text:
Q: Show that $f(x)=3x^{2}-2x+1$ is continuous at 2 Please check my proof
Let$\delta ,\epsilon >0$
$$|x-2|<\delta \rightarrow |f(x)-f(2)<\epsilon $$
$$             \rightarrow  |3x^{2}-2x+1-3x^{2}-2x+1|<\epsilon $$
$$             \rightarrow |-4x|<\epsilon $$
$$             \rightarrow 4|-x|<\epsilon $$
$$             \rightarrow  |-x|<\frac{\epsilon }{4}$$
choose $\delta =\frac{\epsilon }{4}$
then$ 4|-x|<\frac{4\epsilon }{4}=\epsilon $
therefore it 's continuous at 2

A: No, this is incorrect. There is a general "formula" for how these proofs should go. Whatever "$\delta$" calculations you do are in some way inessential. You should try again like so:
Let $\epsilon>0$. Suppose that $\delta=a>0$. Then $|x-2|<\delta$ implies that $|f(x)-f(2)|<\epsilon$. This asserts the existence of an appropriate $\delta$ for each $\epsilon$, which is what you need for continuity.
The "implies that" is the majority of the proof. You should plug in the function $f$ for both values, and show how your assumption on the size of $\delta$ can be used to prove the claim.
Additionally, you have made algebra errors in the "solution" for $\delta$. perhaps somebody will give a full solution, but as written, your proof is incorrect.

A: If $f(x)=3x^{2}-2x+1$, then $f(2)=3\cdot2^2-2\cdot2+1=9$. So you want to make
$$\left|f(x)-f(2)\right|=\left|3x^{2}-2x+1-9\right|=\left|3x^{2}-2x-8\right|=\left|x-2\right|\left|3x+4\right|$$
arbitrarily small given that you can make $|x-2|$ sufficiently small. Can you proceed?

Two typical ways to proceed to find a suitable $\delta$ as a function of $\varepsilon$:

*

*first bound $\delta$ (e.g. $\delta \le 1$) to get an upper bound on the factor $\left|3x+4\right|$;

*rewrite: $3x+4=3(x-2)+10$, then $\left|3x+4\right| \le 3\left|x-2\right|+10$.


text:
'Watch out' for Wilsons Auctions Unreserved Government Auction
Over 60 high-value watches to go under the hammer with no reserve this week
Take a look at some of the items up for grabs at Wilsons Auctions this week
Wilsons Auctions, the UK and Ireland's largest independent auction company, is preparing to auction over 60 high-value watches along with other luxury goods during its monthly Unreserved Government Auction on Thursday June 28.
The popular auction, which is available to online bidders, will feature a significant number of watches from designers including Hublot, Rolex, Audemars Piguet, Cartier, Tag Heuer, Breitling, Bulgari and Omega.
With over 100 Lots in total, other items that will feature in this month's auction, which will take place at 6pm in Wilsons Auctions Belfast branch, includes seven Scoop Fatty Aluminum Rigid Fatbikes, an Audi S3, a Volkswagen Transporter Campervan, personalised registration plates, designer good from Christian Louboutin and Giuseppe Zanotti and a selection of jewellery including Cartier bracelets.
The Government Property Auction will directly follow with a selection of land and property across the UK including seven properties located in the Kettering, Northamptonshire area, a ground-floor retail unit in Exeter, Devon, as well as property in Southampton, Hampshire, Bracknell, Berkshire and South Bermondsey, London with guide prices ranging from £45,000 to £465,000.
Scoop Fatty Aluminium Rigid Fatbike
Wilsons Auctions' Asset Recovery Executive Michael Streight said: "The clock really is ticking down to this month's Unreserved Government Auction with our biggest collection of high-value watches to feature in one auction that will whet the appetite of any watch enthusiast.
"With all items going under the hammer with no reserve, this is a great opportunity to purchase quality goods for an affordable price.
"All items will be sold to the highest bidder at the fall of the gavel, with reserve requirements on the land and property only.
"Each month Wilsons Auctions plays an important role in realising a large quantity of assets on behalf of our government clients which has seen us responsible in returning more than £85million back into the public purse and we are delighted to have recently announced that we can add the Metropolitan Police Service to the law enforcement agencies we work with."
"We are proud to facilitate these auctions across the group, which are proving more and more popular each month," he added.
A family-owned business, Wilsons Auctions was formed in 1936 in Northern Ireland and has grown to become the largest independent Auction Company in the British Isles with sites in the Northern Ireland, Republic of Ireland, England, Scotland and Wales.
Wilsons Auctions is more than just an auction company, managing the whole asset realisation process for private and public sector and over 40 law enforcement agencies across the UK and Ireland.
Physical viewing of Lots will take place at Wilsons Auctions' Belfast branch on Wednesday 27 June from 1pm – 6pm and Thursday 28 June from 10am – 5.30pm. All Lots can be viewed at any time online with additional images available on request. Specific Land & Property viewing dates can be found on the Wilsons Auctions website.
For full details on all Lots or to register by midday on Thursday 28 June, go to www.wilsonsauctions.com , follow on Facebook @wilsonsauctionsltd or go to @wilsonsauctions on Twitter and Instagram.
Keep up-to-date with all the very latest news, what's on, sport and everything else in Belfast and beyond with the Belfast Live app.
Only select news that interests you by picking the topics you want to display on the app's homepage. Plus, our enhanced user experience includes live blogs, video, interactive maps and slick picture galleries. Download it now and get involved.
Click here to get it from the App Store or here for Google Play .
BBCFilming begins in South Belfast for new Dylan Moran BBC comedy series called StuckShooting for the show has been taking place in a house on South Parade street, off Ormeau Road
Sophie the giraffe teether warning after Co Tyrone mum discovers mould inside
Co TyroneThe mum was shocked to find the dark spots after close inspection of her daughter's teether
Inside My Wedding: See inside Co Armagh couple's big day at the Carrickdale Hotel and Spa
Real LifeThe McEntees had three days of celebrations!
Short breaks Northern Ireland: Nine great weekend getaways within two hours of Belfast
TravelIf you're looking for a handy staycation, here's your answer
Who is Jude Hill - the leading actor in Kenneth Branagh film Belfast?
Belfast FilmThe 11-year-old actor was plucked from a local talent agency - and is now winning awards internationally
Real LifeSome of the issues he faced were chronic lung disease, renal failure, hypertension, sepsis several times and he was on antibiotics for more than 100 days.
Filming begins in South Belfast for new Dylan Moran BBC comedy series called Stuck
BBCShooting for the show has been taking place in a house on South Parade street, off Ormeau Road
Jamie Dornan's life and career from modelling to TV and film as Belfast is released
Belfast FilmWe take a look back at the actor's life and career as 'Belfast' is released in UK cinemas
Travel rules for Spain, France and Italy from Northern Ireland
TravelWe've pulled together what you need to know
East BelfastCharity box, cigarettes and alcohol stolen in 'terrifying' armed robbery in East Belfast"Both staff members, whilst physically unharmed, were left shaken by what was obviously a terrifying experience for them"
Tiger's Bay bonfire court challenge against Stormont ministers set for this week
StormontJamie Bryson claims two ministers' course of action was "clearly unlawful"
Northern Ireland U21 and Wolves full-back Jack Scott eager to impress in League of Ireland
Wolverhampton Wanderers FCVersatile teenager has joined St Patrick's Athletic on loan ahead of new campaign
Ashling Murphy's funeral hears family 'robbed' of the 'most precious gift'
Republic of IrelandThousands turned out for the funeral of school teacher Ashling Murphy
Ashling Murphy funeral: GAA club pays emotional tribute to murdered primary school teacher
CamogiePlayers and members from the Kilcormac/Killoughey camogie club were among the huge crowd that gathered to pay its respects
Charity box, cigarettes and alcohol stolen in 'terrifying' armed robbery in East Belfast
East Belfast"Both staff members, whilst physically unharmed, were left shaken by what was obviously a terrifying experience for them"
Irish League fans saying the same thing after watching Cliftonville vs Glentoran
Glentoran FCGlentoran came from behind to earn a 2-1 win at Solitude in front of the Sky Sports cameras
GAA club pays emotional tribute at Ashling Murphy
What channel is Aberdeen vs Rangers on? TV and live stream info for Tuesday's game
Rangers FCRangers travel to Pittodrie for their first game following the winter break - kick-off 7.45pm

redpajama_set_name: RedPajamaCommonCrawl


text:
Il Premier Padel è un circuito professionistico mondiale di padel.

Storia

Il Premier Padel è stato fondato nel 2022, il nuovo circuito mondiale si affianca al già noto World Padel Tour. La differenza con quest ultimo, è che il Premier Padel è l'unico circuito riconosciuto ufficialmente dalla Federazione Internazionale Padel (FIP), e ha ottenuto il sostegno della Professional Players Association (PPA) e dal Qatar Sports Investments (QSI).. A differenza del World Padel Tour, il premier padel organizza solo tornei maschili, per una scelta personale delle giocatrici del world padel tour. L'intenzione per gli organizzatori del circuito è di ampliarlo anche con tornei femminili in futuro.

