3,362 research outputs found

    Long term time-lapse microgravity and geotechnical monitoring of relict salt-mines, Marston, Cheshire, UK.

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    The area around the town of Northwich in Cheshire, U. K., has a long history of catastrophic ground subsidence caused by a combination of natural dissolution and collapsing abandoned mine workings within the underlying Triassic halite bedrock geology. In the village of Marston, the Trent and Mersey Canal crosses several abandoned salt mine workings and previously subsiding areas, the canal being breached by a catastrophic subsidence event in 1953. This canal section is the focus of a long-term monitoring study by conventional geotechnical topographic and microgravity surveys. Results of 20 years of topographic time-lapse surveys indicate specific areas of local subsidence that could not be predicted by available site and mine abandonment plan and shaft data. Subsidence has subsequently necessitated four phases of temporary canal bank remediation. Ten years of microgravity time-lapse data have recorded major deepening negative anomalies in specific sections that correlate with topographic data. Gravity 2D modeling using available site data found upwardly propagating voids, and associated collapse material produced a good match with observed microgravity data. Intrusive investigations have confirmed a void at the major anomaly. The advantages of undertaking such long-term studies for near-surface geophysicists, geotechnical engineers, and researchers working in other application areas are discussed

    A Review of Using Mathematical Modeling to Improve Our Understanding of Bacteriophage, Bacteria, and Eukaryotic Interactions

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    Phage therapy, the therapeutic usage of viruses to treat bacterial infections, has many theoretical benefits in the ‘post antibiotic era’. Nevertheless, there are currently no approved mainstream phage therapies. One reason for this is a lack of understanding of the complex interactions between bacteriophage, bacteria and eukaryotic hosts. These three-component interactions are complex, with non-linear or synergistic relationships, anatomical barriers and genetic or phenotypic heterogeneity all leading to disparity between performance and efficacy in in vivo versus in vitro environments. Realistic computer or mathematical models of these complex environments are a potential route to improve the predictive power of in vitro studies and to streamline lab work. Here, we review the current status of mathematical modelling and highlight that data on mutational stochasticity, time delays and population densities could be critical in the development of realistic phage therapy models. With this in mind, we aim to inform and encourage the collaboration and sharing of knowledge and expertise between microbiologists and theoretical modellers, smoothing the road to regulatory approval and widespread use of phage therapy

    Evaluation of Year 1 of the Tuition Partners Programme: Impact Evaluation for Primary Schools. Evaluation Report

