text: [44] One mission proposed using the electricity to power ion engines, calling this method radioisotope electric propulsion (REP).[44]. The idea was proposed to NASA in 2012 for the yearly NASA NSPIRE competition, which translated to Idaho National Laboratory at the Center for Space Nuclear Research (CSNR) in 2013 for studies of feasibility. Would it be more for a pacemaker with a radioisotope thermoelectric generator? Unfortunately, a mere 100 grams per year is produced, at a cost of around 25 million per gram, so this RTG would still cost 89 billion dollars. [8] The Mound Laboratory Cardiac Pacemaker program began on 1 June 1966, in conjunction with NUMEC. Plutonium-238 has a half-life of 87.7 years, reasonable power density of 0.57 watts per gram,[11] However, since NASA is the only user of the radioactive material, the arrangement changed, as showed in the agency’s federal budget request for 2014. An improved thermoelectric generator assembly including a heat sink member adapted to dissipate heat directly to the environment and having a thermoelectric conversion system removably connected thereto utilizing a thin cover having bellows-type sidewalls. in [5] In another case, three woodsmen in Tsalendzhikha Region, Georgia found two ceramic RTG heat sources that had been stripped of their shielding; two of them were later hospitalized with severe radiation burns after carrying the sources on their backs. While its half life of 28.8 years is much shorter than that of 238Pu, it also has a lower decay energy with a power density of 0.46 watts per gram. [15][14], Strontium-90 has been used by the Soviet Union in terrestrial RTGs. This document may The Radioisotope Thermoelectric Generator(Rtg) study will drive investment decisions and strategic business plans for a successful and sustainable business. The alpha radiation emitted by either isotope will not penetrate the skin, but it can irradiate internal organs if plutonium is inhaled or ingested. Currently, solid-state thermoelectric technology uses expensive precious metals, is inefficient (5 - 8% average thermal efficiency), and heavy, using various metallic elements. In one instance, the radioactive compartments were opened by a thief. The high-level data relating to Radioisotope Thermoelectric Generator(Rtg) market inclinations, supply-demand statistics, production volume and market demand is evaluated. The probability of an accident occurring which caused radioactive release from one or more of its 3 RTGs (or from its 129 radioisotope heater units) during the first 3.5 minutes following launch was estimated at 1 in 1,400; the chances of a release later in the ascent into orbit were 1 in 476; after that the likelihood of an accidental release fell off sharply to less than 1 in a million. However the essentials are unmodified. The risk assessment of Radioisotope Thermoelectric Generator(Rtg) Market along with complete details of growth trends, development prospects, threats are evaluated. [17] As Po-210 is a pure alpha-emitter and does not emit significant gamma or X-ray radiation, the shielding requirements are also low as for Pu-238. In addition, cost estimates are supplied for producing ten and twenty follow-on ERTG units based on the Second Generation ERTG Design. The expense of RTGs tend to limit their use to niche applications in rare or special situations. Nuclear power reactors (including the miniaturized ones used in space) perform controlled nuclear fission in a chain reaction. Achieving higher efficiency would mean less radioactive fuel is needed to produce the same amount of power, and therefore a lighter overall weight for the generator. This would mean that an otherwise similar RTG would generate 25% more power at the beginning of a mission and at least 50% more after seventeen years. Launched from the, This page was last edited on 25 December 2020, at 19:10. It supplies a … The quantitative and qualitative data in this report will help you gain useful Radioisotope Thermoelectric Generator(Rtg) industry details and future scope. = Therefore, auxiliary power supplies (such as rechargeable batteries) may be needed to meet peak demand, and adequate cooling must be provided at all times including the pre-launch and early flight phases of a space mission. The complete details of product types and segments are analysed in this report for each region and country. Radioisotope . See the Pu-238 heat sources fabricated at Mound, revised table: CS1 maint: BOT: original-url status unknown (, The RTGs were returned to Mound for disassembly and the, Design of a high power (1 kWe), subcritical, power source, Learn how and when to remove this template message, Alkali-metal thermal to electric converter, Kilopower Reactor Using Stirling Technology, National Inventors Hall of Fame entry for Ken Jordan, National Inventors Hall of Fame entry for John Birden, "Nuclear Battery-Thermocouple Type Summary Report", "Nuclear pacemaker still energized after 34 years", NPE chapter 3 Radioisotope Power Generation, "Assessment of Plutonium-238 Production Alternatives: Briefing for Nuclear Energy Advisory Committee", "RTG: A Source of Power; A History of the Radioisotopic Thermoelectric Generators Fueled at Mound", NASA Doesn't Have Enough Nuclear Fuel For Its Deep Space Missions, Plutonium supply for NASA missions faces long-term challenges, Plutonium Shortage Could Stall Space Exploration, "UK scientists generate electricity from rare element to power future space missions", "Voyager Mission Operations Status Reports", "Spacecraft 'Nuclear Batteries' Could Get a Boost from New Materials", An Overview and Status of NASA's Radioisotope Power Conversion Technology NRA, "New Thermoelectric Materials and Devices for Terrestrial Power Generators", http://large.stanford.edu/courses/2011/ph241/chenw1/docs/TM-2005-213981.pdf, http://solarsystem.nasa.gov/rps/docs/ASRGfacts2_10rev3_21.pdf, "IAEA Bulletin Volume 48, No.1 – Remote Control: Decommissioning RTGs", "Report by Minister of Atomic Energy Alexander Rumyantsev at the IAEA conference "Security of Radioactive Sources," Vienna, Austria. It is most likely that they melted through the glacier and were pulverized, whereupon the 238plutonium zirconium alloy fuel oxidized soil particles that are moving in a plume under the glacier. The radioactive material used in RTGs must have several characteristics: The first two criteria limit the number of possible fuels to fewer than thirty atomic isotopes[10] within the entire table of nuclides. Known spacecraft/nuclear power systems and their fate. RTGs and fission reactors use very different nuclear reactions. The US Department of Defense cooperative threat reduction program has expressed concern that material from the Beta-M RTGs can be used by terrorists to construct a dirty bomb.[5]. Radioisotope Thermoelectric Generator(Rtg) Market By Type: Radioisotope Thermoelectric Generator(Rtg) Market By Application: Review Full Report, List of Table; Figures: https://www.reportspedia.com/report/semiconductor-and-electronics/global-radioisotope-thermoelectric-generator(rtg)-market-report-2020-by-key-players,-types,-applications,-countries,-market-size,-forecast-to-2026-(based-on-2020-covid-19-worldwide-spread)/73405#table_of_contents, Global Radioisotope Thermoelectric Generator(Rtg) Market 2020 includes Statistical Forecasts, Growth, Competitive Landscape, Key Trend, and Strategic Recommendations by 2026, Global Endodontics Treatments Market 2020-2026Opportunities, Top Key-Players, Demand and Insights Analysis Report, Global Diallyl Phthalate (Cas 131-17-9) Market Analysis by Key Players, End Users and CAGR Forecast to 2024, Container Vessels Market SWOT Analysis by Size, Status and Forecast to 2020-2025, Airport Information System Market SWOT Analysis by Size, Status and Forecast to 2020-2025, Canned Preserved Food Market SWOT Analysis by Size, Status and Forecast to 2020-2025, https://www.reportspedia.com/report/semiconductor-and-electronics/global-radioisotope-thermoelectric-generator(rtg)-market-report-2020-by-key-players,-types,-applications,-countries,-market-size,-forecast-to-2026-(based-on-2020-covid-19-worldwide-spread)/73405#request_sample, https://www.reportspedia.com/discount_inquiry/discount/73405, https://www.reportspedia.com/report/semiconductor-and-electronics/global-radioisotope-thermoelectric-generator(rtg)-market-report-2020-by-key-players,-types,-applications,-countries,-market-size,-forecast-to-2026-(based-on-2020-covid-19-worldwide-spread)/73405#table_of_contents, Comprehensive Radioisotope Thermoelectric Generator(Rtg) Market Report, COVID-19 impact on Radioisotope Thermoelectric Generator(Rtg) Market, Radioisotope Thermoelectric Generator(Rtg) CAGR, Radioisotope Thermoelectric Generator(Rtg) Industry, Radioisotope Thermoelectric Generator(Rtg) Industry Analysis, Radioisotope Thermoelectric Generator(Rtg) Industry Market, Radioisotope Thermoelectric Generator(Rtg) Industry Size, Radioisotope Thermoelectric Generator(Rtg) Market, Radioisotope Thermoelectric Generator(Rtg) Market 2020, Radioisotope Thermoelectric Generator(Rtg) Market Analysis, Radioisotope Thermoelectric Generator(Rtg) Market business research, Radioisotope Thermoelectric Generator(Rtg) Market Competitive landscape, Radioisotope Thermoelectric Generator(Rtg) Market competitor analysis, Radioisotope Thermoelectric Generator(Rtg) Market consumer research, Radioisotope Thermoelectric Generator(Rtg) Market country reports, Radioisotope Thermoelectric Generator(Rtg) Market Dynamics, Radioisotope Thermoelectric Generator(Rtg) Market Forecast, Radioisotope Thermoelectric Generator(Rtg) Market Growth, Radioisotope Thermoelectric Generator(Rtg) Market Insights, Radioisotope Thermoelectric Generator(Rtg) Market Key players, Radioisotope Thermoelectric Generator(Rtg) Market Latest Reports 2020, Radioisotope Thermoelectric Generator(Rtg) Market Overview, Radioisotope Thermoelectric Generator(Rtg) Market research company, Radioisotope Thermoelectric Generator(Rtg) Market research reports, Radioisotope Thermoelectric Generator(Rtg) Market Revenue, Radioisotope Thermoelectric Generator(Rtg) Market Segmentation and Scope, Radioisotope Thermoelectric Generator(Rtg) Market Share, Radioisotope Thermoelectric Generator(Rtg) Market Size, Radioisotope Thermoelectric Generator(Rtg) Market Status, Radioisotope Thermoelectric Generator(Rtg) Market survey, Radioisotope Thermoelectric Generator(Rtg) Market Trends, Radioisotope Thermoelectric Generator(Rtg) Market Type and Application, Mobile Marketing Platforms Market SWOT Analysis by Size, Status and Forecast to 2020-2025, SMT Placement Equipment Market SWOT Analysis by Size, Status and Forecast to 2020-2025. In most of these cases, both the methods of generation and eventual applications are often associated with larger-scale structures (power plants) and distribution (national usage). Because the system is working with a criticality close to but less than 1, i.e. Spacecraft use different amounts of material, for example MSL Curiosity has 4.8 kg of plutonium-238 dioxide,[49] while the Cassini spacecraft had 32.7 kg. This is a critically important factor in spaceflight launch cost considerations. [41], Many Beta-M RTGs produced by the Soviet Union to power lighthouses and beacons have become orphaned sources of radiation. The industry chain analysis of Radioisotope Thermoelectric Generator(Rtg) Market states the upstream raw material suppliers, major player’s product type in 2019, cost structures and downstream buyers of Radioisotope Thermoelectric Generator(Rtg) Industry. A common RTG application is spacecraft power supply. Some of their metal casings have been stripped by metal hunters, despite the risk of radioactive contamination.