Description: 21st Century Oncology is a business categorized under testing laboratories, which is part of the larger category testing laboratories. 21st Century Oncology is located at the address 130 Carnie Boulevard Suite 1 in Voorhees, New Jersey 08043-4521. You can contact by phone (856)325-3000.
Location & access map for "21st Century Oncology"


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Q: struts2 action redirect to "outside" url i need my action to be able to redirect to outside url address, lets say for exemple http://google.com
Right now i have:
<default-action-ref name="home" />
<global-results>
  <result name="redirect" type="redirect">${targetUrl}</result>
</global-results>

if in targetUrl i have http://google.com my action will call home page and it iwll not redirect to google.
I saw the similar question here
How to do dynamic URL redirects in Struts 2?
but I can see that only the last part of url is being used as a destination for the redirection.
can you please help me?
thanks

A: To redirect to a specific action from an interceptor I did the following:
response.sendRedirect("specificAction.action");
return null;

No need for global results in this case.

A: This will solve your question.
From the Action class from you returning the redirect the targetUrl should be member variable for the class and should have public getter and setter.
public class YourAction extends ActionSupport {
    private String targetUrl;

    public String execute() {
         return "redirect";
    }

    public String getTargetUrl() {
        return targetUrl;
    }

    public void setTargetUrl(String targetUrl) {
        this.targetUrl = targetUrl;
    }

}

A: You can do this by using the Http Header result type. That will work because a redirect instruction to the browser is simply a status code plus 'Location' header.
<result name="startCheckout" type="httpheader">
    <param name="status">303</param>
    <param name="headers.location">${externalUrl}</param>
</result>

redpajama_set_name: RedPajamaStackExchange


The Bridage over the years has recognised a small group of members that have provided extraordinary service to the brigade and our community at large.
Details of these past and present members along with a citation of their service are shown below.
All members of the brigade acknowledge that there concerted efforts see us in the position we are today.
Peter was born in Batemans Bay and spent time on the land in the Mittagong area, helping to fight fires from a young age. He returned to Malua Bay where he was building a house in 1978.
A bush fire came through a couple of years later from Dunns Creek Road and impacted on the back of Malua Bay. Peter, along with anyone else who was available, jumped on a truck to help, and at the end of the day, he was asked to take over leadership of the brigade. Peter has been involved in the Malua Bay brigade for over 30 years and is a "life member" of the Brigade.
Helen was a member of St John Ambulance for many years before joining the Malua Bay Brigade. She has served in the brigade since 1997, and has held the offices of Secretary and Treasurer for most of the past 12 years.
Apart from brigade activities, Helen is a member of the Eurobodalla Volunteer Operations Support Group, doing radio communications for big fires and aviation at Fire Control. Helen is actively involved in Community Engagement and is a delegate for the RFSA.
Helen is also a member of EVOS.
To recognise Helen's service to the brigade she has been made a life member.
Martin takes time out of his plumbing business to lead crews, mentor members and be an active ongoing member ready to assist whenever needed. He's been a volunteer with MBRFB for over 30 years and has held various position including being the Captain from 2008 until 2015, He also acted as Captain during the latter part of 2015 when the brigade Captain was overseas. He is a very experienced brigade member and has been awarded "life membership" of the Brigade.
He has experienced many of the major bush fires in that time, like the 1994 fires, and 'Section 44s' in the Deua National Park as well as attending most of the house fires and motor vehicle accidents in his area.


Think about coming and getting your groceries for the week, grabbing some lunch, picking up some awesome plant starts for your garden, getting some face painting done, and screenprinting an old shirt or tote bag. The Market is such a hub for this neighborhood and it is turning 8 years old…it's time to celebrate!
There are a lot of folks working to make this celebration free and inclusive. We want to make sure we can welcome all of our neighbors and friends. Please donate today to help us make sure this event is a success. We will have a tote bag to gift you for any donation over $25.


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Q: Android automatic SQL insert How can I create a DB table and fill it up with some data onto application startup?I have a init_sql.sql file with create table and insert statements but only CREATE TABLE is executed so I have my table but it is empty.
init_sql.sql
CREATE TABLE IF NOT EXISTS Event (
   id INTEGER PRIMARY KEY NOT NULL,
   time TEXT NOT NULL,
   name TEXT NOT NULL,
   description TEXT NOT NULL,
   additional_info TEXT,
   stage CHAR(50)
);

INSERT INTO Event (name, time, description, stage)
VALUES ('13:30 - 14:30', 'koncert Blue tone Band',
 'Mladá, energická jazzfunková kapela Blue tone Band Vás pobaví a rozhýbe zaručeně každého absolventa!', 'mainStage');

I verified that this file is correct by issuing sqlite3 myDb.db < init_sql.sql, this creates the table and inserts data.
My SQLHelper looks like this
public class SQLiteHelper extends SQLiteOpenHelper {

public static final String DB_NAME = "alumni.db";

private Context context;

public SQLiteHelper(Context context) {
    super(context, DB_NAME, null, 6);
    this.context = context;
}

@Override
public void onCreate(SQLiteDatabase db) {
    InputStream stream = context.getResources().openRawResource(R.raw.init_sql);
    try {
        String sqlString = convertStreamToString(stream);
        db.execSQL(sqlString);
    } catch (IOException ex) {
        //TODO
    }
}

@Override
public void onUpgrade(SQLiteDatabase db, int oldVersion, int newVersion) {
    db.execSQL("DROP TABLE IF EXISTS Event;");
    onCreate(db);
}

And I am using it inside my DAO class like new SQLiteHelper(context).getWritableDatabase();
So any ideas what could I've been doing wrong?

A: execSql executes a single SQL command.
When you want to execute multiple commands, you have to execute them separately.
A better idea might be to ship the precreated database with the app.
(In that case, consider using SQLiteAssetHelper.)


Creative Resume Templates Free Download, here is the latest Example on Creative Resume Templates Free Download This example can be your reference when you are confused to write the right Sample Resume Format for your Cover Letter. This Creative Resume Templates Free Download is just one of many Sample Resume Template we have in this site. If you need more Sample Resume Example or Cover Letter Template, don't forget to always visit Cometmerch.com to get the latest update and new Sample Resume Template or Cover Letter Design and more.
Resume Sample For College, here is the latest Example on Resume Sample For College This example can be your reference when you are confused to write the right Sample Resume Format for your Cover Letter. This Resume Sample For College is just one of many Sample Resume Template we have in this site. If you need more Sample Resume Example or Cover Letter Template, don't forget to always visit Cometmerch.com to get the latest update and new Sample Resume Template or Cover Letter Design and more.
Sample Resume For A Social Worker, here is the latest Example on Sample Resume For A Social Worker This example can be your reference when you are confused to write the right Sample Resume Format for your Cover Letter. This Sample Resume For A Social Worker is just one of many Sample Resume Template we have in this site. If you need more Sample Resume Example or Cover Letter Template, don't forget to always visit Cometmerch.com to get the latest update and new Sample Resume Template or Cover Letter Design and more.
Examples Of Resumes For First Job, here is the latest Example on Examples Of Resumes For First Job This example can be your reference when you are confused to write the right Sample Resume Format for your Cover Letter. This Examples Of Resumes For First Job is just one of many Sample Resume Template we have in this site. If you need more Sample Resume Example or Cover Letter Template, don't forget to always visit Cometmerch.com to get the latest update and new Sample Resume Template or Cover Letter Design and more.
Human Resources Sample Resume, here is the latest Example on Human Resources Sample Resume This example can be your reference when you are confused to write the right Sample Resume Format for your Cover Letter. This Human Resources Sample Resume is just one of many Sample Resume Template we have in this site. If you need more Sample Resume Example or Cover Letter Template, don't forget to always visit Cometmerch.com to get the latest update and new Sample Resume Template or Cover Letter Design and more.
Acting Resume Template For Microsoft Word, here is the latest Example on Acting Resume Template For Microsoft Word This example can be your reference when you are confused to write the right Sample Resume Format for your Cover Letter. This Acting Resume Template For Microsoft Word is just one of many Sample Resume Template we have in this site. If you need more Sample Resume Example or Cover Letter Template, don't forget to always visit Cometmerch.com to get the latest update and new Sample Resume Template or Cover Letter Design and more.
Business Resume Sample, here is the latest Example on Business Resume Sample This example can be your reference when you are confused to write the right Sample Resume Format for your Cover Letter. This Business Resume Sample is just one of many Sample Resume Template we have in this site. If you need more Sample Resume Example or Cover Letter Template, don't forget to always visit Cometmerch.com to get the latest update and new Sample Resume Template or Cover Letter Design and more.
Free Resume Templates Word, here is the latest Example on Free Resume Templates Word This example can be your reference when you are confused to write the right Sample Resume Format for your Cover Letter. This Free Resume Templates Word is just one of many Sample Resume Template we have in this site. If you need more Sample Resume Example or Cover Letter Template, don't forget to always visit Cometmerch.com to get the latest update and new Sample Resume Template or Cover Letter Design and more.
Resume Sample Templates, here is the latest Example on Resume Sample Templates This example can be your reference when you are confused to write the right Sample Resume Format for your Cover Letter. This Resume Sample Templates is just one of many Sample Resume Template we have in this site. If you need more Sample Resume Example or Cover Letter Template, don't forget to always visit Cometmerch.com to get the latest update and new Sample Resume Template or Cover Letter Design and more.
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Despite the trends and fads in fashion, it's true that some clothing items are true classics and never go out of style: a black suit, a basic white tee, dark wash jeans. One of these pieces is the well-known and much loved button-down collar, worn for decades by everyone from athletes and politicians to celebrities.
In the late 19th century, polo players traditionally wore collared Oxford shirts on the field. When the players rode their horses, their collars would flap around in the wind. Not only did this interfere with their playing, but it was considered visually unappealing by those watching.
During one match, John E. Brooks, of Brooks Brothers fame, noticed that some players had sewn buttons onto their collars to keep them down and out of the way. Liking the look, Brooks brought it back to the U.S. and in 1896 he produced the iconic button-down polo shirt. This shirt became one of Brooks Brothers' most iconic pieces. Initially worn by the wealthy as formal attire, athletes everywhere were soon drawn to this style for the very same reasons as the original polo players. In short order following its introduction, the button-down collar was established as a menswear staple.
Fast forward to the 21st century and this style of shirt is still hanging in our closets. What's made the button-down collar timeless is its versatility. Due to its historical connection to sport and its association with American collegiate look, this collar is generally considered a preppy, casual style. But just as fashion rules were made to be broken, this style can be dressed both up or down. While a few may consider the combination of a suit and button-down collar a fashion faux pas, this combination looks great when it is done right and can be seen on men of style everywhere.
To keep things casual, pair your button-down collar with a knit cardigan and denim jeans, leaving the uppermost button of the collar open. For a more formal but fashion-forward look, try sporting it with a checkered suit and dotted knit tie. While there is debate on whether or not you can wear a tie with a button-down collar, there's no issue if you stick with a more casual jacket option. It's important to remember that the roll of the collar should still be soft—reserve the stiff collar for more formal shirting.
Time and again, the button-down collar has proven itself to be a versatile style essential. From the polo player to the CEO, this classic collar style is a go-to for men everywhere.


