Manifold spirals, disc-halo interactions and the secular evolution in N-body models of barred galaxies

The manifold theory of barred-spiral structure provides a dynamical mechanism explaining how spiral arms beyond the ends of galactic bars can be supported by chaotic flows extending beyond the bar's co-rotation zone. We discuss its applicability to N-body simulations of secularly evolving barred galaxies. In these simulations, we observe consecutive `incidents' of spiral activity, leading to a time-varying disc morphology. Besides disc self-excitations, we provide evidence of a newly noted excitation mechanism related to the `off-centering' effect: particles ejected in elongated orbits at major incidents cause the disc center-of-mass to recoil and be set in a wobble-type orbit with respect to the halo center of mass. The time-dependent m=1 perturbation on the disc by the above mechanism correlates with the excitation of new incidents of non-axisymmetric activity beyond the bar. At every new excitation, the manifolds act as dynamical avenues attracting particles which are directed far from corotation along chaotic orbits. The fact that the manifolds evolve morphologically in time, due to varying non-axisymmetric perturbations, allows to reconcile manifolds with the presence of multiple patterns and frequencies in the disc. We find a time-oscillating pattern speed profile $\Omega_p(R)$ at distances R between the bar's corotation, at resonance with the succession of minima and maxima of the non-axisymmetric activity beyond the bar. Finally, we discuss disc thermalization, i.e., the evolution of the disc velocity dispersion profile and its connection with disc responsiveness to manifold spirals.Comment: 20 pages, 22 figures. Accepted for publication in MNRA

Femur Stress Fracture - Marathon

HISTORY: During a race, a 35-year-old marathon runner complained of experiencing dull, achy pain in the right groin. After the race, he occasionally experienced radiating pain in the right thigh. The athlete was examined by a general practitioner (GP). During the clinical evaluation, the athlete had no signs of tenderness or swelling. The GP suggested rest and prescribed anti-inflammatory medication. PHYSICAL EXAMINATION: Ten days later, during training, the athlete felt the same discomfort after a challenging training session. He, then, decided to see an orthopedic physician. At the clinical examination, there was no localized pain. Focal pain was present during weight bearing activities only. Initial x-rays showed no significant abnormality or fracture. However, due to the complaints of the athlete, the doctor suggested additional x-rays and an MRI. DIFFERENTIAL DIAGNOSIS: Lumbar radiculopathy Rectus femoris strain Abductor strain Trochanteric bursitis TEST AND RESULTS: - X-ray showed a fracture of the middle shaft of the femur - MRI showed a medial periosteal reaction in the femoral shaft (high fluid signal) - Pain, especially during internal rotation - Pain on the affected side with a single-leg stance - Pain during activity, reproducible on passive range of motion FINAL / WORKING DIAGNOSIS: Stress fracture of the middle shaft of the right femur TREATMENT AND OUTCOMES: Tolerate weight bearing if no displacement occurs (four months max.) Treatment by a metabolic physician (Vitamin D deficiency or other) Continuing follow-up with repeated imaging: Verify resolution and minimize the progression to displacement Surgery if conservative management fails (see #1-3) Intramedullary rodding (surgical procedure

An Aggregation-Based Algebraic Multigrid Method with Deflation Techniques and Modified Generic Factored Approximate Sparse Inverses

In this paper, we examine deflation-based algebraic multigrid methods for solving large systems of linear equations. Aggregation of the unknown terms is applied for coarsening, while deflation techniques are proposed for improving the rate of convergence. More specifically, the V-cycle strategy is adopted, in which, at each iteration, the solution is computed by initially decomposing it utilizing two complementary subspaces. The approximate solution is formed by combining the solution obtained using multigrids and deflation. In order to improve performance and convergence behavior, the proposed scheme was coupled with the Modified Generic Factored Approximate Sparse Inverse preconditioner. Furthermore, a parallel version of the multigrid scheme is proposed for multicore parallel systems, improving the performance of the techniques. Finally, characteristic model problems are solved to demonstrate the applicability of the proposed schemes, while numerical results are given

