Parity-Violating Electron Scattering from the Pion-Correlated Relativistic Fermi Gas

Parity-violating quasielastic electron scattering is studied within the context of the relativistic Fermi gas and its extensions to include the effects of pionic correlations and meson-exchange currents. The work builds on previous studies using the same model; here the part of the parity-violating asymmetry that contains axial-vector hadronic currents is developed in detail using those previous studies and a link is provided to the transverse vector-isovector response. Various integrated observables are constructed from the differential asymmetry. These include an asymmetry averaged over the quasielastic peak, as well as the difference of the asymmetry integrated to the left and right of the peak -- the latter is shown to be optimal for bringing out the nature of the pionic correlations. Special weighted integrals involving the differential asymmetry and electromagnetic cross section, based on the concepts of y-scaling and sum rules, are constructed and shown to be suited to studies of the single-nucleon form factor content in the problem, in particular, to determinations of the isovector/axial-vector and electric strangeness form factors. Comparisons are also made with recent predictions made on the basis of relativistic mean-field theory.Comment: 28 pages, LATeX, 13 figures (tar-compressed postscript files, available from the authors), MIT preprint CTP#222

Forty years of paleoecology in the Galapagos

The Galapagos Islands provided one of the first lowland paleoecological records from the Neotropics. Since the first cores were raised from the islands in 1966, there has been a substantial increase in knowledge of past systems, and development of the science of paleoclimatology. The study of fossil pollen, diatoms, corals and compound-specific isotopes on the Galapagos has contributed to the maturation of this discipline. As research has moved from questions about ice-age conditions and mean states of the Holocene to past frequency of El Niño Southern Oscillation, the resolution of fossil records has shifted from millennial to sub-decadal. Understanding the vulnerability of the Galapagos to climate change will be enhanced by knowledge of past climate change and responses in the islands

Optical properties of thin semiconductor device structures with reflective back-surface layers

Ultrathin semiconductor device structures incorporating reflective internal or back surface layers have been investigated recently as a means of improving photon recuperation, eliminating losses associated with free carrier absorption in conductive substrates and increasing the above bandgap optical thickness of thermophotovoltaic device structures. However, optical losses in the form of resonance absorptions in these ultrathin devices have been observed. This behavior in cells incorporating epitaxially grown FeAl layers and in devices that lack a substrate but have a back-surface reflector (BSR) at the rear of the active layers has been studied experimentally and modeled effectively. For thermophotovoltaic devices, these resonances represent a significant loss mechanism since the wavelengths at which they occur are defined by the active TPV cell thickness of {approximately} 2--5 microns and are in a spectral range of significant energy content for thermal radiators. This study demonstrates that ultrathin semiconductor structures that are clad by such highly reflective layers or by films with largely different indices of refraction display resonance absorptions that can only be overcome through the implementation of some external spectral control strategy. Effective broadband, below-bandgap spectral control using a back-surface reflector is only achievable using a large separation between the TPV active layers and the back-surface reflector

Ruled Laguerre minimal surfaces

A Laguerre minimal surface is an immersed surface in the Euclidean space being an extremal of the functional \int (H^2/K - 1) dA. In the present paper, we prove that the only ruled Laguerre minimal surfaces are up to isometry the surfaces R(u,v) = (Au, Bu, Cu + D cos 2u) + v (sin u, cos u, 0), where A, B, C, D are fixed real numbers. To achieve invariance under Laguerre transformations, we also derive all Laguerre minimal surfaces that are enveloped by a family of cones. The methodology is based on the isotropic model of Laguerre geometry. In this model a Laguerre minimal surface enveloped by a family of cones corresponds to a graph of a biharmonic function carrying a family of isotropic circles. We classify such functions by showing that the top view of the family of circles is a pencil.Comment: 28 pages, 9 figures. Minor correction: missed assumption (*) added to Propositions 1-2 and Theorem 2, missed case (nested circles having nonempty envelope) added in the proof of Pencil Theorem 4, missed proof that the arcs cut off by the envelope are disjoint added in the proof of Lemma

On perfect fluid models in non-comoving observational spherical coordinates

We use null spherical (observational) coordinates to describe a class of inhomogeneous cosmological models. The proposed cosmological construction is based on the observer past null cone. A known difficulty in using inhomogeneous models is that the null geodesic equation is not integrable in general. Our choice of null coordinates solves the radial ingoing null geodesic by construction. Furthermore, we use an approach where the velocity field is uniquely calculated from the metric rather than put in by hand. Conveniently, this allows us to explore models in a non-comoving frame of reference. In this frame, we find that the velocity field has shear, acceleration and expansion rate in general. We show that a comoving frame is not compatible with expanding perfect fluid models in the coordinates proposed and dust models are simply not possible. We describe the models in a non-comoving frame. We use the dust models in a non-comoving frame to outline a fitting procedure.Comment: 8 pages, 1 figure. To appear in Phys.Rev.

Markets and marketing research on poverty and its alleviation: Summarizing an evolving logic toward human capabilities, well-being goals and transformation

Marketing practitioners and business scholars now view some of the world’s poorest communities as profitable growth markets. Hence a market-based approach to poverty alleviation has gathered momentum. This article traces the evolution of such a market-based approach over four decades and highlights a gradual trend away from a deficit-reduction approach (focused on constraints and justice) towards an opportunity-expansion approach (focused on capabilities and well-being). This trend is summarized in an analytical framework of human capabilities, well-being goals and transformative impact evolved from the literature. The framework is then used to analyse the practice of sanitation marketing, which has emerged as a key method in one of the highest priority domains in international development discourse – sanitation. The article concludes with a discussion of how contemporary work can further take forward the key tenets of the framework and guide the development of ‘good markets’ for the poor

Gap-filling eddy covariance methane fluxes:Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET)