Imaging and controlling electron transport inside a quantum ring

Traditionally, the understanding of quantum transport, coherent and ballistic1, relies on the measurement of macroscopic properties such as the conductance. While powerful when coupled to statistical theories, this approach cannot provide a detailed image of "how electrons behave down there". Ideally, understanding transport at the nanoscale would require tracking each electron inside the nano-device. Significant progress towards this goal was obtained by combining Scanning Probe Microscopy (SPM) with transport measurements2-7. Some studies even showed signatures of quantum transport in the surrounding of nanostructures4-6. Here, SPM is used to probe electron propagation inside an open quantum ring exhibiting the archetype of electron wave interference phenomena: the Aharonov-Bohm effect8. Conductance maps recorded while scanning the biased tip of a cryogenic atomic force microscope above the quantum ring show that the propagation of electrons, both coherent and ballistic, can be investigated in situ, and even be controlled by tuning the tip potential.Comment: 11 text pages + 3 figure

Spatial Current Patterns, Dephasing and Current Imaging in Graphene Nanoribbons

Using the non-equilibrium Keldysh Green's function formalism, we investigate the local, non-equilibrium charge transport in graphene nanoribbons (GNRs). In particular, we demonstrate that the spatial current patterns associated with discrete transmission resonances sensitively depend on the GNRs' geometry, size, and aspect ratio, the location and number of leads, and the presence of dephasing. We identify a relation between the spatial form of the current patterns, and the number of degenerate energy states participating in the charge transport. Furthermore, we demonstrate a principle of superposition for the conductance and spatial current patterns in multiple-lead configurations. We demonstrate that scanning tunneling microscopy (STM) can be employed to image spatial current paths in GNR with atomic resolution, providing important insight into the form of local charge transport. Finally, we investigate the effects of dephasing on the spatial current patterns, and show that with decreasing dephasing time, the current patterns evolve smoothly from those of a ballistic quantum network to those of classical resistor network.Comment: 25 pages, 12 figure

From multiple perspectives to shared understanding

The aim of this study was to explore how learners operating in a small group reach shared understanding as they work out joint research questions and build a theoretical framework and to identify the resources and tools they used in the process. The learners’ own interpretations of their group activities and learning were also taken into account. The data, consisting of group discussions and the documents produced by the group, were subjected to a qualitative content analysis. The group members employed a variety of resources and tools to exchange their individual perspectives and achieve shared understanding. Summaries of relevant literature laid a foundation for the group’s theoretical discussions. Reflective comparisons between their book knowledge and their personal experiences of online interaction and collaboration were frequent, suggesting that such juxtapositions may have enhanced their learning by intertwining the content to be mastered and the activities entailed by this particular content

Plasmid classification in an era of whole-genome sequencing: application in studies of antibiotic resistance epidemiology

Plasmids are extra-chromosomal genetic elements ubiquitous in bacteria, and commonly transmissible between host cells. Their genomes include variable repertoires of ‘accessory genes,’ such as antibiotic resistance genes, as well as ‘backbone’ loci which are largely conserved within plasmid families, and often involved in key plasmid-specific functions (e.g., replication, stable inheritance, mobility). Classifying plasmids into different types according to their phylogenetic relatedness provides insight into the epidemiology of plasmid-mediated antibiotic resistance. Current typing schemes exploit backbone loci associated with replication (replicon typing), or plasmid mobility (MOB typing). Conventional PCR-based methods for plasmid typing remain widely used. With the emergence of whole-genome sequencing (WGS), large datasets can be analyzed using in silico plasmid typing methods. However, short reads from popular high-throughput sequencers can be challenging to assemble, so complete plasmid sequences may not be accurately reconstructed. Therefore, localizing resistance genes to specific plasmids may be difficult, limiting epidemiological insight. Long-read sequencing will become increasingly popular as costs decline, especially when resolving accurate plasmid structures is the primary goal. This review discusses the application of plasmid classification in WGS-based studies of antibiotic resistance epidemiology; novel in silico plasmid analysis tools are highlighted. Due to the diverse and plastic nature of plasmid genomes, current typing schemes do not classify all plasmids, and identifying conserved, phylogenetically concordant genes for subtyping and phylogenetics is challenging. Analyzing plasmids as nodes in a network that represents gene-sharing relationships between plasmids provides a complementary way to assess plasmid diversity, and allows inferences about horizontal gene transfer to be made

