Teratogenicity of depleted uranium aerosols: A review from an epidemiological perspective

BACKGROUND: Depleted uranium is being used increasingly often as a component of munitions in military conflicts. Military personnel, civilians and the DU munitions producers are being exposed to the DU aerosols that are generated. METHODS: We reviewed toxicological data on both natural and depleted uranium. We included peer reviewed studies and gray literature on birth malformations due to natural and depleted uranium. Our approach was to assess the "weight of evidence" with respect to teratogenicity of depleted uranium. RESULTS: Animal studies firmly support the possibility that DU is a teratogen. While the detailed pathways by which environmental DU can be internalized and reach reproductive cells are not yet fully elucidated, again, the evidence supports plausibility. To date, human epidemiological data include case examples, disease registry records, a case-control study and prospective longitudinal studies. DISCUSSION: The two most significant challenges to establishing a causal pathway between (human) parental DU exposure and the birth of offspring with defects are: i) distinguishing the role of DU from that of exposure to other potential teratogens; ii) documentation on the individual level of extent of parental DU exposure. Studies that use biomarkers, none yet reported, can help address the latter challenge. Thoughtful triangulation of the results of multiple studies (epidemiological and other) of DU teratogenicity contributes to disentangling the roles of various potentially teratogenic parental exposures. This paper is just such an endeavor. CONCLUSION: In aggregate the human epidemiological evidence is consistent with increased risk of birth defects in offspring of persons exposed to DU

Management Forecast Credibility and Underreaction to News

In this paper, we first document evidence of underreaction to management forecast news. We then hypothesize that the credibility of the forecast influences the magnitude of this underreaction. Relying on evidence that more credible forecasts are associated with a larger reaction in the short window around the management forecasts and a smaller post-management forecast drift in returns, we show that the magnitude of the underreaction is smaller for firms that provide more credible forecasts. Our paper contributes to the literature by providing out-of-sample evidence of the drift in returns documented in the post-earnings-announcement drift literature, with the credibility of the news being one explanation for the phenomenon.Sloan School of ManagementWharton SchoolDeloitte Foundatio

Design of the ECCE Detector for the Electron Ion Collider

Preprint submitted to Nuclear Instruments and Methods A. The file archived on this institutional repository has not been certified by peer review.32 pages, 29 figures, 9 tablesThe EIC Comprehensive Chromodynamics Experiment (ECCE) detector has been designed to address the full scope of the proposed Electron Ion Collider (EIC) physics program as presented by the National Academy of Science and provide a deeper understanding of the quark-gluon structure of matter. To accomplish this, the ECCE detector offers nearly acceptance and energy coverage along with excellent tracking and particle identification. The ECCE detector was designed to be built within the budget envelope set out by the EIC project while simultaneously managing cost and schedule risks. This detector concept has been selected to be the basis for the EIC project detector.Office of Science in the Department of Energy, the National Science Foundation, and the Los Alamos National Laboratory Laboratory Directed Research and Development (LDRD) 20200022DR; This research used resources of the Compute and Data Environment for Science (CADES) at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05- 00OR22725. The work of AANL group are supported by the Science Committee of RA, in the frames of the research project # 21AG-1C028. And we gratefully acknowledge that support of Brookhaven National Lab and the Thomas Jefferson National Accelerator Facility which are operated under contracts DESC0012704 and DE-AC05-06OR23177 respectivel

AI-assisted optimization of the ECCE tracking system at the Electron Ion Collider

arXiv preprint [v2] Fri, 20 May 2022 03:23:44 UTC (2,296 KB) made available under a Creative Commons (CC BY) Attribution Licence, now in press, published by Elsevier: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, available online 17 November 2022 at: https://doi.org/10.1016/j.nima.2022.167748The Electron-Ion Collider (EIC) is a cutting-edge accelerator facility that will study the nature of the "glue" that binds the building blocks of the visible matter in the universe. The proposed experiment will be realized at Brookhaven National Laboratory in approximately 10 years from now, with detector design and R&D currently ongoing. Notably, EIC is one of the first large-scale facilities to leverage Artificial Intelligence (AI) already starting from the design and R&D phases. The EIC Comprehensive Chromodynamics Experiment (ECCE) is a consortium that proposed a detector design based on a 1.5T solenoid. The EIC detector proposal review concluded that the ECCE design will serve as the reference design for an EIC detector. Herein we describe a comprehensive optimization of the ECCE tracker using AI. The work required a complex parametrization of the simulated detector system. Our approach dealt with an optimization problem in a multidimensional design space driven by multiple objectives that encode the detector performance, while satisfying several mechanical constraints. We describe our strategy and show results obtained for the ECCE tracking system. The AI-assisted design is agnostic to the simulation framework and can be extended to other sub-detectors or to a system of sub-detectors to further optimize the performance of the EIC detector.Office of Nuclear Physics in the Office of Science in the Department of Energy; National Science Foundation, and the Los Alamos National Laboratory Laboratory Directed Research and Development (LDRD) 20200022DR

Accounting for intangible assets: suggested solutions

Current accounting practice expenses many investments in intangible assets to the income statement, confusing earnings from current revenues with investments to gain future revenues. This has led to increasing calls to book those investments to the balance sheet. Drawing on relevant research, we evaluate solutions for intangible asset accounting that contrast with balance sheet recognition, and we compare these with current practice under IFRS. Key is acknowledging that an accounting solution comes from a double-entry system, which produces both an income statement and a balance sheet, and which has features that both enable and limit the information that can be conveyed about intangible asset value. In this system, asset recognition in the balance sheet must consider the effect on measurement in the income statement, for the income statement conveys value added to investment on the balance sheet. A determining feature is uncertainty about investment outcome and how that affects the income statement, so our solutions centre on accounting under uncertainty. Two other accounting features are added: there has to be an investment expenditure for balance sheet recognition, and that expenditure must be separately identifiable from transactions. These features, rather than the tangible-intangible asset dichotomy, lead to the prescribed solutions