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Main sequence
In astronomy, the main sequence is a continuous and distinctive band of stars that appears on plots of stellar color versus brightness. These color-magnitude plots are known as Hertzsprung–Russell diagrams after their co-developers, Ejnar Hertzsprung and Henry Norris Russell. Stars on this band are known as main-sequence stars or dwarf stars. These are the most numerous true stars in the universe, and include the Earth's Sun.
After condensation and ignition of a star, it generates thermal energy in its dense core region through nuclear fusion of hydrogen into helium. During this stage of the star's lifetime, it is located on the main sequence at a position determined primarily by its mass, but also based upon its chemical composition and age. The cores of main-sequence stars are in hydrostatic equilibrium, where outward thermal pressure from the hot core is balanced by the inward pressure of gravitational collapse from the overlying layers. The strong dependence of the rate of energy generation on temperature and pressure helps to sustain this balance. Energy generated at the core makes its way to the surface and is radiated away at the photosphere. The energy is carried by either radiation or convection, with the latter occurring in regions with steeper temperature gradients, higher opacity or both.
The main sequence is sometimes divided into upper and lower parts, based on the dominant process that a star uses to generate energy. Stars below about 1.5 times the mass of the Sun (1.5 M☉) primarily fuse hydrogen atoms together in a series of stages to form helium, a sequence called the proton–proton chain. Above this mass, in the upper main sequence, the nuclear fusion process mainly uses atoms of carbon, nitrogen and oxygen as intermediaries in the CNO cycle that produces helium from hydrogen atoms. Main-sequence stars with more than two solar masses undergo convection in their core regions, which acts to stir up the newly created helium and maintain the proportion of fuel needed for fusion to occur. Below this mass, stars have cores that are entirely radiative with convective zones near the surface. With decreasing stellar mass, the proportion of the star forming a convective envelope steadily increases. Main-sequence stars below 0.4 M☉ undergo convection throughout their mass. When core convection does not occur, a helium-rich core develops surrounded by an outer layer of hydrogen.
In general, the more massive a star is, the shorter its lifespan on the main sequence. After the hydrogen fuel at the core has been consumed, the star evolves away from the main sequence on the HR diagram, into a supergiant, red giant, or directly to a white dwarf.
Hot and brilliant O-type main-sequence stars in star-forming regions. These are all regions of star formation that contain many hot young stars including several bright stars of spectral type O.[1]
In the early part of the 20th century, information about the types and distances of stars became more readily available. The spectra of stars were shown to have distinctive features, which allowed them to be categorized. Annie Jump Cannon and Edward C. Pickering at Harvard College Observatory developed a method of categorization that became known as the Harvard Classification Scheme, published in the Harvard Annals in 1901.[2]
In Potsdam in 1906, the Danish astronomer Ejnar Hertzsprung noticed that the reddest stars—classified as K and M in the Harvard scheme—could be divided into two distinct groups. These stars are either much brighter than the Sun, or much fainter. To distinguish these groups, he called them "giant" and "dwarf" stars. The following year he began studying star clusters; large groupings of stars that are co-located at approximately the same distance. He published the first plots of color versus luminosity for these stars. These plots showed a prominent and continuous sequence of stars, which he named the Main Sequence.[3]
At Princeton University, Henry Norris Russell was following a similar course of research. He was studying the relationship between the spectral classification of stars and their actual brightness as corrected for distance—their absolute magnitude. For this purpose he used a set of stars that had reliable parallaxes and many of which had been categorized at Harvard. When he plotted the spectral types of these stars against their absolute magnitude, he found that dwarf stars followed a distinct relationship. This allowed the real brightness of a dwarf star to be predicted with reasonable accuracy.[4]
Of the red stars observed by Hertzsprung, the dwarf stars also followed the spectra-luminosity relationship discovered by Russell. However, the giant stars are much brighter than dwarfs and so do not follow the same relationship. Russell proposed that the "giant stars must have low density or great surface-brightness, and the reverse is true of dwarf stars". The same curve also showed that there were very few faint white stars.[4]
In 1933, Bengt Strömgren introduced the term Hertzsprung–Russell diagram to denote a luminosity-spectral class diagram.[5] This name reflected the parallel development of this technique by both Hertzsprung and Russell earlier in the century.[3]
As evolutionary models of stars were developed during the 1930s, it was shown that, for stars of a uniform chemical composition, a relationship exists between a star's mass and its luminosity and radius. That is, for a given mass and composition, there is a unique solution for determining the star's radius and luminosity. This became known as the Vogt–Russell theorem; named after Heinrich Vogt and Henry Norris Russell. By this theorem, when a star's chemical composition and its position on the main sequence is known, so too is the star's mass and radius. (However, it was subsequently discovered that the theorem breaks down somewhat for stars of non-uniform composition.)[6]
A refined scheme for stellar classification was published in 1943 by William Wilson Morgan and Philip Childs Keenan.[7] The MK classification assigned each star a spectral type—based on the Harvard classification—and a luminosity class. The Harvard classification had been developed by assigning a different letter to each star based on the strength of the hydrogen spectral line, before the relationship between spectra and temperature was known. When ordered by temperature and when duplicate classes were removed, the spectral types of stars followed, in order of decreasing temperature with colors ranging from blue to red, the sequence O, B, A, F, G, K and M. (A popular mnemonic for memorizing this sequence of stellar classes is "Oh Be A Fine Girl/Guy, Kiss Me".) The luminosity class ranged from I to V, in order of decreasing luminosity. Stars of luminosity class V belonged to the main sequence.[8]
In April 2018, astronomers reported the detection of the most distant "ordinary" (i.e., main sequence) star, named Icarus (formally, MACS J1149 Lensed Star 1), at 9 billion light-years away from Earth.[9][10]
Formation and evolution
Main articles: Star formation, Protostar, Pre-main-sequence star, and Stellar evolution § Main sequence
When a protostar is formed from the collapse of a giant molecular cloud of gas and dust in the local interstellar medium, the initial composition is homogeneous throughout, consisting of about 70% hydrogen, 28% helium and trace amounts of other elements, by mass.[11] The initial mass of the star depends on the local conditions within the cloud. (The mass distribution of newly formed stars is described empirically by the initial mass function.)[12] During the initial collapse, this pre-main-sequence star generates energy through gravitational contraction. Once sufficiently dense, stars begin converting hydrogen into helium and giving off energy through an exothermic nuclear fusion process.[8]
Hertzsprung–Russell diagram
Brown dwarfs
White dwarfs
Red dwarfs
Subdwarfs
("dwarfs")
Subgiants
Bright giants
Supergiants
Hypergiants
magni-
tude
(MV)
When nuclear fusion of hydrogen becomes the dominant energy production process and the excess energy gained from gravitational contraction has been lost,[13] the star lies along a curve on the Hertzsprung–Russell diagram (or HR diagram) called the standard main sequence. Astronomers will sometimes refer to this stage as "zero age main sequence", or ZAMS.[14][15] The ZAMS curve can be calculated using computer models of stellar properties at the point when stars begin hydrogen fusion. From this point, the brightness and surface temperature of stars typically increase with age.[16]
A star remains near its initial position on the main sequence until a significant amount of hydrogen in the core has been consumed, then begins to evolve into a more luminous star. (On the HR diagram, the evolving star moves up and to the right of the main sequence.) Thus the main sequence represents the primary hydrogen-burning stage of a star's lifetime.[8]
The majority of stars on a typical HR diagram lie along the main-sequence curve. This line is pronounced because both the spectral type and the luminosity depend only on a star's mass, at least to zeroth-order approximation, as long as it is fusing hydrogen at its core—and that is what almost all stars spend most of their "active" lives doing.[17]
The temperature of a star determines its spectral type via its effect on the physical properties of plasma in its photosphere. A star's energy emission as a function of wavelength is influenced by both its temperature and composition. A key indicator of this energy distribution is given by the color index, B − V, which measures the star's magnitude in blue (B) and green-yellow (V) light by means of filters.[note 1] This difference in magnitude provides a measure of a star's temperature.
Dwarf terminology
Main-sequence stars are called dwarf stars,[18][19] but this terminology is partly historical and can be somewhat confusing. For the cooler stars, dwarfs such as red dwarfs, orange dwarfs, and yellow dwarfs are indeed much smaller and dimmer than other stars of those colors. However, for hotter blue and white stars, the difference in size and brightness between so-called "dwarf" stars that are on the main sequence and so-called "giant" stars that are not, becomes smaller. For the hottest stars the difference is not directly observable and for these stars the terms "dwarf" and "giant" refer to differences in spectral lines which indicate whether a star is on or off the main sequence. Nevertheless, very hot main-sequence stars are still sometimes called dwarfs, even though they have roughly the same size and brightness as the "giant" stars of that temperature.[20]
The common use of "dwarf" to mean main sequence is confusing in another way, because there are dwarf stars which are not main-sequence stars. For example, a white dwarf is the dead core left over after a star has shed its outer layers, and is much smaller than a main-sequence star, roughly the size of Earth. These represent the final evolutionary stage of many main-sequence stars.[21]
Comparison of main sequence stars of each spectral class
By treating the star as an idealized energy radiator known as a black body, the luminosity L and radius R can be related to the effective temperature Teff by the Stefan–Boltzmann law:
L = 4 π σ R 2 T e f f 4 {\displaystyle L=4\pi \sigma R^{2}T_{eff}^{4}} {\displaystyle L=4\pi \sigma R^{2}T_{eff}^{4}}
where σ is the Stefan–Boltzmann constant. As the position of a star on the HR diagram shows its approximate luminosity, this relation can be used to estimate its radius.[22]
The mass, radius and luminosity of a star are closely interlinked, and their respective values can be approximated by three relations. First is the Stefan–Boltzmann law, which relates the luminosity L, the radius R and the surface temperature Teff. Second is the mass–luminosity relation, which relates the luminosity L and the mass M. Finally, the relationship between M and R is close to linear. The ratio of M to R increases by a factor of only three over 2.5 orders of magnitude of M. This relation is roughly proportional to the star's inner temperature TI, and its extremely slow increase reflects the fact that the rate of energy generation in the core strongly depends on this temperature, whereas it has to fit the mass–luminosity relation. Thus, a too high or too low temperature will result in stellar instability.
A better approximation is to take ε = L/M, the energy generation rate per unit mass, as ε is proportional to TI15, where TI is the core temperature. This is suitable for stars at least as massive as the Sun, exhibiting the CNO cycle, and gives the better fit R ∝ M0.78.[23]
Sample parameters
The table below shows typical values for stars along the main sequence. The values of luminosity (L), radius (R) and mass (M) are relative to the Sun—a dwarf star with a spectral classification of G2 V. The actual values for a star may vary by as much as 20–30% from the values listed below.[24]
Table of main-sequence stellar parameters[25] Stellar
Class Radius Mass Luminosity Temp. Examples[26]
R/R☉ M/M☉ L/L☉ K
O6 18 40 500,000 38,000 Theta1 Orionis C
B0 7.4 18 20,000 30,000 Phi1 Orionis
B5 3.8 6.5 800 16,400 Pi Andromedae A
A0 2.5 3.2 80 10,800 Alpha Coronae Borealis A
A5 1.7 2.1 20 8,620 Beta Pictoris
F0 1.3 1.7 6 7,240 Gamma Virginis
F5 1.2 1.3 2.5 6,540 Eta Arietis
G0 1.05 1.10 1.26 5,920 Beta Comae Berenices
G2 1 1 1 5,780 Sun[note 2]
G5 0.93 0.93 0.79 5,610 Alpha Mensae
K0 0.85 0.78 0.40 5,240 70 Ophiuchi A
K5 0.74 0.69 0.16 4,410 61 Cygni A[27]
M0 0.51 0.60 0.072 3,800 Lacaille 8760
M5 0.32 0.21 0.0079 3,120 EZ Aquarii A
M8 0.13 0.10 0.0008 2,660 Van Biesbroeck's star[28]
See also: Stellar nucleosynthesis
Logarithm of the relative energy output (ε) of proton–proton (PP), CNO and Triple-α fusion processes at different temperatures (T). The dashed line shows the combined energy generation of the PP and CNO processes within a star. At the Sun's core temperature, the PP process is more efficient.
All main-sequence stars have a core region where energy is generated by nuclear fusion. The temperature and density of this core are at the levels necessary to sustain the energy production that will support the remainder of the star. A reduction of energy production would cause the overlaying mass to compress the core, resulting in an increase in the fusion rate because of higher temperature and pressure. Likewise an increase in energy production would cause the star to expand, lowering the pressure at the core. Thus the star forms a self-regulating system in hydrostatic equilibrium that is stable over the course of its main sequence lifetime.[29]
Main-sequence stars employ two types of hydrogen fusion processes, and the rate of energy generation from each type depends on the temperature in the core region. Astronomers divide the main sequence into upper and lower parts, based on which of the two is the dominant fusion process. In the lower main sequence, energy is primarily generated as the result of the proton-proton chain, which directly fuses hydrogen together in a series of stages to produce helium.[30] Stars in the upper main sequence have sufficiently high core temperatures to efficiently use the CNO cycle (see chart). This process uses atoms of carbon, nitrogen and oxygen as intermediaries in the process of fusing hydrogen into helium.
At a stellar core temperature of 18 million Kelvin, the PP process and CNO cycle are equally efficient, and each type generates half of the star's net luminosity. As this is the core temperature of a star with about 1.5 M☉, the upper main sequence consists of stars above this mass. Thus, roughly speaking, stars of spectral class F or cooler belong to the lower main sequence, while A-type stars or hotter are upper main-sequence stars.[16] The transition in primary energy production from one form to the other spans a range difference of less than a single solar mass. In the Sun, a one solar-mass star, only 1.5% of the energy is generated by the CNO cycle.[31] By contrast, stars with 1.8 M☉ or above generate almost their entire energy output through the CNO cycle.[32]
The observed upper limit for a main-sequence star is 120–200 M☉.[33] The theoretical explanation for this limit is that stars above this mass can not radiate energy fast enough to remain stable, so any additional mass will be ejected in a series of pulsations until the star reaches a stable limit.[34] The lower limit for sustained proton–proton nuclear fusion is about 0.08 M☉ or 80 times the mass of Jupiter.[30] Below this threshold are sub-stellar objects that can not sustain hydrogen fusion, known as brown dwarfs.[35]
Main article: Stellar structure
This diagram shows a cross-section of a Sun-like star, showing the internal structure.
Because there is a temperature difference between the core and the surface, or photosphere, energy is transported outward. The two modes for transporting this energy are radiation and convection. A radiation zone, where energy is transported by radiation, is stable against convection and there is very little mixing of the plasma. By contrast, in a convection zone the energy is transported by bulk movement of plasma, with hotter material rising and cooler material descending. Convection is a more efficient mode for carrying energy than radiation, but it will only occur under conditions that create a steep temperature gradient.[29][36]
In massive stars (above 10 M☉)[37] the rate of energy generation by the CNO cycle is very sensitive to temperature, so the fusion is highly concentrated at the core. Consequently, there is a high temperature gradient in the core region, which results in a convection zone for more efficient energy transport.[30] This mixing of material around the core removes the helium ash from the hydrogen-burning region, allowing more of the hydrogen in the star to be consumed during the main-sequence lifetime. The outer regions of a massive star transport energy by radiation, with little or no convection.[29]
Intermediate-mass stars such as Sirius may transport energy primarily by radiation, with a small core convection region.[38] Medium-sized, low-mass stars like the Sun have a core region that is stable against convection, with a convection zone near the surface that mixes the outer layers. This results in a steady buildup of a helium-rich core, surrounded by a hydrogen-rich outer region. By contrast, cool, very low-mass stars (below 0.4 M☉) are convective throughout.[12] Thus the helium produced at the core is distributed across the star, producing a relatively uniform atmosphere and a proportionately longer main sequence lifespan.[29]
Luminosity-color variation
The Sun is the most familiar example of a main-sequence star
As non-fusing helium ash accumulates in the core of a main-sequence star, the reduction in the abundance of hydrogen per unit mass results in a gradual lowering of the fusion rate within that mass. Since it is the outflow of fusion-supplied energy that supports the higher layers of the star, the core is compressed, producing higher temperatures and pressures. Both factors increase the rate of fusion thus moving the equilibrium towards a smaller, denser, hotter core producing more energy whose increased outflow pushes the higher layers further out. Thus there is a steady increase in the luminosity and radius of the star over time.[16] For example, the luminosity of the early Sun was only about 70% of its current value.[39] As a star ages this luminosity increase changes its position on the HR diagram. This effect results in a broadening of the main sequence band because stars are observed at random stages in their lifetime. That is, the main sequence band develops a thickness on the HR diagram; it is not simply a narrow line.[40]
Other factors that broaden the main sequence band on the HR diagram include uncertainty in the distance to stars and the presence of unresolved binary stars that can alter the observed stellar parameters. However, even perfect observation would show a fuzzy main sequence because mass is not the only parameter that affects a star's color and luminosity. Variations in chemical composition caused by the initial abundances, the star's evolutionary status,[41] interaction with a close companion,[42] rapid rotation,[43] or a magnetic field can all slightly change a main-sequence star's HR diagram position, to name just a few factors. As an example, there are metal-poor stars (with a very low abundance of elements with higher atomic numbers than helium) that lie just below the main sequence and are known as subdwarfs. These stars are fusing hydrogen in their cores and so they mark the lower edge of main sequence fuzziness caused by variance in chemical composition.[44]
