Manipulating infrared photons using plasmons in transparent graphene superlattices

Superlattices are artificial periodic nanostructures which can control the flow of electrons. Their operation typically relies on the periodic modulation of the electric potential in the direction of electron wave propagation. Here we demonstrate transparent graphene superlattices which can manipulate infrared photons utilizing the collective oscillations of carriers, i.e., plasmons of the ensemble of multiple graphene layers. The superlattice is formed by depositing alternating wafer-scale graphene sheets and thin insulating layers, followed by patterning them all together into 3-dimensional photonic-crystal-like structures. We demonstrate experimentally that the collective oscillation of Dirac fermions in such graphene superlattices is unambiguously nonclassical: compared to doping single layer graphene, distributing carriers into multiple graphene layers strongly enhances the plasmonic resonance frequency and magnitude, which is fundamentally different from that in a conventional semiconductor superlattice. This property allows us to construct widely tunable far-infrared notch filters with 8.2 dB rejection ratio and terahertz linear polarizers with 9.5 dB extinction ratio, using a superlattice with merely five graphene atomic layers. Moreover, an unpatterned superlattice shields up to 97.5% of the electromagnetic radiations below 1.2 terahertz. This demonstration also opens an avenue for the realization of other transparent mid- and far-infrared photonic devices such as detectors, modulators, and 3-dimensional meta-material systems.Comment: under revie

Directed self-organization of graphene nanoribbons on SiC

Realization of post-CMOS graphene electronics requires production of semiconducting graphene, which has been a labor-intensive process. We present tailoring of silicon carbide crystals via conventional photolithography and microelectronics processing to enable templated graphene growth on 4H-SiC{1-10n} (n = 8) crystal facets rather than the customary {0001} planes. This allows self-organized growth of graphene nanoribbons with dimensions defined by those of the facet. Preferential growth is confirmed by Raman spectroscopy and high-resolution transmission electron microscopy (HRTEM) measurements, and electrical characterization of prototypic graphene devices is presented. Fabrication of > 10,000 top-gated graphene transistors on a 0.24 cm2 SiC chip demonstrates scalability of this process and represents the highest density of graphene devices reported to date.Comment: 13 pages, 5 figure

Omega-3 polyunsaturated fatty acids favourably modulate cardiometabolic biomarkers in type 2 diabetes: a meta-analysis and meta-regression of randomized controlled trials

BACKGROUND: Randomized controlled trials (RCTs) suggest that supplementation with omega-3 polyunsaturated fatty acids (n-3PUFAs) may favourably modify cardiometabolic biomarkers in type 2 diabetes (T2DM). Previous meta-analyses are limited by insufficient sample sizes and omission of meta-regression techniques, and a large number of RCTs have subsequently been published since the last comprehensive meta-analysis. Updated information regarding the impact of dosage, duration or an interaction between these two factors is therefore warranted. The objective was to comprehensively assess the effect of n-3PUFAs supplementation on cardiometabolic biomarkers including lipid profiles, inflammatory parameters, blood pressure, and indices of glycaemic control, in people with T2DM, and identify whether treatment dosage, duration or an interaction thereof modify these effects. METHODS: Databases including PubMed and MEDLINE were searched until 13th July 2017 for RCTs investigating the effect of n-3PUFAs supplementation on lipid profiles, inflammatory parameters, blood pressure, and indices of glycaemic control. Data were pooled using random-effects meta-analysis and presented as standardised mean difference (Hedges g) with 95% confidence intervals (95% CI). Meta-regression analysis was performed to investigate the effects of duration of supplementation and total dosage of n-3PUFAs as moderator variables where appropriate. RESULTS: A total of 45 RCTs were identified, involving 2674 people with T2DM. n-3PUFAs supplementation was associated with significant reductions in LDL [ES: - 0.10, (95% CI - 0.17, - 0.03); p = 0.007], VLDL (ES: - 0.26 (- 0.51, - 0.01); p = 0.044], triglycerides (ES: - 0.39 (- 0.55, - 0.24; p ≤ 0.001] and HbA1c (ES: - 0.27 (- 0.48, - 0.06); p = 0.010]. Moreover, n-3PUFAs supplementation was associated with reduction in plasma levels of TNF-α [ES: - 0.59 (- 1.17, - 0.01); p = 0.045] and IL-6 (ES: - 1.67 (- 3.14, - 0.20); p = 0.026]. All other lipid markers, indices of glycaemic control, inflammatory parameters, and blood pressure remained unchanged (p > 0.05). CONCLUSIONS: n-3PUFAs supplementation produces favourable hypolipidemic effects, a reduction in pro-inflammatory cytokine levels and improvement in glycaemia. Neither duration nor dosage appear to explain the observed heterogeneity in response to n-3PUFAs. Trial registration This trial was registered at http://www.crd.york.ac.uk as CRD42016050802

