The effect of time constraint on anticipation, decision making, and option generation in complex and dynamic environments

Researchers interested in performance in complex and dynamic situations have focused on how individuals predict their opponent(s) potential courses of action (i.e., during assessment) and generate potential options about how to respond (i.e., during intervention). When generating predictive options, previous research supports the use of cognitive mechanisms that are consistent with long-term working memory (LTWM) theory (Ericsson and Kintsch in Phychol Rev 102(2):211–245, 1995; Ward et al. in J Cogn Eng Decis Mak 7:231–254, 2013). However, when generating options about how to respond, the extant research supports the use of the take-the-first (TTF) heuristic (Johnson and Raab in Organ Behav Hum Decis Process 91:215–229, 2003). While these models provide possible explanations about how options are generated in situ, often under time pressure, few researchers have tested the claims of these models experimentally by explicitly manipulating time pressure. The current research investigates the effect of time constraint on option-generation behavior during the assessment and intervention phases of decision making by employing a modified version of an established option-generation task in soccer. The results provide additional support for the use of LTWM mechanisms during assessment across both time conditions. During the intervention phase, option-generation behavior appeared consistent with TTF, but only in the non-time-constrained condition. Counter to our expectations, the implementation of time constraint resulted in a shift toward the use of LTWM-type mechanisms during the intervention phase. Modifications to the cognitive-process level descriptions of decision making during intervention are proposed, and implications for training during both phases of decision making are discussed

Metformin and carotid intima media thickness in never smokers with type 1 diabetes: the REMOVAL trial

Aim: To determine whether metformin's effects on carotid artery intima-media thickness (cIMT) in type 1 diabetes differ according to smoking status. Methods: Regression model effect estimates for the effect of metformin versus placebo (double-blind) on carotid IMT were calculated as a subgroup analysis of the REMOVAL trial. Results: In 428 randomized participants (227 never-smokers, 201 ever-smokers), averaged mean carotid IMT progression (per year) was reduced by metformin versus placebo in never-smokers (−0.012 mm, 95% CI −0.021 to −0.002; p = .0137) but not in ever-smokers (0.003 mm, 95% CI −0.008 to 0.014; p = .5767); and similarly in non-current smokers (−0.008 mm, 95% CI −0.015 to −0.00001; p = .0497) but not in current smokers (0.013 mm, 95% CI −0.007 to 0.032; p = .1887). Three-way interaction terms (treatment*time*smoking status) were significant for never versus ever smoking (p = .0373, prespecified) and non-current versus current smoking (p = .0496, exploratory). Averaged maximal carotid IMT progression (per year) was reduced by metformin versus placebo in never-smokers (−0.020 mm, 95% CI −0.034 to −0.006; p = .0067) but not in ever-smokers (−0.006 mm, 95% CI −0.020 to 0.008; p = .4067), although this analysis was not supported by a significant three-way interaction term. Conclusions: This subgroup analysis of the REMOVAL trial provides additional support for a potentially wider role of adjunct metformin therapy in cardiovascular risk management in type 1 diabetes, particularly for individuals who have never smoked cigarettes

Universal scaling relation in high-temperature superconductors

Scaling laws express a systematic and universal simplicity among complex systems in nature. For example, such laws are of enormous significance in biology. Scaling relations are also important in the physical sciences. The seminal 1986 discovery of high transition-temperature (high-T_c) superconductivity in cuprate materials has sparked an intensive investigation of these and related complex oxides, yet the mechanism for superconductivity is still not agreed upon. In addition, no universal scaling law involving such fundamental properties as T_c and the superfluid density \rho_s, a quantity indicative of the number of charge carriers in the superconducting state, has been discovered. Here we demonstrate that the scaling relation \rho_s \propto \sigma_{dc} T_c, where the conductivity \sigma_{dc} characterizes the unidirectional, constant flow of electric charge carriers just above T_c, universally holds for a wide variety of materials and doping levels. This surprising unifying observation is likely to have important consequences for theories of high-T_c superconductivity.Comment: 11 pages, 2 figures, 2 table

Simple rules can guide whether land or ocean based conservation will best benefit marine ecosystems

Coastal marine ecosystems can be managed by actions undertaken both on the land and in the ocean. Quantifying and comparing the costs and benefits of actions in both realms is therefore necessary for efficient management. Here, we quantify the link between terrestrial sediment run-off and a downstream coastal marine ecosystem, and contrast the cost-effectiveness of marine and land-based conservation actions. We use a dynamic land- and sea-scape model to determine whether limited funds should be directed to one of four alternative conservation actions – protection on land, protection in the ocean, restoration on land, or restoration in the ocean – to maximise the extent of light-dependent marine benthic habitats, across decadal time-scales. We apply the model to a case study seagrass meadow in Australia. We find that marine restoration is the most cost-effective action over decadal time-scales in this system, based on a conservative estimate of the rate at which seagrass can expand into new habitat. The optimal decision will vary in different social-ecological contexts, but some basic information can guide optimal investments to counteract land and ocean based stressors: (1) marine restoration should be prioritised if the rates of marine ecosystem decline and expansion are similar and low; (2) marine protection should take precedence if the rate of marine ecosystem decline is high, or if the adjacent catchment is relatively intact and has a low rate of vegetation decline; (3) land-based actions are optimal when the ratio of marine ecosystem expansion to decline is >1.4, with terrestrial restoration typically the most cost effective; and (4) land protection should be prioritised if the catchment is relatively intact, but the rate of vegetation decline is high. These rules-of-thumb illustrate how cost-effective conservation outcomes for connected land-ocean systems can proceed without complex modelling

