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Soft light is broadly de ned as any light that is diffused or re ected by some material to scatter the light rays so that they strike the subject from various angles. This type of light lls in the shadows a bit and reduces the intensity of highlights. Soft lighting is the preferred choice for portrait photography because of its natural depiction of skin, hair, and clothing, moderate contrast, and overall pleasing visual effects. Soft light is most commonly found on a cloudy day where the light from the sun passes through the clouds and scatters, producing less intense shadows, softer transfer edges to shadows, and more diffused highlights. Soft light from overcast days can look slightly cool in your images, so setting your camera to the cloudy white balance setting brings back some necessary warmth to the image. Soft light can also be created in the studio by using lighting modi ers to diffuse the hard light emitted from the direct ash, such as umbrellas, softboxes, and beauty dishes. Much like hard light, too much soft light can reduce shadows and have a detrimental effect on the image by reducing contrast and making the image look at. In these situations, I try to nd some color-contrasting elements to work into the image to give it some edge.



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which differs by a constant factor from the analogous Shub Smale result for (1 + u)d , which is d m/2 . 4. Linear systems with a quadratic perturbation. Consider linear systems with a quadratic perturbation Xi (s) = i + < i , s > + i s 2 , where the i , i , i , i = 1, . . . , m are independent and standard normal in R, R, and Rm , respectively. This corresponds to the covariance r Xi (s, t) = 1 + s, t + s 2 t 2 . If there is no quadratic perturbation, it is obvious that the number of roots is a.s. equal to 1. For the perturbed system, applying Theorem 12.11 and performing the computations required in this case, we obtain q(x) = r(x) = 1 , 1 + x + x2 4 (1 + 2x)2 , 2 1+x+x (1 + x + x 2 )2 h(x) = 1 + 4x + x 2 1 + x + x2





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public UserForm() { } public String getAction() { return action; } public void setAction(String _action) { action = _action; } public String getFirstName() {

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The integral involved in the Hilbert transform is an improper integral, which is actually an abbreviation of the following:

3

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is indeed a solution to the Vasicek SDE dr = a(r r)dt + dz subject to the initial condition r(t0) = r0.

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e / 2 ( / 2)i p (i + v / 2,1/ 2) (z) i!

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