Cocaine and the nervous system

Cocaine abuse today has reached greater heights than it did during the first cocaine epidemic in the late nineteenth century. It is estimated that one out of every four Americans has used cocaine and some six million people in the US use it regularly. Although cocaine affects all systems in the body, the central nervous system (CNS) is the primary target. Cocaine blocks the reuptake of neurotransmitters in the neuronal synapses. Almost all CNS effects of cocaine can be attributed to this mechanism. Euphoria, pharmacological pleasure and intense cocaine craving share basis in this system. The effects of cocaine on other organ systems, in addition to its effects on the CNS, account for the majority of the complications associated with cocaine abuse. In this paper, the CNS effects following cocaine administration and their treatment are discussed.     

Preparation,structural elucidation,molecular weight determination,and molecular recognition of first‐ and second‐tier dendrimer molecules

1,3,5‐Triglyceratetriazine [first tier (G₁)] and tri(1,3,5‐triglycerate) triazine [second tier (G₂)] dendrimers were prepared with 1,3,5‐trichlorotriazine and sodium glycerate in a 1 : 3 mass ratio in an ethanolic medium.G₁ and G₂ were amorphous, white, solid substances. Their structures were elucidated with IR, ¹H‐NMR, and ¹³C‐NMR, and their thermal stability was studied with thermogravimetric analysis. The activation energy was calculated with the Freeman–Carroll model. Densities, viscosities, and surface tensions for 0.01–0.08 mol/kg aqueous solutions increased at 0.01 mol/kg for sodium glycerate, 1,3,5‐trichlorotriazine, 1,3,5‐triazine triglycerate chloride, G₁, and G₂. These values were measured at 298.15 K. The apparent molal volume, reduced viscosity, and inherent viscosity were calculated from the densities and viscosities, respectively. The data were regressed for the limiting densities, limiting apparent molal volumes, intrinsic viscosities, limiting inherent viscosities, and limiting surface tensions for solute–solvent interactions. The positive limiting apparent molal volume values were noted in the order of G₂ > 1,3,5‐triazine triglycerate chloride > G₁ > 1,3,5‐trichlorotriazine > sodium glycerate, with weaker hydrophilic intermolecular interactions of G₂. The higher intrinsic viscosity and limiting inherent viscosity values for G₂ implied stronger G₂–H₂O hydrophilic interactions, and the higher limiting apparent molal volume of G₂ indicated slightly higher dynamic conformational changes in comparison with G₁, with stronger structural activities. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Photoacoustic Thermal Characterization of Porous Rare-Earth Phosphate Ceramics

The laser induced non-destructive photoacoustic technique has been employed to measure the thermal diffusivity of lanthanum phosphate ceramics prepared by the sol–gel route. The thermal diffusivity value was evaluated by knowing the transition frequency between the thermally thin to thermally thick region from the log–log plot of photoacoustic amplitude versus chopping frequency. Analysis of the data was carried out on the basis of the one-dimensional model of Rosencwaig and Gersho. The present investigation reveals that the sintering temperature has great influence on the propagation of heat carriers and hence on the thermal diffusivity value. The results were interpreted in terms of variations in porosity with sintering temperature as well as with changes in grain size.     

Mechanism of heat transport in nanofluids

We have calculated thermal conductivity of alumina nanofluids (with water and ethylene glycol as base fluids) using temperature as well as concentration-dependent viscosity, η. The temperature profile of η is obtained using Gaussian fit to the available experimental data. In the model, the interfacial resistance effects are incorporated through a phenomenological parameter α. The micro-convection of the alumina nanoparticle (diameter less than 100 nm) is included through Reynolds and Prandtl numbers. The model is further improved by explicitly incorporating the thermal conductivity of the nanolayer surrounding the nanoparticles. Using this improved model, thermal conductivity of copper nanofluid is calculated. These calculations capture the particle concentration-dependent thermal conductivity and predict the dependence of the thermal conductivity on the size of the nanoparticle. These studies are significant to understand the underlying processes of heat transport in nanofluids and are crucial to design superior coolants of next generation.     

Synthesis of corneal keratan sulfate proteoglycans by bovine keratocytes in vitro

Keratan sulfate proteoglycans (KSPGs) are the major proteoglycans of the cornea and are secreted by keratocytes in the corneal stroma. Previous studies have been able to show only transient secretion of KSPG in cell culture. In this study, cultures of bovine keratocytes were found to secrete the three previously characterized KSPG proteins into culture medium. Reactivity with monoclonal antibody I22 demonstrated substitution of these proteins with keratan sulfate chains. KSPG constituted 15% of the proteoglycan metabolically labeled with [35S]sulfate in keratocyte culture medium. This labeled KSPG contained keratan sulfate chains of 4700 Da compared to 21,000 Da for bovine corneal keratan sulfate. Labeled keratan sulfate from cultures contained nonsulfated, monosulfated, and disulfated disaccharides that were released by digestion with endo-beta-galactosidase or keratanase II. Nonsulfated disaccharides were relatively more abundant in keratan sulfate from culture than in corneal keratan sulfate. These results show that cultured bovine keratocytes maintain the ability to express all three of the known KSPG proteins, modified with keratan sulfate chains and sulfated on both N-acetylglucosamine and galactose moieties. KSPG made in vitro differs from that found in vivo in the length and sulfation of its keratan sulfate chains. The availability of cell cultures secreting corneal keratan sulfate proteoglycans provides an opportunity to examine biosynthesis and control of this important class of molecules.     

