Microbial mats of the Tswaing impact crater: results of a South African exobiology expedition and implications for the search for biological molecules on Mars

We describe microbial mats from the Tswaing impact crater in South Africa. The mats provide insights into the unique biological characteristics of impact craters and can help strategies for the search for biomolecules on Mars

Trustworthiness of statistical inference

We examine the role of trustworthiness and trust in statistical inference, arguing that it is the extent of trustworthiness in inferential statistical tools which enables trust in the conclusions. Certain tools, such as the p‐value and significance test, have recently come under renewed criticism, with some arguing that they damage trust in statistics. We argue the contrary, beginning from the position that the central role of these methods is to form the basis for trusted conclusions in the face of uncertainty in the data, and noting that it is the misuse and misunderstanding of these tools which damages trustworthiness and hence trust. We go on to argue that recent calls to ban these tools would tackle the symptom, not the cause, and themselves risk damaging the capability of science to advance, as well as risking feeding into public suspicion of the discipline of statistics. The consequence could be aggravated mistrust of our discipline and of science more generally. In short, the very proposals could work in quite the contrary direction from that intended. We make some alternative proposals for tackling the misuse and misunderstanding of these methods, and for how trust in our discipline might be promoted

Quality Improvement Project to Enhance Provider Awareness and Use of the Coping Strategies Questionnaire (CSQ) to Assess Patients\u27 Level of Coping with Chronic Pain

Chronic pain is a public health problem that has an effect on 20-30% (100 million) of the population of Western countries, with costs to manage chronic pain ranging from $560 to$635 billion annually. Many chronic body system problems, especially those involving musculoskeletal and neurological sequelae, aggravate the pain sensation over time. Chronic pain is depicted by physical dysfunction, disability, and mood alteration; exacerbated by a lack of appropriate coping strategies. Treatment for patients with chronic pain, by providers, has been proven to be inadequate, secondary to providers’ reports of lack of time and lack of a consistent, efficient, effective protocol, and tool for assessment of patients’ chronic pain and coping. Therefore, it was necessary to investigate a method for providers to assess and intervene with patients to foster improved health outcomes and aid them in coping with chronic pain. The Coping Strategies Questionnaire (CSQ) was developed, refined, and decreased from the original 50-item questionnaire to a more ‘user-friendly’ 14-item version. The shorter CSQ has been proven to be a valid and reliable tool in assessing coping strategies for patients with chronic pain. Consistent results in identifying patients who have low to poor coping strategies have been produced when using the refined 14-item CSQ. The goals and objectives of this quality improvement project were to pilot the use of the CSQ to assess patients with chronic pain within a targeted primary care practice and to offer providers a sustainable use tool that identifies patients’ positive and negative coping mechanisms. With the CSQ data in hand providers were able to intervene when patients demonstrated ineffective coping. This paper describes the results and success of the intervention including providers’ comments and commitment to sustainable use of the CSQ

Measurement Invariance, Entropy, and Probability

We show that the natural scaling of measurement for a particular problem defines the most likely probability distribution of observations taken from that measurement scale. Our approach extends the method of maximum entropy to use measurement scale as a type of information constraint. We argue that a very common measurement scale is linear at small magnitudes grading into logarithmic at large magnitudes, leading to observations that often follow Student's probability distribution which has a Gaussian shape for small fluctuations from the mean and a power law shape for large fluctuations from the mean. An inverse scaling often arises in which measures naturally grade from logarithmic to linear as one moves from small to large magnitudes, leading to observations that often follow a gamma probability distribution. A gamma distribution has a power law shape for small magnitudes and an exponential shape for large magnitudes. The two measurement scales are natural inverses connected by the Laplace integral transform. This inversion connects the two major scaling patterns commonly found in nature. We also show that superstatistics is a special case of an integral transform, and thus can be understood as a particular way in which to change the scale of measurement. Incorporating information about measurement scale into maximum entropy provides a general approach to the relations between measurement, information and probability

Validating and verifying AI systems

AI systems will only fulfil their promise for society if they can be relied upon. This means that the role and task of the system must be properly formulated, and that the system must be bug-free, based on properly representative data, can cope with anomalies and data quality issues, and that its output is sufficiently accurate for the task

A tool for subjective and interactive visual data exploration

We present SIDE, a tool for Subjective and Interactive Visual Data Exploration, which lets users explore high dimensional data via subjectively informative 2D data visualizations. Many existing visual analytics tools are either restricted to specific problems and domains or they aim to find visualizations that align with user’s belief about the data. In contrast, our generic tool computes data visualizations that are surprising given a user’s current understanding of the data. The user’s belief state is represented as a set of projection tiles. Hence, this user-awareness offers users an efficient way to interactively explore yet-unknown features of complex high dimensional datasets