text:
Home » News » AEW News and Rumors » Konnan Compares MJF To The Rock
Konnan Compares MJF To The Rock
in AEW News and Rumors
Speaking on a recent episode of his Keepin' It 100 podcast, former WCW star Konnan heaped praise on MJF.
The veteran said that MJF is one of the main reasons that people tune into AEW, leading him to compare the AEW World Champion to the likes of The Rock and John Cena.
"So he's like a supernova burning bright. Like, you know, at one time Shawn Michaels or Eddie [Guerrero] or Cena or The Rock. He's a great talent with natural talking talent and charisma. He's got a swag, confidence, his delivery. He's just great at such a young age, and he can command a crowd in a room. I'm very happy for him. He's one of the main reasons that people watch AEW because his segments are always fire,"
Quotes via SportsKeeda
Kenny Omega Responds To Jake Roberts Calling Him One Of The Best Ever: "High Praise From An Absolute Master of Psychology"
Jim Cornette Thinks Lana Is Serious About Miro Re-Joining WWE
Josh Alexander Becomes Longest Reigning IMPACT World Champion In History, IMPACT and more Comment On Alexander's Reign

redpajama_set_name: RedPajamaCommonCrawl


text:
Blockchain Technologies: Current State and Key Insights
BlockchainApplied ResearchDigitalization
Outstanding quotes from SPIEF 2019: Forum participants on business and human capital
Sergey Kirienko, Andrei Belousov, Svetlana Chupsheva, Kirill Dmitriev, Konstantin Chuychenko, Boris Titov, Tatyana Golikova, Veronika Skvortsova, Vitaly Mutko, Sergei Sobyanin
FriendsforLeadershipMoscowEntrepreneurshipRegions of RussiaThe City of St. PetersburgSustainable Development
Igor Levitin
Aide to the President of the Russian Federation
Dmitry Chernyshenko
Mikhail Murashko
Minister of Health of the Russian Federation
Maksim Reshetnikov
Minister of Economic Development of the Russian Federation
Alexey Miller
Chairman of the Management Committee, Deputy Chairman of the Board of Directors, Gazprom
Vladimir Evtushenkov
Entrepreneur, founder and largest shareholder of AFK Sistema
Vladimir Potanin
President, Chairman of the Management Board, Norilsk Nickel
Sergey Gorkov
General Director, Chairman of the Management Board, Rosgeo
Maxim Akimov
Chief Executive Officer, Russian Post
Eastern Economic Forum 2019
Central Russia: New Opportunities for Investors
KEY CONCLUSIONS
A package of investment projects in priority industries has been created for the Central Federal District
As of the beginning of September, the Investment Council has created a portfolio of 208 projects worth a total of USD 15 billion. This is the first project for proposals. An online resource has been specially developed (selectcr.site) — Igor Shchegolev, Presidential Plenipotentiary Envoy to the Central Federal District.
The project portfolio covers 12 sectors of the economy, and encompasses 208 projects which are already in a position to attract investment. <...> The average return on projects in this portfolio is 10–35%, depending on the sector — Sergei Kachaev, Co-Chairman, Council on Investment Authorized in the Central Federal District .
The Central Federal District has the infrastructure needed for investors
Central Russia has 15,000 hectares of industrial land with transport and utilities infrastructure in place. It also has 7 special economic zones, 16 regions with special tax and administrative regimes, 136 industrial parks, and 193 individual plots with fully developed infrastructure — Sergei Kachaev, Co-Chairman, Council on Investment Authorized in the Central Federal District .
Trade between Central Russia and countries of the Far East is growing at a rapid rate
Last year, trade with Japan increased by 21%, with South Korea by 34%, and with China by 35%. In addition, talks took place in June this year between the leaders of Russia and China. <...> A new form of interregional collaboration between the Central Federal District and Northern China was announced — Igor Shchegolev, Presidential Plenipotentiary Envoy to the Central Federal District.
All aspects related to transport have been solved, trains regularly travel to all ports in China, and we have seen the first trains travel to Japan, Vietnam, and India. <...> Today will see the signing of a deal <...> related to the new so-called 'agro-train — Vladimir Potemkin, Deputy Governor of Kaluga Region.
The Central Russian economy possesses considerable investment potential
A fundamental driver of growth will be <...> the number of cars per 1,000 people. In Russia, the figure is half that of Europe. That is why the Russian automotive market must grow in the long term — Maxim Kondratyev, Chief Executive Officer, Alfa Automative Technologies.
Why is the chemicals industry in Central Russia attractive to investors? First of all, it accounts for sizeable part of the market at USD 72 billion. Chemicals are used substantially. <...> We export chemical products worth a total of USD 8 billion — Sergei Kachaev, Co-Chairman, Council on Investment Authorized in the Central Federal District .
Central Russia not only opens for me the whole of Russia, but also the CIS. <...> My aim is to maximize exports from here — Rajesh Sharma, Chief Executive Officer, Advanced Group.
Central Russia offers highly qualified personnel
We have a highly productive workforce concentrated in Central Russia. Forty per cent of our workers are university educated, and we have the biggest research centres, which can aid scientific developments in the chemicals industry — Sergei Kachaev, Co-Chairman, Council on Investment Authorized in the Central Federal District .
Why did we come to Belgorod? We signed an agreement, but other reasons were that in our field we require manpower, and Belgorod University is one of the universities in Russia which is giving out a lot of good professionals. What also interested us in Belgorod was the infrastructure. Already there existed a polyvitamin factory — Rajesh Sharma, Chief Executive Officer, Advanced Group.
Qualification requirements for local and regional managers are increasing
Success depends greatly on the work done by local and regional teams who support these projects. <...> Regional support measures and services in the regions of Central Russia are constantly adapting to new conditions. They are improving — Artur Niyazmetov, Deputy Presidential Plenipotentiary Envoy to the Central Federal District .
The need to improve the urban environment
The second priority is the quality of the urban environment. People don't just work at our enterprises, they live in the city. <...> A pleasant environment is very often the deciding factor for an investor, — Denis Tikhonov, Minister of the Moscow Government, Head of the Department of Economic Policy and Development of the City of Moscow.
Simplifying bureaucratic procedures
With regards the Construction Support Centre, we brought together representatives from all agencies responsible for issuing permits at one site. And there are a great many such agencies. <...> We agreed that all these documents could be sent electronically. <...> We have agreements with representatives of federal government bodies whereby we can receive answers regarding the approval of projects within 15–30 days maximum, rather than the standard 60 days. <...> A personal manager helps coordinate our interactions with all department — Vadim Khromov, Deputy Chairman of the Moscow Region Government.
My experience is that there is a lot of help which you can get. If we can create one window for the investors, then this will help the investor understand the climate, to get all the information, and decide fast — Rajesh Sharma, Chief Executive Officer, Advanced Group.
Involving several regions in projects from the start
We view the investment plans of 18 regions as a comprehensive proposal to investors from the entire district. The investor has the option of increasing returns on a project through leveraging the advantages offered by each region. One place may have lower energy tariffs, while somewhere else may have the requisite infrastructure already in place. <...> By involving several regions from the start, we can significantly expand the range of profitable business sectors — Igor Shchegolev, Presidential Plenipotentiary Envoy to the Central Federal District.
Comprehensive government support for investments
When factories are constructed, we compensate part of the expenses which have gone on putting utilities infrastructure in place. Once the factory is commissioned, we refund up to 10% of the cost of the project — Vadim Khromov, Deputy Chairman of the Moscow Region Government.
Moscow Region has added an online calculator to the new investment portal <...> to help ascertain the value of government support. The investor specifies <...> a range of parameters for their project, and they are immediately shown a package of government services they can take advantage of — Artur Niyazmetov, Deputy Presidential Plenipotentiary Envoy to the Central Federal District .
The material was prepared by the Russian news agency TASS


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Police bid to trace missing 12-year-old thought to be with her father
Tess de La Mare
Leona Peach, 12, is missing from her home in Newton Abbot (Devon and Cornwall Police/PA)
Police are searching for a 12-year-old girl who has been missing for more than a week and is thought to be with her father.
Leona Peach was last seen in the Hele Park area of Newton Abbot in Devon on the morning of Monday December 20.
It is believed she may have left home to be with her father Billy Peach, who lives in Bideford, north Devon.
Devon and Cornwall Police are appealing for Mr Peach or Leona to get in touch with them, or Leona's family in Newton Abbot, to let them know she is safe.
Members of the public with any information on their whereabouts are also asked to come forward.
Leona is white, around 4ft 9in, of slim to medium build with hazel eyes.
Leona was last seek (Devon and Cornwall Police/PA)
She has long, light-brown hair and a bald patch above her right ear.
Leona was last seen wearing grey or blue leggings or skinny trousers, a dark-coloured fur coat, flip-flops and was carrying a pink bag.
Detective Inspector Dave Pebworth said: "Inquiries are continuing in our efforts to locate Leona and we are asking the public to help us.
"We would ask Mr Peach to get in touch as we believe he may be able to help us with our inquiries.
"We are supporting her friends and family and are appealing to Leona to contact home so that they know that she is safe and well.
"We would ask that anyone who is with her encourages Leona to contact her family in Newton Abbot.
"Leona if you are reading this, we want you to know you are not in any trouble, please contact us, or someone you trust, to let us know you are safe."
Anyone with any information should contact police on 999 quoting log number 0222 of December 20.
'We've Been Forgotten': 5-Day Isolation Leaves Clinically Vulnerable Fearing For Their Lives
"That one action can literally kill someone else."
Carer suffocated suspected burglar during citizen's arrest, court hears
Nathan Smith is accused of the manslaughter of Craig Wiltshire after he knelt on his back for nine minutes.
PA Media: Science
Asteroid bigger than any building on Earth to soar past the planet
Called 7482 (1994 PC1), the asteroid is more than a kilometre wide.


