Applying an Error Taxonomy to Examine Inexperienced Spreadsheet Users’ Planning and Execution Errors

This paper presents preliminary findings of an application of the Panko-Aurigemma (2010) error taxonomy to errors generated in a spreadsheet training task. Data from 11 inexperienced trainees were obtained on two spreadsheet training tasks of different complexity and scored by two judges. High levels of inter-rater reliability were obtained for a refined planning and execution error classification. Preliminary findings relating to the likely processes underlying task completion indicate that trainees make more execution than planning errors on easy tasks. Negative associations were found between the frequency of execution and planning errors and task performance when completing easy tasks. For hard tasks, we found a negative association between task performance and frequency of execution errors; however, the association between the number of planning errors and performance was positive. These findings point to the utility of examining error types in IS training strategy research

When should we prefer Decision Transformers for Offline Reinforcement Learning?

Offline reinforcement learning (RL) allows agents to learn effective, return-maximizing policies from a static dataset. Three popular algorithms for offline RL are Conservative Q-Learning (CQL), Behavior Cloning (BC), and Decision Transformer (DT), from the class of Q-Learning, Imitation Learning, and Sequence Modeling respectively. A key open question is: which algorithm is preferred under what conditions? We study this question empirically by exploring the performance of these algorithms across the commonly used D4RL and Robomimic benchmarks. We design targeted experiments to understand their behavior concerning data suboptimality, task complexity, and stochasticity. Our key findings are: (1) DT requires more data than CQL to learn competitive policies but is more robust; (2) DT is a substantially better choice than both CQL and BC in sparse-reward and low-quality data settings; (3) DT and BC are preferable as task horizon increases, or when data is obtained from human demonstrators; and (4) CQL excels in situations characterized by the combination of high stochasticity and low data quality. We also investigate architectural choices and scaling trends for DT on Atari and D4RL and make design/scaling recommendations. We find that scaling the amount of data for DT by 5x gives a 2.5x average score improvement on Atari.Comment: International Conference on Learning Representations (ICLR) 202

Early coronary angiography and survival after out-of-hospital cardiac arrest: a systematic review and meta-analysis

Background: Although acute myocardial infarction is a common cause of out-of-hospital cardiac arrest (OHCA), the role of early coronary angiography in OHCA remains uncertain. We conducted a meta-analysis of observational studies to determine the association of early coronary angiography with survival in OHCA. Methods: We searched multiple electronic databases for published studies on early coronary angiography in OHCA between 1 January 1990 and 18 January 2017. Studies were included if (1) restricted to only OHCA, (2) included an exposure group that underwent early coronary angiography within 1  day of arrest onset and a concurrent control group that did not undergo early coronary angiography, and (3) reported survival outcomes. We used a random-effects model to obtain pooled OR. I2 statistics and Cochran's Q test were used to determine between-study heterogeneity. Results: A total of 17 studies with 14 972 patients were included, of whom 6424 (44%) received early coronary angiography. Early coronary angiography was associated with higher odds of survival (pooled OR 2.54 (95% CI 1.94 to 3.33)) and survival with favourable neurological outcome (pooled OR 2.37 (95%  CI 1.71 to 3.28)). However, there was substantial heterogeneity in our pooled estimate (I2=88%  and p value for Cochran's test <0.0001 for both outcomes). The large heterogeneity in pooled estimates was reduced after including adjusted estimates when available, and was explained by differences in methodological rigour and characteristics of included studies. Conclusion: Among patients resuscitated from OHCA, early coronary angiography is associated with increased survival to discharge and favourable neurological outcome

The Classical Pink-Eyed Dilution Mutation Affects Angiogenic Responsiveness

Angiogenesis is the process by which new blood vessels are formed from existing vessels. Mammalian populations, including humans and mice, harbor genetic variations that alter angiogenesis. Angiogenesis-regulating gene variants can result in increased susceptibility to multiple angiogenesis-dependent diseases in humans. Our efforts to dissect the complexity of the genetic diversity that regulates angiogenesis have used laboratory animals due to the availability of genome sequence for many species and the ability to perform high volume controlled breeding. Using the murine corneal micropocket assay, we have observed more than ten-fold difference in angiogenic responsiveness among various mouse strains. This degree of difference is observed with either bFGF or VEGF induced corneal neovascularization. Ongoing mapping studies have identified multiple loci that affect angiogenic responsiveness in several mouse models. In this study, we used F2 intercrosses between C57BL/6J and the 129 substrains 129P1/ReJ and 129P3/J, as well as the SJL/J strain, where we have identified new QTLs that affect angiogenic responsiveness. In the case of AngFq5, on chromosome 7, congenic animals were used to confirm the existence of this locus and subcongenic animals, combined with a haplotype-based mapping approach that identified the pink-eyed dilution mutation as a candidate polymorphism to explain AngFq5. The ability of mutations in the pink-eyed dilution gene to affect angiogenic response was demonstrated using the p-J allele at the same locus. Using this allele, we demonstrate that pink-eyed dilution mutations in Oca2 can affect both bFGF and VEGF-induced corneal angiogenesis