Opposizione del World Padel Tour
Il World Padel Tour si è mostrata fin dall'inizio contraria alla nascita di un nuovo circuito, citando in giudizio la federazione internazionale ed imponendo ai propri giocatori di non prenderne parte. Successivamente il tribunale di Madrid respinse il ricorso dichiarando che i giocatori fossero liberi di giocare qualsiasi torneo.
Per la stagione 2023 il Premier Padel ha comunicato la volontà di parlare con gli organizzatori del World Padel Tour per esplorare possibili collaborazioni e lavorare insieme sulla crescita del padel mondiale.

Vittorie per giocatore

Maschile

Note

Collegamenti esterni

Competizioni sportive

redpajama_set_name: RedPajamaWikipedia


Brooke Weston Teaching School Alliance (TSA) is running a bespoke training programme for Sixth Form students who are considering joining the teaching profession.
The 'Future Teachers' programme gives students the opportunity to visit different schools across primary, secondary and special settings. The experience involves lesson observations and opportunities to talk to experienced and newly qualified teachers.
A total of 12 Sixth Formers are on the first cohort. So far they have visited Kingsley Special School in Kettering, and Beanfield Primary School with a final session at Brooke Weston Academy scheduled later this month. Each visit consists of a school tour, classroom observations and an informative workshop at Brooke Weston Teaching School, all led by experienced teachers who can answer any queries the students have.
Reka Szalontai from Kettering Science Academy said: 'I was in reception class and we talked to the children and helped them out and observed a few lessons. It has been really useful.
To see more pictures of the first two sessions, click here.
Newly qualified and recently qualified teachers (left) and BWA's Head of Sixth Form Nina Smith (right) withsome of the KSA and BWA students who are attending the course.


text:
Winless Texas Southern shocks Florida with upset of Gators who were 26-0 vs. teams from the SWAC
Posted by nbanews — December 7, 2021 in College Basketball 0 0
After starting the season by playing six road games in 15 days, Texas Southern only recently was able to get some time off between games for its players to rest their bodies. That rest paid off as the winless Tigers outplayed No. 20 Florida from start to finish in a 69-54 upset of the Gators at the O'Connell Center on Monday.
Texas Southern entered the game ranked No. 273 in the NCAA's NET rankings which made its debut Monday. The Tigers started the season with a brutal schedule that included losses at Oregon, Washington, NC State and BYU.
But that didn't matter when Texas Southern took the court vs. the Gators. The Tigers (1-7) shot 54.4% from the field including 45.5% from 3-point range and outrebounded Florida 46-23. Junior guard PJ Henry scored 16 points and forward John Walker II scored 13 points to lead Texas Southern.
The Gators (6-2) were hoping to bounce back from a loss at Oklahoma last week and a home game against Texas Southern should have been just what they needed.
Instead Florida, a 23.5-point favorite according to Caesars Sportsbook, lost for the first time in 27 games against Southwestern Athletic Conference team. It was the first time a SWAC team beat a ranked SEC program according to ESPN Stats & Info. Ranked SEC teams had been 51-0 against teams from the SWAC.
Florida got 15 points from Brandon McKissic, but struggled all night vs. the Tigers. The Gators shot 38.2% from the field and were just 5-of-24 from 3-point range.
Texas Southern coach Johnny Jones, a former coach at LSU, improved his record to 2-2 against UF coach Mike White.
The Tigers have made five NCAA Tournament appearances since 2014 but were predicted to finish fourth in the SWAC's preseason poll.
Ohio State leads Northwestern by double digits at the half behind E.J. Liddell's hot shooting
Morris, Jokic brothers take beef to Twitter after shove
Draymond Green gives reason Steph Curry's 3-point record will be broken
Klay Thompson going full-speed in G-League practice, hits first 18 shots
Jaylen Brown leads the Celtics to a needed bounce back win over Orlando
Lakers have championship talent, plenty of questions as they attempt to reclaim NBA title in 2021-22 season
Andre Iguodala to be free agent as team option declined
College basketball rankings: Transfers have Texas making a big jump in early preseason Top 25 And 1


text:
Q: Catching get request in java Let's say I have a HTML page and I am running back-end on java and I want to make simple ajax request call.
e.g
fetch('localhost:8080/testResponse)
.then(function(response) {
  return response.json();
})

and on my java server I have
@Path('testResponse')
public class NewClass {
    private String name = "MyName";
    private String age = "MyAge";
    @GET
    public String getName(){
        return this.name;
    }
    @GET
    public String getAge(){
        return this.age;
    }
}

So basically there is get request to /testResponse , and Path annotation indicates what class should catch it but how do I choose what method will get invoked and returns data? Whats the logic behind it? I cannot find anything about it.
/////////////////////////////////
So. I have created new web project in netbeans. It generated html file , i added just basic ajax call to server.

        <title>TODO supply a title</title>
        <meta charset="UTF-8">
        <meta name="viewport" content="width=device-width, initial-scale=1.0">

TODO write content

When i run it it shows on localhost:8080/ajax_test
I created a file by comments here e.g
@Path("/ajax_test")
public class testik {
    private String name = "MyName";
     private String age = "MyAge";
    @GET
    @Path("/name")
    public String getName(){
        return this.name;
    }
    @GET
    @Path("/age")
    public String getAge(){
        return this.age;
    }
}

Yet its still 404  did i miss something? Thank you again for help

A: SImply use the @Path to further delineate the endpoint.
So if you want 'URL Prefix/testResponse/name' and 'URL Prefix/testResponse/age' then do the following:
@Path("/testResponse")
public class NewClass {
    private String name = "MyName";
     private String age = "MyAge";
    @GET
    @Path("/name")
    public String getName(){
        return this.name;
    }
    @GET
    @Path("/age")
    public String getAge(){
        return this.age;
    }

A: The first matching method for your resource /testResponse and its annotations will be called, in your case getName(). You can add additional annotations, to specialize your methods:

*

*@Consumes: Defines the MIME media types for your request, like application/json

*@Produces: What MIME media type the data you return has. This attribute corresponds to the Accept header you have sent.

*@Path: Further sub path to your resource.

In your case, getName() will always be called, because it is the first in line and there are no other annotations that differentiate both methods further. Also, since you are using REST resources, each resource must have a unique path, so you could define subresources for name and age like this:
@Path('testResponse')
public class NewClass {
    private String name = "MyName";
    private String age = "MyAge";

    @GET
    @Path("/name")
    public String getName(){
        return this.name;
    }

    @GET
    @Path("/age")
    public String getAge(){
        return this.age;
    }
}

Your resources are then available at /testResponse/name and /testResponse/age.
Look at the following example. Here, both methods share the same path, namely /testResponse, however the actual method to be called is selected by the Content-Type header you have sent in your Ajax request. If you set Content-Type: application/json, getJsonName() is called and analogously for XML and getXmlName().
@Path('testResponse')
public class NewClass {
    private String name = "MyName";
    private String age = "MyAge";

    @GET
    @Consumes("application/json")
    public String getJsonName(){
        return this.name;
    }

    @GET
    @Consumes("application/xml")
    public String getXmlName(){
        return this.name;
    }
}

You can combine this with the other annotations mentioned above. The method to be called is always the first that matches your resource path and request header attributes with the provided annotations.

A: If I understood you correctly then you want to invoke one of the GET methods when you hit testResponse. You are allowed to annotate your methods with @Path like this:
@Path("/")
public class NewClass {
    private String name = "MyName";
    private String age = "MyAge";

    @GET
    @Path("/testSomething")
    public String getName(){
        return this.name;
    }

    @GET
    @Path("/testResponse")
    public String getAge(){
        return this.age;
    }
}

redpajama_set_name: RedPajamaStackExchange


Petroflex North America (PNA) PNA manufactures superior quality, continuous length HDPE duct and accessories to the Electric Utility, Renewables, Irrigation, Oil & Gas, Telecommunications, CATV and Data Voice industries.
ROTOMOLDING PLASTICS FOR THE FUTURE. Dura-Cast Products, Inc. is Florida's largest rotomolder of custom plastic products. We manufacture and sell high-quality products to original equipment manufacturers (OEMs), distributors, dealers, and consumers.
The Trump administration has canceled a study of a proposed 20-year mining ban within the watershed of the Boundary Waters Canoe Area Wilderness, clearing the way for renewed mineral leasing.
Priefert's Heavy Duty Bull Mineral Feeder is constructed from weather resistant black poly. This durable ground feeder includes three mineral compartments to provide expensive mineral supplements protection from the elements.
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What is the country code of Costa Rica?
The Costa Rica country code is +506. It is used for calling to the Costa Rica from other country. Below the data are arranged only for your reference. Also you may find other necessary information about others countries from the top right Search Box.
What is the area code of Costa Rica?
The Costa Rica area code is one kind of code that help you make international phone call to Costa Rica. For making an international call to Costa Rica, use the country code of Costa Rica before the area code and the local number.
What is the dialing code of Costa Rica?
The Costa Rica dialing code is a code number which familiar with the name Costa Rica international dialing code, telephone code, phone code, or calling code. Without the dialing code, nobody can't make a call from the other country to the Costa Rica.
How to make an international call to Costa Rica?
To make an international call to Costa Rica, first dial the IDD, then country code, any area code, and the local number. The Costa Rica international dial code is usually followed by the city or area code.


