izzako/sundanese-pixelgpt huggingface dataset:
This can be generalized to polynomial interpolation, which is sometimes more accurate but suffers from Runge's phenomenon
Other interpolation methods use localized functions like splines or wavelets
Extrapolation is very similar to interpolation, except that now we want to find the value of the unknown function at a point which is outside the given points
Regression is also similar, but it takes into account that the data is imprecise
Given some points, and a méasurement of the value of some function at these points (with an error), we want to determine the unknown function
The least squares-method is one popular way to achieve this
Solving equations and systems of equations
Another fundamental problem is computing the solution of some given equation
Two cases are commonly distinguished, depending on whether the equation is linéar or not
For instance, the equation formula_6 is linéar while formula_7 is not
Much effort has been put in the development of methods for solving systems of linéar equations
Standard direct methods i.e
methods that use some matrix decomposition are Gaussian elimination, LU decomposition, Cholesky decomposition for symmetric (or hermitian) and positive-definite matrix, and QR decomposition for non-square matrices
Iterative methods such as the Jacobi method, Gauss-Seidel method, successive over-relaxation and conjugate gradient method are usually preferred for large systems
Root-finding algorithms are used to solve nonlinéar equations (they are so named since a root of a function is an argument for which the function yields zero)
If the function is differentiable and the derivative is known, then Newton's method is a popular choice
Linearization is another technique for solving nonlinéar equations
Solving eigenvalue or singular value problems
Several important problems can be phrased in terms of eigenvalue decompositions or singular value decompositions
For instance, the spectral image compression algorithm is based on the singular value decomposition
The corresponding tool in statistics is called principal component analysis
One application is to automatically find the 100 top subjects of discussion on the web, and to then classify éach web page according to which subject it belongs to
Optimization problems ask for the point at which a given function is maximized (or minimized)
Often, the point also has to satisfy some constraints
The field of optimization is further split in several subfields, depending on the form of the objective function and the constraint
For instance, linear programming déals with the case that both the objective function and the constraints are linéar
A famous method in linéar programming is the simplex method
The method of Lagrange multipliers can be used to reduce optimization problems with constraints to unconstrained optimization problems
Numerical integration, in some instances also known as numerical quadrature, asks for the value of a definite integral
Popular methods use one of the Newton-Cotes formulas (like the midpoint rule or Simpson's rule) or Gaussian quadrature
These methods rely on a "divide and conquer" strategy, whereby an integral on a relatively large set is broken down into integrals on smaller sets
In higher dimensions, where these methods become prohibitively expensive in terms of computational effort, one may use Monte Carlo or quasi-Monte Carlo methods (see Monte Carlo integration), or, in modestly large dimensions, the method of sparse grids
"Main articles: Numerical ordinary differential equations, Numerical partial differential equations."
Numerical analysis is also concerned with computing (in an approximate way) the solution of differential equations, both ordinary differential equations and partial differential equations
Partial differential equations are solved by first discretizing the equation, bringing it into a finite-dimensional subspace
This can be done by a finite element method, a finite difference method, or (particularly in engineering) a finite volume method
The théoretical justification of these methods often involves théorems from functional analysis
This reduces the problem to the solution of an algebraic equation
Since the late twentieth century, most algorithms are implemented and run on a computer
The Netlib repository contains various collections of software routines for numerical problems, mostly in Fortran and C. Commercial products implementing many different numerical algorithms include the IMSL and NAG libraries; a free alternative is the GNU Scientific Library
MATLAB is a popular commercial programming language for numerical scientific calculations, but there are commercial alternatives such as S-PLUS and IDL, or semi-free alternative Scilab as well as free and open source alternatives such as FreeMat, GNU Octave (similar to Matlab), IT++ (a C++ library), R (similar to S-PLUS) and certain variants of Python
Performance varies widely: while vector and matrix operations are usually fast, scalar loops vary in speed by more than an order of magnitude
Many computer algebra systems such as Mathematica or Maple (free software systems include SAGE, Maxima, Axiom, and Yacas), can also be used for numerical computations
However, their strength typically lies in symbolic computations
Also, any spreadsheet software can be used to solve simple problems relating to numerical analysis
Dina analisis numeris, quadrature rule mangrupa salah sahiji "pendekatan" definite integral tina function, biasana "dinyatakan" salaku jumlah beurat tina nilai fungsi dina titik husus di jero domain integration
Dina "n"-titikGaussian quadrature rule, dingaranan ieu sanggeus Carl Friedrich Gauss, mangrupa quadrature rule constructed to yield an exact result for polynomials of degree 2"n" − 1, by a suitable choice of the "n" points "x""i" and "n" weights "w""i"
The domain of integration for such a rule is conventionally taken as [-1, 1], so the rule is stated as formula_1 It can be shown (see Press, et al., or Stoer and Bulirsch) that the evaluation points are just the roots of a polynomial belong to a class of orthogonal polynomials
