Mary M. Newson to James Meredith (Undated)

https://egrove.olemiss.edu/mercorr_pro/1732/thumbnail.jp

Modelling failure mechanisms of soft cliff profiles

A large proportion of the 11,000 km coastline of the United Kingdom is backed by soft cliffs. These cliffs are subject to frequent slumping and landslip events, particularly where sea and ground water percolates into the soil and rock. Many of these cliffs are formed from glaciogenic sediments, which experience severe erosion and rapid recession with long-term horizontal recession rates typically up to 2-3 m/year. A series of scaled physical model tests have been conducted using a large centrifuge facility with two-dimensional cliff models. These were tested in a wave flume container located on the centrifuge. Wave loading was created using a quasi-flap paddle system that was located at the opposite end of the centrifuge box. A number of tests were conducted using different cliff materials (i.e. combinations of sand and Portland cement). A parametric study was carried out to assess the influence of variations in cliff geometry and height, soil properties, wave amplitude and period. From these tests, it has been found that generally, failures occurred by progressive undercutting of the cliff toe, followed by global failure of the cliff mass

Review of Available Methods for Evaluation of Soil Sensitivity for Seismic Design

Sensitivity describes the effect of soil disturbance/remoulding on shear strength. Cyclic stresses during seismic events may lead to varying levels of disturbance and remoulding of brittle sensitive clays. The Canadian Foundation Engineering Manual (CFEM) recommends site-specific evaluation of the seismic hazard, including site response analysis, for sites that have quick or highly sensitive clays. Different levels of soil sensitivity have been shown in different versions of CFEM and their errata. The current manual CFEM (2006) classifies clay as highly sensitive if its sensitivity is greater than 40 (classified as Class F soil). However, there is considerable variation within the literature with respect to descriptions of sensitivity and more importantly, the related seismic risks that different soil states represent. This can have a significant impact on determination of the appropriate seismic forces on supported structures according to the seismic provisions of the current National Building Code of Canada, NBCC (2005). This paper reviews the different methods used to evaluate soil sensitivity and the sensitivity classifications in the literature. Based on this review, suggestions are provided for improvements of this approach to seismic design

Statistical nature of secondary electron emission

The energy-dependence of the secondary electron yield by electron impact on clean materials is shown, through comparisons with both experimental data and previous semi-empirical models, to be described well by a log-normal distribution. The maximum yield and corresponding energy are calculated in terms of the fit parameters. The function also agrees with the ‘universal curve’ obtained by expressing the experimental data in terms of the position and magnitude of maximum yield. The positron- and ion-induced secondary electron yields also exhibit a log-normal dependence and this is used to extend their energy ranges without prior knowledge of the position and magnitude of their maxima. In addition to their intrinsic usefulness, the results provide further support for the statistical description of inelastic processes advanced by Laricchia et al. (2018)

Changes in heart failure management and long-term mortality over ten years: observational study

Objectives: To estimate the long-term survival of two cohorts of people diagnosed with heart failure 10 years apart and to assess differences in patient characteristics, clinical guideline compliance and survival by diagnosis setting. Methods Data: for patients aged 18 and over with a new diagnosis of heart failure in the Clinical Practice Research Datalink in 2001–2002 (5966 patients in 156 practices) and 2011–2012 (12 827 patients in 331 practices). Survival rates since diagnosis were described using Kaplan-Meier plots. Compliance with national guidelines was summarised. Results: 2011/2012 patients were older than those diagnosed a decade before, with lower blood pressure and cholesterol but more comorbidity and healthcare contacts. For those diagnosed in 2001/2002, the 5-year survival was 40.0% (40.2% in the 2011/2012 cohort), 10-year survival was 20.8%, and 15-year survival 11.1%. Improvement in survival between the two time periods was seen only in those diagnosed in primary care (5-year survival 46.0% vs 57.4%, compared with 33.9% and 32.6% for hospital-diagnosed patients). Beta-blocker use rose from 24.3% to 39.1%; renin–angiotensin system blockers rose from 31.8% to 54.3% (both p<0.001). There was little change for loop diuretics and none for thiazide diuretics. For the 9963 patients with symptoms recorded by their general practitioner before diagnosis, brain natriuretic peptide (BNP) testing was low, but echocardiogram use rose from 8.3% to 19.3%, and specialist referral rose from 7.2% to 24.6% (all p<0.001)

Social influence matters: We follow pandemic guidelines most when our close circle does

Why do we adopt new rules, such as social distancing? Although human sciences research stresses the key role of social influence in behaviour change, most COVID-19 campaigns emphasize the disease’s medical threat. In a global data set (n = 6,674), we investigated how social influences predict people’s adherence to distancing rules during the pandemic. Bayesian regression analyses controlling for stringency of local measures showed that people distanced most when they thought their close social circle did. Such social influence mattered more than people thinking distancing was the right thing to do. People’s adherence also aligned with their fellow citizens, but only if they felt deeply bonded with their country. Self-vulnerability to the disease predicted distancing more for people with larger social circles. Collective efficacy and collectivism also significantly predicted distancing. To achieve behavioural change during crises, policymakers must emphasize shared values and harness the social influence of close friends and family