1,445 research outputs found
Modeling of Island Block Scatter for Intensity Modulated Bolus Electron Conformal Therapy
Purpose: Bolus electron conformal therapy (BECT) benefits treatment of the post-mastectomy chest wall, head and neck, paraspinal muscles, and extremities. Patient dose heterogeneities caused by bolus can be reduced through intensity modulation (IM) across the incident electron beam. This requires passive radiotherapy intensity modulation for electrons (PRIME) devices, which utilize tungsten pins (island blocks) imbedded in machinable foam. IM-BECT treatment planning requires accurate dose calculation using the pencil beam redefinition dose algorithm (PBRA). Currently, the PBRA models island blocks as perfect collimators. This work explores models to account for electrons scattering into and out of the sides of island blocks.
Methods: A pencil beam model was used to compute a pin diameter (dIS) that corrected for in-scatter for a given beam energy and physical (nominal) pin diameter (dnom). Percent depth-dose and off-axis profiles in water were measured for each of 36 combinations of four PRIME devices, each with uniform pin diameters (0.0, 0.158, 0.273, 0.352 cm), three beam energies (7, 13, 20 MeV), and three SSDs (100, 105, 110 cm). Similarly, out-scattered electrons were modeled by modifying pin diameter. An initial model based on Monte Carlo calculating a pin’s effect on the dose distribution failed to improve accuracy of the PBRA-calculated dose relative to that calculated using dnom. Therefore, a second model was developed, which estimated out-scatter as the difference between measured and in-scatter-adjusted PBRA-calculated dose distributions. Then, a single out-scatter dose correction was determined using a least squares minimization, from which a new pin diameter (dIS+OS) was determined.
Results: A table of dIS+OS values was generated as a function of beam energy, SSD, and dnom. For the 27 combinations, passing rates (3%/3 mm) for the PBRA-calculated versus measured dose distributions were determined; compared to those using dnom, those using dIS+OS improved for 11, remained the same for 13, and worsened for 3.
Conclusions: The hypothesis was only conditionally met. However, upon study completion it was discovered that PRIME devices used for measurement were incorrectly fabricated. Future measurements and data analysis with correctly fabricated devices will refine scatter corrections, possibly making both Monte Carlo and measurement methods acceptable
On the extremes of randomly sub-sampled time series
In this paper, we investigate the extremal properties of randomly sub-sampled stationary sequences. Motivation comes from the need to account for the effect of missing values on the analysis of time series and the comparison of schemes for monitoring systems with breakdowns or systems with automatic replacement of devices in case of failures
The role of architectural reconstruction in a post-war context: the case of Mosul
This work addresses the topic of architectural reconstruction in a post-war context, in
this case in Mosul, Iraq. Heavily damaged during the war against ISIS, the city faces the immense
task of cleaning, restructuring, and rebuilding. The damaged buildings are diverse, but the
ancient monuments require specific care as they carry the memory and the heritage of a
traumatized community. Both in the cases of partial or complete destruction, the architectural
intervention needs to face both cultural and the preservation dimensions of reconstruction. This
approach is based on interventions in strategic neuralgic points for the community life such as
the market, a religious structure, and the baths. These symbolic spaces host the social, economic,
and religious activities that gather the inhabitants. They are also the stages of the traditions and
cultural life of Mosul. The reconstitution of the inhabitants' habits and sense of community is
centred around these locations and planned to spread around the urban fabric following the
redevelopment of the city. Our three different sites are the Souk, the Great Mosque and the
Hammam. These projects address several challenges: the construction of a new building inspired
by the existing urban fabric, the partial reconstruction of an ancient monument and the
construction of a new building in dialogue with existing Ottoman ruins. The balance between
tradition and modernization; memory and oblivion; reconstruction and restoration is the focus of
the paper
An Optimal Algorithm for the Maximum-Density Segment Problem
We address a fundamental problem arising from analysis of biomolecular
sequences. The input consists of two numbers and and a
sequence of number pairs with . Let {\em segment}
of be the consecutive subsequence of between indices and
. The {\em density} of is
. The {\em maximum-density
segment problem} is to find a maximum-density segment over all segments
with . The best
previously known algorithm for the problem, due to Goldwasser, Kao, and Lu,
runs in time. In the present paper, we solve
the problem in O(n) time. Our approach bypasses the complicated {\em right-skew
decomposition}, introduced by Lin, Jiang, and Chao. As a result, our algorithm
has the capability to process the input sequence in an online manner, which is
an important feature for dealing with genome-scale sequences. Moreover, for a
type of input sequences representable in space, we show how to
exploit the sparsity of and solve the maximum-density segment problem for
in time.Comment: 15 pages, 12 figures, an early version of this paper was presented at
11th Annual European Symposium on Algorithms (ESA 2003), Budapest, Hungary,
September 15-20, 200
Dynamic fator Models for bivariate Count Data: an application to fire activity
The study of forest re activity, in its several aspects, is essencial to understand the
phenomenon and to prevent environmental public catastrophes. In this context the
analysis of monthly number of res along several years is one aspect to have into
account in order to better comprehend this tematic. The goal of this work is to analyze
the monthly number of forest res in the neighboring districts of Aveiro and Coimbra,
Portugal, through dynamic factor models for bivariate count series. We use a bayesian
approach, through MCMC methods, to estimate the model parameters as well as to
estimate the common latent factor to both series
Bivariate models for time series of counts: a comparison study between PBINAR models and dynamic factor models
The aim of this work is to assess the modeling performance of two bivariate models for time series of counts, within the context of a forest fires analysis in two counties of Portugal. The first model is a periodic bivariate integer-valued autoregressive (PBINAR), easily interpreted due to the PINAR description of each component. The alternative model is a bivariate dynamic factor (BDF) that has a flexible structure, with the dynamics described through the mean value of each component that is a function of latent factors. The results reveal that BDF model exhibits a better ability to capture the dependence structure.publishe
The Role of PARP Inhibitors in the Ovarian Cancer Microenvironment: Moving Forward From Synthetic Lethality
PARP inhibitors (PARPi) have shown promising clinical results and have revolutionized the landscape of ovarian cancer management in the last few years. While the core mechanism of action of these drugs has been largely analyzed, the interaction between PARP inhibitors and the microenvironment has been scarcely researched so far. Recent data shows a variety of mechanism through which PARPi might influence the tumor microenvironment and especially the immune system response, that might even partly be the reason behind PARPi efficacy. One of many pathways that are affected is the cGAS-cGAMP-STING; the upregulation of STING (stimulator of interferon genes), produces more Interferon ϒ and pro inflammatory cytokines, thus increasing intratumoral CD4+ and CD8+ T cells. Upregulation of immune checkpoints such as PD1-PDL1 has also been observed. Another interesting mechanism of interaction between PARPi and microenvironment is the ability of PARPi to kill hypoxic cells, as these cells show an intrinsic reduction in the expression and function of the proteins involved in HR. This process has been defined “contextual synthetic lethality”. Despite ovarian cancer having always been considered a poor responder to immune therapy, data is now shedding a new light on the matter. First, OC is much more heterogenous than previously thought, therefore it is fundamental to select predictive biomarkers for target therapies. While single agent therapies have not yielded significant results on the long term, influencing the immune system and the tumor microenvironment via the concomitant use of PARPi and other target therapies might be a more successful approach
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