Science topics: Mathematics
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Mathematics - Science topic

Mathematics, Pure and Applied Math
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Recently I've discussed this topic with a tautologist researcher, Quine's follower. The denial of the capacity of deductive logic to generate new knowledge implies that all deductive results in mathematics wont increase our knowledge for real.
The tautologic nature of the deduction seems to lead to this conclusion. In my opinion some sort of logic omniscience is involved in that position.
So the questions would be:
  • Is the set of theorems that follow logically from a set A of axioms, "implicit" knowledge? if so, what would be the proper difference between "implicit" and "explicit" knowledge?
  • If we embrace the idea that no new knowledge comes from deduction, what is the precise meaning of "new" in this context?
  • How do you avoid the problem of logic omniscience?
Thanks beforehand for your insights.
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Almost all new mathematical knowledges are new definitions-concepts and new deductions-theorems. For example, Gödel's incompleteness theorems tells debunked the hope of founding mathematics on an consistent system of axioms. This was totally unexpected and put an end to the Hilbert program in mathematical foundation. Most of the knowledge in mathematics is totally irrelevant to the logical axioms onto which mathematics is currently expressed. A totally new logical foundations could one day substitute the current one and it would not be relevant to the mass of mathematical knowledge. The core of mathematical knowledge originates from abstactions made on different core human trade activities: logical debate, accounting, land measurement, art of building, etc. Mathematics is the systematic organisation of the world of relations originally present in these trade activities and which were already present in our sensory-motor sysyems allowing our bodily interaction with the world. It is why abstracting these relation in the first place and organising them are natural to us.
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In the 'Collection of Geometric Problems' from 1966, there is a problem in which the author made a mistake.
Try to find the author's error!
In the picture, you can see the conditions of this mathematical problem without changes, with an error.
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Dear Peter, thank you for your interest in finding the author's mistake. It was nice to see your geometric vision, answer 6R is indeed incorrect. Let me share with you my proof of why the answer is not correct.
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The experiment conducted by Bose at the Royal Society of London in 1901 demonstrated that plants have feelings like humans. Placing a plant in a vessel containing poisonous solution he showed the rapid movement of the plant which finally died down. His finding was praised and the concept of plant’s life has been established. If we scold a plant it doesn’t respond, but an AI bot does. Then how can we disprove the life of a Chatbot?
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@ Dr. Chen, Thank you for consulting with AI bot on behalf of me. It's interesting!
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Article Topic: Some Algebraic Inequalitties
I have been collecting some algebraic inequalities, soonly it has been completed and published on Romanian Mathematical Magazine.
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Certainly some exotic collection.
Often inequalities are better
Understood as comming from
Some identity, if you suppress
some always positive or negative
term.
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For computer science, is mathematics more of a tool or a language?
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An equation can be considered as a sentence in the language of mathematics, at least in its formalized version as can be seen in every book about mathematical logic or ZFC set theory. Programming languages are also formalized languages, and you have to stick to these formalizations in order for a computer to work correctly. However, most mathematicians use a semi formal mathematical language, but when for instance a theorem is correct, meaning that is has a correct proof, then one can write theorem and proof in the formalized language of mathematics, but the result is almost always unreadable by a human being, but " understandable " by a formal proof system, that can be implemented on a computer. In this sense one can let computers prove theorems, but then it needs a lot of input from a human being. But doing mathematics is also an art, and in order to be able to practice this art one needs a lot of practice and mathematical knowledge.
A Gaussian law is a concept in statistics or probability theory. The notion of linear function belongs to the areas of calculus , analysis and linear algebra.
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The choice of coordinate systems is a mathematical tool used to describe physical events. Local or universal spatial events occur in multiple coordinate systems of space and time or spacetime as we know it under classical, relativistic and cosmological physics.
Whether the fundamental laws of physics remains consistent across different coordinate systems.
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Coordination system just imagination of any system. In that particular system, we just calculate any motion or any physical quantity in particular system. All systems do not contain infinite range, all theories are existing till particular coordinates. Dimensions could be change, but coordinate systems remain unchanged. So it doesn't matter.
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The fundamental theorem of calculus is the backbone of natural sciences, thus, given the occasional thin line between the natural and social, how common is the fundamental theorem of calculus in social sciences?
Examples I found:
Ohnemus , Alexander . "Proving the Fundamental Theorem of Calculus through Critical Race Theory." ResearchGate.net . 1 July 2023. www.researchgate.net/publication/372338504_Proving_the_Fundamental_Theorem_of_Calculus_through_Critical_Race_Theory. Accessed 9 Aug. 2023.
Ohnemus , Alexander . "Correlations in Game Theory, Category Theory, Linking Calculus with Statistics and Forms (Alexander Ohnemus' Contributions to Mathematics Book 9)." amazon.com. 12 Dec. 2022. www.amazon.com/gp/aw/d/B0BPX1CSHS?ref_=dbs_m_mng_wam_calw_tkin_8&storeType=ebooks. Accessed 11 July 2023.
Ohnemus , Alexander . "Linguistic mapping of critical race theory(the evolution of languages and oppression. How Germanic languages came to dominate the world) (Alexander Ohnemus' Contributions to Mathematics Book 20)." amazon.com. 3 Jan. 2023. www.amazon.com/Linguistic-evolution-oppression-Contributions-Mathematics-ebook/dp/B0BRP1KYLR/ref=mp_s_a_1_13?qid=1688598986&refinements=p_27%3AAlexander+Ohnemus&s=digital-text&sr=1-13. Accessed 5 July 2023.
Ohnemus , Alexander . "Fundamental Theorem of Calculus proved by Wagner's Law (Alexander Ohnemus' Contributions to Mathematics Book 8)." amazon.com. 11 Dec. 2022. www.amazon.com/gp/aw/d/B0BPS2ZMXC?ref_=dbs_m_mng_wam_calw_tkin_7&storeType=ebooks. Accessed 25 June 2023.
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Further support:
"This particularly elegant theorem shows the inverse function relationship of the derivative and the integral and serves as the backbone of the physical sciences"(Brittanica 2023).
Image belongs to Brittanica(I added the highlight)
Britannica, The Editors of Encyclopaedia. "fundamental theorem of calculus". Encyclopedia Britannica, 29 Jul. 2023, https://www.britannica.com/science/fundamental-theorem-of-calculus. Accessed 20 September 2023.
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Most masters focus on general review of qm, classical mechanics, assesing students skills in classical yet heneric and self-value calculative and interpreting capabilities.
The English MSc's on the other hand, provide an introduction to the physical principles and mathematical techniques of current research in:
general relativity
quantum gravity
quantum f. Theory
quantum information
cosmology and the early universe
There is also a particular focus on topics reflecting research strengths.
Graduates are more well equiped to contribute to research and make impressive ph. D dissertations.
Of course instructors that teach masters are working in classical and quantum gravity, geometry and relativity, to take the theoretical physics sub-domain, in all universities but the emphasis on current research's mathematical techniques and principles is only found in English university'masters offerings.
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Μr Verch indeed My research, which was not fully developped at the time I asked my question, showed that this the case.
Still, a 30% offer the classic calculative phys quantities - based skills of big 4 (and less conceptual understanding assesment or less actual "doing the science" skills of qm, CM, statistical and thermal. Physics) which trends to be considered classic masters structilure or outdated.
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I have deep neural network where I want to include a layer which should have one input and two outputs. For example, I want to construct an intermediate layer where Layer-1 is connected to the input of this intermediate layer and one output of the intermediate layer is connected to Layer-2 and another output is connected to Layer-3. Moreover, the intermediate layer just passes the data as it is through it without doing any mathematical operation on the input data. I have seen additionLayer in MATLAB, but it has only 1 output and this function is read-only for the number of outputs.
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% Define your input data and labels (adjust as needed) X = randn(100, 10); % Input data (100 samples, 10 features) Y1 = randn(100, 1); % Output 1 (e.g., regression task) Y2 = randi([0, 1], 100, 1); % Output 2 (e.g., binary classification) % Create a neural network architecture inputSize = size(X, 2); numHiddenUnits = 64; inputLayer = imageInputLayer([inputSize, 1, 1]); commonHiddenLayer = fullyConnectedLayer(numHiddenUnits); outputLayer1 = fullyConnectedLayer(1); % Output layer for task 1 outputLayer2 = fullyConnectedLayer(2); % Output layer for task 2 % Create a branch for task 1 branch1 = [ inputLayer commonHiddenLayer outputLayer1 regressionLayer ]; % Create a branch for task 2 branch2 = [ inputLayer commonHiddenLayer outputLayer2 softmaxLayer classificationLayer ]; % Define the layers for the entire network (both branches) layers = [ branch1 branch2 ]; % Create and train the neural network options = trainingOptions('adam', ... 'MaxEpochs', 10, ... 'MiniBatchSize', 32, ... 'Verbose', true); net = trainNetwork(X, {Y1, Y2}, layers, options); % Make predictions X_test = randn(10, 10); % Test input data (10 samples) [Y1_pred, Y2_pred] = predict(net, X_test);
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"Mathematics is logical systems formulising relationships of variable(s) with other variable(s) quantitatively &/or qualitatively as science language." (Sinan Ibaguner)
I tried to devise my best description as shortly & clearly !
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Mr.Jiolito Benitez PhD
"Mathematics is an area of knowledge that includes the topics of numbers, formulas and related structures, shapes and the spaces in which they are contained, and quantities and their changes. These topics are represented in modern mathematics with the major subdisciplines of number theory,[1] algebra,[2] geometry,[1] and analysis,[3][4] respectively. There is no general consensus among mathematicians about a common definition for their academic discipline."
As stated in wikipedia there is no common definition at all. Since I did not find any sufficiently satisfactory clear and short definition of maths, therefore I devised my own original definition which seems to be the best until now, at least for me... What I wait from readers to criticise me positively or negatively about my own definition of maths.
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For physics, is mathematics more of a tool or a language?
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In the context of physics, mathematics serves both as a tool and a language.
Mathematics is a powerful tool that physicists use to model and describe physical phenomena. It provides a precise and systematic way to formulate theories, make predictions, and solve problems. Physicists use mathematical equations, formulas, and techniques to analyze data, perform calculations, and develop theoretical frameworks. Without mathematics, it would be extremely challenging to quantitatively understand and describe the behavior of the physical universe.