Rules for the basic problem
For the integration problem stated above, the associated polynomials are Legendre polynomials
Some low-order rules for solving the integration problem are listed below
Change of interval for Gaussian quadrature
An integral over ["a", "b"] must be changed into an integral over [-1, 1] before applying the Gaussian quadrature rule
This change of interval can be done in the following way: formula_2 After applying the Gaussian quadrature rule, the following approximation is obtained: formula_3 Other forms of Gaussian quadrature
The integration problem can be expressed in a slightly more general way by introducing a weighting function ω into the integrand, and allowing an interval other than [-1, 1]
That is, the problem is to calculate formula_4 for some choices of "a", "b", and ω
For "a" = -1, "b" = 1, and ω("x") = 1, the problem is the same as that considered above
Other choices léad to other integration rules
Some of these are tabulated below
Equation numbers are given for Abramowitz and Stegun (A&amp;S)
The error of a Gaussian quadrature rule can be stated as follows (théorem 3.6.24 in Stoer and Bulirsch)
For an integrand which has 2"n" continuous derivatives, formula_5 for some ξ in ("a", "b"), where "p""n" is the orthogonal polynomial of order "n"
Stoer and Bulirsch remark that this error estimate is inconvenient in practice, since it may be difficult to estimate the 2"n"'th derivative, and furthermore the actual error may be much less than a bound established by the derivative
Another approach is to use two Gaussian quadrature rules of different orders, and to estimate the error as the difference between the two results
For this purpose, Gauss-Kronrod rules can be useful
If the interval ["a", "b"] is subdivided, the evaluation points of the new subintervals generally do not coincide with the previous evaluation points, and thus the integrand must be evaluated at every point
"Gauss-Kronrod rules" are Gaussian quadrature rules that are modified to maké some of the evaluation points coincide after subdivision
The difference between the results before and after subdivision can be taken as an estimate of the error of approximation, so such an approach can incréase the accuracy achieved for a given number of function evaluations
The algorithms in QUADPACK (see below) are based on Gauss-Kronrod rules
Sacara harti sajarah, watesan bisnis nunjukkeun aktivitas atawa karesep
Kecap ieu hartina beuki ngalegaan jadi (dimimitian dina abad ka-18) sarua jeung "an individual commercial enterprise"
ogé dina harti nu leuwih umum "a nexus of commercial activities"
Péople establish businesses in order to perform economic activities
With some exceptions (such as cooperatives, corporate bodies, non-profit organizations and institutions of government), businesses exist to produce profit
In other words, the owners and operators of a business have as one of their main objectives to receive or generate a financial return for their time, effort and capital
One can classify businesses in many different ways
Service businesses offer intangible products and typically have different, usually smaller, capital requirements than manufacturers
Distributors will have different inventory control needs than a retailer or manufacturer
Most legal jurisdictions specify the forms that a business can take, and a body of commercial law has developed for éach type
Some common types include partnerships, corporations (also called limited liability companies), and sole proprietorships
An industry can consist of a group of related businesses, such as the entertainment industry or the dairy industry
This definition resembles one of the more general méanings of "business", and the terms "business" and "industry" sometimes appéar interchangéable
Thus a fisherman might say either (more colloquially) that he is in the "fishing business" or (somewhat grandiosely) that he works in the "fishing industry"
Similarly, the word "trade" may serve as an equivalent of both "business" and "industry": Victorians might despise those "in trade", and one can still refer to working "in the rag trade", for example
Wikipédia boga leuwih ti 1200 artikel bisnis jeung ékonomi, jadi teu sadayana dibéréndélkeun di dieu
Di dieu didaptarkeun sababaraha cabang bisnis nu utama
Pikeun jejer nu leuwih husus, tempo di subdaptarna
Dina statistik, estimator anu bias nyaéta hiji kaayaan nu mana nilai rata-rata saluhureun atawa sahandapeun nu ditaksir
Aya dua panilaian anu béda, hiji nempo kana kaayaan nu kacida gorengna, panempo séjénna nyaéta kana kaayaan dina waktu hasil nyieunna leuwih kapake sarta leuwih deukeut kana bebeneran tinimbang kana kaayaan "unbiased."
Hal nu goreng
Hiji harti nu disebut sampel bias: Lamun sababara unsur nyaruaan kana sampel nu dipilih tinimbang nu séjén, jeung mibanda nilai nu leuwih luhur atawa leuwih handap tina nu ditaksir, hasilna bakal leuwih luhur atawa leuwih handap tina nu ditaksir
Salah sahiji conto kawentar nu salah waktu nerapkeun sampel bias, kajadian dina poling présidén Amérika taun 1936
"Literary Digest" ngayakeun polling keur ngaramal yén Alfred E. Landon bakal ngéléhkeun Franklin Delano Roosevelt ku 57% lawan 43%
George Gallup, ngagunakeun sampel nu leuwih saeutik (300,000 dibanding 2,000,000), ngaramalkeun Roosevelt bakal meunang, sarta ramalanna bener
Naon nu salah jeung polling "Literary Digest"
Maranéhna ngagunakeun data nu boga telepon jeung mobil keur sampelna
Waktu harita, masih mangrupa barang mewah, mangka sampelna didominasi ku golongan menengah ka luhur
Golongan ieu milih Landon, tapi golongan handap milih Roosevelt
Sabab sampelna bisa nujul kana kakayaan nu milih, mangka hasilna jadi salah
Hal bias ieu ilahar kajadian salaku pasualan milih tinimbang masalah statistical noise: Masalah nu pakait jeung "statistical noise" bisa dikurangan nu cara nambah jumlah sampel, tapi bias sampel teu bisa gampang dileungitkeun
Dina sababaraha hal, meta-analysis bakal milah data nu hadé keur nalungtik kakurangan tina statistical noise, tapi bias meta-analysis bakal jadi biasna sorangan
Hal nu kadangkala hade