DhAnAnJAy pArKhe℠Author, Speaker, Educator, Advisor, Independent Director, Mentor to Startups and C-Suite. Mentor for Change - Atal Innovation Mentor for AIM- NITI AYOGWhat's New?
Posted in R&R- Read and Recommend | Tagged # 0 Daily Blog #0 10 Top ListVerse Newsletter New Advances New Ideas New Learning Newsletter of the Day Political Commentary R&R- Read and Recommend What's New?


Description: Sail with us across an interactive storytelling exploration of a swashbuckling new adventure about pirates, treasure, and friendship. Suitable for children age 2-5 years. £2 per child call 01904 552828 to book.


It will be recalled that the President made the announcement at the Council Chambers, Presidential Villa, Abuja. In Onnoghen's place, Buhari immediately named Justice Ibrahim Tanko Muhammed, who is from Bauchi State, as the new CJN.
We now have photos from the moment President Buhari swore the man in. These new photos were released on the verified page of the Presidency on Twiter.


text:
Artist, Blog Tour, Book Review, Celebrity, Contemporary, Contemporary Romance, Enemies-to-lovers, Entrepreneur, Family, Farmer, Friendship, Happiness, Loneliness, Relationships, Romance, Strong Heroine, Swoony Hero, Unrequited Love
Home at Summer's End by Alys Murray | #BlogTour #BookReview @writeralys @Bookouture #NetGalley #ContemporaryRomance
Flower-shop-girl meets Hollywood Star
Today, we are thrilled to be the stop on the Blog Tour for Home at Summer's End by Alys Murray.
Our thanks to Bookouture and NetGalley for the advanced reader's copy.
Home at Summer's End is a story of loving people for what they really are, despite all misleading appearances.
Title: Home at Summer's End by Alys Murray.
Publisher: Bookouture (October 15, 2020)
Print Lenght: 249 pages
ASIN: B08F7VJBRC
Rose Anderson is done with being known as "the nice one" in the small town in Northern California where she lives. She's done with playing third, fifth, seventh wheel at loud gatherings on her family's flower farm. And most of all, she is done with the pitying looks and well-meaning comments she gets about her single status from the way-too-interested townsfolk.
No one seems to care that she's single by choice. That she actually enjoys going to bed early with a good book—love stories are always better in fiction anyway. Busy with her flower arranging business, Rose has no time for a man, thank you very much. So when news spreads that Hillsboro is being used to shoot an upcoming Hollywood movie, Rose gets an idea. One that will appease her family while keeping her heart safely intact…
Cole McKittrick is trying to keep calm. So what if he quit a steady TV gig for a shot at his dream, was dumped by his superstar girlfriend and—having just read the fifteenth script re-write—is now convinced this movie is going to be career-ending? It's all about perspective. And when he meets the beautiful Rose Anderson, he can't believe his luck. She'll help him fix his lines, pose for a few shots to make his ex jealous, and all for the bargain price of a few fake dates.
But in a town like Hillsboro, the resident beauty queen and Hollywood's hottest bachelor can't expect a plan like this to work. And the more time they spend together under the scrutiny of their neighbors, the more blurred the lines become between what's real and what's fake.
But Cole has been hiding a big secret from his past. And when Rose finds out could it spell CUT for their picture-perfect romance, or will she realize that he has taken over not just her home, but her heart…?
A fun, charming romance about family and finding the one, perfect for fans of Robyn Carr, Debbie Macomber and Carolyn Brown.
Amazon | Apple | Kobo | Google
Rose Anderson owned a flower shop in a small town selling the flowers produced on her family's farm.
She loved the peaceful and quiet town and was content with her life choices. She wished her family and friends would understand that, instead of keeping matchmaking and worrying about her absent love life.
Their intentions were good, but they were quite over the top.
Rose's friend Annie, a social media mogul, went as far as to set Rose up on a date with Cole McKittrick, a beautiful Hollywood star in town to film a movie.
Rose and Cole had nothing in common. He was a celebrity trying to recover from a public breakup, and Rose wanted nothing to do with the spotlight.
Thrown together, Rose and Cole agreed on a fake relationship to end her family meddling. Rose, in return, would help Cole developing his romantic role in the movie and making his ex jealous.
The story is very romantic. Two people with preconceived ideas about each other slowly getting close and seeing beyond mere appearances.
I like that together they found balance and figured out what is really important in life.
I'm a sucker for fake relationships, and Home at Summer's End is a sweet and romantic read.
Alys Murray is an author who writes for the romantic in all of us. Though she graduated with a degree in Drama from NYU's Tisch School of the Arts and a Master's in Film Studies from King's College London, her irrepressible love of romance led her to a career as an author, and she couldn't be happier to write these stories!
Her debut novel, The Christmas Company, was the first original Christmas novel published by Hallmark, and it is currently optioned for a future Hallmark Christmas movie. Additionally, Alys pens screenplays for Lifetime. You can see her work most recently in 2019's Christmas in Louisiana, starring Jana Kramer, Percy Daggs III, Moira Kelly, Dee Wallace, and Barry Bostwick.
She enjoys kissing books, Star Wars, and reminding people that Michael Bay has two movies in the Criterion Collection. Tobey Maguire is her Spider-Man.
 Website| Twitter | Instagram | Facebook | Goodreads
Tagged Blog Tour, Book Review, Contemporary Romance, NetGalley
Previous postA Christmas Reunion in Paris by Liz Fielding | #BlogTour #BookReview @lizfielding @HarlequinBooks @MillsandBoon @Rararesources #NetGalley #RomCom
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6 thoughts on "Home at Summer's End by Alys Murray | #BlogTour #BookReview @writeralys @Bookouture #NetGalley #ContemporaryRomance"
Sounds like a nice light summer read! Nice review!
Thanks for reading, Brooke 😉
Sounds like a great book. Love when characters fake something and it ends up being real.
Thank you, Mae 😉
Discovering the real selves is what life is all about. Good review, Lu. 🙂
Thank you, Debjani 😉


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text:
package org.condast.wph.core.model;

import org.condast.commons.data.latlng.LatLng;
import org.condast.symbiotic.core.def.ITransformation;
import org.condast.wph.core.def.IIntervalProcess;
import org.condast.wph.core.def.IStakeHolder;
import org.condast.wph.core.definition.IModel.ModelTypes;

public class StakeHolder<I,O extends Object> implements IStakeHolder<I, O> {

	private IIntervalProcess<I, O> process;
	private ModelTypes model;
	private LatLng latlng;

	public StakeHolder( IIntervalProcess<I, O> process, ModelTypes model, LatLng latlng ) {
		this.process = process;
		this.model = model;
		this.latlng = latlng;
	}

	@Override
	public int compareTo(IStakeHolder<I, O> arg0) {
		int compare = (int)( this.latlng.getLongitude() - arg0.getLnglat().getLongitude())*1000;
		return compare;
	}

	@Override
	public String getName() {
		return process.getName();
	}

	@Override
	public ModelTypes getModel() {
		return model;
	}

	@Override
	public LatLng getLnglat() {
		return latlng;
	}

	@Override
	public void next(long time ) {
		process.next(time);
	}

	@SuppressWarnings("unchecked")
	@Override
	public ITransformation<I, O> getTransformation() {
		ITransformation<I, O> trf = (ITransformation<I, O>) process;
		return trf;
	}

}

redpajama_set_name: RedPajamaGithub


text:
\section{Credits}

This document has been adapted from the instructions
for earlier ACL and NAACL proceedings,
including
those for
NAACL 2019 by Stephanie Lukin and Alla Roskovskaya,
ACL 2018 by Shay Cohen, Kevin Gimpel, and Wei Lu,
NAACL 2018 by Margaret Michell and Stephanie Lukin,
2017/2018 (NA)ACL bibtex suggestions from Jason Eisner,
ACL 2017 by Dan Gildea and Min-Yen Kan,
NAACL 2017 by Margaret Mitchell,
ACL 2012 by Maggie Li and Michael White,
those from ACL 2010 by Jing-Shing Chang and Philipp Koehn,
those for ACL 2008 by JohannaD. Moore, Simone Teufel, James Allan, and Sadaoki Furui,
those for ACL 2005 by Hwee Tou Ng and Kemal Oflazer,
those for ACL 2002 by Eugene Charniak and Dekang Lin,
and earlier ACL and EACL formats.
Those versions were written by several
people, including John Chen, Henry S. Thompson and Donald
Walker. Additional elements were taken from the formatting
instructions of the \emph{International Joint Conference on Artificial
  Intelligence} and the \emph{Conference on Computer Vision and
  Pattern Recognition}.

\section{Introduction}

The following instructions are directed to authors of papers submitted
to ACL 2019 or accepted for publication in its proceedings. All
authors are required to adhere to these specifications. Authors are
required to provide a Portable Document Format (PDF) version of their
papers. \textbf{The proceedings are designed for printing on A4
paper.}

\section{General Instructions}

Manuscripts must be in two-column format.  Exceptions to the
two-column format include the title, authors' names and complete
addresses, which must be centered at the top of the first page, and
any full-width figures or tables (see the guidelines in
Subsection~\ref{ssec:first}). \textbf{Type single-spaced.}  Start all
pages directly under the top margin. See the guidelines later
regarding formatting the first page.  The manuscript should be
printed single-sided and its length
should not exceed the maximum page limit described in Section~\ref{sec:length}.
Pages are numbered for  initial submission. However, \textbf{do not number the pages in the camera-ready version}.

