The Origin of Doping in Quasi-Free Standing Graphene on Silicon Carbide

We explain the robust p-type doping observed for quasi-free standing graphene on hexagonal silicon carbide by the spontaneous polarization of the substrate. This mechanism is based on a bulk property of SiC, unavoidable for any hexagonal polytype of the material and independent of any details of the interface formation. We show that sign and magnitude of the polarization are in perfect agreement with the doping level observed in the graphene layer. With this mechanism, models based on hypothetical acceptor-type defects as they are discussed so far are obsolete. The n-type doping of epitaxial graphene is explained conventionally by donor-like states associated with the buffer layer and its interface to the substrate which overcompensate the polarization doping.Comment: 10 pages, 1 figur

Coverage in WLAN: Optimization Model and Algorithm

When designing wireless communication systems, it is very important to know the optimum numbers of access points (APs) in order to provide a reliable design. In this paper we describe a mathematical model developed for finding the optimal number and location of APs. A new Global Optimization Algorithm (AGOP) is used to solve the problem. Results obtained demonstrate that the model and software are able to solve optimal coverage problems for design areas with different types of obstacles and number of users

Extracellular matrix mimetic peptide scaffolds for neural stem cell culture and differentiation

Self-assembled peptide nanofibers form three-dimensional networks that are quite similar to fibrous extracellular matrix (ECM) in their physical structure. By incorporating short peptide sequences derived from ECM proteins, these nanofibers provide bioactive platforms for cell culture studies. This protocol provides information about preparation and characterization of self-assembled peptide nanofiber scaffolds, culturing of neural stem cells (NSCs) on these scaffolds, and analysis of cell behavior. As cell behavior analyses, viability and proliferation of NSCs as well as investigation of differentiation by immunocytochemistry, qRT-PCR, western blot, and morphological analysis on ECM mimetic peptide nanofiber scaffolds are described

Electro-plating and characterisation of cadmium sulphide thin films using ammonium thiosulphate as the sulphur source

Cadmium sulphide (CdS) thin films have been successfully prepared from an aqueous electrolyte bath containing CdCl2 and ammonium thiosulphate ((NH4)2S2O3) using electrodeposition technique. The structural, compositional, optical, morphological and electrical properties of these thin films have been characterized using X-ray diffraction (XRD), Raman spectroscopy, energy dispersive X-ray spectroscopy, UV–Vis spectrophotometry, scanning electron microscopy (SEM), atomic force microscopy (AFM), photoelectrochemical cell and D.C. current–voltage (I–V) measurements. The optimum deposition cathodic potential has been observed at 1,455 mV, in a 2-electrode system with respect to carbon anode. Structural analysis using XRD shows a mixture of hexagonal and cubic phases in the as-deposited CdS samples and a phase transformation to the hexagonal structure occurred after heat treatment at 400 °C for 20 min. Optical studies demonstrate an improvement in the band edge, producing 2.42 eV for the band gap of the films after heat treatment. The heat treated CdS thin films show better transmission for wavelengths longer than 500 nm. SEM and AFM show that the heat-treated samples are more uniform, smoother and have larger grain size. Electrical studies confirm that the CdS thin films have n-type electrical conductivity and heat treated CdS thin films have resistivities of the order of 105 Ω cm

Emotional intelligence and British expatriates’ cross-cultural adjustment in international construction projects

© 2016 Informa UK Limited, trading as Taylor & Francis Group. Today’s internationalized business demands global mindset, intercultural sensitivity and the ability to skilfully negotiate through cross-cultural interactions. Therefore, the overall aim was to investigate the influence of emotional intelligence (EI) on cross-cultural adjustment (CCA) of British expatriates working on International Architectural, Engineering and Construction assignments in Sub-Saharan Africa, China, Middle East and Indian Sub-Continent. Specifically, the causal relationship between EI and three facets of CCA i.e. work, general and interaction adjustment was explored. A sequential exploratory mixed methods design was adopted. These include extensive review of existing literature, eighteen unstructured interviews, and questionnaire survey of 191 British expatriates operating in 29 different countries from the four regions under investigation. Structural equation modelling was used to assess the causal relationship between EI and CCA. Results show that EI accounted for 91, 64 and 24% of the variance in work, interaction and general adjustment respectively. Overall, the model was able to explain 60% variance in CCA, suggesting that EI competencies play a huge role in facilitating an expatriate understand and adapt to host country culture. The findings would help decision-makers (HR managers) during expatriate selection process, in understanding that along with technical skills, it is the emotional competencies that are crucial in assisting expatriates adjust to foreign way of life

