I Khalil Gibran (mibait Gibran Khalil Gibran bin Mikhā'īl bin Sa'ad; Arabu , Enero 6, 1883 – Abril 10, 1931) a mayayaus muring Kahlil Gibran, metung yang talagulis, poeta, ampong talasulat a Lebanese American. Mibait ya king balen ning Bsharri a ngeni atiu king Lebanon (at kanita atiu king Ottoman Syria), minalis ya kayabe ning kayang pamilia king Estados Unidos nung nu ya megaral arte, at nung nu na inumpisan ing kayang carera king paniulat. Makikilala ya keraklan uling king kayang librung mibulalag aniang 1923, ing The Prophet, a serie da reng salese o essay a makasulat king prosang Ingles. Metung yang maranun a alimbawa ning inspirational fiction ing libru, a matalik misali lipat ning marimla dang pamanggap deng criticu, at sinikat yang ustu king  1960s counterculture.

Obra
king Arabu:
 Nubthah fi Fan Al-Musiqa (1905)
 Ara'is al-Muruj (Nymphs of the Valley, also translated as Spirit Brides, 1906)
 al-Arwah al-Mutamarrida (Spirits Rebellious, 1908)
 al-Ajniha al-Mutakassira (Broken Wings, 1912)
 Dam'a wa Ibtisama (A Tear and A Smile, 1914)
 al-Mawakib (The Processions, 1919)
 al-'Awāsif (The Tempests, 1920)
 al-Bada'i' waal-Tara'if (The New and the Marvellous,1923)

king Ingles, bayu ya mete:
 The Madman (1918) (downloadable free version)
 Twenty Drawings (1919)
 The Forerunner (1920)
 The Prophet, (1923)
 Sand and Foam (1926)
 Kingdom Of The Imagination (1927)
 Jesus, The Son of Man (1928)
 The Earth Gods (1931)

King Ingles, kaibat ning kamatayan na:
 The Wanderer (1932)
 The Garden of the Prophet(1933)
 Lazarus and his Beloved (1933)
 Prose and Poems (1934)
 A Self-Portrait (1959)
 Thought and Meditations (1960)
 Spiritual sayings (1962)
 Voice of the master (1963)
 Mirrors of the Soul (1965)
 The Vision (1994)
 Eye of the Prophet (1995)

Aliwa:
 Beloved Prophet, The love letters of Khalil Gibran and Mary Haskell, and her private journal (1972, edited by Virginia Hilu)

Galal
 Lebanese Ministry of Post and Telecommunications published a stamp in his honor in 1971.
 Gibran Museum in Bsharri, Lebanon
 Gibran Khalil Gibran Garden, Beirut, Lebanon
 Khalil Gibran Street, Ville Saint-Laurent, Quebec, Canada inaugurated on 27 Sept. 2008 on occasion of the 125th anniversary of his birth.
 Gibran Khalil Gibran Skiing Piste, The Cedars Ski Resort, Lebanon
 Khalil Gibran Memorial Garden in Washington, D.C., dedicated in 1990
 Pavilion K. Gibran at École Pasteur in Montréal, Quebec, Canada
 Gibran Memorial Plaque in Copley Square, Boston, Massachusetts
 Khalil Gibran International Academy, a public high school in Brooklyn, NY, opened in September 2007
 Khalil Gibran Park (Parcul Khalil Gibran) in Bucharest, Romania
 Gibran Kalil Gibran sculpture on a marble pedestal indoors at Arab Memorial building at Curitiba, Paraná, Brazil

Pamamanggit king popular a cultura

Pelicula
 A phrase from The Prophet is read aloud by Norma Shearer's character in The Women (1939 film) just before her daughter gives her the information that sends her to get her husband back.
 The Prophet is seen in the Johnny Cash biopic Walk the Line when June Carter hands it to J.R. to read in the motel.
 Gibran is quoted in South Central (film), "You may tie my hands with chains and my feet with shackles, and put me in the dark prison, but you shall not enslave my thinking, for it is free, like the breeze in the spacious sky."
 Gibran's poem, For What is it to Die, is read during a funeral in Todd Field's 2001 film, In the Bedroom.
 Lines from Gibran's poem "On Love" from his book "The Prophet" are read to a sleeping Rachel in the movie "The Poet" (US title "Hearts of War")

Musica
 The Lebanese Tenor Gabriel Abdel Nour dedicated a complete album to Gibran, Gabriel Abdel Nour sings Gibran Khalil Gibran, where all the songs were extracts from Gibran's writings. Gabriel is the only singer to dedicate a complete album to Gibran. He has celebrated as well the memorial of Gibran in different countries.
 The song Broken Wings, a US #1 hit for the band Mr. Mister was inspired by Gibran's book of the same name.
 The Egyptian Singer Tony Kaldas presented in 2008 Big Concerts Celebrating the Jubilee 125 Years of Gibran Khalil Gibran Birth in The Egyptian Opera House and in Bibliotheca Alexandrina in Egypt. Also, he released two new songs from Gibran Words.
 Jazz saxophonist Jackie McLean's "Khalil the Prophet" is on his album Destination...Out! (1963) (Blue Note BLP 4165)
 Brisbane based improvisational Jazz Quintet, The Neighbourhood Groove Collective, name 2 songs "The Firefly & the Stars" and "Love Crowns" on their second release titled "Pieces" inspired by imagery from the Prophet.
 Jason Mraz's song "God Rests In Reason" on the album Selections For Friends features words from the poem "The Prophet"
 The lyrics to David Bowie's "The Width of a Circle", off his album The Man Who Sold the World (1970), relates a surrealist scene in which the narrator and his doppelgänger seek the help of a blackbird, who just "laughed insane and quipped 'Khalil Gibran'".
 Michigan experimental screamo outfit Men As Trees quote Gibran in the liner notes to their 2008 album, Weltschmerz: "We wanderers, ever seeking the lonelier way, begin no day where we have ended another day; and no sunrise finds us where sunset has left us."
 Tyrannosaurus Rex's second album, Prophets, Seers & Sages – The Angels of the Ages, released in October 1968, was dedicated in Gibran's memory.
 Guitarist Derek Trucks named his son Charles Khalil Trucks for saxophonist Charlie Parker, guitarist Charlie Christian, and Gibran.
 His book The Prophet is mentioned in the Mad Season song, "River of Deceit". "My pain is self-chosen. At least, so The Prophet says".
 The Chicago-based metal band Minsk's second album The Ritual Fires of Abandonment's lyrics are inspired by Gibran, who also is credited as an author of the lyrics in the CD booklet.
 Khalil Gibran is briefly mentioned in the Common Market song; "Connect For".
 Khalil Gibran is referenced in the Van Morrison song "Rave On John Donne"
 Sweet Honey In The Rock's song "On Children" is a musical version of Khalil Gibran's poem by the same name.
 Electronic band Children of the Bong use samples quoting from 'The Prophet' in their track 'The Veil'
 Album on Atlantic Records (K50109 Stereo) (1974) *The Prophet" Kahlil Gibran "A Musical Interpretation Featuring Richard Harris" ~ Produced And Composed By Arif Mardin

Aliwa
 Syrian mini-series titled "Gibran Khalil Gibran", broadcast on the Syrian state television in November 2008.
 In the popular video game Deus Ex, one of the three possible ending quotes is Gibran's quote: "Yesterday we obeyed kings and bent our necks before emperors. But today we kneel only to truth..." The western spelling of his name, Khalil Gibran, was used to credit him.
 Gibran is referenced briefly in the episode Wingmen of the show The Boondocks. When Huey (the central character) is asked by his grandfather to say something "deep", he recites part of the poem "On Pain" from The Prophet.
 In the hit TV show One Tree Hill, Lucas Scott (Chad Michael Murray) quotes Gibran.
 Gibran is referenced in the popular American sitcom Friends. Richard, played by Tom Selleck, quotes from the friendship passage of The Prophet during a meal with Chandler and Monica. (Season 6)
 San Diego Padres shortstop Khalil Greene was named after Gibran.
 In the 2000 TV Series The Invisible Man, main character Darien Fawkes quotes Gibran on the subject of parents and children in the season 2 episode "The Camp."
 At the end of an episode of Criminal Minds, entitled "Perfect Storm", Gibran is quoted as saying "Out of suffering have emerged the strongest souls. The most massive characters are seared with scars."
 "Love has no other desire but to fulfil itself..." quoted in the novel Georgia by Leslie Pearse, page 571
 Jodi Picoult quoted Gibran in one of her novels on one of the pages which contain just a quote, to begin another section of the story.

