text:
goog.provide('ol.test.source.ImageWMS');

goog.require('ol.source.ImageWMS');
goog.require('ol.proj');

describe('ol.source.ImageWMS', function() {

  var extent, pixelRatio, options, projection, resolution;
  beforeEach(function() {
    extent = [10, 20, 30, 40];
    pixelRatio = 1;
    projection = ol.proj.get('EPSG:4326');
    resolution = 0.1;
    options = {
      params: {
        'LAYERS': 'layer'
      },
      ratio: 1,
      url: 'http://example.com/wms'
    };
  });

  describe('#getImage', function() {

    it('returns the expected image URL', function() {
      options.ratio = 1.5;
      var source = new ol.source.ImageWMS(options);
      var image = source.getImage([10, 20, 30.1, 39.9], resolution, pixelRatio, projection);
      var uri = new URL(image.src_);
      var queryData = uri.searchParams;
      var extent = queryData.get('BBOX').split(',').map(Number);
      var extentAspectRatio = (extent[3] - extent[1]) / (extent[2] - extent[0]);
      var imageAspectRatio = Number(queryData.get('WIDTH') / Number(queryData.get('HEIGHT')));
      expect(extentAspectRatio).to.roughlyEqual(imageAspectRatio, 1e-12);
    });

    it('uses correct WIDTH and HEIGHT for HiDPI devices', function() {
      pixelRatio = 2;
      options.serverType = 'geoserver';
      var source = new ol.source.ImageWMS(options);
      var image = source.getImage(extent, resolution, pixelRatio, projection);
      var uri = new URL(image.src_);
      var queryData = uri.searchParams;
      var width = Number(queryData.get('WIDTH'));
      var height = Number(queryData.get('HEIGHT'));
      expect(width).to.be(400);
      expect(height).to.be(400);
    });

    it('requests integer WIDTH and HEIGHT', function() {
      options.ratio = 1.5;
      var source = new ol.source.ImageWMS(options);
      var image = source.getImage([10, 20, 30.1, 39.9], resolution, pixelRatio, projection);
      var uri = new URL(image.src_);
      var queryData = uri.searchParams;
      var width = parseFloat(queryData.get('WIDTH'));
      var height = parseFloat(queryData.get('HEIGHT'));
      expect(width).to.be(Math.round(width));
      expect(height).to.be(Math.round(height));
    });

    it('sets WIDTH and HEIGHT to match the aspect ratio of BBOX', function() {
      var source = new ol.source.ImageWMS(options);
      var image = source.getImage(extent, resolution, pixelRatio, projection);
      var uri = new URL(image.src_);
      expect(uri.protocol).to.be('http:');
      expect(uri.hostname).to.be('example.com');
      expect(uri.pathname).to.be('/wms');
      var queryData = uri.searchParams;
      expect(queryData.get('BBOX')).to.be('20,10,40,30');
      expect(queryData.get('CRS')).to.be('EPSG:4326');
      expect(queryData.get('FORMAT')).to.be('image/png');
      expect(queryData.get('HEIGHT')).to.be('200');
      expect(queryData.get('LAYERS')).to.be('layer');
      expect(queryData.get('REQUEST')).to.be('GetMap');
      expect(queryData.get('SERVICE')).to.be('WMS');
      expect(queryData.get('SRS')).to.be(null);
      expect(queryData.get('STYLES')).to.be('');
      expect(queryData.get('TRANSPARENT')).to.be('true');
      expect(queryData.get('VERSION')).to.be('1.3.0');
      expect(queryData.get('WIDTH')).to.be('200');
      expect(uri.hash.replace('#', '')).to.be.empty();
    });

    it('sets the SRS query value instead of CRS if version < 1.3', function() {
      options.params.VERSION = '1.2';
      var source = new ol.source.ImageWMS(options);
      var image = source.getImage(extent, resolution, pixelRatio, projection);
      var uri = new URL(image.src_);
      var queryData = uri.searchParams;
      expect(queryData.get('CRS')).to.be(null);
      expect(queryData.get('SRS')).to.be('EPSG:4326');
    });

    it('allows various parameters to be overridden', function() {
      options.params.FORMAT = 'image/jpeg';
      options.params.TRANSPARENT = false;
      var source = new ol.source.ImageWMS(options);
      var image = source.getImage(extent, resolution, pixelRatio, projection);
      var uri = new URL(image.src_);
      var queryData = uri.searchParams;
      expect(queryData.get('FORMAT')).to.be('image/jpeg');
      expect(queryData.get('TRANSPARENT')).to.be('false');
    });

    it('does not add a STYLES= option if one is specified', function() {
      options.params.STYLES = 'foo';
      var source = new ol.source.ImageWMS(options);
      var image = source.getImage(extent, resolution, pixelRatio, projection);
      var uri = new URL(image.src_);
      var queryData = uri.searchParams;
      expect(queryData.get('STYLES')).to.be('foo');
    });

    it('changes the BBOX order for EN axis orientations', function() {
      var source = new ol.source.ImageWMS(options);
      projection = ol.proj.get('CRS:84');
      var image = source.getImage(extent, resolution, pixelRatio, projection);
      var uri = new URL(image.src_);
      var queryData = uri.searchParams;
      expect(queryData.get('BBOX')).to.be('10,20,30,40');
    });

    it('uses EN BBOX order if version < 1.3', function() {
      options.params.VERSION = '1.1.0';
      var source = new ol.source.ImageWMS(options);
      var image =
          source.getImage(extent, resolution, pixelRatio, projection);
      var uri = new URL(image.src_);
      var queryData = uri.searchParams;
      expect(queryData.get('BBOX')).to.be('10,20,30,40');
    });

    it('sets MAP_RESOLUTION when the server is MapServer', function() {
      options.serverType = 'mapserver';
      var source = new ol.source.ImageWMS(options);
      pixelRatio = 2;
      var image = source.getImage(extent, resolution, pixelRatio, projection);
      var uri = new URL(image.src_);
      var queryData = uri.searchParams;
      expect(queryData.get('MAP_RESOLUTION')).to.be('180');
    });

    it('sets FORMAT_OPTIONS when the server is GeoServer', function() {
      options.serverType = 'geoserver';
      var source = new ol.source.ImageWMS(options);
      pixelRatio = 2;
      var image = source.getImage(extent, resolution, pixelRatio, projection);
      var uri = new URL(image.src_);
      var queryData = uri.searchParams;
      expect(queryData.get('FORMAT_OPTIONS')).to.be('dpi:180');
    });

    it('extends FORMAT_OPTIONS if it is already present', function() {
      options.serverType = 'geoserver';
      var source = new ol.source.ImageWMS(options);
      options.params.FORMAT_OPTIONS = 'param1:value1';
      pixelRatio = 2;
      var image = source.getImage(extent, resolution, pixelRatio, projection);
      var uri = new URL(image.src_);
      var queryData = uri.searchParams;
      expect(queryData.get('FORMAT_OPTIONS')).to.be('param1:value1;dpi:180');
    });

    it('rounds FORMAT_OPTIONS to an integer when the server is GeoServer',
        function() {
          options.serverType = 'geoserver';
          var source = new ol.source.ImageWMS(options);
          pixelRatio = 1.325;
          var image =
             source.getImage(extent, resolution, pixelRatio, projection);
          var uri = new URL(image.src_);
          var queryData = uri.searchParams;
          expect(queryData.get('FORMAT_OPTIONS')).to.be('dpi:119');
        });

    it('sets DPI when the server is QGIS', function() {
      options.serverType = 'qgis';
      var source = new ol.source.ImageWMS(options);
      pixelRatio = 2;
      var image = source.getImage(extent, resolution, pixelRatio, projection);
      var uri = new URL(image.src_);
      var queryData = uri.searchParams;
      expect(queryData.get('DPI')).to.be('180');
    });

    it('creates an image with a custom imageLoadFunction', function() {
      var imageLoadFunction = sinon.spy();
      options.imageLoadFunction = imageLoadFunction;
      var source = new ol.source.ImageWMS(options);
      var image = source.getImage(extent, resolution, pixelRatio, projection);
      image.load();
      expect(imageLoadFunction).to.be.called();
      expect(imageLoadFunction.calledWith(image, image.src_)).to.be(true);
    });

    it('returns same image for consecutive calls with same args', function() {
      var extent = [10.01, 20, 30.01, 40];
      var source = new ol.source.ImageWMS(options);
      var image1 = source.getImage(extent, resolution, pixelRatio, projection);
      var image2 = source.getImage(extent, resolution, pixelRatio, projection);
      expect(image1).to.equal(image2);
    });

    it('returns same image for calls with similar extents', function() {
      options.ratio = 1.5;
      var source = new ol.source.ImageWMS(options);
      var extent = [10.01, 20, 30.01, 40];
      var image1 = source.getImage(extent, resolution, pixelRatio, projection);
      extent = [10.01, 20.1, 30.01, 40.1];
      var image2 = source.getImage(extent, resolution, pixelRatio, projection);
      expect(image1).to.equal(image2);
    });

    it('calculates correct image size with ratio', function() {
      options.ratio = 1.5;
      var source = new ol.source.ImageWMS(options);
      var extent = [10, 5, 30, 45];
      source.getImage(extent, resolution, pixelRatio, projection);
      expect(source.imageSize_).to.eql([300, 600]);
    });

