est une série de light novel japonaise écrite Myōjin Katō et illustrée par Sao Mizuno. Elle est initialement publiée sur le site de romans en ligne Shōsetsuka ni narō, depuis . Ses droits sont ensuite acquis par Fujimi Shobo, qui édite la série de light novels depuis  sous le label Fujimi Fantasia Bunko. Une adaptation en manga dessinée par Misuho Kotobaest prépubliée dans le Monthly Big Gangan de Square Enix depuis . Une adaptation en série d'animation produite par les stuidos Silver Link et Blade est diffusée entre le  et le . Hors de l'Asie, cette diffusion est assurée par Crunchyroll.

Synopsis
Souffrant d'ennui et de solitude, Varvatos, le plus puissant des Rois Démons, décide de se réincarner en tant que personnage le plus banal qui soit, afin de vivre une vie normale dans laquelle il pourra se faire des amis.

Personnages

Productions et supports

Light novel
La série de light novel est écrite par Myōjin Katō et illustrée par Sao Mizuno. Elle est initialement publiée en ligne à partir d' sur le site de romans en ligne Shōsetsuka ni narō. Ses droits sont ensuite acquis par Fujimi Shobo, qui publie dix volumes depuis  sous le label Fujimi Fantasia Bunko.

|}

Manga
Une adaptation en manga dessinée par Misuho Kotoba est prépubliée dans le magazine Monthly Big Gangan de Square Enix depuis le . Sept volumes reliés sont publiés au .

|}

Anime
Une adaptation en série d'animation est annoncée lors de la  le . La série télévisée est produite par Silver Link et  et réalisée par Mirai Minato, avec Michiko Yokote écrivant les scripts, Takayuki Noguchi concevant les personnages et Takeshi Nakatsuka composant la musique. Elle est diffusée entre le  et le  sur AT-X, Tokyo MX, BS NTV, KBS Kyoto et SUN. Le thème d'ouverture intitulé Be My Friend!!! est interprété par Ayaka Ōhashi, tandis que le thème de fin est Reincarnation, interprété par ChouCho. Crunchyroll diffuse la série hors de l'Asie.

Liste des épisodes

|}

Notes et références

Notes

Références

Œuvres

Light novel

Manga

Liens externes
  sur Shōsetsuka ni Narō

Roman publié sur Shōsetsuka ni narō
Light novel
Seinen manga
Manga paru dans le Monthly Big Gangan
Animation réalisée par Silver Link
Série diffusée sur Crunchyroll

The Greatest Demon Lord Is Reborn as a Typical Nobody


Hilma Natalia Granqvist (Sipoo, 17 de julho de 1890 – Helsinque, 25 de fevereiro de 1972) foi uma antropóloga finlandesa de língua sueca que conduziu longos estudos de campo sobre palestinos. Ela foi aluna de Edvard Westermarck.

Estudos sobre a aldeia Palestina
Na década de 1920, Granqvist chegou à vila de Artas, nos arredores de Belém, no então Mandato Britânico da Palestina, como parte de sua pesquisa sobre as mulheres do Antigo Testamento. Ela tinha ido para a Palestina "para encontrar os ancestrais judeus das Escrituras". O que ela encontrou, em vez disso, foi um povo palestino com uma cultura e modo de vida distintos. Assim, mudou o foco de sua pesquisa para uma investigação completa dos costumes, hábitos e formas de pensar das pessoas daquela aldeia. Granqvist acabou ficando até 1931 documentando todos os aspectos da vida da aldeia. Ao fazê-lo, ela tirou centenas de fotografias."

Exemplo de música de casamento, gravada por Granqvist
"Deus sabe que nossa roupa hoje
Cem vestes 'reais' que cortamos
Para a noiva a quem estamos noivos.
Deus sabe - hoje é a nossa roupa
Um vestido verde e um 'real' [malak] que compramos
Para a noiva a quem estamos noivos!
Dez jaquetas [taqsireh] que compramos
Para os amados, a fim de apaziguá-la"

(Granqvist: Condições de casamento em uma vila palestina, vol. 2 (1931), p. 42.)

Obras publicadas

  (em inglês)
 1931: Marriage conditions in a Palestinian village I. Helsingfors: Societas Scientiarum Fennica (em inglês)
 1935: Marriage conditions in a Palestinian village II. Helsingfors: Societas Scientiarum Fennica (em inglês)
 1947: Birth and childhood among the Arabs: studies in a Muhammadan village in Palestine. Helsingfors; Söderström. (Reprinted 1975, New York: AMS Press. ISBN 0-404-57447-5) (em inglês)
 1950: Child problems among the Arabs: Studies in a Muhammadan village in Palestine. Helsingfors : Söderström (em inglês)
 1965: Muslim death and burial: Arab customs and traditions studies in a village in Jordan. Helsingfors: Societas Scientiarum Fennica (em inglês)
 1981: Portrait of a Palestinian village: The photographs of Hilma Granqvist. Editor Karen Seger, with a foreword by Shelagh Weir. London: Third World Centre for Research and Publishing. ISBN 0-86199-006-4 (em inglês)

Bibliografia

 Naili, Falestin (2007): "L'oeuvre de Hilma Granqvist: L'Orient imaginaire confronté à la réalité d'un village palestinien." Revue d'Etudes Palestiniennes, 105 (em inglês), pp. 74–84.
 Naili, Falestin (2008): "Hilma Granqvist, Louise Baldensperger et la 'tradition' de rencontre au village palestinien d'Artas." Civilisations 57 (em francês), pp. 126–138.
 Sirignano, Rosanna (2012): "Mother and Child in Palestine: the Artas material in Hilma Granqvist's Nachlass at the Palestine Exploration Fund." Studi Interculturali 3/2013 (em inglês), pp. 159–181. Mediterránea, Centro di Studi Interculturali, Trieste. ISBN 978-1-291-59885-8
 Weir, Shelagh (1975): "Hilma Granqvist and Her Contribution to Palestine Studies." Bulletin of the  British Society for Middle Eastern Studies, 2, 1 (em inglês), pp. 6–13.
 Weir, Shelagh (2012): "A pioneering anthropologist." Palestine, The Middle East in London, vol 8, No. 4 (em inglês), Abril–Maio 2012, pp. 16–17.
 Willman, Jarkko (1997): Ideal och verklighet: Hilma Granqvists studier av "Kvinnorna i Gamla testamentet" åren 1921–1925. Åbo: Åbo Akademi. ISBN 952-12-0033-2. (em sueco)

Ligações externas
 Biografia. Universidade de Helsinque. (em inglês)
 Hilma Granqvist. 375 humanistas 6.4.2015. Universidade de Helsinque. (em inglês)
 Arquivos de Hilma Granqvist (em sueco).

Mortos em 1972
Nascidos em 1890
!Mais Teoria da História na Wiki (Wikiconcurso de edição)

Hilma Granqvist


الأراواكية هي عائلة لغوية من لغات الهنود بأمريكا الجنوبية والكاريبي.

اٍستخدم أصلا اٍسم أراواك حصرا للاٍشارة للقبيلة القوية في جزر الأنتيل الهولندية، غيانا وسورينام. القبيلة أصبحت حليفة للإسبان لأنهم كانوا أعداء لجماعات الكاريب وفي حالة حرب معهم. أشكال من اللغة الأراواكية لا تزال تتحدث في سورينام.

مراجع

أسر لغات
الأراواكية
لغات سورينام

لغات أراواكية


Republika Hrvatska i Država Katar održavaju diplomatske odnose od 5. prosinca 1992. Sjedište veleposlanstva je u Dohi.

Veleposlanici
Veleposlanstvo Republike Hrvatske u Državi Katar osnovano je odlukom predsjednika Republike od 21. listopada 2011.

Vidi još
Ministarstvo vanjskih i europskih poslova Republike Hrvatske

Vanjske poveznice
 Katar na stranici MVEP-a

Izvori

Katar

Popis hrvatskih veleposlanika u Kataru


القلب الكبير بلدية بدائرة القلب الكبير ولاية المدية الجزائرية.

المصادر

أماكن مأهولة في ولاية المدية
قلب الكبير

القلب الكبير


Bulgărica este un sat din cadrul comunei Sărata Nouă din raionul Leova, Republica Moldova. Localitatea a fost înființată în anul 2013.

Referințe

Localități din raionul Leova

Bulgărica, Leova


Aksaağaç, Adana ilinin Saimbeyli ilçesine bağlı bir mahalledir.

Coğrafya
Adana iline 182 km, Saimbeyli ilçesine 53 km uzaklıktadır.

Nüfus

Dış bağlantılar

Saimbeyli'nin mahalleleri

Aksaağaç, Saimbeyli


An Alocasia reginae in uska species han Liliopsida nga ginhulagway ni Nicholas Edward Brown. An Alocasia reginae in nahilalakip ha genus nga Alocasia, ngan familia nga Araceae. Waray hini subspecies nga nakalista.

Mga kasarigan

Alocasia

Alocasia reginae


An Cyperus chrysocephalus in uska species han Liliopsida nga syahan ginhulagway ni Karl Moritz Schumann, ngan ginhatag han pagkayana nga asya nga ngaran ni Georg Kükenthal. An Cyperus chrysocephalus in nahilalakip ha genus nga Cyperus, ngan familia nga Cyperaceae. Waray hini subspecies nga nakalista.

Mga kasarigan

Cyperus

Cyperus chrysocephalus


Rex Morgan (Charleston, Illinois, 27 de octubre de 1948-Jacksonville, Florida, 15 de enero de 2016) fue un jugador y entrenador de baloncesto estadounidense que disputó dos temporadas en la NBA, y como entrenador dirigió diversos equipos de la USBL durante 14 años. Con 1,96 metros de estatura, lo hacía en la posición de base.

Trayectoria deportiva

Universidad
Tras pasar dos años en el Community College de Lake Land, jugó durante dos temporadas con los Dolphins de la Universidad de Jacksonville, en las que promedió 22,2 puntos y 6,8 rebotes por partido. En su primera temporada promedió 26,9 puntos por partido, el segundo mejor de la historia de los Dolphins, siendo también segundo en la media de toda una carrera, y primero en número de asistencias, con 344.

Profesional
Fue elegido en la vigésimo primera posición del Draft de la NBA de 1970 por Boston Celtics, y también por los Pittsburgh Pipers en el Draft de la ABA, eligiendo la primera opción. Jugó durante dos temporadas con los Celtics, siendo siempre una de las últimas opciones del banquillo. Su mejor temporada fue la primera, en la que promedió 3,4 puntos y 1,8 rebotes por partido.

Entrenador
En 1988 se hizo cargo del banquillo de los Jacksonville Hooters de la USBL, a los que dirigió durante 14 años en sus diferentes denominaciones y localizaciones. En 1990 fue elegido Entrenador del Año, tras ganar su primer campeonato, repitiendo título en 1994.

Estadísticas de su carrera en la NBA

Temporada regular

Playoffs

Referencias

Enlaces externos

 Ficha de Morgan en NBA.com
 Ficha de Rex Morgan en ultimatenba.com

Entrenadores de baloncesto de Estados Unidos
Baloncestistas de la NBA
Baloncestistas de los Jacksonville Dolphins
Baloncestistas de los Boston Celtics
Baloncestistas de Illinois
Fallecidos en Jacksonville (Florida)

Rex Morgan


Tax returns in the United States are reports filed with the Internal Revenue Service (IRS) or with the state or local tax collection agency (California Franchise Tax Board, for example) containing information used to calculate income tax or other taxes. Tax returns are generally prepared using forms prescribed by the IRS or other applicable taxing authority.

