Multivariate Decomposition for Hazard Rate Models

We develop a regression decomposition technique for hazard rate models, where the difference in observed rates is decomposed into components attributable to group differences in characteristics and group differences in effects. The baseline hazard is specified using a piecewise constant exponential model, which leads to convenient estimation based on a Poisson regression model fit to person-period, or split-episode data. This specification allows for a flexible representation of the baseline hazard and provides a straightforward way to introduce time-varying covariates and time-varying effects. We provide computational details underlying the method and apply the technique to the decomposition of the black-white difference in first premarital birth rates into components reflecting characteristics and effect contributions of several predictors, as well as the effect contribution attributable to race differences in the baseline hazard.Poisson regression, hazard rates, decomposition, piecewise constant exponential model

Language of Interview and the Subjectively-Rated Health of Hispanic Mothers and their Children

Hispanics tend to be as healthy as non-Hispanic whites across a number of indicators, yet they consistently rate their health as worse than non-Hispanic whites. This incongruous finding has been tied both to levels of acculturation and Spanish-language use, questioning the validity of self-reported health for Spanish speakers in the United States. Furthermore, in the same way that Hispanic adults interviewed in Spanish have worse self-rated health, when asked in Spanish mothers rate their children’s health as worse than those mothers who answer in English. The exact reasons for this relationship, though, are unclear. Frequently this language effect has been taken as an indicator of acculturation; as such, the assumption is that as time progresses Hispanics become more acculturated and answer questions regarding their health more similarly to non-Hispanic whites. However, up until this point there has been no longitudinal research examining the relationship between rated health and language of interview. Using three waves of data on Hispanic mothers and their children from the Fragile Families and Child Well-being Study, this paper addresses the following questions: 1. Is Spanish language interview predictive of worse rated health for both mothers and children, and do these relationships change over time? 2. Does the effect of language on rated health persist after controlling for potential mediators? By employing two-level generalized linear models, we find that on average, those who were interviewed in Spanish are more likely to rate their and their children’s health as worse than those who answered in English. The effect of language of interview on reported health persists over time, even after controlling for measures of acculturation, physical and mental health, and access to health care. Contrary to what some have proposed, we see no discernable change over time in the way women rate their own health or that of their children.

Fitting Age-Period-Cohort Models Using the Intrinsic Estimator: Assumptions and Misapplications

We thank Demography’s editorial office for the opportunity to respond to te Grotenhuis et al.’s commentary regarding the methods used and the results presented in our earlier paper (Masters et al. 2014). In this response, we briefly reply to three general themes raised in the commentary: (1) the presentation and discussion of APC results, (2) the fitting of full APC models to data for which a simpler model holds, and (3) the variation in the estimated age, period, and cohort coefficients produced by the intrinsic estimator (IE) (i.e., the “non-uniqueness property” of the IE, as referred to by Pelzer et al. (2015))

\u3csup\u3e1\u3c/sup\u3eH, \u3csup\u3e15\u3c/sup\u3eN, \u3csup\u3e13\u3c/sup\u3eC, and \u3csup\u3e13\u3c/sup\u3eCO Assignments of Human Interleukin-4 Using Three-Dimensional Double- and Triple-Resonance Heteronuclear Magnetic Resonance Spectroscopy

The assignment of the 1H, 15N, 13CO, and 13C resonances of recombinant human interleukin-4 (IL-4), a protein of 133 residues and molecular mass of 15.4 kDa, is presented based on a series of 11 three-dimensional (3D) double- and triple resonance heteronuclear NMR experiments. These studies employ uniformly labeled 15N- and 15N/13C-labeled IL-4 with an isotope incorporation of \u3e95% for the protein expressed in yeast. Five independent sequential connectivity pathways via one-, two-, and three-bond heteronuclear J couplings are exploited to obtain unambiguous sequential assignments. Specifically, CO(i)-N(i+l),NH(i+l) correlations are observed in the HNCO experiment, the CαH(i),Cα(i)-N(i+l) correlations in the HCA(CO)N experiment, the Cα(i)-N(i+l),NH(i+ 1) correlations in the HNCA and HN(C0)CA experiments, the CαH(i)-N(i+ l),NH(i+l) correlations in the H(CA)NH and HN(CO)HB experiments, and the Cβ(i)-N(i+ l),NH(i+ 1) correlations in the HN(CO)HB experiments. The backbone intraresidue CαH(i)-15N(i)-NH(i) correlations are provided by the 15N-edited Hartmann-Hahn (HOHAHA) and H(CA)NH experiments, the CβH(i)-15N(i)-NH(i) correlations by the 15N-edited HOHAHA and HNHB experiments, the l3Cα(i)-l5N(i)-NH(i) correlations by the HNCA experiment, and the CαH(1)-13Cα(i)-13CO(i) correlations by the HCACO experiment. Aliphatic side-chain spin systems are assigned by 3D 1H-13C-13C-1H correlated (HCCH-COSY) and total correlated (HCCH-TOCSY) spectroscopy. Because of the high resolution afforded by these experiments, as well as the availability of multiple sequential connectivity pathways, ambiguities associated with the limited chemical shift dispersion associated with helical proteins are readily resolved. Further, in the majority of cases (88%), four or more sequential correlations are observed between successive residues. Consequently, the interpretation of these experiments readily lends itself to semiautomated analysis which significantly simplifies and speeds up the assignment process. The assignments presented in this paper provide the essential basis for studies aimed at determining the high-resolution three-dimensional structure of IL-4 in solution

What can ecosystems learn? Expanding evolutionary ecology with learning theory

Background: The structure and organisation of ecological interactions within an ecosystem is modified by the evolution and coevolution of the individual species it contains. Understanding how historical conditions have shaped this architecture is vital for understanding system responses to change at scales from the microbial upwards. However, in the absence of a group selection process, the collective behaviours and ecosystem functions exhibited by the whole community cannot be organised or adapted in a Darwinian sense. A long-standing open question thus persists: Are there alternative organising principles that enable us to understand and predict how the coevolution of the component species creates and maintains complex collective behaviours exhibited by the ecosystem as a whole?Results: Here we answer this question by incorporating principles from connectionist learning, a previously unrelated discipline already using well-developed theories on how emergent behaviours arise in simple networks. Specifically, we show conditions where natural selection on ecological interactions is functionally equivalent to a simple type of connectionist learning, ‘unsupervised learning’, well-known in neural-network models of cognitive systems to produce many non-trivial collective behaviours. Accordingly, we find that a community can self-organise in a well-defined and non-trivial sense without selection at the community level; its organisation can be conditioned by past experience in the same sense as connectionist learning models habituate to stimuli. This conditioning drives the community to form a distributed ecological memory of multiple past states, causing the community to: a) converge to these states from any random initial composition; b) accurately restore historical compositions from small fragments; c) recover a state composition following disturbance; and d) to correctly classify ambiguous initial compositions according to their similarity to learned compositions. We examine how the formation of alternative stable states alters the community’s response to changing environmental forcing, and we identify conditions under which the ecosystem exhibits hysteresis with potential for catastrophic regime shifts.Conclusions: This work highlights the potential of connectionist theory to expand our understanding of evo-eco dynamics and collective ecological behaviours. Within this framework we find that, despite not being a Darwinian unit, ecological communities can behave like connectionist learning systems, creating internal conditions that habituate to past environmental conditions and actively recalling those conditions.Theoretical ecology, Communityassembly, Network structures, Ecological memory, Associative learning, Regime shifts, Community matrix*Correspondence

Modification of HDL by reactive aldehydes alters select cardioprotective functions of HDL in macrophages

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154382/1/febs15034_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154382/2/febs15034.pd

Topological structure and dynamics of three-dimensional active nematics.

Topological structures are effective descriptors of the nonequilibrium dynamics of diverse many-body systems. For example, motile, point-like topological defects capture the salient features of two-dimensional active liquid crystals composed of energy-consuming anisotropic units. We dispersed force-generating microtubule bundles in a passive colloidal liquid crystal to form a three-dimensional active nematic. Light-sheet microscopy revealed the temporal evolution of the millimeter-scale structure of these active nematics with single-bundle resolution. The primary topological excitations are extended, charge-neutral disclination loops that undergo complex dynamics and recombination events. Our work suggests a framework for analyzing the nonequilibrium dynamics of bulk anisotropic systems as diverse as driven complex fluids, active metamaterials, biological tissues, and collections of robots or organisms

