Alien Registration- Markussen, Anna E. (Baldwin, Cumberland County)

https://digitalmaine.com/alien_docs/32974/thumbnail.jp

Surface decorated silicon nanowires: a route to high-ZT thermoelectrics

Based on atomistic calculations of electron and phonon transport, we propose to use surface decorated Silicon nanowires (SiNWs) for thermoelectric applications. Two examples of surface decorations are studied to illustrate the underlying deas: Nanotrees and alkyl functionalized SiNWs. For both systems we find, (i) that the phonon conductance is significantly reduced compared to the electronic conductance leading to high thermoelectric figure of merit, $ZT$, and (ii) for ultra-thin wires surface decoration leads to significantly better performance than surface disorder.Comment: Accepted for PR

Ab initio vibrations in nonequilibrium nanowires

We review recent results on electronic and thermal transport in two different quasi one-dimensional systems: Silicon nanowires (SiNW) and atomic gold chains. For SiNW's we compute the ballistic electronic and thermal transport properties on equal footing, allowing us to make quantitative predictions for the thermoelectric properties, while for the atomic gold chains we evaluate microscopically the damping of the vibrations, due to the coupling of the chain atoms to the modes in the bulk contacts. Both approaches are based on a combination of density-functional theory, and nonequilibrium Green's functions.Comment: 16 pages, to appear in Progress in Nonequilibrium Green's Functions IV (PNGF4), Eds. M. Bonitz and K. Baltzer, Glasgow, August 200

Reaction mechanism of trypsin-catalysed semisynthesis of human insulin studied by fast atom bombardment mass spectrometry

The production of semisynthetic human insulin for therapeutic purposes is of considerable importance. During trypsin-catalysed transformation of pig insulin into an ester of insulin of human sequence, the alanyl residue at position B30 is removed and replaced with an esterified residue of threonine. We have carried out this transformation in a medium enriched in 18OH2 and studied the product by MS. In contrast to a previous report, we find that incorporation of label into the B29−B30 peptide bond occurs during the transformation with threonine methyl ester in aqueous N, N-dimethylacetamide. Quantitative data are presented and the implications of these findings are discusse

A saturated consensus linkage map of Picea abies including AFLP, SSR, STS, 5S rDNA and morphological markers

International audienc

Regional N-Glycan and Lipid Analysis from Tissues Using MALDI-Mass Spectrometry Imaging

N-glycans and lipids are structural metabolites that play important roles in cellular processes. Both show unique regional distribution in tissues; therefore, spatial analyses of these metabolites are crucial to our understanding of cellular physiology. Matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) is an innovative technique that enables in situ detection of analytes with spatial distribution. This workflow details a MALDI-MSI protocol for the spatial profiling of N-glycans and lipids from tissues following application of enzyme and MALDI matrix. For complete details on the use and execution of this protocol, please refer to Drake et al. (2018) and Andres et al. (2020)

Statistical M-Estimation and Consistency in Large Deformable Models for Image Warping

The problem of defining appropriate distances between shapes or images and modeling the variability of natural images by group transformations is at the heart of modern image analysis. A current trend is the study of probabilistic and statistical aspects of deformation models, and the development of consistent statistical procedure for the estimation of template images. In this paper, we consider a set of images randomly warped from a mean template which has to be recovered. For this, we define an appropriate statistical parametric model to generate random diffeomorphic deformations in two-dimensions. Then, we focus on the problem of estimating the mean pattern when the images are observed with noise. This problem is challenging both from a theoretical and a practical point of view. M-estimation theory enables us to build an estimator defined as a minimizer of a well-tailored empirical criterion. We prove the convergence of this estimator and propose a gradient descent algorithm to compute this M-estimator in practice. Simulations of template extraction and an application to image clustering and classification are also provided

Effects of allochthonous dissolved organic matter input on microbial composition and nitrogen cycling genes at two contrasting estuarine sites

Heterotrophic bacteria are important drivers of nitrogen (N) cycling and the processing of dissolved organic matter (DOM). Projected increases in precipitation will potentially cause increased loads of riverine DOM to the Baltic Sea and likely affect the composition and function of bacterioplankton communities. To investigate this, the effects of riverine DOM from two different catchment areas (agricultural and forest) on natural bacterioplankton assemblages from two contrasting sites in the Baltic Sea were examined. Two microcosm experiments were carried out, where the community composition (16S rRNA gene sequencing), the composition of a suite of N-cycling genes (metagenomics) and the abundance and transcription of ammonia monooxygenase (amoA) genes involved in nitrification (quantitative PCR) were investigated. The river water treatments evoked a significant response in bacterial growth, but the effects on overall community composition and the representation of N-cycling genes were limited. Instead, treatment effects were reflected in the prevalence of specific taxonomic families, specific N-related functions and in the transcription of amoA genes. The study suggests that bacterioplankton responses to changes in the DOM pool are constrained to part of the bacterial community, whereas most taxa remain relatively unaffected.Peer reviewe

An Experimental Framework for 5G Wireless System Integration into Industry 4.0 Applications

The fourth industrial revolution, or Industry 4.0 (I4.0), makes use of wireless technologies together with other industrial Internet-of-Things (IIoT) technologies, cyber–physical systems (CPS), and edge computing to enable the optimization and the faster re-configuration of industrial production processes. As I4.0 deployments are ramping up, the practical integration of 5G wireless systems with existing industrial applications is being explored in both Industry and Academia, in order to find optimized strategies and to develop guidelines oriented towards ensuring the success of the industrial wireless digitalization process. This paper explores the challenges arisen from such integration between industrial systems and 5G wireless, and presents a framework applicable to achieve a structured and successful integration. The paper aims at describing the different aspects of the framework such as the application operational flow and its associated tools, developed based on analytical and experimental applied research methodologies. The applicability of the framework is illustrated by addressing the integration of 5G technology into a specific industrial use case: the control of autonomous mobile robots. The results indicate that 5G technology can be used for reliable fleet management control of autonomous mobile robots in industrial scenarios, and that 5G can support the migration of the on-board path planning intelligence to the edge-cloud