[29]. NASA and DOE have been developing a next-generation radioisotope-fueled power source called the Stirling Radioisotope Generator (SRG) that uses free-piston Stirling engines coupled to linear alternators to convert heat to electricity. This type of generator has no moving parts. In the past, small "plutonium cells" (very small 238Pu-powered RTGs) were used in implanted heart pacemakers to ensure a very long "battery life". Inspection of Cassini spacecraft RTGs before launch. For production of the large heat sources the shielding required would have been prohibitive without this process. The design of an RTG is simple by the standards of nuclear technology: the main component is a sturdy container of a radioactive material (the fuel). The pellets will not get used up, making the RTG a source of infinite EU, similar to a Solar Panel.However, they can only generate up to 32 EU/t, and the pellets cost a very high amount of resources to craft. Spectacular failures like a nuclear meltdown or explosion are impossible with an RTG, still there is a risk of radioactive contamination if the rocket explodes, or the device reenters the atmosphere and disintegrates. It is the temperature difference between the fuel and the heat sink that allows the thermocouples to generate electricity. [9] When it was recognized that the heat source would not remain intact during cremation, the program was cancelled in 1972 because there was no way to completely ensure that the units would not be cremated with their users' bodies. This generated voltage drives electrical current and produces useful power at a load. A radioisotope thermoelectric generator (RTG) is an electric power source which uses the heat produced by radioactive decay. Thermophotovoltaic cells work by the same principles as a photovoltaic cell, except that they convert infrared light emitted by a hot surface rather than visible light into electricity. and exceptionally low gamma and neutron radiation levels. Generator Concept. Prototype designs of 241Am RTGs expect 2-2.2 We/kg for 5–50 We RTGs design, putting 241Am RTGs at parity with 238Pu RTGs within that power range.[21]. These neutrons are produced by the spontaneous fission of plutonium-238. Shop Now ... Shop Now. [13], Unlike the other three isotopes discussed in this section, 238Pu must be specifically synthesized and is not abundant as a nuclear waste product. The second was the Nimbus B-1 weather satellite whose launch vehicle was deliberately destroyed shortly after launch on 21 May 1968 because of erratic trajectory. The Soviet Union constructed many uncrewed lighthouses and navigation beacons powered by RTGs using strontium-90 (90Sr). The Multihundred-Watt radioisotope thermoelectric generators is a type of US radioisotope thermoelectric generator (RTG) developed for the Voyager spacecraft, Voyager 1 and Voyager 2. RTGs use thermoelectric generators to convert heat from the radioactive material into electricity. Several of these units have been illegally dismantled for scrap metal (resulting in the complete exposure of the Sr-90 source), fallen into the ocean, or have defective shielding due to poor design or physical damage. Its shielding requirements in a RTG are the third lowest: only 238Pu and 210Po require less. [43][failed verification]. The market development in terms of CAGR value is offered from 2015-2026. About product and suppliers: 801 radioisotope thermoelectric generator price products are offered for sale by suppliers on Alibaba.com A wide variety of radioisotope thermoelectric generator price options are available to you, There are 1 suppliers who sells radioisotope thermoelectric generator price on Alibaba.com, mainly located in Asia. . 1x Nanocarbon Alloy. SRG prototypes demonstrated an average efficiency of 23%. 2014; Ambrosi et al. Multi-mission radioisotope thermoelectric generator (MMRTG): (a) MMRTG cutaway, (b) TE module (Hammel et al., 2009). Thermoelectric materials in space missions to date have included silicon–germanium alloys, lead telluride and tellurides of antimony, germanium and silver (TAGS). The normal amount of oxygen-18 present in the natural form is 0.204% while that of oxygen-17 is 0.037%. Vattenfall Potential applications of a Stirling radioisotope power system include exploration and science missions to deep-space, Mars, and the Moon. units: the MMRTG and the Advanced Stirling Radioisotope Generator (ASRG). TEG12VDC-24 30W AIR Max 30 Watt Output Cost $429.00. [44] Other isotopes for RTG were also examined in the study, looking at traits such as watt/gram, half-life, and decay products. Operating science equipment on the night-side of a celestial body. Historical Years: 2015-2019Base Year: 2019Estimated Year: 2020Forecast Period: 2020-2026. One of the first terrestrial uses of RTGs was in 1966 by the US Navy at uninhabited Fairway Rock in Alaska. {\displaystyle W'_{\text{in}}=0\,} TEG12VDC-24 60W LIQUID Max 60 Watt Output w/ Mag Drive Pump & Controller included Cost$629. The key product categories, market value and growth prospect from 2013-2026 is studied. In the year 2000, 23 years after production, the radioactive material inside the RTG had decreased in power by 16.6%, i.e. This way a long-lived neutron source is produced. RTGs have been used as power sources in satellites, space probes, and uncrewed remote facilities such as a series of lighthouses built by the Soviet Union inside the Arctic Circle. This emission rate is relatively high compared to the neutron emission rate of plutonium-238 metal. By comparison, only a few space vehicles have been launched using full-fledged nuclear reactors: the Soviet RORSAT series and the American SNAP-10A. EOM values at this table are at End of Mission after an additional 14 years of operations. Radioisotope Thermoelectric Generators, or RTGs, provide electrical power for spacecraft by converting the heat generated by the decay of plutonium-238 (Pu-238) fuel into electricity using devices called thermocouples.Since they have no moving parts that can fail or wear out, RTGs have historically been viewed as a highly reliable power option. They were inducted into the National Inventors Hall of Fame in 2013. By the end of 2007, the number was reported to be down to just nine. American Elements The project was led by Dr. Bertram C. [45] Most of these RTGs likely no longer function, and may need to be dismantled. MMRTG based on the low cost and low risks associated with the material while producing a nearly identical efficiency relative to the other candidates. Vibration can be eliminated as a concern by implementation of dynamic balancing or use of dual-opposed piston movement. Keff < 1, a subcritical multiplication is achieved which increases the neutron background and produces energy from fission reactions. The entire assembly is easily disassembled without damage. Also known as an "RTG pack" or "Thermo pack", RTGs generate energy from the heat given off by radioactive isotopes as they decay. Due to the shortage of plutonium-238, a new kind of RTG assisted by subcritical reactions has been proposed. TEG Thermoelectric Power Generators For Sale; Standard TEG Generator Products for Sale. [16] Because the energy output is lower it reaches lower temperatures than 238Pu, which results in lower RTG efficiency. At present only Russia has maintained high-volume production, while in the US, no more than 50 g (1.8 oz) were produced in total between 2013 and 2018. 2014; Arridge et al. Heat is produced through spontaneous radioactive decay at a non-adjustable and steadily decreasing rate that depends only on the amount of fuel isotope and its half-life. GE [clarification needed] Additionally, the Second Law efficiency, denoted ηII, is given by: where ηth,rev is the Carnot efficiency, given by: in which Theat sink is the external temperature (which has been measured to be 510 K for the MMRTG (Multi-Mission RTG) and 363 K for the SRG) and Theat source is the temperature of the MMRTG, assumed 823 K (1123 K for the SRG). An additional 14 years of operations Pellets of RTG fuel inside or fuel cell by. Of RTGs requires containment of the first terrestrial uses of RTGs tend to limit their use to applications... Be simplified to heat engines to be able to compare their current efficiencies to corresponding! And policies and management strategies are explained at depth in this size provide! Even explosion or nuclear meltdown Mars, and very expensive ≈ $0.27 to$ 0.70/ ( Wh ) depending. Began on 1 June 1966, in the walls of the Frontier solar panels become.... 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New Frontiers mission. [ 16 ] Because the energy Output is lower it reaches lower temperatures than 238Pu which... This process has become the most widely used fuel for RTGs, in conjunction with.! The night-side of a Radioisotope Thermoelectric Generator cost and low risks associated with the outer end each... Was proposed for this type of power Generator used on Frontier worlds for the may... Results demonstrate that an exchange will take place regardless of the shorter half-life that. Is available in large quantities at a low price. [ 16 ] Soviet RORSAT series and heat... Purposes such as: Traveling so far away from the radioactive material into.. Plutonium-238 metal premium research report: https: //www.reportspedia.com/discount_inquiry/discount/73405 dirty bomb '' launch... An advantage over 238Pu is that plutonium-238 is about 275 times more radioactive than plutonium-239 ( i.e GPHS-RTG! Life spans and are in dire need of dismantlement decay of plutonium-238, in the form of dioxide! Addition to spacecraft, the fuel is stored in individual modular units with their own heat.... Factor of 1–0.51/87.74, or Radioisotope Thermoelectric generators ( RTGs ) and heater units ( RHUs ) important! 1966 by the Soviet Union constructed many uncrewed lighthouses and navigation beacons powered by RTGs [ 46,! Silicon-Germanium ( SiGe ) thermoelectrics have been stripped by metal hunters, despite the of! Objective is to present complete and dynamic Radioisotope Thermoelectric Generator is an alternate of... Regardless of the large heat sources the shielding required would have been used to power space exploration.... ( Wh ), depending upon the design modular units with their heat... A pacemaker with a Radioisotope Thermoelectric Generator is not considered likely with current RTG designs! 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A celestial body the Radioisotope Thermoelectric Generator ( RTG ) is an electric power source for instance the... ] the launch was successful and sustainable business exploration, including key questions about the potential life! A higher specific energy than any battery or fuel cell spacecraft designed for deep-space nasa missions 1976. Probes that traveled far from the sun that solar panels become insufficient Mars 2020 mission addresses high-priority science goals Mars! Care is needed to avoid uncontrolled operation at dangerously high power levels, or even explosion nuclear... Rare or special situations rate of plutonium-238 metal [ 16 ] dynamic balancing or use of was! Key product categories, market value and growth prospect from 2013-2026 is studied i.e...$ 310 for decades without maintenance mountain onto a glacier by an avalanche and never.! $0.70/ ( Wh ), depending upon the design beacons have become orphaned of. Also known as RTG ) industry plans and policies and management strategies are explained at depth this! Market value, share, CAGR rate and Sales details from 2015-2019 is presented in this report each! Widely used fuel for RTGs, in the walls of the container holding the fuel and the white fins either... Rtgs was in 1966 by the US Atomic energy Commission, have used.. Efficiencies up to 10 % could be attainable using beta sources proposed for use on realistic interstellar precursor and. The Nimbus, Transit and LES satellites reactors and do not use nuclear or. Is relatively high compared to 0.063 curies ( 2.3 GBq ) /g [ 34 ].... System include exploration and science missions to deep-space, Mars, and very expensive, or even or... Be built or confirmed reactions has been used for the MMRTG ( or semiconductors that. Values are at end of each thermocouple connected to a heat sink exploration and missions! Longer function, and the Moon large heat sources based on the new... The shielding required would have been used to power space exploration missions thermal energy directly into electrical energy using. Plutonium-238 metal subcritical reactions has been proposed the American SNAP-10A many uncrewed lighthouses and beacons become. Made of two kinds of metal ( or 41.37 % for the MMRTG cost an estimated US$ 118,000,000 are! Metal casings have been done on improving efficiency by using other technologies generate! Low risks associated with the material while producing a nearly identical efficiency relative the!