Federal returns

Under the Internal Revenue Code returns can be classified as either tax returns or information returns, although the term "tax return" is sometimes used to describe both kinds of returns in a broad sense. Tax returns, in the more narrow sense, are reports of tax liabilities and payments, often including financial information used to compute the tax. A very common federal tax form is IRS Form 1040.

A tax return provides information so that the taxation authority can check on the taxpayer's calculations, or can determine the amount of tax owed if the taxpayer is not required to calculate that amount. In contrast, an information return is a declaration by some person, such as a third party, providing economic information about one or more potential taxpayers.

Information returns
Information returns are reports used to transmit information about income, receipts or other matters that may affect tax liabilities. For example, Form W-2 and Form 1099 are used to report on the amount of income that an employer, independent contractor, broker, or other payer pays to a taxpayer. A company, employer, or party which has paid income (or, in a few cases, proceeds that may ultimately be determined not to be income) to a taxpayer is required to file the applicable information return directly with the IRS. A copy of the information return is also sent directly to the payee. These procedures enable the IRS to make reasonably sure that taxpayers report income correctly.

Tax returns
The filing of Federal tax returns is required under federal law. Individuals who receive more than the statutory minimum amount of gross income must file. The standard U.S. individual tax return is Form 1040. There are several variations of this form, such as the 1040EZ and the 1040A, as well as many supplemental forms. U.S. citizens and residents who realize gross income in excess of a specified amount (adjusted annually for inflation) are required by law to file Federal income tax returns (and pay remaining income taxes if applicable). Gross income includes most kinds of income regardless of whether the income arises from legitimate businesses. Income from the sale of illegal drugs, for example, is taxable. Many criminals, such as Al Capone, are indicted not only for their non-tax crimes, but for failure to file Federal income tax returns (and pay income taxes).

Many Americans find the process of filling out the tax forms more onerous than paying the taxes themselves. A recent survey by Credello uncovered that only 13% of Americans file their taxes completely on their own and 53% rely on an online software system. Many companies offer free and paid options for reducing the tedious labor involved in preparing one's tax return.

Preparation

TurboTax is the most popular tax preparation software in the United States, holding a 66.6% market share of self-prepared returns in 2018. H&R Block at Home (formerly TaxCut) is the second most popular with a 14% share. Other popular tax software includes: TaxACT at 7%, Tax Hawk (including FreeTaxUSA) at 5.9%, Credit Karma's free tax software (now owned by Intuit/TurboTax) at 1.7%, and TaxSlayer at 1.5%.

In some countries, the tax agency provides a prefilled return to streamline the process, but the United States has failed to adopt these technologies as of 2013 after lobbying by tax preparation companies like Intuit. A similar reform was unsuccessfully attempted in California, after a pilot known as ReadyReturn.

Deadline
The annual deadline to file one's Federal individual income tax return is April 15. The IRS lists scenarios for which Tax Day does not follow this standard deadline - Taxpayers can file an extension where the taxes owed must be paid by April 15 but the completed tax return filed by October 15.

Proof of timely filing

Amended return
A taxpayer who finds a mistake on a previously filed individual income tax return can file corrections with Form 1040X.

In the United States, taxpayers may file an amended return with the Internal Revenue Service to correct errors reported on a previously paid tax return. Typically a taxpayer does not need to file an amended return if he or she has math errors as the IRS will make the necessary corrections. For individuals, amended returns are filed using Form 1040X, Amended U.S. Individual Income Tax Return. In some cases taxpayers may use Form 1045, for example, to carry back a Net Operating Loss to a prior tax period. Form 1045 is generally processed much faster than Form 1040X.

Privacy and public disclosure
Tax return laws generally prohibit disclosure of any information gathered on a state tax return. Likewise, the federal government may not (with certain exceptions) disclose tax return information without the filer's permission, and each federal agency is also limited in how it can share such information with other federal agencies.

Occasionally there have been efforts in Congress to require tax returns to be open to public inspection. For example, Senators Robert M. La Follette and George W. Norris supported such legislation, applicable to both individual and corporate returns, and public disclosure for wealthy taxpayers was required from 1923 to 1926. Presidential candidates have sometimes voluntarily released their tax returns.

The IRS occasionally has seen "Fifth Amendment" returns from people who accurately report their annual income and tax liability but refuse to reveal the source of the funds on the grounds that such a statement would tend to incriminate the individual.

List of common forms

Examples of common Federal tax returns (and, where noted, information returns) include:

Transfer taxes

Form 706, U.S. Estate Tax Return;
Form 709, U.S. Gift (and Generation-Skipping Transfer) Tax Return;

Statutory excise taxes

Form 720, Quarterly Federal Excise Tax Return;
Form 2290, Heavy Vehicle Use Tax Return;
Form 5330, Return of Excise Taxes Related to Employee Benefit Plans;

Employment (payroll) taxes

Form 940, Employer's Annual Federal Unemployment (FUTA) Tax Return;
Form 941, Employer's Quarterly Federal Tax Return;

Income taxes

Form 1040, U.S. Individual Income Tax Return;
Form 1040A, U.S. Individual Income Tax Return;
Form 1040EZ, Income Tax Return for Single and Joint Filers with No Dependents;
Form 1041, U.S. Income Tax Return for Estates and Trusts (for 1993 and prior years, this was known as "U.S. Fiduciary Income Tax Return");
Form 1065, U.S. Return of Partnership Income (for 1999 and prior years, this was known as "U.S. Partnership Return of Income") (information return);
Form 1099 series (various titles) (information return);
Form W-2 (information return);
Form 1120, U.S. Corporation Income Tax Return;
Form 1120S, U.S. Income Tax Return for an S Corporation;
Form 2290, Heavy Highway Vehicle Use Tax Return;

See also
 Affordable Care Act tax provisions
 Taxation in the United States
 Tax return (Australia)
 Tax return (Canada)
 Tax return (United Kingdom)

References

External links
Federal laws requiring the filing of income tax returns:

Taxation in the United States
 Tax return (United States)
Tax forms

Tax returns in the United States


Kuća srebrnog vjenčanja ime je dano arheološkim ostacima rimske kuće u Pompejima, zatrpanoj pepelom nakon erupcije Vezuva 79. godine. Kuća je iskopana 1893. godine i dobila je ime po srebrnoj (25.) godišnjici braka Umberta i Margherite Savojske koja se održala te godine.

Opis

Kuća se nalazi u posljednjoj sporednoj ulici Via Vesuvio, pokraj još neiskopanog dijela nalazišta. Izgrađen negdje oko 300. pr. Kr. i renoviran početkom 1. stoljeća nove ere, bio je domus bogatog stanovnika. Njegova arhitektura je klasična i nosi fini ukras u atriju, koji ima četiri visoka korintska stupa koji podupiru krov i elegantno ukrašenu eksedru. Općenito se smatra najljepšim atrijem u tetrastilu u gradu, sa svojim komluvijalnim krovom s palmetnim antefiksima i žlijebovima s lavljim glavama.

Postoje dva vrta: najveći sa središnjim bazenom i triklinijem; drugi s kupaonicom, otvorenim bazenom, kuhinjom i dnevnim boravkom s podom od mozaika, zidnim slikama i bačvastim svodom koji podupiru četiri osmerokutna stupa ukrašena imitacijom porfira.

Izvori

Daljnje čitanje

Vanjske poveznice

Srebrnog vjenčanja

Kuća srebrnog vjenčanja


Meyer "Mike" Bloom (nacido el  en Nueva York, Nueva York y fallecido el  en Baltimore, Maryland) fue un jugador de baloncesto estadounidense que disputó dos temporadas en la BAA, además de jugar previamente en la ABL. Con 1,98 metros de estatura, jugaba en la posición de ala-pívot.

Trayectoria deportiva

Universidad
Jugó durante dos temporadas con los Owls de la Universidad de Temple, donde en su primera temporada logró anotar 25 puntos en un partido ante Georgetown, incluida la canasta que les dio la victoria. Al año siguiente conseguirían ganar la primera edición del NIT, derrotando a Colorado Buffaloes en una final en la que Bloom anotó 6 puntos, distinguiéndose por su trabajo defensivo. Fue además incluido esa temporada en el mejor quinteto consensuado All-American.

Profesional
Comenzó su carrera profesional en los Philadelphia Sphas de la ABL, donde en su primera temporada promedió 4,1 puntos por partido. Al año siguiente fue traspasado a los Washington Brewers, mejorando sus estadísticas hasta los 5,8 puntos por encuentro. Tras pasar por los Baltimore Clippers, en 1941 ficha por los Trenton Tigers, donde comienza su etapa más exitosa de su carrera profesional. Al año siguiente acaba en cuarta posición entre los máximos anotadores de la liga, promediando 8,8 puntos por partido, para en 1944 liderar la clasificación de máximos anotadores de la liga con 10,5 puntos por encuentro, (la cuarta parte de los puntos de su equipo), siendo elegido mejor jugador del campeonato, algo que repetiría al año siguiente, tras acabar segundo entre los máximos encestadores con 10,7.

En 1945 ficha por los Baltimore Bullets, equipo nuevo en la competición, y en su primera temporada vuelve a acabar entre los diez mejores anotadores de la liga, ganando el campeonato tras derrotar a los Sphas en las finales. Jugaría una temporada más en la liga, acabando finalmente en la octava posición entre los mejores anotadores históricos de la ABL, con 1.639 puntos (10,6 por partido).

En  el equipo se une a la BAA, en una temporada en la que ganaron la liga, pero Bloom fue traspasado mediada la competición a los Boston Celtics a cambio de Connie Simmons, a pesar de estar promediando hasta ese momento 11,1 puntos por partido, el tercer mejor anotador del equipo.

Al año siguiente, ya con 34 años, ficha por los Minneapolis Lakers, recién llegados de la NBL, donde fue suplente de Jim Pollard hasta que mediada la temporada es enviado a los Chicago Stags, retirándose al término de la misma.

Estadísticas en la BAA

Temporada regular

Playoffs

Referencias

Enlaces externos

 Ficha de Mike Bloom en ultimatenba.com

Baloncestistas de Nueva York
Baloncestistas de la NBA
Baloncestistas de los Temple Owls
Baloncestistas de los Philadelphia Sphas
Baloncestistas de los Baltimore Bullets (original)
Baloncestistas de los Minneapolis Lakers
Baloncestistas de los Boston Celtics
Baloncestistas de los Chicago Stags
Baloncestistas de los Trenton Tigers

Mike Bloom


William Matthews (born July 22, 1947) is a Canadian politician.

Political career
Matthews was a Progressive Conservative member of the Newfoundland and Labrador House of Assembly from 1982 to 1996. During this time, he was a cabinet minister, as Minister of Culture, Recreation and Youth from 1985 to 1988 and Minister of Career Development and Advanced Studies from 1988 to 1989.

Matthews was later elected to the House of Commons of Canada in 1997 as a member of the Progressive Conservative Party of Canada, representing the riding of Burin—St. George's. He crossed the floor to the Liberals in 1999, and continued to represent the riding until 2004. In that year's federal election, he was elected to the newly redistributed district of Random—Burin—St. George's, which he represented until 2008.