text:
function [nrows,ncols]=panelsize(pwells,dim)
% Get the number of columns/rows of the panels of pseudo-wells
%
% Written by: E. Rietsch: January 15, 2004
% Last updated:
%
%         [nrows,ncols]=panelsize(pwells,dim)
% INPUT
% pwells  pseudo-well structure
% dim     optional dimension for which to compute length (like size(a,2))
% OUTPUT
% nrows   number of rows
% ncols   number of columns

mnem=pwells.panel_info{1};
if nargin == 1
   [nrows,ncols]=size(pwells.(mnem));

elseif nargin == 2
   nrows=size(pwells.(mnem),dim);

else
   error('One or two input arguments required')

end

redpajama_set_name: RedPajamaGithub


text:
Q: NSFetchedResultsController doesn't update count after delete I'm learning CoreData on mac os. I have a demo program which basically works, except that when I delete a row from my tableView,
fetchedResultsController.fetchedObjects?.count

hasn't updated.
Revelevant properties are defined as follows
    var container: NSPersistentContainer!
    var fetchedResultsController: NSFetchedResultsController<Commit>!
    var count: Int { get {
        if fetchedResultsController == nil { return 0 }
        return fetchedResultsController.fetchedObjects?.count ?? 0
        } }

The remove method:
    func remove(itemAt index: Int) {
        guard let n = fetchedResultsController.fetchedObjects?.count,
            index < n && index >= 0,
            let commit = fetchedResultsController.fetchedObjects?[index] else { return }
        container.viewContext.delete(commit)
        saveContext()
        ddt("remove \(count)", caller: self)
    }

The count after remove hasn't been updated, however the persistent store is correct. If I remove another row, it still doesn't update, but if I change predicate (even to the nil predicate) it refreshes properly.
On relaunch, all is updated.
My delegate doesn't do anything. The table gets updated in its delegate:
    func tableView(_ tableView: NSTableView, rowActionsForRow row: Int, edge: NSTableView.RowActionEdge) -> [NSTableViewRowAction] {
        // left swipe
        if edge == .trailing {
            let deleteAction = NSTableViewRowAction(style: .destructive, title: "Delete", handler: {
                [unowned self] (rowAction, row) in
                    self.dataContainer.remove(itemAt: row)
                    tableView.removeRows(at: [row], withAnimation: .slideLeft)
            })
            deleteAction.backgroundColor = NSColor.red
            return [deleteAction]
        }
        // Anything other than left does nothing
        return []
    }

What have I left out?
(ddt, for those too young to remember, was an insecticide banned many years ago because it tended to propagate up the food chain, killing off birds, among other species. I think it's safe to use on bugs in Swift.)

A: *

*First of all declare the fetchedResultsController as lazy non-optional property and set the delegate in the closure
lazy var fetchedResultsController: NSFetchedResultsController<Commit> = {

    ...

    let controller = NSFetchedResultsController( ...
    controller.delegate = self

    ...
    return controller
}()

*Adopt NSFetchedResultsControllerDelegate and implement the delegate methods

*

*func controllerWillChangeContent(_ controller: NSFetchedResultsController<NSFetchRequestResult>)

*func controller(_ controller: NSFetchedResultsController<NSFetchRequestResult>, didChange anObject: Any, at indexPath: IndexPath?, for type: NSFetchedResultsChangeType, newIndexPath: IndexPath?)

*func controllerDidChangeContent(_ controller: NSFetchedResultsController<NSFetchRequestResult>)

*To delete a record in a NSTableViewRowAction get the item at indexPath and delete the record in the Core Data stack. You don't need to check the index, the row does exist
let indexPath = IndexPath(item: row, section: 0)
let commit = fetchedResultsController.object(at: indexPath)
container.viewContext.delete(commit)
saveContext()

The NSFetchedResultsControllerDelegate methods manage the update of the UI


text:
» Home » Distance Learning » Courses » HIST – History » HIST 303 (6 cr): History of the Canadian West
Available Course Sections
[more-course-info-2]
This is a print-based, correspondence course.
Six assignments
Final examination options
Course Description and Prerequisites
Selected topics in the history of the Canadian West: First Nations people and the fur trade, Louis Riel, prairie settlement, and western social and political protest.
This course focuses on selected topics in the history of western Canada from 1670 to 1970. Among the included topics are: First Nations and the fur trade; women and fur trade society; colonial society in Red River and Fort Victoria; the west and Confederation; Indian Treaties, the North West Mounted Police and Louis Riel; the homestead experience; social reform, farm and labour protest; the rise of Social Credit and the Cooperative Commonwealth Federation; and the "new" West post-World War II. As the listed topics suggest the course is focussed more on the prairie than Pacific west. To help the student approach the readings and assignments with greater insight, the course begins with a discussion on the nature of historical enquiry.
Students considering the possibility of completing a major in History are reminded that they must have 6 units of History 100-299 or the equivalent from another institution and that their third- and fourth-year courses must be chosen in consultation with a departmental adviser.
Second-year students wishing to enrol in this course must first obtain permission from the instructor.
The first of the course's ten lessons explores some answers to the question "what is history?" before going on to consider the influence of geography on the opening of the Canadian West to Europeans. In the first part of Lesson 2 we look at several aspects of the fur trade, first in relation to the indigenous population, then from a European perspective, and finally at its larger legacy for contemporary First Nations people and other Canadians; the second half of the lesson uses first-hand accounts for the study of fur trade society. Lesson 3 examines the relationship between the fur trade and the colonial development of the Red River and British Columbia. In Lesson 4 the entry of those two western regions into Confederation, and the problems attendant on their inclusion, are studied. Lesson 5 covers the transition from the old to the new west by focussing on three topics: the Indian treaties; law and order and the role of the North-West Mounted Police; and the place of Louis Riel in Canadian history. We move on in Lesson 6 to settlement of the west in the late nineteenth and early twentieth centuries, and consider the economic and social issues that prompted the drive to attract immigrants as well as the experiences of the settlers who came. The growth of reform ideas and movements in the west make up the major topics of Lesson 7 and the following lesson looks at the ways in which the Depression of the 1930s renewed the impetus for change begun a generation earlier. In Lesson 9 we consider the dynamic period of growth that followed the Depression and Second World War, both in the prairie West and British Columbia. The final lesson of the course, "The Canadian West in Retrospect," reviews western Canadian history in search of notable themes and patterns that might help us refine our understanding of contemporary social and political issues.
The course is organized on the basis of ten lessons, each developed around a broad theme or topic in Western Canadian history. Each lesson or topic is sub-divided into two or three parts that deal with more specific aspects of the broad topic being considered. Though it is intended that students will proceed through the materials at their own pace, a course schedule is provided to help you organize your activities according to the following time sequence; that is, one lesson completed approximately every three weeks. This would mean that you could work through the entire course in roughly thirty weeks.
There is an ungraded assignment early in the course, followed by six graded ones. The latter involve a variety of activities from writing a period journal and letter to the preparation of three short-to-moderate length essays (approx 1,250-2,500 words) and one term paper (3,500-4,000 words). The course may be completed in either of two ways:
a) a final essay of about 4,000-5,000 words (Lesson 11)
b) a three-hour invigilated examination (part one will be a short-answer question where you will be asked in a paragraph to identify and explain the historical significance of five out of nine names, events, or terms; the remaining two sections will require three essay answers to a selection of questions drawn previously from the list of study topics and questions which accompany each lesson.).
The 100 marks awarded for History 303 will be divided into the following percentages:
Lesson 2 (journal assignment) 15%
Lesson 4 (short essay) 5%
Lesson 6 (letter assignment) 10%
Lesson 7 (term paper) 25%
Lesson 10 (moderate essay) 10%
Final exam or local history project 30%
Required Textbooks and Course Materials
Friesen, Gerald. The Canadian Prairies: A History. Toronto: University of Toronto Press, 1987.
Hallet, Mary, and Marilyn Davis. Firing the Heather: The Life and Times of Nellie McClung. Saskatoon: Fifth House Publishers, 1994. (now available as CCM at the UBC Bookstore)
Horn, Michiel. "The Great Depression of the 1930s in Canada". Ottawa: Canadian Historical Association Booklet No. 39, 1984. (now available as CCM at the UBC Bookstore)
Custom Course Materials for HIST 303. Distance Education Section. UBC Bookstore. (This book has been compiled by the course author and is indexed to indicate the reading(s) required for each lesson).
HIST 303 Learner Package (includes course manual)
HIST303 Textbook Order Form
Last updated on June 28, 2010 @10:51 am
The course outline is subject to change. The official outline for this course can be found in the course materials.


