High throughput synthesis of 2,5-substituted indoles using a titanium carbenoid bearing boronate functionality

A titanium benzylidene complex bearing a boronate group converted resin-bound esters into enol ethers. Suzuki cross-coupling with aryl iodides followed by cleavage with acid completed the solid-phase synthesis of 2,5-disubstituted N-Boc-indoles. Also reported is the use of tert-butyllithium and 2-isopropoxy-4,4,5,5-tetramethyl-1,3,2-dioxaborolane to convert an aryl bromide into an arylboronate in the presence of a dithiane, with simultaneous reduction of an aryl azide to an amine

Synchronization of fractional order chaotic systems

The chaotic dynamics of fractional order systems begin to attract much attentions in recent years. In this brief report, we study the master-slave synchronization of fractional order chaotic systems. It is shown that fractional order chaotic systems can also be synchronized.Comment: 3 pages, 5 figure

Ratio Estimation in SIMS Analysis

The determination of an isotope ratio by secondary ion mass spectrometry (SIMS) traditionally involves averaging a number of ratios collected over the course of a measurement. We show that this method leads to an additive positive bias in the expectation value of the estimated ratio that is approximately equal to the true ratio divided by the counts of the denominator isotope of an individual ratio. This bias does not decrease as the number of ratios used in the average increases. By summing all counts in the numerator isotope, then dividing by the sum of counts in the denominator isotope, the estimated ratio is less biased: the bias is approximately equal to the ratio divided by the summed counts of the denominator isotope over the entire measurement. We propose a third ratio estimator (Beale's estimator) that can be used when the bias from the summed counts is unacceptably large for the hypothesis being tested. We derive expressions for the variance of these ratio estimators as well as the conditions under which they are normally distributed. Finally, we investigate a SIMS dataset showing the effects of ratio bias, and discuss proper ratio estimation for SIMS analysis

The impacts of climate change on sea temperature around the UK and Ireland

What is already happening? • Sea surface temperature (SST) around the UK generally shows a significant warming trend of around 0.3C per decade over the last 40 years. • Regional variations exist in this trend with surface warming being greatest across the southern North Sea and least across the north-west of the domain. • Warm-season (Autumn) near-bottom temperatures have increased significantly across the southern North Sea over the last 30 years, but not across other regions of the domain. • Compared to 1982–1998, the annual number of marine heatwaves increased around the British Isles by an average of four events per year in the period 2000–2016. Larger increases of up to six additional events per year occurred to the north of the British Isles. Smaller changes occurred to the south of the region

Rapid inference of object rigidity and reflectance using optic flow

Rigidity and reflectance are key object properties, important in their own rights, and they are key properties that stratify motion reconstruction algorithms. However, the inference of rigidity and reflectance are both difficult without additional information about the object's shape, the environment, or lighting. For humans, relative motions of object and observer provides rich information about object shape, rigidity, and reflectivity. We show that it is possible to detect rigid object motion for both specular and diffuse reflective surfaces using only optic flow, and that flow can distinguish specular and diffuse motion for rigid objects. Unlike nonrigid objects, optic flow fields for rigid moving surfaces are constrained by a global transformation, which can be detected using an optic flow matching procedure across time. In addition, using a Procrustes analysis of structure from motion reconstructed 3D points, we show how to classify specular from diffuse surfaces. © 2009 Springer Berlin Heidelberg

Transfer learning for galaxy morphology from one survey to another

© 2018 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society.Deep Learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications. However, these algorithms rely on large training samples of labelled galaxies (typically thousands of them). A key question for using DL classifications in future Big Data surveys is how much of the knowledge acquired from an existing survey can be exported to a new dataset, i.e. if the features learned by the machines are meaningful for different data. We test the performance of DL models, trained with Sloan Digital Sky Survey (SDSS) data, on Dark Energy survey (DES) using images for a sample of $\sim$5000 galaxies with a similar redshift distribution to SDSS. Applying the models directly to DES data provides a reasonable global accuracy ($\sim$ 90%), but small completeness and purity values. A fast domain adaptation step, consisting in a further training with a small DES sample of galaxies ($\sim$500-300), is enough for obtaining an accuracy > 95% and a significant improvement in the completeness and purity values. This demonstrates that, once trained with a particular dataset, machines can quickly adapt to new instrument characteristics (e.g., PSF, seeing, depth), reducing by almost one order of magnitude the necessary training sample for morphological classification. Redshift evolution effects or significant depth differences are not taken into account in this study.Peer reviewedFinal Accepted Versio

Stuart Warren (24 Dec 1938–22 Mar 2020)

Celebrating the life of Stuart Warren

Microplastics in personal care products: Exploring perceptions of environmentalists, beauticians and students

Microplastics enter the environment as a result of larger plastic items breaking down (‘secondary’) and from particles originally manufactured at that size (‘primary’). Personal care productsare an important contributor of secondary microplastics (typically referred to as ‘microbeads’), for example in toothpaste, facial scrubs and soaps. Consumers play an important role in influencing the demand for these products and therefore any associated environmental consequences. Hence we need to understand public perceptions in order to help reduce emissions of microplastics. This study explored awareness of plastic microbeads in personal care products in three groups: environmental activists, trainee beauticians and university students in South West England. Focus groups were run, where participants were shown the quantity of microbeads found in individual high-street personal care products. Qualitative analysis showed that while the environmentalists were originally aware of the issue, it lacked visibility and immediacy for the beauticians and students. Yet when shown the amount of plastic in a range of familiar everyday personal care products, all participants expressed considerable surprise and concern at the quantities and potential impact. Regardless of any perceived level of harm in the environment, the consensus was that their use was unnatural and unnecessary. This research could inform future communications with the public and industry as well as policy initiatives to phase out the use of microbeads

Superluminous supernovae from the Dark Energy Survey

We present a sample of 21 hydrogen-free superluminous supernovae (SLSNe-I) and one hydrogen-rich SLSN (SLSN-II) detected during the five-year Dark Energy Survey (DES). These SNe, located in the redshift range 0.220 < z < 1.998, represent the largest homogeneously selected sample of SLSN events at high redshift. We present the observed g, r, i, z light curves for these SNe, which we interpolate using Gaussian processes. The resulting light curves are analysed to determine the luminosity function of SLSNe-I, and their evolutionary timescales. The DES SLSN-I sample significantly broadens the distribution of SLSN-I light-curve properties when combined with existing samples from the literature. We fit a magnetar model to our SLSNe, and find that this model alone is unable to replicate the behaviour of many of the bolometric light curves. We search the DES SLSN-I light curves for the presence of initial peaks prior to the main light-curve peak. Using a shock breakout model, our Monte Carlo search finds that 3 of our 14 events with pre-max data display such initial peaks. However, 10 events show no evidence for such peaks, in some cases down to an absolute magnitude of<−16, suggesting that such features are not ubiquitous to all SLSN-I events. We also identify a red pre-peak feature within the light curve of one SLSN, which is comparable to that observed within SN2018bsz

First cosmology results using SNe Ia from the dark energy survey: analysis, systematic uncertainties, and validation

International audienceWe present the analysis underpinning the measurement of cosmological parameters from 207 spectroscopically classified type Ia supernovae (SNe Ia) from the first three years of the Dark Energy Survey Supernova Program (DES-SN), spanning a redshift range of 0.01