A nearly vertical region of the HR diagram, known as the instability strip, is occupied by pulsating variable stars known as Cepheid variables. These stars vary in magnitude at regular intervals, giving them a pulsating appearance. The strip intersects the upper part of the main sequence in the region of class A and F stars, which are between one and two solar masses. Pulsating stars in this part of the instability strip that intersects the upper part of the main sequence are called Delta Scuti variables. Main-sequence stars in this region experience only small changes in magnitude and so this variation is difficult to detect.[45] Other classes of unstable main-sequence stars, like Beta Cephei variables, are unrelated to this instability strip.
This plot gives an example of the mass-luminosity relationship for zero-age main-sequence stars. The mass and luminosity are relative to the present-day Sun.
The total amount of energy that a star can generate through nuclear fusion of hydrogen is limited by the amount of hydrogen fuel that can be consumed at the core. For a star in equilibrium, the thermal energy generated at the core must be at least equal to the energy radiated at the surface. Since the luminosity gives the amount of energy radiated per unit time, the total life span can be estimated, to first approximation, as the total energy produced divided by the star's luminosity.[46]
For a star with at least 0.5 M☉, when the hydrogen supply in its core is exhausted and it expands to become a red giant, it can start to fuse helium atoms to form carbon. The energy output of the helium fusion process per unit mass is only about a tenth the energy output of the hydrogen process, and the luminosity of the star increases.[47] This results in a much shorter length of time in this stage compared to the main sequence lifetime. (For example, the Sun is predicted to spend 130 million years burning helium, compared to about 12 billion years burning hydrogen.)[48] Thus, about 90% of the observed stars above 0.5 M☉ will be on the main sequence.[49] On average, main-sequence stars are known to follow an empirical mass-luminosity relationship.[50] The luminosity (L) of the star is roughly proportional to the total mass (M) as the following power law:
L ∝ M 3.5 {\displaystyle {\begin{smallmatrix}L\ \propto \ M^{3.5}\end{smallmatrix}}} {\begin{smallmatrix}L\ \propto \ M^{3.5}\end{smallmatrix}}
This relationship applies to main-sequence stars in the range 0.1–50 M☉.[51]
The amount of fuel available for nuclear fusion is proportional to the mass of the star. Thus, the lifetime of a star on the main sequence can be estimated by comparing it to solar evolutionary models. The Sun has been a main-sequence star for about 4.5 billion years and it will become a red giant in 6.5 billion years,[52] for a total main sequence lifetime of roughly 1010 years. Hence:[53]
τ M S ≈ 10 10 years ⋅ [ M M ⨀ ] ⋅ [ L ⨀ L ] = 10 10 years ⋅ [ M M ⨀ ] − 2.5 {\displaystyle {\begin{smallmatrix}\tau _{\rm {MS}}\ \approx \ 10^{10}{\text{years}}\cdot \left[{\frac {M}{M_{\bigodot }}}\right]\cdot \left[{\frac {L_{\bigodot }}{L}}\right]\ =\ 10^{10}{\text{years}}\cdot \left[{\frac {M}{M_{\bigodot }}}\right]^{-2.5}\end{smallmatrix}}} {\begin{smallmatrix}\tau _{\rm {MS}}\ \approx \ 10^{10}{\text{years}}\cdot \left[{\frac {M}{M_{\bigodot }}}\right]\cdot \left[{\frac {L_{\bigodot }}{L}}\right]\ =\ 10^{10}{\text{years}}\cdot \left[{\frac {M}{M_{\bigodot }}}\right]^{-2.5}\end{smallmatrix}}
where M and L are the mass and luminosity of the star, respectively, M ⨀ {\displaystyle {\begin{smallmatrix}M_{\bigodot }\end{smallmatrix}}} {\begin{smallmatrix}M_{\bigodot }\end{smallmatrix}} is a solar mass, L ⨀ {\displaystyle {\begin{smallmatrix}L_{\bigodot }\end{smallmatrix}}} {\begin{smallmatrix}L_{\bigodot }\end{smallmatrix}} is the solar luminosity and τ M S {\displaystyle \tau _{\rm {MS}}} \tau _{\rm {MS}} is the star's estimated main sequence lifetime.
Although more massive stars have more fuel to burn and might intuitively be expected to last longer, they also radiate a proportionately greater amount with increased mass. This is required by the stellar equation of state; for a massive star to maintain equilibrium, the outward pressure of radiated energy generated in the core not only must but will rise to match the titanic inward gravitational pressure of its envelope. Thus, the most massive stars may remain on the main sequence for only a few million years, while stars with less than a tenth of a solar mass may last for over a trillion years.[54]
The exact mass-luminosity relationship depends on how efficiently energy can be transported from the core to the surface. A higher opacity has an insulating effect that retains more energy at the core, so the star does not need to produce as much energy to remain in hydrostatic equilibrium. By contrast, a lower opacity means energy escapes more rapidly and the star must burn more fuel to remain in equilibrium.[55] A sufficiently high opacity can result in energy transport via convection, which changes the conditions needed to remain in equilibrium.[16]
In high-mass main-sequence stars, the opacity is dominated by electron scattering, which is nearly constant with increasing temperature. Thus the luminosity only increases as the cube of the star's mass.[47] For stars below 10 M☉, the opacity becomes dependent on temperature, resulting in the luminosity varying approximately as the fourth power of the star's mass.[51] For very low-mass stars, molecules in the atmosphere also contribute to the opacity. Below about 0.5 M☉, the luminosity of the star varies as the mass to the power of 2.3, producing a flattening of the slope on a graph of mass versus luminosity. Even these refinements are only an approximation, however, and the mass-luminosity relation can vary depending on a star's composition.[12]
Evolutionary tracks
Main article: Stellar evolution
Evolutionary track of a star like the sun
When a main-sequence star has consumed the hydrogen at its core, the loss of energy generation causes its gravitational collapse to resume and the star evolves off the main sequence. The path which the star follows across the HR diagram is called an evolutionary track.[56]
H–R diagram for two open clusters: NGC 188 (blue) is older and shows a lower turn off from the main sequence than M67 (yellow). The dots outside the two sequences are mostly foreground and background stars with no relation to the clusters.
Stars with less than 0.23 M☉[57] are predicted to directly become white dwarfs when energy generation by nuclear fusion of hydrogen at their core comes to a halt, although no stars are old enough for this to have occurred.
In stars more massive than 0.23 M☉, the hydrogen surrounding the helium core reaches sufficient temperature and pressure to undergo fusion, forming a hydrogen-burning shell and causing the outer layers of the star to expand and cool. The stage as these stars move away from the main sequence is known as the subgiant branch; it is relatively brief and appears as a gap in the evolutionary track since few stars are observed at that point.
When the helium core of low-mass stars becomes degenerate, or the outer layers of intermediate-mass stars cool sufficiently to become opaque, their hydrogen shells increase in temperature and the stars start to become more luminous. This is known as the red giant branch; it is a relatively long-lived stage and it appears prominently in H–R diagrams. These stars will eventually end their lives as white dwarfs.[58][59]
The most massive stars do not become red giants; instead, their cores quickly become hot enough to fuse helium and eventually heavier elements and they are known as supergiants. They follow approximately horizontal evolutionary tracks from the main sequence across the top of the H–R diagram. Supergiants are relatively rare and do not show prominently on most H–R diagrams. Their cores will eventually collapse, usually leading to a supernova and leaving behind either a neutron star or black hole.[60]
When a cluster of stars is formed at about the same time, the main sequence lifespan of these stars will depend on their individual masses. The most massive stars will leave the main sequence first, followed in sequence by stars of ever lower masses. The position where stars in the cluster are leaving the main sequence is known as the turnoff point. By knowing the main sequence lifespan of stars at this point, it becomes possible to estimate the age of the cluster.[61]
By measuring the difference between these values, this eliminates the need to correct the magnitudes for distance. However, this can be affected by interstellar extinction.
The Sun is a typical type G2V star.
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Bahcall, John N.; Pinsonneault, M. H.; Basu, Sarbani (2003). "Solar Models: Current Epoch and Time Dependences, Neutrinos, and Helioseismological Properties". The Astrophysical Journal. 555 (2): 990–1012. arXiv:astro-ph/0212331. Bibcode:2001ApJ...555..990B. doi:10.1086/321493. S2CID 13798091.
Salaris, Maurizio; Cassisi, Santi (2005). Evolution of Stars and Stellar Populations. John Wiley and Sons. p. 128. ISBN 978-0-470-09220-0.
Oey, M. S.; Clarke, C. J. (2005). "Statistical Confirmation of a Stellar Upper Mass Limit". The Astrophysical Journal. 620 (1): L43–L46. arXiv:astro-ph/0501135. Bibcode:2005ApJ...620L..43O. doi:10.1086/428396. S2CID 7280299.
Ziebarth, Kenneth (1970). "On the Upper Mass Limit for Main-Sequence Stars". Astrophysical Journal. 162: 947–962. Bibcode:1970ApJ...162..947Z. doi:10.1086/150726.
Burrows, A.; Hubbard, W. B.; Saumon, D.; Lunine, J. I. (March 1993). "An expanded set of brown dwarf and very low mass star models". Astrophysical Journal, Part 1. 406 (1): 158–171. Bibcode:1993ApJ...406..158B. doi:10.1086/172427.
Aller, Lawrence H. (1991). Atoms, Stars, and Nebulae. Cambridge University Press. ISBN 978-0-521-31040-6.
Bressan, A. G.; Chiosi, C.; Bertelli, G. (1981). "Mass loss and overshooting in massive stars". Astronomy and Astrophysics. 102 (1): 25–30. Bibcode:1981A&A...102...25B.
Lochner, Jim; Gibb, Meredith; Newman, Phil (6 September 2006). "Stars". NASA. Retrieved 2007-12-05.
Gough, D. O. (1981). "Solar interior structure and luminosity variations". Solar Physics. 74 (1): 21–34. Bibcode:1981SoPh...74...21G. doi:10.1007/BF00151270. S2CID 120541081.
Padmanabhan, Thanu (2001). Theoretical Astrophysics. Cambridge University Press. ISBN 978-0-521-56241-6.
Wright, J. T. (2004). "Do We Know of Any Maunder Minimum Stars?". The Astronomical Journal. 128 (3): 1273–1278. arXiv:astro-ph/0406338. Bibcode:2004AJ....128.1273W. doi:10.1086/423221. S2CID 118975831. Retrieved 2007-12-06.
Tayler, Roger John (1994). The Stars: Their Structure and Evolution. Cambridge University Press. ISBN 978-0-521-45885-6.
Sweet, I. P. A.; Roy, A. E. (1953). "The structure of rotating stars". Monthly Notices of the Royal Astronomical Society. 113 (6): 701–715. Bibcode:1953MNRAS.113..701S. doi:10.1093/mnras/113.6.701.
Burgasser, Adam J.; Kirkpatrick, J. Davy; Lepine, Sebastien (5–9 July 2004). Spitzer Studies of Ultracool Subdwarfs: Metal-poor Late-type M, L and T Dwarfs. Proceedings of the 13th Cambridge Workshop on Cool Stars, Stellar Systems and the Sun. Hamburg, Germany: Dordrecht, D. Reidel Publishing Co. p. 237. Retrieved 2007-12-06.
Green, S. F.; Jones, Mark Henry; Burnell, S. Jocelyn (2004). An Introduction to the Sun and Stars. Cambridge University Press. ISBN 978-0-521-54622-5.
Richmond, Michael W. (10 November 2004). "Stellar evolution on the main sequence". Rochester Institute of Technology. Retrieved 2007-12-03.
Prialnik, Dina (2000). An Introduction to the Theory of Stellar Structure and Evolution. Cambridge University Press. ISBN 978-0-521-65937-6.
Schröder, K.-P.; Connon Smith, Robert (May 2008). "Distant future of the Sun and Earth revisited". Monthly Notices of the Royal Astronomical Society. 386 (1): 155–163. arXiv:0801.4031. Bibcode:2008MNRAS.386..155S. doi:10.1111/j.1365-2966.2008.13022.x. S2CID 10073988.
Arnett, David (1996). Supernovae and Nucleosynthesis: An Investigation of the History of Matter, from the Big Bang to the Present. Princeton University Press. ISBN 978-0-691-01147-9.—Hydrogen fusion produces 8×1018 erg/g while helium fusion produces 8×1017 erg/g.
For a detailed historical reconstruction of the theoretical derivation of this relationship by Eddington in 1924, see: Lecchini, Stefano (2007). How Dwarfs Became Giants. The Discovery of the Mass-Luminosity Relation. Bern Studies in the History and Philosophy of Science. ISBN 978-3-9522882-6-9.
Rolfs, Claus E.; Rodney, William S. (1988). Cauldrons in the Cosmos: Nuclear Astrophysics. University of Chicago Press. ISBN 978-0-226-72457-7.
Sackmann, I.-Juliana; Boothroyd, Arnold I.; Kraemer, Kathleen E. (November 1993). "Our Sun. III. Present and Future". Astrophysical Journal. 418: 457–468. Bibcode:1993ApJ...418..457S. doi:10.1086/173407.
Hansen, Carl J.; Kawaler, Steven D. (1994). Stellar Interiors: Physical Principles, Structure, and Evolution. Birkhäuser. p. 28. ISBN 978-0-387-94138-7.
Laughlin, Gregory; Bodenheimer, Peter; Adams, Fred C. (1997). "The End of the Main Sequence". The Astrophysical Journal. 482 (1): 420–432. Bibcode:1997ApJ...482..420L. doi:10.1086/304125.
Imamura, James N. (7 February 1995). "Mass-Luminosity Relationship". University of Oregon. Archived from the original on 14 December 2006. Retrieved 8 January 2007.
Icko Iben (29 November 2012). Stellar Evolution Physics. Cambridge University Press. pp. 1481–. ISBN 978-1-107-01657-6.
Adams, Fred C.; Laughlin, Gregory (April 1997). "A Dying Universe: The Long Term Fate and Evolution of Astrophysical Objects". Reviews of Modern Physics. 69 (2): 337–372. arXiv:astro-ph/9701131. Bibcode:1997RvMP...69..337A. doi:10.1103/RevModPhys.69.337. S2CID 12173790.
Staff (12 October 2006). "Post-Main Sequence Stars". Australia Telescope Outreach and Education. Archived from the original on 20 January 2013. Retrieved 2008-01-08.
Girardi, L.; Bressan, A.; Bertelli, G.; Chiosi, C. (2000). "Evolutionary tracks and isochrones for low- and intermediate-mass stars: From 0.15 to 7 Msun, and from Z=0.0004 to 0.03". Astronomy and Astrophysics Supplement. 141 (3): 371–383. arXiv:astro-ph/9910164. Bibcode:2000A&AS..141..371G. doi:10.1051/aas:2000126. S2CID 14566232.
Sitko, Michael L. (24 March 2000). "Stellar Structure and Evolution". University of Cincinnati. Archived from the original on 26 March 2005. Retrieved 2007-12-05.
Krauss, Lawrence M.; Chaboyer, Brian (2003). "Age Estimates of Globular Clusters in the Milky Way: Constraints on Cosmology". Science. 299 (5603): 65–69. Bibcode:2003Sci...299...65K. doi:10.1126/science.1075631. PMID 12511641. S2CID 10814581.
Kippenhahn, Rudolf, 100 Billion Suns, Basic Books, New York, 1983.
Arnett, David (1996). Supernovae and Nucleosynthesis. Princeton: Princeton University Press.
Bahcall, John N. (1989). Neutrino Astrophysics. Cambridge: Cambridge University Press.
Bahcall, John N.; Pinsonneault, M.H.; Basu, Sarbani (2001). "Solar Models: Current Epoch and Time Dependences, Neutrinos, and Helioseismological Properties". The Astrophysical Journal. 555 (2): 990–1012. arXiv:astro-ph/0010346. Bibcode:2001ApJ...555..990B. doi:10.1086/321493. S2CID 13798091.
Barnes, C. A.; Clayton, D. D.; Schramm, D. N., eds. (1982). Essays in Nuclear Astrophysics. Cambridge: Cambridge University Press.
Bowers, Richard L.; Deeming, Terry (1984). Astrophysics I: Stars. Boston: Jones and Bartlett.
Carroll, Bradley W. & Ostlie, Dale A. (2007). An Introduction to Modern Astrophysics. San Francisco: Person Education Addison-Wesley. ISBN 978-0-8053-0402-2.
Chabrier, Gilles; Baraffe, Isabelle (2000). "Theory of Low-Mass Stars and Substellar Objects". Annual Review of Astronomy and Astrophysics. 38: 337–377. arXiv:astro-ph/0006383. Bibcode:2000ARA&A..38..337C. doi:10.1146/annurev.astro.38.1.337. S2CID 59325115.
Chandrasekhar, S. (1967). An Introduction to the study of stellar Structure. New York: Dover.
Clayton, Donald D. (1983). Principles of Stellar Evolution and Nucleosynthesis. Chicago: University of Chicago.
Cox, J. P.; Giuli, R. T. (1968). Principles of Stellar Structure. New York City: Gordon and Breach.
Fowler, William A.; Caughlan, Georgeanne R.; Zimmerman, Barbara A. (1967). "Thermonuclear Reaction Rates, I". Annual Review of Astronomy and Astrophysics. 5: 525. Bibcode:1967ARA&A...5..525F. doi:10.1146/annurev.aa.05.090167.002521.
Fowler, William A.; Caughlan, Georgeanne R.; Zimmerman, Barbara A. (1975). "Thermonuclear Reaction Rates, II". Annual Review of Astronomy and Astrophysics. 13: 69. Bibcode:1975ARA&A..13...69F. doi:10.1146/annurev.aa.13.090175.000441.
Hansen, Carl J.; Kawaler, Steven D.; Trimble, Virginia (2004). Stellar Interiors: Physical Principles, Structure, and Evolution, Second Edition. New York: Springer-Verlag.
Harris, Michael J.; Fowler, William A.; Caughlan, Georgeanne R.; Zimmerman, Barbara A. (1983). "Thermonuclear Reaction Rates, III". Annual Review of Astronomy and Astrophysics. 21: 165. Bibcode:1983ARA&A..21..165H. doi:10.1146/annurev.aa.21.090183.001121.
Iben, Icko, Jr (1967). "Stellar Evolution Within and Off the Main Sequence". Annual Review of Astronomy and Astrophysics. 5: 571. Bibcode:1967ARA&A...5..571I. doi:10.1146/annurev.aa.05.090167.003035.
Iglesias, Carlos A.; Rogers, Forrest J. (1996). "Updated Opal Opacities". The Astrophysical Journal. 464: 943. Bibcode:1996ApJ...464..943I. doi:10.1086/177381.
Kippenhahn, Rudolf; Weigert, Alfred (1990). Stellar Structure and Evolution. Berlin: Springer-Verlag.
Liebert, James; Probst, Ronald G. (1987). "Very Low Mass Stars". Annual Review of Astronomy and Astrophysics. 25: 437. Bibcode:1987ARA&A..25..473L. doi:10.1146/annurev.aa.25.090187.002353.
Novotny, Eva (1973). Introduction to Stellar Atmospheres and Interior. New York City: Oxford University Press.
Padmanabhan, T. (2002). Theoretical Astrophysics. Cambridge: Cambridge University Press.
Prialnik, Dina (2000). An Introduction to the Theory of Stellar Structure and Evolution. Cambridge: Cambridge University Press.
Shore, Steven N. (2003). The Tapestry of Modern Astrophysics. Hoboken: John Wiley and Sons.
Accretion Molecular cloud Bok globule Young stellar object
Protostar Pre-main-sequence Herbig Ae/Be T Tauri FU Orionis Herbig–Haro object Hayashi track Henyey track
Main sequence Red-giant branch Horizontal branch
Red clump Asymptotic giant branch
super-AGB Blue loop Protoplanetary nebula Planetary nebula PG1159 Dredge-up OH/IR Instability strip Luminous blue variable Blue straggler Stellar population Supernova Superluminous supernova / Hypernova
Spectral classification
Early Late Main sequence
O B A F G K M Brown dwarf WR OB Subdwarf
O B Subgiant Giant
Blue Red Yellow Bright giant Supergiant
Blue Red Yellow Hypergiant
Yellow Carbon
S CN CH White dwarf Chemically peculiar
Am Ap/Bp HgMn Helium-weak Barium Extreme helium Lambda Boötis Lead Technetium Be
Shell B[e]
Helium planet Black dwarf Neutron
Radio-quiet Pulsar
Binary X-ray Magnetar Stellar black hole X-ray binary
Blue dwarf Green Black dwarf Exotic
Boson Electroweak Strange Preon Planck Dark Dark-energy Quark Q Black Gravastar Frozen Quasi-star Thorne–Żytkow object Iron Blitzar
Stellar nucleosynthesis
Deuterium burning Lithium burning Proton–proton chain CNO cycle Helium flash Triple-alpha process Alpha process Carbon burning Neon burning Oxygen burning Silicon burning S-process R-process Fusor Nova
Symbiotic Remnant Luminous red nova
Core Convection zone
Microturbulence Oscillations Radiation zone Atmosphere
Photosphere Starspot Chromosphere Stellar corona Stellar wind
Bubble Bipolar outflow Accretion disk Asteroseismology
Helioseismology Eddington luminosity Kelvin–Helmholtz mechanism
Designation Dynamics Effective temperature Luminosity Kinematics Magnetic field Absolute magnitude Mass Metallicity Rotation Starlight Variable Photometric system Color index Hertzsprung–Russell diagram Color–color diagram
Star systems
Contact Common envelope Eclipsing Symbiotic Multiple Cluster
Open Globular Super Planetary system
Earth-centric
Solar System Sunlight Pole star Circumpolar Constellation Asterism Magnitude
Apparent Extinction Photographic Radial velocity Proper motion Parallax Photometric-standard
Proper names
Arabic Chinese Extremes Most massive Highest temperature Lowest temperature Largest volume Smallest volume Brightest
Historical Most luminous Nearest
Nearest bright With exoplanets Brown dwarfs White dwarfs Milky Way novae Supernovae
Candidates Remnants Planetary nebulae Timeline of stellar astronomy
Substellar object
Brown dwarf Sub-brown dwarf Planet Galactic year Galaxy Guest Gravity Intergalactic Planet-hosting stars Tidal disruption event
Physics Encyclopedia
Retrieved from "http://en.wikipedia.org/"
All text is available under the terms of the GNU Free Documentation License


