How effective is the Forestry Commission Scotland's woodland improvement programme--'Woods In and Around Towns' (WIAT)--at improving psychological well-being in deprived urban communities? A quasi-experimental study

Introduction: There is a growing body of evidence that suggests that green spaces may positively influence psychological well-being. This project is designed to take advantage of a natural experiment where planned physical and social interventions to enhance access to natural environments in deprived communities provide an opportunity to prospectively assess impacts on perceived stress and mental well-being.<p></p> Study design and methods: A controlled, prospective study comprising a repeat cross-sectional survey of residents living within 1.5 km of intervention and comparison sites. Three waves of data will be collected: prephysical environment intervention (2013); postphysical environment intervention (2014) and postwoodland promotion social intervention (2015). The primary outcome will be a measure of perceived stress (Perceived Stress Scale) preintervention and postintervention. Secondary, self-report outcomes include: mental well-being (Short Warwick-Edinburgh Mental Well-being Scale), changes in physical activity (IPAQ-short form), health (EuroQoL EQ-5D), perception and use of the woodlands, connectedness to nature (Inclusion of Nature in Self Scale), social cohesion and social capital. An environmental audit will complement the study by evaluating the physical changes in the environment over time and recording any other contextual changes over time. A process evaluation will assess the implementation of the programme. A health economics analysis will assess the cost consequences of each stage of the intervention in relation to the primary and secondary outcomes of the study.<p></p> Ethics and dissemination: Ethical approval has been given by the University of Edinburgh, Edinburgh College of Art Research, Ethics and Knowledge Exchange Committee (ref. 19/06/2012). Findings will be disseminated through peer-reviewed publications, national and international conferences and, at the final stage of the project, through a workshop for those interested in implementing environmental interventions.<p></p&gt

Alternative Covid-19 mitigation measures in school classrooms:analysis using an agent-based model of SARS-CoV-2 transmission

The SARS-CoV-2 epidemic has impacted children's education, with schools required to implement infection control measures that have led to periods of absence and classroom closures. We developed an agent-based epidemiological model of SARS-CoV-2 transmission in a school classroom that allows us to quantify projected infection patterns within primary school classrooms, and related uncertainties. Our approach is based on a contact model constructed using random networks, informed by structured expert judgement. The effectiveness of mitigation strategies in suppressing infection outbreaks and limiting pupil absence are considered. COVID-19 infections in primary schools in England in autumn 2020 were re-examined and the model was then used to estimate infection levels in autumn 2021, as the Delta variant was emerging and it was thought likely that school transmission would play a major role in an incipient new wave of the epidemic. Our results were in good agreement with available data. These findings indicate that testing-based surveillance is more effective than bubble quarantine, both for reducing transmission and avoiding pupil absence, even accounting for insensitivity of self-administered tests. Bubble quarantine entails large numbers of absences, with only modest impact on classroom infections. However, maintaining reduced contact rates within the classroom can have a major benefit for managing COVID-19 in school settings

Alternative Covid-19 mitigation measures in school classrooms:analysis using an agent-based model of SARS-CoV-2 transmission

The SARS-CoV-2 epidemic has impacted children's education, with schools required to implement infection control measures that have led to periods of absence and classroom closures. We developed an agent-based epidemiological model of SARS-CoV-2 transmission in a school classroom that allows us to quantify projected infection patterns within primary school classrooms, and related uncertainties. Our approach is based on a contact model constructed using random networks, informed by structured expert judgement. The effectiveness of mitigation strategies in suppressing infection outbreaks and limiting pupil absence are considered. COVID-19 infections in primary schools in England in autumn 2020 were re-examined and the model was then used to estimate infection levels in autumn 2021, as the Delta variant was emerging and it was thought likely that school transmission would play a major role in an incipient new wave of the epidemic. Our results were in good agreement with available data. These findings indicate that testing-based surveillance is more effective than bubble quarantine, both for reducing transmission and avoiding pupil absence, even accounting for insensitivity of self-administered tests. Bubble quarantine entails large numbers of absences, with only modest impact on classroom infections. However, maintaining reduced contact rates within the classroom can have a major benefit for managing COVID-19 in school settings

Emergency planning and mitigation at Vesuvius: A new evidence-based approach

Disasters from explosive volcanic eruptions are infrequent and experience in emergency planning and mitigation for such events remains limited. The need for urgently developing more robust methods for risk assessment and decision making in volcanic crises has become increasingly apparent as world populations continue to expand in areas of active explosive volcanism. Nowhere is this more challenging than at Vesuvius, Italy, with hundreds of thousands of people living on the flanks of one of the most dangerous volcanoes in the world. We describe how a new paradigm, evidence-based volcanology, has been applied in EXPLORIS to contribute to crisis planning and management for when the volcano enters its next state of unrest, as well as in long-term land-use planning. The analytical approach we adopted enumerates and quantifies all the processes and effects of the eruptive hazards of the volcano known to influence risk, a scientific challenge that combines field data on the vulnerability of the built environment and humans in past volcanic disasters with theoretical research on the state of the volcano, and including evidence from the field on previous eruptions as well as numerical simulation modelling of eruptive processes. Formal probabilistic reasoning under uncertainty and a decision analysis approach have provided the basis for the development of an event tree for a future range of eruption types with probability paths and hypothetical casualty outcomes for risk assessment. The most likely future eruption scenarios for emergency planning were derived from the event tree and elaborated upon from the geological and historical record. Modelling the impacts in these scenarios and quantifying the consequences for the circumvesuvian area provide realistic assessments for disaster planning and for showing the potential risk–benefit of mitigation measures, the main one being timely evacuation, but include for consideration protecting buildings against dilute, low dynamic pressure surges, and temporary roof supports in the most vulnerable buildings, as well as hardening infrastructure and lifelines. This innovative work suggests that risk-based methods could have an important role in crisis management at cities on volcanoes and small volcanic islands

