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# Function - Science topic

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*Edit: I updated question 1 and added a link in Section 3.1. I also explained the intuition in section 4.4.1.*

I have yet to understand amenability and group theory, but the questions in my attachment might be of interest.

I would be glad if all the questions were answered; however, if you wish for a particular question, read section 4 of my paper and the question in section 5.

I want an elegant choice function where, for specific A in 4.4, gives the structure (defined in 4.2) that I'm looking for.

I'm doing a homework about finding the CpG islands within a gene of our interest. I picked the FXN gene and found 11 possible CpG islands using this website http://dbcat.cgm.ntu.edu.tw/.

I'm also supposed to find out what role do these regions may play in gene regulation and transcription however I'm lost at this point. I know that if there is a CpG island close to the promoter region, it has a role in gene silencing but all of the islands in this gene appear to be located in introns only so they don't overlap with exons either. What kind of a role CpG islands may play if they're on the non-coding sequences?

How to linearize any of these surface functions (separately) near the origin?

I have attached the statement of the question, both as a screenshot, and as well as a PDF, for your perusal. Thank you.

Hello,

I established transfer functions with PAST 4.01, and I would like to input some downcore data (lake sediments, diatoms) to reconstruct past environmental change quantitatively using the transfer function.

However, I don't know how to put the data into the transfer function in PAST.

Does anyone know how to do that?

Or I appreciate any other suggestions for methods to build a transfer function and its application.

Thank you very much in advance!

Here we discuss about one of the famous unsolved problems in mathematics, the Riemann hypothesis. We construct a vision from a student about this hypothesis, we ask a questions maybe it will give a help for researchers and scientist.

I want to perform a checkerboard resolution test of my tomographic inversion. What kind of function do people use to make the checkerboard model of low/high anomalies? Bell-shaped (gaussian) anomalies?

Under what conditions the solution of nonlinear ordinary differential equations belong to the space of continouse functions? Need opinions

Can any body tell me what is difference between 'probability density function' and 'power spectral density function' for random data like wind speed?

Hello everyone,

I am thinking how the function should look like in order to generate this kind of curve shown below.

I am guessing the

*variables*should be :- the
**radius**that increases by "x" after every half-rotation, **how many rotations**should take place before stopping.

Can anyone shed some light on this?

the predicted ORFs were annotated using Batch CD-Search in NCBI and now I really want to classify their functions like the COG does.

Hello everyone,

Please I have this transfer function model of numerator order 1 and denominator order 5. I want to reduce this to a numerator order 1 and denominator order 2 or simply a first order system with a coefficient as the numerator. How do I achieve this using MATLAB. I know of the function BALRED. But this function reduces the model to an even order for both numerator and denominator. I also know of MINREAL which is for pole-zero cancellation. This function can only cancel the single order numerator thereby reducing the denominator order by one. I would like to know if there's any function that could help me achieve this or if there's another way to go about this. Thank you!

Hello all I need help please

How to create a function for the Renyi and Shannon formulas?

**RENYI=(1/1-alpha).* log2(sum(q .^alpha))**

**SHANNON=-(sum (q .* log2 (q)))**

thanks in advance

Some modular functions, such as the Riemann zeta one, display a fractal behaviour.

Does also the curve of the j-function display power law properties, or a scale free structure?

It it feasible to calculate the j-function's power law slope, or its Lyapunov exponent? Is the j-function somehow correlated with the Feigenbaum constant of logistic plots?

Hi. I am intrested in studing the Mittag Leffler type functions. Can any one suggest some book or article that discusses the orthogonality of Mittag Leffler type functions.

Knee locking refers to when the leg gets stuck in one position, making it impossible to bend or straighten it. It may only last a few seconds, it may last longer. It all depends on what is causing it. Most cases fall into one of two categories.

There is true locking caused by a mechanical block where something gets stuck inside the joint, preventing movement. This type most commonly occurs as you move the knee into full extension, i.e. towards being fully straight.

Secondly, there is pseudo locking, caused by severe pain which temporarily limits movement in any direction.

Hi everyone, I would like to define a heavy side function in comsol multiphysics (flc2hs) for the variable y giving as follows.

y = '1e-6' (for t<=1e-6) or 'x' (for 1e-6<t<=0.999) or '1' (for t>0.999)

where x is a variable.

How could I do implement that ?

best greetings.

I have data values and try to find some kind of function that decribes these data as good as possible. The attached files are two examples (simple text files, one value per row, 1498 values). The corresponding x-values are 0, 1, 2, ... 1497.

The data starts at y=0 and the asymptote for x->inf is y = 1. Whatever I tried did not fit the data well, especially not the first 50 or so values.

If someone has fun finding a function that fits these data really well, then try your luck :)

The two data series should follow the same kind of function and should differ only in the parameter values (possibly onle in a single parameter - but I don't know for sure).

