Two Different Mismatches: Integrating the Developmental and the Evolutionary-Mismatch Hypothesis

Evolutionary psychology aims to understand the origins of the human mind, including disease. Several theories about the origins of disease have been proposed. One concerns a developmental mismatch—a mismatch might occur at the individual level between the environment experienced during childhood and the environment the adult finds herself in, possibly resulting in disease. A second theory concerns the idea of an evolutionary mismatch—humans are adapted to ancestral conditions so they might now experience a mismatch with their modern environment, possibly resulting in disease. A third theory—differential susceptibility—outlines how genetic and epigenetic differences influence the extent to which humans are susceptible to rearing, including positive and negative experiences. Because of these differences, some individuals are more prone to develop disease than others. We review empirical studies that substantiate these theories and argue that an overarching theory that integrates these three lines into one provides a more accurate understanding of disease from an evolutionary perspective

An explorative philosophical study of envisaging the electrical energy infrastructure of the future

The electrical energy infrastructure is one of the key life-sustaining technologies of contemporary Western society. This infrastructure is extremely complex due to its size, its multifarious technologies, and its interweaving with societal structures. Smart grids are important in future infrastructure, yet extant literature does not adequately address this complexity. This paper argues that different elements of the philosophy of Dooyeweerd offer a key to understanding this intricate complexity more fundamentally. Key concepts are the ideas of normative practices, enkapsis (intertwinement) of practices, individuality structures, and ideals and basic beliefs. By developing these ideas in the context of smart grid engineering, our research contributes to philosophy of technology, philosophy of design, and philosophy of sustainability. It offers an ontological analysis of these infrastructures, pointing a direction to the development of workable infrastructures and supporting the transition to a sustainable society

Monte Carlo Renormalization of the 3-D Ising model: Analyticity and Convergence

We review the assumptions on which the Monte Carlo renormalization technique is based, in particular the analyticity of the block spin transformations. On this basis, we select an optimized Kadanoff blocking rule in combination with the simulation of a d=3 Ising model with reduced corrections to scaling. This is achieved by including interactions with second and third neighbors. As a consequence of the improved analyticity properties, this Monte Carlo renormalization method yields a fast convergence and a high accuracy. The results for the critical exponents are y_H=2.481(1) and y_T=1.585(3).Comment: RevTeX, 4 PostScript file

Linked shrinkage to improve estimation of interaction effects in regression models

We address a classical problem in statistics: adding two-way interaction terms to a regression model. As the covariate dimension increases quadratically, we develop an estimator that adapts well to this increase, while providing accurate estimates and appropriate inference. Existing strategies overcome the dimensionality problem by only allowing interactions between relevant main effects. Building on this philosophy, we implement a softer link between the two types of effects using a local shrinkage model. We empirically show that borrowing strength between the amount of shrinkage for main effects and their interactions can strongly improve estimation of the regression coefficients. Moreover, we evaluate the potential of the model for inference, which is notoriously hard for selection strategies. Large-scale cohort data are used to provide realistic illustrations and evaluations. Comparisons with other methods are provided. The evaluation of variable importance is not trivial in regression models with many interaction terms. Therefore, we derive a new analytical formula for the Shapley value, which enables rapid assessment of individual-specific variable importance scores and their uncertainties. Finally, while not targeting for prediction, we do show that our models can be very competitive to a more advanced machine learner, like random forest, even for fairly large sample sizes. The implementation of our method in RStan is fairly straightforward, allowing for adjustments to specific needs.Comment: 28 pages, 18 figure

The effect of population variation on the accuracy of sex estimates derived from basal occipital discriminant functions

