The natural plasma testosterone profile of male blue tits during the breeding season and its relation to song output

In male birds, the gonadal hormone testosterone (T) is known to influence territorial and mating behaviour. Plasma levels of T show seasonal fluctuations which vary in relation to mating system and social instability. First, we determined the natural T profile of male blue tits Parus caeruleus during the breeding season. We found that plasma levels of T increased at the onset of nest building. Thus, the increase in circulating T was not associated with territory establishment, nor with the fertile period of the males' mates. In most individuals, T levels dropped to values close to zero during the period of chick feeding. Second, we investigated the relationship between plasma levels of T and male age, size, and singing behaviour. During the mating period, T levels did not differ between 1 yr old and older males and did not correlate with body size or condition. However, song output during the dawn chorus tended to be positively correlated with T levels. Therefore, if high T levels are costly, song output might be an honest indicator of male quality in blue tits. Finally, we show that plasma levels of T are significantly higher during the night than during the day. This pattern has also been observed in captive non-passerine birds, but its functional significance remains unknown.

Reliability of the input-output properties of the cortico-spinal pathway obtained from transcranial magnetic and electrical stimulation

The purpose of this experiment was to assess the test-retest reliability of input-output parameters of the cortico-spinal pathway derived from transcranial magnetic (TMS) and electrical (TES) stimulation at rest and during muscle contraction. Motor evoked potentials (MEPs) were recorded from the first dorsal interosseous muscle of eight individuals on three separate days. The intensity of TMS at rest was varied from 5% below threshold to the maximal output of the stimulator. During trials in which the muscle was active, TMS and TES intensities were selected that elicited MEPs of between 150 and 300 X at rest. MEPs were evoked while the participants exerted torques up to 50% of their maximum capacity. The relationship between MEP size and stimulus intensity at rest was sigmoidal (R-2 = 0.97). Intra-class correlation coefficients (ICC) ranged between 0.47 and 0.81 for the parameters of the sigmoid function. For the active trials, the slope and intercept of regression equations of MEP size on level of background contraction were obtained more reliably for TES (ICC = 0.63 and 0.78, respectively) than for TMS (ICC = 0.50 and 0.53, respectively), These results suggest that input-output parameters of the cortico-spinal pathway may be reliably obtained via transcranial stimulation during longitudinal investigations of cortico-spinal plasticity. (C) 2001 Elsevier Science B.V. All rights reserved.

Increased cerebral output of free radicals during hypoxia: implications for acute mountain sickness?

Bailey DM, Taudorf S, Berg RMG, Lundby C, McEneny J, Young IS, Evans KA, James PE, Shore A, Hullin DA, McCord JM, Pedersen BK, Moller K. Increased cerebral output of free radicals during hypoxia: implications for acute mountain sickness? Am J Physiol Regul Integr Comp Physiol 297: R1283-R1292, 2009. First published September 2, 2009; doi: 10.1152/ajpregu.00366.2009.-This study examined whether hypoxia causes free radical-mediated disruption of the blood-brain barrier (BBB) and impaired cerebral oxidative metabolism and whether this has any bearing on neurological symptoms ascribed to acute mountain sickness (AMS). Ten men provided internal jugular vein and radial artery blood samples during normoxia and 9-h passive exposure to hypoxia (12.9% O-2). Cerebral blood flow was determined by the Kety-Schmidt technique with net exchange calculated by the Fick principle. AMS and headache were determined with clinically validated questionnaires. Electron paramagnetic resonance spectroscopy and ozone-based chemiluminescence were employed for direct detection of spin-trapped free radicals and nitric oxide metabolites. Neuron-specific enolase (NSE), S100 beta, and 3-nitrotyrosine (3-NT) were determined by ELISA. Hypoxia increased the arterio-jugular venous concentration difference (a-v(D)) and net cerebral output of lipid-derived alkoxyl-alkyl free radicals and lipid hydroperoxides (P

A fast multi-output RBF neural network construction method

This paper investigates the center selection of multi-output radial basis function (RBF) networks, and a multi-output fast recursive algorithm (MFRA) is proposed. This method can not only reveal the significance of each candidate center based on the reduction in the trace of the error covariance matrix, but also can estimate the network weights simultaneously using a back substitution approach. The main contribution is that the center selection procedure and the weight estimation are performed within a well-defined regression context, leading to a significantly reduced computational complexity. The efficiency of the algorithm is confirmed by a computational complexity analysis, and simulation results demonstrate its effectiveness. (C) 2010 Elsevier B.V. All rights reserved.

Output Additionality of Public Support for Innovation: Evidence for Irish Manufacturing Plants

Public support for private R&D and innovation is part of most national and regional innovation support regimes. In this article, we estimate the effect of public innovation support on innovation outputs in Ireland and Northern Ireland. Three dimensions of output additionality are considered: extensive additionality, in which public support encourages a larger proportion of the population of firms to innovate; improved product additionality, in which there is an increase in the average importance of incremental innovation; new product additionality, in which there is an increase in the average importance of more radical innovation. Using an instrumental variable approach, our results are generally positive, with public support for innovation having positive, and generally significant, extensive, improved and new product additionality effects. These results hold both for all plants and indigenously owned plants, a specific target of policy in both jurisdictions. The suggestion is that grant aid to firms can be effective in both encouraging firms to initiate new innovation and improve the quality and sophistication of their innovation activity. Our results also emphasize the importance for innovation of in-house R&D, supply-chain linkages, skill levels and capital investment, all of which may be the focus of complementary policy initiatives.

Potential output in a rapidly developing economy: the case of China and a comparison with the United States and the European Union

The authors use a growth accounting framework to examine growth of the rapidly developing Chinese economy. Their findings support the view that, although feasible in the intermediate term, China's recent pattern of extensive growth is not sustainable in the long run. The authors believe that China will be able to sustain a growth rate of 8 to 9 percent for an extended period if it moves from extensive to intensive growth. They next compare potential growth in China with historical developments in the United States and the European Union. They discuss the differences in production structure and level of development across the three economies that may explain the countries' varied intermediate-term growth prospects. Finally, the authors provide an analysis of "green" gross domestic product and the role of natural resources in China's growth. © 2009, The Federal Reserve Bank of St. Louis.

Neural network forecasts of input-output technology

A significant part of the literature on input-output (IO) analysis is dedicated to the development and application of methodologies forecasting and updating technology coefficients and multipliers. Prominent among such techniques is the RAS method, while more information demanding econometric methods, as well as other less promising ones, have been proposed. However, there has been little interest expressed in the use of more modern and often more innovative methods, such as neural networks in IO analysis in general. This study constructs, proposes and applies a Backpropagation Neural Network (BPN) with the purpose of forecasting IO technology coefficients and subsequently multipliers. The RAS method is also applied on the same set of UK IO tables, and the discussion of results of both methods is accompanied by a comparative analysis. The results show that the BPN offers a valid alternative way of IO technology forecasting and many forecasts were more accurate using this method. Overall, however, the RAS method outperformed the BPN but the difference is rather small to be systematic and there are further ways to improve the performance of the BPN.