The molecular recognition of kink-turn structure by the L7Ae class of proteins

L7Ae is a member of a protein family that binds kink-turns (k-turns) in many functional RNA species. We have solved the X-ray crystal structure of the near-consensus sequence Kt-7 of Haloarcula marismortui bound by Archaeoglobus fulgidus L7Ae at 2.3-Å resolution. We also present a structure of Kt-7 in the absence of bound protein at 2.2-Å resolution. As a result, we can describe a general mode of recognition of k-turn structure by the L7Ae family proteins. The protein makes interactions in the widened major groove on the outer face of the k-turn. Two regions of the protein are involved. One is an α-helix that enters the major groove of the NC helix, making both nonspecific backbone interactions and specific interactions with the guanine nucleobases of the conserved G•A pairs. A hydrophobic loop makes close contact with the L1 and L2 bases, and a glutamate side chain hydrogen bonds with L1. Taken together, these interactions are highly selective for the structure of the k-turn and suggest how conformational selection of the folded k-turn occurs

Protection of Coastal Infrastructure under Rising Flood Risk

The 2005 hurricane season was particularly damaging to the United States, contributing to significant losses to energy infrastructure—much of it the result of flooding from storm surge during hurricanes Katrina and Rita. In 2012, Hurricane Sandy devastated New York City and Northern New Jersey. Research suggests that these events are not isolated, but rather foreshadow a risk that is to continue and likely increase with a changing climate. Extensive energy infrastructure is located along the U.S. Atlantic and Gulf coasts, and these facilities are exposed to an increasing risk of flooding. We study the combined impacts of anticipated sea level rise, hurricane activity and subsidence on energy infrastructure with a first application to Galveston Bay. Using future climate conditions as projected by four different Global Circulation Models (GCMs), we model the change in hurricane activity from present day climate conditions in response to a climate projected in 2100 under the IPCC A1B emissions scenario. We apply the results from hurricane runs from each model to the SLOSH model to investigate the projected change in frequency and distribution of surge heights across climates. Further, we incorporate uncertainty surrounding the magnitude of sea level rise and subsidence, resulting in more detailed projections of risk levels for energy infrastructure over the next century. Applying this model of changing risk exposure, we apply a dynamic programming cost-benefit analysis to the adaptation decision.Thanks are due to Professor Kerry Emanuel for his guidance in the application of his hurricane analysis. Any errors in its application are attributable to the authors. The authors gratefully acknowledge the financial support for this work provided by the MIT Joint Program on the Science and Policy of Global Change through a consortium of industrial sponsors and Federal grants with special support from the U.S. Department of Energy (DE-FE02-94ER61937). N. L. was supported by the NOAA Climate and Global Change Postdoctoral Fellowship Program, administered by the University Corporation for Atmospheric Research

Econometric Analysis of Financial Derivatives

__Abstract__ One of the fastest growing areas in empirical finance, and also one of the least rigorously analyzed, especially from a financial econometrics perspective, is the econometric analysis of financial derivatives, which are typically complicated and difficult to analyze. The purpose of this special issue of the journal on “Econometric Analysis of Financial Derivatives” is to highlight several areas of research by leading academics in which novel econometric, financial econometric, mathematical finance and empirical finance methods have contributed significantly to the econometric analysis of financial derivatives, including market-based estimation of stochastic volatility models, the fine structure of equity-index option dynamics, leverage and feedback effects in multifactor Wishart stochastic volatility for option pricing, option pricing with non-Gaussian scaling and infinite-state switching volatility, stock return and cash flow predictability: the role of volatility risk, the long and the short of the risk-return trade-off, What’s beneath the surface? option pricing with multifrequency latent states, bootstrap score tests for fractional integration in heteroskedastic ARFIMA models, with an application to price dynamics in commodity spot and futures markets, a stochastic dominance approach to financial risk management strategies, empirical evidence on the importance of aggregation, asymmetry, and jumps for volatility prediction, non-linear dynamic model of the variance risk premium, pricing with finite dimensional dependence, quanto option pricing in the presence of fat tails and asymmetric dependence, smile from the past: a general option pricing framework with multiple volatility and leverage components, COMFORT: A common market factor non-Gaussian returns model, divided governments and futures prices, and model-based pricing for financial derivative

What Do Experts Know About Forecasting Journal Quality? A Comparison with ISI Research Impact in Finance

