Hyperpolarized Xe MR imaging of alveolar gas uptake in humans.

BACKGROUND: One of the central physiological functions of the lungs is to transfer inhaled gases from the alveoli to pulmonary capillary blood. However, current measures of alveolar gas uptake provide only global information and thus lack the sensitivity and specificity needed to account for regional variations in gas exchange. METHODS AND PRINCIPAL FINDINGS: Here we exploit the solubility, high magnetic resonance (MR) signal intensity, and large chemical shift of hyperpolarized (HP) (129)Xe to probe the regional uptake of alveolar gases by directly imaging HP (129)Xe dissolved in the gas exchange tissues and pulmonary capillary blood of human subjects. The resulting single breath-hold, three-dimensional MR images are optimized using millisecond repetition times and high flip angle radio-frequency pulses, because the dissolved HP (129)Xe magnetization is rapidly replenished by diffusive exchange with alveolar (129)Xe. The dissolved HP (129)Xe MR images display significant, directional heterogeneity, with increased signal intensity observed from the gravity-dependent portions of the lungs. CONCLUSIONS: The features observed in dissolved-phase (129)Xe MR images are consistent with gravity-dependent lung deformation, which produces increased ventilation, reduced alveolar size (i.e., higher surface-to-volume ratios), higher tissue densities, and increased perfusion in the dependent portions of the lungs. Thus, these results suggest that dissolved HP (129)Xe imaging reports on pulmonary function at a fundamental level.

Ultralow Silicon Substrate Noise Crosstalk Using Metal Faraday Cages in an SOI Technology

In mixed signal integrated circuits noise from the digital circuitry can upset the sensitive analogue circuitry. The Faraday cage structure reported here is based on the unique ground plane SOI technology developed some of the authors. The suppression of crosstalk achieved is an order of magnitude greater than that previously published for frequencies up to 10 GHz. The significance of the technology will be even greater as the operating frequency is increased. This collaborative EPSRC project was judge as tending to outstanding.

Paul Karl Feyerabend Las proyecciones de la proliferación teórica en la relación ciencia-metafísica

La doctrina de la Proliferación teórica de Paul Karl Feyerabend ha sido interpretada por sus especialistas como un intento de salvaguardar el ideal del progreso científico. Aunque tales estudios hacen justicia, en parte, a la intencionalidad de nuestro filósofo no explicitan la crítica fundamental que implica para Feyerabend el pluralismo teórico. La proliferación teórica constituye en sí misma una reductio ad absurdum de los distintos intentos del positivismo lógico y del racionalismo crítico por definir la ciencia a expensas de lo metafísico. Este artículo presenta la proliferación teórica como una reivindicación del papel positivo que ocupa la metafísica en el quehacer científico. Se consigna la defensa que hace Feyerabend de la metafísica en cuanto que ésta constituye la posibilidad de superar el conservadurismo conceptual, aumentar de contenido empírico de la ciencia y recuperar el valor descriptivo de las teorías científicas.

Hot Electrons Transverse Refluxing in Ultraintense Laser-Solid Interactions

We have analyzed the coupling of ultraintense lasers (at similar to 2 X 1019 W/cm(2)) with solid foils of limited transverse extent (similar to 10 s of mu m) by monitoring the electrons and ions emitted from the target. We observe that reducing the target surface area allows electrons at the target surface to be reflected from the target edges during or shortly after the laser pulse. This transverse refluxing can maintain a hotter, denser and more homogeneous electron sheath around the target for a longer time. Consequently, when transverse refluxing takes places within the acceleration time of associated ions, we observe increased maximum proton energies (up to threefold), increased laser-to-ion conversion efficiency (up to a factor 30), and reduced divergence which bodes well for a number of applications.

Performance models of storage contention in cloud environments

We propose simple models to predict the performance degradation of disk requests due to storage device contention in consolidated virtualized environments. Model parameters can be deduced from measurements obtained inside Virtual Machines (VMs) from a system where a single VM accesses a remote storage server. The parameterized model can then be used to predict the effect of storage contention when multiple VMs are consolidated on the same server. We first propose a trace-driven approach that evaluates a queueing network with fair share scheduling using simulation. The model parameters consider Virtual Machine Monitor level disk access optimizations and rely on a calibration technique. We further present a measurement-based approach that allows a distinct characterization of read/write performance attributes. In particular, we define simple linear prediction models for I/O request mean response times, throughputs and read/write mixes, as well as a simulation model for predicting response time distributions. We found our models to be effective in predicting such quantities across a range of synthetic and emulated application workloads. 