Mathematics also serves as a language through which physicists communicate their ideas and discoveries. Just as natural languages like English or Spanish enable people to convey thoughts and information, mathematics allows physicists to express complex concepts and relationships in a concise and unambiguous manner. Equations and mathematical notation provide a common, universally understood language that bridges linguistic and cultural barriers among scientists.
In essence, mathematics is an indispensable tool for conducting physics research, but it also acts as a language for conveying the results and theories of that research to the broader scientific community. It plays a dual role, facilitating both the practical application of physics and the effective communication of its findings.
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"Matematik, değişken(ler)in diğer değişken(ler)le ilişkilerini niceliksel ve(ya) niteliksel tarz formüle eden mantıksal sistemlerin sanatsal bilim dili. "
Kısa ve net matematik tanımım ! Daha iyisi ne olabilir !?
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Since I did not find any sufficiently satisfactory definition of maths so, I devised my own definition which seems to be the best until now, in my opinion !?
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Hello,
I am looking for mathematical formulas that calculate the rigid body movement of an element based on the nodal displacements. Can anyone give a brief explanation and recommend some materials to read? Thanks a lot.
Best,
Chen
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Rigid body modes correspond to zero strain energy U=0. Where U=(1/2)*{d}t*[K]*{d} the stiffness matrix and the degrees of freedom. In this case all the degrees of freedom have the same constant displacement which means that the structure displaces without deformation.
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I am using SPSS to perform binary logistic regression. One of the parameters generated is the prediction probability. Is there a simple mathematical formula that could be used to calculate it manually? e.g. based on the B values generated for each variable in model?
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People have certainly done that, Nasir Al-Allawi. A Google search on <logistic regression scoring system> turns up lots of resources. Good luck with your work.
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Paradox Etymology can be traced back to at least Plato's Parmenides [1]. Paradox comes from para ("contrary to") and doxa ("opinion"). The word appeared in Latin "paradoxum" which means "contrary to expectation," or "incredible. We propose, in this discussion thread, to debate philosophical or scientific paradoxes: their geneses, formulations, solutions, or propositions of solutions... All contributions on "Paradoxes", including paradoxical ones, are welcome.
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Let's dive into a discussion about paradoxes, their origins, and some famous examples.
The Nature of Paradoxes:Paradoxes have always been a fascinating aspect of philosophy and science. They challenge our understanding of reality and often lead to deep philosophical and scientific inquiries. The etymology of the word, as you mentioned, reveals that paradoxes are inherently linked to contradictions or ideas contrary to common opinion.
Philosophical Paradoxes:One of the most famous philosophical paradoxes is Zeno's Paradox, which comes in several forms. The most well-known version involves Achilles and the Tortoise, where Achilles, the faster runner, can never overtake a slower tortoise if it has a head start. How do you think this paradox challenges our understanding of motion and infinity?
Scientific Paradoxes:In the realm of science, the Twin Paradox from Einstein's theory of relativity is a classic example. It proposes that if one twin travels into space at near-light speed while the other stays on Earth, the traveling twin will age slower, leading to a paradoxical situation where the traveling twin can return home younger than the twin who remained on Earth. How can we reconcile this with our everyday understanding of time?
Resolving Paradoxes:One approach to resolving paradoxes is to reexamine our fundamental assumptions. For example, Zeno's Paradox can be resolved by understanding that in calculus, we can sum an infinite series of decreasing distances, ultimately reaching a finite total. How important is it to redefine our assumptions and frameworks when dealing with paradoxes?
The Paradox of Self-Reference:Another intriguing type of paradox is the paradox of self-reference, as seen in the famous liar paradox. If a person says, "I am lying," is that statement true or false? This paradox raises questions about the limits of language and self-reference. How do you think we can grapple with such paradoxes?
Modern Paradoxes:Paradoxes are not confined to the ancient or classical realms. In modern times, we encounter new paradoxes in fields like quantum mechanics and artificial intelligence. One example is Schrödinger's Cat, which explores the bizarre nature of quantum superposition. How do these modern paradoxes challenge our understanding of reality?
Final Thoughts:Paradoxes are like intellectual puzzles that invite us to question our assumptions and delve deeper into the mysteries of the universe. They often spark innovation and lead to breakthroughs in both philosophy and science. As we explore these paradoxes, we may find that the journey of seeking solutions can be as enlightening as the resolutions themselves.
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If someone can help me understand Helicity in the context of the High Harmonic Generation, it will be helpful. Due to mathematical notations, the exact question can be found "https://physics.stackexchange.com/questions/778274/what-is-helicity-in-high-harmonic-generation".
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Air above the equator is heated more and areas near the equator receive more heat from the sun than those near the poles due to a phenomenon called "solar angle" and the way the Earth's curvature and atmosphere interact with incoming solar radiation. This is primarily caused by the Earth's axial tilt and its spherical shape.
1. Solar Angle: The angle at which sunlight reaches a particular location on Earth's surface is a crucial factor. Near the equator, sunlight strikes the surface more directly and perpendicularly compared to regions near the poles. When sunlight strikes a surface at a steeper angle, the same amount of energy is concentrated over a smaller area, leading to higher temperatures. In contrast, at higher latitudes (closer to the poles), sunlight is spread over a larger surface area due to the oblique angle of incidence, resulting in less heating.
2. Earth's Curvature and Atmosphere: The curvature of the Earth plays a role in how sunlight is distributed. Near the equator, the curved surface presents a relatively small area for the sun's energy to be distributed, concentrating the heat. Additionally, the atmosphere plays a significant role in moderating the amount of solar radiation that reaches the surface. When sunlight passes through a thicker layer of atmosphere, it can scatter and be absorbed, reducing the amount of energy that reaches the surface. Near the equator, the sunlight has to pass through a smaller portion of the atmosphere, allowing more energy to reach the surface and result in higher temperatures.
3. Day Length: Near the equator, the length of day and night remains relatively consistent throughout the year. This means that the sun is up for a significant portion of the day, allowing more time for the surface to absorb and store heat. In contrast, areas closer to the poles experience more extreme variations in day length, with long days in the summer and long nights in the winter. This variation affects the amount of time available for solar heating.
4. Heat Redistribution: The equatorial region receives more heat than it radiates back into space, creating a surplus of energy. This excess heat is then transported toward the poles through atmospheric and oceanic circulation patterns, which help to distribute heat around the planet and regulate global climate patterns.
The combination of the solar angle, Earth's curvature, atmospheric effects, and heat redistribution mechanisms results in the equatorial region receiving more direct and concentrated solar energy, leading to higher temperatures compared to areas closer to the poles.
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In what ways may a STEM facility develop these skills?
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Anecdotal: I have seen children in STEM activities gain insight to mathematical thinking when engaged in problem solving. The activities involved measurements: length, volume, and area. Constructing models - free form and then using written instructions. Instructions can be numerical or visual model with dimensions on the part or on a map/template.
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1. On the “Field” concept of objective reality:
Einstein in an August 10, letter to his friend Besso (1954): “I consider it quite possible that physics cannot be based on the field concept, i.e., continuous structure. In that case, nothing remains of my entire castle in the air, gravitation theory included, (and of) the rest of modern physics” A. Pais, Subtle is the Lord …” The Science and the Life of Albert Einstein”, Oxford University Press, (1982) 467,
2. On “Black Hole”:
"The essential result of this investigation is a clear understanding as to why the "Schwarzschild singularities" do not exist in physical reality. Although the theory given here treats only clusters whose particles move along circular paths it does not seem to be subject to reasonable doubt that more general cases will have analogous results. The "Schwarzschild singularity" does not appear for the reason that matter cannot be concentrated arbitrarily. And this is due to the fact that otherwise the constituting particles would reach the velocity of light.
This investigation arose out of discussions the author conducted with Professor H. P. Robertson and with Drs. V. Bargmann and P. Bergmann on the mathematical and physical significance of the Schwarzschild singularity. The problem quite naturally leads to the question, answered by this paper in the negative, as to whether physical models are capable of exhibiting such a singularity.", A. Einstein, The Annals of Mathematics, Second Series, Vol. 40, No. 4 (Oct., 1939), pp. 922-936
3. On the Quantum Phenomena:
“Many physicists maintain - and there are weighty arguments in their favour – that in the face of these facts (quantum mechanical), not merely the differential law, but the law of causation itself - hitherto the ultimate basic postulate of all natural science – has collapsed”. A. Einstein, “Essays in Science”, p. 38-39 (1934)
4. On Gravitational Wave:
Einstein dismissed the idea of gravitational wave until his death:
“Together with a young collaborator, I arrived at the interesting result that gravitational waves do not exist, though they had been assumed a certainty to the first approximation,” he wrote in a letter to his friend Max Born. Einstein's paper to the Physical Review Letters titled “Do gravitational waves exist?”; was rejected.
Arthur Eddington who brought an obscure Einstein to world fame, and considered himself to be the second person (other than Einstein), who understood General Relativity (GR); dismissed the idea of gravitational wave in the following way: "They are not objective, and (like absolute velocity) are not detectable by any conceivable experiment. They are merely sinuosities in the co-ordinate-system, and the only speed of propagation relevant to them is 'the speed of thought'".
A.S. Eddington, F.R.S., The Proceedings of the Royal Society of London, Series A, Containing Papers of a Mathematical and Physical Character. The Propagation of Gravitational Waves. (Received October 11, 1922), page 268
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Okay, I got your point. This is what I think. Common people are weak. They need God to tell them what to do with their life and death, and heroes (superstars) to follow in every activity they are seriously involved including religions, sports, music and politics. Among these superstar spirits, some followers become prophets such that they can win powers and profits over others. Those prophets care for nothing about truth. Their only ambitions are to gain big powers and fortunes by building a big group of fans and followers. Also, there are a lot of cowers, who are afraid of being blamed and threatened by the big group of fans which may damage their positions and fortunes if they oppose to the superstars and the spirits. This includes those big shots in scientific fields.
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Mathematics is purely science or just a numbers buckets.
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"Mathematics is the most beautiful and most powerful creation of the human spirit."
Stefan Banach
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Dear Colleaugues & Allies ~ I just posted the final prepublication draft of an article on the nature of the Langlands Program, RH, P v. NP, and other "open" problems of pure maths, number theory, etc., and the proofs. I would deeply appreciate your feedback and suggestions. So, if you are interested, please send me a request for access to the [private] file, for review and comment. Thanks & best of luck etc. ~ M
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R. 4, page 001
Dear Michael, that's the point. You did a lot. It's hard for me to take care of all.
If you are interested we may do it by a single point, the most important:
√-1
Will you hold the old definition? Or will you go the way as I did and look behind the veil? At least you may have your own opinion on that.
But not been able to see where the results of (+1)(-1) or (-1)(+1) came from, denies half the area of reasons. Most mathematicians find it too kiddy to talk about that. Let them be limited.
There are many ways to find it obscure to stop doing the exercise for square-root only by having a negative radicand.
Transforming the coordinates makes the other areas not calculable.
Martinez (negative math) introduced the inverse rule for the prefixes of products. So no definition is complete except this of holding all the prefixes of the quantities which are to combine.
If you know they were + and – => the result is + and – , not? If you don't know the way the sources were, you have to deal with absolutes and further conditions.
Riemann took `imaginary´. Will you too?
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pls answer
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Howdy Selim Molla ,
No.
The problem of fluid behavior after energy extraction in the range of sea states the ocean can accomplish is too difficult to explain mathematically as one's primary activity, and certainly it must not be attempted "on the side" of energy extraction equipment research and development. The situation is not quite that bad in practice, however, especially with your focus on energy extraction equipment.
An engineering approximation to mathematical treatment of oceanic waves after wave energy extraction might be possible with sufficient attention to the energy extracted and the wave recovery under wind stress, fetch, etc. An expression starting from the wave energy equation before interference by extraction equipment which is then reduced by the actual value of the energy extracted would be a start. Then, if you were to factor in the efficiency as an additional loss of energy by the wave and you would have an estimate of the wave energy several wavelengths beyond your equipment, that is, beyond initial turbulence details, etc. For the wave state further along one would have to apply the approximations available for the affect of wind fetch, currents, etc., but that is your field, I'm just a visitor who hates to see questions without replies.
Perhaps this suggestion is too obvious, too simple to be of value, but unfortunately, the explanation you request is not available at present.
Happy Trails, Len
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The mathematical function of TPMS unit cell is as follows: (for example Gyroid)
sin x * cos y+ sin y * cos z+ sin z * cos x = c
parameter 𝑐 determines the relative density of the unit cell.
I am interested to design TPMS unit cell with nTopology software. In this software, TPMS network-based unit cell is designed with "Mid-surface offset" parameter and TPMS sheet-based unit cell is designed with "approximate thickness" parameter.
What is the relation between these parameters and the relative density of the unit cell?
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Just for your information, in the current nTop version, it allows users to generate TPMS with approximate thickness.
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After sharing that article, I received an email saying
"I have read the abstract. But can not see the connections between the individual topics. They are completely different areas that can not be easily related to each other. e.g. the electromagnetic wave to the Wick rotation or Möbius band."
I admit that I struggled with the connections between topics myself, and I wasn't satisfied with my posting. I'd decided to dispense with a classical approach and tackle these topics from the point of view that everything is connected to everything else (what may be called a Theory of Everything or Quantum Gravity or Unified Field approach). I'm convinced the connections are there, and wrote the following in my notepad before getting out of bed this morning (I dreamed about the Riemann hypothesis last night). It clarified things for me and I hope it will help the other ResearchGaters I'm sharing with.
The Riemann hypothesis, proposed in 1859 by the German mathematician Georg Friedrich Bernhard Riemann, is fascinating. It seems to fit these ideas on various subjects in physics very well. The Riemann hypothesis doesn’t just apply to the distribution of prime numbers but can also apply to the fundamental structure of the mathematical universe’s space-time (addressed in the article with the Mobius strip, figure-8 Klein bottle, Wick rotation, and vector-tensor-scalar geometry). In mapping the distribution of prime numbers, the Riemann hypothesis is concerned with the locations of “nontrivial zeros” on the “critical line”, and says these zeros must lie on the vertical line of the complex number plane i.e. on the y-axis in the attached figure of Wick Rotation. Besides having a real part, zeros in the critical line (the y-axis) have an imaginary part. This is reflected in the real +1 and -1 of the x-axis in the attached figure, as well as by the imaginary +i and -i of the y-axis. In the upper half-plane of the attached figure, a quarter rotation plus a quarter rotation equals a half – both quadrants begin with positive values and ¼ + ¼ = ½. (The Riemann hypothesis states that the real part of every nontrivial zero must be 1/2.) While in the lower half-plane, both quadrants begin with negative numbers and a quarter rotation plus a negative quarter rotation equals zero: 1/4 + (-1/4) = 0. In the Riemann zeta function, there may be infinitely many zeros on the critical line. This suggests the y-axis is literally infinite. To truly be infinite, the gravitational and electromagnetic waves it represents cannot be restricted to the up-down direction but must include all directions. That means it would include the horizontal direction and interact with the x-axis – with the waves rotating to produce ordinary mass (and wave-particle duality) in the x-axis’ space-time, and (acting as dark energy) to produce dark matter in the y-axis’ imaginary space-time.
The Riemann hypothesis can apply to the fundamental structure of the mathematical universe’s space-time, and VTS geometry unites the fermions composing the Sun and planets with bosons filling space-time. Thus, the hypothesis also applies to the bodies of the Sun and Mercury themselves. Its link to Wick Rotation means Mercury’s orbit rotates (the Riemann hypothesis is the cause of precession, which doesn’t only exist close to the Sun but throughout astronomical space-time as well as the quantum scale). The link between the half-planes of the hypothesis and the half-periods of Alternating Current’s sine wave suggests the Sun is composed, in part, of AC waves.
Vector-Tensor-Scalar (VTS) Geometry suggests matter is built up layer by layer from the 1 divided by 2 interaction described in the article. The Sun and stars are a special case of VTS geometry in which stellar bodies are built up layer by layer with AC waves in addition to matter such as hydrogen and helium etc. If the Sun only used 1 / 2 (without the AC interaction), it’d be powered by high temperatures and pressures compressing its particles by nuclear fusion. When powered by AC waves, the half-periods entangle to produce phonons which manifest as vibrations apparent in its rising and falling convection cells of, respectively, hot and cooler plasma.
Summation of AC’s sine waves leads to the Sun’s vibratory waves, emission of photons (and to a small extent, of gravitons whose push contributes to planetary orbits increasing in diameter). Because of the connection to Wick rotation, the convective rising and falling in the Sun correlates with time dilation’s rising and falling photons and gravitons. As explained in the article, this slows time near the speed of light and near intense gravitation because the particles interfere with each other. Thus, even if it's never refreshed/reloaded by future Information Technology, our solar system's star will exist far longer than currently predicted.
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Dear Rodney Bartlett I'm confuse. Are you talking about our universe with billions of galaxies, where each galaxy hold several billions of solar systems? I'm sure you know quantum mechanic still a theory and never been proved of it existence, thus what is quantum gravity? Ambiguous empirical evidence shows, nothing is universe is working with our one dimension mathematical, our push/pull of any gravity as far as my research dictated to me. Thanks for sharing..
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II need to know how a suggested mechanism for a problem of players' private information which describes a market of selling and buying things can change the outcome and direction of incentives.
I need to discuss this more. It would be my gratitude if any expert in mechanism design and game theory can help me to model the idea mathematically and prove its efficiency.
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Price of Anarchy is a concept that helps to find out the efficiency of a non-cooperative game or its bounds. There are some good price of anarchy bound results for various designed mechanisms, like if you design your mechanism in such a way that the loss of welfare is low. Please search about price of anarchy.
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I did not find a mathematical formula to find or through which we can determine or choose the correspondences in the case of unequal sample sizes
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Hello Mohammed,
The answer depends on whether your intention in a contrast is to treat means as having equal import regardless of group size (n), which is the unweighted means approach, or to weight means relative to their sample size, which of course, is a weighted means approach.
For an unweighted means approach, two contrasts are orthogonal if the sum of coefficient product terms, across groups, equals zero: e.g., c11c21 + c12c22 + ... + c1kc2k = 0 (where cij is the coefficient used for the i-th contrast and j-th group).
For a weighted means approach, two contrasts are orthogonal if: n1c11c21 + n2c12c22 + ... + nkc1kc2k = 0 (where cij is defined as above and nj is the sample size for group j).
In many experimental designs, the usual intention of behind a contrast is to compare means as having equal import regardless of group size. Therefore (using cij and nj as defined above):
SS(contrast i) = (ci1*M1 + ci2M2 + ... + cikMk)^2 / (ci1^2/n1 + ci2^2/n2 + ... + cik^2/nk) (where Mj is the mean for group j)
Finally, B. J. Winer's 1971 text, Statistical principles in experimental design (2nd ed.). also addresses the issue.
Good luck with your work.
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This question is dedicated only to sharing important research of OTHER RESEARCHERS (not our own) about complex systems, self-organization, emergence, self-repair, self-assembly, and other exiting phenomena observed in Complex Systems.
Please keep in own mind that each research has to promote complex systems and help others to understand them in the context of any scientific filed. We can educate each other in this way.
Experiments, simulations, and theoretical results are equally important.
Links to videos and animations will help everyone to understand the given phenomenon under study quickly and efficiently.
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An electrogenetic interface to program mammalian gene expression by direct current
Jinbo Huang, Shuai Xue , Peter Buchmann, Ana Palma Teixeira & Martin Fussenegger 
Nature Metabolism (2023)
DOI: 10.1038/s42255-023-00850-7
###
Abstract:
Wearable electronic devices are playing a rapidly expanding role in the acquisition of individuals’ health data for personalized medical interventions; however, wearables cannot yet directly program gene-based therapies because of the lack of a direct electrogenetic interface. Here we provide the missing link by developing an electrogenetic interface that we call direct current (DC)-actuated regulation technology (DART), which enables electrode-mediated, time- and voltage-dependent transgene expression in human cells using DC from batteries. DART utilizes a DC supply to generate non-toxic levels of reactive oxygen species that act via a biosensor to reversibly fine-tune synthetic promoters. In a proof-of-concept study in a type 1 diabetic male mouse model, a once-daily transdermal stimulation of subcutaneously implanted microencapsulated engineered human cells by energized acupuncture needles (4.5 V DC for 10 s) stimulated insulin release and restored normoglycemia. We believe this technology will enable wearable electronic devices to directly program metabolic interventions.
