Self-evaluation of decision-making: A general Bayesian framework for metacognitive computation.

People are often aware of their mistakes, and report levels of confidence in their choices that correlate with objective performance. These metacognitive assessments of decision quality are important for the guidance of behavior, particularly when external feedback is absent or sporadic. However, a computational framework that accounts for both confidence and error detection is lacking. In addition, accounts of dissociations between performance and metacognition have often relied on ad hoc assumptions, precluding a unified account of intact and impaired self-evaluation. Here we present a general Bayesian framework in which self-evaluation is cast as a "second-order" inference on a coupled but distinct decision system, computationally equivalent to inferring the performance of another actor. Second-order computation may ensue whenever there is a separation between internal states supporting decisions and confidence estimates over space and/or time. We contrast second-order computation against simpler first-order models in which the same internal state supports both decisions and confidence estimates. Through simulations we show that second-order computation provides a unified account of different types of self-evaluation often considered in separate literatures, such as confidence and error detection, and generates novel predictions about the contribution of one's own actions to metacognitive judgments. In addition, the model provides insight into why subjects' metacognition may sometimes be better or worse than task performance. We suggest that second-order computation may underpin self-evaluative judgments across a range of domains. (PsycINFO Database Recor

Design of Electronic Learning Courses for IT Students Considering the Dominant Learning Style

Methods of using e-learning courses to support learning activities of students at higher educational institutions is the subject of a large number of scientific and educational studies. In particular, much attention is paid to the structure, content and format of educational resources of e-learning courses. However, the problem of dependency of their efficiency on the learning styles of students still needs to be further researched. This paper deals with the learning styles characteristic for IT students on the basis of determining their leading modality; designs the structure of e-learning courses for IT students considering the dominating learning styles and provides the results of pedagogical experiment by measuring the performance and satisfaction in learning activity

A Systems Biology Approach to Drug Targets in Pseudomonas aeruginosa Biofilm

Antibiotic resistance is an increasing problem in the health care system and we are in a constant race with evolving bacteria. Biofilm-associated growth is thought to play a key role in bacterial adaptability and antibiotic resistance. We employed a systems biology approach to identify candidate drug targets for biofilm-associated bacteria by imitating specific microenvironments found in microbial communities associated with biofilm formation. A previously reconstructed metabolic model of Pseudomonas aeruginosa (PA) was used to study the effect of gene deletion on bacterial growth in planktonic and biofilm-like environmental conditions. A set of 26 genes essential in both conditions was identified. Moreover, these genes have no homology with any human gene. While none of these genes were essential in only one of the conditions, we found condition-dependent genes, which could be used to slow growth specifically in biofilm-associated PA. Furthermore, we performed a double gene deletion study and obtained 17 combinations consisting of 21 different genes, which were conditionally essential. While most of the difference in double essential gene sets could be explained by different medium composition found in biofilm-like and planktonic conditions, we observed a clear effect of changes in oxygen availability on the growth performance. Eight gene pairs were found to be synthetic lethal in oxygen-limited conditions. These gene sets may serve as novel metabolic drug targets to combat particularly biofilm-associated PA. Taken together, this study demonstrates that metabolic modeling of human pathogens can be used to identify oxygen-sensitive drug targets and thus, that this systems biology approach represents a powerful tool to identify novel candidate antibiotic targets

Conserved presence of G-quadruplex forming sequences in the Long Terminal Repeat Promoter of Lentiviruses

G-quadruplexes (G4s) are secondary structures of nucleic acids that epigenetically regulate cellular processes. In the human immunodeficiency lentivirus 1 (HIV-1), dynamic G4s are located in the unique viral LTR promoter. Folding of HIV-1 LTR G4s inhibits viral transcription; stabilization by G4 ligands intensifies this effect. Cellular proteins modulate viral transcription by inducing/unfolding LTR G4s. We here expanded our investigation on the presence of LTR G4s to all lentiviruses. G4s in the 5'-LTR U3 region were completely conserved in primate lentiviruses. A G4 was also present in a cattle-infecting lentivirus. All other non-primate lentiviruses displayed hints of less stable G4s. In primate lentiviruses, the possibility to fold into G4s was highly conserved among strains. LTR G4 sequences were very similar among phylogenetically related primate viruses, while they increasingly differed in viruses that diverged early from a common ancestor. A strong correlation between primate lentivirus LTR G4s and Sp1/NF\u3baB binding sites was found. All LTR G4s folded: their complexity was assessed by polymerase stop assay. Our data support a role of the lentiviruses 5'-LTR G4 region as control centre of viral transcription, where folding/unfolding of G4s and multiple recruitment of factors based on both sequence and structure may take place

Dual Use of Veterans Health Administration and Indian Health Service: Healthcare Provider and Patient Perspectives