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A garden without bugs is like a city without people. Gardens are like a private zoo or nature reserve. You can see a thriving array of wildlife! For example, millions of organisms live in harmony most of the time. Not all of them are nasty bugs or dangerous enemies. But when we have the wrong combination of plants which attract various bugs, then our plants get eaten by too many of the little critters!
If you look at your garden like an eco-system, a whole world opens up before your eyes. When you look at your vegetable garden, you have to realize it will attract pests. Either you can control this with pesticide, which may damage your garden in the future – or you can use a biological control. For example, if you plant lettuce then you should plant marigold or daisies around the vegetable so that they counteract any pests attracted by the lettuce.
In general, there is not a home gardener who needs to use herbicides. It is easier to dig up a few weeds than to spray them and risk damaging other plants, and damaging your own health, the health of your children and your pets. If you do use pesticides, look at the label for the most eco-safe ones you can find. Then use them sparingly and only according to their printed directions.
Do your own Biological Control!
You can collect the good predator insects on your walking trips and put them to work in your garden. For example, cut a piece of plant with ladybug or larvae ladybugs with aphids, and put them into a jar. Do not expose the bottle to heat or to sun; it is best to keep them covered, perhaps under a towel. At home, carefully transfer these good predator insects onto your infested plants. You can also use diatomaceous earth around your garden and it will control many types of harmful insects, snails and slugs. Look at other organic gardening websites for eco-friendly ways to a successful garden.
Many insects in their childhood or larval stage live in the soil and change rotting plant and compost into humus. They are everywhere in your garden, if you don't use pesticides. Often people confuse earthworms in this category. But earthworms are not an insect or an insect larvae. They belong to a group of animals called annelids, the ringed or segmented worms. But earthworms are certainly great soil-builders and every gardener's friend, but pesticides can send them fleeing to your neighbor's garden if you're not careful!
These are the good guys which protect your garden against the pests.
A field guide to the insects of America North of Mexico.
Borror, D. J. & R. E. White, 1970. Peterson field guide series, Houghton Mifflin.
Debach, P., ed. 1964, London, Chapman and Hall Ltd.
Debach, P., ed. 1974, London, Cambridge University Press.
Kaston, B. J., 1948. St. Geol. and Nat. Hist. Surv. Bull. 70: 1-874.
The Audubon Society field guide to North American insects and spiders.
Milne, L. & M., 1980. Alfred A. Knopf, New York.