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Links between electricity and biology are gradually revealing the true nature of functioning of cells, single cell organisms, plants, and animals.
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Is it possible to create a random 2- dimensional shape using mathematical equations Or in software like 3D-max and AutoCAD? like this one:
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Yes, it is definitely possible to create a random 2-dimensional shape using mathematical equations or software like 3D Max and AutoCAD.
Using Mathematical Equations:
  1. Parametric Equations: You can create a random shape by defining parametric equations that determine the x and y coordinates of points on the shape. For example, you could use sine and cosine functions with random parameters to create smooth curves, or use random step functions to create jagged shapes.
  2. Random Point Generation: Generate random points within a defined boundary and then use interpolation or smoothing techniques to connect these points to form a shape.
  3. Fractal Geometry: You can use fractal algorithms to generate intricate and complex shapes. For example, the Mandelbrot set is a famous example of a fractal shape.
Using 2D Software (e.g., 3D Max and AutoCAD):
  1. Drawing Tools: Most 2D software packages provide various drawing tools that allow you to create shapes freehand, which you can then modify and transform to make them appear random.
  2. Random Transformations: Apply random transformations like scaling, rotation, and translation to basic shapes like circles, squares, or polygons. Repeatedly applying random transformations can lead to more complex and organic shapes.
  3. Noise Functions: Use noise functions to displace points on a shape, giving it a random and irregular appearance.
  4. Procedural Texture Mapping: Create a texture that is procedurally generated using noise patterns or other algorithms, and then apply it to a simple shape. This can give the appearance of a complex and random pattern on the shape.
In both cases, the randomness can be controlled to various extents, allowing you to fine-tune the level of randomness or repeatability of the generated shapes.
Keep in mind that while the shapes may appear random, they are still generated by deterministic algorithms or equations. For truly unpredictable shapes, you might want to explore generative adversarial networks (GANs) or other advanced machine learning techniques, but that goes beyond the scope of traditional mathematical equations and standard 2D software.
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If you have please share it with me at stevegjostwriter@gmail.com Basic Technical
Mathematics with
Calculus, SI Version, 11th edition
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Use the source for book pdf: https://libgen.is/
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In the field of solid mechanics, Navier’s partial differential equation of linear elasticity for material in vector form is:
(λ+G)∇(∇⋅f) + G∇2f = 0, where f = (u, v, w)
The corresponding component form can be evaluated by expanding the ∇ operator and organizing it as follows:
For x-component (u):
(λ+2G)*∂2u/∂x2 + G*(∂2u/∂y2 + ∂2u/∂z2) + (λ+G)*(∂2v/(∂x∂y) + ∂2v/(∂x∂z)) = 0
However, I find it difficult to convert from the component form back to its compact vector form using the combination of divergence, gradient, and Laplacian operators, especially when there are coefficients involved.
Does anyone have any experience with this? Any advice would be appreciated.
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Dear Doan Cong Dinh,
Thank you for your professional input, and I appreciate this valuable article.
I will try to grasp the concepts of quaternion analysis.
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Mathematical Literacy prepares students for real-life situations while using aspects of Mathematics taught in younger grades. Students will be able to do basic tax, calculate water and electricity tariffs, the amount of paint needed to paint a room or the amount of tiles needed to tile a floor. Isn't this adding to adulting life and preparing students for society? While Mathematics can be a compulsory subject for those that want to go to university and have a great talent in Mathematics?
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Education requires special qualifications that are not available to everyone
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Invitation to Contribute to an Edited Book
Banach Contraction Principle: A Centurial Journey­­­­­­
As editors, we are pleased to invite you and your colleagues to contribute your research work to an Edited Book entitled Banach Contraction Principle: A Centurial Journey­­­­­­ to be published by Springer.
The main objective of this book is to focus on the journey of the Banach Contraction Principle, its generalizations, extensions, and consequences in the form of applications that are of interest to a wide range of audiences. Different results for fixed points as well as fixed figures for single-valued and multi-valued mappings satisfying various contractive conditions in distinct spaces have been investigated, and this research is still ongoing. The book is expected to contain new applications of fixed point techniques in diverse fields besides the survey/advancements of 100 years of the celebrated Banach contraction principle.
Please go through the details below for the deadlines.
Full chapter submission: July 12, 2023
Review results: Aug. 12, 2023
Revision Submission: Sept. 01, 2023
Final acceptance/rejection notification: Sept.16, 2023
Submission of final chapters to Springer: Sept.21, 2023
Email your papers to anitatmr@yahoo.com or jainmanish26128301@gmail.com (pdf and tex files) at the earliest possible. Submitted papers will be peer-reviewed by 3 reviewers. On acceptance, authors will be requested to submit the final paper as per the format of the book.
We firmly believe that your contribution will enrich the academic and intellectual content of the book along with opening up of new endeavors of research.
Kindly note that there is no fee or charge from authors at any stage of publication.
Looking forward to your valuable contribution.
Best Regards
Anita Tomar
Professor & Head
Department of Mathematics
Pt. L. M. S. Campus
Sridev Suman Uttarakhand University
Rishikesh-249201, India
&
Manish Jain
Head
Department of Mathematics,
Ahir College, Rewari-123401, India
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Last call.If anyone interested .
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How we express the quantitative research method in mathematical forms including studied variables?
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While quantitative research is a way of studying and analyzing data using mathematical methods, it's important to note that not all research questions or studies can be effectively expressed in mathematical equations. However, if your research involves studying relationships between variables, you can express these relationships using mathematical equations.
For example, if you are studying the relationship between the amount of time students spend studying and their exam scores, you can express this relationship using a mathematical equation. Let X represent the amount of time students spend studying and let Y represent their exam scores. You can then create a simple linear regression model to analyze the relationship between X and Y:
Y = a + bX
where "a" is the y-intercept, or the predicted value of Y when X is 0, and "b" is the slope, or the change in Y for every one-unit increase in X. This equation can be used to predict the exam scores for a given amount of time spent studying (X). Other mathematical methods such as statistical analysis and correlation coefficients can also be used in quantitative research to measure relationships between variables and support conclusions.
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Could something that does not have an end be related to the concept of eternal in nature? Could you cite without any doubt something that could prove it?
If could the infinity to be linked to eternity, is it possible to think about it that it is something without any limit known? How assume that something that you can observe its limits could be infinite in its area? If the infinity doesn't fit in limits, and cannot be totally observed, how we can assume that the infinity could be inside a circle, for example? Or between two numbers as zero and 1, with zero and 1 being limits?
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But a second is a limited and an amount of time, again, so in this case you can see its limits, the begin and the end of it. If you can perceive its end, so is plausible did not assume that the infinity could fit there. If you consider that infinity as eternal them it is something that has a start, but you cannot see, or even perceive its end. Even your perception, has a limit, so cannot perceive the end of it. A perception assume someone that could learn through his senses or through his mind, but noneone can live forever to perceive the infinity in its completeness. Could the infinity fits in limits? Even if you infinitelly divided the spaces between zero and 1 in a given moment you will reach a moment that you will not can divided more, because the space that you are dividing, reached an end, exactly because the area or the space that you are considering, is finity due to the limits considered since the begining.
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ResponderEncaminhar
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Dear Professional/Researchers/Students,
Can you please suggest any technique or mathematical approach to optimize spare parts management(Automobile industry) for improve or increase production.
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Try a start with Jay Forrester: Industrial Dynamics, MIT Press 1961
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Mathematics is an elegance.
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"The Gods Must Be Crazy" is a 1980 comedy film directed by Jamie Uys. It tells the story of a Kalahari bushman who encounters a Coca-Cola bottle and believes it to be a gift from the gods.
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Is it logical to assume that the probability created by nature produces symmetry?
And if this is true, is anti-symmetry just a mathematical tool that can be misleading in specific situations?
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In my opinion, the symmetry created by nature is most closely described by a class of theorems, generically called the "central limit theorem". Deviations from the conditions of the central limit theorem (dependence of factors, dominance of one or more factors, etc.) generate asymmetry, which is observed in nature much more often than symmetry.
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I understand that we can produce that number in MATLAB by evaluating exp(1), or possibly using exp(sym(1)) for the exact representation. But e is a very common constant in mathematics and it is as important as pi to some scholars, so after all these many versions of MATLAB, why haven't they recognize this valuable constant yet and show some appreciation by defining it as an individual constant rather than having to use the exp function for that?
Below is a conversation between me and MATLAB illustrating why MATLAB developers have ZERO common sense... Enjoy the conversation dear fellows and no regret for MATLAB staff...
Me: Hello MATLAB, how is things?
MATLAB: All good! How can I serve you today sir?
Me: Yes, please. Could you give me the value of Euler's number? You know... it's a very popular and fundamental constant in mathematics.
MATLAB: Sure, but wait until I call the exponential function and ask it to evaluate it for me...
Me: Why would you call the exponential function bro??? Isn't Euler's number always constant and its value is well known for thousands of digits?
MATLAB: You will never know sir... Maybe its value will change in the future, so we continuously check its value with the exponential function every time I'm turned on...
Me: You do WHAT!!!
MATLAB: Well... This is a normal procedure sir and I have to do this every time you turn me on...
Me: Stop right there and don't tell me more please...
MATLAB: No, wait sir... I agree with you that this is perhaps one of the most cloddish things that was ever made in the history of programming, but what can I do sir? The guys who developed me actually believe that this is ingenius.
Me: Ooooh oooh ooooh.... reeeeeally!!! Now ain't that something...
MATLAB: They say sir that this is for your security plus there are no applications for that number sir, so why should they care? Even Euler himself, if resurrected again, would fail to find a single application for that number sir. Probably Jacob Bernoulli, the first to discover this number in 1683, would fail also sir, so why should we bother sir? Though it's a mathematical constant and deeply appreciated by the mathematicians around the world for centuries, we don't respect that number sir and find it useless.
Me: Who decides on the importance of Euler's number as a mathematical quantity? Mathematicians or the guys who develop you?
MATLAB: The guys who develop me sir; right?!?!?!?!?
