Phase structure of the generalized two dimensional Yang-Mills theories on sphere

We find a general expression for the free energy of $G(\phi)=\phi^{2k}$ generalized 2D Yang-Mills theories in the strong ($A>A_c$) region at large $N$. We also show that in this region, the density function of Young tableau of these models is a three-cut problem. In the specific $\phi^6$ model, we show that the theory has a third order phase transition, like $\phi^2$ (YM_2) and $\phi^4$ models. We have some comments for $k \geq 4$ cases. At the end, we study the phase structure of $\phi^2 + g \phi^4$ model for $g \leq A/4$ region.Comment: 13 pages, LaTex,the introduction section was changed,will be appeared in: Eur. Phys. J. C (1999

Phase transition in multi-scalar-singlet extensions of the Standard Model

We propose a generalization of the Standard Model (SM) by adding two real gaugesinglets S1, S2. The field S1 will improve the strength of the electroweak phase transition (EWPT). Imposing a Z2 symmetry on the field S2 makes this field a possible candidate for dark matter. Both singlets interact with other observable fields through Higgs boson. They are allowed to interact with each other as well. We find that by introducing two different scalar fields, the model is less vulnerable to experimental constraints. In this paper, we consider the effects of a heavy scalar(M1 > MH) on the electroweak phase transition. And we present configurations that produce a strong first order EWPT

Projections Onto Convex Sets (POCS) Based Optimization by Lifting

Two new optimization techniques based on projections onto convex space (POCS) framework for solving convex and some non-convex optimization problems are presented. The dimension of the minimization problem is lifted by one and sets corresponding to the cost function are defined. If the cost function is a convex function in R^N the corresponding set is a convex set in R^(N+1). The iterative optimization approach starts with an arbitrary initial estimate in R^(N+1) and an orthogonal projection is performed onto one of the sets in a sequential manner at each step of the optimization problem. The method provides globally optimal solutions in total-variation, filtered variation, l1, and entropic cost functions. It is also experimentally observed that cost functions based on lp, p<1 can be handled by using the supporting hyperplane concept

Relationship between emotional intelligence and organizational citizenship behavior in critical and emergency nurses in south east of Iran

Background: Several factors including emotional intelligence affect the efficiency of people. It seems that organizational behavior of each person is strongly influenced by emotional intelligence. Therefore, the present study is aimed to examine the relationship between emotional intelligence and organizational citizenship behavior in critical and emergency nurses in teaching hospitals supervised by Kerman Medical University in Southeast of Iran.Methods: This study employed a descriptive cross sectional design. A census sample consisted of 150 critical and emergency nurses working in teaching hospitals supervised by Kerman Medical University participated in this study. Emotional intelligence and organizational citizenship behavior questionnaire was used to assess nurses’ emotional intelligence and organizational citizenship behavior by available sampling method.Results: The results showed that the mean age of the participants was 35 years. Most participants (94%) were females and belonged to the age group of 26-30 years. Overall mean score of organizational citizenship behavior scale was 88.21 (±10.4). In the organizational citizenship behavior categories, altruism mean score was higher than the other mean scores. Overall mean score of emotional intelligence was (121.08 ± 17.56). In the subgroups of emotional intelligence, mean score of the relationship management, was higher than the average of other factors. Pearson's correlation coefficient showed no significant relationship between emotional intelligence and organizational citizenship behavior (p ≥ 0.05).Conclusion: The study suggests that health care managers should organize systematic and dynamic policies and procedures in dealing with emotional intelligence and organizational citizenship behavior to assist critical and emergency nurses.Keywords: Emotional intelligence, Oorganizational citizenship behavior, nurse, critical ward, emergency war

Projections onto the epigraph set of the filtered variation function based deconvolution algorithm

A new deconvolution algorithm based on orthogonal projections onto the hyperplanes and the epigraph set of a convex cost function is presented. In this algorithm, the convex sets corresponding to the cost function are defined by increasing the dimension of the minimization problem by one. The Filtered Variation (FV) function is used as the convex cost function in this algorithm. Since the FV cost function is a convex function in RN, then the corresponding epigraph set is also a convex set in the lifted set in RN+1. At each step of the iterative deconvolution algorithm, starting with an arbitrary initial estimate in RN+1, first the projections onto the hyperplanes are performed to obtain the first deconvolution estimate. Then an orthogonal projection is performed onto the epigraph set of the FV cost function, in order to regularize and denoise the deconvolution estimate, in a sequential manner. The algorithm converges to the deblurred image. © 2016 IEEE

Denoising images corrupted by impulsive noise using projections onto the epigraph set of the total variation function (PES-TV)

In this article, a novel algorithm for denoising images corrupted by impulsive noise is presented. Impulsive noise generates pixels whose gray level values are not consistent with the neighboring pixels. The proposed denoising algorithm is a two-step procedure. In the first step, image denoising is formulated as a convex optimization problem, whose constraints are defined as limitations on local variations between neighboring pixels. We use Projections onto the Epigraph Set of the TV function (PES-TV) to solve this problem. Unlike other approaches in the literature, the PES-TV method does not require any prior information about the noise variance. It is only capable of utilizing local relations among pixels and does not fully take advantage of correlations between spatially distant areas of an image with similar appearance. In the second step, a Wiener filtering approach is cascaded to the PES-TV-based method to take advantage of global correlations in an image. In this step, the image is first divided into blocks and those with similar content are jointly denoised using a 3D Wiener filter. The denoising performance of the proposed two-step method was compared against three state-of-the-art denoising methods under various impulsive noise models. © 2015, Springer-Verlag London

Denoising using projections onto the epigraph set of convex cost functions

A new denoising algorithm based on orthogonal projections onto the epigraph set of a convex cost function is presented. In this algorithm, the dimension of the minimization problem is lifted by one and feasibility sets corresponding to the cost function using the epigraph concept are defined. As the utilized cost function is a convex function in RN, the corresponding epigraph set is also a convex set in RN+1. The denoising algorithm starts with an arbitrary initial estimate in RN+1. At each step of the iterative denoising, an orthogonal projection is performed onto one of the constraint sets associated with the cost function in a sequential manner. The method provides globally optimal solutions for total-variation, ℓ1, ℓ2, and entropic cost functions.1 © 2014 IEEE