Dalerayan

 Khalil Gibran and Ameen Rihani: Prophets of Lebanese-American Literature. Ed. by Naji B. Oueijan, et al. Louaize: Notre Dame Press, 1999.
Michael Corrigan mentions another writer's use of The Prophet in his grief memoir, A Year and a Day, published by the Idaho State University Press, 2008.

Suglung palual

 Online copies of texts by Gibran
 , documentary, May 31, 2007
 Works by Khalil Gibran
 Gibran paintings and love letters
 History page links Gibran to W.B Yeats
 The Prophet by Gibran Parts of the Prophet in English, French, Czech and Arabic
 Short commentary on The Prophet

1883 kebaitan
1931 kematyan
Deaths from cirrhosis
Deaths from tuberculosis
Lebanese Americans
Arab American writers
Arabs of the Ottoman Empire
American poets
Lebanese poets
Lebanese writers
Cultural history of Boston, Massachusetts
Lebanese Maronites
Syrian nationalists
American Maronites
Mystics
Infectious disease deaths in New York

Khalil Gibran


Shenfield is part of the conurbation of Brentwood, Essex, England. The original town centre is located one mile (1.6 km) north-east of the centre of Brentwood. There are some small industrial areas and a modest, but busy, shopping area. Shenfield serves predominantly as a dormitory town for commuters to London and surrounding towns such as Romford and Basildon. This is facilitated by easy access to the A12 Road, the M25 motorway and rail services on the Great Eastern Main Line.

References

Towns in Essex

Shenfield


A memristor (; a portmanteau of memory resistor) is a non-linear two-terminal electrical component relating electric charge and magnetic flux linkage. It was described and named in 1971 by Leon Chua, completing a theoretical quartet of fundamental electrical components which also comprises the resistor, capacitor and inductor.

Chua and Kang later generalized the concept to memristive systems. Such a system comprises a circuit, of multiple conventional components, which mimics key properties of the ideal memristor component and is also commonly referred to as a memristor. Several such memristor system technologies have been developed, notably ReRAM.

The identification of memristive properties in electronic devices has attracted controversy. Experimentally, the ideal memristor has yet to be demonstrated.

As a fundamental electrical component

Chua in his 1971 paper identified a theoretical symmetry between the non-linear resistor (voltage vs. current), non-linear capacitor (voltage vs. charge), and non-linear inductor (magnetic flux linkage vs. current). From this symmetry he inferred the characteristics of a fourth fundamental non-linear circuit element, linking magnetic flux and charge, which he called the memristor. In contrast to a linear (or non-linear) resistor, the memristor has a dynamic relationship between current and voltage, including a memory of past voltages or currents. Other scientists had proposed dynamic memory resistors such as the memistor of Bernard Widrow, but Chua introduced a mathematical generality.

Derivation and characteristics
The memristor was originally defined in terms of a non-linear functional relationship between magnetic flux linkage Φm(t) and the amount of electric charge that has flowed, q(t):

The magnetic flux linkage, Φm, is generalized from the circuit characteristic of an inductor. It does not represent a magnetic field here. Its physical meaning is discussed below. The symbol Φm may be regarded as the integral of voltage over time.

In the relationship between Φm and q, the derivative of one with respect to the other depends on the value of one or the other, and so each memristor is characterized by its memristance function describing the charge-dependent rate of change of flux with charge.

Substituting the flux as the time integral of the voltage, and charge as the time integral of current, the more convenient forms are;

To relate the memristor to the resistor, capacitor, and inductor, it is helpful to isolate the term M(q), which characterizes the device, and write it as a differential equation.

The above table covers all meaningful ratios of differentials of I, q, Φm, and V. No device can relate dI to dq, or dΦm to dV, because I is the derivative of q and Φm is the integral of V.

It can be inferred from this that memristance is charge-dependent resistance. If M(q(t)) is a constant, then we obtain Ohm's law R(t) = V(t)/I(t). If M(q(t)) is nontrivial, however, the equation is not equivalent because q(t) and M(q(t)) can vary with time. Solving for voltage as a function of time produces

This equation reveals that memristance defines a linear relationship between current and voltage, as long as M does not vary with charge. Nonzero current implies time varying charge. Alternating current, however, may reveal the linear dependence in circuit operation by inducing a measurable voltage without net charge movement—as long as the maximum change in q does not cause much change in M.

Furthermore, the memristor is static if no current is applied. If I(t) = 0, we find V(t) = 0 and M(t) is constant. This is the essence of the memory effect.

Analogously, we can define a  as menductance.

The power consumption characteristic recalls that of a resistor, I2R.

As long as M(q(t)) varies little, such as under alternating current, the memristor will appear as a constant resistor. If M(q(t)) increases rapidly, however, current and power consumption will quickly stop.

M(q) is physically restricted to be positive for all values of q (assuming the device is passive and does not become superconductive at some q). A negative value would mean that it would perpetually supply energy when operated with alternating current.

Modelling and validation
In order to understand the nature of memristor function, some knowledge of fundamental circuit theoretic concepts is useful, starting with the concept of device modeling.

Engineers and scientists seldom analyze a physical system in its original form. Instead, they construct a model which approximates the behaviour of the system. By analyzing the behaviour of the model, they hope to predict the behaviour of the actual system. The primary reason for constructing models is that physical systems are usually too complex to be amenable to a practical analysis.

In the 20th century, work was done on devices where researchers did not recognize the memristive characteristics. This has raised the suggestion that such devices should be recognised as memristors. Pershin and Di Ventra have proposed a test that can help to resolve some of the long-standing controversies about whether an ideal memristor does actually exist or is a purely mathematical concept.

The rest of this article primarily addresses memristors as related to ReRAM devices, since the majority of work since 2008 has been concentrated in this area.

Superconducting memristor component
Dr. Paul Penfield, in a 1974 MIT technical report mentions the memristor in connection with Josephson junctions. This was an early use of the word "memristor" in the context of a circuit device.

One of the terms in the current through a Josephson junction is of the form:

where  is a constant based on the physical superconducting materials,  is the voltage across the junction and  is the current through the junction.

Through the late 20th century, research regarding this phase-dependent conductance in Josephson junctions was carried out. A more comprehensive approach to extracting this phase-dependent conductance appeared with Peotta and DiVentra's seminal paper in 2014.

Memristor circuits
Due to the practical difficulty of studying the ideal memristor, we will discuss other electrical devices which can be modelled using memristors. For a mathematical description of a memristive device (systems), see Theory.

A discharge tube can be modelled as a memristive device, with resistance being a function of the number of conduction electrons .

 is the voltage across the discharge tube,  is the current flowing through it and  is the number of conduction electrons. A simple memristance function is .  and  are parameters depending on the dimensions of the tube and the gas fillings. An experimental identification of memristive behaviour is the "pinched hysteresis loop" in the  plane. For an experiment that shows such a characteristic for a common discharge tube, see "A physical memristor Lissajous figure" (YouTube). The video also illustrates how to understand deviations in the pinched hysteresis characteristics of physical memristors.

Thermistors can be modelled as memristive devices.

 is a material constant,  is the absolute body temperature of the thermistor,  is the ambient temperature (both temperatures in Kelvin),  denotes the cold temperature resistance at ,  is the heat capacitance and  is the dissipation constant for the thermistor.

A fundamental phenomenon that has hardly been studied is memristive behaviour in pn-junctions. The memristor plays a crucial role in mimicking the charge storage effect in the diode base, and is also responsible for the conductivity modulation phenomenon (that is so important during forward transients).

Criticisms
In 2008, a team at HP Labs found experimental evidence for the Chua's memristor based on an analysis of a thin film of titanium dioxide, thus connecting the operation of ReRAM devices to the memristor concept. According to HP Labs, the memristor would operate in the following way: the memristor's electrical resistance is not constant but depends on the current that had previously flowed through the device, i.e., its present resistance depends on how much electric charge has previously flowed through it and in what direction; the device remembers its history—the so-called non-volatility property. When the electric power supply is turned off, the memristor remembers its most recent resistance until it is turned on again.

The HP Labs result was published in the scientific journal Nature.
Following this claim, Leon Chua has argued that the memristor definition could be generalized to cover all forms of two-terminal non-volatile memory devices based on resistance switching effects. Chua also argued that the memristor is the oldest known circuit element, with its effects predating the resistor, capacitor, and inductor. There are, however, some serious doubts as to whether a genuine memristor can actually exist in physical reality. Additionally, some experimental evidence contradicts Chua's generalization since a non-passive nanobattery effect is observable in resistance switching memory. A simple test has been proposed by Pershin and Di Ventra to analyze whether such an ideal or generic memristor does actually exist or is a purely mathematical concept. Up to now, there seems to be no experimental resistance switching device (ReRAM) which can pass the test.

These devices are intended for applications in nanoelectronic memory devices, computer logic, and neuromorphic/neuromemristive computer architectures. In 2013, Hewlett-Packard CTO Martin Fink suggested that memristor memory may become commercially available as early as 2018. In March 2012, a team of researchers from HRL Laboratories and the University of Michigan announced the first functioning memristor array built on a CMOS chip.

According to the original 1971 definition, the memristor is the fourth fundamental circuit element, forming a non-linear relationship between electric charge and magnetic flux linkage. In 2011, Chua argued for a broader definition that includes all two-terminal non-volatile memory devices based on resistance switching. Williams argued that MRAM, phase-change memory and ReRAM are memristor technologies. Some researchers argued that biological structures such as blood and skin fit the definition. Others argued that the memory device under development by HP Labs and other forms of ReRAM are not memristors, but rather part of a broader class of variable-resistance systems, and that a broader definition of memristor is a scientifically unjustifiable land grab that favored HP's memristor patents.

In 2011, Meuffels and Schroeder noted that one of the early memristor papers included a mistaken assumption regarding ionic conduction. In 2012, Meuffels and Soni discussed some fundamental issues and problems in the realization of memristors. They indicated inadequacies in the electrochemical modeling presented in the Nature article "The missing memristor found" because the impact of concentration polarization effects on the behavior of metal−TiO2−x−metal structures under voltage or current stress was not considered. This critique was referred to by Valov et al. in 2013.

In a kind of thought experiment, Meuffels and Soni furthermore revealed a severe inconsistency: If a current-controlled memristor with the so-called non-volatility property exists in physical reality, its behavior would violate Landauer's principle, which places a limit on the minimum amount of energy required to change "information" states of a system. This critique was finally adopted by Di Ventra and Pershin in 2013.

Within this context, Meuffels and Soni pointed to a fundamental thermodynamic principle: Non-volatile information storage requires the existence of free-energy barriers that separate the distinct internal memory states of a system from each other; otherwise, one would be faced with an "indifferent" situation, and the system would arbitrarily fluctuate from one memory state to another just under the influence of thermal fluctuations. When unprotected against thermal fluctuations, the internal memory states exhibit some diffusive dynamics, which causes state degradation. The free-energy barriers must therefore be high enough to ensure a low bit-error probability of bit operation. Consequently, there is always a lower limit of energy requirement – depending on the required bit-error probability – for intentionally changing a bit value in any memory device.

In the general concept of memristive system the defining equations are (see Theory):

where u(t) is an input signal, and y(t) is an output signal. The vector x represents a set of n state variables describing the different internal memory states of the device. ẋ is the time-dependent rate of change of the state vector x with time.

When one wants to go beyond mere curve fitting and aims at a real physical modeling of non-volatile memory elements, e.g., resistive random-access memory devices, one has to keep an eye on the aforementioned physical correlations. To check the adequacy of the proposed model and its resulting state equations, the input signal u(t) can be superposed with a stochastic term ξ(t), which takes into account the existence of inevitable thermal fluctuations. The dynamic state equation in its general form then finally reads:

where ξ(t) is, e.g., white Gaussian current or voltage noise. On base of an analytical or numerical analysis of the time-dependent response of the system towards noise, a decision on the physical validity of the modeling approach can be made, e.g., would the system be able to retain its memory states in power-off mode?

Such an analysis was performed by Di Ventra and Pershin with regard to the genuine current-controlled memristor. As the proposed dynamic state equation provides no physical mechanism enabling such a memristor to cope with inevitable thermal fluctuations, a current-controlled memristor would erratically change its state in course of time just under the influence of current noise. Di Ventra and Pershin thus concluded that memristors whose resistance (memory) states depend solely on the current or voltage history would be unable to protect their memory states against unavoidable Johnson–Nyquist noise and permanently suffer from information loss, a so-called "stochastic catastrophe". A current-controlled memristor can thus not exist as a solid-state device in physical reality.

The above-mentioned thermodynamic principle furthermore implies that the operation of two-terminal non-volatile memory devices (e.g. "resistance-switching" memory devices (ReRAM)) cannot be associated with the memristor concept, i.e., such devices cannot by itself remember their current or voltage history. Transitions between distinct internal memory or resistance states are of probabilistic nature. The probability for a transition from state {i} to state {j} depends on the height of the free-energy barrier between both states. The transition probability can thus be influenced by suitably driving the memory device, i.e., by "lowering" the free-energy barrier for the transition {i} → {j} by means of, for example, an externally applied bias.

A "resistance switching" event can simply be enforced by setting the external bias to a value above a certain threshold value. This is the trivial case, i.e., the free-energy barrier for the transition {i} → {j} is reduced to zero. In case one applies biases below the threshold value, there is still a finite probability that the device will switch in course of time (triggered by a random thermal fluctuation), but – as one is dealing with probabilistic processes – it is impossible to predict when the switching event will occur. That is the basic reason for the stochastic nature of all observed resistance-switching (ReRAM) processes. If the free-energy barriers are not high enough, the memory device can even switch without having to do anything.

When a two-terminal non-volatile memory device is found to be in a distinct resistance state {j}, there exists therefore no physical one-to-one relationship between its present state and its foregoing voltage history. The switching behavior of individual non-volatile memory devices thus cannot be described within the mathematical framework proposed for memristor/memristive systems.

An extra thermodynamic curiosity arises from the definition that memristors/memristive devices should energetically act like resistors. The instantaneous electrical power entering such a device is completely dissipated as Joule heat to the surrounding, so no extra energy remains in the system after it has been brought from one resistance state xi to another one xj. Thus, the internal energy of the memristor device in state xi, U(V, T, xi), would be the same as in state xj, U(V, T, xj), even though these different states would give rise to different device's resistances, which itself must be caused by physical alterations of the device's material.

Other researchers noted that memristor models based on the assumption of linear ionic drift do not account for asymmetry between set time (high-to-low resistance switching) and reset time (low-to-high resistance switching) and do not provide ionic mobility values consistent with experimental data. Non-linear ionic-drift models have been proposed to compensate for this deficiency.

A 2014 article from researchers of ReRAM concluded that Strukov's (HP's) initial/basic memristor modeling equations do not reflect the actual device physics well, whereas subsequent (physics-based) models such as Pickett's model or Menzel's ECM model (Menzel is a co-author of that article) have adequate predictability, but are computationally prohibitive. As of 2014, the search continues for a model that balances these issues; the article identifies Chang's and Yakopcic's models as potentially good compromises.

