Hydrodynamic characterization of soil compaction using integrated electrical resistivity and X‐ray computed tomography

Modern agricultural practices can cause significant stress on soil, which ultimately has degrading effects, such as compaction. There is an urgent need for fast, noninvasive methods to characterize and monitor compaction and its impact on hydraulic processes. Electrical resistivity tomography (ERT) is a well-established method used for the assessment of soil hydraulic properties due to its high temporal resolution and sensitivity to changes in moisture content and salinity, whereas X-ray computed tomography (CT) can be used for high-spatial-resolution imaging of soil structure. We used the combined strengths of both methods to study soil under three different levels of compaction. The soils were X-ray scanned and electrically monitored after the application of a saline solution to the soil surface. The scans revealed the pore network architecture and allowed us to compute its size and connectivity. The ERT models revealed inhibited percolation rates for soils with a lower bulk density, but also how resistivity changes are spatiotemporally distributed within the soil columns. Furthermore, we obtained a quantitative link between the two methods, by which voxels more densely populated with pores were associated with higher temporal variations in electrical resistivity. Building on this, we established a spatial collocation between pore structure and distribution of solution during percolation. This demonstrates the potential of the combined strengths of the two tomographic methods to obtain an enhanced characterization of soil hydrodynamic properties

Health, Wealth, and Air Pollution: Advancing Theory and Methods

The effects of both ambient air pollution and socioeconomic position (SEP) on health are well documented. A limited number of recent studies suggest that SEP may itself play a role in the epidemiology of disease and death associated with exposure to air pollution. Together with evidence that poor and working-class communities are often more exposed to air pollution, these studies have stimulated discussion among scientists, policy makers, and the public about the differential distribution of the health impacts from air pollution. Science and public policy would benefit from additional research that integrates the theory and practice from both air pollution and social epidemiologies to gain a better understanding of this issue. In this article we aim to promote such research by introducing readers to methodologic and conceptual approaches in the fields of air pollution and social epidemiology; by proposing theories and hypotheses about how air pollution and socioeconomic factors may interact to influence health, drawing on studies conducted worldwide; by discussing methodologic issues in the design and analysis of studies to determine whether health effects of exposure to ambient air pollution are modified by SEP; and by proposing specific steps that will advance knowledge in this field, fill information gaps, and apply research results to improve public health in collaboration with affected communities

Joining the dots: Conditional pass and programmatic assessment enhances recognition of problems with professionalism and factors hampering student progress

<p>Abstract</p> <p>Background</p> <p>Programmatic assessment that looks across a whole year may contribute to better decisions compared with those made from isolated assessments alone. The aim of this study is to describe and evaluate a programmatic system to handle student assessment results that is aligned not only with learning and remediation, but also with defensibility. The key components are standards based assessments, use of "Conditional Pass", and regular progress meetings.</p> <p>Methods</p> <p>The new assessment system is described. The evaluation is based on years 4-6 of a 6-year medical course. The types of concerns staff had about students were clustered into themes alongside any interventions and outcomes for the students concerned. The likelihoods of passing the year according to type of problem were compared before and after phasing in of the new assessment system.</p> <p>Results</p> <p>The new system was phased in over four years. In the fourth year of implementation 701 students had 3539 assessment results, of which 4.1% were Conditional Pass. More in-depth analysis for 1516 results available from 447 students revealed the odds ratio (95% confidence intervals) for failure was highest for students with problems identified in more than one part of the course (18.8 (7.7-46.2) p < 0.0001) or with problems with professionalism (17.2 (9.1-33.3) p < 0.0001). The odds ratio for failure was lowest for problems with assignments (0.7 (0.1-5.2) NS). Compared with the previous system, more students failed the year under the new system on the basis of performance during the year (20 or 4.5% compared with four or 1.1% under the previous system (p < 0.01)).</p> <p>Conclusions</p> <p>The new system detects more students in difficulty and has resulted in less "failure to fail". The requirement to state conditions required to pass has contributed to a paper trail that should improve defensibility. Most importantly it has helped detect and act on some of the more difficult areas to assess such as professionalism.</p

Seasonal Arctic sea ice forecasting with probabilistic deep learning.