Me: Bro I was obsessed with you in the past and I was truly a big fan of you for more than a decade. But, with the mentality I saw here from the guys who develop you, I believe you will beset with fundamental issues for a long time to come bro... No wonder why Python have beaten you in many directions and became the most popular programming language in the world. Time to move to Python you closed minded and thanks for helping me in my research works in the past decade!!! Good bye for good.
MATLAB: Wait sir... Don't leave please... As a way to compensate for the absence of Euler's number, we offer the 2 symbols i and j sir to represent the complex unity, so the extra symbol is a good compensation for Euler's number...
Me: What did you just say?
MATLAB: Say what?
Me: You provide 2 symbols to represent the same mathematical complex unity quantity, but you have none for Euler's number???
MATLAB: Yeeeeeeeap... you got it.
Me: You can't be serious!
MATLAB: I swear sir by the name of the machine I'm installed in that this is true; I'm not making that up.
Me: But why 2 symbols for the same constant; pick up one for God sake!
MATLAB: Well... There is a wisdom sir for picking 2 symbols for the same constant not just 1.
Me: What is it?
MATLAB: Have you seen the movie "The Man in the Iron Mask" written by Alexandre Dumas and Randall Wallace or read the novel "The Three Musketeers," by the nineteenth century French author Alexandre Dumas sir?
Me: I only saw the movie. But why???
MATLAB: Then you must have heard the motto the movie heros lived by in their glorious youth, "One for all, all for one".
Me: Yes, I did...
MATLAB: We sir were very impressed by this motto, so we came up with a new one.
Me: Impress me!
MATLAB: "i for j, j for i".
Me: You're killing me...
MATLAB: Wait sir, there is more...
Me: More what?????
MATLAB: Many experts around the world project that the number of letters to represent the complex unity in MATLAB may reach 52 letters sir by the end of 2050, so that you can use any English letter (capital or small) to represent the complex unity. How about this sir? Ain't this ingenious also? Sir ?!!?!?!?!?
Me: And this is when common sense was blown up by a nuclear weapon... This circus is over...
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It's interesting to note that Python developers defines Euler's number as a built-in constant by invoking the supporting module math. In particular, math.e gives 2.718281828459045 without the silly computation of the exponential function at 1 as in MATLAB.
Thumbs up Python Developers 👍
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"What is a non-STEM major? A non-STEM major is a major that isn't in science, technology, engineering, or mathematics. This means non-STEM majors include those in business, literature, education, arts, and humanities. In STEM itself, programs in this category include ones that emphasize research, innovation or the development of new technologies."
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The preference of students for non-STEM (Science, Technology, Engineering, and Mathematics) majors over STEM majors can have various implications for a nation's future in terms of science and technology advancement. However, it's important to note that the situation is more nuanced, and the impact of such preferences can vary depending on several factors.
Here are some considerations:
  1. Diversity of Skills: While STEM fields are crucial for technological advancement and innovation, non-STEM fields also play a significant role in society. Business, literature, arts, humanities, and other non-STEM fields contribute to the diversity of skills and knowledge within a society, fostering well-rounded individuals who can approach challenges from various perspectives.
  2. Economic Contribution: Non-STEM fields can be profitable and contribute to the economy in different ways. For example, the entertainment industry, arts, design, and business sectors generate revenue and create jobs. A balanced mix of STEM and non-STEM professionals is necessary for a thriving economy.
  3. Interdisciplinary Collaboration: The future of innovation often lies in interdisciplinary collaboration. Many complex challenges require the integration of STEM and non-STEM expertise. For example, solving environmental issues may require input from environmental scientists (STEM) and policy experts (non-STEM).
  4. Education and Awareness: Sometimes, students may choose non-STEM majors due to a lack of awareness about the potential and opportunities in STEM fields. Addressing this issue by promoting STEM education and showcasing the exciting prospects in STEM careers can influence students' choices positively.
  5. Global Perspective: The impact of students' preferences for majors extends beyond national boundaries. In a globalized world, innovation and progress depend on collaboration among countries, regardless of their STEM/non-STEM focus.
  6. Balancing the Workforce: Nations need a diverse workforce with a mix of STEM and non-STEM professionals. An overemphasis on STEM majors may lead to a shortage of skilled professionals in non-STEM fields and potentially hinder the growth of industries that rely on such expertise.
Ultimately, the ideal scenario is a balanced approach that encourages students to pursue their passions and interests while being informed about the opportunities and challenges in various fields. The promotion of STEM education is crucial for technological advancement, but it should be complemented with efforts to recognize the value of non-STEM fields and encourage a diverse range of career choices. An educated and well-rounded society, with a mix of STEM and non-STEM professionals, is essential for holistic progress and development.
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Here is list of Impact factor 2023.
Journal Citation Reports 2023
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This is not the complete list ... where are all the Human Resource Management journals, for example?
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Given: x = 10sin(0.2t), y = 10cos(0.2t), z = 2.5sin(0.2t) (1)
There exists the following mathematical relationship:
u = x'cos(z) + y'sin(z),
v = -x'sin(z) + y'cos(z), (2)
r = z'
How to express rd=[x,y,z,u,v,r]' in the form of drd/dt = h(rd), where the function h(rd) does not explicitly depend on the time variable t?
My approach is as follows:
From (2), we have:
x' = ucos(z) - vsin(z), y' = usin(z) + vcos(z), z' = r (3) with initial values x(0) = 0, y(0) = 10, z(0) = 0
From (2), we have:
u' = x''cos(z) - x'sin(z)z' + y''sin(z) + y'cos(z)z',
v' = -x''sin(z) - x'cos(z)z' + y''cos(z) - y'sin(z)z',
r' = z''
By calculating based on (1), we obtain:
x' = 2cos(0.2t) = 0.2y
x'' = -0.4sin(0.2t) = -0.04x
y' = -2sin(0.2t) = -0.2x (4)
y'' = -0.4cos(0.2t) = -0.04y
z' = 0.5cos(0.2t) = 0.05y
z'' = -0.1sin(0.2t) = -0.01x
Substituting x', x'', y', y'', z', z'' into (4), we get:
u' = -0.04xcos(z) - 0.2y * 0.05ysin(z) - 0.04ysin(z) - 0.2x * 0.05y*cos(z)
v' = -x''sin(z) - x'cos(z)z' + y''cos(z) - y'sin(z)z'
r' = z''
with initial values u(0)=2, v(0)=0, r(0)=0.5
The calculation process is accurate, but is the problem-solving approach correct?
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Qamar Ul Islam Thank you for your prompt and helpful response. I appreciate your insights and suggestions on how to resolve the discrepancy. I will follow your advice and check my code, numerical method, and solver parameters. I hope to get a better result with your guidance. Thank you again for your time and expertise.
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I have a dataset of rice leaf for training and testing in machine learning. Here is the link: https://data.mendeley.com/datasets/znsxdctwtt/1
I want to develop my project with these techniques;
  1. RGB Image Acquisition & Preprocessing (HSV Conversation, Thresholding and Masking)
  2. Image Segmentation(GLCM matrices, Wavelets(DWT))
  3. Classifications (SVM, CNN ,KNN, Random Forest)
  4. Results with Matlab Codings.
  • But I have a confusion for final scores for confusion matrices. So I need any technique to check which extraction method is good for dataset.
  • My main target is detection normal and abnormal(disease) leaf with labels.
#image #processing #mathematics #machinelearning #matlab #deeplearning
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There are two commonly used extraction techniques that can be appropriate for rice plant disease detection: (1) Color-based Extraction and (2) Texture-based Extraction.The most appropriate extraction technique for rice plant disease detection depends on the specific requirements and characteristics of the dataset and the detection algorithm being used.
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I am trying to find a mathematical model of a loudspeaker in an enclosure. By this, I mean an equation that describes the electrical impedance of the speaker as a function of the physical characteristics of the cone and the air in its enclosure.
As an analogy, I am familiar with the model of a servo motor, which relates its electrical impedance to the inertia of the load and the shaft speed. You can read an article I wrote about that at https://www.researchgate.net/publication/355587208_Regenerative_Brake_Charges_Your_Caving_Lamp_Whilst_You_Abseil.
Interestingly, one of the terms in that expression is the inertia divided by the product of torque constant and voltage constant, which has the dimensions of capacitance, showing that a electrical model of a servo motor includes a large capacitance. I am looking for something similar for loudspeakers, which shows how the physical characteristics of the enclosure and speaker are reflected in its electrical circuit model.
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Dear friend David Gibson
Understanding the relationship between the physical characteristics of a loudspeaker and its enclosure and their representation in a mathematical circuit model is an intriguing endeavor.
The mathematical modeling of a loudspeaker and its enclosure involves the interplay of electrical, mechanical, and acoustical components.
Let's explore some key aspects:
1. Electrical components: The electrical model of a loudspeaker typically includes an electrical impedance that represents the combined effect of the voice coil resistance, inductance, and the capacitive behavior of the driver. The voice coil resistance can be related to the conductor material and dimensions. The voice coil inductance is influenced by the coil winding geometry and the magnetic circuit design. The capacitance component can arise from various sources, such as the inherent capacitance between the voice coil and the speaker's diaphragm.
2. Mechanical components: The mechanical behavior of the loudspeaker driver is typically represented by a combination of mass, compliance, and damping. The mass reflects the moving components of the driver, such as the diaphragm and voice coil. Compliance characterizes the flexibility of the suspension system that holds the diaphragm in place. Damping accounts for energy dissipation mechanisms, such as losses due to air resistance and materials.
3. Acoustical components: The interaction between the loudspeaker driver and the air in the enclosure results in sound radiation. The enclosure affects the loudspeaker's performance by providing an acoustic load, influencing resonances, and contributing to the overall system response. The enclosure geometry, volume, and construction materials play a crucial role in shaping the acoustic output.
Creating a comprehensive mathematical model that captures all the complexities of a loudspeaker and its enclosure is challenging. However, various simplified models exist, such as the Thiele-Small parameters, which describe the loudspeaker's electrical and mechanical characteristics in a simplified manner. These parameters, combined with enclosure-related parameters like volume and port characteristics, can provide insights into the system behavior.
It's important to note that loudspeaker design and modeling involve a multidisciplinary approach, combining electrical engineering, mechanical engineering, acoustics, and signal processing. Advanced modeling techniques, such as finite element analysis (FEA) and boundary element method (BEM), are often employed for more accurate representations.