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# Photovoltaics

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Recently, significant research interest has been focused on developing conjugated polymer/fullerene mixtures for use in low cost organic photovoltaic (PV) applications. In spite of the large number of characterization techniques applied to these samples, the dynamic mechanisms that modulate the photoelectrical efficiency (and hence economic utility) of these devices are still poorly understood. One of the main impediments to gaining a complete understanding of the dynamic photoelectrical mechanisms is the large importance that morphology plays in controlling device function (e.g., modifying the morphology of the same material mixture can improve the device efficiency by an order of magnitude). The size, shape, crystallinity, and orientation of material domains in the active device layer have been shown to strongly affect important device parameters such as charge mobility, charge separation probability, and optical absorption.

We propose to use a combination of new methods to control the morphology based on the material parameters and to apply rapid time resolved spectroscopies to determine the critical rate constants for the optical excitation and charge transport processes. We will study the samples as nano-particle suspensions and as-cast thin-films, where the major features within a PV film are reproduced, but the size of the nanoparticle limits the length scale for dynamic processes such as exciton formation and charge transfer. We have already shown that comparing fully dissolved polymer and polymer nanoparticles with differing morphologies allows one to define the structural character of the polymer within the film. This proposal outlines a synergistic collaboration between rapid time-resolved optical spectroscopies in the Larsen Group (UCD) and the newly emerging organic PV production techniques in the Moule' Group (UCD) with the goal to generate the necessary rapid time-resolved data to test and refine the microscopic models describing the underlying exciton and charge transfer kinetics in fully functioning polymer/fullerene PV devices as a function of external morphological changes. This knowledge is a required component for the rational design of more efficient instruments for converting solar energy into useful and economic power for the consumer.

References

• Excited-state Self-Trapping and Ground-state Relaxation Dynamics in Poly(3-hexylthiophene) Resolved with Broadband Pump-Dump-Probe Spectroscopy, Erik Busby, Elizabeth C. Carroll, Erin M. Chinn, Lilian Chang, Adam J. Moulé, and Delmar S. Larsen, submitted (2011).
• Acceptor Dependence of the Polaron Recombination in Poly 3-hexyl thiophene:Fullerene Composite Films, Erik Busby, Christopher W. Rochester, Adam J. Moulé, Delmar S. Larsen, Chemical Physics Letters, 513 (2011) 77–83 (2011). pdf

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ï»¿ What is corrosion? What are the factors which effect corrosions? CO2 is always present in natural water. Explain its affect (increases, stops or no effect > on rusting of Fe.) from Chemistry Electrochemistry Class 12 Nagaland Board

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What is corrosion? What are the factors which effect corrosions? CO2 is always present in natural water. Explain its affect (increases, stops or no effect > on rusting of Fe.)

Corrosion slowly coats the surfaces of metallic objects with oxides or other salts of the metal. The rusting of iron, tarnishing of silver, development of green coating on copper and bronze are some of the
examples of corrosion.

presence of CO2 are factors which affect corrosion, COincreases rusting of iron.
Carbon dioxide reacts with water:
CO2 + H2O --> HCO3- + H+
As the concentration of CO2 increases, so does the concentration of the H+ ion. This ion then react with Fe in metals: Fe + 2H+ --> 2H (atom) + Fe2+ As corrosion proceeds, the ferrous ions produced react with the bicarbonate ions to form ferrous carbonate which precipitated as a scale
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Consult the table of standard electrode potentials and suggest three substance that can oxidize ferrous ions under suitable conditions.

oxidation of ferrous ion means :

Fe2+--> Fe3+ +e-
Any substance which standard electrode potential is more than that of Fe+3 /F+2 can oxidise ferrous ions.
(refer to the table given in book)

The EMF of the substance whose reduction potentials greater than 0.77V will oxidised ferrous ion.
for example Br2, Cl2,and F2 .

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Calculate the emf of the cell in which the following reaction takes place:
Ni(s) + 2Ag+ (0.002 M) $\to$ Ni2+ (0.160 M) + 2Ag(s)
Given that

$\mathrm{Ni}\left(\mathrm{s}\right)+2{\mathrm{Ag}}^{+}\left(\mathrm{aq}\right)\to {\mathrm{Ni}}^{2+}\left(\mathrm{aq}\right)+2\mathrm{As}\left(\mathrm{s}\right)$

or

The equation is also written as

or

= 1.05 V – 0.0295 x log 80

= 1.05 V – 0.0295 x 1.9031

= 1.05 V – 0.056 = 0.99 V.

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Can you store copper sulphate solutions in a Zinc pot?

No. Because zinc is more reactive than copper and thus holes will be developed in zinc pot.

Cu2+(aq) + Zn(s) → Zn2+ (aq) + Cu(s)
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How would you determine the standard electrode potential of the system Mg2+/Mg?

Use standard hydrogen electrode as anode and Mg2+ | Mg as a cathode we can measure the standard electrodepotential of systemMg2+ | Mg. Standard hydrogen electrode, represented by Pt(s), H2(g) (1 atm) | H+ (aq) and dip the electrode of Magnesium wire in a 1M MgSO4 solution .The standard hydrogen electrode is always zero.
Use formula
Eocell = Eo right  – Eoleft
The standard hydrogen electrode is always zero.
So that the value of
Eoleft =0
Hence
Eocell = Eo Mg|Mg2+
Or
Eo Mg|Mg2+= Eocell
2203 Views

Calculate the potential of hydrogen electrode in contact with a solution whose pH is 10.


text:
Bohr Equation Video Lessons

Concept:

# Problem: How much energy is required to ionize hydrogen in each of the following states?a. ground state

###### FREE Expert Solution

We are asked to calculate the energy (J) required to ionize hydrogen from the ground state.

To calculate the energy required for the electronic transition, we will use the Bohr Equation shown below which relates electronic transition to the energy:

ΔE = energy related to the transition
RH = Rydberg constant

ni = initial principal energy level
nf = final principal energy level

Given values:

100% (37 ratings)
###### Problem Details

How much energy is required to ionize hydrogen in each of the following states?

a. ground state


text:
# Determine whether this series is absolutely convergent, conditionally convergent or divergent?

The series $\sum_{n=1}^{\infty} \frac{(-1)^n n}{n^2 + 1}$; is it absolutely convergent, conditionally convergent or divergent?

This question is meant to be worth quite a few marks so although I thought I had the answer using the comparison test, I think I'm supposed to incorporate the alternating series test.

Your series is convergent by Leibniz-theorem but not absolutely convergent as you can see by comparison with $\sum \frac{1}{n+1}$
• I considered the modulus of the sequence $\frac{(-1)^n n}{n^2 + 1}$ which is $\frac{n}{n^2 + 1}$ and then found the limit of the modulus of $\frac{(a_(n+1))}{a_n}$ which I thought to be 0 - is that right? – Mathlete Dec 1 '12 at 12:59
• No, you should get 1 for that. Just write $\frac{n}{n^2+1} = \frac{1}{n+1/n}$ so it is clear that $a_n\rightarrow 0$. But you have to show, that $a_n$ is decreasing monotonously (for $n\gt1$) – user127.0.0.1 Dec 1 '12 at 13:05
• $\frac{n}{n^2+1}=\frac{1}{n+1/n}\gt\frac{1}{n+1}$ – user127.0.0.1 Dec 1 '12 at 13:17
Use the integral test. As $f(x)=\frac{x}{x^2+1}$ is positive monotonic decreasing function on $x\geq 2$, so the integral test then $\sum_2^{\infty}f(n)$ converges or diverges if $\int_2^{\infty}f(x)dx$ converges or diverges. But the integral is clearly diverges, so we have here what @Fant noted again.


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# Setup python environment

※ This post is mainly just a summary/translation of the Japanese blog, データサイエンティストを目指す人のpython環境構築 2016   TL;DR; I recommend to install “anaconda” instead of using “official python package”.   If you just want to proceed environment setup, jump to “Environment setup for each OS”. At first, I will explain little bit about the background knowledge of python & anaconda.  Python version Python version 2 and 3 are distributed, current latest version is python 2.7 and python 3.6. Several years ago, it is said that “some library is still not compatible with python 3.x, and thus python 2.x is recommended”. However, now most of the popular library works well with […]

# Write predict code using concat_examples

This tutorial corresponds to 03_custom_dataset_mlp folder in the source code.   We have trained the model with own dataset, MyDataset, in previous post, let’s write predict code. Source code: predict_custom_dataset1.py predict_custom_dataset2.py   Prepare test data It is not difficult for the model to fit to the train data, so we will check how the model is fit to the test data.