Landscape and architectural photographers are always darkening skies to call attention to the foreground elements in their photos. In the past, this correction required the use of a graduated neutral-density filter over the front of your camera lens, or sophisticated Photoshop tricks. The Graduated Filter tool in ACR makes it quick and easy to darken skies, lighten foregrounds or smooth out uneven lighting. One key to remember with the Graduated Filter tool is your gradient is always created from "corrected to protected." Start the gradient on the area you wish to correct then drag it toward the uncorrected part of the image.
This tool is a life-saver for landscape photographers and is one of the most useful tools in the Photoshop CS4 update. Performing your gradient adjustment in ACR offers several advantages of doing it in Photoshop.
1) Speed: By not having to open an image into Photoshop you've eliminated processing time as well as an additional file you have to save, store, manage and back up on your hard drive. This makes your workflow, and your image library, more efficient.
2) Quality: Working on the raw file gives you the best results. With gradients, this equates to smoother transitions between corrected and unaffected areas and more natural, more pleasing photographs.
3) Flexibility: Once you've performed your initial correction, you can quickly modify the intensity of the correction or adjust additional attributes (sharpening, saturation) by adjusting the sliders. You can also reposition the gradient to hide the transition along a horizon line or lengthen the gradient. Your corrections are always performed non-destructively to your raw file.
Bonus Tip: Add Color: Adding a slight color tint to your gradient enhances the mood of your photos considerably. Consider adding a slight blue tint while darkening skies to make clouds feel more foreboding. Add orange to gradients lightening foreground elements to separate them from the background and make subjects appear more approachable and warm.
For a video tutorial on using the Graduated Filter tool, visit the Layers Magazine Web site http://www.layersmagazine.com/photoshop-cs4-graduated-filters.html or for a Lightroom version, visit http://www.prorgb.com/lightroom-2.


This 4 tower-based flat roof lighting trusses rigging is set up with 4 sets common lifting towers and 4 beams. All the trusses rigging is with ITSC-CS29 spigoted trusses segments. It can be extended to within 10m span with 450kg capacity.
Below is how ot install the whole trussing rigging system.
This lighting truss rigging is applied for outdoor events. It is easy and quick to install.


Schulze, K., Knights, K., Coad, L., Geldmann, J., Leverington, F., Eassom, A., Marr, M., Butchart, S. H. M., Hockings, M. & Burgess, N. D., May 2018, In : Conservation Letters. 11, 3, p. 1-10 10 p., e12435.
The Conventional Versus Alternative Agricultural Divide: A Response to Garibaldi et al.
Mehrabi, Z., Seufert, V. & Ramankutty, N., 1 Oct 2017, In : Trends In Ecology and Evolution. 32, 10, p. 720-721 2 p.


text:
Khloe Kardashian Was Banned From The Met Gala
The annual Met Gala was earlier this week…
The annual Met Gala was earlier this week in New York.
It's like prom for famous people, and it's also like a costume party, and there are obviously lots of photographers.
Kim Kardashian was there, of course. And Kendall and Kylie and Kris.
But the biggest and easiest to spot Kardashian, Khloe, was nowhere to be found.
It's not because Khloe suddenly got shy and didn't want to be photographed. She wanted very much to be photographed, in a costume, surrounded by famous people. However, Vogue boss Anna Wintour, who sets the guest list, deemed Khloe too C-list for the soiree.
Can Khloe find a rapper or baller famous enough to make her B-list and willing to be seen with her and/or put a baby in her belly? Tune in to next year's Met Gala to find out!


MSRP: $795.00 - Please Login or call to view pricing.
The Har-Tru Ball Mower is designed for use on clay courts as well as hard courts. When a mower captures too many balls, the wheels lock up and the unit skids across the surface. On a clay court the friction between the wheel on the mower and the court surface is lessened and skidding is more frequent. This leaves marks on the court that are unsightly, and on clay affect ball bounce and play. Enter the patented, anti-jamming mechanism on the Har-Tru Ball Mower. The back plate is spring loaded so that as more balls enter the rolling mechanism it flexes to handle the capacity. The Har-Tru ball mower has also been constructed using stainless steel and aluminum parts, as well as specialized pins and casters to hold up in the moist, gritty environment. We know you are going to love this product.


Thank you! I did check out your post on positive parenting and fully agree. It's tough when the messages around us and our families daily offer judgment (school, peers) and negativity (social media, news). So I agree that we have to become intentional about setting positive goals with our kids and talking about what we are grateful for daily. Similarly, how can we become more intentional in talking about inclusion, about kindness, about how to turnaround unfairness to those who have different skin colors, have differing family structures (divorce, two moms, raised by grandma), or have learning differences? Again, it takes our willingness to embrace discomfort to really take on the important issues our children will face and prepare them to be agents of positive change. Thanks for your comment! Hope you will continue to read and contribute to the dialogue!


text:
Shipyards 'Fight for Survival' for New Orders
With "bleak" prospects ahead, the world's shipbuilders will have to fight for survival warns the latest report from Drewry Maritime Research, of London. This is because of the slump that has hit shipping markets says the company in its Annual World Shipbuilding Market Review and Forecast.
The review says shipbuilding production levels have remained at record high levels for two consecutive years (2010 -2011), with 2012 forecasted to remain close to 2011 levels. However, the orderbook has diminished rapidly and tails-off to very low levels for 2014 and beyond.
"Over-tonnaging and large operating inefficiencies mask the true levels of fleet under-utilisation and are hindering a recovery," says the Drewry review.
"With the orderbook dominated by bulk carriers and container ships, two of the worst hit markets in terms of over supply wreaking havoc with rates, it reflects the fact that for some time now ordering activity by shipowners has exceeded the requirements of trade growth."
To give an insight into the shipbuilding industry's prospect, the Drewry' report presents two scenarios covering the projected new building requirement by sector and ship type over a 15 year period, reflecting the uncertainty that surrounds the industry.
Only under the High Case scenario is there a requirement for further new ordering beyond the size of the orderbook at the start of 2012. Whereas under the more realistic Base Case, in virtually all fleet sectors, the size of the orderbook at the start of 2012 more than exceeded the new building requirement to 2016.


Cinema and restaurant-goers in Huntingdon have been left outraged after receiving £100 fines for overstaying a new time limit.
Furious readers contacted The Hunts Post after being fined for parking at the Towerfields Leisure Park for longer than three-and-a-half hours, following the introduction of a new parking regime on November 30.
Legal & General, the site's landlord, said it introduced the limit to reduce congestion and to stop people abusing the free parking – it claimed people parked at Towerfields and went shopping elsewhere.
Signs have been installed around the car park warning of the changes, and there is an option inside Cineworld to register a car to allow for longer parking. However, critics say the signs are not visible enough and the extended parking scheme is not well advertised.
The limit was introduced seven weeks after new restaurants Bella Italia and Chiquito opened at Towerfields – the two units were built on 25 parking spaces.
David Collon, 52, of Park Road, Ramsey, went to Chiquito and to see Gravity with his partner Lynne Thurlbourn on November 30. "We had a good night and thought nothing of it until we got the fine through the post," he said. "I thought it was fake at first.
"It's terrible that after so many years they put this in without telling anyone. If you have been there many times before, you are not going to look for the signs, why would you? You can't see them in the dark as they're not lit.
Martin Ive, 35, of St Ives, and Lee Frankham and Amy Hollinshead of Chatteris, also contacted The Hunts Post after being fined.
According to a letter sent to those who have been fined, drivers can contest the penalty notice if they can prove they visited the cinema or one of the Towerfields restaurants.
A spokesman for Legal & General told The Hunts Post the scheme had the backing of the businesses on site.
She said: "A new initiative has been put in place in order to ease any potential congestion for the benefit of our customers, to ensure that the facilities were not being abused by members of the public using Towerfields' free car park to go shopping elsewhere.
"Following lengthy consideration and consultation we have installed a vehicle number plate recognition system to monitor dwell times of vehicles visiting the site.
"We opted for a maximum period of three-and-a-half hours – similar to other leisure parks – as we felt this was adequate to cover the vast majority of visits.
The company said it was waiting for feedback from the first two weeks since the introduction of fines.
As reported in The Hunts Post in October, Legal & General undertook a parking study at Towerfields, which found the site was not fully occupied, even at peak times.
INFORMATION: To contest a fine, or for more information, call 0870 919 8000.