To delve deeper into the specific mathematical equations and modeling techniques, consulting specialized literature, research papers, or textbooks on loudspeaker design and acoustics can provide valuable insights.
Let us keep exploring this interesting topic.
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Подтверждается мнение о том, что математическая подготовка физиков, даже ведущих, недостаточна. Именно такие претензии В.А. Фок и Н.Н. Боголюбов предъявляли Ландау. Математика не сводится к набору формул и решения уравнений. Предложена формулировка принципа эквивалентности гравитационного поля и ускоренной системы отсчета на основе стандартного математического эпсилон-дельта метода (черновик).
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Hi, My name Is Debi, I'm master student Mathematics Education major at Yogyakarta State University 2nd month. Please give me advice what the trend topic on mathematics education aspecially topic learning media math and learning psychology of math. May you share with me about it on your country or your universisty. Thank you so much.
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Development and Validation of Instructional Materials in Teaching Trigonometry
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Actually, I am working these field. Sometimes I don't understand what should I do. If anyone supervise me, I will be thankful.
I have a dataset of rice leaf for training and testing in machine learning. Here is the link: https://data.mendeley.com/datasets/znsxdctwtt/1
I want to develop my project with these techniques;
  1. RGB Image Acquisition & Preprocessing (HSV Conversation, Thresholding and Masking)
  2. Image Segmentation(GLCM matrices, Wavelets(DWT))
  3. Classifications (SVM, CNN ,KNN, Random Forest)
  4. Results with Matlab Codings.
  • But I have a confusion for final scores for confusion matrices. So I need any technique to check which extraction method is good for dataset.
  • My main target is detection normal and abnormal(disease) leaf with labels.
Attached image is collected from a paper.
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Sure, I'd be happy to provide you with guidelines for your Matlab project. Please reach out to me via email at erickkirui@kabarak.ac.ke, and I will promptly assist you with the necessary guidance for your project
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Image processing is the beauty of mathematics. Because many basic parts of mathematics used in this field. But I have a confusion about extraction methods.
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Image data processing is one of the most under-explored problems in the data science community.
Every developer has a unique way of doing it. Some of the tools and platforms used in image preprocessing include Python, Pytorch, OpenCV, Keras, Tensorflow, and Pillow.
Here's a useful link to the best programs available for image preprocessing.
These are some great software options in my opinion. Let me know if this is helpful!
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The statement inquires about the potential mathematical relationship between entropy and standard deviation. Entropy and standard deviation are both concepts used in statistics and information theory.
Entropy is a measure of uncertainty or randomness in a probability distribution. It quantifies the average amount of information required to describe an event or a set of outcomes. It is commonly used in the field of information theory to assess the efficiency of data compression algorithms or to analyze the randomness of data.
On the other hand, standard deviation is a statistical measure that quantifies the dispersion or variability of a set of data points. It provides information about the average distance of data points from the mean or central value. It is widely used in data analysis to understand the spread of data and to compare the variability among different datasets.
While entropy and standard deviation are both statistical measures, they capture different aspects of data. Entropy focuses on the uncertainty or information content, while standard deviation focuses on the dispersion or variability. As such, there is no direct mathematical relationship between entropy and standard deviation.
However, depending on the specific context and the nature of the data, there might be some indirect connections or relationships between entropy and standard deviation. For instance, in certain probability distributions, higher entropy might be associated with higher variability or larger standard deviation, but this relationship is not universally applicable.
In summary, while entropy and standard deviation are both important statistical measures, they serve different purposes and do not have a direct mathematical relationship. The relationship between them, if any, would depend on the specific characteristics of the data being analyzed.
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I appreciate your reply, and it has provided me with a clear understanding of the connection between entropy and standard deviation.
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SOURCE OF MAJOR FLAWS IN COSMOLOGICAL THEORIES:
MATHEMATICS-TO-PHYSICS APPLICATION DISCREPENCY
Raphael Neelamkavil, Ph.D., Dr. phil.
The big bang theory has many limitations. These are,
(1) the uncertainty regarding the causes / triggers of the big bang,
(2) the need to trace the determination of certain physical constants to the big bang moments and not further backwards,
(3) the necessity to explain the notion of what scientists and philosophers call “time” in terms of the original bang of the universe,
(4) the compulsion to define the notion of “space” with respect to the inner and outer regions of the big bang universe,
(5) the possibility of and the uncertainty about there being other finite or infinite number of universes,
(6) the choice between an infinite number of oscillations between big bangs and big crunches in the big bang universe (in case of there being only our finite-content universe in existence), in every big hang universe (if there are an infinite number of universes),
(7) the question whether energy will be lost from the universe during each phase of the oscillation, and in that case how an infinite number of oscillations can be the whole process of the finite-content universe,
(8) the difficulty involved in mathematizing these cases, etc.
These have given rise to many other cosmological and cosmogenetic theories – mythical, religious, philosophical, physical, and even purely mathematical. It must also be mentioned that the thermodynamic laws created primarily for earth-based physical systems have played a big role in determining the nature of these theories.
The big bang is already a cosmogenetic theory regarding a finite-content universe. The consideration of an INFINITE-CONTENT universe has always been taken as an alternative source of theories to the big bang model. Here, in the absence of conceptual clarity on the physically permissible meaning of infinite content and without attempting such clarity, cosmologists have been accessing the various mathematical tools available to explain the meaning of infinite content. They do not also seem to keep themselves aware that locally possible mathematical definitions of infinity cannot apply to physical localities at all.
The result has been the acceptance of temporal eternality to the infinite-content universe without fixing physically possible varieties of eternality. For example, pre-existence from the past eternity is already an eternality. Continuance from any arbitrary point of time with respect to any cluster of universes is also an eternality. But models of an infinite-content cosmos and even of a finite-content universe have been suggested in the past one century, which never took care of the fact that mathematical infinity of content or action within a finite locality has nothing to do with physical feasibility. This, for example, is the source of the quantum-cosmological quick-fix that a quantum vacuum can go on create new universes.
But due to their obsession with our access to observational details merely from our local big bang universe, and the obsession to keep the big bang universe as an infinite-content universe and as temporally eternal by using the mathematical tools found, a mathematically automatic recycling of the content of the universe was conceived. Here they naturally found it safe to accommodate the big universe, and clearly maintain a sort of eternality for the local big bang universe and its content, without recourse to external creation.
Quantum-cosmological and superstrings-cosmological gimmicks like considering each universe as a membrane and the “space” between them as vacuum have given rise to the consideration that it is these vacua that just create other membranes or at least supplies new matter-energy to the membranes to continue to give rise to other universes. (1) The ubiquitous sensationalized science journalism with rating motivation and (2) the physicists’ and cosmologists’ need to stick to mathematical mystification in the absence of clarity concurring physical feasibility in their infinities – these give fame to the originators of such universes as great and original scientists.
I suggest that the need to justify an eternal recycling of the big bang universe with no energy loss at the fringes of the finite-content big bang universe was fulfilled by cosmologists with the automatically working mathematical tools like the Lambda term and its equivalents. This in my opinion is the origin of the concepts of the almighty versions of dark energy, virtual quantum soup, quantum vacuum, ether, etc., for cosmological applications. Here too the physical feasibility of these concepts by comparing them with the maximal-medial-minimal possibilities of existence of dark energy, virtual quantum soup, quantum vacuum, ether, etc. within the finite-content and infinite-content cosmos, has not been considered. Their almighty versions were required because they had to justify an eternal pre-existence and an eternal future for the universe from a crass physicalist viewpoint, of which most scientists are prey even today. (See: Minimal Metaphysical Physicalism (MMP) vs. Panpsychisms and Monisms: Beyond Mind-Body Dualism: https://www.researchgate.net/post/Minimal_Metaphysical_Physicalism_MMP_vs_Panpsychisms_and_Monisms_Beyond_Mind-Body_Dualism)
I believe that the inconsistencies present in the mathematically artificialized notions and in the various cosmogenetic theories in general are due to the blind acceptance of available mathematical tools to explain an infinite-content and eternally existent universe.
What should in fact have been done? We know that physics is not mathematics. In mathematics all sorts of predefined continuities and discretenesses may be created without recourse to solutions as to whether they are sufficiently applicable to be genuinely physics-justifying by reason of the general compulsions of physical existence. I CONTINUE TO ATTEMPT TO DISCOVER WHERE THE DISCREPENCIES LIE. History is on the side of sanity.
One clear example for the partial incompatibility between physics and mathematics is where the so-called black hole singularity is being mathematized by use of asymptotic approach. I admit that we have only this tool. But we do not have to blindly accept it without setting rationally limiting boundaries between the physics of the black hole and the mathematics applied here. It must be recognized that the definition of any fundamental notion of mathematics is absolute and exact only in the definition, and not in the physical counterparts. (See: Mathematics and Causality: A Systemic Reconciliation, https://www.researchgate.net/post/Mathematics_and_Causality_A_Systemic_Reconciliation)
I shall continue to add material here on the asymptotic approach in cosmology and other similar theoretical and application-level concepts.
Bibliography
(1) Gravitational Coalescence Paradox and Cosmogenetic Causality in Quantum Astrophysical Cosmology, 647 pp., Berlin, 2018.
(2) Physics without Metaphysics? Categories of Second Generation Scientific Ontology, 386 pp., Frankfurt, 2015.
(3) Causal Ubiquity in Quantum Physics: A Superluminal and Local-Causal Physical Ontology, 361 pp., Frankfurt, 2014.
(4) Essential Cosmology and Philosophy for All: Gravitational Coalescence Cosmology, 92 pp., KDP Amazon, 2022, 2nd Edition.
(5) Essenzielle Kosmologie und Philosophie für alle: Gravitational-Koaleszenz-Kosmologie, 104 pp., KDP Amazon, 2022, 1st Edition.
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The cause of gravity
Gravity is caused by the product of m and M in 2 different positions.
The cause of gravity must be a concept with information about both the values, m and M.
The only concept with this information is the ether.
Gravity must be a process in 2 steps.
M (Earth) causes a change in the ether. A radial ether wind.
This ether wind is the cause of gravity.
Michelson measured horizontally to avoid gravity. He did not see that the ether wind is gravity. You can feel the ether wind just now in your bottom.
First step: matter tells ether how to move.
Second step: ether tells matter how to move.
Gravity is action at a distance at a time delay.