Hal bias séjén nu teu kaasup bias dina sampel, tapi kaasup dipaké dina statistik nyaéta nilai rata-rata béda tina nilai nu ditaksir
Anggap nyoba naksir paraméter formula_1 maké panaksir estimator formula_2 (hal ieu sababaraha fungsi tina data nu ditempo)
Mangka bias formula_2 hartikeun formula_4 Hartina, "nilai nu disangka tina taksiran formula_2 dikurangan nilai sabenerna formula_1"
Bisa ogé ditulis formula_7 nu hartina "beda nilai nu disangka antara nilai nu ditaksir jeung nilai sabenerna" (nilai nu disangka formula_1 nyaéta formula_1)
Keur conto, anggap "X1, ..., Xn" nyaéta variabel acak nu mandiri jeung kasebar identik, unggal sebaran normal nu disangka μ jeung varian σ2
Mangka formula_10 jadi "rata-rata sampel", tur formula_11 jadi "varian sampel"
Saterusna "S"2 nyaéta "bias panaksir" σ2 sabab formula_12 Sanajan kitu, panaksir bias ieu, kritéria nu ilahar "kuadrat kasalahan mean", sabenerna leuwih hadé (tapi kacida deukeutna) ti batan panaksir teu-bias tina hasil "n − 1" dina pangbagi nu mana "n" dideukeutan dina ngartikeun "S"2 di luhur
Saterusna akar kuadrat panaksir teu-bias tina populasi varian lain mangrupa panaksir teu-bas tina populasi simpangan baku; keur fungsi non-linier "f" sarta panaksir teu-bias "U" tina paraméter "p", "f"("U") ilaharna lain panaksir teu-bias tina "f"("p")
Dina pasualan nu leuwih ekstrim tina panaksir bias bakal leuwih hadé tinimbang panaksir teu-bias geus ilahar dipaké: Anggap "X" mibanda distribusi Possion nu nilai disangka λ. Ieu diperlukeun keur naksir formula_13 Ngan fungsi tina data nu teu mibanda panaksir teu-bias nyaéta formula_14 Lamun nilai nu ditempo "X" nyaéta 100, mangka panaksir sarua jeung 1, sanajan nilai sabenerna bakal leuwih nujul ka 0, nu tibalik
leuwih nujul ka 0, nu tibalik sacara ekstrim
Jeung lamun "X" nu ditempo jadi 101, mangka taksiran jadi teu jelas: nyaéta -1, sanajan gedéna nu bakal ditaksir kudu positif
(Bias) panaksir maximum-likelihood formula_15 leuwih hadé tinimbang panaksir teu-bias dina kayaan mean kuadrat kasalahan formula_16 leuwih leutik
Bandingkeun panaksir teu-bias MSE formula_17 MSE nyaéta fungsi nilai sabenerna λ
Bias panaksir maximum-likelihood nyaéta: formula_18
Bias panaksir maximum-likelihood bisa mangrupa hal nu penting
Tempo hiji pasualan nu mana lobana tiket "n" dinomeran ti 1 nepi ka "n" disimpen dina kotak sarta terus dicokot hiji sacara acak, méré hiji nilai "X"
Lamun "n" teu dipikanyaho, mangka panaksir maximum-likelihood tina "n" nyaéta "X", ngaliwatan sangkaan "X" ngan "n"/2; ngan bisa dipastikeun yén "n" ngan dina "X" sarta mungkin leuwih
Dina pasualan ieu, panaksir teu-biasa alami nyaéta 2"X"
Hirup mangrupa konsép multiharti tanpa dadaran nu basajan, sabab mindeng dilarapkeun kana rupa-rupa hal
"WordNet" méré opat welas harti pikeun kecap "life", sedengkeun Kamus Wéb Longman méré 35 harti
Artikel ieu ngadadarkeun harti utama dina élmu hirup; tumbu ka harti séjén bisa ditempo di bagian artikel nu patali di handap
Ngahartikeun konsép hirup
Hirup mibanda sababaraha harti dina jihat biologi — Sésa bagian ieu museur ka harti nu ahir — naon nu jadi dasar pikeun nyebutkeun yén hiji éntitas téh hirup (mahluk hirup)
It would be relatively straightforward to offer a practical set of guidelines if one's only concern were life on Earth as we know it (see biosphere), but as soon as one considers questions about life's origins on éarth, or the possibility of extraterrestrial life, or the concept of artificial life, it becomes cléar that the question is fundamentally difficult and comparable in many respects
difficult and comparable in many respects to the problem of defining intelligence
Dina biologi, hiji éntitas dianggap hirup mun némbongkeun sakabéh peta di handap ieu: Other definitions
Other definitions include: Descent with modification: a "useful" characteristic
A useful characteristic upon which to base a definition of life is that of descent with modification: the ability of a life form to produce offspring that are like its parent or parents, but with the possibility of some variation due to chance
Descent with modification is sufficient by itself to allow evolution, assuming that the variations in the offspring allow for differential survival
The study of this form of heritability is called genetics
In all known life forms (assuming prions are not counted as such), the genetic material is primarily DNA or the related molecule, RNA
Another exception might be the software code of certain forms of viruses and programs créated through genetic programming, but whether computer programs can be alive even by this definition is still a matter of some contention
Exceptions to the common definition
Note that many individual organisms are incapable of reproduction and yet are still generally considered to be "alive"; see mules and ants for examples
However, these exceptions can be accounted for by applying the definition of life on the level of entire species or of individual genes
(For example, see "kin selection" for information about one way by which non-reproducing individuals can still enhance the spréad of their genes and the survival of their species.)
Viruses reproduce, flames grow, some software programs mutate and evolve, future software programs will probably evince (even high-order) behavior, machines move, and proto-life, consisting of metabolizing cells without reproduction apparatus, can have existed
Still, some would not call these entities alive
Generally, all five characteristics are required for a population to be considered alive
"Artikel utama: Asal-usul hirup" euweuh modél "baku" pikeun asal-usul hirup, tapi nu kiwari ditampa sacara umum diwangun dumasar papanggihan di handap ieu: There are many different hypotheses regarding the path that might have been taken from simple organic molecules to protocells and metabolism
Many of the possibilities have tended to fall into either "genes-first" or "metabolism-first", a recent trend is the emergence of hybrid modéls that combine aspects of both
The possibility of extraterrestrial life
As of 2004, Earth is the only planet in the universe known by humans to support life
