X-ray photoelectron spectroscopy of oxygen adsorbates on Al(111): Theory experiment

We present the result of polar angle resolved x¿ray photoemission spectroscopy on Al(111)/O and cluster calculations of the O(1s) binding energy (BE) for various model situations. In the experimental data two O(1s) peaks are observed, separated by 1.3 eV. The angular behavior (depth¿resolution) could indicate that the lower BE peak is associated with an O atom under the surface, and the higher BE peak with an O atom above the surface. Equally, it could indicate oxygen islands on the surface where the perimeter atoms have a higher O(1s) BE than the interior atoms. The cluster calculations show that the former interpretation cannot be correct, since an O ads below the surface has a higher calculated O(1s) BE than one above. Cluster calculations simulating oxygen islands are, however, consistent with the experimental data.

Modelling plant species distribution in alpine grasslands using airborne imaging spectroscopy.

Remote sensing using airborne imaging spectroscopy (AIS) is known to retrieve fundamental optical properties of ecosystems. However, the value of these properties for predicting plant species distribution remains unclear. Here, we assess whether such data can add value to topographic variables for predicting plant distributions in French and Swiss alpine grasslands. We fitted statistical models with high spectral and spatial resolution reflectance data and tested four optical indices sensitive to leaf chlorophyll content, leaf water content and leaf area index. We found moderate added-value of AIS data for predicting alpine plant species distribution. Contrary to expectations, differences between species distribution models (SDMs) were not linked to their local abundance or phylogenetic/functional similarity. Moreover, spectral signatures of species were found to be partly site-specific. We discuss current limits of AIS-based SDMs, highlighting issues of scale and informational content of AIS data.

Evidence for oxygen-island formation on Al(111): Cluster-model theory and x-ray photoelectron spectroscopy

The O 1s x-ray photoelectron spectroscopy spectrum for Al(111)/O at 300 K shows two components whose behavior as a function of time and variation of detection angle are consistent with either (a) a surface species represented by the higher binding-energy (BE) component and a subsurface species represented by the lower BE component, or (b) small close-packed oxygen islands with the interior atoms represented by the lower BE component and the perimeter atoms by the higher BE component. We have modeled both situations using ab initio Hartree-Fock wave functions for clusters of Al and O atoms. For an O atom in a threefold site, it was found that a below-surface position gave a higher O 1s BE than an above-surface position, incompatible with interpretation (a). This change in the O 1s BE could arise because the bond for O to Al may have a more covalent character when the O is below the surface than when it is above the surface. We present evidence consistent with this view. An O adatom island with all the O atoms in threefold sites gives calculated O 1s BE's which are significantly higher for the perimeter O atoms. Further, the results for an isolated O island without the Al substrate present also give higher BE¿s for the perimeter atoms. Both these results are consistent with interpretation (b). Published scanning-tunneling-microscopy data supports the suggestion that the chemisorbed state consists of small, close-packed islands, whereas the presence of two vibrational modes in high-resolution electron-energy-loss spectroscopy data has been interpreted as representing surface and subsurface oxygen atoms. In light of the present results, we suggest that a vibrational interpretation in terms of interior and perimeter adatoms should be considered.

Assessing the pH and DP of canvasses with NIR spectroscopy

The canvas support in easel paintings is composed mainly of cellulose. One of the maindegradation paths of cellulose is acid-catalysed hydrolysis, which means that in an acidic environment (low pH), its degradation proceeds at a faster rate (Strlič et al., 2005).The main effect of acid-catalysed hydrolysis is the breaking up of the polymer chains,measured by the “Degree of Polymerisation” (DP). The lowering of the DP value impliesa lower mechanical strength of the textile (Scicolone, 1993), and thus this parameter canbe used to monitor degradation. Knowing these two parameters can, therefore, be veryinformative regarding the condition of the canvas support.

The neurochemical profile quantified by in vivo 1H NMR spectroscopy.

Proton NMR spectroscopy is emerging from translational and preclinical neuroscience research as an important tool for evidence based diagnosis and therapy monitoring. It provides biomarkers that offer fingerprints of neurological disorders even in cases where a lesion is not yet observed in MR images. The collection of molecules used as cerebral biomarkers that are detectable by (1)H NMR spectroscopy define the so-called "neurochemical profile". The non-invasive quality of this technique makes it suitable not only for diagnostic purposes but also for therapy monitoring paralleling an eventual neuroprotection. The application of (1)H NMR spectroscopy in basic and translational neuroscience research is discussed here.