  });

  describe('#getGetFeatureInfo', function() {

    it('returns the expected GetFeatureInfo URL', function() {
      var source = new ol.source.ImageWMS(options);
      var url = source.getGetFeatureInfoUrl(
          [20, 30], resolution, projection,
          {INFO_FORMAT: 'text/plain'});
      var uri = new URL(url);
      expect(uri.protocol).to.be('http:');
      expect(uri.hostname).to.be('example.com');
      expect(uri.pathname).to.be('/wms');
      var queryData = uri.searchParams;
      expect(queryData.get('BBOX')).to.be('24.95,14.95,35.05,25.05');
      expect(queryData.get('CRS')).to.be('EPSG:4326');
      expect(queryData.get('FORMAT')).to.be('image/png');
      expect(queryData.get('HEIGHT')).to.be('101');
      expect(queryData.get('I')).to.be('50');
      expect(queryData.get('J')).to.be('50');
      expect(queryData.get('LAYERS')).to.be('layer');
      expect(queryData.get('QUERY_LAYERS')).to.be('layer');
      expect(queryData.get('REQUEST')).to.be('GetFeatureInfo');
      expect(queryData.get('SERVICE')).to.be('WMS');
      expect(queryData.get('SRS')).to.be(null);
      expect(queryData.get('STYLES')).to.be('');
      expect(queryData.get('TRANSPARENT')).to.be('true');
      expect(queryData.get('VERSION')).to.be('1.3.0');
      expect(queryData.get('WIDTH')).to.be('101');
      expect(uri.hash.replace('#', '')).to.be.empty();
    });

    it('sets the QUERY_LAYERS param as expected', function() {
      var source = new ol.source.ImageWMS(options);
      var url = source.getGetFeatureInfoUrl(
          [20, 30], resolution, projection,
          {INFO_FORMAT: 'text/plain', QUERY_LAYERS: 'foo,bar'});
      var uri = new URL(url);
      expect(uri.protocol).to.be('http:');
      expect(uri.hostname).to.be('example.com');
      expect(uri.pathname).to.be('/wms');
      var queryData = uri.searchParams;
      expect(queryData.get('BBOX')).to.be('24.95,14.95,35.05,25.05');
      expect(queryData.get('CRS')).to.be('EPSG:4326');
      expect(queryData.get('FORMAT')).to.be('image/png');
      expect(queryData.get('HEIGHT')).to.be('101');
      expect(queryData.get('I')).to.be('50');
      expect(queryData.get('J')).to.be('50');
      expect(queryData.get('LAYERS')).to.be('layer');
      expect(queryData.get('QUERY_LAYERS')).to.be('foo,bar');
      expect(queryData.get('REQUEST')).to.be('GetFeatureInfo');
      expect(queryData.get('SERVICE')).to.be('WMS');
      expect(queryData.get('SRS')).to.be(null);
      expect(queryData.get('STYLES')).to.be('');
      expect(queryData.get('TRANSPARENT')).to.be('true');
      expect(queryData.get('VERSION')).to.be('1.3.0');
      expect(queryData.get('WIDTH')).to.be('101');
      expect(uri.hash.replace('#', '')).to.be.empty();
    });
  });

});


text:
Paul Farmer steps down as chair of Acevo
16 July 2018 by Andy Ricketts
Chief executive of Mind, Farmer has left with immediate effect in order to support his wife through serious illness; vice chair Joe Irvin will take over temporarily
Paul Farmer, chair of the charity leaders body Acevo, has stepped down from the role for personal reasons.
The chief executive of the mental health charity Mind was due to relinquish his Acevo position in December after four years, but has stepped down with immediate effect to devote time to supporting his wife through a serious illness.
Farmer has been at Mind since 2006 and was voted Most Admired Chief Executive by readers of Third Sector in 2013.
A spokeswoman for Mind said his position at the charity remained unchanged.
Refuge secures domestic violence helpline grant ahead of former partner Women's Aid
Action for Children creates new logo to mark 150th birthday
Regulator probes charity alleged to have paid Islamic State to free hostages
There is confusion about leadership, but enormous potential in the sector, says report
Pay of top earner at London Clinic falls significantly
Joe Irvin, vice chair of Acevo and chief executive of Living Streets, which campaigns on behalf of pedestrians, has become chair of Acevo until the umbrella body's annual general meeting in December, when he will have reached the maximum six-year term and must step down.
Acevo has launched a recruitment exercise to find a new chair to take up the role for the next three years, with the possibility of a second three-year term.
Irvin, a former chief executive of the local infrastructure body Navca, will lead the recruitment process.
Vicky Browning, chief executive of Acevo, said: "I would like to thank Paul Farmer for the unwavering support, calm approach and skilled leadership he has shown during his time as chair."
She said the charity was looking for a leader who could lead its board with "an enabling and inclusive approach in order to bring out the best of board members and the executive team".
"We'd like to talk to candidates that have a depth of experience, but a lightness of touch," said Browning.
Applicants must be full or associate Acevo members.
Governance Management News
Mind's Paul Farmer appointed next chair of Acevo
Paul Farmer named Britain's most admired charity chief executive
WWF denies it covered up probe into rape and torture allegations
Change law so charities don't have to set up separate trading subsidiaries, says report
Latest Governance Jobs
Treasurer/Trustee
Keyring Living Support Networks London, SE16 2XB
Trustee/Director
Hounds For Heroes Petersfield, Hampshire
The Not Forgotten Association London (Central), London (Greater)

redpajama_set_name: RedPajamaCommonCrawl


Invest in these classic Jimmy Choo pointy Attila flats to wear weekday to weekend. Features black patent leather and pointy tow. These pre-loved Jimmy Choo Attila pumps have olny been worn a few times by the previous owner and come in a excellent condition complete in box.


WeatherThe daily flow of water from the lakes of the country's main hydroelectric dams shows they are still not reaching the optimal water levels required to produce electrical energy.
The situation regarding Panama's ability to generate electrical power is becoming worrisome, because of the looming threat of an El Niño phenomenon that will shorten the rainy season.
The National Oceanic and Atmospheric Administration of the United States issued a prediction on 23 June there is a 70% chance of El Niño conditions from this month through September, and then afterwards an 80% chance from October 2014 through March 2015.
"That in itself is worrying, and even more so, given the situation and the generation shortages in our electrical system," said Victor Urrutia, the former Administrator of the National Authority of Public Services (ASEP).
Panama depends on electrical power generate by hydroelectric sources for 60% of its requirements. The remaining 40% is generated by "thermal" generation plants burning bunker fuel, diesel, and coal.
A newly installed wind farm began operations last January in Cocle, but the facility only generates less than 1% of the energy required by the total production system.