A qualitative analysis of smokers’ perceptions about lung cancer screening

Background In 2013, the US Preventive Services Task Force (USPSTF) began recommending lung cancer screening for high risk smokers aged 55–80 years using low-dose computed tomography (CT) scan. In light of these updated recommendations, there is a need to understand smokers’ knowledge of and experiences with lung cancer screening in order to inform the design of patient education and tobacco cessation programs. The purpose of this study is to describe results of a qualitative study examining smokers’ perceptions around lung cancer screening tests. Methods In 2009, prior to the release of the updated USPSTF recommendations, we conducted 12 120-min, gender-specific focus groups with 105 current smokers in Charlotte, North Carolina and Cincinnati, Ohio. Focus group facilitators asked participants about their experience with three lung cancer screening tests, including CT scan, chest x-ray, and sputum cytology. Focus group transcripts were transcribed and qualitatively analyzed using constant comparative methods. Results Participants were 41–67 years-old, with a mean smoking history of 38.9 pack-years. Overall, 34.3% would meet the USPSTF’s current eligibility criteria for screening. Most participants were unaware of all three lung cancer screening tests. The few participants who had been screened recalled limited information about the test. Nevertheless, many participants expressed a strong desire to pursue lung cancer screening. Using the social ecological model for health promotion, we identified potential barriers to lung cancer screening at the 1) health care system level (cost of procedure, confusion around results), 2) cultural level (fatalistic beliefs, distrust of medical system), and 3) individual level (lack of knowledge, denial of risk, concerns about the procedure). Although this study was conducted prior to the updated USPSTF recommendations, these findings provide a baseline for future studies examining smokers’ perceptions of lung cancer screening. Conclusion We recommend clear and patient-friendly educational tools to improve patient understanding of screening risks and benefits and the use of best practices to help smokers quit. Further qualitative studies are needed to assess changes in smokers’ perceptions as lung cancer screening with CT scan becomes more widely used in community practice

Prediction of MET Overexpression in Non-Small Cell Lung Adenocarcinomas from Hematoxylin and Eosin Images

MET protein overexpression is a targetable event in non-small cell lung cancer (NSCLC) and is the subject of active drug development. Challenges in identifying patients for these therapies include lack of access to validated testing, such as standardized immunohistochemistry (IHC) assessment, and consumption of valuable tissue for a single gene/protein assay. Development of pre-screening algorithms using routinely available digitized hematoxylin and eosin (H&E)-stained slides to predict MET overexpression could promote testing for those who will benefit most. While assessment of MET expression using IHC is currently not routinely performed in NSCLC, next-generation sequencing is common and in some cases includes RNA expression panel testing. In this work, we leveraged a large database of matched H&E slides and RNA expression data to train a weakly supervised model to predict MET RNA overexpression directly from H&E images. This model was evaluated on an independent holdout test set of 300 over-expressed and 289 normal patients, demonstrating an ROC-AUC of 0.70 (95th percentile interval: 0.66 - 0.74) with stable performance characteristics across different patient clinical variables and robust to synthetic noise on the test set. These results suggest that H&E-based predictive models could be useful to prioritize patients for confirmatory testing of MET protein or MET gene expression status

Encouraging healthier grocery purchases online: a randomised controlled trial and lessons learned

Online supermarket platforms present an opportunity for encouraging healthier consumer purchases. A parallel, double-blind randomised controlled trial tested whether promoting healthier products (e.g. lower fat and lower calorie) on the Sainsbury's online supermarket platform would increase purchases of those products. Participants were Nectar loyalty membership scheme cardholders who shopped online with Sainsbury's between 20th September and 10th October 2017. Intervention arm customers saw advertisement banners and recipe ingredient lists containing healthier versions of the products presented in control arm banners and ingredient lists. The primary outcome measure was purchases of healthier products. Additional outcome measures were banner clicks, purchases of standard products, overall purchases and energy (kcal) purchased. Sample sizes were small due to customers navigating the website differently than expected. The intervention encouraged purchases of some promoted healthier products (spaghetti [B = 2.10, p < 0.001], spaghetti sauce [B = 2.06, p < 0.001], spaghetti cheese [B = 2.45, p = 0.001], sour cream [B = 2.52, p < 0.001], fajita wraps [B = 2.10, p < 0.001], fajita cheese [B = 1.19, p < 0.001], bakery aisle products (B = 3.05, p = 0.003) and cola aisle products [B = 0.97, p < 0.002]) but not others (spaghetti mince, or products in the yogurt and ice cream aisles). There was little evidence of effects on banner clicks and energy purchased. Small sample sizes may affect the robustness of these findings. We discuss the benefits of collaborating to share expertise and implement a trial in a live commercial environment, alongside key learnings for future collaborative research in similar contexts

Synchronous seasonality in the gut microbiota of wild mouse populations

The gut microbiome performs many important functions in mammalian hosts, with community composition shaping its functional role. However, the factors that drive individual microbiota variation in wild animals and to what extent these are predictable or idiosyncratic across populations remains poorly understood. Here, we use a multi-population dataset from a common rodent species (the wood mouse, Apodemus sylvaticus), to test whether a consistent “core” gut microbiota is identifiable in this species, and to what extent the predictors of microbiota variation are consistent across populations. Between 2014 and 2018 we used capture-mark-recapture and 16S rRNA profiling to intensively monitor two wild wood mouse populations and their gut microbiota, as well as characterising the microbiota from a laboratory-housed colony of the same species. Although the microbiota was broadly similar at high taxonomic levels, the two wild populations did not share a single bacterial amplicon sequence variant (ASV), despite being only 50km apart. Meanwhile, the laboratory-housed colony shared many ASVs with one of the wild populations from which it is thought to have been founded decades ago. Despite not sharing any ASVs, the two wild populations shared a phylogenetically more similar microbiota than either did with the colony, and the factors predicting compositional variation in each wild population were remarkably similar. We identified a strong and consistent pattern of seasonal microbiota restructuring that occurred at both sites, in all years, and within individual mice. While the microbiota was highly individualised, some seasonal convergence occurred in late winter/early spring. These findings reveal highly repeatable seasonal gut microbiota dynamics in multiple populations of this species, despite different taxa being involved. This provides a platform for future work to understand the drivers and functional implications of such predictable seasonal microbiome restructuring, including whether it might provide the host with adaptive seasonal phenotypic plasticity