Continuous Flow Multi-Step Organic Synthesis

Using continuous flow techniques for multi-step synthesis enables multiple reaction steps to be combined into a single continuous operation. In this mini-review we discuss the current state of the art in this field and highlight recent progress and current challenges facing this emerging area

Divergent drivers of carbon dioxide and methane dynamics in an agricultural coastal floodplain: post-flood hydrological and biological drivers

Many coastal floodplains have been artificially drained for agriculture, altering hydrological connectivity and the delivery of groundwater-derived solutes including carbon dioxide (CO2) and methane (CH4) to surface waters. Here, we investigated the drivers of CO2 and CH4 within the artificial drains.of a coastal floodplain under sugarcane plantation and quantify the contribution of groundwater discharge to CO2 and CH4 dynamics over a flood event (290 mm of rainfall). High temporal resolution, in situ observations of dissolved CO2 and CH4, carbon stable isotopes of CH4 (delta C-13-CH4), and the natural groundwater tracer radon (Rn-222) allowed us to quantify. CO2, CH4 and groundwater dynamics during the rapid recession of a flood over a five day period. Extreme super-saturation of free CO2 ([CO2*]) up to 2,951 mu M (25,480% of atmospheric equilibrium) was driven by large groundwater input into the drains (maximum 87 cm day-(1)), caused by a steep hydraulic head in the adjacent water table. Groundwater input sustained between 95 and 124% of the surface [CO2*] flux during the flood recession by delivering high carbonate alkalinity groundwater (DIC = 10,533 mu M, similar to pH = 7.05) to acidic surface water (pH <4), consequently transforming all groundwater-derived DIC to [CO2*]. In contrast, groundwater was not a major direct driver of CH4 contributing only 14% of total CH4 fluxes. A progressive increase in CH4 concentrations of up to similar to 2400 nM day-(1) occurred as a combination of increased substrate availability delivered by post-flood drainage water and longer residence times, which allowed for a biogenic CH4 signal to develop. The progressive enrichment in delta C-13-CH4 values (- 70%. to-48%.) and increase in CH4 concentrations (46-2460 nM) support coupled production-oxidation, with concentrations and delta C-13 values remaining higher (2,798 nM and-47%.) than pre-flood conditions (534 nM and-55 parts per thousand) three weeks after the flood. Our findings demonstrate how separate processes can drive the aquatic CO2 and CH4 response to a flood event in a drained coastal floodplain, and the key role groundwater had in post-flood [CO2*] evasion to the atmosphere, but not CH4. (C) 2016 Elsevier B.V. All rights reserved

Forecasting solar photosynthetic photon flux density under cloud cover effects: novel predictive model using convolutional neural network integrated with long short-term memory network

Forecast models of solar radiation incorporating cloud effects are useful tools to evaluate the impact of stochastic behaviour of cloud movement, real-time integration of photovoltaic energy in power grids, skin cancer and eye disease risk minimisation through solar ultraviolet (UV) index prediction and bio-photosynthetic processes through the modelling of solar photosynthetic photon flux density (PPFD). This research has developed deep learning hybrid model (i.e., CNN-LSTM) to factor in role of cloud effects integrating the merits of convolutional neural networks with long short-term memory networks to forecast near real-time (i.e., 5-min) PPFD in a sub-tropical region Queensland, Australia. The prescribed CLSTM model is trained with real-time sky images that depict stochastic cloud movements captured through a total sky imager (TSI-440) utilising advanced sky image segmentation to reveal cloud chromatic features into their statistical values, and to purposely factor in the cloud variation to optimise the CLSTM model. The model, with its competing algorithms (i.e., CNN, LSTM, deep neural network, extreme learning machine and multivariate adaptive regression spline), are trained with 17 distinct cloud cover inputs considering the chromaticity of red, blue, thin, and opaque cloud statistics, supplemented by solar zenith angle (SZA) to predict short-term PPFD. The models developed with cloud inputs yield accurate results, outperforming the SZA-based models while the best testing performance is recorded by the objective method (i.e., CLSTM) tested over a 7-day measurement period. Specifically, CLSTM yields a testing performance with correlation coefficient r = 0.92, root mean square error RMSE = 210.31 μ mol of photons m−2 s−1, mean absolute error MAE = 150.24 μ mol of photons m−2 s−1, including a relative error of RRMSE = 24.92% MAPE = 38.01%, and Nash Sutcliffe’s coefficient ENS = 0.85, and Legate and McCabe’s Index LM = 0.68 using cloud cover in addition to the SZA as an input. The study shows the importance of cloud inclusion in forecasting solar radiation and evaluating the risk with practical implications in monitoring solar energy, greenhouses and high-value agricultural operations affected by stochastic behaviour of clouds. Additional methodological refinements such as retraining the CLSTM model for hourly and seasonal time scales may aid in the promotion of agricultural crop farming and environmental risk evaluation applications such as predicting the solar UV index and direct normal solar irradiance for renewable energy monitoring systems

