Wave-vector dependence of spin and density multipole excitations in quantum dots

We have employed time-dependent local-spin density-functional theory to analyze the multipole spin and charge density excitations in GaAs-AlxGa1-xAs quantum dots. The on-plane transferred momentum degree of freedom has been taken into account, and the wave-vector dependence of the excitations is discussed. In agreement with previous experiments, we have found that the energies of these modes do not depend on the transferred wave vector, although their intensities do. Comparison with a recent resonant Raman scattering experiment [C. Schüller et al., Phys. Rev. Lett. 80, 2673 (1998)] is made. This allows us to identify the angular momentum of several of the observed modes as well as to reproduce their energies

Computational problems in perfect phylogeny haplotyping: typing without calling the allele.

A haplotype is an m-long binary vector. The XOR-genotype of two haplotypes is the m-vector of their coordinate-wise XOR. We study the following problem: Given a set of XOR-genotypes, reconstruct their haplotypes so that the set of resulting haplotypes can be mapped onto a perfect phylogeny (PP) tree. The question is motivated by studying population evolution in human genetics, and is a variant of the perfect phylogeny haplotyping problem that has received intensive attention recently. Unlike the latter problem, in which the input is "full" genotypes, here we assume less informative input, and so may be more economical to obtain experimentally. Building on ideas of Gusfield, we show how to solve the problem in polynomial time, by a reduction to the graph realization problem. The actual haplotypes are not uniquely determined by that tree they map onto, and the tree itself may or may not be unique. We show that tree uniqueness implies uniquely determined haplotypes, up to inherent degrees of freedom, and give a sufficient condition for the uniqueness. To actually determine the haplotypes given the tree, additional information is necessary. We show that two or three full genotypes suffice to reconstruct all the haplotypes, and present a linear algorithm for identifying those genotypes.

Generation of a tightly regulated all-cis beta cell-specific tetracycline-inducible vector.

Ability to induce protein expression at will in a cell is a powerful strategy used by scientists to better understand the function of a protein of interest. Various inducible systems have been designed in eukaryotic cells to achieve this goal. Most of them rely on two distinct vectors, one encoding a protein that can regulate transcription by binding a compound X, and one hosting the cDNA encoding the protein of interest placed downstream of promoter sequences that can bind the protein regulated by compound X (e.g., tetracycline, ecdysone). The commercially available systems are not designed to allow cell- or tissue-specific regulated expression. Additionally, although these systems can be used to generate stable clones that can be induced to express a given protein, extensive screening is often required to eliminate the clones that display poor induction or high basal levels. In the present report, we aimed to design a pancreatic beta cell-specific tetracycline-inducible system. Since the classical two-vector based tetracycline-inducible system proved to be unsatisfactory in our hands, a single vector was eventually designed that allowed tight beta cell-specific tetracycline induction in unselected cell populations.

Task 6: Material Thermal Input for Iowa Materials, May 2008

The present research project was designed to determine thermal properties, such as coefficient of thermal expansion (CTE) and thermal conductivity, of Iowa concrete pavement materials. These properties are required as input values by the Mechanistic-Empirical Pavement Design Guide (MEPDG). In this project, a literature review was conducted to determine the factors that affect thermal properties of concrete and the existing prediction equations for CTE and thermal conductivity of concrete. CTE tests were performed on various lab and field samples of portland cement concrete (PCC) at the Iowa Department of Transportation and Iowa State University. The variations due to the test procedure, the equipment used, and the consistency of field batch materials were evaluated. The test results showed that the CTE variations due to test procedure and batch consistency were less than 5%, and the variation due to the different equipment was less than 15%. Concrete CTE values were significantly affected by different types of coarse aggregate. The CTE values of Iowa concrete made with limestone+graval, quartzite, dolomite, limestone+dolomite, and limestone were 7.27, 6.86, 6.68, 5.83, and 5.69 microstrain/oF (13.08, 12.35, 12.03, 10.50, and 10.25 microstrain/oC), respectively, which were all higher than the default value of 5.50 microstrain/oF in the MEPDG program. The thermal conductivity of a typical Iowa PCC mix and an asphalt cement concrete (ACC) mix (both with limestone as coarse aggregate) were tested at Concrete Technology Laboratory in Skokie, Illinois. The thermal conductivity was 0.77 Btu/hr•ft•oF (1.33 W/m•K) for PCC and 1.21 Btu/hr•ft•oF (2.09 W/m•K) for ACC, which are different from the default values (1.25 Btu/hr•ft•oF or 2.16 W/m•K for PCC and 0.67 Btu/hr•ft•oF or 1.16 W/m•K for ACC) in the MEPDG program. The investigations onto the CTE of ACC and the effects of concrete materials (such as cementitious material and aggregate types) and mix proportions on concrete thermal conductivity are recommended to be considered in future studies.

MEPDG Work Plan Task No. 7: Existing Pavement Input Information for the Mechanistic-Empirical Pavement Design Guide, 2009

The objective of this study is to systematically evaluate the Iowa Department of Transportation’s (DOT’s) existing Pavement Management Information System (PMIS) with respect to the input information required for Mechanistic-Empirical Pavement Design Guide (MEPDG) rehabilitation analysis and design. To accomplish this objective, all of available PMIS data for interstate and primary roads in Iowa were retrieved from the Iowa DOT PMIS. The retrieved data were evaluated with respect to the input requirements and outputs for the latest version of the MEPDG software (version 1.0). The input parameters that are required for MEPDG HMA rehabilitation design, but currently unavailable in the Iowa DOT PMIS were identified. The differences in the specific measurement metrics used and their units for some of the pavement performance measures between the Iowa DOT PMIS and MEPDG were identified and discussed. Based on the results of this study, it is recommended that the Iowa DOT PMIS should be updated, if possible, to include the identified parameters that are currently unavailable, but are required for MEPDG rehabilitation design. Similarly, the measurement units of distress survey results in the Iowa DOT PMIS should be revised to correspond to those of MEPDG performance predictions. *******************Large File**************************

Monitoring network optimisation for spatial data classification using support vector machines

The paper presents a novel method for monitoring network optimisation, based on a recent machine learning technique known as support vector machine. It is problem-oriented in the sense that it directly answers the question of whether the advised spatial location is important for the classification model. The method can be used to increase the accuracy of classification models by taking a small number of additional measurements. Traditionally, network optimisation is performed by means of the analysis of the kriging variances. The comparison of the method with the traditional approach is presented on a real case study with climate data.

Monitoring detrital input and resuspension effects on sediment trap material using mineralogy and stable isotopes (δ18O and δ13C): the case of Lake Neuchatel (Switzerland)

Isotopic analyses on bulk carbonates are considered a useful tool for palaeoclimatic reconstruction assuming calcite precipitation occurring at oxygen isotope equilibrium with local water and detrital carbonate input being absent or insignificant. We present results from Lake Neuchatel (western Switzerland) that demonstrate equilibrium precipitation of calcite, except during high productivity periods, and the presence of detrital and resuspended calcite. Mineralogy, geochemistry and stable isotope values of Lake Neuchatel trap sediments and adjacent rivers suspension were studied. Mineralogy of suspended matter in the major inflowing rivers documents an important contribution of detrital carbonates, predominantly calcite with minor amounts of dolomite and ankerite. Using mineralogical data, the quantity of allochthonous calcite can be estimated by comparing the ratio ankerite + dolomite/calcite + ankerite + dolomite in the inflowing rivers and in the traps. Material taken from sediment traps shows an evolution from practically pure endogenic calcite in summer (10-20% detrital material) to higher percentages of detrital material in winter (up to 20-40%). Reflecting these mineralogical variations, delta(13)C and delta(18)O values of calcite from sediment traps are more negative in summer than in winter times. Since no significant variations in isotopic composition of lake water were detected over one year, factors controlling oxygen isotopic composition of calcite in sediment traps are the precipitation temperature, and the percentage of resuspended and detrital calcite. Samples taken close to the river inflow generally have higher delta values than the others, confirming detrital influence. SEM and isotopic studies on different size fractions (<2, 2-6, 6-20, 20-60, >60 mu m) of winter and summer samples allowed the recognition of resuspension and to separate new endogenic calcite from detrital calcite. Fractions >60 and (2 mu m have the highest percentage of detritus, Fractions 2-6 and 6-20 mu m are typical for the new endogenic calcite in summer, as given by calculations assuming isotopic equilibrium with local water. In winter such fractions show similar values than in summer, indicating resuspension. Using the isotopic composition of sediment traps material and of different size fractions, as well as the isotopic composition of lake water, the water temperature measurements and mineralogy, we re-evaluated the bulk carbonate potential for palaeoclimatic reconstruction in the presence of detrital and re-suspended calcite. This re-evaluation leads to the following conclusion: (1) the endogenic signal can be amplified by applying a particle-size separation, once the size of endogenic calcite is known from SEM study; (2) resuspended calcite does not alter the endogenic signal, but it lowers the time resolution; (3) detrital input decreases at increasing distances from the source, and it modifies the isotopic signal only when very abundant; (4) influence of detrital calcite on bulk sediment isotopic composition can be calculated. (C) 1998 Elsevier Science B.V. All rights reserved.

