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Thrissur () (originally Thiru Siva Peroor and previously known by its anglicised form as Trichur, is the fourth largest city, the (Pop. 1,854,783) and the 20th largest in. It is also the headquarters of the, the City is built around a 65-acre (26 ha) hillock called the which seats the. Thrissur was once the capital of the, it is located 300 kilometres (186 mi) towards north-west of the state capital. Thrissur [തൃശ്ശൂർ] is also known as the Cultural Capital of because of its cultural, spiritual and religious leanings throughout history.

It contains the, and. The city hosts the festival, the most colourful and spectacular temple festival in, the festival is held at the in April or May.

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Thrissur has a large number of well-known temples including the, and, and the as well as two famous churches, the and the, the largest Christian church in India. Thrissur has historically been a centre of Hindu scholarship, the city has one of the most important temples of, that is the. The district is also home of one of the most holiest temples, the. Christianity, and entered into the through the. The works of scholars and writings claim to have set foot in near Thrissur 2,000 years ago. (AD 51–52) India's first mosque,, opened in AD 629. Thrissur has opened the gates for,,, and English.

The city has served as an incubator for many entrepreneurs, and is a major financial and commercial hub of Kerala, it flexes its economic muscle in as the headquarters of three major,, and Ltd and a clutch of. The city is also a big centre for shopping in for silks and gold jewellery. Thrissur attracts the largest number of domestic tourists in. Apart from being the cultural nerve centre of, it is also a major academic hub and is home to several educational institutions including the,,,,,, and. Contents • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • Etymology [ ] The name Thrissur is a shortened form of Thiru-Shiva-Per-Ur (Tamil /: തിരു-ശിവ-പേര്-ഊര്, Lord-Shiva-Name-Town) literally translates to 'The City or Town with the name of the 'Lord '. The name owes itself to the most prominent feature of the city, that is the, which has as its presiding deity.

Alternately, Thri-Shiva-Perur (: ത്രി-ശിവ-പേരൂർ, Three-Shiva-Palace) means the place with three famous Shiva temples which are said to be – the Vadakkumnathan Temple, Kottapuram Shiva temple and the. Thrissur was known by its anglicised name Trichur until 1990, when the government decided to replace it with its Malayalam name. Thrissur was also known as 'Vrishabhadripuram' (Kailasam of the South) in ancient days. The 15 feet (4.6 m) in high and 12 feet 4 inches (3.76 m) wide menhir The monument is in granite and is of the type, the monument in is 15 feet (4.6 m) in height and 12 feet 4 inches (3.76 m) wide. Since 1944, it has been protected by the Department of Archaeology, the monument is locally known as Padakkallu or Pulachikkallu.

These menhirs are memorials put up at burial sites for the departed souls, they belong to the Megalithic Age of, which is roughly estimated between 1000 BCE and 500 CE. All such monuments have not been dated exactly, some experts are of the view that these are the remnants of the Neolithic Age in the development of human technology.

The is also believed to be a monument belonging to the Sangam period in the South Indian history. Another monolithic monuments like and rock-cut caves are at Porkulam, Chiramanengad, Eyyal, Kattakambal and Kakkad. According to historians, the are burial sites.

Though most of the monuments were well protected, the dolmen at Porkulam was in a neglected condition, the monument excavated under eminent Archaeologist B. Thapar, between 1949 and 1950, was under the Department of Archaeology. Another megalithic monument is situated at Ariyannur in Thrissur, this place has unravelled monuments such as the Kudakkallu or Thoppikkallu (Mushroom stones or Umbrella stones) and 'Munimada' (Saint's abode). The laterite hillocks of Ariyannur rise to about 50 metres. Another reference in Ariyannur dates back to the early 15th century in the poem Chandrotsavam. Image of main entrance of seen from from Illustrated Guide to the South Indian Railway Pre-colonial history [ ] The region can claim to have played a significant part in fostering the trade relations between and the outside world in the ancient and medieval period, the early political history of Thrissur is interlinked with that of the of the, who ruled over vast portions of and.

After the Cheras, the place was later ruled by the (Perumpadapu Swaroopam). Later, a powerful dynasty known as of captured most of the Thrissur in 14th and 15th century. Colonial period [ ] Next was the turn of Portuguese who ruled Thrissur in the 16th century; in the beginning of the 17th century the Portuguese power was reduced and Dutch became the main power. With the help of Dutch, recaptured Thrissur from in 1710. A marriage procession going through the High Road, Thrissur City. The modern City of Thrissur rose to importance after ascended the throne of (1769–1805), he changed the capital of to Thrissur from and abolished the power of community, which controlled most of the temples of. The maharaja destroyed the forest around the which seats the, and started the most spectacular cultural festival called.

Laid the modern foundation stone of Thrissur and made the city into a major financial and commercial hub of, by inviting families and from adjoining areas. However, during 1750–60, the Sultan of Mysore, attacked Thrissur and became tributary of the. Tipu Sultan, his son led another invasion in 1786 to Thrissur, where he destroyed the churches of community and Hindu temples. Tipu Sultan's Army set fire to the church at and attacked the church, the economy of Thrissur totally collapsed because of this invasion. Later he made a retreat from Thrissur, which served as the headquarters of Kerala region, after the Srirangapattanam war; in the meantime,, the successor of signed a treaty with East Indian Company, and made a subsidiary of the British. Anti-Colonial movements [ ].

The first known map of Thrissur City with prepared by in 1816 The Indian freedom movement struggle also grew in momentum in Thrissur after a Committee was formed in 1919 of the; in 1921, the Civil Disobedience Movement also attracted a large number of people into the freedom struggle. In 1927 visited Vivekodayam School in the city; in 1934, father of the nation, again visited the city for the housewarming of Barrister Krishna Menon. The house afterwards was known 'Gandhi Mandiram' in Chembukkavu; in the mean time,, the controversial Diwan of from 1935 to 1941, was developing City by constructing and. Even now also two monuments remain as the epicentre of politics.

DR M R Menon, a minister in Government of was instrumental in building the and the Municipal Office Road. He even concerted and other peripheries of the city road. An old photo of.