Assessing the pH and DP of canvasses with NIR spectroscopy

The canvas support in easel paintings is composed mainly of cellulose. One of the maindegradation paths of cellulose is acid-catalysed hydrolysis, which means that in an acidic environment (low pH), its degradation proceeds at a faster rate (Strlič et al., 2005).The main effect of acid-catalysed hydrolysis is the breaking up of the polymer chains,measured by the “Degree of Polymerisation” (DP). The lowering of the DP value impliesa lower mechanical strength of the textile (Scicolone, 1993), and thus this parameter canbe used to monitor degradation. Knowing these two parameters can, therefore, be veryinformative regarding the condition of the canvas support.

Evaluation of Photoacoustic Spectroscopy for Quality Control of Cement, TR-409, 1998

This report discusses the feasibility of using infrared photoacoustic spectroscopy (PAS) as a viable technique that can quickly provide information on cement composition prior to use. The PAS technique is of interest because the cost is much lower than for other types of instrumentation used for mineral analysis, it requires virtually no sample preparation, and it can perform multi-component analysis in a matter of minutes. Feasibility of the technique was based on the ability of PAS to identify and quantify sulfate species and major cement matrix components. Strengths and limitations of the technique are presented.

Memory-based scheduling of scientific computing clusters

This study looks at how increased memory utilisation affects throughput and energy consumption in scientific computing, especially in high-energy physics. Our aim is to minimise energy consumed by a set of jobs without increasing the processing time. The earlier tests indicated that, especially in data analysis, throughput can increase over 100% and energy consumption decrease 50% by processing multiple jobs in parallel per CPU core. Since jobs are heterogeneous, it is not possible to find an optimum value for the number of parallel jobs. A better solution is based on memory utilisation, but finding an optimum memory threshold is not straightforward. Therefore, a fuzzy logic-based algorithm was developed that can dynamically adapt the memory threshold based on the overall load. In this way, it is possible to keep memory consumption stable with different workloads while achieving significantly higher throughput and energy-efficiency than using a traditional fixed number of jobs or fixed memory threshold approaches.

FastEpistasis: a high performance computing solution for quantitative trait epistasis.

Motivation: Genome-wide association studies have become widely used tools to study effects of genetic variants on complex diseases. While it is of great interest to extend existing analysis methods by considering interaction effects between pairs of loci, the large number of possible tests presents a significant computational challenge. The number of computations is further multiplied in the study of gene expression quantitative trait mapping, in which tests are performed for thousands of gene phenotypes simultaneously. Results: We present FastEpistasis, an efficient parallel solution extending the PLINK epistasis module, designed to test for epistasis effects when analyzing continuous phenotypes. Our results show that the algorithm scales with the number of processors and offers a reduction in computation time when several phenotypes are analyzed simultaneously. FastEpistasis is capable of testing the association of a continuous trait with all single nucleotide polymorphism ( SNP) pairs from 500 000 SNPs, totaling 125 billion tests, in a population of 5000 individuals in 29, 4 or 0.5 days using 8, 64 or 512 processors.

Raman spectroscopy as a powerful analytical tool: probing the structure of matter

Podeu consultar el llibre complet a: http://hdl.handle.net/2445/32166

Applications of Fourier transform infrared spectroscopy

This article summarizes the basic principles of Fourier Transform Infrared Spectroscopy, with examples of methodologies and applications to different field sciences.

Photoelectron spectroscopy for surface analysis: X-ray and UV excitation

This article summarizes the basic principles of photoelectron spectroscopy for surface analysis, with examples of applications in material science that illustrate the capabilities of the related techniques.

Electron energy loss spectroscopy: physical principles, state of the art and applications to the nanosciences

In the present work we review the way in which the electron-matter interaction allows us to perform electron energy loss spectroscopy (EELS), as well as the latest developments in the technique and some of the most relevant results of EELS as a characterization tool in nanoscience and nanotechnology.

In vivo 13C NMR spectroscopy and metabolic modeling in the brain: a practical perspective.

In vivo 13C NMR spectroscopy has the unique capability to measure metabolic fluxes noninvasively in the brain. Quantitative measurements of metabolic fluxes require analysis of the 13C labeling time courses obtained experimentally with a metabolic model. The present work reviews the ingredients necessary for a dynamic metabolic modeling study, with particular emphasis on practical issues.