3,652 research outputs found
Posture shift alters pattern of heart rate and blood pressure response during valsalva maneuver
No full textObjective: To compare the different postures under the Valsalva maneuver, cardiovascular response patterns difference. Method in -15 ° head-down tilt, the level of supine and +75 ° head-up tilt three positions, respectively 4 kPa / 30s the Valsalva maneuver, by jumping and record heart rate and arterial blood pressure changes. results +75 ° head-up tilt posture, heart rate increased in phase II the largest in the Phase III was at the lower changes, and in the other two there was a higher position changes. blood pressure in the early phase II to reduce the margin in -15 ° head-down tilt posture, to the smallest, +75 ° head-up tilt posture, to the greatest. +75 ° head-up tilt posture under Phase III of blood pressure was elevated in response, In -15 ° head-down tilt and level under the supine position was typical lower blood pressure changes. postural changes phase II of the Valsalva maneuver heart rate, blood pressure response mode most affected. conclusions postural changes can cause central blood volume and redistribution of the balance of the autonomic nervous change, so the Valsalva maneuver, heart rate and blood pressure response patterns have an impact.Aim: To examine the influence of posture shift on the pattern of heart rate and blood pressure response to Valsalva. Methods: Thirty seconds Valsalva maneuver strains at 4 kPa were performed under -15° head-down tilt, supine or +75° head-up tilt posture, and the beat-by-beat changes of heart rate and blood pressure were noninvasively recorded and analyzed. Results: The increasing change of heart rate for phase ? under +75° head-up tilt was beyond that under the other two postures. Under +75° head-up tilt, the heart rate decreased during phase ?, whereas under horizontal supine or -15° head-down tilt posture, the heat rate manifested an increasing change. The decreasing change of blood pressure during early phase ? was lowest under -15° head-down tilt, and highest under +75° head-up tilt. Blood pressure increased during phase ? under +75° head-up tilt, and decreased under other two postures. Conclusion: Posture shift alters the response pattern of heart rate and blood pressure during Valsalva maneuver, by circulating blood volume redistribution and autonomic balance shift to sympathetic predomination
Acroclita digitata Zhang & Li 2017
No full textAcroclita digitata Zhang & Li, 2017 Acroclita digitata Zhang & Li, 2017: 33. TL: China, Qinghai Province, Arboretum of Xining City; TD: NKUM. Specimens examined. 9♁ 14♀, Qinghai Province, Arboretum of Xining City (36.38 °N, 101.48 °E), alt. 2280 m, 20 July 1995, leg. Li H.H. & Wang S.X. (genitalia slide nos. WXP02455, WXP02456); 1♁ 2♀, Qinghai Province, Xining City, Beichuan, alt. 2290 m, 8 July 1995, leg. Li H.H. & Wang S.X. (genitalia slide no. ZAH04098); 1♁, Qinghai Province, Huangyuan County, 25 August 1995, leg. Zhu L.F.; 1♀, Hebei Province, Weichang County, Mt. Qipan, 17 July 2001, leg. Du Y.L. & Hao S.L.; 1♀, Hebei Province, Yuxian, Mt. Xiaowutai, alt. 1200 m, 25 July 2000, leg. Du Y.L. & Li Z.D. Host plant. Unknown. Distribution. China (Hebei, Qinghai). Remarks. This species is similar to Acroclita elaeagnivora Oku, but can be separated by the following features of the male genitalia: socius digitate, and ventral margin of basal opening with a nearly triangular process. In Acroclita elaeagnivora, the socius is long, hook-shaped, and the ventral margin of the basal opening bears a process with a blunt termination.Published as part of Zhang, Aihuan, 2023, Systematic study of Chinese Acroclita Lederer (Lepidoptera: Tortricidae), with the description of a new species, pp. 195-200 in Zootaxa 5228 (2) on page 198, DOI: 10.11646/zootaxa.5228.2.7, http://zenodo.org/record/753232
Cardiovascular age of aviation personnel: based on principal component analysis of heart rate and blood pressure variability
