Reducibility of polynomials f(x,y)f(x,y) modulo pp

We consider absolutely irreducible polynomials $f \in Z[x,y]$ with $\deg_x(f)=m$, $\deg_y(f)=n$ and height $H$. We show that for any prime $p$ with $p>c_{mn} H^{2mn+n-1}$ the reduction $f \bmod p$ is also absolutely irreducible. Furthermore if the Bouniakowsky conjecture is true we show that there are infinitely many absolutely irreducible polynomials $f \in Z[x,y]$ which are reducible mod $p$ where $p$ is a prime with $p>H^{2m}$.Comment: Latex, 7 page

Flow dependence of high pTp_T parton energy loss in heavy-ion collisions

The measured transverse momentum spectra and HBT correlations of bulk (i.e. low $p_T$) matter can be well explained by assuming that the soft sector of particles produced in ultrarelativistic heavy-ion collisions is (approximately) thermalized and undergoes collective accelerated expansion in both longitudinal and transverse direction. However, this implies that bulk matter will have a non-vanishing flow component transverse to the trajectory of a high $p_T$ partonic jets. In general, this will increase the energy loss experienced by the jet parton and modify the shape of the jet cone. In this paper, we present a systematic study of the magnitude of the additional energy loss induced by flow under realistic assumptions for the medium evolution. We argue that a perturbative QGP description may be sufficient for the measured $R_{AA}$ if flow during the medium evolution is taken into account properly

Bayesian Analysis for Penalized Spline Regression Using WinBUGS

Penalized splines can be viewed as BLUPs in a mixed model framework, which allows the use of mixed model software for smoothing. Thus, software originally developed for Bayesian analysis of mixed models can be used for penalized spline regression. Bayesian inference for nonparametric models enjoys the flexibility of nonparametric models and the exact inference provided by the Bayesian inferential machinery. This paper provides a simple, yet comprehensive, set of programs for the implementation of nonparametric Bayesian analysis in WinBUGS. Good mixing properties of the MCMC chains are obtained by using low-rank thin-plate splines, while simulation times per iteration are reduced employing WinBUGS specific computational tricks.

Development and Assessment of an Environmental DNA (eDNA) Assay for the Rio Grande Siren and Review of eDNA Metabarcoding Applications

Environmental DNA (eDNA) assays have become a major aspect of amphibian surveys in the past decade. These methods are highly sensitive, making them well-suited for monitoring rare and cryptic species. Current efforts to study the Rio Grande Siren in south Texas have been hampered due to the cryptic nature of these aquatic salamanders. Arid conditions further add to the difficulty in studying this species, as many water bodies they inhabit are ephemeral, sometimes constraining sampling efforts to a short window after heavy rain. Additionally, sirens are known to cease activity and reside underground when ponds begin to dry or as water temperatures increase. Conventional sampling efforts require extensive trap-hours to be effective, which is not always possible within the required sampling window. This study presents the development of a novel eDNA assay technique for this elusive species and compare eDNA results with simultaneous trapping at multiple sites to assess the relative effectiveness of the procedure. This methodology gives promise for future work assessing the distribution and status of the Rio Grande Siren and has potential for use on other south Texas amphibians. An expansive literature review on the subject of eDNA metabarcoding is also presented, along with a plan for implementation of this method in south Texas for community amphibian studies

Intrinsically Legal-For-Trade Objects by Digital Signatures

The established techniques for legal-for-trade registration of weight values meet the legal requirements, but in praxis they show serious disadvantages. We report on the first implementation of intrinsically legal-for-trade objects, namely weight values signed by the scale, that is accepted by the approval authority. The strict requirements from both the approval- and the verification-authority as well as the limitations due to the hardware of the scale were a special challenge. The presented solution fulfills all legal requirements and eliminates the existing practical disadvantages.Comment: 4 pages, 0 figure

Interferon y Stimulation Modulates the Proteolytic Activity and Cleavage Site Preference of 20S Mouse Proteasomes

The proteasome is a 700-kD multisubunit enzyme complex with several proteolytically active sites. The enzyme complex is involved in both ubiquitin-dependent and -independent protein degradation and may contribute to the processing of antigens presented by major histocompatibility complex (MHC) class I molecules. Here we demonstrate that treatment of mouse fibroblast cells with 20 U interferon qr (IFN-y) for 3 d induces a change in the proteasome subunit composition and that the B-type subunit LMP2, which is encoded in the MHC class II region, is incorporated into the enzyme complex. This is paralleled by reduction of the homologous 6-subunit. IFN-3' stimulation results in a downregulation of the chymotrypsin-like Suc-LLVY-MCA peptide hydrolyzing activity of 20S proteasomes whereas the trypsin-like activity remains unaffected. When tested as a substrate a synthetic 25-mer polypeptide whose sequence covers the antigenic nonapeptide YPHFMPTNL of the MCMV pp89, 20S proteasomes of IFN-3'-induced cells exhibit altered chymotrypsin-like cleavage site preferences. In the absence of IFN-qr induction, the naturally processed nonamer peptide that is presented by MHC class.I molecules appears as a minor cleavage product. IFN-'y activation does not result in an increase of the final peptide but results in a different set of peptides. We hypothesize that these peptides represent precursor peptides that can be trimmed to final peptide size

Bayesian Analysis for Penalized Spline Regression Using Win BUGS

Penalized splines can be viewed as BLUPs in a mixed model framework, which allows the use of mixed model software for smoothing. Thus, software originally developed for Bayesian analysis of mixed models can be used for penalized spline regression. Bayesian inference for nonparametric models enjoys the flexibility of nonparametric models and the exact inference provided by the Bayesian inferential machinery. This paper provides a simple, yet comprehensive, set of programs for the implementation of nonparametric Bayesian analysis in WinBUGS. MCMC mixing is substantially improved from the previous versions by using low{rank thin{plate splines instead of truncated polynomial basis. Simulation time per iteration is reduced 5 to 10 times using a computational trick

COX MODELS WITH NONLINEAR EFFECT OF COVARIATES MEASURED WITH ERROR: A CASE STUDY OF CHRONIC KIDNEY DISEASE INCIDENCE

We propose, develop and implement the simulation extrapolation (SIMEX) methodology for Cox regression models when the log hazard function is linear in the model parameters but nonlinear in the variables measured with error (LPNE). The class of LPNE functions contains but is not limited to strata indicators, splines, quadratic and interaction terms. The first order bias correction method proposed here has the advantage that it remains computationally feasible even when the number of observations is very large and multiple models need to be explored. Theoretical and simulation results show that the SIMEX method outperforms the naive method even with small amounts of measurement error. Our methodology was motivated by and applied to the study of time to chronic kidney disease (CKD) progression as a function of baseline kidney function and applied to the Atherosclerosis Risk in Communities (ARIC), a large epidemiological cohort stud