Scalar Glueball Mass Reduction at Finite Temperature in SU(3) Anisotropic Lattice QCD

We report the first study of the glueball properties at finite temperatures below T_c using SU(3) anisotropic lattice QCD with beta=6.25, the renormalized anisotropy xi \equiv a_s/a_t = 4 and 20^3 \times N_t (N_t=35,36,37,38,40,43,45,50,72) at the quenched level. From the temporal correlation analysis with the smearing method, about 20 % mass reduction is observed for the lowest scalar glueball as m_G(T)=1250 \pm 50MeV for 0.8 T_c < T < T_c in comparison with m_G \simeq 1500 \sim 1700MeV at T \simeq 0.Comment: This is the second revised version using more gauge configurations. 5 pages, Latex2e, 5 figure

Hadron Mass Predictions of the Valence Approximation to Lattice QCD

We evaluate the infinite volume, continuum limits of eight hadron mass ratios predicted by lattice QCD with Wilson quarks in the valence (quenched) approximation. Each predicted ratio differs from the corresponding observed value by less than 6\%.Comment: 13 pages of Latex + 2 PostScript files attached, IBM/HET 92-

Psychometric Characteristics of the Connor-Davidson Resilience Scale (CD-RISC) in Postpartum Mothers with Histories of Childhood Maltreatment

Background: There is increased awareness that resilience serves as a protective factor against adverse psychophysiological sequelae in the context of stress. However, there are few instruments to assess this construct in adult populations. The Connor-Davidson resilience scale (CD-RISC) has been developed to assess adaptation following stress exposure. While this instrument has previously demonstrated impressive reliability and construct validity, prior research has not supported the consistency of the originally described factor structure. There is also limited evidence regarding the measurement of resilience in the context of cumulative stress exposure. Objectives: This research explores the psychometric properties of the CD-RISC in mothers with childhood histories of maltreatment Materials and Methods: Postpartum women who endorsed a history of childhood abuse or neglect (N = 141) completed the CD-RISC, the childhood trauma questionnaire and other surveys measuring positive and negative health and functioning. We calculated descriptive statistics with percentage counts and means as appropriate. Internal reliability was evaluated by Cronbach’s alpha and the calculation of item-to-total score correlations. Parallel analysis (PA) was utilized to derive the number of retained factors. Results: A recent parenting transition concomitant with a history of maltreatment was associated with lower CD-RISC scores. Internal reliability and concurrent validity analyses were satisfactory and consistent with predicted hypotheses. Exploratory factor analysis (EFA) supported a four-factor model of resilience with this population. Conclusions: This research offers further evidence of the reliability and validity of the CD-RISC. Further, the results of the EFA with parallel analysis offer an empirically-driven derivation of factors for this population

The significance of circulating tumor cells in prostate cancer patients undergoing adjuvant or salvage radiation therapy

Background:Following radical prostatectomy, success of adjuvant and salvage radiation therapy (RT) is dependent on the absence of micrometastatic disease. However, reliable prognostic/predictive factors for determining this are lacking. Therefore, novel biomarkers are needed to assist with clinical decision-making in this setting. Enumeration of circulating tumor cells (CTCs) using the regulatory-approved CellSearch System (CSS) is prognostic in metastatic prostate cancer. We hypothesize that CTCs may also be prognostic in the post-prostatectomy setting. Methods:Patient blood samples (n=55) were processed on the CSS to enumerate CTCs at 0, 6, 12 and 24 months after completion of RT. CTC values were correlated with predictive/prognostic factors and progression-free survival.Results:CTC status (presence/absence) correlated significantly with positive margins (increased likelihood of CTC neg disease; P=0.032), and trended toward significance with the presence of seminal vesicle invasion (CTC pos; P=0.113) and extracapsular extension (CTC neg; P=0.116). Although there was a trend toward a decreased time to biochemical failure (BCF) in baseline CTC-positive patients (n=9), this trend was not significant (hazard ratio (HR)=0.3505; P=0.166). However, CTC-positive status at any point (n=16) predicted for time to BCF (HR=0.2868; P=0.0437).Conclusions:One caveat of this study is the small sample size utilized (n=55) and the low number of patients with CTC-positive disease (n=16). However, our results suggest that CTCs may be indicative of disseminated disease and assessment of CTCs during RT may be helpful in clinical decision-making to determine, which patients may benefit from RT versus those who may benefit more from systemic treatments

Semantic aware Bayesian network model for actionable knowledge discovery in linked data