Martin Reynolds, an electrical engineering analyst with research outfit Gartner, commented that while HP was being sloppy in calling their device a memristor, critics were being pedantic in saying that it was not a memristor.

Experimental tests
Chua suggested experimental tests to determine if a device may properly be categorized as a memristor:
 The Lissajous curve in the voltage-current plane is a pinched hysteresis loop when driven by any bipolar periodic voltage or current without respect to initial conditions.
 The area of each lobe of the pinched hysteresis loop shrinks as the frequency of the forcing signal increases.
 As the frequency tends to infinity, the hysteresis loop degenerates to a straight line through the origin, whose slope depends on the amplitude and shape of the forcing signal.

According to Chua all resistive switching memories including ReRAM, MRAM and phase-change memory meet these criteria and are memristors. However, the lack of data for the Lissajous curves over a range of initial conditions or over a range of frequencies complicates assessments of this claim.

Experimental evidence shows that redox-based resistance memory (ReRAM) includes a nanobattery effect that is contrary to Chua's memristor model. This indicates that the memristor theory needs to be extended or corrected to enable accurate ReRAM modeling.

Theory
In 2008, researchers from HP Labs introduced a model for a memristance function based on thin films of titanium dioxide. For RON ≪ ROFF the memristance function was determined to be

where ROFF represents the high resistance state, RON represents the low resistance state, μv represents the mobility of dopants in the thin film, and D represents the film thickness. The HP Labs group noted that "window functions" were necessary to compensate for differences between experimental measurements and their memristor model due to non-linear ionic drift and boundary effects.

Operation as a switch
For some memristors, applied current or voltage causes substantial change in resistance. Such devices may be characterized as switches by investigating the time and energy that must be spent to achieve a desired change in resistance. This assumes that the applied voltage remains constant. Solving for energy dissipation during a single switching event reveals that for a memristor to switch from Ron to Roff in time Ton to Toff, the charge must change by ΔQ = Qon−Qoff.

Substituting V = I(q)M(q), and then ∫dq/V = ∆Q/V for constant VTo produces the final expression. This power characteristic differs fundamentally from that of a metal oxide semiconductor transistor, which is capacitor-based. Unlike the transistor, the final state of the memristor in terms of charge does not depend on bias voltage.

The type of memristor described by Williams ceases to be ideal after switching over its entire resistance range, creating hysteresis, also called the "hard-switching regime". Another kind of switch would have a cyclic M(q) so that each off-on event would be followed by an on-off event under constant bias. Such a device would act as a memristor under all conditions, but would be less practical.

Memristive systems
In the more general concept of an n-th order memristive system the defining equations are

where u(t) is an input signal, y(t) is an output signal, the vector x represents a set of n state variables describing the device, and g and f are continuous functions. For a current-controlled memristive system the signal u(t) represents the current signal i(t) and the signal y(t) represents the voltage signal v(t). For a voltage-controlled memristive system the signal u(t) represents the voltage signal v(t) and the signal y(t) represents the current signal i(t).

The pure memristor is a particular case of these equations, namely when x depends only on charge (x = q) and since the charge is related to the current via the time derivative dq/dt = i(t). Thus for pure memristors f (i.e. the rate of change of the state) must be equal or proportional to the current i(t) .

Pinched hysteresis

One of the resulting properties of memristors and memristive systems is the existence of a pinched hysteresis effect. For a current-controlled memristive system, the input u(t) is the current i(t), the output y(t) is the voltage v(t), and the slope of the curve represents the electrical resistance. The change in slope of the pinched hysteresis curves demonstrates switching between different resistance states which is a phenomenon central to ReRAM and other forms of two-terminal resistance memory. At high frequencies, memristive theory predicts the pinched hysteresis effect will degenerate, resulting in a straight line representative of a linear resistor. It has been proven that some types of non-crossing pinched hysteresis curves (denoted Type-II) cannot be described by memristors.

Memristive networks and mathematical models of circuit interactions
The concept of memristive networks was first introduced by Leon Chua in his 1965 paper "Memristive Devices and Systems." Chua proposed the use of memristive devices as a means of building artificial neural networks that could simulate the behavior of the human brain. In fact, memristive devices in circuits have complex interactions due to Kirchhoff's laws.
A memristive network is a type of artificial neural network that is based on memristive devices, which are electronic components that exhibit the property of memristance.
In a memristive network, the memristive devices are used to simulate the behavior of neurons and synapses in the human brain. The network consists of layers of memristive devices, each of which is connected to other layers through a set of weights. These weights are adjusted during the training process, allowing the network to learn and adapt to new input data.
One advantage of memristive networks is that they can be implemented using relatively simple and inexpensive hardware, making them an attractive option for developing low-cost artificial intelligence systems. They also have the potential to be more energy efficient than traditional artificial neural networks, as they can store and process information using less power. However, the field of memristive networks is still in the early stages of development, and more research is needed to fully understand their capabilities and limitations.
For the simplest model with only memristive devices with voltage generators in series,
there is an exact and in closed form equation (Caravelli-Traversa-Di Ventra equation, CTD) which describes the evolution of the internal memory of the network for each device.
For a simple memristor model (but not realistic) of a switch between two resistance values, given by the Williams-Strukov model , with ,
there is a set of nonlinearly coupled differential equations that takes the form:

where  is the diagonal matrix with elements  on the diagonal,  are based on the memristors physical parameters. The vector  is the vector of voltage generators in series to the memristors. The circuit topology enters only in the projector operator , defined in terms of the cycle matrix of the graph. The equation provides a concise mathematical description of the interactions due to Kirchhoff 's laws. Interestingly, the equation shares many properties in common with a Hopfield network, such as the existence of Lyapunov functions and classical tunnelling phenomena. In the context of memristive networks, the CTD equation may be used to predict the behavior of memristive devices under different operating conditions, or to design and optimize memristive circuits for specific applications.

Extended systems
Some researchers have raised the question of the scientific legitimacy of HP's memristor models in explaining the behavior of ReRAM. and have suggested extended memristive models to remedy perceived deficiencies.

One example attempts to extend the memristive systems framework by including dynamic systems incorporating higher-order derivatives of the input signal u(t) as a series expansion

where m is a positive integer, u(t) is an input signal, y(t) is an output signal, the vector x represents a set of n state variables describing the device, and the functions g and f are continuous functions. This equation produces the same zero-crossing hysteresis curves as memristive systems but with a different frequency response than that predicted by memristive systems.

Another example suggests including an offset value  to account for an observed nanobattery effect which violates the predicted zero-crossing pinched hysteresis effect.

Implementations

Titanium dioxide memristor
Interest in the memristor revived when an experimental solid-state version was reported by R. Stanley Williams of Hewlett Packard in 2007. The article was the first to demonstrate that a solid-state device could have the characteristics of a memristor based on the behavior of nanoscale thin films. The device neither uses magnetic flux as the theoretical memristor suggested, nor stores charge as a capacitor does, but instead achieves a resistance dependent on the history of current.

Although not cited in HP's initial reports on their TiO2 memristor, the resistance switching characteristics of titanium dioxide were originally described in the 1960s.

The HP device is composed of a thin (50 nm) titanium dioxide film between two 5 nm thick electrodes, one titanium, the other platinum. Initially, there are two layers to the titanium dioxide film, one of which has a slight depletion of oxygen atoms. The oxygen vacancies act as charge carriers, meaning that the depleted layer has a much lower resistance than the non-depleted layer. When an electric field is applied, the oxygen vacancies drift (see Fast ion conductor), changing the boundary between the high-resistance and low-resistance layers. Thus the resistance of the film as a whole is dependent on how much charge has been passed through it in a particular direction, which is reversible by changing the direction of current. Since the HP device displays fast ion conduction at nanoscale, it is considered a nanoionic device.