Rao, advisor to the Rajapramukh and acting, is another person who Thrissurian is indebted to, he expanded Thrissur City by shifting all the administrative and government offices like Thrissur Collectorate to from Chembukavu., is another gift from, the controversial former education minister who introduced Kerala Education Act., the former Chief Minister of Kerala gifted in 1971, a university for all agricultural related activities., the of politics started his career in Thrissur as a painter. Later on he became the 'Leader' of city, during his regime and Poonkunnam Over Bridge was built., the Comptroller and Auditor General of India, is another person who turned fortunes of the city by building when he was collector of. He is also known as the second of Thrissur by shifting the Municipal Stand near the M.O. Road to Shaktan Thampuran Nagar, now known as. Another IAS officer who made remarkable contributions to the development of Trichur is Raju Narayana Swamy, he single-handedly widened five roads of the city- Pattalom Road, Inner Ring Road, Ragam Theatre Road, Padinjare Kotta and Chemputti Lane – thereby changing the face of the town. Geography [ ]. The is one of largest, highly productive and threatened wetlands in.

It acts as natural drainage for City of Thrissur. The city of Thrissur is situated in of Central in India, the city is located at and has an average altitude of 2.83 metres.

The city is 75 km north-east of, 133 km south-west of and 144 km south-east of. The city is located in a hillock called which is the second highest point in city after the, from the hillock, the geography of the city move towards middle land where is situated. The Kole Wetlands act as a natural drainage for the city where the water is carried out to river and from there to the, thus keeping Thrissur city safe from flood waters which affect most of the other cities in. Different ponds, rivers and canals also keep the ground water safe from salt waters, the city is located in midland regions of, with an extended part of Palakkad plains.

The city geologically is composed of Archaean gneisses and crystalline schists. Major parts of city is covered by rocks, the city lies near the centre of the Indian tectonic plate (the Indian Plate) and is subject to comparatively little or activity. Ponds and canals save City of Thrissur from flooding in the monsoon. Climate [ ] Under the, City of Thrissur features a. Summer lasts from March to May which is the hottest time of the year. Summer months are uncomfortable due to higher levels of heat and humidity.

Daytime temperatures can rise up to 36- 38°C coupled with excessive humidity. Summer is followed by the from June to September. October and November form the post monsoon or retreating monsoon season. Winter from December through February is cooler, and windy, due to winds from the. Winter months are generally dry and less humid compared to other months of the year.

Morning temperatures are usually cool and daytime temperatures hover around 30°C. The City is drained in the monsoonal season by heavy showers, the average annual rainfall is 300 cm.

The generally sets in during the last week of May, after July the rainfall decreases. On an average, there are 124 rainy days in a year, the maximum average temperature of the City in the summer season is 36-degree Celsius while the minimum temperature recorded is 27degrees Celsius. The winter season records a maximum average of 31-degree Celsius and a minimum average of 20-degree Celsius.

Main article: Thrissur is home to many leading Malayali entrepreneurs, and is a major financial and commercial hub of. Historians say that King had invited several families and to settle in Thrissur city from their business centres in adjoining areas. Soon, Thrissur became a flourishing centre of internal trade in.

Thrissur is one of the major manufacturing centres of plain gold and jewellery in; up to 70% of 's jewellery is manufactured in Thrissur. There are around 3,000 gold ornaments manufacturing units in the city and 40,000-odd artisans and others work in these units, the industry provides direct and indirect employment to 200,000 people in Thrissur. The artisans based in these units, craft nearly 85 percent of one tonne gold which is used per day in.

About 90 tonnes of gold was being used annually in for manufacturing of ornaments daily. The Town Hall in Thrissur According to, the city in the 1930s boasted of head offices of 58 banks and was recognised by RBI as 'Banking Town'. Even now also it's the headquarters of major banks like,,, and non-banking institutions like, and and Investments. The city's financial capabilities also saw the rise of.

According to All Kerala Kuri Foreman's Association, have around 5,000 chit companies, with accounting for the maximum of 3,000, these chit companies provide employment to about 35,000 persons directly and an equal number indirectly. Headquarters in Thrissur City The city is also emerging as the largest hub for Ayurvedic drug manufacturing industry in. Out of the 850 ayurvedic drug-manufacturing units in, about 150 units, including some of the major ayurvedic drug manufacturers in the state are located in and around the city. Of these, some of the companies like the,,,, Kandamkulathy Vaidyasala, SNA Oushadhasala etc. Are among the leading ayurvedic drug manufacturers in the state., anonther initiative by a group of Ayurvedic manufacturers of Thrissur, has developed a cluster in KINFRA Park in in. Modern retailing is a big business and revenue earner for the city. Jewellery and textile retailing occupies a major part of the retailing business in Thrissur, the city is considered as hub of jewellery and textile business in.

Most of the jewellery groups have outlets in Thrissur and provide jobs to thousands of people.,, and Josco Group have their bases in city., the fourth technology park in after and and is situated in. Tourism has also contributed heavily to the economy of Thrissur. Domestic tourists generally use the city as a hub to explore the highly promoted tourism industry of the state of, the city with its temples, old churches and its culture, is ranked first in the number of domestic tourists visiting. Administration [ ]. Seen from M.O.

Road Thrissur city functioned as a municipality since 1921 under the Municipal Regulations; in 1932, the new corporation building was constructed, and in 1972 new areas from other Panchayats were added to the municipality. On 1 October 2000, the municipal town was upgraded to the level of a Municipal Corporation with the Panchayats of, Koorkkenchery,, Vilvattom (part), and.

The Corporation comprises three legislative assemblies Thrissur, and, the city is administered by the, headed by a mayor. The corporation is the second-largest city corporation in the state of in India, the city is the only local body in which directly controls power, water supply and solid waste management system in the city. For administrative purposes, the city is divided into 52 wards, from which the members of the corporation council are elected for five years, the corporation has its headquarters in Thrissur city. The and Town and Country Planning Department (TCPD) are the agencies that prepare development plan for the city. Law and order [ ] The city is the headquarters of and Thrissur Rural Police, the Thrissur City Police is headed by a Police Commissioner, an (IPS) officer.

