Research on Liquid Flow Rate Detection of Mixed Fluid Based on Vibration Signal Characteristic Analysis of Gas Liquid Two-Phase Flow

,


Introduction
Gas-liquid two-phase fow is a common mixed fow state in the industrial feld [1][2][3], which widely exists in petroleum, metallurgy, frepower, and other industrial production. Due to the interaction between phases and the alternation of time and space, the gas-liquid two-phase fow has the characteristics of complex and changeable fow, violent fuctuation, and strong randomness and presents diversifed fow patterns in the pipeline [4][5][6]. Among them, the fow parameter in the gas-liquid two-phase fow is one of the important parameters to characterize the many characteristics of the gas-liquid two-phase fow. An accurate and efcient fow parameter measurement of gas-liquid two-phase fow is of great signifcance to improving the safety and stability of gas well production.
Due to the complex and changeable hydrodynamic characteristics of gas-liquid two-phase fow, there are many uncertain factors in its parameter detection [7]. It is difcult to achieve an accurate measurement of the two-phase fow characteristic parameters, especially the fow rate of mixed fuid, only by means of the traditional single-phase fow parameter measurement method. Accurate detection of liquid holdup in multiphase fow has become a hot research issue in this feld [8]. Te research on its online detection method is of great signifcance for the production management, control, and safe operation and maintenance of oilfeld gas well production operations.
In recent years, researchers have carried out continuous research on the detection methods of fow parameters in gas-liquid two-phase fow. Based on the Doppler shift information obtained by UVP, Wang used the ultrasonic pulse echo intensity information to judge the phase interface so as to measure the fow rate of oil-gas-waterthreephase stratifed fow and compare it with the results of PIV and a high-speed camera [9]. Murdock gave a modifed calculation formula for the split-phase fow model by performing a gas-water mixture experiment [10]. Chisholm assumed that the gas-liquid two-phase fow through the orifce plate is a split-phase fow, and the measurement model of the orifce plate split-phase fow is derived from the gas-liquid two-phase fow equation [11]. Xu et al. from Tianjin University used a double diferential pressure long throat Venturi fow sensor as a measurement method to predict the gas-liquid two-phase fow of wet gas through computational fuid dynamics simulation technology [12]. Li put forward the design idea of installing the nearinfrared probe along the direction of fuid fow and proved the advantages of the new gas-liquid two-phase fow detection device in using near-infrared to measure phase holdup through experiments [13]. Fang used laser diode with a wavelength of 980 nm and silicon photodiode to carry out real-time online measurements of gas-liquid twophase fow in horizontal and vertical directions [14]. Liang determined the wavelength of near-infrared light through static and dynamic experiments and obtained the estimated value ftting formula of phase content [15]. By analyzing the relationship between the propagation velocity, temperature, and medium density of an ultrasonic wave in light fuel, Zhang et al. established a model by using artifcial neural network and completed the mass fow measurement of light fuel [16]. Hou et al. established the functional relationship between energy fraction and particle size by using the vibration noise signals collected by acoustic emission with diferent particle size distributions from the collision between particles in a gas-solid fuidized bed and distribution plate [17].
Te abovementioned detection methods have played a positive role in promoting the development of gas-liquid two-phase fow measurement methods, but there are few reports on the monitoring of liquid fow rate in gas-liquid two-phase fow. At the same time, the time-frequency analysis of unsteady and nonlinear random signals excited by gas-liquid two-phase fow impacting on the pipe wall has not achieved a unifed and complete description. Ong et al. constructed a threshold function based on wavelet transform to characterize the noise excited by the fuid, but it is difcult to construct a wavelet base matching the fuid's characteristics [18]. Aghdam et al. extracted the features of nonstationary vibration signals based on the ARMA time series model, but there are some problems such as complex modeling, contradiction between order selection, and calculation amount [19]. Liu obtained the optimal timefrequency representation of energy concentration based on the VWD distribution, but it is disturbed by the cross terms when analyzing the multicomponent signals [20]. In summary, it is of great practical signifcance to study the detection method of liquid fow rate in gas-liquid two-phase fow based on the analysis of time-frequency characteristics of vibration signals.
Aiming at the problem of liquid production in gas wells at high water cut stage, an innovative method is designed in this paper, which uses an acceleration sensor detection system to obtain the vibration signals excited by fuid impact at the elbow pipe wall and analyzes the time-frequency characteristics of the signal to monitor the change in the liquid fow rate. Compared with traditional detection methods, this method has the advantages of convenient installation, real-time online monitoring, better accuracy, and higher cost performance. At the same time, this method can also provide technical support for adjusting the production parameters in time, reducing excessive liquid production, improving gas well recovery efciency, reducing costs, and increasing the efciency of gas production.