No full textObjective: To introduce a method to calculate cardiovascular age, a new, accurate and much simpler index for assessing cardiovascular autonomic regulatory function, based on statistical analysis of heart rate and blood pressure variability (HRV and BPV) and baroreflex sensitivity (BRS) data. Methods: Firstly, HRV and BPV of 89 healthy aviation personnel were analyzed by the conventional autoregressive (AR) spectral analysis and their spontaneous BRS was obtained by the sequence method. Secondly, principal component analysis was conducted over original and derived indices of HRV, BPV and BRS data and the relevant principal components, Pciorig and Pcideri (I=1, 2, 3,...) were obtained. Finally, the equation for calculating cardiovascular age was obtained by multiple regression with the chronological age being assigned as the dependent variable and the principal components significantly related to age as the regressors. Results: The first four principal components of original indices accounted for over 90? of total variance of the indices, so did the first three principal components of derived indices. So, these seven principal components could reflect the information of cardiovascular autonomic regulation which was embodied in the 17 indices of HRV, BPV and BRS exactly with a minimal loss of information. Of the seven principal components, PC2orig, PC4orig and PC2deri were negatively correlated with the chronological age (P<0.05), whereas the PC3orig was positively correlated with the chronological age (P<0.01). The cardiovascular age thus calculated from the regression equation was significantly correlated with the chronological age among the 89 aviation personnel (r=0.73, P<0.01). Conclusion: The cardiovascular age calculated based on a multi-variate analysis of HRV, BPV and BRS could be regarded as a comprehensive indicator reflecting the age dependency of autonomic regulation of cardiovascular system in healthy aviation personnel
Recent advances in multi-variate and multi-dimensional analysis of heart rate variability and blood pressure variability
No full textHeart rate variability and blood pressure variability reflected the cardiovascular autonomic nervous system modulation, studies in recent years have been made variable, multi-dimensional, dynamic analysis direction. Heart rate and blood pressure variability in multivariable system identification, time-frequency analysis and nonlinear kinetic analysis, and other technical methods, will be the risk of cardiovascular disease prediction, condition assessment, evaluation and special effects in areas such as the environment more medical applications
Removing Love waves from shallow seismic SH-wave data
No full textGeophysical exploration measurements are used to obtain an image of the geological structures of the subsurface, as detailed as possible. To this end, a wavefield is generated by a seismic source. This wavefield propagates through the subsurface, and will partly reflect on boundaries between layers with contrasting properties, and it will partly propagate further into the subsurface. De wavefields that have propagated back to the surface are measured with receivers. When this experiment is repeated several times on different locations, the measured data can be used to obtain the desired image. There are two kinds of seismic waves that can propagate through the subsurface. The ones that are generally used are the pressure waves, or P-waves, where the movement of the particles is parallel to the propagation direction of the wave. The other ones are the shear waves, or S-waves, where the movement of the particles is perpendicular to the propagation direction of the wave. When the particle movement is horizontally polarized (perpendicular to the plane of propagation), this wave type is often decoupled, or in other words, it propagates independently of other wave types. These waves are also called SH-waves. The surface of the Earth behaves as a perfect reflector for SH-waves. This means that all SH-waves that reach the surface will be completely reflected back into the subsurface. When the top layer of the subsurface is thin (smaller than the wavelength of the SH-wave), and when this top layer has a lower wave velocity than deeper layers, then the presence of the surface leads to a kind of surface waves, which were first described by A.E.H. Love, and are therefore called 'Love waves'. Love wave characteristics are: their group velocity is almost equal to the shear wave velocity; since they propagate solely along the surface, they attenuate slowly and are thus often stronger than reflected waves; and they are dispersive. The presence of Love waves deteriorates the quality of the final picture (or seismogram), because they obscure the desired reflections. Existing techniques to remove Love waves from seismic data often perform insufficient, or require certain knowledge about the subsurface. This knowledge is generally not available. Therefore, the ideal method should be one where the measured data alone is sufficient to separate the Love waves from the desired