Isolation and characterisation of mast cells from the prostate and other locations in normal and inflamed tissue.

The present study has shown that the majority of rat prostatic mast cells counterstained with safranin O but a significant proportion were also sensitive to formaldehyde fixation. This indicates that they may be intermediate in phenotype between the traditional connective tissue and mucosal mast cell extremes. Consistently, the cells released histamine on challenge such polyamines, which is characteristic of connective tissue mast cells, but were refractory to DSCG and nedrocromil sodium, which is typical of mucosal mast cells. Cells isolated from sites distal to the locus of inflammation in nematode infected rats were generally more responsive than normal cells to calcium ionophores and immunological stimuli. In contrast, cells did not show any differences in responsiveness towards polybasic compounds after sensitisation. Moreover, mast cells isolated from the lungs were more responsive towards immunological stimuli after nematodes infection but, in contrast, they were generally less responsive to both calcium ionophores and polybasic compounds. These data suggest that the induction of airway inflammation with nematodes may led to mast cell hyperplasia in the lungs and that the newly recruited cells may be immature or of the mucosal phenotype as judged by their Histochemical and functional characteristics. The synergistic effect of polybasic compounds on IgE induced histamine release was more pronounced in connective tissue than mucosal type mast cells. The level of enhancement produced by a single dose of a given polybasic compound increased as the histamine release induced by anti-IgE decreased. Human lung mast cells and basophil leukocytes did not respond to polyamines alone. Our study also showed that the enhancement by bradykinin of anti-IgE induced histamine release is due to an increased production of IP3 and a corresponding elevated rise in intracellular Ca2+

Development of a hot water tank simulation program with improved prediction of thermal stratification in the tank

AbstractA simulation programSpiralSolwas developed in previous investigations to calculate thermal performance of a solar domestic hot water (SDHW) system with a hot water tank with a built-in heat exchanger spiral[1]. The simulation program is improved in the paper in term of prediction of thermal stratification in the tank. The transient fluid flow and heat transfer in the hot water tank during cooling caused by standby heat loss are investigated by validated computational fluid dynamics (CFD) calculations. Detailed CFD investigations are carried out to determine the influence of thickness and material property of the tank wall on thermal stratification in the tank. It is elucidated how thermal stratification in the tank is influenced by the natural convection and how the heat loss from the tank sides will be distributed at different levels of the tank at different thermal conditions. The existing equation of the heat loss removal factor used in SpiralSol is evaluated by means of the detailed CFD calculations. A generalized new equation for the heat loss removal factor is obtained by regression. The new equation calculates the heat loss removal factor for a given temperature gradient in the tank,taking into account the influences of tank volume, height to diameter ratio, tank insulation, thickness and material property of the tankand initial thermal conditions of the tank. The equation is validated for a tank volume between 150 l and 500 l, a tank height to tank diameter ratio of 1-5,a tank wall thickness of 1.5mm to 3mm for a stainless steel tank and a tank wall thickness of between 3mm to 5mm for a normal steel tank. Accuracy and reliability of the SpiralSol program with the improved prediction of heat loss removal factor will be examined in future investigations

Smart charging for electric vehicles to minimize charging cost

This paper assumes a smart grid framework where the driving patterns for electric vehicles are known, time variations in electricity prices are communicated to householders, and data on voltage variation throughout the distribution system is available. Based on this information an aggregator with access to this data can be employed to minimize EV owner charging costs whilst maintaining acceptable distribution system voltages. In this study EV charging is assumed to take place only in the home. A single-phase LV distribution network is investigated where the local EV penetration level is assumed to be 100%. EV use patterns have been extracted from the UK Time of Use Survey data with 10-minute resolution and the domestic base load is generated from an existing public domain model. Apart from the so-called real time price signal, which is derived from the electricity system wholesale price, the cost of battery degradation is also considered in the optimal scheduling of EV charging. A simple and effective heuristic method is proposed to minimize the EV charging cost whilst satisfying the requirement of state of charge for the EV battery. A simulation in OpenDSS over a period of 24 hours has been implemented, taking care of the network constraints for voltage level at the customer connection points. The optimization results are compared with those obtained using dynamic optimal power flow

Static and dynamic measures of human brain connectivity predict complementary aspects of human cognitive performance

In cognitive network neuroscience, the connectivity and community structure of the brain network is related to cognition. Much of this research has focused on two measures of connectivity - modularity and flexibility - which frequently have been examined in isolation. By using resting state fMRI data from 52 young adults, we investigate the relationship between modularity, flexibility and performance on cognitive tasks. We show that flexibility and modularity are highly negatively correlated. However, we also demonstrate that flexibility and modularity make unique contributions to explain task performance, with modularity predicting performance for simple tasks and flexibility predicting performance on complex tasks that require cognitive control and executive functioning. The theory and results presented here allow for stronger links between measures of brain network connectivity and cognitive processes.Comment: 37 pages; 7 figure

