Born in Glen Ellyn to Korean parents, violinist Jennifer Koh studied early on at the Music Institute of Chicago with Almita and Roland Vamos, the wife-and-husband teaching team that has groomed two generations of string players, including their own sons. She played with the Chicago Symphony Orchestra at age 13, began collecting honors shortly after (Tchaikovsky Competition, Avery Fisher Prize), and soon got an agent, who's booked engagements with many second-tier orchestras in North America (the usual course for young soloists who show exceptional promise). Koh is an exciting violinist to hear and to watch, and though her unbridled enthusiasm and sentimental streak can sometimes hinder her, studies with string veteran Jaime Laredo have helped her get them under control. (The change in style is evident on her latest CD, the enjoyable Solo Chaconnes, released by the local label Cedille.) This weekend, however, Koh will be free to cut loose: the two concert showpieces in which she'll star were written with unabashed virtuosity in mind. Saint-Saens's Introduction and Rondo Capriccioso takes some of its spiky rhythms from an Aragonese dance, and Ravel's Tzigane was inspired by Gypsy music. But though both require stunning pyrotechnics, neither thrives on thrills alone, and conductor Carlos Kalmar should coax some degree of subtlety from Koh and the Grant Park Orchestra. This concert of short orchestral works is also a tribute to Robert Kurka, the Cicero-born composer who died young and is best remembered for his operatic satire The Good Soldier Schweik. His Music for Orchestra (1949) will be given a belated premiere, and his 1954 Serenade for Small Orchestra (a reflection on Walt Whitman's poetry) will receive a rare performance. Richard Strauss's Till Eulenspiegel's Merry Pranks, an often revived symphonic poem, rounds out the program. Friday and Saturday, June 27 and 28, 7:30 PM, Orchestra Hall, Symphony Center, 220 S. Michigan; 312-742-4763.


text:
Covid booster jab walk in centres Edinburgh: where to get third vaccine near me - without booking an appointment
These are the 10 most deprived areas in Edinburgh
Delta Plus Variant UK: What is the Delta Variant? Is it different from Indian variant? Covid-19 strain explained
The Delta Variant has been in the news lately, but what is it?
By Ginny Sanderson
2nd Jul 2021, 3:34pm - 3 min read
There are a lot of Covid-19 variant names flying around, and it's easy to be overwhelmed by all the information.
The Delta variant – previously known as the Indian variant – has become the dominant strain of coronavirus in Scotland and the rest of the UK.
It is between 30 per cent and 100 per cent more transmissible than the Alpha (Kent) variant, Professor Neil Ferguson told Radio 4's Today programme.
Edinburgh Jenners fire: Hundreds of tributes left in Princes Street following death of firefighter Barry Martin
But what is it, how did it develop, and how will it affect the easing of lockdown?
Scotland records highest Covid case numbers since February
What is the Delta Variant?
Let's begin by explaining all of its different names. This variant goes by more titles than Daenerys Targaryen.
The Delta Variant has become the dominant strain of Covid in Scotland (Getty Images)
It was initially called the Indian Variant, due to being first detected there in April this year.
But it was later renamed the April 02 Variant by the Scottish Government to avoid stigma in associating the variant with people from India.
However, the WHO (World Health Organisation) has now officially renamed the variant Delta (B.1.617.2).
And finally, scientists call it VOC-21APR-02 (VOC is short for Variant of Concern).
Nepal Variant: How accurate are claims of new Covid-19 strain?
A variant is what happens when a virus replicates itself and the copy is slightly different.
Scientists say Covid-19 is changing all the time and there are thousands of new variants.
It only becomes an issue when it is more transmissible, or deadly, than the original virus.
The Delta variant has developed to spread more rapidly through the population, which is why UK leaders are being more cautious with the easing of lockdown.
The UK Government previously said there is no evidence this variant is more severe or evades the vaccine.
However, Public Health England has since said: "Early evidence suggests there may be an increased risk of hospitalisation for Delta compared to Alpha, although more data is needed for us to have more confidence in that finding."
Covid symptoms: What are the symptoms of the Delta variant? What are most common...
What is the Delta Plus variant?
India has reported a new 'Delta plus' coronavirus variant of concern, officials have said.
Delta plus (B.1.617.2) is a further mutation of Delta, which is thought to be even more transmissible than the original strain.
An outbreak of 16 cases of the new Delta Plus variant were detected on June 22 in the western state of Maharashtra, and Indian officials are said to be increasing testing and vaccination drives.
What has Nicola Sturgeon said about the Delta variant?
Nicola Sturgeon says the Delta variant is driving a third wave of coronavirus.
Speaking at a coronavirus briefing, the First Minister said: "The new Delta variant which now makes up the majority of all new cases in Scotland.
"This variant is thought to be quite significantly more transmissible than even the Kent variant we were dealing with at the turn of the year and there is early data suggesting that, all else being equal, it may increase the risk of hospitalisation.
"Now, hopefully, vaccines are reducing overall the risk of hospitalisation but even if it is a lower risk the early data suggests that this new Delta variant has a higher risk than the variants that went before it."
The health advice is to keep following the rules, get tested for coronavirus often, and get two doses of the vaccine when it is offered to you.
People are encouraged to work from home if they can, meet people outside where possible, keep up hand washing and social distancing.
The latest Scottish Government advice can be found here.
Covid-19Radio 4ScotlandKentPublic Health England

redpajama_set_name: RedPajamaCommonCrawl


بجیلہ نام کا شمار لڑکیوں کے ناموں میں ہوتا ہے۔ بجیلہ نام کی ابتدائی تاریخ اردو زبان سے نکلتی ہے۔ بجیلہ نام کے افراد کے لیئے خوش قسمت نمر 8 مانا جاتا ہے . جبکہ خوش قسمت دنوں میں جمعہ, سوموار شامل ہیں ۔ خوش قسمتی والی دھاتوں میں ہندسوں کے حساب ے چاندی شامل ہیں بجیلہ نام کے افراد کے لیئے موافق پتھروں میں مرکت شامل ہیں .
Bajila is a Muslim Girl name which originates from the Urdu language. Lucky number for name Bajila is 8. Lucky days for name Bajila are Friday, Monday and lucky metals are Silver for name Bajila. Lucky stones for name Bajila are Emerald.
Urdu names and meanings, Urdu name dictionary of Bajila, and other Girl names. Urdu names meaning dictionary for Muslim boys, and Muslim girls, Urdu baby name like Bajila and others. A complete Urdu names dictionary, a complete Arabic and Islamic name encyclopedia for new born babies. Bajila Urdu names English meaning. Check Bajila name English and Urdu spelling.
Islamic Name Bajila, Name Meaning in Urdu. Girl name Bajila and other Muslim Girl names dictionary. Bajila baby meaning in Urdu, Arabic and English. Find baby Girl names with easy translation. a complete Arabic and Islamic name encyclopedia for new born babies. Find Urdu name English meaning. Check name English and Urdu spelling and audio Pronunciation of the name!.


Choose your area of specialisation!
This course develops the skills and knowledge needed to become a leader in the sport, recreation and exercise industry. Study the area of your interest with the option to select Human Performance or Sport Management as your area of interest.
We offer a 50/50 approach to learning within this course, between course work and practical work experience. Your learning will directly link to the individual and community needs within the cultural, social and economic health & well-being of New Zealand.
Work Placement Opportunities: Gain a well-rounded learning experience with work placements at our partnered organisations and get the chance to work with clients of your own.
Give back to the community: Work with our partnered Government Health Agency to assist in health initiatives that support the well-being of others.
Take on leadership roles at a large scale: Experience working with our partnered organisations from a regional to a national level.
This course is structure around 4 core papers and 4 electives based on your study and career pathway.
You will graduate as a trained professional, capable to lead others and manage a team, or pursue degree-level study onto university. Enrol in a third year bachelor degree with the University of Canterbury or Manukau Institute of Sport or pursue degree opportunities with Victoria University in Melbourne, Australia.
Areas of work include; health providers, outdoor education centres, exercise facilities, iwi organisations, local councils, cultural centres, primary health organisations, regional sports trusts, and recreation, sport and leisure centres.
You must have completed the New Zealand Diploma in Sport, Recreation and Exercise (Multi-sector) (Level 5) or other tertiary equivalent or; international equivalent.
If you fail to reach the requirements, you may still be eligible for discretionary approval and may still be considered upon a personal interview.
You may be have relevant qualifications from other institutions and be eligible through a Credit Transfer and Recognition of Prior Learning process.


text:
Séance du CCSEHDAA
3 avril à 19 h 00 min-22 h 00 min
|Recurring Évènement (See all)
One event on 7 November 2022 at 7:00pm
One event on 28 November 2022 at 7:00pm
One event on 9 January 2023 at 7:00pm
One event on 6 February 2023 at 7:00pm
One event on 13 March 2023 at 7:00pm
One event on 3 April 2023 at 7:00pm
One event on 8 May 2023 at 7:00pm
One event on 5 June 2023 at 7:00pm
« Séance du Comité de parents
Séance du Comité de parents »
Séance ordinaire du CCSEHDAA.
19 h 00 min-22 h 00 min
Centre administratif du CSS Laval
955 boulevard Saint-Martin Ouest
Laval, Québec H7S 1M5 + Google Map


What could be better than a delicious breakfast overlooking a beautiful turquoise sea? That's what awaits you every morning at "Le Caravelle"
Its fine cuisine is able to satisfy even the most demanding palates.
Ideal for a mouth-watering lunchtime buffet or an elegant candlelit dinner, "Le Caravelle" serves exquisite local and international dishes thanks to the imagination and skill of our Chef. Prepare to be impressed by fine gastronomy and impeccable service!.
Men are required to wear long trousers.
A cuisine inspired by passion in a sophisticated environment dedicated to taste.


text:
The Five Mile Press
Bonnier Publishing Australia is a publishing house, based in Melbourne. We're agile like a start-up, with the financial backing of a parent company with an international network. We represent UK sister-company imprints across the ANZ markets, as well as creating a successful and exciting local publishing under Five Mile, a 25-year old children's imprint, and Echo, a fresh voice in Australian adult publishing. Our business is driven by the belief that books should be published for everyone and to deliver this everything we do is underpinned by a book's relevance, accessibility and affordability. Bonnier Publishing Australia is a division of international publishing group, Bonnier Publishing.
The Things I Love About Bedtime (Paperback)
This delightful book addresses the everyday world of preschoolers and encourages them to thin..
The Things I Love About Friends (Paperback)
The Things I Love About Grandparents (Paperback)
The Things I Love About Me (Paperback)
The Things I Love About Pets (Paperback)
The Things I Love About Playtime (Paperback)
The Things I Love About School (Paperback)
When I'm Feeling Angry (Paperback)
When you're really angry you feel like you're going to explode. It's okay to be angry sometimes, a..
When I'm Feeling Jealous (Paperback)
Feeling jealous can sometimes make you do silly things. But always remember that everyone is speci..
When I'm Feeling Kind (Paperback)
Helping people, listening to your friends, feeling good about yourself. Feeling kind is all of the..
When I'm Feeling Lonely (Paperback)
Lots of things can make you feel lonely. It's not a nice feeling, but just remember that everyone ..
When I'm Feeling Loved (Paperback)
Feeling loved is the most wonderful feeling. It makes you feel safe, warm protected and special. E..
When I'm Feeling Sad (Paperback)
Everyone feels sad sometimes. It's a quiet, lonely feeling. But it can often help to talk to someo..
The Things I Love About Family (Paperback)
When I'm Feeling Happy (Paperback)
So many things can make you happy. Playing with friends, a special treat - or just a big hug. &nbs..


Hundreds of U.S. Postal Service workers protested against experimental mini post offices at Staples. Here's why some Washington, D.C. workers don't like the deal.
My senior citizens don't trust the Internet. If they give me their letter, they know I'm going to make sure it gets there and go the extra step -- wrapping their packages with priority tape, making corrections on their address label. You can't tell me a person from Staples is qualified to do my job.


Grey Ops: Milsig MK-III Coming Soon!
The eagerly awaited (well on my part anyway) Milsig MK-III is now available for pre-order via Milsig.ca's online store. The best part? The price point is only $250 CAD (special pricing ends the 31st). For full details, check out the product page, and for an upcoming review check out magfedpaintball.com (with Evan Henshaw reviewing the marker).
RANT WEEK 2 is coming!


Relaunch Amstel on the Bulgarian market as the beer for keen professionals and their leisure time.
Keen professionals can't take a proper break even after work – they stay connected to the office or are in a constant rush.
To inspire people to take a break, we created an installation that asks them to do… nothing!