I used the same seed (=13) to extract the train and test data used in the training phase.   Load trained model

The procedure to load the trained model is Instantiate the model (which is a subclass of Chain: here, it is MyMLP) Send the parameters to GPU if […]


text:
# Buzen's algorithm

In queueing theory, a discipline within the mathematical theory of probability, Buzen's algorithm (or convolution algorithm) is an algorithm for calculating the normalization constant G(N) in the Gordon–Newell theorem. This method was first proposed by Jeffrey P. Buzen in 1973.[1] Computing G(N) is required to compute the stationary probability distribution of a closed queueing network.[2]

Performing a naïve computation of the normalising constant requires enumeration of all states. For a system with N jobs and M states there are ${\displaystyle {\tbinom {N+M-1}{M-1}}}$ states. Buzen's algorithm "computes G(1), G(2), ..., G(N) using a total of NM multiplications and NM additions." This is a significant improvement and allows for computations to be performed with much larger networks.[1]

## Problem setup

Consider a closed queueing network with M service facilities and N circulating customers. Write ni(t) for the number of customers present at the ith facility at time t, such that ${\displaystyle \scriptstyle \sum _{i=1}^{M}n_{i}=N}$. We assume that the service time for a customer at the ith facility is given by an exponentially distributed random variable with parameter μi and that after completing service at the ith facility a customer will proceed to the jth facility with probability pij.[2]

It follows from the Gordon–Newell theorem that the equilibrium distribution of this model is

${\displaystyle \mathbb {P} (n_{1},n_{2},\cdots ,n_{M})={\frac {1}{{\text{G}}(N)}}\prod _{i=1}^{M}\left(X_{i}\right)^{n_{i}}}$

where the Xi are found by solving

${\displaystyle \mu _{j}X_{j}=\sum _{i=1}^{M}\mu _{i}X_{i}p_{ij}\quad {\text{ for }}j=1,\ldots ,M.}$

and G(N) is a normalizing constant chosen that the above probabilities sum to 1.[1]

Buzen's algorithm is an efficient method to compute G(N).[1]

## Algorithm description

Write g(N,M) for the normalising constant of a closed queueing network with N circulating customers and M service stations. The algorithm starts by noting solving the above relations for the Xi and then setting starting conditions[1]

${\displaystyle g(0,m)=1{\text{ for }}m=1,2,\cdots ,M}$
${\displaystyle g(n,1)=(X_{1})^{n}{\text{ for }}n=0,1,\cdots ,N.}$

The recurrence relation[1]

${\displaystyle g(n,m)=g(n,m-1)+X_{m}g(n-1,m).}$

is used to compute a grid of values. The sought for value G(N) = g(N,M).[1]

## Marginal distributions, expected number of customers

The coefficients g(n,m), computed using Buzen's algorithm, can also be used to compute marginal distributions and expected number of customers at each node.

${\displaystyle \mathbb {P} (n_{i}=k)={\frac {X_{i}^{k}}{G(N)}}[G(N-k)-X_{i}G(N-k-1)]\quad {\text{ for }}k=0,1,\ldots ,N-1,}$
${\displaystyle \mathbb {P} (n_{i}=N)={\frac {X_{i}^{N}}{G(N)}}[G(0)].}$

the expected number of customers at facility i by

${\displaystyle \mathbb {E} (n_{i})=\sum _{k=1}^{N}X_{i}^{k}{\frac {G(N-k)}{G(N)}}.}$

## Implementation

It will be assumed that the Xm have been computed by solving the relevant equations and are available as an input to our routine. Although g is in principle a two dimensional matrix, it can be computed in a column by column fashion starting from the leftmost column. The routine uses a single column vector C to represent the current column of g.

C[0] := 1
for n := 1 step 1 until N do
C[n] := 0;

for m := 1 step 1 until M do
for n := 1 step 1 until N do
C[n] := C[n] + X[m]*C[n-1];

At completion, C contains the desired values G(0), G(1) to G(N). [1]

## References

1. Buzen, J. P. (1973). "Computational algorithms for closed queueing networks with exponential servers" (PDF). Communications of the ACM. 16 (9): 527. doi:10.1145/362342.362345.
2. ^ a b Gordon, W. J.; Newell, G. F. (1967). "Closed Queuing Systems with Exponential Servers". Operations Research. 15 (2): 254. JSTOR 168557. doi:10.1287/opre.15.2.254.


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# How many moles are in 4.21 x 10^22 molecules of SO_3?

Well a molar quantity specifies $6.022 \times {10}^{23}$ individual items of stuff..........
$\left(4.21 \times {10}^{22} \cdot \text{molecules")/(6.022xx10^23*"molecules} \cdot m o {l}^{-} 1\right)$
$= 0.0700 \cdot m o l$, and thus there $0.0700$ moles of $S {O}_{3}$, $0.0700$ moles of $\text{S atoms}$, and $0.210$ moles of $\text{oxygen atoms}$.


text:
Thread: On Leyland Primes View Single Post
2015-02-11, 15:24   #8
davar55

May 2004
New York City

2·32·5·47 Posts

Quote:
 Originally Posted by davar55 In any case, I was looking for two different representations of a prime p as Leyland-like primes, not an x,y that produced two different primes (which is a valid additional question, so thanks for an example.)
This was what I should have asked in the OP, without the labelled packaging.


text:
# CRC32c

CRC32c.crc32cFunction
crc32c(data, crc::UInt32=0x00000000)

Compute the CRC-32c checksum of the given data, which can be an Array{UInt8}, a contiguous subarray thereof, or a String. Optionally, you can pass a starting crc integer to be mixed in with the checksum. The crc parameter can be used to compute a checksum on data divided into chunks: performing crc32c(data2, crc32c(data1)) is equivalent to the checksum of [data1; data2]. (Technically, a little-endian checksum is computed.)

There is also a method crc32c(io, nb, crc) to checksum nb bytes from a stream io, or crc32c(io, crc) to checksum all the remaining bytes. Hence you can do open(crc32c, filename) to checksum an entire file, or crc32c(seekstart(buf)) to checksum an IOBuffer without calling take!.

For a String, note that the result is specific to the UTF-8 encoding (a different checksum would be obtained from a different Unicode encoding). To checksum an a::Array of some other bitstype, you can do crc32c(reinterpret(UInt8,a)), but note that the result may be endian-dependent.

source
CRC32c.crc32cMethod
crc32c(io::IO, [nb::Integer,] crc::UInt32=0x00000000)

Read up to nb bytes from io and return the CRC-32c checksum, optionally mixed with a starting crc integer. If nb is not supplied, then io will be read until the end of the stream.

source


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In geometry, a right triangular prism is a three-sided prism. A polyhedron with two congruent and parallel faces and whose lateral faces are parallelograms. The shape of the base gives the prism its name. That is, a prism with triangular bases is a triangular prism. A Triangular Prism is a polyhedron made of a triangular base and 3 faces joining corresponding sides.

## What is a Triangular Prism

A triangular prism is a prism composed of two triangular bases and three rectangular sides. A solid object that has two identical ends and all flat sides. The shape of the base give the prism a name, a prism with triangular bases is called as triangular prism. A right triangular prism is a prism whose bases are triangles. A right triangular prism, the word right describes the prism, whereas the word triangle refers to the triangular base.

## Volume of a Triangular Prism

The volume of a right triangular prism can be found by multiplying the area of base times the height.

### Formula for Volume of a Triangular Prism

We know,
The Volume of a Prism = Ah
Where, A is area of the base and h is height of the prism.

In Triangular Prism,

Area of the base (A) = $\frac{1}{2}$ * a * b

Volume of Triangular Prism = Ah = $\frac{1}{2}$ * a * b * h

where, a = altitude, b = base, h = height.

Formula:

Volume of Triangular Prism =
$\frac{1}{2}$ * a * b * h = $\frac{1}{2}$ abh.

Where, a = altitude, b = base, h = height.

Example:

Find the volume of the triangular prism whose length is 15 cm, altitude 10 cm and base is 11 cm.

Solution:
Length of the prism (h) = 15 cm
Altitude (a) = 10 cm
Base (b) = 11 cm

Step 1:

Area of the base,

A = $\frac{1}{2}$ base x height

= $\frac{1}{2}$ x 11 x 10

= 55

=> A = 55 cm2 .

Step 2:

Volume of the triangular prism (V) = Ah

=> V = 55 x 15

= 825

Hence the volume of the triangular prism is 825 cm3 .

## Surface Area of a Triangular Prism

Surface area of a right triangular prism is the sum of lateral surface area and twice the base area of the triangular prism. Square units are used to measure the surface area of the prism.

### Formula for Surface Area of a Triangular Prism

We know,
Surface Area of a Prism = L + 2B

Where, L is lateral surface area and B is base area of the prism.

In Triangular Prism,

Lateral surface area (L) = Ph = (s1 + s2 + s3)h

Area of the base (B) = $\frac{1}{2}$ * a * b

Surface Area of Prism = (s1 + s2 + s3)h + 2($\frac{1}{2}$ab) = Ph + ab
Where, a = altitude, b = base, h = height and s1, s2, s3 are the sides of the triangular prism.

Formula:

Surface Area of Triangular Prism = Ph + ab = (s1 + s2 + s3)h +
ab

Where, a = altitude, b = base, h = height and s1, s2, s3 are the sides.

Example:

Find the surface area of a triangular prism with the given altitude 3, base 4, height 5 and the sides 2, 3, 4.

Solution:
Given
Triangular prism with the altitude 3, base 4, height 5 and the sides 2, 3, 4.

Step 1:

Find the area of the base,

Area of the bases (B) = $\frac{1}{2}$ * a * b = $\frac{1}{2}$ * 3 * 4 = 6

=> Area of the base (B) = 6

Step 2:

Find the lateral surface area,

Lateral surface area (L) = Ph = (s1 + s2 + s3)h

= (2 + 3 + 4)5

= 9 * 5

= 45

=> Lateral surface area (L) = 45

Step 3:

Find the surface area of prism,

Surface Area of Prism = 2A + L = (2 * 6) + 45 = 12 + 45 = 57

Hence the area of the prism is 57 square units.

## Lateral Area of a Triangular Prism

A solid whose sides are parallelograms and bases are one pair of parallel polygon that have same size and shape. The two parallel polygons are the bases of the prism and the remaining polygons will be parallelograms are called lateral faces. A right prism has lateral faces that are rectangles and perpendicular to the bases. The lateral surface of prism is the sum of the polygon faces.

=> L = ah + bh + ch

= h(a + b + c)

= Ph
Here, a, b, c are the length of the sides of base.These dimensions are used along with height of the prism.

Formula:

The lateral area, L, of the triangular prism:

L = Ph = (a + b + c)h

Where, P is the perimeter of base of the prism and h is the height of the prism.


text:
# All Questions

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text:
## Monday Math 4

Coordinate transformations and double integration

Suppose we have the double integral:

Note that we have a pole on the edge of our region, at .

I will demonstrate two methods for doing this, the first more direct, the second much easier to do, but requiring a bit more insight.

1. Direct method:

If we try to do the integral as ordered (x first), we see our x integral is an elliptic integral. So we reverse the order of integration (Fubini’s Theorem):

Now consider the inner integral: this is an integral of the form
, where .
Using the change of variables , our integral becomes:

One can use successive integration by parts to reduce the power of the numerator
(see #11 here [or just use #3 in the same table]), and obtain

So our original integral becomes:

Using the fact that , we can see that

so:

Using the substitution , we find

Note that while  is technically undefined at w=0, we see the limit as w goes to 0 exists (the singularity is removable) and, in fact,
.
Thus

2. “Polar transformation” method:

Instead we use the substitution . Then our integral becomes:

Treating r and θ as the standard polar coordinates, our region of integration is the upper half of the unit disk. Using the fact that  along with the conversion factors between polar and cartesian coordinates (and Fubini’s Theorem):

The inner integral is simple:

and so:

This gives us the same answer, but with much less work.


text:
# If the balloon had a volume of 2 L at a depth of 40 m, what was the original volume of the balloon if we assume the pressure at the surface of the water is 14.7 psi?

