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Significant discoveries and breakthroughs have been made in the shale gas exploration in the southern slope zone of the Huangling uplift, periphery of the Sichuan basin. Based on previous research results, regional geological data, geophysical data and drilling data, it is proposed that the uplift has experienced four structural evolution stages since the Proterozoic, including the formation of crystalline basement in the pre-Sinian period, the intrusion of rock mass in the early Sinian period, the alternation of subsidence, deposition, uplift and denudation in the Sinian-middle Jurassic period, and the rapid uplift in the late Jurassic-Paleogene period. This distinctive structural evolution history of the Huangling uplift plays an important role in the shale gas accumulation, in which the third stage assures the appropriate depth and moderate thermal evolution and porosity, and the strong basement formed in the first stage protects the relative integrity and continuity of the sedimentary cap. We also found some uplifts with similar structural evolution history, basement and cap features as the Huangling uplift in the middle and lower Yangtze River area, such as the Xuefeng uplift and Qianzhong uplift on the periphery of the Sichuan Basin, and the Huoqiu uplift in the southern North China Basin. Through further geological, geophysical and drilling work, oil/gas reservoir may be discovered in the above uplifts.

The Tarim Basin Craton is located in the center of the Tarim Basin. Since the beginning of the Miocene, the tectonic activity has been weaker in the Tarim Basin Craton than in the marginal depression and the peripheral orogenic belts. This study investigates the tectonic movements in the Tarim Basin Craton by calculating the sedimentation rates and constructing balanced cross-sections based on well, seismic and geologic data. The tectonic movements in the Tarim Basin Craton have mainly been revealed by geological processes such as sedimentation and subsidence, structural inversion, changes in the structural feature, migration of the structural highs, and faulting. The Neogene sedimentary strata were mainly deposited in two sedimentation centers, the southern and northern sedimentation centers, and the strata in the Central Uplift Zone are relatively thin. The different depressions in different geological periods experienced wide variations in tectonic activity. Tectonic subsidence was significant and the sedimentation rates were high in the Tarim Basin Craton during the Pliocene Period (phase II). During the Neotectonic period, the stresses in the South-North direction converged in the Central Uplift Zone (the Bachu uplift-Central Tarim uplift), and the tectonic activity in this region was more intense than that in the Northern Depression and the Maigaiti Slope in the southwest. In addition, the scale of the paleo-uplift, including paleo-North Tarim Uplift and paleo-Central Uplift Zone, gradually decreased. The faults and fault systems developed zonationally in Neotectonic formations in different structural units, and always distributed discontinuously in vertical direction in sections. [ABSTRACT FROM AUTHOR]

Rhythmic respiratory movement in a deep and slow pattern can be beneficial to cardiovascular system, this paper investigates the effect of step-wise paced breathing procedure on blood oxygen saturation (SpO2). Experiment objects were divided into two groups, the normobaric hypoxia (simulated altitude of 4 500 meters hypoxia environment, 8 persons), normoxia and normobaric group (laboratory environment, 49 persons). The respiratory movements were performed by a high-to-low progressive change in two groups respectively. During the experiment, each object's blood oxygen saturation and heart rate were recorded. Results showed that progressive guided breathing could significantly increase the subjects' blood oxygen saturation level from 90% to 95% under the hypoxic condition. Even under the normobaric and normoxic condition, progressive guided breathing with stable blood oxygen saturation level can also enhance the blood oxygen saturation level. In both groups, mean heart rate declined in the progressive guided breathing. The research showed that the step-wise paced breathing technique could regulate the blood oxygen saturation and effectively improve the level of blood oxygen saturation by adjusting the respiratory motion in the low oxygen environment.

Heart rate variability (HRV) analysis technology based on an autoregressive (AR) model is widely used in the assessment of autonomic nervous system function. The order of AR models has important influence on the accuracy of HRV analysis. This article presents a method to determine the optimum order of AR models. After acquiring the ECG signal of 46 healthy adults in their natural breathing state and extracting the beat-to-beat intervals (RRI) in the ECG, we used two criteria, i. e. final prediction error (FPE) criterion to estimate the optimum model order for AR models, and prediction error whiteness test to decide the reliability of the model. We compared the frequency domain parameters including total power, power in high frequency (HF), power in low frequency (LF), LF power in normalized units and ratio of LF/HF of our HRV analysis to the results of Kubios-HRV. The results showed that the correlation coefficients of the five parameters between our methods and Kubios-HRV were greater than 0.95, and the Bland-Altman plot of the parameters was in the consistent band. The results indicate that the optimization algorithm of HRV analysis based on AR models proposed in this paper can obtain accurate results, and the results of this algorithm has good coherence with those of the Kubios-HRV software in HRV analysis.

In comparison with the measurement of heart rate variability from ECG and from photoplethysmographic signal from 46 healthy adults in their spontaneous breathing state. The beat-to-beat intervals in ECG and pulse-to-pulse intervals in photoplethysmographic signal are extracted, and then the parameters of heart rate variability are calculated. Three kinds of algorithms are chosen to get the pulse-to-pulse intervals, which are the intervals of maximum of second derivative, the maximum of PPG signal and the tangent intersection. The results show that the correlation coefficients of the HRV parameters in the two calculation methods are highly correlated. The Bland-Altman scattered plots show the relative bias results from the algorithm of the maximum of PPG signal are smallest and singular points that deviate from the consistent limits are the least compared with the other two algorithms.