Matthews is a former teacher. He is a former Parliamentary Secretary to the Queen's Privy Council for Canada and Minister of Intergovernmental Affairs, Deputy House Leader of the Progressive Conservative Party, and Progressive Conservative critic of Fisheries and Oceans.

In March 2007, Matthews called Prime Minister Stephen Harper a "liar." While Speaker of the House Peter Milliken didn't give in to demands from outraged Tories to throw Matthews out of the chamber, Milliken did not allow Matthews to rise in the House for what would be the last 14 months of Matthews' career.  Matthews did not run for reelection in the 2008 election.

In October 2018, Matthews was appointed as Chief of Staff to provincial PC leader Ches Crosbie in the Opposition Office.

Matthews contested the 2019 provincial election as the PC candidate in Burin-Grand Bank, but was defeated by Liberal incumbent Carol Anne Haley.

Electoral record

|NDP
|Joseph L. Edwards
|align="right"|181
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|NDP
|Calvin Peach
|align="right"|431
|align="right"|7.0
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|NDP
|Eric Miller
|align="right"|234
|align="right"|4.23
|align="right"|
|-
|}

References

External links

1947 births
Liberal Party of Canada MPs
Living people
Members of the House of Commons of Canada from Newfoundland and Labrador
Progressive Conservative Party of Newfoundland and Labrador MHAs
Progressive Conservative Party of Canada MPs
People from Grand Bank
21st-century Canadian politicians

Bill Matthews


Joseph Harry Fowler Connick, Jr. (11 Eylül 1967) Amerikalı şarkıcı, piyanist, bestekâr, oyuncu.

Albümleri
 Oh, My NOLA (Columbia, 2007)
 Chanson du Vieux Carre: Connick On Piano, Vol. 3 (Rounder, 2007)
 Harry on Broadway, Act I (Columbia, 2006)
 Occasion: Connick on Piano, Vol. 2 (Rounder, 2005)
 Only You (Columbia, 2004)
 Other Hours: Connick on Piano, Vol. 1 (Rounder, 2003)
 Harry for the Holidays (Columbia, 2003)
 Thou Shalt Not (2002)
 Songs I Heard (Columbia, 2001)
 30 (Columbia, 2001)
 Come by Me (Columbia, 1999)
 To See You (Columbia, 1997)
 Star Turtle (Columbia, 1995)
 She (Columbia, 1994)
 When My Heart Finds Christmas (Columbia, 1993)
 25 (Columbia, 1992)
 Blue Light, Red Light (Columbia, 1991)
 We Are in Love (Columbia, 1990)
 Lofty's Roach Souffle (Columbia, 1990)
 When Harry Met Sally (Columbia, 1989)
 20 (Columbia, 1988)
 Harry Connick, Jr. (Columbia, 1987)
 11 (1978)

Filmleri
 Dolphin Tale  (2011) (Dr.Clay Haskett)
 Chilled in Miami (2009)
 P.S., I Love You (2008)
 Böcek (en Bug) (2007)
 The Happy Elf (2005)
 Mickey (2004)
 Basic (2003)
 Will & Grace (2002-2006)
 South Pacific (2001)
 Life Without Dick (2001)
 The Simian Line (2000)
 My Dog Skip (2000)
 Wayward Son (1999)
 The Iron Giant (1999)
 Hope Floats (1998)
 Excess Baggage (1997)
 Independence Day (1996)
 Copycat (1995)
 Little Man Tate (1991)
 Memphis Belle (1990)

1967 doğumlular
Amerikalı erkek sinema oyuncuları
Amerikalı erkek dizi oyuncuları
Grammy Ödülü sahipleri
Yaşayan insanlar
Columbia Records sanatçıları
Amerikalı caz bestecileri
21. yüzyılda Amerikalı şarkıcılar
20. yüzyılda Amerikalı piyanistler
21. yüzyılda Amerikalı piyanistler
Amerikalı baritonlar
Amerikalı erkek pop şarkıcıları
Amerikalı erkek şarkıcı-şarkı yazarları

Harry Connick, Jr.


Joshua Oghenetega Peter Onomah (født d. 27. april 1997) er en engelsk professionel fodboldspiller, som spiller for Premier League-klubben Fulham.

Klubkarriere

Tottenham Hotspur
Onomah begyndte sin karriere hos Tottenham Hotspur, hvor han gjorde sin førsteholdsdebut i januar 2015.

Han tilbragte under sin tid i klubben lejeaftaler hos Aston Villa og Sheffield Wednesday.

Fulham
Onomah skiftede i august 2019 til Fulham som del af aftalen som sendte Ryan Sessegnon den anden vej.

Landsholdskarriere
Onomah har repræsenteret England på flere ungdomsniveauer. Han var del af Englands U/20-trup som vandt U/20-verdensmesterskabet i 2017.

Titler
Fulham
 EFL Championship: 1 (2021-22)

England U/17

 U/17-Europamesterskabet: 1 (2014)

England U/20

 U/20-Verdensmesterskabet: 1 (2017)

Referencer

Eksterne henvisninger

Personer fra London
Fodboldspillere fra England
Fodboldspillere fra Tottenham Hotspur F.C.
Fodboldspillere fra Aston Villa F.C.
Fodboldspillere fra Sheffield Wednesday F.C.
Fodboldspillere fra Fulham F.C.

Josh Onomah


Maksutlu, Çorum ilinin Kargı ilçesine bağlı bir köydür.

Tarihçe
Köy, 1925 yılından beri aynı adı taşımaktadır.

Coğrafya
Köy, Çorum il merkezine 92 km, Kargı ilçe merkezine 18 km uzaklıktadır.

Nüfus

Kaynakça

Dış bağlantılar

Kargı belde ve köyleri

Maksutlu, Kargı


Mayara & Annabelle é uma série em quadrinhos criada por Pablo Casado e Talles Rodrigues em 2014.

As primeiras histórias da série foram publicadas de forma independente, sendo viabilizadas por financiamento coletivo. Foram também lançadas nos Estados Unidos pela editora Behemoth Comics, além de terem sido adaptadas para um jogo de celular. Em 2021, a Conrad Editora compilou as HQs independentes e lançando uma "edição definitiva" da série.

A trama gira em torno das personagens que dão título à série: Mayara é uma ninja paulista e Annabelle é uma maga cearense, que trabalham como funcionárias públicas na unidade do Ceará da fictícia Secretaria de Controle de Atividades Fora do Comum, lutando juntas contra os perigos sobrenaturais que ameaçam Fortaleza.

Em 2021, o livro Mayara & Annabelle: Hora Extra ganhou o Troféu HQ Mix de melhor publicação independente edição única. Em 2022, foi anunciada uma série em live-action baseada na série, produzida pela Floresta, produtora da Sony, e pela Clube Filmes.

Ligações externas

Histórias em quadrinhos do Brasil
Obras ganhadoras do Troféu HQ Mix

Mayara & Annabelle


The black geese of the genus Branta are waterfowl belonging to the true geese and swans subfamily Anserinae. They occur in the northern coastal regions of the Palearctic and all over North America, migrating to more southernly coasts in winter, and as resident birds in the Hawaiian Islands. Alone in the Southern Hemisphere, a self-sustaining feral population derived from introduced Canada geese is also found in New Zealand.

The black geese derive their vernacular name for the prominent areas of black coloration found in all species. They can be distinguished from all other true geese by their legs and feet, which are black or very dark grey. Furthermore, they have black bills and large areas of black on the head and neck, with white (ochre in one species) markings that can be used to tell apart most species. As with most geese, their undertail and uppertail coverts are white. They are also on average smaller than other geese, though some very large taxa are known, which rival the swan goose and the black-necked swan in size.

The Eurasian species of black geese have a more coastal distribution compared to the grey geese (genus Anser) which share the same general area of occurrence, not being found far inland even in winter (except for occasional stray birds or individuals escaped from captivity). This does not hold true for the American and Pacific species, in whose ranges grey geese are, for the most part, absent.

Taxonomy
The genus Branta was introduced by the Austrian naturalist Giovanni Antonio Scopoli in 1769. The name is a Latinised form of Old Norse Brandgás meaning burnt as in "burnt (black) goose". The type species is the brant goose (Branta bernicla).

Ottenburghs and colleagues published a study in 2016 that established the phylogenetic relationships between the species.

Species list
The genus contains six living species.

Two species have been described from subfossil remains found in the Hawaiian Islands, where they became extinct in prehistoric times:
 Nēnē-nui or wood-walking goose, Branta hylobadistes (prehistoric)
Similar but hitherto undescribed remains are known from on Kauaʻi and Oʻahu.
 Giant Hawaii goose, Branta rhuax (prehistoric), formerly Geochen rhuax

The relationships of the enigmatic Geochen rhuax, formerly known only from parts of a single bird's skeleton damaged due to apparently dying in a lava flow, were long unresolved. After reexamination of the subfossil material and comparisons with other subfossil bones from the island of Hawaii assigned to the genus Branta, it was redescribed as Branta rhuax in 2013. While a presumed relation between B. rhuax and the shelducks, proposed by Lester Short in 1970, has thus been refuted, bones of a shelduck-like bird have been found more recently on Kaua'i. Whether this latter anatid was indeed a shelduck is presently undetermined.

Similarly, two bones found on Oʻahu indicate the erstwhile presence of a gigantic waterfowl on this island. Its relationships relative to this genus and the moa-nalos, enormous goose-like dabbling ducks, are completely undeterminable at present.

Early fossil record
Several fossil species of Branta have been described. Since the true geese are hardly distinguishable by anatomical features, the allocation of these to this genus is somewhat uncertain. A number of supposed prehistoric grey geese have been described from North America, partially from the same sites as species assigned to Branta. Whether these are correctly assigned – meaning that the genus Anser was once much more widespread than today and that it coexisted with Branta in freshwater habitat which it today does only most rarely – is not clear. Especially in the case of B. dickeyi and B. howardae, doubts have been expressed about its correct generic assignment.
Branta woolfendeni (Big Sandy Late Miocene of Wickieup, USA)
Branta thessaliensis (Late Miocene of Perivolaki, Greece)
Branta dickeyi (Late Pliocene – Late Pleistocene of W USA)
Branta esmeralda (Esmeralda Early Pliocene)
Branta howardae (Ricardo Early Pliocene)
Branta propinqua (Middle Pleistocene of Fossil Lake, USA)
Branta hypsibata (Pleistocene of Fossil Lake, USA)

The former "Branta" minuscula is now placed with the prehistoric American shelducks, Anabernicula. On the other hand, a goose fossil from the Early-Middle Pleistocene of El Salvador is highly similar to Anser and given its age and biogeography it is likely to belong to that genus or Branta.

Footnotes

References

Further reading

Bird genera
Geese
Anatidae
Extant Miocene first appearances
Taxa named by Giovanni Antonio Scopoli

Branta


Miraculous, le film, ou Miraculous : Ladybug et Chat Noir, le film à l'international, est un film d'animation français réalisé et coécrit par Jeremy Zag, sorti en 2023.

C'est une libre adaptation de la série télévisée d'animation Miraculous : Les Aventures de Ladybug et Chat Noir. Le film suit deux adolescents parisiens, Marinette Dupain-Cheng et Adrien Agreste qui peuvent se transformer en super-héros, Ladybug et Chat Noir, respectivement. Il met en scène les débuts de leurs aventures pour protéger la ville de Paris.

