A view of Estimation of Distribution Algorithms through the lens of Expectation-Maximization

We show that a large class of Estimation of Distribution Algorithms, including, but not limited to, Covariance Matrix Adaption, can be written as a Monte Carlo Expectation-Maximization algorithm, and as exact EM in the limit of infinite samples. Because EM sits on a rigorous statistical foundation and has been thoroughly analyzed, this connection provides a new coherent framework with which to reason about EDAs

Contrastive losses as generalized models of global epistasis

Fitness functions map large combinatorial spaces of biological sequences to properties of interest. Inferring these multimodal functions from experimental data is a central task in modern protein engineering. Global epistasis models are an effective and physically-grounded class of models for estimating fitness functions from observed data. These models assume that a sparse latent function is transformed by a monotonic nonlinearity to emit measurable fitness. Here we demonstrate that minimizing contrastive loss functions, such as the Bradley-Terry loss, is a simple and flexible technique for extracting the sparse latent function implied by global epistasis. We argue by way of a fitness-epistasis uncertainty principle that the nonlinearities in global epistasis models can produce observed fitness functions that do not admit sparse representations, and thus may be inefficient to learn from observations when using a Mean Squared Error (MSE) loss (a common practice). We show that contrastive losses are able to accurately estimate a ranking function from limited data even in regimes where MSE is ineffective. We validate the practical utility of this insight by showing contrastive loss functions result in consistently improved performance on benchmark tasks

Improvements to the APBS biomolecular solvation software suite

The Adaptive Poisson-Boltzmann Solver (APBS) software was developed to solve the equations of continuum electrostatics for large biomolecular assemblages that has provided impact in the study of a broad range of chemical, biological, and biomedical applications. APBS addresses three key technology challenges for understanding solvation and electrostatics in biomedical applications: accurate and efficient models for biomolecular solvation and electrostatics, robust and scalable software for applying those theories to biomolecular systems, and mechanisms for sharing and analyzing biomolecular electrostatics data in the scientific community. To address new research applications and advancing computational capabilities, we have continually updated APBS and its suite of accompanying software since its release in 2001. In this manuscript, we discuss the models and capabilities that have recently been implemented within the APBS software package including: a Poisson-Boltzmann analytical and a semi-analytical solver, an optimized boundary element solver, a geometry-based geometric flow solvation model, a graph theory based algorithm for determining p$K_a$ values, and an improved web-based visualization tool for viewing electrostatics

Using conceptual metaphor and functional grammar to explore how language used in physics affects student learning

This paper introduces a theory about the role of language in learning physics. The theory is developed in the context of physics students' and physicists' talking and writing about the subject of quantum mechanics. We found that physicists' language encodes different varieties of analogical models through the use of grammar and conceptual metaphor. We hypothesize that students categorize concepts into ontological categories based on the grammatical structure of physicists' language. We also hypothesize that students over-extend and misapply conceptual metaphors in physicists' speech and writing. Using our theory, we will show how, in some cases, we can explain student difficulties in quantum mechanics as difficulties with language.Comment: Accepted for publication in Phys. Rev. ST:PE

Interleukin-1 regulates multiple atherogenic mechanisms in response to fat feeding

Background: Atherosclerosis is an inflammatory process that develops in individuals with known risk factors that include hypertension and hyperlipidaemia, influenced by diet. However, the interplay between diet, inflammatory mechanisms and vascular risk factors requires further research. We hypothesised that interleukin-1 (IL-1) signaling in the vessel wall would raise arterial blood pressure and promote atheroma. Methodology/Principal Findings: Apoe(-/-) and Apoe(-/-)/IL-1R1(-/-) mice were fed high fat diets for 8 weeks, and their blood pressure and atherosclerosis development measured. Apoe(-/-)/IL-R1(-/-) mice had a reduced blood pressure and significantly less atheroma than Apoe(-/-) mice. Selective loss of IL-1 signaling in the vessel wall by bone marrow transplantation also reduced plaque burden (p<0.05). This was associated with an IL-1 mediated loss of endothelium-dependent relaxation and an increase in vessel wall Nox 4. Inhibition of IL-1 restored endothelium-dependent vasodilatation and reduced levels of arterial oxidative stress. Conclusions/Significance: The IL-1 cytokine system links atherogenic environmental stimuli with arterial inflammation, oxidative stress, increased blood pressure and atherosclerosis. This is the first demonstration that inhibition of a single cytokine can block the rise in blood pressure in response to an environmental stimulus. IL-1 inhibition may have profound beneficial effects on atherogenesis in man

