Russian Dumping of Radioactive Wastes in the Sea of Japan: An Opportunity to Evaluate the Effectiveness of the London Convention 1972

By dumping 900 tons of radioactive waste into the Sea of Japan on October, 13, 1993, the Russian navy violated the moratorium on low-level radioactive waste dumping of the London Convention (the international treaty controlling ocean dumping). However, legal liability under the London Convention, the 1982 United Nations Convention on the Law of the Sea, and international customary law arguably does not attach to this activity. Indeed, even though the London Convention was amended in November of 1993 to prohibit all ocean dumping of radioactive waste, Russia remains legally entitled to use the ocean as a disposal site for low-level wastes as a result of its formal objection to the amendment. Further, it is suggested that activity and ecosystem-specific regulations merely transfer the risks associated with the activity and may actually result in greater environmental harm. For this reason, the London Convention and indeed all international agreements should consider the global impacts of environmental regulations prior to prohibiting an activity

Professional Retention of BSW Social Workers: Planned and Actual Career Choices

The assumption that BSW students will remain in social work was examined with a survey of 107 current students and 177 graduates from 1977 through 1980. The findings suggest that most of the current students planned to practice social work and most of the graduates entered social work practice upon graduation. Recent graduates, however, had more difficulty obtaining social work jobs than graduates in 1977. Characteristics of social work education are not associated with retention, leading to the hypothesis that factors outside the control of social work education are more predictive of BSWS\u27 retention in the profession

Longitudinal LASSO: Jointly Learning Features and Temporal Contingency for Outcome Prediction

Longitudinal analysis is important in many disciplines, such as the study of behavioral transitions in social science. Only very recently, feature selection has drawn adequate attention in the context of longitudinal modeling. Standard techniques, such as generalized estimating equations, have been modified to select features by imposing sparsity-inducing regularizers. However, they do not explicitly model how a dependent variable relies on features measured at proximal time points. Recent graphical Granger modeling can select features in lagged time points but ignores the temporal correlations within an individual's repeated measurements. We propose an approach to automatically and simultaneously determine both the relevant features and the relevant temporal points that impact the current outcome of the dependent variable. Meanwhile, the proposed model takes into account the non-{\em i.i.d} nature of the data by estimating the within-individual correlations. This approach decomposes model parameters into a summation of two components and imposes separate block-wise LASSO penalties to each component when building a linear model in terms of the past $\tau$ measurements of features. One component is used to select features whereas the other is used to select temporal contingent points. An accelerated gradient descent algorithm is developed to efficiently solve the related optimization problem with detailed convergence analysis and asymptotic analysis. Computational results on both synthetic and real world problems demonstrate the superior performance of the proposed approach over existing techniques.Comment: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 201

Distributed utterances

I propose an apparatus for handling intrasentential change in context. The standard approach has problems with sentences with multiple occurrences of the same demonstrative or indexical. My proposal involves the idea that contexts can be complex. Complex contexts are built out of (“simple”) Kaplanian contexts by ordered n-tupling. With these we can revise the clauses of Kaplan’s Logic of Demonstratives so that each part of a sentence is taken in a different component of a complex context. I consider other applications of the framework: to agentially distributed utterances (ones made partly by one speaker and partly by another); to an account of scare-quoting; and to an account of a binding-like phenomenon that avoids what Kit Fine calls “the antinomy of the variable.

Harvesting traffic-induced vibrations for structural health monitoring of bridges

This paper discusses the development and testing of a renewable energy source for powering wireless sensors used to monitor the structural health of bridges. Traditional power cables or battery replacement are excessively expensive or infeasible in this type of application. An inertial power generator has been developed that can harvest traffic-induced bridge vibrations. Vibrations on bridges have very low acceleration (0.1–0.5 m s _2 ), low frequency (2–30 Hz), and they are non-periodic. A novel parametric frequency-increased generator (PFIG) is developed to address these challenges. The fabricated device can generate a peak power of 57 µW and an average power of 2.3 µW from an input acceleration of 0.54 m s _2 at only 2 Hz. The generator is capable of operating over an unprecedentedly large acceleration (0.54–9.8 m s _2 ) and frequency range (up to 30 Hz) without any modifications or tuning. Its performance was tested along the length of a suspension bridge and it generated 0.5–0.75 µW of average power without manipulation during installation or tuning at each bridge location. A preliminary power conversion system has also been developed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90794/1/0960-1317_21_10_104005.pd

Binary Models for Marginal Independence

Log-linear models are a classical tool for the analysis of contingency tables. In particular, the subclass of graphical log-linear models provides a general framework for modelling conditional independences. However, with the exception of special structures, marginal independence hypotheses cannot be accommodated by these traditional models. Focusing on binary variables, we present a model class that provides a framework for modelling marginal independences in contingency tables. The approach taken is graphical and draws on analogies to multivariate Gaussian models for marginal independence. For the graphical model representation we use bi-directed graphs, which are in the tradition of path diagrams. We show how the models can be parameterized in a simple fashion, and how maximum likelihood estimation can be performed using a version of the Iterated Conditional Fitting algorithm. Finally we consider combining these models with symmetry restrictions

Adsorption models of hybridization and post-hybridisation behaviour on oligonucleotide microarrays

Analysis of data from an Affymetrix Latin Square spike-in experiment indicates that measured fluorescence intensities of features on an oligonucleotide microarray are related to spike-in RNA target concentrations via a hyperbolic response function, generally identified as a Langmuir adsorption isotherm. Furthermore the asymptotic signal at high spike-in concentrations is almost invariably lower for a mismatch feature than for its partner perfect match feature. We survey a number of theoretical adsorption models of hybridization at the microarray surface and find that in general they are unable to explain the differing saturation responses of perfect and mismatch features. On the other hand, we find that a simple and consistent explanation can be found in a model in which equilibrium hybridization followed by partial dissociation of duplexes during the post-hybridization washing phase.Comment: 26 pages, 6 figures, some rearrangement of sections and some additions. To appear in J.Phys.(condensed matter