Bignose

If you read the wikipedia article, they cite some very recent MM-like experiments, and how the more modern results have driven the error margins down several more orders of magnitude.

You had best explain why the Michelson-Morley experiment http://en.wikipedia.org/wiki/Michelson%E2%80%93Morley_experiment (and the various repetitions of that experiment) didn't detect anything like an ether or medium for light. If your idea is correct, MM should have detected it.

Be careful, there, ox. The 2 gallons of diesel to 1 gallon of ethanol isn't just straightforward. It assumes a lot of 'worst-case' scenarios; for example completely tilling the field after harvest. When, today, if the farmer is going to grow corn cycle after cycle after cycle, no-till practices are pretty well established. Also, it doesn't account for cellulosic use of the corn -- that is, fermenting the entire plant, not just the corn kernels. I do agree that just-kernel ethanol is kind of silly, and that hopefully as more and more cellulosic plants come on line, that form of fermenting will become more common. Possibly even in the form of harvesting the kernels, and then baling the stalks and other residue for the cellulosic fermenter. Or, hopefully developing a crop that is better suited for ethanol creating, like Brazil has done with the sugarcane crop. Most of the U.S. isn't the right climate for sugarcane, but again something like switchgrass is an excellent fast-growing, study crop that could be perfect for the cellulosic plants. In short, I think that while it may not be a really great trade off at the moment, I think that there is potential to make it really great.

I don't see what the problem is. No one is forcing anyone to put E15 into their cars now. This seems to be to actually be a proactive move to get E15 distributed and available ahead of when cars will be able to make good use of it. Again, it is something the manufacturers can do.... Brazil's gas has been at least E22 for years now, and is commonly E25 to even E30. The car makers can make cars that run just fine on that fuel. And the gov't can mandate that they do just that. As I wrote above, I can actually see this is a grand compromise coming. The gov't will let them get out of meeting those very strict and aggressive mpg regulations they are supposed to hit (54.4 mpg by 2025)... so long as they make cars that can handle E15, E20, maybe even up to Brazil's E30. But, in the meantime, it sounds like only MY2013 and later cars can handle E15. So, in 4 years as 4 more years of cars that can handle it are on the road, then there might actually be some stations selling it. It should be very clearly labeled, you really shouldn't be putting into your car unless you want to.

Brazil has been using E22 for over 20 years now. It isn't going to just kill every single car. And it makes me wonder why they don't have the 'phase separation' issues the video mentions. That physical behavior is dependent on the amount of water that is also in the blend... so it becomes critical that the producers of the fuel make sure water doesn't get into the tank, and then it is also on the station owners to ensure their tanks remain intact. Now, that said, I wouldn't just shove it into your car willy nilly, either. The computer has tuned the engine to work as best it can for a certain fuel, and I don't think it is worth changing that up. Even the people with the flex fuel vehicles say that it takes the car some time to start running smooth if they change from an E10 to and E75 blend and back -- and those cars are designed to handle the changes. It doesn't seem worth it to throw your car a curve ball and give it E15 for no good reason. And, I have little doubt that the manufacturers are going to stick to their guns of not honoring warranties because 1) they probably haven't done as much testing with it as they want and 2) the gov't hasn't forced them to honor the warranties. Again, that said, they all sell vehicles in Brazil just fine. In 10 years, when all gasoline is E15, the gov't will offer the companies a deal: the OEMs will have to honor their warranties, and the gov't will let them out of those aggressive fuel standards that were recently passed.

It really comes down to what $3000 means to you. Most of these purchased algorithms come with some guarantee of performance and accuracy, as well as you mentioned, the tech support and assistance being offered. For my personal applications, I have always found that I could write my own or use freely available algorithms that performed well enough. But, if performance, accuracy, or development time were all at a premium, it could very well be worth $3000 or more. If the given budget for a project is $750,000, $3000 may be meaningless. If the budget is $5000, $3000 is clearly mountainous. It also is worth being very clear what the licenses and fees would be if you should use their algorithms in some software that you plan to distribute or sell.

Oh oh oh oh oh oh!! this is big news. Best Boxing Day ever! Or best St. Stephen's Day ever!