text:
Coronary computed tomography angiography for the detection of cardiac allograft vasculopathy: A meta-analysis of prospective trials
Omar Wever-Pinzon, Jorge Romero, Iosif Kelesidis, James Wever-Pinzon, Carlos Manrique, Deborah Budge, Stavros G. Drakos, Ileana L. Piña, Abdallah G. Kfoury, Mario J. Garcia, Josef Stehlik
Objectives This study aimed to evaluate the diagnostic accuracy of coronary computed tomography angiography (CCTA) for detecting cardiac allograft vasculopathy (CAV) in comparison with conventional coronary angiography (CCAG) alone or with intravascular ultrasound (IVUS). Background CAV limits long-term survival after heart transplantation, and screening for CAV is performed on annual basis. CCTA is currently not recommended for CAV screening due to the limited accuracy reported by early studies. Technological advances, however, might have resulted in improved test performance and might justify re-evaluation of this recommendation. Methods A systematic review of Medline, Cochrane, and Embase for all prospective trials assessing CAV using CCTA was performed using a standard approach for meta-analysis for diagnostic test and a bivariate analysis. Results Thirteen studies evaluating 615 patients (mean age 52 years, 83% male) and 9,481 segments fulfilled inclusion criteria. Patient-based analyses comparing CCTA versus CCAG for the detection of any CAV (> luminal irregularities) and significant CAV (stenosis ≥50%), showed mean weighted sensitivities of 97% and 94%, specificities of 81% and 92%, a negative predictive value (NPV) of 97% and 99%, a positive predictive value (PPV) of 78% and 67%, and diagnostic accuracies of 88% and 94%, respectively. There was a strong trend toward improved sensitivity (97% vs. 91%, p = 0.06) and NPV (99% vs. 97%, p = 0.06) to detect significant CAV with 64-slice compared with 16-slice CCTA. A patient-based analysis of 64-slice CCTA versus IVUS showed a mean weighted sensitivity and specificity of 81% and 75% to detect CAV (intimal thickening >0.5 mm), whereas the PPV and NPV were 93% and 50%, respectively. Conclusions CCTA using currently available technology is a reliable noninvasive imaging alternative to coronary angiography with an excellent sensitivity, specificity, and NPV for the detection of CAV.
Journal of the American College of Cardiology
https://doi.org/10.1016/j.jacc.2014.01.071
cardiac allograft vasculopathy
coronary computed tomography angiography
transplant vasculopathy
10.1016/j.jacc.2014.01.071
Dive into the research topics of 'Coronary computed tomography angiography for the detection of cardiac allograft vasculopathy: A meta-analysis of prospective trials'. Together they form a unique fingerprint.
Computed Tomography Angiography Medicine & Life Sciences 100%
Allografts Medicine & Life Sciences 83%
Meta-Analysis Medicine & Life Sciences 71%
Coronary Angiography Medicine & Life Sciences 28%
Tunica Intima Medicine & Life Sciences 10%
Heart Transplantation Medicine & Life Sciences 10%
Routine Diagnostic Tests Medicine & Life Sciences 9%
Wever-Pinzon, O., Romero, J., Kelesidis, I., Wever-Pinzon, J., Manrique, C., Budge, D., Drakos, S. G., Piña, I. L., Kfoury, A. G., Garcia, M. J., & Stehlik, J. (2014). Coronary computed tomography angiography for the detection of cardiac allograft vasculopathy: A meta-analysis of prospective trials. Journal of the American College of Cardiology, 63(19), 1992-2004. https://doi.org/10.1016/j.jacc.2014.01.071
Coronary computed tomography angiography for the detection of cardiac allograft vasculopathy : A meta-analysis of prospective trials. / Wever-Pinzon, Omar; Romero, Jorge; Kelesidis, Iosif et al.
In: Journal of the American College of Cardiology, Vol. 63, No. 19, 20.05.2014, p. 1992-2004.
Wever-Pinzon, O, Romero, J, Kelesidis, I, Wever-Pinzon, J, Manrique, C, Budge, D, Drakos, SG, Piña, IL, Kfoury, AG, Garcia, MJ & Stehlik, J 2014, 'Coronary computed tomography angiography for the detection of cardiac allograft vasculopathy: A meta-analysis of prospective trials', Journal of the American College of Cardiology, vol. 63, no. 19, pp. 1992-2004. https://doi.org/10.1016/j.jacc.2014.01.071
Wever-Pinzon O, Romero J, Kelesidis I, Wever-Pinzon J, Manrique C, Budge D et al. Coronary computed tomography angiography for the detection of cardiac allograft vasculopathy: A meta-analysis of prospective trials. Journal of the American College of Cardiology. 2014 May 20;63(19):1992-2004. doi: 10.1016/j.jacc.2014.01.071
Wever-Pinzon, Omar ; Romero, Jorge ; Kelesidis, Iosif et al. / Coronary computed tomography angiography for the detection of cardiac allograft vasculopathy : A meta-analysis of prospective trials. In: Journal of the American College of Cardiology. 2014 ; Vol. 63, No. 19. pp. 1992-2004.
@article{8db9ecee02734bb8822d7201beca7f05,
title = "Coronary computed tomography angiography for the detection of cardiac allograft vasculopathy: A meta-analysis of prospective trials",
abstract = "Objectives This study aimed to evaluate the diagnostic accuracy of coronary computed tomography angiography (CCTA) for detecting cardiac allograft vasculopathy (CAV) in comparison with conventional coronary angiography (CCAG) alone or with intravascular ultrasound (IVUS). Background CAV limits long-term survival after heart transplantation, and screening for CAV is performed on annual basis. CCTA is currently not recommended for CAV screening due to the limited accuracy reported by early studies. Technological advances, however, might have resulted in improved test performance and might justify re-evaluation of this recommendation. Methods A systematic review of Medline, Cochrane, and Embase for all prospective trials assessing CAV using CCTA was performed using a standard approach for meta-analysis for diagnostic test and a bivariate analysis. Results Thirteen studies evaluating 615 patients (mean age 52 years, 83% male) and 9,481 segments fulfilled inclusion criteria. Patient-based analyses comparing CCTA versus CCAG for the detection of any CAV (> luminal irregularities) and significant CAV (stenosis ≥50%), showed mean weighted sensitivities of 97% and 94%, specificities of 81% and 92%, a negative predictive value (NPV) of 97% and 99%, a positive predictive value (PPV) of 78% and 67%, and diagnostic accuracies of 88% and 94%, respectively. There was a strong trend toward improved sensitivity (97% vs. 91%, p = 0.06) and NPV (99% vs. 97%, p = 0.06) to detect significant CAV with 64-slice compared with 16-slice CCTA. A patient-based analysis of 64-slice CCTA versus IVUS showed a mean weighted sensitivity and specificity of 81% and 75% to detect CAV (intimal thickening >0.5 mm), whereas the PPV and NPV were 93% and 50%, respectively. Conclusions CCTA using currently available technology is a reliable noninvasive imaging alternative to coronary angiography with an excellent sensitivity, specificity, and NPV for the detection of CAV.",
keywords = "accuracy, cardiac allograft vasculopathy, coronary computed tomography angiography, heart transplantation, transplant vasculopathy",
author = "Omar Wever-Pinzon and Jorge Romero and Iosif Kelesidis and James Wever-Pinzon and Carlos Manrique and Deborah Budge and Drakos, {Stavros G.} and Pi{\~n}a, {Ileana L.} and Kfoury, {Abdallah G.} and Garcia, {Mario J.} and Josef Stehlik",
doi = "10.1016/j.jacc.2014.01.071",
journal = "Journal of the American College of Cardiology",
T1 - Coronary computed tomography angiography for the detection of cardiac allograft vasculopathy
T2 - A meta-analysis of prospective trials
AU - Wever-Pinzon, Omar
AU - Romero, Jorge
AU - Kelesidis, Iosif
AU - Wever-Pinzon, James
AU - Manrique, Carlos
AU - Budge, Deborah
AU - Drakos, Stavros G.
AU - Piña, Ileana L.
AU - Kfoury, Abdallah G.
AU - Garcia, Mario J.
AU - Stehlik, Josef
N2 - Objectives This study aimed to evaluate the diagnostic accuracy of coronary computed tomography angiography (CCTA) for detecting cardiac allograft vasculopathy (CAV) in comparison with conventional coronary angiography (CCAG) alone or with intravascular ultrasound (IVUS). Background CAV limits long-term survival after heart transplantation, and screening for CAV is performed on annual basis. CCTA is currently not recommended for CAV screening due to the limited accuracy reported by early studies. Technological advances, however, might have resulted in improved test performance and might justify re-evaluation of this recommendation. Methods A systematic review of Medline, Cochrane, and Embase for all prospective trials assessing CAV using CCTA was performed using a standard approach for meta-analysis for diagnostic test and a bivariate analysis. Results Thirteen studies evaluating 615 patients (mean age 52 years, 83% male) and 9,481 segments fulfilled inclusion criteria. Patient-based analyses comparing CCTA versus CCAG for the detection of any CAV (> luminal irregularities) and significant CAV (stenosis ≥50%), showed mean weighted sensitivities of 97% and 94%, specificities of 81% and 92%, a negative predictive value (NPV) of 97% and 99%, a positive predictive value (PPV) of 78% and 67%, and diagnostic accuracies of 88% and 94%, respectively. There was a strong trend toward improved sensitivity (97% vs. 91%, p = 0.06) and NPV (99% vs. 97%, p = 0.06) to detect significant CAV with 64-slice compared with 16-slice CCTA. A patient-based analysis of 64-slice CCTA versus IVUS showed a mean weighted sensitivity and specificity of 81% and 75% to detect CAV (intimal thickening >0.5 mm), whereas the PPV and NPV were 93% and 50%, respectively. Conclusions CCTA using currently available technology is a reliable noninvasive imaging alternative to coronary angiography with an excellent sensitivity, specificity, and NPV for the detection of CAV.
AB - Objectives This study aimed to evaluate the diagnostic accuracy of coronary computed tomography angiography (CCTA) for detecting cardiac allograft vasculopathy (CAV) in comparison with conventional coronary angiography (CCAG) alone or with intravascular ultrasound (IVUS). Background CAV limits long-term survival after heart transplantation, and screening for CAV is performed on annual basis. CCTA is currently not recommended for CAV screening due to the limited accuracy reported by early studies. Technological advances, however, might have resulted in improved test performance and might justify re-evaluation of this recommendation. Methods A systematic review of Medline, Cochrane, and Embase for all prospective trials assessing CAV using CCTA was performed using a standard approach for meta-analysis for diagnostic test and a bivariate analysis. Results Thirteen studies evaluating 615 patients (mean age 52 years, 83% male) and 9,481 segments fulfilled inclusion criteria. Patient-based analyses comparing CCTA versus CCAG for the detection of any CAV (> luminal irregularities) and significant CAV (stenosis ≥50%), showed mean weighted sensitivities of 97% and 94%, specificities of 81% and 92%, a negative predictive value (NPV) of 97% and 99%, a positive predictive value (PPV) of 78% and 67%, and diagnostic accuracies of 88% and 94%, respectively. There was a strong trend toward improved sensitivity (97% vs. 91%, p = 0.06) and NPV (99% vs. 97%, p = 0.06) to detect significant CAV with 64-slice compared with 16-slice CCTA. A patient-based analysis of 64-slice CCTA versus IVUS showed a mean weighted sensitivity and specificity of 81% and 75% to detect CAV (intimal thickening >0.5 mm), whereas the PPV and NPV were 93% and 50%, respectively. Conclusions CCTA using currently available technology is a reliable noninvasive imaging alternative to coronary angiography with an excellent sensitivity, specificity, and NPV for the detection of CAV.
KW - accuracy
KW - cardiac allograft vasculopathy
KW - coronary computed tomography angiography
KW - heart transplantation
KW - transplant vasculopathy
U2 - 10.1016/j.jacc.2014.01.071
DO - 10.1016/j.jacc.2014.01.071
JO - Journal of the American College of Cardiology
JF - Journal of the American College of Cardiology