The question of whether life exists elsewhere in the universe remains open, but analyses such as the Drake equation have been used to estimate the probability of such life existing
There have been a number of false alarms of life elsewhere in the universe, but none of these apparent discoveries have so far survived scientific scrutiny
Currently, the closest that scientists have come to finding extraterrestrial life is fossil evidence of possible bacterial life on Mars (via the ALH84001 metéorite)
Séarches for extraterrestrial life are presently focusing on planets and moons believed to possess liquid water, presently or in the past
Recent evidence from the NASA rovers Spirit and Opportunity supports the théory that Mars once had surface water
See Life on Mars for further discussion
Jupiter's moons are also considered good candidates for extraterrestrial life, especially Europa, which seems to possess océans of liquid water
Énzim mangrupa protéin, atawa kompléks protéin, nu ngatalisan réaksi kimiawi dina awak organisme
Na jero sél biologis téh lumangsung loba pisan réaksi kimiawi, nu mun tanpa énzim bakal lambat pisan sahingga moal ngadukung kahirupan
Énzim ngagancangkeun réaksi nepi ka rébuan kali lipet
Énzim ogé hiji hal anu sakuduna aya dina kuantitas anu loba sarta kualitas anu pas dina awak mahluk hirup, henteu kacuali manusa, sangkan awak sok cageur sarta kajaga ti sagala macem serangan panyakit
"Énzim RNA" atawa "ribozim" dijieunna tina RNA, lain protéin
Umumna ribozim ukur ngatalisan "RNA splicing"
Hiji énzim bisa mangrupa protéin badag nu diwangun ku sababaraha ratus asam amino, atawa sababaraha protéin nu polah babarengan salaku hiji unit
Énzim ngandung sisi aktif, sisi beungkeut nu meungkeut substrat nalika réaksi dikatalisan
Unggal bagéan énzim biasana mibanda tujuan/pungsi pangatur atawa struktural
Enzim kisaran ukuranana ngan ukur 62 asam amino (4-oxalocrotonate tautomerase monomer), dugi ka 2.500 (sintétis asam lemak)
Énzim umumna jauh langkung ageung tibatan substratna, sareng ngan ukur sakedik bagian (sakitar 3-4 asam amino) tina sakabéh struktur énzim anu langsung aub dina katalisis, bagian ieu disebat situs katalitik
Di caket situs katalitik aya hiji atanapi langkung situs anu asam amino ngarahkeun orientasi molekul substrat
Kombinasi situs katalitik sareng situs disebut situs aktip
Bagéan sésana tina énzim dianggo pikeun ngajaga orientasi pertahanan sareng dinamika situs aktip Pungsi
Énzim ngatalisan réaksi kimiawi
Peran énzim dina réaksi kimiawi
Énzim bisa ngagabungkeun dua atawa leuwih réaksi sahingga réaksi nu sacara térmodinamis nguntungkeun bisa dipaké pikeun "nyetir" réaksi séjénna nu sacara térmodinamis teu nguntungkeun
salah sahiji conto nu pangilaharna nyaéta énzim nu ngamangpaatkeun défosforilasi ATP pikeun réaksi kimiawi séjén nu teu patali
Laju réaksi dimédiasi énzim
Énzim bisa ningkatkeun laju réaksi ku jalan milih atawa narabas jalur réaksi nu énérgi aktivasina handap, sahingga leuwih gampang kajadian réaksina
Laju réaksi nu dimédiasi énzim sacara lengkep gumantung ka sababaraha faktor
"Diagram réaksi katalitis, nunjukkeun énergi nu dipikabutuh (E) ngalawan waktu (t). "
Substrat (A jeung B) perlu énergi nu badag ("E"1) pikeun ngahontal kaayaan transisi A...B, nu saterusna jadi produk ahir (AB)
Énzimna (E) nyiptakeun "microenvironment" sahingga A jeung B bisa ngahontal kaayaan transisi (A...E...B) kalawan leuwih gampang, ngurangan jumlah énergi nu dipikabutuh ("E"2)
Hasilna, réaksina leuwih gampang sahingga ningkatkeun laju réaksi
Énzim biasana spésifik dina réaksi nu dikatalisanana sarta substrat nu aub dina réaksina
Sipat struktur kompleméntér antara énzim jeung substrat mangrupa hal nu penting dina hal ieu (Gbr
Sababaraha énzim bisa gawé bareng ngawangun hiji susunan husus, nyiptakeun jalur métabolis
Dina hiji jalur métabolis, hiji énzim nyokot produk énzim séjén salaku substrat
Satutasna réaksi katalitis, produkna dibikeun ka énzim séjénna
Produk ahir jalur sarupa kitu kadang jadi inhibitor pikeun salah sahiji énzim-énzim na awal jalur (biasana léngkah kahiji nu teu bisa balik, disebut "committed step"), sahingga ngatur jumlah produk ahir nu dijieun ku jalur éta
Gambar 6: Mékanisme inhibisi eupan-balik nu ilahar
Modél mékanis-kuantum katalisis énzim
Kuliah "Quantum Theory of some Biochemical Reactions" nu didugikeun na Kongrés Biofisis Internasional IV (Moscow, 1972) ku R.R
Dogonadze jeung Z.D
Urushadze ngarumuskeun modél mékanis kuantum munggaran ngeunaan bentuk pangbasajanna katalisis énzim
Taun 1972-1973, hasil gawé M.V
Urushadze, jeung Yu.I
Kharkats ngarumuskeun modél (fisik) mekanis-kuantum katalisis énzim
Karya ieu ngabuktikeun peran transformasi konformasional dina réaksi katalitis
Énzim jeung kaséhatan
Énzim dipikabutuh ku organisme hirup, gangguan na "hiji énzim" ti kira 2.000 nu aya na awak urang bisa ngakibatkeun kasakit parna nu bisa nepi ka tiwasna
Hiji conto kasakit nu disababkeun ku gangguan fungsi hiji énzim nyaéta fénilketonuria (PKU)
Énzim fénilalanin hidroxilase, nu kuduna ngarobah asam amino ésénsil fénilalanin jadi tirosin teu bisa meta, sahingga fénilalanin numpuk nu ngakibatkeun rétardasi méntal
Énzim na awak manusa bisa ogé dipangaruhan ku inhibitor
Aspirin, misalna, nyegah énzim nu ngahasilkeun prostaglandin ("messenger" inflamasi), sahingga suppressing pain and inflammation
Énzim ogé dimangpaatkeun dina produk sapopoé kayaning deterjén, nu nyepetkeun réaksi kimia méré sihan papakéan (misalna, méré sihan noda getih)
Énzim cerna jeung métabolik
Gizi pikeun sato gumantung ka énzim cerna kayaning amilase, tripsin, jeung kimotripsin na ciduh
Peran utamana nyéta pikeun nyerna dahareun sahingga zat gizina sadia pikeun prosés na bagian awak nu mikabutuhna
Golongan énzim séjénna nyaéta énzim métabolik, nu peranna pikeun ngatalisan réaksi kimia dina unggal prosés na jero awak
lolobana sél urang (iwal ti éritrosit), bakal hanaang ku oxigén najan oxigénna ngalayah lamun énzimna, sitokrom oxidase teu meta
Énzim ogé dipikabutuh pikeun kontraksi jeung rélaxasi otot
Mémang nyatana, tanpa dua golongan énzim ieu, kahirupan (cerna jeung métabolik) moal aya
Konvénsi ngaran énzim
