Examination of applicability of the ISO slab phantom as calibration phantom for the new ICRU 95 operational quantity personal dose

In this article, the proposal of ICRU/ICRP, that the ISO slab phantom should continue to be used as calibration phantom for the new ICRU Report 95 operational quantity personal dose should be legitimized by simulation and performance of experiments to determine backscatter factors on the ISO slab phantom and, in comparison, on an anthropomorphic Alderson Rando phantom. The scope of this work was restricted to the photon energy range of radiation qualities commonly used in X-ray diagnostics. For this purpose, a shadow-free diagnostic (SFD) ionization chamber was used to measure backscatter factors for X radiation in the energy range of 24 keV to 118 keV. The Monte Carlo code MCNP 6.2 was used to validate measurement results on the ISO slab phantom. Additionally, the influence of varying the SFD position on the Rando phantom on the backscatter factor was determined. Since backscatter factors on the ISO slab phantom differ only up to 5 % from those on the Rando phantom, it could be concluded that it is not necessary to develop a new phantom for calibrations in terms of personal dose. A position variation of the detector by few centimeters on the surface of the Rando phantom causes similarly large deviations and thus alone represents an equally large uncertainty contribution in practical personal dosimetry than that arising from the dissimilarity of the real human body to the ISO slab phantom.

Benchmarking the vertically integrated ice-sheet model IMAU-ICE (version 2.0)

Ice-dynamical processes constitute a large uncertainty in future projections of sea-level rise caused by anthropogenic climate change. Improving our understanding of these processes requires ice-sheet models that perform well at simulating both past and future ice-sheet evolution. Here, we present version 2.0 of the ice-sheet model IMAU-ICE, which uses the depth-integrated viscosity approximation (DIVA) to solve the stress balance. We evaluate its performance in a range of benchmark experiments, including simple analytical solutions, as well as both schematic and realistic model intercomparison exercises. IMAU-ICE has adopted recent developments in the numerical treatment of englacial stress and sub-shelf melt near the grounding-line, which result in good performance in experiments concerning grounding-line migration (MISMIP) and buttressing (ABUMIP). This makes it a model that is robust, versatile, and user-friendly, and which will provide a firm basis for (palaeo-)glaciological research in the coming years.

Application of random forest regressions on stellar parameters of A-type stars and feature extraction

Measuring the stellar parameters of A-type stars is more difficult than FGK stars because of the sparse features in their spectra and the degeneracy between effective temperature (Teff ) and gravity (logg). Modeling the relationship between fundamental stellar parameters and features through Machine Learning is possible because we can employ the advantage of big data rather than sparse known features. As soon as the model is successfully trained, it can be an efficient approach for predicting Teff and logg for A-type stars especially when there is large uncertainty in the continuum caused by flux calibration or extinction. In this paper, A- type stars are selected from LAMOST DR7 with signal-to-noise ratio greater than 50 and the Teff ranging within 7000K to 8500K. We perform the Random Forest (RF) algorithm, one of the most widely used Machine Learning algorithms to establish the regressio，relationship between the flux of all wavelengths and their corresponding stellar parameters((Teff ) and (logg) respectively). The trained RF model not only can regress the stellar parameters but also can obtain the rank of the wavelength based on their sensibility to parameters.According to the rankings, we define line indices by merging adjacent wavelengths. The objectively defined line indices in this work are amendments to Lick indices including some weak lines. We use the Support Vector Regression algorithm based on our new defined line indices to measure the temperature and gravity and use some common stars from Simbad to evaluate our result. In addition, the Gaia HR diagram is used for checking the accuracy of Teff and logg.