The city is divided into two sub divisions, Thrissur and, it also operates 14 police stations, including a woman police station and a traffic police station. The Commissionerate operates out of the erst-while District Armed Police headquarters at, the Thrissur Rural Police has its headquarters at the District Collectorate complex. The city is also the headquarters of, Thrissur Range, which looks after the law and order of Thrissur District, and. All the of these three districts come under his jurisdiction, the city also contains the,, and. India Reserve Battalion, new commando unit of is headquartered in.

(148 battalion) have its first centre in Kerala in Thrissur only. Demographics [ ] Population Growth of Thrissur Census Pop.%± 1941 57,500.

— 1951 69,500 20.9% 1961 73,000 5.0% 1971 76,200 4.4% 1981 77,900 2.2% 1991 74,600 -4.2% 2001 317,526 325.6% 2011 315,957 -0.5% source: As of 2011 India census, Thrissur city had a population of 315,957. Males constitute 48.2% and females constitute 51.8% of the total population numbering 152,296 and 163,661 respectively.

The density of population is 3,130/km 2, the sex ratio is 1,092/1,000 male. The total number of the households in the city is 66,827, the average family size in the city is 4.27 members. The city has a slum population equivalent to 0.30% of the total city population and 0.37% of the 's slum population.

The city has an average literacy rate of 95.5%: male literacy rate is 97% whereas female literacy rate is 94.6%. Is spread over an area of 101.42 km 2.

The city alone accounts for 38% of the urban population in the. Area encompasses the municipal corporation area and adjoining panchayats. The total area under municipal corporation jurisdiction is 101.42 km 2, and the area under the Panchayats is 18.83 km 2 Together, these constitute an area covering 120.25 km 2. Constitute the majority with 54.2% of the population and numbering 171,252.

Constitute 40% of the population with 126,443 members. Constitute 5.4% of the population with 17,375 members. Politics [ ].

Main article: Thrissur has played a significant part in the political history of, the city of Thrissur is represented in the by two elected members, one from and another from. Is the representative of and from. Thrissur city is also a part of the and elects a member to the Lok Sabha, the lower house of the Parliament of India, once every five years. The current is.

The seat has been held by the for six terms (1951–1957, 1984–1989, 1989–1991, 1991–1996, 1999–2004 and 2009–2014) and the for ten terms (1957–1962, 1962–1967, 1967–1970, 1971–1977, 1977–1979, 1980–1984, 1996–1997, 1998–1999, 2004–2009 and 2014-present). Borobudur Dan Nabi Sulaiman Pdf Editor. Transport [ ]. Schematic Road network map of Thrissur City Road [ ] The city is connected to the via the four-lane, the highway traverses through the entire length and breadth of the city from different points and provides access to the nearby cities such of, and. Provides two main exit points at and which is bypass to the Thrissur city and. The city is largely dependent on private buses, and (called autos) for public transport. A transit terminal mobility hub situated in is also under wraps to be made on lines of to reduce traffic congestion is recently approved to be realised soon. State-owned (KSRTC) runs inter-state, inter-district and city services.

Thrissur has three bus stations, the in, Vadakke Stand (Northern Bus Stand) and the near the. Thrissur- Road, – Road, Thrissur – Kanjani – Road are the three state highways which connect city with its suburbs and municipalities. Railway [ ] The Zone of the operates the main rail transport system in Thrissur. There are four railway stations in Thrissur city., one of the four A+ railway station in provides trains to three directions and lies on the busy. It has a satellite station, and two minor stations, and. Also connects to the temple town of.

In addition, is running a suburban railway system connecting Thrissur to and using Mainline Electrical Multiple Unit services (). Building in Thrissur Known as the Cultural Capital of, the city enjoys a thriving cultural tradition dating back to centuries, and being the centre of 's cultural activities. Also called as 'the of all poorams' is celebrated in every year in the month of (mid-April to mid-may) as per the. It is the biggest of all poorams held in, the city plays host, for 36 hours from the wee hours of the pooram day, to one of the most largest collection of people and elephants. Also known as Kavakali is another festival, which attracts thousands of people to the city. It is performed by trained artists to entertain people on the occasion of, an annual harvest festival, celebrated mainly in, the most important festivals celebrated in the City include Christmas,, Easter, and.

The City is widely acclaimed as the land of elephant lovers. Aanayoottu (feeding of elephants), is the world largest elephant feeding ceremony held in in the City annually.

The ceremony is conducted on the first day of the month of Karkidakam. Literature [ ] Literary lineage of city dates back to early history of but it came to prominence after Government set up,, and for promoting literature, music and arts in. After the, Thrissur became the literary capital of as turned to the playground of novelist, poets and orators. In 1952 when Current Books set its first shop in Thrissur by former education Minister Professor, it become the abode of writer's like,,,,,, and. The area was later known as Current Moola ('Current Corner'), the building that housed the Current Books bookshop was demolished in 2011. Thrissur is home to prominent literary figures like,,,,,,,,,. Temples, Churches and Mosques [ ].

One of the four Gates, inside the. Temples The, believed to have been founded by the legendary saint, is a classic example of the style of architecture and houses several sacred shrines and with beautiful murals delineating graphically, various episodes from the., one of the largest temples in and which is one of the largest temples in is also situated in the city., is located in (municipal town), Thrissur District. It is also referred to as which means 'Holy Abode of Vishnu on Earth'. Churches Asia's tallest church, the (Puthan Pally), which has an underground shrine, is a masterpiece of architecture., the oldest church in the city, which belongs to the also known as, is situated in Thrissur. The, also known as Chinna Roma (Small Rome) are also in Thrissur. Mosques The Chettiyangadi Hanafi Mosque in Thrissur City is one of the oldest mosque in Thrissur. Kalathode Mosque (Kalathode Juma Masjid) in Thrissur city has the facility of cemetery.

Kokkalai Juma Masjid, Westfort Sunni Juma Masjid (West Fort), Salafi Juma Masjid near Railway Station, MIC Juma Masjid near Shakthan Bus Stand, Ayyanthole Juma Masjid (Ayyanthole), Olari Juma Masjid(Olari) are other mosques in Thrissur City. Cheraman Juma Masjid in Kodungalloor, ( 40 km from Thrissur ) is the First Mosque in India. Cuisine [ ] The cuisine of Thrissur is linked to its history, geography, demography and culture. Rice is the staple food. Achappam and Kuzhalappam are popular snacks.

