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The solidification of a binary alloy results in the formation of a porous mushy layer, within which spontaneous localisation of fluid flow can lead to the emergence of features over a range of spatial scales. We describe a finite volume method for simulating binary alloy solidification in two dimensions with local mesh refinement in space and time. The coupled heat, solute, and mass transport is described using an enthalpy method with flow described by a Darcy-Brinkman equation for flow across porous and liquid regions. The resulting equations are solved on a hierarchy of block-structured adaptive grids. A projection method is used to compute the fluid velocity, whilst the viscous and nonlinear diffusive terms are calculated using a semi-implicit scheme. A series of synchronization steps ensure that the scheme is flux-conservative and correct for errors that arise at the boundaries between different levels of refinement. We also develop a corresponding method using Darcy's law for flow in a porous medium/narrow Hele-Shaw cell. We demonstrate the accuracy and efficiency of our method using established benchmarks for solidification without flow and convection in a fixed porous medium, along with convergence tests for the fully coupled code. Finally, we demonstrate the ability of our method to simulate transient mushy layer growth with narrow liquid channels which evolve over time.

Many natural, engineered and social systems can be represented using the framework of a layered network, where each layer captures a different type of interaction between the same set of nodes. The study of such multiplex networks is a vibrant area of research. Yet, understanding how to quantify the correlations present between pairs of layers, and more so present in their co-evolution, is lacking. Such methods would enable us to address fundamental questions involving issues such as function, redundancy, and potential disruptions. Here, we show first how the edge set of a multiplex network can be used to construct an estimator of a joint probability distribution describing edge existence over all layers. We then adapt an information-theoretic measure of general correlation called the conditional mutual information, which uses the estimated joint probability distribution, to quantify the pairwise correlations present between layers. The pairwise comparisons can also be temporal, allowing us to identify if knowledge of a certain layer can provide additional information about the evolution of another layer. We analyse datasets from three distinct domains-economic, political, and airline networks-to demonstrate how pairwise correlation in structure and dynamical evolution between layers can be identified and show that anomalies can serve as potential indicators of major events such as shocks.

The partial information decomposition (PID) is perhaps the leading proposal for resolving information shared between a set of sources and a target into redundant, synergistic, and unique constituents. Unfortunately, the PID framework has been hindered by a lack of a generally agreed-upon, multivariate method of quantifying the constituents. Here, we take a step toward rectifying this by developing a decomposition based on a new method that quantifies unique information. We first develop a broadly applicable method - the dependency decomposition - that delineates how statistical dependencies influence the structure of a joint distribution. The dependency decomposition then allows us to define a measure of the information about a target that can be uniquely attributed to a particular source as the least amount which the source-target statistical dependency can influence the information shared between the sources and the target. The result is the first measure that satisfies the core axioms of the PID framework while not satisfying the Blackwell relation, which depends on a particular interpretation of how the variables are related. This makes a key step forward to a practical PID.

© 2017 by the authors. Collective organization in matter plays a significant role in its expressed physical properties. Typically, it is detected via an order parameter, appropriately defined for each given system's observed emergent patterns. Recent developments in information theory, however, suggest quantifying collective organization in a system- and phenomenon-agnostic way: decomposing the system's thermodynamic entropy density into a localized entropy, that is solely contained in the dynamics at a single location, and a bound entropy, that is stored in space as domains, clusters, excitations, or other emergent structures. As a concrete demonstration, we compute this decomposition and related quantities explicitly for the nearest-neighbor Ising model on the 1D chain, on the Bethe lattice with coordination number k = 3, and on the 2D square lattice, illustrating its generality and the functional insights it gives near and away from phase transitions. In particular, we consider the roles that different spin motifs play (in cluster bulk, cluster edges, and the like) and how these affect the dependencies between spins.

The hallmark of deterministic chaos is that it creates information - the rate being given by the Kolmogorov-Sinai metric entropy. Since its introduction half a century ago, the metric entropy has been used as a unitary quantity to measure a system's intrinsic unpredictability. Here, we show that it naturally decomposes into two structurally meaningful components: A portion of the created information - the ephemeral information - is forgotten and a portion - the bound information - is remembered. The bound information is a new kind of intrinsic computation that differs fundamentally from information creation: it measures the rate of active information storage. We show that it can be directly and accurately calculated via symbolic dynamics, revealing a hitherto unknown richness in how dynamical systems compute. © 2014 Elsevier B.V.

The introduction of the partial information decomposition generated a flurry of proposals for defining an intersection information that quantifies how much of "the same information" two or more random variables specify about a target random variable. As of yet, none is wholly satisfactory. A palatable measure of intersection information would provide a principled way to quantify slippery concepts, such as synergy. Here, we introduce an intersection information measure based on the Gács-Körner common random variable that is the first to satisfy the coveted target monotonicity property. Our measure is imperfect, too, and we suggest directions for improvement. © 2014 by the authors.