About: Common Law Admission Test for postgraduate law programmes commonly known as CLAT PG is a gateway for admissions to Master of Laws(LLM) programs in 19 National Law Universities (NLUs). In 2001, CLAT PG exam was conducted by Rajiv Gandhi National University of Law (RGNUL), Patiala. The CLAT PG 2019 scores are used by other private law colleges across the country and Public Sector Undertakings for admissions and recruitment respectively.
Organizing Authority: CLAT Exam is conducted on a rotational basis by each National Law Universities every year. The eleventh CLAT 2019 is organized by National Law University Odisha, Cuttack (NLUO).
Admission: The Common Law Admission Test (CLAT) PG is a centralized test for admission to 19 National Law Universities in India for admissions in post-graduate Law courses.
Exam: CLAT PG 2019 is a national level law entrance exam conducted every year for screening candidates for as many as 604 seats distributed among the 19 participating NLUs.
Enrollment: More than 40,000 students apply for CLAT exam every year for getting admission to various law colleges in India.
Frequency: The CLAT PG 2019 exam is conducted once in a year in India.
Mode: It is an online based examination.
Time Duration: 2 hours i.e, 120 minutes.
The CLAT PG Exam 2019 will be conducted on 13th May 2019. It is advised that the aspirants should follow the CLAT PG 2019 Important Dates.
Admit Card: The CLAT PG 2019 Admit Card will be released on 20th April 2019.
Examination: CLAT PG 2019 Exam will be conducted on 13th May 2019.
Result: The results will be announced on the official website on 2nd June 2019.
Counselling: Once the results are out, the CLAT PG Counselling 2019 date will be on 1st July 2019.
Qualification: Candidates must have a three-year LLB degree or a three-year integrated LLB degree if equivalent LLB degree from a recognized University.
Minimum Aggregate: 55% for General/ OBC/ SAP, and 50% for SC/ST.
Age limit: There is no upper age limit to apply for CLAT PG 2019 exam.
Nationality: The candidate must be the citizen of India and NRI students can also apply.
To get more details and information regarding the eligibility criteria for CLAT PG 2019.
Availability: The Conducting authority National University of Law Odisha, Cuttack will release the application form for CLAT PG 2019 from 1st January 2019 to 31st March 2019.
Payment: Candidates can register for CLAT PG 2019 by paying the CLAT PG 2019 registration fee of INR 4000 for General category candidates and INR 3500 for SC/ST/BC category candidates which is payable by credit card/debit card or net banking only.
Gender: Male, Female, or Transgender.
Know more details about the CLAT PG 2019 Application form details.
Availability: Candidates who have successfully submitted the CLAT PG 2019 can download the admit card from the official website of CLAT.
Credentials: The CLAT PG 2019 admit card will contain all the details like Candidate's name, roll number, test centre, Test timing, etc.
Know more details about how to access the CLAT PG 2019 admit card.
Mode: CLAT PG 2019 Examination is the Computer-based exam with a duration of 2 hours.
Question type: The CLAT PG 2019 Exam will be containing multiple choice questions having a total of 150 marks. Each question carries 1 mark.
Subjects: Jurisprudence (50 questions), Constitutional Law (50 questions), and Other Subjects (50 questions).
Know more about the detailed and latest exam pattern of CLAT PG 2019 exam.
Prerequisite Knowledge: Candidates must have to be prepared for syllabus of CLAT PG 2019 before appearing in the examination.
Topics: The syllabus of CLAT PG 2019 will be asked from the following areas of law like Constitutional Law, Jurisprudence and other law subjects such as Contract, Torts, Criminal Law, International Law, IPR etc.
Know more about the syllabus for CLAT PG 2019 entrance exam.
Credential: The Candidate needs to enter the registered email ID and password. Candidates are advised to download and take the printout of the result and keep it safe till the admission process ends.
Declaration: The result of CLAT PG 2019 will be declared on 2nd June 2019 at the official website of CLAT PG.
Know more details about the results of CLAT PG 2019.
Commencement: The process of CLAT PG 2019 counselling starts from 1st July 2019.
Seat Allocation: Candidates who are seeking admission to the LLM course, they must have to appear for counselling process for final seat allocation.
Know more about the counselling process for CLAT PG 2019.
The commencement of the online CLAT PG 2019 applications submissions is on 1st January 2019.
The last date for CLAT PG 2019 Online Applications is on 31st March 2019.
The last date to Download the CLAT PG 2019 Admit Card is on the 20th April 2019.
The CLAT PG 2019 exam date is scheduled to be on 13th May 2019.
The CLAT PG authority will declare results on 2nd June 2019.
The qualification standards for CLAT PG 2019 are the base qualification prerequisites that the hopefuls must satisfy.
Chanakya National Law University (CNLU) Patna will begin inviting CLAT PG 2019 application for admissions to five-year integrated and two-year postgraduate law degree programs.
Candidates can fill application form of CLAT PG 2019 in only online mode after they have registered themselves for the Common Law Admission Test.
The application form for CLAT PG 2019 will be available from 1st January 2019 to 31st March 2019.
The candidates can pay the application fee via online as well as offline mode.
The application forms for CLAT PG 2019 will be available online at the official website of CLAT PG 2019 from 1st January 2019.
The applicants are advised to go through eligibility criteria before filling the application form.
They need to be ready with scanned images of photograph and signature, SC/ST/SAP certificates (if applicable) and domicile certificates (if applicable) as well.
The applicants should apply before the last date of application which is 31st March 2019.
To apply for the test, the candidates are required to get themselves registered. To register, the candidates are required to enter their Name, Father's name, Mother's name, Date of birth, Email ID, the Mobile number in the registration form.
The candidates can download their application form along with the fee payment details.
The candidates are advised to take a printout of the application form for future use.
The candidates must keep their Login credentials i.e. the CAPS User ID and Password safe.
With these login credentials, the candidates will be able to check their application status, download their hall ticket and also check the result.
The admit card for CLAT PG 2019 will be available online from 20th April 2019.
The candidates can download it from the official website of CLAT PG 2019 and are advised to take a printout as a soft copy of the CLAT PG 2019 will come handy.
The candidates can download the admit cards by logging into your registered accounts using the login id and password generated while applying.
The candidates are advised to take a print out of the same for future correspondences.
CLAT PG 2019 Hall Ticket/Admit Card will mention the PG exam details including the name of the appearing candidate, venue, and timing. In case of any discrepancy, you can bring it to notice of exam authorities, at the earliest.
Exam mode: The CLAT PG 2019 exam will be conducted Offline in pen-paper mode.
Exam duration: The time duration for CLAT PG 2019 exam will be 2 hours.
Questions: There will be 50 multiple choice questions and other will be subjective type questions.
Total Marks: The CLAT PG 2019 entrance examination will be of total 150 marks. Out of 75 marks, 50 marks are for multiple choice questions and 100 marks are for subjective type questions.
Marking Scheme: For each incorrect answer or un-attempted question, ¼ marks will be deducted.
Language: The CLAT PG 2019 examination will be conducted in the English language.
The examination syllabus will be prepared by the examination authority.
The syllabus of CLAT PG changes every year.
The syllabus of CLAT PG 2019 will cover the topics of GK & current affairs, Legal aptitude, Elementary Mathematics, Constitutional laws, etc.
The Syllabus of CLAT PG comprises of questions on Law of Contracts, Law of Torts, Criminal Law, International Law, Family Law, Property Law, Intellectual Property Law, etc. will be Multiple Choice Questions.
The Results for CLAT PG 2019 will be announced on the 2nd June 2019.
The candidates can go to the official website of CLAT PG 2019 for checking their Results.
There are 17 NLUs that will be accepting the CLAT PG 2019 scores for admission to the 604 LLM seats.
The candidates scoring the required cutoff scores will be eligible for the counselling rounds of the participating Institutes.
The conunselling procedure of CLAT PG 2019 will start from 1st July 2019.
On scoring the required CLAT PG cutoff scores, the candidates will be shortlisted for the admission process.
I want to get admission in NMIMS. I am expecting 95 score in CLAT PG 2018.Will I get the admission?
You have good chances of getting admission in NMIMS through CLAT PG score.
But it will also depend on your rank so keep yourself updated.
Click here to know about the CLAT PG results and other details.
How much score is required in CLAT PG 2018 to get into NLS?
You need to score above 145 in order to get admission in NLUs through CLAT PG 2018.
I have completed LLB with 52 % marks. Am I Eligible to appear for CLAT PG?
If you belong from the reserved category(SC/ST) then you will be eligible for CLAT PG as minimum marks required for SC/ST candidate is 50 %.
Click here to know about CLAT PG eligibility.
What is the Age limit to apply for CLAT PG?
There is no upper age limit to appear for CLAT PG.
Click here to know more about CLAT PG eligibility criteria.


