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Experience has shown that a priori created static resource allocation plans are vulnerable to runtime deviations and hence often become uneconomic or highly exceed a predefined soft deadline. The assumption of constant task execution times during allocation planning is even more unlikely in a cloud environment where virtualized resources vary in performance. Revising the initially created resource allocation plan at runtime allows the scheduler to react on deviations between planning and execution. Such an adaptive rescheduling of a many-task application workflow is only feasible, when the planning time can be handled efficiently at runtime. In this paper, we present the static low-complexity resource allocation planning algorithm (LCP) applicable to efficiently schedule many-task scientific application workflows on cloud resources of different capabilities. The benefits of the presented algorithm are benchmarked against alternative approaches. The benchmark results show that LCP is not only able to compete against higher complexity algorithms in terms of planned costs and planned makespan but also outperforms them significantly by magnitudes of 2 to 160 in terms of required planning time. Hence, LCP is superior in terms of practical usability where low planning time is essential such as in our targeted online rescheduling scenario.
Thermal and Optical Study on the Frequency Dependence of an Atmospheric Microwave Argon Plasma Jet
(2019)
Clearance of blood components and fluid drainage play a crucial role in subarachnoid hemorrhage (SAH) and post hemorrhagic hydrocephalus (PHH). With the involvement of interstitial fluid (ISF) and cerebrospinal fluid (CSF), two pathways for the clearance of fluid and solutes in the brain are proposed. Starting at the level of capillaries, flow of ISF follows along the basement membranes in the walls of cerebral arteries out of the parenchyma to drain into the lymphatics and CSF [1]–[3]. Conversely, it is shown that CSF enters the parenchyma between glial and pial basement membranes of penetrating arteries [4]–[6]. Nevertheless, the involved structures and the contribution of either flow pathway to fluid balance between the subarachnoid space and interstitial space remains controversial. Low frequency oscillations in vascular tone are referred to as vasomotion and corresponding vasomotion waves are modeled as the driving force for flow of ISF out of the parenchyma [7]. Retinal vessel analysis (RVA) allows non-invasive measurement of retinal vessel vasomotion with respect to diameter changes [8]. Thus, the aim of the study is to investigate vasomotion in RVA signals of SAH and PHH patients.
Recognition of subjects with mild cognitive impairment (MCI) by the use of retinal arterial vessels.
(2019)
Hypertension describes the pathological increase of blood pressure, which is most commonly associated with the increase of vascular wall stiffness [1]. Referring to the “Deutsche Bluthochdruck Liga” this pathology shows a growing trend in our aging society. In order to find novel pharmacological and probably personalized treatments, we want to present a functional approach to study biomechanical properties of a human aortic vascular model.
In this method review we will give an overview of recent studies which were carried out with the CellDrum technology [2] and underline the added value to already existing standard procedures known from the field of physiology.
Herein described CellDrum technology is a system to measure functional mechanical properties of cell monolayers and thin tissue constructs in-vitro. Additionally, the CellDrum enables to elucidate the mechanical response of cells to pharmacological drugs, toxins and vasoactive agents. Due to its highly flexible polymer support, cells can also be mechanically stimulated by steady and cyclic biaxial stretching.