I really, really miss the old quote tags where you could just hit the balloon-button, that would inset the [ ] tags and then you could fill in the details yourself... i.e. attribute the quote to someone. Maybe I am missing it, but I don't see how to do that with this box thing that just appears... The old method was really nice when you wanted to quote multiple people, especially from multiple threads -- you could just copy and paste them into one reply and so long as the details in the

yes, it is my opinion that there is indeed a non-ridiculous chance that future discoveries would indeed be profitable. I don't think that it is too much of a stretch to think that if a unification of the 4 forces could be found, that that could lead to many developments. This span that I added the emphasis to in your quote is almost unbelievable. There is not a single person in 1712 who would have imagined 1% of the technology the world is using today. What a scientist in 1712 would have called 'reasonably affordable' or 'accessible' -- is stuff we do in grade school science labs today. I, for one, am glad that a 300 year old policy is not governing science today. And, I really don't understand how you can be so sure what will be reasonably affordable or accessible 25 years from now, much less 300. 300 years ago, one could call themselves a 'scientist', and be reasonably up-to-date with most of the rest of the science being performed in the world. Today, that just isn't true. Not only is it impossible to be a 'scientist' (again, one who keeps up with all branches of science), one can hardly call themselves a 'chemist' or 'physicist'.... they are 'polypeptide chemists' or 'solid matter physicists' etc. A 'physicist' cannot keep up with all the developments just in physics, they end up pretty much out of necessity to specialize on one area like solid matter and read just the journals devoted to solid matter physics and going to the conferences on solid matter physics. My point here being that I am curious what knowledge you possess that lets you so confidently know what will be affordable and accessible over the next 300 years? Why you think you have such a grasp of the current and future states of science to be able to make such bold predictions? This is why I was asking about calculation-implying terms like "average expectable financial value". Because I thought maybe you did actually have some knowledge to could lead to reasonable calculations. It doesn't appear so, however. Again, to summarize: it looks like you have your opinions, and the rest of us have ours. It is always good to see someone else's opinions, even if one doesn't necessarily agree with them.

I'm not sure why it was wrong, considering the first statement I quoted there, to assume that you think our current models don't need any further refinement. As I see it, that's precisely what the 1st quote says (along with the text around it). What I saw in your posts was some sort of calculation that the unknown future benefits of some kinds of research are worth less than the unknown future benefits from some other kinds of research. But no details of that calculation. It is my opinion, that arguments like this are almost wholly based on opinions; all we can really do is look at history and try to learn lessons from that. And the lessons from history are rather clear, in my mind: 1) that when research into the fundamental questions are dug into, the answers they yield are often very surprising, and then the knowledge from those answers are often applied in an incredibly wide and rarely initially imagined way. 2) we know that all of our current models are wrong, or at least incomplete. Which means that there are answers to these fundamental questions that we don't have yet. 3) some big open problems I see -- and I'll admit I am not a physicist so these observations are from an more amateur point of view -- is the resolution of quantum level phenomena with astronomical level phenomena, e.g. some kind of quantum gravity. And the other is a unified theory of forces: doing to electromagetism, weak, strong, and gravity what has currently been accomplished for the electromagnetic and the weak forces: the so-called electroweak force. These two 'big' open problems aren't unrelated, of course. And really, it is my opinion that if we had a unified description of all the forces, that there is great potential for many valuable applications. Ok, fine. That is your opinion, and mine is stated above -- that I think resolving some of these large problems are actually quite likely to yield 'profitable' applications (whatever your definition of profitable is). ---------------------------------- I actually think all the above was rather clear. Where it got opaque from me, was when you started using phrases like "average expectable financial value", which to me implies some kind of calculation of probability distributions and payoffs of $ spent in various forms of research. If this wasn't actually a calculation -- and again just your opinion -- of just you 'gut feeling', then that is fine. But may I suggest dropping words that imply calculation like 'average' and 'value'. It was when you were using words like that, that I start to question the calculation. Not even necessarily because I think you are wrong, but because I'd like to see how those calculations were done. I'd like to see what assumptions went into such a calculation, see what data was generated or created to support those assumptions etc. Especially in light of what I see as the recent history of successes stemming from research into the basic fundamental laws of physics. ---------------------------------- Lastly, really, the personal attacks are uncalled for. I haven't come even close to using them against you, and I've shown you all the requisite manners in this thread. Additionally, ad hominem attacks really aren't a terribly valid form of argument. If you could just leave them out of the thread from now on, I'd appreciate it.

