University of Cyprus

About: University of Cyprus is a education organization based out in Nicosia, Cyprus. It is known for research contribution in the topics: Large Hadron Collider & Context (language use). The organization has 3624 authors who have published 15157 publications receiving 412135 citations.

Variants of callous-unemotional conduct problems in a community sample of adolescents.

Abstract: Callous-unemotional traits are believed to be a childhood precursor to psychopathy, and among youth with conduct problems they designate those showing a particularly severe, stable, and aggressive pattern of antisocial behavior. Youth with callous-unemotional traits are a heterogeneous population and, analogous to adults with psychopathy, research suggests that lower anxious primary and high-anxious secondary variants exist. Using a community sample of 2,306 Greek-Cypriot adolescents (M age = 16 years; 49.7 % female), the first aim of the study was to examine whether variants of callous-unemotional traits could be identified using latent profile analysis of scores on measures of callous-unemotional traits, conduct problems, and anxiety. Additional aims of the study were to compare the identified clusters on external measures theorized to distinguish them (i.e., self-esteem, narcissism, impulsivity, sensation seeking and proactive/reactive aggression) and social factors relevant to adolescent development. Results indicated that, in addition to low risk (i.e., low scores on callous-unemotional traits, conduct problems, and anxiety) and anxious (i.e., high scores on anxiety, low scores on callous-unemotional traits and conduct problems) subgroups, two groups of youth scoring high on callous-unemotional traits and conduct problems were identified. High-anxious secondary callous-unemotional variants were distinguished by lower self-esteem in combination with greater narcissism, aggression, and markedly higher conduct problems, whereas lower anxious primary variants showed higher self-esteem. Secondary callous-unemotional variants also reported greater susceptibility to peer pressure and popularity striving than primary variants. Both variants exhibited poorer outcomes relative to low risk and anxious youth, although anxious youth reported lower self-esteem and higher impulsivity and reactive aggression scores in comparison with low risk youth. Findings integrate two lines of inquiry focused on subtyping children and adults with psychopathic traits and antisocial behaviors. They also support the utility of subtyping callous-unemotional traits based on conduct problems and anxiety levels and provide information on common and distinct risk factors associated with primary and secondary callous-unemotional variants in a community sample of adolescent boys and girls.

State-of-the-art review on deep learning in medical imaging.

Abstract: Deep learning (DL) is affecting each and every sphere of public and private lives and becoming a tool for daily use. The power of DL lies in the fact that it tries to imitate the activities of neurons in the neocortex of human brain where the thought process takes place. Therefore, like the brain, it tries to learn and recognize patterns in the form of digital images. This power is built on the depth of many layers of computing neurons backed by high power processors and graphics processing units (GPUs) easily available today. In the current scenario, we have provided detailed survey of various types of DL systems available today, and specifically, we have concentrated our efforts on current applications of DL in medical imaging. We have also focused our efforts on explaining the readers the rapid transition of technology from machine learning to DL and have tried our best in reasoning this paradigm shift. Further, a detailed analysis of complexities involved in this shift and possible benefits accrued by the users and developers.

Performance of reconstruction and identification of τ leptons decaying to hadrons and vτ in pp collisions at √s=13 TeV

Abstract: The algorithm developed by the CMS Collaboration to reconstruct and identify τ leptons produced in proton-proton collisions at √s=7 and 8 TeV, via their decays to hadrons and a neutrino, has been significantly improved. The changes include a revised reconstruction of π0 candidates, and improvements in multivariate discriminants to separate τ leptons from jets and electrons. The algorithm is extended to reconstruct τ leptons in highly Lorentz-boosted pair production, and in the high-level trigger. The performance of the algorithm is studied using proton-proton collisions recorded during 2016 at √s=13 TeV, corresponding to an integrated luminosity of 35.9 fb-1. The performance is evaluated in terms of the efficiency for a genuine τ lepton to pass the identification criteria and of the probabilities for jets, electrons, and muons to be misidentified as τ leptons. The results are found to be very close to those expected from Monte Carlo simulation.

An interior point method with Bregman functions for the variational inequality problem with paramonotone operators

Abstract: We present an algorithm for the variational inequality problem on convex sets with nonempty interior. The use of Bregman functions whose zone is the convex set allows for the generation of a sequence contained in the interior, without taking explicitly into account the constraints which define the convex set. We establish full convergence to a solution with minimal conditions upon the monotone operatorF, weaker than strong monotonicity or Lipschitz continuity, for instance, and including cases where the solution needs not be unique. We apply our algorithm to several relevant classes of convex sets, including orthants, boxes, polyhedra and balls, for which Bregman functions are presented which give rise to explicit iteration formulae, up to the determination of two scalar stepsizes, which can be found through finite search procedures. © 1998 The Mathematical Programming Society, Inc. Published by Elsevier Science B.V.

Hidden Liquidity: An Analysis of Order Exposure Strategies in Electronic Stock Markets

Abstract: Many stock exchanges choose to reduce market transparency by allowing traders to hide some or all of their order size. We study costs and benefits of hidden order usage for a sample of Euronext-Paris stocks, where hidden orders represent 44% of sample order volume. All else equal, hidden orders are associated with smaller opportunity costs and lower implementation shortfall costs. However, hidden orders are less likely to execute completely and exhibit longer times to execution. The presence and magnitude of hidden orders can be predicted to a significant but imperfect degree based on observable order attributes, firm characteristics and market conditions. We find that the option to hide order size is used differently by traders who submit passive versus aggressively priced orders. Specifically, aggressively priced orders tend to be exposed, to draw out potential counterparties and allow quick execution, while larger and less aggressively priced orders tend to be hidden, to reduce the option value of standing limit orders. Overall, the results indicate that the option to hide order size is valuable, in particular to patient traders without superior information on future security price movements.