WIQ:Work-intensive query scheduling for in-memory database systems

We propose a novel admission control policy for database queries. Our methodology uses system measurements of CPU utilization and query backlogs to determine interference between queries in execution on the same database server. Query interference may arise due to the concurrent access of hardware and software resources and can affect performance in positive and negative ways. Specifically our admission control considers the mix of jobs in service and prioritizes the query classes consuming CPU resources more efficiently. The policy ignores I/O subsystems and is therefore highly appropriate for in-memory databases. We validate our approach in trace-driven simulation and show performance increases of query slowdowns and throughputs compared to first-come first-served and shortest expected processing time first scheduling. Simulation experiments are parameterized from system traces of a SAP HANA in-memory database installation with TPC-H type workloads. © 2012 IEEE.

IO Performance Prediction in Consolidated Virtualized Environments

We propose a trace-driven approach to predict the performance degradation of disk request response times due to storage device contention in consolidated virtualized environments. Our performance model evaluates a queueing network with fair share scheduling using trace-driven simulation. The model parameters can be deduced from measurements obtained inside Virtual Machines (VMs) from a system where a single VM accesses a remote storage server. The parameterized model can then be used to predict the effect of storage contention when multiple VMs are consolidated on the same virtualized server. The model parameter estimation relies on a search technique that tries to estimate the splitting and merging of blocks at the the Virtual Machine Monitor (VMM) level in the case of multiple competing VMs. Simulation experiments based on traces of the Postmark and FFSB disk benchmarks show that our model is able to accurately predict the impact of workload consolidation on VM disk IO response times.

Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores

Polygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R(2) increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase.

Assessing the effectiveness of chemical treatment with nanomaterials in improving the quality of different industrial effluents

Industrial activities are the major sources of pollution in all environments. Depending on the type of industry, various levels of organic and inorganic pollutants are being continuously discharged into the environment. Although, several kinds of physical, chemical, biological or the combination of methods have been proposed and applied to minimize the impact of industrial effluents, few have proved to be totally effective in terms of removal rates of several contaminants, toxicity reduction or amelioration of physical and chemical properties. Hence, it is imperative to develop new and innovative methodologies for industrial wastewater treatment. In this context nanotechnology arises announcing the offer of new possibilities for the treatment of wastewaters mainly based on the enhanced physical and chemical proprieties of nanomaterials (NMs), which can remarkably increase their adsorption and oxidation potential. Although applications of NMs may bring benefits, their widespread use will also contribute for their introduction into the environment and concerns have been raised about the intentional use of these materials. Further, the same properties that make NMs so appealing can also be responsible for producing ecotoxicological effects. In a first stage, with the objective of selecting NMs for the treatment of organic and inorganic effluents we first assessed the potential toxicity of nanoparticles of nickel oxide (NiO) with two different sizes (100 and 10-20 nm), titanium dioxide (TiO2, < 25 nm) and iron oxide (Fe2O3, ≈ 85x425 nm). The ecotoxicological assessment was performed with a battery of assays using aquatic organisms from different trophic levels. Since TiO2 and Fe2O3 were the NMs that presented lower risks to the aquatic systems, they were selected for the second stage of this work. Thus, the two NMs pre-selected were tested for the treatment of olive mill wastewater (OMW). They were used as catalyst in photodegradation systems (TiO2/UV, Fe2O3/UV, TiO2/H2O2/UV and Fe2O3/H2O2/UV). The treatments with TiO2 or Fe2O3 combined with H2O2 were the most efficient in ameliorating some chemical properties of the effluent. Regarding the toxicity to V. fischeri the highest reduction was recorded for the H2O2/UV system, without NMs. Afterwards a sequential treatment using photocatalytic oxidation with NMs and degradation with white-rot fungi was applied to OMW. This new approach increased the reduction of chemical oxygen demand, phenolic content and ecotoxicity to V. fischeri. However, no reduction in color and aromatic compounds was achieved after 21 days of biological treatment. The photodegradation systems were also applied to treat the kraft pulp mill and mining effluents. For the organic effluent the combination NMs and H2O2 had the best performances in reduction the chemical parameters as well in terms of toxicity reduction. However, for the mine effluent the best (TiO2/UV and Fe2O3/UV) were only able to significantly remove three metals (Zn, Al and Cd). Nonetheless the treatments were able of reducing the toxicity of the effluent. As a final stage, the toxicity of solid wastes formed during wastewater treatment with NMs was assessed with Chironomus riparius larvae, a representative species of the sediment compartment. Certain solid wastes showed the potential to negatively affect C. riparius survival and growth, depending on the type of effluent treated. This work also brings new insights to the use of NMs for the treatment of industrial wastewaters. Although some potential applications have been announced, many evaluations have to be performed before the upscaling of the chemical treatments with NMs.