Anthropogenic warming has led to an unprecedented year-round reduction in Arctic sea ice extent. This has far-reaching consequences for indigenous and local communities, polar ecosystems, and global climate, motivating the need for accurate seasonal sea ice forecasts. While physics-based dynamical models can successfully forecast sea ice concentration several weeks ahead, they struggle to outperform simple statistical benchmarks at longer lead times. We present a probabilistic, deep learning sea ice forecasting system, IceNet. The system has been trained on climate simulations and observational data to forecast the next 6 months of monthly-averaged sea ice concentration maps. We show that IceNet advances the range of accurate sea ice forecasts, outperforming a state-of-the-art dynamical model in seasonal forecasts of summer sea ice, particularly for extreme sea ice events. This step-change in sea ice forecasting ability brings us closer to conservation tools that mitigate risks associated with rapid sea ice loss

Health, wealth, and air pollution: advancing theory and methods.

The effects of both ambient air pollution and socioeconomic position (SEP) on health are well documented. A limited number of recent studies suggest that SEP may itself play a role in the epidemiology of disease and death associated with exposure to air pollution. Together with evidence that poor and working-class communities are often more exposed to air pollution, these studies have stimulated discussion among scientists, policy makers, and the public about the differential distribution of the health impacts from air pollution. Science and public policy would benefit from additional research that integrates the theory and practice from both air pollution and social epidemiologies to gain a better understanding of this issue. In this article we aim to promote such research by introducing readers to methodologic and conceptual approaches in the fields of air pollution and social epidemiology; by proposing theories and hypotheses about how air pollution and socioeconomic factors may interact to influence health, drawing on studies conducted worldwide; by discussing methodologic issues in the design and analysis of studies to determine whether health effects of exposure to ambient air pollution are modified by SEP; and by proposing specific steps that will advance knowledge in this field, fill information gaps, and apply research results to improve public health in collaboration with affected communities

Feasibility of trial procedures for a randomised controlled trial of a community based group exercise intervention for falls prevention for visually impaired older people: the VIOLET study

Background Visually impaired older people (VIOP) have a higher risk of falling than their sighted peers, and are likely to avoid physical activity. The aim was to adapt the existing Falls Management Exercise (FaME) programme for VIOP, delivered in the community, and to investigate the feasibility of conducting a definitive randomised controlled trial (RCT) of this adapted intervention. Methods Two-centre randomised mixed methods pilot trial and economic evaluation of the adapted group-based FaME programme for VIOP versus usual care. A one hour exercise programme ran weekly over 12 weeks at the study sites (Newcastle and Glasgow), delivered by third sector (voluntary and community) organisations. Participants were advised to exercise at home for an additional two hours over the week. Those randomised to the usual activities group received no intervention. Outcome measures were completed at baseline, 12 and 24 weeks. The potential primary outcome was the Short Form Falls Efficacy Scale – International (SFES-I). Participants’ adherence was assessed by reviewing attendance records and self-reported compliance to the home exercises. Adherence with the course content (fidelity) by instructors was assessed by a researcher. Adverse events were collected in a weekly phone call. Results Eighteen participants, drawn from community-living VIOP were screened; 68 met the inclusion criteria; 64 participants were randomised with 33 allocated to the intervention and 31 to the usual activities arm. 94% of participants provided data at the 12 week visit and 92% at 24 weeks. Adherence was high. The intervention was found to be safe with 76% attending nine or more classes. Median time for home exercise was 50 min per week. There was little or no evidence that fear of falling, balance and falls risk, physical activity, emotional, attitudinal or quality of life outcomes differed between trial arms at follow-up. Conclusions The intervention, FaME, was implemented successfully for VIOP and all progression criteria for a main trial were met. The lack of difference between groups on fear of falling was unsurprising given it was a pilot study but there may have been other contributory factors including suboptimal exercise dose and apparent low risk of falls in participants. These issues need addressing for a future trial

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy