A hybrid MBE-based growth method for large-area synthesis of stacked hexagonal boron nitride/graphene heterostructures

Van der Waals heterostructures combining hexagonal boron nitride (h-BN) and graphene offer many potential advantages, but remain difficult to produce as continuous films over large areas. In particular, the growth of h-BN on graphene has proven to be challenging due to the inertness of the graphene surface. Here we exploit a scalable molecular beam epitaxy based method to allow both the h-BN and graphene to form in a stacked heterostructure in the favorable growth environment provided by a Ni(111) substrate. This involves first saturating a Ni film on MgO(111) with C, growing h-BN on the exposed metal surface, and precipitating the C back to the h-BN/Ni interface to form graphene. The resulting laterally continuous heterostructure is composed of a top layer of few-layer thick h-BN on an intermediate few-layer thick graphene, lying on top of Ni/MgO(111). Examinations by synchrotron-based grazing incidence diffraction, X-ray photoemission spectroscopy, and UV-Raman spectroscopy reveal that while the h-BN is relaxed, the lattice constant of graphene is significantly reduced, likely due to nitrogen doping. These results illustrate a different pathway for the production of h-BN/graphene heterostructures, and open a new perspective for the large-area preparation of heterosystems combining graphene and other 2D or 3D materials

Testing a global standard for quantifying species recovery and assessing conservation impact

Recognizing the imperative to evaluate species recovery and conservation impact, in 2012 the International Union for Conservation of Nature (IUCN) called for development of a “Green List of Species” (now the IUCN Green Status of Species). A draft Green Status framework for assessing species’ progress toward recovery, published in 2018, proposed 2 separate but interlinked components: a standardized method (i.e., measurement against benchmarks of species’ viability, functionality, and preimpact distribution) to determine current species recovery status (herein species recovery score) and application of that method to estimate past and potential future impacts of conservation based on 4 metrics (conservation legacy, conservation dependence, conservation gain, and recovery potential). We tested the framework with 181 species representing diverse taxa, life histories, biomes, and IUCN Red List categories (extinction risk). Based on the observed distribution of species’ recovery scores, we propose the following species recovery categories: fully recovered, slightly depleted, moderately depleted, largely depleted, critically depleted, extinct in the wild, and indeterminate. Fifty-nine percent of tested species were considered largely or critically depleted. Although there was a negative relationship between extinction risk and species recovery score, variation was considerable. Some species in lower risk categories were assessed as farther from recovery than those at higher risk. This emphasizes that species recovery is conceptually different from extinction risk and reinforces the utility of the IUCN Green Status of Species to more fully understand species conservation status. Although extinction risk did not predict conservation legacy, conservation dependence, or conservation gain, it was positively correlated with recovery potential. Only 1.7% of tested species were categorized as zero across all 4 of these conservation impact metrics, indicating that conservation has, or will, play a role in improving or maintaining species status for the vast majority of these species. Based on our results, we devised an updated assessment framework that introduces the option of using a dynamic baseline to assess future impacts of conservation over the short term to avoid misleading results which were generated in a small number of cases, and redefines short term as 10 years to better align with conservation planning. These changes are reflected in the IUCN Green Status of Species Standard

Journal Co-Citation Analysis for Identifying Trends of Inter-Disciplinary Research: An Exploratory Case Study in a University

© 2018 World Scientific Publishing Co. A journal stands as a marker of the intellectual space which holds vast areas of literature. Exploring and analysing the underlined knowledge sources and themes of the journal literature will significantly benefit any institution to identify the key intellectual domain strength and improve in research collaboration. The main objective of this paper is to identify inter-disciplinary trends of research for one university as a case study, using journal co-citation analysis. With the help of correlation metric and cluster analysis, the published literature between 2004 and 2013 from seven subject domains (i.e. including medicine, pharmacy and pharmacology, biological sciences, linguistics, modern languages, chemistry, and computer science and information systems) are analysed and interpreted. The results can demonstrate that there are the strong research dominance in the medical field and the prospective collaboration in social science and chemistry. In addition, the interpretation of the findings could be served as a foundation for future research in the direction of strong bonding between inter-disciplinary fields

The prognostic utility of soluble fms-like tyrosine kinase-1 (sFlt-1) and placental growth factor (PIGF) biomarkers for predicting preeclampsia: a secondary analysis of data from the INSPIRE trial

Objective To compare the prognostic performance of biomarkers soluble fms-like tyrosine kinase-1 (sFlt-1), Placental Growth Factor (PIGF), and sFlt-1/PIGF ratio as continuous values or as a binary cut-off of 38 for predicting preeclampsia (PE) within 7 days. Design Secondary analysis of a randomised clinical trial. Setting Oxford University Hospitals, Oxford, United Kingdom (UK). Population Pregnant women between 24+0 to 37+0 weeks of gestation with a clinical suspicion of preeclampsia. Main outcome Onset of preeclampsia within 7 days of the initial biomarker test. Methods Logistic regression model for onset of preeclampsia using: (i) sFlt-1 (ii) PIGF, (iii) sFlt-1/PIGF ratio (continuous), and (iv) sFlt-1/PIGF ratio as a cut-off above or below 38. Results Of the total 370 women, 42 (11.3%) developed PE within 7 days of screening. Models with sFlt-1 and sFlt-1/PIGF ratio (continuous) had greater overall performance than models with PIGF or with sFlt-1/PIGF ratio as a cut-off at 38 (R2: sFlt-1 = 55%, PIGF = 38%, sFlt-1/PIGF ratio = 57%, sFlt-1/PIGF ratio as cut-off at 38 model = 46%). The discrimination performance was the highest in sFlt-1 and sFlt-1/PIGF ratio (continuous) (c-statistic, sFlt-1 = 0.94, sFlt-1/PIGF ratio (continuous) = 0.94) models compared to PIGF or sFlt-1/PIGF cut-off models (c-statistic, PIGF = 0.87, sFlt-1/PIGF cut-off = 0.89). Conclusion Models using continuous values of sFlt-1 only or sFlt-1/PIGF ratio had better predictive performance compared to a PIGF only or the model with sFlt-1/PIGF ratio as a cut-off at 38. Further studies based on a larger sample size are warranted to substantiate this finding