Annoncé en 2018, sa production débute l'année suivante. La réalisation est confiée à Jeremy Zag, qui coécrit le film avec Bettina Lopez Mendoza. Zag est également producteur du film avec sa société ZAG Inc. via la bannière The Awakening Production. SND est en charge de la distribution et participe également en tant que coproducteur.

Il s'agit de la seconde adaptation cinématographique d'une série d'animation de l'émission Tfou de TF1 après Totally Spies! Le Film (2009) et du deuxième film français le plus cher de l'histoire avec un budget de .

À Paris, les jeunes Marinette et Adrien vont endosser les costumes des héros Ladybug et Chat Noir. En plus des défis quotidiens de leur vie normale, ils se lancent pour devenir de véritables super-héros. Ils doivent affronter le Papillon qui rêve de créer le chaos pour détruire le monde entier avec les Miraculous de Ladybug et Chat Noir. Le pouvoir du Papillon permet de créer des héros. Mais, au lieu de créer des super-héros, il crée des super-vilains.

Synopsis détaillé
Dans un récit de l'histoire d'origine de la série Miraculous, Marinette Dupain-Cheng, une adolescente anxieuse socialement, va à l'école en essayant d'éviter d'attirer l'attention. Bien qu'elle ait noué une amitié avec une autre étudiante, Alya Césaire, Marinette tente désespérément d'éviter la colère de Chloé Bourgeois, une fille riche. En cherchant à s'échapper, Marinette rencontre Adrien Agreste, beau garçon de sa classe, dans la bibliothèque et tombe amoureuse de lui. Adrien, émotionnellement distant des autres depuis le décès de sa mère Emilie, est également profondément affecté par cette perte. Son père, Gabriel, est également dévasté par cette tragédie et utilise le Miraculous du Papillon pour se transformer en un super-vilain nommé Papillon. Son but est de trouver les Miraculous dont il a besoin pour faire un vœu et ramener sa femme Émilie à la vie.

L'apparition du Papillon est détectée par Maître Fu, le gardien de la Miracle Box. Maître Fu décide alors de libérer les Miraculous de la Coccinelle et du Chat Noir, mais ils s'enfuient avant qu'il ne puisse les aider à trouver de nouveaux porteurs. Alors qu'un bus s'approche de lui, Marinette, toujours en fuite devant Chloé, le sauve, ce qui amène Maître Fu à réaliser qu'elle est digne du Miraculous. Marinette, le pensant sénile, se réfugie sans le savoir dans sa boutique, située dans une ruelle où elle est retrouvée par Tikki, le Kwami de la Création, tandis que Plagg, le Kwami de la Destruction, se dirige vers Adrien. Les deux adolescents deviennent Ladybug et Chat Noir et finissent par se rencontrer, travaillant ensemble pour vaincre leur premier Akumatisé, un méchant créé par le Papillon à partir d'émotions négatives.

Après le combat, Maître Fu suit les deux héros et souligne l'importance de rester ensemble. Marinette refuse initialement de continuer à être Ladybug, mais le Papillon recrute d'autres méchants qui causent des ravages lors du carnaval. Rassemblant son courage, Marinette redevient Ladybug et les bat aux côtés de Chat Noir. Les mois passent et Marinette envisage d'avouer ses sentiments à Adrien, tandis qu'Adrien envisage d'avouer les siens à Ladybug. Cependant, ignorant leurs véritables identités, aucune confession ne se passe comme prévu.

Se sentant vaincu, le Papillon s'akumatise lui-même et déclenche une apocalypse sur Paris, incitant Ladybug et Chat Noir à intervenir. Les deux héros sont submergés et Ladybug se fait arracher ses boucles d'oreilles, mais Marinette parvient à intervenir brièvement pour aider à éloigner Chat Noir du Papillon. En raison des dégâts causés par le combat, le Papillon réalise qu'Adrien est Chat Noir et arrête son saccage, s'effondrant. Adrien pardonne à son père, tandis que Ladybug rend le Miraculous du Papillon à Maître Fu avant de réparer les dommages causés à Paris.

Le bal de l'hiver arrive et Marinette s'y rend. Elle retrouve Adrien et révèle qu'elle connaît son identité, l'ayant vu se réconcilier avec son père pendant le combat. Elle révèle également sa propre identité. Les deux s'embrassent. Plus tard, Nathalie Sancoeur, secrétaire des Agreste, se rend au sous-sol de leur maison, où se trouve le corps d'Émilie, portant le Miraculous du Paon.

Fiche technique

 Titre original : Miraculous, le film
 Titre dans les autres pays francophones : Miraculous : Ladybug et Chat Noir, le film
 Réalisation : Jeremy Zag
 Scénario : Jeremy Zag et Bettina Lopez Mendoza, d'après une histoire de Jeremy Zag
 Storyboard : Karim El Mokaddem
 Montage : Yvann Thibaudeau
 Musique : Jeremy Zag
 Production : Aton Soumache, Jeremy Zag et Daisy Chang
 Société de production : The Awakening Production, SND et ON Animation Studios
 Société de distribution : SND
 Budget :
 Pays :
 Langue originale : anglais, français
 Format : couleur
 Genre : animation, action, super-héros
 Dates de sortie :
 France :  (avant-première au Grand Rex) ;  (sortie nationale)
 Belgique, Suisse romande et Luxembourg :
 États-Unis et Québec :  (sur Netflix)

Distribution

 Anouck Hautbois : Marinette Dupain-Cheng / Ladybug
 Lou Jean : Marinette Dupain-Cheng / Ladybug (voix chantée)
 Benjamin Bollen : Adrien Agreste / Chat Noir
 Elliott Schmitt : Adrien Agreste / Chat Noir (voix chantée)
 Antoine Tomé : Gabriel Agreste / le Papillon
 Marie Nonnenmacher : Tikki, Sabrina Raincomprix, Juleka Couffaine et Alix Kubdel
 Cerise Calixte : Tikki (voix chantée)
 Thierry Kazazian : Plagg et le Monstre
 Fanny Bloc : Alya Césaire
 Alexandre Nguyen : Nino Lahiffe et Kim Chiên Le
 Marie Chevalot : Chloé Bourgeois et Nathalie Sancoeur
 Martial Le Minoux : Tom Dupain, Max Kanté et Nooroo
 Gilbert Lévy : Maître Fu et Denis Damoclès
 Jessie Lambotte : Sabine Cheng, Mylène Haprèle, Rose Lavillant, Nadja Chamack et Caline Bustier
 Jeanne Chartier : Émilie Agreste
 Flora Kaprielian : La Magicienne
 Franck Tordjman : Nathaniel Kurtzberg et Ivan Bruel
 Version française
 Studio de doublage : Dubbing Brothers
 Adaptation des dialogues : Gilles Coiffard
 Adaptation des chansons : Virginie Acaries et Jeremy Zag
 Direction artistique : Paolo Domingo

Production

Développement
Le 5 décembre 2018, il est annoncé que le film sortira en 2021. Son intrigue sera un mélange entre l'origine des personnages de l'univers et la fin de la saison 5. Le lendemain, lors du panel Miraculous à Comic Con Experience 2018, Zag confirme que le film sera une comédie musicale composée par lui-même.

Le 16 mai 2019, lors du festival de Cannes 2019, il est confirmé que le titre anglophone sera Ladybug and Cat Noir Awakening. Il est précisé que la production du film est en cours. Le film est présenté comme une aventure fantastique romantique. Michael Gracey, le réalisateur de The Greatest Showman, a également été confirmé pour travailler sur le film. Le 7 juin 2019, Jeremy Zag dévoilait sur son Instagram, une chanson pour le film intitulé Ce mur qui nous sépare, interprétée par Lou Jean et Lenni-Kim. Le 24 juillet 2019, un solo interprété par Lou pour le film a été révélé.

Le 12 février 2020, il a été annoncé que Fantawild est l'un des studios responsable de la création et l'animation du film. Le 22 juillet 2020, il a été annoncé que film sortirait en 2021.

Chansons du film

Lors de l'expérience Comic Con 2018, Jeremy Zag a annoncé que le film était une comédie musicale et un long métrage composé par lui-même. Le cinéaste australien Michael Gracey a rejoint le film en tant que producteur exécutif pour aider à développer l'aspect musical.

La bande originale du film sortira le 30 juin 2023 chez Muzeek One sous le label TF1 Musique. "Plus forts ensemble" de Lou et Elliott est sorti en tant que premier single de l'album le 9 juin 2023. Le clip vidéo est sorti le 21 juin 2023.

Un showcase avec les voix chantantes de Ladybug et Chat Noir, Lou et Elliott, sera organisé au Salon Gustave Eiffel au 1er étage de la Tour Eiffel le 28 juin 2023 pour promouvoir la bande originale.

Accueil

Sortie et promotion
Le 9 septembre 2019, sort un teaser du clip vidéo de la chanson Ce mur qui nous sépare. Le 18 septembre 2019 sort le clip de la chanson. Le 5 octobre 2019, un teaser animé mettant en vedette Ladybug a été dévoilé. Le 21 décembre 2019, il a été confirmé que le film sortira vers fin 2021, selon Le Figaro. .

La campagne marketing pour le film a commencé le 5 décembre 2022, lorsque la bande-annonce et l'affiche teaser ont été révélées par SND. La bande-annonce officielle et l'affiche de sortie en salle ont été publiées le 4 avril 2023 en France, avec la bande-annonce également diffusée dans les territoires internationaux où le film est prévu en sortie cinéma. Pour les territoires où le film sera distribué par Netflix, la bande-annonce a été publiée le 17 mai 2023 sur les plateformes de médias sociaux du service.

Le 12 juin 2023, il a été révélé que le film présentera des voitures Volkswagen à la suite d'un accord entre le constructeur automobile allemand et ZAG Inc. Une publicité animée de Volkswagen mettant en vedette des personnages du film sera diffusée dans les cinémas pour coïncider avec la sortie. Des produits de la marque pour enfants The Swatch Group Flik Flak seront également présents dans le film, la marque lançant également une collection de montres inspirée du film.

Le 28 juin 2023, une présentation musicale sera organisée au Salon Gustave Eiffel au 1er étage de la Tour Eiffel pour promouvoir le film et sa bande originale, avec les voix chantées de Ladybug et Cat Noir, Lou et Elliott. Pour coïncider avec la sortie, Playmates Toys a sorti une collection de poupées inspirée du film.

Le 4 juillet 2023, le personnage de Ladybug est interviewé au 1945 de M6 par le journaliste Xavier de Moulins.

À l'international, le film sortira simultanément en salles aux Pays-Bas et dans les régions francophones de Belgique, de Suisse et du Luxembourg. Il commencera à être diffusé dans d'autres territoires à partir du 7 juillet 2023, en commençant par l'Allemagne et les régions germanophones de la Belgique, de la Suisse et du Luxembourg. Au Québec, le film a commencé à être projeté dans une des salles du réseau Cineplex le 21 juillet 2023, à Montréal.

Dans les territoires internationaux où le film ne sera pas diffusé en salle, il sera disponible sur Netflix à partir du 28 juillet 2023.

