COVID-19 infection and death rates: the need to incorporate causal explanations for the data and avoid bias in testing

COVID-19 testing strategies are primarily driven by medical need - focusing on people already hospitalized with significant symptoms or on people most at risk. However, such testing is highly biased because it fails to identify the extent to which COVID-19 is present in people with mild or no symptoms. If we wish to understand the true rate of COVID-19 infection and death, we need to take full account of the causal explanations for the resulting data to avoid highly misleading conclusions about infection and death rates. We describe how causal (Bayesian network) models can provide such explanations and the need to combine these with more random testing in order to achieve reliable data and predictions for the both policy makers and the public

Cognitive Mechanisms in Chronic Tinnitus: Psychological Markers of a Failure to Switch Attention

The cognitive mechanisms underpinning chronic tinnitus (CT; phantom auditory perceptions) are underexplored but may reflect a failure to switch attention away from a tinnitus sound. Here, we investigated a range of components that influence the ability to switch attention, including cognitive control, inhibition, working memory and mood, on the presence and severity of CT. Our participants with tinnitus showed significant impairments in cognitive control and inhibition as well as lower levels of emotional well-being, compared to healthy-hearing participants. Moreover, the subjective cognitive complaints of tinnitus participants correlated with their emotional well-being whereas complaints in healthy participants correlated with objective cognitive functioning. Combined, cognitive control and depressive symptoms correctly classified 67% of participants. These results demonstrate the core role of cognition in CT. They also provide the foundations for a neurocognitive account of the maintenance of tinnitus, involving impaired interactions between the neurocognitive networks underpinning attention-switching and mood

Using Spatial Manipulation to Examine Interactions between Visual and Auditory Encoding of Pitch and Time

Music notations use both symbolic and spatial representation systems. Novice musicians do not have the training to associate symbolic information with musical identities, such as chords or rhythmic and melodic patterns. They provide an opportunity to explore the mechanisms underpinning multimodal learning when spatial encoding strategies of feature dimensions might be expected to dominate. In this study, we applied a range of transformations (such as time reversal) to short melodies and rhythms and asked novice musicians to identify them with or without the aid of notation. Performance using a purely spatial (graphic) notation was contrasted with the more symbolic, traditional western notation over a series of weekly sessions. The results showed learning effects for both notation types, but performance improved more for graphic notation. This points to greater compatibility of auditory and visual neural codes for novice musicians when using spatial notation, suggesting that pitch and time may be spatially encoded in multimodal associative memory. The findings also point to new strategies for training novice musicians

Smart automotive technology adherence to the law: (de)constructing road rules for autonomous system development, verification and safety

Driving is an intuitive task that requires skill, constant alertness and vigilance for unexpected events. The driving task also requires long concentration spans, focusing on the entire task for prolonged periods, and sophisticated negotiation skills with other road users including wild animals. Modern motor vehicles include an array of smart assistive and autonomous driving systems capable of subsuming some, most, or in limited cases, all of the driving task. Building these smart automotive systems requires software developers with highly technical software engineering skills, and now a lawyer’s in-depth knowledge of traffic legislation as well. This article presents an approach for deconstructing the complicated legalese of traffic law and representing its requirements and flow. Our approach (de)constructs road rules in legal terminology and specifies them in ‘structured English logic’ that is expressed as ‘Boolean logic’ for automation and ‘Lawmaps’ for visualization. We demonstrate an example using these tools leading to the construction and validation of a ‘Bayesian Network model’. We strongly believe these tools to be approachable by programmers and the general public, useful in development of Artificial Intelligence to underpin motor vehicle smart systems, and in validation to ensure these systems are considerate of the law when making decisions.fals

Learning from Behavioural Changes That Fail

Behavioural change techniques are currently used by many global organisations and public institutions. The amassing evidence base is used to answer practical and scientific questions regarding what cognitive, affective, and environment factors lead to successful behavioural change in the laboratory and in the field. In this piece we show that there is also value to examining interventions that inadvertently fail in achieving their desired behavioural change (e.g., backfiring effects). We identify the underlying causal pathways that characterise different types of failure, and show how a taxonomy of causal interactions that result in failure exposes new insights that can advance theory and practice