reflection information. The method we describe in this thesis uses the Betti-Rayleigh reciprocity theorem for elastic media. Reciprocity is a mathematical tool to relate two different states to each other. Here, one state is the actual situation, where the medium is bounded by a stress-free surface. The other state is an ideal situation, where there is no surface, and the top layer is extended to infinity. When there is no surface, there are also no surface waves. By applying the reciprocity theorem, we derive an integral equation, from which the Love wave free wavefield can be solved as a function of the data that do contain these surface waves. Other input parameters are the (shear-) wave velocity and the mass density of the top layer, and the source wavelet. When the data are discrete, the integral equation becomes a matrix equation. This can be solved using conventional numerical methods, such as matrix inversion. When the medium is horizontally layered (a so called 1-D medium), the kernel of the matrix equation becomes diagonal in the wave-number domain. Then the matrix equation reduces to a scalar expression. We tested the method on several synthetic datasets. In all cases, the Love waves were completely removed. Even other noise in the form of scattered Love waves was removed, in the cases where it was present. The method also had no problems when the input parameters were chosen wrongly. And when distortions were introduced into the data (distortions like random noise, or the effects of anelastic attenuation), the method still performed well. To test the method on field data, we performed a seismic experiment on the site of the Sofia tunnel (before it was drilled) near Hendrik Ido Ambacht in the Netherlands. The dataset that was the result seemed all right at first. Strong Love waves were indeed present in the data. However, we could not succeed in removing these Love waves with the method. Even worse, the method added noise to the data, to such an extent, that it completely obscured the original data. Although we searched extensively for possible reasons, we were not able to find the exact cause of the bad results. In the final chapter, we made a start to remove the surface waves from coupled P- and SV-wave systems, using the same method as we did for SH-waves. Because P- and SV-waves are coupled, the resulting equations are also coupled. This means that we need all possible source and receiver combinations to remove the surface waves. But it appeared that the equations could be solved independently with regard to the source direction. We validated the theory with an example where we removed the Rayleigh wave from the response of a homogeneousCivil Engineering and Geoscience
Age dependency and correlation of heart rate variability, pressure variability and baroreflex sensitivity
No full textSimultaneous analysis of heart rate variability (HRV), blood pressure variability (BPV) and baroreflex sensitivity (BRS) with different types of measures may provide non-duplicative information about autonomic cardiovascular regulation. Therefore, a multiple signal analysis of cardiovascular time series will enhance the physiological understanding of neuro cardiovascular regulation with deconditioning in bedrest or related gravitational physiological studies. It has been shown that age is an important determinant of HRV and BRS in healthy subjects. Whereas in the case of BPV, the effect of aging seems to depend upon the activity status of the subjects. In view of the facts that most of the previous works were dealing with only the variability of one kind of cardiovascular parameters in one study with conventional time-domain and/or frequency-domain analysis, we therefore designed the present work to compare the HRV, BPV and BRS between young and middle-aged male healthy subjects in one study with the same subjects using various techniques, including the approximate entropy (ApEn) measurement, a statistic quantifying HRV "complexity" derived from non-linear dynamics
QRS complexes detection based on wavelet transform and correlation analysis (In Chinese)
No full textDS_10.1177_0022034519850574 – Supplemental material for Antiadipogenesis and Osseointegration of Strontium-Doped Implant Surfaces
No full textSupplemental material, DS_10.1177_0022034519850574 for Antiadipogenesis and Osseointegration of Strontium-Doped Implant Surfaces by C. Zhou, Y.Q. Chen, Y.H. Zhu, G.F. Lin, L.F. Zhang, X.C. Liu and F.M. He in Journal of Dental Research</p
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