Osteological and Soft-Tissue Evidence for Pneumatization in the Cervical Column of the Ostrich (Struthio camelus) and Observations on the Vertebral Columns of Non-Volant, Semi-Volant and Semi-Aquatic Birds

© 2015 Apostolaki et al. This is an open access article distributed under the terms of the Creative Commons Attribution License [4.0], which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The attached file is the published version of the article

Spatiotemporal scaling of North American continental interior wetlands: implications for shorebird conservation

Within interior North America, erratic weather patterns and heterogeneous wetland complexes cause wide spatio-temporal variation in the resources available to migrating shorebirds. Identifying the pattern-generating components of landscape-level resources and the scales at which shorebirds respond to these patterns will better facilitate conservation efforts for these species. We constructed descriptive models that identified weather variables associated with creating the spatio-temporal patterns of shorebird habitat in ten landscapes in north-central Oklahoma. We developed a metric capable of measuring the dynamic composition and configuration of shorebird habitat in the region and used field data to empirically estimate the spatial scale at which shorebirds respond to the amount and configuration of habitat. Precipitation, temperature, solar radiation and wind speed best explained the incidence of wetland habitat, but relationships varied among wetland types. Shorebird occurrence patterns were best explained by habitat density estimates at a 1.5 km scale. This model correctly classified 86 % of shorebird observations. At this scale, when habitat density was low, shorebirds occurred in 5 % of surveyed habitat patches but occurrence reached 60 % when habitat density was high. Our results suggest scale dependence in the habitat-use patterns of migratory shorebirds. We discuss potential implications of our results and how integrating this information into conservation efforts may improve conservation strategies and management practices

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Using quantile regression to investigate racial disparities in medication non-adherence

<p>Abstract</p> <p>Background</p> <p>Many studies have investigated racial/ethnic disparities in medication non-adherence in patients with type 2 diabetes using common measures such as medication possession ratio (MPR) or gaps between refills. All these measures including MPR are quasi-continuous and bounded and their distribution is usually skewed. Analysis of such measures using traditional regression methods that model mean changes in the dependent variable may fail to provide a full picture about differential patterns in non-adherence between groups.</p> <p>Methods</p> <p>A retrospective cohort of 11,272 veterans with type 2 diabetes was assembled from Veterans Administration datasets from April 1996 to May 2006. The main outcome measure was MPR with quantile cutoffs Q1-Q4 taking values of 0.4, 0.6, 0.8 and 0.9. Quantile-regression (QReg) was used to model the association between MPR and race/ethnicity after adjusting for covariates. Comparison was made with commonly used ordinary-least-squares (OLS) and generalized linear mixed models (GLMM).</p> <p>Results</p> <p>Quantile-regression showed that Non-Hispanic-Black (NHB) had statistically significantly lower MPR compared to Non-Hispanic-White (NHW) holding all other variables constant across all quantiles with estimates and p-values given as -3.4% (p = 0.11), -5.4% (p = 0.01), -3.1% (p = 0.001), and -2.00% (p = 0.001) for Q1 to Q4, respectively. Other racial/ethnic groups had lower adherence than NHW only in the lowest quantile (Q1) of about -6.3% (p = 0.003). In contrast, OLS and GLMM only showed differences in mean MPR between NHB and NHW while the mean MPR difference between other racial groups and NHW was not significant.</p> <p>Conclusion</p> <p>Quantile regression is recommended for analysis of data that are heterogeneous such that the tails and the central location of the conditional distributions vary differently with the covariates. QReg provides a comprehensive view of the relationships between independent and dependent variables (i.e. not just centrally but also in the tails of the conditional distribution of the dependent variable). Indeed, without performing QReg at different quantiles, an investigator would have no way of assessing whether a difference in these relationships might exist.</p

