458 research outputs found
LibCPIXE: a PIXE simulation open-source library for multilayered samples
Most particle induced X-ray emission (PIXE) data analysis codes are not
focused on handling multilayered samples. We have developed an open-source
library called "LibCPIXE", for PIXE data analysis. It is written in standard C
and implements functions for simulating X-ray yields of PIXE spectra taken from
arbitrary samples, including multilayered targets. The library is designed to
be fast, portable, modular and scalable, as well as to facilitate its
incorporation into any existing program. In order to demonstrate the
capabilities of the library, a program called CPIXE was developed and used to
analyze various real samples involving both bulk and layered samples. Just as
the library, the CPIXE source code is freely available under the General Public
License. We demonstrate that it runs both under GNU/Linux systems as well as
under MS Windows. There is in principle no limitation to port it to other
platforms
Application of Minimal Subtraction Renormalization to Crossover Behavior near the He Liquid-Vapor Critical Point
Parametric expressions are used to calculate the isothermal susceptibility,
specific heat, order parameter, and correlation length along the critical
isochore and coexistence curve from the asymptotic region to crossover region.
These expressions are based on the minimal-subtraction renormalization scheme
within the model. Using two adjustable parameters in these
expressions, we fit the theory globally to recently obtained experimental
measurements of isothermal susceptibility and specific heat along the critical
isochore and coexistence curve, and early measurements of coexistence curve and
light scattering intensity along the critical isochore of He near its
liquid-vapor critical point. The theory provides good agreement with these
experimental measurements within the reduced temperature range
Childhood maltreatment and adulthood victimization:An evidence-based model
There is ample evidence showing that childhood maltreatment increases two to three fold the risk of victimization in adulthood. Various risk factors, including posttraumatic stress disorder (PTSD) symptoms, dissociation, self-blame, and alcohol abuse are related to revictimization. Although previous research examined associations between risk factors for revictimization, the evidence is limited and the proposed models mostly include a handful of risk factors. Therefore, it is critical to investigate a more comprehensive model explaining the link between childhood maltreatment and adulthood (re)victimization. Accordingly, this study tested a data-driven theoretical path model consisting of 33 variables (and their associations) that could potentially enhance understanding of factors explaining revictimization. Cross-sectional data derived from a multi-wave study were used for this investigation. Participants (N = 2156, age mean = 19.94, SD = 2.89) were first-year female psychology students in the Netherlands and New Zealand, who responded to a battery of questionnaires and performed two computer tasks. The path model created by structural equation modelling using modification indices showed that peritraumatic dissociation, PTSD symptoms, trauma load, loneliness, and drug use were important mediators. Attachment styles, maladaptive schemas, meaning in life, and sex motives connected childhood maltreatment to adulthood victimization via other factors (i.e., PTSD symptoms, risky sex behavior, loneliness, emotion dysregulation, and sex motives). The model indicated that childhood maltreatment was associated with cognitive patterns (e.g., anxious attachment style), which in turn were associated with emotional factors (e.g., emotion dysregulation), and then with behavioral factors (e.g., risky sex behavior) resulting in revictimization. The findings of the study should be interpreted in the light of the limitations. In particular, the cross-sectional design of the study hinders us from ascertaining that the mediators preceded the outcome variable. </p
Genomic and protein expression analysis reveals flap endonuclease 1 (FEN1) as a key biomarker in breast and ovarian cancer
FEN1 has key roles in Okazaki fragment maturation during replication, long patch base excision repair, rescue of stalled replication forks, maintenance of telomere stability and apoptosis. FEN1 may be dysregulated in breast and ovarian cancers and have clinicopathological significance in patients. We comprehensively investigated FEN1 mRNA expression in multiple cohorts of breast cancer [training set (128), test set (249), external validation (1952)]. FEN1 protein expression was evaluated in 568 oestrogen receptor (ER) negative breast cancers, 894 ER positive breast cancers and 156 ovarian epithelial cancers. FEN1 mRNA overexpression was highly significantly associated with high grade (p= 4.89 x 10 - 57) , high mitotic index (p= 5.25 x 10 - 28), pleomorphism (p= 6.31 x 10-19), ER negative (p= 9.02 x 10-35 ), PR negative (p= 9.24 x 10-24 ), triple negative phenotype (p= 6.67 x 10-21) , PAM50.Her2 (p=5.19 x 10-13 ), PAM50.Basal (p=2.7 x 10-41), PAM50.LumB (p=1.56 x 10-26), integrative molecular cluster 1 (intClust.1) ( p=7.47 x 10-12), intClust.5 (p=4.05 x 10-12) and intClust. 10 (p=7.59 x 10-38 ) breast cancers. FEN1 mRNA overexpression is associated with poor breast cancer specific survival in univariate (p=4.4 x 10-16) and multivariate analysis (p=9.19 x 10-7). At the protein level, in ER positive tumours , FEN1 overexpression remains significantly linked to high grade, high mitotic index and pleomorphism (ps< 0.01). In ER negative tumours, high FEN1 is significantly associated with pleomorphism, tumour type, lymphovascular invasion, triple negative phenotype, EGFR and HER2 expression (ps<0.05). In ER positive as well as in ER negative tumours, FEN1 protein over expression is associated with poor survival in univariate and multivariate analysis (ps<0.01). In ovarian epithelial cancers , similarly, FEN1 overexpression is associated with high grade, high stage and poor survival (ps<0.05). We conclude that FEN1 is a promising biomarker in breast and ovarian epithelial cancer
Higgs-Boson Production Induced by Bottom Quarks
Bottom quark-induced processes are responsible for a large fraction of the
LHC discovery potential, in particular for supersymmetric Higgs bosons.
