9,359 research outputs found
HOW TO CHANGE AGRICULTURAL RESEARCH AND EXTENSION TO MAKE IT A BETTER INVESTMENT
Research and Development/Tech Change/Emerging Technologies,
THE ECONOMICS OF RURAL PLACES AND AGRICULTURAL ECONOMICS
Community/Rural/Urban Development, Teaching/Communication/Extension/Profession,
Land, Economic Change, and Agricultural Economics
This paper analyzes in three contexts the effects of changing economic conditions and varying economic perspectives on the way land is considered in economic doctrine. The first considers agricultural land use where agriculture is connected to the rest of the economy exclusively through input and commodity markets, and when all other parts of the economy are assumed to remain constant. The second connects agriculture to the remainder of the economy by virtue of a shared natural environment, facilitating a discussion of natural resource and environmental economics in relation to agricultural, institutional, and land economics. The third context permits economic change in the entire economy with particular attention given to population density, space, and distance. Private and public decision making are discussed with attention to federal, state, and local division of powers.Land Economics/Use,
AGRICULTURAL EDUCATION AND RESEARCH: ACADEMIC CROWN JEWELS OR COUNTRY COUSIN?
Research and Development/Tech Change/Emerging Technologies, Teaching/Communication/Extension/Profession,
Internal structure of preformed Cooper pairs
In order to obtain information about the internal structure of the preformed
pairs in the pseudogap state of high superconductors, we calculate the
propagator of a singlet pair with center of mass coordinate , and
relative distance , by solving the Bethe-Salpeter equation,
representing the sum over repeated two-particle scattering events due to a
distance dependent attraction. We define then a ``pair structure function''
that depends on the internal distance
between the partners and on the momentum of the pair.
We calculate this function both for a local potential and wave symmetry of
the order parameter and for a separable potential and wave symmetry of the
order parameter. The influence of the center of mass momentum, strenght of the
interaction, temperature, density of particles and of the pseudogap in the
one-electron spectrum is studied for both cases.Comment: 12 pages, REVTeX4, 8 EPS figure
Particle-hole symmetry in the antiferromagnetic state of the cuprates
In the layered cuprate perovskites, the occurence of high-temperature
superconductivity seems deeply related to the unusual nature of the hole
excitations. The limiting case of a very small number of holes diffusing in the
antiferromagnetic (AF) background may provide important insights into this
problem. We have investigated the transport properties in a series of crystals
of , and found that the temperature dependences of the Hall
coefficient and thermopower change abruptly as soon as the AF phase
boundary is crossed. In the AF state at low temperatures , both and
are unexpectedly suppressed to nearly zero over a broad interval of . We
argue that this suppression arises from near-exact symmetry in the
particle-hole currents. From the trends in and , we infer that the
symmetry is increasingly robust as the hole density becomes very small
(). We discuss implications for electronic properties both within
the AF state and outside.Comment: 8 pages, 7 figure
A comparison of spike time prediction and receptive field mapping with point process generalized linear models, Wiener-Voltera kernels, and spike-triggered averaging methods
Poster presentation: Characterizing neuronal encoding is essential for understanding information processing in the brain. Three methods are commonly used to characterize the relationship between neural spiking activity and the features of putative stimuli. These methods include: Wiener-Volterra kernel methods (WVK), the spike-triggered average (STA), and more recently, the point process generalized linear model (GLM). We compared the performance of these three approaches in estimating receptive field properties and orientation tuning of 251 V1 neurons recorded from 2 monkeys during a fixation period in response to a moving bar. The GLM consisted of two formulations of the conditional intensity function for a point process characterization of the spiking activity: one with a stimulus only component and one with the stimulus and spike history. We fit the GLMs by maximum likelihood using GLMfit in Matlab. Goodness-of-fit was assessed using cross-validation with Kolmogorov-Smirnov (KS) tests based on the time-rescaling theorem to evaluate the accuracy with which each model predicts the spiking activity of individual neurons and for each movement direction (4016 models in total, for 251 neurons and 16 different directions). The GLMs that considered spike history of up to 35 ms, accurately predicted neuronal spiking activity (95% confidence intervals for KS test) with a performance of 97.0% (3895/4016) for the training data, and 96.5% (3876/4016) for the test data. If spike history was not considered, performance dropped to 73,1% in the training and 71.3% in the testing data. In contrast, the WVF and the STA predicted spiking accurately for 24.2% and 44.5% of the test data examples respectively. The receptive field size estimates obtained from the GLM (with and without history), WVF and STA were comparable. Relative to the GLM orientation tuning was underestimated on average by a factor of 0.45 by the WVF and the STA. The main reason for using the STA and WVF approaches is their apparent simplicity. However, our analyses suggest that more accurate spike prediction as well as more credible estimates of receptive field size and orientation tuning can be computed easily using GLMs implemented in Matlab with standard functions such as GLMfit
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