Experts possess knowledge and information that are not publicly available. The paper is concerned with forecasting academic journal quality and research impact using a survey of international experts from a national project on ranking academic finance journals in Taiwan. A comparison is made with publicly available bibliometric data, namely the Thomson Reuters ISI Web of Science citations database (hereafter ISI) for the Business - Finance (hereafter Finance) category. The paper analyses the leading international journals in Finance using expert scores and quantifiable Research Assessment Measures (RAMs), and highlights the similarities and differences in the expert scores and alternative RAMs, where the RAMs are based on alternative transformations of citations taken from the ISI database. Alternative RAMs may be calculated annually or updated daily to answer the perennial questions as to When, Where and How (frequently) published papers are cited (see Chang et al. (2011a, b, c)). The RAMs include the most widely used RAM, namely the classic 2-year impact factor including journal self citations (2YIF), 2-year impact factor excluding journal self citations (2YIF*), 5-year impact factor including journal self citations (5YIF), Immediacy (or zero-year impact factor (0YIF)), Eigenfactor, Article Influence, C3PO (Citation Performance Per Paper Online), h-index, PI-BETA (Papers Ignored - By Even The Authors), 2-year Self-citation Threshold Approval Ratings (2Y-STAR), Historical Self-citation Threshold Approval Ratings (H-STAR), Impact Factor Inflation (IFI), and Cited Article Influence (CAI). As data are not available for 5YIF, Article Influence and CAI for 13 of the leading 34 journals considered, 10 RAMs are analysed for 21 highly-cited journals in Finance. The harmonic mean of the ranks of the 10 RAMs for the 34 highly-cited journals are also presented. It is shown that emphasizing the 2-year impact factor of a journal, which partly answers the question as to When published papers are cited, to the exclusion of other informative RAMs, which answer Where and How (frequently) published papers are cited, can lead to a distorted evaluation of journal impact and influence relative to the Harmonic Mean rankings. A linear regression model is used to forecast expert scores on the basis of RAMs that capture journal impact, journal policy, the number of high quality papers, and quantitative information about a journal. The robustness of the rankings is also analysed

Coercive Journal Self Citations, Impact Factor, Journal Influence and Article Influence

This paper examines the issue of coercive journal self citations and the practical usefulness of two recent journal performance metrics, namely the Eigenfactor score, which may be interpreted as measuring “Journal Influence”, and the Article Influence score, using the Thomson Reuters ISI Web of Science (hereafter ISI) data for 2009 for the 200 most highly cited journals in each of the Sciences and Social Sciences. The paper also compares the two new bibliometric measures with two existing ISI metrics, namely Total Citations and the 5-year Impact Factor (5YIF) (including journal self citations) of a journal. It is shown that the Sciences and Social Sciences are different in terms of the strength of the relationship of journal performance metrics, although the actual relationships are very similar. Moreover, the journal influence and article influence journal performance metrics are shown to be closely related empirically to the two existing ISI metrics, and hence add little in practical usefulness to what is already known, except for eliminating the pressure arising from coercive journal self citations. These empirical results are compared with existing results in the bibliometrics literature

What do Experts Know About Ranking Journal Quality? A Comparison with ISI Research Impact in Finance

Experts possess knowledge and information that are not publicly available. The paper is concerned with the ranking of academic journal quality and research impact using a survey of experts from a national project on ranking academic finance journals. A comparison is made with publicly available bibliometric data, namely the Thomson Reuters ISI Web of Science citations database (hereafter ISI) for the Business - Finance category. The paper analyses the leading international journals in Finance using expert scores and quantifiable Research Assessment Measures (RAMs), and highlights the similarities and differences in the expert scores and alternative RAMs, where the RAMs are based on alternative transformations of citations taken from the ISI database. Alternative RAMs may be calculated annually or updated daily to answer the perennial questions as to When, Where and How (frequently) published papers are cited (see Chang et al. (2011a, b, c)). The RAMs include the most widely used RAM, namely the classic 2-year impact factor including journal self citations (2YIF), 2-year impact factor excluding journal self citations (2YIF*), 5-year impact factor including journal self citations (5YIF), Immediacy (or zero-year impact factor (0YIF)), Eigenfactor, Article Influence, C3PO (Citation Performance Per Paper Online), h-index, PI-BETA (Papers Ignored - By Even The Authors), 2-year Self-citation Threshold Approval Ratings (2Y-STAR), Historical Self-citation Threshold Approval Ratings (H-STAR), Impact Factor Inflation (IFI), and Cited Article Influence (CAI). As data are not available for 5YIF, Article Influence and CAI for 13 of the leading 34 journals considered, 10 RAMs are analysed for 21 highly-cited journals in Finance. Harmonic mean rankings of the 10 RAMs for the 34 highly-cited journals are also presented. It is shown that emphasizing the 2-year impact factor of a journal, which partly answers the question as to When published papers are cited, to the exclusion of other informative RAMs, which answer Where and How (frequently) published papers are cited, can lead to a distorted evaluation of journal impact and influence relative to the Harmonic Mean rankings. A simple regression model is used to predict expert scores on the basis of RAMs that capture journal impact, journal policy, the number of high quality papers, and quantitative information about a journal

