The ANU WiFeS SuperNovA Program (AWSNAP)

This paper presents the first major data release and survey description for the ANU WiFeS SuperNovA Program (AWSNAP). AWSNAP is an ongoing supernova spectroscopy campaign utilising the Wide Field Spectrograph (WiFeS) on the Australian National University (ANU) 2.3m telescope. The first and primary data release of this program (AWSNAP-DR1) releases 357 spectra of 175 unique objects collected over 82 equivalent full nights of observing from July 2012 to August 2015. These spectra have been made publicly available via the WISeREP supernova spectroscopy repository. We analyse the AWSNAP sample of Type Ia supernova spectra, including measurements of narrow sodium absorption features afforded by the high spectral resolution of the WiFeS instrument. In some cases we were able to use the integral-field nature of the WiFeS instrument to measure the rotation velocity of the SN host galaxy near the SN location in order to obtain precision sodium absorption velocities. We also present an extensive time series of SN 2012dn, including a near-nebular spectrum which both confirms its "super-Chandrasekhar" status and enables measurement of the sub-solar host metallicity at the SN site.Comment: Submitted to Publications of the Astronomical Society of Australia (PASA). Spectra publicly released via WISeREP at http://wiserep.weizmann.ac.il

Platform effects on optical variability and prediction of underwater visibility

We present hydrographic and optical data collected concurrently from two different platforms, the R/P FLoating Instrument Platform and the R/V Kilo Moana, located about 2km apart in the Santa Barbara Channel in California. We show that optical variability between the two platforms was due primarily to platform effects, specifically the breakdown of stratification from mixing by the hull of R/P FLIP. Modeled underwater radiance distribution differed by as much as 50% between the two platforms during stratified conditions. We determine that the observed optical variability resulted in up to 57% differences in predicted horizontal visibility of a black target

Inflammation, insulin resistance, and diabetes-mendelian randomization using CRP haplotypes points upstream

Background Raised C-reactive protein (CRP) is a risk factor for type 2 diabetes. According to the Mendelian randomization method, the association is likely to be causal if genetic variants that affect CRP level are associated with markers of diabetes development and diabetes. Our objective was to examine the nature of the association between CRP phenotype and diabetes development using CRP haplotypes as instrumental variables. Methods and Findings We genotyped three tagging SNPs (CRP + 2302G > A; CRP + 1444T > C; CRP + 4899T > G) in the CRP gene and measured serum CRP in 5,274 men and women at mean ages 49 and 61 y (Whitehall II Study). Homeostasis model assessment-insulin resistance (HOMA-IR) and hemoglobin A1c (HbA1c) were measured at age 61 y. Diabetes was ascertained by glucose tolerance test and self-report. Common major haplotypes were strongly associated with serum CRP levels, but unrelated to obesity, blood pressure, and socioeconomic position, which may confound the association between CRP and diabetes risk. Serum CRP was associated with these potential confounding factors. After adjustment for age and sex, baseline serum CRP was associated with incident diabetes (hazard ratio = 1.39 [95% confidence interval 1.29-1.51], HOMA-IR, and HbA1c, but the associations were considerably attenuated on adjustment for potential confounding factors. In contrast, CRP haplotypes were not associated with HOMA-IR or HbA1c (p=0.52-0.92). The associations of CRP with HOMA-IR and HbA1c were all null when examined using instrumental variables analysis, with genetic variants as the instrument for serum CRP. Instrumental variables estimates differed from the directly observed associations (p=0.007-0.11). Pooled analysis of CRP haplotypes and diabetes in Whitehall II and Northwick Park Heart Study II produced null findings (p=0.25-0.88). Analyses based on the Wellcome Trust Case Control Consortium (1,923 diabetes cases, 2,932 controls) using three SNPs in tight linkage disequilibrium with our tagging SNPs also demonstrated null associations. Conclusions Observed associations between serum CRP and insulin resistance, glycemia, and diabetes are likely to be noncausal. Inflammation may play a causal role via upstream effectors rather than the downstream marker CRP

Vadose Zone Hydrogeology Data Package for Hanford Assessments

This data package documents the technical basis for selecting physical and geochemical parameters and input values that will be used in vadose zone modeling for Hanford assessments. This work was originally conducted as part of the Characterization of Systems Task of the Groundwater Remediation Project managed by Fluor Hanford, Inc., Richland, Washington, and revised as part of the Characterization of Systems Project managed by the Pacific Northwest National Laboratory (PNNL) for the U.S. Department of Energy, Richland Operations Office (DOE-RL). This data package describes the geologic framework, the physical, hydrologic, and contaminant transport properties of the geologic materials, and deep drainage (i.e., recharge) estimates, and builds on the general framework developed for the initial assessment conducted using the System Assessment Capability (SAC) (Bryce et al. 2002). The general approach for this work was to update and provide incremental improvements over the previous SAC data package completed in 2001. As with the previous SAC data package, much of the data and interpreted information were extracted from existing documents and databases. Every attempt was made to provide traceability to the original source(s) of the data or interpretations

From Expert Administration to Accountability Network: A New Paradigm for Comparative Administrative Law

Notwithstanding the radically changed landscape of contemporary administrative governance, the categories that guide comparative administrative law and that determine what will be compared remain similar to those used at the founding of the discipline in the late 1800s. These categories are rooted in confidence in an expert bureaucracy to accomplish public purposes and are mainly twofold - administrative organization and judicial review. This outdated model has limited the ability of comparative law to engage with contemporary debates on the administrative state, which instead display considerable skepticism of public administration and are premised on achieving the public good through a plural accountability network of public and private actors. This Article seeks to correct the anachronism by reframing comparative administrative law as an accountability network of rules and procedures designed to embed public administration and civil servants in their liberal democratic societies: accountability to elected officials, organized interests, the courts, and the general public. Based on this paradigm, the Article compares American and European administrative law in a global context. Among the many differences explored are parliamentary versus presidential political control, pluralist versus neo-corporatist forms of self-regulation and public-private collaboration, judicial review focused on fundamental rights versus policy rationality, and reliance on ombudsmen in lieu of courts. The Article concludes with a number of suggestions for how comparative law can speak to current debates on reforming administrative governance

The Future of Agent-Based Modeling

In this paper, I elaborate on the role of agent-based (AB) modeling for macroeconomic research. My main tenet is that the full potential of the AB approach has not been realized yet. This potential lies in the modular nature of the models, which is bought by abandoning the straitjacket of rational expectations and embracing an evolutionary perspective. I envisage the foundation of a Modular Macroeconomic Science, where new models with heterogeneous interacting agents, endowed with partial information and limited computational ability, can be created by recombining and extending existing models in a unified computational framework