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    The National Tutoring Programme (NTP) Tuition Partners (TP) programme was designed to provide additional support to schools and teachers to supplement classroom teaching through subsidised high-quality tutoring for pupils from an approved list of tutoring organisations, the Tuition Partners. This evaluation covers the TP programme as delivered in its first year by the Education Endowment Foundation (EEF), from November 2020 to August 2021. Tuition Partners was one arm of the NTP. The NTP aimed to support teachers and schools in providing a sustained response to the Covid-19 pandemic and to provide a longer term contribution to closing the attainment gap between disadvantaged pupils and their peers. The NTP was part of a wider government response to the pandemic, funded by the Department for Education and originally developed by the EEF, Nesta, Impetus, The Sutton Trust, and Teach First, and with the support of the KPMG Foundation. The EEF appointed 33 approved ‘Tuition Partners’ that schools could select from to deliver tuition. Schools could access 15 hours of tutoring per selected pupil (with a minimum of 12 hours being considered a completed block of tuition). Tuition was provided online and/or face-to-face; and was 1:1, or in small groups (1:2 or 1:3); and available in English, maths, science, humanities and modern foreign languages. Tuition was expected to be delivered in schools (before, during and after school), in addition to usual teaching; and, in certain circumstances, at home. The programme was targeted at disadvantaged pupils attending state-maintained schools in England, including those eligible for Pupil Premium funding (PP-eligible), Free School Meals (FSM), or those identified by schools as having an equivalent need for support. Participating schools had discretion to identify which of their pupils they felt would most benefit from additional tuition support. Pupils in Years 1–11 were eligible (5–16 years old). The programme aimed to reach 215,000 to 265,000 pupils, across 6000 state-maintained schools in England, and it was expected that approximately 20,000 tutors would be recruited by Tuition Partners. The TP programme was set up and delivered during the Covid-19 pandemic, requiring continued responsiveness to the challenges faced by schools including restricted attendance, remote teaching, and ongoing widespread staff and pupil absences. During the school closures to most pupils from January – March 2021, the EEF approved TPs to deliver online tuition at home, however many schools chose to wait to commence tutoring until schools reopened fully, and therefore started tutoring later than planned. This evaluation report covers the analysis on the impact of the TP programme on the maths and English attainment outcomes for primary school pupils (Years 1–6) using standardised classroom assessments. Separate reports relate to analysis on Year 11 pupils and an implementation and process evaluation (IPE). The evaluation findings for the TP programme are brought together in a summary and interpretation report that is available here. This evaluation uses a quasi-experimental design (QED), involving a group of intervention schools that participated in the TP programme, and a group of comparison schools that did not receive the programme. The evaluation relies on a propensity score matching and re-weighting approach to ensure that the intervention and comparison schools are similar to each other in important, observable regards. As pupils who would have received TP in comparison schools were difficult to identify, the evaluation focused on pupils eligible for Pupil Premium and on all pupils, as these groups can be identified in both TP and comparison schools. For English, the analysis is based on 165 primary schools with 7073 pupils eligible for Pupil Premium and for maths, 126 primary schools with 5102 pupils eligible for Pupil Premium3. An additional instrumental variable (IV) analysis, based on the sample of TP schools only, looked at the impact of TP in schools that signed up to the TP programme earlier (and that delivered more tutoring) compared to schools that signed up later. On average, pupils eligible for Pupil Premium in schools that received TP made similar progress in English and maths compared to pupils eligible for Pupil Premium in comparison schools (no evidence of an effect in English or in maths). This result has a low security rating. A particular challenge is that, on average, only approximately 20% of pupils eligible for Pupil Premium were selected for tutoring, meaning a large proportion of pupils eligible for Pupil Premium were included in the analysis who did not receive tutoring. Therefore, this estimated impact of TP is diluted and it is hard to detect any effect that may (or may not) be present. Similar analysis on all pupils found that pupils in schools that received TP made, on average, similar progress in English compared to all pupils in comparison schools (no evidence of an effect), and an additional one month’s progress in maths compared to pupils in comparison schools. However, there is uncertainty around these estimates, with the positive maths result being consistent with a null (0 months) or slightly larger positive effect (2 months) and the English result being consistent with small positive (1 month) or small negative effect (−1 months). Furthermore, this analysis was subject to even further dilution: on average, only 12% (for maths) and 14% (for English) of pupils in the analysed schools were selected for tutoring. Given this context, it is unlikely that any of these differences were due to TP. In the sample of TP schools, completing a 12-hour block of tutoring (compared to zero hours) was related to higher English scores amongst pupils eligible for Pupil Premium that received more tutoring due to the early sign-up of the school. An equivalent analysis for maths was not able to proceed. A different analysis within TP schools showed that pupils who received more hours of tutoring were associated with higher English scores on average than pupils who received fewer hours of tutoring. However, this was not the case for maths, where receiving more hours of tutoring was not associated with higher maths scores. These results are associations and are not necessarily causal estimates of impact; there may be other explanations for the results

    Evaluation of Year 1 of the Tuition Partners Programme: Impact Evaluation Report for Year 11. Evaluation Report: An exploration of impact in Year 11

