Employer-Based Insurance: Coverage and Cost

Explores the variation in cost by employers and enrollees, types of employers that offer coverage, access to coverage by workers, and how costs would change, especially for small businesses, if new policies required coverage for all full-time workers

Generating all polynomial invariants in simple loops

AbstractThis paper presents a method for automatically generating all polynomial invariants in simple loops. It is first shown that the set of polynomials serving as loop invariants has the algebraic structure of an ideal. Based on this connection, a fixpoint procedure using operations on ideals and Gröbner basis constructions is proposed for finding all polynomial invariants. Most importantly, it is proved that the procedure terminates in at most m+1 iterations, where m is the number of program variables. The proof relies on showing that the irreducible components of the varieties associated with the ideals generated by the procedure either remain the same or increase their dimension at every iteration of the fixpoint procedure. This yields a correct and complete algorithm for inferring conjunctions of polynomial equalities as invariants. The method has been implemented in Maple using the Groebner package. The implementation has been used to automatically discover non-trivial invariants for several examples to illustrate the power of the technique

Refinements and Advancements in Anterior Component Separation

This chapter will explore the newest innovations for performing anterior component separation (CS). It will include open CS, perforator sparing CS and minimally invasive component separation (MICS). It will also address the use of various meshes and their plane of inset. It will cover soft tissue management including panniculectomy, quilting sutures and drains. Fascial closure techniques will also be included. The highlight of this chapter will be the description of tips and tricks of performing MICS. We will also touch upon preoperative preparation such as body mass index (BMI) optimization and smoking cessation as well as management of postoperative complications including surgical site infections, skin necrosis and seroma

Information entropy and nucleon correlations in nuclei

The information entropies in coordinate and momentum spaces and their sum ($S_r$, $S_k$, $S$) are evaluated for many nuclei using "experimental" densities or/and momentum distributions. The results are compared with the harmonic oscillator model and with the short-range correlated distributions. It is found that $S_r$ depends strongly on $\ln A$ and does not depend very much on the model. The behaviour of $S_k$ is opposite. The various cases we consider can be classified according to either the quantity of the experimental data we use or by the values of $S$, i.e., the increase of the quality of the density and of the momentum distributions leads to an increase of the values of $S$. In all cases, apart from the linear relation $S=a+b\ln A$, the linear relation $S=a_V+b_V \ln V$ also holds. V is the mean volume of the nucleus. If $S$ is considered as an ensemble entropy, a relation between $A$ or $V$ and the ensemble volume can be found. Finally, comparing different electron scattering experiments for the same nucleus, it is found that the larger the momentum transfer ranges, the larger the information entropy is. It is concluded that $S$ could be used to compare different experiments for the same nucleus and to choose the most reliable one.Comment: 14 pages, 4 figures, 2 table

Jetting behavior in drop-on-demand printing: Laboratory experiments and numerical simulations

The formation and evolution of micron-sized droplets of a Newtonian liquid generated on demand in an industrial inkjet printhead are studied experimentally and simulated numerically. The shapes and positions of droplets during droplet formation are observed using a high-speed camera and compared with their numerically obtained analogs. Both the experiments and the simulations use practical length scales for inkjet printing. The results show how fluid properties, specifically viscosity and surface tension, affect the drop formation, ligament length, and breakoff time. We identify the parameter space of fluid properties for producing single drops at a prescribed speed and show this is not simply a restriction on the Ohnesorge number, but that there is an additional restriction on the Reynolds number that is distinct from the Reynolds number limit associated with the prevention of splashing. This phase diagram provides more precise guidance on the space of fluid parameters for jetting single droplets in drop-on-demand inkjet printers

Differential rates of perinatal maturation of human primary and nonprimary auditory cortex

Abstract Primary and nonprimary cerebral cortex mature along different timescales; however, the differences between the rates of maturation of primary and nonprimary cortex are unclear. Cortical maturation can be measured through changes in tissue microstructure detectable by diffusion magnetic resonance imaging (MRI). In this study, diffusion tensor imaging (DTI) was used to characterize the maturation of Heschl’s gyrus (HG), which contains both primary auditory cortex (pAC) and nonprimary auditory cortex (nAC), in 90 preterm infants between 26 and 42 weeks postmenstrual age (PMA). The preterm infants were in different acoustical environments during their hospitalization: 46 in open ward beds and 44 in single rooms. A control group consisted of 15 term-born infants. Diffusion parameters revealed that (1) changes in cortical microstructure that accompany cortical maturation had largely already occurred in pAC by 28 weeks PMA, and (2) rapid changes were taking place in nAC between 26 and 42 weeks PMA. At term equivalent PMA, diffusion parameters for auditory cortex were different between preterm infants and term control infants, reflecting either delayed maturation or injury. No effect of room type was observed. For the preterm group, disturbed maturation of nonprimary (but not primary) auditory cortex was associated with poorer language performance at age two years

Dynamic Modeling of In-Use Cement Stocks in the United States

A dynamic substance-flow model is developed to characterize the stocks and flows of cement utilized during the 20th century in the United States, using the generic cement life cycle as a systems boundary. The motivation for estimating historical inventories of cement stocks and flows is to provide accurate estimates of contemporary cement in-use stocks in U.S. infrastructure and future discards to relevant stakeholders in U.S. infrastructure, such as the federal and state highway administrators, departments of transportation, public and private utilities, and the construction and cement industries. Such information will assist in planning future rehabilitation projects and better life cycle management of infrastructure systems. In the present policy environment of climate negotiations, estimates of in-use cement infrastructure can provide insights about to what extent built environment can act as a carbon sink over its lifetime. The rate of addition of new stock, its composition, and the repair of existing stock are key determinants of infrastructure sustainability. Based upon a probability of failure approach, a dynamic stock and flow model was developed utilizing three statistical lifetime distributions—Weibull, gamma, and lognormal—for each cement end-use. The model-derived estimate of the “in-use” cement stocks in the United States is in the range of 4.2 to 4.4 billion metric tons (gigatonnes, Gt). This indicates that 82% to 87% of cement utilized during the last century is still in use. On a per capita basis, this is equivalent to 14.3 to 15.0 tonnes of in-use cement stock per person. The in-use cement stock per capita has doubled over the last 50 years, although the rate of growth has slowed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72233/1/JIEC_055_sm_SuppMat.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/72233/2/j.1530-9290.2008.00055.x.pd

Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation

Magnetic Resonance Imaging (MRI) is widely used in routine clinical diagnosis and treatment. However, variations in MRI acquisition protocols result in different appearances of normal and diseased tissue in the images. Convolutional neural networks (CNNs), which have shown to be successful in many medical image analysis tasks, are typically sensitive to the variations in imaging protocols. Therefore, in many cases, networks trained on data acquired with one MRI protocol, do not perform satisfactorily on data acquired with different protocols. This limits the use of models trained with large annotated legacy datasets on a new dataset with a different domain which is often a recurring situation in clinical settings. In this study, we aim to answer the following central questions regarding domain adaptation in medical image analysis: Given a fitted legacy model, 1) How much data from the new domain is required for a decent adaptation of the original network?; and, 2) What portion of the pre-trained model parameters should be retrained given a certain number of the new domain training samples? To address these questions, we conducted extensive experiments in white matter hyperintensity segmentation task. We trained a CNN on legacy MR images of brain and evaluated the performance of the domain-adapted network on the same task with images from a different domain. We then compared the performance of the model to the surrogate scenarios where either the same trained network is used or a new network is trained from scratch on the new dataset.The domain-adapted network tuned only by two training examples achieved a Dice score of 0.63 substantially outperforming a similar network trained on the same set of examples from scratch.Comment: 8 pages, 3 figure

Striatal dopamine D2 receptor binding of risperidone in schizophrenic patients as assessed by 123I-iodobenzamide SPECT: a comparative study with olanzapine

The aim of this investigation was to compare the degree of striatal dopamine-(D2) receptor blockade by two atypical antipsychotic drugs, risperidone and olanzapine. The percentage of D2 receptor occupancy during treatment was calculated by comparing the results of 123I-iodobenzamide SPECT with those from healthy control subjects. Twenty inpatients suffering from schizophrenia or schizoaffective psychosis according to DSM IV/ICD-10 criteria were treated with clinically recommended doses of risperidone and compared with 13 inpatients treated with up to 20 mg olanzapine. Neuroleptic dose and D2 receptor blockade correlated strongly for both risperidone (Pearson r = –0.86, p = 0.0001) and olanzapine (Pearson r = –0.77, p = 0.002). There was no significant difference between the D2 receptor occupancy of the two substances when given in the clinically recommended dose range (unpaired t-test, t= –0.112, p=0.911)