Snowpack response in the Assiniboine-Red River basin associated with projected global warming of 1.0 °C to 3.0 °C

This study assesses snow response in the Assiniboine-Red River basin, located in the Lake Winnipeg watershed, due to anthropogenic climate change. We use a process-based distributed snow model driven by an ensemble of eight statistically downscaled global climate models (GCMs) to project future changes under policy-relevant global mean temperature (GMT) increases of 1.0 °C to 3.0 °C above the pre-industrial period. Results indicate that basin scale seasonal warmings generally exceed the GMT increases, with greater warming in winter months. The majority of GCMs project wetter winters and springs, and drier summers, while autumn could become either drier or wetter. An analysis of snow water equivalent (SWE) responses under GMT changes reveal higher correlations of snow cover duration (SCD), snowmelt rate, maximum SWE (SWE_max) and timing of SWE_max with winter and spring temperatures compared to precipitation, implying that these variables are predominantly temperature controlled. Consequently, under the GMT increases from 1.0 °C to 3.0 °C, the basin will experience successively shorter SCD, slower snowmelt, smaller monthly SWE and SWE_max, earlier SWE_max, and a transition from snow-dominated to rain-snow hybrid regime. Further, while the winter precipitation increases for some GCMs compensate the temperature-driven changes in SWE, the increases for most GCMs occur as rainfall, thus limiting the positive contribution to snow storage. Overall, this study provides a detailed diagnosis of the snow regime changes under the policy-relevant GMT changes, and a basis for further investigations on water quantity and quality changes.     

Estimation of elastic constant of rocks using an ANFIS approach

The engineering properties of the rocks have the most vital role in planning of rock excavation and construction for optimum utilization of earth resources with greater safety and least damage to surroundings. The design and construction of structure is influenced by physico-mechanical properties of rock mass. Young's modulus provides insight about the magnitude and characteristic of the rock mass deformation due to change in stress field. The determination of the Young's modulus in laboratory is very time consuming and costly. Therefore, basic rock properties like point load, density and water absorption have been used to predict the Young's modulus. Point load, density and water absorption can be easily determined in field as well as laboratory and are pertinent properties to characterize a rock mass. The artificial neural network (ANN), fuzzy inference system (FIS) and neuro fuzzy are promising techniques which have proven to be very reliable in recent years. In, present study, neuro fuzzy system is applied to predict the rock Young's modulus to overcome the limitation of ANN and fuzzy logic. Total 85 dataset were used for training the network and 10 dataset for testing and validation of network rules. The network performance indices correlation coefficient, mean absolute percentage error (MAPE), root mean square error (RMSE), and variance account for (VAF) are found to be 0.6643, 7.583, 6.799, and 91.95 respectively, which endow with high performance of predictive neuro-fuzzy system to make use for prediction of complex rock parameter.     

Average-case analysis of the Modified Harmonic algorithm

In this paper we analyze the average-case performance of the Modified Harmonic algorithm for on-line bin packing. We first analyze the average-case performance for arbitrary distribution of item sizes over (0,1]. This analysis is based on the following result. Letf ₁ andf ₂ be two linear combinations of random variables {N _i } _i=1 ^k where theN _i 's have a joint multinomial distribution for eachn= _i=1 ^k ,N _i . LetE(f ₁) O andE(f ₂) 0. Then lim_n E(max(_{f 1},f ₂ ))/n = lim _n max(E(f ₁),E(f ₂))/n. We then consider the special case when the item sizes are uniformly distributed over (0,1]. For specific values of the parameters, the Modified Harmonic algorithm turns out to be better than the other two linear-time on-line algorithms—Next Fit and Harmonic—in both the worst case as well as the average case. We also obtain optimal values for the parameters of the algorithm from the average-case standpoint. For these values of the parameters, the average-case performance ratio is less than 1.19. This compares well with the performance ratios 1.333. and 1.2865. of the Next Fit algorithm and the Harmonic algorithm, respectively.     

Average-case analysis of the Modified Harmonic algorithm

In this paper we analyze the average-case performance of the Modified Harmonic algorithm for on-line bin packing. We first analyze the average-case performance for arbitrary distribution of item sizes over (0,1]. This analysis is based on the following result. Letf ₁ andf ₂ be two linear combinations of random variables {N _i } _i=1 ^k where theN _i 's have a joint multinomial distribution for eachn=σ _i=1 ^k ,N _i . LetE(f ₁) ≠ O andE(f ₂)≠ 0. Then lim_{n →}∞E(max(_{f 1},f ₂ ))/n = lim _n →∞ max(E(f ₁),E(f ₂))/n. We then consider the special case when the item sizes are uniformly distributed over (0,1]. For specific values of the parameters, the Modified Harmonic algorithm turns out to be better than the other two linear-time on-line algorithms—Next Fit and Harmonic—in both the worst case as well as the average case. We also obtain optimal values for the parameters of the algorithm from the average-case standpoint. For these values of the parameters, the average-case performance ratio is less than 1.19. This compares well with the performance ratios 1.333. and 1.2865. of the Next Fit algorithm and the Harmonic algorithm, respectively.     

Structural Studies of TeO2–SeO2–Na2O Glass System

Glass Physics and Chemistry - The growth of nanocrystalization in TeO2–SeO2–Na2O glasses is achieved by the conventional heat treatment method. The influence of Na2O concentration on...