Box office

En France :

En France, lors de la première mondiale au Grand Rex le 11 juin 2023, le film a également été projeté simultanément dans certaines salles de cinéma, vendant 68 582 billets. Le jour de sa sortie en France, le film bat le record d'entrées pour un premier jour pour un film d'animation français avec 318 144 entrées, en comptant les avant-premières.

Le film atteint la barre du millions d'entrées à l'échelle national lors de sa troisième semaine d'exploitation.

Hors France :

En Allemagne le film cumule  entrées (avant première comprise) lors de sa première semaine d'exploitation, terminant deuxième derrière Indiana Jones et le Cadran de la destinée.

Trois semaines après sa sortie en salle dans plusieurs pays d'Europe, le film cumule près d'1,3 million d'entrées hors France, dont les principaux marchés sont l'Allemagne (586 000 entrées) et la Pologne (540 000 entrées).
Le film ne sort pas en salle dans tous les pays puisqu'il est diffusé sur Netflix à partir du 28 juillet 2023 en Amérique, Asie, Océanie, Grande-Bretagne, Italie et Espagne.

Fin juillet, le film cumule 1,8 million d'entrées hors France, après un mois d'exploitation en salle dans plusieurs pays d'Europe.

Le film amasse plus de 3,7 millions d'entrées en plus à l'international lors du mois d'août grâce à notamment sa sortie en Russie où le film a dépassé la barre des 2 millions d'entrées, un record historique pour un film français. Son cumule porte donc après près de deux mois d'exploitation à plus de 5,6 millions d'entrées hors France.

Fin septembre, le cumule monde hors France atteint près de 6,3 millions d'entrées pour un total de près de 8 millions d'entrées avec les nombres d'entrées français, un record pour un film français jamais atteint depuis la pandémie.

Accueil critique

Notes et références

Notes

Références

Liens externes

Film dont la sortie a été reportée en raison de la pandémie de Covid-19
Film français sorti en 2023
Miraculous : Les Aventures de Ladybug et Chat Noir
Film d'animation français
Film musical français
Film se déroulant à Paris
Adaptation d'une série télévisée d'animation au cinéma

Miraculous, le film


ISO 7092 er en ISO standard for en planskive.

En planskive ISO 7092 er en af de mest brugte skiver indenfor befæstelse området.

Kilde
 http://bolte.dk/planskiver-iso-7092/

7092

ISO 7092


Încă un film despre adolescenți?! (en. Not Another Teen Movie) este un film de comedie american, regizat de Joel Gallen și scris de Mike Bender, Adam Jay Epstein, Andrew Jacobson, Phil Beauman și Buddy Johnson. Filmul are o distributie de ansamblu incluzand actorii principali: Chyler Leigh, Chris Evans, Jaime Pressly, Eric Christian Jones, Eric Christian Jones, Mia Kirshner, Deon Richmond, Cody McMains, Sam Huntington, Samm Levine, Cerna Vincent, Ron Lester, Randy Quaid și Riley Smith.

Lansat pe 14 decembrie 2001 de studioul Columbia Pictures, aceata este o parodie a filmelor adolescente care s-a acumulat la Hollywood de-a lungul deceniilor anterioare eliberării sale. În timp ce complotul general se bazează pe She's All That, precum și Varsity Blues, 10 Things I Hate About You, Can't Hardly Wait și Pretty in Pink, filmul este de asemenea umplut cu aluzii la numeroase alte filme despre adolescenti din anii 1980 și 1990, cum ar fi Bring It On, American Pie, Cruel Intentions, American Beauty,  Never Been Kissed, Ferris Bueller's Day Off,  Can't Buy Me Love, Jawbreaker, Sixteen Candles, Lucas si The Breakfast Club.

Note
Filme de comedie americane
Filme din 2001

Încă un film despre adolescenți?!


Niels Jørgen Nielsen, kendt som Jørgen Nielsen (18. november 1902 i Engesvang – 27. marts 1945 i Gentofte), var en dansk roman- og novelleforfatter. Efter nogle år i landbruget blev han journalist i Silkeborg og Ringsted og fra 1933 forfatter på fuld tid. Blandt hans værker kan nævnes romanen En Kvinde ved Bålet (1933) og novellesamlingen Lavt Land.

Værker

Henvisninger

Eksterne kilder

 Navne i dansk litteratur, Gyldendals Bibliotek, 1963 (s. 105-106)

Romanforfattere fra Danmark
Novelleforfattere fra Danmark
Journalister fra Danmark

Jørgen Nielsen (forfatter)


In signal processing, independent component analysis (ICA) is a computational method for separating a multivariate signal into additive subcomponents. This is done by assuming that at most one subcomponent is Gaussian and that the subcomponents are statistically independent from each other. ICA is a special case of blind source separation. A common example application is the "cocktail party problem" of listening in on one person's speech in a noisy room.

Introduction

Independent component analysis attempts to decompose a multivariate signal into independent non-Gaussian signals. As an example, sound is usually a signal that is composed of the numerical addition, at each time t, of signals from several sources. The question then is whether it is possible to separate these contributing sources from the observed total signal. When the statistical independence assumption is correct, blind ICA separation of a mixed signal gives very good results. It is also used for signals that are not supposed to be generated by mixing for analysis purposes.

A simple application of ICA is the "cocktail party problem", where the underlying speech signals are separated from a sample data consisting of people talking simultaneously in a room. Usually the problem is simplified by assuming no time delays or echoes. Note that a filtered and delayed signal is a copy of a dependent component, and thus the statistical independence assumption is not violated.

Mixing weights for constructing the  observed signals from the  components can be placed in an  matrix. An important thing to consider is that if  sources are present, at least  observations (e.g. microphones if the observed signal is audio) are needed to recover the original signals. When there are an equal number of observations and source signals, the mixing matrix is square (). Other cases of underdetermined () and overdetermined () have been investigated.

The success of ICA separation of mixed signals relies on two assumptions and three effects of mixing source signals. Two assumptions:
The source signals are independent of each other.
The values in each source signal have non-Gaussian distributions.
Three effects of mixing source signals:
Independence: As per assumption 1, the source signals are independent; however, their signal mixtures are not. This is because the signal mixtures share the same source signals.
Normality: According to the Central Limit Theorem, the distribution of a sum of independent random variables with finite variance tends towards a Gaussian distribution.Loosely speaking, a sum of two independent random variables usually has a distribution that is closer to Gaussian than any of the two original variables. Here we consider the value of each signal as the random variable.
Complexity: The temporal complexity of any signal mixture is greater than that of its simplest constituent source signal.
Those principles contribute to the basic establishment of ICA. If the signals extracted from a set of mixtures are independent and have non-Gaussian distributions or have low complexity, then they must be source signals.

Defining component independence
ICA finds the independent components (also called factors, latent variables or sources) by maximizing the statistical independence of the estimated components. We may choose one of many ways to define a proxy for independence, and this choice governs the form of the ICA algorithm. The two broadest definitions of independence for ICA are

 Minimization of mutual information
 Maximization of non-Gaussianity

The Minimization-of-Mutual information (MMI) family of ICA algorithms uses measures like Kullback-Leibler Divergence and maximum entropy.  The non-Gaussianity family of ICA algorithms, motivated by the central limit theorem, uses kurtosis and negentropy.

Typical algorithms for ICA use centering (subtract the mean to create a zero mean signal), whitening (usually with the eigenvalue decomposition), and dimensionality reduction as preprocessing steps in order to simplify and reduce the complexity of the problem for the actual iterative algorithm. Whitening and dimension reduction can be achieved with principal component analysis or singular value decomposition. Whitening ensures that all dimensions are treated equally a priori before the algorithm is run. Well-known algorithms for ICA include infomax, FastICA, JADE, and kernel-independent component analysis, among others. In general, ICA cannot identify the actual number of source signals, a uniquely correct ordering of the source signals, nor the proper scaling (including sign) of the source signals.

ICA is important to blind signal separation and has many practical applications. It is closely related to (or even a special case of) the search for a factorial code of the data, i.e., a new vector-valued representation of each data vector such that it gets uniquely encoded by the resulting code vector (loss-free coding), but the code components are statistically independent.

Mathematical definitions

Linear independent component analysis can be divided into noiseless and noisy cases, where noiseless ICA is a special case of noisy ICA. Nonlinear ICA should be considered as a separate case.

General definition

The data are represented by the observed random vector  and the hidden components as the random vector  The task is to transform the observed data  using a linear static transformation  as  into a vector of maximally independent components  measured by some function  of independence.

Generative model

Linear noiseless ICA

The components  of the observed random vector  are generated as a sum of the independent components , :

weighted by the mixing weights .

The same generative model can be written in vector form as , where the observed random vector  is represented by the basis vectors . The basis vectors  form the columns of the mixing matrix  and the generative formula can be written as , where .

Given the model and realizations (samples)  of the random vector , the task is to estimate both the mixing matrix  and the sources . This is done by adaptively calculating the  vectors and setting up a cost function which either maximizes the non-gaussianity of the calculated  or minimizes the mutual information. In some cases, a priori knowledge of the probability distributions of the sources can be used in the cost function.

The original sources  can be recovered by multiplying the observed signals  with the inverse of the mixing matrix , also known as the unmixing matrix. Here it is assumed that the mixing matrix is square (). If the number of basis vectors is greater than the dimensionality of the observed vectors, , the task is overcomplete but is still solvable with the pseudo inverse.

Linear noisy ICA

With the added assumption of zero-mean and uncorrelated Gaussian noise , the ICA model takes the form .

Nonlinear ICA

The mixing of the sources does not need to be linear. Using a nonlinear mixing function  with parameters  the nonlinear ICA model is .

Identifiability

The independent components are identifiable up to a permutation and scaling of the sources. This identifiability requires that:

 At most one of the sources  is Gaussian,
 The number of observed mixtures, , must be at least as large as the number of estimated components : . It is equivalent to say that the mixing matrix  must be of full rank for its inverse to exist.

Binary ICA

A special variant of ICA is binary ICA in which both signal sources and monitors are in binary form and observations from monitors are disjunctive mixtures of binary independent sources. The problem was shown to have applications in many domains including medical diagnosis, multi-cluster assignment, network tomography and internet resource management.

Let  be the set of binary variables from  monitors and  be the set of binary variables from  sources. Source-monitor connections are represented by the (unknown) mixing matrix , where  indicates that signal from the i-th source can be observed by the j-th monitor. The system works as follows: at any time, if a source  is active () and it is connected to the monitor  () then the monitor  will observe some activity (). Formally we have:

where  is Boolean AND and  is Boolean OR. Noise is not explicitly modelled, rather, can be treated as independent sources.

The above problem can be heuristically solved by assuming variables are continuous and running FastICA on binary observation data to get the mixing matrix  (real values), then apply round number techniques on  to obtain the binary values. This approach has been shown to produce a highly inaccurate result.

Another method is to use dynamic programming: recursively breaking the observation matrix  into its sub-matrices and run the inference algorithm on these sub-matrices. The key observation which leads to this algorithm is the sub-matrix  of  where  corresponds to the unbiased observation matrix of hidden components that do not have connection to the -th monitor. Experimental results from show that this approach is accurate under moderate noise levels.

The Generalized Binary ICA framework introduces a broader problem formulation which does not necessitate any knowledge on the generative model. In other words, this method attempts to decompose a source into its independent components (as much as possible, and without losing any information) with no prior assumption on the way it was generated. Although this problem appears quite complex, it can be accurately solved with a branch and bound search tree algorithm or tightly upper bounded with a single multiplication of a matrix with a vector.