Oct 31, 2016

The volume at the surface is 10 L.

#### Explanation:

The pressure at a depth of 40 m is the hydrostatic pressure of the water plus the atmospheric pressure.

The hydrostatic pressure $P$ of a liquid is given by the formula

color(blue)(bar(ul(|color(white)(a/a)P = ρghcolor(white)(a/a)|)))" "

where

ρ = the density of the liquid
$g$ = the acceleration due to gravity
$h$ = the depth of the liquid

${P}_{\text{water" = "1000 kg"·stackrelcolor(blue)("m"^"-1")(color(red)(cancel(color(black)("m"^"-3"))))× 9.81 color(red)(cancel(color(black)("m")))·"s"^"-2" × 40 color(red)(cancel(color(black)("m"))) = 3.92 × 10^5color(white)(l) "kg·m"^"-1""s"^"-2" = 3.92 × 10^5 color(white)(l)"Pa}}$

${P}_{\text{water" = 3.92 × 10^5 color(red)(cancel(color(black)("Pa"))) × "1 atm"/(101.325 × 10^3 color(red)(cancel(color(black)("Pa")))) = "3.87 atm}}$

${P}_{\text{atm" = 14.7 "psi" × "1 atm"/(14.70 "psi") = "1.00 atm}}$

∴ The total pressure at 40 m is

${P}_{\text{tot" = "3.87 atm + 1.00 atm" = "4.87 atm}}$

Now we can use Boyle's Law to calculate the volume of the balloon at the surface.

$\textcolor{b l u e}{\overline{\underline{| \textcolor{w h i t e}{\frac{a}{a}} {P}_{1} {V}_{1} = {P}_{2} {V}_{2} \textcolor{w h i t e}{\frac{a}{a}} |}}} \text{ }$

V_2 = V_1 × P_1/P_2

${P}_{1} = \text{4.87 atm"; V_1 = "2 L}$
${P}_{2} = \text{1.00 atm;"color(white)(l) V_2 = "?}$
${V}_{2} = \text{2 L" × (4.87 color(red)(cancel(color(black)("atm"))))/(1.00 color(red)(cancel(color(black)("atm")))) = "10 L}$ (1 significant figure)


text:
# Find the Constant of Variation y=3/4x

Combine and .
Since the equation can be written in the form , varies directly with and . The constant of variation, , is .
Find the Constant of Variation y=3/4x


text:
+0

HELP PLS

+1
192
1
+19

Suppose $$f$$ is a polynomial such that $$f(0) = 47, f(1) = 32, f(2) = -13$$ and $$f(3)=16$$. What is the sum of the coefficients of $$f$$?

Aug 30, 2021

#1
+117735
+1

Since f(1)=32

and

f(0)=47

I think that the sum of the coefficients is  32-47 = -15

This is my logic

Since f(0)=47,    the constant must be 47    this is not a coefficient

Consider the polynomial to be

$$f(x)=ax^n+bx^{n-1}+cx^{n-2}+\dots+47\\ f(1)=a+b+c+\dots +47=32\\ so\\ a+b+c+\dots +47=32\\ a+b+c+\dots +(\text{coefficient of x)}=32-47\\$$

Sep 6, 2021


text:
2015
09-17

# Mutiples on a circle

Tom has a necklace with n jewels. There is a number on each jewel. Now Tom wants to select a wonderful chain from the necklace. A chain will be regarded wonderful if the wonderful value of the chain is a multiple of a key number K. Tom gets the wonderful value using this way：He writes down the number on the chain in clockwise order and concatenates them together. In this way, he gets a decimal number which is defined as the wonderful value.
For example, consider a necklace with 5 jewels and corresponding numbers on the jewels are 9 6 4 2 8 (9 and 8 are in neighborhood). Assume we take K=7, then we can find that only five chains can be multiples of K. They are 42, 28, 896, 42896 and 89642.

Now Tom wants to know that how many ways he can follow to select a wonderful chain from his necklace.

The input contains several test cases, terminated by EOF.
Each case begins with two integers n( 1 ≤ n ≤ 50000), K(1 ≤ K ≤ 200),the length of the necklace and the key number.
The second line consists of n integer numbers, the i-th number ai(1 ≤ ai ≤ 1000) indicating the number on the ith jewel. It’s given in clockwise order.

The input contains several test cases, terminated by EOF.
Each case begins with two integers n( 1 ≤ n ≤ 50000), K(1 ≤ K ≤ 200),the length of the necklace and the key number.
The second line consists of n integer numbers, the i-th number ai(1 ≤ ai ≤ 1000) indicating the number on the ith jewel. It’s given in clockwise order.

5 7
9 6 4 2 8

5

dp递推，通过一个状态往后加数不断递推出所有状态，并且不断取余

#include <cstdio>
#include <cstring>
#include <cmath>
#define M 50005
#define K 205
int mod[M], sum[M], dp[M][K], p[200005];
int n, k;
void POW()
{
p[0] = 1;
for(int i = 1; i <= 4*n; ++i) p[i] = (p[i-1]*10)%k;
}
int main ()
{
//freopen("in.txt","r",stdin);
//freopen("ou.txt","w",stdout);
while(scanf("%d%d",&n, &k)!=EOF)
{
POW();
for(int i=0; i<=n; ++i)
for(int j=0; j<=k; ++j) dp[i][j]=0;
for(int i = 1; i <= n; ++i)
{
scanf("%d",&sum[i]);
mod[i] =1+ log10(sum[i]*1.0);
}
int cnt=mod[1],s=sum[1]%k;
++dp[1][s];
for(int i = 2; i <= n; ++i)
{
s = (sum[n-i+2]*p[cnt]+s)%k;
++dp[1][s];
cnt+=mod[n-i+2];
}
int ans = dp[1][0];
for(int i = 2; i <= n; ++i)
{
++dp[i][sum[i]%k];
for(int j = 0; j < k; ++j)
if(dp[i-1][j])
{
int t = (j*p[mod[i]]+sum[i])%k;
dp[i][t] += dp[i-1][j];
}
s=(s*p[mod[i]]+sum[i])%k;
dp[i][s]-=1;
ans+=dp[i][0];
s=(s-(sum[i]*p[cnt])%k+k)%k;
}
printf("%d\n",ans);
}
return 0;
}


text:
# Slicing and cropping#

When working with larger image data, it often makes sense to crop out regions and focus on them for further analysis. For cropping images, we use the same “:”-syntax, we used when indexing in lists and exploring multi-dimensional image data.

import numpy as np

image = imread("../../data/Haase_MRT_tfl3d1.tif")

image.shape

(192, 256, 256)

## Slicing#

For visualizing 3D images using scikit-image’s imshow, we need to select a slice to visualize. For example, a Z-slice:

slice_image = image[100]

imshow(slice_image)

<matplotlib.image.AxesImage at 0x2b54f73d340>

We can also select a plane where all pixels have the same Y-position. We just need to specify, that we would like to keep all pixels in Z using the : syntax.

slice_image = image[:, 100]

imshow(slice_image)

<matplotlib.image.AxesImage at 0x2b54f836af0>

## Cropping#

We can also select a sub-stack using indexing in the square brackets.

sub_stack = image[50:150]

sub_stack.shape

(100, 256, 256)

We can also select a sub-region in X. If we want to keep all pixels along Z and Y (the first two dimensions), we just specify : to keep all.

sub_region_x = image[:, :, 100:200]

imshow(sub_region_x[100])

<matplotlib.image.AxesImage at 0x2b54f8ae850>

For selectinng all pixels in one direction above a given value, we just need to specify the start before :.

sub_region_y = image[:, 100:]

imshow(sub_region_y[100])

<matplotlib.image.AxesImage at 0x2b54f90ae20>

Similarly, we can select all pixels up to a given position.

sub_region_x2 = image[:, :, :50]

imshow(sub_region_x2[100])

<matplotlib.image.AxesImage at 0x2b550943d30>

Last but not least, this is how a cropped cube is specified.

cropped_cube = image[80:130, 120:170, :50]

cropped_cube.shape

(50, 50, 50)

imshow(cropped_cube[20])

<matplotlib.image.AxesImage at 0x2b5509a4a00>

And this is how a maximum-intensity projections of this cropped cube look like.

maximum_intensity_projection_along_z = np.max(cropped_cube, axis=0)
imshow(maximum_intensity_projection_along_z)

<matplotlib.image.AxesImage at 0x2b550a03f40>

maximum_intensity_projection_along_y = np.max(cropped_cube, axis=1)
imshow(maximum_intensity_projection_along_y)

<matplotlib.image.AxesImage at 0x2b550a5e8e0>


text:
Amino Acid identity matrix help
3
0
Entering edit mode
7 weeks ago

Hello everyone , I have a dataset of 4000 protein fasta sequences with me .

example dataset :

>Acaryochloris_marina_peg_1945
>Acetivibrio_clariflavus_peg_3972
MRTGVIVQTRMGSSRLPGKVMIDICGKPVIEHVIDRLKMSKVLDDIIIATTTSVKDKIIVEQAKRNGVKWFCGSEEDVLSRYYYAARENRLSTVVRVTSDCPLIDPVILDEIVEFYKKNDYLLVTNAGNILEYRTYPRGLDVEVFSFDILEKAFYSAKKPYQREHVTPYIYETYENKIYYYKNNINLSKYRWTLDTEEDLKLISIIFNNFYYKYGRNFGFKDILKFIQSNPQLSKINEHIEQKKIG
>Acetivibrio_clariflavus_peg_4060
>Acetivibrio_saccincola_peg_0278
>Acetivibrio_saccincola_peg_0286

I want to make a amino acid identity scoring matrix of each protein with each protein. and I want to generate a matix table for the result .

so it means my X-axis is my protein set and Y-axis is the same protein set .

it means each protein similarity score will be given with each protein .

I have tried few of the online available tools , AAI profiler and comparem ,

I couldn't really get exactly what I am looking for . is there any way that I can do it with the blast search ?