Vellayappam, a kind of is another dish which is special to the city. Education [ ]. Government Engineering College, Thrissur Already known as the Cultural Capital of, it is also fast developing as an education hub. The City has traditionally been a centre of learning from ancient times, with the decline of and and due to the growing supremacy of Brahminism during the revival of, the City became an important centre of learning. Schools in city are either run publicly by the Government or privately, some with financial aid from the Government, the medium of education is either English or, with the former being the majority. Most schools are affiliated with the or (ICSE) or the (CBSE) or the (NIOS) or the Montessori system. There are 93 lower primary schools; 34 upper primary schools; and 78 high schools; and 157 higher secondary schools in the city.

With universities like,,,,, Cheruthuruthy and, the City would add another feather in its crown by having 'World Class University' and a 'Science City'. With the three medical colleges,,, and a medical university, the city has become synonymous with medical education in there are has 2 kendriya vidyalayas. Healthcare [ ]. Main article: The city serves as a centre for healthcare in the Central, the portion covers,, and northern part of. Most of the people in these districts come to city of Thrissur for their medical care.

There are three medical colleges,, and, and few other hi-tech hospitals. The city has an ancient tradition of Ayurvedic treatment, from the tradition,,, and SNA Oushadhasala is located in city of Thrissur, All these firms have been instrumental in spreading the fame of Ayurvedic treatment, as thousands of overseas patients visit the Ayurvedic treatment facilities in and around Thrissur, every year.

Vaidyaratnam runs a medical college and Chikitsalayam, with global standards. Sitaram have a 100 bedded eight storied super speciality hospital in the city of Thrissur, envisaged as the first of its kind Ayurveda super speciality hospital in the country. Main article: The city has been the breeding ground for the footballers, and Football is the most popular sport in the city. There are two football stadiums in the city, and Thope Stadium. Famous international players and former Indian captains, and belong to Thrissur. The, an annual inter-club football tournament is held in Thrissur every year.

The football championship was started in 1996 by the then Superintendent of Police, Thrissur. The city has a floodlit stadium, known as. It also has two indoor stadiums, and a (SAI) maintained with international facilities. Thrissur has contributed many national and international bodybuilding stars to such as TV Poly and VM Basheer. Main article: The first newspaper which published from Thrissur was Lokamanyan in 1920. Then came edited. Ezhuthachan started publishing as a weekly in 1941 from Thrissur.

It was one of the first periodicals that supported the national movement, as soon as the movement was started, its editor and staff were sent to jail and publications were banned. Later Lokamanyan (1920); Kerala Chintamani (1905); Kerala Kesari (1924); Mahatma (1930); Gomathy (1930) and Navajeevan of was also published from Thrissur.

The Express started in 1944 from Thrissur with K Krishanan as the editor is very popular in Central for its nationalist and socialist views. Major Malayalam newspapers published in Thrissur include,,,,,,,, and. A number of evening papers, like in Malayalam and in English, are also published from the City. Newspapers in other regional languages like,, and are also available in city.

Daily newspaper 's Thrissur office The first cinema hall in, with a manually operated film projector, was opened in Thrissur by in 1907; in 1913, the first electrically operated film projector was established in city again by and was called the Jose Electrical Bioscope now famously known as. A film festival, known as, is held in the city every year, it is an international short and documentary film festival. Telephony services are provided by various players like,,,,,,,, and the state owned.

BSNL is also offering 3G services in Thrissur, the city also have Broadband wireless services on platform. Private FM radio stations in the Thrissur are Club FM 104.8 MHz, MHz, BEST FM 95 by (), 91.1 MHz. Has an AM (630 kHz) and an FM (101.1 MHz) station for the city. The transmitter of the (630 kHz) was commissioned on 4 November 1956. The station started independent broadcasting in 1974. Thrissur has a studio with a low power transmitter located near the studio. Toursim Circuit Tourism [ ] 2017 is being celebrated by the United Nation Organisation as the year of sustainable development of tourism.

Keeping this in mind, DTPC, Thrissur, under the department of tourism, Kerala has launched Tourism Circuits all across the District, with a view to promote and uplift these cherished hopes; in order to full fill the goals, six (06) Tourism Circuits have been formed in Thrissur District, namely, • Blue Circuit • Brown Circuit • Yellow Circuit • Orange Circuit • Green Circuit • Red Circuit These circuits were conceptualised by the Assistant Collector Under Trainee Mr. M.V.R Krishna Teja IAS under the aegis of the District Collector Dr. Kowsigan IAS. They were inaugurated by the Honb Minister of Industries Sri A.C.

Moideen and Honb Agriculture Minister Sri V.S. Sunil Kumar on 7 April. Picture gallery [ ] •.

• Pastorello, G.; Papale, D.; Agarwal, D.; Trotta, C.; Chu, H.; Canfora, E.; Torn, M. S.; Baldocchi, D. 2016-12-01 The synthesis datasets have become one of the signature products of the FLUXNET global network. They are composed from contributions of individual site teams to regional networks, being then compiled into uniform data products - now used in a wide variety of research efforts: from plant-scale microbiology to global-scale climate change. The FLUXNET Marconi Dataset in 2000 was the first in the series, followed by the FLUXNET LaThuile Dataset in 2007, with significant additions of data products and coverage, solidifying the adoption of the datasets as a research tool.

The FLUXNET2015 Dataset counts with another round of substantial improvements, including extended quality control processes and checks, use of downscaled reanalysis data for filling long gaps in micrometeorological variables, multiple methods for USTAR threshold estimation and flux partitioning, and uncertainty estimates - all of which accompanied by auxiliary flags. This 'batteries included' approach provides a lot of information for someone who wants to explore the data (and the processing methods) in detail. This inevitably leads to a large number of data variables. Although dealing with all these variables might seem overwhelming at first, especially to someone looking at eddy covariance data for the first time, there is method to our madness. In this work we describe the data products and variables that are part of the FLUXNET2015 Dataset, and the rationale behind the organization of the dataset, covering the simplified version (labeled SUBSET), the complete version (labeled FULLSET), and the auxiliary products in the dataset. • Gulsoy, Gunhan 2013-01-01 New experimental methods has resulted in increasing amount of genetic interaction data to be generated every day.