We are looking at GAF and we know that HoNOS has been used for ACT before.

Looking to measure occupational functioning.

Consider a continuous Lipschitz function f of the single variable and an interior point x* in a compact interval of its domain. How to use the fundamental theorem of calculus to describe f(x*) = 0? (The old version of this question was posed for C2 functions. In the current RG project this assumption was relaxed to continuous Lipschitz functions.)

How to take Laplace Transform of functions like sin(f'(t)) or sinh(f'(t)) where f'(t) is the derivative of another function with respect to time.

(p.s1 this information may not be relevant but f'(t) is L(f′(t)) = sL(f(t)) − f(0))

(p.s2 I was thinking of Taylor expansion of the trigonometric function before taking the Laplace transform, but I'm not sure if this is the proper way.)

For system in the attachment, this system with uncertain parameter and state-dependent uncertainties, how do I choose lyapunov function for this system?

How you describe the functional objectives of EHR & CDSS, if EHR is a platform and CDSS is add? Which modules have to work as a lock and key?

Hello all! Please give tip how to find Fourier transformation for function S(x)=[Λ(x/2)⨂1/2 comb(x/4) ]rect(x/60)? Symbol ⨂ mean tensor product?. Available from: https://www.researchgate.net/post/Hello_all_Please_give_tip_how_to_find_Fourier_transformation_for_function_SxLx_21_2_combx_4_rectx_60_Symbol_mean_tensor_product [accessed May 20, 2017].

Can someone help me explain how the function in the picture is used in UG\Open?In UG\Open, how can I use this function to get model information and save the structure of each function member in this function?

like snr=p*r^(-a)/(noise power)

To resize a 2D image, for example in matlab, we use the function "imresize". But, if we use this function for a 3D image on every slice, the distances between voxels, according to Z axis, becomes greater then those distances between voxels according to X axis and Y axis. The resulting voxels become straight pavements not cubes.

Some ones have solution for this problem?

Thanks :)

When choosing th activation function for a MLP neural network want criteria can be used? It depends only on the data?

I've got a humanized bi-specific monoclonal antibody targeting to PD-1 and CTL-4. how can i verify the function of it? what experiment should be taken?

Is there any data about this question? Or any data about other proteins that could function in one single cell.

does it mean that the two functions are not antagonists? I have solved the optimization problem using the weighted sum method in MATLAB .

thank you

It is known that the exact eigen-functions of sturm-liouville problem are orthogonal with respect to the weight function. But what happens when the solutions are obtained using approximate analytical method?

Do the approximate analytical solutions obtained using asymptotic techniques or using WKB method orthogonal?

If Colombeau's algebras existed, what led to the construction of simplified algebras?

When we are faced with an ordinary or partial differential equation, linear or non-linear, how do I decide to attack the problem by one or the other? How do I decide which one is best for each case?

What function is in the plenums, but is not in the simplified? The space of the continuous functions are not totally immersed in simplified GF?

Is there a differential equation that has a solution in one algebra in the other? Because del-bar is solved in the simplified, can also solve in the plenums?

I am doing master thesis in which I have to optimise active power flowing through HVDC link and it is installed in parallel to AC line. I need to know how can I make obective function and what would be my constraints for this function?

I am studying the GABAA receptor composition and its function. I would like to know the difference between α 1 β 2 γ 2 and α 1 β 3 γ 2.

In my research, i came across different distributions on skew student t distribution which from the density function they are so different. I seriously need a clarification and simplicity of the skew student t distribution i.e. the density function and the cumulative function.

for dendroclimatic studies

Is it possible to determine the temporal shape of the laser pulse from

the autocorrelation function?

The Landauer limit L(T) = kTln2, k is the Boltzmann constant, means the energy corresponding to erasing a single bit of information. Thus, one can define t(T)=kTln2/h, h - the Planck constant. What might be the physical meaning of the so-defined function t(T) or that of its reverse function T(t)? Furthermore, t can be referred as f=1/t to the frequency of some wave having a certain physical sense.

A few general considerations might be:

1. The Planck constant means the correspondence of a dimensionless physical quantity to the quantity of action. That dimensionless physical quantity can be interpreted as entropy.

2. The Landauer limit means energy per a bit of information (entropy).

3, Action is a function of energy and time and thus, time as temperature can be interpreted as a relation (e.g. ratio) of energy and entropy.

4. Then, the dependence of time and temperature at both Landauer limit and Planck constant for both time and temperature are interpreted only by energy and entropy as above implies both time and temperature to be referred to the same state of affairs from two different viewpoints: (quantum) mechanics for time, and thermodynamics for temperature.