By uncommenting {\small\verb|\aclfinalcopy|} at the top of this
 document, it will compile to produce an example of the camera-ready formatting; by leaving it commented out, the document will be anonymized for initial submission.  When you first create your submission on softconf, please fill in your submitted paper ID where {\small\verb|***|} appears in the {\small\verb|\def\aclpaperid{***}|} definition at the top.

The review process is double-blind, so do not include any author information (names, addresses) when submitting a paper for review.
However, you should maintain space for names and addresses so that they will fit in the final (accepted) version.  The ACL 2019 \LaTeX\ style will create a titlebox space of 2.5in for you when {\small\verb|\aclfinalcopy|} is commented out.

\subsection{The Ruler}
The ACL 2019 style defines a printed ruler which should be presented in the
version submitted for review.  The ruler is provided in order that
reviewers may comment on particular lines in the paper without
circumlocution.  If you are preparing a document without the provided
style files, please arrange for an equivalent ruler to
appear on the final output pages.  The presence or absence of the ruler
should not change the appearance of any other content on the page.  The
camera ready copy should not contain a ruler. (\LaTeX\ users may uncomment the {\small\verb|\aclfinalcopy|} command in the document preamble.)

Reviewers: note that the ruler measurements do not align well with
lines in the paper -- this turns out to be very difficult to do well
when the paper contains many figures and equations, and, when done,
looks ugly. In most cases one would expect that the approximate
location will be adequate, although you can also use fractional
references (\emph{e.g.}, the first paragraph on this page ends at mark $108.5$).

\subsection{Electronically-available resources}

ACL provides this description in \LaTeX2e{} (\texttt{\small acl2019.tex}) and PDF
format (\texttt{\small acl2019.pdf}), along with the \LaTeX2e{} style file used to
format it (\texttt{\small acl2019.sty}) and an ACL bibliography style (\texttt{\small acl\_natbib.bst})
and example bibliography (\texttt{\small acl2019.bib}).
These files are all available at
\texttt{\small http://acl2019.org/downloads/ acl2019-latex.zip}.
 We
strongly recommend the use of these style files, which have been
appropriately tailored for the ACL 2019 proceedings.

\subsection{Format of Electronic Manuscript}
\label{sect:pdf}

For the production of the electronic manuscript you must use Adobe's
Portable Document Format (PDF). PDF files are usually produced from
\LaTeX\ using the \textit{pdflatex} command. If your version of
\LaTeX\ produces Postscript files, you can convert these into PDF
using \textit{ps2pdf} or \textit{dvipdf}. On Windows, you can also use
Adobe Distiller to generate PDF.

Please make sure that your PDF file includes all the necessary fonts
(especially tree diagrams, symbols, and fonts with Asian
characters). When you print or create the PDF file, there is usually
an option in your printer setup to include none, all or just
non-standard fonts.  Please make sure that you select the option of
including ALL the fonts. \textbf{Before sending it, test your PDF by
  printing it from a computer different from the one where it was
  created.} Moreover, some word processors may generate very large PDF
files, where each page is rendered as an image. Such images may
reproduce poorly. In this case, try alternative ways to obtain the
PDF. One way on some systems is to install a driver for a postscript
printer, send your document to the printer specifying ``Output to a
file'', then convert the file to PDF.

It is of utmost importance to specify the \textbf{A4 format} (21 cm
x 29.7 cm) when formatting the paper. When working with
\texttt{dvips}, for instance, one should specify \texttt{-t a4}.
Or using the command \verb|\special{papersize=210mm,297mm}| in the latex
preamble (directly below the \verb|\usepackage| commands). Then using
\texttt{dvipdf} and/or \texttt{pdflatex} which would make it easier for some.

Print-outs of the PDF file on A4 paper should be identical to the
hardcopy version. If you cannot meet the above requirements about the
production of your electronic submission, please contact the
publication chairs as soon as possible.

\subsection{Layout}
\label{ssec:layout}

Format manuscripts two columns to a page, in the manner these
instructions are formatted. The exact dimensions for a page on A4
paper are:

\begin{itemize}
\item Left and right margins: 2.5 cm
\item Top margin: 2.5 cm
\item Bottom margin: 2.5 cm
\item Column width: 7.7 cm
\item Column height: 24.7 cm
\item Gap between columns: 0.6 cm
\end{itemize}

\noindent Papers should not be submitted on any other paper size.
 If you cannot meet the above requirements about the production of
 your electronic submission, please contact the publication chairs
 above as soon as possible.

\subsection{Fonts}

For reasons of uniformity, Adobe's \textbf{Times Roman} font should be
used. In \LaTeX2e{} this is accomplished by putting

\begin{quote}
\begin{verbatim}
\usepackage{times}
\usepackage{latexsym}
\end{verbatim}
\end{quote}
in the preamble. If Times Roman is unavailable, use \textbf{Computer
  Modern Roman} (\LaTeX2e{}'s default).  Note that the latter is about
  10\% less dense than Adobe's Times Roman font.

\begin{table}[t!]
\begin{center}
\begin{tabular}{|l|rl|}
\hline \textbf{Type of Text} & \textbf{Font Size} & \textbf{Style} \\ \hline
paper title & 15 pt & bold \\
author names & 12 pt & bold \\
author affiliation & 12 pt & \\
the word ``Abstract'' & 12 pt & bold \\
section titles & 12 pt & bold \\
subsection titles & 11 pt & bold \\
document text & 11 pt  &\\
captions & 10 pt & \\
abstract text & 10 pt & \\
bibliography & 10 pt & \\
footnotes & 9 pt & \\
\hline
\end{tabular}
\end{center}
\caption{\label{font-table} Font guide. }
\end{table}

\subsection{The First Page}
\label{ssec:first}

Center the title, author's name(s) and affiliation(s) across both
columns. Do not use footnotes for affiliations. Do not include the
paper ID number assigned during the submission process. Use the
two-column format only when you begin the abstract.

\textbf{Title}: Place the title centered at the top of the first page, in
a 15-point bold font. (For a complete guide to font sizes and styles,
see Table~\ref{font-table}) Long titles should be typed on two lines
without a blank line intervening. Approximately, put the title at 2.5
cm from the top of the page, followed by a blank line, then the
author's names(s), and the affiliation on the following line. Do not
use only initials for given names (middle initials are allowed). Do
not format surnames in all capitals (\emph{e.g.}, use ``Mitchell'' not
``MITCHELL'').  Do not format title and section headings in all
capitals as well except for proper names (such as ``BLEU'') that are
conventionally in all capitals.  The affiliation should contain the
author's complete address, and if possible, an electronic mail
address. Start the body of the first page 7.5 cm from the top of the
page.

The title, author names and addresses should be completely identical
to those entered to the electronical paper submission website in order
to maintain the consistency of author information among all
publications of the conference. If they are different, the publication
chairs may resolve the difference without consulting with you; so it
is in your own interest to double-check that the information is
consistent.

\textbf{Abstract}: Type the abstract at the beginning of the first
column. The width of the abstract text should be smaller than the
width of the columns for the text in the body of the paper by about
0.6 cm on each side. Center the word \textbf{Abstract} in a 12 point bold
font above the body of the abstract. The abstract should be a concise
summary of the general thesis and conclusions of the paper. It should
be no longer than 200 words. The abstract text should be in 10 point font.

\textbf{Text}: Begin typing the main body of the text immediately after
the abstract, observing the two-column format as shown in the present document. Do not include page numbers.

\textbf{Indent}: Indent when starting a new paragraph, about 0.4 cm. Use 11 points for text and subsection headings, 12 points for section headings and 15 points for the title.

\begin{table}
\centering
\small
\begin{tabular}{cc}
\begin{tabular}{|l|l|}
\hline
\textbf{Command} & \textbf{Output}\\\hline
\verb|{\"a}| & {\"a} \\
\verb|{\^e}| & {\^e} \\
\verb|{\`i}| & {\`i} \\
\verb|{\.I}| & {\.I} \\
\verb|{\o}| & {\o} \\
\verb|{\'u}| & {\'u}  \\
\verb|{\aa}| & {\aa}  \\\hline
\end{tabular} &
\begin{tabular}{|l|l|}
\hline
\textbf{Command} & \textbf{Output}\\\hline
\verb|{\c c}| & {\c c} \\
\verb|{\u g}| & {\u g} \\
\verb|{\l}| & {\l} \\
\verb|{\~n}| & {\~n} \\
\verb|{\H o}| & {\H o} \\
\verb|{\v r}| & {\v r} \\
\verb|{\ss}| & {\ss} \\\hline
\end{tabular}
\end{tabular}
\caption{Example commands for accented characters, to be used in, \emph{e.g.}, \BibTeX\ names.}\label{tab:accents}
\end{table}

\subsection{Sections}

\textbf{Headings}: Type and label section and subsection headings in the
style shown on the present document.  Use numbered sections (Arabic
numerals) in order to facilitate cross references. Number subsections
with the section number and the subsection number separated by a dot,
in Arabic numerals.
Do not number subsubsections.

\begin{table*}[t!]
\centering
\begin{tabular}{lll}
  output & natbib & previous ACL style files\\
  \hline
  \citep{Gusfield:97} & \verb|\citep| & \verb|\cite| \\
  \citet{Gusfield:97} & \verb|\citet| & \verb|\newcite| \\
  \citeyearpar{Gusfield:97} & \verb|\citeyearpar| & \verb|\shortcite| \\
\end{tabular}
\caption{Citation commands supported by the style file.
  The citation style is based on the natbib package and
  supports all natbib citation commands.
  It also supports commands defined in previous ACL style files
  for compatibility.
  }
\end{table*}

\textbf{Citations}: Citations within the text appear in parentheses
as~\cite{Gusfield:97} or, if the author's name appears in the text
itself, as Gusfield~\shortcite{Gusfield:97}.
Using the provided \LaTeX\ style, the former is accomplished using
{\small\verb|\cite|} and the latter with {\small\verb|\shortcite|} or {\small\verb|\newcite|}. Collapse multiple citations as in~\cite{Gusfield:97,Aho:72}; this is accomplished with the provided style using commas within the {\small\verb|\cite|} command, \emph{e.g.}, {\small\verb|\cite{Gusfield:97,Aho:72}|}. Append lowercase letters to the year in cases of ambiguities.
 Treat double authors as
in~\cite{Aho:72}, but write as in~\cite{Chandra:81} when more than two
authors are involved. Collapse multiple citations as
in~\cite{Gusfield:97,Aho:72}. Also refrain from using full citations
as sentence constituents.