The cyclin-dependent kinase inhibitor p57(Kip2) is epigenetically regulated in carboplatin resistance and results in collateral sensitivity to the CDK inhibitor seliciclib in ovarian cancer

Carboplatin remains a first-line agent in the management of epithelial ovarian cancer (EOC). Unfortunately, platinum-resistant disease ultimately occurs in most patients. Using a novel EOC cell line with acquired resistance to carboplatin: PEO1CarbR, genome-wide micro-array profiling identified the cyclin-dependent kinase inhibitor p57(Kip2) as specifically downregulated in carboplatin resistance. Presently, we describe confirmation of these preliminary data with a variety of approaches

High-resolution characterisation of short-term temporal variability in the taxonomic and resistome composition of wastewater influent

Wastewater-based epidemiology (WBE) for population-level surveillance of antimicrobial resistance (AMR) is gaining significant traction, but the impact of wastewater sampling methods on results is unclear. In this study, we characterized taxonomic and resistome differences between single-timepoint-grab and 24 h composites of wastewater influent from a large UK-based wastewater treatment work [WWTW (population equivalent: 223435)]. We autosampled hourly influent grab samples (n=72) over three consecutive weekdays, and prepared additional 24 h composites (n=3) from respective grabs. For taxonomic profiling, metagenomic DNA was extracted from all samples and 16S rRNA gene sequencing was performed. One composite and six grabs from day 1 underwent metagenomic sequencing for metagenomic dissimilarity estimation and resistome profiling. Taxonomic abundances of phyla varied significantly across hourly grab samples but followed a repeating diurnal pattern for all 3days. Hierarchical clustering grouped grab samples into four time periods dissimilar in both 16S rRNA gene-based profiles and metagenomic distances. 24H-composites resembled mean daily phyla abundances and showed low variability of taxonomic profiles. Of the 122 AMR gene families (AGFs) identified across all day 1 samples, single grab samples identified a median of six (IQR: 5–8) AGFs not seen in the composite. However, 36/36 of these hits were at lateral coverage <0.5 (median: 0.19; interquartile range: 0.16–0.22) and potential false positives. Conversely, the 24H-composite identified three AGFs not seen in any grab with higher lateral coverage (0.82; 0.55–0.84). Additionally, several clinically significant human AGFs (blaVIM, blaIMP, blaKPC) were intermittently or completely missed by grab sampling but captured by the 24 h composite. Wastewater influent undergoes significant taxonomic and resistome changes on short timescales potentially affecting interpretation of results based on sampling strategy. Grab samples are more convenient and potentially capture low-prevalence/transient targets but are less comprehensive and temporally variable. Therefore, we recommend 24H-composite sampling where feasible. Further validation and optimization of WBE methods is vital for its development into a robust AMR surveillance approach

High-resolution characterization of short-term temporal variability in the taxonomic and resistome composition of wastewater influent