Methods for blind source separation

Projection pursuit

Signal mixtures tend to have Gaussian probability density functions, and source signals tend to have non-Gaussian probability density functions.  Each source signal can be extracted from a set of signal mixtures by taking the inner product of a weight vector and those signal mixtures where this inner product provides an orthogonal projection of the signal mixtures.  The remaining challenge is finding such a weight vector. One type of method for doing so is projection pursuit.

Projection pursuit seeks one projection at a time such that the extracted signal is as non-Gaussian as possible. This contrasts with ICA, which typically extracts M signals simultaneously from M signal mixtures, which requires estimating a M × M unmixing matrix. One practical advantage of projection pursuit over ICA is that fewer than M signals can be extracted if required, where each source signal is extracted from M signal mixtures using an M-element weight vector.

We can use kurtosis to recover the multiple source signal by finding the correct weight vectors with the use of projection pursuit.

The kurtosis of the probability density function of a signal, for a finite sample, is computed as

where  is the sample mean of , the extracted signals. The constant 3 ensures that Gaussian signals have zero kurtosis, Super-Gaussian signals have positive kurtosis, and Sub-Gaussian signals have negative kurtosis. The denominator is the variance of , and ensures that the measured kurtosis takes account of signal variance. The goal of projection pursuit is to maximize the kurtosis, and make the extracted signal as non-normal as possible.

Using kurtosis as a measure of non-normality, we can now examine how the kurtosis of a signal  extracted from a set of M mixtures  varies as the weight vector  is rotated around the origin. Given our assumption that each source signal  is super-gaussian we would expect:
the kurtosis of the extracted signal  to be maximal precisely when .
the kurtosis of the extracted signal  to be maximal when  is orthogonal to the projected axes  or , because we know the optimal weight vector should be orthogonal to a transformed axis  or .

For multiple source mixture signals, we can use kurtosis and Gram-Schmidt Orthogonalization (GSO) to recover the signals. Given M signal mixtures in an M-dimensional space, GSO project these data points onto an (M-1)-dimensional space by using the weight vector. We can guarantee the independence of the extracted signals with the use of GSO.

In order to find the correct value of , we can use gradient descent method.  We first of all whiten the data, and transform  into a new mixture , which has unit variance, and . This process can be achieved by applying Singular value decomposition to ,

Rescaling each vector , and let . The signal extracted by a weighted vector  is . If the weight vector w has unit length, then the variance of y is also 1, that is . The kurtosis can thus be written as:

The updating process for  is:

where  is a small constant to guarantee that  converges to the optimal solution. After each update, we normalize , and set , and repeat the updating process until convergence. We can also use another algorithm to update the weight vector .

Another approach is using negentropy instead of kurtosis. Using negentropy is a more robust method than kurtosis, as kurtosis is very sensitive to outliers. The negentropy methods are based on an important property of Gaussian distribution: a Gaussian variable has the largest entropy among all continuous random variables of equal variance. This is also the reason why we want to find the most nongaussian variables. A simple proof can be found in Differential entropy.

y is a Gaussian random variable of the same covariance matrix as x

An approximation for negentropy is

A proof can be found in the original papers of Comon; it has been reproduced in the book Independent Component Analysis by Aapo Hyvärinen, Juha Karhunen, and Erkki Oja This approximation also suffers from the same problem as kurtosis (sensitivity to outliers). Other approaches have been developed.

A choice of  and  are
 and

Based on infomax

Infomax ICA is essentially a multivariate, parallel version of projection pursuit. Whereas projection pursuit extracts a series of signals one at a time from a set of M signal mixtures, ICA extracts M signals in parallel. This tends to make ICA more robust than projection pursuit.

The projection pursuit method uses Gram-Schmidt orthogonalization to ensure the independence of the extracted signal, while ICA use infomax and maximum likelihood estimate to ensure the independence of the extracted signal. The Non-Normality of the extracted signal is achieved by assigning an appropriate model, or prior, for the signal.

The process of ICA based on infomax in short is: given a set of signal mixtures  and a set of identical independent model cumulative distribution functions(cdfs) , we seek the unmixing matrix  which maximizes the joint entropy of the signals , where  are the signals extracted by . Given the optimal , the signals  have maximum entropy and are therefore independent, which ensures that the extracted signals  are also independent.  is an invertible function, and is the signal model. Note that if the source signal model probability density function  matches the probability density function of the extracted signal , then maximizing the joint entropy of  also maximizes the amount of mutual information between  and . For this reason, using entropy to extract independent signals is known as infomax.

Consider the entropy of the vector variable , where  is the set of signals extracted by the unmixing matrix . For a finite set of values sampled from a distribution with pdf , the entropy of  can be estimated as:

The joint pdf  can be shown to be related to the joint pdf  of the extracted signals by the multivariate form:

where  is the Jacobian matrix. We have , and  is the pdf assumed for source signals , therefore,

therefore,

We know that when ,  is of uniform distribution, and  is maximized. Since

where  is the absolute value of the determinant of the unmixing matrix . Therefore,

so,

since , and maximizing  does not affect , so we can maximize the function

to achieve the independence of extracted signal.

If there are M marginal pdfs of the model joint pdf  are independent and use the commonly super-gaussian model pdf for the source signals , then we have

In the sum, given an observed signal mixture  , the corresponding set of extracted signals    and source signal model ,  we can find the optimal unmixing matrix , and make the extracted signals independent and non-gaussian. Like the projection pursuit situation, we can use gradient descent method to find the optimal solution of the unmixing matrix.

Based on maximum likelihood estimation

Maximum likelihood estimation (MLE) is a standard statistical tool for finding parameter values (e.g. the unmixing matrix ) that provide the best fit of some data (e.g., the extracted signals ) to a given a model (e.g., the assumed joint probability density function (pdf)  of source signals).

The ML "model" includes a specification of a pdf, which in this case is the pdf  of the unknown source signals . Using ML ICA, the objective is to find an unmixing matrix that yields extracted signals  with a joint pdf as similar as possible to the joint pdf  of the unknown source signals .

MLE is thus based on the assumption that if the model pdf  and the model parameters  are correct then a high probability should be obtained for the data  that were actually observed. Conversely, if  is far from the correct parameter values then a low probability of the observed data would be expected.

Using MLE, we call the probability of the observed data for a given set of model parameter values (e.g., a pdf  and a matrix ) the likelihood of the model parameter values given the observed data.

We define a likelihood function  of :

This equals to the probability density at , since .

Thus, if we wish to find a  that is most likely to have generated the observed mixtures  from the unknown source signals  with pdf  then we need only find that  which maximizes the likelihood . The unmixing matrix that maximizes equation is known as the MLE of the optimal unmixing matrix.

It is common practice to use the log likelihood, because this is easier to evaluate. As the logarithm is a monotonic function, the  that maximizes the function  also maximizes its logarithm . This allows us to take the logarithm of equation above, which yields the log likelihood function

If we substitute a commonly used high-Kurtosis model pdf for the source signals  then we have

This matrix  that maximizes this function is the maximum likelihood estimation.

History and background

The early general framework for independent component analysis was introduced by Jeanny Hérault and Bernard Ans from 1984, further developed by Christian Jutten in 1985 and 1986, and refined by Pierre Comon in 1991, and popularized in his paper of 1994. In 1995, Tony Bell and Terry Sejnowski introduced a fast and efficient ICA algorithm based on infomax, a principle introduced by Ralph Linsker in 1987.

There are many algorithms available in the literature which do ICA. A largely used one, including in industrial applications, is the FastICA algorithm, developed by Hyvärinen and Oja, which uses the negentropy as cost function. Other examples are rather related to blind source separation where a more general approach is used. For example, one can drop the independence assumption and separate mutually correlated signals, thus, statistically "dependent" signals. Sepp Hochreiter and Jürgen Schmidhuber showed how to obtain non-linear ICA or source separation as a by-product of regularization (1999). Their method does not require a priori knowledge about the number of independent sources.

Applications

ICA can be extended to analyze non-physical signals. For instance, ICA has been applied to discover discussion topics on a bag of news list archives.

Some ICA applications are listed below:

 optical Imaging of neurons
 neuronal spike sorting
 face recognition
 modelling receptive fields of primary visual neurons
 predicting stock market prices
 mobile phone communications
 colour based detection of the ripeness of tomatoes
 removing artifacts, such as eye blinks, from EEG data.
 predicting decision-making using EEG
 analysis of changes in gene expression over time in single cell RNA-sequencing experiments.
 studies of the resting state network of the brain.
 astronomy and cosmology
 finance

Availability

ICA can be applied through the following software:

 SAS PROC ICA
 R ICA package
 scikit-learn Python implementation sklearn.decomposition.FastICA

See also

 Blind deconvolution
 Factor analysis
 Hilbert spectrum
 Image processing
 Non-negative matrix factorization (NMF)
 Nonlinear dimensionality reduction
 Projection pursuit
 Varimax rotation

Notes

References

 Comon, Pierre (1994): "Independent Component Analysis: a new concept?", Signal Processing, 36(3):287–314 (The original paper describing the concept of ICA)
 Hyvärinen, A.; Karhunen, J.; Oja, E. (2001): Independent Component Analysis, New York: Wiley,  ( Introductory chapter )
 Hyvärinen, A.; Oja, E. (2000): "Independent Component Analysis: Algorithms and Application", Neural Networks, 13(4-5):411-430. (Technical but pedagogical introduction).
 Comon, P.; Jutten C., (2010): Handbook of Blind Source Separation, Independent Component Analysis and Applications. Academic Press, Oxford UK.
 Lee, T.-W. (1998): Independent component analysis: Theory and applications, Boston, Mass: Kluwer Academic Publishers,
 Acharyya, Ranjan (2008): A New Approach for Blind Source Separation of Convolutive Sources - Wavelet Based Separation Using Shrinkage Function   (this book focuses on unsupervised learning with Blind Source Separation)

External links
 What is independent component analysis? by Aapo Hyvärinen
 Independent Component Analysis: A Tutorial by Aapo Hyvärinen
 A Tutorial on Independent Component Analysis
 FastICA as a package for Matlab, in R language, C++
 ICALAB Toolboxes for Matlab, developed at RIKEN
 High Performance Signal Analysis Toolkit provides C++ implementations of FastICA and Infomax
 ICA toolbox Matlab tools for ICA with Bell-Sejnowski, Molgedey-Schuster and mean field ICA. Developed at DTU.
 Demonstration of the cocktail party problem
 EEGLAB Toolbox ICA of EEG for Matlab, developed at UCSD.
 FMRLAB Toolbox ICA of fMRI for Matlab, developed at UCSD
 MELODIC, part of the FMRIB Software Library.
 Discussion of ICA used in a biomedical shape-representation context
 FastICA, CuBICA, JADE and TDSEP algorithm for Python and more...
 Group ICA Toolbox and Fusion ICA Toolbox
 Tutorial: Using ICA for cleaning EEG signals

Signal estimation
Dimension reduction

Independent component analysis


Beisfjord-massakren i Norge fandt sted natten til 18. juli 1942 i Beisfjord i Norge. Beisfjord var en krigsfangelejr 12 km sydøst for Narvik oprettet af SS i juni 1942 for 900 jugoslaviske fanger. Beisfjord var den fangelejr i Norge, hvor flest jugoslaviske fanger døde: 748 af 900 på fire måneder. 4.268 jugoslaviske fanger opholdt sig i Norge fra juni 1942 til 1945; omkring 2.400 blev dræbt eller døde af sygdom og underernæring. De fleste var taget til fange som partisaner eller sympatisører i Jugoslavien og afventede dødsstraf. I stedet for sendte SS dem til Norge for at arbejde i Trøndelag, Nordland og Finnmark i 25 lejre. I den første periode, da SS havde ansvaret, døde 72 % af de jugoslaviske fanger. Da de blev overført til Wehrmacht og fik krigsfangestatus, sank dødsraten til 18 %.