text:
Southwest Airlines Reports Drop in Bookings Amid Coronavirus Fears
Mario Tama/Getty Images
Nate Church
Southwest Airlines Co. warned investors on Thursday that a drop in bookings and an increase in cancellations will diminish their expected first-quarter revenue.
"In recent days, the company has experienced a significant decline in customer demand, as well as an increase in trip cancellations," the Dallas-based airline said Thursday in a regulatory filing, citing the spread of coronavirus as a probable cause. Southwest expects a $200-300 million dollar dent, dropping as much as two percent — rather than the 3.5 percent increase of their original forecast.
According to the filing, the unpredictable nature of both the duration and severity of the global pandemic makes the future hard to see. Fortunately for shareholders, Southwest's predominantly domestic income has taken less damage than many of its more internationally-inclined competitors. Still, Southwest fell 4.9 percent to $44.61 on Thursday morning, with shares down about 13 percent for the year.
"The stocks right now are caught between a spreading virus of unknown duration and the potential of an economic slowdown of unknown proportions," Bernstein analyst David Vernon wrote in a note to investors cutting Southwest's target price from $61 to $55.
Southwest CEO Gary Kelly lamented the "very noticeable, precipitous decline in bookings" in an interview with CNBC's Phil LeBeau on Thursday. "It's really all of a sudden," he said. When LaBeau asked whether Southwest would consider discounting flights to draw more traffic, Kelly seemed skeptical.
"I don't know that it's a price issue," he said. "The economy is strong. People have money. They have the means to travel and to spend. This is they don't want to fly, for the obvious reason." Specifically, Kelly compared the public's reaction to the terrorist attacks on September 11, 2001.
"9/11 wasn't an economically driven issue for travel – it was more fear, quite frankly," he said. "And I think that's really what's manifested this time. … It has a 9/11-like feel. Hopefully, we'll get this behind us very quickly."
EconomyHealthPoliticsairlinescoronavirusSouthwest Airlinestourismtravel
Hurt: Greatest Political Show on Earth Winds to Spectacular Close
Left Calls for 'Army of Citizen Detectives' to Expose Trump Supporters
Shep Smith: Some Former Fox News Colleagues 'Propagated the Lies'
Watch Live: President Donald Trump's Departure Ceremony
Cuomo: Trump Could Pardon Sheldon Silver as 'Favor for Someone in the Jewish Community'
Pro-Life Black Group Commends Trump: 'You Have Fully Demonstrated Your Commitment to Support Black Life'
GOP Rep. Cawthorn: America Should Not Become 'Used to,' 'Desensitized' to Washington, DC 'Police State'

