Dopamine-D1 and δ-opioid receptors co-exist in rat striatal neurons

Cocaine’s enhancement of dopaminergic neurotransmission in the mesolimbic pathway plays a critical role in the initial reinforcing properties of this drug. However, other neurotransmitter systems are also integral to the addiction process. A large body of data indicates that opioids and dopamine together mediate emotional and reinforced behaviors. In support of this, cocaine-mediated increases in activation of dopamine D1 receptors (D1R) results in a desensitization of δ-opioid receptor (DOR) signaling through adenylyl cyclase (AC) in striatal neurons. To further define cellular mechanisms underlying this effect, the subcellular distribution of DOR and D1R was examined in the rat dorsolateral striatum. Dual immunoperoxidase/gold-silver detection combined with electron microscopy was used to identify DOR and D1R immunoreactivities in the same section of tissue. Semi-quantitative analysis revealed that a subset of dendritic cellular profiles exhibited both DOR and D1R immunoreactivities. Of 165 randomly sampled D1R immunoreactive profiles, 43% contained DOR. Similarly of 198 DOR-labeled cellular profiles, 52% contained D1R. The present data provide ultrastructural evidence for co-existence between DOR and D1R in striatal neurons, suggesting a possible mechanism whereby D1R modulation may alter DOR function

Neural networks applied to traffic management in telephone networks

In this paper the application of neural networks to some of the network management tasks carried out in a regional Bell telephone company is described. Network managers monitor the telephone network for abnormal conditions and have the ability to place controls in the network to improve traffic flow. Conclusions are drawn regarding the utility and effectiveness of the neural networks in automating the network management tasks

Mathematical Modelling of Compressive Strength of Recycled Ceramic Tile Aggregate Concrete Using Modified Regression Theory

At present, the large quantity of wastes generated by the ceramic industry is not reused in any significant quantity. Research has shown the feasibility of incorporating these wastes into concrete production. This will benefit both the ceramic and concrete industries. However, not much research data is available on the use of ceramic wastes as fine aggregate material compared to their use as coarse aggregate material. Moreover, there are presently no models for predicting the properties of ceramic waste aggregate concretes. In this study, a modified regression theory based on Taylor’s series was adopted to formulate mathematical model for predicting compressive strength of concrete into which Recycled Ceramic Tile (RCT) is incorporated as fine aggregate.  Preliminary tests on RCT indicate that it is a suitable fine aggregate material for concrete production. It has also been established that addition of RCT improves compressive strength of concrete and reduces concrete’s workability. The formulated model is a function of the mix proportions of its constituents and its predicted responses are in good agreement with experimentally observed data. The model has been tested using student’s t-test and analysis of variance and has been confirmed to be adequate and hence is validated

Finite-size scaling in thin Fe/Ir(100) layers

The critical temperature of thin Fe layers on Ir(100) is measured through M\"o{\ss}bauer spectroscopy as a function of the layer thickness. From a phenomenological finite-size scaling analysis, we find an effective shift exponent lambda = 3.15 +/- 0.15, which is twice as large as the value expected from the conventional finite-size scaling prediction lambda=1/nu, where nu is the correlation length critical exponent. Taking corrections to finite-size scaling into account, we derive the effective shift exponent lambda=(1+2\Delta_1)/nu, where Delta_1 describes the leading corrections to scaling. For the 3D Heisenberg universality class, this leads to lambda = 3.0 +/- 0.1, in agreement with the experimental data. Earlier data by Ambrose and Chien on the effective shift exponent in CoO films are also explained.Comment: Latex, 4 pages, with 2 figures, to appear in Phys. Rev. Lett

Response of selected plant and insect species to simulated solid rocket exhaust mixtures and to exhaust components from solid rocket fuels

The effects of solid rocket fuel (SRF) exhaust on selected plant and and insect species in the Merritt Island, Florida area was investigated in order to determine if the exhaust clouds generated by shuttle launches would adversely affect the native, plants of the Merritt Island Wildlife Refuge, the citrus production, or the beekeeping industry of the island. Conditions were simulated in greenhouse exposure chambers and field chambers constructed to model the ideal continuous stirred tank reactor. A plant exposure system was developed for dispensing and monitoring the two major chemicals in SRF exhaust, HCl and Al203, and for dispensing and monitoring SRF exhaust (controlled fuel burns). Plants native to Merritt Island, Florida were grown and used as test species. Dose-response relationships were determined for short term exposure of selected plant species to HCl, Al203, and mixtures of the two to SRF exhaust