Characteristic Analysis of Vibration Signals Excited by Liquid Particle in Gas-Liquid Two-Phase Flow
Te gas-liquid two-phase fow has a certain kinetic energy when fowing in the pipeline. When the gas-liquid mixed fuid passes through the 90°elbow of the pipeline at a higher speed, due to the sudden change of the fow direction, the liquid particles will break away from the drag force of the air fow under the inertial action and impact the pipe wall and cause vibration, as shown in Figure 1. Te liquid particles in the gas-liquid two-phase fow impact the pipe wall to generate continuous kinetic energy. Te acceleration sensor arranged outside the elbow picks up the vibration signal and further converts it into the required liquid particle parameters. Te kinetic energy KE excited by the liquid particle impact is shown in the following formula: In the formula, m is the mass of liquid particles and v is the velocity of liquid particles impacting on the pipe wall. It can be concluded from the qualitative analysis that the kinetic energy of liquid particles is positively correlated with its mass, and the kinetic energy of liquid particles increases exponentially with its migration velocity.
Te nonstationary and nonlinear random vibration signals excited by the low content liquid droplet impacting on the pipe wall in the gas-liquid mixed fow are very weak, and the conventional signal processing methods are based on static assumptions. Terefore, only the statistical characteristics of the signals are studied in a single range of time domain or frequency domain, which cannot reveal the independent characteristics of the liquid particle signals in the time-frequency joint domain. In order to efectively distinguish the diferent characteristics of the signals excited by the liquid particle impacting on the pipe wall and the air fow impacting on the pipe wall [21] and at the same time make up for the defciency that the conventional Fourier transform method cannot be applied to the analysis of nonperiodic and nonstationary signals [22], in this paper, the time-frequency analysis method based on the short-time Fourier transform (STFT) [23] is adopted to process the random signal excited by the liquid particle impacting on the pipe wall. Yichen Li et al. [24] proposed a method for monitoring sand production in ofshore oil wells which are based on the vibration response characteristics of sandcarrying fuid fow impinging on the pipe wall. Tis method uses acceleration sensors to obtain the weak vibration response characteristics of sand particles impinging on the pipe wall on a two-dimensional time-frequency plane. Te time-frequency parameters are further optimized, and the ability to identify weakly excited vibration signals of sand particles in the fuid stream is enhanced. In this method, the window function method operation is frst performed on the nonstationary signal, and the signal is segmented at a series of short-time intervals, which is similar to the superposition of several stationary signals. Once again, the Fourier decomposition operation is carried out for each approximated stationary signal. Te short-time Fourier transform method not only solves the defect that the traditional Fourier transform cannot refect the time resolution but also solves the frequency aliasing problem that the conventional wavelet transform cannot avoid in the frequency domain. It can directly provide the broad-spectrum frequency characteristics of the signals and the corresponding energy characteristics, and the energy amplitude is characterized as follows: In the formula, h * (τ − t) is a window function centered on t � 0, which has time aggregation and frequency aggregation. Its transformation can be regarded as the decomposition of the signal on the orthogonal basis function. Te basis function has both time and frequency resolution in diferent transformations.
After obtaining the characteristic frequency band of the vibration signals excited by the liquid particle impact, band-pass fltering is used to further flter out the characteristic signal of the airfow frequency band, and then the fuid particle frequency band signal is extracted. Te transfer function is as follows: In the formula, N is the fltering order, M is the zero point of the transfer function, and a 1k and b 1k are weight function coefcients.
Te power spectrum characteristics of the random vibration signals excited by the multiphase fow impacting on the pipe wall refect the variation characteristics of the signal power with frequency in the unit frequency band. Terefore, the variation law of the random signal energy with frequency can be obtained by the power spectrum density function. Te average power of the power spectrum signal f(t) in the time domain t � [− (T/2), (T/2)] can be expressed as follows:

Experimental Device.
Te two-phase mediums in the gas-liquid two-phase fow rate test are air and water. Figure 2 is composed of gas supply system, liquid supply system, test pipe section, metering system, signal acquisition system, and gas-liquid separation system [25].
In the liquid supply system, the tap water extracts the water from the liquid metering tank into the single-phase pipe section of the water fow. Te opening of the tap water valve can adjust the size of the water fow. Te liquid metering tank (with the measurement range of 0-20 m 3 /h, fow velocity range of 0-2.83 m/s, and accuracy of ±0.5%) is used to measure water fow before mixing.
In the gas supply system, the air is pressurized by the air compressor (the maximum displacement is 35 m 3 /min) and sent to the gas tank, and then the compressed gas is fully dried by the air dryer. Te tape gas valve is installed between the gas tank and the blender. Te regulating valve can play the role of depressurization and pressure stabilization to ensure the stability of the gas tape pressure during the experiment. At the same time, the opening of the tape gas valve is controlled to adjust the intake gas fow rate. Te gas metering tank (with the measurement range of 0-210 m 3 /h and accuracy of ±1%) measures the gas fow rate before mixing.
Te inner diameter of the test pipe is 60 mm, and the whole pipe section is about 14 m. Te length of the pipe involved in the experiment is 9.5 m, and the observation section is a transparent organic glass pipe of 7 m, so as to observe the liquid carrying state of the airfow and the gas- Shock and Vibration 3 liquid two-phase fow pattern. Te inlet and outlet of the test pipe are respectively provided with quick closing valves. Te distance between the two quick closing valves is 9.5 m. Te air and water excited by the pump and the air compressor respectively enter from two pipe branches, as shown in Figure 3. When starting the experimental device, the liquid is frst flled with the pipeline, and the pneumatic valve is opened after the water fow velocity is stable, and then the gas fow rate is adjusted from small to large. Gasliquid two phases respectively fow in their single-phase pipes for a certain distance and then reach a stable fow velocity. Te fow velocity is measured by a standard fowmeter, and then gas-liquid two phases are fully mixed by a jet and sent to the horizontal test pipe section for experiment. Te high-speed camera is used to photograph the two-phase fow pattern in the pipe.
Acceleration sensors are arranged at 2-3 times the pipe diameter of the lower elbow of the pipeline, that is, the position where the liquid particles impact the pipe wall at a high speed to obtain the vibration signals excited by the pure airfow and the gas-liquid two-phase fow impacting on the pipe wall. Te vibration signals excited by the simulated gas well liquid production under indoor experimental conditions are obtained through the acceleration sensor and data processing system.

Experimental Design.
Te experimental parameters for characteristic analysis of gas-liquid two-phase pipe fow excitation signal are shown in Table 1, and the experimental process is as follows: (1) Experimental temperature is 24°C. Te gas volume regulation increases from 10, 20, 30, 40, 50, and 60 m 3 / h in turn, and the step is 10 m 3 /h. Liquid volume regulation increases from 0.2 to 0.6 m 3 as needed.
(2) After the gas-liquid mixing is carried out on the experimental platform, the gas-liquid two-phase fow through the 90°elbow pipe causes the liquid particles impacting on the pipe wall, so as to stimulate the vibration signal. A total of 18 sets of tests are carried out after the combination of the gas and liquid at diferent fow rates.
(3) Due to the hardware limitations of the experimental device and the change in the measurement method, the values of the parameters in the table are within the error range.

