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wolfson

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Everything posted by wolfson

  1. lmao so what I lol
  2. Dave im waiting for the next problem!!!
  3. why does everyone around here seem to demand evidence, is there something here i missed? I mean i always found evidence a bit overrated Well for obvious reasons, we want to make sure that your post is not just your opinion (when you say fact <or> quote fact(s)), but a fact, by using references, you can prove it.
  4. Its ok
  5. Demosthenes You immense idiot I don’t know whether to pity your stupidity or just put you on ignore. MORON
  6. Very intresting a good site for research ill have to add http://www.bioit-magazine.com/ to my favourites Welcome to the Science forums Teacha, nice to meet you.
  7. ACHRE Report The functions of living tissue are carried out by molecules, that is, combinations of different types of atoms united by chemical bonds. Some of these molecules can be quite large. The proper functioning of these molecules depends upon their composition and also their structure (shape). Altering chemical bonds may change composition or structure. Ionizing radiation is powerful enough to do this. For example, a typical ionization releases six to seven times the energy needed to break the chemical bond between two carbon atoms.[91] This ability to disrupt chemical bonds means that ionizing radiation focuses its impact in a very small but crucial area, a bit like a karate master focusing energy to break a brick. The same amount of raw energy, distributed more broadly in nonionizing form, would have much less effect. For example, the amount of energy in a lethal dose of ionizing radiation is roughly equal to the amount of thermal energy in a single sip of hot coffee.[92] The crucial difference is that the coffee's energy is broadly distributed in the form of nonionizing heat, while the radiation's energy is concentrated in a form that can ionize. What is DNA? Of all the molecules in the body, the most crucial is DNA (deoxyribose nucleic acid), the fundamental blueprint for all of the body's structures. The DNA blueprint is encoded in each cell as a long sequence of small molecules, linked together into a chain, much like the letters in a telegram. DNA molecules are enormously long chains of atoms wound around proteins and packed into structures called chromosomes within the cell nucleus. When unwound, the DNA in a single human cell would be more than 2 meters long. It normally exists as twenty-three pairs of chromosomes packed within the cell nucleus, which itself has a diameter of only 10 micrometers (0.00001 meter).[93] Only a small part of this DNA needs to be read at any one time to build a specific molecule. Each cell is continually reading various parts of its own DNA as it constructs fresh molecules to perform a variety of tasks. It is worth remembering that the structure of DNA was not solved until 1953, nine years after the beginning of the period studied by the Advisory Committee. We now have a much clearer picture of what happens within a cell than did the scientists of 1944. What effect can ionizing radiation have on DNA? Ionizing radiation, by definition, "ionizes," that is, it pushes an electron out of its orbit around an atomic nucleus, causing the formation of electrical charges on atoms or molecules. If this electron comes from the DNA itself or from a neighboring molecule and directly strikes and disrupts the DNA molecule, the effect is called direct action. This initial ionization takes place very quickly, in about 0.000000000000001 of a second. However, today it is estimated that about two-thirds of the damage caused by x rays is due to indirect action. This occurs when the liberated electron does not directly strike the DNA, but instead strikes an ordinary water molecule. This ionizes the water molecule, eventually producing what is known as a free radical. A free radical reacts very strongly with other molecules as it seeks to restore a stable configuration of electrons. A free radical may drift about up to 10,000,000,000 times longer than the time needed for the initial ionization (this is still a very short time, about 0.00001 of a second), increasing the chance of it disrupting the crucial DNA molecule. This also increases the possibility that other substances could be introduced that would neutralize free radicals before they do damage.