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    The National Tutoring Programme (NTP) Tuition Partners (TP) programme was designed to provide additional support to schools and teachers to supplement classroom teaching through subsidised, high quality tutoring for pupils from an approved list of tutoring organisations, the Tuition Partners. This evaluation covers the TP programme as delivered in its first year by the Education Endowment Foundation (EEF), from November 2020 to August 2021. Tuition Partners was one arm of the NTP. The NTP aimed to support teachers and schools in providing a sustained response to the Covid-19 pandemic and to provide a longer term contribution to closing the attainment gap between disadvantaged pupils and their peers. The NTP was part of a wider government response to the pandemic, funded by the Department for Education and originally developed by the EEF, Nesta, Impetus, The Sutton Trust, and Teach First, and with the support of the KPMG Foundation. The EEF appointed 33 approved ‘Tuition Partners’ that schools could select from to deliver tuition. Schools could access 15 hours of tutoring per selected pupil (with a minimum of 12 hours being considered a completed block of tuition). Tuition was provided online and/or face-to-face; and was 1:1, or in small groups (1:2 or 1:3); and available in English, maths, science, humanities and modern foreign languages. Tuition was expected to be delivered in schools (before, during and after school), in addition to usual teaching; and in certain circumstances, at home. The programme was targeted at disadvantaged pupils attending state-maintained schools in England, including those eligible for Pupil Premium funding (PP-eligible), Free School Meals (FSM), or those identified by schools as having an equivalent need for support. Participating schools had discretion to identify which of their pupils they felt would most benefit from additional tuition support. Pupils in Years 1–11 were eligible (5–16 years old). The programme aimed to reach 215,000 to 265,000 pupils, across 6,000 state-maintained schools in England, and it was expected that approximately 20,000 tutors would be recruited by Tuition Partners. The TP programme was set up and delivered during the Covid-19 pandemic, requiring continued responsiveness to the challenges faced by schools including restricted attendance, remote teaching, and ongoing widespread staff and pupil absences. During school closures to most pupils from January – March 2021, the EEF approved TPs to deliver online tuition at home, however many schools chose to wait to commence tutoring until schools reopened fully, and therefore started tutoring later than planned. The usual summer exams process for Year 11 pupils could not go ahead as planned in summer 2021, and GCSEs were determined by TAGs instead. This evaluation report covers the analysis on the impact of the TP programme on the maths and English attainment outcomes for Year 11 pupils only. Separate reports relate to analysis on a sample of primary schools and an implementation and process evaluation (IPE). The evaluation findings for the TP programme are brought together in a summary and interpretation report that is available here. This evaluation uses a quasi-experimental design (QED), involving a group of intervention schools that participated in the TP programme, and a group of comparison schools that did not receive the programme. The evaluation relies on a propensity score matching approach to ensure that the intervention and comparison schools are similar to each other in important, observable regards. As pupils who would have received TP in comparison schools were difficult to identify, the evaluation focused on pupils eligible for Pupil Premium and on all pupils, as these groups can be identified in both TP and non-TP schools. The analysis is based on 1,464 secondary schools with a total of 62,024 pupils eligible for Pupil Premium. The evaluation assessed impact in English and maths using Teacher Assessed Grades (TAGs) from 2021. Year 11 pupils eligible for Pupil Premium in schools that received TP made similar progress in English and maths compared to pupils eligible for Pupil Premium in comparison schools (there was no evidence of an effect in English or maths). A particular challenge is that, on average, only 12% of pupils eligible for Pupil Premium were selected for tutoring in maths and 9% were selected for tutoring in English, meaning the vast majority of the pupils included in the analysis did not receive tutoring. Therefore, this estimated impact of TP is diluted and it is hard to detect any effect that may (or may not) be present. When looking at all pupils in Year 11, pupils in schools that received TP made, on average, similar progress in English compared to all Year 11 pupils in comparison schools (there was no evidence of an effect). In maths, Year 11 pupils in schools that received TP made slightly less progress than all Year 11 pupils in comparison schools (though this effect was very small and equivalent to zero months ’ additional progress). However, this analysis was subject to even further dilution than the PPeligible analysis: only 7% of Year 11 pupils were selected for tutoring in maths and 6% in English. Given this context, it is unlikely that any of these differences were due to TP. Additional analysis restricted the sample of schools to those that targeted higher proportions of pupils eligible for Pupil Premium to receive tutoring, to reduce the issue of dilution and bring the group of analysed pupils closer to those that were selected for the intervention. In schools that selected over 50% of pupils eligible for Pupil Premium for tutoring, pupils eligible for Pupil Premium made similar progress in TP and comparison schools in English and maths. However, when the sample was restricted to schools that selected over 70% of pupils eligible for Pupil Premium for tutoring (and reducing dilution further), the impact of TP on pupils eligible for Pupil Premium is positive. In these schools, pupils eligible for Pupil Premium made, on average, the equivalent of two months additional progress in English and two months additional progress in maths, compared to pupils eligible for Pupil Premium in comparison schools. This analysis was based on a smaller sample of schools that were rematched to a comparison sample. However, different characteristics to the rest of the TP population of schools remained (more ‘Outstanding’ schools, lower percentage of FSM students), so this finding may not necessarily be generalisable to all TP schools. Within schools that participated in TP, pupils who received more hours of tutoring in maths obtained higher maths TAGs, and pupils who received more hours of tutoring in English obtained higher English TAGs, than pupils who received fewer hours of tutoring in the respective subjects. These results are associations and are not necessarily causal estimates of impact; there may be other explanations for the higher grades among these pupils

    ACADEMIC DISCIPLINE «ALTERNATIVE ENERGY»: A TUTORIAL ASPECT

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    The necessity to update academic discipline contents taking into account international experience is shown. At the School of Ecology in the framework of British Council project «Alternative Energy: Education and Science» (implemented together with Keele University, UK) the course «Alternative Energy» was updated: new topics were included, new methods of teaching were introduced. The content of the course is presented in details. Due to up-dating students receive new competencies which allow them to solve complex problems and to be more competitive on the labour market

    Multispin correlations and pseudo-thermalization of the transient density matrix in solid-state NMR: free induction decay and magic echo

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    Quantum unitary evolution typically leads to thermalization of generic interacting many-body systems. There are very few known general methods for reversing this process, and we focus on the magic echo, a radio-frequency pulse sequence known to approximately "rewind" the time evolution of dipolar coupled homonuclear spin systems in a large magnetic field. By combining analytic, numerical, and experimental results we systematically investigate factors leading to the degradation of magic echoes, as observed in reduced revival of mean transverse magnetization. Going beyond the conventional analysis based on mean magnetization we use a phase encoding technique to measure the growth of spin correlations in the density matrix at different points in time following magic echoes of varied durations and compare the results to those obtained during a free induction decay (FID). While considerable differences are documented at short times, the long-time behavior of the density matrix appears to be remarkably universal among the types of initial states considered - simple low order multispin correlations are observed to decay exponentially at the same rate, seeding the onset of increasingly complex high order correlations. This manifestly athermal process is constrained by conservation of the second moment of the spectrum of the density matrix and proceeds indefinitely, assuming unitary dynamics.Comment: 12 Pages, 9 figure

    Investigating bacteriophages targeting the opportunistic pathogen Acinetobacter baumannii

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    The multi-drug resistance of the opportunistic pathogen Acinetobacter baumannii is of growing concern, with many clinical isolates proving to be resistant to last resort as well as front line antibiotic treatments. The use of bacteriophages is an attractive alternative to controlling and treating this emerging nosocomial pathogen. In this study, we have investigated bacteriophages collected from hospital wastewater in Thailand and we have explored their activity against clinical isolates of A. baumannii. Bacteriophage vB_AbaM_PhT2 showed 28% host range against 150 multidrug resistant (MDR) isolates and whole genome sequencing did not detect any known virulence factors or antibiotic resistance genes. Purified vB_AbaM_PhT2 samples had endotoxin levels below those recommended for preclinical trials and were not shown to be directly cytotoxic to human cell lines in vitro. The treatment of human brain and bladder cell lines grown in the presence of A. baumannii with this bacteriophage released significantly less lactate dehydrogenase compared to samples with no bacteriophage treatment, indicating that vB_AbaM_PhT2 can protect from A. baumannii induced cellular damage. Our results have also indicated that there is synergy between this bacteriophage and the end line antibiotic colistin. We therefore propose bacteriophage vB_AbaM_PhT2 as a good candidate for future research and for its potential development into a surface antimicrobial for use in hospitals. View Full-Tex

    Environmental impacts of Scottish faba bean-based beer in an integrated beer and animal feed value chain

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    Beer is one of themost popular drinks globally and productionmethods clearly need to becomemore sustainable. The brewing of legume grains could contribute to improved sustainability through encouraging the diversification of cropped systems and by providing more nutritious local co-products as animal feed. The aim of this studywas to assess the potential environmental effect of partially substituting malted barley with grain legumes as an option to mitigate the environmental impact of beer. A Life Cycle Assessment (LCA) was performed to compare a novel Scottish beer produced with malted barley and UK-grown faba beans with a traditional malted barley beer. Weconsidered beer production as part of amulti-functional beer and animal feed value chain, where coproducts are used as a high-protein UK-grown animal feed. The environmental performances of the different beers were highly dependent on the system boundaries adopted. The simple attributional LCA indicated that a barley-bean beer could offer environmental savingswhen alcohol yields are optimised, with environmental burdens that were significantly smaller than those of the barley beer across 6 categories. When boundarieswere expanded to include both feed substitution and agricultural rotations, the barley-bean beer with current alcohol yields outperformed the barley beer across 8 impact categories, with a 15 %-17 % smaller climate change burden, mainly due to higher feed substitution achieved froma larger volumeof brewing co-productswith higher protein concentrations. Therefore, brewers should consider the use of legumes in their brewing recipes to lower their environmental footprint, increasing the availability of more nutritious beer co-products as a local source of animal feed, and diversifying cropping systems while adding novelty to their product range. Different boundaries settings and scenarios should be assessed in a beer LCA, and entire cropping rotations should be integrated to capture a more accurate picture of the agricultural stage.(c) 2022 Published by Elsevier Ltd on behalf of Institution of Chemical Engineers
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