5. That idea (4) implies that energy and entropy in turn can be seen as the same quantity from two different viewpoints, and time and temperature represent the difference between the latter two viewpoints from the former two viewpoints accordingly of (quantum) mechanics and thermodynamics.

6. That quantity described whether as time or as temperature means intuitively the transition "inside - outside", or a little more exact: the transition "inside of a physical system" to "outside of the same system". That transition in (quantum) mechanics is called motion and mathematically described as a function of time. It means that system as a single whole conventionally called "particle", which is moving from the past position ("inside") to the future position ("outside") right now. That transition seems not to be called in thermodynamics (at least, I cannot guess how),but it means the transition from considering the system as consisting of many, many elements (“inside”) to a thermodynamic whole (“outside”).

Step function of applied voltage in dbd plasma actuator

in stroke patient, hand functions is usually affected, I am wondering if you have experienced a good method to evaluate hand functions in stroke patient?

I am starting in the molecular docking field. I would like to have some help about this question. I have generated the grid.cnt, grid.ngr, grid.bmp files but I dont know where can I find or how can I generate the pairwise GB grids and the SA grids to do the calculation of the Zou GB/SA scoring function. I am using the Dock6.7

I would really appreciate all the help that can be provided! :)

Huge hugs!

I am working at making a overexpression vector of SESN1,but its three variation seem no recognizable function difference.i have already identfied isform 1 and 2 were expressed in my cell line .so i hope get more information about these 2 isforms.

hi

How find centroids vertices using LOF function in highlighted section(Definition 3) in attached file ?

Suppose that I have the normal and diseased populations as functions of a variable (x), how can I use them to draw a receiver operator curve (ROC)? Assuming the two functions are normal distribution functions and I know the means and the standard deviations of them, how to calculate the ROC at each value of x?

Suppose that f and f′ are continuous functions on R.

If f's limit is zero at infinity, does that imply f' has same limit at infinity?

Dear researchers,

can you explain to me the difference between constraint satisfaction of preferences with fuzzy constraints (knowing that there is no objective function with satisfaction problems) , and constraint optimization ?

In other words, what's the difference between CSP, CSOP, and FCSP formalisms ?

Regards !

Assume two real random vectors from observation such that ${\bf{z_1}}=[x_r(0) x_i(0) x_r(1) x_i(1)...x_r(N/2-1) x_i(N/2-1)]$ and ${\bf{z_2}}=[x_r(T) x_i(T) x_r(T+1) x_i(T+1)...x_r(N/2+T-1) x_i(N/2+T-1)]$. Here $x_r(t)$ and $x_i(t)$ are the real and the imaginary parts of x(t). Due to circularly symmetry assumption, zero mean random variables $x_r(t)$ and $x_i(t)$ are independent and identically distributed (i.i.d). The the correlation coefficient is given as

$\rho = \frac{E[x(t)x(t+T)]}{E[x(t)x^*(t)]}$

More Detail is Given in Image attached. Waiting for comments.

Let A be a subset of R^n then the rearrangement of A denoted by A* is the ball B(0,r) having the same volume with A i

**.e if |A| =|B(0,r)| with respect to the Lebesgue measure then****A*= B(0,r)**

Let f be a function from R^n to R and f* its symmetric decreasing rearrangement is the function define for x in R^n by

f*(x) = integral

_{0}^{infinity }1_{{f>t}*}(x) dt.**Where 1**

_{{f>t}* }is the characteristic function of the set {f>t}*= B(0 r_{t}) on R^n for some r_{t}>0.The set {f>t} := {x in R^n : f(x)>t} is called t-level set of the function f.

**QUESTION: How to show that**

**{f>t}* = {f*>t}?**

This is mentioned to be easy in the book of

**Elliott Lieb and Loss (**Analysis second edition, Graduate Studies in Mathematical,vol 14, American mathematical Society, providence, RI 2001).

Hello,

In theory of Nevanlinna, and in the unit disc, an analytic function for which order and lower order are the same is said to be of

*regular growth*, and the function which is not of*regular growth*is said to be of*irregular growth*.I need some examples of functions of irregular growth (it's okay if are entire or analytic in the unit disc),

best regards

Is it possible to do feature normalization with respective to class. EX: 10x10 data matrix with two class. Each class of size 5x5. Now normalize 25 features of class 1 and 25 features of class 2 separately. Is this process acceptable.

I want convert below function:

f(x)= {1 if 0<=x<0.5

{ -1 if 0.5<=x<1

{ 0 O. w.

In the same situation the probability of occurrence of which event is more poisson or uniform?(is it possible to estimate approximately ?)

Lateral, anterior and posterior Fontanelles, which are gapes in the skull of catfishes, covered by tough membrane, what are the functions of these gaps?

