Longitudinal Double-Spin Asymmetries for Dijet Production at Intermediate Pseudorapidity in Polarized pppp Collisions at s\sqrt{s} = 200 GeV

One of the primary goals of the RHIC spin program is to determine the spin-dependent gluon distribution, $\Delta g(x)$, of the proton. The measurements of the 2009 longitudinal double-helicity asymmetry, $A_{LL}$, for mid-rapidity inclusive jet and $\pi^{0}$ production place strong constraints on $\Delta g(x)$ and, for the first time, find evidence for non-zero gluon polarization values for partonic momentum fraction $x$ greater than 0.05. In contrast to inclusive jets, dijet correlation measurements provide access to partonic kinematics at leading order, and thus give better constraints on the behavior of $\Delta g(x)$ as a function of gluon momentum fraction. Furthermore, dijet measurements at higher rapidity probe the lower $x$ values where $\Delta G$ is poorly constrained.\\ In these proceedings, we present the first measurement of $A_{LL}$ for dijets with at least one jet reconstructed within the pseudorapidity range 0.8 $< \eta <$ 1.8 at STAR. The dijets were measured in polarized proton+proton collisions at a center-of-mass energy $\sqrt{s}$ = 200 GeV. Values of $A_{LL}$ are determined for several distinct event topologies, defined by the jet pseudorapidities, and span a range of parton momentum fraction $x$ down to $x \sim 0.01$. The measured asymmetries are found to be consistent with the predictions of global analyses that incorporate the results of previous RHIC measurements. They will provide new constraints on $\Delta g(x)$ in this poorly constrained region when included in future global analyses.Comment: Conference proceeding of 23rd International Spin Physics Symposium - SPIN2018, 10-14 September, 2018 Ferrara, Ital

Probabilistic Sea-Level Rise Hazard Analysis

This paper proposes a framework termed Probabilistic Sea-Level Rise Hazard Analysis (PSLRHA), to integrate the sea-level rise knowledge of current climate change scientific communities for informed engineering and policy decisions that affect coastal infrastructure, populations, and ecosystems. PSLRHA combines probabilities of all emission scenarios with predictions of the resulting sea-level rise over time, in order to compute sea-level rise hazard. PSLRHA also incorporates uncertainties in those sea-level rise predictions, by considering multiple Sea-Level Rise Prediction Models (SLRPMs). The output of the PSLRHA framework could be a Global Sea-Level Rise Hazard Map (GSLRHM) that can be used for Performance- Based Sea-Level Rise Engineering (PBSLRE)

Virtual Reality of Earthquake Ground Motions for Emergency Response

Ground motions interface earthquake science and engineering to advance understanding of seismic hazards and risk. Virtual reality provides an attractive tool to extend knowledge of the research community to a larger audience. This work visualizes emergency response under extreme motions, in the CAVE of the MARquette Visualization Laboratory. The visualization (a) displays ground motions (from the science community), (b) inputs these motions to structural models (from the engineering community) and illustrates the resulting responses, (c) translates structural responses to damage states of building elements, (d) creates a virtual room subjected to the perception associated with such earthquake shaking, and (e) introduces the human element of emergency response in this immersive environment. Building upon previous work on earthquake simulations, performance-based earthquake engineering (PBEE), building information modeling (BIM), and earthquake awareness, this study integrates elements of PBEE and BIM within the CAVE environment to provide visual information for decision making. Real-time or near real-time information via earthquake early warning (EEW) and structural health monitoring (SHM) further facilitates response within a limited time frame. As advanced technologies contribute to the future of community resilience, visualization plays an emerging role in connecting earthquake science, engineering, and policy

Working Capital Requirement and the Unemployment Volatility Puzzle

Shimer (2005) argues that a search and matching model of the labor market in which wage is determined by Nash bargaining cannot generate the observed volatility in unemployment and vacancy in response to reasonable labor productivity shocks. This paper examines how incorporating monopolistically competitive firms with a working capital requirement (in which firms borrow funds to pay their wage bills) improves the ability of the search models to match the empirical fluctuations in unemployment and vacancy without resorting to an alternative wage setting mechanism. The monetary authority follows an interest rate rule in the model. A positive labor productivity shock lowers the real marginal cost of production and lowers inflation. In response to the fall in price level, the monetary authority reduces the nominal interest rate. A lower interest rate reduces the cost of financing and partially offsets the increase in labor cost from a higher productivity. A reduced labor cost implies the firms retain a greater portion of the gain from a productivity shock, which gives them a greater incentive to create vacancies. Simulations show that a working capital requirement does indeed improve the ability of the search models to generate fluctuations in key labor market variables to better match the U.S. data

Introducing Adaptive Incremental Dynamic Analysis: A New Tool for Linking Ground Motion Selection and Structural Response Assessment

Adaptive Incremental Dynamic Analysis (AIDA) is a novel ground motion selection scheme that adaptively changes the ground motion suites at different ground motion intensity levels to match hazardconsistent properties for structural response assessment. Incremental DynamicAnalysis (IDA), a current dynamic response history analysis practice in Performance-Based Earthquake Engineering (PBEE), uses the same suite of ground motions at all Intensity Measure (IM) levels to estimate structural response. Probabilistic Seismic Hazard Analysis (PSHA) deaggregation tells us, however, that the target distributions of important ground motion properties change as the IM levels change. To match hazard-consistent ground motion properties, ground motions can be re-selected at each IM level, but ground motion continuity is lost when using such “stripes” (i.e., individual analysis points at each IM level). Alternatively, the data from the same ground motions in IDA can be re-weighted at various IM levels to match their respective target distributions of properties, but this implies potential omission of data and curse of dimensionality. Adaptive Incremental Dynamic Analysis, in contrast, gradually changes ground motion records to match ground motion properties as the IM level changes, while also partially maintaining ground motion continuity without the omission of useful data. AIDA requires careful record selection across IM levels. Potential record selection criteria include ground motion properties from deaggregation, or target spectrum such as the Conditional Spectrum. Steps to perform AIDA are listed as follows: (1) obtain target ground motion properties for each IM level; (2) determine “bin sizes” (i.e., tolerance for acceptable ground motion properties) and identify all candidate ground motions that fall within target bins; (3) keep ground motions that are usable at multiple IM levels, to maintain continuity; (4) use each ground motion for IDA within its allowable IM range. As a result, if we keep increasing the “bin sizes”, AIDA will approach IDA asymptotically; on the other hand, if we decrease the “bin sizes”, AIDA will approach the other end of “stripes”. This paper addresses the challenges of changing records across various IM levels. Different ground motion selection schemes are compared with AIDA to demonstrate the advantages of using AIDA. Example structural analyses are used to illustrate the impact of AIDA on the estimation of structural response in PBEE. By combining the benefits of IDA and PSHA without the omission of useful data, AIDA is a promising new tool for linking ground motion selection and structural response assessment