We suggest that instead of
\begin{quote}
  ``\cite{Gusfield:97} showed that ...''
\end{quote}
you use
\begin{quote}
``Gusfield \shortcite{Gusfield:97}   showed that ...''
\end{quote}

If you are using the provided \LaTeX{} and Bib\TeX{} style files, you
can use the command \verb|\citet| (cite in text)
to get ``author (year)'' citations.

You can use the command \verb|\citealp| (alternative cite without
parentheses) to get ``author year'' citations (which is useful for
using citations within parentheses, as in \citealp{Gusfield:97}).

If the Bib\TeX{} file contains DOI fields, the paper
title in the references section will appear as a hyperlink
to the DOI, using the hyperref \LaTeX{} package.
To disable the hyperref package, load the style file
with the \verb|nohyperref| option: \\{\small
\verb|\usepackage[nohyperref]{acl2019}|}

\textbf{Compilation Issues}: Some of you might encounter the following error during compilation:

``{\em \verb|\pdfendlink| ended up in different nesting level than \verb|\pdfstartlink|.}''

This happens when \verb|pdflatex| is used and a citation splits across a page boundary. To fix this, the style file contains a patch consisting of the following two lines: (1) \verb|\RequirePackage{etoolbox}| (line 454 in \texttt{acl2019.sty}), and (2) A long line below (line 455 in \texttt{acl2019.sty}).

If you still encounter compilation issues even with the patch enabled, disable the patch by commenting the two lines, and then disable the \verb|hyperref| package (see above), recompile and see the problematic citation.
Next rewrite that sentence containing the citation. (See, {\em e.g.}, {\small\tt http://tug.org/errors.html})

\textbf{Digital Object Identifiers}:  As part of our work to make ACL
materials more widely used and cited outside of our discipline, ACL
has registered as a CrossRef member, as a registrant of Digital Object
Identifiers (DOIs), the standard for registering permanent URNs for
referencing scholarly materials.  As of 2017, we are requiring all
camera-ready references to contain the appropriate DOIs (or as a
second resort, the hyperlinked ACL Anthology Identifier) to all cited
works.  Thus, please ensure that you use Bib\TeX\ records that contain
DOI or URLs for any of the ACL materials that you reference.
Appropriate records should be found for most materials in the current
ACL Anthology at \url{http://aclanthology.info/}.

As examples, we cite \cite{P16-1001} to show you how papers with a DOI
will appear in the bibliography.  We cite \cite{C14-1001} to show how
papers without a DOI but with an ACL Anthology Identifier will appear
in the bibliography.

As reviewing will be double-blind, the submitted version of the papers
should not include the authors' names and affiliations. Furthermore,
self-references that reveal the author's identity, \emph{e.g.},
\begin{quote}
``We previously showed \cite{Gusfield:97} ...''
\end{quote}
should be avoided. Instead, use citations such as
\begin{quote}
``\citeauthor{Gusfield:97} \shortcite{Gusfield:97}
previously showed ... ''
\end{quote}

Any preliminary non-archival versions of submitted papers should be listed in the submission form but not in the review version of the paper. ACL 2019 reviewers are generally aware that authors may present preliminary versions of their work in other venues, but will not be provided the list of previous presentations from the submission form.

\textbf{Please do not use anonymous citations} and do not include
 when submitting your papers. Papers that do not
conform to these requirements may be rejected without review.

\textbf{References}: Gather the full set of references together under
the heading \textbf{References}; place the section before any Appendices.
Arrange the references alphabetically
by first author, rather than by order of occurrence in the text.
By using a .bib file, as in this template, this will be automatically
handled for you. See the \verb|\bibliography| commands near the end for more.

Provide as complete a citation as possible, using a consistent format,
such as the one for \emph{Computational Linguistics\/} or the one in the
\emph{Publication Manual of the American
Psychological Association\/}~\cite{APA:83}. Use of full names for
authors rather than initials is preferred. A list of abbreviations
for common computer science journals can be found in the ACM
\emph{Computing Reviews\/}~\cite{ACM:83}.

The \LaTeX{} and Bib\TeX{} style files provided roughly fit the
American Psychological Association format, allowing regular citations,
short citations and multiple citations as described above.

\begin{itemize}
\item Example citing an arxiv paper: \cite{rasooli-tetrault-2015}.
\item Example article in journal citation: \cite{Ando2005}.
\item Example article in proceedings, with location: \cite{borsch2011}.
\item Example article in proceedings, without location: \cite{andrew2007scalable}.
\end{itemize}
See corresponding .bib file for further details.

Submissions should accurately reference prior and related work, including code and data. If a piece of prior work appeared in multiple venues, the version that appeared in a refereed, archival venue should be referenced. If multiple versions of a piece of prior work exist, the one used by the authors should be referenced. Authors should not rely on automated citation indices to provide accurate references for prior and related work.

\textbf{Appendices}: Appendices, if any, directly follow the text and the
references (but see above).  Letter them in sequence and provide an
informative title: \textbf{Appendix A. Title of Appendix}.

\subsection{Footnotes}

\textbf{Footnotes}: Put footnotes at the bottom of the page and use 9
point font. They may be numbered or referred to by asterisks or other
symbols.\footnote{This is how a footnote should appear.} Footnotes
should be separated from the text by a line.\footnote{Note the line
separating the footnotes from the text.}

\subsection{Graphics}

\textbf{Illustrations}: Place figures, tables, and photographs in the
paper near where they are first discussed, rather than at the end, if
possible.  Wide illustrations may run across both columns.  Color
illustrations are discouraged, unless you have verified that
they will be understandable when printed in black ink.

\textbf{Captions}: Provide a caption for every illustration; number each one
sequentially in the form:  ``Figure 1. Caption of the Figure.'' ``Table 1.
Caption of the Table.''  Type the captions of the figures and
tables below the body, using 10 point text. Captions should be placed below illustrations. Captions that are one line are centered (see Table~\ref{font-table}). Captions longer than one line are left-aligned (see Table~\ref{tab:accents}). Do not overwrite the default caption sizes. The acl2019.sty file is compatible with the caption and subcaption packages; do not add optional arguments.

\subsection{Accessibility}
\label{ssec:accessibility}

In an effort to accommodate people who are color-blind (as well as those printing
to paper), grayscale readability for all accepted papers will be
encouraged.  Color is not forbidden, but authors should ensure that
tables and figures do not rely solely on color to convey critical
distinctions. A simple criterion: All curves and points in your figures should be clearly distinguishable without color.

\section{Translation of non-English Terms}

It is also advised to supplement non-English characters and terms
with appropriate transliterations and/or translations
since not all readers understand all such characters and terms.
Inline transliteration or translation can be represented in
the order of: original-form transliteration ``translation''.

\section{Length of Submission}
\label{sec:length}

The ACL 2019 main conference accepts submissions of long papers and
short papers.
 Long papers may consist of up to eight (8) pages of
content plus unlimited pages for references. Upon acceptance, final
versions of long papers will be given one additional page -- up to nine (9)
pages of content plus unlimited pages for references -- so that reviewers' comments
can be taken into account. Short papers may consist of up to four (4)
pages of content, plus unlimited pages for references. Upon
acceptance, short papers will be given five (5) pages in the
proceedings and unlimited pages for references.
For both long and short papers, all illustrations and tables that are part
of the main text must be accommodated within these page limits, observing
the formatting instructions given in the present document. Papers that do not conform to the specified length and formatting requirements are subject to be rejected without review.

ACL 2019 does encourage the submission of additional material that is relevant to the reviewers but not an integral part of the paper. There are two such types of material: appendices, which can be read, and non-readable supplementary materials, often data or code.  Do not include this additional material in the same document as your main paper. Additional material must be submitted as one or more separate files, and must adhere to the same anonymity guidelines as the main paper. The paper must be self-contained: it is optional for reviewers to look at the supplementary material. Papers should not refer, for further detail, to documents, code or data resources that are not available to the reviewers. Refer to Appendix~\ref{sec:appendix} and Appendix~\ref{sec:supplemental} for further information.

Workshop chairs may have different rules for allowed length and
whether supplemental material is welcome. As always, the respective
call for papers is the authoritative source.

\section*{Acknowledgments}

The acknowledgments should go immediately before the references.  Do
not number the acknowledgments section. Do not include this section
when submitting your paper for review. \\

\noindent \textbf{Preparing References:} \\
Include your own bib file like this:
\verb|\bibliographystyle{acl_natbib}|
\verb|
\section{Introduction}
Abbreviations are shortened forms of text-strings. They are prevalent in biomedical literature such as scientific articles, clinical notes and user queries in information retrieval systems. Abbreviations can be ambiguous (e.g.: ER can refer to estrogen receptor, endoplasmic reticulum, emergency room etc.), especially when they appear in short or professional texts where the definitions are not given. For instance, about 15\% of PubMed queries include abbreviations \cite{islamaj2009understanding}, and about 14.8\% of all tokens in a clinical note dataset are abbreviations \cite{xu2007study}. In both cases, the definitions of the abbreviations are rarely provided. Thus, automatic expansion of ambiguous abbreviations to their full forms is vital in biomedical natural language processing (NLP) systems.

In this paper, we focus on the cases where definitions of ambiguous abbreviations are not directly available in the contexts, so reasoning over the contexts is required for disambiguation. Under the conditions where definitions are provided in the contexts, one can easily extract them using rule-based methods.

We present DEep Contextualized Biomedical Abbreviation Expansion (DECBAE) model. DECBAE uses a simple heuristic to automatically construct large supervised disambiguation datasets for 950 abbreviations from PubMed abstracts: In scientific writing, authors define abbreviations the first time they are used, and the same abbreviations in the following sentences have the same definitions as those of the first ones. We extract all the sentences containing the same abbreviations in each PubMed abstract, and use the definition given in the first sentence as the full form label of abbreviations in the following sentences. We group the definitions for each abbreviation and formulate abbreviation expansion as a classification task, where input is an ambiguous abbreviation with its context, and the output is one of its possible definitions.