redpajama_set_name: RedPajamaCommonCrawl


text:
//
// Copyright (c) 2018 Advanced Micro Devices, Inc. All rights reserved.
//
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to deal
// in the Software without restriction, including without limitation the rights
// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
// copies of the Software, and to permit persons to whom the Software is
// furnished to do so, subject to the following conditions:
//
// The above copyright notice and this permission notice shall be included in
// all copies or substantial portions of the Software.
//
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL THE
// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
// THE SOFTWARE.
//

#include "misc/debug.h"
#include "misc/descriptor_set_create_info.h"
#include "misc/object_tracker.h"
#include "wrappers/descriptor_set.h"
#include "wrappers/descriptor_set_layout.h"
#include "wrappers/descriptor_update_template.h"
#include "wrappers/device.h"
#include "wrappers/physical_device.h"

Anvil::DescriptorUpdateTemplate::DescriptorUpdateTemplate(const Anvil::BaseDevice* in_device_ptr,
                                                          bool                     in_mt_safe)
    :DebugMarkerSupportProvider(in_device_ptr,
                                Anvil::ObjectType::DESCRIPTOR_UPDATE_TEMPLATE),
     MTSafetySupportProvider   (in_mt_safe),
     m_device_ptr              (in_device_ptr),
     m_vk_object               (VK_NULL_HANDLE)
{
    /* Register this instance */
    Anvil::ObjectTracker::get()->register_object(Anvil::ObjectType::DESCRIPTOR_UPDATE_TEMPLATE,
                                                 this);

}

Anvil::DescriptorUpdateTemplate::~DescriptorUpdateTemplate()
{
    if (m_vk_object != VK_NULL_HANDLE)
    {
        const auto& entrypoints = m_device_ptr->get_extension_khr_descriptor_update_template_entrypoints();

        entrypoints.vkDestroyDescriptorUpdateTemplateKHR(m_device_ptr->get_device_vk(),
                                                         m_vk_object,
                                                         nullptr); /* pAllocator */

        m_vk_object = VK_NULL_HANDLE;
    }

    /* Unregister the object */
    Anvil::ObjectTracker::get()->unregister_object(Anvil::ObjectType::DESCRIPTOR_UPDATE_TEMPLATE,
                                                   this);

