarding to the configuration, ask me please in the PrimeFaces Extensions forum. This forum is also a good place for all questions to the components and more. Unfortunately, but PrimeFaces lead doesn't like to see any discussions related to our extensions in the main PrimeFaces forum. He considers such topics as advertisement and locks / removes them. That hurts and is weird because if it would be an advertisement, it would be an advertisement for PrimeFaces. We have "PrimeFaces" in the name "PrimeFaces Extensions". The aim was never to do an advertisement or get money. This project is just for fun, everybody can participate in.
Currently we are working on the last use cases for our showcase and plan to do a release in the middle of January. Next releases will be published at frequent intervals and include less stuff - approximately 2-4 new components, client behaviors, converters or similar JSF 2 related artefacts. Some stuff is amazing, so stay tuned.


text:
Who will the Twins purge from the 40-man roster this offseason?
At the beginning of each offseason every team goes through the ritual housecleaning of shedding players from the 40-man roster to prepare for a winter of adding new players and protecting new prospects. As one of baseball's worst teams for a fourth straight year the Twins have no shortage of dead weight on the 40-man roster, plus plenty of marginal talents clinging to spots, so here's my breakdown of the players most likely to be shed and where they stand (in alphabetical order):
A.J. Achter: Added to the 40-man roster in September after a nice season between Double-A and Triple-A, the former 46th-round pick debuted at age 26. His success this season was driven largely by an unsustainably great batting average on balls in play and Achter's control has never been particularly good, which along with a high-80s fastball and unspectacular strikeout rates makes him unlikely to project as more than a middle reliever.
Doug Bernier: Last year the Twins called up Bernier to fill a little-used bench role and dropped him from the 40-man roster after the season, which is presumably the plan again this time. He had a solid season at Triple-A, hitting .280/.348/.396 in 124 games, but Bernier is 34 years old and the epitome of a replacement-level player. Great to have stashed at Triple-A, not great to have in the majors or even taking up a spot on the 40-man roster.
Jared Burton: One of the Twins' better scrap-heap pickups, Burton was a high-end setup man for a year-and-a-half before struggling down the stretch last year and showing major signs of decline this season. Dating back to August of last season Burton has a 5.12 ERA and 50/28 K/BB ratio in 72 innings. His velocity is down, he's ceased missing bats, and at age 33 it's hard to see him being trusted enough in a high-leverage role to justify picking up his $3.6 million option for 2015.
Chris Colabello: He was a good story and absolutely deserved a shot in the majors after crushing Triple-A pitching, but Colabello hit .214/.284/.364 with a ghastly 124/34 K/BB ratio in 114 games. He has no defensive value and, unlike most right-handed hitters, his approach at the plate doesn't lend itself to crushing left-handers. At age 31 it's tough to imagine giving him another extended opportunity, especially considering the Twins' depth at first base and designated hitter.
Logan Darnell: It's tough to see Darnell sticking in the big leagues as a starter. He has a 3.82 ERA with a poor strikeout rate and mediocre control in 172 innings at Triple-A, his average fastball so far in the majors is 89 miles per hour, and he struggles against right-handed hitters. At age 25 he may still have a future in the bullpen, but the same could be said of nearly every left-handed starter and there isn't much in his track record to suggest his upside there is notable.
Brian Duensing: It's masked by a strong ERA, but Duensing's secondary numbers collapsed with a 32/20 K/BB ratio in 53 innings. His inability to handle righties means he can't be trusted in the late innings and he's not dominant enough against lefties to be a southpaw specialist. Duensing is a perfectly decent middle reliever, but at age 31 and with an arbitration-fueled raise to at least $3 million coming for his final pre-free agency season he's a non-tender candidate.
Eric Fryer: Tabbed to fill the Drew Butera role as a catcher who can't hit enough to warrant a roster spot, Fryer took over as Kurt Suzuki's backup when the Twins demoted Josmil Pinto to the minors. He's hit .248/.325/.345 in limited MLB action, which is actually much better than his .217/.314/.316 line in 204 games at Triple-A. Even if the Twins are convinced Pinto has no future behind the plate they can do better than Fryer as a second (or third) catcher.