. Flow Characteristics of Gas-Liquid Two-Phase Flow
Te fow pattern of two-phase fow near the pipe elbow is studied by using the conventional observation method [26]. In order to obtain the vibration signals excited by liquid particles impacting on the pipe wall in gas-liquid two-phase fow as comprehensively as possible, the fow velocity interval that is relatively stable in a specifc range and has no obvious change in the trajectory observation is selected as the observation object. By observing the fow characteristics of gas-liquid twophase fow in the fow velocity range of 0.46-1.2 m/s, the Te application range of this measurement method is suitable for the measurement scenario combining medium gas fow range (0-60 m 3 /h) and small fow range (0.2-0.6 m 3 /h). In such a mixing mode of medium gas volume and small liquid volume, the gas-liquid mixed fuid presents a liquid bubble fow, in which the liquid presents a liquid particle state under the impact of the gas fow, which is suspended in a large amount of gas and moves forward at a constant speed, impacting the pipe wall at the elbow and causing vibration.

Analysis of Experimental Results
In this paper, the three-dimensional spectral array diagram analysis method based on STFT is used to analyze and study the nonstationary and nonlinear random vibration signals of gas-liquid two-phase fow. Te spectrum array diagram superimposes the energy of the vibration signal with time into a three-dimensional spectrum diagram, showing the relationship between the frequency and amplitude of the signal with time. Te logarithmic coordinate is selected for the energy amplitude. Te basic principle is as follows:

Time-Frequency Characteristic Analysis of Airfow Signal
at Diferent Flow Velocities. Te vibration signals excited by the gas-liquid two-phase fow impacting on the pipe wall are the superposition of the strong vibration signals excited by airfow impacting on the pipe wall and the weak vibration signals excited by liquid particles impacting on the pipe wall. Figure 4 shows the time domain characteristics of the vibration signals excited by the airfow impacting on the pipe wall at diferent fow velocities. Te amplitude of the time domain signal is positively correlated with the change in the airfow velocity, so the fow velocity has a great infuence on the signal amplitude. In order to efectively extract the weak vibration signals excited by the liquid particle impacting on the pipe wall in the gas-liquid two-phase fow, it is necessary to further analyze the characteristics of the relatively strong vibration signals excited by the airfow impacting on the pipe wall. Figure 5 shows the frequency domain characteristics of airfow signals at diferent fow velocities. Te results show that the amplitude of the signal changes signifcantly with the fow velocity in the frequency band range of 45-75 Hz. Tis frequency band is identifed as the main frequency band of the vibration signals excited by the airfow impacting on the pipe wall, indicating that the fow velocity has a significant impact on the signal in this frequency band. Terefore, it is not suitable to fnd the signal characteristics of liquid particles in this frequency band. gas-liquid mixing the air-entry

Shock and Vibration
Te gas-liquid two-phase fow impacts the elbow pipe wall to generate nonstationary and nonlinear random vibration signals. However, the traditional Fourier transform analysis only reveals the statistical characteristics of the signals in the frequency domain and cannot express the time-varying characteristics of the airfow signals in the joint timefrequency plane. Terefore, the STFT time-frequency analysis method is selected to further study the time-varying energy characteristics of the vibration signals excited by the airfow impacting on the elbow pipe wall at diferent fow velocities. Figure 6 shows the 3D surface diagram analysis of the vibration signals excited by the airfow impact at diferent fow velocities in a certain period of time. Te selected window function is Hamming window [27], and the FFT length is 20000 points.
It can be seen from Figure 6(a) that when the fow velocity is 0.46 m/s, the frequency domain range of the signal excited by the airfow impact is concentrated in the three frequency bands of 6.5-15 Hz, 34-43.5 Hz, and 45-78.5 Hz. In the range of 45-78.5 Hz, the signal intensity is higher than that in other frequency bands, and the stability is acceptable. In the range of 34-43.5 Hz, the signal strength and the stability take the second place. In the range of 6.5− 15 Hz, the signal intensity is relatively low, and the signal amplitude fuctuation is weak. In summary, at a fow velocity of 0.46 m/ s, the characteristic frequency band of the signal excited by the airfow impacting on the pipe wall is determined to be within the range of 45-78.5 Hz.
By analyzing the results of Figures 6(b)-6(d), it is concluded that the frequency response characteristics of the vibration signals excited by the airfow impacting on the pipe wall are roughly similar to those of Figure 6

Analysis of Time-Frequency Characteristics of Vibration Signals Excited by Gas-Liquid Two-Phase Flow at Diferent
Flow Velocities. Due to the small particle size of the liquid particles in the gas-liquid mixed fuid, the fow velocity of the liquid particles in the pipeline can be regarded as similar to the fow velocity of the gas in the pipeline. Te time domain and frequency domain analysis of gas-liquid mixed fuid at diferent fow velocities is carried out. Te results are shown in Figures 7 and 8.
It can be seen from Figure 8 that in the frequency band of 45-78.5 Hz, the range and trend of signal amplitude show signifcant change in characteristics with the change in fow velocity. Compared with the time domain analysis results in Figure 7, at diferent fow velocities, the amplitude change of signal in the same frequency band of 45-78.5 Hz is very similar to the trend change, so this frequency band is considered as the sensitive frequency band of the two-phase fow. However, the frequency band for analyzing the characteristics of vibration signals excited by the liquid particles impacting on the pipe wall should be within 5− 15 Hz, and the amplitude of the signal frequency domain shows a small order of fuctuation characteristics. Terefore, this frequency band is selected as the characteristic frequency band of the vibration signals excited by the liquid particle impacting on the pipe wall.
Te STFT time-frequency analysis method is used to analyze the characteristics of the vibration signals excited by the gas-liquid two-phase fow impacting on the elbow pipe wall. Figure 9 shows the 3D surface energy analysis results of the vibration signals excited by the gas-liquid two-phase fow within a certain time range.
As can be seen from Figure 9(a), when the gas-liquid two-phase fow velocity is 0.46 m/s, the frequency range of the excited vibration signals mainly focuses on the three frequency bands of 40− 75 Hz, 34-43.5 Hz, and 6.5− 15 Hz. Te signal amplitude intensity in the frequency band of 34-43.5 Hz is lower than before; at the same time, the signal stability is also reduced. Te signal amplitude intensity in the frequency band of 6.5− 15 Hz is higher than that in the frequency band of 34-43.5 Hz, but the fuctuation of signal amplitude is obvious. Terefore, when the airfow velocity is 0.46 m/s, the main frequency band of the signal excited by the gas-liquid two-phase fow impacting on the pipe wall is 40− 75 Hz, and the frequency band with obvious fuctuation is 6.5− 15 Hz.
Te analysis results of Figures 9(b)-9(d) show that when the fuid velocities are 0.75 m/s, 0.89 m/s, and 1.20 m/s, respectively, the frequency response characteristics of the signals excited by the gas-liquid two-phase fow impacting on the pipe wall are consistent with Figure 9(a).
By comparing the analysis result of the spectral array diagram of vibration signals excited by airfow in Figure 6 with that of vibration signals excited by gas-liquid two-phase fow in Figure 9, it is concluded that the frequency band of vibration signals excited by two-phase fow impacting on the pipe wall is mainly concentrated in 40− 75 Hz, but the signal amplitude fuctuates signifcantly in the range of 6.5− 15 Hz. Terefore, the signal excited by the liquid particles impacting on the pipe wall in the 40− 75 Hz frequency band is easily submerged, and then the 6.5− 15 Hz frequency band is identifed as the characteristic frequency band of the vibration signals excited by the liquid particles impacting on the pipe wall.