A new scoring system in Cystic Fibrosis: statistical tools for database analysis – a preliminary report

<p>Abstract</p> <p>Background</p> <p>Cystic fibrosis is the most common fatal genetic disorder in the Caucasian population. Scoring systems for assessment of Cystic fibrosis disease severity have been used for almost 50 years, without being adapted to the milder phenotype of the disease in the 21^stcentury. The aim of this current project is to develop a new scoring system using a database and employing various statistical tools. This study protocol reports the development of the statistical tools in order to create such a scoring system.</p> <p>Methods</p> <p>The evaluation is based on the Cystic Fibrosis database from the cohort at the Royal Children's Hospital in Melbourne. Initially, unsupervised clustering of the all data records was performed using a range of clustering algorithms. In particular incremental clustering algorithms were used. The clusters obtained were characterised using rules from decision trees and the results examined by clinicians. In order to obtain a clearer definition of classes expert opinion of each individual's clinical severity was sought. After data preparation including expert-opinion of an individual's clinical severity on a 3 point-scale (mild, moderate and severe disease), two multivariate techniques were used throughout the analysis to establish a method that would have a better success in feature selection and model derivation: 'Canonical Analysis of Principal Coordinates' and 'Linear Discriminant Analysis'. A 3-step procedure was performed with (1) selection of features, (2) extracting 5 severity classes out of a 3 severity class as defined per expert-opinion and (3) establishment of calibration datasets.</p> <p>Results</p> <p>(1) Feature selection: CAP has a more effective "modelling" focus than DA.</p> <p>(2) Extraction of 5 severity classes: after variables were identified as important in discriminating contiguous CF severity groups on the 3-point scale as mild/moderate and moderate/severe, Discriminant Function (DF) was used to determine the new groups mild, intermediate moderate, moderate, intermediate severe and severe disease. (3) Generated confusion tables showed a misclassification rate of 19.1% for males and 16.5% for females, with a majority of misallocations into adjacent severity classes particularly for males.</p> <p>Conclusion</p> <p>Our preliminary data show that using CAP for detection of selection features and Linear DA to derive the actual model in a CF database might be helpful in developing a scoring system. However, there are several limitations, particularly more data entry points are needed to finalize a score and the statistical tools have further to be refined and validated, with re-running the statistical methods in the larger dataset.</p

Coding SNPs analysis highlights genetic relationships and evolution pattern in eggplant complexes