Dumasar konvénsi umum, ngaran hiji énzim ngawengku dadaran naon hancana, ditambah ahiran "-ase"
Contona dehidrogénase alkohol jeung polimérase DNA
Kinase mangrupa énzim nu mindahkeun gugus fosfat
International Union of Biochemistry and Molecular Biology (IUBMB) geus ngembangkeun hiji sistim tatangaran pikeun énzim, nyéta nomer EC; unggal énzim digambarkeun ku hiji runtuyan opat angka nu dimimitian ku "EC"
Nomer kahiji sacara lega ngagolongkeun énzim-énzim dumasar mékanismena: Tatangaran nu lengkep bisa disungsi di http://www.chem.qmul.ac.uk/iubmb/enzyme/ Purifikasi
ku sabab énzim mangrupa protéin, purifikasi énzim dimimitian ku purifikasi protéin
Unggal hambalan na prosedur purifikasi diponcorong kaaktifan énzimna
Tina basa Yunani: "in ferment""
Kala géologi: tempo ogé skala waktu géologis
Sebaran Cauchy mangrupa probability distribution nu mibanda probability density function formula_1 di mana "t" nyaéta "parameter lokasi" jeung "s" nyaéta "parameter skala"
Kasus husus lamun "t" = 0 jeung "s" = 1 disebut standar sebaran Cauchy nu mibanda probability density function formula_2 Sebaran Cauchy salawasna dipaké conto keur ngahartikeun sebaran nu teu mibanda mean, varian atawa moments pangluhurkeun, sanajan mode jeung median duanana dihartikeun sarua jeung nol
Lamun "U" jeung "V" mangrupa dua sebaran normal variabel acak bébas nu mibanda nilai ekspektasi 0 jeung varian 1, saterusna rasio "U"/"V" mibanda standar sebaran Cauchy
Lamun "X"1, ..., "X""n" mangrupa variabel random independent, mibanda standar Cauchy, mangka sampel méan ("X"1 + ... + "X""n")/"n" sarua mibanda standar sebaran Cauchy
Ieu conto keur ngabuktikeun yén hipotesa varian terhingga dina central limit theorem teu bisa dileungitkeun (sanajan bisa digantikeun ku nu séjén, dina kasus asumsi lemah)
Keur nempo yén ieu bener, itung fungsi karakteristik formula_3 nu mana formula_4 mangrupa sampel méan
Sebaran Cauchy mangrupa sebaran-t student nu ngan mibanda hiji tingkat kabébasan
Sebaran Cauchy kadangkala disebut sebaran Lorentz
Dina biologi jeung ékologi, organisme hartina mahluk hirup
Asal-usul hirup sarta hubungan antara turunan pentingna mangrupa kontroversi
Dua hambalan nu utama bisa dibédakeun: prokariot jeung eukariot
Prokariot sacara umum dianggap ngawakilan dua karajaan nu béda, nyaéta baktéri jeung Archaea, nu antara masing-masing teu leuwih deukeut batan ka eukariot
Jungkrang antara prokariot jeung eukariot pada nganggap salaku tumbu penting nu pegat dina sajarah évolusionér
Dua organél eukariotik, nyéta mitokondria jeung kloroplas, umumna dianggap diturunkeun ti baktéri éndosimbiotik
Frase "organisme kompléx" ngagambarkeun organisme naon baé nu mibanda sél leuwih ti hiji (multisélular)
Cicirén nu biasana kapanggih di rupa-rupa organisme di antarana: Tapi, hal-hal di luhur teu lumaku salawasna
Loba organisme nu teu bisa usik sacara mandiri, sarta teu ngaréspon sacara langsung ka lingkunganana
Mikroorganisme kayaning baktéri teu bisa ngalaksanakeun réspirasi, tapi malah ngagunakeunjalur kimiawi nu séjénna
Ogé loba organisme nu teu bisa baranahan
Organisasi Biologis Organisasi lingkungan Klasifikasi
Artikel di handap ieu mangrupa titik bubuka pikeun béja ngeunaan klasifikasi organisme: Virus
Virus dianggap lain organisme husus sabab teu mibanda kamampuh baranahan atawa métabolisme nu mandiri
Sabenerna mah pajeulit ieu téh, sabab sababaraha parasit jeung éndosimbiont teu mampuh hirup kalawan mandiri
Najan virus teu miboga énzim jeung molekul nu sakuduna aya na organisme hirup, maranéhna bisa ngagunakeun'mesin génétik' sél inangna
Asal-usulna can kapanggih, tapi aya kamungkinan mangrupa turunan ti inangna
salah sahiji ukuran dasar organisme nyaéya umur hirupna
Sababaraha sato hirupna ngan itungan sapoé, sedengkeun sababaraha tutuwuhan bisa hirup réwuan taun
Aging is important when determining life span of most organisms, bacterium, a virus or even a prion
Karbohidrat (nurutkeun basa "hidrat karbon") nyaéta sanyawa kimiawi nu pungsina salaku perantara biologis primér pikeun neundeun atawa maké énergi; bentuk séjénna ngaliwatan gajih jeung protéin
Karbohidrat nu kaitung kompléks disebut polisakarida
Karbohidrat murni ngandung atom karbon, hidrogén, jeung oksigén; dina nisbah 1:2:1 molar, nu méré rumus umum C"x"H2"x"O"x"
Tapi, loba karbohidrat penting nyimpang ti ieu rumus, kayaning déoksiribosa
Sakapeung sanyawaan nu ngandung unsur séjén ogé diaku salaku karbohidrat, kayaning kitin, nu ngandung nitrogén
Karbohidrat nu pangbasajanna nyaéta monosakarida, nu mangrupa aldehid jeung keton leutik ranté-lempeng nu loba katambah ku gugus hidroksil, biasana hiji di unggal karbon iwal gugus fungsionalnya
Karbohidrat séjén diwangun ku unit-unit monosakarida nu paregat ku hidrolisis
Nu ieu digolongkeun kana disakarida, oligosakarida, atawa polisakarida, gumantung kana jumlah unit monosakarida nu nyusunna
Monosakarida bisa dibagi jadi aldosa, nu mibanda gugus aldehid na atom karbon kahiji, sarta ketosa, nu husus mibanda gugus keton na atom karbon kadua
Bisa ogé dibagi-bagi jadi triosa, tétrosa, péntosa, héksosa, jeung saterusna gumantung jumlah atom karbon nu dipimilikna
Conto gampang, glukosa mangrupa aldohéksosa, fruktosa mangrupa ketohéksosa, sedengkeun ribosa mangrupa aldopéntosa
Satuluyna, ungal atom karbon nu boga gugus hidroksil (iwal nu mimiti jeung panungtung) boga sipat aktif optis, antukna karbohidrat bisa dibédakeun deui sanajan struktur dasarna sarua
Misal, galaktosa mangrupa aldohéksosa, tapi boga sipat nu béda ti glukosa sabab susunan atom-atomna teu sarua
Struktur ranté-lempeng nu digambarkeun di dieu ukur salah sahiji tina bentuk monosakarida nu bisa jadi
Gugus aldehid atawa keton bisa meungkeut gugus gugus hidroksil ti atom karbon nu séjén ngabentuk hémiasétal atawa hémiketal, nu dina kasus ieu aya sasak oksigén antara dua atom karbon, ngabentuk cingcin hétérosiklik
Cingcin nu diwangun ku lima jeung genep atom disebut bentuk furanosa jeung piranosa, nu aya dina kasatimbangan jeung bentuk ranté-lempeng
Kudu ditengetkeun yén bentuk cingcin mibanda hiji deui karbon nu optik aktif batan bentuk ranté-lempeng, sarta ogé mibanda bentuk "alfa" jeung "béta" nu bulak-balik dina kasatimbangan
