Covariant description of inelastic electron--deuteron scattering:predictions of the relativistic impulse approximation

Using the covariant spectator theory and the transversity formalism, the unpolarized, coincidence cross section for deuteron electrodisintegration, $d(e,e'p)n$, is studied. The relativistic kinematics are reviewed, and simple theoretical formulae for the relativistic impulse approximation (RIA) are derived and discussed. Numerical predictions for the scattering in the high $Q^2$ region obtained from the RIA and five other approximations are presented and compared. We conclude that measurements of the unpolarized coincidence cross section and the asymmetry $A_\phi$, to an accuracy that will distinguish between different theoretical models, is feasible over most of the wide kinematic range accessible at Jefferson Lab.Comment: 54 pages and 24 figure

Graph Minors and Parameterized Algorithm Design

Abstract. The Graph Minors Theory, developed by Robertson and Sey-mour, has been one of the most influential mathematical theories in pa-rameterized algorithm design. We present some of the basic algorithmic techniques and methods that emerged from this theory. We discuss its direct meta-algorithmic consequences, we present the algorithmic appli-cations of core theorems such as the grid-exclusion theorem, and we give a brief description of the irrelevant vertex technique

Clinical Complications in Procedures for Horizontal Bone Augmentation Through Autologous Onlay Grafts Obtained From the Mandibular Ramus: An Observational Study

Aim and Objective : The aim of this study was to describe clinically the prevalence of postsurgical complications in a group of patients treated with autologous bone grafts obtained from the mandibular ramus. Materials and Methods: Data were obtained from a sample of 76 adults, who were subjected to a surgical procedure of horizontal bone augmentation through autologous onlay bone grafts obtained from the oblique line of mandible. A total of 113 onlay grafts were removed and placed in 152 recipients’ area, previously fitted to the receptor site and stabilized through two fixation screws. All complications were recorded in relation to the recipient and donor sites, and the follow-up time of the sample was of 2 years. Results: Of the entire sample studied, 69.7% did not show any type of postsurgical complication; however, 30.3% of them exhibited a type of complication, with temporary paresthesia being the most prevalent (7.9%). Conclusion: More than 30% of the patients that received horizontal bone augmentation through autologous onlay bone grafts obtained from the oblique line according to the conventional technique showed some type of postsurgical complication

Quadratic kernelization for convex recoloring of trees

The CONVEX RECOLORING (CR) problem measures how far a tree of characters differs from exhibiting a so-called "perfect phylogeny". For input consisting of a vertex-colored tree T, the problem is to determine whether recoloring at most k vertices can achieve a convex coloring, meaning by this a coloring where each color class induces a connected subtree. The problem was introduced by Moran and Snir, who showed that CR is NP-hard, and described a search-tree based FPT algorithm with a running time of O(k(k/log k)(k)n(4)). The Moran and Snir result did not provide any nontrivial kernelization. Subsequently, a kernelization with a large polynomial bound was established. Here we give the strongest FPT results to date on this problem: (1) We show that in polynomial time, a problem kernel of size O(k(2)) can be obtained, and (2) We prove that the problem can be solved in linear time for fixed k. The technique used to establish the second result appears to be of general interest and applicability for bounded treewidth problems

G-DPS:A Game-theoretical Decision-making Framework for Physical Surveillance Games

Critical infrastructure protection becomes increasingly a major concern in governments and industries. Besides the increasing rates of cyber-crime, recent terrorist attacks bring critical infrastructure into a severer environment. Many critical infrastructures, in particular those operating large industry complexes, incorporate some kind of physical surveillance technologies to secure their premises. Surveillance systems, such as access control and malicious behavior detection, have been long used for perimeter security as a first line of defense. Traditional perimeter security solutions typically monitor the outer boundary structures and lines, thus ignoring threats from the inside. Moreover, the deterrent effect of surveillance systems like Closed Circuit Television (CCTV) becomes considerably less important due to the inflexibility induced by their fixed installations. Hence, an infrastructure’s surveillance policy is more predictable and a potential adversary has a better opportunity to observe and bypass it subsequently. Therefore, it is important to maintain situational awareness within such environments so that potential intruders can still be detected. Regardless of whether personnel (e.g., security guards, etc.) or technical solutions (e.g., cameras, etc.) are applied, such surveillance systems have an imperfect detection rate, leaving an intruder with the potential to cause some damage to the infrastructure. Hence, the core problem is to find an optimal application of the surveillance technology at hand to minimize such a potential damage. This problem already has a natural reflection in game theory known as cops-and-robbers game but current models always assume a deterministic outcome of the gameplay. In this work, we present a decision-making framework, which assesses possible choices and alternatives towards finding an optimal surveillance configurations and hence minimizing addressed risks. The decision is made by means of a game-theoretic model for optimizing physical surveillance systems and minimizing the potential damage caused by an intruder with respect to the imperfect detection rates of surveillance technology. With our approach, we have the advantage of using categorical (or continuous) distributions instead of a single numerical value to capture the uncertainty in describing the potential damage of an intruder. This gives us the opportunity to model the imperfection of surveillance systems and to optimize over large collections of empirical or simulated data without losing valuable information during the process