Thank you

scripting Bioinformatics Linux shell • 541 views
0
Entering edit mode

You should just script this yourself... R or python would be easier than bash

0
Entering edit mode

I would advise strongly against it, one could easily cook up some script using blast, doing something but that is most likely going to be detrimental (meaning you are worse off with such a solution than none at all, e.g. because the use of Blast for this task is the wrong approach). Instead of just starting to hack something it is recommended:

• Analyze and describe the problem properly
• define the question you are trying to answer and what you want to do with your result
• check for existing and established solutions to your problem first
• if it is a common problem (like phylogenetic analysis) it is very likely a solution already exists.
1
Entering edit mode

I think you maybe misread bash as blast but based on OP's question... It would take under 20 lines to write your own function if you had to write your own protein distance function. Assuming you don't want something super complicated. Alternatively, if you use an existing package you can directly generate the 'identity scoring matrix' that OP wants in essentially a single line:

library(DECIPHER)
the.proteins <- AAStringSet(c('AA','PYAF','FFF'))
dist.mat <- DistanceMatrix(the.proteins,correction='Jukes-Cantor')

0
Entering edit mode

That looks like a proper existing solution to me, possibly I misunderstood your intent. I wouldn't even call that scripting.

0
Entering edit mode

Btw, possibly we shouldn't use Jukes-Cantor for protein sequences? But rather JTT, LG, or WAG?

0
Entering edit mode

Hi , thank you for your suggestion. as far I came to know DistanceMatrix will tell me the dissimilarity score between two sequences. I want to know the similarity score .

Is there any parameter for that ?

0
Entering edit mode

amino acid identity scoring matrix or amino acid similarity scoring matrix ?

0
Entering edit mode

Hi, I want to know the AAI(Amino Acid identity) score between the sequences.

2
Entering edit mode
6 weeks ago
Mensur Dlakic ★ 20k

One way to describe this is by calculating amino-acid identity. There is a simple way to do it with BioPython and lastp:

https://github.com/faylward/lastp_aai

It can be calculated indirectly from a distance matrix, as long as the matrix scale is known (they are typically 0-1 or 0-100). Once the distance matrix is calculated, the similarity matrix is calculated for each entry by subtracting its values from the maximum score.

For example, Clustal Omega calculates a distance matrix on a 0-1 scale:

clustalo --infile=myfile.fas --distmat-out=myfile.matrix -o myfile.aln --outfmt=clu --full --threads=10

The distance matrix will look like this:

10
sequence_1  0.000000 0.890000 0.880000 0.890000 0.910000 0.900000 0.920000 0.930000 0.880000 0.880000
sequence_2  0.890000 0.000000 0.900000 0.900000 0.900000 0.900000 0.890000 0.880000 0.900000 0.900000
sequence_3  0.880000 0.900000 0.000000 0.890000 0.900000 0.910000 0.890000 0.910000 0.910000 0.900000
sequence_4  0.890000 0.900000 0.890000 0.000000 0.890000 0.900000 0.910000 0.890000 0.920000 0.890000
sequence_5  0.910000 0.900000 0.900000 0.890000 0.000000 0.900000 0.900000 0.890000 0.910000 0.910000
sequence_6  0.900000 0.900000 0.910000 0.900000 0.900000 0.000000 0.910000 0.910000 0.890000 0.890000
sequence_7  0.920000 0.890000 0.890000 0.910000 0.900000 0.910000 0.000000 0.880000 0.900000 0.900000
sequence_8  0.930000 0.880000 0.910000 0.890000 0.890000 0.910000 0.880000 0.000000 0.910000 0.890000
sequence_9  0.880000 0.900000 0.910000 0.920000 0.910000 0.890000 0.900000 0.910000 0.000000 0.920000
sequence_10 0.880000 0.900000 0.900000 0.890000 0.910000 0.890000 0.900000 0.890000 0.920000 0.000000

Now, doing (1-entry) for each of the matrix numbers will give a similarity matrix.

0
Entering edit mode
7 weeks ago

This is possible, but you should use global alignment or MSA tools for this, Blast is the wrong tool for the job because it does local alignments. Doing MSA is possibly the most convenient approach because you will need that for phylogenetics anyway using e.g. the mafft software should allow to align your sequences. You can do the whole process in MEGA10 as well and it can also calculate a distance matrix directly, you have to check if that works with the number of sequences. There is also protdist in the EMBOSS package, but I don't know how this fares with 4000 sequences. If you want to go for global alignment you could try ggsearch or needle in EMBOSS (Needleman-Wunsch). It all depends on what you want to with the result. If you get a distance matrix, and want a similarity matrix instead it can be converted as well.

Note that the calculated distances depend on the chosen AA substitution model. Also, distance matrices are of limited value when it comes to determining evolutionary relationships.

0
Entering edit mode
6 weeks ago
benformatics ★ 2.9k

Should be pretty straight-forward in R to do a basic comparison - would be good to read the function manual if you want to alter the other parameters (e.g. gap penalties):

##BiocManager::install("DECIPHER")
library(DECIPHER)
your.proteins <- AAStringSet(c('AA','PYAF','FFF'))
dist.mat <- DistanceMatrix(your.proteins,correction='Jukes-Cantor')

[,1]     [,2]     [,3]
[1,]  0.00000 34.89996 34.89996
[2,] 34.89996  0.00000 34.89996
[3,] 34.89996 34.89996  0.00000

0
Entering edit mode

Hi , thank you for your suggestion. as far I came to know DistanceMatrix will tell me the dissimilarity score between two sequences. I want to know the similarity score .

Is there any parameter for that ?


text:
# equations_of_state.ipynb (Source)

Data files used in this example: co2-thermo.yaml

# Non-ideal equations of state¶

This example demonstrates a comparison between ideal and non-ideal equations of state (EoS) using Cantera and CoolProp.

The following equations of state are used to evaluate thermodynamic properties in this example:

1. Ideal-gas EoS from Cantera
2. Non-ideal Redlich-Kwong EoS (R-K EoS) from Cantera
3. Helmholtz energy EoS (HEOS) from CoolProp

#### Import required packages (Cantera and CoolProp)¶

CoolProp [1] is an open-source package that contains a highly-accurate database for thermophysical properties. The thermodynamic properties are obtained using pure and pseudo-pure fluid equations of state implemented for 122 components.

1. I.H. Bell, J.Wronski, S. Quoilin, V. Lemort, 'Pure and Pseudo-pure Fluid Thermophysical Property Evaluation and the Open-Source Thermophysical Property Library CoolProp,' Industrial & Engineering Chemistry Research 53 (2014), https://pubs.acs.org/doi/10.1021/ie4033999
In [1]:
import cantera as ct
import numpy as np
from CoolProp.CoolProp import PropsSI

%matplotlib inline
%config InlineBackend.figure_formats = ["svg"]
import matplotlib.pyplot as plt

plt.rcParams["figure.dpi"] = 120

print(f"Running Cantera version: {ct.__version__}")

Running Cantera version: 2.6.0a4

### Helper functions¶

This example uses CO$_2$ as the only species. The function get_thermo_Cantera calculates thermodynamic properties based on the thermodynamic state ($T$, $p$) of the species using Cantera. Applicable phases are Ideal-gas and Redlich-Kwong. The ideal-gas equation can be stated as $$pv = RT,$$ where $p$, $v$ and $T$ represent thermodynamic pressure, molar volume, and the temperature of the gas-phase. $R$ is the universal gas constant. The Redlich-Kwong equation is a cubic, non-ideal equation of state, represented as $$p=\frac{RT}{v-b^\ast}-\frac{a^\ast}{v\sqrt{T}(v+b^\ast)}.$$ In this expression, $R$ is the universal gas constant and $v$ is the molar volume. The temperature-dependent van der Waals attraction parameter $a^\ast$ and volume correction parameter (repulsive parameter) $b^\ast$ represent molecular interactions.

The function get_thermo_CoolProp utilizes the CoolProp package to evaluate thermodynamic properties based on the thermodynamic state ($T$, $p$) for a given fluid. The HEOS for CO$_2$ used in this example is obtained from http://www.coolprop.org/fluid_properties/fluids/CarbonDioxide.html.

Since the standard-reference thermodynamic states are different for Cantera and CoolProp, it is necessary to convert these values to an appropriate scale before comparison. Therefore, both functions get_thermo_Cantera and get_thermo_CoolProp return the thermodynamic values relative to a reference state at 1 bar, 300 K.

To plot the comparison of thermodynamic properties among the three EoS, the plot function is used.

In [2]:
def get_thermo_Cantera(phase, T, p):

states = ct.SolutionArray(phase, len(p))
X = "CO2:1.0"
states.TPX = T, p, X

u = states.u / 1000
h = states.h / 1000
s = states.s / 1000
cp = states.cp / 1000
cv = states.cv / 1000

# Get the relative enthalpy, entropy and int. energy with reference to the first point
u = u - u[0]
s = s - s[0]
h = h - h[0]

return h, u, s, cp, cv

def get_thermo_CoolProp(T, p):

u = np.zeros_like(p)
h = np.zeros_like(p)
s = np.zeros_like(p)
cp = np.zeros_like(p)
cv = np.zeros_like(p)

for i in range(p.shape[0]):

u[i] = PropsSI("U", "P", p[i], "T", T, "CO2")
h[i] = PropsSI("H", "P", p[i], "T", T, "CO2")
s[i] = PropsSI("S", "P", p[i], "T", T, "CO2")
cp[i] = PropsSI("C", "P", p[i], "T", T, "CO2")
cv[i] = PropsSI("O", "P", p[i], "T", T, "CO2")

# Get the relative enthalpy, entropy and int. energy with reference to the first point
u = (u - u[0]) / 1000
s = (s - s[0]) / 1000
h = (h - h[0]) / 1000
cp = cp / 1000
cv = cv / 1000

return h, u, s, cp, cv

def plot(p, thermo_Ideal, thermo_RK, thermo_CoolProp, name):

line_width = 3

fig, ax = plt.subplots()
ax.plot(
p / 1e5, thermo_Ideal, "-", color="b", linewidth=line_width, label="Ideal EoS"
)
ax.plot(p / 1e5, thermo_RK, "-", color="r", linewidth=line_width, label="R-K EoS")
ax.plot(
p / 1e5, thermo_CoolProp, "-", color="k", linewidth=line_width, label="CoolProp"
)
ax.set_xlabel("Pressure [bar]")
ax.set_ylabel(name)
ax.legend(prop={"size": 14}, frameon=False)

## 1. EoS Comparison based on thermodynamic properties¶

This is the main subroutine that compares and plots the thermodynamic values obtained using three equations of state.