Wastewater-based epidemiology (WBE) for population-level surveillance of antimicrobial resistance (AMR) is gaining significant traction, but the impact of wastewater sampling methods on results is unclear. In this study, we characterized taxonomic and resistome differences between single-timepoint-grab and 24 h composites of wastewater influent from a large UK-based wastewater treatment work [WWTW (population equivalent: 223 435)]. We autosampled hourly influent grab samples (n=72) over three consecutive weekdays, and prepared additional 24 h composites (n=3) from respective grabs. For taxonomic profiling, metagenomic DNA was extracted from all samples and 16S rRNA gene sequencing was performed. One composite and six grabs from day 1 underwent metagenomic sequencing for metagenomic dissimilarity estimation and resistome profiling. Taxonomic abundances of phyla varied significantly across hourly grab samples but followed a repeating diurnal pattern for all 3 days. Hierarchical clustering grouped grab samples into four time periods dissimilar in both 16S rRNA gene-based profiles and metagenomic distances. 24H-composites resembled mean daily phyla abundances and showed low variability of taxonomic profiles. Of the 122 AMR gene families (AGFs) identified across all day 1 samples, single grab samples identified a median of six (IQR: 5–8) AGFs not seen in the composite. However, 36/36 of these hits were at lateral coverage <0.5 (median: 0.19; interquartile range: 0.16–0.22) and potential false positives. Conversely, the 24H-composite identified three AGFs not seen in any grab with higher lateral coverage (0.82; 0.55–0.84). Additionally, several clinically significant human AGFs (bla VIM, bla IMP, bla KPC) were intermittently or completely missed by grab sampling but captured by the 24 h composite. Wastewater influent undergoes significant taxonomic and resistome changes on short timescales potentially affecting interpretation of results based on sampling strategy. Grab samples are more convenient and potentially capture low-prevalence/transient targets but are less comprehensive and temporally variable. Therefore, we recommend 24H-composite sampling where feasible. Further validation and optimization of WBE methods is vital for its development into a robust AMR surveillance approach

The impact of sequencing depth on the inferred taxonomic composition and AMR gene content of metagenomic samples

Shotgun metagenomics is increasingly used to characterise microbial communities, particularly for the investigation of antimicrobial resistance (AMR) in different animal and environmental contexts. There are many different approaches for inferring the taxonomic composition and AMR gene content of complex community samples from shotgun metagenomic data, but there has been little work establishing the optimum sequencing depth, data processing and analysis methods for these samples. In this study we used shotgun metagenomics and sequencing of cultured isolates from the same samples to address these issues. We sampled three potential environmental AMR gene reservoirs (pig caeca, river sediment, effluent) and sequenced samples with shotgun metagenomics at high depth (~ 200 million reads per sample). Alongside this, we cultured single-colony isolates of Enterobacteriaceae from the same samples and used hybrid sequencing (short- and long-reads) to create high- quality assemblies for comparison to the metagenomic data. To automate data processing, we developed an open- source software pipeline, ‘ResPipe’

Active flow control systems architectures for civil transport aircraft

Copyright @ 2010 American Institute of Aeronautics and AstronauticsThis paper considers the effect of choice of actuator technology and associated power systems architecture on the mass cost and power consumption of implementing active flow control systems on civil transport aircraft. The research method is based on the use of a mass model that includes a mass due to systems hardware and a mass due to the system energy usage. An Airbus A320 aircraft wing is used as a case-study application. The mass model parameters are based on first-principle physical analysis of electric and pneumatic power systems combined with empirical data on system hardware from existing equipment suppliers. Flow control methods include direct fluidic, electromechanical-fluidic, and electrofluidic actuator technologies. The mass cost of electrical power distribution is shown to be considerably less than that for pneumatic systems; however, this advantage is reduced by the requirement for relatively heavy electrical power management and conversion systems. A tradeoff exists between system power efficiency and the system hardware mass required to achieve this efficiency. For short-duration operation the flow control solution is driven toward lighter but less power-efficient systems, whereas for long-duration operation there is benefit in considering heavier but more efficient systems. It is estimated that a practical electromechanical-fluidic system for flow separation control may have a mass up to 40% of the slat mass for a leading-edge application and 5% of flap mass for a trailing-edge application.This work is funded by the Sixth European Union Framework Programme as part of the AVERT project (Contract No. AST5-CT-2006-030914