text:
Marketing settings
Working with Opt-in
Opt-ins work as checkboxes in your Upsales forms. When a contact checks the checkbox and fills out the form, they are considered as opted in to that specific opt-in. This is good way of ensuring that the recipients of your email campaigns really want to receive your marketing content, and don't report it as spam.
Opt-ins are found in Upsales settings inside the Marketing Automation section.
Upsales offers two types of Opt-ins; Single- & Double Opt-in and here's how they work:
Single opt-in
When a contact fills out a form that has an active opt-in checkbox they receive an email notifying the contact that they' ve just accepted this opt-in. The contact doesn't have to do anything more than filling out your form.
The negative part of the single opt-in is that you won't know if the person that filled in your form actually is the owner of that email adress since anyone can enter whatever email adress they want in a form. But, the owner of that if the person filling out the form wasn't the owner to that email adress the owner can now simply click a unsubscribe link in the email.
Double Opt-in
The Double Opt-in has one more step than the Single Opt-in, and this step is to verify that the person who filled out your form really is the owner of the entered email adress. Here's how it works:
A contact fills out one of your forms (with an active opt-in).
The contact instantly receives an email to the submitted email adress telling that someone filled out a form with this email.
This is the double opt-in step: The user now has to click the link in the confirmation email for the double opt-in to be marked as complete.
When the user clicks the link a Thank-you-page is opened with a "Thank's for subscribing-message" in their web browser.
Double opt-in landing page
The double opt-in thank-you-page
This is referring to the Thank-you-page mentioned in step 4 above. So the contact clicking the link in the double opt-in confirmation email ends up on a thank-you-page, this one is some what customisable. Here's how:
What language that is shown to the visitor depends on their browser language settings.
This is the main title for the page. By default it's set to "Thank's for subscribing" and you can change to what ever fits your organization best.
This is a few lines of text shown below the headline. By default it's set to "You are subscribed to {{Company.name}} email list".
The brackets retrieves the company name from the Company profile inside of Upsales. You don't have to use the brackets.
Customizing the confirmation email
The confirmation email is sent whether you use Single- or Double Opt-in. It's quite simple, but you can customise a few things:
This is the main title for the page. By default it's set to "Thank's for subscribing" and you can change to what ever fits your organisation best.
If you are using a Double Opt-in, the text should encourage the user to click the link to complete their subscription.
Link to accept terms
This is only visible if using a Double Opt-in. What you're writing here is just the title of the link in the confirmation email. When clicked, the link will always direct the contact to the Thank-you-page.
Add an opt-in to your form
After creating your Opt-in in the settings of Upsales, find the form that you'd like to attach that opt-in to. Let's say you want to create a new form and attach that opt-in:
Go to the list of forms & landing pages and click on "New form or landing page".
When asked what type of form, select form.
In the right part of the edit view you'll find the fields that your form contains. Click "Add field".
In the dialog that opened you can find both Single and Double Opt-in. Add one of these.
When you've added the opt-in field you can now choose amongst the opt-in's you've created for what opt-in you'd like to use.
Attaching terms for your Opt-in
This is a way to attach a text to the opt-in toggles in your Upsales forms. The title for your opt-in becomes a link and opens your text in a new browser window.


text:
March 21st – Manic Medan
Today we were visiting a place that's not visited very much by cruise ships, nor is it really on the tourist map for that matter – the port of Belawan, in northern Sumatra, Indonesia. Our guide today told us that the Indonesian media had recently voted the town of Belawan as the dirtiest town in Indonesia (which is quite an achievement in a place like Indonesia), so we were glad that we were getting out of there and travelling to the city of Medan (the capital of Sumatra).
To be honest, since the war, Medan's has grown uncontrollably into a chaotic city of 2.5 million people, suffering from terrible traffic problems, a crumbling infrastructure, and much poverty visible out there on the crowded streets, while the tremendously hot and humid conditions don't help to make it an easier place to visit. But, having said all that, it's not a charmless place, and there are a few historic and cultural gems to discover out there in the urban jungle.
Most of the gems date from a period at the start of the 20th century, when this was one of South East Asia's boom towns, as the Dutch colonists started up lucrative tobacco plantations on the region's fertile soil, and plenty of Chinese workers and businessmen flocked to the city to make their fortune. Judging by the collection of those crumbling colonial buildings that have managed to survive the decades since the war, there must have been fortunes to be made here – however, the years of neglect and unsympathetic town planning (if you can believe that there was a "plan" to the city's sprawl), have left them as crumbling relics of a long lost golden age. Our fatalistic guide gave us a few depressing examples of the rampant corruption that have been holding back the development of his city, so I guess that it was against that background that we have to judge the urban appeal of Medan.
Actually, one of the joys of visiting a place like this, is to dig out the old colonial relics, and place them against the context of the city as a whole, sitting next to falling down buildings, or ugly concrete blocks that should be the ones that need to be demolished. We went into Medan's most splendid colonial building, the old Harrison and Crosfield building, that now houses the offices of London Sumatra (a British rubber company), to get a sense of Medan's former colonial splendour, and to see what was the first ever electric lift in Sumatra. Although it's still a functioning office building, when they heard that we'd come from London specially to see it (or so we told them), they were more than happy to give us a ride up to the top of the building, in this cranking old Victorian lift.
We sampled the exotic atmosphere of the Shri Marriammam Temple – a Hindu temple that caters for the significant Indian community who have been present for the last 150 years or so; but the biggest group attracted here were the Chinese, a minority who make up about 5% of the population these days, but continue to dominate the local economy. To find out more, we paid a visit to probably Medan's most interesting building, the Tjong A Fie House, the once-opulent home to Medan's richest businessman at the turn of the century. Like the rest of the city, the building's clearly seen better days, as his family have lost most of his fortune, but its size and the few furnishings left, show you that he must have been pretty wealthy.
After this, we headed for lunch, where our table was loaded up with an unbelievable amount of dishes – at least thirty different plates appeared at once on the table. Apparently, the way they do things here is that you just pick what dishes you like, leave what you don't want, and they only charge you for those you've started. This means that you get served an array of luke-warm food that's probably sat on a few other people's table first, and you just take lucky dip with flavours and potential subsequent stomach problems! As it turned out, it was all pretty good, and no-one suffered any after-effects.
While the city as a whole isn't particularly attractive, its best feature has got to be its people – everywhere we went, people were coming up to say hello to us, and constantly wanted to have their photo taken with us, we felt like celebrities. The giggling schoolgirls at the Royal Palace were desperate to have their photos taken with me (I felt like a giant next to them), while the ladies at the Grand Mosque wanted their photo taken with Tracy (in her red headscarf). With such lovely people, you can only hope that Medan can get its act together and give them a city worthy of them.
All in all, we had a really fun day in a city that you need to make a bit of an effort to enjoy spending time in – I'm glad we made the effort.
March 26th – An Epic Train Trip To Nowhere
March 25th – Day and Night in Rangoon
March 24th – Back in Burma
March 22nd – Riding Elephants in Phuket
March 20th – Shopping in Port Klang
March 19th – Reunited in Singapore
March 18th – Hiking Up To The Tiger's Nest
March 17th – Beguiling Bhutan
March 16th – Arriving in Bhutan
March 15th – A Morning at Angkor Wat
March 14th – Dinner at Angkor Wat
March 12th – Good Morning Vietnam
March 11th – I've Missed Saigon
March 10th – Here Comes The Sun in Nha Trang
March 9th – Imperial Hue
March 6th – Rainy Day in Taipei
March 4th – A Thought-Provoking Day in Okinawa
March 2nd – Better Weather in Shanghai
March 1st – Consuming in Shanghai


The Automatic Vending Association (AVA) which represents the vending industry in the United Kingdom and Ireland, challenged final-year culinary arts management students from the University College, Birmingham, to develop products for six key vending segments. Their responses will be viewed and judged at the biennial AVEX convention and trade show here.
The service segments are B&I, education, healthcare, leisure, staff catering and transport. The students, taking part in a brand new Culinary Product Development module, recently presented their concept products to AVA officials. The items will be on display at the 2013 AVEX, and will be judged by a panel of experts on Wednesday, June 12.
The judges include Tim Franklin-Heys, head of the culinary team at Unilever Food Solutions; Richard Ehrlich, chairman of the Guild of Food Writers; Tracey Graham, owner of Abercromby Vending (Glasgow); Gillian White, founder of 24Vend; Lee Holdstock, trade relations manager of the Soil Association, a nonprofit organisation that promotes organic farming; and Paul Howard, managing director of Nebrak Ltd., an interior design company specialising in vending and office beverage service facilities.


Beautiful design. The base is made of an elegant metal construction. The chair shows traces of wear like rusty spots and loss of paint (picture #11)of the base and stains (#8-#10)and one little damage of the cover (#9). The cover is fixed/attached by a metal string in tunnel (#12). Also a second chair is available with a black base and a kaki cover. This chair also shows traces of wear like loss of paint, rusty spots and the cover is damaged on several places (#17). These chairs are stackable.


Listen to "Daily Devotional - With God We Soar" on Spreaker.
I pray you all are well. Thank you so much for those of you that have checked in with me and my well being. God has me -- No worries. ;-) My prayers are for God to continue to work in and around you in all you do, in Jesus Name. May you be blessed with tonight's devotional message. Like them all, they are meant for you with love from God, through the Holy Spirit.


I am thrilled that you are interested in working with AcEDemy. Please take some time to read through my terms and conditions of work that are detailed below.
If you have any questions about these terms and conditions, or any aspect about working with AcEDemy, then please also see the Frequently Asked Questions page and/or contact me at: info@acedemy.co.uk.
Deadlines will be agreed before the project commences. I reserve the right to alter the deadline if the brief changes and in the event that the client fails to meet agreed deadlines in the course of the project.
All services are performed in line with the service descriptions provided on the website: https://www.acedemy.co.uk. You will receive a free sample edit on your own text.
In commissioning me to proofread or copy-edit, you are agreeing that I will carry out the service according to the definitions I provide at: https://www.acedemy.co.uk.
My proofreading and editing services involve checking the material once only. I am then happy to answer queries. Should you wish me to look at the document a second time, this will incur further costs.
I accept no liability for ensuring that your work is not plagiarised.
I do not go beyond straightforward copy-editing in my academic editing service; however, it is entirely the client's responsibility to ensure that my services have not breached the plagiarism rules of a body/institute/university to which they are expected to comply.
Any subsequent changes to the agreed brief and deadlines, once the project has started, could incur additional fees.
Costs agreed at the start of a project are not negotiable at a later stage: the client has no right to reduce or refuse agreed payment based on my style of work or interpretation of the brief.
Should the client decide to terminate the project before completion, I will invoice the full project fee subject to the usual payment terms.
For UK clients, project fees up to and including £200 are payable in full in advance. Where a project fee exceeds £200, a project agreement will be written. With this agreement in place, half of the fee will be payable upfront as security and the remainder will be payable within 14 days of the client receiving the edited file.
For non-UK clients, all projects fees are payable in full in advance.
Invoices are payable within 14 days by cheque, direct bank transfer or PayPal. I do not accept cash paid in at a bank branch.
Clients paying by PayPal are liable for the PayPal charge on the transaction.
Clients from outside the UK must pay in pounds sterling, factoring in any cross-currency transfer and international payment fees.
Under the terms of the Late Payment of Commercial Debts (Interest) Act 1998, I reserve the right to charge interest and compensation should payment exceed 14 days.
Should an invoice remain outstanding after 14 days, I reserve the right to refuse to undertake any further work, including work in progress, until all outstanding invoices are paid.
I take non-payment of invoices very seriously and will instigate legal proceedings and instruct debt recovery agents where necessary.
I reserve the right to amend these terms and conditions, with notice to the client.


Headlines and surveys about shadow IT and the measures that CIOs should take to control technology expenditure outside of their budgets are still commonplace. And, whilst the exact level of shadow IT activity may be difficult to quantify and will vary across different organisations, one thing is clear: technology budgets held by non-IT functions are increasing and will continue to grow for the foreseeable future.
Shadow IT is not new, of course. Ever since IT departments have existed, there has been some kind of technology-related activity taking place away from their prying eyes. Originally, this unofficial IT tended to be limited to someone with a penchant for Access databases, enthusiastic individuals arranging vendor demos or a manager trying to buy IT equipment on company expenses. More often that not, however, this was done with good intentions and was usually borne out of a need that was not being met by the central IT function (albeit sometimes for good reasons).
In those halcyon days, CIOs had a firm grip on all technology activity and expenditure; when a locally developed database was discovered – usually because it had become business critical and then experienced an outage – it would be absorbed by the IT function and migrated to a corporate standard database with all the relevant back-up, documentation, support and security provisions added. The CIO was the gatekeeper to the company's network and servers and hence could reject requests to purchase systems that other departments wanted to use on the grounds of standards, support, skills, cost, database, operating system, priorities, security, vendor size, or whatever other reason they could think of to keep control of the technology landscape.
And, in most organisations, it was simply not possible for another department to bypass the IT function by directly purchasing technology; only the IT function could raise orders for technology and, if another department tried to purchase IT equipment or services, this would be trapped by the Finance department and referred to IT for review and approval. And, just in case a department was tempted to hide technology expenditure under a non-IT account or cost code, the company's procurement policies (often at the insistence of IT) made it clear that such an action would be treated as a disciplinary offence.
But the world has changed. In the last five years or so, shadow IT has moved to a whole new level. Technologies such as mobile and cloud have made it a lot easier for non-IT functions to access technology solutions and services without the need to go near the company's servers. Apps can be installed on mobile devices in a matter of seconds, and cloud-based solutions can be accessed without IT even knowing.
And the organisation's approach to IT has changed. Technology is now fundamental to what most organisations do; it has moved from supporting the back office to driving revenue streams at the front of the business. An increasing number of other functions want, and need, to have a say in technology decisions and many now have their own IT budgets. It will eventually become the norm for other functions to be spending more than the IT department on technology. Shadow IT has come out of the shadows; it is now official, sanctioned and, in many cases, necessary.
CIO attitudes towards shadow IT have also been changing over the last few years – although perhaps not as quickly as the rest of the business. In fact, the relationship between CIOs and shadow IT maps very well to the classic change curve. Stage 1 – denial – saw most IT leaders reject the suggestion that shadow IT was even happening in their organisation. This was followed by stage 2 where denial turned to anger and the IT function actively fought against any unsanctioned technology activity.
In stage 3 – the bargaining or acceptance stage – CIOs acknowledge that shadow IT exists within the business and that it will continue to do so. They talk about embracing shadow IT but also talk about how to control what other functions are doing. In other words they – they accept that it has to happen but only if it happens on their terms. Stage 4 is about learning; CIOs at this point actively engage with shadow IT teams and seek to understand why it exists, what they can learn from it, and how they and their department can work with these other groups. This can be a difficult stage with the CIO learning some harsh lessons about the service the IT function provides and where it may be lacking in terms of skills and capability to support the rest of the business.
In the fifth and final stage, CIOs not only accept that other functions have to be involved in technology decisions, have their own budgets and need their own IT skills, but actively embrace, encourage and facilitate this happening. At this point there is no such thing as shadow IT. All IT activity – wherever it happens and whoever is leading it – is official. CIOs that reach this stage have made the final step from gatekeeper to broker. They have worked out how to influence, guide and facilitate what other functions are doing without having control or the ability to say no. And they are comfortable with this model as they realise that it enables them to focus on more important and value-adding activities.
Worryingly, a small number of CIOs are still in stages 1 and 2 of this process. They are either insisting that shadow IT does not exist in their organisation or they continue to use the tactics of the past to try to supress any IT activity outside of their function. These IT leaders are fighting a losing battle and will gradually become isolated and irrelevant before disappearing altogether.
In my experience, the majority of IT functions are at stage 3 – they engage with shadow IT but their main objective is to exert control over what other teams are doing – whilst a small number are operating at stage 4. IT leaders at stage 5 are the exception but this is where the rest of the organisation is at; other functions do not see what they are doing as shadow IT. People outside of the IT department see their technology activity as essential to meeting customer needs, enabling innovation and driving growth. And this is how CIOs also need to see the role of other functions with regard to technology. It is time for IT leaders to embrace their role as the organisation's technology broker and to accept that there is now no such thing as shadow IT.


text:
\section{Introduction}

A few years ago, Nagel and Schreckenberg \cite{NaSch} (NaSch) have proposed a
probabilistic cellular automaton (CA) for the description of
single-lane highway traffic\footnote{For an overview of other approaches, see
e.g.\ \cite{juelich,duis,helbing,may}}.
Using very simple rules, this model is able to reproduce the basic
phenomena encountered in real traffic, e.g.\ the occurance of phantom
traffic jams ('jams out of nowhere'). The NaSch model is 'minimal' in the
sense that every simplification of the rules no longer produces realistic
results. On the other hand, for the description of more complex situations
(e.g.\ multi-lane traffic, ramps)\footnote{For applications to urban traffic,
see e.g.\ \cite{dallas,duisburg}.} or for a proper modelling of the
'fine-structure' of traffic flow, additional rules have to be added and/or
the basic rules have to be modified.

The NaSch model \cite{NaSch} is a probabilistic cellular automaton.
Space and time (and hence the velocities) are discrete. The road is divided
into cells of length 7.5 m. Each cell can either be empty or occupied by
just one car. The state
of car $j$ ($j=1,\ldots,N$) is characterised by its momentary velocity
$v_j$ ($v_j=0,1,\ldots, v_{max}$). The state of the system at time $t+1$ can be
obtained from the state at time $t$ by applying the following four
rules to all cars at the same time (parallel dynamics):
\begin{description}
\item[R1:] Acceleration:\ \ \  $v_j(t)\rightarrow v_j(t+\frac{1}{3})
=\min\{v_j(t)+1,v_{max}\}$
\item[R2:] Braking:\ \ \  if\ \  $v_j(t+\frac{1}{3}) > d_j(t)$\ \ \ then\ \ \
$v_j(t+\frac{2}{3})=d_j(t)$\\
\phantom{ Braking:\ \ \  if\ \  $v_j(t+\frac{1}{3}) > d_j(t)$\ \,}else\ \ \ \
$v_j(t+\frac{2}{3})=v_j(t+\frac{1}{3})$
\item[R3:] Randomization:\ \ \  $v_j(t+\frac{2}{3})\
{\stackrel{p}{\rightarrow}}\ v_j(t+1)=\max\{0,v_j(t+\frac{2}{3})-1\}$\\
\phantom{ Randomization:} with probability $p$
\item[R4:] Driving:\ \ \  car $j$ moves $v_j(t+1)$ cells.
\end{description}
Here $d_j(t)$ denotes the number of empty cells in front of car $j$, i.e.\
the gap or headway. One timestep $t\to t+1$
corresponds to approximately 1 sec in real time \cite{NaSch}.