Biological networks are used to store genetic interaction data gathered. Increasing amount of data available requires fast large scale analysis methods. Therefore, we address the problem of querying large biological network datasets.

• Gulsoy, Gunhan 2013-01-01 New experimental methods has resulted in increasing amount of genetic interaction data to be generated every day. Biological networks are used to store genetic interaction data gathered.

Increasing amount of data available requires fast large scale analysis methods. Therefore, we address the problem of querying large biological network datasets. • Fang, Kuangnan; Ma, Shuangge 2017-03-01 Data with a large p (number of covariates) and/or a large n (sample size) are now commonly encountered. For many problems, regularization especially penalization is adopted for estimation and variable selection.

The straightforward application of penalization to large datasets demands a 'big computer' with high computational power. To improve computational feasibility, we develop bootstrap penalization, which dissects a big penalized estimation into a set of small ones, which can be executed in a highly parallel manner and each only demands a 'small computer'. The proposed approach takes different strategies for data with different characteristics. For data with a large p but a small to moderate n, covariates are first clustered into relatively homogeneous blocks. The proposed approach consists of two sequential steps. In each step and for each bootstrap sample, we select blocks of covariates and run penalization.

The results from multiple bootstrap samples are pooled to generate the final estimate. For data with a large n but a small to moderate p, we bootstrap a small number of subjects, apply penalized estimation, and then conduct a weighted average over multiple bootstrap samples. For data with a large p and a large n, the natural marriage of the previous two methods is applied. Numerical studies, including simulations and data analysis, show that the proposed approach has computational and numerical advantages over the straightforward application of penalization. An R package has been developed to implement the proposed methods. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

E.; Sundell, K. E., II 2014-12-01 Implementation of quantitative metrics for inter-sample comparison of detrital geochronological data sets has lagged the increase in data set size, and ability to identify sub-populations and quantify their relative proportions. Visual comparison or application of some statistical approaches, particularly the Kolmogorov-Smirnov (KS) test, that initially appeared to provide a simple way of comparing detrital data sets, may be inadequate to quantify their similarity. We evaluate several proposed metrics by applying them to four large synthetic datasets drawn randomly from a parent dataset, as well as a recently published large empirical dataset consisting of four separate (n = ~1000 each) analyses of the same rock sample. Visual inspection of the cumulative probability density functions (CDF) and relative probability density functions (PDF) confirms an increasingly close correlation between data sets as the number of analyses increases.

However, as data set size increases the KS test yields lower mean p-values implying greater confidence that the samples were not drawn from the same parent population and high standard deviations despite minor decreases in the mean difference between sample CDFs. We attribute this to the increasing sensitivity of the KS test when applied to larger data sets, which in turn limits its use for quantitative inter-sample comparison in detrital geochronology.

Proposed alternative metrics, including Similarity, Likeness (complement to Mismatch), and the coefficient of determination (R2) of a cross-plot of PDF quantiles, point to an increasingly close correlation between data sets with increasing size, although they are the most sensitive at different ranges of data set sizes. The Similarity test is most sensitive to variation in data sets with n. • Vicente, G. 2013-12-01 The NASA Goddard Earth Sciences Data (GES) and Information Services Center (DISC) is one of the major Science Mission Directorate (SMD) for archiving and distribution of Earth Science remote sensing data, products and services. This virtual portal provides convenient access to Atmospheric Composition and Dynamics, Hydrology, Precipitation, Ozone, and model derived datasets (generated by GSFC's Global Modeling and Assimilation Office), the North American Land Data Assimilation System (NLDAS) and the Global Land Data Assimilation System (GLDAS) data products (both generated by GSFC's Hydrological Sciences Branch).

This presentation demonstrates various tools and computational technologies developed in the GES DISC to manage the huge volume of data and products acquired from various missions and programs over the years. It explores approaches to archive, document, distribute, access and analyze Earth Science data and information as well as addresses the technical and scientific issues, governance and user support problem faced by scientists in need of multi-disciplinary datasets. It also discusses data and product metrics, user distribution profiles and lessons learned through interactions with the science communities around the world. Finally it demonstrates some of the most used data and product visualization and analyses tools developed and maintained by the GES DISC. • Nutricato, Raffaele; Nitti, Davide O.; Bovenga, Fabio; Refice, Alberto; Chiaradia, Maria T. 2014-10-01 In this work we explored a dataset made by more than 100 images acquired by COSMO-SkyMed (CSK) constellation over the Port-au-Prince (Haiti) metropolitan and surrounding areas that were severely hit by the January 12th, 2010 earthquake.

The images were acquired along ascending pass by all the four sensors of the constellation with a mean rate of 1 acquisition/week. This consistent CSK dataset was fully exploited by using the Persistent Scatterer Interferometry algorithm SPINUA with the aim of: i) providing a displacement map of the area; ii) assessing the use of CSK and PSI for ground elevation measurements; iii) exploring the CSK satellite orbital tube in terms of both precision and size. In particular, significant subsidence phenomena were detected affecting river deltas and coastal areas of the Port-au-Prince and Carrefour region, as well as very slow slope movements and local ground instabilities. Ground elevation was also measured on PS targets with resolution of 3m. The density of these measurable targets depends on the ground coverage, and reaches values higher than 4000 PS/km2 over urban areas, while it drops over vegetated areas or along slopes affected by layover and shadow. Heights values were compared with LIDAR data at 1m of resolution collected soon after the 2010 earthquake.

