AN INVESTIGATION OF THE RELATION BETWEEN COTTON FIBRE PROPERTIES AND YARN QUALITY BY USING HIGH VOLUME INSTRUMENT(HVI)SYSTEM

The objective of this paper is to establish reliable prediction equations relating cotton fibreproperties measured by HVI system and yarn quality,A useful statistical method is adopted for de-veloping a multiple regression model interpreting the relation between the data of Spinlab HVIfibre properties and quality parameters of yarn STQ (Strength Tex Quotient).The percent relativecontribution of a fibre property with respect of STQ is also assessed.The results show that the totalcontribution of the HVI measured fibre properties can account for 77.4% of known variation ofyarn STQ.The main feature of the approach is its flexibility in accommodating all fibre properties.The examination of regression equation showed that it could be well applied to predict STQ ofyarns spun from the same spinning system,but,for different spinning systems and also for yarns ofdifferent linear density,modification of the equation would be needed.     

The temporal requirement for endothelin receptor-B signalling during neural crest development

Endothelin receptor B (EDNRB) is a G-protein-coupled receptor with seven transmembrane domains which is required for the development of melanocytes and enteric neurons. Mice that are homozygous for a null mutation in the Ednrb gene are almost completely white and die as juveniles from megacolon. To determine when EDNRB signalling is required during embryogenesis, we have exploited the tetracycline-inducible system to generate strains of mice in which the endogenous Ednrb locus is under the control of the tetracycline-dependant transactivators tTa or rtTA. By using this system to express Ednrb at different stages of embryogenesis, we have determined that EDNRB is required during a restricted period of neural crest development between embryonic days 10 and 12.5. Moreover, our results imply that EDNRB is required for the migration of both melanoblasts and enteric neuroblasts.     

Sympatric speciation by sexual selection

There is increasing evidence for the process of sympatric speciation, in which reproductive isolation of species occurs without physical isolation. Theoretical models have focused on disruptive natural selection as the crucial pressure for splitting a species. Here we report the theoretical finding that sympatric speciation may be caused by sexual selection even without disruptive natural selection. Specifically, we show that variation in a male secondary sexual character with two conspicuous extremes and the corresponding variance in female mating preference around no preference may jointly evolve into bimodal distributions with increasing modal divergence of the male and female traits, pulling a population apart into two prezygotically isolated populations. This mode of speciation, driven by two runaway processes in different directions, is promoted by an increase in the efficiency of females in discriminating among males or a decrease in the cost of male conspicuousness, indicating that sympatric speciation may occur more readily if barrier-free or predator-free conditions arise. Although even a slight cost of female preference would cancel the runaway process of sexual selection, it would not cancel the divergent runaway processes of sympatric speciation.     

Stable propagation of synchronous spiking in cortical neural networks

The classical view of neural coding has emphasized the importance of information carried by the rate at which neurons discharge action potentials. More recent proposals that information may be carried by precise spike timing have been challenged by the assumption that these neurons operate in a noisy fashion--presumably reflecting fluctuations in synaptic input and, thus, incapable of transmitting signals with millisecond fidelity. Here we show that precisely synchronized action potentials can propagate within a model of cortical network activity that recapitulates many of the features of biological systems. An attractor, yielding a stable spiking precision in the (sub)millisecond range, governs the dynamics of synchronization. Our results indicate that a combinatorial neural code, based on rapid associations of groups of neurons co-ordinating their activity at the single spike level, is possible within a cortical-like network.