Ranking Economics and Econometrics ISI Journals by Quality Weighted Citations

__Abstract__ The paper analyses academic journal quality and impact using quality weighted citations that are based on the widely-used Thomson Reuters ISI Web of Science citations database (ISI). A recently developed Index of Citations Quality (ICQ), based on quality weighted citations, is used to analyse the top 276 Economics and top 10 Econometrics journals in the ISI Economics category using alternative quantifiable Research Assessment Measures (RAMs). It is shown that ICQ is a useful additional measure to the 2-Year Impact Factor (2YIF) and other well known RAMs available in ISI for the purpose of evaluating journal impact and quality, as well as ranking, of Economics and Econometrics journals as it contains information that has very low correlations with the information contained in alternative well-known RAMs. Among other findings, the top Econometrics journals have some of the highest ICQ scores in the ISI category of Economics

Quality Weighted Citations Versus Total Citations in the Sciences and Social Sciences

__Abstract__ The paper analyses academic journal quality and research impact using quality weighted citations versus total citations, based on the widely-used Thomson Reuters ISI Web of Science citations database (ISI). A new Index of Citations Quality (ICQ) is presented, based on quality weighted citations. The new index is used to analyse the leading 500 journals in both the Sciences and Social Sciences using quantifiable Research Assessment Measures (RAMs) that are based on alternative transformations of citations. It is shown that ICQ is a useful additional measure to 2YIF and other well known RAMs for the purpose of evaluating the impact and quality, as well as ranking, of journals as it contains information that has very low correlations with the information contained in the well known RAMs for both the Sciences and Social Sciences

Ranking Journal Quality by Harmonic Mean of Ranks: An Application to ISI Statistics & Probability

As the preponderance of journal rankings becomes increasingly more frequent and prominent in academic decision making, such rankings in broad discipline categories is taking on an increasingly important role. The paper focuses on the robustness of rankings of academic journal quality and research impact using on the widely-used Thomson Reuters ISI Web of Science citations database (ISI) for the Statistics & Probability category. The paper analyses 110 ISI international journals in Statistics & Probability using quantifiable Research Assessment Measures (RAMs), and highlights the similarities and differences in various RAMs, which are based on alternative transformations of citations and influence. Alternative RAMs may be calculated annually or updated daily to determine When, Where and How (frequently) published papers are cited (see Chang et al. (2011a, b, c), Chang et al. (2012)). The RAMs are grouped in four distinct classes that include impact factor, mean citations and non-citations, journal policy, number of high quality papers, and journal influence and article influence. These classes include the most widely used RAMs, namely the classic 2-year impact factor including journal self citations (2YIF), 2-year impact factor excluding journal self citations (2YIF*), 5-year impact factor including journal self citations (5YIF), Eigenfactor (or Journal Influence), Article Influence, h-index, PI-BETA (Papers Ignored - By Even The Authors), 5YD2 (= 5YIF/2YIF) as a measure of citations longevity, and Escalating Self Citations (ESC) as a measure of increasing journal self citations. The paper highlights robust rankings based on the harmonic mean of the ranks of RAMs across the 4 classes. It is shown that focusing solely on the 2-year impact factor (2YIF) of a journal, which partly answers the question as to When published papers are cited, to the exclusion of other informative RAMs, which answer Where and How (frequently) published papers are cited, can lead to a distorted evaluation of journal quality, impact and influence relative to the more robust harmonic mean of the ranks