text:
<?php
defined('BASEPATH') OR exit('No direct script access allowed');

/*
| -------------------------------------------------------------------------
| URI ROUTING
| -------------------------------------------------------------------------
| This file lets you re-map URI requests to specific controller functions.
|
| Typically there is a one-to-one relationship between a URL string
| and its corresponding controller class/method. The segments in a
| URL normally follow this pattern:
|
|	example.com/class/method/id/
|
| In some instances, however, you may want to remap this relationship
| so that a different class/function is called than the one
| corresponding to the URL.
|
| Please see the user guide for complete details:
|
|	http://codeigniter.com/user_guide/general/routing.html
|
| -------------------------------------------------------------------------
| RESERVED ROUTES
| -------------------------------------------------------------------------
|
| There are three reserved routes:
|
|	$route['default_controller'] = 'welcome';
|
| This route indicates which controller class should be loaded if the
| URI contains no data. In the above example, the "welcome" class
| would be loaded.
|
|	$route['404_override'] = 'errors/page_missing';
|
| This route will tell the Router which controller/method to use if those
| provided in the URL cannot be matched to a valid route.
|
|	$route['translate_uri_dashes'] = FALSE;
|
| This is not exactly a route, but allows you to automatically route
| controller and method names that contain dashes. '-' isn't a valid
| class or method name character, so it requires translation.
| When you set this option to TRUE, it will replace ALL dashes in the
| controller and method URI segments.
|
| Examples:	my-controller/index	-> my_controller/index
|		my-controller/my-method	-> my_controller/my_method
*/
$route['default_controller'] = 'home';
$route['404_override'] = '';
$route['translate_uri_dashes'] = FALSE;
$route['assets/(:any)'] = 'assets/$1';
$route['signup'] = 'auth/userSignup';
$route['user-login-local'] = 'auth/userLogin';
$route['user-login-social'] = 'auth/userLoginSocial';
$route['logout'] = 'auth/userLogout';
$route['user-profile'] = 'auth/userProfile';
$route['search'] = 'home/search';
$route['activate'] = 'auth/userActivate';
$route['activate-user'] = 'auth/activateProfile';
$route['update-password'] = 'auth/updatePassword';
$route['update-profile'] = 'auth/profileUpdate';
$route['contactus/post'] = 'home/contactPost';
$route['([a-z0-9-]+)/([a-z0-9-]+)/([a-z-]+)'] = 'home/search';
$route['([a-z0-9-]+)/([a-z0-9-]+)/([a-z0-9-]+-[0-9]{1,10})/([a-z-]+)'] = 'home/schoolDetail/$1-$2';
//$route['([a-z0-9-]+)/([a-z0-9-]+)/([a-z-]+)'] = 'home/schoolDetail2/$1';
$route['download'] = 'download/downloadApp';
$route['permlink'] = 'home/getLocation';
$route['list-your-school'] = 'home/listSchool';
$route['save-school'] = 'home/saveSchool';
$route['post-your-requirement'] = 'home/postRequirement';
$route['save-requirement'] = 'home/saveRequirement';
$route['post-rating-review'] = 'home/userRatingReview';
$route['about-us'] = 'home/aboutUs';
$route['career'] = 'home/joinUs';
$route['our-team'] = 'home/ourTeam';
$route['contact-us'] = 'home/contactUs';
$route['privacy'] = 'home/privacy';
$route['terms'] = 'home/terms';
$route['share-social-login'] = 'home/socialLoginData';
$route['contactus/showcontact'] = 'home/showSchoolContact';

redpajama_set_name: RedPajamaGithub


text:
// Package flowgraph for scalable asynchronous development.
// Build systems out of hubs interconnected by streams of data.
// https://github.com/vectaport/flowgraph/wiki
package flowgraph

import (
	"github.com/vectaport/fgbase"

	"flag"
	"fmt"
	"log"
)

type Error string

func (e Error) Error() string {
	return string(e)
}

// End of flow. Transmitted when end-of-file occurs, and promises no more
// data to follow.
const EOF = Error("EOF")

var flatDot = false

// ParseFlags parses the command line flags for this package
func ParseFlags() {
	flag.BoolVar(&flatDot, "flatdot", false, "flatten dot output")
	fgbase.ConfigByFlag(map[string]interface{}{"trace": "V"})
	fgbase.TraceStyle = fgbase.New
}

// Flowgraph interface for flowgraphs assembled out of hubs and streams
type Flowgraph interface {

	// Title returns the title of this flowgraph
	Title() string

	// Hub returns a hub by index
	Hub(n int) Hub

	// Stream returns a stream by index
	Stream(n int) Stream

	// NumHub returns the number of hubs
	NumHub() int

	// NumStream returns the number of streams
	NumStream() int

	// NewHub returns a new unconnected hub
	NewHub(name string, code HubCode, init interface{}) Hub