Individual prediction of cognitive decline in mild cognitive impairment using support vector machine-based analysis of diffusion tensor imaging data.

Although cross-sectional diffusion tensor imaging (DTI) studies revealed significant white matter changes in mild cognitive impairment (MCI), the utility of this technique in predicting further cognitive decline is debated. Thirty-five healthy controls (HC) and 67 MCI subjects with DTI baseline data were neuropsychologically assessed at one year. Among them, there were 40 stable (sMCI; 9 single domain amnestic, 7 single domain frontal, 24 multiple domain) and 27 were progressive (pMCI; 7 single domain amnestic, 4 single domain frontal, 16 multiple domain). Fractional anisotropy (FA) and longitudinal, radial, and mean diffusivity were measured using Tract-Based Spatial Statistics. Statistics included group comparisons and individual classification of MCI cases using support vector machines (SVM). FA was significantly higher in HC compared to MCI in a distributed network including the ventral part of the corpus callosum, right temporal and frontal pathways. There were no significant group-level differences between sMCI versus pMCI or between MCI subtypes after correction for multiple comparisons. However, SVM analysis allowed for an individual classification with accuracies up to 91.4% (HC versus MCI) and 98.4% (sMCI versus pMCI). When considering the MCI subgroups separately, the minimum SVM classification accuracy for stable versus progressive cognitive decline was 97.5% in the multiple domain MCI group. SVM analysis of DTI data provided highly accurate individual classification of stable versus progressive MCI regardless of MCI subtype, indicating that this method may become an easily applicable tool for early individual detection of MCI subjects evolving to dementia.

Optimal priming of poxvirus vector (NYVAC)-based HIV vaccine regimens requires 3 DNA injections. Results of the EV03/ANRS Vac20 Phase I/II Trial

Background: Two or three DNA primes have been used in previous smaller clinical trials, but the number required for optimal priming of viral vectors has never been assessed in adequately powered clinical trials. The EV03/ANRS Vac20 phase I/II trial investigated this issue using the DNA prime/poxvirus NYVAC boost combination, both expressing a common HIV-1 clade C immunogen consisting of Env and Gag-Pol-Nef polypeptide. Methods: 147 healthy volunteers were randomly allocated through 8 European centres to either 3xDNA plus 1xNYVAC (weeks 0, 4, 8 plus 24; n¼74) or to 2xDNA plus 2xNYVAC (weeks 0, 4 plus 20, 24; n¼73), stratified by geographical region and sex. T cell responses were quantified using the interferon g Elispot assay and 8 peptide pools; samples from weeks 0, 26 and 28 (time points for primary immunogenicity endpoint), 48 and 72 were considered for this analysis. Results: 140 of 147 participants were evaluable at weeks 26 and/ or 28. 64/70 (91%) in the 3xDNA arm compared to 56/70 (80%) in the 2xDNA arm developed a T cell response (P¼0.053). 26 (37%) participants of the 3xDNA arm developed a broader T cell response (Env plus at least to one of the Gag, Pol, Nef peptide pools) versus 15 (22%) in the 2xDNA arm (P¼0.047). At week 26, the overall magnitude of responses was also higher in the 3xDNA than in the 2xDNA arm (similar at week 28), with a median of 545 versus 328 SFUs/106 cells at week 26 (P<0.001). Preliminary overall evaluation showed that participants still developed T-cell response at weeks 48 (78%, n¼67) and 72 (70%, n¼66). Conclusion: This large clinical trial demonstrates that optimal priming of poxvirus-based vaccine regimens requires 3 DNA regimens and further confirms that the DNA/NYVAC prime boost vaccine combination is highly immunogenic and induced durable T-cell responses.

Ensemble methods for environmental data modelling with support vector regression

This paper investigates the use of ensemble of predictors in order to improve the performance of spatial prediction methods. Support vector regression (SVR), a popular method from the field of statistical machine learning, is used. Several instances of SVR are combined using different data sampling schemes (bagging and boosting). Bagging shows good performance, and proves to be more computationally efficient than training a single SVR model while reducing error. Boosting, however, does not improve results on this specific problem.