Orbital Period Refinement of CoRoT Planets with TESS Observations

CoRoT was the first space mission dedicated to exoplanet detection. Operational between 2007 and 2012, this mission discovered 37 transiting planets, including CoRoT-7b, the first terrestrial exoplanet with a measured size. The precision of the published transit ephemeris of most of these planets has been limited by the relative short durations of the CoRoT pointings, which implied a danger that the transits will become unobservable within a few years due to the uncertainty of their future transit epochs. Ground-based follow-up observations of the majority of the CoRoT planets have been published in recent years. Between Dec. 2018 and Jan. 2021, the TESS mission in its sectors 6 and 33 re-observed those CoRoT fields that pointed towards the Galactic anti-center. These data permitted the identification of transits from nine of the CoRoT planets, and the derivation of precise new transit epochs. The main motivation of this study has been to derive precise new ephemerides of the CoRoT planets, in order to keep these planets’ transits observable for future generations of telescopes. The TESS data were analyzed for the presence of transits and the epochs of these re-observed transits were measured. The original CoRoT epochs, epochs from ground-based follow-up observations and those from TESS were collected. From these data, updated ephemerides are presented for nine transiting planets discovered by the CoRoT mission in its fields pointing towards the Galactic anti-center. In three cases (CoRoT-4b, 19b and 20b), transits that would have been lost for ground observations, due to the large uncertainty in the previous ephemeris, have been recovered. The updated ephemerides permit transit predictions with uncertainties of less than 30 min for observations at least until the year 2030. No significant transit timing variations were found in these systems.

Modeling and interpreting hydrological responses of sustainable urban drainage systems with explainable machine learning methods

Sustainable urban drainage systems (SuDS) are decentralized stormwater management practices that mimic natural drainage processes. The hydrological processes of SuDS are often modeled using process-based models. However, it can require considerable effort to set up these models. This study thus proposes a machine learning (ML) method to directly learn the statistical correlations between the hydrological responses of SuDS and the forcing variables at sub-hourly timescales from observation data. The proposed methods are applied to two SuDS catchments with different sizes, SuDS practice types, and data availabilities in the USA for discharge prediction. The resulting models have high prediction accuracies (Nash–Sutcliffe efficiency, NSE, >0.70). ML explanation methods are then employed to derive the basis of each ML prediction, based on which the hydrological processes being modeled are then inferred. The physical realism of the inferred hydrological processes is then compared to that would be expected based on the domain-specific knowledge of the system being modeled. The inferred processes of some models, however, are found to be physically implausible. For instance, negative contributions of rainfall to runoff have been identified in some models. This study further empirically shows that an ML model's ability to provide accurate predictions can be uncorrelated with its ability to offer plausible explanations to the physical processes being modeled. Finally, this study provides a high-level overview of the practices of inferring physical processes from the ML modeling results and shows both conceptually and empirically that large uncertainty exists in every step of the inference processes. In summary, this study shows that ML methods are a useful tool for predicting the hydrological responses of SuDS catchments, and the hydrological processes inferred from modeling results should be interpreted cautiously due to the existence of large uncertainty in the inference processes.

Win-Stay-Lose-Shift as a self-confirming equilibrium in the iterated Prisoner’s Dilemma

Evolutionary game theory assumes that players replicate a highly scored player’s strategy through genetic inheritance. However, when learning occurs culturally, it is often difficult to recognize someone’s strategy just by observing the behaviour. In this work, we consider players with memory-one stochastic strategies in the iterated Prisoner’s Dilemma, with an assumption that they cannot directly access each other’s strategy but only observe the actual moves for a certain number of rounds. Based on the observation, the observer has to infer the resident strategy in a Bayesian way and chooses his or her own strategy accordingly. By examining the best-response relations, we argue that players can escape from full defection into a cooperative equilibrium supported by Win-Stay-Lose-Shift in a self-confirming manner, provided that the cost of cooperation is low and the observational learning supplies sufficiently large uncertainty.

Development of a GUI Based Program for Design of various Steel Connections

Steel frame buildings consist of a number of different types of structural elements. Every element must be attached properly to its neighbouring part of structure. This will involve use of various types of connections. Connections account for more than half the cost of structural steel work. Connection failure is not a ductile failure and hence it should be avoided before member failure. Large uncertainty is there in the design of connections. Connections are usually the most vulnerable part of the structure, failure of which may lead to the failure of whole structure. Thus, design of connection is an important and integral part of design of the steel structure. This MATLAB GUI program developed will be a very useful and user-friendly tool for the design of connections.