The discovery of the first electromagnetic counterpart to a gravitational wave signal has generated follow-up observations by over 50 facilities world-wide, ushering in the new era of multi-messenger astronomy. In this paper, we present follow-up observations of the gravitational wave event GW170817 and its electromagnetic counterpart SSS17a/DLT17ck (IAU label AT2017gfo) by 14 Australian telescopes and partner observatories as part of Australian-based and Australian-led research programs. We report early- to late-time multi-wavelength observations, including optical imaging and spectroscopy, mid-infrared imaging, radio imaging, and searches for fast radio bursts. Our optical spectra reveal that the transient source emission cooled from approximately 6 400 K to 2 100 K over a 7-d period and produced no significant optical emission lines. The spectral profiles, cooling rate, and photometric light curves are consistent with the expected outburst and subsequent processes of a binary neutron star merger. Star formation in the host galaxy probably ceased at least a Gyr ago, although there is evidence for a galaxy merger. Binary pulsars with short (100 Myr) decay times are therefore unlikely progenitors, but pulsars like PSR B1534+12 with its 2.7 Gyr coalescence time could produce such a merger. The displacement (~2.2 kpc) of the binary star system from the centre of the main galaxy is not unusual for stars in the host galaxy or stars originating in the merging galaxy, and therefore any constraints on the kick velocity imparted to the progenitor are poor.

Interactions of water-soluble soil organic matter (WSSOM) with the herbicides bromacil, metribuzin, alachlor, diquat, and paraquat were examined to determine if these interactions can improve predictions of herbicide leaching potential. A high-performance liquid chromatography gel filtration column was used to separate WSSOM extracts from four mineral agricultural soils into fractions with approximate log molecular weights of 4.96 to 6.82. WSSOM fractions were predominantly anionic in nature with some hydrophobic character. The amount of paraquat bound by WSSOM ranged from 1.1 to 2.1 mmol g−1DOC−1 with KDOC (partition coefficient for dissolved organic carbon) values from 0.050 to 0.187 L kg−1. Diquat was bound at 0.9 to 1.5 mmol g−1DOC−1 by the extracts with KDOC values from 0.044 to 0.143 L kg−1. Bromacil, metribuzin, and alachlor did not bind to the extracts tested. WSSOM did not increase paraquat solubility in the presence of soil. Binding of these herbicides to WSSOM in the soils used in this study would not be a significant mechanism for increased mobility and groundwater contamination potential.

Studies were conducted during a 2-yr period measuring corn silage and grain yield and velvetleaf seed production in response to velvetleaf density. Velvetleaf densities of 0, 2, 5, 10, and 21 plants/m2 were established in conventionally tilled corn. The percent corn yield reduction in response to velvetleaf density was similar for both years despite differences in total corn yield. Corn grain and silage yield responded differently to velvetleaf interference. Although both were adversely affected, silage yield reductions were twice that of grain at the low velvetleaf densities. A hyperbolic yield model predicted a maximum yield loss for corn silage and grain of 36 and 37% with incremental losses of 7 and 3%, respectively, as velvetleaf density increased. Velvetleaf seed production ranged from 2,256 to 4,844 seed/m2 from the lowest to the highest density. This study demonstrates that corn silage yield is more sensitive than corn grain yield to velvetleaf interference, as well as how crop value plays an important role in determining economic thresholds. Finally, this research confirms the prolific nature of velvetleaf and shows that even at low densities, velvetleaf seed production could affect weed control decisions for many seasons to come.

The Akaike Information Criterion can be a valuable tool of scientific inference. This statistic, or any other statistical method for that matter, cannot, however, be the whole of scientific methodology. In this paper some of the limitations of Akaikean statistical methods are discussed. It is argued that the full import of empirical evidence is realized only by adopting a richer ideal of empirical success than predictive accuracy, and that the ability of a theory to turn phenomena into accurate, agreeing measurements of causally relevant parameters contributes to the evidential support of the theory. This is illustrated by Newton's argument from orbital phenomena to the inverse-square law of gravitation.

Brian Skyrms' investigation of dynamic deliberation began when he contrasted dynamical deliberation based on evidential decision theory with dynamical deliberation based on causal decision theory (Skyrms 1982). According to Skyrms, counter intuitive features of deliberation dynamics based on evidential decision theory undercut attempts by Ellery Eells and Richard Jeffrey to use dynamical considerations to argue that evidential decision theory could be trusted to agree with the recommendations of causal decision theory in the examples that had been used to motivate causal decision theory.

In order to license an underground nuclear waste repository DOE must demonstrate its safety. Sensitivity and uncertainty analyses play a critical role in both performance assessment and licensing. This paper focuses on the application of a variety of techniques to arrive at a comprehensive sensitivity and uncertainty analysis for performance measures relating to ground-water travel in the Wolfcamp aquifer of the Palo Duro Basin (see Figure 1). Scenario analysis is not examined; rather, analysis is based on well understood models for flow in porous media. Both Monte Carlo and first order second moment techniques are utilized to obtain output uncertainties. The approach results in a logical, comprehensive analysis that blends both deterministic and statistical methods. It provides for an extensive screening of the parameters, accounts for parameter and spatial correlations, and quantifies uncertainties for the major performance measures in ground-water travel. The results are useful for both licensing and the identification of additional data needs.

One of the salient features of Carnap's systems of inductive logic is a conditionalization learning model, which also plays a fundamental role in the orthodox Bayesian account of rationality. This learning model does not allow for revision of previously accepted evidence. It is, therefore, not adequate to represent all rational learning by an agent who accepts corrigible propositions as evidence. Recently I used a generalization of the concept of conditional belief to extend the model so that rational revision of previously accepted evidence can be accommodated. My generalization of conditional belief carries with it a natural way of representing an agent's conceptual framework. In this paper I exploit this representation to produce learning models that can accommodate rational conceptual change.

The idea of conceptual change has received considerable attention in recent work of philosophers of science. The following quotation from Hilary Putnam is instructive.