Memristance is displayed only when both the doped layer and depleted layer contribute to resistance. When enough charge has passed through the memristor that the ions can no longer move, the device enters hysteresis. It ceases to integrate q=∫I dt, but rather keeps q at an upper bound and M fixed, thus acting as a constant resistor until current is reversed.

Memory applications of thin-film oxides had been an area of active investigation for some time. IBM published an article in 2000 regarding structures similar to that described by Williams. Samsung has a U.S. patent for oxide-vacancy based switches similar to that described by Williams.

In April 2010, HP labs announced that they had practical memristors working at 1 ns (~1 GHz) switching times and 3 nm by 3 nm sizes, which bodes well for the future of the technology. At these densities it could easily rival the current sub-25 nm flash memory technology.

Silicon dioxide memristor
It seems that memristance has been registered in nanoscale thin films realized with silicon dioxide since 60s
.

However, hysteretic conductance in silicon has been associated to memristive effect
in 2009 only,
while Tony Kenyon and his group has clearly demonstrated that the resistive switching in silicon oxide thin films is due to silicon nanoinclusions in highly nonstoichiometric suboxide phases
.

Polymeric memristor
In 2004, Krieger and Spitzer described dynamic doping of polymer and inorganic dielectric-like materials that improved the switching characteristics and retention required to create functioning nonvolatile memory cells. They used a passive layer between electrode and active thin films, which enhanced the extraction of ions from the electrode. It is possible to use fast ion conductor as this passive layer, which allows a significant reduction of the ionic extraction field.

In July 2008, Erokhin and Fontana claimed to have developed a polymeric memristor before the more recently announced titanium dioxide memristor.

In 2010, Alibart, Gamrat, Vuillaume et al. introduced a new hybrid organic/nanoparticle device (the NOMFET : Nanoparticle Organic Memory Field Effect Transistor), which behaves as a memristor and which exhibits the main behavior of a biological spiking synapse. This device, also called a synapstor (synapse transistor), was used to demonstrate a neuro-inspired circuit (associative memory showing a pavlovian learning).

In 2012, Crupi, Pradhan and Tozer described a proof of concept design to create neural synaptic memory circuits using organic ion-based memristors. The synapse circuit demonstrated long-term potentiation for learning as well as inactivity based forgetting. Using a grid of circuits, a pattern of light was stored and later recalled. This mimics the behavior of the V1 neurons in the primary visual cortex that act as spatiotemporal filters that process visual signals such as edges and moving lines.

In 2012, Erokhin and co-authors have demonstrated a stochastic three-dimensional matrix with capabilities for learning and adapting based on polymeric memristor.

Layered memristor
In 2014, Bessonov et al. reported a flexible memristive device comprising a MoOx/MoS2 heterostructure sandwiched between silver electrodes on a plastic foil. The fabrication method is entirely based on printing and solution-processing technologies using two-dimensional layered transition metal dichalcogenides (TMDs). The memristors are mechanically flexible, optically transparent and produced at low cost. The memristive behaviour of switches was found to be accompanied by a prominent memcapacitive effect. High switching performance, demonstrated synaptic plasticity and sustainability to mechanical deformations promise to emulate the appealing characteristics of biological neural systems in novel computing technologies.

Atomristor
Atomristor is defined as the electrical devices showing memristive behavior in atomically thin nanomaterials or atomic sheets. In 2018, Ge and Wu et al. in the Akinwande group at the University of Texas, first reported a universal memristive effect in single-layer TMD (MX2, M = Mo, W; and X = S, Se) atomic sheets based on vertical metal-insulator-metal (MIM) device structure. The work was later extended to monolayer hexagonal boron nitride, which is the thinnest memory material of around 0.33 nm. These atomristors offer forming-free switching and both unipolar and bipolar operation. The switching behavior is found in single-crystalline and poly-crystalline films, with various conducting electrodes (gold, silver and graphene). Atomically thin TMD sheets are prepared via CVD/MOCVD, enabling low-cost fabrication. Afterwards, taking advantage of the low "on" resistance and large on/off ratio, a high-performance zero-power RF switch is proved based on MoS2 or h-BN atomristors, indicating a new application of memristors for 5G, 6G and THz communication and connectivity systems. In 2020, atomistic understanding of the conductive virtual point mechanism was elucidated in an article in nature nanotechnology.

Ferroelectric memristor

The ferroelectric memristor is based on a thin ferroelectric barrier sandwiched between two metallic electrodes. Switching the polarization of the ferroelectric material by applying a positive or negative voltage across the junction can lead to a two order of magnitude resistance variation:  (an effect called Tunnel Electro-Resistance). In general, the polarization does not switch abruptly. The reversal occurs gradually through the nucleation and growth of ferroelectric domains with opposite polarization. During this process, the resistance is neither RON or ROFF, but in between. When the voltage is cycled, the ferroelectric domain configuration evolves, allowing a fine tuning of the resistance value. The ferroelectric memristor's main advantages are that ferroelectric domain dynamics can be tuned, offering a way to engineer the memristor response, and that the resistance variations are due to purely electronic phenomena, aiding device reliability, as no deep change to the material structure is involved.

Carbon nanotube memristor
In 2013, Ageev, Blinov et al. reported observing memristor effect in structure based on vertically aligned carbon nanotubes studying bundles of CNT by scanning tunneling microscope.

Later it was found that CNT memristive switching is observed when a nanotube has a non-uniform elastic strain ΔL0. It was shown that the memristive switching mechanism of strained СNT is based on the formation and subsequent redistribution of non-uniform elastic strain and piezoelectric field Edef in the nanotube under the influence of an external electric field E(x,t).

Biomolecular memristor
Biomaterials have been evaluated for use in artificial synapses and have shown potential for application in neuromorphic systems. In particular, the feasibility of using a collagen‐based biomemristor as an artificial synaptic device has been investigated, whereas a synaptic device based on lignin demonstrated rising or lowering current with consecutive voltage sweeps depending on the sign of the voltage furthermore a natural silk fibroin demonstrated memristive properties; spin-memristive systems based on biomolecules are also being studied.

In 2012, Sandro Carrara and co-authors have proposed the first biomolecular memristor with aims to realize highly sensitive biosensors. Since then, several memristive sensors have been demonstrated.

Spin memristive systems

Spintronic memristor
Chen and Wang, researchers at disk-drive manufacturer Seagate Technology described three examples of possible magnetic memristors. In one device resistance occurs when the spin of electrons in one section of the device points in a different direction from those in another section, creating a "domain wall", a boundary between the two sections. Electrons flowing into the device have a certain spin, which alters the device's magnetization state. Changing the magnetization, in turn, moves the domain wall and changes the resistance. The work's significance led to an interview by IEEE Spectrum. A first experimental proof of the spintronic memristor based on domain wall motion by spin currents in a magnetic tunnel junction was given in 2011.

Memristance in a magnetic tunnel junction
The magnetic tunnel junction has been proposed to act as a memristor through several potentially complementary mechanisms, both extrinsic (redox reactions, charge trapping/detrapping and electromigration within the barrier) and intrinsic (spin-transfer torque).

Extrinsic mechanism

Based on research performed between 1999 and 2003, Bowen et al. published experiments in 2006 on a magnetic tunnel junction (MTJ) endowed with bi-stable spin-dependent states(resistive switching).
The MTJ consists in a SrTiO3 (STO) tunnel barrier that separates half-metallic oxide LSMO and ferromagnetic metal CoCr electrodes. The MTJ's usual two device resistance states, characterized by a parallel or antiparallel alignment of electrode magnetization, are altered by applying an electric field. When the electric field is applied from the CoCr to the LSMO electrode, the tunnel magnetoresistance (TMR) ratio is positive. When the direction of electric field is reversed, the TMR is negative. In both cases, large amplitudes of TMR on the order of 30% are found. Since a fully spin-polarized current flows from the half-metallic LSMO electrode, within the Julliere model, this sign change suggests a sign change in the effective spin polarization of the STO/CoCr interface. The origin to this multistate effect lies with the observed migration of Cr into the barrier and its state of oxidation. The sign change of TMR can originate from modifications to the STO/CoCr interface density of states, as well as from changes to the tunneling landscape at the STO/CoCr interface induced by CrOx redox reactions.

