Impact mass flow sensor for monitoring peanut harvest yields

Yield monitoring systems for harvesting machines and methods that can provide yield monitoring of crops are described. Machines include those that pneumatically convey crop through the machine such as peanut harvesting machines. The yield monitoring system includes a force sensor that can be located in conjunction with a duct of the harvesting machine such that impact of the crop materials on an impact plate within the duct will be registered by the force sensor. This registration can be used to determine a mass flow rate for the crop, which can be correlated to yield of the crop. The systems can include additional components such as optical monitors, moisture sensors, and pressure sensors

Electron affinities of the first- and second- row atoms: benchmark ab initio and density functional calculations

A benchmark ab initio and density functional (DFT) study has been carried out on the electron affinities of the first- and second-row atoms. The ab initio study involves basis sets of $spdfgh$ and $spdfghi$ quality, extrapolations to the 1-particle basis set limit, and a combination of the CCSD(T), CCSDT, and full CI electron correlation methods. Scalar relativistic and spin-orbit coupling effects were taken into account. On average, the best ab initio results agree to better than 0.001 eV with the most recent experimental results. Correcting for imperfections in the CCSD(T) method improves the mean absolute error by an order of magnitude, while for accurate results on the second-row atoms inclusion of relativistic corrections is essential. The latter are significantly overestimated at the SCF level; for accurate spin-orbit splitting constants of second-row atoms inclusion of (2s,2p) correlation is essential. In the DFT calculations it is found that results for the 1st-row atoms are very sensitive to the exchange functional, while those for second-row atoms are rather more sensitive to the correlation functional. While the LYP correlation functional works best for first-row atoms, its PW91 counterpart appears to be preferable for second-row atoms. Among ``pure DFT'' (nonhybrid) functionals, G96PW91 (Gill 1996 exchange combined with Perdew-Wang 1991 correlation) puts in the best overall performance. The best results overall are obtained with the 1-parameter hybrid modified Perdew-Wang (mPW1) exchange functionals of Adamo and Barone [J. Chem. Phys. {\bf 108}, 664 (1998)], with mPW1LYP yielding the best results for first-row, and mPW1PW91 for second-row atoms. Indications exist that a hybrid of the type $a$ mPW1LYP + $(1-a)$ mPW1PW91 yields better results than either of the constituent functionals.Comment: Phys. Rev. A, in press (revised version, review of issues concerning DFT and electron affinities added

Electron attachment to valence-excited CO

The possibility of electron attachment to the valence $^{3}\Pi$ state of CO is examined using an {\it ab initio} bound-state multireference configuration interaction approach. The resulting resonance has $^{4}\Sigma^{-}$ symmetry; the higher vibrational levels of this resonance state coincide with, or are nearly coincident with, levels of the parent $a^{3}\Pi$ state. Collisional relaxation to the lowest vibrational levels in hot plasma situations might yield the possibility of a long-lived CO$^-$ state.Comment: Revtex file + postscript file for one figur

Differential Geometry for Model Independent Analysis of Images and Other Non-Euclidean Data: Recent Developments

This article provides an exposition of recent methodologies for nonparametric analysis of digital observations on images and other non-Euclidean objects. Fr\'echet means of distributions on metric spaces, such as manifolds and stratified spaces, have played an important role in this endeavor. Apart from theoretical issues of uniqueness of the Fr\'echet minimizer and the asymptotic distribution of the sample Fr\'echet mean under uniqueness, applications to image analysis are highlighted. In addition, nonparametric Bayes theory is brought to bear on the problems of density estimation and classification on manifolds

Use of traditional knowledge by the United States Bureau of Ocean Energy Management to support resource management

Professionals who collect and use traditional knowledge to support resource management decisions often are preoccupied with concerns over how and if traditional knowledge should be integrated with science. To move beyond the integration dilemma, we treat traditional knowledge and science as distinct and complementary knowledge systems. We focus on applying traditional knowledge within the decision-making process. We present succinct examples of how the Bureau of Ocean Energy Management has used traditional knowledge in decision making in the North Slope Borough, Alaska: 1) using traditional knowledge in designing, planning, and conducting scientific research; 2) applying information from both knowledge systems at the earliest opportunity in the process; 3) using traditional knowledge in environmental impacts assessment; 4) consulting with indigenous leaders at key decision points; and 5) applying traditional knowledge at a programmatic decision level. Clearly articulating, early in the process, how best to use traditional knowledge and science can allow for more complete and inclusive use of available and pertinent information

