Vascular Changes Following Exercise-Induced Hyperthermia

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Simultaneous observation of high order multiple quantum coherences at ultralow magnetic fields

We present a method for the simultaneous observation of heteronuclear multi-quantum coherences (up to the 3rd order), which give an additional degree of freedom for ultralow magnetic field (ULF) MR experiments, where the chemical shift is negligible. The nonequilibrium spin state is generated by Signal Amplification By Reversible Exchange (SABRE) and detected at ULF with SQUID-based NMR. We compare the results obtained by the heteronuclei Correlated SpectroscopY (COSY) with a Flip Angle FOurier Series (FAFOS) method. COSY allows a quantitative analysis of homo- and heteronuclei quantum coherences

A new technique for the reconstruction, validation, and simulation of hits in the CMS Pixel Detector

This note describes new techniques for the reconstruction/validation and the simulation of pixel hits. The techniques are based upon the use of pre-computed projected cluster shapes or ``templates''. A detailed simulation called Pixelav that has successfully described the profiles of clusters measured in beam tests of radiation-damaged sensors is used to generate the templates. Although the reconstruction technique was originally developed to optimally estimate the coordinates of hits after the detector became radiation damaged, it also has superior performance before irradiation. The technique requires a priori knowledge of the track angle which makes it suitable for the second in a two-pass reconstruction algorithm. However, the same modest angle sensitivity allows the algorithm to determine if the sizes and shapes of the cluster projections are consistent with the input angles. This information may be useful in suppressing spurious hits caused by secondary particles and in validating seeds used in track finding. The seed validation is currently under study but has the potential to significantly increase the speed of track finding in the offline reconstruction. Finally, a new procedure that uses the templates to re-weight clusters generated by the CMSSW simulation is described. The first tests of this technique are encouraging and when fully implemented, the technique will enable the fast simulation of pixel hits that have the characteristics of the much more CPU-intensive Pixelav hits. In particular, it may be the only practical technique available to simulate hits from a radiation damaged detector in CMSSW

Orthogonal variability modeling to support multi-cloud application configuration

Cloud service providers benefit from a vast majority of customers due to variability and making profit from commonalities between the cloud services that they provide. Recently, application configuration dimensions has been increased dramatically due to multi-tenant, multi-device and multi-cloud paradigm. This challenges the configuration and customization of cloud-based software that are typically offered as a service due to the intrinsic variability. In this paper, we present a model-driven approach based on variability models originating from the software product line community to handle such multi-dimensional variability in the cloud. We exploit orthogonal variability models to systematically manage and create tenant-specific configuration and customizations. We also demonstrate how such variability models can be utilized to take into account the already deployed application parts to enable harmonized deployments for new tenants in a multi-cloud setting. The approach considers application functional and non-functional requirements to provide a set of valid multi-cloud configurations. We illustrate our approach through a case study

Towards virtual machine energy-aware cost prediction in clouds

Pricing mechanisms employed by different service providers significantly influence the role of cloud computing within the IT industry. With the increasing cost of electricity, Cloud providers consider power consumption as one of the major cost factors to be maintained within their infrastructures. Consequently, modelling a new pricing mechanism that allow Cloud providers to determine the potential cost of resource usage and power consumption has attracted the attention of many researchers. Furthermore, predicting the future cost of Cloud services can help the service providers to offer the suitable services to the customers that meet their requirements. This paper introduces an Energy-Aware Cost Prediction Framework to estimate the total cost of Virtual Machines (VMs) by considering the resource usage and power consumption. The VMs’ workload is firstly predicted based on an Autoregressive Integrated Moving Average (ARIMA) model. The power consumption is then predicted using regression models. The comparison between the predicted and actual results obtained in a real Cloud testbed shows that this framework is capable of predicting the workload, power consumption and total cost for different VMs with good prediction accuracy, e.g. with 0.06 absolute percentage error for the predicted total cost of the VM

Cloud migration patterns: a multi-cloud service architecture perspective

Many organizations migrate their on-premise software systems to the cloud. However, current coarse-grained cloud migration solutions have made a transparent migration of on-premise applications to the cloud a difficult, sometimes trial-and-error based endeavor. This paper suggests a catalogue of fine-grained service-based cloud architecture migration patterns that target multi-cloud settings and are specified with architectural notations. The proposed migration patterns are based on empirical evi-dence from a number of migration projects, best practices for cloud architectures and a systematic literature review of existing research. The pattern catalogue allows an or-ganization to (1) select appropriate architecture migration patterns based on their ob-jectives, (2) compose them to define a migration plan, and (3) extend them based on the identification of new patterns in new contexts

The Relationship between Phytoplankton Distribution and Water Column Characteristics in North West European Shelf Sea Waters

Phytoplankton underpin the marine food web in shelf seas, with some species having properties that are harmful to human health and coastal aquaculture. Pressures such as climate change and anthropogenic nutrient input are hypothesized to influence phytoplankton community composition and distribution. Yet the primary environmental drivers in shelf seas are poorly understood. To begin to address this in North Western European waters, the phytoplankton community composition was assessed in light of measured physical and chemical drivers during the “Ellett Line” cruise of autumn 2001 across the Scottish Continental shelf and into adjacent open Atlantic waters. Spatial variability existed in both phytoplankton and environmental conditions, with clear differences not only between on and off shelf stations but also between different on shelf locations. Temperature/salinity plots demonstrated different water masses existed in the region. In turn, principal component analysis (PCA), of the measured environmental conditions (temperature, salinity, water density and inorganic nutrient concentrations) clearly discriminated between shelf and oceanic stations on the basis of DIN∶DSi ratio that was correlated with both salinity and temperature. Discrimination between shelf stations was also related to this ratio, but also the concentration of DIN and DSi. The phytoplankton community was diatom dominated, with multidimensional scaling (MDS) demonstrating spatial variability in its composition. Redundancy analysis (RDA) was used to investigate the link between environment and the phytoplankton community. This demonstrated a significant relationship between community composition and water mass as indexed by salinity (whole community), and both salinity and DIN∶DSi (diatoms alone). Diatoms of the Pseudo-nitzschia seriata group occurred at densities potentially harmful to shellfish aquaculture, with the potential for toxicity being elevated by the likelihood of DSi limitation of growth at most stations and depths