Reports on MgO-based memristive switching within MgO-based MTJs appeared starting in 2008
and 2009. While the drift of oxygen vacancies within the insulating MgO layer has been proposed to describe the observed memristive effects, another explanation could be charge trapping/detrapping on the localized states of oxygen vacancies
and its impact on spintronics. This highlights the importance of understanding what role oxygen vacancies play in the memristive operation of devices that deploy complex oxides with an intrinsic property such as ferroelectricity or multiferroicity.

Intrinsic mechanism

The magnetization state of a MTJ can be controlled by Spin-transfer torque, and can thus, through this intrinsic physical mechanism, exhibit memristive behavior. This spin torque is induced by current flowing through the junction, and leads to an efficient means of achieving a MRAM. However, the length of time the current flows through the junction determines the amount of current needed, i.e., charge is the key variable.

The combination of intrinsic (spin-transfer torque) and extrinsic (resistive switching) mechanisms naturally leads to a second-order memristive system described by the state vector x = (x1,x2), where x1 describes the magnetic state of the electrodes and x2 denotes the resistive state of the MgO barrier. In this case the change of x1 is current-controlled (spin torque is due to a high current density) whereas the change of x2 is voltage-controlled (the drift of oxygen vacancies is due to high electric fields). The presence of both effects in a memristive magnetic tunnel junction led to the idea of a nanoscopic synapse-neuron system.

Spin memristive system
A fundamentally different mechanism for memristive behavior has been proposed by Pershin and Di Ventra. The authors show that certain types of semiconductor spintronic structures belong to a broad class of memristive systems as defined by Chua and Kang. The mechanism of memristive behavior in such structures is based entirely on the electron spin degree of freedom which allows for a more convenient control than the ionic transport in nanostructures. When an external control parameter (such as voltage) is changed, the adjustment of electron spin polarization is delayed because of the diffusion and relaxation processes causing hysteresis. This result was anticipated in the study of spin extraction at semiconductor/ferromagnet interfaces, but was not described in terms of memristive behavior. On a short time scale, these structures behave almost as an ideal memristor. This result broadens the possible range of applications of semiconductor spintronics and makes a step forward in future practical applications.

Self-directed channel memristor
In 2017, Kris Campbell formally introduced the self-directed channel (SDC) memristor.
The SDC device is the first memristive device available commercially to researchers, students and electronics enthusiast worldwide.
The SDC device is operational immediately after fabrication. In the Ge2Se3 active layer, Ge-Ge homopolar bonds are found and switching occurs. The three layers consisting of Ge2Se3/Ag/Ge2Se3, directly below the top tungsten electrode, mix together during deposition and jointly form the silver-source layer. A layer of SnSe is between these two layers ensuring that the silver-source layer is not in direct contact with the active layer. Since silver does not migrate into the active layer at high temperatures, and the active layer maintains a high glass transition temperature of about , the device has significantly higher processing and operating temperatures at  and at least , respectively. These processing and operating temperatures are higher than most ion-conducting chalcogenide device types, including the S-based glasses (e.g. GeS) that need to be photodoped or thermally annealed. These factors allow the SDC device to operate over a wide range of temperatures, including long-term continuous operation at .

Potential applications
Memristors remain a laboratory curiosity, as yet made in insufficient numbers to gain any commercial applications. Despite this lack of mass availability, according to Allied Market Research the memristor market was worth $3.2 million in 2015 and was at the time projected to be worth $79.0 million by 2022. In fact, it was worth $190.0 million in 2022.

A potential application of memristors is in analog memories for superconducting quantum computers.

Memristors can potentially be fashioned into non-volatile solid-state memory, which could allow greater data density than hard drives with access times similar to DRAM, replacing both components. HP prototyped a crossbar latch memory that can fit 100 gigabits in a square centimeter, and proposed a scalable 3D design (consisting of up to 1000 layers or 1 petabit per cm3). In May 2008 HP reported that its device reaches currently about one-tenth the speed of DRAM. The devices' resistance would be read with alternating current so that the stored value would not be affected. In May 2012, it was reported that the access time had been improved to 90 nanoseconds, which is nearly one hundred times faster than the contemporaneous Flash memory. At the same time, the energy consumption was just one percent of that consumed by Flash memory.

Memristor have applications in programmable logic signal processing, Super-resolution imaging physical neural networks, control systems, reconfigurable computing, in-memory computing, brain–computer interfaces and RFID. Memristive devices are potentially used for stateful logic implication, allowing a replacement for CMOS-based logic computation Several early works have been reported in this direction.

In 2009, a simple electronic circuit consisting of an LC network and a memristor was used to model experiments on adaptive behavior of unicellular organisms. It was shown that subjected to a train of periodic pulses, the circuit learns and anticipates the next pulse similar to the behavior of slime molds Physarum polycephalum where the viscosity of channels in the cytoplasm responds to periodic environment changes. Applications of such circuits may include, e.g., pattern recognition. The DARPA SyNAPSE project funded HP Labs, in collaboration with the Boston University Neuromorphics Lab, has been developing neuromorphic architectures which may be based on memristive systems. In 2010, Versace and Chandler described the MoNETA (Modular Neural Exploring Traveling Agent) model. MoNETA is the first large-scale neural network model to implement whole-brain circuits to power a virtual and robotic agent using memristive hardware. Application of the memristor crossbar structure in the construction of an analog soft computing system was demonstrated by Merrikh-Bayat and Shouraki. In 2011, they showed how memristor crossbars can be combined with fuzzy logic to create an analog memristive neuro-fuzzy computing system with fuzzy input and output terminals. Learning is based on the creation of fuzzy relations inspired from Hebbian learning rule.

In 2013 Leon Chua published a tutorial underlining the broad span of complex phenomena and applications that memristors span and how they can be used as non-volatile analog memories and can mimic classic habituation and learning phenomena.

Derivative devices

Memistor and memtransistor
The memistor and memtransistor are transistor based devices which include memristor function.

Memcapacitors and meminductors
In 2009, Di Ventra, Pershin, and Chua extended the notion of memristive systems to capacitive and inductive elements in the form of memcapacitors and meminductors, whose properties depend on the state and history of the system, further extended in 2013 by Di Ventra and Pershin.

Memfractance and memfractor, 2nd- and 3rd-order memristor, memcapacitor and meminductor
In September 2014, Mohamed-Salah Abdelouahab, Rene Lozi, and Leon Chua published a general theory of 1st-, 2nd-, 3rd-, and nth-order memristive elements using fractional derivatives.

History

Precursors
Sir Humphry Davy is said by some to have performed the first experiments which can be explained by memristor effects as long ago as 1808. However the first device of a related nature to be constructed was the memistor (i.e. memory resistor), a term coined in 1960 by Bernard Widrow to describe a circuit element of an early artificial neural network called ADALINE. A few years later, in 1968, Argall published an article showing the resistance switching effects of TiO2 which was later claimed by researchers from Hewlett Packard to be evidence of a memristor.

Theoretical description
Leon Chua postulated his new two-terminal circuit element in 1971. It was characterized by a relationship between charge and flux linkage as a fourth fundamental circuit element. Five years later he and his student Sung Mo Kang generalized the theory of memristors and memristive systems including a property of zero crossing in the Lissajous curve characterizing current vs. voltage behavior.

Twenty-first century
On May 1, 2008, Strukov, Snider, Stewart, and Williams published an article in Nature identifying a link between the two-terminal resistance switching behavior found in nanoscale systems and memristors.

On 23 January 2009, Di Ventra, Pershin, and Chua extended the notion of memristive systems to capacitive and inductive elements, namely capacitors and inductors, whose properties depend on the state and history of the system.

