Cerebral hemodynamics during graded Valsalva maneuvers

The Valsalva maneuver (VM) produces large and abrupt changes in mean arterial pressure (MAP) that challenge cerebral blood flow and oxygenation. We examined the effect of VM intensity on middle cerebral artery blood velocity (MCAv) and cortical oxygenation responses during (phases I-III) and following (phase IV) a VM. Healthy participants (n = 20 mean +/- SD: 27 +/- 7 years) completed 30 and 90% of their maximal VM mouth pressure for 10 s (order randomized) whilst standing. Beat-to-beat MCAv, cerebral oxygenation (NIRS) and MAP across the different phases of the VM are reported as the difference from standing baseline. There were significant interaction (phase * intensity) effects for MCAv, total oxygenation index (TOI) and MAP (all P < 0.01). MCAv decreased during phases II and III (P < 0.01), with the greatest decrease during phase III (-5 +/- 8 and -19 +/- 15 cm.s(-1) for 30 and 90% VM, respectively). This pattern was also evident in TOI (phase III: -1 +/- 1 and -5 +/- 4%, both P < 0.05). Phase IV increased MCAv (22 +/- 15 and 34 +/- 23 cm.s(-1)), MAP (15 +/- 14 and 24 +/- 17 mm Hg) and TOI (5 +/- 6 and 7 +/- 5%) relative to baseline (all P < 0.05). Cerebral autoregulation, indexed, as the % MCAv/%MAP ratio, showed a phase effect only (P < 0.001), with the least regulation during phase IV (2.4 +/- 3.0 and 3.2 +/- 2.9). These data illustrate that an intense VM profoundly affects cerebral hemodynamics, with a reactive hyperemia occurring during phase IV following modest ischemia during phases II and III.

Empirical Doppler Characterization of Signals Scattered by Wind Turbines in the UHF Band under Near Field Condition

Time variability of the scattering signals from wind turbines may lead to degradation problems on the communication systems provided in the UHF band, especially under near field condition. In order to analyze the variability due to the rotation of the blades, this paper characterizes empirical Doppler spectra obtained from real samples of signals scattered by wind turbines with rotating blades under near field condition. A new Doppler spectrum model is proposed to fit the spectral characteristics of these signals, providing notable goodness of fit. Finally, the effect of this kind of time variability on the degradation of OFDM signals is studied.