In the spirit of modelling complex phenomena in statistical physics,
the NaSch model does not try to describe traffic flow very accurately
on a microscopic level. Macroscopic effects observed in real traffic,
e.g.\ the spontaneous formation of jams, can be understood by
introducing just one simple stochastic parameter, the braking
probability $p$. Note that the motion of a single car might exhibit
(on short timescales) unrealistic features, like stopping from maximum
velocity within a few timesteps without any reason. However, after
averaging over the motion of all cars or on long timescales, the NaSch
model produces quite realistic results. Therefore one should not try
to relate these large fluctuations to those observed in real traffic.

Besides the CA models which are discrete in space and time, several
other approaches to traffic flow have been discussed recently. Among
these are space-continuous models in discrete time like the model of
Krauss et.\ al.\ \cite{zprmod1,zprmod2}, as well as models continuous both
in space and time, e.g.\ the macroscopic (fluid-dynamical) models \cite{KK},
the optimum-velocity model \cite{bando}, coupled-map models \cite{kikuchi}
and gas-kinetic models \cite{helbinggas}. For further
references we refer to \cite{juelich,duis,helbing}.

In the present paper we want to investigate hysteresis effects encountered
in empirical observations \cite{Treit,Kerner2,helbingexp}. Such effects are
related to the existence of metastable states in certain density regimes. In
the NaSch model these states have not be observed. Here we want to present
slightly modified models which are able to produce metastable states and
hysteresis. As a consequence, the occurance of metastable states is
therefore not related to the use of realistic braking rules, a continuum
description or deterministic models.

In order to establish the existence of metastable states one can follow
two basic strategies. In the first method, the density of cars is changed
adiabatically by adding or removing vehicles from the stationary
state at a certain density. Starting in the jamming phase (large densities)
and removing cars, one obtains the lower branch of the hysteresis curve.
On the other hand, by adding cars to a free flowing state (low densities),
one obtains the upper branch. The second method does not require changing
the density. Instead one starts from two different initial conditions, the
megajam and the homogeneous state. The megajam consists of one large, compact
cluster of standing cars. In the homogeneous state, cars are distributed
equidistantly (with one large gap for incommensurate densities).

In certain density regimes the fundamental diagram can consist of two
branches. In the upper branch (with higher flow) there are almost
no interactions between the cars and the system remains in a homogeneous,
jam-free state.
In the lower branch, however, the system is in a `phase-separated' state,
consisting of one large jam and a free-flowing part.

Experimental observations \cite{KernerReh2} suggest that a reduction
of the outflow from a jam compared to the maximum possible
flow\footnote{This reduction is often referred to as `capacity drop'.}
is an important ingredient for the occurrance of metastable states with
large lifetimes. Such a reduction can be implemented by so-called
slow-to-start rules, where standing cars accelerate with lower
probability than moving cars.  It leads to a downstream flow with a
relatively low density corresponding to the lower branch of the
hysteresis curve.  Due to the reduction of the density in the outflow
region of a jam, the flow in the jammed state is significantly lower
than the flow of the homogeneous state at the same density.

The paper is organized as follows: In Sect.\ \ref{sec_s2s} two models
with slow-to-start rules are investigated. In Sect.\ \ref{sec_nasch}
we introduce a slightly modified NaSch model with a velocity-dependent
randomization. In this way, one incorporates the
basic ingredients necessary to produce hysteresis.
In the concluding Section \ref{sec_disc} we summarize our results and
compare with those for other models and real traffic.

\section{Models with slow-to-start rules}
\label{sec_s2s}

In this Section we briefly present results for two models with slow-to-start
(s2s) rules \cite{slow_comf}, the T$^{2}$ model \cite{T2mod,fukui} and the
BJH model \cite{BJH}.
These models have been introduced in order to model the restart behaviour
of stopped cars in a more realistic fashion. As will be demonstrated below,
these s2s rules are an important ingredient for the occurance of metastable
states, although the authors of \cite{T2mod,BJH} did not realize the
connection between s2s rules and metastability encountered in real traffic.

\subsection{T$^{2}$ model}

Takayasu and Takayasu (T$^{2}$) \cite{T2mod} have first suggested a CA
model with a s2s rule. This rule has been generalized in \cite{slow_comf}
as follows: A standing car with exactly one empty cell in front of it
accelerates with probability $q_t = 1-p_t$, while all other cars
accelerate deterministically. The other update rules (R2-R4) of the
NaSch model are unchanged, e.g.\ all cars are still subject to the
randomization step.
Due to this modification already for $v_{max}=1$ the
particle-hole symmetry is  broken.

In Fig.~\ref{taka_fund} we show the fundamental diagram of the T$^2$
model with $v_{max} =5$, $p=0.01$ and $p_t =0.75$. The system size
used for the simulation was $L=1000$. In order to equilibrate the
system, 10000 lattice updates have been performed. The data shown in
Fig.~\ref{taka_fund} represent an average over 100000 sweeps through
the lattice.
\begin{figure}[h]
 \centerline{\psfig{figure=taka.ps,bbllx=50pt,bblly=50pt,bburx=550pt,bbury=400pt,height=5cm}}
\caption{\protect{Fundamental diagram of the T$^2$ model ($v_{max}= 5$,
   $p = 0.01$, $p_t =0.75$) obtained by starting from two different
   initial conditions, a completely jammed state (full line) and a
   homogeneous state (broken line). The peak of the full line
   is a finite-size effect.}}
\label{taka_fund}
\end{figure}

Comparing the simulation results with those for the NaSch model,
two qualitative differences have to be discussed.
First, the fundamental diagram has an inflection point
in the high density regime and second the flow behaviour is non-unique
in a density regime below the density of maximum flow $\rho_{max}$.

The existence of an inflection point for large $p_t$ has first been
noticed in \cite{slow_comf} for the case $v_{max}=1$. In contrast, the
fundamental diagram of the NaSch model is always convex. The
different behaviour of the T$^2$ model for large $p_t$ and large
densities $\rho$ is related to the fact that space is not used as
efficiently as in the NaSch model. One finds a similar behaviour in
space-continuous models \cite{Krauss}.
There is some experimental evidence that in certain situations the shape of
the fundamental diagram differs from the convex form. This
behaviour of the average flow can be easily obtained tuning the parameter
$p_t$ \cite{slow_comf,duiproc}.

The non-unique behaviour of the flow for densities just below $\rho_{max}$
is due to the fact that for these densities the average flow still
depends on the initial configuration. The measurements in Fig.~\ref{taka_fund}
have been performed by applying the second method described in the
introduction. The lower branch of the fundamental diagram corresponds
to measurements starting from a initially completely jammed configuration
while the upper branch  has been obtained starting with a homogeneous
initialization. It should be mentioned that the same result can also be
obtained by applying the first method, i.e.\ by changing the density
adiabatically. Since the flow depends on the history of the system,
diagrams like those of Fig.~\ref{taka_fund} are usually called hysteresis
curves.

For low densities the stationary state consists of homogeneous configurations
which are completely jam-free. At higher values of the global density
the configurations contain one large jam.
In contrast to the NaSch model, no spontaneous formation of jams in the
outflow region of the large jam has been observed for the system sizes
we took into account. Therefore the jammed states are phase separated
states, unlike for the case of the NaSch model.

It should be noted that the maximum value of the average flow still
depends on the number of updates as well as on the system
size. Therefore we can not exclude that the stationary value of the
average flow is unique in the thermodynamic limit. Nevertherless
the metastable states are extremely stable, even for large systems.
Moreover, in contrast to standard problems of statistical mechanics,
not the thermodynamic limit is relevant for practical purposes, but
the behavior of systems of finite length (note that 10000 lattice sites
correspond to a road of length 75~km in reality).
Since in reality roads and observation times are always finite,
the above results are sufficient for all practical purposes.