In July 2014, the MeMOSat/LabOSat group (composed of researchers from Universidad Nacional de General San Martín (Argentina), INTI, CNEA, and CONICET) put memory devices into a Low Earth orbit. Since then, seven missions with different devices are performing experiments in low orbits, onboard Satellogic's Ñu-Sat satellites.

On 7 July 2015, Knowm Inc announced Self Directed Channel (SDC) memristors commercially.
These devices remain available in small numbers.

On 13 July 2018, MemSat (Memristor Satellite) was launched to fly a memristor evaluation payload.

In 2021, Jennifer Rupp and Martin Bazant of MIT started a "Lithionics" research programme to investigate applications of lithium beyond their use in battery electrodes, including lithium oxide-based memristors in neuromorphic computing.

In the September 2023 issue of Science Magazine, Chinese scientists Wenbin Zhang et al. described the development and testing of a memristor-based integrated circuit, designed to dramatically increase the speed and efficiency of Machine Learning and Artificial Intelligence tasks, optimized for Edge Computing applications.

See also

 3D XPoint
 Electrical element
 Hybrid Memory Cube
 List of emerging technologies
 Neuromorphic engineering
 Trancitor

References

Further reading

External links

 Interactive database of memristor papers (2013)

 "Leon Chua: A bulb versus Google go player" - (in Polish) an interview with Leon Chua, the creator of memristor
 "Leon Chua: A bulb versus Google go player" - (in English) an interview with Leon Chua, the creator of memristor

Electrical components
Emerging technologies
American inventions
Electronic circuits in computer storage
Experimental electrical components

Memristor


Jack Parr (March 13, 1936 – January 4, 2015) was an American professional basketball player.  Parr was born in Louisville, Kentucky.  He played college basketball at Kansas State University.  Kansas State retired his jersey, and his number 33 is hanging from the rafters.  He was drafted by the Cincinnati Royals in the 10th round of the 1958 NBA draft.  He played 66 games for the Royals in 1958–1959, averaging 4.0 points per game.

Jack Parr was not what you would call a picture player early in his career, but he was endowed with an intensity and inner drive that spearheaded him to All-America stature. Rugged and strong, he would sweep the boards. Parr's assortment of shots included a hook and a soft "face the basket" jumper. Against Kansas in Lawrence in 1958, Parr made perhaps his greatest defensive play. With the final seconds ticking away, Kansas went to Wilt Chamberlain under the basket for an assumed easy lay-in. Parr went straight up and batted the ball away, enabling K-State to take a thrilling 79–75 victory.

Three times Parr gained all-league honors. Twice he helped the Wildcats to conference championships and NCAA play and twice received All-America recognition. He still holds KSU's single-season rebounding record and is second on the career charts. He ranks 10th among the all-time Wildcat scoring leaders with 1,184 points. Parr played one season professionally with the Cincinnati Royals before turning to private business and becoming a Big Eight basketball official. He died in January 2015, aged 78, at his home in Lindsborg, Kansas.

References

1936 births
2015 deaths
All-American college men's basketball players
American men's basketball players
Basketball players from Louisville, Kentucky
Centers (basketball)
Cincinnati Royals draft picks
Cincinnati Royals players
Kansas State Wildcats men's basketball players
People from Lindsborg, Kansas

Jack Parr


Chaudhary Devi Lal (born Devi Dayal; 25 September 1914 — 6 April 2001) was an Indian politician. He served as 6th Deputy Prime Minister of India from 1989 to 1991 in the management of V. P. Singh and Chandra Shekhar. He is popularly known as Tau (uncle). Devi Lal came out as farmer leader from the state of Haryana. He served as the Chief Minister of Haryana first in 1977-79 and then in 1987-89.

Personal life
Chaudhary Devi Lal was born in Teja Khera village of Sirsa district in present-day Haryana to Shunga Devi and Lekh Ram Sihag. Lekh Ram was a Jat of Chautala village. He owned 2750 bighas of land. Lal received education up to middle-school. His son, Om Prakash Chautala has also served as Haryana's chief minister four times.

In 1928 at the age of 16, Devi Lal participated in independence struggle event by Lala Lajpat Rai. He was a student of "Dev Samaj Public High School Moga" in Moga during his 10th class. At that time, he was arrested at Congress office in 1930. He quit studies and joined freedom movement. He also took wrestling lesson at an Akhara in Badal village of Punjab. He was first elected MLA in 1952.

Lal comes from a productive political period of time with his powerful family rulers of Haryana. His older brother Sahib Ram Sihag was the first politician from the family. Sahib Ram Sihag became Congress MLA from Hisar in 1938 and 1947. Lal had four sons - Partap Singh, Om Prakash Chautala, Ranjit Singh and Jagdish Chander. His eldest son, Partap Singh, was an MLA from Indian National Lok Dal in the 1960s.

Independence movement
Lal was a follower of Mahatma Gandhi. He was involved in the struggle for India's independence from the British Raj. Both he and his elder brother, Sahib Ram, left their studies unfinished to take part in the freedom movement.

For this, he was sentenced to one year rigorous imprisonment and sent to Hissar jail on 8 October 1930. He took part in the movement of 1932. He was then kept in Sadar Delhi Thana (Jail). In 1938 he was selected delegate of All-India Congress Committee. In March 1938, his elder brother was elected a Member of the Legislative Assembly in a by-election on the Congress party ticket. In January 1940, Sahib Ram courted arrest as a satyagrahi in the presence of Lal and over ten thousand people. He was fined Rs 100 and sentenced to 9 months imprisonment.

Lal was arrested again on 5 October 1942. He then kept in jail for two years for taking part in the 1942 Quit India movement. He was released from prison in October 1943. He negotiated parole for his elder brother. In August 1944, Chhotu Ram, the then Revenue Minister, visited Chautala village. He, along with Lajpat Rai Alakhpura, made efforts to woo both Sahib Ram and Lal to desert Congress and join the Unionist Party. But both workers, being dedicated freedom fighters, refused to leave the Congress Party.

Post independence

Pre-1960: Punjab Assembly politics
After independence, Lal emerged as a popular farmer leader in the 1950s and started a farmers' movement, for which he was arrested along with his 500 workers. After some time, then chief minister, Gopi Chand Bhargava, made an agreement and the Muzzara Act was amended. He was elected a member of the Punjab Assembly in 1952 and President of the Punjab Congress in 1956. In 1958, he was elected from Sirsa.

Pre-1980: Haryana Assembly politics
He played an active and clear role in the (creation and construction/ group of objects) of Haryana as a separate state. In 1971, he left Congress. In 1972 Vidhan Sabha elections, he argued over unsuccessfully against the two Congress heavyweights. One was Bansi Lal in Tosham (Vidhan Sabha seat) and another was Bhajan Lal in Adampur seat. In 1974, he successfully contested in the Rori constituency. In 1975, Indira Gandhi declared the Emergency. Lal along with all opposition leaders were jailed for 19 months. In 1977, the emergency ended and general elections were held. He was elected on the Janata Party ticket from Bhattu Kalan. He then became the Chief Minister of Haryana. As the chief minister of Haryana he made several decisions benefiting farmers and rural people.

Post-1980: national and state politics
He remained a Member of Parliament from 1980 to 1982. He was a member of State assembly between 1982 and 1987. He formed Lok Dal. He started Nyaya Yuddh (en. battle for justice), under the banner of Haryana Sangharsh Samiti. In the 1987 state elections, the alliance led by Lal won a record victory winning 85 seats in the 90 member house. Congress won the other five seats. Lal became the chief minister of Haryana for the second time. In the 1989 parliamentary election, he was simultaneously elected, both from Sikar, Rajasthan and Rohtak, Haryana.

He went on to become deputy prime minister of the country from 1989 to 1991.

He was elected to Rajya Sabha in August 1998. Later, his son Om Prakash Chautala also became the chief minister of Haryana.