Recently, the discrepancy between exclusive and inclusive Higgs boson
production rates has been linked to the choice of an appropriate bottom
factorization scale. We investigate the process kinematics at hadron colliders
and show that it leads to a considerable decrease in the bottom factorization
scale. This effect is the missing piece needed to understand the corresponding
higher order results. Our results hold generally for charged and for neutral
Higgs boson production at the LHC as well as at the Tevatron. The situation is
different for single top quark production, where we find no sizeable
suppression of the factorization scale. Turning the argument around, we can
specify how large the collinear logarithms are, which can be resummed using the
bottom parton picture.Comment: 18 page
Understanding Helical Magnetic Dynamo Spectra with a Nonlinear Four-Scale Theory
Recent MHD dynamo simulations for magnetic Prandtl number demonstrate
that when MHD turbulence is forced with sufficient kinetic helicity, the
saturated magnetic energy spectrum evolves from having a single peak below the
forcing scale to become doubly peaked with one peak at the system (=largest)
scale and one at the forcing scale. The system scale field growth is well
modeled by a recent nonlinear two-scale nonlinear helical dynamo theory in
which the system and forcing scales carry magnetic helicity of opposite sign.
But a two-scale theory cannot model the shift of the small-scale peak toward
the forcing scale. Here I develop a four-scale helical dynamo theory which
shows that the small-scale helical magnetic energy first saturates at very
small scales, but then successively saturates at larger values at larger
scales, eventually becoming dominated by the forcing scale. The transfer of the
small scale peak to the forcing scale is completed by the end of the kinematic
growth regime of the large scale field, and does not depend on magnetic
Reynolds number for large . The four-scale and two-scale theories
subsequently evolve almost identically, and both show significant field growth
on the system and forcing scales that is independent of . In the present
approach, the helical and nonhelical parts of the spectrum are largely
decoupled. Implications for fractionally helical turbulence are discussed.Comment: 19 Pages, LaTex, (includes 4 figs at the end), in press, MNRA
Charged Higgs Boson Production in Bottom-Gluon Fusion
We compute the complete next-to-leading order SUSY-QCD corrections for the
associated production of a charged Higgs boson with a top quark via
bottom-gluon fusion. We investigate the applicability of the bottom parton
description in detail. The higher order corrections can be split into real and
virtual corrections for a general two Higgs doublet model and into additional
massive supersymmetric loop contributions. We find that the perturbative
behavior is well under control. The supersymmetric contributions consist of the
universal bottom Yukawa coupling corrections and non-factorizable diagrams.
Over most of the relevant supersymmetric parameter space the Yukawa coupling
corrections are sizeable, while the remaining supersymmetric loop contributions
are negligible.Comment: 18 pages, v2: some discussions added, v3: published versio
Progress in operational modeling in support of oil spill response
Following the 2010 Deepwater Horizon accident of a massive blow-out in the Gulf of Mexico, scientists from government, industry, and academia collaborated to advance oil spill modeling and share best practices in model algorithms, parameterizations, and application protocols. This synergy was greatly enhanced by research funded under the Gulf of Mexico Research Initiative (GoMRI), a 10-year enterprise that allowed unprecedented collection of observations and data products, novel experiments, and international collaborations that focused on the Gulf of Mexico, but resulted in the generation of scientific findings and tools of broader value. Operational oil spill modeling greatly benefited from research during the GoMRI decade. This paper provides a comprehensive synthesis of the related scientific advances, remaining challenges, and future outlook. Two main modeling components are discussed: Ocean circulation and oil spill models, to provide details on all attributes that contribute to the success and limitations of the integrated oil spill forecasts. These forecasts are discussed in tandem with uncertainty factors and methods to mitigate them. The paper focuses on operational aspects of oil spill modeling and forecasting, including examples of international operational center practices, observational needs, communication protocols, and promising new methodologies
Role of carbonate burial in Blue Carbon budgets
Calcium carbonates (CaCO 3 ) often accumulate in mangrove and seagrass sediments. As CaCO 3 production emits CO 2 , there is concern that this may partially offset the role of Blue Carbon ecosystems as CO 2 sinks through the burial of organic carbon (C org ). A global collection of data on inorganic carbon burial rates (C inorg , 12% of CaCO 3 mass) revealed global rates of 0.8 TgC inorg yr −1 and 15–62 TgC inorg yr −1 in mangrove and seagrass ecosystems, respectively. In seagrass, CaCO 3 burial may correspond to an offset of 30% of the net CO 2 sequestration. However, a mass balance assessment highlights that the C inorg burial is mainly supported by inputs from adjacent ecosystems rather than by local calcification, and that Blue Carbon ecosystems are sites of net CaCO 3 dissolution. Hence, CaCO 3 burial in Blue Carbon ecosystems contribute to seabed elevation and therefore buffers sea-level rise, without undermining their role as CO 2 sinks. © 2019, The Author(s)
- …