Shoulder Arthroscopy After a Proximal Humeral Fracture Malunion: Athlete Care and Clinical Medicine in Middle-Aged Athletes

Malunion of the proximal humerus is operationally defined as healing of the fractured bone in a non-anatomical position, resulting in a painful and disabling deformity (e.g., a bone being shorter than normal, twisted or rotated in a bad position, or bent), which affects the range of motion (ROM) and functional movement. A correction and functional restoration are often needed in athletes, since their profession requires superior physical functioning. Shoulder arthroscopy has evolved dramatically over the past 15 years and has been used in cases of malunion of the humerus in athletes. However, there is a scarcity of evidence concerning middle-aged athletes. PURPOSE: To examine the benefits of shoulder arthroscopy after a proximal humeral fracture unified in malposition in middle-aged athletes. METHODS: Physical examination and imaging evaluation using 3D Computed Tomography(3D-CT), Magnetic Resonance Imaging (MRI), and shoulder radiographs (anteroposterior, internal rotation, and lateral scapular view) were used to evaluate shoulder dysfunction after proximal humeral fracture in malposition. Fourteen athletes (9 males, 5 females; Mage = 43.1, SD = 3.5) were included in this research. According to Neer classification before surgery, 11 (78%) had one part displaced and the rest three (22%) had two parts displaced. Post-operative clinical results were evaluated with self-reported pain score (1-10), UCLA scores, and shoulder abduction ROM measured with a goniometer. RESULTS: There was significant difference in pain scores (Mbefore = 8, Range: 6-9; Mafter = 4, Range: 2-6; p \u3c .001), in UCLA scores (Mbefore = 12, Range: 9-16; Mafter = 28, Range: 20-31; p \u3c .01), and in shoulder abduction ROM (Mbefore = 80, Range: 70-100; Mafter = 135, Range: 120-150; p \u3c .05). CONCLUSION: Our research provides evidence for clinical translation in improving health outcomes in middle-aged athletes with a history of proximal humeral fracture union in malposition: shoulder arthroscopy can be simultaneously beneficial in terms of decreasing pain level, increasing ROM, and restoring limb function

Parallel N

During the last decades, Multigrid methods have been extensively used for solving large sparse linear systems. Considering their efficiency and the convergence behavior, Multigrid methods are used in many scientific fields as solvers or preconditioners. Herewith, we propose two hybrid parallel algorithms for N-Body simulations using the Particle Mesh method and the Particle Particle Particle Mesh method, respectively, based on the V-Cycle Multigrid method in conjunction with Generic Approximate Sparse Inverses. The N-Body problem resides in a three-dimensional torus space, and the bodies are subject only to gravitational forces. In each time step of the above methods, a large sparse linear system is solved to compute the gravity potential at each nodal point in order to interpolate the solution to each body. Then the Velocity Verlet method is used to compute the new position and velocity from the acceleration of each respective body. Moreover, a parallel Multigrid algorithm, with a truncated approach in the levels computed in parallel, is proposed for solving large linear systems. Furthermore, parallel results are provided indicating the efficiency of the proposed Multigrid N-Body scheme. Theoretical estimates for the complexity of the proposed simulation schemes are provided

Simulating fog and edge computing scenarios: an overview and research challenges

The fourth industrial revolution heralds a paradigm shift in how people, processes, things, data and networks communicate and connect with each other. Conventional computing infrastructures are struggling to satisfy dramatic growth in demand from a deluge of connected heterogeneous endpoints located at the edge of networks while, at the same time, meeting quality of service levels. The complexity of computing at the edge makes it increasingly difficult for infrastructure providers to plan for and provision resources to meet this demand. While simulation frameworks are used extensively in the modelling of cloud computing environments in order to test and validate technical solutions, they are at a nascent stage of development and adoption for fog and edge computing. This paper provides an overview of challenges posed by fog and edge computing in relation to simulation

On issues concerning Cloud environments in scope of scalable multi-projection methods