}

Anvil::DescriptorUpdateTemplateUniquePtr Anvil::DescriptorUpdateTemplate::create_for_descriptor_set_updates(const Anvil::BaseDevice*                    in_device_ptr,
                                                                                const Anvil::DescriptorSetLayout*           in_descriptor_set_layout_ptr,
                                                                                const Anvil::DescriptorUpdateTemplateEntry* in_update_entries_ptr,
                                                                                const uint32_t&                             in_n_update_entries,
                                                                                MTSafety                                    in_mt_safety)
{
    DescriptorUpdateTemplateUniquePtr result_ptr(nullptr,
                                                 std::default_delete<Anvil::DescriptorUpdateTemplate>() );

    result_ptr.reset(
        new DescriptorUpdateTemplate(in_device_ptr,
                                     Anvil::Utils::convert_mt_safety_enum_to_boolean(in_mt_safety,
                                                                                in_device_ptr) )
    );

    if (result_ptr != nullptr)
    {
        if (!result_ptr->init(in_descriptor_set_layout_ptr,
                              in_update_entries_ptr,
                              in_n_update_entries) )
        {
            result_ptr.reset();
        }
    }

    return result_ptr;
}

bool Anvil::DescriptorUpdateTemplate::init(const Anvil::DescriptorSetLayout*           in_descriptor_set_layout_ptr,
                                           const Anvil::DescriptorUpdateTemplateEntry* in_update_entries_ptr,
                                           const uint32_t&                             in_n_update_entries)
{
    const Anvil::ExtensionKHRDescriptorUpdateTemplateEntrypoints* entrypoints_ptr = nullptr;
    bool                                                          result          = true;

    if (!m_device_ptr->get_extension_info()->khr_descriptor_update_template() )
    {
        anvil_assert(m_device_ptr->get_extension_info()->khr_descriptor_update_template() );

        result = false;
        goto end;
    }

    if (in_descriptor_set_layout_ptr == nullptr)
    {
        anvil_assert(in_descriptor_set_layout_ptr != nullptr);

        result = false;
        goto end;
    }

    if (in_n_update_entries == 0)
    {
        anvil_assert(in_n_update_entries != 0);

        result = false;
        goto end;
    }

    if (in_update_entries_ptr == nullptr)
    {
        anvil_assert(in_update_entries_ptr != nullptr);

        result = false;
        goto end;
    }

    entrypoints_ptr = &m_device_ptr->get_extension_khr_descriptor_update_template_entrypoints();

    if (entrypoints_ptr == nullptr)
    {
        anvil_assert(entrypoints_ptr != nullptr);

        result = false;
        goto end;
    }

    {
        VkDescriptorUpdateTemplateCreateInfoKHR         create_info;
        std::vector<VkDescriptorUpdateTemplateEntryKHR> update_entries(in_n_update_entries);

        for (uint32_t n_update_entry = 0;
                      n_update_entry < in_n_update_entries;
                    ++n_update_entry)
        {
            update_entries.at(n_update_entry) = in_update_entries_ptr[n_update_entry].get_vk_descriptor_update_template_entry_khr();
        }

        create_info.descriptorSetLayout        = in_descriptor_set_layout_ptr->get_layout();
        create_info.descriptorUpdateEntryCount = in_n_update_entries;
        create_info.flags                      = 0;
        create_info.pDescriptorUpdateEntries   = &update_entries.at(0);
        create_info.pipelineBindPoint          = VK_PIPELINE_BIND_POINT_MAX_ENUM;
        create_info.pipelineLayout             = VK_NULL_HANDLE;
        create_info.pNext                      = nullptr;
        create_info.set                        = VK_NULL_HANDLE;
        create_info.sType                      = VK_STRUCTURE_TYPE_DESCRIPTOR_UPDATE_TEMPLATE_CREATE_INFO_KHR;
        create_info.templateType               = VK_DESCRIPTOR_UPDATE_TEMPLATE_TYPE_DESCRIPTOR_SET_KHR;

        in_descriptor_set_layout_ptr->lock();
        {
            result = is_vk_call_successful(entrypoints_ptr->vkCreateDescriptorUpdateTemplateKHR(m_device_ptr->get_device_vk(),
                                                                                &create_info,
                                                                                nullptr, /* pAllocator */
                                                                                &m_vk_object) );
        }
        in_descriptor_set_layout_ptr->unlock();
    }

    if (!result                        ||
         m_vk_object == VK_NULL_HANDLE)
    {
        anvil_assert(result);
        anvil_assert(m_vk_object != VK_NULL_HANDLE);

        result = false;
        goto end;
    }

    set_vk_handle(m_vk_object);

    /* Finally, also cache descriptor set create info using the user-specified DS layout */
    m_ds_create_info_ptr.reset(
        new Anvil::DescriptorSetCreateInfo(*in_descriptor_set_layout_ptr->get_create_info() )
    );

    if (m_ds_create_info_ptr == nullptr)
    {
        anvil_assert(m_ds_create_info_ptr != nullptr);

        result = false;
        goto end;
    }

end:
    return result;
}

void Anvil::DescriptorUpdateTemplate::update_descriptor_set(const Anvil::DescriptorSet* inout_ds_ptr,
                                                            const void*                 in_data_ptr) const
{
    const auto& entrypoints = m_device_ptr->get_extension_khr_descriptor_update_template_entrypoints();

    if (in_data_ptr == nullptr)
    {
        anvil_assert(in_data_ptr != nullptr);

        goto end;
    }

    #ifdef _DEBUG
    {
        if (!(*inout_ds_ptr->get_descriptor_set_layout()->get_create_info() == *m_ds_create_info_ptr) )
        {
            anvil_assert_fail();

            goto end;
        }
    }
    #endif

    inout_ds_ptr->lock();
    lock();
    {
        entrypoints.vkUpdateDescriptorSetWithTemplateKHR(m_device_ptr->get_device_vk(),
                                                         inout_ds_ptr->get_descriptor_set_vk(),
                                                         m_vk_object,
                                                         in_data_ptr);
    }
    unlock();
    inout_ds_ptr->unlock();

end:
    ;
}

redpajama_set_name: RedPajamaGithub


text:
Elon Musk Writes "Bitcoin" to his Twitter Account
Elon Musk, the richest man in the world, wrote "Bitcoin" in the statement part of his Twitter account after his tweets about stocks, and the price of BTC increased from 32 thousand dollars to 37 thousand dollars in minutes. In addition, Musk, in the last tweet he shared, "In retrospect, this is inevitable." gave his statement.
Record USDT Entry To Exchanges
After Bitcoin, which became active after Elon Musk's move, a large amount of Tether entered the stock markets within 1 hour. The USDT entry worth $ 330 million is an indicator of the buying appetite for the cryptocurrency market.
Visa Can Run Cryptocurrencies On Its Own Network
The CEO of San Francisco-based payment giant Visa said in a statement that he sees Bitcoin and other cryptocurrencies as "digital gold". In the next step, he stated that they can use Bitcoin as one of the payment methods along with 160 other fiat currencies.
Tendency to Crypto Currency Exchanges Increases
As the interest in bitcoin and cryptocurrencies increases, more and more people are turning to invest. For this reason, cryptocurreny exchanges are also very popular because they are the most preferred platforms to buy and sell cryptocurrency
MicroStrategy Seeks to Increase BTC Assets
The giant business intelligence company MicroStrategy signaled that it could buy BTC again in its fourth quarter report. The company, which has a total of 70 thousand 784 Bitcoin assets, stated that they want to keep their Bitcoins and invest more Bitcoin in the future. Announcing that it is developing new strategies to buy Bitcoin, MicroStrategy's conference on February 3-4 is eagerly awaited.
Bitcoin Market Volume Rises Again
Bitcoin entered the top 10 again in the list where assets are listed according to market volume. Thus, it surpassed the eleventh place Taiwan Semiconductor. After its rapid rise of 5 thousand dollars, it increased its dominance from 62.6% in the morning hours to 64.2% and the market volume increased to the level of 685 trillion dollars.
Ripple Submits Report to Court
Ripple has compiled a detailed report that disproves all the reasons the SEC used to judge XRP as a security. Then XRP prices saw an increase of over 60%. Although the main reason for this increase is not known yet, the trade volume of XRP has increased from $ 4 billion to $ 12 billion in a very short time. In Turkey "Ripple" and "XRP" On January 30 the volume of searches for words broke the record of seven days.
Ripple Stands Out With New Deals
Francisco-based blockchain company Ripple has invested in MoneyTap, a subsidiary of Japanese financial giant SBI Holdings. The MoneyTap app, powered by the RippleNet network, is expected to connect to 20 banking institutions by the end of 2021. By the end of February, three more banks are expected to come into play.
Bitcoin is priced around $ 33,800 on the first day of the new week. Last week, the positions opened against hedge funds with the organization of the Gamestock share in the forums in the USA and this revolt movement was also reflected in crypto currencies, and on the same day, Bitcoin rose above $ 38,000. For the future, BTC's dominance continues to lag behind 63%. There is no significant increase in the number of new and active addresses. However, there is an increase in the amount of BTC withdrawn from the stock markets. Does this situation set new records? Weak possibility but may support intraday movements into the $ 38,000 zone. BTC's daily volatility has increased to 3.5%. Therefore, when determining take profit and stop loss levels, daily and 30-day volatility should be considered.
When we consider BTC / USD technically, the fact that it has been priced behind the 30-day moving average in the last two weeks does not present a strong view. In order for the purchases to strengthen, the average level of $ 35,000 must be broken. On the other hand, the MACD and momentum indicators also give negative mismatch in the 4-hour period, with the $ 31,500 level as sub-support. For this reason, it is useful to pay attention to buying from high levels while there is negative mismatch and below the average in Bitcoin. The view is horizontal. However, with the outlook that finds support, we keep our view of being positive in Bitcoin and evaluating pullbacks.
Ethereum held a slightly sideways trend this morning while holding above the $ 1300 level. Although it draws attention with its technical appearance, Ethereum's on chain data is also remarkable and at a point that can support the course in the coming days. There is a rapid withdrawal in the amount of ETH withdrawn from the exchanges in the last 1.5 weeks. There are also positive signals in the changes in the number of active and new addresses in on chain data. Ethereum is presenting a positive fundamental picture in the current moment. There was also a move in favor of BTC in the ETH / BTC clipper. However, in this shear, we maintain our view that movements towards BTC should be evaluated in favor of ETH.
When we consider the ETH / USD parity; The recovery in the lows of the last month and the highs remaining stuck at around $ 1440 offer a rising triangle outlook. In this view, we think that the rises may accelerate after the breaks and this break can be activated after the $ 1140 level is exceeded. Considering the on chain data and technical outlook, we see that the $ 1500 scenario gets stronger. With this view also supported by momentum, the $ 1285 levels are in the major support position in pullbacks.
The AVAX / USD pair retreated by 2% this morning, pricing at $ 13.18. The descending channel (blue channel), which started on January 17, was broken with the last movement and ended its effect. This was a sign that the selling pressure on prices was lessening, and it rose rapidly by 25% as it broke up the upper band of the channel at $ 12.00. Subsequent drawdowns brought AVAX back below $ 13,450. With the weakening price momentum, if the downward position continues, the $ 11.80 support may be raised. Staying above $ 13.50 could set new records, but the idle period for a while seems more likely for now. The increase in the sales volume after the record of $ 15.20 indicates that sales at high prices suppress the parity. Still, the outlook is positive.
SUPPORTS 11,7227 / 10,3764 / 8,5514
RESISTANCES 14,8940 / 16,7190 / 18,0653
Ripple is the most positively differentiated crypto currency compared to other crypto currencies, with a 16% increase this morning. Since its lawsuit with the SEC, Ripple has made many statements defending the falsehood of these allegations, but it has not been able to relieve XRP from the selling pressure, most importantly because it has submitted official documents that will comfort XRP investors. A day before XRP's increase of up to 60%, Ripple submitted its defense report on the lawsuit with the SEC. On the other hand, it is said that there are organizations to increase XRP prices on many platforms. The alleged 55,000-person Telegram groups have too few investors to achieve a 60% increase on their own, considering Jed McCaleb, who sold $ 1.3 billion in just one day. Still, it is possible that it triggered prices, but it's hard to be the only reason. As we have stated in our newsletters and Crypto Zoom publications many times, we have emphasized that the macro support for XRP, which has been at the bottom for a long time after the pricing of the worst story that could happen, could easily carry it to $ 0.50 and above.
When the XRP / USD parity is examined technically, the target of $ 0.50 was realized with a positive development to be obtained from the data flow of the recovered lows and the created double bottom formation. We can see that it becomes more volatile in the next period. Therefore, it would be more correct to wait for their retracement in XRP. Therefore, caution should be exercised in XRP transactions. As the February 22 litigation deadline approaches, we can see more volatile price levels. The $ 0.46 level is the starting point of the move and our main support level.
Litecoin is priced at $ 130.00, with a horizontal change on the first day of the week. Looking at monthly returns, almost all cryptocurrencies except Litecoin performed well in the first month of 2021, while LTC remained at -4% in monthly returns. However, while it is said that the new update will be made in February, this situation provides a basic story and leads to the preservation of its potential. On the other hand, Grayscale has been expanding its Litecoin Trust fund by adding 25,500 to its LTC assets last week.
When the LTC / USD parity is analyzed technically, it is observed that the horizontal view is preserved. The levels of the Fibonacci retracements are working as resistance and support levels in the $ 122.30 and $ 145.15 horizontal band. Although the peaks are falling with prices that have been weakening since mid-January, the lows are maintained. This actually created a triangular appearance and we have approached the tip of the triangle, that is, after the compression. These regions and the continuation of the compression may create sudden price movements in the extreme regions of the triangle. With the break above the $ 145.80 level, the upward trend could be increased. The view is horizontal for now.
Chainlink is pricing at $ 22.46 this morning with a horizontal percentage change. While we witness that altcoins, which are moving successively, are increasing day by day, this is also very positive for LINK, which is the largest DeFi token in terms of market value. The rapid increase of some stocks, as well as some cryptocurrencies, which has been observed for a long time by organizing thousands of investors on online chat platforms, is unusual. Likewise, considering that DeFi, with its name of decentralized finance, has all the functionality of today's financial system, the increasing mass in this direction may increase the demand for Chainlink. In-chain data shows that the amount of LINK held in stock exchanges is at the lowest level of the last month. In addition, the level of transfers to stock exchanges has dropped to the lowest level in the last three months. The decrease in the amount of LINK ready for sale on the exchanges indicates that the LINKs in cold - hot wallets are increasing and are being kept in line with long-term expectations.
When the LINK / USD parity is considered technically, it is seen that it remains in the bullish channel. So much so that in the last withdrawal, the sub-support of this channel was tested and a hold was achieved above it. The subchannel also coincides with the midpoint of the daily Bollinger bands. Therefore, it is holding at $ 21.60 both in the middle-upper band region where purchases are accelerated, and in the upper middle zone of Bollinger. All of this data can move LINK to the channel midband of $ 25.80, indicating a 15% movement potential. Although the outlook has been horizontal for the past few days, it is within the rising channel and positive in the general frame.
The BAT / USD pair is down 2.5% this morning, pricing around $ 0.2960. BAT's double bottom formation target is now $ 0.3820, rising above the neckline of $ 0.2785, despite a 15% retracement after testing the $ 0.3410 level. The target price scenario will be preserved as long as we go below the neckline. This indicates that it has a potential close to 30% over its level. The parabolic trend created in the technical table represents that the lows remaining at higher levels show a more accelerated increase compared to the linear upward trend. Continuing the rise on the parabolic trend, the $ 0.3410 level in the Fibo'61.80 retracement zone will be the initial resistance and there is no further resistance until the formation target is crossed. The rises are supported by volume, the outlook is very positive.


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Q: Trying to parse Word Documents and getting PdfReadError: EOF marker not found I am testing some Python code to loop through resumes, open each, parse each, and create a comprehensive report based on the contents of each resume.  Here is the code that I am running.
#importing all required libraries

import PyPDF2
import os
from os import listdir
from os.path import isfile, join
from io import StringIO
import pandas as pd
from collections import Counter
import en_core_web_sm
nlp = en_core_web_sm.load()
from spacy.matcher import PhraseMatcher

#Function to read resumes from the folder one by one
mypath='C:\\path_to_resumes\\' #enter your path here where you saved the resumes
onlyfiles = [os.path.join(mypath, f) for f in os.listdir(mypath) if os.path.isfile(os.path.join(mypath, f))]

def pdfextract(file):
    fileReader = PyPDF2.PdfFileReader(open(file,'rb'))
    countpage = fileReader.getNumPages()
    count = 0
    text = []
    while count < countpage:
        pageObj = fileReader.getPage(count)
        count +=1
        t = pageObj.extractText()
        print (t)
        text.append(t)
    return text

#function to read resume ends

#function that does phrase matching and builds a candidate profile
def create_profile(file):
    text = pdfextract(file)
    text = str(text)
    text = text.replace("\\n", "")
    text = text.lower()
    #below is the csv where we have all the keywords, you can customize your own
    keyword_dict = pd.read_csv('D:/NLP_Resume/resume/template_new.csv')
    stats_words = [nlp(text) for text in keyword_dict['Statistics'].dropna(axis = 0)]
    NLP_words = [nlp(text) for text in keyword_dict['NLP'].dropna(axis = 0)]
    ML_words = [nlp(text) for text in keyword_dict['Machine Learning'].dropna(axis = 0)]
    DL_words = [nlp(text) for text in keyword_dict['Deep Learning'].dropna(axis = 0)]
    R_words = [nlp(text) for text in keyword_dict['R Language'].dropna(axis = 0)]
    python_words = [nlp(text) for text in keyword_dict['Python Language'].dropna(axis = 0)]
    Data_Engineering_words = [nlp(text) for text in keyword_dict['Data Engineering'].dropna(axis = 0)]

    matcher = PhraseMatcher(nlp.vocab)
    matcher.add('Stats', None, *stats_words)
    matcher.add('NLP', None, *NLP_words)
    matcher.add('ML', None, *ML_words)
    matcher.add('DL', None, *DL_words)
    matcher.add('R', None, *R_words)
    matcher.add('Python', None, *python_words)
    matcher.add('DE', None, *Data_Engineering_words)
    doc = nlp(text)

    d = []
    matches = matcher(doc)
    for match_id, start, end in matches:
        rule_id = nlp.vocab.strings[match_id]  # get the unicode ID, i.e. 'COLOR'
        span = doc[start : end]  # get the matched slice of the doc
        d.append((rule_id, span.text))
    keywords = "\n".join(f'{i[0]} {i[1]} ({j})' for i,j in Counter(d).items())

