A Probabilistic Model of the Unidirectional Tensile Strength of Fiber-Reinforced Polymers for Structural Design

In this paper, a statistical analysis of the tensile strength of FRP composites is conducted. A relatively large experimental database including 58 datasets is first constructed, and the Normal, Lognormal, and Weibull distributions are fitted to the data using a tail-sensitive Anderson–Darling statistic as the measure of goodness of fit. Fitting results show that the Normal, Lognormal, and Weibull distributions can be used to model the tensile strength of FRP composites. Then, the characteristic value for the tensile strength of FRP composites at a fixed percentile is analyzed. It is found that the Weibull distribution results in a higher safety margin in comparison to either the Normal or the Lognormal distribution. When the experimental justification, the theoretical justification, as well as the design conservativeness are taken into consideration, the Weibull distribution is the most recommended distribution to model the tensile strength of FRP composites. Furthermore, a probabilistic model considering the statistical uncertainty for the tensile strength for FRP composites is proposed. It is believed that the statistical uncertainty can be modeled as a reduction factor, and the recommended value of such factor for engineering design practices is provided based on regression analysis.

P.051 Do clinical confounders to the neurological examination modify the diagnostic accuracy of CT-angiography for death by neurological criteria/brain death?

Background: CT-angiography is an ancillary test used to diagnose death by neurological criteria (DNC), notably in cases of unreliable neurological examinations due to clinical confounders. We studied whether clinical confounders to the neurological examination modified CT-angiography diagnostic accuracy. Methods: Systematic review and meta-analysis of studies including deeply comatose patients undergoing DNC ancillary testing. We estimated pooled sensitivities and specificities using a Bayesian hierarchical model, including data on CT-angiography (4-point, 7-point, 10-point scales, and no intracranial flow), and performing a subgroup analysis on clinical confounders to the reference neurological examination. Results: Of 40 studies included in the meta-analysis, 7 involve CT-angiography (n=586). There was no difference between subgroups (Table). The degree of uncertainty involving sensitivity estimates was high in both subgroups. Conclusions: Statistical uncertainty in diagnostic accuracy estimates preclude any conclusion regarding the impact of clinical confounders on CT-angiography diagnostic accuracy. Further research is required to validate CT-angiography as an accurate ancillary test for DNC. Table. Pooled sensitivities and specificities of CT-angiography for death by neurological criteria

Weak lensing magnification reconstruction with the modified internal linear combination method

Measuring weak lensing cosmic magnification signal is very challenging due to the overwhelming intrinsic clustering in the observed galaxy distribution. In this paper, we modify the Internal Linear Combination (ILC) method to reconstruct the lensing signal with an extra constraint to suppress the intrinsic clustering. To quantify the performance, we construct a realistic galaxy catalogue for the LSST-like photometric survey, covering 20 000 deg2 with mean source redshift at zs ∼ 1. We find that the reconstruction performance depends on the width of the photo-z bin we choose. Due to the correlation between the lensing signal and the source galaxy distribution, the derived signal has smaller systematic bias but larger statistical uncertainty for a narrower photo-z bin. We conclude that the lensing signal reconstruction with the Modified ILC method is unbiased with a statistical uncertainty <5% for bin width Δ zP = 0.2.

Standardization and Validation of Brachytherapy Seeds’ Modelling Using GATE and GGEMS Monte Carlo Toolkits

