Abstract
The IPD-IMGT/HLA Database, http://www.ebi.ac.uk/ipd/imgt/hla/, currently contains over 25 000 allele sequence for 45 genes, which are located within the Major Histocompatibility Complex ...(MHC) of the human genome. This region is the most polymorphic region of the human genome, and the levels of polymorphism seen exceed most other genes. Some of the genes have several thousand variants and are now termed hyperpolymorphic, rather than just simply polymorphic. The IPD-IMGT/HLA Database has provided a stable, highly accessible, user-friendly repository for this information, providing the scientific and medical community access to the many variant sequences of this gene system, that are critical for the successful outcome of transplantation. The number of currently known variants, and dramatic increase in the number of new variants being identified has necessitated a dedicated resource with custom tools for curation and publication. The challenge for the database is to continue to provide a highly curated database of sequence variants, while supporting the increased number of submissions and complexity of sequences. In order to do this, traditional methods of accessing and presenting data will be challenged, and new methods will need to be utilized to keep pace with new discoveries.
To efficiently capture the energy of the nuclear bond, advanced nuclear reactor concepts seek solid fuels that must withstand unprecedented temperature and radiation extremes. In these advanced ...fuels, thermal energy transport under irradiation is directly related to reactor performance as well as reactor safety. The science of thermal transport in nuclear fuel is a grand challenge as a result of both computational and experimental complexities. Here we provide a comprehensive review of thermal transport research on two actinide oxides: one currently in use in commercial nuclear reactors, uranium dioxide (UO2), and one advanced fuel candidate material, thorium dioxide (ThO2). In both materials, heat is carried by lattice waves or phonons. Crystalline defects caused by fission events effectively scatter phonons and lead to a degradation in fuel performance over time. Bolstered by new computational and experimental tools, researchers are now developing the foundational work necessary to accurately model and ultimately control thermal transport in advanced nuclear fuels. We begin by reviewing research aimed at understanding thermal transport in perfect single crystals. The absence of defects enables studies that focus on the fundamental aspects of phonon transport. Next, we review research that targets defect generation and evolution. Here the focus is on ion irradiation studies used as surrogates for damage caused by fission products. We end this review with a discussion of modeling and experimental efforts directed at predicting and validating mesoscale thermal transport in the presence of irradiation defects. While efforts in these research areas have been robust, challenging work remains in developing holistic tools to capture and predict thermal energy transport across widely varying environmental conditions.
It is 24 years since the IPD-IMGT/HLA Database, http://www.ebi.ac.uk/ipd/imgt/hla/, was first released, providing the HLA community with a searchable repository of highly curated HLA sequences. The ...database now contains over 35 000 alleles of the human Major Histocompatibility Complex (MHC) named by the WHO Nomenclature Committee for Factors of the HLA System. This complex contains the most polymorphic genes in the human genome and is now considered hyperpolymorphic. The IPD-IMGT/HLA Database provides a stable and user-friendly repository for this information. Uptake of Next Generation Sequencing technology in recent years has driven an increase in the number of alleles and the length of sequences submitted. As the size of the database has grown the traditional methods of accessing and presenting this data have been challenged, in response, we have developed a suite of tools providing an enhanced user experience to our traditional web-based users while creating new programmatic access for our bioinformatics user base. This suite of tools is powered by the IPD-API, an Application Programming Interface (API), providing scalable and flexible access to the database. The IPD-API provides a stable platform for our future development allowing us to meet the future challenges of the HLA field and needs of the community.
Predicting materials properties of nuclear fuel compounds is a challenging task in materials science. Their thermodynamical behaviors around and above the operational temperature are essential for ...the design of nuclear reactors. However, they are not easy to measure, because the target temperature range is too high to perform various standard experiments safely and accurately. Moreover, theoretical methods such as first-principles calculations also suffer from the computational limitations in calculating thermodynamical properties due to their high calculation-costs and complicated electronic structures stemming from f-orbital occupations of valence electrons in actinide elements. Here, we demonstrate, for the first time, machine-learning molecular-dynamics to theoretically explore high-temperature thermodynamical properties of a nuclear fuel material, thorium dioxide. The target compound satisfies first-principles calculation accuracy because f-electron occupation coincidentally diminishes and the scheme meets sampling sufficiency because it works at the computational cost of classical molecular-dynamics levels. We prepare a set of training data using first-principles molecular dynamics with small number of atoms, which cannot directly evaluate thermodynamical properties but captures essential atomistic dynamics at the high temperature range. Then, we construct a machine-learning molecular-dynamics potential and carry out large-scale molecular-dynamics calculations. Consequently, we successfully access two kinds of thermodynamic phase transitions, namely the melting and the anomalous Formula: see text transition induced by large diffusions of oxygen atoms. Furthermore, we quantitatively reproduce various experimental data in the best agreement manner by selecting a density functional scheme known as SCAN. Our results suggest that the present scale-up simulation-scheme using machine-learning techniques opens up a new pathway on theoretical studies of not only nuclear fuel compounds, but also a variety of similar materials that contain both heavy and light elements, like thorium dioxide.
We test for firm-level asset investment effects in returns by examining the cross-sectional relation between firm asset growth and subsequent stock returns. Asset growth rates are strong predictors ...of future abnormal returns. Asset growth retains its forecasting ability even on large capitalization stocks. When we compare asset growth rates with the previously documented determinants of the cross-section of returns (i.e., book-to-market ratios, firm capitalization, lagged returns, accruals, and other growth measures), we find that a firm's annual asset growth rate emerges as an economically and statistically significant predictor of the cross-section of U.S. stock returns.
RQ Innovative Efficiency and Firm Value Cooper, Michael; Knott, Anne Marie; Yang, Wenhao
Journal of financial and quantitative analysis,
08/2022, Letnik:
57, Številka:
5
Journal Article
Recenzirano
We introduce and test a firm-level innovation-efficiency measure new to the finance literature. The measure, termed the research quotient (RQ), defined as the firm-specific output elasticity of ...research and development (R&D), was first developed in the management literature. RQ has a low correlation with existing innovation input, output, and efficiency measures. We test RQ in a number of innovation tests common to the finance literature and find that RQ is robust in all tests of firm value, even after controlling for previous innovation measures. The results suggest that RQ may serve as a relevant complementary measure of a company’s innovation.
We show that the performance of the new factor models of Hou et al. (2015) and Fama and French (2015) depends crucially on how their investment factor is constructed. Both models use growth in total ...assets to measure investment. Their ability to price the cross-section of returns decreases significantly when the investment factor is constructed using traditional investment measures, or measures that also account for investment in intangibles. In contrast, we find that factors based on growth in inventory and accounts receivable contain the bulk of the pricing information in the asset growth factor. We show evidence that the superior performance of the asset growth factor seems to be attributable to its ability to capture aggregate shocks to equity financing costs.
Mutual fund performance at long horizons Bessembinder, Hendrik; Cooper, Michael J.; Zhang, Feng
Journal of financial economics,
January 2023, 2023-01-00, Letnik:
147, Številka:
1
Journal Article
Recenzirano
The percentage of U.S. equity mutual funds that outperform the SPY ETF over the last 30 years decreases substantially as the horizon over which returns are measured is increased. Further, some funds ...with positive monthly alpha estimates have negative long-horizon abnormal returns. These results reflect positive skewness in the distribution of fund returns that increases with horizon, and highlight the limitations of conditional arithmetic means of short-horizon returns (e.g., alpha) for long-horizon investors. We tabulate an aggregate wealth loss of $1.02 trillion to mutual fund investors over our 30-year sample, when opportunity costs are based on beta-adjusted SPY returns.
We develop a new and comprehensive database of firm-level contributions to U.S. political campaigns from 1979 to 2004. We construct variables that measure the extent of firm support for candidates. ...We find that these measures are positively and significantly correlated with the cross-section of future returns. The effect is strongest for firms that support a greater number of candidates that hold office in the same state that the firm is based. In addition, there are stronger effects for firms whose contributions are slanted toward House candidates and Democrats.
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