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Analyses of the bone microarchitecture were carried out in a region of interest (ROI), which was defined as the cancellous bone compartment beginning 0.6 mm proximal to the most proximal point of the growth plate and extending proximally 1.0 mm, corresponding to approximately 1.55 mm thick region of the distal femora.
We note that the proximal point of (imath_{C}) can easily be calculated or even has a closed-form solution if C has some special structure.
An increase in arterial stiffness leads to a more proximal point of reflection, thus altering the wave profile as measured by the instruments.
Prior to performing AP, the treating physician must perform a thorough evaluation with duplex ultrasound imaging to identify the source of venous hypertension and its most proximal point of reflux.
Li et al. [10] presented a proximal alternating linearization method for the sum of two nonconvex functions based on the assumption that the proximal point of the two functions at a given point can easily be calculated.
Between the bases of the first and second metacarpal bone, the tip of the triangular first web space can be palpated, indicating the most proximal point of the pedicle dissection.
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One popular method of solving is the proximal point algorithm of Rockafellar [3] which is recognized as a powerful and successful algorithm in finding a zero of monotone operators.
The proximal point algorithm of Rockafellar [4] is a successful algorithm for finding a zero point of maximal monotone operators.
involving the accretive mapping A. One popular method of solving equation 0 ∈ A x) is the proximal point algorithm of Rockafellar [1] which is recognized as a powerful and successful algorithm for finding a zero of monotone operators.
The proximal point algorithm of Martinet [35] and Rockafellar [36] was introduced to approximate a solution of (0in Au) where A is the subdifferential of some convex functional defined on a real Hilbert space.
The proximal point mapping of the function f at the point (xinmathbb{R}^{n}) is defined by p_{R}f(x):=argmin_{omegainmathbb{R}^{n}} biggl{ f omega )+ frac{1}{2}R Vert omega-x Vert ^{2} biggr}.
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