A survey on resource allocation in high performance distributed computing systems

An efficient resource allocation is a fundamental requirement in high performance computing (HPC) systems. Many projects are dedicated to large-scale distributed computing systems that have designed and developed resource allocation mechanisms with a variety of architectures and services. In our study, through analysis, a comprehensive survey for describing resource allocation in various HPCs is reported. The aim of the work is to aggregate under a joint framework, the existing solutions for HPC to provide a thorough analysis and characteristics of the resource management and allocation strategies. Resource allocation mechanisms and strategies play a vital role towards the performance improvement of all the HPCs classifications. Therefore, a comprehensive discussion of widely used resource allocation strategies deployed in HPC environment is required, which is one of the motivations of this survey. Moreover, we have classified the HPC systems into three broad categories, namely: (a) cluster, (b) grid, and (c) cloud systems and define the characteristics of each class by extracting sets of common attributes. All of the aforementioned systems are cataloged into pure software and hybrid/hardware solutions. The system classification is used to identify approaches followed by the implementation of existing resource allocation strategies that are widely presented in the literature.     

Potential effects in multi-resolution post-classification change detection

Change detection is one of the primary applications of remote-sensing data, and many techniques have been developed during the past three decades. Although frequently criticized and despite many alternatives, due to its simplicity and intuitive manner, post-classification change detection still remains one of the most applied techniques. Many studies in the field of change detection analysis acknowledge, for instance, the impact of misregistration, inconsistencies in classification schemes or differences in methods for image interpretation. However, there are additional, rarely studied influences that can cause large errors in change detection results, including integrating multi-resolution data, the adjacency effect and the minimum mapping units (MMUs) that are applied to the classification before change detection. This study demonstrates these effects for the complex land cover of the Alvarado mangrove area at the Mexican Gulf Coast, employing 10 m Système Pour l'Observation de la Terre 5 (SPOT-5) high geometric resolution (HRG)‐based and 57 m Landsat Multispectral Scanner (MSS) classifications. As a baseline, the proportion of the fine spatial resolution classes within the coarse spatial resolution cells were derived, from which proportional change matrices were computed. The analysis employs difference measures to compare change matrices and proportional maps. The impact of various tested resampling functions was negligible if coarse resolution data were refined. For coarsening fine spatial resolution data, change matrix comparison was comparatively small but yielded differences of approximately 20% in spatially explicit measures. Incorrect positional alignment indicated differences of up to 5% in the change matrix for a misregistration of 100 m and even higher spatially explicit differences (28%). The discrepancies due to the adjacency effect were rather low. MMUs of 25 ha resulted in differences of up to 36% in the change matrix. The magnitude of the discrepancies of all studied effects depends on the class diversity in the map, and some can also be related to the difference in spatial resolution.     

Field-Assisted Sintering of Nanocrystalline Titanium Nitride

Nanosized TiN powder was densified via field-assisted sintering at temperatures of 1150°–1350°C and a pressure of 66 MPa under vacuum. A maximum relative density of ∼97% and a maximum mean grain size of 150–200 nm were obtained. Densification and microstructural evolution have been discussed, in terms of superplasticity and electric-field effects.     

Characterization of Photoluminescent (Y1–xEux)2O3 Thin Films Prepared by Metallorganic Chemical Vapor Deposition

The purpose of this study was to identify and correlate the microstructural and luminescence properties of europium-doped Y₂O₃ (Y_{1– x} Eu _x )₂O₃ thin films deposited by metallorganic chemical vapor deposition (MOCVD), as a function of deposition time and temperature. The influence of deposition parameters on the crystallite size and microstructural morphology were examined, as well as the influence of these parameters on the photoluminescence emission spectra. (Y_{1– x} Eu _x )₂O₃ thin films were deposited onto (111) silicon and (001) sapphire substrates by MOCVD. The films were grown by reacting yttrium and europium tris(2,2,6,6-tetramethyl–3,5-heptanedionate) precursors with an oxygen atmosphere at low pressures (5 torr (1.7 × 10³ Pa)) and low substrate temperatures (500°–700°C). The films deposited at 500°C were smooth and composed of nanocrystalline regions of cubic Y₂O₃, grown in a textured [100] or [110] orientation to the substrate surface. Films deposited at 600°C developed, with increasing deposition time, from a flat, nanocrystalline morphology into a platelike growth morphology with [111] orientation. Monoclinic (Y_{1– x} Eu _x )₂O₃ was observed in the photoluminescence emission spectra for all deposition temperatures. The increase in photoluminescence emission intensity with increasing postdeposition annealing temperature was attributed to the surface/grain boundary area-reduction effect.     