Furthermore, by using geocoding procedures and the precise LIDAR data as reference, the orbital errors affecting CSK records were investigated. The results are in line with other recent studies. • 2015-01-01 Background While the discovery of new drugs is a complex, lengthy and costly process, identifying new uses for existing drugs is a cost-effective approach to therapeutic discovery. Connectivity mapping integrates gene expression profiling with advanced algorithms to connect genes, diseases and small molecule compounds and has been applied in a large number of studies to identify potential drugs, particularly to facilitate drug repurposing. Colorectal cancer (CRC) is a commonly diagnosed cancer with high mortality rates, presenting a worldwide health problem. With the advancement of high throughput omics technologies, a number of large scale gene expression profiling studies have been conducted on CRCs, providing multiple datasets in gene expression data repositories. In this work, we systematically apply gene expression connectivity mapping to multiple CRC datasets to identify candidate therapeutics to this disease.

Results We developed a robust method to compile a combined gene signature for colorectal cancer across multiple datasets. Connectivity mapping analysis with this signature of 148 genes identified 10 candidate compounds, including irinotecan and etoposide, which are chemotherapy drugs currently used to treat CRCs.

These results indicate that we have discovered high quality connections between the CRC disease state and the candidate compounds, and that the gene signature we created may be used as a potential therapeutic target in treating the disease. The method we proposed is highly effective in generating quality gene signature through multiple datasets; the publication of the combined CRC gene signature and the list of candidate compounds from this work will benefit both cancer and systems biology research communities for further development and investigations. PMID:26356760 • Stassun, Keivan; Burger, D.; Pepper, J.; De Lee, N. M.; Siverd, R.; Paegert, M. 2014-01-01 We present Filtergraph as a web application designed to rapidly and intuitively visualize large datasets.

The user loads a dataset in a variety of supported file types into Filtergraph, which automatically generates an interactive data portal that can be easily shared with others. From this portal, the user can immediately generate scatter plots of up to 5 dimensions as well as histograms and tables based on the dataset.

Key features of the portal include intuitive controls with auto-completed variable names, the ability to filter the data in real time through user-specified criteria, the ability to select data by dragging on the screen, and the ability to perform arithmetic operations on the data in real time. To enable seamless data visualization and exploration, changes are quickly rendered on screen and visualizations can be exported as high quality graphics files or shared as simple URLs. The application is optimized for speed: for instance, a plot generated from a database of 3.1 million entries renders in less than 2 seconds on a standard web server platform, allowing rapid-fire exploration of massive datasets with little time cost. Filtergraph is free to use at • Zhao, Weizhong; Zou, Wen; Chen, James J 2014-01-01 The big data moniker is nowhere better deserved than to describe the ever-increasing prodigiousness and complexity of biological and medical datasets. New methods are needed to generate and test hypotheses, foster biological interpretation, and build validated predictors. Although multivariate techniques such as cluster analysis may allow researchers to identify groups, or clusters, of related variables, the accuracies and effectiveness of traditional clustering methods diminish for large and hyper dimensional datasets.

Topic modeling is an active research field in machine learning and has been mainly used as an analytical tool to structure large textual corpora for data mining. Its ability to reduce high dimensionality to a small number of latent variables makes it suitable as a means for clustering or overcoming clustering difficulties in large biological and medical datasets. In this study, three topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, are proposed and tested on the cluster analysis of three large datasets: Salmonella pulsed-field gel electrophoresis (PFGE) dataset, lung cancer dataset, and breast cancer dataset, which represent various types of large biological or medical datasets. All three various methods are shown to improve the efficacy/effectiveness of clustering results on the three datasets in comparison to traditional methods. A preferable cluster analysis method emerged for each of the three datasets on the basis of replicating known biological truths. Topic modeling could be advantageously applied to the large datasets of biological or medical research. The three proposed topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, yield clustering improvements for the three different data types.

Clusters more efficaciously represent truthful groupings and subgroupings in the data than traditional methods, suggesting • 2014-01-01 Background The big data moniker is nowhere better deserved than to describe the ever-increasing prodigiousness and complexity of biological and medical datasets. New methods are needed to generate and test hypotheses, foster biological interpretation, and build validated predictors. Although multivariate techniques such as cluster analysis may allow researchers to identify groups, or clusters, of related variables, the accuracies and effectiveness of traditional clustering methods diminish for large and hyper dimensional datasets. Topic modeling is an active research field in machine learning and has been mainly used as an analytical tool to structure large textual corpora for data mining. Its ability to reduce high dimensionality to a small number of latent variables makes it suitable as a means for clustering or overcoming clustering difficulties in large biological and medical datasets.

Results In this study, three topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, are proposed and tested on the cluster analysis of three large datasets: Salmonella pulsed-field gel electrophoresis (PFGE) dataset, lung cancer dataset, and breast cancer dataset, which represent various types of large biological or medical datasets. All three various methods are shown to improve the efficacy/effectiveness of clustering results on the three datasets in comparison to traditional methods. A preferable cluster analysis method emerged for each of the three datasets on the basis of replicating known biological truths.

Conclusion Topic modeling could be advantageously applied to the large datasets of biological or medical research. The three proposed topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, yield clustering improvements for the three different data types. Clusters more efficaciously represent truthful groupings and subgroupings in the data than • Wang, Zhe; Ferreira, Nivan; Wei, Youhao; Bhaskar, Aarthy Sankari; Scheidegger, Carlos 2017-01-01 Recently proposed techniques have finally made it possible for analysts to interactively explore very large datasets in real time. However powerful, the class of analyses these systems enable is somewhat limited: specifically, one can only quickly obtain plots such as histograms and heatmaps.

In this paper, we contribute Gaussian Cubes, which significantly improves on state-of-the-art systems by providing interactive modeling capabilities, which include but are not limited to linear least squares and principal components analysis (PCA). The fundamental insight in Gaussian Cubes is that instead of precomputing counts of many data subsets (as state-of-the-art systems do), Gaussian Cubes precomputes the best multivariate Gaussian for the respective data subsets. As an example, Gaussian Cubes can fit hundreds of models over millions of data points in well under a second, enabling novel types of visual exploration of such large datasets. We present three case studies that highlight the visualization and analysis capabilities in Gaussian Cubes, using earthquake safety simulations, astronomical catalogs, and transportation statistics. The dataset sizes range around one hundred million elements and 5 to 10 dimensions. We present extensive performance results, a discussion of the limitations in Gaussian Cubes, and future research directions.