Twist-averaged Boundary Conditions in Continuum Quantum Monte Carlo

We develop and test Quantum Monte Carlo algorithms which use a``twist'' or a phase in the wave function for fermions in periodic boundary conditions. For metallic systems, averaging over the twist results in faster convergence to the thermodynamic limit than periodic boundary conditions for properties involving the kinetic energy with the same computational complexity. We determine exponents for the rate of convergence to the thermodynamic limit for the components of the energy of coulomb systems. We show results with twist averaged variational Monte Carlo on free particles, the Stoner model and the electron gas using Hartree-Fock, Slater-Jastrow, three-body and backflow wavefunction. We also discuss the use of twist averaging in the grand canonical ensemble, and numerical methods to accomplish the twist averaging.Comment: 8 figures, 12 page

Woodland Recovery after Suppression of Deer: Cascade effects for Small Mammals, Wood Mice (Apodemus sylvaticus) and Bank Voles (Myodes glareolus)

Over the past century, increases in both density and distribution of deer species in the Northern Hemisphere have resulted in major changes in ground flora and undergrowth vegetation of woodland habitats, and consequentially the animal communities that inhabit them. In this study, we tested whether recovery in the vegetative habitat of a woodland due to effective deer management (from a peak of 0.4–1.5 to <0.17 deer per ha) had translated to the small mammal community as an example of a higher order cascade effect. We compared deer-free exclosures with neighboring open woodland using capture-mark-recapture (CMR) methods to see if the significant difference in bank vole (Myodes glareolus) and wood mouse (Apodemus sylvaticus) numbers between these environments from 2001–2003 persisted in 2010. Using the multi-state Robust Design method in program MARK we found survival and abundance of both voles and mice to be equivalent between the open woodland and the experimental exclosures with no differences in various metrics of population structure (age structure, sex composition, reproductive activity) and individual fitness (weight), although the vole population showed variation both locally and temporally. This suggests that the vegetative habitat - having passed some threshold of complexity due to lowered deer density - has allowed recovery of the small mammal community, although patch dynamics associated with vegetation complexity still remain. We conclude that the response of small mammal communities to environmental disturbance such as intense browsing pressure can be rapidly reversed once the disturbing agent has been removed and the vegetative habitat is allowed to increase in density and complexity, although we encourage caution, as a source/sink dynamic may emerge between old growth patches and the recently disturbed habitat under harsh conditions

Processing of ultrafine-size particulate metal matrix composites by advanced shear technology

Copyright @ 2009 ASM International. This paper was published in Metallurgical & Materials Transactions A 40A(3) and is made available as an electronic reprint with the permission of ASM International. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplications of any material in this paper for a fee or for commercial purposes, or modification of the content of this paper are prohibited.Lack of efficient mixing technology to achieve a uniform distribution of fine-size reinforcement within the matrix and the high cost of producing components have hindered the widespread adaptation of particulate metal matrix composites (PMMCs) for engineering applications. A new rheo-processing method, the melt-conditioning high-pressure die-cast (MC-HPDC) process, has been developed for manufacturing near-net-shape components of high integrity. The MC-HPDC process adapts the well-established high shear dispersive mixing action of a twin-screw mechanism to the task of overcoming the cohesive force of the agglomerates under a high shear rate and high intensity of turbulence. This is followed by direct shaping of the slurry into near-net-shape components using an existing cold-chamber die-casting process. The results indicate that the MC-HPDC samples have a uniform distribution of ultrafine-sized SiC particles throughout the entire sample in the as-cast condition. Compared to those produced by conventional high-pressure die casting (HPDC), MC-HPDC samples have a much improved tensile strength and ductility.EP-SR