Does green tea affect postprandial glucose,insulin and satiety in healthy subjects: a randomized controlled trial

Background  

Results of epidemiological studies have suggested that consumption of green tea could lower the risk of type 2 diabetes. Intervention studies show that green tea may decrease blood glucose levels, and also increase satiety. This study was conducted to examine the postprandial effects of green tea on glucose levels, glycemic index, insulin levels and satiety in healthy individuals after the consumption of a meal including green tea.     

The Influence of Strontium on Bone Tissue Metabolism and Its Application in Osteoporosis Treatment

Osteoporosis is a chronic disease characterized by low bone mass caused by increased bone turnover and impaired bone microarchitecture. In treatment, we use antiresorptive or anabolic drugs, which usually have a unidirectional effect, i.e., they inhibit the activity of osteoclasts or stimulate the effect of osteoblasts. Strontium ranelate is an anti-osteoporosis drug with a unique mechanism of action (used primarily in postmenopausal women). Unlike other medicines, it has a multidirectional effect on bone tissue, intensifying osteoblastogenesis while inhibiting osteoclastogenesis. It turns out that this effect is demonstrated by strontium ions, an element showing physical and chemical similarity to calcium, the basic element that builds the mineral fraction of bone. As a result, strontium acts through the calcium-sensing receptor (CaSR) receptor in bone tissue cells. In recent years, there has been a significant increase in interest in the introduction of strontium ions in place of calcium ions in ceramics used as bone replacement materials for the treatment of bone fractures and defects caused by osteoporosis. The aim of this study was to summarize current knowledge about the role of strontium in the treatment of osteoporosis, its effects (in various forms), and the ways in which it is administered.     

Involving domain experts in assistive technology research

Teams engaging in assistive technology research should include expertise in the domain of disability itself, in addition to other areas of expertise that are more typical in human–computer interaction (HCI) research, such as computer science and psychology. However, unexpected problems can arise when HCI researchers do not adequately plan the involvement of domain experts in a research project. Although many research teams have included domain experts when designing assistive technologies, there has been little work published on how to best involve these experts in the research process. This paper is a first step towards filling that void. Based on the authors’ own experiences involving domain experts in research, as well as those documented in the literature, five types of domain experts and three broad roles that domain experts can play are identified, and five guidelines for their involvement are presented. This analysis will be useful to anyone in the assistive technology and universal accessibility communities, especially those who are in the early stages of conducting research in this area. It is intended to lay the foundation of best practices for involving domain experts in assistive technology research.     

Initial Stages of Sintering of Alumina by Thermo-Optical Measurements

The behavior of nanostructured and submicrometer α-Al₂O₃ powders during the initial stages of field-assisted sintering technique (FAST), conventional, and microwave sintering was investigated using the laser-flash technique for thermo-optical measurements (TOM). An enhanced neck formation due to surface diffusion at very early stages of sintering was found in FAST samples. No significant difference due to heating rate has been found in these various samples.     

Magnetic resonance studies of cement based materials in inhomogeneous magnetic fields

Single-sided magnets give hope that Nuclear Magnetic Resonance (NMR) might in future be used for in situ characterisation of hydration and water transport in the surface layers of concrete slabs. Towards that end, a portable NMR-MOUSE (MObile Universal Surface Explorer) has been used to follow the hydration of gypsum based plaster, a Portland cement paste and concrete mortar. The results compare favourably to those obtained using a standard laboratory bench-top spectrometer. Further, stray field imaging (STRAFI) based methods have been used with embedded NMR detector coils to study water transport across a mortar/topping interface. The measured signal amplitudes are found to correlate with varying sample conditions.