Infinite mixture-of-experts model for sparse survival regression with application to breast cancer

BACKGROUND: We present an infinite mixture-of-experts model to find an unknown number of sub-groups within a given patient cohort based on survival analysis. The effect of patient features on survival is modeled using the Cox's proportionality hazards model which yields a non-standard regression component. The model is able to find key explanatory factors (chosen from main effects and higher-order interactions) for each sub-group by enforcing sparsity on the regression coefficients via the Bayesian Group-Lasso. RESULTS: Simulated examples justify the need of such an elaborate framework for identifying sub-groups along with their key characteristics versus other simpler models. When applied to a breast-cancer dataset consisting of survival times and protein expression levels of patients, it results in identifying two distinct sub-groups with different survival patterns (low-risk and high-risk) along with the respective sets of compound markers. CONCLUSIONS: The unified framework presented here, combining elements of cluster and feature detection for survival analysis, is clearly a powerful tool for analyzing survival patterns within a patient group. The model also demonstrates the feasibility of analyzing complex interactions which can contribute to definition of novel prognostic compound markers

The inner centromere is a biomolecular condensate scaffolded by the chromosomal passenger complex.

The inner centromere is a region on every mitotic chromosome that enables specific biochemical reactions that underlie properties, such as the maintenance of cohesion, the regulation of kinetochores and the assembly of specialized chromatin, that can resist microtubule pulling forces. The chromosomal passenger complex (CPC) is abundantly localized to the inner centromeres and it is unclear whether it is involved in non-kinase activities that contribute to the generation of these unique chromatin properties. We find that the borealin subunit of the CPC drives phase separation of the CPC in vitro at concentrations that are below those found on the inner centromere. We also provide strong evidence that the CPC exists in a phase-separated state at the inner centromere. CPC phase separation is required for its inner-centromere localization and function during mitosis. We suggest that the CPC combines phase separation, kinase and histone code-reading activities to enable the formation of a chromatin body with unique biochemical activities at the inner centromere

The role of expertise in dynamic risk assessment: A reflection of the problem-solving strategies used by experienced fireground commanders

Although the concept of dynamic risk assessment has in recent times become more topical in the training manuals of most high risk domains, only a few empirical studies have reported how experts actually carry out this crucial task. The knowledge gap between research and practice in this area therefore calls for more empirical investigation within the naturalistic environment. In this paper, we present and discuss the problem solving strategies employed by sixteen experienced operational firefighters using a qualitative knowledge elicitation tool — the critical decision method. Findings revealed that dynamic risk assessment is not merely a process of weighing the risks of a proposed course of action against its benefits, but rather an experiential and pattern recognition process. The paper concludes by discussing the implications of designing training curriculum for the less experienced officers using the elicited expert knowledge

RNA secondary structure prediction from multi-aligned sequences

It has been well accepted that the RNA secondary structures of most functional non-coding RNAs (ncRNAs) are closely related to their functions and are conserved during evolution. Hence, prediction of conserved secondary structures from evolutionarily related sequences is one important task in RNA bioinformatics; the methods are useful not only to further functional analyses of ncRNAs but also to improve the accuracy of secondary structure predictions and to find novel functional RNAs from the genome. In this review, I focus on common secondary structure prediction from a given aligned RNA sequence, in which one secondary structure whose length is equal to that of the input alignment is predicted. I systematically review and classify existing tools and algorithms for the problem, by utilizing the information employed in the tools and by adopting a unified viewpoint based on maximum expected gain (MEG) estimators. I believe that this classification will allow a deeper understanding of each tool and provide users with useful information for selecting tools for common secondary structure predictions.Comment: A preprint of an invited review manuscript that will be published in a chapter of the book `Methods in Molecular Biology'. Note that this version of the manuscript may differ from the published versio

Intraventricular dyssynchrony in light chain amyloidosis: a new mechanism of systolic dysfunction assessed by 3-dimensional echocardiography

<p>Abstract</p> <p>Background</p> <p>Light chain amyloidosis (AL) is a rare but often fatal disease due to intractable heart failure. Amyloid deposition leads to diastolic dysfunction and often preserved ejection fraction. We hypothesize that AL is associated with regional systolic dyssynchrony. The aim is to compare left ventricular (LV) regional synchrony in AL subjects versus healthy controls using 16-segment dyssynchrony index measured from 3-dimension-al (3D) echocardiography.</p> <p>Methods</p> <p>Cardiac 3D echocardiography full volumes were acquired in 10 biopsy-proven AL subjects (60 ± 3 years, 5 females) and 10 healthy controls (52 ± 1 years, 5 females). The LV was subdivided into 16 segments and the time from end-diastole to the minimal systolic volume for each of the 16 segments was expressed as a percent of the cycle length. The standard deviations of these times provided a 16-segment dyssynchrony index (16-SD%). 16-SD% was compared between healthy and AL subjects.</p> <p>Results</p> <p>Left ventricular ejection fraction was comparable (control vs. AL: 62.4 ± 0.6 vs. 58.6 ± 2.8%, p = NS). 16-SD% was significantly higher in AL versus healthy subjects (5.93 ± 4.4 vs. 1.67 ± 0.87%, p = 0.003). 16-SD% correlated with left ventricular mass index (R 0.45, p = 0.04) but not to left ventricular ejection fraction.</p> <p>Conclusion</p> <p>Light chain amyloidosis is associated with left ventricular regional systolic dyssynchrony. Regional dyssynchrony may be an unrecognized mechanism of heart failure in AL subjects.</p