Abstract Background Type 2 diabetes is rapidly growing as a proportion of the disease burden in Australia as elsewhere. This study addresses the cost effectiveness of an integrated approach to assisting general practitioners (GPs) with diabetes management. This approach uses a centralized database of clinical data of an Australian Division of General Practice (a network of GPs) to co-ordinate care according to national guidelines. Methods Long term outcomes for patients in the program were derived using clinical parameters after 5 years of program participation, and the United Kingdom Prospective Diabetes Study (UKPDS) Outcomes Model, to project outcomes for 40 years from the time of diagnosis and from 5 years post-diagnosis. Cost information was obtained from a range of sources. While program costs are directly available, and costs of complications can be estimated from the UKPDS model, other costs are estimated by comparing costs in the Division with average costs across the state or the nation. The outcome and cost measures are used derive incremental cost-effectiveness ratios. Results The clinical data show that the program is effective in the short term, with improvement or no statistical difference in most clinical measures over 5 years. Average HbA1c levels increased by less than expected over the 5 year period. While the program is estimated to generate treatment cost savings, overall net costs are positive. However, the program led to projected improvements in expected life years and Quality Adjusted Life Expectancy (QALE), with incremental cost effectiveness ratios of $A8,106 per life-year saved and $A9,730 per year of QALE gained. Conclusions The combination of an established model of diabetes progression and generally available data has provided an opportunity to establish robust methods of testing the cost effectiveness of a program for which a formal control group was not available. Based on this methodology, integrated health care delivery provided by a network of GPs improved health outcomes of type 2 diabetics with acceptable cost effectiveness, which suggests that similar outcomes may be obtained elsewhere.

Background Recent avoidable mortality trends in Australia suggest that health care has made a substantial contribution to reducing mortality. This study investigates if the benefits of health care have been distributed equally by comparing declines in avoidable with non-avoidable mortality over time by socioeconomic status (SES). Methods We calculated avoidable and non-avoidable mortality rates in Australia by small areas for 1986, 1991, 1997 and 2002. We performed pooled cross-sectional trend analysis of indirectly standardized mortality rates by SES and year, modelling using Poisson regression with over-dispersion. Socioeconomic inequalities were quantified using the relative (RII) and slope (SII) index of inequality. Results The annual percentage decline in avoidable mortality at the higher end of the socioeconomic continuum (5.0%; 95% CI: 4.7–5.4%) was larger than at the lower end (3.5%; 3.2–3.8%), with increasing relative inequality between 1986 (RII = 1.54; 1.46–1.63) and 2002 (RII = 2.00; 1.95–2.06), greater than that in non-avoidable mortality (P = 0.036). In absolute terms, avoidable deaths fell annually by 7.4 (6.9–7.8) and 8.4 (7.9–8.9) deaths per 100?000?at the higher and lower end of the spectrum, respectively, with absolute inequality decreasing between 1986 (SII = 97.8; 87.6–107.9) and 2002 (SII = 81.5; 74.6–88.5). Conclusions Health care has contributed to decreasing the absolute SES mortality gap. However, advantaged people have obtained a disproportionate benefit of health care, contributing to widening relative health inequalities. A universal heath care system does not guarantee equality in health-care-related outcomes. [ABSTRACT FROM AUTHOR]

Research examining the impact of Focus of Attention (FoA) has consistently demonstrated a benefit of adopting an external FoA over an internal FoA across a variety of sports and other domains. However, FoA research has yet to be applied within the rapidly growing world of competitive gaming. This study investigated whether an external FoA provided benefits over an internal FoA for aiming performance in First-Person Shooter (FPS) videogames, using the aim-training game Aim Lab. The study explored whether the level of participants' previous experience of FPS games impacted any effect, as few studies have investigated this directly. Participants with high (N = 20) and low (N = 17) FPS experience who had a minimum of 200 hours FPS experience were selected for the study. The participants were instructed before each set of ten trials to either attend to their wrist/arm movements (internal FoA) or to the target (external FoA). There was no significant main effect of FoA on performance and no significant interaction between FoA and experience. In contrast to findings in other studies, an external FoA provided no performance benefits over an internal FoA in the FPS game Aim Lab. We discuss methodological issues related to the measures used and suggest avenues for future research with a view to improving understanding of putative underlying mechanisms for FoA effects., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Lamers James, O'Connor. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Genetic testing has increased the number of variants identified in disease genes, but the diagnostic utility is limited by lack of understanding variant function. CARD11 encodes an adaptor protein that expresses dominant-negative and gain-of-function variants associated with distinct immunodeficiencies. Here, we used a "cloning-free" saturation genome editing approach in a diploid cell line to simultaneously score 2,542 variants for decreased or increased function in the region of CARD11 associated with immunodeficiency. We also described an exon-skipping mechanism for CARD11 dominant-negative activity. The classification of reported clinical variants was sensitive (94.6%) and specific (88.9%), which rendered the data immediately useful for interpretation of seven coding and splicing variants implicated in immunodeficiency found in our clinic. This approach is generalizable for variant interpretation in many other clinically actionable genes, in any relevant cell type., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

The Wnt/ß-catenin signaling pathway controls important cellular events during development and often contributes to disease when dysregulated. Using high throughput screening we have identified a new small molecule inhibitor of Wnt/ß-catenin signaling, WIKI4. WIKI4 inhibits expression of ß-catenin target genes and cellular responses to Wnt/ß-catenin signaling in cancer cell lines as well as in human embryonic stem cells. Furthermore, we demonstrate that WIKI4 mediates its effects on Wnt/ß-catenin signaling by inhibiting the enzymatic activity of TNKS2, a regulator of AXIN ubiquitylation and degradation. While TNKS has previously been shown to be the target of small molecule inhibitors of Wnt/ß-catenin signaling, WIKI4 is structurally distinct from previously identified TNKS inhibitors.