I think the remark about research being wrong, in general, is exactly on subject because your main assumption is that our current models do not need any further refinement. Yet, basically, the probability is hugely on the side that the current models are wrong and are at least incomplete. You throw another number out there, 10^-100. Where exactly do you get that? I mean, I can make up numbers, too. That doesn't mean they are right in any way.

I asked, exactly, how to calculate the value you mentioned. I want to know what percentages/likelihoods you give each possibility. I'd like an actual calculation, please, with citations or sources on each number, as you seem to represent that such a calculation has been done, and its results are obviously conclusive. Because, keying off the word 'imagination' above, all I really see are your personal opinions about what is and isn't more valuable and more likely. And these are fine things to debate -- again, I fully agree that they are good questions to talk about -- but I don't think it is fair to represent either side as 'clearly correct', with some hand-waving opinion-based math. I also still don't know how you can be so sure that there are areas that "are not the right ones for this purpose anymore?" If anything, we know that the models we have today are wrong or incomplete. Almost all published research is wrong, in the sense that it is at least incomplete See http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.0020124 for an example from medicine, but fully applicable to all sciences. I don't understand why you think that there aren't possibly tremendously useful things to learn in more fully completing this knowledge. And I don't know how you can be so sure which areas will be more productive that others. I have my opinions about which ones would be more productive, too, but they are only just opinions, and I recognize them as such.

How, exactly, does one calculate this?

I am curious how you know this (and the rest). Seems to me that there are plenty of large open questions at the moment -- relating the quantum scale with the astronomical scale, for example. Not having these two unified, I would call that a significant fundamental law that we are currently missing. Most everything you write are opinions you currently have, not facts. And I'm not going to 'refute' opinions, just put mine out there and see where the chips may fall.

Ok, here is what I am asking: give an exact mathematical prediction that can be compared with experimentally measured values. That way one can calculate whether your prediction is 0.1% off, 1% off, 10% off or 1000000% off. And, I don't need to explain anything. It isn't my theory that is trying to be defended. It is yours. And, really, until an estimation of what % error your idea has, all you have is a story. Not science. It may very well be a good story, it may be very interesting, and 'logical' to some, but it isn't science. It is just story telling. I don't understand why there is such a resistance to this step. If your idea can be calculated and shown to be 0.1% off, I bet it would get all sorts of attention. Isn't that exactly what you want? Turning your idea into mathematics is exactly the next step towards acceptance -- why aren't you embracing it? and if you really want something to try to clarify, ydoaPs sure asked a good one.

Dude, did you even read my post? I didn't insist on anything -- I precisely said that it is fair to question whether the money spent couldn't be put to better use. All I said is that research into fundamental questions often pays off in dividends later. If someone has said around 1900 -- "you know, Newtonian physics is pretty darn excellent is all the 'accessible physical phenomena' we have today, there really isn't much a need for anything else" ... we wouldn't have discovered the theory of relativity. And hence we wouldn't have a working set of GPS satellites that, I have to say, are pretty darn useful. So, my point is that fundamental research can very well be worth-while. The knowledge we gain from it often isn't immediately applicable to something tangible, but often that knowledge IS key for future applications. And really, no one when working on the theory of relativity was aiming for a set of GPS satellites... they were just looking for answers to more fundamental questions than what the current answers could provide. I'll say again, to be very clear, I do think it is a fair question to wonder if the money spend on the research couldn't be better spent somewhere else. For example, better plant genetics for more drought and pest resistant crops to help feed a quickly growing population. BUT, you do have to acknowledge that we can talk about that research precisely because the fundamental research which allows us to map genomes, and change molecules on an atomic level are due to previously having spent the money fundamental research into genetics and studies on quantum physics. If you had tasked someone 50 years ago with breeding more drought-resistant crops, they would have started getting out paintbrushes to gather pollen from one set of flowers to pollinate another set of flowers. We have the tools today to more directly do that research precisely because we spent the money before on fundamental research. So, it is always a balance. I think it is foolish to swing the pendulum too far in either direction. I can use your same argument against you that we don't know what laws or results from the fundamental research will come out -- it may be a 1 ppm refinement to a current law, or it may be a game-changer. You're right, we don't know. But, I for one think it is worthwhile to spend some money on seeing what we find. And, in full disclosure, none of this at all affects any of my 'projects'. I don't know if you meant to toss me into your characterization of "high level scientists ready to tell any bullshit to politicians in order to keep the credits on their projects", but it certainly doesn't apply to me.

Just speculation, of course, but if we do know the physics that govern those first moments after the big bang, the potential is there to be able to develop some novel energy source, or propulsion source, or many other technologies that could go a long way toward alleviating some of those issues. Such as war over energy sources like oil. In short, pure research's gain are rarely immediately obvious. Often, the fruits of that labor come some time later. It is a fair question to wonder if the large amount of money spent couldn't be better spent somewhere else, but the gain from pure research do have value.

It is certainly possible. As ajb said, in all likelihood you will need to complete work akin to PhD level in order to contribute papers or monographs to the current body of knowledge. On the other hand, you mention wanting to work with math every day; if that is the case, there are careers that use math all the time without needing a PhD. I am thinking, for example, of jobs in statistics like an actuarial or the currently hot field of 'big' data analysis. In fact, some of the actuarial jobs, all you have to do is pass the formal exams -- some won't care if you have a degree or not because passing the exams indicates your level of knowledge and skill. Other ideas are careers where writing computer simulations would require doing a great deal of math. Most of these are probably going to require at least a B.S. in the field, however: e.g. most likely you aren't going to get a job writing computer simulations of a refinery without a degree in chemical engineering or a job writing software that simulates a computer chip without a degree in electrical or computer engineering. Lastly, I would like to say that most any job can benefit from someone willing to try to apply more mathematical or analytical skills to the position. Most jobs will be happy for someone to volunteer to learn more about the business and take on trying to analyze more complex problems. This is something to talk with your current supervisor about.

This doesn't answer why 'scale' needs to be a 4th dimension when it is perfectly well described by the 3 space dimensions we have now. I have no problem introducing additional dimensions when they describe something that can't be described without a new dimension. For example, 3 dimensions isn't enough to describe a particle's position and speed. For example, I can have a particle at time t located a (0,0,0), but that doesn't tell me the speed. It could be moving at (0, 1, 0) m/s or (100, 100, 1000) m/s. Hence to fully describe that particle's position and velocity, I need a 6-vector (x, y, z, vx, vy, vz). But, I don't see how scale falls into that example. The scale of something is a function of the three spatial dimensions -- I don't need to invoke an extra dimension to handle it. ------------------------- also, holy thread necromancy, Batman. Did you see the original dates of the 1st posts?

The classically defined Reynolds number shouldn't ever be negative. [math]\textrm{Re} = \frac{vl \rho}{\mu}[/math] none of these terms can be negative, l is a characteristic length, v is a characteristic velocity, rho is the density, mu is the viscosity. Now, that said, there are lots of times problem-specific Reynolds numbers are defined. e.g. ones for flow through a packed bed, or as Ophiolite above mentions, ones for non-Newtonian fluids. Now, that said, the specifics about the defined Re will be needed for how to correctly interpret it. I will admit, I've never seen a negative one, unless someone naively just puts in a negative velocity. But, if they do that, they really are losing the meaning behind what the ratio is supposed to mean in the first place.

Wow Eqn 1 is [math]\frac{\frac{s}{1}}{+.-(\sqrt{s})}=1[/math] and Eqn 2 is [math]\partial\left(\frac{\frac{s}{1}}{+.-(\sqrt{s})}\right)= 1 + or - 1[/math] I stopped reading after that. It literally looks like you just took some math symbols and tossed them together. Because it is otherwise meaningless. Specifically: why write s/1 in a fractional form? Isn't that just s? the numerator of equation 1 is jibberish. What are you adding to what with the + sign? the decimal point? the minus sign? In equation 2 What are you taking the partial derivative of? And with respect to what? What is that 'or' doing on the RHS of eqn 2? How does one know if it is +1 or -1? After these numerous mistakes, I just quit reading. I posted this simply in the hopes that no one else wastes their time or bandwidth downloading the .pdf file. Trust me, it is worth neither.

Yeah. This quote is a nice sound bite and all. But there is some poetic license in it -- 'never' is obviously too strong a word. There are cases when good ideas come from a 'community'. And maybe most importantly, it doesn't really address the point mooey was making -- namely the importance of being educated about the current state of the problem you are performing research on, not what community one should be a part of. They are not synonyms for each other; however, most scientists would probably say that by being a member of the community and by going to conferences and seminars it helps a significant amount in remaining current. But it isn't required. One could remain current by remaining very diligent in their literature reading.

You really didn't bother to read the post did you? Logic is certainly important, but logic alone isn't enough. Again, at one time, it was logical to deduce that the world was flat. It is easy to be lured into thinking things are logical that just aren't true. Hence the importance on making predictions with mathematics and comparing them with measured values. no you're not. you're using phrases like "the object falls". Does it fall quickly, slowly? Quickly to me and slowly to you? MATH is needed when you make statements like that so that you can make a statement like "the object falls at 5 m/s". Then we can set up the experiment and see just how fast it actually does fall. This lets us have an idea on how right or wrong you are. It really is that simple.

This is actually rather easy. It is because equations make exact predictions. And how close those predictions are to measured values is the best objective measure we have for judging how good a particular prediction is. Let me make a simple example: If I sat a box down in front of you and told you it was heavy, what do that mean? What if an Olympic weightlifter said the same thing? A ballet dancer? A toll booth attendant? My point here is that 'heavy' has fairly different meanings depending on who is saying it. Words are inexact, fungible, and open to interpretations. Look, words can be exceptionally powerful. The classics of literature are considered the classics because the authors chose their words exceptionally well and the readers are very moved reading those words. But, the classics are constantly be re-evaluated, re-interpreted, and dissected from different points of view. On the other hand, if the measured force needed to lift that box above was 785 N, it is 785 N. It is not 1000 N, 100 N, or any other number other than 785 N. While an Olympic weightlifter may be able to exert 785 N a lot easier than I can, it is still 785 N. And if you have two different models in front of you: model A predicts 783 N needed to lift the box and model B predicts 14 N needed to lift the box, model A is clearly superior in this instance. Model A is only a few tenths of a percent in error whereas model B is several orders of magnitude off. THIS is the objective independent comparison that lets us judge these two models. There is no discussion over which model's words are better chosen, or which model is more logical, or prettier. Model A is clearly vastly superior at making predictions that conform to actual measurements. And THAT is really what science is about -- being able to predict was nature will do without actually having to measure it each and every time. e.g. our models for putting up buildings let us know how much steel to use without having to actually measure it every time. We have moved past the dark ages where models were judged on how 'logical' they were, or on whose authority they were said. It once was logical to deduce the world was flat, and the moon was made of cheese. It used to be that the king or the church would declare that the bad humors inside you made you sick. Once real evidence came in, and compared with these 'predictions', they were dropped in favor of models that agreed with reality. THIS is why you should 'bother to learn the equations'. So that you too can make objective predictions which can then be objectively compared to experimentally measured values, and one can see just how well your predictions agree. If you make predictions with excellent agreement, I guarantee you will generate a lot of excitement in the scientific community. edited for spelling

You never challenged me to write in fewer characters. You told me that the 'current math' couldn't write it. Which is blatantly wrong. Your ignorance of the 'current math' doesn't mean that you can claim things which it cannot do. Are you going to retract the statements about how the current math can't do this yet? Now, are you going to quit treating this forum like your personal blog? Or are you going to answer some of the really meaningful questions that were asked of you at the top of the thread? Like what practical applications do you have?