To investigate the effect of stepwise paced breathing (PB) on pulse transit time (PTT), we collected physiological signals of electrocardiogram (ECG), respiration and arterial pulse wave during a procedure of stepwise PB, which consists of 6 different breathing rates changing in a protocol of 14.0-12.5-11.0-9.5-8.0-7.0 breath per minute (BPM), with each breathing rate lasting 3 minutes. Twenty two healthy adults involved in this experiment and the change of PTT was analyzed during the stepwise PB procedure. In our study, the PTT was measured by calculating the time interval from the R-spike of the ECG to the peaks of the second derivative of the arterial pulse wave. Ensemble empirical mode decomposition (EEMD) was applied to PTT to decompose the signal into different intrinsic mode function, and respiratory oscillation and trend component (baseline) in PTT were further extracted. It was found that the respiratory oscillations in the PTT increased with decreasing of the PB rate, and many of the subjects (14 out of 22) showed the phenomena of PTT baseline increasing during the stepwise PB procedure. The results indicated that the stepwise PB procedure induced a high level of cardiovascular oscillation and produced an accumulative effect of PTT baseline increase. As PTT is capable of predicting changes in BP over a short period of time, increase of PTT baseline indicates the decrease of blood pressure. The experiments showed that the stepwise PB procedure could reduce blood pressure for most subjects. For future work, it is necessary to develop certain indices differentiating the effectiveness of the stepwise PB procedure on the PTT baseline change, and to test the effectiveness of this stepwise PB procedure on blood pressure reduction for patients with essential hypertension.

Biomedical signal analysis often needs to separate the trend component from the non-trend component to achieve different purposes and applications in signal analysis. This article introduces three kinds of detrending nonlinear component methods used in the process of biomedical signal analysis: wavelet analysis, empirical mode decomposition, smoothness priors approach as well as the application in the separation of the actual biomedical data. The different separation methods should be selected according to different research goals as well as the feature of the signal.

To investigate the modulation effects of breathing movement on cardiovascular system and to study the physiological coupling relationship between respiration and cardiovascular system, we designed a comprehensive testing system for cardiorespiratory interaction research. This system, comprising three parts, i. e. physiological signal conditioning unit, data acquisition and USB medical isolation unit, and a PC based program, can acquire multiple physiological data such as respiratory flow, rib cage and abdomen movement, electrocardiograph, artery pulse wave, cardiac sounds, skin temperature, and electromyography simultaneously under certain experimental protocols. Furthermore this system can be used in research on short-term cardiovascular variability by paced breathing. Preliminary experiments showed that this system could accurately record rib cage and abdomen movement under very low breathing rate, using respiratory inductive plethysmography to acquire respiration signal in direct-current coupling mode. After calibration, this system can be used to estimate ventilation non-intrusively and correctly. The PC based program can generate audio and visual biofeedback signal, and guide the volunteers to perform a slow and regular breathing. An experiment on healthy volunteers showed that this system was able to guide the volunteers to do slow breathing effectively and simultaneously record multiple physiological data during the experiments. Signal processing techniques were used for off-line data analysis, such as non-invasive ventilation calibration, QRS complex wave detection, and respiratory sinus arrhythmia and pulse wave transit time calculation. The experiment result showed that the modulation effect on RR interval, respiratory sinus arrhythmia (RSA), pulse wave transit time (PWTT) by respiration would get stronger with the going of the slow and regular breathing.

A heart rate variability (HRV)analysis system is presented. The change of the activity of Sympathetic and vagus nerve is evaluated by detecting the parameters of heart rate variability of the tested in different states using the system. The system provides a tool for the study of heart rate variability.

A design of handheld heart rate variability acquisition and analysis system is proposed. The system collects and stores the patient's ECG every five minutes through both hands touching on the electrodes, and then -uploads data to a PC through USB port. The system uses software written in LabVIEW to analyze heart rate variability parameters, The parameters calculated function is programmed and generated to components in Matlab.

To investigate the effects of gradually guided breathing on respiratory sinus arrhythmia (RSA), 15 healthy men's simultaneous ECG and respiratory signals during the guided breathing process (14 beats/min-12.5 beats/ min--1 beats/min--9.5 beats/min--8 beats/minute--7 beats/min) were acquired. Based on the frequency domain and time domain methods, the effects of respiratory rate on RSA were studied. A general tendency increase features the three parameters of RSA as respiratory rate decreased. RSA represents the reflection control of respiratory system to cardiovascular system. The results suggested that the function of the reflection control of respiratory system to cardiovascular system increaseed with guided breathing decreasing. The conclusion indicates that the cardiovascular system could be improved by regulating the mode of respiration.

Respiratory sinus arrhythmia (RSA) is known as fluctuations of heart rate associated with breathing. It has been increasingly used as a noninvasive index of cardiac vagal tone in psychophysiological research recently. Its analysis is often influenced or distorted by respiratory parameters, posture and action, etc. This paper reviews five methods of quantification, including the root mean square of successive differences (RMSSD), peak valley RSA (pvRSA), cosinor fitting, spectral analysis, and joint timing-frequency analysis (JTFA). Paced breathing, analysis of covariance, residua method and msRSA per liter tidal volume are adjustment strategies of measurement and analysis of RSA in this article as well. At last, some prospects of solutions of the problems of RSA research are given.

Singularity is a basic feature of biological signals. Based on the variations of wavelet transform modulus maxima in multi-scales, we studied the basic theorem for analyzing the singularity and proposed an algorithm for calculating lipschitz exponent. Then we applied the algorithm to calculate the singularity of R-wave in ECG. Our study found that the level of singularity of R-waves in ECG between the 10 arrhythm patients randomly chosen and the healthy persons was significantly different, with the level of singularity of R-wave of normal persons remarkably higher than that of arrhythmia patients.