[94] Neutrons act quite differently. A fast neutron will bypass orbiting electrons and occasionally crash directly into an atomic nucleus, knocking out large particles such as alpha particles, protons, or larger fragments of the nucleus. The most common collisions are with carbon or oxygen nuclei. The particles created will themselves then set about ionizing nearby electrons. A slow neutron will not have the energy to knock out large particles when it strikes a nucleus. Instead, the neutron and the nucleus will bounce off each other, like billiard balls. In so doing, the neutron will slow down, and the nucleus will gain speed. The most common collision is with a hydrogen nucleus, a proton that can excite or ionize electrons in nearby atoms.[95] What immediate effects can ionizing radiation have on living cells? All of these collisions and ionizations take place very quickly, in less than a second. It takes much longer for the biological effects to become apparent. If the damage is sufficient to kill the cell, the effect may become noticeable in hours or days. Cell "death" can be of two types. First, the cell may no longer perform its function due to internal ionization; this requires a dose to the cell of about 100 gray (10,000 rad). (For a definition of gray and rad, see the section below titled "How Do We Measure the Biological Effects of Radiation?") Second, "reproductive death" (mitotic inhibition) may occur when a cell can no longer reproduce, but still performs its other functions. This requires a dose of 2 gray (200 rad), which will cause reproductive death in half the cells irradiated (hence such a quantity is called a "mean lethal dose.")[96] Today we still lack enough information to choose among the various models proposed to explain cell death in terms of what happens at the level of atoms and molecules inside a cell.[97] If enough crucial cells within the body totally cease to function, the effect is fatal. Death may also result if cell reproduction ceases in parts of the body where cells are continuously being replaced at a high rate (such as the blood cell-forming tissues and the lining of the intestinal tract). A very high dose of 100 gray (10,000 rad) to the entire body causes death within twenty-four to forty-eight hours; a whole-body dose of 2.5 to 5 gray (250 to 500 rad) may produce death within several weeks.[98] At lower or more localized doses, the effect will not be death, but specific symptoms due to the loss of a large number of cells. These effects were once called nonstochastic; they are now called deterministic.[99] A beta burn is an example of a deterministic effect. What long-term effects can radiation have? The effect of the radiation may not be to kill the cell, but to alter its DNA code in a way that leaves the cell alive but with an error in the DNA blueprint. The effect of this mutation will depend on the nature of the error and when it is read. Since this is a random process, such effects are now called stochastic.[100] Two important stochastic effects of radiation are cancer, which results from mutations in nongerm cells (termed somatic cells), and heritable changes, which result from mutations in germ cells (eggs and sperm). How can ionizing radiation cause cancer? Cancer is produced if radiation does not kill the cell but creates an error in the DNA blueprint that contributes to eventual loss of control of cell division, and the cell begins dividing uncontrollably. This effect might not appear for many years. Cancers induced by radiation do not differ from cancers due to other causes, so there is no simple way to measure the rate of cancer due to radiation. During the period studied by the Advisory Committee, great effort was devoted to studies of irradiated animals and exposed groups of people to develop better estimates of the risk of cancer due to radiation. This type of research is complicated by the variety of cancers, which vary in radiosensitivity. For example, bone marrow is more sensitive than skin cells to radiation-induced cancer.[101] Large doses of radiation to large numbers of people are needed in order to cause measurable increases in the number of cancers and thus determine the differences in the sensitivity of different organs to radiation. Because the cancers can occur anytime in the exposed person's lifetime, these studies can take seventy years or more to complete. For example, the largest and scientifically most valuable epidemiologic study of radiation effects has been the ongoing study of the Japanese atomic bomb survivors. Other important studies include studies of large groups exposed to radiation as a consequence of their occupation (such as uranium miners) or as a consequence of medical treatment. These types of studies are discussed in greater detail in the section titled Taken from the report.
  8. On this occasion we will have to agree to disagree.
  9. MD did you want me to expalin probabilities to you?
  10. Fluent i do not think standard error and effective reduction is applicable at this level.
  11. Yep MW = d x R x T / P is correct. Since no temp was given i would use 273.15K <or> 295K
  12. wolfson

    Bear with us

    Its looks amazing Good job blike and co...
  13. ethanol + propionic acid => ethyl propionate & Propionic acid does not undergo polyaddition/ploymerisation, however with its anhydride on purified cellulose, it forms the basis of a thermoplastic moulding material.
  14. wolfson

    Question?

    I think if you started drilling holes deep in the earth, depending on how many metres you penetrate, thn i think the main affect would be one of "volcanic" such as many new volcanoes, that is the best I can imagine at the moment without knowing the depth of the drilling.
  15. As I mentioned, my most obvious objection is to the whole 'p<0.05' criterion. As I mentioned, there is absolutely no reason why p<0.05 should indicate 'significance' and p>0.05 should not, the threshold value is completely arbitrary. The statistician who first suggested the use of p-values just picked the number 0.05 for no reason other than that it's small. My second objection is that there's often no clearly defined way of calculating p-values accurately. A p-value is supposed to indicate the probability that the observations happened 'by chance', the idea of the 'p<0.05' criterion is that if the probability of the results happening 'by chance' is low, then you've likely observed something 'significant.' The trouble is, how do you calculate the probability that something happened 'by chance,' when all you have is a set of data? You have to assume that the data was generated by some particular model, and estimate the probabilities based on that model. There's nothing immediately wrong with doing that, (in fact it's only very recently that techniques have been devised that don't require you to do this) but to calculate accurate p-values you would need to know the precise model generating the data, rather than just restricting to a particular class of models, as other tests, such as the t-test, do (apologies if this sounds very vague, but things would get very long-winded if I were to try to be more precise). So to calculate (estimate, actually) the p-values you have to pick a model based on the data you have, then use the data again to estimate the p-values; you're using the data twice. That's not necessarily a bad thing in itself (I can think of several good techniques that do this); but it's certainly dubious, and needs theoretical justification, which is lacking in the case of p-values. But my biggest objection to p-values is their scope for abuse. P-values don't give you any estimate of how accurate or otherwise your findings are; they just say 'significant' or not, with no indication of how accurate this answer is (you can't define a confidence interval based on a p-value, but you can for the t-test and others). A basic principle that I adhere to is that unless a test can give you some idea of how accurate its conclusions are you can't rely on anything it tells you. Statistical inference just isn't as straightforward as saying 'significant' or not.
  16. yw look at website for futher info.
  17. In microwave cooking, the radio waves penetrate the food and excite water and fat molecules pretty much evenly throughout the food. There is no "heat having to migrate toward the interior by conduction". There is heat everywhere all at once because the molecules are all excited together. There are limits of course. Radio waves penetrate unevenly in thick pieces of food (they don't make it all the way to the middle), and there are also "hot spots" caused by wave interference, but you get the idea. The whole heating process is different because you are "exciting atoms" rather than "conducting heat". In a microwave oven, the air in the oven is at room temperture, so there is no way to form a crust. That is why foods like "Hot Pockets" come with a little cardboard/foil sleeve. You put the food in the sleeve and then microwave it. The sleeve reacts to microwave energy by becoming very hot. This exterior heat lets the crust become crispy as it would in a conventional oven. (http://home.howstuffworks.com/microwave.htm)
  18. Don't worry about it if you haven't; it's very famous, but to understand it requires a lot of knowledge about quantum mechanics and special relativity. if you don't know about these then you won't understand it.
  19. Ok so I may have been slightly too fluent with my wording, however we all know that does occur. The p-value is the probability that an product as large as or larger than that experiential would occur in a correctly planned, executed, and analysed analytical research if in reality there was no distinction between the groups, i.e., that the outcome was due completely to possibility inconsistency of persons or capacity alone. A p-value isn’t the probability that a given result is wrong or right, the probability that the result occurred by chance, or a rate of the clinical implication of the results. A very small p-value cannot compensate for the occurrence of a large amount of systematic error (bias). If the opening for bias is large, the p-value is likely unfounded and irrelevant. Also p-values may be unreliable, because they correspond to events that have not been explored by the model in the available control integrations. (Referenced, Durk .M, Advanced statistical analysis 2001, & Olive .L, An introduction to research methods and statistical error 2003 & Moore .D, McCabe .G, Introduction to the practice of statistics 2nd edition 1993).
  20. Extraordinary intellectual and creative power, nobody here (Brainman), wishful thinking.
  21. Sorry YT must have posted at the same time lol
  22. Zinc(Zn) + Hydrochloric acid(HCL) = Zinc Chloride(ZnCl) + Hydrogen H.
  23. Yes Chemistry your right just as Greg was!!
  24. Yes, the t-statistic can take negative values. It doesn't affect the test itself, which is based on the absolute value of the statistic. I'd avoid using p-values, myself. Textbooks often quote something along the lines of: "A p-value < 0.05 indicates a significant result" I object to this for two reasons: a) The threshold value 0.05 is completely arbitrary, and has no particular significance. b) There are usually much better tests available. The only reason p-values are used is because these tests are often more complicated to implement; they have few desirable statistical properties. They're usually abused to attempt to give significance to very small samples. The use of p-values has even been blamed for a spate of apparent 'breakthroughs' in pharmaceutical trials a few years back. What happened was that a large number of initial trials reported supposedly 'significant' results based on the 'p<0.05' criterion; however larger and more extensive trials revealed that in most cases there was no actual benefit to patients. In summary, forget about p-values, they're complete and utter rubbish.
  25. And greg as far as I can see 5 is the correct calculation.
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