• Pugmire, David; Childs, Hank; Garth, Christoph; Ahern, Sean; Weber, Gunther H. 2009-09-01 Understanding vector fields resulting from large scientific simulations is an important and often difficult task. Streamlines, curves that are tangential to a vector field at each point, are a powerful visualization method in this context.

Application of streamline-based visualization to very large vector field data represents a significant challenge due to the non-local and data-dependent nature of streamline computation, and requires careful balancing of computational demands placed on I/O, memory, communication, and processors. In this paper we review two parallelization approaches based on established parallelization paradigms (static decomposition and on-demand loading) and present a novel hybrid algorithm for computing streamlines. Our algorithm is aimed at good scalability and performance across the widely varying computational characteristics of streamline-based problems. We perform performance and scalability studies of all three algorithms on a number of prototypical application problems and demonstrate that our hybrid scheme is able to perform well in different settings. • Moolekamp, Fred 2015-07-01 Toyz is a python web framework that allows scientists to interact with large images and data sets stored on a remote server. A web application is run on the server containing the data and clients are run from web browsers on the user's computer.

Toyz displays large FITS images also also renders any image format supported by Pillow (a fork of the Python Imaging Library), contains a GUI to interact with linked plots, and offers a customizable framework that allows students and researchers to create their own work spaces inside a Toyz environment. Astro-Toyz extends the features of the Toyz image viewer, allowing users to view world coordinates and align images based on their WCS. • Verschueren, Erik; Von Dollen, John; Cimermancic, Peter; Gulbahce, Natali; Sali, Andrej; Krogan, Nevan 2015-01-01 High-throughput Affinity Purification Mass Spectrometry (AP-MS) experiments can identify a large number of protein interactions but only a fraction of these interactions are biologically relevant. Here, we describe a comprehensive computational strategy to process raw AP-MS data, perform quality controls and prioritize biologically relevant bait-prey pairs in a set of replicated AP-MS experiments with Mass spectrometry interaction STatistics (MiST). The MiST score is a linear combination of prey quantity (abundance), abundance invariability across repeated experiments (reproducibility), and prey uniqueness relative to other baits (specificity); We describe how to run the full MiST analysis pipeline in an R environment and discuss a number of configurable options that allow the lay user to convert any large-scale AP-MS data into an interpretable, biologically relevant protein-protein interaction network. PMID:25754993 • Maddox, Brian G. 2004-01-01 Modern information needs have resulted in very large amounts of data being used in geographic information systems.

Problems arise when trying to project these data in a reasonable amount of time and accuracy, however. Current single-threaded methods can suffer from two problems: fast projection with poor accuracy, or accurate projection with long processing time. A possible solution may be to combine accurate interpolation methods and distributed processing algorithms to quickly and accurately convert digital geospatial data between coordinate systems. Modern technology has made it possible to construct systems, such as Beowulf clusters, for a low cost and provide access to supercomputer-class technology. Combining these techniques may result in the ability to use large amounts of geographic data in time-critical situations. • Jesse Caputo; Brett Butler; Andy.

Hartsell 2017-01-01 Forest ownership size is a continuous variable, albeit one with a distinctly nonnormal distribution. Although large corporate forest ownerships are expected to differ in terms of behavior and objectives from smaller corporate ownerships, there is no clear and unambiguous means of defined these two ownership groups. We examined the distribution of the ownership size.

• Song, Chunqiao; Huang, Bo; Ke, Linghong; Ye, Qinghua 2016-10-01 For the period 1979-2011, eight gridded monthly precipitation datasets, including GPCP, CMAP-1/2, TRMM, PREC/L, APHRODITE, NCEP-2 and ERA-Interim, are inter-compared with each other and station observations over High Mountain Asia (HMA). The precipitation variability from the first six gauge-based or merged analysis datasets agree better with each other than with the two reanalysis data. The long-term trend analysis of GPCP, CMAP-1, PREC/L and APHRODITE precipitation datasets consistently reveals moderate increases in the inner and northeastern Tibetan Plateau (TP) and northwest Xinjiang, and obvious decreases in the southeast TP. However, in the Himalayas and Karakorum, there are large discrepancies among different datasets, where GPCP and APHRODITE precipitation datasets show significant decreases along the Himalayas while other datasets show strong spatial heterogeneity or slight variations. The larger uncertainties in the rugged area may be largely attributed to scarce station observations, as well as the stronger snow-induced scattering by microwave measurement.

To assess which precipitation datasets tend to be more suitable for hydrologic analysis in HMA, we further investigate the accuracy of precipitation estimates at basin scale by comparing with gauge-based observations, and examine the coherences of annual lake water budgets and precipitation variability over four large closed lake catchments. The results indicate that two reanalysis precipitation datasets show evidently weaker correlations with station observations; the other six datasets perform better in indicating inter-annual variations of lake water budgets.

It suggests that these merged analysis precipitation datasets, especially for GPCP, CMAP-1/2 and PREC/L, have the potential in examining regional water balances of the inner basins in HMA. J.; Killworth, P. D.; Cornell, V. C.; Challenor, P. 2005-10-01 The oceans relinquish O(1PW) of heat into the atmosphere at high latitudes, the lion's share of which originates in localised hotspots of violent convective mixing, but despite their small horizontal scale - O(10-100km) - these features may penetrate deeply into the thermocline and are vital in maintaining the Atlantic Meridional Overturning Circulation (MOC). Accurate modelling of the MOC, therefore, requires a large-scale numerical model with very fine resolution.The global high-resolution ocean model, Ocean Circulation Climate Advanced Model (OCCAM) has been developed and run at the Southampton Oceanography Centre (SOC) for many years. It was configured to resolve the energetic scales of oceanic motions, and its output is stored at the Manchester Supercomputer Centre.

Although this community resource represents a treasure trove of potential new insights into the nature of the world ocean, it remains relatively unexploited for a number of reasons, not the least of which is its sheer size.A system being developed at SOC under the auspices of the Grid for Ocean Diagnostics, Interactive Visualisation and Analysis (GODIVA) project makes the remote visualisation of very large volumes of data on modest hardware (e.g. A laptop with no special graphics capability) a present reality. The GODIVA system is enabling the unresolved question of oceanic convection and its relationship to large-scale flows to be investigated; a question that lies at the heart of many current climate change issues.In this article, one aspect of the GODIVA is presented, and used to locate and visualise regions of convective mixing in the OCCAM Labrador Sea.

