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Purpose — to compare the chemical elemental composition of vitreous cavity content taken from cadaveric eyes compared to samples taken from the eyes with terminal stage refractory glaucoma with decompensated intraocular pressure (IOP). Material and methods. The vitreous contents of the eyes from 2 groups were studied. The 1st group included 15 cadaveric eyes; the 2nd group included 15 eyes with refractory glaucoma in the terminal stage of the disease with decompensated IOP in patients with hypertension pain. The vitreal content samples were taken in the course of antiglaucoma surgery aimed at preserving the eye as an organ and involving employment of drainage in the vitreous cavity. The study of virtual contents was carried out on energy dispersive spectrometer Oxford X-Max 50 integrated into scanning electron microscope Zeiss EVO LS10. Results. Increased concentrations of Kalium and Phosphorus were detected in the vitreous content of cadaveric eyes compared with the vitreal content from the eyes with terminal glaucoma with decompensated IOP taken in vivo (K — 0.172/0.093; P — 0.045/0.025 mmol/L). In the vitreous cavity in the eyes with end-stage glaucoma with decompensated IOP, the concentration of Nitrogen was higher in comparison with human cadaver eyes (2.030/1.424 mmol/L). Conclusion. The increased concentrations of Kalium and Phosphorus in the vitreous content of cadaveric eyes is associated with postmortem autolytic processes and with the release of intracellular content in the destruction of cell membranes. The increased Nitrogen concentration in the vitreal contents of the eyes with terminal stage glaucoma with decompensated IOP may be associated with the presence of osmotically active nitrogen-containing compounds in the eyes with increased IOP.
A light-addressable potentiometric sensor (LAPS) is a field-effect-based (bio-) chemical sensor, in which a desired sensing area on the sensor surface can be defined by illumination. Light addressability can be used to visualize the concentration and spatial distribution of the target molecules, e.g., H+ ions. This unique feature has great potential for the label-free imaging of the metabolic activity of living organisms. The cultivation of those organisms needs specially tailored surface properties of the sensor. O2 plasma treatment is an attractive and promising tool for rapid surface engineering. However, the potential impacts of the technique are carefully investigated for the sensors that suffer from plasma-induced damage. Herein, a LAPS with a Ta2O5 pH-sensitive surface is successfully patterned by plasma treatment, and its effects are investigated by contact angle and scanning LAPS measurements. The plasma duration of 30 s (30 W) is found to be the threshold value, where excessive wettability begins. Furthermore, this treatment approach causes moderate plasma-induced damage, which can be reduced by thermal annealing (10 min at 300 °C). These findings provide a useful guideline to support future studies, where the LAPS surface is desired to be more hydrophilic by O2 plasma treatment.
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.