320 research outputs found
Parameterized Differential Equations over k((t))(x)
In this article, we consider the inverse Galois problem for parameterized
differential equations over k((t))(x) with k any field of characteristic zero
and use the method of patching over fields due to Harbater and Hartmann. As an
application, we prove that every connected semisimple k((t))-split linear
algebraic group is a parameterized Galois group over k((t))(x).Comment: 13 page
Embedding problems of division algebras
A finite group G is called admissible over a given field if there exists a
central division algebra that contains a G-Galois field extension as a maximal
subfield. We give a definition of embedding problems of division algebras that
extends both the notion of embedding problems of fields as in classical Galois
theory, and the question which finite groups are admissible over a field. In a
recent work by Harbater, Hartmann and Krashen, all admissible groups over
function fields of curves over complete discretely valued fields with
algebraically closed residue field of characteristic zero have been
characterized. We show that also certain embedding problems of division
algebras over such a field can be solved for admissible groups.Comment: 19 page
Tenfold your photons -- a physically-sound approach to filtering-based variance reduction of Monte-Carlo-simulated dose distributions
X-ray dose constantly gains interest in the interventional suite. With dose
being generally difficult to monitor reliably, fast computational methods are
desirable. A major drawback of the gold standard based on Monte Carlo (MC)
methods is its computational complexity. Besides common variance reduction
techniques, filter approaches are often applied to achieve conclusive results
within a fraction of time. Inspired by these methods, we propose a novel
approach. We down-sample the target volume based on the fraction of mass,
simulate the imaging situation, and then revert the down-sampling. To this end,
the dose is weighted by the mass energy absorption, up-sampled, and distributed
using a guided filter. Eventually, the weighting is inverted resulting in
accurate high resolution dose distributions. The approach has the potential to
considerably speed-up MC simulations since less photons and boundary checks are
necessary. First experiments substantiate these assumptions. We achieve a
median accuracy of 96.7 % to 97.4 % of the dose estimation with the proposed
method and a down-sampling factor of 8 and 4, respectively. While maintaining a
high accuracy, the proposed method provides for a tenfold speed-up. The overall
findings suggest the conclusion that the proposed method has the potential to
allow for further efficiency.Comment: 6 pages, 3 figures, Bildverarbeitung f\"ur die Medizin 202
An RDoC-inspired examination of pharmacological, sex-specific, and hormonal modulators of Positive Valence Systems
The Positive Valence Systems (PVS) are a major domain of the Research
Domain Criteria framework (RDoC), which aims at promoting precision medicine
for psychiatry, based on a profound understanding of the psychological and
biological basis of shared behavioral symptoms. The PVS domain describes
basic processes of reward processing, which can be disrupted in several mental
disorders, such as schizophrenia, substance use disorders, and major
depressive disorder. Investigating basic mechanisms of PVS constructs is
important to understand central aspects which contribute to these transdiagnostic
motivational syndromes.
In my doctoral thesis, I investigated pharmacological, sex-specific, and
hormonal modulators of PVS constructs. I focused on the constructs reward
responsiveness and reward valuation in the context of motivational behavior in
healthy humans. In study 1, I examined the neurotransmitter serotonin, and in
particular a selective serotonin reuptake inhibitor (SSRI) as modulator of reward
responsiveness on a neural level, using functional magnetic resonance imaging
(fMRI). In studies 2 and 3, I inquired into sex-specific and hormonal modulators
of reward valuation to elucidate sex-specific integration of benefits and costs on
a behavioral level.
In study 1, I found that an acute SSRI dose modulated the processing of
punishment cues in caudate and thalamus brain regions, which have been
identified as transdiagnostic neural markers of disrupted reward responsiveness.
In study 2, I identified sex differences in reward valuation, which depended on
different encoding of benefits, not costs. Study 3 did not yield substantial
differences in reward valuation depending on different hormonal states in women.
The RDoC initiative aims at understanding core features and modulators of
shared behavioral symptoms, ranging from normal to abnormal behavior.
Understanding basic mechanisms is an important first step towards
transdiagnostic clinical translation. Within this scope, my work has implications
for testing clinical translation of pharmacological and behavioral treatments specifically targeted to PVS constructs, which take sex-specific behavioral
variability into account
Correlates of depressive symptoms among Latino and Non-Latino White adolescents: Findings from the 2003 California Health Interview Survey
BACKGROUND: The prevalence of depression is increasing not only among adults, but also among adolescents. Several risk factors for depression in youth have been identified, including female gender, increasing age, lower socio-economic status, and Latino ethnic background. The literature is divided regarding the role of acculturation as risk factor among Latino youth. We analyzed the correlates of depressive symptoms among Latino and Non-Latino White adolescents residing in California with a special focus on acculturation. METHODS: We performed an analysis of the adolescent sample of the 2003 California Health Interview Survey, which included 3,196 telephone-interviews with Latino and Non-Latino White adolescents between the ages of 12 and 17. Depressive symptomatology was measured with a reduced version of the Center for Epidemiologic Studies Depression Scale. Acculturation was measured by a score based on language in which the interview was conducted, language(s) spoken at home, place of birth, number of years lived in the United States, and citizenship status of the adolescent and both of his/her parents, using canonical principal component analysis. Other variables used in the analysis were: support provided by adults at school and at home, age of the adolescent, gender, socio-economic status, and household type (two parent or one parent household). RESULTS: Unadjusted analysis suggested that the risk of depressive symptoms was twice as high among Latinos as compared to Non-Latino Whites (10.5% versus 5.5 %, p < 0.001). The risk was slightly higher in the low acculturation group than in the high acculturation group (13.1% versus 9.7%, p = 0.12). Similarly, low acculturation was associated with an increased risk of depressive symptoms in multivariate analysis within the Latino subsample (OR 1.54, CI 0.97–2.44, p = 0.07). Latino ethnicity emerged as risk factor for depressive symptoms among the strata with higher income and high support at home and at school. In the disadvantaged subgroups (higher poverty, low support at home and at school) Non-Latino Whites and Latinos had a similar risk of depressive symptoms. CONCLUSION: Our findings suggest that the differences in depressive symptoms between Non-Latino Whites and Latino adolescents disappear at least in some strata after adjusting for socio-demographic and social support variables
Effects of Tissue Material Properties on X-Ray Image, Scatter and Patient Dose Determined using Monte Carlo Simulations
With increasing patient and staff X-ray radiation awareness, many efforts
have been made to develop accurate patient dose estimation methods. To date,
Monte Carlo (MC) simulations are considered golden standard to simulate the
interaction of X-ray radiation with matter. However, sensitivity of MC
simulation results to variations in the experimental or clinical setup of image
guided interventional procedures are only limited studied. In particular, the
impact of patient material compositions is poorly investigated. This is mainly
due to the fact, that these methods are commonly validated in phantom studies
utilizing a single anthropomorphic phantom. In this study, we therefore
investigate the impact of patient material parameters mapping on the outcome of
MC X-ray dose simulations. A computation phantom geometry is constructed and
three different commonly used material composition mappings are applied. We
used the MC toolkit Geant4 to simulate X-ray radiation in an interventional
setup and compared the differences in dose deposition, scatter distributions
and resulting X-ray images. The evaluation shows a discrepancy between
different material composition mapping up to 20 % concerning directly
irradiated organs. These results highlight the need for standardization of
material composition mapping for MC simulations in a clinical setup.Comment: 6 pages, 4 figures, Bildverarbeitung f\"ur die Medizin 201
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