Over the last decade, Cloud environments have gained significant attention by the scientific community, due to their flexibility in the allocation of resources and the various applications hosted in such environments. Recently, high performance computing applications are migrating to Cloud environments. Efficient methods are sought for solving very large sparse linear systems occurring in various scientific fields such as Computational Fluid Dynamics, N-Body simulations and Computational Finance. Herewith, the parallel multi-projection type methods are reviewed and discussions concerning the implementation issues for IaaS-type Cloud environments are given. Moreover, phenomena occurring due to the "noisy neighbor" problem, varying interconnection speeds as well as load imbalance are studied. Furthermore, the level of exposure of specialized hardware residing in modern CPUs through the different layers of software is also examined. Finally, numerical results concerning the applicability and effectiveness of multi-projection type methods in Cloud environments based on OpenStack are presented

Towards simulation and optimization of cache placement on large virtual Content Distribution Networks

IP video traffic is forecast to be 82% of all IP traffic by 2022. Traditionally, Content Distribution Networks (CDN) were used extensively to meet the quality of service levels for IP video services. To handle the dramatic growth in video traffic, CDN operators are migrating their infrastructure to the cloud and fog in order to leverage its greater availability and flexibility. For hyper-scale deployments, energy consumption, cache placement, and resource availability can be analyzed using simulation in order to improve resource utilization and performance. Recently, a discrete-time simulator for modelling hierarchical virtual CDNs (vCDNs) was proposed with reduced memory requirements and increased performance using multi-core systems to cater to the scale and complexity of these networks. The first iteration of this discrete-time simulator featured a number of limitations impacting accuracy and applicability: it supports only tree-based topology structures, the results are computed per level, and requests of the same content differ only in time duration. In this paper, we present an improved simulation framework that (a) supports graph-based network topologies, (b) requests have been reconstituted for differentiation of requirements, and (c) statistics are now computed per site and network metrics per link, improving the granularity and parallel performance. Moreover, we also propose a two-phase optimization scheme that makes use of simulation outputs to guide the search for optimal cache placements. In order to evaluate our proposal, we simulate a vCDN network based on real traces obtained from the BT vCDN infrastructure and analyze performance and scalability aspects

Heterogeneity, high performance computing, self-organization and the Cloud

This open access book addresses the most recent developments in cloud computing such as HPC in the Cloud, heterogeneous cloud, self-organising and self-management, and discusses the business implications of cloud computing adoption. Establishing the need for a new architecture for cloud computing, it discusses a novel cloud management and delivery architecture based on the principles of self-organisation and self-management. This focus shifts the deployment and optimisation effort from the consumer to the software stack running on the cloud infrastructure. It also outlines validation challenges and introduces a novel generalised extensible simulation framework to illustrate the effectiveness, performance and scalability of self-organising and self-managing delivery models on hyperscale cloud infrastructures. It concludes with a number of potential use cases for self-organising, self-managing clouds and the impact on those businesses

Practical recipes for the model order reduction, dynamical simulation, and compressive sampling of large-scale open quantum systems

This article presents numerical recipes for simulating high-temperature and non-equilibrium quantum spin systems that are continuously measured and controlled. The notion of a spin system is broadly conceived, in order to encompass macroscopic test masses as the limiting case of large-j spins. The simulation technique has three stages: first the deliberate introduction of noise into the simulation, then the conversion of that noise into an equivalent continuous measurement and control process, and finally, projection of the trajectory onto a state-space manifold having reduced dimensionality and possessing a Kahler potential of multi-linear form. The resulting simulation formalism is used to construct a positive P-representation for the thermal density matrix. Single-spin detection by magnetic resonance force microscopy (MRFM) is simulated, and the data statistics are shown to be those of a random telegraph signal with additive white noise. Larger-scale spin-dust models are simulated, having no spatial symmetry and no spatial ordering; the high-fidelity projection of numerically computed quantum trajectories onto low-dimensionality Kahler state-space manifolds is demonstrated. The reconstruction of quantum trajectories from sparse random projections is demonstrated, the onset of Donoho-Stodden breakdown at the Candes-Tao sparsity limit is observed, a deterministic construction for sampling matrices is given, and methods for quantum state optimization by Dantzig selection are given.Comment: 104 pages, 13 figures, 2 table