Good mourning, i used the demostration shown in the figure below to reduce the integral shown to a simple form, the function Psi is an odd function with respect to x independant variable. I just want to check whether it is right or not, could any one help?

where can I find results dealing with prederivative of non smooth functions ?

How to compute the limit of a complex function below? Thanks.

For $b>a>0$, $x\in(-\infty,-a)$, $r>0$, $s\in\mathbb{R}$, and $i=\sqrt{-1}\,$, let

\begin{equation*}

f_{a,b;s}(x+ir)=

\begin{cases}

\ln\dfrac{(x+ir+b)^s-(x+ir+a)^s}s, & s\ne0;\\

\ln\ln\dfrac{x+ir+b}{x+ir+a}, & s=0.

\end{cases}

\end{equation*}

Compute the limit

\begin{equation*}

\lim_{r\to0^+}f_{a,b;s}(x+ir).

\end{equation*}

By giving evidence or reference,

Who first discovered hypergeometic functions?

I m asking this for any function means for example If we take

f(x)=sqrt(x); etc;

then how can we proceed for calculating the wavelet coefficients.

Say for a given a function f, there are functions h and g satisfying h leq f leq g. What do we call h and g? I've used upper and lower bounds, which is incorrect. I reckon g could be called a dominant. What is h?

Respected Sir

I want to solve optimal placement of capacitor for distribution system. So I want a good multi objective function for it.

Dear Sirs,

I want to invert following set of equations:

Y(i)=a(i)X1+b(i)X2+c(i)X3+d(i)X1X2+e(i)X1X3+f(i)X2X3+g(i)X1^2+h(i)X2^2+i(i)X3^2 i=[1,4]

It consists of four outputs (Y1-Y4), 3 inputs (X1-X3), and (9*4) coeff.

I intend to generate X1,X2,X3=function(Y1,Y2,Y3,Y4).i.e. Equations of X1,X2,X3. We may assume coefficients of your choice to simplify the solution. Please help me with possible guidance.

I am trying to model the combined effect of different customer orders on the manufacturing system. Having difficulty in understanding the application. Is there a tutorial help anywhere to guide me through this? Could someone give me a quick step-by-step procedure for using Array function in a model, please?

Midconvex functions that are not convex are not Lebesgue measurable

I have come across this condition for a function to be continuous and differentiable both but I was wondering in what cases and how it can be useful for us? In context of applicability.

_{ How can I solve Riccati inequality in Matlab using a modified function "care"? See attachment, please. }

a function f(x,y) Any suggestion of a function f(x,y) such that the partial derivative with respect to the variable x is ax and with respect to the variable y is bx?

I have been wondering about the function of the ventral spine displayed by acanthosomatid bugs. Have there been studies on this topic? Thanks!

Frank

I have to make a nested loop function to move from one co-ordinate of the obstruction to another in a nested loop form. I am unable to figure out how can I develop it in FDS/ WFDS software of NIST?

Here is generic method to transform a random set of values to normality:

1. Compute the empirical cumulative distribution function from the observed data (e.g., by using 'ecdf' function in R)

2. Smooth the function using smoothing spline and call in G(x) (e.g., by using the 'smooth.spline' function in R)

3. Now let U=G(X) should approximately be distributed as uniform distribution on [0, 1].

4. Z=Q(U) would then be distributed approximately normal with mean zero and variance 1.

The question is why do we still keep trying various arbitrary transformations (such as log, square-root, Box-Cox etc.)? Can't we simply use the above steps to transform a data (obtained from an arbitrary continuous distribution) to normally distributed?

In fact, here is a set of sample R codes to illustrate the method:

#####Generic Transformation to normality#######################

x=c(rnorm(25,-1.5,0.5),rnorm(75,1,0.5)) #data from mixture of normals

par(mfrow=c(2,2))

hist(x,prob=T) #you will see a bimodal shape

Fn=ecdf(x); fit=smooth.spline(x,Fn(x))

plot(fit,type="l")

u=predict(fit)$y

hist(u,prob=T) #you will see uniform shape

z=qnorm(u)

hist(z,prob=T) #you will see a normal shape

lines(sort(z),dnorm(sort(z)))

ks.test(z,"pnorm") #formally tests if transformed data is normal

#####Copyright (2015): Sujit K. Ghosh###############

A sample output is attached where the data is generated from a mixture of normal distribution.

hello,please show me how to express the dielectric function of hydrogenated graphene ,any guidance

I noticed in the attached research paper (page- 82, eq. (2)),

x(k+1)=f(x(k))+g(x(k))u(k),

where f(x(k)) and g(x(k)) are smooth in their domain of definition.

My problem is how a discrete-time function is smooth? Discrete-time function is defined only on sampling instants. Thus, it is not continuous in conventional sense. How can we claim discrete-time function smooth? What could be the domain of definition?

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