Warming of Central European lakes and their response to the 1980s climate regime shift

Lake surface water temperatures (LSWTs) are sensitive to atmospheric warming and have previously been shown to respond to regional changes in the climate. Using a combination of in situ and simulated surface temperatures from 20 Central European lakes, with data spanning between 50 and ∼100 years, we investigate the long-term increase in annually averaged LSWT. We demonstrate that Central European lakes are warming most in spring and experience a seasonal variation in LSWT trends. We calculate significant LSWT warming during the past few decades and illustrate, using a sequential t test analysis of regime shifts, a substantial increase in annually averaged LSWT during the late 1980s, in response to an abrupt shift in the climate. Surface air temperature measurements from 122 meteorological stations situated throughout Central Europe demonstrate similar increases at this time. Climatic modification of LSWT has numerous consequences for water quality and lake ecosystems. Quantifying the response of LSWT increase to large-scale and abrupt climatic shifts is essential to understand how lakes will respond in the future

Fair Play For Girls

This report highlights the urgent need for equitable opportunities for girls in football. The report endorsed by leading figures in the football community and backed by the UK Government, underscores the importance of addressing gender disparities in sports provision and support

The Impact of Different Antibiotic Regimens on the Emergence of Antimicrobial-Resistant Bacteria

Backgroud: The emergence and ongoing spread of antimicrobial-resistant bacteria is a major public health threat. Infections caused by antimicrobial-resistant bacteria are associated with substantially higher rates of morbidity and mortality compared to infections caused by antimicrobial-susceptible bacteria. The emergence and spread of these bacteria is complex and requires incorporating numerous interrelated factors which clinical studies cannot adequately address. Methods/Principal Findings: A model is created which incorporates several key factors contributing to the emergence and spread of resistant bacteria including the effects of the immune system, acquisition of resistance genes and antimicrobial exposure. The model identifies key strategies which would limit the emergence of antimicrobial-resistant bacterial strains. Specifically, the simulations show that early initiation of antimicrobial therapy and combination therapy with two antibiotics prevents the emergence of resistant bacteria, whereas shorter courses of therapy and sequential administration of antibiotics promote the emergence of resistant strains. Conclusions/Significance: The principal findings suggest that (i) shorter lengths of antibiotic therapy and early interruption of antibiotic therapy provide an advantage for the resistant strains, (ii) combination therapy with two antibiotics prevents the emergence of resistance strains in contrast to sequential antibiotic therapy, and (iii) early initiation of antibiotics is among the most important factors preventing the emergence of resistant strains. These findings provide new insights into strategies aimed at optimizing the administration of antimicrobials for the treatment of infections and the prevention of the emergence of antimicrobial resistance

The surveillance of teachers and the simulation of teaching

Just as surveillance in general has become more sophisticated, penetrative and ubiquitous, so has the surveillance of teachers. Enacted through an assemblage of strategies such as learning walks, parental networks, student voice and management information systems, the surveillance of teachers has proliferated as a means of managing the risks of school life, driven forward by neoliberal notions of quality and competition. However, where once the surveillance of teachers was panoptic, a means of detecting the truth of teaching behind fabrications, this article argues that surveillance within schools has become a simulation in Baudrillard’s terms, using models and codes such as the Teachers’ Standards and the Schools Inspection Handbook as predictors of future outcomes, simulating practice as a means of managing risk. And if surveillance in schools has become a simulation then so perhaps has teaching itself, moving beyond a preoccupation with an essentialist truth of teaching to the hyperreality of normalised visibility and the simulation of teaching. This article argues that surveillance – including external agencies such as Ofsted – no longer exists to find the truth of teaching, the surveillance of teachers exists only to test the accuracy of the models and codes upon which the simulation is based

Regional variability in peatland burning at mid- to high-latitudes during the Holocene

Acknowledgements This work developed from the PAGES (Past Global Changes) C-PEAT (Carbon in Peat on EArth through Time) working group. PAGES has been supported by the US National Science Foundation, Swiss National Science Foundation, Swiss Academy of Sciences and Chinese Academy of Sciences. We acknowledge the following financial support: UK Natural Environment Research Council Training Grants NE/L002574/1 (T.G.S.) and NE/S007458/1 (R.E.F.); Dutch Foundation for the Conservation of Irish Bogs, Quaternary Research Association and Leverhulme Trust RPG-2021-354 (G.T.S); the Academy of Finland (M.V); PAI/SIA 80002 and FONDECYT Iniciación 11220705 - ANID, Chile (C.A.M.); R20F0002 (PATSER) ANID Chile (R.D.M.); Swedish Strategic Research Area (SRA) MERGE (ModElling the Regional and Global Earth system) (M.J.G.); Polish National Science Centre Grant number NCN 2018/29/B/ST10/00120 (K.A.); Russian Science Foundation Grant No. 19-14-00102 (Y.A.M.); University of Latvia Grant No. AAp2016/B041/Zd2016/AZ03 and the Estonian Science Council grant PRG323 (TrackLag) (N.S. and A.M.); U.S. Geological Survey Land Change Science/Climate Research & Development Program (M.J., L.A., and D.W.); German Research Foundation (DFG), grant MA 8083/2-1 (P.M.) and grant BL 563/19-1 (K.H.K.); German Academic Exchange Service (DAAD), grant no. 57044554, Faculty of Geosciences, University of Münster, and Bavarian University Centre for Latin America (BAYLAT) (K.H.K). Records from the Global Charcoal Database supplemented this work and therefore we would like to thank the contributors and managers of this open-source resource. We also thank Annica Greisman, Jennifer Shiller, Fredrik Olsson and Simon van Bellen for contributing charcoal data to our analyses. Any use of trade, firm, or product name is for descriptive purposes only and does not imply endorsement by the U.S. Government.Peer reviewedPostprin

The Athena X-ray Integral Field Unit (X-IFU)

The X-ray Integral Field Unit (X-IFU) is the high resolution X-ray spectrometer of the ESA Athena X-ray observatory. Over a field of view of 5' equivalent diameter, it will deliver X-ray spectra from 0.2 to 12 keV with a spectral resolution of 2.5 eV up to 7 keV on similar to 5 '' pixels. The X-IFU is based on a large format array of super-conducting molybdenum-gold Transition Edge Sensors cooled at similar to 90 mK, each coupled with an absorber made of gold and bismuth with a pitch of 249 mu m. A cryogenic anti-coincidence detector located underneath the prime TES array enables the non X-ray background to be reduced. A bath temperature of similar to 50 mK is obtained by a series of mechanical coolers combining 15K Pulse Tubes, 4K and 2K Joule-Thomson coolers which pre-cool a sub Kelvin cooler made of a He-3 sorption cooler coupled with an Adiabatic Demagnetization Refrigerator. Frequency domain multiplexing enables to read out 40 pixels in one single channel. A photon interacting with an absorber leads to a current pulse, amplified by the readout electronics and whose shape is reconstructed on board to recover its energy with high accuracy. The defocusing capability offered by the Athena movable mirror assembly enables the X-IFU to observe the brightest X-ray sources of the sky (up to Crab-like intensities) by spreading the telescope point spread function over hundreds of pixels. Thus the X-IFU delivers low pile-up, high throughput (> 50%), and typically 10 eV spectral resolution at 1 Crab intensities, i.e. a factor of 10 or more better than Silicon based X-ray detectors. In this paper, the current X-IFU baseline is presented, together with an assessment of its anticipated performance in terms of spectral resolution, background, and count rate capability. The X-IFU baseline configuration will be subject to a preliminary requirement review that is scheduled at the end of 2018. The X-IFU will be provided by an international consortium led by France, the Netherlands and Italy, with further ESA member state contributions from Belgium, Czech Republic, Finland, Germany, Ireland, Poland, Spain, Switzerland and contributions from Japan and the United States.Peer reviewe