You are not pulled by Earth, but pushed by the ether, although Earth is the primary source.
John-Erik
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In mathematics, many authors working in the area of integer sequence, fibonacci polynomial, perin sequence......
Now what is the current research topics in this subject?.
I request , suggest some research topics which is related to Fibonacci sequence.
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V. James : You started the following post/discussion thread on June 01, 2023, and I quote verbatim:
"In mathematics, many authors working in the area of integer sequence, fibonacci polynomial, perin sequence......
Now what is the current research topics in this subject?.
I request , suggest some research topics which is related to Fibonacci sequence."
The topic that I am about to suggest to you may not necessarily be related to the Fibonacci sequence, but I think you can try looking up recursively enumerable sets. In deed, the problem of determining whether a specific rational number greater than unity is an abundancy index (i.e. a ratio of the form sigma(m)/m, for some positive integer m and where sigma(m) is the classical sum of divisors of m) or an abundancy outlaw (see Holdener and Stanton's paper [https://www.researchgate.net/publication/264925121] published in JIS [2007]) is equivalent to finding out whether the set of abundancy indices (or the set of abundancy outlaws, for that matter) is a recursive set. (You can also refer to the following paper: https://cs.uwaterloo.ca/journals/JIS/VOL23/Holdener/holdener4.pdf, where it is mentioned that: "In the early 1970’s, [C. W.] Anderson conjectured that the set Image(I) [the set of abundancy indices] is a recursive set, meaning that there exists a recursive algorithm that can be employed to determine whether or not a given rational number k/m is an outlaw. This remains an open problem today.")
If you find this particular topic interesting, then you may contact me privately via e-mail (it is indicated in this recent paper of mine: https://www.researchgate.net/publication/370979239), and we can collaborate.
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I am doing a project on plastic biodegradation by G. mellonella larvae. I am doing a project on plastic biodegradation by G. mellonella larvae. I am just getting into this field and I want to know how I can determine the biodegradation. Do I have to use some mathematical formula? Thank you very much.
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I am working with expanded polystyrene. I understand, thank you very much.
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From Newton's Metaphysics to Einstein's Theology!
The crisis in modern theoretical physics and cosmology has its root in its use, along with theology as a ruling-class tool, since medieval Europe. The Copernican revolution overthrowing the geocentric cosmology of theology led to unprecedented social and scientific developments in history. But Isaac Newton’s mathematical idealism-based and on-sided theory of universal gravitational attraction, in essence, restored the idealist geocentric cosmology; undermining the Copernican revolution. Albert Einstein’s theories of relativity proposed since the turn of the 20th century reinforced Newtonian mathematical idealism in modern theoretical physics and cosmology, exacerbating the crisis and hampering further progress. Moreover, the recognition of the quantum world - a fundamentally unintuitive new realm of objective reality, which is in conflict with the prevailing causality-based epistemology, requires a rethink of the philosophical foundation of theoretical physics and cosmology in particular and of natural science in general.
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Today we demand of physics some understanding of existence itself.
John Wheeler
(9 Jul 1911 - 13 Apr 2008)
Quoted in Denis Brian, The Voice Of Genius: Conversations with Nobel Scientists and Other Luminaries, 127
The only thing harder to understand than a law of statistical origin would be a law that is not of statistical origin, for then there would be no way for it—or its progenitor principles—to come into being. On the other hand, when we view each of the laws of physics—and no laws are more magnificent in scope or better tested—as at bottom statistical in character, then we are at last able to forego the idea of a law that endures from everlasting to everlasting.
— John Wheeler
In 'Law without Law' (1979), in John Archibald Wheeler and Wojciech Hubert Zurek (eds.), Quantum Theory and Measurement(1983), 203.
No theory of physics that deals only with physics will ever explain physics. I believe that as we go on trying to understand the universe, we are at the same time trying to understand man.
— John Wheeler
In The Intellectual Digest (June 1973), as quoted and cited in Mark Chandos, 'Philosophical Essay: Story Theory", Kosmoautikon: Exodus From Sapiens (2015)
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In the world of science, Jehovah was superseded by Copernicus, Galileo, and Kepler. All that God told Moses, admitting the entire account to be true, is dust and ashes compared to the discoveries of Descartes, Laplace, and Humboldt. In matters of fact, the bible has ceased to be regarded as a standard. Science has succeeded in breaking the chains of theology. A few years ago, Science endeavored to show that it was not inconsistent with the bible. The tables have been turned, and now, Religion is endeavoring to prove that the bible is not inconsistent with Science. The standard has been changed. Robert G. Ingersoll, Some Mistakes of Moses
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If we should calculate it by experimental test on target organism or we should find it mathematically?
co- toxicity factor =(O-E)*100/E
that
O is observed % mortality of combined plant extracts
E is expedcted m% mortality
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In the context of the co-toxicity factor formula, the term "expected mortality" refers to the predicted or estimated mortality rate of an organism under the combined effects of multiple toxic substances. The co-toxicity factor formula is used to assess the combined toxicity of different substances on an organism, taking into account their toxicities.
To calculate the expected mortality using the co-toxicity factor formula, you typically follow these steps:
  1. Determine the individual toxicity values: Obtain the toxicity values or toxicological data for each of the substances of interest. This could be in the form of lethal concentration (LC50) or lethal dose (LD50) values, which represent the concentration or dose at which 50% mortality is expected.
  2. Calculate the co-toxicity factor: Calculate the co-toxicity factor for each substance by dividing the concentration or dose of the substance by its individual toxicity value. This step involves normalizing the concentration or dose of each substance concerning its toxicity.
  3. Calculate the expected mortality: Sum up the co-toxicity factors for all the substances. The resulting value represents the expected mortality of the organism under the combined effects of the substances.
It's important to note that the co-toxicity factor formula is a simplified approach to assess combined toxicity and may not account for all possible interactions between substances. The formula assumes an additive or independent effect of the substances. In reality, interactions between substances can be more complex, including synergistic (enhanced) or antagonistic (reduced) effects.
Furthermore, the specific formula or equation used for calculating the co-toxicity factor may vary depending on the context, study design, and toxicological data available. It is essential to consult relevant literature, regulatory guidelines, or expert advice to ensure the appropriate use of the co-toxicity factor formula and interpretation of the results in your specific research or assessment.
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Bonjour a tous,
je voudrais savoir la relation entre la temperature du verre ( viscosite ) et le radius de la fibre de verre?
merci
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La relation entre la température du verre et le diamètre de la fibre de verre dépend de plusieurs facteurs, notamment la composition du verre et le processus de fabrication spécifique. Il n'y a pas de formule mathématique générale unique qui puisse décrire cette relation pour tous les types de verre.
Cependant, pour certains types de fibres de verre, une approximation couramment utilisée est la formule de coefficient de dilatation thermique linéaire. Cette formule relie la variation du diamètre d'un matériau à sa variation de température. La formule générale est la suivante :
ΔD = α * D * ΔT
où :
  • ΔD est le changement de diamètre de la fibre de verre,
  • α est le coefficient de dilatation thermique linéaire du verre,
  • D est le diamètre initial de la fibre de verre, et
  • ΔT est la variation de température.
Le coefficient de dilatation thermique linéaire (α) est une propriété spécifique du matériau de la fibre de verre et peut varier en fonction de sa composition. Il est généralement exprimé en unités de (1/°C) ou (1/K).
Il est important de noter que cette formule est une approximation et peut ne pas être exacte pour tous les types de verre ou dans toutes les plages de température. Pour obtenir des résultats précis, il est recommandé de consulter les spécifications techniques du matériau de la fibre de verre spécifique que vous utilisez, ou de vous référer aux données fournies par le fabricant.
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- What is the relationship between the scientific understanding of the world and the reality in nature? It may be said that the real world is much richer in terms of structure than the results of the physical and mathematical models that were developed for it. In these models, there is one or more angles of view limited to the natural phenomenon in question, inventing a complete theory, whose results are correct from any angle, may be the dream theory of "Theory of Everything"!
- Is there an unknown form of mathematics that has not yet been found to solve all the problems of a theory of everything?
- Is it necessary to change the conceptual view of physicists on the subject of the theory of everything? So that this new look can include new concepts for problem solving?
- Is there a mathematical system, which has a distinct ability to represent the maximum possible states of the world!?
- Is it possible to imagine that the world is like a carpet that has infinite texture, but its colors and roles are determined by scientists with their theories about the world?! And are we looking for the most realistic pattern and design for the world's carpet?
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The relationship between scientific understanding and the reality of nature is a complex and ongoing philosophical debate. Science aims to provide explanations and models that describe and predict the behavior of the natural world. However, it is important to recognize that scientific models are simplifications and abstractions of reality, and they can never fully capture the intricacies and complexities of the real world.
  1. Unknown Form of Mathematics: It is possible that there may be undiscovered mathematical frameworks or tools that could help in developing a comprehensive theory of everything. The search for such frameworks is an active area of research in theoretical physics and mathematics. However, it is challenging to predict what form this new mathematics might take or whether it exists at all.
  2. Changing Conceptual View: Scientists continually refine their conceptual frameworks and theories as new evidence and insights emerge. The quest for a theory of everything may require physicists to adopt new conceptual viewpoints and frameworks to address the outstanding challenges. This flexibility allows for the incorporation of new concepts and approaches in problem-solving.
  3. Mathematical System Representing Possible States: Mathematics is a powerful tool for representing and describing the natural world, but it is not clear if there exists a single mathematical system that can encompass all possible states of the world. Different branches of mathematics are often used to describe specific phenomena or aspects of reality. The search for a comprehensive mathematical framework that can represent all possible states of the world is an ongoing pursuit.
  4. The world as a Carpet: The analogy of the world is like a carpet with scientists searching for the most realistic pattern and design can be seen as a metaphorical representation of the scientific endeavor. Scientists develop theories and models that attempt to capture the underlying patterns and principles governing the natural world. However, it is important to remember that scientific theories are human constructs that are constantly refined and updated as our understanding deepens.
In summary, the relationship between scientific understanding and the reality of nature is complex and evolving. Scientific models and theories aim to capture aspects of reality, but they are limited abstractions. The search for a theory of everything requires ongoing exploration, including potential changes in conceptual viewpoints, the possibility of undiscovered mathematical frameworks, and the continuous refinement of scientific models to approach a more complete understanding of the world.
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Three grade teachers response can help researcher measure the students creativity? Age of students is 8-11 years
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It is possible for a mathematics class teacher to report on the creativity of students in third grade. However, it is important to clarify what is meant by "creativity" and to use a valid and reliable measure to assess it. In general, creativity can be defined as the ability to generate novel and useful ideas, and it can be assessed through a variety of measures such as divergent thinking tasks, creative problem-solving tasks, and self-assessment scales. It is also important to consider the limitations of relying solely on teacher reports to assess creativity, as teachers may have biases and may not always have a complete picture of a student's creative abilities. Therefore, a more comprehensive approach that includes multiple sources of information would be preferable.
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Our department is offering an elective on Fluid Mechanics in daily life. The course is supposed to be more of a physical treatment of the fluid phenomena rather than mathematical. I would like some recommendations for books on the subject which are light and speak about fluid physics from a physical and application based perspective
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Filippo Maria Denaro wrote, "I don’t think that any fluid dynamics course can be done without some fundamental math.." I completely agree. Among the many books on Fluid Mechanics, I find that the one that best embraces the physical point of view of the discipline is that of Guyon, E., Hulin, J. P., Petit, L., & de Gennes, P. G. (2001). Physical hydrodynamics, EDP sciences, whose first edition (2001) was prefaced by Pierre Gilles de Gennes (Nobel Prize for Physics) who did not lack praise for the particularity of the integration of physics in the very conception of the book. The book is in its third edition and has more than 750 citations.
Guyon, E., Hulin, J. P., & Petit, L. (2021). Hydrodynamique physique. EDP sciences.
Even if the book is in French, I think it would be interesting to consult it if only to have an idea of its construction
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hello
How can I determine the tortuosity factor in a porous material with simple mathematical formula?
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What about using the fractal dimension (box-counting) as a measure? Here is a paper on tortuosity.
Regards,
Joachim
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Apart from the mathematical systems that confirm human feelings and perceptive sensors, there are countless mathematical systems that do not confirm these sensors and our sensory data! A question arises, are the worlds that these mathematical systems evoke are real? So in this way, there are countless worlds that can be realized with their respective physics. Can multiple universes be concluded from this point of view?
Don't we see that only one of these possible worlds is felt by our body?! Why? Have we created mathematics to suit our feelings in the beginning?! And now, in modern physics and the maturation of our powers of understanding, we have created mathematical systems that fit our dreams about the world!? Which of these mathematical devices is actually true about the world and has been realized?! If all of them have come true! So there is no single and objective world and everyone experiences their own world! If only one of these mathematical systems has been realized, how is this system the best?!
If the worlds created by these countless mathematical systems are not real, why do they exist in the human mind?!
The last question is, does the tangibleness of some of these mathematical systems for human senses, and the intangibleness of most of them, indicate the separation of the observable and hidden worlds?!
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I know that δ(f(x))=∑δ(x−xi)/f′(xi). What will be the expression if "f" is a function of two variables, i.e. δ(f(x,y))=?
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K. Kassner You are right.
The method that I proposed may not work for all functions f(x,y), especially if they are continuous and do not have isolated zeros. In that case, one might try to separate the integrals or use a coordinate transformation as you suggested in your comment. For example, if we use polar coordinates $(r,\theta)$, then we have
$$\delta(f(r,\theta))=\frac{1}{r}\delta(r-r(\theta))$$
where $r(\theta)$ is the zero of f(r,$\theta$) as a function of r for a fixed $\theta$. This can be seen by using the Jacobian of the transformation and the property of the delta function.
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Why prime numbers have a great importance in mathematics for the rest of the numbers ?
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I worked considerable time related to prime numbers but it seems to obey no rules at all and they go up to both negative and positive infinity !
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Vehicle routing problem is a classical application case of Operation research.
I need to implement the same in electric vehicle routing problem with different constraints.
I want to understand mathematics behind this. The journals available discuss different applications without much talking of mathematics.
Any book/ basic research paper/ PhD/ m.tech thesis will do the needful.
Thanks in advance.
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There is a vast literature on exact and heuristic approaches to vehicle routing problems. (You are looking at several thousands journal articles!)
If you are interested in exact approaches, then you need to be familiar with the following:
(i) The basics of integer programming, including the branch-and-bound method and cutting-plane methods.
(ii) The basics of computational complexity, including the concept of polynomial-time algorithms, pseudo-polynomial-time algorithms and NP-completeness.
(iii) Elementary graph theory (nodes, edges, arcs, and so on).
It also helps to know a bit about:
(iv) Dynamic programming.
(v) Lagrangian relaxation.
(vi) The branch-and-cut method, which combines branch-and-bound with strong cutting planes from polyhedral studies.
(vii) The branch-and-price method, which combines branch-and-bound with Dantzig-Wolfe decomposition and dynamic programming.
A good place to start is the book "The Vehicle Routing Problem", edited by Toth and Vigo. There is also "The Vehicle Routing Problem: Latest Advances and New Challenges", edited by Golden et al.
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Qm is the ultimate realists utilization of the powerful differential equations, because the integer options and necessities of solutions correspond to nature's quanta.
The same can be said for GR whose differential manifolds, an sdvanced concept or hranch in mathematics, have a realistic implementation in nature compatible motional geodesics.
1 century later,so new such feats have been possible, making one to think if the limit of heuristic mathematical supplementation in powerful ways towards realist results in physics in reached.
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Yazen Alawaideh hello,
I am not talking about the limit of mathematics or. Physics but about the limit of combining them to make wonders such these 2 theories. Despite their issues they are the lighthouses of physics.
Still maybe they are the last expression of genuiys childs from the marriage, as for 30 years and tens of millions of dollars research no unified or underliing theory with better or more fundamental mathematics has been found..
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Applying mathematical knowledge in research models: This question has been in my mind for a long time. Can advance mathematics and applied mathematics solve all the problems in modeling research? Especially the formula derivation in the theoretical model part, can the analysis conclusion be obtained through multiple derivations or other methods? You have also read some mathematics-related publications yourself, and you have to admire the mystery of mathematics.
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We all know that Mathematics include Reading , Writing & Arithmetic & its starts with every action of our life image & as such it is the action of our performance & image in every part of our life. With this some years back I have expressed my views in this areas which I submit herewith for your kind perusal .
In my early days students interested in Mathematics & scoring full marks they can perform in their working of mathematics either by listening to music or song or prior to during a home work they have formulated a habit of reading either a lesson or interested topics & after carrying out their working system they used to give justice to the subject of Mathematics.
This is my personal opinion
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Which areas in mathematics education is trending currently
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As an AI language model, I can provide an overview of some current research trends in mathematics education up until my knowledge cutoff in September 2021. However, please note that the field of research is constantly evolving, and there may have been new developments since then. Here are a few prevalent research trends in mathematics education:
  1. Technology Integration: Researchers are exploring the effective use of technology in mathematics education. This includes studying the impact of digital tools, interactive software, simulations, and online resources on teaching and learning mathematics. Additionally, there is a focus on designing technology-enhanced learning environments and investigating the role of technology in fostering conceptual understanding and problem-solving skills.
  2. Problem-Solving and Mathematical Thinking: There is an emphasis on promoting problem-solving skills and mathematical thinking among students. Researchers are investigating instructional strategies and interventions that help students develop problem-solving abilities, reasoning skills, and a deep conceptual understanding of mathematical concepts. This includes exploring the use of open-ended problems, mathematical modeling, and real-world contexts to engage students in authentic mathematical experiences.
  3. Learning Trajectories and Progressions: Research in this area focuses on understanding the developmental progression of mathematical concepts and skills. Learning trajectories provide a framework for mapping out the sequence of learning in different mathematical domains and identifying the key milestones along the way. By understanding how students progress through these trajectories, researchers aim to develop effective instructional approaches and interventions that cater to students' diverse learning needs.
  4. Assessment and Feedback: There is ongoing research on developing innovative assessment methods and providing effective feedback in mathematics education. This includes investigating formative assessment strategies, computer-based assessments, and alternative approaches to evaluating mathematical competencies. Researchers are also exploring the role of feedback in enhancing students' learning and understanding of mathematics.
  5. Equity and Access: Mathematics education research is increasingly focusing on issues of equity, diversity, and inclusion. Researchers are examining the factors that contribute to achievement gaps among different student populations and investigating strategies to promote equitable mathematics learning experiences. This includes exploring culturally responsive teaching practices, addressing stereotype threats, and promoting access to high-quality mathematics education for all students.
These research trends highlight some of the current areas of focus in mathematics education. However, it is essential to note that the field is dynamic, and new trends may have emerged since my knowledge cutoff. For the most up-to-date information, it is advisable to consult recent academic journals and conferences in the field of mathematics education.
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As it is not possible to show mathematical expressions here I am attaching link to the question.
Your expertise in determining and comprehending the boundaries of integration within the Delta function's tantalizing grip will be treasured beyond measure.
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Use δ(a-√x2+y2)=(a/√a2-x2)(δ(y-√a2-x2)+δ(y+√a2-x2)) to do the integral over y. Then the integral over x remains and its integration interval is [-a,a].
The general recipe is to transform the δ function δ(a-g(y)) into a sum of δ functions δ(y-yk), where yk are the zeros of g(y)-a. Each term acquires a denominator |g'(yk)| in the process.
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An attempt to extrapolate reality
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Both textbooks and also most of secondary school maths teachers are not sufficient to excite students. Some of the USA textbooks are really extraordinary attractive but still very common in so many other countries apart from Europe !?
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Our answer is a competitive YES. However, universities face the laissez-faire of old staff.
This reference must be included:
Gerck, E. “Algorithms for Quantum Computation: Derivatives of Discontinuous Functions.” Mathematics 2023, 11, 68. https://doi.org/10.3390/math1101006, 2023.
announcing quantum computing on a physical basis, deprecating infinitesimals, epsilon-deltas, continuity, limits, mathematical real-numbers, imaginary numbers, and more, making calculus middle-school easy and with the same formulas.
Otherwise, difficulties and obsolescence follows. A hopeless scenario, no argument is possible against facts.
What is your qualified opinion? Must one self-study? A free PDF is currently available at my profile at RG.
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Physics confirming math, or denying it. Time for colleges to catch-up and be competitive.