[EN] Brinjal (Solanum melongena), scarlet (S. aethiopicum) and gboma (S. macrocarpon) eggplants are three Old World domesticates. The genomic DNA of a collection of accessions belonging to the three cultivated species, along with a representation of various wild relatives, was characterized for the presence of single nucleotide polymorphisms (SNPs) using a genotype-by-sequencing approach. A total of 210 million useful reads were produced and were successfully aligned to the reference eggplant genome sequence. Out of the 75,399 polymorphic sites identified among the 76 entries in study, 12,859 were associated with coding sequence. A genetic relationships analysis, supported by the output of the FastSTRUCTURE software, identified four major sub-groups as present in the germplasm panel. The first of these clustered S. aethiopicum with its wild ancestor S. anguivi; the second, S. melongena, its wild progenitor S. insanum, and its relatives S. incanum, S. lichtensteinii and S. linneanum; the third, S. macrocarpon and its wild ancestor S. dasyphyllum; and the fourth, the New World species S. sisymbriifolium, S. torvum and S. elaeagnifolium. By applying a hierarchical FastSTRUCTURE analysis on partitioned data, it was also possible to resolve the ambiguous membership of the accessions of S. campylacanthum, S. violaceum, S. lidii, S. vespertilio and S. tomentsum, as well as to genetically differentiate the three species of New World Origin. A principal coordinates analysis performed both on the entire germplasm panel and also separately on the entries belonging to sub-groups revealed a clear separation among species, although not between each of the domesticates and their respective wild ancestors. There was no clear differentiation between either distinct cultivar groups or different geographical provenance. Adopting various approaches to analyze SNP variation provided support for interpretation of results. The genotyping-by-sequencing approach showed to be highly efficient for both quantifying genetic diversity and establishing genetic relationships among and within cultivated eggplants and their wild relatives. The relevance of these results to the evolution of eggplants, as well as to their genetic improvement, is discussed.This work has been funded in part by European Unions Horizon 2020 Research and Innovation Programme under grant agreement No 677379 (G2P-SOL project: Linking genetic resources, genomes and phenotypes of Solanaceous crops) and by Spanish Ministerio de Economia, Industria y Competitividad and Fondo Europeo de Desarrollo Regional (grant AGL2015-64755-R from MINECO/FEDER). Funding has also been received from the initiative "Adapting Agriculture to Climate Change: Collecting, Protecting and Preparing Crop Wild Relatives", which is supported by the Government of Norway. This last project is managed by the Global Crop Diversity Trust with the Millennium Seed Bank of the Royal Botanic Gardens, Kew and implemented in partnership with national and international gene banks and plant breeding institutes around the world. For further information see the project website:http://www.cwrdiversity.org/. Pietro Gramazio is grateful to Universitat Politecnica de Valencia for a pre-doctoral (Programa FPI de la UPV-Subprograma 1/2013 call) contract. Mariola Plazas is grateful to Spanish Ministerio de Economia, Industria y Competitividad for a post-doctoral grant within the Santiago Grisolia Programme (FCJI-2015-24835). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Acquadro, A.; Barchi, L.; Gramazio, P.; Portis, E.; Vilanova Navarro, S.; Comino, C.; Plazas Ávila, MDLO.... (2017). Coding SNPs analysis highlights genetic relationships and evolution pattern in eggplant complexes. PLoS ONE. 12(7). https://doi.org/10.1371/journal.pone.0180774Se018077412

An eQTL Analysis of Partial Resistance to Puccinia hordei in Barley

Background - Genetic resistance to barley leaf rust caused by Puccinia hordei involves both R genes and quantitative trait loci. The R genes provide higher but less durable resistance than the quantitative trait loci. Consequently, exploring quantitative or partial resistance has become a favorable alternative for controlling disease. Four quantitative trait loci for partial resistance to leaf rust have been identified in the doubled haploid Steptoe (St)/Morex (Mx) mapping population. Further investigations are required to study the molecular mechanisms underpinning partial resistance and ultimately identify the causal genes.Methodology/Principal Findings - We explored partial resistance to barley leaf rust using a genetical genomics approach. We recorded RNA transcript abundance corresponding to each probe on a 15K Agilent custom barley microarray in seedlings from St and Mx and 144 doubled haploid lines of the St/Mx population. A total of 1154 and 1037 genes were, respectively, identified as being P. hordei-responsive among the St and Mx and differentially expressed between P. hordei-infected St and Mx. Normalized ratios from 72 distant-pair hybridisations were used to map the genetic determinants of variation in transcript abundance by expression quantitative trait locus (eQTL) mapping generating 15685 eQTL from 9557 genes. Correlation analysis identified 128 genes that were correlated with resistance, of which 89 had eQTL co-locating with the phenotypic quantitative trait loci (pQTL). Transcript abundance in the parents and conservation of synteny with rice allowed us to prioritise six genes as candidates for Rphq11, the pQTL of largest effect, and highlight one, a phospholipid hydroperoxide glutathione peroxidase (HvPHGPx) for detailed analysis.Conclusions/Significance - The eQTL approach yielded information that led to the identification of strong candidate genes underlying pQTL for resistance to leaf rust in barley and on the general pathogen response pathway. The dataset will facilitate a systems appraisal of this host-pathogen interaction and, potentially, for other traits measured in this populatio