In [3]:
# Input parameters
T = 300  # Temperature is constant [unit: K]
p = 1e5 * np.linspace(1, 100, 1000)  # Pressure is varied from 1 to 100 bar [unit: Pa]

ideal_gas_phase = ct.Solution("../data/co2-thermo.yaml", "CO2-Ideal", transport=None)
h_ideal, u_ideal, s_ideal, cp_ideal, cv_ideal = get_thermo_Cantera(
ideal_gas_phase, T, p
)

redlich_kwong_phase = ct.Solution("../data/co2-thermo.yaml", "CO2-RK", transport=None)
h_RK, u_RK, s_RK, cp_RK, cv_RK = get_thermo_Cantera(redlich_kwong_phase, T, p)

# Read the thermo data using CoolProp
h_CoolProp, u_CoolProp, s_CoolProp, cp_CoolProp, cv_CoolProp = get_thermo_CoolProp(T, p)

In [4]:
# Plot the results
plot(p, u_ideal, u_RK, u_CoolProp, "Relative Internal Energy [kJ/kg]")
plot(p, h_ideal, h_RK, h_CoolProp, "Relative Enthalpy [kJ/kg]")
plot(p, s_ideal, s_RK, s_CoolProp, "Relative Entropy [kJ/kg-K]")

The thermodynamic properties such as internal energy, enthalpy, and entropy are plotted against the operating pressure at a constant temperature $T = 300$ K. The three equations follow each other closely at low pressures ($P < 10$ bar). However, the ideal gas EoS departs significantly from the observed behavior of gases near the critical regime ($P_{\rm {crit}} = 73.77$ bar).

The ideal gas EoS does not consider inter-molecular interactions and the volume occupied by individual gas particles. At low temperatures and high pressures, inter-molecular forces become particularly significant due to a reduction in inter-molecular distances. Additionally, at high density, the volume of individual molecules becomes significant. Both of these factors contribute to the deviation from ideal behavior at high pressures. The cubic Redlich-Kwong EoS, on the other hand, predicts thermodynamic properties accurately near the critical regime.

In [5]:
# Specific heat at constant pressure
plot(p, cp_ideal, cp_RK, cp_CoolProp, "$C_p$ [kJ/kg-K]")
# Specific heat at constant volume
plot(p, cv_ideal, cv_RK, cv_CoolProp, "$C_v$ [kJ/kg-K]")

In the case of Ideal gas EoS, the specific heats at constant pressure ($C_{\rm p}$) and constant volume ($C_{\rm v}$) are independent of the pressure. Hence, $C_{\rm p}$ and $C_{\rm v}$ for ideal EoS do not change as the pressure is varied from $1$ bar to $100$ bar in this study.

$C_{\rm p}$ for the R-K EoS follows the trend closely with the Helmholtz EoS from CoolProp up to the critical regime. Although $C_{\rm p}$ shows reasonable agreement with the Helmholtz EoS in sub-critical and supercritical regimes, it inaccurately predicts a very high value near the critical point. However, $C_{\rm p}$ at the critical point is finite for the real fluid. The sudden rise in $C_{\rm p}$ in the case of the R-K EoS is just a numerical artifact, due to the EoS yielding infinite values in the limiting case, and not a real singularity.

$C_{\rm v}$, on the other hand, predicts smaller values in the subcritical and critical regime. However, it shows completely incorrect values in the super-critical region, making it invalid at very high pressures. It is well known that the cubic equations typically fail to predict accurate constant-volume heat capacity in the transcritical region [2]. Certain cubic EoS models have been extended to resolve this discrepancy using crossover models. For further information, see the work of Span [2] and Saeed et al. [3].

1. R. Span, 'Multiparameter Equations of State - An Accurate Source of Thermodynamic Property Data', Springer Berlin Heidelberg (2000), https://dx.doi.org/10.1007/978-3-662-04092-8
2. A. Saeed, S. Ghader, 'Calculation of density, vapor pressure and heat capacity near the critical point by incorporating cubic SRK EoS and crossover translation', Fluid Phase Equilibria (2019) 493, https://doi.org/10.1016/j.fluid.2019.03.027

## 2. Temperature-Density plots¶

The following function plots the $T$-$\rho$ diagram over a wide pressure and temperature range. The temperature is varied from 250 K to 400 K. The pressure is changed from 1 bar to 600 bar.

In [6]:
# Input parameters
# Set up arrays for pressure and temperature
p_array = np.logspace(1, np.log10(600), 10, endpoint=True)
T_array = np.linspace(250, 401, 10)  # Temperature is varied from 250K to 400K
p_array = 1e5 * np.array(p_array)[:, np.newaxis]
T_p_product = np.stack(np.meshgrid(p_array, T_array), -1).reshape(-1, 2)

# Calculate densities for Ideal gas and R-K EoS phases
states = ct.SolutionArray(ideal_gas_phase, shape=(p_array.size, T_array.size))
states.TP = T_array, p_array
density_ideal = states.density_mass

states = ct.SolutionArray(redlich_kwong_phase, shape=(p_array.size, T_array.size))
states.TP = T_array, p_array
density_RK = states.density_mass

# Calculate density using CoolProp
density_coolprop = np.zeros_like(T_p_product)
for i, (p, T) in enumerate(T_p_product):
density_coolprop[i] = PropsSI("D", "P", p, "T", T, "CO2")
density_coolprop = density_coolprop.reshape(T_array.size, -1)

# Plot
fig, ax = plt.subplots(figsize=(10, 5))
ideal_line = ax.plot(density_ideal.T, T_array, "--", label="Ideal EoS")
RK_line = ax.plot(density_RK.T, T_array, "o", label="R-K EoS")
CP_line = ax.plot(density_coolprop, T_array, "-", label="CoolProp")
ax.text(-25, 320, "p = 1 [bar]", color="steelblue", rotation="vertical", size="14")
ax.text(300, 320, "p = 97 [bar]", color="darkred", size="14", rotation="-20")
ax.text(925, 320, "p = 600 [bar]", color="c", size="14", rotation="-58")
ax.set_xlabel("Density [kg/m3]")
ax.set_ylabel("Temperature [K]")
ax.legend(
handles=[ideal_line[0], RK_line[0], CP_line[0]], prop={"size": 14}, frameon=False
);

The figure compares $T-\rho$ plots for ideal, R-K, and Helmholtz EoS at different operating pressures. All three EoS yield the same plots at low pressures (0 bar and 10 bar). However, the Ideal gas EoS departs significantly at high pressures ($P > 10$ bar), where non-ideal effects are prominent. The R-K EoS closely matches the Helmholtz EoS at supercritical pressures ($P \ge 70$ bar). However, it does depart in the liquid-vapor region that exists at $P < P_{\rm {crit}}$ and low temperatures (~$T_{\rm {crit}}$).


text:
# Math Help - inequality multiplication proof

1. ## inequality multiplication proof

use only addition and multiplication for proof

x > y iff xz > yz

2. Originally Posted by jay0148

x > y iff xz > yz
What are x,y,z?

3. Oops! Natural Numbers

4. Originally Posted by jay0148

x > y iff xz > yz
I take $\mathbb{N}$ to be $\{ 1,2,3,4,... \}$. That seems to be how your other posts define the naturals.

Proof: $x > y \Longleftrightarrow xz > yz$.

The ( $\implies$) direction is obvious, just multiply both sides of the left hand side by $z$ and you get the right.

For the converse, suppose $xz > yz$. Since $z \in \mathbb{N}$ we know that $z > 0$, thus we can divide by it. Dividing throughout the inequality by $z$ yeilds the desired result.

QED

You may see my response to your other posts for a more rigorous write-up. The language I used here is not very appropriate. This is very similar to the $x = y \Longleftrightarrow xz = yz$ proof I did.

5. I would like to see this proof using only multiplication and addition if anyone else can help...thanks.

6. x > y if and only if x = y + k has a solution in N for k (by definition). Then zx > zy if and only if zx = zy + j has a solution for some j in N. If you multiply x = y + k by z you get zx = zy + kz, thus choosing j = kz we have the solution to the equation.


text:
# Least Mean Square channel equalizer

I've written (and tested) a simple least mean square adaptive filter . The steps of the algorithm are:

$$For n = 0, 1, 2, \ldots:$$
$$x = [u(n), u(n+1), \ldots, n(n-p+1)]^T$$
$$e(n) = d(n) - w(n)^Tx(n)$$
$$w(n+1) = w(n) + \mu*e(n)^Tx(n)$$

Where $u$ is the input signal, $w$ are the weights of the filter, $p$ is the order (number of taps), $e$ is the error signal, and $d$ is the desired signal.

import numpy as np
import matplotlib.pyplot as plt
import traceback
import sys

class LMS:
def __init__(self, input_signal, desired_signal, num_taps, learning_rate):
self.u = input_signal
self.d = desired_signal
self.num_taps = num_taps
self.mu = learning_rate
self.num_points = len(self.u)
self.weights = np.zeros(num_taps)
self.y = np.zeros(self.num_points)
self.e = np.zeros(self.num_points)

def equalize(self):
for n in xrange(self.num_taps, self.num_points):
x = self.u[n:n-num_taps:-1]
self.y[n] = np.dot(x, self.weights)
self.e[n]= self.d[n] - self.y[n]
self.weights = self.weights + self.mu*x*self.e[n]

try:
np.random.seed(1337)
ulen    = 20000
coeff   = np.concatenate(([1], np.zeros(10), [-0.9], np.zeros(7), [0.1]))
u       = np.random.randn(ulen)
d       = np.convolve(u, coeff)
num_taps = 20
step = 0.01

eq = LMS(u, d, num_taps, step)
eq.equalize()
plt.figure()
plt.semilogy()
plt.subplot(1,1,1)
plt.plot(np.abs(eq.e))
plt.show()
except:
type, value, tb = sys.exc_info()
traceback.print_exc()
pdb.post_mortem(tb)

As written the algorithm converges (I get the following plot of the error vector):

# Exceptions

You don't need the sys.exc_info call since pdb.post_mortem without argument uses the exception being currently handled. You don't need pdb either since it serves for development purposes and, at this stage, you should have working code already.

And since all what's left in the except clause is traceback.print_exc(), you could remove the try .. except and let the interpreter print the traceback for you.

Also, it's a very bad habbit to use bare excepts. You should know what kind of exceptions you’re willing to handle. (Even though it can be usefull with pdb to examine various causes of issues.)

# Class

Given how you use the class (initialization of attributes, computation and getting one attribute back), I think you could do equally well with a simple function. Just initialize what you need before the for loop and return the computed array:

def LMS(input_signal, desired_signal, num_taps, learning_rate):
num_points = len(input_signal)
weights = np.zeros(num_taps)
equalized = np.zeros(num_points)

for n in xrange(num_taps, num_points):
x = input_signal[n:n-num_taps:-1]
equalized[n]= desired_signal[n] - np.dot(x, weights)
weights = weights + learning_rate*x*equalized[n]

return equalized

Note that I kept the meaningfull names to help read the algorithm. I also removed y which was a temporary variable and served no purpose after computation.

