Monte Carlo Simulations for Ghost Imaging Based on Scattered Photons

X-ray based imaging modalities are widely used in research, industry, and in the medical field. Consequently, there is a strong motivation to improve their performances with respect to resolution, dose, and contrast. Ghost imaging (GI) is an imaging technique in which the images are reconstructed from measurements with a single-pixel detector using correlation between the detected intensities and the intensity structures of the input beam. The method that has been recently extended to X-rays provides intriguing possibilities to overcome several fundamental challenges of X-ray imaging. However, understanding the potential of the method and designing X-ray GI systems pose challenges since in addition to geometric optic effects, radiation-matter interactions must be considered. Such considerations are fundamentally more complex than those at longer wavelengths as relativistic effects such as Compton scattering become significant. In this work we present a new method for designing and implementing GI systems using the particle transport code FLUKA, that rely on Monte Carlo (MC) sampling. This new approach enables comprehensive consideration of the radiation-matter interactions, facilitating successful planning of complex GI systems. As an example of an advanced imaging system, we simulate a high-resolution scattered photons GI technique

Deducing the stage of origin of Wilms tumours from a developmental series of Wt1 mutants

Wilms' tumours, paediatric kidney cancers, are the archetypal example of tumours caused through the disruption of normal development. The genetically best-defined subgroup of Wilms' tumours is the group caused by biallelic loss of the WT1 tumour suppressor gene. Here, we describe a developmental series of mouse models with conditional loss of Wt1 in different stages of nephron development before and after the mesenchymal-to-epithelial transition (MET). We demonstrate that Wt1 is essential for normal development at all kidney developmental stages under study. Comparison of genome-wide expression data from the mutant mouse models with human tumour material of mutant or wild-type WT1 datasets identified the stage of origin of human WT1-mutant tumours, and emphasizes fundamental differences between the two human tumour groups due to different developmental stages of origin

Interdisciplinary Lessons Learned While Researching Fake News

The misleading and propagandistic tendencies in American news reporting have been a part of public discussion from its earliest days as a republic (Innis, 2007; Sheppard, 2007). “Fake news” is hardly new (McKernon, 1925), and the term has been applied to a variety of distinct phenomenon ranging from satire to news, which one may find disagreeable (Jankowski, 2018; Tandoc et al., 2018). However, this problem has become increasingly acute in recent years with the Macquarie Dictionary declaring “fake news” the word of the year in 2016 (Lavoipierre, 2017). The international recognition of fake news as a problem (Pomerantsev and Weiss, 2014; Applebaum and Lucas, 2016) has led to a number of initiatives to mitigate perceived causes, with varying levels of success (Flanagin and Metzger, 2014; Horne and Adali, 2017; Sample et al., 2018). The inability to create a holistic solution continues to stymie researchers and vested parties. A significant contributor to the problem is the interdisciplinary nature of digital deception. While technology enables the rapid and wide dissemination of digitally deceptive data, the design and consumption of data rely on a mixture of psychology, sociology, political science, economics, linguistics, marketing, and fine arts. The authors for this effort discuss deception’s history, both old and new, from an interdisciplinary viewpoint and then proceed to discuss how various disciplines contribute to aiding in the detection and countering of fake news narratives. A discussion of various fake news types (printed, staged events, altered photographs, and deep fakes) ensues with the various technologies being used to identify these; the shortcomings of those technologies and finally the insights offered by the other disciplines can be incorporated to improve outcomes. A three-point evaluation model that focuses on contextual data evaluation, pattern spread, and archival analysis of both the author and publication archives is introduced. While the model put forth cannot determine fact from fiction, the ability to measure distance from fact across various domains provides a starting point for evaluating the veracity of a new story. “If it is not true, it is very well invented.” —Giordano Brun