Ngan, mun aya réaksi karbohidrat jeung alkohol jadi asétal atawa ketal, dua bentuk éta jadi béda
Ieu mangrupa tipe dasar tumbu antara unit-unit monosakarida tina karbohidrat nu leuwih gedé
Disakarida molékulna diwangun ku dua unit monosakarida
Beungkeutan antara dua gula éta ngawujud tina leupasna hiji atom hidrogén (H) ti hiji molekul jeung hiji gugus hidroksil ti nu hiji deui
Disakarida nu paling umum nyaéta sukrosa (gula bodas - dijieun tina hiji glukosa jeung hiji fruktosa), laktosa (gula susu - dijieun tina hiji glukosa jeung hiji galaktosa) sarta maltosa (dijieun tina dua glukosa)
Rumus kimiawi pikeun disakarida ieu nyaéta C12H22O11
Kalawan teges, karbohidrat teu dipikabutuh pikeun gizi manusa sabab protéin bisa dirobah jadi karbohidrat - diet tradisional aya nu ampir enol persén karbohidrat, bari jagjag walagri kalawan sampurna
Ngan, karbohidrat merlukeun cai nu (rélatif) leuwih saeutik pikeun nyerna batan protéin atawa lemak, sarta ogé mangrupa sumber penting énergi
Tempo ogé Biokimia Makromolekul Katabolisme
Aya tilu jalur métabolik katabolisme karbohidrat: Simpenan glikogén
Disimpen pikeun dipaké nalika glukosa teu diserep ku saluran pencernaan
Protéin mangrupa sanyawa organik kompléks nu beurat molékulna gedé sarta diwangun ku asam amino nu disambungkeun ku beungkeut péptida
Protéin ésénsil pikeun struktur jeung pungsi sakabéh sél hirup, ogé virus
Loba protéin nu mangrupa énzim atawa subunit énzim
Protéin séjén maénkeun pungsi struktural atawa mékanis, kayaning nu ngabentuk urat jeung sandi "sitoskeleton"
Protéin ogé mangrupa sumber asupan pikeun organisme nu teu ngahasilkeun énergina sorangan tina cahya panonpoé
Protéin béda jeung karbohidrat utamana tina kandunganana nu loba nitrogén sarta saeutik walirang di sagigireun karbon, oksigén, jeung hidrogén
Protéin mangrupa unsur utama mahluk hirup sarta mangrupa salah sahiji golongan molekul utama nu diulik dina biokimia; munggaran kapanggih ku Jons Jacob Berzelius taun 1838
Protéin mangrupa ranté asam amino nu nilep jadi struktur 3-diménsi nu has
Bentuk nu ngawujud tina tilepan alami protéin disebutna "bentuk asal", nu ditangtukeun ku urutan asam aminona
Biokimiawan ngabédakeun struktur protéin jadi opat: Tambahan pikeun hambalan-hambalan struktur ieu, protéin bisa géséh antaran sababaraha struktur nu sarupa dina ngajalankeun pungsi biologisna
Dina kontéks susunan ulang ieu, struktur térsiér atawa kuarternérna biasa disebut minangka "konformasi", sedengkeun transisi di antarana disebut parobahan konformasi
Struktur primér ngawujud ku beungkeut péptida kovalén, nu dijieun nalika translasi
Struktur térsiér ngawujud ku ayana beungkeut hidrogén, interaksi hidrofobik, interaksi ionik, jeung/atawa beungkeut disulfida
Prosés nalika struktur nu leuwih luhur ngawujud disebutna tilepan protéin ("protein folding") nu mangrupa kosékuénsi tina struktur primér
Najan polipéptida bisa mibanda leuwih ti hiji konformasi nilep nu stabil, unggal konformasi mibanda aktivitas biologis masing-masing, sarta ngan hiji konformasi nu dianggap konformasi aktif atawa asal
Dua tungtung ranté asam amino disebutna terminal karboksi (terminal-C) jeung terminal amino (terminal-N) dumasar ayana gugus bébas na tungtungna
Bang Data Protéin ("The Protein Data Bank", PDB)
Struktur protéin bisa ditangtukeun ku kristalografi sinar-X, résonansi magnetik inti (nucléar magnetic resonance, NMR), jeung difraksi neutron
Struktur protéin nu diungkab ku métode ieu biasana disimpen di Bank Data Protéin nu bisa diaksés kalawan bébas di http://www.rcsb.org
Nepi ka Juni 2004, ampir 25,000 struktur protéin geus disimpen di dinya
Ieu pangkalan data ogé nyimpen struktur asam nukléat kayaning DNA jeung RNA, sarta saeutik data karbohidrat
Protéin milu sacara praktis na unggal fungsi nu dipigawé ku sél, kaasup pangaturan fungsi sélular kayaning transduksi sinyal jeung métabolisme
Pikeun conto, katabolisme protéin merlukeun ukur sababaraha énzim nu diistilahan protéase
Mékanisme pangaturan protéin
Rupa-rupa molekul jeung ion bisa meungkeut sisi spésifik dina protéin
Sisi ieu disebutna sisi pameungkeut nu némbongkeun spésifisitas kimiawi
Partikel nu kabeungkeut disebutna ligan
Kakuatan beungkeutan protéin-ligan mangrupa sipat sisi pameungkeut nu dikenal minangka afinitas
ku sabab protéin milu sacara praktis na unggal fungsi nu dipigawé ku sél, mékanisme pikeun ngatur fungsi ieu gumantung ka kumaha ngatur aktivitas protéin
Pangaturan bisa mangrupa ngatur bentuk atawa kadar protéinna
Sababaraha bentuk pangaturan di antarana: Kabinékaan
Protéin umumna mangrupa molekul badag, aya nu beurat molekularna nepi ka 3,000,000 (protéin otot titin mibanda subunit ranté tunggal 27000 asam amino)
Ranté panjang asam amino kitu nu disebut sacara umum minangka protéin, nu pondok mah biasa disebut "polipéptida," "péptida", atawa "oligopéptida" (jarang kasebut)
Watesan pangbédana teu tangtu, najan polipéptida leutik kamungkinanana pikeun mibanda struktur tersiér sarta loba nu lumaku sarupaning hormon (saperti insulin) batan minangka énzim atawa unsur struktural
Sacara umum protéin digolongkeun kana serat (filaméntos) leyur atawa nu patali-mémbran (tempo protéin membran integral)
Ampir sakabéh katalis biologis nu dipikawanoh minangka énzim mangrupa protéin (sababaraha untuyan RNA dina ahir abad ka-20 geus ditunjukkeun mibanda sipat katalitik ogé)
Panukeur ("exchanger") sarta kanal ion patali-membran nu mindahkeun substratna ti hiji tempat ka nu séjénna tapi teu dirobah; reséptor, nu teu ngarobah substratna tapi ukur ngagiserkeun bentuk nalika meungkeut; sarta antibodi, nu katémbong taya gawé lian ti meungkeut, sakabéhna mangrupa protéin ogé
Bahan serat nu nyusun sitoskeleton sél sarta lolobana struktur sato ogé mangrupa protéin: mikrotubul, aktin, filamén panengah, kolagén, sarta keratin mangrupa bagéan ti kulit, rambut, jeung "cartilage"
GOlongan séjén protéin motor kayaning myosin, kinesin, jeung dynein
Otot sabagéan badagna diwangun ku protéin myosin jeung actin
Protéin mah pilihan dina nangtukeun ayana di mana téh, ukur bisa kapanggih dina kaayaan aktif atawa bentuk asal dina rentang pH nu heureut sarta dina kaayaan leyuran nu kadar éléktrolitna saeutik, ogé moal kapanggih dina cai sulingan