Recent breakthroughs of language models (LM) pre-trained on large corpora like ELMo \cite{peters2018deep} and BERT \cite{devlin2018bert} clearly show that unsupervised LM pre-training can vastly improve performance of downstream models. To fully utilize the knowledge encoded in PubMed abstracts, DECBAE uses BioELMo \cite{jin2019probing}, a domain adapation verison of ELMo, to embed the words. After the embedding layer, DECBAE applies abbreviation-specific bidirectional LSTM (biLSTM) classifiers to do the abbreviation expansion, where the biLSTM parameters are trained separately for each abbreviation. We train DECBAE from the automatically collected dataset of 950 ambiguous abbreviations.

At inference time, DECBAE feeds the BioELMo embeddings of the whole sentence and uses the corresponding abbreviation-specific biLSTM classifiers to perform disambiguation of abbreviations in the sentence. We show that DECBAE outperforms other baselines by large margins and even performs better than single human expert. Although training instances of DECBAE are collected from PubMed, it covers 85\% of clinically related abbreviations mentioned in a previous work \cite{xu2012combining}. Moreover, DECBAE remains robust in low-resource and imbalanced settings.

\section{Related Work}
\paragraph{Contextualized word embeddings:} Recently, contextualized word representations pre-trained by large corpora like ELMo \cite{peters2018deep} and BERT \cite{devlin2018bert} significantly improve the performance of various NLP tasks. ELMo is a pre-trained biLSTM language model. ELMo word embeddings are calculated by a weighted sum of the hidden states of each biLSTM layer. The weights are task-specific learnable parameters while biLSTM layers are fixed. In-domain trained contextual embeddings further improve the performance on domain-specific tasks. In this paper, we use BioELMo, which is a biomedical version of ELMo trained on 10M PubMed abstracts \cite{jin2019probing}. BioELMo outperforms general ELMo by large margins on several biomedical NLP tasks.

We don't use BERT for contextualized embeddings due to its fine-tuning nature: users just need to download 1 BioELMo and $N$ abbreviation-specifc biLSTM weights to run DECBAE locally, which takes significantly less disk size than $N$ fine-tuned BERTs for each abbreviation. $N$ is the number of abbreviations.

\paragraph{Word sense disambiguation (WSD):} The goal of WSD is to determine the correct sense of words in different contexts. Abbreviation expansion is a specific case of WSD where the ambiguous words are abbreviations. In this paper, we use abbreviation expansion and abbreviation disambiguation interchangeably. Several human-annotated datasets are available for supervised WSD \cite{navigli2013semeval,camacho2016nasari,raganato2017word}. However, human annotations could be expensive, especially in domain specific settings. To address this problem, some automatic dataset collection methods have been proposed \cite{yu2007using, ciosici2019unsupervised}, where abbreviations are automatically labeled if they are defined previously in the same documents. We use a similar approach in this work.

\citet{peters2018deep} report that just matching the ELMo embedding of the target words with the nearest sense representations, calculated by averaging their ELMo embeddings, leads to comparable WSD performance with state-of-the-art models using hand crafted features \cite{iacobacci2016embeddings} or task-specific biLSTM trained with multiple tasks \cite{raganato2017neural}. Instead of searching the nearest contextualized embeddings neighbors of the abbreviation and definitions, we model abbreviation expansion as classification.

\paragraph{Biomedical abbreviation expansion:} Various methods have been introduced for automatically expanding biomedical abbreviations.
\citet{yu2007using} train naive Bayes and SVM classifiers with bag-of-word features on an automatically collected dataset from PubMed. Some works disambiguate abbreviations to their senses in controlled vocabularies like Medical Subject Headings\footnote{\url{https://www.nlm.nih.gov/mesh}} (MeSH) and Unified Medical Language System\footnote{\url{https://www.nlm.nih.gov/research/umls/}} (UMLS). \citet{xu2015clinical} use pooled neighbor word embeddings of the abbreviations as features to train SVM classifiers for clinical abbreviaiton disambiguation. \citet{jimeno2011exploiting} introduced MSH WSD dataset to test the performance of supervised biomedical WSD systems and several supervised models have been proposed on it \cite{antunes2017supervised, yepes2017word}. Recently \citet{pesaranghader2019deepbiowsd} presented deepBioWSD which sets new state-of-the-art performance on it. DeepBioWSD uses a single biLSTM encoder for disambiguation of all abbreviations by calculating the pairwise similarity between context representations and sense representations.

To the best of our knowledge, DECBAE is the first model that uses deep contextualized word embeddings for biomedical abbreviation expansion.

\section{Methods}
\begin{figure*}
    \centering
    \includegraphics[width=\linewidth]{img/pipeline.pdf}
    \caption{Architecture of DECBAE. Training and inference phases are illustrated in the left and right boxes, respectively. The PubMed corpus is used in training BioELMo \cite{jin2019probing} and collecting the disambiguation dataset. We train a separate biLSTM classifier for each abbreviation, and the specific pre-trained classifier is retrieved in inference phase.}
    \label{fig:pipeline}
\end{figure*}

Figure \ref{fig:pipeline} shows the architecture of DECBAE. During training, we first construct abbreviation expansion datasets from PubMed (\S\ref{constr}). We use BioELMo (\S\ref{bioelmo}) to get the contextualized representations of words, and train a specific biLSTM classifier (\S\ref{bilstm}) for each abbreviation. During inference (\S\ref{infer}), we first detect whether there are ambiguous abbreviations in input sentences by the expert-curated ambiguous abbreviation vocabulary. If so, we use BioELMo and the corresponding abbreviation-specific biLSTM classifiers to do the disambiguation.

\subsection{Dataset Collection} \label{constr}

Figure \ref{fig:dataset} shows our approach of automatically collecting disambiguation dataset. For each abstract, we first detect and extract the pattern of ``\textit{Definition} (\textit{Abbreviation})", e.g.: ``endoplasmic reticulum (ER)". Then we collect all the following sentences that contain the abbreviation, and label them with the definition.

\begin{figure*}
    \centering
    \includegraphics[width=0.8\linewidth]{img/dataset.pdf}
    \caption{An example of automatically generated training instances for disambiguation from the abstract of \citet{schwarz2016endoplasmic}. In this case, we extract ``endoplasmic reticulum'' as the definition for all ER mentions in the abstract, and store those instances to the dataset.}
    \label{fig:dataset}
    \vspace{0.2cm}
\end{figure*}

This would generate a noisy label set due to the variations of writing the same definition (e.g.: emergency department and emergency departments). To group the same definitions together, we use MetaMap-derived MeSH terms \cite{demner2017metamap} as features of definitions and define the MeSH similarity between definition $a$ and definition $b$ as:
\[
s = \frac{\left|\mathcal{M}_a \cap \mathcal{M}_b\right|}{\sqrt{\left|\mathcal{M}_a\right|\left|\mathcal{M}_b\right|}}
\]
where $\mathcal{M}_a$ and $\mathcal{M}_b$ are the MeSH term sets of definition a and b, respectively. We group those definitions with high MeSH similarity and close edit distance by heuristic thresholds.

We collected 1970 abbreviations. However, due to the unsupervised nature of the collection process, some abbreviations are invalid or not ambiguous. For this, one biomedical expert\footnote{A post-doctoral fellow with a Ph.D. degree in biology.} filtered the abbreviations we found, based on 1) \textbf{Validity}: abbreviations should be biomedically meaningful; 2) \textbf{Ambiguity}: abbreviations should have multiple possible definitions, and prevalence of the dominant one should be $<99\%$. After the filtering, there are 950 valid ambiguous abbreviations. Their statistics are shown in Table \ref{tab:stat}. We split the instances of each abbreviation into training, development and test sets: If there is more than $10$k instances, we randomly select $1$k for both development and test sets. Otherwise, we randomly select 10\% of all instances for both development and test sets.
\begin{table*}[htbp]
\centering
\small
\begin{tabular}{lcccccc}
\toprule
\textbf{Statistic} & \textbf{Whole} & \textbf{Random} & \textbf{Imbalanced} & \textbf{Low-resources} & \textbf{Clinical} & \textbf{Human} \\
\midrule
\textbf{\# of all abbreviations} & 950 & 100 & 42 & 28 & 11 & 1\\
\textbf{Average \# of instances} & 8790.0 & 6564.3 & 19493.1 & 958.8 & 28642.8 & 8312.0\\
\textbf{Average \# of possible definitions} & 4.1 & 3.7 & 2.3 & 2.2 & 8.5 & 4.0\\
\textbf{Average \% of dominant definition} & 64.1 & 63.5 & 96.7 & 66.7 & 53.3 & 63.8\\
\bottomrule
\end{tabular}
\caption{Statistics of the automatically generated abbreviation disambiguation dataset and its subsets.}
\label{tab:stat}
\end{table*}

\subsection{BioELMo} \label{bioelmo}
BioELMo is a biomedical version of ELMo pre-trained on $10$ millions of PubMed abstracts \cite{jin2019probing}. It serves as a contextualized feature extractor in DECBAE: given an input sentence of $L$ tokens:
\[\text{input} = [t_1;t_2;...;t_L]\]
We use BioELMo to embed it to
\[\mathbf{E} = [\mathbf{e_1};\mathbf{e_2};...;\mathbf{e_L}] \in \mathbb{R} ^ {L \times D}\]
where $\mathbf{e} \in \mathbb{R} ^ D$ is the token embedding and $D$ is the embedding dimension\footnote{Note that it's after scaling and averaging the 3 BioELMo layers using task-specific weights.}.

