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UK Ancestry visa

A UK Ancestry visa is a visa issued by the United Kingdom to Commonwealth citizens with a grandparent born in the United Kingdom, Channel Islands, Isle of Man or Ireland (before 1922) who wish to work in the United Kingdom. It is used mainly by young Canadians, Australians, New Zealanders and South Africans of British descent coming to the UK to work and as a base to explore Europe.

Requirements
The main requirements are:

 * to have a grandparent born in the United Kingdom, Channel Islands or Isle of Man at any time; or a grandparent born in what is now the Republic of Ireland on or before March 31, 1922.
 * to be a citizen of a Commonwealth country (it does not matter how citizenship was acquired), applying from outside the UK. Zimbabwe remains a Commonwealth country for immigration purposes.
 * to be aged 17 or over
 * ability, and intention, to undertake employment
 * ability to support oneself (and one's dependents) in the United Kingdom without recourse to public funds.

As a result of the Immigration Act 2014, the applicant may also be required to pay a healthcare surcharge as part of the process.

Terms of visa
The visa is granted for five years in the 'limited leave to enter' category. After this, the holder can apply for an extension (limited leave to remain) or for indefinite leave to remain (ILR). For ILR, the holder must show that he or she has been living continuously in the UK and is currently in continuing employment or has worked throughout the five years. The Home Office's guidance makes clear that if the applicant is working at the time of the ILR application, the applicant needs to show only that his or her current employment will continue. If not working at the time of the ILR application, the applicant will need to show that he or she has been continually working or looking for work throughout the five-year period.

This visa does not prevent the holder from undertaking study; however, to stay within the terms of the status the holder should also be working.

British citizenship
After acquiring indefinite leave to remain, it is possible to apply for British citizenship by naturalisation after meeting normal residence requirements. See British nationality law.

 * The increase in the period of time under UK ancestry to five years before ILR can be applied for effectively means that applicants (who are usually not married to British citizens) must wait six years for British citizenship. This is because naturalisation as a British citizen for a person not married to a British citizen requires that ILR or its equivalent be held for twelve months.
 * Children born in the United Kingdom to persons with UK ancestry (since 1983) are not British citizens by birth. However, the child can be registered a British citizen once the parent obtains ILR if the child is still under 18 (it is not necessary to wait for the parent to become British).

Irish-born grandparent
A grandparent born in Northern Ireland at any time, or what is now the Republic of Ireland prior to 1 April 1922, gives rise to an entitlement to a right to admission under UK ancestry. However, there may also be an entitlement to register as an Irish citizen by descent which grants de facto permanent residency in the UK immediately.

This may be possible as an alternative to, or in addition to, a UK Ancestry visa.

2008 abolition proposal
On 26 October 2005, The Times published an article outlining possible plans by the British Home Office to abolish admission under UK ancestry in favour of a points-based migration system. The issue had apparently been raised in the House of Commons Home Affairs Select Committee. The possibility of abolition alarmed many people with British-born grandparents living in Commonwealth countries.

Scotland's First Minister, Jack McConnell, expressed his concern over the possible abolition of the UK Ancestry visa. Mr. McConnell had recently been in Canada to encourage Canadians of Scottish heritage to move to Scotland. Canada has over four million citizens that are of Scottish descent. Part of the reason for this campaign was the concern over declining population and birth-rate in Scotland. His campaign received a great deal of interest in Canada.

In March 2006, the announcement of a new points-based system made it clear that the ancestry route to the UK was outside its scope.

The abolition of this route was once again brought up by the Home Office in February 2008 in a green paper. After receiving substantial feedback during consultation, the proposal was revised in July 2008 to preserve the clearance, but to provide that people taking that route to go through a probationary citizenship stage before applying for British citizenship or permanent residence.

title: UK Ancestry visa


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Southern Tutchone

The Southern Tutchone are a First Nations people of the Athabaskan-speaking ethnolinguistic group living mainly in the southern Yukon in Canada. The Southern Tutchone language, traditionally spoken by the Southern Tutchone people, is a variety of the Tutchone language, part of the Athabaskan language family. Some linguists suggest that Northern and Southern Tutchone are distinct and separate languages.

Southern Tutchone First Nations governments and communities include:
 * Champagne and Aishihik First Nations (Haines Junction, Champagne, and Aishihik in Yukon) Many Champagne and Aishihik members also live in Whitehorse.
 * Ta'an Kwach'an Council (Whitehorse, Yukon and Lake Laberge) (Ta’an Kwäch’än - ″People of Lake Laberge″, because they called it Tàa'an Män)
 * Kluane First Nation (Burwash Landing, Yukon) (Lù’àn Män Ku Dän or Lù’àn Mun Ku Dän - ″Kluane Lake People″, referring to their territory around Kluane Lake).

Many citizens of the Kwanlin Dün First Nation (Kwänlin Dän kwächʼǟn - "Whitehorse people", formerly White Horse Indian Band) in Whitehorse are of Southern Tutchone origin; their name refers to a section of the Yukon River from Miles Canyon Basalts to the White Horse Rapids which their ancestors called Kwanlin meaning "running water through canyon” and together with the Southern Tutchone word Dän or Dün for ″people″, they referred to this location for naming the KDFN)

Southern Tutchone language
The Southern Tutchone people named by the late Catharine McClellan; are a group of Athabaskan speaking indigenous people of Southern Yukon, Canada. Today, the Southern Tutchone language is more often being called, "Dän'ke" which means 'our way' or, "Dän k'e kwänje" which means 'our way of speaking' in the Athabaskan language. This territory stretches over the south-west Yukon, and is controversial in what is overlap with different indigenous groups of people in Yukon. The Tutchone language was separated into two groups by McClellan in which she called them Southern and Northern Tutchone. The languages themselves are close, but are different in subtle dialects.

Demographics
In the early 1950s there were close to 20,000 Southern Tutchone speaking individuals. This has since plummeted to less than a few hundred speakers. As of 2004 the number of individuals who spoke Southern Tutchone as their first language was 404, and the total number of individuals who had some knowledge of the language was 645.

Revitalization efforts
The Southern Tutchone language is an endangered language with fewer than 100 speakers. There have been revitalization efforts in place to help combat the dwindling numbers. This includes signage throughout the Yukon highlighting the language. Other revitalization efforts includes an adult immersion program focused on increasing the number of speakers in the Champagne and Aishihik traditional territory. In 2015 the Champagne and Aishihik First Nations launched the first Da Ku Nän Ts'tthèt (Our House is Waking Up the Land) dance festival which focused on Southern Tutchone language and culture. This was hosted at the cultural centre named Da Ku, meaning "our house" in Southern Tutchone. Efforts for revitalization have also included school programs throughout the territory, as well as a language nest in Haines Junction, Yukon. The Yukon Native Language Centre has played a key role in many revitalization efforts as they have developed Indigenous teacher education programs, as well as curriculum materials.

Landclaims
In other places in the Southern Tutchone region there are four First Nations governments that have settled their land claims in the Southern Tutchone cultural area these include:
 * Champagne and Aishihik First Nations (Haines Junction)
 * Ta'an Kwach'an Council (Lake Laberge)
 * Kluane First Nation (Burwash Landing)
 * Kwanlin Dün First Nations (Whitehorse)

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/

title: Southern Tutchone


text:
Coast (disambiguation)

The coast is where the land meets the sea or ocean.

Coast, Coastal, or Coastline may also refer to:

Places

 * Coast (PAT station), a station on the Port Authority of Allegheny County's light rail network
 * Coast at Lakeshore East, a Chicago residential skyscraper
 * Coast Province, a province in Kenya
 * Coast Region, a region in Tanzania
 * The Coast, Newark, New Jersey, a neighborhood in Newark, New Jersey

Groups and labels

 * Coast (folk rock band), an English folk rock band on Awen Records, 2007
 * Coast (Scottish band) 1991-1996
 * Coasts (band), an indie-pop quintet from Bristol, England
 * The Coast (band), a Canadian band on Aporia Records

Albums

 * Coastal (Godstar album)
 * Coastal (The Field Mice album)

Songs

 * "Coast" (song), a 2022 song by Hailee Steinfeld featuring Anderson Paak

Periodicals

 * Coast (magazine), a consumer magazine about the British seaside
 * Coastal Leader, a newspaper in Kingston, South Australia

Other uses in arts, entertainment, and media

 * Coast (radio station), a New Zealand radio station, started in 2005
 * Coast (TV series), a BBC TV documentary series
 * Coastline (sculpture), a 1993 outdoor sculpture by American artist Jim Sanborn
 * Coast (film), a 2022 film featuring Melissa Leo
 * Coastlines (film), a 2002 dramatic film

Brands and enterprises

 * Coast (clothing), British women's clothing retail chain
 * Coast (soap), a brand of bar soap and body wash, currently manufactured by High Ridge Brands

Schools

 * COAST Laboratory (Computer Operations, Audit, and Security Technology), of Purdue University
 * Coastal Carolina University in South Carolina, or its athletic program, the Coastal Carolina Chanticleers

Science and technology

 * Coast (web browser), a web browser developed by Opera Software
 * Cache on a stick (COAST), computer memory
 * Cambridge Optical Aperture Synthesis Telescope, an astronomical optical interferometer
 * Coastal class airship, a class of British World War I airships

Other uses

 * Coastal (horse) (1976–2005), American Thoroughbred racehorse
 * Coastal Corporation, an American oil company
 * Coasting or gliding, a technique of driving a manual transmission car
 * Cooperative Alliance for Seacoast Transportation (COAST), a public bus system in the coastal region of New Hampshire, United States
 * Team Coast, a German professional cycling team year 2000

title: Coast (disambiguation)


text: User talk:70.190.205.83

title: User talk:70.190.205.83


text:
Wally Dallenbach Sr.

Wallace Jacob Dallenbach (December 12, 1936 – April 29, 2024) was an American racing driver and official. He competed primarily in United States Auto Club (USAC) sanctioned Championship cars, and was the winner of the 1973 California 500. After retiring from driving, he served for more than 20 years as Chief Steward of Competition for Championship Auto Racing Teams (CART).

Dallenbach was the father of NASCAR driver and commentator, Wallace Paul Dallenbach. After the younger Dallenbach began a professional racing career during the middle 1980s, the elder Dallenbach came to be known by the retronym Dallenbach Sr.

