The Circadian Clock Gene Period1 Connects the Molecular Clock to Neural Activity in the Suprachiasmatic Nucleus.

The neural activity patterns of suprachiasmatic nucleus (SCN) neurons are dynamically regulated throughout the circadian cycle with highest levels of spontaneous action potentials during the day. These rhythms in electrical activity are critical for the function of the circadian timing system and yet the mechanisms by which the molecular clockwork drives changes in the membrane are not well understood. In this study, we sought to examine how the clock gene Period1 (Per1) regulates the electrical activity in the mouse SCN by transiently and selectively decreasing levels of PER1 through use of an antisense oligodeoxynucleotide. We found that this treatment effectively reduced SCN neural activity. Direct current injection to restore the normal membrane potential partially, but not completely, returned firing rate to normal levels. The antisense treatment also reduced baseline [Ca(2+)]i levels as measured by Fura2 imaging technique. Whole cell patch clamp recording techniques were used to examine which specific potassium currents were altered by the treatment. These recordings revealed that the large conductance [Ca(2+)]i-activated potassium currents were reduced in antisense-treated neurons and that blocking this current mimicked the effects of the anti-sense on SCN firing rate. These results indicate that the circadian clock gene Per1 alters firing rate in SCN neurons and raise the possibility that the large conductance [Ca(2+)]i-activated channel is one of the targets

Hedging Diffusion Processes by Local Risk-Minimisation with Applications to Index Tracking

The solution to the problem of hedging contingent claims by local risk-minimisation has been considered in detail in Follmer and Sondermann (1986), Follmer and Schweizer (1991) and Schweizer (1991). However, given a stochastic process Xt and tau1 tau2, the strategy that is locally risk-minimising for Xtau1 is in general not locally risk-minimising for Xtau2. In the case of diffusion processes, this paper considers the problem of determining a strategy that is simultaneously locally risk-minimising for Xtau for all tau. That is, a strategy that is locally risk-minimising for the entire process Xt. The necessary and sufficient conditions under which this is possible are obtained, and applied to the problem of index tracking. In particular, a close connection between the local risk-minimising and the tracking error variance minimising strategies for index tracking is established, and leads to a simple criterion for the selection of optimal set of assets from which to form a tracker portfolio, as well as a value-at-risk type measure for the set of assets used.minimal martingale measure; local risk-minimisation; hedging; incomplete market; index tracking; portfolio selection

Application of LANDSAT system for improving methodology for inventory and classification of wetlands

There are no author-identified significant results in this report

Forecasts of winter wheat yield and production using LANDSAT data

There are no author-identified significant results in this report

The use of high altitude, color and spectrozonal imagery for the inventory of wildland resources. Volume II - The range resource Annual progress report

High altitude multispectral imagery for identifying and mapping rangeland characteristic

Wheat yield forecasts using LANDSAT data

Several considerations of winter wheat yield prediction using LANDSAT data were discussed. In addition, a simple technique which permits direct early season forecasts of wheat production was described

Wheat productivity estimates using LANDSAT data

The author has identified the following significant results. Large area LANDSAT yield estimates were generated. These results were compared with estimates computed using a meteorological yield model (CCEA). Both of these estimates were compared with Kansas Crop and Livestock Reporting Service (KCLRS) estimates of yield, in an attempt to assess the relative and absolute accuracy of the LANDSAT and CCEA estimates. Results were inconclusive. A large area direct wheat prediction procedure was implemented. Initial results have produced a wheat production estimate comparable with the KCLRS estimate

Wheat productivity estimates using LANDSAT data

The author has identified the following significant results. Objective measurements of percent green wheat cover on May 21 were significantly correlated with yield, as were measurements of green LAI and LANDSAT data. Three data sets from the Finney test site were analyzed from LANDSAT passes on 22 November 1974, 15 April 1975, and 21 May 1975. After mean signal values in each band were computed for each sufficiently large wheat field, the mean values were correlated with the farmer estimates of wheat grain yield in order to assess relative information content. It is clear that the single best spectral temporal band for predicting yield is the 15 April red band (0.6-0.7 microns, band 5), with the 15 April green band (0.5-0.6 microns, band 4) a close second

Wheat productivity estimates using LANDSAT data

There are no author-identified significant results in this report