The Case for Dynamic Models of Learners' Ontologies in Physics

In a series of well-known papers, Chi and Slotta (Chi, 1992; Chi & Slotta, 1993; Chi, Slotta & de Leeuw, 1994; Slotta, Chi & Joram, 1995; Chi, 2005; Slotta & Chi, 2006) have contended that a reason for students' difficulties in learning physics is that they think about concepts as things rather than as processes, and that there is a significant barrier between these two ontological categories. We contest this view, arguing that expert and novice reasoning often and productively traverses ontological categories. We cite examples from everyday, classroom, and professional contexts to illustrate this. We agree with Chi and Slotta that instruction should attend to learners' ontologies; but we find these ontologies are better understood as dynamic and context-dependent, rather than as static constraints. To promote one ontological description in physics instruction, as suggested by Slotta and Chi, could undermine novices' access to productive cognitive resources they bring to their studies and inhibit their transition to the dynamic ontological flexibility required of experts.Comment: The Journal of the Learning Sciences (In Press

Lake-size dependency of wind shear and convection as controls on gas exchange

High-frequency physical observations from 40 temperate lakes were used to examine the relative contributions of wind shear (u*) and convection (w*) to turbulence in the surface mixed layer. Seasonal patterns of u* and w* were dissimilar; u* was often highest in the spring, while w * increased throughout the summer to a maximum in early fall. Convection was a larger mixed-layer turbulence source than wind shear (u */w*-1 for lakes* and w* differ in temporal pattern and magnitude across lakes, both convection and wind shear should be considered in future formulations of lake-air gas exchange, especially for small lakes. © 2012 by the American Geophysical Union.Jordan S. Read, David P. Hamilton, Ankur R. Desai, Kevin C. Rose, Sally MacIntyre, John D. Lenters, Robyn L. Smyth, Paul C. Hanson, Jonathan J. Cole, Peter A. Staehr, James A. Rusak, Donald C. Pierson, Justin D. Brookes, Alo Laas, and Chin H. W

Intravenous sildenafil citrate and post-cardiac surgery acute kidney injury: a double-blind, randomised, placebo-controlled trial

Clinical trial registration ISRCTN18386427. open access articleBackground This study assessed whether i.v. sildenafil citrate prevented acute kidney injury in at-risk patients undergoing cardiac surgery with cardiopulmonary bypass. Methods In a double-blind RCT, adults at increased risk of acute kidney injury undergoing cardiac surgery in a single UK tertiary centre were randomised to receive sildenafil citrate 12.5 mg kg−1 i.v. over 150 min or dextrose 5% at the commencement of surgery. The primary outcome was serum creatinine measured at six post-randomisation time points. The primary analysis used a linear mixed-effects model adjusted for the stratification variables, baseline estimated glomerular filtration rate, and surgical procedure. Secondary outcomes considered clinical events and potential disease mechanisms. Effect estimates were expressed as mean differences (MDs) or odds ratios with 95% confidence intervals. Results The analysis population comprised eligible randomised patients that underwent valve surgery or combined coronary artery bypass graft and valve surgery, with cardiopulmonary bypass, between May 2015 and June 2018. There were 60 subjects in the sildenafil group and 69 in the placebo control group. The difference between groups in creatinine concentration was not statistically significant (MD: 0.88 μmol L−1 [–5.82, 7.59]). There was a statistically significant increase in multiple organ dysfunction scores in the sildenafil group (MD: 0.54 [0.02, 1.07]; P=0.044). Secondary outcomes, and biomarkers of kidney injury, endothelial function, and inflammatory cell activation, were not significantly different between the groups. Conclusions These results do not support the use of i.v. sildenafil citrate for kidney protection in adult cardiac surgery