Epsilon Version 10 Free Download
Fenna Jaggers
In 2011 I started browsing the latest graphical/sound quake mods, putting together a pretty build using LordHavoc's darkplaces, rygel's ultra textures packs, the reforged packs and a variety of mods, to play quake original.Anyone can do the same, however the hassle comes when you have to browse the quakeone forums, stumbling to find the posts which detail what cvars and what configs/files you have to overwrite etc in order to get each mod to work. I literally spent as much time getting the mods working as playing the game. So I put together a nice-looking build of quake original and it's expansions called epsilon for everybody to get into, without getting into the hassle of config files and searching to find every available mod then getting them to work!The main quake build also includes the original shareware first quarter of the quake game - it is easily upgraded to the full game by dropping in the pak0.pak and pak1.pak files from the full game's id1 directory (more details below).
Protein kinase C epsilon (nPKCε), a novel PKC isoform, is involved in the regulation of diverse cellular functions. It is highly expressed in the brain and several neural functions of nPKCε, including neurotransmitter release, have been identified [10]. It has been shown by Western blot analysis that nPKCε is also present in the skeletal muscle [11,12]. However, to date, no reports have been published on the localization and function of the nPKCε at the paradigmatic neuromuscular junction (NMJ). The present study is designed to examine the distribution of nPKCε at the NMJ of the adult rat and to know whether nPKCε level in synaptic membrane is modulated by synaptic activity and muscle contraction.
We used the nPKCε-specific translocation inhibitor peptide, epsilonV1-2 (εV1-2; [20]), to block the isoform activity. We first wanted to show that the peptide εV1-2 inhibits the presence of nPKCε and pnPKCε in the synaptic membrane of the diaphragm muscle. Figure 5A shows that incubation with the peptide εV1-2 (100 μM) produces a rapid (10 min) and significant decrease in nPKCε and pnPKCε that is maintained after 60 minutes of incubation with the peptide (not shown). This decrease in the level of the nPKCε and pnPKCε induced by incubation with εV1-2 suggests that the nPKCε isoform may be tonically involved in some nerve terminal mechanism. No change in the level of the nPKCε and pnPKCε was observed in the presence of 100 μM of the scrambled peptide (not shown). Furthermore, the inhibition of nPKCε by the peptide has a different effect on nPKCε and pnPKCε (nPKCε decreases a 70% while pnPKCε a 40%). In this context, Figure 5A also shows that Hsp70 (heat shock protein 70), which has a role in prolonging the lifetime of activated PKC, significantly increases in the presence of the inhibitor peptide of nPKCε. This suggests a major interaction of Hsp70 with pnPKCε, which could prolong the lifetime of active nPKCε (pnPKCε) and sustain its function.
On the other hand, the blockade, in not stimulated muscles, of the translocation of nPKCε (and therefore its phosphorylating activity) with the εV1-2 peptide, decreased the level of nPKCε and pnPKCε (see Figure 5A). We interpret this result as the nPKCε activity inhibition as a result of the incubation with the specific translocation inhibitor peptide. This can be confirmed because the decrease in nPKCε is accompanied by a parallel decrease in pMARCKS (Figure 5A), which indicates not only that this isoform plays a role in phosphorylating MARCKS but also that the inhibitor peptide acts on the epsilon isoform.
Except that that is rubbish. For numbers between 1.0 and 2.0 FLT_EPSILON represents the difference between adjacent floats. For numbers smaller than 1.0 an epsilon of FLT_EPSILON quickly becomes too large, and with small enough numbers FLT_EPSILON may be bigger than the numbers you are comparing (a variant of this led to a flaky Chromium test)!
The idea of a relative epsilon comparison is to find the difference between the two numbers, and see how big it is compared to their magnitudes. In order to get consistent results you should always compare the difference to the larger of the two numbers. In English:
It turns out checking for adjacent floats using the ULPs based comparison is quite similar to using AlmostEqualRelative with epsilon set to FLT_EPSILON. For numbers that are slightly above a power of two the results are generally the same. For numbers that are slightly below a power of two the FLT_EPSILON technique is twice as lenient. In other words, if we compare 4.0 to 4.0 plus two ULPs then a one ULPs comparison and a FLT_EPSILON relative comparison will both say they are not equal. However if you compare 4.0 to 4.0 minus two ULPs then a one ULPs comparison will say they are not equal (of course) but a FLT_EPSILON relative comparison will say that they are equal.
It turns out that the entire idea of relative epsilons breaks down near zero. The reason is fairly straightforward. If you are expecting a result of zero then you are probably getting it by subtracting two numbers. In order to hit exactly zero the numbers you are subtracting need to be identical. If the numbers differ by one ULP then you will get an answer that is small compared to the numbers you are subtracting, but enormous compared to zero.
I eliminated the absolute epsilon test. It might not be so clear ?
I did this in a way that corresponds to your AlmostRelativeEquals-function with the following modification:
float largest = (B > A) ? B : A;
if(largest < 1f) largest = 1f; // eliminates absolute epsilon test, good idea or too hacky?
Too hacky. You are implicitly assuming that the absolute epsilon should be FLT_EPSILON and there is no justification for this. Given my favorite test case of sin(theta) the absolute epsilon (necessary for comparing sin(pi*n) to zero) is equal to the epsilon of theta, which may be arbitrarily larger than FLT_EPSILON. For instance:
Ah no. The absolute epsilon is an expectation of rounding errors that may have occurred the inputs. That can be less or greater than the error we accept between the inputs (if they had no rounding errors). Apples and Pears.
float has 24 bits mantissa.
double has 53 bits mantissa.
i.e. if epsilon is smaller than the float can represent, epsilon^3 must require at least 3*24 = 72 bits to represent which is more than that of double.
I tried to use the Character Map from Windows to combine the "epsilon" and "dot above" and copy that to JMP but always end up with a dot at the position of the superscript instead of above: ε. What I would need is more like this έ but with a dot instead of an accent. Is there a way to do this?
Unfortunately that doesn't seem to solve the problem. I could find ġ and ḣ without problem, but version with a "dot above" don't seem to exist for the Greek letters (I checked epsilon, alpha and omega). There are many versions with different accents but no simple dot.
It doesn't look like there is a straightforward way of doing exactly what you are looking for, use epsilon-dot as a symbol in a column heading. There may be ways of working around this, but probably the simplest thing to do would be to use another symbol, if that is an option: _for_differentiation
Name of column containing the within factor (only required if datais in long format).If within is a list with two strings, this function computesthe epsilon factor for the interaction between the two within-subjectfactor.
The well-known Impossibility Theorem of Arrow asserts that any Generalized Social Welfare Function (GSWF) with at least three alternatives, which satisfies Independence of Irrelevant Alternatives (IIA) and Unanimity and is not a dictatorship, is necessarily non-transitive. In 2002, Kalai asked whether one can obtain the following quantitative version of the theorem: For any $\epsilon>0$, there exists $\delta=\delta(\epsilon)$ such that if a GSWF on three alternatives satisfies the IIA condition and its probability of non-transitive outcome is at most $\delta$, then the GSWF is at most $\epsilon$-far from being a dictatorship or from breaching the Unanimity condition. In 2009, Mossel proved such quantitative version, with $\delta(\epsilon)=\exp(-C/\epsilon^21)$, and generalized it to GSWFs with $k$ alternatives, for all $k \geq 3$. In this paper we show that the quantitative version holds with $\delta(\epsilon)=C \cdot \epsilon^3$, and that this result is tight up to logarithmic factors. Furthermore, our result (like Mossel's) generalizes to GSWFs with $k$ alternatives. Our proof is based on the works of Kalai and Mossel, but uses also an additional ingredient: a combination of the Bonami-Beckner hypercontractive inequality with a reverse hypercontractive inequality due to Borell, applied to find simultaneously upper bounds and lower bounds on the "noise correlation" between Boolean functions on the discrete cube.
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