A Quantile Variant of the EM Algorithm and Its Applications to Parameter Estimation with Interval Data

The expectation-maximization (EM) algorithm is a powerful computational technique for finding the maximum likelihood estimates for parametric models when the data are not fully observed. The EM is best suited for situations where the expectation in each E-step and the maximization in each M-step are straightforward. A difficulty with the implementation of the EM algorithm is that each E-step requires the integration of the log-likelihood function in closed form. The explicit integration can be avoided by using what is known as the Monte Carlo EM (MCEM) algorithm. The MCEM uses a random sample to estimate the integral at each E-step. However, the problem with the MCEM is that it often converges to the integral quite slowly and the convergence behavior can also be unstable, which causes a computational burden. In this paper, we propose what we refer to as the quantile variant of the EM (QEM) algorithm. We prove that the proposed QEM method has an accuracy of $O(1/K^2)$ while the MCEM method has an accuracy of $O_p(1/\sqrt{K})$. Thus, the proposed QEM method possesses faster and more stable convergence properties when compared with the MCEM algorithm. The improved performance is illustrated through the numerical studies. Several practical examples illustrating its use in interval-censored data problems are also provided

Reprogramming of lysosomal gene expression by interleukin-4 and Stat6.

BACKGROUND: Lysosomes play important roles in multiple aspects of physiology, but the problem of how the transcription of lysosomal genes is coordinated remains incompletely understood. The goal of this study was to illuminate the physiological contexts in which lysosomal genes are coordinately regulated and to identify transcription factors involved in this control. RESULTS: As transcription factors and their target genes are often co-regulated, we performed meta-analyses of array-based expression data to identify regulators whose mRNA profiles are highly correlated with those of a core set of lysosomal genes. Among the ~50 transcription factors that rank highest by this measure, 65% are involved in differentiation or development, and 22% have been implicated in interferon signaling. The most strongly correlated candidate was Stat6, a factor commonly activated by interleukin-4 (IL-4) or IL-13. Publicly available chromatin immunoprecipitation (ChIP) data from alternatively activated mouse macrophages show that lysosomal genes are overrepresented among Stat6-bound targets. Quantification of RNA from wild-type and Stat6-deficient cells indicates that Stat6 promotes the expression of over 100 lysosomal genes, including hydrolases, subunits of the vacuolar H⁺ ATPase and trafficking factors. While IL-4 inhibits and activates different sets of lysosomal genes, Stat6 mediates only the activating effects of IL-4, by promoting increased expression and by neutralizing undefined inhibitory signals induced by IL-4. CONCLUSIONS: The current data establish Stat6 as a broadly acting regulator of lysosomal gene expression in mouse macrophages. Other regulators whose expression correlates with lysosomal genes suggest that lysosome function is frequently re-programmed during differentiation, development and interferon signaling

A Bound on the Superpotential

We prove a general bound on the superpotential in theories with broken supersymmetry and broken R-symmetry, 2|W|< f_a F, where f_a and F are the R-axion and Goldstino decay constants, respectively. The bound holds for weakly coupled as well as strongly coupled theories, thereby providing an exact result in theories with broken supersymmetry. We briefly discuss several possible applications.Comment: 20 page

Quantification of the effect of cross-shear and applied nominal contact pressure on the wear of moderately cross-linked polyethylene

Polyethylene wear is a great concern in total joint replacement. It is now considered a major limiting factor to the long life of such prostheses. Cross-linking has been introduced to reduce the wear of ultra-high-molecular-weight polyethylene (UHMWPE). Computational models have been used extensively for wear prediction and optimization of artificial knee designs. However, in order to be independent and have general applicability and predictability, computational wear models should be based on inputs from independent experimentally determined wear parameters (wear factors or wear coefficients). The objective of this study was to investigate moderately cross-linked UHMWPE, using a multidirectional pin-on-plate wear test machine, under a wide range of applied nominal contact pressure (from 1 to 11 MPa) and under five different kinematic inputs, varying from a purely linear track to a maximum rotation of ±55°. A computational model, based on a direct simulation of the multidirectional pin-on-plate wear tester, was developed to quantify the degree of cross-shear (CS) of the polyethylene pins articulating against the metallic plates. The moderately cross-linked UHMWPE showed wear factors less than half of that reported in the literature for the conventional UHMWPE, under the same loading and kinematic inputs. In addition, under high applied nominal contact stress, the moderately cross-linked UHMWPE wear showed lower dependence on the degree of CS compared to that under low applied nominal contact stress. The calculated wear coefficients were found to be independent of the applied nominal contact stress, in contrast to the wear factors that were shown to be highly pressure dependent. This study provided independent wear data for inputs into computational models for moderately cross-linked polyethylene and supported the application of wear coefficient–based computational wear models

Association between antipsychotic use in pregnancy and the risk of gestational diabetes: Population-based cohort studies from the United Kingdom and Hong Kong and an updated meta-analysis

Aims: To investigate whether exposure to antipsychotic medications during pregnancy is associated with gestational diabetes mellitus (GDM) in United Kingdom (UK) and Hong Kong (HK) population cohorts. / Methods: Two population-based cohort studies were conducted using data from the UK The Health Improvement Network (THIN) and HK Clinical Data Analysis and Reporting System (CDARS). Nondiabetic women who received any type of antipsychotic medicine before their first pregnancy were included in our cohorts. The exposed group comprised women who continued using antipsychotics from the start of pregnancy to delivery (continuers), while the comparison group included women who were prescribed antipsychotics before the start of pregnancy but stopped during pregnancy (discontinuers). GDM was identified using GDM diagnosis and/or clinicians reported GDM. Odds ratios (ORs) with a 95% confidence interval (CI) were calculated to assess the association between antipsychotic use during pregnancy and GDM. Propensity Score fine-stratification weighting was used to adjust for potential confounding factors. / Results: 3114 women with registered first pregnancies (2351 in THIN and 763 in CDARS) were included. 5.49% (2.55% in THIN and 14.55% in CDARS) were diagnosed with GDM. The adjusted OR of GDM in continuers was 0.73 (95% CI: 0.43‐1.25) in THIN and 1.16 (95% CI: 0.78‐1.73) in CDARS compared with discontinuers. / Conclusions: Our results do not suggest an increased risk of GDM in women who continued using antipsychotics during pregnancy compared to women who stopped. Based on these results, women should not stop their regular antipsychotics prescriptions in pregnancy due to the fear of GDM

Tame D-tadpoles in gauge mediation

We revisit models of gauge mediated supersymmetry breaking where messenger parity is violated. Such a symmetry is usually invoked in order to set to zero potentially dangerous hypercharge D-term tadpoles. A milder hypothesis is that the D-tadpole vanishes only at the first order in the gauge coupling constant. Then the next order leads to a contribution to the sfermion masses which is of the same magnitude as the usual radiative one. This enlarges the parameter space of gauge mediated models. We first give a completely general characterization of this contribution, in terms of particular three-point functions of hidden sector current multiplet operators. We then explore the parameter space by means of two simple weakly coupled models, where the D-tadpole arising at two-loops has actually a mild logarithmic divergence.Comment: 13 pages + 9 pages of appendix, 1 figure; v2: some clarifying comments added, version to appear in JHE

Single Cut Integration

We present an analytic technique for evaluating single cuts for one-loop integrands, where exactly one propagator is taken to be on shell. Our method extends the double-cut integration formalism of one-loop amplitudes to the single-cut case. We argue that single cuts give meaningful information about amplitudes when taken at the integrand level. We discuss applications to the computation of tadpole coefficients.Comment: v2: corrected typo in abstrac