The influence of different versions of FLUKA and GEANT4 on the calculation of response functions of ionization chambers in clinical proton beams

Objective.To investigate the influence of different versions of the Monte Carlo codesgeant4 andflukaon the calculation of overall response functionsfQof air-filled ionization chambers in clinical proton beams.Approach. fQfactors were calculated for six plane-parallel and four cylindrical ionization chambers withgeant4 andfluka. These factors were compared to already published values that were derived using older versions of these codes.Main results.Differences infQfactors calculated with different versions of the same Monte Carlo code can be up to ∼1%. Especially forgeant4, the updated version leads to a more pronounced dependence offQon proton energy and to smallerfQfactors for high energies.Significance.Different versions of the same Monte Carlo code can lead to differences in the calculation offQfactors of up to ∼1% without changing the simulation setup, transport parameters, ionization chamber geometry modeling, or employed physics lists. These findings support the statement that the dominant contributor to the overall uncertainty of Monte Carlo calculatedfQfactors are type-B uncertainties.

Butterfly Transforms for Efficient Representation of Spatially Variant Point Spread Functions in Bayesian Imaging

Bayesian imaging algorithms are becoming increasingly important in, e.g., astronomy, medicine and biology. Given that many of these algorithms compute iterative solutions to high-dimensional inverse problems, the efficiency and accuracy of the instrument response representation are of high importance for the imaging process. For efficiency reasons, point spread functions, which make up a large fraction of the response functions of telescopes and microscopes, are usually assumed to be spatially invariant in a given field of view and can thus be represented by a convolution. For many instruments, this assumption does not hold and degrades the accuracy of the instrument representation. Here, we discuss the application of butterfly transforms, which are linear neural network structures whose sizes scale sub-quadratically with the number of data points. Butterfly transforms are efficient by design, since they are inspired by the structure of the Cooley-Tukey fast Fourier transform. In this work, we combine them in several ways into butterfly networks, compare the different architectures with respect to their performance and identify a representation that is suitable for the efficient representation of a synthetic spatially variant point spread function up to a 1% error. Furthermore, we show its application in a short synthetic example.

Reducing the influence of geometry-induced gradient deformation in liquid chromatographic retention modelling

Rapid optimization of gradient liquid chromatographic (LC) separations often utilizes analyte retention modelling to predict retention times as function of eluent composition. However, due to the dwell volume and technical imperfections, the actual gradient may deviate from the set gradient in a fashion unique to the employed instrument. This makes accurate retention modelling for gradient LC challenging, in particular when very fast separations are pursued. Although gradient deformation has been addressed in method-transfer situations, it is rarely taken into account when reporting analyte retention parameters obtained from gradient LC data, hampering the comparison of data from various sources. In this study, a response-function-based algorithm was developed to determine analyte retention parameters corrected for geometry-induced deformations by specific LC instruments. Out of a number of mathematical distributions investigated as response-functions, the so-called "stable function" was found to describe the formed gradient most accurately. The four parameters describing the model resemble the statistical moments of the distribution and are related to chromatographic parameters, such as dwell volume and flow rate. The instrument-specific response function can then be used to predict the actual shape of any other gradient programmed on that instrument. To incorporate the predicted gradient in the retention modelling of the analytes, the model was extended to facilitate an unlimited number of linear gradient steps to solve the equations numerically. The significance and impact of distinct gradient deformation for fast gradients was demonstrated using three different LC instruments. As a proof of principle, the algorithm and retention parameters obtained on a specific instrument were used to predict the retention times on different instruments. The relative error in the predicted retention times went down from an average of 9.8% and 12.2% on the two other instruments when using only a dwell-volume correction to 2.1% and 6.5%, respectively, when using the proposed algorithm. The corrected retention parameters are less dependent on geometry-induced instrument effects.