Ved massakren i juli 1942 blev 288 fanger dræbt i Lager I Beisfjord, som den tyske besættelsesmagt kaldte lejren. Den har været beskrevet som en udryddelseslejr;   den er også blevet kaldt "koncentrationslejr" og "serberlejr".

Den tyske rigskommissær i Norge, Josef Terboven, beordrede massakren nogle dage tidligere.

Baggrund
I april 1941 angreb Tyskland og landets allierede kongeriget Jugoslavien. Efter ti dages kampe blev en ny stat oprettet: Kroatien, styret af et tyskvenligt marionetregime, der slog hårdt ned på alle former for modstand. Store dele af befolkningen blev arresteret og interneret i fangelejre. Mest udsat var serbere. Lederen for den tyske besættelsesmagt i Norge, Josef Terboven, opdagede, at jugoslaviske lejre var overfyldte, og han fik nogle af fangerne sendt til Norge som arbejdskraft. I modsætning til de sovjetiske krigsfanger var jugoslaverne ikke taget til fange i krig og blev langt værre behandlet. Jugoslaverne var arresteret som fjender af regimet og dømt til døden. Uden krigsfangestatus var de heller ikke beskyttet af Genèvekonventionen, som indeholder bestemmelser om behandlingen af krigsfanger. SS omtalte dem som mordere og banditter, der fortjente at dø. De jugoslaviske fanger blev udsat for tortur og dræbt i en målestok, som ellers kun kendes fra jødeudryddelserne. Det første år døde henved 2.000. SS styrede lejrene; men vagthold sørgede nordmænd i NS-organisationen Hirden for. Otte af ti jugoslaviske fanger døde af tortur, sult, sygdom eller regulær henrettelse det første år. Dødeligheden var langt højere end for sovjetiske soldater. Eksempelvis blev de tvunget til at arbejde med bar overkrop i det kolde klima.

Vejvæsenet og statsbanerne
Udbygningen af et godt vej- og jernbanenet i Norge var vigtigt for den tyske besættelsesmagt, der havde brug for at flytte sine tropper hurtigt og sikkert ind mod Sovjetunionens grænse. Dertil behøvede den tyske krigsindustri sikker og effektiv tilgang til metal; først og fremmest jernmalm fra Kiruna og nikkel fra Petsamo. Skibstransport var udelukket, da allierede fly lurede langs den norske kyst, og Østersøen frøs til om vinteren. Ikke mindre end 140.000 tvangsarbejdere kom til Norge under anden verdenskrig; de 20.000 døde under arbejdet med udbedring og udbygning af jernbaner, veje, lufthavne og anden infrastruktur.

De jugoslaviske fanger blev først sat til at udbygge vejnettet i Norge, hovedsageligt på strækningerne Rognan–Langset, Elsfjord–Korgen, Mo–Krokstrand og Karasjok–den finske grænse, og dertil Bjørnefjell-vejen. I tilknytning til disse strækninger lå fangelejrene Karasjok, Beisfjord, Botn, Osen og Korgen, bygget af Vejvæsenet. På to af vejstrækningerne ledede Vejvæsenet også arbejdet.

Lejren i Beisfjord

24. juni 1942 lagde Kerkplein til i Narvik havn. På Fagernes kaj blev 900 fanger landsat. Derfra gik de ti km til Beisfjord og den nybyggede fangelejr. På vejen faldt fanger om af udmattelse, og vagterne slog dem med stokke eller stak dem med bajonetter. Fem fanger omkom langs vejen og én blev skudt. Også norske vagter deltog i mishandlingen. I lejren blev fangerne fordelt i syv barakker på en stor mark midt i den lille bygd. Det var også barakker til vask, køkken og latriner. Ved siden af lå lejrledelsens og vagternes barakker. Der var omkring 150 tyske vagter fra Ordnungspolizei under SS; dertil omkring 50 norske vagter fra Hirdvaktbataljonen, senere SS-Vaktbataljon. Nordmændene havde meldt sig frivilligt, lokket af gode økonomiske betingelser. Fangerne blev brutalt behandlet; de måtte ikke opholde sig inde i barakkerne mellem kl. 5 om morgenen og kl. 20 aften, og selv i regn og kulde skulle de gå halvnøgne rundt. Officerer og vagter gik omkring i lejren og fik tiden til at gå med at beordre fanger til at løbe lejren rundt, eller køre trillebør med medfanger i. Magtede de det ikke, blev de slået. De fik dagligt kun 250 gram brød, lidt margarine og en suppe med nogle grøntsager i. De syge blev indlagt i barakker, hvor der hverken var senge eller madrasser, så de var nødt til at ligge direkte på gulvet. Antallet syge og nedbrudte fanger forøgedes hurtigt:
 5. juli 1942: 87 syge / 800 raske
 10. juli 1942: 175 syge / 710 raske
 14. juli 1942: 205 syge / 677 raske
 16. juli 1942: 260 syge / 618 raske
 17. juli 1942: 310 syge / 566 raske

12. juli 1942 kom nogle tyske officerer, en tysk og en norsk læge på inspektion. Under forhør af den britiske krigsforbryderkommisionen i efteråret 1945, udtalte den norske læge: "Alle fanger havde lus og var ubeskriveligt afmagrede. De fleste i snavset og forrevet tøj og uden sko. De havde sår og bylder over hele kroppen fra dårlig mad og mangel på hygiejne. De syge lå som sild. De lå direkte på gulvet uden nogen form for medicinsk hjælp. Der var medicin, men det var forbudt at bruge den på serbere. Hver morgen var der 15-20 nye tilfælde af isolation, og hver morgen døde omtrent det samme antal. De døde blev taget udenfor og smidt i massegrave. Disse mennesker havde arbejdet under absolut ubeskrivelige omstændigheder." SS-officerernes mistanke om tyfus var nu bekræftet af lægen. Tyfoidfeber må diagnosticeres ved prøver af blod eller afføring. Den norske læge tog 85 fanger ud, som angiveligt havde tyfus. Han skal ikke have undersøgt dem grundigt, med udpeget dem på afstand. De blev umiddelbart sendt til sygebarakken. Konsekvenserne for dem, der fejlagtigt fik diagnosen tyfus, var forfærdelig. Rigskommissær Terboven ankom til lejren 15. juli. Lejren blev delt i to med pigtråd. Den tyske læge samlede de syge i to barakker. Derefter startede arbejdet med at få gravet store grøfter udenfor pigtrådshegnet.

Massakren
Om aftenen 17. juli blev 588 uden tyfus ført ud af lejren med kurs mod et karantænested på Bjørnefjell. 287 blev tilbage i sygebarakkerne. Vagterne satte maskingeværer op på taget af en barak og i et vagttårn, og i grupper på 20 blev de syge ført ud til grøfterne udenfor pigtråden. Her blev de skudt. Nogle fanger barrikaderede sig i den ene barak. Så satte SS ild til barakken, og de syge indebrændte. De to yngste fanger var 14 år gamle, den ældste 58.

Det er den størst kendte massakre på norsk jord. 17 norske fangevogtere deltog.

Lejren på Bjørnfjell
De 588 fanger, der måtte gå de 30 km til Bjørnfjell i karantæne, måtte i to uger overnatte udendørs. Kun vogternes barakker stod færdige. Fangerne måtte i gang med at bygge barakker til dem selv. SS inspicerede fangerne nøje og skød uden videre de syge. 22. juli, to dage efter ankomsten, måtte alle fanger løbe lejren rundt seks gange. Ti fanger klarede det ikke og blev skudt nede ved vandet i en grav, der snart fyldtes af døde. Den type løb blev gentaget med flere døde som resultat. Fangerne skulle anlægge vej til grænsen, men manglede værktøj. De forsøgte at holde modet oppe med at synge sange hjemmefra. Efter fem uger på Bjørnfjell var 242 fanger døde. De sidste 43 var syge, der blev skudt under tilbageturen til Beisfjord. 346 fanger returnerede til Beisfjord 25. august.

Retsopgøret
Syv af de omkring 20 SS-officerer, der arbejdede i lejrene i Beisfjord og Øvre Jernvann, blev arresteret og i foråret 1946 sendt til Beograd, hvor de fik dødsstraf. I 2012 fandt man også navnene på de 400 norske fangevogtere, der dog ikke blev offentliggjort. Vogterne kom fra hele Norge, dog flest fra Østlandet. Oplæringen blev givet af tyskere i en egen lejr ved Halden. Efter krigen blev kun 50 af fangevogterne tiltalt og dømt. Halvdelen blev dømt for drab, resten for grov mishandling. Under retssagerne var det helt klart, at de tiltalte støttede hinanden i bortforklaringer. I Norsk rettstidende er flere sager fremlagt. Den ene, Lars S., 43 år gammel fra Vestlandet, var NS-medlem og far til fire, da han tog vagttjeneste i Osen lejr i Vefsn, hvor fangerne arbejdede på vejen over Korgfjellet. 11 syge fanger skulle blive liggende på jorden, og SS-officeren bad Lars S. om at skyde dem, der forsøgte at rejse sig. En fange løftede hovedet, og Lars S. skød ham. Efter krigen blev han idømt syv års tvangsarbejde. Hans appel førte kun til, at Højesteret skærpede dommen til 16 års fængsel for drab. Alligevel slap Lars S. ud efter fem og et halvt år. Flere af de drabsdømte fik ellers 12 års fængsel; men allerede i 1948 blev straffene halveret.

I 1949 blev et mindesmærke rejst til minde om de jugoslaviske fanger i Beisfjord.

Efter krigen åbnedes massegravene, og de døde blev gravlagt blandt andet i Narvik og på Tjøtta.

Reaktioner på massakren

Kritik af manglende fokus på nordmænds deltagelse
Hirden var oprindeligt NS' eget elitekorps, en form for politisk politi med klart definerede opgaver indenfor vagthold og orden. Under den tyske besættelse gjorde Quisling hirdmedlemskab obligatorisk for alle op til 30 år, og fra 1943 var Hirden formelt en del af den norske hær. Der dannede sig også et indtryk af Hirden som tyskernes håndlangere. Dels som vagter i arbejdslejrene, hvor de deltog i vilkårlig sadisme og grufulde voldshandlinger. Dels som rekrutter (dog ofte under pres) til Waffen-SS og soldater på Østfronten.

Flere i Hirdvaktbataljonen var yderst brutale og blottet for disciplin. Selv tyskerne mente, at de gik langt over stregen; mens andre foretog henrettelser med trusler om dødsstraf, hvis de afslog at følge de brutale ordrer. Juraprofessor Nils Christie har udtalt: "I dag sender vi skoleungdom til Auschwitz for at lære om folkemord og ondskab, tortur og lidelser. De fleste af dem aner intet om, at vi havde det samme her i landet. Vi kunne ha' sendt de unge nordpå i stedet for."

Leder ved Simon Wiesenthal-centerets afdeling i Jerusalem
I 2013 ønskede Efraim Zuroff, direktør ved Simon Wiesenthal-centeret i Jerusalem, at genoptage jagten på nulevende soldater fra SS-Division Wiking, som blandt andet var med til at massakrere jøder på Østfronten for 70 år siden; på soldater, der tjenestegjorde ved Hirdvaktbataljonen i Nordnorge og udsatte serbiske krigsfanger for grusomme overgreb og på de nordmænd, der deltog i arrestationerne af jøder under krigen. Tidligere var forældelsesfristen for krigsforbrydelser 25 år, og krigsforbrydere benyttede Norge som frihavn for at slippe for tiltale. Forældelsesfristen blev derfor fjernet.

Noter

Litteratur
  Beisfjordska tragedija (1988).
 Beisfjordtragedien (1989, 2013; begge på norsk). Oslo: Grøndahl, 1989.
  Store drømmer og harde realiteter (2014)

Se også
 Besættelsesmagtens fangelejre i Norge under Anden verdenskrig

Eksterne henvisninger
 dagbladet.no
 Eirik Veums liste over de 20 værste torturister i Hirden
 Photo of the unveiling (in 2011) of a monument dedicated to the victims of the massacre
 Billede af lejren
 Billede af lejren

Massakrer i Norge
Norge under 2. verdenskrig
Narvik

Beisfjord-massakren


Raluca Alexandra Prună (n. 24 septembrie 1969, București, România) a fost ministrul justiției în România din 17 noiembrie 2015 până la încheierea mandatului în urma alegerilor din decembrie 2016.

Educație
Raluca Alexandra Prună este licențiată în drept și filosofie. A absolvit Facultatea de Drept, Universitatea Ecologică București în anul 1994 și a obținut licența în drept la Universitatea Al. I. Cuza Iași, în februarie 1996. În perioada 1992 - 1997 a urmat cursurile Facultății de Filosofie, Universitatea București și în perioada 1997 - 1998 a urmat cursurile de masterat la Universitatea Central Europeană, Departamentul de Științe Politice, (CEU) Budapesta, Ungaria.

R. Prună a fost bursier Tempus în perioada martie–iulie 1997 la Universitatea Paris VII Nanterre, Departamentul de Filosofie. În anul 2002 Raluca Alexandra Prună și-a întrerupt programul doctoral început în anul 2000 la Universitatea București, Facultatea de Filosofie.

Carieră
Raluca Prună este de profesie avocat și are o experiență de 20 de ani în domeniul justiției, inclusiv la nivelul instituțiilor Uniunii Europene. Anterior numirii în funcția de ministru al justiției a ocupat, la Comisia Europeană, funcția de consilier coordonator la Direcția Generală Piața internă, antreprenoriat, industrie și IMM-uri, Unitatea Politică privind piața unică, recunoașterea reciprocă și supravegherea pieței. Din anul 2007 a ocupat în Comisia Europeană, pe rând diverse funcții: jurist și coordonator de program la Direcția Generală Justiție, Libertate și Securitate, funcționar responsabil cu politicile privind lupta împotriva criminalității organizate la Direcția Generală Afaceri Interne, șef de unitate la Direcția Generală Antreprenoriat și Industrie și șef de unitate la Direcția Generală Piața internă, antreprenoriat, industrie și IMM-uri.
În perioada negocierilor pentru aderarea la Uniunea Europeană (2000-2004), a fost manager al portofoliului Justiție, afaceri interne și anticorupție la Delegația Comisiei Europene în România.În 2005 și 2006, a fost jurist lingvist la Consiliul Uniunii Europene.
Raluca Prună a fost membru fondator și președinte al organizației neguvernamentale Transparency International România.

Experiența didactică
În perioada octombrie 1996 - iulie 2001 a fost asistent universitar la Universitatea din București, Facultatea de Filosofie și la Școala Națională de Studii Politice și Administrative Școala Națională de Studii Politice și Administrative, Facultatea de Științe Politice, București.

Legături externe

 Ministrul Justiției, Raluca Prună, acordă primul interviu de la preluarea funcției la Adevărul Live
 Interviu Raluca Prună, Ministrul justiției la Jurnalul de seară DIGI 24
 Raluca Prună: Nu cred că problema sistemului judiciar sunt ofițerii acoperiți - Interviu Revista 22

Nașteri în 1969
Juriști români
Miniștri de justiție ai României
Guvernul Cioloș
Bucureșteni
Oameni în viață

Raluca Prună


هذه التصفيات التأهيلية بطولة أوروبا لكرة القدم للناشئين تحت 19 سنة 2009 التي ستقام في فترة من أكتوبر إلى نوفمبر 2008. البطولة ستقام في أوكرانيا

المجموعة الأولى

المجموعة الثانية

المجموعة الثالثة

المجموعة الرابعة

المجموعة الخامسة

المجموعة السادسة

المجموعة السابعة

المجموعة الثامنة

المجموعة التاسعة

المجموعة العاشرة

المجموعة الحادية عشرة

المجموعة الثانية عشرة

المجموعة الثالثة عشرة

كرة القدم في 2009

تصفيات بطولة أوروبا لكرة القدم للناشئين تحت 19 سنة 2009


An Micraira compacta in uska species han Liliopsida nga ginhulagway ni Michael Lazarides. An Micraira compacta in nahilalakip ha genus nga Micraira, ngan familia nga Poaceae. Waray hini subspecies nga nakalista.

Mga kasarigan

Micraira

Micraira compacta


قصر الثقافة في ياش شمالي رومانيا (بالرومانية:Palatul Culturii), استخدم كقصر عدلي للمدينة حتى عام 1955, ثم حول إلى مجمع متاحف ويحوي مكتبة جيورجي اساشي الوطنية ويضم عدة صالات للمعارض وللمؤتمرات.

تاريخيا
بدأ بناء القصر عام 1906 على انقاض القصر الملكي المولدافي الذي كان مبنيا على الطراز الكلاسيكي الجديد عام 1434 والذي كان يحوي 365 غرفة على عدد أيام السنة ثم تم هدمه عام 1904.

القصر الجديد تم تصميمه من قبل المعماري الروماني بيرنيدي على الطراز القوطي الجديد, خلال الحرب العالمية الأولى اوقف العمل بالبناء لنقص الموارد, وبعد نهاية الحرب تم اكمال البناء تحت أمر فرديناند الأول ملك رومانيا وذلك في 11 اوكتوبر عام 1925.

مساحة القصر تمتد 36.000 متر مربع وغرف واسعة بعدد 298 غرفة, 92 نافذة على الواجهة وأخرى 36 داخل المبنى.

المتاحف
يعتبر القصر كمجمع للعديد من المتاحف  حيث يضم المتاحف التالية:
 متحف الفنون الجميلة : يضم أكثر من 8000 لوحة منها 1000 من التراث الوطني لفنانين رومان وأجانب.
 متحف التاريخ المولدافي : يحوي أكثر من 35000 قطعة أثرية للعديد من المواضيع من تحف, موزاييك, كتب, قطع أثرية وغيرها.
 متحف التراث الشعبي
 متحف العلوم والتكنولوجيا

مراجع

وصلات خارجية
 الموقع الرسمي

قصور
قصور رومانيا
مبان ومنشآت اكتملت في 1925
متاحف تاريخية في رومانيا
متاحف علوم
متاحف فنية ومعارض في رومانيا
مواقع أثرية
مبان ومنشآت في ياش
متاحف في ياش

قصر الثقافة (ياش)


Leubucó est une petite localité dans la province de Buenos Aires, en Argentine. Elle est située dans le partido d'Adolfo Alsina.

Géographie
Leubucó se situe à  au sud-ouest de Buenos Aires, à  au sud-ouest de Salliqueló et à  au nord-ouest de Carhué, chef-lieu du partido. Aucun cours d'eau ne traverse la localité, bien qu'elle soit entourée de plusieurs lagunes.

Transports
La localité est reliée à Salliqueló et Rivera par le chemin provincial secondaire 001-05, mais aussi à Carhué par le chemin provincial secondaire 001-01. Leubucó entretenait une liaison ferroviaire avec Salliqueló et Rivera par le Chemin de fer Domingo Faustino Sarmiento (ligne Salliqueló-Rivera).

Toponymie
Le nom Leubucó fait référence à la localité et ancienne capitale ranquel de Leubucó, dans la province de La Pampa. Le nom signifie « source qui court », composé des mots mapudungún ḻewfü (« courant ») et ko (« eau »).

Le nom de Villa Martín Ayerúa rend hommage à Martín Ayerúa, ancien propriétaire des terrains et père du fondateur de la localité. Ce toponyme a lentement été remplacé par celui de la gare, Leubucó.

Histoire
Le  est mise en service la ligne de chemin de fer de Salliqueló à Rivera, puis, le  est ouverte la gare de Leubucó. Les terrains appartenaient à Martín Ayerúa à partir de 1919, qui les léga à sont fils Francisco Martín Ayerúa. Celui-ci demanda l'autorisation de fonder un village autour de la gare, qui devait prendre le nom de Villa Martín Ayerúa.. La fondation a été autorisée le , devenue date officielle de fondation de la ville.

Population et société
La localité a été désignée comme population rurale dispersée durant les recensements de 2001 et 2010, sa population est estimée à  par le partido. Elle dispose tout de même d'une délégation municipale, la plus petite du partido en matière de population, représentée par María Soledad Nassini.

On trouve une école primaire à Leubucó. De nombreux services et commerces ont fermé après la fermeture de la gare dans les années 1970.

Économie
L'économie de Leubucó est exclusivement agricole. Anciennement, la localité disposait de commerces et de services, et exportait ses produits jusqu'à Buenos Aires, mais la fermeture de la gare annonça la fin de ces activités.

Sports

Football

Culture et loisirs

Patrimoine culturel et touristique
 Ancienne gare de la localité, inaugurée en 1909.

Personnalités

Notes et références

Liens externes
  Carte détaillée de la province de Buenos Aires
  Site officiel du partido d'Adolfo Alsina, section dédiée à Leubucó
  site officiel du partido.
 Coordonnées :

Ville dans la province de Buenos Aires
Division administrative fondée en 1930

Leubucó (Buenos Aires)


Ekonomijana je knjižnica Ekonomskog fakulteta u Osijeku.

Povijest

Knjižnica Ekonomskog fakulteta u Osijeku osnovana je 31. svibnja 1961., a ime Ekonomijana ponijela je 2021. godine povodom proslave 60 godina rada.

Ekonomijana je istoimeni naziv za nakladničku cjelinu Ekonomskog fakuleta u Osijeku. Nakladnička cjelina Ekonomijana uspostavljena je 31. svibnja 2021. godine.

Vanjske poveznice

Ekonomijana - knjižnica Ekonomskog fakulteta u Osijeku

 Ave, OsEconomia! (Jasna Horvat, 2021. Osijek: Ekonomski fakultet u Osijeku) - spomenica objavljena povodom šezdesete obljetnice

Sveučilište Josipa Jurja Strossmayera u Osijeku
Fakulteti u Hrvatskoj
Ekonomska učilišta

Ekonomijana