Chris Herrmann: In theory Herrmann brings versatility to the table as a catcher/outfielder, but the Twins want nothing to do with him behind the plate defensively and he doesn't hit enough to have any business in the outfield. He's hit .184/.256/.268 in 91 games for the third-worst OPS in the Ron Gardenhire era of 2002-2014, ahead of only Butera and Tsuyoshi Nishioka. And at age 27 his .262/.331/.399 line in 129 games at Triple-A is barely any better.
Kris Johnson: Acquired from the Pirates as part of the Justin Morneau trade, it was never clear why the Twins wanted Johnson unless they focused on his misleadingly good 2.39 ERA at Triple-A last season. He posted another decent-looking 3.48 ERA at Triple-A this year, but managed just 102 strikeouts in 132 innings while walking 3.8 per nine frames. Johnson is 30 years old with 6.2 strikeouts and 3.5 walks per nine innings for his career at Triple-A.
Eduardo Nunez: When the Twins acquired Nunez they talked up his offensive potential as if he hadn't hit .267/.313/.379 for the Yankees or had similar numbers in the minors. He's been even worse for the Twins, hitting .251/.274/.385 in 67 games. Ultimate Zone Rating pegs him as one of the worst shortstops in baseball at 30 runs below average per 150 games and he's looked shaky at third base as well. It's unclear where exactly the upside is with the 27-year-old Nunez.
Lester Oliveros: He hasn't looked good in the majors yet, but Oliveros put together an excellent season between Double-A and Triple-A in his first full year back from Tommy John elbow surgery. He struck out 88 batters in 66 total innings, posting a 1.64 ERA while allowing zero home runs. His control remains spotty, but with a mid-90s fastball and outstanding strikeout rates Oliveros seems deserving of an extended chance. It's just unclear if he'll get that in Minnesota.
Chris Parmelee: Since his big September debut Parmelee has hit .237/.303/.372 in 248 games for the Twins, showing mediocre power while failing to control the strike zone. Good numbers at Triple-A suggested the former first-round pick may have finally figured things out, but he's failed to do anything with semi-regular playing time in three straight seasons and will soon be 27 years old. Why keep waiting for what might be, at best, an average first baseman/corner outfielder?
Mike Pelfrey: Re-signing Pelfrey to a two-year, $12 million deal never made any sense and he allowed 23 runs in 24 innings before being shut down with an elbow injury. He's owed $5.5 million next season, so Pelfrey being cut loose would be a surprise, but he's 12-29 with a 5.00 ERA in 390 innings since 2011, throws one mediocre pitch, and injuries have wiped out two of his last three seasons. He's a sunk cost, but perhaps they can salvage some value out of Pelfrey in the bullpen.
Yohan Pino: When he was a prospect posting great numbers in the minors from 2005-2009 the Twins never called up Pino, but they finally gave him a chance as a 30-year-old journeyman in his second stint with the organization. Pino had an ugly 5.07 ERA in 11 starts and struggles to limit home runs, but his 50/14 K/BB ratio in 60 innings was solid. As the past four seasons have shown there's always plenty of need for rotation depth, but elbow problems cloud his status for 2015.
Ryan Pressly: After spending all of last year in the majors as a Rule 5 pick Pressly spent most of this year at Triple-A, throwing 60 innings with a 2.98 ERA and 63/21 K/BB ratio. He throws hard, but it has never led to big strikeout rates and Pressly has just 63 strikeouts 102 innings for the Twins. He has a nice-looking 3.54 ERA and the Twins have been to known to let that sway their opinion more than it should, but at age 26 it's tough to see significant upside.
Stephen Pryor: Acquired from the Mariners in the Kendrys Morales swap/salary dump, Pryor is one of the few players on the 40-man roster not to receive a September call-up. He was once a top reliever prospect with a high-90s fastball, but he's struggled to regain velocity after shoulder surgery. He posted a 3.93 ERA at Triple-A with awful control and just 52 strikeouts in 55 innings. Still just 25 years old, presumably the Twins liked Pryor enough to see what he looks like in 2015.
Jordan Schafer: It seems unlikely that the Twins would get rid of Schafer after how well he's played in 40 games since they claimed him off waivers in early August, but he's the type of player who regularly gets dropped from 40-man rosters. Schafer is a 27-year-old career .230/.312/.311 hitter who also batted just .225/.278/.294 at Triple-A and despite great speed he's a mediocre defensive center fielder. He's a decent fit as a backup outfielder, but that skill set is plentiful.
Anthony Swarzak: After flopping as a starter Swarzak found a fit as a long reliever able to soak up low-leverage innings, but his effectiveness slipped this year and he's due for a raise to around $2 million via arbitration. Swarzak's strikeout rate of 5.2 per nine innings ranks 125th out of the 131 pitchers with at least 50 innings as relievers and his career rate as a reliever is 5.8 per nine innings. His role could be better utilized to break in a young starter.
Aaron Thompson: His flukishly good numbers versus lefties this season caught the Twins' eye and earned him a call-up, but Thompson is a 27-year-old journeyman with a high-80s fastball and a 4.33 ERA in a decade as a minor leaguer. That includes a 3.52 ERA and 107/51 K/BB ratio in 120 innings at Triple-A. Like most reasonably effective lefties he could probably hold his own in a southpaw specialist role, but the Twins should be aiming higher for a Duensing replacement.
A.J. Achter
Aaron Thompson
Anthony Swarzak
Brian Duensing
Chris Colabello
Chris Parmelee
Doug Bernier
Eduardo Nunez
Eric Fryer
Jared Burton
Jordan Schafer
Kris Johnson
Lester Oliveros
Logan Darnell
Mike Pelfrey
Ryan Pressly
Stephen Pryor
Yohan Pino


Are the allies on the same page after Biden's trip to Pakistan? was carried in The National in Jan 2011.
It was later reprinted in Counter Punch as Why Did Joe Biden Rush to Visit Pakistan in Feb 2011.
The report on ISI by the London School of Economics discusses the original report where the ISI connection with the Taliban was first highlighted – the wikiLeaks report was merely a repetition of this.
This is the unedited version of the article published in The National in June 2010. The published article can be found here.


Avalon Waterways has announced its plans to unveil a new Suite Ship in 2019.
Features exclusive to the Avalon all-suite eet includes open-air balconies and wide opening windows.
The Avalon Waterways 2019 programme, including bookings for Avalon Envision is on sale now and includes earlybird oers such as air credits of up to $5000 per couple and single traveller savings.


text:
HP 10 HP 10
HP 10 HP 10 (Indomethacin 25 mg)
Pill with imprint HP 10 HP 10 is Pink & White, Capsule-shape and has been identified as Indomethacin 25 mg. It is supplied by Heritage Pharmaceuticals, Inc..
Indomethacin is used in the treatment of ankylosing spondylitis; back pain; bursitis; bartter syndrome; pain and belongs to the drug class Nonsteroidal anti-inflammatory drugs. Prior to 30 weeks gestation: Risk cannot be ruled out during pregnancy. Starting at 30 weeks gestation: There is positive evidence of human fetal risk during pregnancy. Indomethacin 25 mg is not a controlled substance under the Controlled Substances Act (CSA).
Images for HP 10 HP 10
Nonsteroidal anti-inflammatory drugs
C - Risk cannot be ruled out - prior to 30 weeks gestation, D - Positive evidence of risk - starting at 30 weeks gestation
Heritage Pharmaceuticals, Inc.
D&C Red No. 28, FD&C Blue No. 1, FD&C Red No. 3, gelatin, lactose monohydrate, magnesium stearate, povidone, silicon dioxide, sodium lauryl sulfate, titanium dioxide, corn starch
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Drug class: Nonsteroidal anti-inflammatory drugs
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text:
Using Pause Information for More Accurate Entity Recognition
by Sahas Dendukuri, et al.
Entity tags in human-machine dialog are integral to natural language understanding (NLU) tasks in conversational assistants. However, current systems struggle to accurately parse spoken queries with the typical use of text input alone, and often fail to understand the user intent. Previous work in linguistics has identified a cross-language tendency for longer speech pauses surrounding nouns as compared to verbs. We demonstrate that the linguistic observation on pauses can be used to improve accuracy in machine-learnt language understanding tasks. Analysis of pauses in French and English utterances from a commercial voice assistant shows the statistically significant difference in pause duration around multi-token entity span boundaries compared to within entity spans. Additionally, in contrast to text-based NLU, we apply pause duration to enrich contextual embeddings to improve shallow parsing of entities. Results show that our proposed novel embeddings improve the relative error rate by up to 8 three domains for French, without any added annotation or alignment costs to the parser.
Sahas Dendukuri
Pooja Chitkara
Joel Ruben Antony Moniz
Xiao Yang
Manos Tsagkias
Stephen Pulman
Dependency Parsing for Spoken Dialog Systems
Dependency parsing of conversational input can play an important role in...
Sam Davidson, et al. ∙
Benchmarking Natural Language Understanding Services for building Conversational Agents
We have recently seen the emergence of several publicly available Natura...
Xingkun Liu, et al. ∙
Convo: What does conversational programming need? An exploration of machine learning interface design
Vast improvements in natural language understanding and speech recogniti...
Jessica Van Brummelen, et al. ∙
Water quality information dissemination at real-time in South Africa using language modelling
We present a conversational model to apprise users with limited access t...
Laing Lourens, et al. ∙
Fast Intent Classification for Spoken Language Understanding
Spoken Language Understanding (SLU) systems consist of several machine l...
Akshit Tyagi, et al. ∙
Givenness Hierarchy Theoretic Cognitive Status Filtering
For language-capable interactive robots to be effectively introduced int...
Poulomi Pal, et al. ∙
End-to-End Natural Language Understanding Pipeline for Bangla Conversational Agents
Chatbots are intelligent software built to be used as a replacement for ...
Fahim Shahriar Khan, et al. ∙
1 Introduction and Related Work
Measure French English
Number of utterances 17,799 22,388
Average # tokens in an utterance 3.67 4.71
% of tokens that are entities 24% 24.52%
Average pause duration per token 51.60ms 33.64ms
Table 1: Statistics for the dataset EngFrPauseData.
Voice assistants are increasingly becoming a part of our daily lives as they empower us to complete diverse and complex tasks. Today, voice assistants are able to make phone calls, take notes, set alarms, narrate bed time stories, or even rap hip-hop. Given a user's request, the assistant transcribes the input audio to text, and a natural language understanding (NLU) system classifies and routes the transcribed text to components that handle the request (e.g., phone call, notes, alarm).
Typical conversational NLU systems rely on text, the output of an automatic speech recognition (ASR) system
Muralidharan et al. (2019) . These systems have proven successful, but relying wholly on text means that some analyses may be inaccurate Nygaard et al. (2009) , since acoustic signals may be needed to arrive at the right intent. For example, in the utterance "play thank you next", the pause duration between "you" and "next" can help determine if the request is to play the specific song "thank you next" or to play the song "thank you" but next in the queue. This disambiguating function of pause information is well known, but the potential role of pause information in signalling different types of constituents, as described in Seifart et al. (2018) , has not, to our knowledge, been investigated in this setting.
Our goal is two-fold. Our first objective is to analyze the findings of Seifart et al. (2018) in the context of spoken conversations typical of those processed by voice assistants. Specifically, we show that differences in pause length around named entity spans is a statistically reliable processing cue. Our second goal is to demonstrate that the intuitive role of pause duration in aiding language understanding can be used in practice. Specifically, we present novel pause-grounded contextual embeddings that consistently outperform text-based representations in a language understanding task across multiple domains.
A standard approach to a tighter integration between acoustic information and NLU has been to use end-to-end models that can consume acoustic waveforms directly and learn NLU labels Haghani et al. (2018) . However, this approach can be difficult to adapt to traditional text-based tasks since audio inputs need to be labeled with task-specific information, introducing additional annotation costs.