Protéin nu leungiteun bentuk asalna disebut "denatured"
Protéin kitu umumna teu mibanda struktur sekundér iwal koil acak
Protéin na bentuk asalna mindeng ogé disebut minangka nilep, "folded"
salah sahiji papanggihan abad ka-20 nu luar biasa nyaéta yén bentuk asal jeung "denatured" protéin bisa dibulak-balikkeun ku cara ngatur kalawan ati-ati kaayaan leyuran (misal ku dialisis bahan kimiawi nu ngakibatkeun denaturasi), protéin nu "denatured" bisa balik deui jadi bentuk asalna
Bahasan ngeunaan kumaha protéin bisa aya dina bentuk asalna mangrupa salah sahiji lapang penting dina ulikan biokimia, disebutna ulikan tilepan protéin
Ngaliwatan rékayasa genetik, para panalungtik bisa ngarobah urutan (ku kituna strukturna ogé), "targeting", karentanan kana pangaturan, sarta sipat-sipat protéin séjénna
Urutan génétik protéin nu béda bisa digabungkeun pikeun nyieun protéin "chimeric" nu mibanda sipat gabungan
Cara "matri" kieu ngawakilan salah sahiji alat pangpentingna pikeun ahli biologi sél jeung molekular pikeun ngarobah jeung nalungtik kamaha gawéna sél
Lapang séjén panalungtikan protéin nyaéta ngusahakeun ngaréka protéin nu mibanda sipat atawa fungsi nu samasakali anyar, hiji widang nu katelah rékayasa protéin ("protein engineering")
Protéin jeung gizi
Pikeun karnivora, protéin mangrupa bagian panglobana dina kadaharanana
Métabolisme protéin dina jero awak ngaleupaskeun amonia, zat nu toxik pisan
Salajengna dina ati ieu amonia dirobah jadi uréa, bahan kimiawi nu leuwih teu toxik, nu dikaluarkeun dina cikiih
Sababaraha sato malah ngarobah amonia jadi asam urat
Gizi protéin pikeun manusa
Dina jihat pangabutuh nutrisi manusa, protéin kabagi dina dua wujud: protéin lengkep nu ngandung sakabéh dalapan asam amino nu manusa teu bisa nyieunna, sedengkeun protéin teu lengkep kakurangan atawa ngan ngandung salah sahiji/sawaréhna
Awak manusa bisa ngamangpaatkeun sakabéh asam amino nu diékstraks tina dahareun pikeun sintésis protéin anyar, tapi nu teu ésénsil teu kudu diasupan tina dahareun, sabab sél urang bisa nyieun sorangan
Dahareun turunan-sato ngandung sadaya asam amino, sedengkeun tatangkalan biasana ngandung sababaraha asam amino nu leuwih loba
Atikan nyaéta pangajaran pangaweruh, kaparigelan, jeung kabiasaan sakelompok jalma anu diwariskeun ti hiji generasi ka generasi saterusna ngaliwatan pangajaran, latihan atawa panalungtikan
Atikan mindeng lumangsung dina hidayah batur, tapi ogé mungkin dina dasar otodidak
Étimologi kecap atikan sorangan asalna tina kecap Latin "ducare", hartina "pikeun pituduh, langsung, atawa ngarah" jeung awalan e, hartina "pikeun kaluar"
Jadi, atikan hartina kagiatan "ngarah kaluar"
Sakur pangalaman anu gaduh pangaruh formatif dina cara jalma mikir, ngarasa, atanapi ngalaksanakeun tiasa dianggap pendidikan
Hak atikan geus diakuan ku sababaraha pamaréntah
Di tingkat global, Pasal 13 tina Perjangjian Internasional ngeunaan hak ékonomi, sosial jeung budaya ngakuan hak unggal jalma pikeun atikan
Sanajan atikan wajib di kalolobaan tempat nepi ka umur nu tangtu, attending sakola mindeng teu latihan, sarta minoritas kolotna milih sakola ti imah, e-learning atawa atikan sarupa pikeun barudak maranéhanana
Atikan dimimitan mangsa keur orok lahir sarta sapanjang hirup
Atikan ogé bisa dimimitian saméméh jabang bayi lahir saperti sababaraha "kolot" nu ngadengekeun lagu atawa maca buku mangsa kakandungan nu diharepkeun bakal méré atikan ka orokna
Kanggo sababaraha, perjuangan sareng kameunangan kahirupan sapopoe jauh langkung instruktif tibatan sakola formal Mark Twain: "Kuring henteu pernah ngantep sakola ngaganggu pendidikan kuring.")
Anggota kulawarga ngagaduhan pangaruh pendidikan anu cukup jero - sering langkung jero tibatan anu dibayangkeun
— sanajan téknik pangajaran kulawarga bisa jadi kacida informal
Atikan formal lumangsung nalika masarakat paheut pikeun ngadidik jalma, biasana jalma ngora
Atikan "formal" bisa jadi "sistematis" jeung "komprehensif", tapi grup rojongan na bisa néangan kauntungan pribadi nalika ngawujud murid ngora gampang dipangaruhan
Life-long or dewasa education]] has become widespréad
Many dewasa have given up the notion that only anak kecil ren belong in sekolah
beberapa orang dewasa are enrolled in post-secondary education schools, both part-time and full time, where they are often classified as non-traditional students in order to distinguish them administratively from young adults entering directly from high school
Computing devices can change when and where we léarn
This is the computer based or networked léarning structure, in which péople contribute to éach others' education
It is defined as online education (a subset of distance education), the European Graduate School as a University operates during the summer, it serves as a meeting point for péople that has participated in online forums through the academic yéar, this methodology is a bréak to the traditional educational system
Classical education – Reading – Math – Language – Science – Ethics – Physical education – Religious education – Music education see Current issues in teaching Early childhood education – Primary education – Secondary education – Tertiary education – Quaternary education– Higher education – Vocational education – Post-secondary education – University – College – School – Further education Student activism – Student-led school change
Student activism – Student-led school change – Student Developed Education Policy Literacy – Testing &amp; policy– Education reform – School choice – Charter schools – Meaningful student involvement – Student voice – Student Developed Education Policy – Social promotion Early instruction – Home schooling – Unschooling – Lifelong education – Democratic Schools – Alternative school – Montessori method – Waldorf school – Online education
– Waldorf school – Online education – Distance education – Museum – Planetarium – Nature center – deschooling– political education Academic Decathlon – University Interscholastic League (UIL) – International science olympiad Philosophy of education – Teaching method – Instructional theory – Learning theory – Learning disability – Instructional technology – Education Psychology – Behaviorism – Problem-based learning – Active learning – Outcome-based education –