Multiple discriminant functions that estimate sex from the dimensions of the basal occipital have been published. However, as there is limited exploration of basal dimension variation between groups, the accuracy of these functions when applied to archaeological material is unknown. This study compares basal dimensions between four known sex-at-death post-medieval European samples and explores how metric differences impact on the accuracy of sex assessment discriminant functions. Published data from St Bride’s, London (n = 146) and the Georges Olivier collection, Paris (n = 68) were compared with new data from the eighteenth to nineteenth century Dutch Middenbeemster sample (n = 74) and the early twentieth century Rainer sample, Romania (n = 282) using independent t tests. The Middenbeemster and Rainer data were substituted into six published discriminant functions derived from the St Bride’s and the Georges Olivier samples, and the results were compared to their known sex. Multiple statistically significant differences were found between the four groups. Of the six discriminant functions tested, five failed to reach the published accuracy and fell below chance. In addition, even where the samples were statistically comparable in means, trends for difference also impacted the accuracy of discriminant functions. Enough variation in basal occipital dimensions existed in the European groups to decrease the accuracy of sex estimation discriminant functions to unusable. Possible inter-observer error, varying genetic, socioeconomic, and geographical factors are likely causes of dimension variation. This research further highlights the dangers of using sex estimation discriminant functions on samples that differ to the original derivative population and demonstrates the need for more rigorous testing

Preparation and Supramolecular Recognition of Multivalent Peptide-Polysaccharide Conjugates by Cucurbit[8]uril in Hydrogel Formation.

Supramolecular hydrogels were fabricated by physically cross-linking phenylalanine functionalized polysaccharides with cucurbit[8]uril in water. We report a facile 2-step method of functionalization of the polysaccharides hyaluronic acid (HA), carboxymethyl cellulose (CMC), hydroxyethyl cellulose (HEC), and guar with the dipeptide Phe-Cys. Addition of cucurbit[8]uril to the functional polysaccharides initiated physical cross-linking on account of strong 1:2 "homoternary" complexes with the pendant Phe residues. In particular, HA and CMC based soft hydrogels displayed impressive viscoelastic behavior which was characterized using rheology, demonstrating accessibility to an array of material properties which would find broad applicability in many fields.M.J.R. thanks the University of Cambridge Chemical Biology and Molecular Medicine PhD Training Programme for funding. OAS thanks ERC Starting Investigator Grant (ASPiRe). The authors would also like to thank Silvia Sonzini for her assistance with collecting ITC data.This is the author accepted manuscript. The final version is available from ACS via http://dx.doi.org/10.1021/acs.biomac.5b0068

SUE: A Special Purpose Computer for Spin Glass Models

The use of last generation Programmable Electronic Components makes possible the construction of very powerful and competitive special purpose computers. We have designed, constructed and tested a three-dimensional Spin Glass model dedicated machine, which consists of 12 identical boards. Each single board can simulate 8 different systems, updating all the systems at every clock cycle. The update speed of the whole machine is 217ps/spin with 48 MHz clock frequency. A device devoted to fast random number generation has been developed and included in every board. The on-board reprogrammability permits us to change easily the lattice size, or even the update algorithm or the action. We present here a detailed description of the machine and the first runs using the Heat Bath algorithm.Comment: Submitted to Computer Physics Communications, 19 pages, 5 figures, references adde

Surface and bulk transitions in three-dimensional O(n) models

Using Monte Carlo methods and finite-size scaling, we investigate surface criticality in the O$(n)$ models on the simple-cubic lattice with $n=1$, 2, and 3, i.e. the Ising, XY, and Heisenberg models. For the critical couplings we find $K_{\rm c}(n=2)=0.454 1655 (10)$ and $K_{\rm c}(n=3)= 0.693 002 (2)$. We simulate the three models with open surfaces and determine the surface magnetic exponents at the ordinary transition to be $y_{h1}^{\rm (o)}=0.7374 (15)$, $0.781 (2)$, and $0.813 (2)$ for $n=1$, 2, and 3, respectively. Then we vary the surface coupling $K_1$ and locate the so-called special transition at $\kappa_{\rm c} (n=1)=0.50214 (8)$ and $\kappa_{\rm c} (n=2)=0.6222 (3)$, where $\kappa=K_1/K-1$. The corresponding surface thermal and magnetic exponents are $y_{t1}^{\rm (s)} =0.715 (1)$ and $y_{h1}^{\rm (s)} =1.636 (1)$ for the Ising model, and $y_{t1}^{\rm (s)} =0.608 (4)$ and$y_{h1}^{\rm (s)} =1.675 (1)$ for the XY model. Finite-size corrections with an exponent close to -1/2 occur for both models. Also for the Heisenberg model we find substantial evidence for the existence of a special surface transition.Comment: TeX paper and 10 eps figure