An alternative approach is suggested by the recent and growing body of research which encodes text along with other modalities, such as audio and video, in a single embedding, known as multi-modal grounded embeddings Settle et al. (2019); Jeon et al. (2019); Rahman et al. (2020); Lan et al. (2020); Chuang et al. (2019); Chung et al. (2020) . These models have proven successful in tasks like speech recognition Settle et al. (2019)
and sentiment analysis
Rahman et al. (2020) . However, they require the data from different modalities to be aligned in order to produce the embeddings, again increasing the cost of generating training data.
We work within this paradigm of multi-modal grounded embeddings using pause markers in spoken utterances for the task of shallow parsing Ladhak et al. (2016); Vijayakumar et al. (2017); Rahman et al. (2020); Liu et al. (2020); Lan et al. (2020)
. We propose a novel self-supervised architecture adding a pause prediction task to traditional text-based BERT-style language models
Devlin et al. (2019) . To the best of our knowledge, this is the first study on grounding textual embeddings in spoken pause signals.
We pre-train our embeddings using token-level pauses from the ASR system, and consume the representations in the downstream parsing task without fine-tuning. We do not input pause duration in our downstream task and, therefore, do not require data from different modalities to be aligned. This sets our approach apart from end-to-end approaches that use speech signals as input during inference, requiring additional task-specific annotation (such as Chi et al. (2020); Liu et al. (2020); Ling et al. (2020) ).
2 Analysis of Pause Duration
Figure 1: Histograms showing the normalized frequency distribution of the pause duration for French on the EngFrPause Data described in Table 1
across three domains: sports, movies, and music. x-axis marks pause duration in milliseconds (up to 3 standard deviations from the mean) for before (O-B) and inside (B-I and I-I) an entity (left), and after (B-O and I-O) and inside (B-I and I-I) an entity (right). y-axis shows log-normalized counts. Note that the deep purple-grey color is indicative of the red and blue histograms overlapping.
Figure 2: Histograms showing the normalized frequency distribution of the pause duration for English on the EngFrPause Data described in Table 1 across three domains: sports, movies, and music. x-axis marks pause duration in milliseconds (up to 3 standard deviations from the mean) for before (O-B) and inside (B-I and I-I) an entity (left), and after (B-O and I-O) and inside (B-I and I-I) an entity (right). y-axis shows log-normalized counts. Note that the deep purple-grey color is indicative of the red and blue histograms overlapping.
In Seifart et al. (2018) , time-aligned spoken language corpora in multiple languages were compared in terms of speech rate and pause duration. The variable of interest was the difference between nouns and verbs, with the subtlety that nominalisations of verbs still counted as verbs, and (less frequent) verbalisings of nouns counted as nouns. This means the the distinction was close to the traditional semantic distinction of 'object' and 'action' words. Their main findings were that speech rate slows relatively before nouns, and for most languages, pauses are more likely before nouns than before verbs.
We are most interested in the observation about pauses before nouns, as a potential signal for an upcoming named entity sequence. Named entities may not be limited to single nouns, but may be a span of tokens with at least a head noun. We analyze if pauses are more likely and/or longer before (or after) the boundary of an entity span than within the span itself.
We investigate this as follows. We consider a set of utterances from a large internal, anonymous dataset, collected over several months and domains (referred to throughout as UsageData). Given the sampling methodology, it can be concluded that there are no speaker-dependent effects in our dataset. The utterances have been taken from an upstream ASR system which provides each utterance hypothesis with pause durations following each token, in milliseconds. In order to test the findings of Seifart et al. (2018) in the voice assistant setting, we randomly sample UsageData utterances from the sports, movies, and music domains in English and French (referred as EngFrPauseData); see Table 1 for an overview.
Figure 3: Histogram of percentage frequency of pause duration >=60ms on the EngFrPause Data (described in Table 1) per label type for (a) French and (b) English. x-axis marks entity label type and y-axis shows percentage frequency of long pauses. O-B, I-O, and B-O indicate label types at entity span boundaries (before/after entites), and B-I and I-I indicate label types within entity spans.
Figure 4: Illustration of our shallow parser module.
We manually annotate EngFrPauseData with BIO-style tags Ramshaw and Marcus (1995); Tjong Kim Sang and De Meulder (2003) ; O for non-entity, B for beginning of an entity, I for inside an entity. Furthermore, if a token is tagged with a B or I, it contains an additional entity tag (e.g., Artist). We combine the pause information from ASR with the named entity tags to derive pauses before, during, and after an entity. We aggregate pause and token duration statistics across all utterances for all domains in a language and fit distributions for the following pairs of settings: O-B, B-I, I-I, B-O, I-O. For example, an O-B pair marks the pause duration between a token tagged O and the token following it tagged B, while an I-I pair denotes the pause between a token tagged I and the token following it also tagged I.
Figure 5: Pause-Sensitive Contextual Embedding. (a) Joint Utterance Encoder, in which the prediction layer can be (b) HBC, (c) NLR, or absent (baseline).
To analyze whether the study in Seifart et al. (2018) can be extended to spoken entity sequences, we ask whether the pause duration before, within, and after an entity is different in a statistically significant way. To do this, we first log normalize the frequency of pauses before, inside, and after an entity to account for differences in their raw counts. In Fig. 1 and Fig. 2 we plot and compare histograms showing the normalized frequency distributions of pauses before an entity (O-B) and inside an entity (B-I and I-I), and inside an entity and after an entity (B-O and I-O) for French and English respectively. We observe that pauses before uttering and after uttering an entity are longer than pauses within the entity itself.
For French, the mean duration for pause within an entity is 18.17ms, for pause before an entity is 55.04ms, and for pause after an entity is 63.86ms. The differences in mean pause duration for both within and before an entity, and for within and after an entity are found statistically significant using a two sample statistical significance t-test; p-values are 4.59e-34 and 3.97e-20, respectively.
For English, the mean duration for pause within an entity is 15.21ms, for pause before an entity is 33.99ms, and for pause after an entity is 38.08ms. The differences in pause duration are again found to be statistically significant for both before and within an entity (p-value: 7.31e-33), and within and after an entity (p-value: 6.81e-36). These findings are in line with those from Seifart et al. (2018) and suggests that acoustic pauses are indeed a useful and complementary signal to text-based features.
Likewise, in Figure 3, we show the percentage frequency of pauses greater than or equal to 60ms for different types of entity labels. Here, too, we observe that such pauses are more frequent after or before entities (label types O-B, I-O, B-O) as compared to within entities (label types B-I, I-I), for both French (Figure 3a) and English (Figure 3b).
Note that the pause length difference within and outside an entity span tends to be greater in French than in English. Similarly, the difference in frequency of longer pauses at entity boundaries versus within entity spans is greater in French than in English, as can be visualized in Figure 3. We therefore carried out our further experiments on the French data (hereafter, FrPauseData), both for reasons of time, and on the grounds that any effects were more likely to show up there. 111Regrettably, we could not find a public domain dataset with analogous properties so that our findings could be replicated by others, and so we have have presented results on this proprietary data and shared the statistics of our dataset.
3 Shallow Parsing
Our primary downstream setting that consumes contextual embeddings (described in Section 4) comprises of shallow parsing, as a sequence labelling task. It takes text output from an ASR system as the input, and produces an output label for each input token. The labels aim to recognize the intent of the spoken utterance, typically picking out a verb and the phrases that could constitute arguments of the verb. For example, "play thank you next" would be parsed as "play/Verb thank/Song you/Song next/Song".222"thank you next" is the ASR recognition result for the song "Thank u, Next".
In all experiments, we first pass the text output obtained from ASR into either a pre-trained baseline or pause-sensitive contextual embedding (refer Section 4). We pass the so-obtained contextual embedding representations into a relatively simple shallow parsing model. The shallow parser is a sequence tagger model that feeds the contextual embedding corresponding to each text token into a single-layered BiLSTM with a CRF on top, obtaining a predicted label for each token as the output (refer Fig. 4). During training, our shallow parser is optimized by minimizing the Negative Log Likelihood (NLL) over the data. Our shallow parser is identical to that of Muralidharan et al. (2021) , except that we feed the output of the BiLSTM into a CRF layer, which we empirically observe boosts performance in all cases.
4 Pre-training Embeddings with Pause Information
The baseline version of the shallow parser uses a text-only embedding. This embedding is a BERT-style text-based language model Devlin et al. (2019) trained without the next sentence prediction auxiliary task of the original BERT architecture.
To investigate the effect of pauses, we compare the baseline architecture with an identical BERT-based model extended with an additional spoken pause prediction task, as shown in Fig. 5
. We are given, for each utterance, the pauses following each token in milliseconds, and we learn a model jointly optimizing a text-based language modeling task and a token-level pause duration prediction task. We add additional linear projections over intermediary representations from the encoder to predict pause durations following a token. We refer to the encoder as the "Joint Utterance Encoder", and to the linear projection as the "Pause Prediction Layer". We use negative log-likelihood (NLL) for categorical loss and mean squared error (MSE) for regression loss optimizations. We backpropagate the sum of the losses from both the text-based and the speech-based pause prediction tasks into the Joint Utterance Encoder.
We consider two variants of the prediction task:
Hierarchical Bin Classification [HBC]: The task is to perform hierarchical classification where the first linear projection predicts the boolean presence/absence of a pause and the second linear projection maps non-zero pauses (in the case of presence of a pause) into one of three labels: short, medium, and long, indicative of the pause durations.
Normalized Linear Regression [NLR]
: The task is to linearly predict the length of pause (normalized into a range from zero to one) following a token.
More concretely, in a given utterance, let Tb be the set of tokens used to train the BERT-style model using a Masked Language Model (MLM) objective and lbi
be the softmaxed LM prediction for the probability of the
ith token ti. Further, let Ts be the set of tokens on which the pause prediction tasks are to be trained, and for the tthi token, let lci be the predicted probability of the true coarse-grained (presence/absence) label by HBC, let lfi be the predicted probability of the true fine-grained short (S), medium (M), or long (L) label by HBC, let lri be the predicted pause by the NLR module, let 1gci indicate the presence/absence of a pause, and let gri be the true normalized pause duration. Then the baseline BERT-style encoder is trained by minimizing the loss
LBERT=−∑ti∈Tbloglbi. (1)
The loss for the HBC task is
LHBC=−∑ti∈Ts(loglci+1gciloglfi). (2)
The loss for the NLR task is
LNLR=∑ti∈Ts(gri−lri)2. (3)
The joint loss is LBERT+λLHBC or LBERT+λLNLR respectively, where λ is a weighting factor set to 1 in our experiments.
5 Experimental Design
+0.47% +0.22% -2.34%
-2.83% -2.78% -0.57%
Table 2: Relative percent change in error rates for Shallow Parser with pause-sensitive embeddings. Boldface marks best performance for domain and metric.
In our experiments, we compare the parser with the baseline version of text-only embeddings against a version using embeddings enhanced with pause information (HBC and NLR). This is the only difference between the two systems: the speech pause signals used to pre-train the embeddings are not used directly in the parser. Neither the baseline version nor the pause-sensitive embeddings are fine-tuned in the parser.
For pre-training the BERT-style language models, we train over a random sample from the French section of UsageData without entity annotations ('FrTrainData'). FrTrainData contains about 50 million utterances with token-level ASR feature tuples consisting of recognized text and post-token pause duration (in milliseconds) for each input point.
To generate label boundaries for the HBC task, we sort pause durations in FrPauseData in ascending order and divide the resulting list of pauses into three parts with an equal number of data points. These serve as the label boundaries for the S, M, and L length labels for HBC. Empirically, pause durations less than 60ms are labeled as S, those between 60ms and 310ms are labeled as M, and those greater than 310ms are labeled as L. During training, we discard any pause greater than 10,000ms as noise from upstream ASR. For NLR, we normalize the pauses between 0 and 1 by dividing each duration by 10,000ms (the longest pause duration in the pruned dataset).
