Reconstructing Nonparametric Productivity Networks

Network models provide a general representation of inter-connected system dynamics. This ability to connect systems has led to a proliferation of network models for economic productivity analysis, primarily estimated non-parametrically using Data Envelopment Analysis (DEA). While network DEA models can be used to measure system performance, they lack a statistical framework for inference, due in part to the complex structure of network processes. We fill this gap by developing a general framework to infer the network structure in a Bayesian sense, in order to better understand the underlying relationships driving system performance. Our approach draws on recent advances in information science, machine learning and statistical inference from the physics of complex systems to estimate unobserved network linkages. To illustrate, we apply our framework to analyze the production of knowledge, via own and cross-disciplinary research, for a world-country panel of bibliometric data. We find significant interactions between related disciplinary research output, both in terms of quantity and quality. In the context of research productivity, our results on cross-disciplinary linkages could be used to better target research funding across disciplines and institutions. More generally, our framework for inferring the underlying network production technology could be applied to both public and private settings which entail spillovers, including intra- and inter-firm managerial decisions and public agency coordination. This framework also provides a systematic approach to model selection when the underlying network structure is unknown.     

Local Observation of Field Polarity Dependent Flux Pinning by Magnetic Dipoles

A scanning Hall probe microscope is used to study flux pinning in a thin superconducting Pb film covering a square array of single-domain Co dots with in-plane magnetization. We show that single flux quanta of opposite sign thread the superconducting film below T(c) at the opposite poles of these dipoles. Depending on the polarity of the applied field, flux lines are attracted to a specific pole of the dipoles, due to the direct interaction with the vortexlike structures induced by the local stray field.     

Determining a 'safe' high-mass limit in matrix-assisted laser desorption/ionisation time-of-flight mass spectra of coal derived materials with reference to instrument noise

Three methods for determining a 'safe' estimate for high-mass limits of MALDI spectra of coal derived liquids were explored, using a sample of coal-tar pitch and its pyridine-insoluble fraction. Co-addition of increasing numbers of single-shot spectra (10, 30, 50 and 100 pulses) showed visually observable reductions in noise levels, consistent with robust and statistically meaningful signals. Three separate types of post-acquisition calculation were used to identify high-mass limits of the spectra. (i) A literature method indicated high-mass limits similar to those observed visually-as a shift from baseline at the highest masses, nearly 350 000 u for the coal tar pitch and about 390 000 u for its pyridine insoluble fraction. (ii) Comparing instrument signal with pre-selected multiples of the standard deviation, upper mass estimates of between 40-60 000 u for the coal-tar pitch and about 95 000 u for its pyridine-insoluble fraction were found. (iii) Calculation of the slope was used to identify 'lift-off' of the spectrum from baseline. The angle between the smoothed spectrum and the baseline was matched to a pre-selected value (e.g. 0.5 degrees and 1 degrees ). However, the arbitrary specification of the key parameter did not establish this last method on a firm basis. The choice of a criterion for estimating high-mass limits of MALDI spectra remains a semi-quantitative procedure; a reasonably conservative high-mass limit may be estimated by comparison of signal with five times the standard deviation. However, evaluation of size exclusion chromatograms of the present samples using polystyrene standards suggests that molecular mass distributions of pitch samples arrived at by MALDI mass spectrometry are, at least partly, determined by the limitations of available instruments. Copyright 1999 John Wiley & Sons, Ltd.     

Gelation and yielding behavior of polymer–nanoparticle hydrogels

Polymer–nanoparticle hydrogels are a unique class of self-assembled, shear-thinning, yield-stress fluids that have demonstrated potential utility in many impactful applications. Here, we present a thorough analysis of the gelation and yielding behavior of these materials with respect to the polymer and nanoparticle component stoichiometry. Through comprehensive rheological and diffusion studies, we reveal insights into the structural dynamics of the polymer nanoparticle network that identify that stoichiometry plays a key role in gelation and yielding, ultimately enabling the development of hydrogel formulations with unique shear-thinning and yield-stress behaviors. Access to these materials opens new doors for interesting applications in a variety of fields including tissue engineering, drug delivery, and controlled solution viscosity.     

Modeling of aspheric,diverging hydrodynamic instability experiments on the National Ignition Facility

One branch of work in the laboratory astrophysics community has been focused on developing the understanding of hydrodynamic mixing in core-collapse supernovae (ccSNe) by the Rayleigh–Taylor instability. Experiments studying these processes in the past have been limited to planar systems in large part due to limitations of drive energy. The National Ignition Facility (NIF) is now capable of providing experiments with far more energy than has been previously available on laser facilities, enabling supernova-relevant hydrodynamics in a diverging system. This paper focuses on a proposed design in which hydrodynamic instabilities develop from an aspheric blast-wave driven through multiple, coupled interfaces in a hemispheric target in which the relative masses of the layers are scaled to those within the ccSNe progenitor star. The simulations investigate the diagnosability and experimental value of different designs using a variety of drive conditions.