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The presentation is composed of the slides used in various NEST lectures including: Interaction of Radiation with Matter, Biological and Health Effects of Radiation Exposure, Radionuclide Detection and Dose Assessment, Plutonium, Other Radionuclides Monitored by Bioassay and Case Studies, and, Counting Statistics.
Background Selenium (Se) is an essential trace element for the human body. Serum Se and urinary Se are also biomarkers to assess Se exposure status. However, studies focusing on the association between urinary Se and the risk of gestational diabetes mellitus (GDM) are rare. Objective To investigate the association between urinary Se and the risk of GDM. Methods A nested case–control study based on a prospective birth cohort in Wuhan, China, which focuses on the effects of prenatal environmental factors exposure on pregnant women and children’s health was conducted. Two hundred and twenty-six cases and 452 controls were included. Maternal urine samples were collected before GDM diagnosis, and the urinary Se levels were determined. We assessed the association of urinary Se with GDM by conditional logistic regression with maternal urinary Se level as a categorical variable, and estimated the association between Se and glucose levels by multiple linear regression. The potential modifier roles of maternal age and fetal sex have also been assessed. Results Lower urinary level of Se was significantly associated with a higher risk of GDM (OR = 2.35 for the tertile 1, 95% CI:1.36-4.06; adjusted OR = 1.79 for the tertile 2, 95%CI:1.09-2.95; p for trend = 0.01). Fetal sex had an interaction with Se in the association with GDM. The association was more pronounced among pregnant women with female fetuses than with male fetuses. Discussion Our study suggested a significant negative association between urinary Se and the risk of GDM, and this association may vary depending on the fetal sex.
Detectors based upon the noble elements, especially liquid xenon as well as liquid argon, as both single- and dual-phase types, require reconstruction of the energies of interacting particles, both in the field of direct detection of dark matter (weakly interacting massive particles WIMPs, axions, etc.) and in neutrino physics. Experimentalists, as well as theorists who reanalyze/reinterpret experimental data, have used a few different techniques over the past few decades. In this paper, we review techniques based on solely the primary scintillation channel, the ionization or secondary channel available at non-zero drift electric fields, and combined techniques that include a simple linear combination and weighted averages, with a brief discussion of the application of profile likelihood, maximum likelihood, and machine learning. Comparing results for electron recoils (beta and gamma interactions) and nuclear recoils (primarily from neutrons) from the Noble Element Simulation Technique (NEST) simulation to available data, we confirm that combining all available information generates higher-precision means, lower widths (energy resolution), and more symmetric shapes (approximately Gaussian) especially at keV-scale energies, with the symmetry even greater when thresholding is addressed. Near thresholds, bias from upward fluctuations matters. For MeV-GeV scales, if only one channel is utilized, an ionization-only-based energy scale outperforms scintillation; channel combination remains beneficial. We discuss here what major collaborations use.
A device for bubbling a gas into a liquid is disclosed. The device comprises a first bubbling apparatus nested inside a second bubbling apparatus. The first bubbling apparatus comprises a gas inlet for receiving the gas and a plurality of first openings for releasing the gas. The second bubbling apparatus at least partially encloses the plurality of first openings of the first bubbling apparatus. The second bubbling apparatus receives the gas from the plurality of first openings. The second bubbling apparatus comprises a plurality of second openings for bubbling the gas into the liquid.
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Abstract The 2D transition‐metal dichalcogenides (2D TMDCs) are an intriguing platform for studying strong light–matter interactions because they combine the electronic properties of conventional semiconductors with the optical resonances found in organic systems. However, the coupling strengths demonstrated in strong exciton–polariton coupling in the 2D TMDCs remain much lower than those found in organic systems. In this paper, a new approach is taken by utilizing the large oscillator strength of the above‐band gap C exciton in few‐layer molybdenum disulphide (FL‐MoS 2 ). A k ‐space Rabi splitting of 293 meV is shown when coupling FL‐MoS 2 C excitons to surface plasmon polaritons at room temperature. This value is 11% of the uncoupled exciton energy (2.67 eV or 464 nm), ≈2× what is typically seen in the TMDCs, placing the system in the ultrastrong coupling regime. The results take a step toward finally achieving the efficient quantum coherent processes of ultrastrong coupling in a CMOS‐compatible system—the 2D TMDCs—in the visible spectrum.