    ## convertimg string of keywords to dataframe
    df = pd.read_csv(StringIO(keywords),names = ['Keywords_List'])
    df1 = pd.DataFrame(df.Keywords_List.str.split(' ',1).tolist(),columns = ['Subject','Keyword'])
    df2 = pd.DataFrame(df1.Keyword.str.split('(',1).tolist(),columns = ['Keyword', 'Count'])
    df3 = pd.concat([df1['Subject'],df2['Keyword'], df2['Count']], axis =1)
    df3['Count'] = df3['Count'].apply(lambda x: x.rstrip(")"))

    base = os.path.basename(file)
    filename = os.path.splitext(base)[0]

    name = filename.split('_')
    name2 = name[0]
    name2 = name2.lower()
    ## converting str to dataframe
    name3 = pd.read_csv(StringIO(name2),names = ['Candidate Name'])

    dataf = pd.concat([name3['Candidate Name'], df3['Subject'], df3['Keyword'], df3['Count']], axis = 1)
    dataf['Candidate Name'].fillna(dataf['Candidate Name'].iloc[0], inplace = True)

    return(dataf)

#function ends

#code to execute/call the above functions

final_database=pd.DataFrame()
i = 0
while i < len(onlyfiles):
    file = onlyfiles[i]
    dat = create_profile(file)
    final_database = final_database.append(dat)
    i +=1
    print(final_database)

#code to count words under each category and visulaize it through Matplotlib

final_database2 = final_database['Keyword'].groupby([final_database['Candidate Name'], final_database['Subject']]).count().unstack()
final_database2.reset_index(inplace = True)
final_database2.fillna(0,inplace=True)
new_data = final_database2.iloc[:,1:]
new_data.index = final_database2['Candidate Name']
#execute the below line if you want to see the candidate profile in a csv format
#sample2=new_data.to_csv('sample.csv')
import matplotlib.pyplot as plt
plt.rcParams.update({'font.size': 10})
ax = new_data.plot.barh(title="Resume keywords by category", legend=False, figsize=(25,7), stacked=True)
labels = []
for j in new_data.columns:
    for i in new_data.index:
        label = str(j)+": " + str(new_data.loc[i][j])
        labels.append(label)
patches = ax.patches
for label, rect in zip(labels, patches):
    width = rect.get_width()
    if width > 0:
        x = rect.get_x()
        y = rect.get_y()
        height = rect.get_height()
        ax.text(x + width/2., y + height/2., label, ha='center', va='center')
plt.show()

In the folder, I have '.doc' and '.docx' files.  Everything seems to work fine, up until this point, directly below.  When I get here, the code throws an error.  Here is the troublesome code.  The weird thing is, that it looks like some kind of PDF error, but I'm iterating only through '.doc' and '.docx' files.
final_database=pd.DataFrame()
i = 0
while i < len(onlyfiles):
    file = onlyfiles[i]
    dat = create_profile(file)
    final_database = final_database.append(dat)
    i +=1
    print(final_database)

Here is the StackTrace:
Traceback (most recent call last):

  File "<ipython-input-2-c63fca79d39f>", line 5, in <module>
    dat = create_profile(file)

  File "<ipython-input-1-cdc3bf75cd26>", line 34, in create_profile
    text = pdfextract(file)

  File "<ipython-input-1-cdc3bf75cd26>", line 17, in pdfextract
    fileReader = PyPDF2.PdfFileReader(open(file,'rb'))

  File "C:\Users\ryans\Anaconda3\lib\site-packages\PyPDF2\pdf.py", line 1084, in __init__
    self.read(stream)

  File "C:\Users\ryans\Anaconda3\lib\site-packages\PyPDF2\pdf.py", line 1696, in read
    raise utils.PdfReadError("EOF marker not found")

PdfReadError: EOF marker not found

The code comes from here.
https://towardsdatascience.com/do-the-keywords-in-your-resume-aptly-represent-what-type-of-data-scientist-you-are-59134105ba0d

A: You are using package PyPDF2, which is used to read and manipulate pdf files. In the article from towardsdatascience that you mentioned all resumes that author was working on were in pdf format.
Maybe if your resumes are in doc/docx format you should explore python-docx library:
https://python-docx.readthedocs.io/en/latest/index.html

redpajama_set_name: RedPajamaStackExchange


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text:
Insurgency, Fraud Pose Risks For Credible Nigerian Election
Nigeria has made an effort to clean up voter registration for elections next February, but holding a credible poll is a daunting prospect amid chaotic distribution of ballot cards and an Islamist insurgency that could disenfranchise millions.
Nigeria's last presidential poll in 2011 was deemed the cleanest to date in Africa's most populous nation, but since previous elections had been characterized by ballot box snatching, intimidation of voters by armed thugs and completely made up results, this was a modest achievement.
The election will test whether Africa's biggest economy can improve its patchy record on democracy.
"Looking at overt, simple forms of election manipulation, in 2011, there was a decrease and we think … that trajectory is going to continue," Thomas Hansen of Control Risks says.
Yet questions remain over whether the coming elections will actually continue that trajectory.
The race largely between President Goodluck Jonathan and former military ruler Muhammadu Buhari on Feb. 14 is expected to be Nigeria's most closely fought since the end of military rule in 1999, which will encourage both to play dirty.
A violent Islamist Boko Haram insurgency that has killed thousands will make voting almost impossible in swathes of the northeast, possibly disenfranchising millions.
New technology, such as biometric I.D. card readers, should make ballot box stuffing harder. But glitches have caused hundreds of thousands of voters to be struck out.
TEST FOR NIGERIA
The election must be seen as credible to avoid violence by the losing side. In 2011, 800 people were killed after Buhari lost to Jonathan.
The growing polarization of Nigeria between the largely Muslim north and majority Christian parts of the south, and ugly rhetoric on both sides, send ominous signals.
"The demonization of the opponent, the threats of violence, the accusations of plans to rig the election, the whipping up of ethnic and religious sentiments. The clouds are indeed dark," wrote Azuka Onwuka in The Punch daily this month.
When Jonathan ran in 2011, northern elites said he scrapped an unwritten deal to rotate power between north and south every two terms. Amid the heightened tension, parties could use minor irregularities as an excuse to whip up violence.
Three states in the northeast under a state of emergency will be too dangerous for most election observers.
There are more than a million Boko Haram displaced who cannot vote unless the law changes to allow them to do so away from home, a move Parliament is considering.
Borno electoral commissioner Tukur Saad said the state had registered 11 camps for refugees, but many more were unregistered in schools and mosques.
Since many displaced did not take their voting cards when they fled, they may be unable to vote.
"Creating polling units in camps does not mean people will not be disenfranchised," said Idayat Hassan of the Abuja-based Centre for Democracy and Development. "How many will actually have identification of any form with them?"
Insecurity will prevent voting in many places. Most of Borno's 1.76 million voters won't be able to vote.
"It's a very tricky situation … We may only be able to hold the vote for … 600,000 voters," Saad told Reuters.
TECHNICAL 'GLITCHES'
The electoral commission has culled duplicates and fake names from the register in order to issue biometric voter cards, in a bid to curb practices like ballot box stuffing.
But 11.5 million people were, in some cases wrongly, struck off the list this year, electoral commission (INEC) spokesman Kayode Idowu said, owing to data collection problems.
The total voter count fell to 58.9 million, from 70.4 million at the end of 2013. Voters wrongfully removed will have to queue up to re-register. Some won't bother.
The fact that many were in strongholds of the opposition All Progressives Congress (APC), such as Lagos, rather than those of the ruling People's Democratic Party (PDP), angered the opposition.
"I am worried this is the beginning of a plan to
disenfranchise Lagosians," Lagos state governor Babatunde Fashola, himself stuck off the list, said last month.
Another worry for election observers is whether the card readers will be deployed in time and if they will work.
INEC says it anticipates the inevitable failure of some readers so extras will be supplied. The readers will run on batteries to escape frequent power cuts.
Idowu said that if a machine fails and a replacement is unavailable, the election will be delayed in that area. That would draw out an already fraught process.
In the Niger Delta, Jonathan's home region, a history of political thuggery looks set to continue.
Two security sources say large amounts of weapons are being imported into the region. In past polls, militias carved out areas where they controlled voting. That could happen again.


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text:
Budo Banter
Styles I Train
Styles & Techniques
Random Rantings
Tournaments Must Be Well-Organized
I check a participant's name in the category list
Last weekend, I was Tatami Manager at an open Karate tournament. The competition was for both kata and kumite The turnout was massive. Male and female participants of all ages, of various nationalities and from so many different styles and dojos from across the country.
It should have been an active, fun day of competition, with adrenaline flowing off the tatami and onto the medals' platform. The adrenaline was there. But I saw more of it from concerned, angry and frustrated coaches and parents off the tatami than from the competition arena.
With good reason, too! Kids who had been there since as early as 7:30 a.m. were still waiting for their event to be announced 12 hours later! The P. A. system was in audible at the galleries. People were asked (via the same P. A. system!) to leave the competition area and wait in the galleries till their event is announced. But nobody was actually there to usher them out; or back in, for that matter. There was no actual schedule of events.
Modifying rules, changing match times, and generally being a little flexible to ensure a smooth and quick competition are all acceptable practices. What is not, however, is a general lack of preparation. When organizing a tournament, it must be planned and scheduled to, first and foremost, finish at a reasonable hour. Everything from manpower requirements to refreshments; evaluation systems to appeals desk; and a pre-determined sequence of events; should be made available.
As martial artists, we should lead by example in being systematic and organized, and paying attention to details in every endeavour. That should also extend to event planning and management.