Factors associated with disease evolution in Greek patients with inflammatory bowel disease

BACKGROUND: The majority of Crohn's disease patients with B1 phenotype at diagnosis (i.e. non-stricturing non-penetrating disease) will develop over time a stricturing or a penetrating pattern. Conflicting data exist on the rate of proximal disease extension in ulcerative colitis patients with proctitis or left-sided colitis at diagnosis. We aimed to study disease evolution in Crohn's disease B1 patients and ulcerative colitis patients with proctitis and left-sided colitis at diagnosis. METHODS: 116 Crohn's disease and 256 ulcerative colitis patients were followed-up for at least 5 years after diagnosis. Crohn's disease patients were classified according to the Vienna criteria. Data were analysed actuarially. RESULTS: B1 phenotype accounted for 68.9% of Crohn's disease patients at diagnosis. The cumulative probability of change in disease behaviour in B1 patients was 43.6% at 10 years after diagnosis. Active smoking (Hazard Ratio: 3.01) and non-colonic disease (non-L2) (Hazard Ratio: 3.01) were associated with behavioural change in B1 patients. Proctitis and left-sided colitis accounted for 24.2%, and 48.4% of ulcerative colitis patients at diagnosis. The 10 year cumulative probability of proximal disease extension in patients with proctitis and left-sided colitis was 36.8%, and 17.1%, respectively (p: 0.003). Among proctitis patients, proximal extension was more common in non-smokers (Hazard Ratio: 4.39). CONCLUSION: Classification of Crohn's disease patients in B1 phenotype should be considered as temporary. Smoking and non-colonic disease are risk factors for behavioural change in B1 Crohn's disease patients. Proximal extension is more common in ulcerative colitis patients with proctitis than in those with left-sided colitis. Among proctitis patients, proximal extension is more common in non-smokers

Ensemble Modeling for Aromatic Production in Escherichia coli

Ensemble Modeling (EM) is a recently developed method for metabolic modeling, particularly for utilizing the effect of enzyme tuning data on the production of a specific compound to refine the model. This approach is used here to investigate the production of aromatic products in Escherichia coli. Instead of using dynamic metabolite data to fit a model, the EM approach uses phenotypic data (effects of enzyme overexpression or knockouts on the steady state production rate) to screen possible models. These data are routinely generated during strain design. An ensemble of models is constructed that all reach the same steady state and are based on the same mechanistic framework at the elementary reaction level. The behavior of the models spans the kinetics allowable by thermodynamics. Then by using existing data from the literature for the overexpression of genes coding for transketolase (Tkt), transaldolase (Tal), and phosphoenolpyruvate synthase (Pps) to screen the ensemble, we arrive at a set of models that properly describes the known enzyme overexpression phenotypes. This subset of models becomes more predictive as additional data are used to refine the models. The final ensemble of models demonstrates the characteristic of the cell that Tkt is the first rate controlling step, and correctly predicts that only after Tkt is overexpressed does an increase in Pps increase the production rate of aromatics. This work demonstrates that EM is able to capture the result of enzyme overexpression on aromatic producing bacteria by successfully utilizing routinely generated enzyme tuning data to guide model learning