Macro- and microscale variables regulate stent haemodynamics,fibrin deposition and thrombomodulin expression

Drug eluting stents are associated with late stent thrombosis (LST), delayed healing and prolonged exposure of stent struts to blood flow. Using macroscale disturbed and undisturbed fluid flow waveforms, we numerically and experimentally determined the effects of microscale model strut geometries upon the generation of prothrombotic conditions that are mediated by flow perturbations. Rectangular cross-sectional stent strut geometries of varying heights and corresponding streamlined versions were studied in the presence of disturbed and undisturbed bulk fluid flow. Numerical simulations and particle flow visualization experiments demonstrated that the interaction of bulk fluid flow and stent struts regulated the generation, size and dynamics of the peristrut flow recirculation zones. In the absence of endothelial cells, deposition of thrombin-generated fibrin occurred primarily in the recirculation zones. When endothelium was present, peristrut expression of anticoagulant thrombomodulin (TM) was dependent on strut height and geometry. Thinner and streamlined strut geometries reduced peristrut flow recirculation zones decreasing prothrombotic fibrin deposition and increasing endothelial anticoagulant TM expression. The studies define physical and functional consequences of macro- and microscale variables that relate to thrombogenicity associated with the most current stent designs, and particularly to LST.     

A comparative study of rate monotonic schedulability tests

With the increased penetration of real-time systems into our surroundings, the selection of an efficient schedulability test under fixed priority system from a plethora of existing results, has become a matter of primary interest to real-time system designers. The need for a faster schedulability tests becomes more prominent when it applies to online systems, where processor time is a sacred resource and it is of central importance to assign processor to execute tasks instead of determining system schedulability. Under fixed priority nonpreemptive real-time systems, current schedulability tests (in exact form) can be divided into: response time based tests, and scheduling points tests. To the best of our knowledge, no comparative study of these test to date has ever been presented. The aim of this work is to assist the system designers in the process of selecting a suitable technique from the existing literature after knowing the pros and cons associated with these tests. We highlight the mechanism behind the feasibility tests, theoretically and experimentally. Our experimental results show that response time based tests are faster than scheduling points tests, which make the response time based tests an excellent choice for online systems.     

Computation Controllable Mode Decision and Motion Estimation for Scalable Video Coding

This paper proposes an efficient computation‐aware mode decision and search point (SP) allocation algorithm for spatial and quality scalabilities in Scalable Video Coding. In our proposal, a linear model is derived to allocate the computation for macroblocks in enhancement layers by using the rate distortion costs of the base layer. In addition, an adaptive SP decision algorithm is proposed to decide the number of SPs for motion estimation under the constraint of the allocated computation. Experiment results demonstrate that the proposed algorithm allocates the computation resource efficiently and outperforms other works in rate distortion performance under the same computational availability constraint.     

An algorithm comparison for dynamic optimization problems

This work presents a study on the performance of several algorithms on different continuous dynamic optimization problems. Eight algorithms have been used: SORIGA (an Evolutionary Algorithm), an agents-based algorithm, the mQSO (a widely used multi-population PSO) as well as three heuristic-rule-based variations of it, and two trajectory-based cooperative strategies. The algorithms have been tested on the Moving Peaks Benchmark and the dynamic version of the Ackley, Griewank and Rastrigin functions. For each problem, a wide variety of configuration variations have been used, emphasizing the influence of dynamism, and using a full-factorial experimental design. The results give an interesting overview of the properties of the algorithms and their applicability, and provide useful hints to face new problems of this type with the best algorithmic approach. Additionally, a recently introduced methodology for comparing a high number of experimental results in a graphical way is used.     

Situation identification techniques in pervasive computing: A review

Pervasive systems must offer an open, extensible, and evolving portfolio of services which integrate sensor data from a diverse range of sources. The core challenge is to provide appropriate and consistent adaptive behaviours for these services in the face of huge volumes of sensor data exhibiting varying degrees of precision, accuracy and dynamism. Situation identification is an enabling technology that resolves noisy sensor data and abstracts it into higher-level concepts that are interesting to applications. We provide a comprehensive analysis of the nature and characteristics of situations, discuss the complexities of situation identification, and review the techniques that are most popularly used in modelling and inferring situations from sensor data. We compare and contrast these techniques, and conclude by identifying some of the open research opportunities in the area.     

Motion planning algorithms for molecular simulations: A survey

Motion planning is a fundamental problem in robotics that has motivated research since more than three decades ago. A large variety of algorithms have been proposed to compute feasible motions of multi-body systems in constrained workspaces. In recent years, some of these algorithms have surpassed the frontiers of robotics, finding applications in other domains such as industrial manufacturing, computer animation and computational structural biology. This paper concerns the latter domain, providing a survey on motion planning algorithms applied to molecular modeling and simulation. Both the algorithmic and application sides are discussed, as well as the different issues to be taken into consideration when extending robot motion planning algorithms to deal with molecules. From an algorithmic perspective, the paper gives a general overview of the different extensions to sampling-based motion planners. From the point of view of applications, the survey deals with problems involving protein folding and conformational transitions, as well as protein–ligand interactions.