text:
Securing the security industry
By Patrick Blennerhassett
The sector is booming in Canada and elsewhere, but hiring remains an issue
The security industry is growing so rapidly that the sector faces huge hurdles in hiring and retaining enough employees, industry insiders say.
Dan Popowich, CEO of security firm Commissionaires BC, said multiple industries including airports, local governments, pipelines, universities, construction and non-core policing are all hiring more security – and have been for the past few years.
"It's just widely expanding," said Popowich. "I was just looking at a report: in Canada's private security industry [hiring has] gone up 40% in five years. We have 140,000 people in private security in Canada alone now."
Popowich said finding good employees remains a challenge for outfits such as Commissionaires BC, which is run as a not-for-profit with 2,100 employees in B.C. and annual revenue of $50 million.
"It's always a burden because the pay is not that great," he said. "The pay is not minimum wage – some people think it is, and it could be as some companies pay minimum wage. But overall most of the very credible companies in the security industry, let's say the top 10 or eight, pay more than minimum wage and there's very good wages to be made."
Popowich said the biggest hurdle is finding employees who have training in technology. He said a large part of the job now involves managing security camera footage, engaging in electronic reporting and using devices like iPads. Popowich said there are still basic security jobs, such as watching over construction sites, that do not require as much training, but those jobs are dwindling. He added he doesn't think the influx of new immigrants can help solve the industry's problem of low employee retention.
"Although we encourage new immigrants to apply, we find that most of them, and I'm talking in terms of our company, do not meet the skill sets of writing and understanding and speaking English."
Popowich said a lot of companies are not willing to pay more when it comes to security contracts, which pushes the industry into a catch-22.
"If we can obviously pay more, then it would attract a different type of person," he said. "The other thing is if we could charge more, then we could provide more training to our officers."
According to B.C. government statistics, the need for security guards rose from 2009, when 16,164 licences were approved, to 2015, when 17,590 were issued. The number of security consultants, the installation of closed-circuit televisions and electronic locking devices and alarm installations under supervision also grew during that period. The global demand for security services rose 7.4% in 2016 to $244 billion.
Paul Stanley, who runs the security consultancy TSC Consulting and holds a master's degree in risk management, was part of BC Hydro's corporate security team for nine years. He said wages for security guards are on par with the fast-food industry, which doesn't reflect the amount of responsibility taken on by security personnel, especially with increasing regulation and rising training standards.
Stanley said the major security companies across Canada require extensive training before their guards are assigned to their duties. Personnel also are required to have a high level of English reading, writing and speaking skills for most positions, and they must also be licensed by the government.
"Guards [are] able to participate in employer-supplied training that enables them to provide first aid and CPR," Stanley said. "[They must be able] to effectively manage a stressful encounter with the public, to communicate with the client's senior management, to write security occurrence reports using advanced software, to manage complex closed-circuit video systems and to administer access control functions using the latest systems available."
Stanley added that finding security guards who will work for the wages available and provide a wide range of services is difficult, and turnover is high.
"This is not an easy task; ask any professional in the business," he said.
Popowich said some regular clients are starting to understand that they can't simply lowball contracts.
"Some of them do understand that you get what you pay for these days."


CapRock Real Estate, LLC's Real Estate Agents Selling your home can be easy. Let our experienced staff help you make it happen.
CapRock Real Estate, LLC is comprised of a team of local real estate professionals committed to selling some of the most desired homes in Grand Junction. Selling these "right addresses" is the mission of CapRock Real Estate, LLC. Let us know what you're looking for. Please take advantage of the helpful tools on this website, including our exclusive Grand Junction Real Estate search, but also feel free to contact us personally.


A great way to add some panache to your ensemble is with a stylish set of cufflinks!
You can purchase these new Paul Smith cuff links for $140- from Nordstrom.
This blog post was originally published on January 18, 2016. If you have questions about these items or would like to purchase them please follow the links provided under each photo to contact the seller. Lulu's Vintage is not selling these items.
Paul Smith London 'Byard' trim fit plaid suit.
Paul Smith 'Miller' spectator shoes in navy.
Paul Smith London 'Kensington' navy windowpane wool pants.
This post was originally published on January 26, 2015.
Here at Lulu's Vintage store we just put out vintage Men's black leather cowboy boots with white stitching, Women's Salvatore Ferragamo pumps with bow detail, Women's pumps with cool wood and metal heels.
Norway's Olympic men's curling team with cool red, white and blue zig zag suits.
This post was originally published on January 27, 2014.
November's theme for our window display is vintage cocktail attire & black tie formal wear. Drop by the store today and shop for your holiday party needs.
This post was originally published on November 9, 2013.
A.P.C. leather and wool varsity jacket.
1970's leather and wool varsity jacket.
This blog post was posted on October 14, 2013. If you have questions about the clothing or would like to purchase any of the items follow the links provided.
Round yourself up an eclectic quilt patterned cowboy shirt with orange accents.
The Men's window featuring a necktie with text and maple leaves advertising for a brand of gin, an Autumnal photo necktie, and college themed advertisements.
A trio of frightfully wonderful ladies ensembles.
Vintage DJS purse displayed alongside a new DJ Scare D Cat Halloween card by local artist Red Bat Press.
This post was originally published on October 10, 2013.
We have moved the Men's clothing and accessories to the left side of the store.
Men's hats are displayed on top of the clothing racks. Men's belts and shoes are displayed on the bottom of the racks.
Vintage bowties, cummerbunds, wallets and hats.
Vintage ascots/scarves, suspenders, ashtray & lighter, and caps.
Our school themed Men's window.
This post was originally published on September 16, 2013.
This super cool vintage Bass Anglers Sportsman Society jumpsuit was on a mannequin in my store window. This man came in and said I want to buy that. He tried it on and it looked great! He said he was going on a fishing trip on the Willamette- so it was the perfect thing to buy.
1950's cap with fish design.
This post was originally published on July 8, 2013.


Here at this station we kicked off the celebrations when you "Open Your Eyes" this morning with William and me. The lineup of artists included the General himself, Ernestine Carballo and the Belize Dance Company just back from Europe and Nello Player. Here's how they got us into the Independence spirit.
Hip! Hip! Happy Independence Day!


And now on every smartphones are equipped with Free Cell Phone Tracking For iOS 7 that is perhaps the golden opportunity for tracking the user's location . No need to spend money on a car located just installing Free Cell Phone Tracking is new information about a user's location will be reported to you on an ongoing basis and accurately buy jumping castle.
Spying relevant people ( kids , teammates , staff … ) GPS location whenever you want ! With tracking device , you can always get the help of the map you do not get lost .
READ Best Cell Phone GPS Tracking For iPhone!


The 3700 is a single-channel panel instrument for sensor conditioning, with adjustable engineering unit's display and true amplified analog output.
The 3700 series is based on the popular Daytronic 3000 meters. Its focus is to provide a stable, user configured, display, as well as a noise free amplified analog signal for the measurement of force, load, displacement and other parameters associated with low level sensor signals.
The display is user configured for engineering unit scaling up to +/- 199950 "independently of the analog signal", maximizing the capabilty of the analog signal output level. The 3700 also has an added feature of a true analog "TARE" button for quick zero offset alignment.


text:
Barry Henry Stobart (6 June 1938 – 28 August 2013) was an English footballer who played in the Football League as a forward for Wolverhampton Wanderers, Manchester City, Aston Villa and Shrewsbury Town during the 1960s.

Career
Stobart began his football career at Wath Wanderers, the Yorkshire-based nursery club of Wolverhampton Wanderers, before heading south in 1953 to join them, turning professional in 1955.

With the likes of Peter Broadbent, Dennis Wilshaw and Jimmy Murray already established in the forward line, Stobart was consigned to the reserves in his early years. He finally made his first team debut on 5 March 1960, when he scored in a 2–0 win at Manchester United.

Although he made just four league appearances before the 1960 FA Cup Final, his performance in the final league game at Chelsea saw him earn a surprise place in the Cup Final team, at the expense of Bobby Mason. This allowed Stobart to collect the only medal of his career, as Wolves defeated Blackburn 3–0 in the Wembley showpiece. Barry Stobart was given the nickname "Kangaroo Kid" due to his unique ability to jump and score many goals via headers.

The following two seasons saw him only appear occasionally for the first team, and it wasn't until the 1962–63 campaign that he enjoyed a lengthy run in the side, during which he scored 14 goals. The next year saw him again largely relegated to the reserves though, and he left Molineux to join Manchester City in summer 1964.

He failed to settle at Maine Road, and returned to the Midlands within months when he joined Aston Villa in November 1964 for £22,000. He remained at Villa for three years, his best season coming in 1966–67 when he scored 11 times from 20 appearances. He dropped down the divisions in October 1967 to join Shrewsbury Town of the Third Division in a £10,000 deal. After a spell with them, he moved to South Africa to play out his career with Durban Spurs.

His eldest son Sean Stobart was a professional footballer a Scunthorpe United scoring on his first team debut against Rochdale FC.

His youngest son Loy was later also on the professional books at Wolverhampton Wanderers during the early 1990s having signed from Nottingham Forrest on a free transfer. He also played for Cheltenham Town FC and Bidvest Witts  in South Africa.

Post Football
Barry went on to coach Willenhall Town FC to an FA vase final in 1981 at Wembley and guided semi-pro footballers, John Muir, Brendan Hackett and Russell Bradley to professional careers in Football. After retirement he worked as a greengrocer and finally as a window cleaner in the Sedgley area.

Vascular dementia
In 2005 it was revealed that Stobart suffered from vascular dementia. He resided in a care home from 2009 and died on 28 August 2013.

References

External links

1938 births
2013 deaths
Footballers from Doncaster
English footballers
Association football forwards
Wolverhampton Wanderers F.C. players
Manchester City F.C. players
Aston Villa F.C. players
Shrewsbury Town F.C. players
Addington F.C. players
Durban United F.C. players
English Football League players
FA Cup Final players


Del is a symbol used in mathematics, in particular, in vector calculus, as a vector differential operator, usually represented by the nabla symbol ∇. When applied to a function defined on a one-dimensional domain, it denotes its standard derivative as defined in calculus. When applied to a field (a function defined on a multi-dimensional domain), del may denote the gradient (locally steepest slope) of a scalar field (or sometimes of a vector field, as in the Navier–Stokes equations), the divergence of a vector field, or the curl (rotation) of a vector field, depending on the way it is applied.
Strictly speaking, del is not a specific operator, but rather a convenient mathematical notation for those three operators, that makes many equations easier to write and remember. The del symbol can be interpreted as a vector of partial derivative operators, and its three possible meanings—gradient, divergence, and curl—can be formally viewed as the product of scalars, dot product, and cross product, respectively, of the del "operator" with the field. These formal products do not necessarily commute with other operators or products.


text:
\section{Introduction}

The goal of text simplification is to transform text into a variant that is more broadly accessible to a wide variety of readers while preserving the content. While this has been accomplished using a range of approaches \cite{shardlow2014survey}, most text simplification research has focused on fully-automated approaches \cite{xu2016optimizing,zhang2017sentence,nishihara2019controllable}. However, in some domains, such as healthcare, using fully-automated text simplification is not appropriate since it is critical that the important information is preserved fully during the simplification process.  For example, Shardlow et al. \shortcite{shardlow2019neural} found that fully automated approaches omitted 30\% of critical information when used to simplify clinical texts. For these types of domains, instead of fully-automated approaches, interactive text simplification tools are better suited to generate more efficient and higher quality simplifications \cite{kloehn2018jmir}.