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A new approach for constructing polar-like boundary-conforming coordinates inside a toroid with strongly shaped cross-sections is presented. A coordinate mapping is obtained through a variational approach, which involves identifying extremal points of a proposed action in the mapping space from [0,2π] 2 ×[0,1] to a toroidal domain in $\mathbb{R}$ 3 . This approach employs an action built on the squared Jacobian and radial length. Extensive testing is conducted on general toroidal boundaries using a global Fourier–Zernike basis via action minimisation. The results demonstrate successful coordinate construction capable of accurately describing strongly shaped toroidal domains. The coordinate construction is successfully applied to the computation of three-dimensional magnetohydrodynamic equilibria in the GVEC code where the use of traditional coordinate construction by interpolation from the boundary failed.
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Here, we reported a strategy of using an eggshell membrane to produce hierarchically porous carbon as a low-cost substrate for synthesizing a nano-nickel oxide catalyst (C@NiO), which can effectively turn biowaste—urea—into energy through an electrochemical approach. Here, the interwoven carbon networks within NiO led to highly efficient urea oxidation due to the strong synergistic effect. The as-prepared electrode only needed 1.36 V versus reversible hydrogen electrode to realize a high efficiency of 10 mA cm –2 in 1.0 M KOH with 0.33 M urea and delivered an even higher current density of 25 mA cm –2 at 1.46 V, which is smaller than that of the porous carbon and commercial Pt/C catalyst. Benefiting from theoretical calculations, Ni(III) active species and the porous carbon further enabled the electrocatalyst to effectively inhibit the “CO 2 poisoning” of electrocatalysts, as well as ensuring its superior performance for urea oxidation.
Abstract Mountains are vital water sources for humans and ecosystems, continuously replenishing lowland aquifers through surface runoff and mountain recharge. Quantifying these fluxes and their relative importance is essential for sustainable water resource management. However, our mechanistic understanding of the flow and transport processes determining the connection between the mountain block and the basin aquifer remains limited. Traditional conceptualizations assume groundwater circulation within the mountain block is predominantly shallow. This view neglects the role of deep groundwater flowpaths significantly contributing to the water, solute, and energy budgets. Overcoming these limitations requires a holistic characterization of the multiscale nature of groundwater flow along the mountain‐to‐valley continuum. As a proof‐of‐concept, we use a coupled groundwater flow and transport model to design a series of numerical experiments that explore the role of geology, topography, and weathering rates in groundwater circulation and their resulting resistivity patterns. Our results show that accumulating solutes near stagnation zones create contrasting electrical resistivity patterns that separate local, intermediate, and regional flow cells, presenting a target for magnetotelluric observations. To demonstrate the sensitivity of magnetotelluric data to features in our resistivity models, we use the MARE2DEM electromagnetic modeling code to perform forward and inverse simulations. This study highlights the potential of magnetotelluric surveys to image the resistivity structure resulting from multiscale groundwater circulation through relatively impervious crystalline basement rocks in mountainous terrains. This capability could change our understanding of the critical zone, offering a holistic perspective that includes deep groundwater circulation and its role in conveying solutes and energy.
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Monte Carlo (MC) neutron transport provides detailed estimates of radiological quantities within fission reactors. This involves tracking individual neutrons through a computational geometry. CPU-based MC codes use multiple polymorphic tracker types with different tracking algorithms to exploit the repeated configurations of reactors, but virtual function calls have high overhead on the GPU. The Shift MC code was modified to support GPU-based tracking with three strategies: dynamic polymorphism with virtual functions, static polymorphism, and a single tracker type with tree-based acceleration. On the Frontier supercomputer these methods achieve 77.8%, 91.2%, and 83.4%, respectively, of the tracking rate obtained using a specialized tracker optimized for rectilinear-grid-based reactors. This indicates that all three methods are suitable for typical reactor problems in which tracking does not dominate runtime. The flexibility of the single tracker method is highlighted with a hexagonal-grid microreactor problem, performed without hexagonal-grid-specific tracking routines, providing a 2.19× speedup over CPU execution.