Fluctuations of elastic interfaces in fluids: Theory and simulation

We study the dynamics of elastic interfaces-membranes-immersed in thermally excited fluids. The work contains three components: the development of a numerical method, a purely theoretical approach, and numerical simulation. In developing a numerical method, we first discuss the dynamical coupling between the interface and the surrounding fluids. An argument is then presented that generalizes the single-relaxation time lattice-Boltzmann method for the simulation of hydrodynamic interfaces to include the elastic properties of the boundary. The implementation of the new method is outlined and it is tested by simulating the static behavior of spherical bubbles and the dynamics of bending waves. By means of the fluctuation-dissipation theorem we recover analytically the equilibrium frequency power spectrum of thermally fluctuating membranes and the correlation function of the excitations. Also, the non-equilibrium scaling properties of the membrane roughening are deduced, leading us to formulate a scaling law describing the interface growth, W^2(L,T)=L^3 g[t/L^(5/2)], where W, L and T are the width of the interface, the linear size of the system and the temperature respectively, and g is a scaling function. Finally, the phenomenology of thermally fluctuating membranes is simulated and the frequency power spectrum is recovered, confirming the decay of the correlation function of the fluctuations. As a further numerical study of fluctuating elastic interfaces, the non-equilibrium regime is reproduced by initializing the system as an interface immersed in thermally pre-excited fluids.Comment: 15 pages, 11 figure

Should age-period-cohort studies return to the methodologies of the 1970s?

Social scientists have recognized the importance of age-period-cohort (APC) models for half a century, but have spent much of this time mired in debates about the feasibility of APC methods. Recently, a new class of APC methods based on modern statistical knowledge has emerged, offering potential solutions. In 2009, Reither, Hauser and Yang used one of these new methods – hierarchical APC (HAPC) modeling – to study how birth cohorts may have contributed to the U.S. obesity epidemic. They found that recent birth cohorts experience higher odds of obesity than their predecessors, but that ubiquitous period-based changes are primarily responsible for the rising prevalence of obesity. Although these findings have been replicated elsewhere, recent commentaries by Bell and Jones call them into question – along with the new class of APC methods. Specifically, Bell and Jones claim that new APC methods do not adequately address model identification and suggest that “solid theory” is often sufficient to remove one of the three temporal dimensions from empirical consideration. They also present a series of simulation models that purportedly show how the HAPC models estimated by Reither et al. (2009) could have produced misleading results. However, these simulation models rest on assumptions that there were no period effects, and associations between period and cohort variables and the outcome were perfectly linear. Those are conditions under which APC models should never be used. Under more tenable assumptions, our own simulations show that HAPC methods perform well, both in recovering the main findings presented by Reither et al. (2009) and the results reported by Bell and Jones. We also respond to critiques about model identification and theoretically-imposed constraints, finding little pragmatic support for such arguments. We conclude by encouraging social scientists to move beyond the debates of the 1970s and toward a deeper appreciation for modern APC methodologies

Synthesis, Characterization, and Computational Study of Three-Coordinate SNS Copper(I) Complexes Based on Bis-Thione Ligand Precursors

A series of tridentate pincer ligands, each possessing two sulfur and one nitrogen donor (SNS), based on bis-imidazolyl or bis-triazolyl salts were metallated with CuCl2 to give new tridentate SNS pincer copper(I) complexes [(SNS)Cu]+. These orange complexes exhibit a three-coordinate pseudo-trigonal-planar geometry in copper. During the formation of these copper(I) complexes, disproportionation is observed as the copper(II) salt precursor is converted into the Cu(I) [(SNS)Cu]+ cation and the [CuCl4]2– counteranion. The [(SNS)Cu]+ complexes were characterized with single crystal X-ray diffraction, electrospray mass spectrometry, EPR spectroscopy, attenuated total reflectance infrared spectroscopy, UV–Vis spectroscopy, cyclic voltammetry, and elemental analysis. The EPR spectra are consistent with anisotropic Cu(II) signals with four hyperfine splittings in the lower-field region (g||) and g values consistent with the presence of the tetrachlorocuprate. Various electronic transitions are apparent in the UV–Vis spectra of the complexes and originate in the copper-containing cations and anions. Density functional calculations support the nature of the SNS binding, allowing assignment of a number of features present in the UV–Vis and IR spectra and cyclic voltammograms of these complexes