	// NewStream returns a new unconnected stream
	NewStream(name string) Stream

	// NewGraphHub returns a hub with a flowgraph inside
	NewGraphHub(name string, code HubCode) GraphHub

	// FindHub finds a hub by name
	FindHub(name string) Hub

	// FindStream finds a stream by name
	FindStream(name string) Stream

	// Connect connects two hubs via named (string) or indexed (int) ports
	Connect(
		upstream Hub, upstreamPort interface{},
		dnstream Hub, dnstreamPort interface{}) Stream

	// ConnectInit connects two hubs via named (string) or indexed (int) ports
	// and sets an initial value for flow
	ConnectInit(
		upstream Hub, upstreamPort interface{},
		dnstream Hub, dnstreamPort interface{},
		init interface{}) Stream

	// Run runs the flowgraph
	Run()
}

type flowgraph struct {
	title        string
	hubs         []Hub
	streams      []Stream
	nameToHub    map[string]Hub
	nameToStream map[string]Stream
}

// New returns a titled flowgraph
func New(title string) Flowgraph {
	nameToHub := make(map[string]Hub)
	nameToStream := make(map[string]Stream)
	fg := flowgraph{title, nil, nil, nameToHub, nameToStream}
	return &fg
}

// Title returns the titleof this flowgraph
func (fg *flowgraph) Title() string {
	return fg.title
}

// Hub returns a hub by index
func (fg *flowgraph) Hub(n int) Hub {
	return fg.hubs[n]
}

// Stream returns a stream by index
func (fg *flowgraph) Stream(n int) Stream {
	return fg.streams[n]
}

// NumHub returns the number of hubs
func (fg *flowgraph) NumHub() int {
	return len(fg.hubs)
}

// NumStream returns the number of hubs
func (fg *flowgraph) NumStream() int {
	return len(fg.streams)
}

type fgTransformer struct {
	fg *flowgraph
	t  Transformer
}

func (f *fgTransformer) String() string {
	return fgbase.String(f.t)
}

type fgRetriever struct {
	fg *flowgraph
	r  Retriever
}

func (f *fgRetriever) String() string {
	return fgbase.String(f.r)
}

type fgTransmitter struct {
	fg *flowgraph
	t  Transmitter
}

func (f *fgTransmitter) String() string {
	return fgbase.String(f.t)
}

// NewHub returns a new unconnected hub
func (fg *flowgraph) NewHub(name string, code HubCode, init interface{}) Hub {

	var n fgbase.Node

	switch code {

	// User Hubs
	case Retrieve:
		if _, ok := init.(Retriever); !ok {
			panic(fmt.Sprintf("Hub with Retrieve code not given Retriever for init %T(%+v)", init, init))
		}
		n = fgbase.MakeNode(name, nil, nil, retrieveRdy, retrieveFire)
		init = &fgRetriever{fg, init.(Retriever)}

	case Transmit:
		if _, ok := init.(Transmitter); !ok {
			panic(fmt.Sprintf("Hub with Transmit code not given Transmitter for init %T(%+v)", init, init))
		}
		n = fgbase.MakeNode(name, nil, nil, nil, transmitFire)
		init = &fgTransmitter{fg, init.(Transmitter)}

	case AllOf:
		if _, ok := init.(Transformer); !ok {
			panic(fmt.Sprintf("Hub with AllOf code not given Transformer for init %T(%+v)", init, init))
		}
		n = fgbase.MakeNode(name, nil, nil, nil, allOfFire)
		init = &fgTransformer{fg, init.(Transformer)}

	case OneOf:
		if _, ok := init.(Transformer); !ok {
			panic(fmt.Sprintf("Hub with OneOf code not given Transformer for init %T(%+v)", init, init))
		}
		n = fgbase.MakeNode(name, nil, nil, oneOfRdy, oneOfFire)
		init = &fgTransformer{fg, init.(Transformer)}

	// Control Hubs
	case Wait:
		if _, ok := init.(Transmitter); ok {
			init = &fgTransmitter{fg, init.(Transmitter)}
		}
		n = fgbase.MakeNode(name, nil, nil, waitRdy, waitFire)

	case Select:
		n = fgbase.MakeNode(name, nil, nil, fgbase.SteervRdy, selectFire)

	case Steer:
		n = fgbase.MakeNode(name, nil, nil, fgbase.SteervRdy, fgbase.SteervFire)

	case Cross:
		n = fgbase.MakeNode(name, nil, nil, crossRdy, crossFire)

	// Data Hubs
	case Array:
		n = fgbase.MakeNode(name, nil, []*fgbase.Edge{nil}, nil, fgbase.ArrayFire)

	case Constant:
		n = fgbase.MakeNode(name, nil, []*fgbase.Edge{nil}, nil, fgbase.ConstFire)

	case Pass:
		n = fgbase.MakeNode(name, []*fgbase.Edge{nil}, []*fgbase.Edge{nil}, nil, nil)

	case Split:
		n = fgbase.MakeNode(name, nil, []*fgbase.Edge{nil}, nil, splitFire)

	case Join:
		n = fgbase.MakeNode(name, nil, []*fgbase.Edge{nil}, nil, joinFire)

	case Sink:
		if init != nil {
			if _, ok := init.(Sinker); !ok {
				panic(fmt.Sprintf("Hub with Sink code not given Sinker for init %T(%+v)", init, init))
			}
		}
		n = fgbase.MakeNode(name, []*fgbase.Edge{nil}, nil, nil, fgbase.SinkFire)

	// Math and Logic Hubs
	case Add:
		n = fgbase.MakeNode(name, []*fgbase.Edge{nil, nil}, []*fgbase.Edge{nil}, nil, fgbase.AddFire)

	case Subtract:
		n = fgbase.MakeNode(name, []*fgbase.Edge{nil, nil}, []*fgbase.Edge{nil}, nil, fgbase.SubFire)

	case Multiply:
		n = fgbase.MakeNode(name, []*fgbase.Edge{nil, nil}, []*fgbase.Edge{nil}, nil, fgbase.MulFire)

	case Divide:
		n = fgbase.MakeNode(name, []*fgbase.Edge{nil, nil}, []*fgbase.Edge{nil}, nil, fgbase.DivFire)

	case Modulo:
		n = fgbase.MakeNode(name, []*fgbase.Edge{nil, nil}, []*fgbase.Edge{nil}, nil, fgbase.ModFire)

	case And:
		n = fgbase.MakeNode(name, []*fgbase.Edge{nil, nil}, []*fgbase.Edge{nil}, nil, andFire)

	case Or:
		n = fgbase.MakeNode(name, []*fgbase.Edge{nil, nil}, []*fgbase.Edge{nil}, nil, orFire)

	case Not:
		n = fgbase.MakeNode(name, []*fgbase.Edge{nil}, []*fgbase.Edge{nil}, nil, notFire)

	case Shift:
		n = fgbase.MakeNode(name, []*fgbase.Edge{nil, nil}, []*fgbase.Edge{nil}, nil, shiftFire)

	default:
		log.Panicf("Unexpected Hub code NewHub:  %s\n", code)
	}
	if n.Aux == nil {
		n.Aux = init
	}

	h := &hub{&n, fg, code}
	n.Owner = h
	fg.hubs = append(fg.hubs, h)
	fg.nameToHub[name] = h
	return h
}

// NewStream returns a new unconnected stream
func (fg *flowgraph) NewStream(name string) Stream {
	e := fgbase.MakeEdge(name, nil)
	s := &stream{&e, fg}
	fg.streams = append(fg.streams, s)
	fg.nameToStream[name] = s
	return s
}

// NewGraphHub returns a hub with an internal flowgraph
func (fg *flowgraph) NewGraphHub(name string, code HubCode) GraphHub {
	newfg := New(name + "_fg")

	var n fgbase.Node

	switch code {
	case While:
		n = fgbase.MakeNode(name, nil, nil, nil, whileFire)
	case During:
		n = fgbase.MakeNode(name, nil, nil, nil, duringFire)
	case Graph:
		n = fgbase.MakeNode(name, nil, nil, nil, graphFire)
	default:
		log.Panicf("Unexpected HubCode for NewGraphHub:  %v\n", code)
	}
	gh := &graphhub{&hub{&n, fg, code}, newfg, nil, nil}
	n.Owner = gh
	fg.hubs = append(fg.hubs, gh)
	fg.nameToHub[name] = gh
	return gh
}

// FindHub finds a hub by name
func (fg *flowgraph) FindHub(name string) Hub {
	return fg.nameToHub[name]
}

// FindStream finds a Stream by name
func (fg *flowgraph) FindStream(name string) Stream {
	return fg.nameToStream[name]
}

// Connect connects two hubs via named (string) or indexed (int) ports
func (fg *flowgraph) Connect(
	upstream Hub, upstreamPort interface{},
	dnstream Hub, dnstreamPort interface{}) Stream {
	return fg.connectInit(upstream, upstreamPort, dnstream, dnstreamPort, nil)
}

// ConnectInit connects two hubs via named (string) or indexed (int) ports
// and sets an initial value for flow
func (fg *flowgraph) ConnectInit(
	upstream Hub, upstreamPort interface{},
	dnstream Hub, dnstreamPort interface{},
	init interface{}) Stream {
	return fg.connectInit(upstream, upstreamPort, dnstream, dnstreamPort, init)
}

// connectInit connects two hubs via named (string) or indexed (int) ports
// and sets an initial value for flow
func (fg *flowgraph) connectInit(
	upstream Hub, upstreamPort interface{},
	dnstream Hub, dnstreamPort interface{},
	init interface{}) Stream {

	checkInternalHub(fg, upstream)
	checkInternalHub(fg, dnstream)

	var us Stream
	var usok bool
	switch v := upstreamPort.(type) {
	case string:
		us, usok = upstream.Result(v), !upstream.Empty()
		if !usok {
			upstream.Panicf("No result port \"%s\" found on Hub \"%s\"\n", v, upstream.Name())
		}
	case int:
		usok = v >= 0 && v < upstream.NumResult()
		if !usok {
			upstream.Panicf("No result port %d found on Hub \"%s\"\n", v, upstream.Name())
		}
		us = upstream.Result(v)
	default:
		upstream.Panicf("Need string or int to specify port on upstream Hub \"%s\"\n", upstream.Name())
	}

	var ds Stream
	var dsok bool
	switch v := dnstreamPort.(type) {
	case string:
		ds, dsok = dnstream.Source(v), !dnstream.Empty()
		if !dsok {
			dnstream.Panicf("No source port \"%s\" found on Hub \"%s\"\n", v, dnstream.Name())
		}
	case int:
		dsok = v >= 0 && v < dnstream.NumSource()
		if !dsok {
			upstream.Panicf("No source port %d found on Hub \"%s\"\n", v, dnstream.Name())
		}
		ds = dnstream.Source(v)
	default:
		dnstream.Panicf("Need string or int to specify port on downstream Hub \"%s\"\n", dnstream.Name())
	}

	if us.Empty() && ds.Empty() {
		s := fg.NewStream("")
		s.Init(init)
		fg.streams = append(fg.streams, s)
		upstream.SetResult(upstreamPort, s)
		dnstream.SetSource(dnstreamPort, s)
		return s
	}
	if us.Empty() {
		upstream.SetResult(upstreamPort, ds)
		return ds
	}
	if ds.Empty() {
		dnstream.SetSource(dnstreamPort, us)
		return us
	}
	/*
		upstream.Panicf("Unexpected that with two ports to connect (%s:%v(%s) and %s:%v(%s() that they both are already connected to another stream as well",
			upstream.Name(), upstreamPort, us.Name(), dnstream.Name(), dnstreamPort, ds.Name())
	*/
	return nil
}

// Run runs the flowgraph
func (fg *flowgraph) Run() {
	fg.run()
}

// checkInternalHub checks that the flowgraph associated with a Hub matches
func checkInternalHub(fg Flowgraph, h Hub) {
	if h == nil {
		return
	}
	fgknown := fg
	fgtest := h.Flowgraph()
	if fgknown != fgtest {
		panic(fmt.Sprintf("Hub %q created by flowgraph %q (expected it to be created by flowgraph %q)",
			h.Name(), fgtest.Title(), fgknown.Title()))
	}
}

// checkExternalHub checks that the flowgraph associated with a Hub doesn't match
func checkExternalHub(fg Flowgraph, h Hub) {
	if h == nil {
		return
	}
	fgknown := fg
	fgtest := h.Flowgraph()
	if fgknown == fgtest {
		panic(fmt.Sprintf("External Hub %q created by same flowgraph %q",
			h.Name(), fgtest.Title()))
	}
}

// checkInternalStream checks that the flowgraph associated with a Stream matches
func checkInternalStream(fg Flowgraph, s Stream) {
	if s == nil {
		return
	}
	fgknown := fg
	fgtest := s.Flowgraph()
	if fgknown != fgtest {
		panic(fmt.Sprintf("Stream %q created by flowgraph %q (expected it to be created by flowgraph %q)",
			s.Name(), fgtest.Title(), fgknown.Title()))
	}
}

// checkExternalStream checks that the flowgraph associated with a Stream doesn't match
func checkExternalStream(fg Flowgraph, s Stream) {
	if s == nil {
		return
	}
	fgknown := fg
	fgtest := s.Flowgraph()
	if fgknown == fgtest {
		panic(fmt.Sprintf("External Stream %q created by same flowgraph %q",
			s.Name(), fgtest.Title()))
	}
}

// flatten connects GraphHub external ports to internal dangling streams
func (fg *flowgraph) flatten() []*fgbase.Node {
	if flatDot {
		fgbase.DotOutput = true
	}
	nodes := make([]*fgbase.Node, 0)
	for _, v := range fg.hubs {
		if gv, ok := v.(GraphHub); ok && (flatDot || !fgbase.DotOutput) {
			nodes = gv.(*graphhub).flatten(nodes)
			if fgbase.DotOutput {
				nodes = append(nodes, v.Base().(*fgbase.Node))
				v.Base().(*fgbase.Node).SetDotAttr("style=\"dashed\"")
			} else {
				for i := 0; i < v.NumSource(); i++ {
					v.Source(i).Base().(*fgbase.Edge).Disconnect(v.Base().(*fgbase.Node))
				}
				for i := 0; i < v.NumResult(); i++ {
					v.Result(i).Base().(*fgbase.Edge).Disconnect(v.Base().(*fgbase.Node))
				}
			}
		} else {
			nodes = append(nodes, v.Base().(*fgbase.Node))
		}
	}
	if fgbase.TraceLevel >= fgbase.V {
		fmt.Printf("\n")
		for _, v := range nodes {
			fmt.Printf("// %s\n", v)
		}
		fmt.Printf("\n")
	}
	return nodes
}

// run runs the flowgraph
func (fg *flowgraph) run() {

	nodes := fg.flatten()
	fgbase.RunGraph(nodes)
}

func allOfFire(n *fgbase.Node) error {
	var a []interface{}
	a = make([]interface{}, len(n.Srcs))
	t := n.Aux.(*fgTransformer).t
	fg := n.Aux.(*fgTransformer).fg
	eofflag := false
	for i, _ := range a {
		a[i] = n.Srcs[i].SrcGet()
		if v, ok := a[i].(error); ok && v == EOF {
			n.Srcs[i].Flow = false
			eofflag = true
		}
	}
	x, _ := t.Transform(&hub{n, fg, AllOf}, a)
	for i, _ := range x {
		if eofflag {
			n.Dsts[i].DstPut(EOF)
		} else {
			if x[i] != nil {
				n.Dsts[i].DstPut(x[i])
			}
		}
	}
	if eofflag {
		return EOF
	} else {
		return nil
	}

}

func oneOfRdy(n *fgbase.Node) bool {
	r := false
	for _, v := range n.Srcs {
		if v.SrcRdy(n) {
			r = true
			break
		}
	}
	if !r {
		return false
	}
	for _, v := range n.Dsts {
		if !v.DstRdy(n) {
			return false
		}
	}
	return true
}

func oneOfFire(n *fgbase.Node) error {
	var a []interface{}
	a = make([]interface{}, len(n.Srcs))
	t := n.Aux.(*fgTransformer).t
	fg := n.Aux.(*fgTransformer).fg
	eofflag := false
	for i, _ := range a {
		if n.Srcs[i].SrcRdy(n) {
			a[i] = n.Srcs[i].SrcGet()
			if v, ok := a[i].(error); ok && v == EOF {
				n.Srcs[i].Flow = false
				eofflag = true
			}
			break
		}
	}
	x, _ := t.Transform(&hub{n, fg, OneOf}, a)
	for i, _ := range x {
		if eofflag {
			n.Dsts[i].DstPut(EOF)
		} else {
			if x[i] != nil {
				n.Dsts[i].DstPut(x[i])
			}
		}
	}
	if eofflag {
		return EOF
	} else {
		return nil
	}

}

func retrieveRdy(n *fgbase.Node) bool {
	r := n.DefaultRdyFunc()
	return r
}

func retrieveFire(n *fgbase.Node) error {
	retriever := n.Aux.(*fgRetriever).r
	fg := n.Aux.(*fgRetriever).fg
	v, err := retriever.Retrieve(&hub{n, fg, Retrieve})
	n.Dsts[0].DstPut(v)
	return err
}

func transmitFire(n *fgbase.Node) error {
	transmitter := n.Aux.(*fgTransmitter).t
	fg := n.Aux.(*fgTransmitter).fg
	err := transmitter.Transmit(&hub{n, fg, Transmit}, n.Srcs[0].SrcGet())
	return err
}

type waitStruct struct {
	Request  int
	Transmit *fgTransmitter
}

func waitRdy(n *fgbase.Node) bool {
	ns := n.SrcCnt()
	nr := n.DstCnt()
	for i := 0; i < nr; i++ {
		if !n.Dsts[i].DstRdy(n) {
			return false
		}
	}

	ws, init := n.Aux.(waitStruct)
	if !init {
		tr, _ := n.Aux.(*fgTransmitter)
		ws = waitStruct{Request: fgbase.ChannelSize - 1, Transmit: tr}
		n.Aux = ws
		elocal := n.Srcs[ns-1]
		usnode := elocal.SrcNode(0)
		if usnode != nil {
			for i := 0; i < len(usnode.Dsts); i++ {
				if usnode.Dsts[i].Same(elocal) {
					usnode.Dsts[i].RdyCnt += fgbase.ChannelSize - 1
					break
				}
			}
		}
	}

	for i := 0; i < ns-1; i++ {
		if !n.Srcs[i].SrcRdy(n) {
			return false
		}
	}
	if ws.Request > 0 {
		ws.Request--
		// n.Srcs[ns-1].Flow = false
		n.Aux = ws
		return true
	}

	rdy := n.Srcs[ns-1].SrcRdy(n)
	if rdy {
		n.Srcs[ns-1].Flow = true
	}
	return rdy
}

func waitFire(n *fgbase.Node) error {
	ws := n.Aux.(waitStruct)
	if ws.Transmit != nil {
		transmitter := ws.Transmit.t
		fg := ws.Transmit.fg
		err := transmitter.Transmit(&hub{n, fg, Transmit}, n.Srcs[0].SrcGet())
		if err != nil {
			n.LogError("Error in waitFire use of transmitter:  %s\n", err)
		}
	}

	ns := n.SrcCnt()
	for i := 0; i < ns-1; i++ {
		n.Dsts[i].DstPut(n.Srcs[i].SrcGet())
	}
	return nil
}

func selectFire(n *fgbase.Node) error {
	n.Panicf("Select HubCode still needs implementation.")
	return nil
}

func ranksz(n *fgbase.Node) int {
	return n.SrcCnt() / 2
}

type crossStruct struct {
	in  int
	out int
}

func crossRdy(n *fgbase.Node) bool {
	cs, init := n.Aux.(crossStruct)
	if !init {
		cs = crossStruct{}
	}

	numrank := ranksz(n)

	f := func(offset int) bool {
		for i := 0; i < numrank; i++ {
			if !n.Srcs[i+offset].SrcRdy(n) {
				return false
			}
		}
		return true
	}
	left := f(0)
	right := f(numrank)

	steerDir := func() int {
		v := n.Srcs[numrank*cs.in].SrcGet()
		if b, ok := v.(Breaker); ok {
			if b.Break() {
				return 0
			}
			return 1
		}
		if fgbase.IsZero(v) {
			return 0
		}
		return 1
	}

	if left || right {
		if cs.in == 0 {
			if right {
				cs.in = 1
			} else {
				cs.in = 0
			}
		} else {
			if left {
				cs.in = 0
			} else {
				cs.in = 1
			}
		}
		notin := 0
		if cs.in == 0 {
			notin = numrank
		}
		for i := 0; i < numrank; i++ {
			n.Srcs[i+notin].Flow = false
		}

		cs.out = steerDir()
		rdy := n.Dsts[cs.out].DstRdy(n)
		if false && rdy {
			n.Tracef("STEERDIR IS %d\n", cs.out)
		}
		n.Aux = cs
		return rdy
	}

	return false
}

func crossFire(n *fgbase.Node) error {

	numrank := ranksz(n)
	cs := n.Aux.(crossStruct)

	if cs.out == 0 {
		for i := 0; i < numrank; i++ {
			v := n.Srcs[cs.in*numrank+i].SrcGet()
			if b, ok := v.(Breaker); ok {
				b.Clear()
			}
			n.Dsts[i].DstPut(v)
		}
	} else {
		for i := 0; i < numrank; i++ {
			v := n.Srcs[cs.in*numrank+i].SrcGet()
			if b, ok := v.(Breaker); ok {
				b.Clear()
			}
			n.Dsts[numrank+i].DstPut(v)
		}
	}
	return nil
}

func splitFire(n *fgbase.Node) error {
	n.Panicf("Split HubCode still needs implementation.")
	return nil
}

func joinFire(n *fgbase.Node) error {
	n.Panicf("Join HubCode still needs implementation.")
	return nil
}

func whileFire(n *fgbase.Node) error {
	n.Panicf("While loop still needs flattening.")
	return nil
}

func duringFire(n *fgbase.Node) error {
	n.Panicf("During loop still needs flattening.")
	return nil
}

func graphFire(n *fgbase.Node) error {
	n.Panicf("Graph still needs flattening.")
	return nil
}

func andFire(n *fgbase.Node) error {
	n.Panicf("And HubCode still needs implementation.")
	return nil
}

func orFire(n *fgbase.Node) error {
	n.Panicf("Or HubCode still needs implementation.")
	return nil
}

func notFire(n *fgbase.Node) error {
	n.Panicf("Not HubCode still needs implementation.")
	return nil
}

func shiftFire(n *fgbase.Node) error {
	n.Panicf("Shift HubCode still needs implementation.")
	return nil
}

func min(a, b int) int {
	if a < b {
		return a
	}
	return b
}

func max(a, b int) int {
	if a > b {
		return a
	}
	return b
}