Death and legacy
His popularity among farmers and rural people earned him the title of 'Tau' (Elder Uncle). Lal died on 6 April 2001 at the age of 85. He was cremated at Sangarsh Sthal on the banks of the river Yamuna in New Delhi. "Kisan Ghat" is the samadhi of another popular leader of the farmers, Charan Singh, the fifth Prime Minister of India.

References

Other websites

Official website of Indian National Lok Dal

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1915 births
2001 deaths
Indian Deputy Prime Ministers
Politicians from Haryana
Indian National Congress politicians

Devi Lal


Dhaka National Medical College is a private medical college in Dhaka, Bangladesh. It was founded in 1925 as the Dhaka National Medical Institute which was then situated near Bahadur Shah Park.

Following the 1972 independence of Bangladesh, the educational function of the Dhaka National Medical Institute became moribund, although the associated hospital remained active. A medical college capability was restored with the creation of the Dhaka National Medical College. It was inaugurated on 15 October 1994 and opened to its first students. It has a 850-bed multidisciplinary hospital complex adjacent to the academic building. The college offers a five-year course of study, approved by the Bangladesh Medical and Dental Council (BMDC), leading to a Bachelor of Medicine & Bachelor of Surgery (MBBS) and Bachelor of Dental Surgery (BDS) degree from Dhaka University. After passing the final professional examination, there is a compulsory one-year internship. Dhaka national medical college offers MBBS course to students from India as well.

References

External links
official website

Old Dhaka
Universities and colleges in Dhaka
Educational institutions established in 1994
Medical colleges in Bangladesh
1994 establishments in Bangladesh

Dhaka National Medical College


These are the results of the rhythmic team all-around competition, one of the two events of the rhythmic gymnastics discipline contested at the 1996 Summer Olympics. These games marked the beginning of the olympic career of Almudena Cid from Spain who went to compete in another three more olympic games.

Qualification

In the first round there were thirty seven competitors. From that thirty seven the highest scoring twenty would go on to the next round. From that twenty the highest scoring ten would go on to the final round.

Final

References

External links
 http://www.gymnasticsresults.com/olympics/og1996rg.html

Women's rhythmic individual all-around
1996
1996 in women's gymnastics
Women's events at the 1996 Summer Olympics

Gymnastics at the 1996 Summer Olympics – Women's rhythmic individual all-around


Per Axel Ankre (born 4 August 1948) is a retired Norwegian handball player who competed in the 1972 Summer Olympics.

He was born in Oslo, has a  Master of Science in Economics and Business Administration and represented the club SK Arild. In 1972 he was part of the Norwegian team which finished ninth in the Olympic tournament. He played all five matches and scored ten goals. After the olympics in 1972 he played professional for Atletico de Madrid until 1975. From 1975 till 1983 he worked with Scandinavian Bulk Traders AS.  Scanfiber AS in 1983, a trading company within the forestry industry. Scanfiber AS is importing wood rawmaterial for the Pulp and paper industry in Europe from overseas sources including trading of pulpwood inside Europe. Per Axel Ankre is married to Maria Katharina Schenk and have 2 sons from a previous marriage.

References

1948 births
Living people
Norwegian male handball players
Olympic handball players for Norway
Handball players at the 1972 Summer Olympics
Handball players from Oslo

Per Ankre


Pierre Dupong (; 1 November 1885 – 23 December 1953) was a Luxembourgish politician and statesman. He was the 16th Prime Minister of Luxembourg, serving for sixteen years, from 5 November 1937 until his death, on 23 December 1953, and was also responsible at different times for the ministries of finance, the army, agriculture, labour and social matters. He founded the Christian Social People's Party (CSV) as the main conservative party after the Second World War, having been a founding member of the Party of the Right (PD) in 1914.

He was one of the founding members in 1914 of the Party of the Right, and was elected to the legislature in 1915. He served as Director-General for Finance from 1926 to 1937 and as Minister for Social Security and Labor in 1936 and 1937.

His first government was the Dupong-Krier Ministry (1937–1940). Between 1940 and 1944, Dupong then led the Luxembourgish government-in-exile, after Luxembourg had been occupied by Nazi Germany. He fled the country along with the rest of the Luxembourg government and the Grand Ducal Family of Luxembourg, settling in France. Once in Bordeaux, they were granted transit visas from the Portuguese consul Aristides de Sousa Mendes, in June 1940. Pierre Dupong, along with his wife Sophie, and their children Marie Thérèse, Lambert Henri, Henriette and Jean, followed the Grand Ducal family through Coimbra and Lisbon, settling at Praia das Maçãs after the Grand Ducal family had moved to Cascais. By August, the entire entourage had moved to Monte Estoril. The Dupong couple stayed at Chalet Posser de Andrade until 26 September 1940, while their children remained there until 2 October 1940. On 26 September, the couple boarded the S.S. Excalibur headed for New York City, arriving on 5 October 1940. Georgette and Betty Bech, the wife and daughter of Joseph Bech, the Foreign Minister of the Luxembourg government-in-exile, traveled with them.

Between 1940 and 1944, he led the government in exile in Montreal.

He then presided over the Liberation Government, the National Union Government, and the Dupong-Schaus and the Dupong-Bodson governments. He is also notable for sending Luxembourgish soldiers in the UN mission during the Korean War, as part of the Belgian United Nations Command.

He was the father of Jean Dupong, who became a minister and CSV deputy himself.

References

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Ministers for Finances of Luxembourg
Prime Ministers of Luxembourg
Ministers for Defence of Luxembourg
Party of the Right (Luxembourg) politicians
Christian Social People's Party politicians
Luxembourgian people of World War II
World War II political leaders
1885 births
1953 deaths
People from Steinsel
Alumni of the Athénée de Luxembourg

Pierre Dupong


Archaeothyris is an extinct genus of ophiacodontid synapsid that lived during the Late Carboniferous and is known from Nova Scotia. Dated to 306 million years ago, Archaeothyris, along with a more poorly known synapsid called Echinerpeton, are the oldest undisputed synapsids known. The name means ancient window (Greek), and refers to the opening in the skull, the temporal fenestra, which indicates this is an early synapsid. Protoclepsydrops also from Nova Scotia is slightly older but is known by very fragmentary materials.

Description

Archaeothyris was more advanced than the early sauropsids, having strong jaws that could open wider than those of the early reptiles. While its sharp teeth were all of the same size & shape, it did possess a pair of enlarged canines, suggesting that it was a carnivore.

Archaeothyris' legs were articulated laterally at its pelvis and shoulders, which gave it a sprawling stance. The first toe is smaller than the second.

Classification
Archaeothyris belonged to the family Ophiacodontidae, a group of early pelycosaurs that evolved early in the Late Carboniferous. It was one of the earliest and most basal synapsids (the group which includes mammals).

Below is a cladogram modified from the analysis of Benson (2012):

Discovery and paleoecology
Fossils of Archaeothyris were first described in 1972 from the Joggins fossil cliffs, the same locality in which the early reptiles Hylonomus and Petrolacosaurus (both of which resemble Archaeothyris) were found.

Archaeothyris lived in what is now Nova Scotia, about 306 million years ago in the Carboniferous Period (Pennsylvanian).
Nova Scotia at this time was a swamp, similar to today's Everglades in Florida. The "trees" (actually giant club mosses) were very tall, some, such as Lepidodendron, up to  tall. Archaeothyris and the other early amniotes lived in the moist vegetation on the forest ground, together with the more terrestrially adapted labyrinthodont amphibians.

See also

 List of pelycosaurs
 Evolution of mammals
 List of transitional fossils
 Carboniferous tetrapods

References

Further reading

External links
 Transitional Vertebrate Fossils - includes description of important transitional genera from reptile to mammal (includes a little information about Archaeothyris)

Ophiacodontids
Prehistoric synapsid genera
Carboniferous synapsids
Carboniferous synapsids of North America
Transitional fossils
Taxa named by Robert R. Reisz
Fossil taxa described in 1972
Paleozoic life of Nova Scotia

Archaeothyris


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References

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2008 songs
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Love Story (song)