Particle segregation in dense flowing size-disperse granular mixtures is driven by gravity and shear, but predicting the associated segregation force due to both effects has remained an unresolved challenge. Here, a model of the combined gravity- and kinematics-induced segregation force on a single intruder particle is integrated with a model of the concentration dependence of the gravity-induced segregation force. The result is a general model of the net particle segregation force in flowing size-bidisperse granular mixtures. Using discrete element method simulations for comparison, the model correctly predicts the segregation force for a variety of mixture concentrations and flow conditions in both idealized and natural shear flows.

This paper compares community responses to Ebola and Covid-19 in two regions of southern and eastern Sierra Leone with reference to the theory of institutional dynamics proposed by the anthropologist Mary Douglas. Institutions, Douglas argued, are conveyed by styles of thought, shaped by the ways human communities, through everyday practices, reinforce systems of classification and denotation. Pandemic advice to ‘follow the science’ proved problematic, since there is no single institution of science, and institutions never stand alone but are bundled with other institutions, reflecting the manifold and intertwined practices of human social life. The paper explores some of the ways a traumatic epidemic of Ebola Virus Disease in Sierra Leone shaped a distinctive local response to this deadly infectious disease in the absence of an effective vaccine. This local approach emphasised social rules based on ideas about sequestration and testing. Communities then proposed to continue this rules-based approach to the pandemic of Covid-19 and showed little initial enthusiasm for vaccination. With Ebola, the adoption of rules resulted in dramatic drops in infection rates. But Covid-19 spreads in different ways, and good results from the application of social rules were much less apparent. The paper shows how communities began to grapple with this new situation. In some cases, vaccine hesitation was overcome by treating the requirement for vaccination as a new form of social discipline. More generally, it is concluded that epidemiologists need to pay specific attention to institutions and institutional dynamics in order to better understand and anticipate public reactions to new disease threats.

We explore some of the risks related to Artificial Intelligence (AI) from an actuarial perspective based on research from a transregional industry focus group. We aim to define the key gaps and challenges faced when implementing and utilising modern modelling techniques within traditional actuarial tasks from a risk perspective and in the context of professional standards and regulations. We explore best practice guidelines to attempt to define an ideal approach and propose potential next steps to help reach the ideal approach. We aim to focus on the considerations, initially from a traditional actuarial perspective and then, if relevant, consider some implications for non-traditional actuarial work, by way of examples. The examples are not intended to be exhaustive. The group considered potential issues and challenges of using AI, related to the following key themes:

• Ethical

  • ○ Bias, fairness, and discrimination

  • ○ Individualisation of risk assessment

  • ○ Public interest

• Professional

  • ○ Interpretability and explainability

  • ○ Transparency, reproducibility, and replicability

  • ○ Validation and governance

• Lack of relevant skills available

• Wider themes

This paper aims to provide observations that could help inform industry and professional guidelines or discussion or to support industry practitioners. It is not intended to replace current regulation, actuarial standards, or guidelines. The paper is aimed at an actuarial and insurance technical audience, specifically those who are utilising or developing AI, and actuarial industry bodies.

PET imaging is increasingly recognized as an important diagnostic tool to investigate patients with cognitive disturbances of possible neurodegenerative origin. PET with 2-[18F]fluoro-2-deoxy-D-glucose ([18F]FDG), assessing glucose metabolism, provides a measure of neurodegeneration and allows a precise differential diagnosis among the most common neurodegenerative diseases, such as Alzheimer’s disease, frontotemporal dementia or dementia with Lewy bodies. PET tracers specific for the pathological deposits characteristic of different neurodegenerative processes, namely amyloid and tau deposits typical of Alzheimer’s Disease, allow the visualization of these aggregates in vivo. [18F]FDG and amyloid PET imaging have reached a high level of clinical validity and are since 2022 investigations that can be offered to patients in standard clinical care in most of Canada.

This article will briefly review and summarize the current knowledge on these diagnostic tools, their integration into diagnostic algorithms as well as perspectives for future developments.

To investigate the symptoms of SARS-CoV-2 infection, their dynamics and their discriminatory power for the disease using longitudinally, prospectively collected information reported at the time of their occurrence. We have analysed data from a large phase 3 clinical UK COVID-19 vaccine trial. The alpha variant was the predominant strain. Participants were assessed for SARS-CoV-2 infection via nasal/throat PCR at recruitment, vaccination appointments, and when symptomatic. Statistical techniques were implemented to infer estimates representative of the UK population, accounting for multiple symptomatic episodes associated with one individual. An optimal diagnostic model for SARS-CoV-2 infection was derived. The 4-month prevalence of SARS-CoV-2 was 2.1%; increasing to 19.4% (16.0%–22.7%) in participants reporting loss of appetite and 31.9% (27.1%–36.8%) in those with anosmia/ageusia. The model identified anosmia and/or ageusia, fever, congestion, and cough to be significantly associated with SARS-CoV-2 infection. Symptoms’ dynamics were vastly different in the two groups; after a slow start peaking later and lasting longer in PCR+ participants, whilst exhibiting a consistent decline in PCR- participants, with, on average, fewer than 3 days of symptoms reported. Anosmia/ageusia peaked late in confirmed SARS-CoV-2 infection (day 12), indicating a low discrimination power for early disease diagnosis.