Understanding causality and uncertainty in volcanic observations: an example of forecasting eruptive activity on Soufrière Hills Volcano, Montserrat

Following a cessation in eruptive activity it is important to understand how a volcano will behave in the future and when it may next erupt. Such an assessment can be based on the volcano's long-term pattern of behaviour and insights into its current state via monitoring observations. We present a Bayesian network that integrates these two strands of evidence to forecast future eruptive scenarios using expert elicitation. The Bayesian approach provides a framework to quantify the magmatic causes in terms of volcanic effects (i.e., eruption and unrest). In October 2013, an expert elicitation was performed to populate a Bayesian network designed to help forecast future eruptive (in-)activity at Soufrière Hills Volcano. The Bayesian network was devised to assess the state of the shallow magmatic system, as a means to forecast the future eruptive activity in the context of the long-term behaviour at similar dome-building volcanoes. The findings highlight coherence amongst experts when interpreting the current behaviour of the volcano, but reveal considerable ambiguity when relating this to longer patterns of volcanism at dome-building volcanoes, as a class. By asking questions in terms of magmatic causes, the Bayesian approach highlights the importance of using short-term unrest indicators from monitoring data as evidence in long-term forecasts at volcanoes. Furthermore, it highlights potential biases in the judgements of volcanologists and identifies sources of uncertainty in terms of magmatic causes rather than scenario-based outcomes

Digital pulse-shape discrimination of fast neutrons and gamma rays

Discrimination of the detection of fast neutrons and gamma rays in a liquid scintillator detector has been investigated using digital pulse-processing techniques. An experimental setup with a 252Cf source, a BC-501 liquid scintillator detector, and a BaF2 detector was used to collect waveforms with a 100 Ms/s, 14 bit sampling ADC. Three identical ADC's were combined to increase the sampling frequency to 300 Ms/s. Four different digital pulse-shape analysis algorithms were developed and compared to each other and to data obtained with an analogue neutron-gamma discrimination unit. Two of the digital algorithms were based on the charge comparison method, while the analogue unit and the other two digital algorithms were based on the zero-crossover method. Two different figure-of-merit parameters, which quantify the neutron-gamma discrimination properties, were evaluated for all four digital algorithms and for the analogue data set. All of the digital algorithms gave similar or better figure-of-merit values than what was obtained with the analogue setup. A detailed study of the discrimination properties as a function of sampling frequency and bit resolution of the ADC was performed. It was shown that a sampling ADC with a bit resolution of 12 bits and a sampling frequency of 100 Ms/s is adequate for achieving an optimal neutron-gamma discrimination for pulses having a dynamic range for deposited neutron energies of 0.3-12 MeV. An investigation of the influence of the sampling frequency on the time resolution was made. A FWHM of 1.7 ns was obtained at 100 Ms/s.Comment: 26 pages, 14 figures, submitted to Nuclear Instruments and Methods in Physics Research

Isabelle/PIDE as Platform for Educational Tools

The Isabelle/PIDE platform addresses the question whether proof assistants of the LCF family are suitable as technological basis for educational tools. The traditionally strong logical foundations of systems like HOL, Coq, or Isabelle have so far been counter-balanced by somewhat inaccessible interaction via the TTY (or minor variations like the well-known Proof General / Emacs interface). Thus the fundamental question of math education tools with fully-formal background theories has often been answered negatively due to accidental weaknesses of existing proof engines. The idea of "PIDE" (which means "Prover IDE") is to integrate existing provers like Isabelle into a larger environment, that facilitates access by end-users and other tools. We use Scala to expose the proof engine in ML to the JVM world, where many user-interfaces, editor frameworks, and educational tools already exist. This shall ultimately lead to combined mathematical assistants, where the logical engine is in the background, without obstructing the view on applications of formal methods, formalized mathematics, and math education in particular.Comment: In Proceedings THedu'11, arXiv:1202.453

Thermal Stability of Neodymium Aluminates High- κ

Thin films of neodymium aluminate (NdAlOx) have been deposited by liquid injection metalorganic chemical vapor deposition (MOCVD) using the bimetallic alkoxide precursor [NdAl(OPri)6(PriOH)]2. The effects of high-temperature postdeposition annealing on NdAlOx thin films are reported. The as-deposited thin films are amorphous in nature. X-ray diffraction (XRD) and medium energy ion scattering (MEIS) show, respectively, no crystallization or interdiffusion of metal ions into the substrate after annealing at 950°C. The capacitance-voltage (C-V) and current-voltage (I-V) characteristics of the thin films exhibited good electrical integrity following annealing. The dielectric permittivity (κ) of the annealed NdAlOx was 12, and a density of interface states at flatband (Dit) of 4.01×1011  cm−2 eV−1 was measured. The deposited NdAlOx thin films are shown to be able to endure high-temperature stress and capable of maintaining excellent dielectric properties