Has the sensitivity of soybean cultivars to ozone pollution increased with time? An analysis of published dose-response data

The rising trend in concentrations of ground-level ozone (O3 ) - a common air pollutant and phytotoxin - currently being experienced in some world regions represents a threat to agricultural yield. Soybean (Glycine max (L.) Merr.) is an O3 -sensitive crop species and is experiencing increasing global demand as a dietary protein source and constituent of livestock feed. In this study, we collate O3 exposure-yield data for 49 soybean cultivars, from 28 experimental studies published between 1982 and 2014, to produce an updated dose-response function for soybean. Different cultivars were seen to vary considerably in their sensitivity to O3 , with estimated yield loss due to O3 ranging from 13.3% for the least sensitive cultivar to 37.9% for the most sensitive, at a 7-h mean O3 concentration (M7) of 55 ppb - a level frequently observed in regions of the USA, India and China in recent years. The year of cultivar release, country of data collection and type of O3 exposure used were all important explanatory variables in a multivariate regression model describing soybean yield response to O3 . The data show that the O3 sensitivity of soybean cultivars increased by an average of 32.5% between 1960 and 2000, suggesting that selective breeding strategies targeting high yield and high stomatal conductance may have inadvertently selected for greater O3 sensitivity over time. Higher sensitivity was observed in data from India and China compared to the USA, although it is difficult to determine whether this effect is the result of differential cultivar physiology, or related to local environmental factors such as co-occurring pollutants. Gaining further understanding of the underlying mechanisms that govern the sensitivity of soybean cultivars to O3 will be important in shaping future strategies for breeding O3 -tolerant cultivars.

Evolution of marginal populations of an invasive vine increases the likelihood of future spread

The prediction of invasion patterns may require an understanding of intraspecific differentiation in invasive species and its interaction with climate change. We compare Japanese honeysuckle (Lonicera japonica) plants from the core (100-150 yr old) and northern margin (< 65 yr old) of their North American invaded range to determine whether evolution during invasion increases the probability of future expansion. Plants from populations in the core and margin were compared in two sites beyond the northern range edge to assess their potential to invade novel areas. Data were compared with previous work to assess the effect of latitudinal climate on L. japonica spread. Winter survival in current climates was modeled and projected for future climates to predict future spread. Margin plants were larger and had 60% greater survival than core plants at sites beyond the northern range edge. Overall, winter survival decreased with increasing latitude and decreasing temperature, and was greater in margin plants than core plants. Models suggested that greater winter tolerance in margin populations has increased L. japonica's northward spread by 76 km, and that this survival advantage will persist under future climates. These results demonstrate that evolution during invasion may increase spread beyond predictions using increasing global temperatures alone.

A point-process response model for spike trains from single neurons in neural circuits under optogenetic stimulation

Optogenetics is a new tool to study neuronal circuits that have been genetically modified to allow stimulation by flashes of light. We study recordings from single neurons within neural circuits under optogenetic stimulation. The data from these experiments present a statistical challenge of modeling a high-frequency point process (neuronal spikes) while the input is another high-frequency point process (light flashes). We further develop a generalized linear model approach to model the relationships between two point processes, employing additive point-process response functions. The resulting model, point-process responses for optogenetics (PRO), provides explicit nonlinear transformations to link the input point process with the output one. Such response functions may provide important and interpretable scientific insights into the properties of the biophysical process that governs neural spiking in response to optogenetic stimulation. We validate and compare the PRO model using a real dataset and simulations, and our model yields a superior area-under-the-curve value as high as 93% for predicting every future spike. For our experiment on the recurrent layer V circuit in the prefrontal cortex, the PRO model provides evidence that neurons integrate their inputs in a sophisticated manner. Another use of the model is that it enables understanding how neural circuits are altered under various disease conditions and/or experimental conditions by comparing the PRO parameters.

Characterization of a piezo bendable X-ray mirror

A full-scale piezo bendable mirror built as a prototype for an offset mirror at the European XFEL is characterized. The piezo ceramic elements are glued onto the mirror substrate, side-face on with respect to the reflecting surface. Using a nanometre optical component measuring machine and a large-aperture Fizeau interferometer, the mirror profile and influence functions were characterized, and further analysis was made to investigate the junction effect, hysteresis, twisting and reproducibility.