Autocomplete tools suggest one or more words during text composition that could follow what has been typed so far. They have been used in a range of applications including web queries \cite{cai2016survey}, database queries \cite{khoussainova2010snipsuggest}, texting \cite{dunlop2000predictive}, e-mail composition \cite{chen2019gmail}, and interactive machine translation,  where a user translating a foreign sentence is given guidance as they type \cite{green-etal-2014-human}. Our work is most similar to interactive machine translation.
Autocomplete tools can speed up the text simplification process and give full control over information preservation to users, which is required in some domains, such as health and medical.

In this paper, we explore the application of pretrained neural language models (PNLMs) to the autocomplete process for sentence-level medical text simplification. Specifically, given (a) a difficult sentence a user is trying to simplify and (b) the simplification typed so far, the goal is to correctly suggest the next simple word to follow what has been typed. Table \ref{tab:example} shows an example of a difficult sentence along with a simplification that the user has partially typed. An autocomplete model predicts the next word to assist in finishing the simplification, in this case a verb like ``take'', which might be continued to a partial simplification of ``take up glucose''. By suggesting the next word, the autocomplete models provide appropriate guidance while giving full control to human experts in simplifying text.  We explore this task in the health and medical domain where information preservation is a necessity.

We make three main contributions:

\begin{table}
    \centering
    \scalebox{0.9}{%
    \begin{tabular}{l l}
    \toprule
    Difficult & Lowered glucose levels result both in the reduced release of insulin from the beta \\
              & cells and in the reverse conversion of glycogen to glucose when glucose levels fall. \rule[-2ex]{0pt}{0pt} \\
    \hline
    Typed &  This insulin tells the cells to $\rule{1cm}{0.15mm}$ \rule{0pt}{3ex} \\
    \bottomrule
    \end{tabular}}
    \caption{ An example text simplification Autocomplete task.  The user is simplifying the difficult sentence on top and has typed the words on the bottom so far. The example is taken from a medical parallel English Wikipedia sentence pair in Table \ref{tab:medexample}.}
    \label{tab:example}
\end{table}

\begin{table}
    \centering
    \scalebox{0.9}{%
    \begin{tabular}{l l}
    \toprule
    Difficult & Lowered glucose levels result both in the reduced release of insulin from the beta \\
              & cells and in the reverse conversion of glycogen to glucose when glucose levels fall. \rule[-2ex]{0pt}{0pt} \\
    \hline
    Simple & This insulin tells the cells to take up glucose from the blood. \rule{0pt}{3ex}\\
    \bottomrule
    \end{tabular}}
    \caption{An example of sentence pair in Medical Wikipedia parallel corpus.}
    \label{tab:medexample}
\end{table}

\begin{enumerate}

\item We introduce a new parallel medical data set consisting of aligned English Wikipedia and Simple Wikipedia sentences, which is extracted from the commonly used general Wikipedia parallel corpus \cite{kauchak2013improving}. The resulting medical corpus has 3.3k sentence pairs.  This corpus is larger than previously generated corpora (by over 1k sentence pairs) and has stricter quality control \cite{van2019evaluating}. Our corpus requires a medical sentence to contain 4 or more medical words and belong to medical titles as compared to the no title requirement and needing to contain only 1 medical word, as described in Van den Bercken et al. \shortcite{van2019evaluating}.

\item We examine the use of PNLMs for the autocomplete task on sentence-level text simplification and provide an initial analysis based on four recent models on this new medical corpus. In traditional autocomplete tasks, only the text being typed is available.  For text simplification, the additional context of the difficult sentence is also available.  We show how this additional information can be integrated into the models to improve the quality of the suggestions made.

\item We introduce an ensemble model that combines the output of the four PNLMs and outperforms all of the individual models. The ensemble approach is not application specific and may be used in other domains where PNLMs have been employed.

\end{enumerate}

\section{Medical Parallel English Wikipedia Corpus Creation} \label{sec:medical_corpora}

We automatically extracted medical sentence pairs from the sentence-aligned English Wikipedia corpus from Kauchak et al. \shortcite{kauchak2013improving}. Table \ref{tab:medexample} shows an example medical sentence pair. To identify the medical sentence pairs, we first created a medical dictionary with 260k medical terms selected from the Unified Medical Language System (UMLS) \cite{bodenreider2004unified} by selecting all UMLS terms that were associated with the semantic types of: Disease or Syndrome, Clinical Drug, Diagnostic Procedure, and Therapeutic or Preventive Procedure.

We extracted sentences from the English Wikipedia corpus based on the occurrence of terms in the medical dictionary.  Specifically, a sentence pair was identified as medical
if both the title of the article and the English Wikipedia sentence had 4 or more terms that matched the medical keywords. A term was considered a match to the UMLS dictionary if it had a similarity score higher than 0.85 using QuickUMLS \cite{soldaini2016quickumls}. We then manually reviewed the sentence pairs and removed all non-medical sentence pairs. The final medical parallel corpus has 3.3k aligned sentence pairs\footnote{\url{https://github.com/vanh17/MedTextSimplifier/tree/master/data_processing/data}}.

Van den Bercken et al. \shortcite{van2019evaluating} also created a parallel medical corpus by filtering sentence pairs from Wikipedia.  Our corpus is significantly larger (45\% larger; 2,267 pairs vs. 3,300 pairs) and uses a stricter criteria for identifying sentences: they only required a single word match in the text itself (not the title) and used a lower similarity threshold of 0.75 (vs. our approach of 0.85).

\section{Approach}
We had three goals for our analysis: understand the effect of incorporating the additional context of the difficult sentence into autocomplete text simplification models, explore a new application for PNLMs, and evaluate our new ensemble approach to the autocomplete text simplification.

\subsection{Autocomplete Approach For Medical Text Simplification}
We pose the autocomplete text simplification problem as a language modeling problem: given a difficult sentence that a user is trying to simplify, $d_1 d_2 ... d_m$, and the simplification typed so far, $s_1 s_2 ... s_i$, the autocomplete task is to suggest word $s_{i+1}$.  Table \ref{tab:example} gives an example of the autocomplete task. To evaluate the models, we calculated how well the models predicted the next word in a test sentence, given the previous words.  A simple test sentence of length $n$, $s_1 s_2 ... s_n$, would result in $n-1$ predictions, i.e., predict $s_2$ given $s_1$, predict $s_3$ given $s_1 s_2$, etc.  For example, Table \ref{tab:medexample} shows a difficult sentence from English Wikipedia and the corresponding simplification from the medical Simple English Wikipedia. Given this test example, we generate 12 prediction tasks, one for each word in the simple sentence after the first word.  Table \ref{fig:testing} shows these 12 test prediction tasks.

\subsection{Increasing Information Through Incorporation of Additional Context}

Unlike other autocomplete tasks, for text simplification, the difficult sentence provides very explicit guidance about what words and information should be included as the user types. As a baseline, we compare the models without the context of this additional information, i.e., we predict word $s_{i+1}$ given only the simplification typed so far, $s_1 s_2 ... s_i$.  We take a straightforward approach to incorporate the context of the difficult sentence: we concatenate the difficult sentence in front of a simplification typed so far, i.e., predict $s_{i+1}$ given $d_1 d_2 ... d_m . s_1 s_2 ... s_i$.  This has the advantage of incorporating the difficult sentence and biasing the predictions towards those found in the encoded context from difficult sentences, but is still model-agnostic, allowing us to apply it to all the different PNLMs without modifying the underlying architecture.

\begin{table}
\centering
\scalebox{0.9}{%
\begin{tabular}{c l l}
\toprule
Difficult sentence & Lowered glucose levels result both in the reduced release of insulin & \\
 & from the betacells and in the reverse conversion of glycogen to   & \\
 & glucose when glucose levels fall. & \\
\midrule
\toprule
Prediction Task & Simplification typed so far & Predict \\
\midrule
1 & This & insulin \\
2 & This insulin & tells \\
3 & This insulin tells & the \\
4 & This insulin tells the & cells \\
5 & This insulin tells the cells & to \\
6 & This insulin tells the cells to & take \\
7 & This insulin tells the cells to take & up \\
8 & This insulin tells the cells to take up & glucose \\
9 & This insulin tells the cells to take up glucose & from \\
10 & This insulin tells the cells to take up glucose from & the \\
11 & This insulin tells the cells to take up glucose from the & blood \\
12 & This insulin tells the cells to take up glucose from the blood & .\\
\bottomrule
\end{tabular}}
\caption{The resulting prediction tasks that are generated from the example in Table \ref{tab:medexample}.}
\label{fig:testing}
\end{table}

\subsection{Transformer-based Language Models}

We examined four PNLMs based on the Transformer network \cite{vaswani2017attention}: BERT \cite{devlin2018bert},  RoBERTa \cite{liu2019roberta},  XLNet \cite{yang2019xlnet},  and GPT-2 \cite{radford2019language}.  For each of the models, we examine versions that only utilize the text typed so far, denoted ``No Context'', as well as ``context-aware'' variants that utilize the difficult sentence. We fine-tuned all four models on the 160k sentence pair general parallel English Wikipedia \cite{kauchak2013improving} (excluding the development and testing data) and then further fine-tuned them on the separate medical training set described in section \ref{sec:medical_corpora}.
Note that none of the test sentences were in a dataset used for fine-tuning.