A comparison of GC-FID and PTR-MS toluene measurements in ambient air under conditions of enhanced monoterpene loading

Toluene was measured using both a gas chromatographic system (GC), with a flame ionization detector (FID), and a proton transfer reaction-mass spectrometer (PTR-MS) at the AIRMAP atmospheric monitoring station Thompson Farm (THF) in rural Durham, NH during the summer of 2004. Simultaneous measurements of monoterpenes, including alpha- and beta-pinene, camphene, Delta(3)-carene, and d-limonene, by GC-FID demonstrated large enhancements in monoterpene mixing ratios relative to toluene, with median and maximum enhancement ratios of similar to 2 and similar to 30, respectively. A detailed comparison between the GC-FID and PTR-MS toluene measurements was conducted to test the specificity of PTR-MS for atmospheric toluene measurements under conditions often dominated by biogenic emissions. We derived quantitative estimates of potential interferences in the PTR-MS toluene measurements related to sampling and analysis of monoterpenes, including fragmentation of the monoterpenes and some of their primary carbonyl oxidation products via reactions with H(3)O(+), O(2)(+) and NO(+) in the PTR-MS drift tube. The PTR-MS and GC-FID toluene measurements were in good quantitative agreement and the two systems tracked one another well from the instrumental limits of detection to maximum mixing ratios of similar to 0.5 ppbv. A correlation plot of the PTR-MS versus GC-FID toluene measurements was described by the least squares regression equation y=(1.13 +/- 0.02)x-(0.008 +/- 0.003) ppbv, suggesting a small similar to 13% positive bias in the PTR-MS measurements. The bias corresponded with a similar to 0.055 ppbv difference at the highest measured toluene level. The two systems agreed quantitatively within the combined 1 sigma measurement precisions for 60% of the measurements. Discrepancies in the measured mixing ratios were not well correlated with enhancements in the monoterpenes. Better quantitative agreement between the two systems was obtained by correcting the PTR-MS measurements for contributions from monoterpene fragmentation in the PTR-MS drift tube; however, the improvement was minor (\u3c10%). Interferences in the PTRMS measurements from fragmentation of the monoterpene oxidation products pinonaldehyde, caronaldehyde and alpha-pinene oxide were also likely negligible. A relatively large and variable toluene background in the PTR-MS instrument likely drove the measurement bias; however, the precise contribution was difficult to accurately quantify and thus was not corrected for in this analysis. The results from THF suggest that toluene can be reliably quantified by PTR-MS using our operating conditions (drift tube pressure, temperature and voltage of 2.0 mbar, 45 degrees C and 600V, respectively) under the ambient compositions probed. This work extends the range of field conditions under which PTR-MS validation studies have been conducted

Applications of discrete element method in modeling of grain postharvest operations

Grain kernels are finite and discrete materials. Although flowing grain can behave like a continuum fluid at times, the discontinuous behavior exhibited by grain kernels cannot be simulated solely with conventional continuum-based computer modeling such as finite-element or finite-difference methods. The discrete element method (DEM) is a proven numerical method that can model discrete particles like grain kernels by tracking the motion of individual particles. DEM has been used extensively in the field of rock mechanics. Its application is gaining popularity in grain postharvest operations, but it has not been applied widely. This paper reviews existing applications of DEM in grain postharvest operations. Published literature that uses DEM to simulate postharvest processing is reviewed, as are applications in handling and processing of grain such as soybean, corn, wheat, rice, rapeseed, and the grain coproduct distillers dried grains with solubles (DDGS). Simulations of grain drying that involve particles in both free-flowing and confined-flow conditions are also included. Review of existing literature indicates that DEM is a promising approach in the study of the behavior of deformable soft particulates such as grain and coproducts and it could benefit from the development of improved particle models for these complex-shaped particles

Neural networks applied to traffic management in telephone networks

In this paper the application of neural networks to some of the network management tasks carried out in a regional Bell telephone company is described. Network managers monitor the telephone network for abnormal conditions and have the ability to place controls in the network to improve traffic flow. Conclusions are drawn regarding the utility and effectiveness of the neural networks in automating the network management tasks