Brain Modularity Mediates the Relation between Task Complexity and Performance

Recent work in cognitive neuroscience has focused on analyzing the brain as a network, rather than as a collection of independent regions. Prior studies taking this approach have found that individual differences in the degree of modularity of the brain network relate to performance on cognitive tasks. However, inconsistent results concerning the direction of this relationship have been obtained, with some tasks showing better performance as modularity increases and other tasks showing worse performance. A recent theoretical model (Chen & Deem, 2015) suggests that these inconsistencies may be explained on the grounds that high-modularity networks favor performance on simple tasks whereas low-modularity networks favor performance on more complex tasks. The current study tests these predictions by relating modularity from resting-state fMRI to performance on a set of simple and complex behavioral tasks. Complex and simple tasks were defined on the basis of whether they did or did not draw on executive attention. Consistent with predictions, we found a negative correlation between individuals' modularity and their performance on a composite measure combining scores from the complex tasks but a positive correlation with performance on a composite measure combining scores from the simple tasks. These results and theory presented here provide a framework for linking measures of whole brain organization from network neuroscience to cognitive processing.Comment: 47 pages; 4 figure

Price Convergence and Market Integration in China

Whether China has successfully transformed from a formally centrally-controlled economy to a market economy is an issue of immense interest and considerable debate. The current study complements the received literature by testing price movements in China using panel data of monthly price indexes across 36 major Chinese cities over a thirteen-year period. By so doing, it extends the early work by Fan and Wei (2006) and thereby adds to the literature in four main aspects. First, price index data provide a wider coverage of all goods traded in the market than a group of individual commodity prices. Thus, it has more relevant implications for monetary and other macroeconomic policies. Second, as Taylor (2001) notes, there are crucial differences of methodologies in the study of price convergence between individual commodity data and index data. Thus, the present study not only further examines market integration in China, but also provides a comparative study of price index movements in a major transitional economy with for example the study for the US by Cecchetti, Mark, and Sonora (2002). Third, a recently developed new nonlinear unit root test is applied in this paper, which is more relevant to our study than other traditional linear unit root tests. Fourth, we developed a new nonlinear half-life estimation procedure that is consistent with the concept of the linear counterpart. We find that not only price indexes do converge to the law of one price in China but also the half life of price index convergence is relatively quick (about 5 to 16 months in the linear cases, and 7 to 24 months in the nonlinear situation)

Thermal conductivity of textile reinforcements for composites

Thermal conductivity data for dry carbon fibre fabrics are required for modelling heat transfer during composites manufacturing processes; however, very few published data are available. This article reports in-plane and through-thickness thermal conductivities measured as a function of fibre volume fraction ( Vf) for non-crimp and twill carbon reinforcement fabrics, three-dimensional weaves and reinforcement stacks assembled with one-sided carbon stitch. Composites made from these reinforcements and glass fibre fabrics are also measured. Clear trends are observed and the effects of Vf, de-bulking and vacuum are quantified along with orthotropy ratios. Limited differences between the conductivity of dry glass and carbon fibre fabrics in the through-thickness direction are reported. An unexpected trend in the relationship between that quantity and Vf is explained summarily through simple simulations

Numerical Simulation Based Targeting of the Magushan Skarn Cu-Mo Deposit, Middle-Lower Yangtze Metallogenic Belt, China

The Magushan Cu–Mo deposit is a skarn deposit within the Nanling–Xuancheng mining district of the Middle-Lower Yangtze River Metallogenic Belt (MLYRMB), China. This study presents the results of a new numerical simulation that models the ore-forming processes that generated the Magushan deposit and enables the identification of unexplored areas that have significant exploration potential under areas covered by thick sedimentary sequences that cannot be easily explored using traditional methods. This study outlines the practical value of numerical simulation in determining the processes that operate during mineral deposit formation and how this knowledge can be used to enhance exploration targeting in areas of known mineralization. Our simulation also links multiple subdisciplines such as heat transfer, pressure, fluid flow, chemical reactions, and material migration. Our simulation allows the modeling of the formation and distribution of garnet, a gangue mineral commonly found within skarn deposits (including within the Magushan deposit). The modeled distribution of garnet matches the distribution of known mineralization as well as delineating areas that may well contain high garnet abundances within and around a concealed intrusion, indicating this area should be considered a prospective target during future mineral exploration. Overall, our study indicates that this type of numerical simulation-based approach to prospectivity modeling is both effective and economical and should be considered an additional tool for future mineral exploration to reduce exploration risks when targeting mineralization in areas with thick and unprospective sedimentary cover sequences

Single-nucleotide polymorphism versus microsatellite markers in a combined linkage and segregation analysis of a quantitative trait

Increasingly, single-nucleotide polymorphism (SNP) markers are being used in preference to microsatellite markers. However, methods developed for microsatellites may be problematic when applied to SNP markers. We evaluated the results of using SNPs vs. microsatellites in Monte Carlo Markov chain (MCMC) oligogenic combined segregation and linkage analysis methods. These methods were developed with microsatellite markers in mind. We selected chromosome 7 from the Collaborative Study on the Genetics of Alcoholism dataset for analysis because linkage to an electrophysiological trait had been reported there. We found linkage in the same region of chromosome 7 with the Affymetrix SNP data, the Illumina SNP data, and the microsatellite marker data. The MCMC sampler appears to mix with both types of data. The sampler implemented in this MCMC oligogenic combined segregation and linkage analysis appears to handle SNP data as well as microsatellite data and it is possible that the localizations with the SNP data are better