\paragraph{BERT:} Bidirectional Encoder Representations from Transformers  \cite{devlin2018bert} is a method for learning language representations using bidirectional training. BERT has been shown to produce state-of-the-art results in a wide range of generation and classification applications. We use the base original BERT\footnote{\url{https://github.com/huggingface/bert/}} model pre-trained on the BooksCorpus \cite{zhu2015aligning} and English Wikipedia.

\paragraph{RoBERTa:} A Robustly Optimized BERT Pretraining Approach \cite{liu2019roberta}. The RoBERTa uses the same model architecture as BERT. However, the differences between RoBERTa and BERT are that RoBERTa does not use Next Sentence Prediction during pre-training and RoBERTa uses larger mini-batch size. We used the publicly released base RoBERTa\footnote{\url{https://github.com/huggingface/roberta}} with 125M parameters model.

\paragraph{XLNet:} Generalized Auto-regressive Pretraining Method \cite{yang2019xlnet}. Like BERT, XLNet benefits from bidirectional contexts. However, XLNet does not suffer limitations of BERT because of its auto-regressive formulation. In this work, we used publicly available base English XLNet\footnote{\url{https://github.com/huggingface/xlnet}} with 110M parameters model.

\paragraph{GPT-2:} Generative Pretrained Transformer 2 \cite{radford2019language}. Like BERT, GPT-2 is also based on the Transformer network, however, GPT-2 uses unidirectional left-to-right pre-training process. We use the publicly released GPT-2\footnote{\url{https://github.com/huggingface/gpt2}} model, which has 117M parameters and is trained on web text.

\subsection{Ensemble Models} \label{sec:ensemble}

Each of the models above utilizes different network variations and was pretrained on different datasets, and therefore they do not always make the same predictions.  Ensemble approaches combine the output of different systems to try and leverage these differences to create a single model that outperforms any of the individual models.  We examined three ensemble approaches that combine the output of the four models.

\paragraph{Majority Vote:} As a baseline ensemble approach, we examined a simple majority vote on what the next word should be. We take the top 5 suggestions from each of the models and do a majority count on the pool of combined suggestions.  The output of the model is the suggestion with highest count. If there is a tie, we randomly select one of the top suggestions. We picked the top 5 suggestions since this was the cutoff where the models tended to peak on the development data (for example, see the accuracy@N as shown in Table \ref{tab:accuracy-@-n}. Having more than 5 suggestions did not improve performance much but slowed the computation.

\paragraph{4-Class Classification (4CC):} \label{sec:4cc} The ensemble problem can be viewed as a classification problem where the goal is to predict which system output should be used given a difficult sentence and the words typed so far, i.e., the autocomplete example. We posed this as a supervised classification problem.  Given an autocomplete text simplification example, we can generate training data for the classifier by comparing the output of each system to the correct answer. If a system does get the example correct, then we include an example with that system as the label. Table \ref{tab:4ccexample} shows three such examples, where RoBERTa correctly predicted the first example, BERT the second, and XLNet the third.  If multiple systems get the example right, we then randomly assign the label to one of the systems.

We train a neural text classifier implemented by huggingface\footnote{\url{https://github.com/huggingface/transformers}} with this training set to the PNLMs given the next-word prediction task. To make use of the models' confidence on top of the results from model selection, we designed a scoring system for output selection as follows:
\[ \label{eq:4cc}
	Score(w, X) = \alpha * P(w|X) + \theta * I (X, S)
\]

\noindent where $P(w|X)$ is model $X$'s confidence on predicted word $w$; $I(X, S)$ is an identity function, which returns $1$ if $X = S$ and $0$ otherwise; $S$ is the predicted model from model selector; and $\alpha$ and $\theta$ are scoring parameters. We use $0.5$ for both $\alpha$ and $\theta$.
At testing time, we pick the highest score and output the word $w$, given a prediction task.
\begin{table}
    \centering
    \scalebox{0.9}{%
    \begin{tabular}{l l}
    \toprule
    Prediction Task  & Class \\
    \midrule
    (Difficult sentence). This (MASK) & RoBERTa \\
    (Difficult sentence). This insulin (MASK) & BERT \\
    (Difficult sentence). This insulin tells (MASK) & XLNet \\
    \bottomrule
    \end{tabular}}
    \caption{An example of training data for the 4CC model. Class can be one of the four option: BERT, RoBERTa,  XLNet, GPT-2.}
    \label{tab:4ccexample}
    \
\end{table}

\paragraph{Autocomplete for Medical Text Simplification (AutoMeTS):} RoBERTa performed significantly better than the other three individual models at the simplification autocomplete task. As a result, there was a strong bias toward RoBERTa in the training data for the 4CC ensemble model.  To mitigate this effect, we also developed an ensemble approach based on a multi-label classifier for model selector, which we denote the AutoMeTS ensemble model. This choice of model selector, to our knowledge, is novel to transformer-based ensemble models. For this choice of classifier, each prediction task is given a sequence of 4 binary labels. Each label represents the correctness of each of the individual PNLMs, with a 0 representing an incorrect prediction on the task and a 1 representing a correct prediction. Table \ref{tab:AutoMeTSexample} shows an example of this dataset with the labels in order ``RoBERTa BERT XLNet GPT-2''.  For the first example, RoBERTa, XNLET, and GPT-2 correctly predicted the next word, while BERT did not.

We trained a neural multi-label classifier implemented by huggingface on this training dataset. To make use of the models' confidence on top of the results from model selection, we designed a scoring system for output selection as follows:
\[ \label{eq:AutoMeTS}
	Score(w, X) = \beta * P(w|X) + \sigma * S(X, Ls)
\]

\noindent where $P(w|X)$ is model $X$'s confidence on predicted word $w$; $S(X, Ls)$ is a function, which returns $0.25$ if model $X$ is in $Ls$ and $0$ otherwise; $Ls$ is the predicted sequence of labels from the model selector; and $\beta$ and $\sigma$ are scoring parameters. We use $0.5$ for both $\beta$ and $\sigma$. At testing time, we output the word $w$ with the highest score, given a prediction task.

\begin{table}
    \centering
    \scalebox{0.9}{%
    \begin{tabular}{l c}
    \toprule
    Prediction Task  & Sequence of Labels \\
    \midrule
    (Difficult sentence). This (MASK) & 1 0 1 1 \\
    (Difficult sentence). This insulin (MASK) & 0 1 0 0 \\
    (Difficult sentence). This insulin tells (MASK) & 1 1 1 1 \\
    \bottomrule
    \end{tabular}}
    \caption{An example of training data for the AutoMeTS model. For a prediction task, a sequence of 4 labels is give in the order "RoBERTa BERT XLNet GPT-2". The value of 1 means the model correctly predicted the right word, and 0 otherwise.}
    \label{tab:AutoMeTSexample}
    \
\end{table}

\section{Experimental Setup} \label{sec:results}

We compare the performance of the models on the medical autocomplete text simplification task.  We used  our medical parallel English Wikipedia corpus with 70\% of the sentence pairs for training, 15\% for development, and 15\% for testing. We fine-tuned individual PNLMs using huggingface\footnote{\url{https://github.com/huggingface/}} with a batch-size of 8, 8 epochs, and a learning rate of $5e^{-5}$. Early stopping was used based on the second time a decrease in the accuracy was seen.

We used two metrics to evaluate the quality of the approaches.  First, we used standard accuracy, where a prediction is counted correct if it matches the test prediction word. Accuracy is pessimistic in that the predicted word must match exactly the word seen in the simple sentence, and as such it does not account for other possible words, such as synonyms, that could be correctly used in the context. Since the parallel English Wikipedia corpus does not offer multiple simplified versions for a given difficult sentence, accuracy is the best metric that considers automated scoring, simplification quality, and information preservation. Accuracy-based metrics can help offset an expensive manual evaluation while providing the best approximation of how the autocomplete systems work. We do not use BLEU \cite{papineni2002bleu} and SARI \cite{xu2016optimizing} scores, which are widely used in text simplification domain, because the two metrics are specifically designed for fully-automated models that predict an entire sentence at a time.  For autocomplete, the models only predict a single word at a time and then, regardless of whether the answer is correct or not, use the additional context of the word that the user typed next to make the next prediction.