Biography
Dallenbach was born in East Brunswick, New Jersey. After working in the construction industry, he began his racing career in modified racing. In 1962, he competed in the Daytona 500. He eventually settled on open-wheel racing, competing in midget and sprint cars before moving to Indy cars in 1965.

Indy car career
After several years competing in uncompetitive equipment, Dallenbach's breakthrough came after being signed by team owner Pat Patrick to replace driver Swede Savage, badly injured during the 1973 Indianapolis 500. After Savage's death, Dallenbach's seat became permanent. Four races into his tenure with Patrick's team, Dallenbach scored his first victory, the Tony Bettenhausen 200 at the Milwaukee Mile. He scored two further victories in 1973, including the California 500. Despite not starting in four races during the 1973 season, Dallenbach finished the 1973 USAC Championship Car season ranked second in points.

Dallenbach nearly won the 1975 Indianapolis 500, dueling with A. J. Foyt for many laps. He led for half of the race, but burned a piston on lap 162, twelve laps before the race was called due to rain. Bobby Unser won the race, which was halted at lap 174 (435 miles).

CART official
Dallenbach joined CART as Competition Director in 1980 and became Chief Steward of the series in 1981. Under his tenure, he greatly improved the safety program in CART, the preeminent sanctioning body of Indy car racing. He played an instrumental role in establishing the first dedicated rapid response trauma team in auto racing. He also established nondenominational church services for drivers and their families. Dallenbach held his position until the end of the 2000 season, after which he went into semi-retirement, serving as Special Advisor to CART and Chris Kneifel, his successor as Chief Steward.

Advance testing and practice in preparation for the 2001 Firestone Firehawk 600 – to be held at Texas Motor Speedway (TMS) – saw numerous drivers black out due to unprecedented g-forces experienced at the track. Dallenbach had visited TMS as early as 1996, deeming it unsafe for Indy car competition. On the day of the race, despite pressure from stakeholders within the CART community to proceed with the event, it was decided to cancel to event in order to ensure the safety of the competitors.

Shortly thereafter, Dallenbach returned as Chief Steward for CART, replacing Kneifel, who had been the subject of criticism from many drivers. Dallenbach served until the conclusion of the 2004 season, after which he retired permanently.

Post-racing activities
Dallenbach served as the president of the Colorado 500 motorcycle charity ride. The events have raised just under three million dollars in community support - including more than $800,000 in student scholarships - for the town of Basalt, Colorado, located in the Roaring Fork Valley region of western Colorado.

With his winnings from the California 500, Dallenbach purchased a ranch, fairground, cabins and a private automotive restoration garage near the Fryingpan River in upper Basalt. In 2023, he sold the property, returning with his wife to New Jersey. During their time in Colorado, the couple supported the development of local emergency services in the area; in 1976, Dallenbach purchased an ambulance for the town of Basalt.

Dallenbach died on April 29, 2024, at the age of 87.

Awards and honors
Dallenbach has been inducted into the following halls of fame:

 * Eastern Motorsport Press Association Hall of Fame (1992)
 * Colorado Motorsports Hall of Fame (2004)
 * Sports Hall of Fame of New Jersey (2004)
 * Motorcycle Hall of Fame (2006)
 * Motorsports Hall of Fame of America (2020)
 * Canadian Motorsport Hall of Fame (2021)
 * Indianapolis Motor Speedway Hall of Fame (2022)
 * Pikes Peak Hill Climb Museum Hall of Fame (2022)

After his death in 2024, the community of Basalt, Colorado named their newest ambulance after Dallenbach; in 1976 he had purchased the community its first ambulance.

USAC Championship Car results
(key) (Races in bold indicate pole position)

CART Championship Car results
(key) (Races in bold indicate pole position)

Indianapolis 500 results

 * In 1972, Dallenbach was bumped on the final day of time trials. Art Pollard crashed his qualified car on May 16, and was too injured to drive on race day. Dallenbach was hired to fill the seat, and the car was moved to 33rd starting position.

title: Wally Dallenbach Sr.


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Cellular neural network

In computer science and machine learning, cellular neural networks (CNN) or cellular nonlinear networks (CNN) are a parallel computing paradigm similar to neural networks, with the difference that communication is allowed between neighbouring units only. Typical applications include image processing, analyzing 3D surfaces, solving partial differential equations, reducing non-visual problems to geometric maps, modelling biological vision and other sensory-motor organs.

CNN is not to be confused with convolutional neural networks (also colloquially called CNN).

CNN architecture
Due to their number and variety of architectures, it is difficult to give a precise definition for a CNN processor. From an architecture standpoint, CNN processors are a system of finite, fixed-number, fixed-location, fixed-topology, locally interconnected, multiple-input, single-output, nonlinear processing units. The nonlinear processing units are often referred to as neurons or cells. Mathematically, each cell can be modeled as a dissipative, nonlinear dynamical system where information is encoded via its initial state, inputs and variables used to define its behavior. Dynamics are usually continuous, as in the case of Continuous-Time CNN (CT-CNN) processors, but can be discrete, as in the case of Discrete-Time CNN (DT-CNN) processors.

Each cell has one output, by which it communicates its state with both other cells and external devices. Output is typically real-valued, but can be complex or even quaternion, i.e. a Multi-Valued CNN (MV-CNN). Most CNN processors, processing units are identical, but there are applications that require non-identical units, which are called Non-Uniform Processor CNN (NUP-CNN) processors, and consist of different types of cells.

Chua-Yang CNN
In the original Chua-Yang CNN (CY-CNN) processor, the state of the cell was a weighted sum of the inputs and the output was a piecewise linear function. However, like the original perceptron-based neural networks, the functions it could perform were limited: specifically, it was incapable of modeling non-linear functions, such as XOR. More complex functions are realizable via Non-Linear CNN (NL-CNN) processors.

Cells are defined in a normed gridded space like two-dimensional Euclidean geometry. However, the cells are not limited to two-dimensional spaces; they can be defined in an arbitrary number of dimensions and can be square, triangle, hexagonal, or any other spatially invariant arrangement. Topologically, cells can be arranged on an infinite plane or on a toroidal space. Cell interconnect is local, meaning that all connections between cells are within a specified radius (with distance measured topologically). Connections can also be time-delayed to allow for processing in the temporal domain.

Most CNN architectures have cells with the same relative interconnects, but there are applications that require a spatially variant topology, i.e. Multiple-Neighborhood-Size CNN (MNS-CNN) processors. Also, Multiple-Layer CNN (ML-CNN) processors, where all cells on the same layer are identical, can be used to extend the capability of CNN processors.

The definition of a system is a collection of independent, interacting entities forming an integrated whole, whose behavior is distinct and qualitatively greater than its entities. Although connections are local, information exchange can happen globally through diffusion. In this sense, CNN processors are systems because their dynamics are derived from the interaction between the processing units and not within processing units. As a result, they exhibit emergent and collective behavior. Mathematically, the relationship between a cell and its neighbors, located within an area of influence, can be defined by a coupling law, and this is what primarily determines the behavior of the processor. When the coupling laws are modeled by fuzzy logic, it is a fuzzy CNN. When these laws are modeled by computational verb logic, it becomes a computational verb CNN. Both fuzzy and verb CNNs are useful for modelling social networks when the local couplings are achieved by linguistic terms.

History
The idea of CNN processors was introduced by Leon Chua and Lin Yang in 1988. In these articles, Chua and Yang outline the underlying mathematics behind CNN processors. They use this mathematical model to demonstrate, for a specific CNN implementation, that if the inputs are static, the processing units will converge, and can be used to perform useful calculations. They then suggest one of the first applications of CNN processors: image processing and pattern recognition (which is still the largest application to date). Leon Chua is still active in CNN research and publishes many of his articles in the International Journal of Bifurcation and Chaos, of which he is an editor. Both IEEE Transactions on Circuits and Systems and the International Journal of Bifurcation also contain a variety of useful articles on CNN processors authored by other knowledgeable researchers. The former tends to focus on new CNN architectures and the latter more on the dynamical aspects of CNN processors.

In 1993, Tamas Roska and Leon Chua introduced the first algorithmically programmable analog CNN processor in the world. The multi-national effort was funded by the Office of Naval Research, the National Science Foundation, and the Hungarian Academy of Sciences, and researched by the Hungarian Academy of Sciences and the University of California. This article proved that CNN processors were producible and provided researchers a physical platform to test their CNN theories. After this article, companies started to invest into larger, more capable processors, based on the same basic architecture as the CNN Universal Processor. Tamas Roska is another key contributor to CNNs. His name is often associated with biologically inspired information processing platforms and algorithms, and he has published numerous key articles and has been involved with companies and research institutions developing CNN technology.

Literature
Two references are considered invaluable since they manage to organize the vast amount of CNN literature into a coherent framework:

 * An overview by Valerio Cimagalli and Marco Balsi. The paper provides a concise intro to definitions, CNN types, dynamics, implementations, and applications.
 * "Cellular Neural Networks and Visual Computing Foundations and Applications", written by Leon Chua and Tamas Roska, which provides examples and exercises. The book covers many different aspects of CNN processors and can serve as a textbook for a Masters or Ph.D. course.

Other resources include

 * The proceedings of "The International Workshop on Cellular Neural Networks and Their Applications" provide much CNN literature.
 * The proceedings are available online, via IEEE Xplore, for conferences held in 1990, 1992, 1994, 1996, 1998, 2000, 2002, 2005 and 2006.
 * There was also a workshop held in Santiago de Composetela, Spain. Topics included theory, design, applications, algorithms, physical implementations and programming and training methods.
 * For an understanding of the analog semiconductor based CNN technology, AnaLogic Computers has their product line, in addition to the published articles available on their homepage and their publication list. They also have information on other CNN technologies such as optical computing. Many of the commonly used functions have already been implemented using CNN processors. A good reference point for some of these can be found in image processing libraries for CNN based visual computers such as Analogic’s CNN-based systems.

Related processing architectures
CNN processors could be thought of as a hybrid between ANN and Continuous Automata (CA).

Artificial Neural Networks
The processing units of CNN and NN are similar. In both cases, the processor units are multi-input, dynamical systems, and the behavior of the overall systems is driven primarily through the weights of the processing unit’s linear interconnect.

However, in CNN processors, connections are made locally, whereas in ANN, connections are global.

For example, neurons in one layer are fully connected to another layer in a feed-forward NN and all the neurons are fully interconnected in Hopfield networks. In ANNs, the weights of interconnections contain information on the processing system’s previous state or feedback.

But in CNN processors, the weights are used to determine the dynamics of the system.

Furthermore, due to the high inter-connectivity of ANNs, they tend not exploit locality in either the data set or the processing and as a result, they usually are highly redundant systems that allow for robust, fault-tolerant behavior without catastrophic errors.

A cross between an ANN and a CNN processor is a Ratio Memory CNN (RMCNN). In RMCNN processors, the cell interconnect is local and topologically invariant, but the weights are used to store previous states and not to control dynamics. The weights of the cells are modified during some learning state creating long-term memory.

Continuous Automata
The topology and dynamics of CNN processors closely resembles that of CA. Like most CNN processors, CA consists of a fixed-number of identical processors that are spatially discrete and topologically uniform. The difference is that most CNN processors are continuous-valued whereas CA have discrete-values. Furthermore, the CNN processor's cell behavior is defined via some non-linear function whereas CA processor cells are defined by some state machine.

However, there are some exceptions. Continuous Valued Cellular Automata are CA with continuous resolution. Depending on how a given Continuous Automata is specified, it can also be a CNN.

There are also Continuous Spatial Automata, which consist of an infinite number of spatially continuous, continuous-valued automata. There is considerable work being performed in this field since continuous spaces are easier to mathematically model than discrete spaces, thus allowing a more quantitative approach as opposed to an empirical approach taken by some researchers of cellular automata. Continuous Spatial Automata processors can be physically realized though an unconventional information processing platform such as a chemical computer. Furthermore, it is conceivable that large CNN processors (in terms of the resolution of the input and output) can be modeled as a Continuous Spatial Automata.

Model of computation
The dynamical behavior of CNN processors can be expressed using differential equations, where each equation represents the state of an individual processing unit. The behavior of the entire CNN processor is defined by its initial conditions, inputs, cell interconnections (topology and weights), and the cells themselves. One possible use of CNN processors is to generate and respond to signals of specific dynamical properties. For example, CNN processors have been used to generate multiscroll chaos (like the Chen attractor), synchronize with chaotic systems, and exhibit multi-level hysteresis. CNN processors are designed specifically to solve local, low-level, processor intensive problems expressed as a function of space and time. For example, CNN processors can be used to implement high-pass and low-pass filters and morphological operators. They can also be used to approximate a wide range of Partial differential equations (PDE) such as heat dissipation and wave propagation.

Reaction-Diffusion
CNN processors can be used as Reaction-Diffusion (RD) processors. RD processors are spatially invariant, topologically invariant, analog, parallel processors characterized by reactions, where two agents can combine to create a third agent, and diffusion, the spreading of agents. RD processors are typically implemented through chemicals in a Petri dish (processor), light (input), and a camera (output) however RD processors can also be implemented through a multi-layer CNN processor. D processors can be used to create Voronoi diagrams and perform skeletonisation. The main difference between the chemical implementation and the CNN implementation is that CNN implementations are considerably faster than their chemical counterparts and chemical processors are spatially continuous whereas the CNN processors are spatially discrete. The most researched RD processor, Belousov-Zhabotinsky (BZ) processors, has already been simulated using a four-layer CNN processors and has been implemented in a semiconductor.

Boolean functions
Like CA, computations can be performed through the generation and propagation of signals that either grow or change over time. Computations can occur within a signal or can occur through the interaction between signals. One type of processing, which uses signals and is gaining momentum is wave processing, which involves the generation, expanding, and eventual collision of waves. Wave processing can be used to measure distances and find optimal paths. Computations can also occur through particles, gliders, solutions, and filterons localized structures that maintain their shape and velocity. Given how these structures interact/collide with each other and with static signals, they can be used to store information as states and implement different Boolean functions. Computations can also occur between complex, potentially growing or evolving localized behavior through worms, ladders, and pixel-snakes. In addition to storing states and performing Boolean functions, these structures can interact, create, and destroy static structures.

The applications of CNNs to Boolean functions is discussed in the paper by Fangyue Chen, Guolong He, Xiubin Xu, and Guanrong Chen, "Implementation of Arbitrary Boolean Functions via CNN".

Automata and Turing machines
Although CNN processors are primarily intended for analog calculations, certain types of CNN processors can implement any Boolean function, allowing simulating CA. Since some CA are Universal Turing machines (UTM), capable of simulating any algorithm can be performed on processors based on the von Neumann architecture, that makes this type of CNN processors, universal CNN, a UTM. One CNN architecture consists of an additional layer. CNN processors have resulted in the simplest realization of Conway’s Game of Life and Wolfram’s Rule 110, the simplest known universal Turing Machine. This unique, dynamical representation of an old systems, allows researchers to apply techniques and hardware developed for CNN to better understand important CA. Furthermore, the continuous state space of CNN processors, with slight modifications that have no equivalent in Cellular Automata, creates emergent behavior never seen before.

Any information processing platform that allows the construction of arbitrary Boolean functions is called universal, and as result, this class CNN processors are commonly referred to as universal CNN processors. The original CNN processors can only perform linearly separable Boolean functions. By translating functions from digital logic or look-up table domains into the CNN domain, some functions can be considerably simplified. For example, the nine-bit, odd parity generation logic, which is typically implemented by eight nested exclusive-or gates, can also be represented by a sum function and four nested absolute value functions. Not only is there a reduction in the function complexity, but the CNN implementation parameters can be represented in the continuous, real-number domain.

There are two methods by which to select a CNN processor along with a template or weights. The first is by synthesis, which involves determine the coefficients offline. This can be done by leveraging previous work, i.e. libraries, papers, and articles, or by mathematically deriving co that best suits the problem. The other is through training the processor. Researchers have used back-propagation and genetic algorithms to learn and perform functions. Back-propagation algorithms tend to be faster, but genetic algorithms are useful because they provide a mechanism to find a solution in a discontinuous, noisy search space.

Physical implementations
There are toy models simulating CNN processors using billiard balls, but these are used for theoretical studies. In practice, CNN are physically implemented on hardware and current technologies such as semiconductors. There are plans to migrate CNN processors to emerging technologies in the future.

Semiconductors
Semiconductor-based CNN processors can be segmented into analog CNN processors, digital CNN processors, and CNN processors emulated using digital processors. Analog CNN processors were the first to be developed. Analog computers were fairly common during the 1950 and 1960s, but they gradually were replaced by digital computers the 1970s. Analog processors were considerably faster in certain applications such as optimizing differential equations and modeling nonlinearities, but the reason why analog computing lost favor was the lack of precision and the difficulty to configure an analog computer to solve a complex equation.

Analog CNN processors share some of the same advantages as their predecessors, specifically speed. The first analog CNN processors were able to perform real-time ultra-high frame-rate (>10,000 frame/s) processing unachievable by digital processors. The analog implementation of CNN processors requires less area and consumes less power than their digital counterparts. Although the accuracy of analog CNN processors does not compare to their digital counterparts, for many applications, noise and process variances are small enough not to perceptually affect the image quality.

The first algorithmically programmable, analog CNN processor was created in 1993. It was named the CNN Universal Processor because its internal controller allowed multiple templates to be performed on the same data set, thus simulating multiple layers and allowing for universal computation. Included in the design was a single layer 8x8 CCN, interfaces, analog memory, switching logic, and software. The processor was developed in order to determine CNN processor producibility and utility. The CNN concept proved promising and by 2000, there were at least six organizations designing algorithmically programmable, analog CNN processors.

AnaFocus, AnaLogic
In the 2000s, AnaFocus, a mixed-signal semiconductor company from the University of Seville, introduced their ACE prototype CNN processor product line. Their first ACE processor contained 20x20 B/W processor units; and subsequent processors provided 48x48 and 128x128 grayscale processor units, improving the speed and processing elements. AnaFocus also had a multilayer CASE prototype CNN processors line. Their processors allowed real-time interaction between the sensing and processing. In 2014, AnaFocus had been sold to e2v technologies.

Another company, AnaLogic Computers was founded in 2000 by many of the same researchers behind the first algorithmically programmable CNN Universal Processor. In 2003, AnaLogic Computers developed a PCI-X visual processor board that included the ACE 4K processor, with a Texas Instrument DIP module and a high-speed frame-grabber. This allowed CNN processing to be easily included in a desktop computer. In 2006, AnaLogic Computers developed their Bi-I Ultra High Speed Smart Camera product line, which includes the ACE 4K processor in their high-end models.

In 2006, Roska et al. published a paper on designing a Bionic Eyeglass for AnaLogic. The Bionic Eyeglass is a dual-camera, wearable platform, based on the Bi-I Ultra High Speed Smart Camera, designed to provide assistance to blind people. Some of its functions include route number recognition and color processing.

Analog CNN processors
Some researchers developed their own custom analog CNN processors. For example:

 * A research team from University degli Studi di Catania made one in order to generate gaits for a hexapod robot.
 * Chung-Yu Wu and Chiu-Hung Cheng from National Chiao Tung University designed a RM-CNN processor to learn more about pattern learning and recognition.
 * Researchers from the National Lien-Ho Institute of Technology (W. Yen, R. Chen and J. Lai) developed a Min-Max CNN (MMCNN) processor to learn more about CNN dynamics.

Despite their speed and low power consumption, there are some significant drawbacks to analog CNN processors. First, analog CNN processors can potentially create erroneous results due to environment and process variation. In most applications, these errors are not noticeable, but there are situations where minor deviations can result in catastrophic system failures. For example, in chaotic communication, process variation will change the trajectory of a given system in phase space, resulting in a loss of synchronicity/stability. Due to the severity of the problem, there is considerable research being performed to ameliorate the problem. Some researchers are optimizing templates to accommodate greater variation. Other researchers are improving the semiconductor process to more closely match theoretical CNN performance. Other researchers are investigating different, potentially more robust CNN architectures. Lastly, researchers are developing methods to tune templates to target a specific chip and operating conditions. In other words, the templates are being optimized to match the information processing platform. Not only does process variation limit what can be done with current analog CNN processors, it is also a barrier for creating more complex processing units. Unless this process variation is resolved, ideas such as nested processing units, non-linear inputs, etc. cannot be implemented in a real-time analog CNN processor. Also, the semiconductor "real estate" for processing units limits the size of CNN processors.

