The antiferromagnetic phi4 Model, II. The one-loop renormalization

It is shown that the four dimensional antiferromagnetic lattice phi4 model has the usual non-asymptotically free scaling law in the UV regime around the chiral symmetrical critical point. The theory describes a scalar and a pseudoscalar particle. A continuum effective theory is derived for low energies. A possibility of constructing a model with a single chiral boson is mentioned.Comment: To appear in Phys. Rev.

Effect of the Dutch Hip Fracture Audit implementation on mortality, length of hospital stay and time until surgery in elderly hip fracture patients; a multi-center cohort study

Background: In 2040 the estimated number of people with a hip fracture in the Netherlands will be about 24,000. The medical care for this group of patients is complicated and challenging. Multidisciplinary approaches aim to improve clinical outcome. Quality indicators that gain insight in the treatment and outcome of hip fracture patients may help to optimize and monit

Measurement of the B0-anti-B0-Oscillation Frequency with Inclusive Dilepton Events

The $B^0$-$\bar B^0$ oscillation frequency has been measured with a sample of 23 million \B\bar B pairs collected with the BABAR detector at the PEP-II asymmetric B Factory at SLAC. In this sample, we select events in which both B mesons decay semileptonically and use the charge of the leptons to identify the flavor of each B meson. A simultaneous fit to the decay time difference distributions for opposite- and same-sign dilepton events gives $\Delta m_d = 0.493 \pm 0.012{(stat)}\pm 0.009{(syst)}$ ps$^{-1}$.Comment: 7 pages, 1 figure, submitted to Physical Review Letter

Modeling Vortex Swarming In Daphnia

Based on experimental observations in \textit{Daphnia}, we introduce an agent-based model for the motion of single and swarms of animals. Each agent is described by a stochastic equation that also considers the conditions for active biological motion. An environmental potential further reflects local conditions for \textit{Daphnia}, such as attraction to light sources. This model is sufficient to describe the observed cycling behavior of single \textit{Daphnia}. To simulate vortex swarming of many \textit{Daphnia}, i.e. the collective rotation of the swarm in one direction, we extend the model by considering avoidance of collisions. Two different ansatzes to model such a behavior are developed and compared. By means of computer simulations of a multi-agent system we show that local avoidance - as a special form of asymmetric repulsion between animals - leads to the emergence of a vortex swarm. The transition from uncorrelated rotation of single agents to the vortex swarming as a function of the swarm size is investigated. Eventually, some evidence of avoidance behavior in \textit{Daphnia} is provided by comparing experimental and simulation results for two animals.Comment: 24 pages including 11 multi-part figs. Major revisions compared to version 1, new results on transition from uncorrelated rotation to vortex swarming. Extended discussion. For related publications see http://www.sg.ethz.ch/people/scfrank/Publication

Synchronous dual primary ovarian and endometrial carcinomas

OBJECTIVES: The synchronous occurrence of carcinoma confined to the ovary and endometrium presents a diagnostic and therapeutic dilemma. These tumors have been variously staged as FIGO Stage IIA ovarian carcinoma, Stage III endometrial carcinoma, or synchronous dual primary carcinomas. Accumulating evidence suggests such patients have a favorable outcome. This retrospective study was undertaken to review our experience with these fascinating tumors. METHODS: The clinical records and the pathologic findings of 16 patients with synchronous dual primary ovarian and endometrial carcinomas were reviewed. RESULTS: The median age was 51 years. Abnormal uterine bleeding was the most common presenting symptom (70%). All patients had Stage I ovarian and endometrial carcinomas. Fourteen patients (88%) had endometrioid carcinoma in both sites, while two patients (12%) had dissimilar histology. For 15 patients (94%), the grade of both tumors was identical. Only three (19%) patients had myometrial invasion, with less than 50% involvement in each case. All patients underwent surgical staging, 11 (70%) of whom received adjuvant radiation or chemotherapy. The five patients treated with surgery alone had Grade 1 endometrioid tumors. The only relapse occurred in a patient with a clear cell component in both sites. No patient has died of disease. CONCLUSIONS: Patients with synchronous dual primary carcinomas appear to have a more favorable prognosis than that expected with Stage IIA ovarian or Stage III endometrial carcinoma (100% vs. 63% or 42% survival at 3 years, respectively). The excellent survival for patients with Grade 1 dual endometrioid tumors treated with surgery alone suggests that adjuvant therapy may not be necessary for this sub-group.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/30414/1/0000034.pd

Mixture of latent trait analyzers for model-based clustering of categorical data

Model-based clustering methods for continuous data are well established and commonly used in a wide range of applications. However, model-based clustering methods for categorical data are less standard. Latent class analysis is a commonly used method for model-based clustering of binary data and/or categorical data, but due to an assumed local independence structure there may not be a correspondence between the estimated latent classes and groups in the population of interest. The mixture of latent trait analyzers model extends latent class analysis by assuming a model for the categorical response variables that depends on both a categorical latent class and a continuous latent trait variable; the discrete latent class accommodates group structure and the continuous latent trait accommodates dependence within these groups. Fitting the mixture of latent trait analyzers model is potentially difficult because the likelihood function involves an integral that cannot be evaluated analytically. We develop a variational approach for fitting the mixture of latent trait models and this provides an efficient model fitting strategy. The mixture of latent trait analyzers model is demonstrated on the analysis of data from the National Long Term Care Survey (NLTCS) and voting in the U.S. Congress. The model is shown to yield intuitive clustering results and it gives a much better fit than either latent class analysis or latent trait analysis alone

Pion condensation of quark matter in the static Einstein universe

In the framework of an extended Nambu--Jona-Lasinio model we are studying pion condensation in quark matter with an asymmetric isospin composition in a gravitational field of the static Einstein universe at finite temperature and chemical potential. This particular choice of the gravitational field configuration enables us to investigate phase transitions of the system with exact consideration of the role of this field in the formation of quark and pion condensates and to point out its influence on the phase portraits. We demonstrate the effect of oscillations of the thermodynamic quantities as functions of the curvature and also refer to a certain similarity between the behavior of these quantities as functions of curvature and finite temperature. Finally, the role of quantum fluctuations for spontaneous symmetry breaking in the case of a finite volume of the universe is shortly discussed.Comment: RevTex4; 15 pages, 10 figure

Improving Genetic Prediction by Leveraging Genetic Correlations Among Human Diseases and Traits

Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7 for height to 47 for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait. © 2018 The Author(s)