Pitch Enumeration: Failure to Subitize in Audition

Background: Subitizing involves recognition mechanisms that allow effortless enumeration of up to four visual objects, however despite ample resolution experimental data suggest that only one pitch can be reliably enumerated. This may be due to the grouping of tones according to harmonic relationships by recognition mechanisms prior to fine pitch processing. Poorer frequency resolution of auditory information available to recognition mechanisms may lead to unrelated tones being grouped, resulting in underestimation of pitch number. Methods, Results and Conclusion: We tested whether pitch enumeration is better for chords of full harmonic complex tones, where grouping errors are less likely, than for complexes with fewer and less accurately tuned harmonics. Chords of low familiarity were used to mitigate the possibility that participants would recognize the chord itself and simply recall the number of pitches. We found that accuracy of pitch enumeration was less than the visual system overall, and underestimation of pitch number increased for stimuli containing fewer harmonics. We conclude that harmonically related tones are first grouped at the poorer frequency resolution of the auditory nerve, leading to poor enumeration of more than one pitch

The thorny problems of Covid-19 Contact Tracing Apps: The need for a holistic approach

Once we accept the potential advantages that may arise from investing in contact tracing apps (CTA) as a response to the current COVID-19 crisis, we need to consider the different challenges that arise, and how they can be solved. In so doing, and to make the job surmountable, we must understand the challenging class of problems that spans both technical and behavioral issues (thorny issues). In thinking about the value of contact tracing, and the potential resolutions to some of the core problems, this short piece outlines what policy makers may need to consider, especially if we are to successfully deal with the predicted second wave

Reheating the Universe After Multi-Field Inflation

We study in detail (p)reheating after multi-field inflation models with a particular focus on N-flation. We consider a variety of different couplings between the inflatons and the matter sector, including both quartic and trilinear interactions with a light scalar field. We show that the presence of multiple oscillating inflatons makes parametric resonance inefficient in the case of the quartic interactions. Moreover, perturbative processes do not permit a complete decay of the inflaton for this coupling. In order to recover the hot big bang, we must instead consider trilinear couplings. In this case we show that strong nonperturbative preheating is possible via multi-field tachyonic resonance. In addition, late-time perturbative effects do permit a complete decay of the condensate. We also study the production of gauge fields for several prototype couplings, finding similar results to the trilinear scalar coupling. During the course of our analysis we develop the mathematical theory of the quasi-periodic Mathieu equation, the multi-field generalization of the Floquet theory familiar from preheating after single field inflation. We also elaborate on the theory of perturbative decays of a classical inflaton condensate, which is applicable in single-field models also.Comment: 46+1 pages, 19 figure

Paracetamol, NSAIDS and opioid analgesics for chronic low back pain: A network meta-analysis (Protocol)

This is a protocol for a Cochrane Review (Intervention). The objectives are as follows: To answer the clinical question: ‘what analgesic medicine shall I prescribe this patient with chronic low back pain to reduce their pain?’. The objectives are to determine the analgesic effects, safety, effect on function, and relative rank according to analgesic effect, safety and effect on function of a single course of opioid analgesics, NSAIDs or paracetamol or combinations of these medicines

Addition of hyaluronic acid to the FIB-4 liver fibrosis score improves prediction of incident cirrhosis and hepatocellular carcinoma in Type 2 diabetes: The Edinburgh Type 2 Diabetes Study

Background: Type 2 diabetes is associated with increased risk of progression to cirrhosis and hepatocellular carcinoma (HCC) in people with chronic liver diseases, particularly non-alcoholic fatty liver disease (NAFLD). However, the absolute risk of progression is low so it is crucial to accurately identify patients who would benefit most from hepatology referral and intensified management. Current risk-stratification tools are sub-optimal and perform worse in people with diabetes.Aims: To determine whether the addition of complementary biomarker(s) to current NAFLD risk-stratification tools in people with Type 2 diabetes could improve the identification of people who are at increased risk of developing incident cirrhosis or HCC.Methods: The Edinburgh Type 2 diabetes Study (ET2DS) is a cohort study of men and women with Type 2 diabetes (n=1066, age 60-75 at baseline). Cases of cirrhosis and HCC were identified over 11-years of follow-up. Biomarkers were measured at baseline and year one and association with incident disease assessed using logistic regression.Results: Of existing risk-stratification scores tested, the Fibrosis-4 (FIB-4) index and the AST:platelet ratio index (APRI) performed best in this cohort. Addition of hyaluronic acid (cut-point ≥50μg/L) to FIB-4 (cut-point ≥1.3) maintained a false negative rate ≤25% and reduced the number of people incorrectly identified as ‘high-risk’ for incident disease by ~50%.Conclusions: The addition of hyaluronic acid to FIB-4 reduced the proportion of people inappropriately identified as ‘high-risk’ for development of cirrhosis/HCC in a community population of otherwise asymptomatic people with Type 2 diabetes. These findings require validation in independent cohorts