Currently the largest AnaVision CNN-based vision processor consists of a 4K detector, which is significantly less than the megapixel detectors found in affordable, consumer cameras. Unfortunately, feature size reductions, as predicted by Moore’s Law, will only result in minor improvements. For this reason, alternate technologies such as Resonant Tunneling Diodes and Neuron-Bipolar Junction Transistors are being explored. Also, CNN processor architecture is being re-evaluated. For example, Star-CNN processors, where one analog multiplier is time-shared between multiple processor units, have been proposed and are expected to result in processor unit reduction size of 80%.

Digital CNN processors, FPGA
Although not nearly as fast and energy efficient, digital CNN processors do not share the problems of process variation and feature size of their analog counterparts. This allows digital CNN processors to include nested processor units, non-linearities, etc. In addition, digital CNN are more flexible, cost less and are easier to integrate. The most common implementation of digital CNN processors uses an FPGA. Eutecus, founded in 2002 and operating in Berkeley, provides intellectual property that can be synthesized into an Altera FPGA. Their digital 320x280, FPGA-based CNN processors run at 30 frame/s and there are plans to make a fast digital ASIC. Eustecus is a strategic partner of AnaLogic computers, and their FPGA designs can be found in several of AnaLogic’s products. Eutecus is also developing software libraries to perform tasks including but not limited to video analytics for the video security market, feature classification, multi-target tracking, signal and image processing and flow processing. Many of these routines are derived using CNN-like processing. For those wanting to perform CNN simulations for prototyping, low-speed applications, or research, there are several options. First, there are precise CNN emulation software packages like SCNN 2000. If the speed is prohibitive, there are mathematical techniques, such as Jacobi’s Iterative Method or Forward-Backward Recursions that can be used to derive the steady state solution of a CNN processor. Lastly, digital CNN processors can be emulated on highly parallel, application-specific processors, such as graphics processors. Implementing neural networks using graphics processors is an area of further research.

Holography, nanotechnology
Researchers are also perusing alternate technologies for CNN processors. Although current CNN processors circumvent some of the problems associated with their digital counterparts, they do share some of the same long-term problems common to all semiconductor-based processors. These include, but are not limited to, speed, reliability, power-consumption, etc. AnaLogic Computers, is developing optical CNN processors, which combine optics, lasers, and biological and holographic memories. What initially was technology exploration resulted in a 500x500 CNN processor able to perform 300 giga-operations per second.

Another promising technology for CNN processors is nanotechnology. One nanotechnology concept being investigated is using single electron tunneling junctions, which can be made into single-electron or high-current transistors, to create McCulloch-Pitts CNN processing units. In summary, CNN processors have been implemented and provide value to their users. They have been able to effectively leverage the advantages and address some of the disadvantages associated with their underling technology, i.e. semiconductors. Researchers are also transitioning CNN processors into emerging technologies. Therefore, if the CNN architecture is suited for a specific information processing system, there are processors available for purchase (as there will be for the foreseeable future).

Applications
CNN researchers have diverse interests, ranging from physical, engineering, theoretical, mathematical, computational, and philosophical applications.

Image processing
CNN processors were designed to perform image processing; specifically, real-time ultra-high frame-rate (>10,000 frame/s) processing for applications like particle detection in jet engine fluids and spark-plug detection. Currently, CNN processors can achieve up to 50,000 frames per second, and for certain applications such as missile tracking, flash detection, and spark-plug diagnostics these microprocessors have outperformed a conventional supercomputer. CNN processors lend themselves to local, low-level, processor intensive operations and have been used in feature extraction, level and gain adjustments, color constancy detection, contrast enhancement, deconvolution, image compression, motion estimation, image encoding, image decoding, image segmentation,  orientation preference maps, pattern learning/recognition, multi-target tracking, image stabilization, resolution enhancement, image deformations and mapping, image inpainting, optical flow, contouring,  moving object detection, axis of symmetry detection, and image fusion.

Due to their processing capabilities and flexibility, CNN processors have been used and prototyped for novel field applications such as flame analysis for monitoring combustion at a waste incinerator, mine-detection using infrared imagery, calorimeter cluster peak for high energy physics, anomaly detection in potential field maps for geophysics, laser dot detection, metal inspection for detecting manufacturing defects, and seismic horizon picking. They have also been used to perform biometric functions such as fingerprint recognition, vein feature extraction, face tracking, and generating visual stimuli via emergent patterns to gauge perceptual resonances.

Biology and medicine
CNN processors have been used for medical and biological research in performing automated nucleated cell counting for detecting hyperplasia, segment images into anatomically and pathologically meaningful regions, measure and quantify cardiac function, measure the timing of neurons, and detect brain abnormalities that would lead to seizures.

One potential future application of CNN microprocessors is to combine them with DNA microarrays to allow for a near-real time DNA analysis of hundreds of thousands of different DNA sequences. Currently, the major bottleneck of DNA microarray analysis is the amount of time needed to process data in the form of images, and using a CNN microprocessor, researchers have reduced the amount of time needed to perform this calculation to 7ms.

Texture recognition
CNN processors have also been used to generate and analyze patterns and textures. One motivation was to use CNN processors to understand pattern generation in natural systems. They were used to generate Turing patterns in order to understand the situations in which they form, the different types of patterns which can emerge, and the presence of defects or asymmetries. Also, CNN processors were used to approximate pattern generation systems that create stationary fronts, spatio-temporal patterns oscillating in time, hysteresis, memory, and heterogeneity. Furthermore, pattern generation was used to aid high-performance image generation and compression via real-time generation of stochastic and coarse-grained biological patterns, texture boundary detection, and pattern and texture recognition and classification.

Control and Actuator Systems
There is an ongoing effort to incorporate CNN processors into sensory-computing-actuating machines as part of the emerging field of Cellular Machines. The basic premise is to create an integrated system that uses CNN processors for the sensory signal-processing and potentially the decision-making and control. The reason is that CNN processors can provide a low power, small size, and eventually low-cost computing and actuating system suited for Cellular Machines. These Cellular Machines will eventually create a Sensor-Actuator Network (SAN), a type of Mobile Ad Hoc Networks (MANET) which can be used for military intelligence gathering, surveillance of inhospitable environments, maintenance of large areas, planetary exploration, etc.

CNN processors have been proven versatile enough for some control functions. They have been used to optimize function via a genetic algorithm, to measure distances, to perform optimal path-finding in a complex, dynamic environment, and theoretically can be used to learn and associate complex stimuli. They have also been used to create antonymous gaits and low-level motors for robotic nematodes, spiders, and lamprey gaits using a Central Pattern Generator (CPG). They were able to function using only feedback from the environment, allowing for a robust, flexible, biologically inspired robot motor system. CNN-based systems were able to operate in different environments and still function if some of the processing units are disabled.

Communication systems
The variety of dynamical behavior seen in CNN processors make them intriguing for communication systems. Chaotic communications using CNN processors is being researched due to their potential low power consumption, robustness and spread spectrum features. The premise behind chaotic communication is to use a chaotic signal for the carrier wave and to use chaotic phase synchronization to reconstruct the original message. CNN processors can be used on both the transmitter and receiver end to encode and decode a given message. They can also be used for data encryption and decryption, source authentication through watermarking, detecting of complex patterns in spectrogram images (sound processing), and transient spectral signals detection.

CNN processors are neuromorphic processors, meaning that they emulate certain aspects of biological neural networks. The original CNN processors were based on mammalian retinas, which consist of a layer of photodetectors connected to several layers of locally coupled neurons. This makes CNN processors part of an interdisciplinary research area whose goal is to design systems that leverage knowledge and ideas from neuroscience and contribute back via real-world validation of theories. CNN processors have implemented a real-time system that replicates mammalian retinas, validating that the original CNN architecture chosen modeled the correct aspects of the biological neural networks used to perform the task in mammalian life. However, CNN processors are not limited to verifying biological neural networks associated with vision processing; they have been used to simulate dynamic activity seen in mammalian neural networks found in the olfactory bulb and locust antennal lobe, responsible for pre-processing sensory information to detect differences in repeating patterns.

CNN processors are being used to understand systems that can be modeled using simple, coupled units, such as living cells, biological networks, physiological systems, and ecosystems. The CNN architecture captures some of the dynamics often seen in nature and is simple enough to analyze and conduct experiments. They are also being used for stochastic simulation techniques, which allow scientists to explore spin problems, population dynamics, lattice-based gas models, percolation, and other phenomena. Other simulation applications include heat transfer, mechanical vibrating systems, protein production, Josephson Junction problems, seismic wave propagation, and geothermal structures. Instances of 3d CNN have been used to prove certain emergent phenomena in complex systems, establishing a link between art, dynamical systems and VLSI technology.

CNN processors have been used to research a variety of mathematical concepts, such as non-equilibrium systems, constructing non-linear systems of arbitrary complexity, emergent chaotic dynamics, and discovering new dynamic behavior. They are often used in researching systemics, a trans-disciplinary, scientific field that studies natural systems. The goal of systemics researchers is to develop a conceptual and mathematical framework necessary to analyze, model, and understand systems, including, but not limited to, atomic, mechanical, molecular, chemical, biological, ecological, social and economic systems. Topics explored are emergence, collective behavior, local activity and its impact on global behavior, and quantifying the complexity of an approximately spatial and topologically invariant system. With another definition of complexity (MIT professor Seth Lloyd has identified 32 different definitions of complexity ), it can potentially be mathematically advantageous when analyzing systems such as economic and social systems.

title: Cellular neural network


text:
Hu Tu Tu

Hu Tu Tu is a 1999 Indian Hindi-language drama film directed by Gulzar, starring Nana Patekar, Sunil Shetty, Tabu and Suhasini Mulay.

Plot
The story opens with the kidnapping of Panna Barve, the daughter of Chief Minister Malti Barve. The responsible gang's demand is that one of their members be released from police custody. While in captivity, Panna reminisces about her childhood, where she had to struggle to grow up with a power hungry and inconsiderate mother and a simple, quiet, and spineless father. Panna's mother had also been carrying on a rather open affair with party co-member Sawantrao Gadre. Flashback over and Panna soon meets the man behind her kidnapping Aditya Patel who Panna knows from before.