The majority of the conventional mining algorithms treat the mining process as an isolated data-driven procedure and overlook the semantic of the targeted data. As a result, the generated patterns are abundant and end users cannot act upon them seamlessly. Furthermore, interdisciplinary knowledge can not be obtained from domain-specific silo of data. The emergence of Linked Data (LD) as a new model for knowledge representation, which intertwines data with its semantics, has introduced new opportunities for data miners. Accordingly, this paper proposes an ontology-based Semantic-Aware Bayesian network (BN) model. In contrast to the existing mining algorithms, the proposed model does into transform the original format of the LD set. Therefore, it not only accommodates the semantic aspects in LD, but also caters to the need of connecting different data-sets from different domains. We evaluate the proposed model on a Bone Dysplasia dataset, Experimental results show promising performance

Outdoor, Indoor, and Personal Exposure to VOCs in Children

We measured volatile organic compound (VOC) exposures in multiple locations for a diverse population of children who attended two inner-city schools in Minneapolis, Minnesota. Fifteen common VOCs were measured at four locations: outdoors (O), indoors at school (S), indoors at home (H), and in personal samples (P). Concentrations of most VOCs followed the general pattern O ≈ S < P ≤ H across the measured microenvironments. The S and O environments had the smallest and H the largest influence on personal exposure to most compounds. A time-weighted model of P exposure using all measured microenvironments and time–activity data provided little additional explanatory power beyond that provided by using the H measurement alone. Although H and P concentrations of most VOCs measured in this study were similar to or lower than levels measured in recent personal monitoring studies of adults and children in the United States, p-dichlorobenzene was the notable exception to this pattern, with upper-bound exposures more than 100 times greater than those found in other studies of children. Median and upper-bound H and P exposures were well above health benchmarks for several compounds, so outdoor measurements likely underestimate long-term health risks from children’s exposure to these compounds

A dynamical model reveals gene co-localizations in nucleus

Co-localization of networks of genes in the nucleus is thought to play an important role in determining gene expression patterns. Based upon experimental data, we built a dynamical model to test whether pure diffusion could account for the observed co-localization of genes within a defined subnuclear region. A simple standard Brownian motion model in two and three dimensions shows that preferential co-localization is possible for co-regulated genes without any direct interaction, and suggests the occurrence may be due to a limitation in the number of available transcription factors. Experimental data of chromatin movements demonstrates that fractional rather than standard Brownian motion is more appropriate to model gene mobilizations, and we tested our dynamical model against recent static experimental data, using a sub-diffusion process by which the genes tend to colocalize more easily. Moreover, in order to compare our model with recently obtained experimental data, we studied the association level between genes and factors, and presented data supporting the validation of this dynamic model. As further applications of our model, we applied it to test against more biological observations. We found that increasing transcription factor number, rather than factory number and nucleus size, might be the reason for decreasing gene co-localization. In the scenario of frequency-or amplitude-modulation of transcription factors, our model predicted that frequency-modulation may increase the co-localization between its targeted genes

Narrow width of a glueball decay into two mesons

The widths of a glueball decay to two pions or kaons are analyzed in the pQCD framework. Our results show that the glueball ground state has small branching ratio for two-meson decay mode, which is around $10^{-2}$. The predicted values are consistent with the data of $\xi\to\pi\pi, KK$ if $\xi$ particle is a $2^{++}$ glueball. Applicability of pQCD to the glueball decay and comparison with $\chi_{cJ}$ decay are also discussed.Comment: 12 pages, revtex, 2 ps figure

The Kentucky Noisy Monte Carlo Algorithm for Wilson Dynamical Fermions

We develop an implementation for a recently proposed Noisy Monte Carlo approach to the simulation of lattice QCD with dynamical fermions by incorporating the full fermion determinant directly. Our algorithm uses a quenched gauge field update with a shifted gauge coupling to minimize fluctuations in the trace log of the Wilson Dirac matrix. The details of tuning the gauge coupling shift as well as results for the distribution of noisy estimators in our implementation are given. We present data for some basic observables from the noisy method, as well as acceptance rate information and discuss potential autocorrelation and sign violation effects. Both the results and the efficiency of the algorithm are compared against those of Hybrid Monte Carlo. PACS Numbers: 12.38.Gc, 11.15.Ha, 02.70.Uu Keywords: Noisy Monte Carlo, Lattice QCD, Determinant, Finite Density, QCDSPComment: 30 pages, 6 figure