• Pugmire, Dave; Garth, Christoph; Childs, Hank; Ahern, Sean; Weber, Gunther H 2009-01-01 nderstanding vector fields resulting from large scientific simulations is an important and often difficult task. Streamlines, curves that are tangential to a ve ctor field at each point, are a powerful visualization method in this context. Application of streamline-based visualization to very large vector field data repr esents a significant challenge due to the non-local and data-dependent nature of streamline computation, and requires careful balancing of computational demands placed on I/O, memory, communication, and processors. In this paper we review two parallelization approaches based on established parallelization paradigms (stat ic decomposition and on-demand loading) and present a novel hybrid algorithm for computing streamlines. Our algorithm is aimed at good scalability and performanc e across the widely varying computational characteristics of streamline-based problems. We perform performance and scalability studies of all three algorithms on a number of prototypical application problems and demonstrate that our hybrid scheme is able to perform well in different settings.

• Pina-Martins, F.; Paulo, O. Sequence databases, such as NCBI, are a very important resource in many areas of science. Downloading small amounts of sequences to local storage can easily be performed using any recent web browser, but downloading tens of thousands of sequences is not as simple.

NCBI Mass Sequence Downloader is an open source program aimed at simplifying obtaining large amounts of sequence data from NCBI databases to local storage. It is written in python (can be run under both python 2 and python 3), and uses PyQt5 for the GUI. The program can be run in either graphical or command line mode. Source code is licensed under the GPLv3, and is supported on Linux, Windows and Mac OSX. Available at • Heath, Allison P; Greenway, Matthew; Powell, Raymond; Spring, Jonathan; Suarez, Rafael; Hanley, David; Bandlamudi, Chai; McNerney, Megan E; White, Kevin P; Grossman, Robert L 2014-01-01 Background As large genomics and phenotypic datasets are becoming more common, it is increasingly difficult for most researchers to access, manage, and analyze them. One possible approach is to provide the research community with several petabyte-scale cloud-based computing platforms containing these data, along with tools and resources to analyze it.

Methods Bionimbus is an open source cloud-computing platform that is based primarily upon OpenStack, which manages on-demand virtual machines that provide the required computational resources, and GlusterFS, which is a high-performance clustered file system. Bionimbus also includes Tukey, which is a portal, and associated middleware that provides a single entry point and a single sign on for the various Bionimbus resources; and Yates, which automates the installation, configuration, and maintenance of the software infrastructure required. Results Bionimbus is used by a variety of projects to process genomics and phenotypic data. For example, it is used by an acute myeloid leukemia resequencing project at the University of Chicago. The project requires several computational pipelines, including pipelines for quality control, alignment, variant calling, and annotation. For each sample, the alignment step requires eight CPUs for about 12 h.

BAM file sizes ranged from 5 GB to 10 GB for each sample. Conclusions Most members of the research community have difficulty downloading large genomics datasets and obtaining sufficient storage and computer resources to manage and analyze the data. Cloud computing platforms, such as Bionimbus, with data commons that contain large genomics datasets, are one choice for broadening access to research data in genomics. PMID:24464852 • Heath, Allison P; Greenway, Matthew; Powell, Raymond; Spring, Jonathan; Suarez, Rafael; Hanley, David; Bandlamudi, Chai; McNerney, Megan E; White, Kevin P; Grossman, Robert L 2014-01-01 As large genomics and phenotypic datasets are becoming more common, it is increasingly difficult for most researchers to access, manage, and analyze them. One possible approach is to provide the research community with several petabyte-scale cloud-based computing platforms containing these data, along with tools and resources to analyze it.

Bionimbus is an open source cloud-computing platform that is based primarily upon OpenStack, which manages on-demand virtual machines that provide the required computational resources, and GlusterFS, which is a high-performance clustered file system. Bionimbus also includes Tukey, which is a portal, and associated middleware that provides a single entry point and a single sign on for the various Bionimbus resources; and Yates, which automates the installation, configuration, and maintenance of the software infrastructure required. Bionimbus is used by a variety of projects to process genomics and phenotypic data. For example, it is used by an acute myeloid leukemia resequencing project at the University of Chicago. The project requires several computational pipelines, including pipelines for quality control, alignment, variant calling, and annotation.

For each sample, the alignment step requires eight CPUs for about 12 h. BAM file sizes ranged from 5 GB to 10 GB for each sample. Most members of the research community have difficulty downloading large genomics datasets and obtaining sufficient storage and computer resources to manage and analyze the data. Cloud computing platforms, such as Bionimbus, with data commons that contain large genomics datasets, are one choice for broadening access to research data in genomics. Published by the BMJ Publishing Group Limited.

For permission to use (where not already granted under a licence) please go to • Socha, John J.; Chung, Julianne 2016-01-01 ABSTRACT In many physiological studies, variables of interest are not directly accessible, requiring that they be estimated indirectly from noisy measured signals. Here, we introduce two empirical methods to estimate the true physiological signals from indirectly measured, noisy data. The first method is an extension of Tikhonov regularization to large-scale problems, using a sequential update approach. In the second method, we improve the conditioning of the problem by assuming that the input is uniform over a known time interval, and then use a least-squares method to estimate the input.

These methods were validated computationally and experimentally by applying them to flow-through respirometry data. Specifically, we infused CO2 in a flow-through respirometry chamber in a known pattern, and used the methods to recover the known input from the recorded data. The results from these experiments indicate that these methods are capable of sub-second accuracy. We also applied the methods on respiratory data from a grasshopper to investigate the exact timing of abdominal pumping, spiracular opening, and CO2 emission.

The methods can be used more generally for input estimation of any linear system. PMID:27444788 • Leblond, Antoine; Kauffmann, Claude 2016-03-01 Even with recent hardware improvements, superpixel segmentation of large 3D medical images at interactive speed (.

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