Via second flashback, we learn that Panna and "Adi" were lovers once upon a time. Their closeness stemmed from the fact that he also was struggling with a corrupt parent in the form of businessman father, P.N. Patel. Panna and Adi both find solace in a poor basti with the company of Adi's old teacher Joshi Master and in the philosophy of poet Bhau, much to the dismay of the couple's respective parents. Bhau even goes to the extent of becoming Malti's most vociferous opponent. Due to a sudden car accident, however, Adi is presumed dead and Panna loses Adi's out-of-wedlock baby before it can be born. Thus ends the second flashback.

Getting back to the kidnapping, Adi and Panna reunite after quite some time. They talk to each other and piece together the events that have occurred since their separation. Just then, the missing gang member is sent back to Adi. It is none other than Bhau, who is returned to the gang with his brain destroyed by electric shock. News also comes that Joshi Master is killed in jail and it is portrayed as a suicide. Panna and Adi then decide what the best form of poetic justice will be for their parents. They both sneak into an election campaign of Malti Barve and P.N. Patel, and explode bombs attached to them, thus destroying everything. The film ends with Panna's father working as headmaster in a school.

Gulzar suggests that although we have already ruined the world for Generation X, we should focus our efforts into the protection and education of our school children. If we shield them from this corruption, they will become the leaders of tomorrow, and they will run the country the way it should be.

Cast

 * Nana Patekar as Bhau
 * Sunil Shetty as Aditya Patel (Adi)
 * Tabu as Panna Barve
 * Suhasini Mulay as Maltibai Barve
 * Shivaji Satam as Barve
 * Mohan Agashe as Sawantrao Gadre
 * Kulbhushan Kharbanda as P.N. Patel
 * Raj Zutshi as Arun Barve
 * Gracy Singh as Shanti
 * Ajit Vachani as Police Commissioner J.D.
 * Rajesh Khera

Soundtrack
Music by Vishal Bhardwaj.
 * 1) "Itna Lamba Kash Lo Yaaro" - Lata Mangeshkar, Hariharan
 * 2) "Bandobast Hai, Jabardast Hai" - Roop Kumar Rathod
 * 3) "Chhai Chhap Chhai, Chhapa Ke Chhai" - Lata Mangeshkar, Hariharan
 * 4) "Ghapla Hai, Ghapla Hai, Ghapla Hai Bhai" - Roop Kumar Rathod
 * 5) "Jago Jago Jagte Raho, Jago Jago Jagte Raho" - Roop Kumar Rathod
 * 6) "Jai Hind Hind, Guru Manter Mera" - Lata Mangeshkar
 * 7) "Nikla Neem Ke Talese Nikla" - Anuradha Paudwal, Kavita Krishnamurthy, Roop Kumar Rathod
 * 8) "Ye Ankhe, Ye Num Ankhe" - Lata Mangeshkar

title: Hu Tu Tu


text:
Stephen Kelly (footballer, born 1983)

Stephen Michael David Kelly (born 6 September 1983) is an Irish former professional footballer who played as a right back. He was part of the team that secured the Republic of Ireland's qualification for UEFA Euro 2012.

Kelly began his professional career at Tottenham Hotspur and also played for Southend United, Queens Park Rangers, Watford, Birmingham City, Stoke City, Fulham and Reading before joining his final club, Rotherham United, in 2015. He was capped 39 times for the Republic of Ireland.

Tottenham Hotspur
Kelly was born in Dublin, where he played football for Belvedere before joining Tottenham Hotspur through their youth programme. He was something of an understudy to Stephen Carr (who was subsequently transferred to Newcastle United) and then to Paul Stalteri. He made his Spurs first team debut in 2003 and then went on to make 37 Premier League appearances, scoring two league goals, against Birmingham City and Aston Villa.

Birmingham City
Birmingham City were reported to have agreed a deal to sign Kelly in January 2006 before Tottenham's shortage of defenders put a stop to the move. He did join Birmingham, however, on 28 June for an initial fee of £750,000, potentially rising to £1.25 million depending on his success with the club. He made 36 appearances in the 2006–07 Championship as Birmingham were promoted as runners-up.

Kelly was the only outfield player in the 2007–08 Premier League season to play every minute of every game for his club.

Stoke City (loan)
On 4 February 2009, Kelly joined Stoke City on loan from Birmingham City until the end of the 2008–09 season. Stoke City had to wait for 36 hours after the January transfer window shut for confirmation of the deal. Kelly made his Stoke debut in their next game, a 2–0 defeat to Sunderland, but picked up a hamstring injury while on international duty which kept him out of Stoke's next fixture.

Fulham

On 16 June 2009, Kelly signed a three-year contract with Fulham, making him the club's first signing of the 2009 summer window. He said he was delighted to join the Cottagers and was looking forward to representing the club in both the Premier League and Europa League. He helped Fulham reach the 2010 UEFA Europa League Final, playing in their memorable win against Juventus on the way, but he was left out of the squad for the final itself.

Reading
Kelly joined Reading on 11 January 2013, signing a $2 1/2$-year contract. He made his debut on 19 January in Reading's 2–1 away win over Newcastle United at St James' Park, made his home debut a week later against Sheffield United in a 4–0 FA Cup win, and soon afterwards, stated that "regardless of what happens now and for the rest of the season, coming here is the best decision I've made in football". Kelly started every game in what remained of the season, and the team were relegated to the Championship.

He was allocated squad number 3 for the 2013–14 season. Kelly scored his first goal for Reading on 1 January 2014, a 95th-minute header from Royston Drenthe's free kick that gave his side a draw at home to Nottingham Forest.

Kelly left Reading at the end of the 2014–15 season, despite being offered a new contract by the club.

Rotherham United
On 19 November 2015, Kelly joined Championship club Rotherham United until the end of the 2015–16 season. He left the club at the end of the 2016–17 season.

International career
Kelly won Irish caps at junior levels and became a member of the senior Irish national squad, making his debut versus Chile. He represented the Republic of Ireland Under-16 team at the 2000 UEFA European Under-16 Football Championship and the Under-20 team at the 2003 FIFA World Youth Championship.

On 29 March 2011, Kelly was named as Ireland captain for the friendly against Uruguay at the Aviva Stadium.

He was a squad member at UEFA Euro 2012 but saw no game time. Then, despite injuries to Richard Dunne and Sean St Ledger, manager Giovanni Trapattoni left him on the bench for the 6-1 home defeat to Germany in 2014 World Cup qualifying. Days later, Kelly had a training ground row with assistant manager Marco Tardelli, and was left so upset by the incident that he did not want to board the plane for the game against the Faroe Islands.

Honours
Birmingham City
 * Championship runner-up: 2006–07

Fulham
 * UEFA Europa League runner-up: 2009–10

International
 * Nations Cup: 2011

title: Stephen Kelly (footballer, born 1983)


text:
User:Amargo Scribe

I come seeking revolution. I joined the blogging revolution first, which I have come to believe has a strong resemblance to the wiki revolution in terms of the rapid way in which information disseminates in the blogosphere. My interest in wikipedia and wikis in general came about half a year later.

I'm probably best described as an inclusionist, as I think that the more information you make accessible here, the better off we all are.

title: User:Amargo Scribe


text:
User:Jengelh

Wikiness

 * Contributions to en.wikipedia.org
 * Contributions to de.wikipedia.org

~
http://inai.de/

title: User:Jengelh


text:
José Vizcaíno

José Luis Vizcaíno Pimental (born March 26, 1968) is a Dominican former professional baseball player. He was a backup infielder for most of his Major League Baseball (MLB) career. He, along with Darryl Strawberry and Ricky Ledée, are the only Major League Baseball players to have played for all four former and current New York teams—the New York Yankees, the New York Mets, the Los Angeles Dodgers, and the San Francisco Giants. With the Yankees, he won the 2000 World Series against the Mets.

Los Angeles Dodgers (1989–1990)
Vizcaíno made his debut with the Dodgers as a late-season call-up in 1989, where he played five games at shortstop for them to conclude the season. In 1990, he was again called up late, playing in 37 games and where he hit a respectable .275. Despite his play, he was traded to the Chicago Cubs on December 14, 1990.

Chicago Cubs (1991–1993)
In Chicago, Vizcaíno saw his playing time increase, appearing in no less than 86 games in any given season, including a career-high 151 games in 1992. In 1993, he played a significant role, having 551 at-bats and being 9th in the National League with 131 singles as well as second in the NL with 9 sacrifice flies.

New York Mets (1994–1996)
The Cubs traded Vizcaíno to the New York Mets on March 30, 1994, for Anthony Young and minor-leaguer Ottis Smith. In 1994, Vizcaíno, now a starter for the first time in his career, collected 105 hits before the strike shortened the season. When play resumed in 1995, Vizcaíno responded with his best season to that point, collecting 146 hits, including a career-high 21 doubles and 56 runs batted in, although his strikeouts increased slightly to 76. He finished fifth in the National League in hits that year. In 1996, Vizcaíno played in 96 games for the Mets, hitting .303 (a career-high) with 32 runs batted in. On July 29, 1996, Vizcaíno was traded to the Cleveland Indians along with Jeff Kent for Carlos Baerga and Alvaro Espinoza.

Cleveland Indians (1996)
In Cleveland, Vizcaíno appeared in 48 games to complete the 1996 season, and made his first career trip to the postseason. In the 1996 American League Division Series against the Baltimore Orioles, Vizcaíno collected four hits (including two doubles) and one run batted in. Despite these contributions, the Indians were defeated by the Orioles. On November 13, 1996, he was traded to the San Francisco Giants along with Matt Williams and a player to be named later (Joe Roa) and Trent Hubbard along with Jeff Kent and Julián Tavárez.

San Francisco Giants (1997)
With the Giants, he appeared in 151 games hitting .266 with a career-high 50 runs batted in, along with a career-high 87 strikeouts while again returning to the postseason and finished tenth in the National League in hits. In the postseason, Vizcaíno collected two hits and one run while striking out five times as the Giants were defeated by the Florida Marlins. On October 29, 1997, he was granted free agency.

Return to the Dodgers (1998–2000)
On December 8, 1997, Vizcaíno re-signed with the Los Angeles Dodgers. He appeared in a career-low 67 games in 1998 hitting .262 with 29 runs batted in. In 1999, Vizcaíno played in 94 games collecting 29 runs batted in.

Vizcaíno began the 2000 season with the Dodgers, hitting a dismal .204 over 40 games (collecting only 19 hits). On June 20, he was traded to the New York Yankees with cash for Jim Leyritz.

New York Yankees (2000)
Vizcaíno appeared in 73 games for the Yankees, hitting .276 with 10 runs batted in, earning a spot on the Yankees postseason roster. In the American League Division Series, he scored one run as a pinch-runner. In the American League Championship Series, he played in four games collecting two hits, three runs, and 2 runs batted in (along with two stolen bases) as the Yankees defeated the Seattle Mariners. Vizcaíno played in four of the five games in the 2000 World Series against the New York Mets. He is most known for his dramatic hit on October 21, 2000, in Game 1. In the bottom of the 12th inning of the then longest game in World Series history, Vizcaíno hit the game-winning RBI single. He earned a World Series ring when the Yankees defeated the Mets in five games. On November 1, he was granted free agency.

Houston Astros (2001–2005)
Vizcaíno signed with the Astros on November 20. In 2001, he hit .277 with 71 hits and 14 runs batted in. He appeared in three games in the 2001 National League Division Series, he was 1 for 6 as Houston was defeated by the Atlanta Braves. In 2002, he hit .303 with five home runs and 37 runs batted in 125 games. In 2003, Vizcaíno appeared in only 91 games, where he collected 26 runs batted in. In 2004, Vizcaíno rebounded, hitting .274 and playing in 138 games at shortstop while Adam Everett was out with a broken wrist. In the 2005 National League Division Series, Vizcaíno went 0-for-5 in two games. Despite his lack of productivity, the Astros defeated the Braves in 5 games. In the 2005 National League Championship Series against the St. Louis Cardinals, Vizcaíno did not fare better, again going hitless. In the 2005 World Series, Vizcaíno collected one hit, one walk, and two runs batted in. In Game 2 of the 2005 World Series, he came close to repeating his 2000 World Series walk-off moment when he hit a two-run single with two outs in the ninth inning to tie the game. Following his game tying hit for the Houston Astros, Vizcaíno stayed in the game at shortstop for the bottom of the ninth, and on the way out to his position, he realized he had forgotten his cap and had to return to the dugout to get it. After the game Vizcaíno commented "It was crazy, I ran out there without [a cap], and when I realized it, I felt funny. More camera time for me, I guess." The Astros went on to lose when Scott Podsednik homered in the bottom of the inning and overshadowed Vizcaíno's heroics. In Game 3 of that year's Series, Vizcaíno played the entire game, which broke the record for the longest game in World Series history on October 25, 2005.

Return to the Giants (2006)
Vizcaíno was not offered arbitration following the 2005 season from Houston. Instead, he signed a one-year contract with the San Francisco Giants, who designated pitcher Brian Burres for assignment to make room for him on the roster. On August 14, Vizcaíno was designated for assignment by the Giants after hitting just .210 over 64 games.

St. Louis Cardinals (2006)
On August 23, 2006, Vizcaíno was signed to a contract by the Cardinals and spent the rest of the 2006 season as a replacement for injured shortstop David Eckstein.

Post-playing career
Vizcaíno was hired as a Special Assistant of Baseball Operations in the Los Angeles Dodgers front office in January 2008.

Personal life
Vizcaíno's son, José Jr., played college baseball for Santa Clara University and was drafted by the San Francisco Giants in the 7th round of the 2015 MLB Draft.

title: José Vizcaíno


text:
Wikipedia:Articles for deletion/Brah Records

 This page is an archive of the proposed deletion of the article below. Further comments should be made on the appropriate discussion page (such as the article's talk page or on a Votes for Undeletion nomination). No further edits should be made to this page.

The result of the debate was Delete --Allen3 talk 22:55, August 28, 2005 (UTC)

Brah Records
del promo of a record label with no releases. mikka (t) 19:24, 21 August 2005 (UTC)
 * Delete per nom Dottore So 20:22, 21 August 2005 (UTC)
 * The above discussion is preserved as an archive of the debate. Please do not modify it. Subsequent comments should be made on the appropriate discussion page (such as the article's talk page or in an undeletion request). No further edits should be made to this page.


text:
Wikipedia:Featured picture candidates/Lake Victoria

Lake Victoria

I know a slightly disproportionate amount of space pictures show up in this article, but this one in particular struck me as worthy of featured picture status. The color contrast between the lake and the surrounding plain draws the eye to the picture, and the slight cloud cover and the other four lakes in the background contribute to the beauty and (in a sense) to the exoticism of the shot. The picture is from NASA, so it is in the public domain- hence, no need to worry about copyright.

~ Veledan • Talk + new 20:44, 7 September 2005 (UTC)
 * Nominate and support. - PatadyBag 19:14, 21 August 2005 (UTC)
 * Unacceptable, unless a larger resolution image is available. Preferably upwards of 800 by 600 pixels. Phoenix2 01:35, August 22, 2005 (UTC)
 * Comment: Checked the NASA website which has this image, and a higher res photo isn't available. -- tomf688  06:08, August 24, 2005 (UTC)
 * ( − ) Oppose Too low res --Fir0002 08:01, August 24, 2005 (UTC)
 * Oppose: It's unfortunate that a larger image is not available, but regardless of size the picture does not stike me as particularly beautiful or interesting. Raven4x4x 10:14, August 24, 2005 (UTC)
 * Oppose. Agree with above. Enochlau 11:17, 24 August 2005 (UTC)
 * Oppose for same reasons as listed as above. --ScottyBoy900Q ∞ 14:10, 25 August 2005 (UTC)


text:
Northern Tutchone

The Northern Tutchone are a First Nations people of the Athabaskan-speaking ethnolinguistic group living mainly in the central Yukon in Canada.

Language and culture
The Northern Tutchone language, originally spoken by the Northern Tutchone people, is a variety of the Tutchone language, part of the Athabaskan language family. Song Keeper Jerry Alfred is leading a movement to keep the language alive through his music.

Governments
Northern Tutchone First Nations governments and communities include:
 * First Nation of Na-Cho Nyäk Dun (Mayo, Yukon) (Na-Cho Nyäk Dun - "Big River People", because they called the Stewart River Na Cho Nyak, meaning Big River, most northerly Northern Tutchone First Nation)
 * Little Salmon/Carmacks First Nation (Carmacks, Yukon) (Tagé Cho Hudän - "Big River People")
 * Selkirk First Nation (Pelly Crossing, Yukon) (Hućha Hudän - "Flatland People", because of the landscape in Fort Selkirk, where the land is flat on both sides of the river)
 * White River First Nation (Beaver Creek, Yukon)

title: Northern Tutchone


text:
File:The Blues and the Abstract Truth (Oliver Nelson album - cover art).jpg

Summary
The Blues and the Abstract Truth


text:
Kulbhushan Kharbanda

Kulbhushan Kharbanda (born 21 October 1944) is an Indian actor who works in Hindi and Punjabi films. He is best known for his role as the antagonist Shakaal in Shaan (1980), Starting off with the Delhi-based theatre group 'Yatrik' in the 1960s, he moved to films with Sai Paranjpye's Jadu Ka Shankh in 1974. He worked in several parallel cinema films before working in the mainstream Hindi film industry. He appeared in Mahesh Bhatt's classic Arth (1982), Ek Chadar Maili Si (1986), Waaris (1988), and in all three parts of Deepa Mehta's Elements trilogy: Fire (1996), Earth (1998), and Water (2005). After nearly two decades he was seen on the theatre stage at the Padatik Theatre in Kolkata in the production of Atmakatha, directed by Vinay Sharma.

Career
After his studies he and a few of his college friends formed a theatre group called "Abhiyaan", and then joined Delhi-based "Yatrik", a bilingual theatre repertory founded by director Joy Michael in 1964; he became its first paid artiste, though after a few years Yatrik collapsed as the director was lecturing in US universities. That is when he moved to Kolkata in 1972 and started working with the theatre group "Padatik" which did Hindi theatre, under director Shyamanand Jalan. Here he worked for a while before moving on to Mumbai and films.

He first got noticed in Nishaant (1974) by Shyam Benegal, with whom he went on to work in several more films including Manthan (1976), Bhumika: The Role (1977), Junoon (1978), and Kalyug (1980). Soon he was a regular with parallel cinema directors, like in Godhuli (1977) with B. V. Karanth.

Playing the bald villain Shakaal in Shaan (1980) directed by Ramesh Sippy, he saw his transition into mainstream cinema. Kharbanda went on to appear in Shakti (1982), Ghayal (1990), Jo Jeeta Wohi Sikandar (1992), Gupt (1997), Border (1997), Yes Boss (1997) and Refugee (2000). However, he continued appearing in art films such as Chakra (1981), with Smita Patil and Naseeruddin Shah, Arth (1982), with Shabana Azmi, Andhi Gali (1984), the first Hindi film of Buddhadeb Dasgupta, Ek Chadar Maili Si (1986), with Hema Malini, Utsav (1984), by Girish Karnad, Mandi (1983), Trikal (1985), Susman (1987), by Shyam Benegal, Naseem (1995), by Saeed Akhtar Mirza and Monsoon Wedding (2001) directed by Mira Nair.

He portrayed Reema Lagoo's husband and Raj Babbar's brother in Shashi Kapoor's Filmwalas Productions' Kalyug. He has also appeared in period films such as Jodha Akbar and Lagaan.

He has acted in a number of Punjabi films. He portrayed the hero in the legendary film Chan Pardesi (1980) and starred in the Punjabi comedy Mahaul Theek Hai (1999).

He has acted in six of Deepa Mehta's movies and all her trilogy films: Earth, Fire and Water. He did a German film in 2009.

He has acted in TV serials, such as Shanno Ki Shaadi and Mahi Ve.

He has been seen on the stage in plays such as Teen Farishtay, Hatya ek akaar ki, Baki Itihaas, Ek Shunya Bajirao, Guinea Pig, Girdhade, Sakharam Binder and, recently, Atmakatha.

title: Kulbhushan Kharbanda


text:
Arsenio Iglesias

Arsenio Iglesias Pardo (24 December 1930 – 5 May 2023) was a Spanish football player and manager.

Nicknamed O Bruxo de Arteixo ("The Wizard of Arteixo"), he had a five-decade professional career closely associated to Deportivo as both a player and manager.

Playing career
Born in Arteixo, Province of A Coruña, Iglesias played as a forward and started his career with local side Deportivo de La Coruña. He made his La Liga debut on 28 October 1951 in a 6–1 away loss against FC Barcelona, and scored the following weekend against RCD Español (3–1 home win).

Iglesias netted seven goals in three separate seasons for the Galicians, adding a career-best eight in 1956–57, which nonetheless ended in relegation. In six of the following eight years he also played in the top division, representing Sevilla FC, Granada CF and Real Oviedo; he amassed competition totals of 238 games and 50 goals, and retired at 35 after a spell in the lower leagues with Albacete Balompié.

Coaching career
Iglesias started coaching one year after retiring, his first appointment being at Deportivo's reserves, which he accumulated with assistant duties in the main squad. Midway through the 1970–71 campaign he was named the first team's manager, leading them to a top-flight promotion and being relegated in 1973.

In 1973–74, Iglesias repeated the feat with another Segunda División side, Hércules CF, then remained at the club's helm for a further three years, always managing to comfortably stay afloat – this included a fifth place in 1975 and a sixth in 1976. In the 1977–78 season another promotion to the main division befell, this time as champions with Real Zaragoza.

Iglesias worked in the top tier in two of the next three seasons, leading Burgos CF to the 13th position in 1978–79 and being fired by AD Almería midway through the 1980–81 campaign amid several internal disputes. In 1982 he returned to Deportivo, with the club in division two.

In 1987–88, Iglesias was one of three coaches as Depor nearly suffered relegation to Segunda División B, being saved by a last-minute goal against Racing de Santander. He was again reinstated as first-team manager, finally attaining promotion to the first division in 1991 after ranking second.

Iglesias replaced the dismissed Marco Antonio Boronat at the club's helm late in 1991–92, as Deportivo had to play a relegation playoff against Real Betis, eventually winning 2–1 on aggregate. In the following seasons, however, Super Depor came to fruition, with several team players winning individual accolades and being called to the Spain national team as the side finished three consecutive campaigns in the top three; during this timeframe, he was named Manager of the Year three times, twice by Don Balón and once by El País.

Iglesias retired from football after 1994–95. Midway through the following campaign, however, he accepted an offer from Real Madrid to replace the fired Jorge Valdano, with the Merengues eventually ranking sixth and being eliminated in the quarter-finals of the UEFA Champions League by eventual winners Juventus FC.

In 2005, Iglesias was appointed manager of the Galicia national team, working alongside Fernando Vázquez. In the previous decade, he also worked as a sports commentator.

In 2016, Iglesias was bestowed with the highest recognition of Deportivo, a special insignia, and was declared "Blue and White Legend". The event took place at halftime of the last game of the 2015–16 season, at the Estadio Riazor.

Death
Iglesias died in A Coruña on 5 May 2023, at age 92.

Manager
Zaragoza
 * Segunda División: 1977–78

Deportivo
 * Copa del Rey: 1994–95

title: Arsenio Iglesias


text:
Wikipedia:WikiProject Formula One/Example race report

This is an example race report which follows all of WikiProject Formula One's standards. It is intended to be copied and modified when creating new reports. Please remove the comments in the source text when copying.
 * Title: 2016 Monaco Grand Prix

The 2016 Monaco Grand Prix (formally known as the Formula 1 Grand Prix de Monaco 2016) was a Formula One motor race held on 29 May 2016 at the Circuit de Monaco, a street circuit that runs through the Principality of Monaco. It was the sixth round of the 2016 season, and marked the seventy-fourth time that the Monaco Grand Prix had been held, as well as the sixty-third time it had been held as a round of the Formula One World Championship since the series inception in.

Nico Rosberg was the defending race winner having won the past three Monaco Grands Prix in a row and entered the race with a thirty-nine-point lead held over Ferrari driver Kimi Räikkönen in the Drivers' Championship. Rosberg's team, Mercedes, held a 48-point lead over Ferrari in the Constructors' Championship.

During Saturday's qualifying, Daniel Ricciardo, who was driving for Red Bull Racing, achieved the first pole position of his career. In an eventful race, Mercedes's Lewis Hamilton took victory ahead of Ricciardo, who had lost time during a pitstop when his mechanics did not have the tyres ready for him. Sergio Pérez completed the podium for Force India, the team's first appearance in the top three of the season and their first since the 2015 Russian Grand Prix.

Background
Following their controversial crash and double retirement at the previous race in Spain two weeks earlier, particular attention was on championship leaders Mercedes and their drivers Nico Rosberg and Lewis Hamilton. The team was adamant that such an incident could not be repeated, with their head of motorsport Toto Wolff saying: "We cannot afford to drop the ball, so we must remain united, remain strong and hit back hard this weekend." With a win, Rosberg would have been able to become the only driver other than Ayrton Senna to win the Monaco Grand Prix four times in a row, while Hamilton had suffered a string of bad results at the circuit, having won only once in 2008. At the race the year before, Hamilton had lost what he felt was a certain victory by a wrong decision to pit him during a safety car period.

Fernando Alonso received a new, revised combustion engine for his car, his third of five allowed over the course of the season without receiving a grid penalty. Power unit supplier Honda stressed that they had not used any development tokens, a set of limited allowed changes to the units, but had instead only improved reliability. The team also equipped both cars with new batteries and electronics control units, set to improve the reliability of the cars as well. During the two-day testing session that took place after the previous Grand Prix at the Circuit de Barcelona-Catalunya, Renault introduced an updated version of their power unit, which was used during the test to the satisfaction of driver Kevin Magnussen, who declared that the new unit was a step forward in both power and driveability. He urged the team to pull the introduction of the power unit forward to the Monaco race, instead of the following Grand Prix in Canada as originally planned. Renault chose to do so, however, they were only able to hand out one updated unit to both their works team and Red Bull, who used them under the name TAG Heuer. The two units were eventually given to Magnussen at Renault and Daniel Ricciardo at Red Bull.

The race saw the competitive début of Pirelli's new ultrasoft tyre compound, which was provided alongside the supersoft and soft compounds. Per the regulations of the 2016 season, every driver needs to set aside one set each of the two softest compounds for the race and one set of the ultrasofts for Q3 (should they advance). The drivers have freedom of what other compounds they choose for the remaining ten out of thirteen sets. From this race onwards, the Fédération Internationale de l'Automobile allowed drivers to choose alternative helmet designs for one race weekend per season, a practice usually prohibited as they have to wear the same design to make them more recognisable to spectators and television audiences. As a consequence, Felipe Massa's helmet featured extensive artwork by graffiti artist Os Gêmeos, teammate Valtteri Bottas featured casino-inspired imagery and Haas driver Romain Grosjean sported a tribute to the late Jules Bianchi on his helmet. The race marked a reason for celebration at McLaren, as the team had started their first ever Grand Prix at Monaco fifty years earlier.

Going into the weekend, Nico Rosberg led the Drivers' Championship with 100 points, followed by Ferrari's Kimi Räikkönen with 61 points. Lewis Hamilton followed in third, a further four points behind, with Sebastian Vettel in fourth with 48 points, level with Daniel Ricciardo in fifth. In the constructors' standings, Mercedes led with 157 points, 48 points ahead of Ferrari, with Red Bull Racing in third with 94 points.

Free practice
Per the regulations for the 2016 season, two ninety-minute practice and one sixty-minute session were held before qualifying on Saturday. The first two usually take place on Friday, with Monaco being the single exemption, where those sessions are held on Thursday, in order to minimise road-closure disruptions to local residents. In the first session on Thursday morning, Lewis Hamilton topped the timesheets with a time of 1:15.537, one tenth of a second faster than his teammate Nico Rosberg. They were followed by Sebastian Vettel, almost half a second down on Hamilton, and the two Red Bull cars of Daniel Ricciardo and Max Verstappen respectively. Daniil Kvyat, driving for Toro Rosso, in sixth was the last driver to get within a second of Hamilton's time. He was the only one of the front runners to set his time on the supersoft instead of the faster ultrasoft tyres. There were several incidents during the session: After twenty-four minutes, Felipe Massa hit the barrier in turn one, damaging his car and leading to a virtual safety car (VSC) period. Later, Lewis Hamilton had a brake lockup at the same spot, but was able to get into the run-off area without touching the guardrail. Several other drivers had dangerous moments in turn one as well, but the most severe incident of the session came three minutes to the end: A drain cover had come loose around the first corner, puncturing Rosberg's left rear tyre and damaging Jenson Button's McLaren MP4-31, causing the practice to be red flagged, ultimately ending the session.

In second practice on Thursday afternoon, Ricciardo was fastest, setting a time of 1:14.607, more than half a second clear of Hamilton in second place. Rosberg and Verstappen, in third and fourth, were the only other drivers to get within a second of Ricciardo, while the two Williams drivers Valtteri Bottas and Felipe Massa struggled, ending the session 14th and 16th respectively. At Ferrari, Kimi Räikkönen was fastest in seventh spot. His teammate, Vettel, had an incident-packed session that eventually ended with him setting the ninth fastest time. He spun at Mirabeau corner, damaging his rear wing, only to hit the wall in turn one after coming back to the track, albeit continuing with wheel rim damage. A VSC period occurred after Romain Grosjean crashed into the outside barrier at the exit of the tunnel. Two more VSC periods ensued when Rio Haryanto touched the inside barrier at the same spot and later after Kevin Magnussen crashed at the final corner.

In the third practice session on Saturday morning, Sebastian Vettel set the fastest time, about one hundredth of a second faster than Hamilton. Nico Rosberg and Daniel Ricciardo followed, both also within two tenth of a second of Vettel. Max Verstappen was fifth fastest although he had a minor crash coming up to Casino square, clipping the wall. Toro Rosso were again quick, getting both drivers into the top ten. Renault had different fortunes, as both drivers had accidents, with Jolyon Palmer hindering one of Hamilton's flying laps as he crashed at the swimming pool section.

Qualifying
Qualifying consisted of three parts, 18, 15 and 12 minutes in length respectively, with six drivers eliminated from competing after each of the first two sessions. In the first part of qualifying (Q1), the session got interrupted shortly after it had started, as Felipe Nasr came to a halt at the exit of the tunnel, caused by an engine failure. A red flag came out while the car was cleared off the track. When the running resumed, all drivers except for the two at Force India went out on the ultrasoft tyres to set their first lap times. Max Verstappen was the last to set a representative time, but touched the guardrail at the swimming pool chicane and crashed into the wall, causing another red flag period. As the session got back under way, it were the two Manor cars of Rio Haryanto and Pascal Wehrlein, as well as Jolyon Palmer and Marcus Ericsson who joined Nasr and Verstappen on the sidelines, as they were eliminated. Kevin Magnussen meanwhile barely made it into Q2, but was under investigation for exiting the pit lane while it was closed.