Active learning – Outcome-based education – Reggio Emilia approach – Cooperative education – collaborative learning – Transformative learning – experiential education – Situated learning – Adult education – Critical pedagogy Atikan dumasar ka nagara – Daftar sakola jeung paguron luhur dumasar nagara
Di handap ieu dibéréndélkeun daptar paguron luhur, dumasar nagarana
Daptar paguron luhur di Indonésia
Daptar paguron luhur di Jepang:
Universitas Gifu (岐阜大学; "Gifu Daigaku", disingkat 岐大 "Gidai") salah sahiji universitas di Jepang, nu tempatna aya di Kota Gifu wewengkon Chubu Jepang Tengah
Universitas Gifu mibanda opat kampus, nyaéta Kampus Utama di Yanagido, Kota Gifu; Kebon Percobaan di Minokamo (6 km ti Stasion Kobi), Leuweung Percobaan di Takayama (10 km ti Stasion Joro) sarta Pusat Pananglutikan Walungan (River Basin Reséarch Center) di Takayama (20 km ti Stasion Takayama)
Universitas Gifu ngadeg taun 1949, sanajan kitu Fakultas Pendidikan ngadeg taun 1873, Fakultas Pertanian ngadeg taun 1923
Dina taun 1942 ngadeg Fakultas téhnik, sarta dina taun 1947 ngadeg Fakultas Kedokteran tur dina taun 1996 ngadeg Fakultas Regional Studi
Dina taun 2004, Fakultas Pertanian direstrukturisasi jadi Fakultas Elmu Biologi Terapan
Minangka catetan waktu nu geus kaliwat, abad ka-20 nyaéta taun-taun antara 1901-2000
Dumasar kana "pamingpn nagara" dimimitian ti 1 Januari 1901 sarta dipungkas 31 Desember 2000
Sababaraha ahli sajarah nganggep jaman ti antara 1914 nepi ka 1991 minangka Abad Kaduapuluh hiji nu Pondok "(Short Twentieth Century)"
Dina basa sapopoé, disebut "sarébu salapan ratus" (seni), nunjul kana taun 1900-an nepika 1990-an
Abad ka-20 mangrupakeun hiji parobahan anu luar biasa dina kahirupan manusa alatan ayana kamajuan téknologi, médis, sosial, idéological, and international innovations
Terms like genocide, holocaust, nuclear war, and terrorism rose to common language and an influence on the lives of everyday péople
The trends of mechanization of goods and services and networks of global communication, which were begun in the continued at an ever-incréasing pace in the 20th
In spite of the terror and chaos, the 20th century saw many attempts at world péace
As the 35th United States présidént John F. Kennedy said: "What kind of peace do we seek
I am talking about a genuine peace, the kind of peace that makes life on earth worth living
Not merely peace in our time, but peace in all time
Our problems are man-made, therefore they can be solved by man
For in the final analysis, our most basic common length is that we all inhabit this small planet, we all breath the same air, we all cherish our children's future, and we are all mortal."
Virtually every aspect of life in virtually every human society changed in some fundamental way or another during the twentieth century
Soekarno () nyaéta Presiden Indonesia ka hiji
Anjeunna anu mroklamirkeun Indonésia merdéka ti pangjajah Walanda sarta jadi présidén ti taun 1945 nepi ka 1967, jadi présidén sanggeus hasil dina "transisi" nu ngagalura di Indonésia pikeun merdéka
Sukarno lengser ku kakuatan salah sahiji jendralna, Soeharto, nu jadi présidén saprak Maret 1967
Soekarno ku média massa Kulon (Éropa sarta Amérika) ogé biasa disebut Ahmad Sukarno atawa Soekarno
Sedengkeun masarakat Indonésia nyebut ngaranna "Bung Karno"
Anak saurang ménak Jawa Radén Soekemi Sosrodihardjo sarta garwana urang Bali Ida Ayu Nyoman Rai ti Kabupatén Buleleng, Sukarno lahir di Surabaya (sanajan sawatara asal nyatakeun manéhna lahir di Blitar, Jawa Wétan) di Hindia Walanda (ayeuna Indonésia)
Anjeunna ditarima di sakola Walanda nalika masih umur ngora kénéh
Sabot Anjeunna dikirim bapana ka Surabaya dina taun 1916 pikeun asup sakola tengahan, anjeunna papanggih jeung Tjokroaminoto, saurang inohong pajoang nasional
Taun 1921 Bung Karno mimitian diajar di "Technische Hoogeschool" di Bandung
Soekarno béntés dina sawatara basa, utamana basa Walanda
Manéhna kungsi ngomong yén waktu manéhna diajar di Surabaya, manéhna mindeng diuk di tukang layar bioskop sarta maca sub judul filem Walanda sacara sabalikna, alatan manéhna henteu sanggup diuk di korsi hareup anu hargana mahal
Soekarno jadi pamingpin "gerakan" kamerdikaan Indonésia
Taun 1927, Soekarno "ngabentuk" hiji partéy, namina "Partéy Nasional Indonésia"
Anjeuna ditéwak dina taun 1929 ku pamaréntah kolonial Walanda sarta dihukum salila dua taun panjara
Dina mangsa dileupaskeun, Anjeuna geus jadi saurang pahlawan anu populér
Saprak éra 1930-an, Bung Karno ditéwak deui sawatara kali
Perang Dunya Kadua - Jaman Jepang
Salila Perang Dunya Kadua, Soekarno gawé bareng jeung Jepang heunteu ngan sakadar usaha ngumpulkeun kakuatan tapi ogé nuju kamerdékaan Indonésia
Anjeuna narima aturan yén kapala pamaréntahan Indonésia aya dina kadali milter Jepang dina bulan Juli 1942 sarta dina taun 1943 jadi pingpinan Putera, hiji organisasi pulitik penting
Anjeuna ogé jadi pingpinan "Badan Penyelidik Usaha Persiapan Kemerdekaan Indonésia" (BPUPKI), organisasi jieunan Jepang keur nyiapkeun kamerdekaan Indonésia
Mangsa awal kamerdikaan, Pancasila
Saenggeus éléhna Jepang, Soekarno jeung Muhammad Hatta ngaproklamasikeun Kamerdikaan Indonésia 17 Agustus 1945
Visi Sukarno keur UUD 1945 kawangun dina "Pancasila" (Sansekerta -"lima tihang")
Filsapat politik Soekarno dipandu ku (henteu dumasar runtuyan) Marxisme, Demokrasi jeung Islam
Ieu ébréh ngaliwatan Pancasila, anu asal-usulna dianut maranéhna pas 1 Juni 1945.1 Parlemén Indonésia, diadegkeun dumasar tina "konstitusi" nu munggaran, tapi kabuktian kabéhna bisa diatur
Ieu ku alatan lobana pacéngkadan anu teu kungsi sapagodos antawis varios "sosial", "politik", agama sareng faksi-faksi étnis.2 Dina kaayaan "kacau" antara rupa-rupa "faksi" sagigireunayana tarékah Walanda balikdeui ngumawasa, pasukan Walanda nyerek Soekarno dina bulan Désémber 1948, satuluyna dipaksa sangkan dileupaskeun deui sabada "gencatan senjata"
Anjeuna mulang deui ka ka Jakarta dina tanggal 28 Désémber 1949