In Fig.~\ref{T2_fund} we show the fundamental diagram for
$v_{max}=1$, $p=0.5$ and $p_t =1$, i.e. stopped cars can only
move if there are at least two empty cells in front.  Obviously
completely blocked states exist for densities $\rho \geq 0.5$, where
the number of empty cells in front of each car is smaller than
two. Since fluctuations are absent in those states, they have an
infinite lifetime. Therefore the flow in the stationary state is zero.
In the region $0.5\le \rho \lesssim 0.66$ states with a finite flow exist.
Although these states are not stationary, one has to
perform an extremely large number of update steps until the flow
vanishes for large system sizes and densities  slightly above $\rho = 0.5$,
because the number of blocked configurations is very
small compared to the total number of configurations. Precisely at
$\rho = 0.5$, the blocked state is unique and the typical time to
reach this state diverges exponentially with the system size. Therefore
we used very small systems in order to obtain the lower branch of
the fundamental diagram.

\begin{figure}[h]
 \centerline{\psfig{figure=t2vm1.ps,bbllx=40pt,bblly=35pt,bburx=540pt,bbury=420pt,height=5cm}}
\caption{\protect{Fundamental diagram of the T$^2$ model ($v_{max}= 1$,
   $p = 0.5$, $p_t =1$) for two system sizes. For densities slightly
  above $\rho = 0.5$ the stationary state could only be reached for
  the smaller system.}}
\label{T2_fund}
\end{figure}

Note that the mechanism for metastability in the case $p_t=1$ is different.
The hysteresis curve in Fig.~\ref{T2_fund} has been obtained by starting
from two different {\em homogeneous} states, differing only in the
velocity of the cars. The jammed branch is reached by starting with a
configuration where all cars $j$ have a velocity $v_j(t=0)=0$, whereas
the upper branch corresponds to an initialization $v_j(t=0)=v_{max}$.
In contrast, by following the first method described in the introduction,
one would not find hysteresis, since a megajam initialization would
also yield the high-current branch.

The reason for the occurance of hysteresis in the limit $v_{max}=1$ and
$p_t=1$ is the existence of a ``geometrical'' phase transition. If
the critical density is exceeded, the cars can no longer move since there is
not enough free space. The ``geometrical'' phase transition
makes it possible to find hysteresis even in the case $v_{max}=1$.

Finally we want to remark that the $p_t =1$ limit of the T$^2$ model is
some sense complementary to the cruise-control limit \cite{Pac} of the
NaSch model. In the T$^2$ model the completely blocked state is stabilized
due to the absence of fluctuations whereas in the cruise-control limit
one finds the absence of fluctuations for homogeneous states at low
densities.

\subsection{BJH model}

The s2s rule of the T$^2$ model is a `spatial' rule. The range of
interaction for standing cars is larger than in the NaSch model and
the restart behaviour depends only on the spatial arrangement of the vehicles.
However, there are other ways of implementing a s2s behaviour.
In the Benjamin-Johnson-Hui (BJH) model \cite{BJH} cars which had to
brake due to the next car ahead, will move on the next opportunity only
with probability $1-p_s$. Note that in contrast to the T$^2$ this slow-to-start
rule requires `memory', i.e.\ it is a `temporal' rule depending on the
number of trials and not on the free space available in front of the car.

For the BJH model no metastable states and hysteresis effects have been
found until now since only the case $v_{max}=1$ has been investigated
thoroughly \cite{BJH,slow_comf}. For higher velocities we expect the
occurance of metastable states, since also in the BJH model the outflow
from a jam is smaller than the maximal flow.

\begin{figure}[h]
 \centerline{\psfig{figure=benja.ps,bbllx=50pt,bblly=50pt,bburx=550pt,bbury=400pt,height=5cm}}
\caption{\protect{Fundamental diagram of the BJH model ($v_{max}= 5$,
   $p = 0.01$, $p_s =0.75$) obtained using two different initial conditions,
   namely a completely jammed state (full line) and a homogeneous state
   (broken line).}}
\label{BJH_fund}
\end{figure}

Our simulations show that for $v_{max}>1$ the overall behaviour of the BJH
model is very similar to that of the T$^2$ model (for $p_t<1$).
Therefore we are not going to discuss it here. In Fig.\ \ref{BJH_fund} we
show a typical fundamental diagram.
There is, however, no inflection point and the fundamental diagram
is convex for all $p_s$. This supports the view that the existence
of an inflection point is a 'spatial' effect.

\section{NaSch model with velocity-dependent randomization}
\label{sec_nasch}

Here we present a simple generalization of the NaSch model which
incorporates slow-to-start behaviour without introducing memory (like in the
BJH model) or a longer-ranged interaction (like in the T$^2$ model). This
new s2s rule is therefore neither temporal nor spatial.

Instead, a velocity-dependent randomization (VDR) parameter $p=p(v(t))$ is
introduced. This parameter has to be determined {\em before} the
acceleration step R1. For simplicity we here study only the case
\begin{equation}
p(v)=\left\lbrace \begin{array}{l@{\quad}l}
p_0 & v=0\\
p   & v>0
\end{array}\right.
\end{equation}
which already contains the most important features of the general case
\cite{barlo}.
Since we are interested in hysteresis phenomena, we restrict ourselves to
the case $p_0\le p$. Note that for $p_0=p$ the NaSch model is recovered.
The cruise-control limit \cite{Pac} corresponds to the choice $p(v_{max})=0$
and $p(v)=p$ for $v<v_{max}$.

In the following we will use a maximum velocity $v_{max}=5$, braking
probability $p=1/64$ of the moving cars and a higher value $p_0 = 0.75$
for the braking probability of stopped cars.
Simulation runs have been performed for periodic systems with $L=10000$
lattice sites.

\begin{figure}[h]
  \centerline{\psfig{figure=bar_comp2.ps,bbllx=40pt,bblly=35pt,bburx=540pt,bbury=410pt,height=5cm}}
\caption{\protect{Fundamental diagram of VDR model ($v_{max}=5$, $p_{0}=0.75$,
$p =1/64$, $L=10000$). For comparison the fundamental diagrams of the
NaSch model with $p=0.75$ and $p=1/64$ are given.}}
\label{fund_nasch}
\end{figure}

Fig.\ \ref{fund_nasch} shows the fundamental diagram of the modified
model. Obviously the average flow $J(\rho)$ can take two values in the
density interval between $\rho_{1}$ and $\rho_{2}$ depending on the
chosen initialization. The larger values of the average flow can be
obtained using a homogeneous initialization of the system. The lower
branch is obtained starting from a completely jammed state. Moreover,
varying the particle number adiabatically, one can trace a hysteresis
loop. One gets the upper branch by adding cars to the stationary state
with $\rho < \rho_1$ and the lower one by removing cars from the
stationary state with $\rho > \rho_2$.
For a fixed value of $p$, $\Delta J = J(\rho_{2})-J(\rho_{1})$ depends
linearly on $p_0$ for wide a range of parameters.

Increasing the system size, we observe a decrease of the density
$\rho_{2}$ towards the branching density $\rho_1$.
The jammed states become stable for densities $\rho \geq \rho_1$
even for global densities very close to $\rho_1$. Again it
should be noted that the homogeneous states have extremely long life-times
and should therefore be relevant for realistic systems.

It is instructive to compare the fundamental diagram of the VDR model
with those of the corresponding NaSch models. For small densities
$\rho \ll 1$ there are no slow cars in the VDR model since interactions
between cars are extremely rare. Here the flow is given by $J(\rho)
\approx \rho(v_{max}-p)$, i.e.\ identical to the NaSch model with randomization
$p$. For large densities $1-\rho \ll 1$, on the other hand, the flow is given
by $J(\rho) \approx (1-p_0)(1-\rho)$ which corresponds to the NaSch model
with randomization $p_0$. For densities close to $\rho=1$, only cars with
velocities $v_j=0$ or $v_j=1$ exist. The number of moving cars goes to
zero so that asymptotically the flow is completely determined by $p_0$.

The microscopic structure of the jammed states in the VDR model
differs from those found in the NaSch model. While jammed states in
the NaSch model contain clusters with an exponential size-distribution
\cite{duiproc}, one can find phase separation in the VDR model. The reason
for this behaviour is the reduction of the outflow from a jam.
If the outflow from a jam is maximal, any small jam in the free flow
regime dissolves immediately since the outflow from such a jam is larger
than the global flow. Therefore phase separation can not occur in that
case. However, if the outflow from a jam is reduced,
the density in the free flow regime is smaller than the density of
maximum flow and cars can propagate freely in the low density part of
the lattice. Due to the reduction of the density in the free flow
regime, no spontaneous formation of jams is observable in the stationary
state, if fluctuations in the free flow regime are rare.