In the second part, Lewis Hamilton quickly set a fast lap time, the quickest of the weekend up to that point, about half a second ahead of his teammate Rosberg. Meanwhile, Daniel Ricciardo set his fastest lap on the harder supersoft compound tyre, meaning that he would be able to start the race on them, should it have stayed dry. On the back end, Williams struggled for pace and both Valtteri Bottas and Felipe Massa missed out on Q3 by qualifying 11th and 14th respectively. Also eliminated were Esteban Gutiérrez, Jenson Button, Romain Grosjean and Magnussen. As Q3 started, Lewis Hamilton stopped in the pit lane with a loss of power and was pushed back into the garage. He was eventually able to go on track and qualified third, after starting several quick laps only to abandon them to leave his final run to the last moment. He was however beaten to pole position by Ricciardo, who was almost three-tenths of a second faster than second placed Rosberg, with Vettel following in fourth almost a second slower. Nico Hülkenberg managed fifth ahead of Kimi Räikkönen, who was to serve a five-place grid penalty for an unscheduled gearbox change, leaving him eleventh on the grid. Carlos Sainz Jr., Sergio Pérez, Daniil Kvyat and Fernando Alonso rounded up the top ten. Ricciardo's pole position was the first for a Renault-powered turbocharged car since Ayrton Senna's front-of-the-grid start at the 1986 Mexican Grand Prix for Lotus.

Post-qualifying
After qualifying, the race stewards decided not to give a penalty to Magnussen for crossing the pit light, since it had only changed to red 0.55 seconds before he crossed the pit exit line. Kvyat escaped penalty as well after his car failed the obligatory front floor deflection test. As the team pointed out, the irregularity was the result of an impact on track, allowing him to keep eighth on the grid.

Qualifying classification

 * Notes:
 * – Kimi Räikkönen received a five-place grid penalty for an unscheduled gearbox change.
 * – Felipe Nasr and Max Verstappen failed to set a time within 107% of the fastest lap during Q1. They had to apply to the stewards for permission to start the race. Both opted to start the race from the pit lane. Verstappen started in front, as he had set a time in qualifying, unlike Nasr.

Race
With rain shortly before the race, the start was taken behind the safety car, forcing all drivers to start the race on the full wet tyres. As Ricciardo led the field behind the safety car, Daniil Kvyat had to come into the pit lane on lap two, complaining of technical issues. He rejoined with a new steering wheel, being a lap down on the rest of the pack already. The race started in earnest on lap seven, with Ricciardo defending his lead at the restart. Kevin Magnussen made a pit stop for intermediate tyres at the end of the lap, but his teammate Jolyon Palmer proved just how slippery it still was when he crashed out just a lap later, being caught out by a wet zebra crossing and causing a virtual safety car period. More cars came into the pitlane for intermediate tyres over the following laps. On lap twelve, Kimi Räikkönen damaged his front wing on the guardrail at the Loews hairpin, resulting in his front wing getting caught under his front tyres, blocking Grosjean's way in the process. Räikkönen retired some corners later. Meanwhile, Ricciardo built a gap at the front, being ten seconds clear of Rosberg on lap 13. One lap later, Sebastian Vettel was the first of the front runners to change to intermediate tyres. Mercedes issued team orders demanding Rosberg let Hamilton past on lap 16, but the gap had by then grown to 13 seconds. On lap 21, Rosberg made a pit stop for the intermediate tyres, leaving only Ricciardo and Hamilton at the front of the field on the full wet tyres. Ricciardo made the switch on lap 24, but Hamilton stayed out, opting to remain on the wet tyre until the track dried out enough to go straight to slicks. In the meantime, Verstappen had fought his way back into the top ten, after having started 21st. In the subsequent laps, Ricciardo was able to reduce the gap to Hamilton in the lead, edging as close as half a second by lap 28. Behind the leading pair, Rosberg was third ahead of Pérez and Vettel. The pivotal moment of the race followed on lap 31, when Hamilton changed to slick tyres. When Ricciardo followed suit a lap later, his pit crew were not ready for him and had the wrong tyres, resulting in a long stop, handing the lead to Hamilton, who stayed narrowly ahead of him. Sergio Pérez was another driver who benefited during the second round of stops, emerging in third. Rosberg was left in sixth after both Vettel and Alonso also came out ahead of him after the switch to dry tyres. On lap 34, Ricciardo made an attempt to repass Hamilton on track, but Hamilton successfully defended his position. Another virtual safety car period ensued on lap 34, caused by Verstappen who crashed his car into the barrier after locking up his tyres. As the VSC ended on lap 37, Ricciardo once more failed in an attempt to regain the lead. At the chicane coming out of the tunnel, Hamilton misjudged the corner and backed Ricciardo off at the exit of the chicane, causing the latter to complain about the move on team radio. While the incident was investigated by the stewards, the decision was not to take action against Hamilton. At that point, the order stood as follows: Hamilton, Ricciardo, Pérez, Vettel, Alonso, Rosberg, Hülkenberg, Sainz, Button and Gutiérrez. The top four drivers pulled away cleanly from the rest of the field behind them. On lap 50, the two Sauber cars collided at Rascasse corner, after Felipe Nasr had ignored instructions from the pit lane to let his teammate Ericsson behind him pass. Another VSC period was called while both Sauber drivers made pit stops to repair damages, only for both to retire some laps later. In front, the race carried on in the same order. On lap 68, the fourth virtual safety car period occurred when a large plastic sheet fell onto the start–finish straight. Hamilton was able to extend his lead over Ricciardo at that point, setting the fastest lap of the race on lap 71. Three laps from the finish, rain started to fall again, although no driver changed tyres before the chequered flag fell. Hamilton crossed the finish line to take victory ahead of Ricciardo and Pérez. This win for Hamilton marked his second at Monaco, the other being in 2008. These two races featured many similarities, such as the Hamilton starting third on the grid, the race starting in wet conditions and finishing in the dry, as well as Hamilton taking the lead on lap 33. Vettel hung on to fourth, followed by Alonso in fifth. Rosberg however lost his sixth place to Nico Hülkenberg on the very last lap.

Post-race
At the podium interviews, conducted by former Formula One driver Martin Brundle, Hamilton thanked his team and expressed satisfaction about how the race went. He pointed to the problems of driving on the full wet tyres for such a long distance, saying that they were about to "drop off", meaning to lose much of their grip to the race surface, when he came in to change. He complimented Ricciardo on driving "phenomenally all weekend". Ricciardo himself lamented his misfortune in losing the race during his second pit stop. In regard to his team's error and their different strategy at the previous race in Spain, which he felt had cost him a chance at victory there as well, he said: "Two weekends in a row I've been screwed now. It sucks. It hurts." He emphasised that it had not been his decision to pit at that time, but that the team had called him in and criticised them for not being ready when he arrived. Sergio Pérez on the other hand was "extremely happy" with the performance by him and the team, saying that the race was his favourite podium finish while driving for Force India. Speaking about the moment when Nico Rosberg let him past in the early stages of the race, Hamilton told the press that he had thanked his teammate for "being a gentleman". When asked how painful it had been to be asked to let Hamilton go by, Rosberg said: "It was more painful the feeling that I had in the car. That was the worst. Around Monaco, that's not a nice feeling to have. I had no confidence at all. The second thing [team order] was just a consequence of that." Mercedes's motorsport director Toto Wolff also praised Rosberg for working for the team and moving to the side without questioning the team's decision. Rosberg was however unable to give an explanation for his slow pace during the early stages. He pointed to the possibility that his car's tyre and brake temperatures had been particularly affected by the period behind the safety car.

Following their intra-team collision, Sauber's team principal Monisha Kaltenborn put blame on both drivers. The stewards penalised Ericsson for the incident, handing him a three-place grid penalty for the following race in Canada as well as three penalty points to his licence. Felipe Nasr was adamant that the team orders he had received prior to the accident had been uncalled for, since his slower pace was due to low tyre temperatures. He also claimed that Ericsson had ignored team orders himself on two occasions in the previous season. Ericsson in turn had a different view and said that the team had told him for "seven or eight laps" that they would swap the positions of the drivers before he decided to go for the pass himself. Valtteri Bottas and Pascal Wehrlein also received penalties during and after the race. Bottas was handed a ten-second time penalty and two penalty points on his licence for causing a collision with Gutiérrez, while Wehrlein received two separate ten-second penalties: the first for exceeding the allowed lap time under VSC conditions and the second for ignoring blue flags. He was also given two penalty points each for both incidents.

Following the Grand Prix, Nico Rosberg retained first place in the Drivers' Championship with 106 points, but his lead over the second-placed driver, now Hamilton, had decreased to 24 points. Daniel Ricciardo moved up to third with 66 points, five points ahead of Räikkönen. In the Constructors' standings, Mercedes extended their lead over Ferrari to 67 points, with Red Bull in third another nine points behind.

Race classification

 * Notes:
 * – Valtteri Bottas originally finished 11th but received a ten-second time penalty after the race for causing a collision with Esteban Gutiérrez.
 * – Pascal Wehrlein received a ten-second time penalty for ignoring blue flags and another ten-second time penalty for driving too quickly under the virtual safety car.

Championship standings after the race

 * Drivers' Championship standings

 * Constructors' Championship standings

 * Note: Only the top five positions are included for both sets of standings.


text:
Talk:Samuel Sharp

Untitled
Given the long history of the abolitionist struggle in England, it seems a bit exaggerated to say that it's the Sharp inquiry that led to slavery's end. If this is the case, can it be explained more thoroughly why this would be, and can we see a specific source for it? For now I'm reducing the claim to make it a factor, rather than as the previous text seemed to imply, the primary cause--but I hope someone who knows more than me will come along and add specifics. --Dvyost 19:25, 21 August 2005 (UTC)

The weblink sais the name is Sharpe. Which is the right version? --84.166.15.36 18:17, 24 August 2006 (UTC)
 * I think Sharpe seems more common. I have moved the text across. My apologies for creating the article under the wrong name. JMcC 19:04, 3 October 2006 (UTC)

title: Talk:Samuel Sharp