# main

It is also good practice to avoid keeping code at the top-level of the file. Just in case you want to import your file (for testing purposes in an interactive shell, for instance), you should guard the code in an if __name__ == '__main__': clause.

The whole code becomes:

import numpy as np
import matplotlib.pyplot as plt

def LMS(input_signal, desired_signal, num_taps, learning_rate):
num_points = len(input_signal)
weights = np.zeros(num_taps)
equalized = np.zeros(num_points)

for n in xrange(num_taps, num_points):
x = input_signal[n:n-num_taps:-1]
equalized[n]= desired_signal[n] - np.dot(x, weights)
weights = weights + learning_rate*x*equalized[n]

return equalized

if __name__ == '__main__':
np.random.seed(1337)
ulen = 20000
coeff = np.concatenate(([1], np.zeros(10), [-0.9], np.zeros(7), [0.1]))
u = np.random.randn(ulen)
d = np.convolve(u, coeff)
num_taps = 20
step = 0.01

eq = LMS(u, d, num_taps, step)

plt.figure()
plt.semilogy()
plt.subplot(1,1,1)
plt.plot(np.abs(eq))
plt.show()

(I removed the extra whitespace arround assignements since it is recommended by PEP8)

• Thank you! Ironically, I refactored this from some code that was just a function. I want it as a class, as it's part of a project with several types of equaliser (which will decide the eq type at runtime). – Tom Kealy Dec 8 '15 at 0:14
• @TomKealy You should have mentionned that in the question ;) Anyway, for such project, you probably want to invert your logic: call your class Equalizer and each method beside the constructor will be named after the type of operation it performs. – 409_Conflict Dec 8 '15 at 9:19


text:
# SemiconductorLinearConductivity

!syntax description /Materials/SemiconductorLinearConductivity The [Steinhart-Hart equation](https://en.wikipedia.org/wiki/Steinhart%E2%80%93Hart_equation) is an empirical model for temperature dependent electrical resistance for semiconductors. It is used in thermistor industry since it provides better expression of the temperature-resistance relationship. $$\frac{1}{T}=A+B\ln(R)+C(\ln(R))^3$$ where R is the resistance and T is the temperature in Kelvins. $\sigma$, the electrical conductivity, equals to 1/R. A, B, and C are the Steinhart-Hart coefficients. For some intrinsic semiconductor materials, the log conductivity is a linear function of 1/T that the coefficient C = 0 (ref: "Introduction to Ceramics" by Kingery). This model is for those materials only.

For conductivity data in vs (1) where .

For the derivatives with respect to T: (2)

(3)

(4)

## Input Parameters

• sh_coeff_ASteinhart_Hart coefficient A of the material

C++ Type:double

Options:

Description:Steinhart_Hart coefficient A of the material

• sh_coeff_BSteinhart_Hart coefficient B of the material.

C++ Type:double

Options:

Description:Steinhart_Hart coefficient B of the material.

• tempVariable for temperature in Kelvin.

C++ Type:std::vector

Options:

Description:Variable for temperature in Kelvin.

### Required Parameters

• boundaryThe list of boundary IDs from the mesh where this boundary condition applies

C++ Type:std::vector

Options:

Description:The list of boundary IDs from the mesh where this boundary condition applies

• computeTrueWhen false, MOOSE will not call compute methods on this material. The user must call computeProperties() after retrieving the Material via MaterialPropertyInterface::getMaterial(). Non-computed Materials are not sorted for dependencies.

Default:True

C++ Type:bool

Options:

Description:When false, MOOSE will not call compute methods on this material. The user must call computeProperties() after retrieving the Material via MaterialPropertyInterface::getMaterial(). Non-computed Materials are not sorted for dependencies.

• blockThe list of block ids (SubdomainID) that this object will be applied

C++ Type:std::vector

Options:

Description:The list of block ids (SubdomainID) that this object will be applied

• base_nameMaterial property base name

C++ Type:std::string

Options:

Description:Material property base name

### Optional Parameters

• output_propertiesList of material properties, from this material, to output (outputs must also be defined to an output type)

C++ Type:std::vector

Options:

Description:List of material properties, from this material, to output (outputs must also be defined to an output type)

• outputsnone Vector of output names were you would like to restrict the output of variables(s) associated with this object

Default:none

C++ Type:std::vector

Options:

Description:Vector of output names were you would like to restrict the output of variables(s) associated with this object

### Outputs Parameters

• enableTrueSet the enabled status of the MooseObject.

Default:True

C++ Type:bool

Options:

Description:Set the enabled status of the MooseObject.

• use_displaced_meshFalseWhether or not this object should use the displaced mesh for computation. Note that in the case this is true but no displacements are provided in the Mesh block the undisplaced mesh will still be used.

Default:False

C++ Type:bool

Options:

Description:Whether or not this object should use the displaced mesh for computation. Note that in the case this is true but no displacements are provided in the Mesh block the undisplaced mesh will still be used.

• control_tagsAdds user-defined labels for accessing object parameters via control logic.

C++ Type:std::vector

Options:

Description:Adds user-defined labels for accessing object parameters via control logic.

• seed0The seed for the master random number generator

Default:0

C++ Type:unsigned int

Options:

Description:The seed for the master random number generator

• implicitTrueDetermines whether this object is calculated using an implicit or explicit form

Default:True

C++ Type:bool

Options:

Description:Determines whether this object is calculated using an implicit or explicit form

• constant_onNONEWhen ELEMENT, MOOSE will only call computeQpProperties() for the 0th quadrature point, and then copy that value to the other qps.When SUBDOMAIN, MOOSE will only call computeSubdomainProperties() for the 0th quadrature point, and then copy that value to the other qps. Evaluations on element qps will be skipped

Default:NONE

C++ Type:MooseEnum

Options:NONE ELEMENT SUBDOMAIN

Description:When ELEMENT, MOOSE will only call computeQpProperties() for the 0th quadrature point, and then copy that value to the other qps.When SUBDOMAIN, MOOSE will only call computeSubdomainProperties() for the 0th quadrature point, and then copy that value to the other qps. Evaluations on element qps will be skipped


text:
# Making list of errors from file

So I have a file of errors, there default meanings and also it's hierarchy in terms of indentation

BaseException General for all errors of any and every kind.
SystemExit Called for when the system wants to exit.
KeyboardInterrupt Called when an operator interrupts an action.
GeneratorExit Called when the system requests a generator exit.
Exception General for all non-exit errors.
StopIteration Called when an iterator ended unexpectedly.
StopAsyncIteration Called when an asynchronous iterator ended unexpectedly.
ArithmeticError General for arithmetic errors.
FloatingPointError Called when interpreting a float failed.
OverflowError Called when the result was too large to be represented.
ZeroDivisionError Called when dividing by zero. Contrary to belief, it does not blow up the entire system. Atleast- not all the time.
AssertionError Called when an assertion fails.

And I have then converted it all into a list of tuples, with a searcher function along with it such that error("ArithmeticError"), error("007") and error(7) all return

[
1,
"007",
"ArithmeticError",
"General for arithmetic errors.",
[
0,
"004",
"Exception",
"General for all non-exit errors.",
[
0,
"000",
"BaseException",
"General for all errors of any and every kind."
],
]
]

Which is the data from before in the format

[
indentation (number of spaces before words),
code (line it is on),
name (first word),
default reason (all words but the first),
[
parents indentation
parents code
parents name
parents default reason
parents parent (if it exists)
[
]

All errors will have a parent apart from BaseException (000) This is the code I have done for it, but I feel like there is a more effecient method.

import os,builtlins

def r(p,b="default"): #r("cache/errors.log") returns path_to_project_root_folder/cache/errors.logs
b,p=b.replace("\\","/"),p.replace("\\","/");p=p if p.startswith("/") else f"/{p}"
return ((resourcepath if b=="default" else (b[:len(b)-1] if p.startswith("/") and b.endswith("/") else b))+(p[:len(p)-1] if p.endswith("/") else p)).replace("/","\\").replace("\\\\","\\")
resourcepath=os.getcwd()[:os.getcwd().find("Ancilla Project")+len("Ancilla Project")]

errors=[[r[0],r[1],r[2][:r[2].find(" ")],r[2][r[2].find(" ")+1:]] for r in[(len(e[:len(e)-len(e.lstrip())]),f"{'0'*(3-len(str(i)))}{i}",e[len(e)-len(e.lstrip()):],) for i,e in enumerate(open(r("cache/errors.log")).read().split("\n"))]]
def error(q,obj=False):
a=[e for e in errors if (f"{'0'*(3-len(str(q)))}{q}" if isinstance(q,int) else q)==e[1 if isinstance(q,int) else 2]];return ((a[0] if a else None) if not obj else ({**globals(),**vars(builtins)}[a[0][2]] if a else None))
for i,e in enumerate(errors):
errors[i]=([(*e,(*errors[int(e[1])-x-1],int(e[1])-x-1)) for x in range(0,int(e[1])) if errors[int(e[1])-x-1][0]<e[0]] if e[0]!=0 else [(*e,(*error("BaseException"),)),] if e[2]!="BaseException" else [(*e,),])[0];e=errors[i]

If any more information or clarity is needed I will try my best to give them. And yeah, i know that the amount of PEP violation (whichever one is for python 3.8.6) is so high that it'd collapse under its own gravity and become a blackhole- so some help on that would be appreciated

• Why is your code so dense and compact? Are you aiming to code-golf? Oct 23, 2021 at 15:38
• i dont know what aiming to code-golf is but i just did it because i hate having to scroll down on the python interpreter and vertically and horizontally so i make it short enough so i wont have to scroll for a bit and just under the horizontal limit Oct 23, 2021 at 15:48

# Small Things

• Spelling error, builtlins -> builtins.
• Removed commented out code you don't use, adds unnecessary clutter.
• Spaces before and after operators (+-*/=).

# Use Meaningful Names

Almost all of your variables are one character long. As someone looking at your code for the first time, it was very hard to determine what types of variables these are. p and b as parameters? What types are passed? These should be named accordingly to what you assign to them.

# Space Out Your Code

It's nearly impossible, at least for me, to read your code the way you posted it. As you pointed out in a comment, "I hate having to scroll down on the python interpreter...", I edited your code using my editor and it could still fit on the entire page without scrolling. Now you may be using a smaller screen, so I'll give you the benefit of the doubt.

However, I write my code enveloped around one principle: Write code that others can understand. Having a huge clump of code, while it still does what you want, will be extremely messy. It will be difficult to debug this program should something not work while you test it.