Many American Indian and Alaska Native veterans are eligible for healthcare from Veterans Health Administration (VHA) and from Indian Health Service (IHS). These organizations executed a Memorandum of Understanding in 2003 to share resources, but little was known about how they collaborated to deliver healthcare. To describe dual use from the stakeholders’ perspectives, including incentives that encourage cross-use, which organization’s primary care is “primary,” and the potential problems and opportunities for care coordination across VHA and IHS. VHA healthcare staff, IHS healthcare staff and American Indian and Alaska Native veterans. Focus groups were conducted using a semi-structured guide. A software-assisted text analysis was performed using grounded theory to develop analytic categories. Dual use was driven by variation in institutional resources, leading patients to actively manage health-seeking behaviors and IHS providers to make ad hoc recommendations for veterans to seek care at VHA. IHS was the “primary” primary care for dual users. There was little coordination between VHA and IHS resulting in delays and treatment conflicts, but all stakeholder groups welcomed future collaboration. Fostering closer alignment between VHA and IHS would reduce care fragmentation and improve accountability for patient care

A scalable algorithm to explore the Gibbs energy landscape of genome-scale metabolic networks

The integration of various types of genomic data into predictive models of biological networks is one of the main challenges currently faced by computational biology. Constraint-based models in particular play a key role in the attempt to obtain a quantitative understanding of cellular metabolism at genome scale. In essence, their goal is to frame the metabolic capabilities of an organism based on minimal assumptions that describe the steady states of the underlying reaction network via suitable stoichiometric constraints, specifically mass balance and energy balance (i.e. thermodynamic feasibility). The implementation of these requirements to generate viable configurations of reaction fluxes and/or to test given flux profiles for thermodynamic feasibility can however prove to be computationally intensive. We propose here a fast and scalable stoichiometry-based method to explore the Gibbs energy landscape of a biochemical network at steady state. The method is applied to the problem of reconstructing the Gibbs energy landscape underlying metabolic activity in the human red blood cell, and to that of identifying and removing thermodynamically infeasible reaction cycles in the Escherichia coli metabolic network (iAF1260). In the former case, we produce consistent predictions for chemical potentials (or log-concentrations) of intracellular metabolites; in the latter, we identify a restricted set of loops (23 in total) in the periplasmic and cytoplasmic core as the origin of thermodynamic infeasibility in a large sample ($10^6$) of flux configurations generated randomly and compatibly with the prior information available on reaction reversibility.Comment: 11 pages, 6 figures, 1 table; for associated supporting material see http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.100256

Superconductivity at 5 K in potassium doped phenanthrene

Organic materials are believed to be potential superconductor with high transition temperature (TC). Organic superconductors mainly have two families: the quasi-one dimensional (TMTSF)2X and two dimensional (BEDT-TTF)2X (Ref. 1 and 2), in which TMTSF is tetramethyltetraselenafulvalene (C10H12Se4) and BEDT-TTF or "ET" is bis(ethylenedithio)tetrathiafulvalene (C10H8S8). One key feature of the organic superconductors is that they have {\pi}-molecular orbitals, and the {\pi}-electron can delocalize throughout the crystal giving rise to metallic conductivity due to a {\pi}-orbital overlap between adjacent molecules. The introduction of charge into C60 solids and graphites with {\pi}-electron networks by doping to realize superconductivity has been extensively reported3,4. Very recently, superconductivity in alkali-metal doped picene with {\pi}-electron networks was reported5. Here we report the discovery of superconductivity in potassium doped Phenanthrene with TC~5 K. TC increases with increasing pressure, and the pressure of 1 GPa leads to an increase of 20% in TC, suggesting that the potassium doped phenanthrene shows unconventional superconductivity. Both phenanthrene and picene are polycyclic aromatic hydrocarbons, and contain three and five fused benzene rings, respectively. The ribbon of fused benzene rings is part of graphene. Therefore, the discovery of superconductivity in K3Phenanthrene produces a novel broad class of superconductors consisting of fused hydrocarbon benzene rings with {\pi}-electron networks. The fact that TC increases from 5 K for KxPhenanthrene with three benzene rings to 18 K for Kxpicene with five benzene rings suggests that such organic hydrocarbons with long benzene rings is potential superconductor with high TC.Comment: 20 pages, 3 figures, one supplementary information. submitted to Nature Communication

The learning styles neuromyth:when the same term means different things to different teachers

Alexia Barrable - ORCID: 0000-0002-5352-8330 https://orcid.org/0000-0002-5352-8330Although learning styles (LS) have been recognised as a neuromyth, they remain a virtual truism within education. A point of concern is that the term LS has been used within theories that describe them using completely different notions and categorisations. This is the first empirical study to investigate education professionals’ conceptualisation, as well as means of identifying and implementing LS in their classroom. A sample of 123 education professionals were administered a questionnaire consisting both closed- and open-ended questions. Responses were analysed using thematic analysis. LS were found to be mainly conceptualised within the Visual-Auditory-(Reading)-Kinaesthetic (VAK/VARK) framework, as well as Gardner’s multiple intelligences. Moreover, a lot of education professionals confused theories of learning (e.g., behavioural or cognitive theories) with LS. In terms of identifying LS, educators reported using a variety of methods, spanning from observation and everyday contact to the use of tests. The ways LS were implemented in the classroom were numerous, comprising various teaching aids, participatory techniques and motor activities. Overall, we argue that the extended use of the term LS gives the illusion of a consensus amongst educators, when a closer examination reveals that the term LS is conceptualised, identified and implemented idiosyncratically by different individuals. This study aims to be of use to pre-service and in-service teacher educators in their effort to debunk the neuromyth of LS and replace it with evidence-based practices.https://doi.org/10.1007/s10212-020-00485-236pubpub

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation