6 resultados para Forward model

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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This paper describes sideband response measurements and atmospheric observations with a double sideband and two Single Sideband (SSB) receiver prototypes developed for the multi-beam limb sounder instrument stratosphere-troposphere exchange and climate monitor radiometer. We first show an advanced Fourier-Transform Spectroscopy (FTS) method for sideband response and spurious signal characterization. We then present sideband response measurements of the different prototype receivers and we compare the results of the SSB receivers with sideband measurements by injecting a continuous wave signal into the upper and lower sidebands. The receivers were integrated into a total-power radiometer and atmospheric observations were carried out. The observed spectra were compared to forward model spectra to conclude on the sideband characteristics of the different receivers. The two sideband characterization methods show a high degree of agreement for both SSB receivers with various local oscillator settings. The measured sideband response was used to correct the forward model simulations. This improves the agreement with the atmospheric observations and explains spectral features caused by an unbalanced sideband response. The FTS method also allows to quantify the influence of spurious harmonic responses of the receiver.

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A growing world population, changing climate and limiting fossil fuels will provide new pressures on human production of food, medicine, fuels and feed stock in the twenty-first century. Enhanced crop production promises to ameliorate these pressures. Crops can be bred for increased yields of calories, starch, nutrients, natural medicinal compounds, and other important products. Enhanced resistance to biotic and abiotic stresses can be introduced, toxins removed, and industrial qualities such as fibre strength and biofuel per mass can be increased. Induced and natural mutations provide a powerful method for the generation of heritable enhanced traits. While mainly exploited in forward, phenotype driven, approaches, the rapid accumulation of plant genomic sequence information and hypotheses regarding gene function allows the use of mutations in reverse genetic approaches to identify lesions in specific target genes. Such gene-driven approaches promise to speed up the process of creating novel phenotypes, and can enable the generation of phenotypes unobtainable by traditional forward methods. TILLING (Targeting Induced Local Lesions IN Genome) is a high-throughput and low cost reverse genetic method for the discovery of induced mutations. The method has been modified for the identification of natural nucleotide polymorphisms, a process called Ecotilling. The methods are general and have been applied to many species, including a variety of different crops. In this chapter the current status of the TILLING and Ecotilling methods and provide an overview of progress in applying these methods to different plant species, with a focus on work related to food production for developing nations.

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Endocrine-disrupting compounds (EDCs) are widespread in the aquatic environment and can cause alterations in development, physiological homeostasis and health of vertebrates. Zebrafish, Danio rerio, has been suggested as a model species to identify targets as well as modes of EDC action. In fact, zebrafish has been found useful in EDC screening, in EDC effects assessment and in studying targets and mechanisms of EDC action. Since many of the environmental EDCs interfere with the sex steroid system of vertebrates, most EDC studies with zebrafish addressed disruption of sexual differentiation and reproduction. However, other targets of EDCs action must not be overlooked. For using a species as a toxicological model, a good knowledge of the biological traits of this species is a pre-requisite for the rational design of test protocols and endpoints as well as for the interpretation and extrapolation of the toxicological findings. Due to the genomic resources available for zebrafish and the long experience with zebrafish in toxicity testing, it is easily possible to establish molecular endpoints for EDC effects assessment. Additionally, the zebrafish model offers a number of technical advantages including ease and cost of maintenance, rapid development, high fecundity, optical transparency of embryos supporting phenotypic screening, existence of many mutant strains, or amenability for both forward and reverse genetics. To date, the zebrafish has been mainly used to identify molecular targets of EDC action and to determine effect thresholds, while the potential of this model species to study immediate and delayed physiological consequences of molecular interactions has been instrumentalized only partly. One factor that may limit the exploitation of this potential is the still rather fragmentary knowledge of basic biological and endocrine traits of zebrafish. Information on species-specific features in endocrine processes and biological properties, however, need to be considered in establishing EDC test protocols using zebrafish, in extrapolating findings from zebrafish to other vertebrate species, and in understanding how EDC-induced gene expression changes translate into disease.

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The past 1500 years provide a valuable opportunity to study the response of the climate system to external forcings. However, the integration of paleoclimate proxies with climate modeling is critical to improving the understanding of climate dynamics. In this paper, a climate system model and proxy records are therefore used to study the role of natural and anthropogenic forcings in driving the global climate. The inverse and forward approaches to paleoclimate data–model comparison are applied, and sources of uncertainty are identified and discussed. In the first of two case studies, the climate model simulations are compared with multiproxy temperature reconstructions. Robust solar and volcanic signals are detected in Southern Hemisphere temperatures, with a possible volcanic signal detected in the Northern Hemisphere. The anthropogenic signal dominates during the industrial period. It is also found that seasonal and geographical biases may cause multiproxy reconstructions to overestimate the magnitude of the long-term preindustrial cooling trend. In the second case study, the model simulations are compared with a coral δ18O record from the central Pacific Ocean. It is found that greenhouse gases, solar irradiance, and volcanic eruptions all influence the mean state of the central Pacific, but there is no evidence that natural or anthropogenic forcings have any systematic impact on El Niño–Southern Oscillation. The proxy climate relationship is found to change over time, challenging the assumption of stationarity that underlies the interpretation of paleoclimate proxies. These case studies demonstrate the value of paleoclimate data–model comparison but also highlight the limitations of current techniques and demonstrate the need to develop alternative approaches.

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PURPOSE This paper describes the development of a forward planning process for modulated electron radiotherapy (MERT). The approach is based on a previously developed electron beam model used to calculate dose distributions of electron beams shaped by a photon multi leaf collimator (pMLC). METHODS As the electron beam model has already been implemented into the Swiss Monte Carlo Plan environment, the Eclipse treatment planning system (Varian Medical Systems, Palo Alto, CA) can be included in the planning process for MERT. In a first step, CT data are imported into Eclipse and a pMLC shaped electron beam is set up. This initial electron beam is then divided into segments, with the electron energy in each segment chosen according to the distal depth of the planning target volume (PTV) in beam direction. In order to improve the homogeneity of the dose distribution in the PTV, a feathering process (Gaussian edge feathering) is launched, which results in a number of feathered segments. For each of these segments a dose calculation is performed employing the in-house developed electron beam model along with the macro Monte Carlo dose calculation algorithm. Finally, an automated weight optimization of all segments is carried out and the total dose distribution is read back into Eclipse for display and evaluation. One academic and two clinical situations are investigated for possible benefits of MERT treatment compared to standard treatments performed in our clinics and treatment with a bolus electron conformal (BolusECT) method. RESULTS The MERT treatment plan of the academic case was superior to the standard single segment electron treatment plan in terms of organs at risk (OAR) sparing. Further, a comparison between an unfeathered and a feathered MERT plan showed better PTV coverage and homogeneity for the feathered plan, with V95% increased from 90% to 96% and V107% decreased from 8% to nearly 0%. For a clinical breast boost irradiation, the MERT plan led to a similar homogeneity in the PTV compared to the standard treatment plan while the mean body dose was lower for the MERT plan. Regarding the second clinical case, a whole breast treatment, MERT resulted in a reduction of the lung volume receiving more than 45% of the prescribed dose when compared to the standard plan. On the other hand, the MERT plan leads to a larger low-dose lung volume and a degraded dose homogeneity in the PTV. For the clinical cases evaluated in this work, treatment plans using the BolusECT technique resulted in a more homogenous PTV and CTV coverage but higher doses to the OARs than the MERT plans. CONCLUSIONS MERT treatments were successfully planned for phantom and clinical cases, applying a newly developed intuitive and efficient forward planning strategy that employs a MC based electron beam model for pMLC shaped electron beams. It is shown that MERT can lead to a dose reduction in OARs compared to other methods. The process of feathering MERT segments results in an improvement of the dose homogeneity in the PTV.

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When considering data from many trials, it is likely that some of them present a markedly different intervention effect or exert an undue influence on the summary results. We develop a forward search algorithm for identifying outlying and influential studies in meta-analysis models. The forward search algorithm starts by fitting the hypothesized model to a small subset of likely outlier-free studies and proceeds by adding studies into the set one-by-one that are determined to be closest to the fitted model of the existing set. As each study is added to the set, plots of estimated parameters and measures of fit are monitored to identify outliers by sharp changes in the forward plots. We apply the proposed outlier detection method to two real data sets; a meta-analysis of 26 studies that examines the effect of writing-to-learn interventions on academic achievement adjusting for three possible effect modifiers, and a meta-analysis of 70 studies that compares a fluoride toothpaste treatment to placebo for preventing dental caries in children. A simple simulated example is used to illustrate the steps of the proposed methodology, and a small-scale simulation study is conducted to evaluate the performance of the proposed method. Copyright © 2016 John Wiley & Sons, Ltd.