For the classification task, we opt for HBC to address the class imbalance problem in our data Tsagkias et al. (2009) (see Figure 1
, which shows a large proportion of tokens with zero pause detected). This coarse-to-fine approach helps with learning the presence/absence of pauses (coarse label) over the skewed dataset while also allowing the auxiliary S/M/L prediction (fine label) to be sufficiently fine-grained to prove useful in improving the feature representation.
To train the embeddings, we consider a vocabulary of the 100k most frequent tokens in FrTrainData. To train the pause prediction layers, we predict the labels over a subset of tokens per utterance. We randomly sample 15% of the tokens per utterance up to a maximum of 3 tokens, including at least one token with a non-empty label (words not contributing to the user intent are given a null label by the shallow parser). We backpropagate the sum of losses from the text-prediction and the pause-prediction tasks to the Joint Utterance Encoder.
We evaluate system performance on shallow parsing with three error rate measures at entity, token, and utterance levels:
Entity Error Rate (EER) measures the proportion of incorrectly labeled entities out of all entities.
Token Error Rate (TER) measures the proportion of incorrectly labeled entities out of all tokens (both entities and non-entities).
Utterance Error Rate (UER) measures the proportion of utterances with at least one mislabeled entity.
We report all metrics as means over 10 runs for each model configuration.
We compare the performance of our pause-sensitive model with that of our baseline text-based BERT architecture in Table 2. Our best performing model consistently outperforms the baseline with an improvement in error rates on entity, token, and utterance levels across all three domains under study. We note that NLR consistently provides a greater improvement over HBC. This is in line with our expectations since user requests to a voice assistant are typically short utterances with small inter-token pauses (Table 1) across domains. Unlike the regression objective of the NLR model which is trained on exact pause durations scaled between 0 and 1, to train over the classification objective of HBC, we discretize these pause durations into four classes losing the granularity of small variations in these recorded pauses.
Looking at performance across domains, we observe that improvement in EER and TER for the Movies domain is consistently higher than that for Music and Sports. We look at FrPauseData to find that entity names in the Movies domain typically contain longer sequences of tokens than entities for the Music and Sports domains, where bynames and abbreviations are often used. On average, entity spans in the Movies domain are relatively longer than entity spans in Music by 49.64%, and in Sports by 39.71% in our dataset. For example, the majority entity span type in the Movies domain is 'movie title' which on average consists of 2.54 tokens and makes 34% of the domain. This token length is more than double that of the majority label type 'team name' in the Sports domain which makes 60% of the domain and contains 1.25 tokens on average. We note a similar pattern on observing the top-3 most frequent entity types per domain. For example, the mean token length for the top-3 most frequent labels in the Movies domain is 2.43 tokens compared with only 1.59 tokens in the Music domain. This relates with our earlier experiment with FrPauseData—we noted a longer mean pause duration of 120.23ms for Movies, compared with 39.06ms for Music, and 29.38ms for Sports. We hypothesize that longer sequences of entity names cause speakers to make longer pauses around these entity spans.
Finally, since the NLR model improves performance across all domains under study, we emphasize that it can be used in settings where a pre-trained set of embeddings are shared across multiple applications, which is particularly relevant in open-topic voice assistant NLU systems where the domain of a user request is ascertained at run time.
In this paper, we analyzed the statistically significant correlation of pause lengths with syntactic properties in real-world usage data for three entity-rich application domains. To exploit this property, we presented a novel pause-sensitive contextual embedding model. The model outperforms text-based representations in a language processing task across multiple domains. Our approach does not impose additional task-specific annotation requirements and can be extended to more text-based target tasks. To the best of our knowledge, this is the first study on grounding textual representations in pause signals for improved understanding in voice assistants.
The authors would like to thank Barry Theobald, Murat Akbacak, Lin Li, Sachin Agarwal, Anusha Kamath, John Bridle, Aaksha Meghawat, Melvyn Hunt, and Ahmed Hussen Abdelaziz for their help and feedback.
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