This picture is supported by a simple phenomenological approach. Obviously
the flow in the homogeneous branch is given by $J_{hom}=\rho(v_{max}-p)=
\rho v_{f}$, because every car can move with the free-flow velocity $v_{f}$.
Assuming that the high density states
are phase separated, we can obtain the second branch of the fundamental
diagram. The phase separated states consist of a large jam and a free
flow regime, where each car moves with velocity $v_f$. The density in
the free flow regime $\rho_f$ is determined by the average waiting
time $T_w = \frac{1}{1-p_0}$  of the first car in the jam  and $v_f$, because
neglecting interactions between cars, the average distance of two
consecutive cars is given by $\Delta x = T_w v_{f} + 1 = \rho_f^{-1}$. Using
the normalisation $L = N_J + N_F \Delta x$ ($N_{F(J)}$ is the number of cars
in the free flow regime (jam)) we find that the flow is given by
\begin{equation}
  \label{jjam}
  J_{sep}(\rho) = (1-p_0)(1-\rho).
\end{equation}
Obviously $\rho_f$ is precisely the lower branching density $\rho_1$, because
for densities below $\rho_f$ the jam-length is zero.
It should be noted that this approach is only valid for $p_0 \gg p$ and
$v_{max} >1$. The condition $p\ll 1$ guarantees that interactions of cars
due to velocity fluctuations are rare. As a consequence, the jam is
compact in that limit. For increasing $p$, the jam becomes less dense.
In the case $v_{max}=1$, cars can stop spontaneously, even in the free-flow regime.
If $p_0$ is large enough, these cars might initiate a jam. This is the
basic reason why hysteresis is usually not observed for $v_{max}=1$.

\begin{figure}[h]
 \centerline{\psfig{figure=length.eps,bbllx=0pt,bblly=0pt,bburx=1170pt,bbury=530pt,height=5cm}}
 \caption{\protect{Time-dependence of the length $L_{Jam}(t)$ of the jam
     for $\rho=0.095$. The left part of the figure shows the time evolution of
     the length $L_{Jam}(t)$ of one sample. The average $\langle L_{Jam}(t)
     \rangle$ over 10000 samples (right part of the figure)
     shows an exponential decay.}}
\label{jam_length}
\end{figure}

Measurements of the average flow show that the lower branch of the
fundamental diagram is not stable near the density $\rho_1$, if small
system sizes are considered. Therefore we performed a more
detailed stability analysis of the homogeneous and
the jammed state near $\rho_1$ and  $\rho_2$.  Close to $\rho_1$, the
large jam present in the initial configuration dissolves and the average length
$\langle L_{Jam}(t)\rangle$ decays exponentially in time
(Fig.~\ref{jam_length}).
It should be noted that this behaviour is not the consequence of a
continuous "melting" of the large jam. In contrast, the jam-length
$L_{Jam}(t)$ is strongly fluctuating without any obvious systematic
time-dependence (Fig.~\ref{jam_length}).
Once a homogeneous state without a jammed car is reached, no new jams are
formed. Therefore the homogeneous state is stable near $\rho_1$.
For large system sizes the jammed states
are stable for $\rho \geq \rho_1$, also for densities only slightly
above $\rho_1$, because the average length of the jam is
proportional to the system size, while the fluctuations grow
sub-extensive.
\begin{figure}[h]
  \centerline{\psfig{figure=spacetime.eps,bbllx=0pt,bblly=0pt,bburx=570pt,bbury=530pt,height=6cm}}
  \caption{\protect{Space-time diagram of the VDR model for
    $\rho=0.15, L=400, p =0.01 $ and $p_0=0.5$. The homogeneous initial
      state is not destroyed immediately, but after approximately 93000
      lattice updates. In the outflow regime of the jam the density is
      reduced compared to the average density.}}
\label{st_diag}
\end{figure}

Analogous to the metastable jammed states near $\rho_1$, homogeneous
initializations for densities slightly above $\rho_2$  lead to
metastable homogeneous states with short lifetimes. Fig.~\ref{st_diag}
shows the spontaneous formation of jams due to velocity fluctuations. The
finite lifetimes of the homogeneous states are the qualitative
difference between this model and the cruise-control limit \cite{Pac} of
the NaSch model, where the time evolution of homogeneous states at low
densities is completely deterministic.

For large system sizes the density difference $\Delta \rho = \rho_2 -\rho_1$
decreases. This can be explained by looking at the
mechanism of an emerging jam. Jams emerge due to velocity fluctuations
in dense regions of the homogeneous states, where the distance $d_j+1$
between consecutive cars is less than $v_{max}$.
In these regions all following cars have to slow down if a car in front
breaks in the randomization step. Over-reactions of following cars
finally can cause jams. The probability to find clusters of an
appropriate length for a given density is proportional to the system
size. Therefore we expect that all homogeneous states are unstable for
$\rho > \rho_1$ in the thermodynamic limit.

For higher values of $p$ the lifetime of homogeneous states at densities
$\rho > \rho_1$ is very small. Nevertheless one can observe the same
microscopic structure of the high density states as long as the outflow
of a jam is sufficiently reduced. A {\em rough} estimate for the
minimal difference between $p_0$ and $p$ necessary to observe phase separation
can be obtained from the following arguments based on the features
of a typical fundamental diagram of the VDR model at small $p$ and
large $v_{max}$ (see Fig.\ \ref{argument}).
\begin{figure}[h]
  \centerline{\psfig{figure=arguments.ps,bbllx=15pt,bblly=560pt,bburx=585pt,bbury=760pt,height=5cm}}
  \caption{\protect{Illustration of the flow branches a) in the
presence of phase separation and b) without phase separation.}}
\label{argument}
\end{figure}
In the following we assume that the fundamental diagram is perfectly linear
up to $\rho_{2}$, i.e.\ $J_{hom}(\rho) = \rho(v_{max}-p)$. As mentioned before,
the phase-separated branch is described by $J_{sep}(\rho) = (1-p_0)(1-\rho)$
(see Eq.~(\ref{jjam})). In order to find phase separation, the flow in the
phase-separated branch at density $\rho_{2}$ must be lower than the flow in
the homogeneous branch, i.e.\ $J_{hom}(\rho_{2}) > J_{sep}(\rho_{2})$
(left part of Fig.\ \ref{argument}). For a situation as depicted in the
right part of Fig.\ \ref{argument} (i.e.\ for  $J_{hom}(\rho_{2}) <
J_{sep}(\rho_{2})$), no phase-separation would be found.
In the following we approximate $\rho_2$ by $\rho_{max}$, the maximum of
the corresponding NaSch model with randomization $p$. Using the estimate
$\rho_{max}=(1-p)/(v_{max}+1)$ \cite{eisi}, the inequality for the current
at $\rho_2\approx \rho_{max}$ can be used to obtain an estimate for the
minimal difference $p_0-p$ necessary to observe phase separation (see
Fig.~\ref{fig_comp}).
Near the deterministic limits ($p=0$ and $p=1$) and for large values of
$v_{max}$, already a small difference $p_0-p$ suffices to generate
phase separation.
For all nondeterministic cases the states of maximum flow are not completely
homogeneous and the flow in the high density branch is somewhat lower
than $J_{sep}(\rho) = (1-p_0)(1-\rho)$ for larger values of
$p$. In addition, the large jam is not compact anymore.
\begin{figure}[h]
  \centerline{\psfig{figure=compare.ps,bbllx=40pt,bblly=30pt,bburx=550pt,bbury=415pt,height=5cm}}
  \caption{\protect{Estimates for the minimum difference $p_0 -p$ necessary
to observe phase separation.}}
\label{fig_comp}
\end{figure}

In order to substantiate the picture developed in this section we also
investigated correlation functions and the effect of perturbations
(i.e.\ stopping a car temporarily to induce a jam) \cite{RB_dipl}.
The results are in full agreement with our interpretation and will be
presented elsewhere \cite{BSSS}.

Another interesting result concerns the outflow from a jam.
Our simulations show \cite{BSSS} that the outflow is (almost)
independent of the density of cars and depends only on $p$.
This in agreement with measurements on real traffic
\cite{KernerReh2} where it was found that the outflow only depends on
road and weather conditions and typical characteristics of the cars.
Furthermore we have found that a structure consisting of two
separated jams is rather stable and can exist for long times. This
is also in agreement with experimental observations \cite{KernerReh2}.

For $v_{max}=1$ we used the so-called car-oriented mean-field theory \cite{comf}
in order to obtain an analytical description of the fundamental diagram.
The results are in good agreement with simulations \cite{RB_dipl}. As
expected, one finds no phase separation at any $p_0$ for $p>0$. In the
deterministic limit, however, a hysteresis curve can be observed for
$p_0>0$. The fundamental diagram constists of two linear branches and is
in perfect agreement with simulations \cite{BSSS}.

\section{Summary and Discussion}
\label{sec_disc}

The ability to describe the existence of hysteresis is a serious test
for any traffic flow model. In this paper we have investigated
several variants of the NaSch model and showed numerically the
existence of metastable states in a density region close to the
maximum flow.

The hysteresis in the fundamental diagram is related
to the existence of metastable states. The latter are a
consequence of phase separation in a certain density regime.
The reason for this phase separation, on the other hand, is
a reduced outflow from jams which destabilizes clusters forming
in the outflow region. Such a reduction can be
incorporated most easily by introducing slow-to-start rules
which try to model the restart behaviour of standing vehicles
more realistically. The three models presented here used
different s2s rules which can be classified as spatial, temporal
and velocity-dependent, respectively. For maximum velocity $v_{max}>1$
the models exhibit a similar behaviour (see below).
For $v_{max}=1$ the spatial s2s rule of the T$2$ model
is exceptional since it leads to a existence of a phase transition
to a completely jammed state in the limit $p_t\to 1$ where $p_t$
is the s2s parameter.

The NaSch model with velocity-dependent randomization shows the
coexistence of phase separated and homogeneous states in a density
interval near the density $\rho_2$ of maximum flow. Near $\rho_2$
interactions between cars become important and one can find
spontaneous formation of jams. Therefore the reduction of the density
in the outflow regime of a jam leads to stable phase separated states.
The reduction of interactions between cars in the free flow regime can
be confirmed by a phenomenological approach, which gives very accurate
results. In contrast to the cruise-control limit of the NaSch model
\cite{Pac}, where also metastable states can be found, fluctuations
are present in both coexisting states.

The results presented here have interesting applications. In real traffic
one is usually interested in stabilizing the homogeneous branch of
the fundamental diagram in order to maximize the throughput. This can
be done using signals to control the inflow, as in the case of the
Lincoln tunnel in New York \cite{lincoln}. Results of simulations
corresponding to such a situation will be presented in a future
publication \cite{BSSS}.

In \cite{Krauss} a family of space-continuous models has been
investigated. Depending on the values of the maximum acceleration and
deceleration three classes can be distinguished. Class III shows no
realistic behaviour since no spontaneous jams are formed. A continuous
analogue of the NaSch model belongs to class II (high decelaration limit).
Here one finds spontaneous formation of jams, but no metastable states.
Finally, in class I spontaneous jamming as well as metastable states
are found. On a macroscopic level, models in classes I and II can be
distinguished by the ordering of the densities $\rho_f$, the density
of the outflow from a jam, and $\rho_c$, where the density of a
homogeneous flow becomes unstable\footnote{Often it is not easy to
define these quantities properly, especially in the  presence of noise.}.
The discrete models discussed here have very simple braking rules, but
nevertheless exhibit the behaviour of class III.
The existence of metastable states is therefore not related to the use
of continuous space coordinates or ``realistic'' braking rules
\cite{zprmod1,zprmod2} (e.g.\ anticipation of the behaviour of the
driver ahead).

Already the NaSch model has a tendency towards the formation
of metastable states. The outflow from a megajam is maximal only in the
deterministic case $p=0$ and in the so-called cruise-control limit
\cite{Pac}. In the generic case $p>0$ the outflow is not maximal
\cite{eisidipl}, but organizes itself towards the `critical' current
$J_c$ where the correlation length becomes maximal \cite{eisi}.
Since the difference between $J_{max}$ and $J_c$ is rather small,
it is very difficult to observe metastable states in the
NaSch model.

The considerations in this paper show the flexibility of the CA
approach to traffic flow problems. A rather simple and natural
extension of the rules of the NaSch model allows us to describe
the formation of metastable states in the fundamental diagram.
The introduction of a velocity-dependent randomization $p(v)$ makes
it possible to control the properties of the free flow and congested
flow independently. Experimentally it has been found \cite{KernerReh2}
that for real traffic the reduction of the outflow $J_{out}$ compared
to the maximum flow $J_{max}$ is approximately $J_{max}/J_{out}\approx 1.5$.
This value can be used to determine a realistic value of $p_0-p$.

If one is willing to give up an overly realistic description of the
interactions between the vehicles one can obtain rather simple CA
models capable of describing even the fine-structure of traffic
flow in a satisfactory way.

redpajama_set_name: RedPajamaArXiv


There has never been a better time to be an independent musician. Today, fans can communicate with their idols by simply picking up their phones, artists are able to produce studio-worthy content from their basement and albums are funded not by "record men" but by generous, engaged supporters. As result, How to Make It in the New Music Business is a must-have guide for anyone hoping to navigate the increasingly complex yet advantageous landscape that is the modern music industry.


Boston Scientific's ImageReady™ CRT-P devices are MR-Conditional Pacing Systems that allow safe and effective scanning in 1.5T and 3T MRI environments¹. All BSC Pacing Systems rely on an exclusive Battery Technology for extended device longevity. VISIONIST X4 models combine MRI safety and longevity with a differentiated RightRate Minute Ventilation sensor.
Boston Scientific Corporation's RHYTHMIA HDx™ Mapping System sets a new bar in Ultra High-Definition mapping by using three main features: density, resolution and automation. Each is essential in creating Ultra High-Definition maps.
The Open-Irrigated (OI) System Empowers Irrigated Ablation Procedures. The OI System empowers your ability to maximize open-irrigated procedure success and helps drive improvement to patient outcomes with the most advanced ablation technology.
The Open-Irrigated (OI) System Empowers Irrigated Ablation Procedures. OI System empowers your ability to maximize open-irrigated procedure success and helps drive improvement to patient outcome with the most advanced ablation technology.
The Blazer™ Open-Irrigated Ablation Catheter is the only catheter with a Total Tip Cooling™ Design which provides total uniform tip cooling internally, an optimized flow pattern with active washing and consistent cooling throughout RF delivery as well as a uniform external flow.
The INTELLATIP MIFI XP, with MicroFidelity (MiFi) sensor technology, introduces a new generation of high-resolution ablation catheters. INTELLATIP MIFI XP technology, only from Boston Scientific, is engineered to deliver highly localised electrical information of unparalleled clarity to allow you to see the critical information you need in real-time.
The INTELLATIP MIFI™ OI Ablation Catheter delivers the critical, multi-dimensional information you need to confidently diagnose and treat complex cardiac arrhythmias and provide the true picture of exactly what is happening at the tip of the ablation catheter in real-time.
Combining the proven performance of the BLAZER™ platform with a navigation-enabled 4 mm tip, the INTELLANAV™ ST Ablation Catheter offers smaller, more precise ablation for increased accuracy, efficiency and performance in RHYTHMIA™ Mapping System procedures.
Designed to work with the RHYTHMIA HDx™ Mapping System, the INTELLAMAP ORION™ Mapping Catheter brings unprecedented resolution and accuracy to mapping procedures.
The ORBITER PV Variable Loop Mapping Catheter has been designed to overcome the challenges of pulmonary vein mapping. With a reduction of complications, fluoroscopy and procedural time in mind, we've created a catheter that keeps you in contact for mapping and confirmation of post-ablation conduction block.
EMBLEM MRI builds upon the excellent clinical performance of the previous generations of S-ICD. EMBLEM MRI provides protection for patients at risk of sudden cardiac death (SCD), while avoiding complications associated with transvenous leads.
Introducing the Resonate™ family of ICDs offering an extraordinary, holistic approach to cardiac care.
As implanted device patients are living longer and the amount of available patient and device data keeps growing larger, remote monitoring has become the standard of care1. The LATITUDE NXT Remote Patient Management System lets you monitor your patients' device data between scheduled appointments for improved efficiency and better patient care.
1 Competitive comparisons: – PHYSICIAN'S TECHNICAL MANUAL DYNAGEN™ EL ICD, DYNAGEN™ MINI ICD, INOGEN™ EL ICD, INOGEN™ MINI ICD, ORIGEN™ EL ICD, ORIGEN™ MINI ICD 2014 page 27-29. – PUNCTUA™ ICD, ENERGEN™ ICD, INCEPTA™ ICD - PHYSICIAN'S TECHNICAL MANUAL 2012 page 40-41. – PROTECTA™ XT VR D314VRM 2013 page 330. – EVERA™ XT VR DVBB1D4 2013 page 24. – AnalyST™, AnalyST Accel™, Current™, Current Accel™, Fortify™, Fortify™ ST, Promote™, Promote Accel™, Promote™ Q, Unify™ Devices User's Manual 2013 page 29. – St. Jude Medical™ High-Voltage Devices User's Manual 2013 page 16. – Ilesto 7 Family of ICDs and CRT-Ds Technical Manual 2013 page 217. 2 20% smaller and 24% thinner defined by volume. Comparison of BSC MINI VR ICD and Medtronic EVERA™ XT VR DVBB1D4 2013 page 24.