This study aims to validate GATE and GGEMS simulation toolkits for brachytherapy applications and to provide accurate models for six commercial brachytherapy seeds, which will be freely available for research purposes. The AAPM TG-43 guidelines were used for the validation of two Low Dose Rate (LDR), three High Dose Rate (HDR), and one Pulsed Dose Rate (PDR) brachytherapy seeds. Each seed was represented as a 3D model and then simulated in GATE to produce one single Phase-Space (PHSP) per seed. To test the validity of the simulations’ outcome, referenced data (provided by the TG-43) was compared with GATE results. Next, validation of the GGEMS toolkit was achieved by comparing its outcome with the GATE MC simulations, incorporating clinical data. The simulation outcomes on the radial dose function (RDF), anisotropy function (AF), and dose rate constant (DRC) for the six commercial seeds were compared with TG-43 values. The statistical uncertainty was limited to 1% for RDF, to 6% (maximum) for AF, and to 2.7% (maximum) for the DRC. GGEMS provided a good agreement with GATE when compared in different situations: a) Homogeneous water sphere, b) heterogeneous CT phantom, and c) a realistic clinical case. In addition, GGEMS has the advantage of very fast simulations. For the clinical case, where TG-186 guidelines were considered, GATE required 1 h for the simulation while GGEMS needed 162 s to reach the same statistical uncertainty. This study produced accurate models and simulations of their emitted spectrum of commonly used commercial brachytherapy seeds which are freely available to the scientific community. Furthermore, GGEMS was validated as an MC GPU based tool for brachytherapy. More research is deemed necessary for the expansion of brachytherapy seed modeling.

Social psyche and closed communicative streams as macro- and microcharacteristics of the military personnel state

In this article, the object of research is the military personnel as a system, and the subject of research is the synergetic property of the system, namely the social psyche. The main objective of the study is to quantitatively describe the system microstatuses (the number of system elements, the maximum number of servicemen included in closed separate communication streams, the total number of these streams). At the macrolevel, a measure of the statistical uncertainty of the social psyche is calculated as a synergistic property of the system. The sociometry method (D.L. Moreno), graph theory and the algorithm for calculating Hamiltonian paths (N. Christophides) are used to identify any military personnel included in closed communication streams. Boltzmann's method of calculating the entropy is used as the initial entropy formula. As a result of the study, recommendations are obtained for restructuring the leadership style, using the tendencies towards organization and disorganization in the personnel making. The novelty of the article lies in formulating the problem of determining the measure of the statistical uncertainty of the social psyche, in proving the significance of the natural scientific approach in describing and identifying the elements of the system (military personnel) and in the quantitative description of the synergetic phenomena of a social group.

The effects of communicating uncertainty around statistics on public trust: an international study

A growing body of research indicates that transparent communication of statistical uncertainty around facts and figures does not undermine credibility. However, the extent to which these findings apply in the context of the COVID-19 pandemic--rife with uncertainties--is unclear. In a large international survey experiment, (Study 1; N = 10,519) we report that communicating uncertainty around COVID-19 statistics in the form of a numeric range (vs. no uncertainty) may lead to slightly lower trust in the number presented but has no impact on trust in the source of the information. We also report the minimal impact of numeric uncertainty on trust is consistent across estimates of current or future COVID-19 statistics (Study 2) and figures relating to environmental or economic research, rather than the pandemic (Study 3). Conversely, we find imprecise statements about the mere existence of uncertainty without quantification can undermine both trust in the numbers and their source--though effects vary across countries and contexts. Communicators can be transparent about statistical uncertainty without concerns about undermining perceptions of their trustworthiness, but ideally should aim to use numerical ranges rather than verbal statements.

The Gift of Moving: Intergenerational Consequences of a Mobility Shock

We exploit a volcanic “experiment” to study the costs and benefits of geographic mobility. In our experiment, a third of the houses in a town were covered by lava. People living in these houses were much more likely to move away permanently. For the dependents in a household (children), our estimates suggest that being induced to move by the “lava shock” dramatically raised lifetime earnings and education. While large, these estimates come with a substantial amount of statistical uncertainty. The benefits of moving were very unequally distributed across generations: the household heads (parents) were made slightly worse off by the shock. These results suggest large barriers to moving for the children, which imply that labor does not flow to locations where it earns the highest returns. The large gains from moving for the young are surprising in light of the fact that the town affected by our volcanic experiment was (and is) a relatively high income town. We interpret our findings as evidence of the importance of comparative advantage: the gains to moving may be very large for those badly matched to the location they happened to be born in, even if differences in average income are small.