\subsection{Abbreviation-specific biLSTM Classifiers} \label{bilstm}
For each abbreviation, we train a specific biLSTM classifier, denoted as $\text{biLSTM}_i$ for abbreviation $i$. We feed the BioELMo representations of sentences containing abbreviation $i$ to $\text{biLSTM}_i$:
\[\text{biLSTM}_i(\mathbf{E}) = [\mathbf{h_1};\mathbf{h_2};...;\mathbf{h_L}] \in \mathbb{R} ^ {L \times 2H}\]
where $\mathbf{h} \in \mathbb{R} ^ {2H}$ is the concatenation of forward and backward hidden states of the biLSTM. We take as input the concatenated hidden states of the abbreviation $i$ (i.e. the ambiguous token) $\mathbf{h_a}$ and use several feed-forward neural network (FFN) layers with softmax output unit to predict its definition:
\[
p(\text{def}_k\,|\,\text{input}) \propto \text{exp}(\mathbf{w_{k}^T} \, \text{FFN}_{i}(\mathbf{h_a}))
\]
where $\mathbf{w_{k}}$ is the learnt weight vector corresponding to definition $k$, and $\text{def}_k$ is the $k$-th definition of abbreviation $i$ in our dataset. Similarly, we train FFN separately for different abbreviations.

\subsection{Training}
The weights of BioELMo are pre-trained and fixed, while the averaging weights and scaling factor of BioELMo embeddings are trained separately for each abbreviation along with the abbreviation-specific biLSTM classifiers. We use Adam \cite{kingma2014adam} to optimize the cross-entropy loss of the predicted label and ground-truth label.

\subsection{Inference} \label{infer}
At inference time, we denote the tokenized input sentence as $[t_1;t_2;...;t_L]$ and our ambiguous abbreviation set as $\mathcal{A}$. If $\exists t_j \in \mathcal{A}$, we run DECBAE to expand the $t_j$: First, we use BioELMo to compute the representations of all the input tokens to $\mathbf{E} = [\mathbf{e_1};\mathbf{e_2};...;\mathbf{e_L}]$. The trained biLSTM for abbreviation $t_j$, denoted as $\text{biLSTM}_{t_j}$, is retrieved and used to calculate the hidden states given the BioELMo embeddings of the input sentence:
\[\text{biLSTM}_{t_j}(\mathbf{E}) = [\mathbf{h_1};\mathbf{h_2};...;\mathbf{h_L}] \in \mathbb{R} ^ {L \times 2H}\]
Then $\mathbf{h_{t_j}}$, which is the concatenated hidden states of the ambiguous abbreviation $t_j$, is used for disambiguation through the trained abbreviation-specific FFN:
\[
\text{Definition}(t_j) = \text{def}_{\operatorname*{argmax}_{k} \mathbf{w_{k}^T} \, \text{FFN}_{t_j}(\mathbf{h_{t_j}})}
\]

\section{Experiments}
\subsection{Baseline Settings}
A trivial baseline is to predict the majority of definition for all cases, which could still lead to high accuracy in severely imbalanced datasets. We denote this method as \textbf{Majority}. We also test other baseline settings of different feature learning schemes. They are all followed by several FFN layers and a softmax output unit.

\textbf{Bag-of-words:} Following most of the previous works, we use bag-of-words features to represent the context by $\mathbf{c} \in \mathbb{R} ^ {\left|\mathcal{V}\right|}$, where $\left|\mathcal{V}\right|$ is the vocabulary size.

\textbf{BioELMo:} We take the BioELMo embeddings of the ambiguous abbreviations as input features.

\textbf{biLSTM:} We use biomedical w2v \cite{moen2013distributional} as word embeddings and train task-specific biLSTMs and use the hidden states of the ambiguous abbreviations as input features.

We also measure the \textbf{human performance}: due to limitation of resources, we just study single-expert performance on one sampled abbreviation. For this, the expert is shown with the test sentences, and asked to classify the ambiguous abbreviation to its possible definitions. An ensemble of experts will obviously generate better results, so our single-human results just represent the lower bound of human performance.

\subsection{Subset Settings}
We report the model performance on different subsets of our dataset. Statistics of those datasets are shown in Table \ref{tab:stat}.

\textbf{Random samples:} It's computationally expensive\footnote{ The rate-determining step is BioELMo due to its large size and recurrent nature.} and unnecessary to test the models on all 950 abbreviations. Instead, we use randomly sampled 100 abbreviations to represent the whole set.

\textbf{Imbalanced samples:} We define abbreviations whose dominant definitions have over 95\% frequency as imbalanced samples. Multi-label classification with imbalanced classes is considered as a hard machine learning task.

\textbf{Low-resources samples:} We define abbreviations that have less than 1k training instances as low-resources samples. It's motivated by the fact that most biomedical datasets are typically limited by scale, so models that can still perform well under low-resources settings have the potential to be applied in real world settings.

\textbf{Clinical samples:} Though our abbreviations are collected from PubMed abstracts, we have included 11 out of 13 of clinical ambiguous abbreviations mentioned in a previous work of clinical abbreviation disambiguation \cite{xu2012combining}. We also test our models on the subset of these 11 clinically related abbreviations.

\textbf{Testing sample for human expert:} We test human performance on one abbreviation (DAT), due to limited resources. The statistics of DAT abbreviation expansion dataset are close to the averages of the whole dataset, as shown in Table \ref{tab:stat}. Possible definitions of DAT include: 1) Dopamine transporter (63.9\%); 2) Direct antiglobulin test (5.8\%); 3) Direct agglutination test (5.8\%); 4) Dementia of the Alzheimer type (24.5\%).

\subsection{Evaluation Metrics}
\begin{figure*}
    \centering
    \includegraphics[width=0.46\textwidth]{img/cm_decbae.pdf} \hspace{0.15in}
    \includegraphics[width=0.46\textwidth]{img/cm_human.pdf}
    \caption{Confusion matrix for the predictions of DECBAE (left) and the human expert (right). Def. 1: dopamine transporter; Def. 2: direct antiglobulin test; Def. 3: direct agglutination test; Def. 4: dementia of the Alzheimer type.}
    \label{fig:cm}
\end{figure*}

\begin{table*}[htbp]
\centering
\small
\begin{tabular}{lcccccc}
\toprule
\textbf{Model} & \textbf{Random subset} & \textbf{Imbalanced subset} & \textbf{Low-resources subset} & \textbf{Clinical subset} & \textbf{Human testset} \\
\midrule
\textbf{Majority}\\
\midrule
\textbf{\hspace*{3mm}Accuracy} & 63.6\,$\pm$\,21.0$^\dagger$ & 96.7\,$\pm$\,1.0$^\dagger$ & 67.0\,$\pm$\,15.6$^\dagger$ & 53.3\,$\pm$\,25.7$^\dagger$ & 63.9\\
\textbf{\hspace*{3mm}Macro-F1} & 28.3\,$\pm$\,14.9$^\dagger$ & 45.4\,$\pm$\,8.8$^\dagger$ & 37.2\,$\pm$\,8.8$^\dagger$ & 12.0\,$\pm$\,10.6$^\dagger$ & 19.5\\
\textbf{\hspace*{3mm}Kappa Statistic} & 0.0\,$\pm$\,0.0$^\dagger$ & 0.0\,$\pm$\,0.0$^\dagger$ & 0.0\,$\pm$\,0.0$^\dagger$ & 0.0\,$\pm$\,0.0$^\dagger$ & 0.0\\
\midrule
\textbf{BoW-FFN}\\
\midrule
\textbf{\hspace*{3mm}Accuracy} & 84.4\,$\pm$\,11.2$^\dagger$ & 97.5\,$\pm$\,1.7$^\dagger$ & 89.6\,$\pm$\,7.5$^\dagger$ & 76.1\,$\pm$\,12.5$^\dagger$ & 84.3\\
\textbf{\hspace*{3mm}Macro-F1} & 73.1\,$\pm$\,17.1$^\dagger$ & 71.5\,$\pm$\,19.9$^\dagger$ & 83.4\,$\pm$\,14.6$^\dagger$ & 57.9\,$\pm$\,14.2$^\dagger$ & 71.9\\
\textbf{\hspace*{3mm}Kappa Statistic} & 63.8\,$\pm$\,25.3$^\dagger$ & 50.4\,$\pm$\,33.7$^\dagger$ & 71.1\,$\pm$\,24.8$^\dagger$ & 60.6\,$\pm$\,8.9$^\dagger$ & 69.6\\
\midrule
\textbf{BioELMo}\\
\midrule
\textbf{\hspace*{3mm}Accuracy} & 94.1\,$\pm$\,7.2$^\dagger$ & 96.3\,$\pm$\,15.3 & 98.1\,$\pm$\,2.7 & 91.1\,$\pm$\,8.4 & 97.1 \\
\textbf{\hspace*{3mm}Macro-F1} & 86.0\,$\pm$\,17.4$^\dagger$ & 81.3\,$\pm$\,23.5$^\dagger$ & 95.4\,$\pm$\,9.3 & 75.5\,$\pm$\,21.7 & 92.6 \\
\textbf{\hspace*{3mm}Kappa Statistic} & 86.1\,$\pm$\,19.8$^\dagger$ & 73.2\,$\pm$\,34.2$^\dagger$ & 93.2\,$\pm$\,10.8$^\dagger$ & 86.6\,$\pm$\,9.3 & 94.6 \\
\midrule
\textbf{biLSTM}\\
\midrule
\textbf{\hspace*{3mm}Accuracy} & 88.0\,$\pm$\,16.8$^\dagger$ & 98.0\,$\pm$\,1.9$^\dagger$ & 92.7\,$\pm$\,10.5$^\dagger$ & 88.2\,$\pm$\,8.2$^\dagger$ & 97.3 \\
\textbf{\hspace*{3mm}Macro-F1} & 77.1\,$\pm$\,26.0$^\dagger$ & 70.2\,$\pm$\,27.0$^\dagger$ & 82.9\,$\pm$\,24.5$^\dagger$ & 68.8\,$\pm$\,26.1 & 93.2 \\
\textbf{\hspace*{3mm}Kappa Statistic} & 69.3\,$\pm$\,37.2$^\dagger$ & 49.1\,$\pm$\,45.7$^\dagger$ & 70.4\,$\pm$\,41.5$^\dagger$ & 70.5\,$\pm$\,35.3 & 94.9 \\
\midrule
\textbf{DECBAE}\\
\midrule
\textbf{\hspace*{3mm}Accuracy} & \textbf{96.1\,$\pm$\,5.5} & \textbf{98.9\,$\pm$\,1.4} & \textbf{98.7\,$\pm$\,2.2} & \textbf{95.1\,$\pm$\,3.3} & \textbf{98.4} \\
\textbf{\hspace*{3mm}Macro-F1} & \textbf{91.7\,$\pm$\,13.2} & \textbf{87.2\,$\pm$\,17.8} & \textbf{98.3\,$\pm$\,3.5} & \textbf{83.0\,$\pm$\,21.9} & \textbf{93.9} \\
\textbf{\hspace*{3mm}Kappa Statistic} & \textbf{90.9\,$\pm$\,15.5} & \textbf{79.6\,$\pm$\,30.2} & \textbf{96.8\,$\pm$\,6.8} & \textbf{91.7\,$\pm$\,5.5} & \textbf{97.0} \\
\midrule
\textbf{Human Expert}\\
\midrule
\textbf{\hspace*{3mm}Accuracy} & -- & -- & -- & -- & 96.3\\
\textbf{\hspace*{3mm}Macro-F1} & -- & -- & -- & -- & 89.0\\
\textbf{\hspace*{3mm}Kappa Statistic} & -- & -- & -- & -- & 92.8\\
\bottomrule
\end{tabular}
\caption{Mean and standard deviation of model performance on different subsets. $^{\dagger}$Significantly lower than the corresponding metric of DECBAE. Significance is defined by $p<0.05$ in paired t-test. All numbers are in percentages. High deviations are expected due to the variety of abbreviations in each subset.}
\label{tab:results}
\end{table*}
We model abbreviation expansion as a multi-label classification task, and use the following metrics to measure the performance of different models:

\textbf{Accuracy:} Accuracy is defined as the proportion of right predictions in all predictions. Most of the definition labels are imbalanced, so accuracy could be misleadingly high for a trivial majority solution in these cases, thus may not reflect the real capability of models.

\textbf{Macro-F1:} In multi-label classification, macro-F1 is calculated as an unweighted average of F1 score for each class. Class-wise F1 score is defined as follows:
\[\text{F1} = 2 \cdot \frac{\text{precision} \cdot \text{recall}}{\text{precision} + \text{recall}} \]
where precision and recall are calculated for each class.

\textbf{Kappa Statistic:} Cohen's kappa was originally introduced as a metric to measure inter-rater agreement \cite{cohen1960coefficient}. It can also be used to evaluate predictions of multi-label classification:
\[\kappa = \frac{p_o - p_e}{1 - p_e} \]
where $p_o$ is the observed agreement and in the case of classification $p_o=\text{accuracy}$, $p_e$ is the expected agreement which can be achieved by pure chance:
\[p_e = \sum_{c} p_c \hat{p_c}\]
$p_c$ and $\hat{p_c}$ refer to the proportion of class c in ground truth labels and predictions, respectively. Empirical results in Table \ref{tab:results} show that Kappa statistics are often lower than accuracy and macro-F1, and thus serving as a more distinctive metric for our task.

\subsection{Results}

In Table \ref{tab:results}, we report means and standard deviations of each model's performance on different subsets evaluated by the three metrics. In all subsets, DECBAE performs significantly better than most other models by large margins. A general trend of DECBAE $>$ BioELMo $>$ biLSTM $>$ BoW-FFN $>$ Majority conserves across subsets.

In the \textbf{Random} subset which represents the whole dataset, all metrics of DECBAE exceed $0.90$, setting very promising state-of-the-art performance despite the potential noise of the dataset.

In the \textbf{Imbalanced} subset where the most frequent definitions consist of over $95$\% of all the labels, a trivial Majority solution gets over $95$\% accuracy. However, for macro-F1 and kappa statistic, performance of the baselines drop dramatically while DECBAE can still generate decent results.

DECBAE and BioELMo alone remain robust in \textbf{Low-resources} setting. This is due to the transfer learning nature of BioELMo, which utilizes the knowledge encoded in the PubMed abstracts.

Our abbreviation expansion dataset covers roughly 85\% of clinical abbreviations mentioned in \citet{xu2012combining}. On this \textbf{Clinical} subset, DECBAE gets pretty good results and vastly outperform other baselines despite its variety in possible definitions (8.5 possible definitions per abbreviation, as shown in Table \ref{tab:stat}).

On the testset for human performance (i.e.: abbreviation expansion for DAT), DECBAE and even some neural baselines outperform single human expert.

\begin{table*}[htbp]
\centering
\small
\begin{tabular}{cccc}
\toprule
\textbf{Test sentence} & \textbf{Label} & \textbf{Human} & \textbf{DECBAE} \\
\midrule
\makecell{The reduction of the number of different segments in \textbf{DAT} compared to controls and\\ patients suffering from depression may be helpful for differential diagnosis.} & Def. 4 & Def. 1 & \textbf{Def. 4} \\
\makecell{Reliance on objective brain phenotype measures, for example, those afforded by brain \\imaging, might critically improve detection of \textbf{DAT} genotype-phenotype association.} & Def. 1 & \textbf{Def. 1} & Def. 4 \\
\makecell{\textbf{DAT} was more commonly positive among BO incompatible (21.5\% in BO vs. 14.8\% \\in AO , P=0.001) and black (18.8\% in blacks vs. 10.8\% in nonblacks , P=0.003) infants.} & Def. 2 & Def. 3 & \textbf{Def. 2} \\
\makecell{NPY-LI showed a significant reduction in \textbf{DAT} but not in FTD.} & Def. 4 & Def. 1 & \textbf{Def. 4} \\
\makecell{The study included 122 healthy subjects, aged 18-83 years, recruited in the multicentre \\`ENC-\textbf{DAT}' study (promoted by the European Association of Nuclear Medicine).} & Def. 1 & Def. 4 & \textbf{Def. 1} \\
\bottomrule
\end{tabular}
\caption{Some samples of errors made by the human expert and DECBAE. Def. 1: dopamine transporter; Def. 2: direct antiglobulin test; Def. 3: direct agglutination test; Def. 4: dementia of the Alzheimer type.}
\label{tab:err}
\end{table*}

\section{Analysis}
In Fig. \ref{fig:cm}, we use confusion matrices to visualize the differences between DECBAE or the human expert and the ground truth labels, for disambiguation of abbreviation ``DAT''. The high agreement level between human expert predictions and the automatically assigned labels indicates that our pipeline of collecting the abbreviation disambiguation dataset is valid.

In general, both DECBAE and the human expert perform well in the task, with only few misclassifications. Specifically, DECBAE, and even other neural baselines like biLSTM and BioELMo, outperform the human expert in all metrics. Compared to DECBAE, the human expert is more likely to misclassify direct agglutination test with direct antiglobulin test (9 v.s. 1), and misclassify dementia of the Alzheimer type with dopamine transporter (7 v.s. 0). We show several instances of human and DECBAE's errors in Table \ref{tab:err}.

One limitation of this work is that we just test DECBAE on our automatically collected dataset. Since the proposed model can also be used on other biomedical abbreviation expansion datasets as well, evaluating on other datasets like MSH WSD is a clear future work to do.

Another potential direction for improvement is to accelerate the inference speed. Currently DECBAE uses BioELMo for embedding and abbreviation-specific biLSTM for classification, resulting in two recurrent models in total. Our results show that just BioELMo with several FFN layers also generates decent results, so in some cases we might use only BioELMo as a compromise for faster inference.

\section{Conclusion}
We present DECBAE, a state-of-the-art biomedical abbreviation expansion model on the automatically collected dataset from PubMed. The results show that, with only minimum expert involvement, we can still perform well in such a domain-specific task by automatically collecting training data from a large corpus and utilize embeddings from pre-trained biomedical language models.

\section{Acknowledgement}
We are grateful for the annonymous reviewers of BioNLP 2019 who gave us very insightful comments and suggestions. J.L. is supported by NLM training grant 5T15LM007059-32.

redpajama_set_name: RedPajamaArXiv


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Football Manager is likely to be extremely likely to be released in November 2018 with the earliest date being late October 2018, however, pre-orders will be available from September 2018. There has not been yet any official announcements by SEGA or Sports Interactive in regards to the release date of Football Manager 2019 but it is at the same period every year so we can give you a pretty accurate guess.
There has been not a lot of news in regards to Football Manager 2019 yet with Football Manager 2018 getting released just two months ago (as of writing this). However, it has been reported that there will be new leagues coming to Football Manager 2019 and also a lot of new licenses which will introduce more real club logos rather than the current colored in crests.
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There has currently been no official Football Manager 2019 trailer released so we will embed the latest Football Manager 2018 trailer until the official Football Manager 2019 trailer is released.
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Add potentially a player-manager mode it will make the game more fun and give it a new side.
A one match mode, there should be a quick match mode where you can select the team you want to play as and the team against and just have one match, it will be great fun if you want to roleplay and test out your strategy.
AI improvements, they should seriously work on improving the AI's decisions not just on the pitch but also in the way it targets transfers.
Improve international management, by giving the player more things to do and more events as currently its just the same old thing.


Thanks mbolo01! Very, very helpful to know, though dissappointing. I wonder - is there a way of using headphones with the any B&O audio masters? Considering how many headphone models they sell for parables, it;s odd none of the Audio systems have headphone ports. Is there a 3rd party solution?
Boom! Millemissen - a really detailed and helpful answer - thank-you for taking the time to write that all down. I shall have to think carefully about how to approach this, as (not surprisingly) the TV & audio systems are not proximate to each other. Same room, but opposite ends, and hiding cables will be a challenge. Once again - to all who answered - thanks!
Re: Moment AUX input delay ?
Re: BL18 connected to multiple devices?
So, you cannot have a set of WISA speakers that can intelligently share themselves between two WISA sources - like a Moment and a BV11? I'm actually asking because i'm interested in sharing a Beolab 19 Sub between these two sources. My room forces me to have a TV area, and an audio area, but both could do with a little oomph from a sub. Ideally I could share, as i'll never have both on simultaneously.


RE: Is Opera for me?
Few years ago, Opera was the leader, all new proposition camed out form Opera. Tabs for example, Opera was the first to introduce them then the others followed.
Now, Opera is facing some problems, and the reason is obvious MONEY.
On this point, Google hasno shame, they are using Ads and a lot o fthem, in every corner of their product.
That said, Opera is very different from Chromium and gives a completely different user experience.
So give it a try and tell us about your experience.


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