Autocomplete models can suggest just the next word, or they can be used to suggest a list of alternative words that the user could select from (since the models are probabilistic they can return a ranked list of suggestions).  To evaluate this use case, and to better understand what words the models are predicting, we also evaluated the models using accuracy@N. Accuracy@N counts a model as correct for an example as long as it suggests the correct word within the first $N$ suggestions.

\begin{figure}[t]
\center{\includegraphics[scale=0.7]
{./images/new_len_fig.png}}
\caption{\label{fig:length_based} Accuracy for the context-aware models based on the length of the difficult sentences: very short ($\le 5$ tokens), short ($6-15$), medium ($16-19$), and long ($\ge20$).}
\end{figure}

\section{Results and Discussion}

We first analyze the results of the individual PNLMs on the medical text simplification autocompletion task and then explore the ensemble approaches.  We also include a number of post-hoc analyses to better understand what the different models are doing and limitations of the models.

\subsection{Individual Language Models}

\paragraph{Accuracy} Table \ref{tab:results} shows the results for the four different variants (RoBERTa, BERT, XLNet, and GPT-2 with and without context). Even without any context, many of the models get every other word correct (accuracy of around 50\%).  With the additional context of the difficult sentence, all models improve.  GPT-2 improves drastically (more than doubling the accuracy) and RoBERTa also achieves a reasonable improvement of 6\% absolute.  Both with and without context, RoBERTa is the best performing model achieving significantly higher results than the other models

\begin{table}[t]
\centering
\scalebox{0.9}{%
\begin{tabular}{l c c }
\toprule
Model & No Context & Context-Aware\\
\midrule
Single PNLMs & & \\
\midrule
RoBERTa & \textbf{56.23} & \textbf{62.40} \\
BERT & 50.43 & 53.28 \\
XLNet & 45.70 & 46.20 \\
GPT-2 & 23.2 & 49.00 \\
\midrule
Ensemble Models & & \\
\midrule
Majority Vote & 39.75 & 48.25 \\
4CC & 52.27 & 59.32 \\
AutoMeTS & \textbf{57.89} & \textbf{64.52} \\
Upper bound & 60.22 & 66.44 \\
\bottomrule
\end{tabular}}
\caption{Accuracy of pretrained neural language models (PNLMs), both with and without the context of the difficult sentence on the medical parallel English Wikipedia corpus.}
\label{tab:results}
\
\end{table}

\begin{table}[t]
\centering
\scalebox{0.9}{%
\begin{tabular}{l c c c c}
\toprule
 & RoBERTa & BERT & XLNet & GPT-2\\
 \midrule
accuracy@1 & 62.40 & 53.28 & 46.20 & 49.00 \\
accuracy@2 & 67.20 & 54.50 & 46.90 & 49.44\\
accuracy@3 & 70.00 & 56.20 & 49.20  & 52.57\\
accuracy@4 & 72.10 & 58.00 & 51.30 & 54.32\\
accuracy@5 & \textbf{73.20} & \textbf{59.40} & \textbf{53.50} & \textbf{56.12}\\
 \bottomrule
\end{tabular}}
\caption{\label{tab:accuracy-@-n} Accuracy@N of the RoBERTa, BERT, XLNet, and GPT-2 with context on next word prediction.}
\vspace{-2mm}
\end{table}

\paragraph{Accuracy@N} Table \ref{tab:accuracy-@-n} shows the accuracy@N from PNLMs on next word prediction.  By allowing the autocomplete system user the option to pick from a list of options, the correct word is much more likely to be available.  Even just showing three options, results in large improvements, e.g., 7.5\% absolute for RoBERTa.  When five options are available, increases range from  6--10.8\%.

\paragraph{Impact of the difficult sentence length} To better understand the models, we compared the average performance of the models based on the length of the sentence that was being simplified.  We divided the test sentence into four different groups based on length: very short ($\leq$5 tokens), short ($6-15$ tokens), medium ($16-19$ tokens), and long ($\geq$20 tokens).  Figure \ref{fig:length_based} shows the test accuracy of the context-aware models broken down into these 4 different groups. RoBERTa, BERT, and XLNet are fairly consistent regardless of the difficult sentence lengths; only for long sentences does the performance drop. GPT-2 performs poorly on short sentences, but well for other lengths. We hypothesize that the training data for GPT-2 (web text) may require more context for this more technical task.

\paragraph{Impact of the number of words typed}  We also analyzed the average performance of the models based on how many of the words of the simplified sentence had been typed so far, i.e., the length of $s_1 s_2 ... s_i$.  Figure \ref{fig:position_based} shows the performance accuracy of the models based on how many words of the simplification the model has access to. Early on, when the sentence is first being constructed, all models perform poorly. As more words are typed, the accuracy of all models increases.  GPT-2 performs the best early on, but then levels off after about 7 words.  Both BERT and RoBERTa continue to improve as more context is added, which may partially explain their better performance overall.

\begin{figure}[t]
\center{\includegraphics[scale=0.7]
{./images/new_pos_fig.png}}
\caption{Accuracy for the four context-aware models based on the number of words typed so far.}
\label{fig:position_based}
\end{figure}

\begin{figure}[t]
\center{\includegraphics[scale=0.7]
{./images/ensemble_pos_fig.png}}
\caption{\label{fig:ensemble_pos} Accuracy for the RoBERTa, AutoMeTS, and upper bound models based on the number of words typed so far.}
\end{figure}

\subsection{Ensemble Models}

Although RoBERTa performs the best overall, as Figures \ref{fig:length_based} and \ref{fig:position_based} show, different models perform better in different scenarios.  The ensemble models try and leverage these differences to generate a better overall model.

As shown in Table \ref{tab:results}, the majority vote ensemble model does not perform better than the best individual PNLM.  The 4CC does outperform the majority vote approach by 11.07\% and does perform better than three of the four PLNMs, but it still fails to beat RoBERTa.  AutoMeTS, by viewing the problem as a multi-label problem, is able to avoid some of the biases in the training data that 4CC has, resulting in an absolute improvement of 2.1\% over the best individual model (RoBERTa).

To understand the performance differences of the ensemble models,  Table \ref{tab:model_frequency} shows the percentage that each of the four PNLMs was used for each of the ensemble approaches.  The problem with the majority vote is that it tends to utilize all of the systems, regardless of their quality.  For example, it shows a high percentage of XLNet, even though its performance was the worst.  Because RoBERTa is the best performing model, the 4CC approach had a very strong bias towards RoBERTa. The multi-label selector reduces the bias towards using RoBERTa (a 11.25\% decrease in the appearance of RoBERTa) and is able to leverage predicions from the other model when appropriate.

\begin{table}[t]
\centering
\scalebox{0.9}{%
\begin{tabular}{l c c c}
\toprule
	 	&	Majority Vote	&	4CC & AutoMeTS\\
\midrule
RoBERTa & 47.29\%  & 	71.00\% 		& 	59.75\% \\
BERT 	& 20.25\%  & 	12.45\% 		& 	18.09\% \\
XLNet 	& 15.41\%  & 	5.72\% 		& 	7.06\% \\
GPT-2 	& 17.05\%  & 	10.83\% 		& 	15.10\% \\
\bottomrule
\end{tabular}}
\caption{The appearance frequency of PNLMs in Majority Vote, 4CC, AutoMeTS ensemble models.}
\label{tab:model_frequency}
\vspace{-2mm}
\end{table}

To understand the limits of an ensemble  approach, we also calculated the upper bound that the ensemble approach could achieve.  Specifically, as long as at least one model among the four PNLMs correctly predicts the next word, we mark it as correct for the upper bound. This means that no other possible combination of the four PNLMs can perform better. Here this upper bound is 66.44\% (Table \ref{tab:results}), which is about a 2\% improvement over our ensemble approach; there is a bit of room for improvement, but also better language modeling techniques also need to be explored.

Figure \ref{fig:ensemble_pos} shows the accuracy for RoBERTa, AutoMeTS, and the upper bound based on size of the context, i.e., words typed so far. For small context, the ensemble approach performs much better than RoBERTa.  This likely can be attributed to selecting one of the other models that performs better for small context, e.g., GPT-2.  As the context size increases, however, RoBERTa and the ensemble model perform similarly.  The upper bound is consistently above the ensemble approach across all context sizes.

\section{Conclusions}

In this paper, we introduced a new medical parallel English Wikipedia corpus for text simplification, which contains 3.3K medical sentence pairs. Further, we proposed a new autocomplete application for PNLMs for medical text simplification. Such autocomplete models can assist users in simplifying text with improved efficiency and higher quality results in domains where information preservation is especially critical, such as healthcare and medicine, and where fully-automated approaches are not appropriate. We examined four recent PNLMs: BERT, RoBERTa, XLNet, and GPT-2, and showed how the additional context of the sentences being simplified could be incorporated into the autocomplete simplification process. Further, we introduced AutoMeTS, an ensemble method that combines the advantages of each of the different PNLMs. The AutoMeTS model outperforms the best individual model, RoBERTa, by 2.1\%. Longer term, we envision that this new application could lead to other interesting model adaptations and advance text simplification in medical domains.

\section*{Acknowledgements}

Research reported in this paper was supported by the National Library of Medicine of the National Institutes of Health under Award Number R01LM011975. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

\bibliographystyle{coling}

redpajama_set_name: RedPajamaArXiv


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