Conditional Spectrum Computation Incorporating Multiple Causal Earthquakes and Ground‐Motion Prediction Models

The Conditional Spectrum (CS) is a target spectrum (with conditional mean and conditional standard deviation) that links seismic hazard information with ground motion selection for nonlinear dynamic analysis. Probabilistic seismic hazard analysis (PSHA) estimates the ground motion hazard by incorporating the aleatory uncertainties in all earthquake scenarios and resulting ground motions as well as the epistemic uncertainties in ground motion prediction models (GMPMs) and seismic source models. Typical CS calculations to date are produced for a single earthquake scenario using a single GMPM, but more precise use requires consideration of at least multiple causal earthquakes and multiple GMPMs that are often considered in a PSHA computation. This paper presents the mathematics underlying these more precise CS calculations. Despite requiring more effort to compute than approximate calculations using a single causal earthquake and GMPM, the proposed approach produces an exact output that has a theoretical basis. To demonstrate the results of this approach and compare the exact and approximate calculations, several example calculations are performed for real sites in the western U.S. (WUS). The results also provide some insights regarding the circumstances under which approximate results are likely to closely match more exact results. To facilitate these more precise calculations for real applications, the exact CS calculations can now be performed for real sites in the U.S. using new deaggregation features in the U.S. Geological Survey hazard mapping tools. Details regarding this implementation are discussed in this paper

Certain Adenylated Non-Coding RNAs, Including 5′ Leader Sequences of Primary MicroRNA Transcripts, Accumulate in Mouse Cells following Depletion of the RNA Helicase MTR4

RNA surveillance plays an important role in posttranscriptional regulation. Seminal work in this field has largely focused on yeast as a model system, whereas exploration of RNA surveillance in mammals is only recently begun. The increased transcriptional complexity of mammalian systems provides a wider array of targets for RNA surveillance, and, while many questions remain unanswered, emerging data suggest the nuclear RNA surveillance machinery exhibits increased complexity as well. We have used a small interfering RNA in mouse N2A cells to target the homolog of a yeast protein that functions in RNA surveillance (Mtr4p). We used high-throughput sequencing of polyadenylated RNAs (PA-seq) to quantify the effects of the mMtr4 knockdown (KD) on RNA surveillance. We demonstrate that overall abundance of polyadenylated protein coding mRNAs is not affected, but several targets of RNA surveillance predicted from work in yeast accumulate as adenylated RNAs in the mMtr4KD. microRNAs are an added layer of transcriptional complexity not found in yeast. After Drosha cleavage separates the pre-miRNA from the microRNA\u27s primary transcript, the byproducts of that transcript are generally thought to be degraded. We have identified the 5′ leading segments of pri-miRNAs as novel targets of mMtr4 dependent RNA surveillance

Legislative Bargaining Under Weighted Voting

Organizations often distribute resources through weighted voting. We analyze this setting using a noncooperative bargaining game based on the Baron-Ferejohn (1989) model. Unlike analyses derived from cooperative game theory, we find that each voter’s expected payoff is proportional to her voting weight. An exception occurs when many high-weight voters exist, as low-weight voters may expect disproportionately high payoffs due to proposal power. The model also predicts that, ex post, the coalition formateur (the party chosen to form a coalition) will receive a disproportionately high payoff. Using data from coalition governments from 1946 to 2001, we find strong evidence of such formateur effects. (JEL D7, D72) Collective decision-making frequently in-volves situations in which actors have different numbers of votes. Some institutions assign un-equal voting weights explicitly. Examples in-clude important political bodies, such as th

Response versus Chain Length of Alkanethiol-Capped Au Nanoparticle Chemiresistive Chemical Vapor Sensors

Au nanoparticles capped with a homologous series of straight chain alkanethiols (containing 4−11 carbons in length) have been investigated as chemiresistive organic vapor sensors. The series of alkanethiols was used to elucidate the mechanisms of vapor detection by such capped nanoparticle chemiresistive films and to highlight the molecular design principles that govern enhanced detection. The thiolated Au nanoparticle chemiresistors demonstrated rapid and reversible responses to a set of test vapors (n-hexane, n-heptane, n-octane, iso-octane, cyclohexane, toluene, ethyl acetate, methanol, ethanol, isopropanol, and 1-butanol) that possessed a variety of analyte physicochemical properties. The resistance sensitivity to nonpolar and aprotic polar vapors systematically increased as the chain length of the capping reagent increased. Decreases in the nanoparticle film resistances, which produced negative values of the differential resistance response, were observed upon exposure of the sensor films to alcohol vapors. The response signals became more negative with higher alcohol vapor concentrations, producing negative values of the sensor sensitivity. Sorption data measured on Au nanoparticle chemiresistor films using a quartz crystal microbalance allowed for the measurement of the partition coefficients of test vapors in the Au nanoparticle films. This measurement assumed that analyte sorption only occurred at the organic interface and not the surface of the Au core. Such an assumption produced partition coefficient values that were independent of the length of the ligand. Furthermore, the value of the partition coefficient was used to obtain the particle-to-particle interfacial effective dielectric constant of films upon exposure to analyte vapors. The values of the dielectric constant upon exposure to alcohol vapors suggested that the observed resistance response changes observed were not significantly influenced by this dielectric change, but rather were primarily influenced by morphological changes and by changes in the interparticle spacing