Relationship between Liquid Content and Vibration Energy in Gas-Liquid Two-Phase Flow.
Te feasibility of the vibration signal detection method in this paper is verifed by constructing a mathematical model of liquid fow rate in gasliquid two-phase fow. Te vibration energy excited by gasliquid two-phase fow impacting on the pipe wall is expressed by E V , as follows: In the formula, V(t) is the voltage value obtained after signal processing and T is the sampling time length of the signal. Te signal refreshing period is 0.5 s and the sampling length is 20,000 points.
In order to reduce the infuence of airfow noise on the characteristics identifcation of vibration signals excited by liquid particles impacting on the pipe wall, the energy characteristics of them are further studied. By comparing the 8 Shock and Vibration frequency domain characteristics of the vibration signals excited by the gas fow and gas-liquid two-phase fow impacting on the pipe wall at diferent fow velocities, bandpass fltering is carried out on the frequency band of the signals excited by the liquid particles impacting on the pipe wall in the range of 6.5− 15 Hz. Figure 10 shows the relative average vibration energy of the signals excited by the liquid particles impacting on the pipe wall at diferent liquid fow rates and fow velocities. Te velocities of liquid particles impacting on the pipe wall are 0.46 m/s, 0.75 m/s, 0.89 m/s, and 1.2 m/s, respectively. Te results show that with the increase in the liquid fow rate and two-phase fow velocity, the vibration energy excited by liquid particles impacting on the pipe wall is positively correlated with it. Te third-order polynomial is used to ft the relative average vibration energy of the fow velocity in the range of 0.46 m/s-1.20 m/s, and the relationship between the velocity of the liquid impacting on the elbow pipe wall and the relative average vibration energy is obtained. F(v, f) liquid is recorded as the relative average vibration energy excited by liquid particles impacting on the pipe wall in the gas-liquid two-phase fow, where v is the fow velocity and f is the signal bandwidth. Te expression after a polynomial ftting is as follows: Te signals in the liquid content characteristic frequency band of 6.5− 15 Hz in the gas-liquid two-phase fow are preprocessed to obtain the relative average vibration energy of the vibration signals excited by gas-liquid two-phase fow impacting on the pipe wall under diferent conditions. Figure 11 shows the distribution of relative average vibration energy excited by gas-liquid two-phase fow impacting on the elbow pipe wall under diferent liquid fow rates and fow velocities.
As shown in Figure 11, when the liquid fow rate is constant, the relative average vibration energy excited by gas-liquid two-phase fow impacting on the pipe wall shows a positive correlation with the increase in two-phase fow velocity. When the fow velocity is constant, the relative average vibration energy excited by gas-liquid two-phase fow impacting on the pipe wall is positively correlated with the increase in liquid fow rate. Tird-order polynomial is used to describe the vibration signals excited by liquid fow impacting on the pipe wall at diferent fow velocities, as shown in the following formula: When the liquid fow rate is set to zero, the average vibration energy corresponding to diferent fow velocities is substituted into formula (9), and the ftting coefcient of third-order polynomial is obtained as shown in Table 2.  Te vibration signals excited by gas-liquid two-phase fow impacting on the elbow pipe wall are processed and converted into corresponding vibration energy, which can describe the change trend of liquid fow rate. However, in order to obtain more accurate liquid fow rate, it is necessary to preprocess the vibration signal energy, that is, the amplitude of vibration signals excited by gas-liquid two-phase fow impacting on the pipe wall subtracts the amplitude of vibration signals excited by pure airfow impacting on the pipe wall under the same condition. Te preprocessed vibration signals excited by gas-liquid two-phase fow impacting on the pipe wall divides by the calibration vibration signals excited by the liquid fow impacting on the pipe wall to obtain a relatively accurate liquid fow rate by using the quantitative analysis. Referring to the calibration liquid fow signal, that is, the vibration signals excited by liquid particle impacting on the pipe wall under the condition of 1 m/s liquid fow, the calculation method of the liquid fow rate is as follows: Te vibration signals excited by gas-liquid two-phase fow impacting on the pipe wall at diferent fow velocities are calculated by formula (10) to verify the accuracy of the liquid holdup calculation formula. Tree experiments are carried out at each fow velocity, as shown in Figure 12. Te triangle marks in the fgure show the liquid fow rate calculated by formula (10). As shown in the fgure, the calculated value fuctuates within 10% of the normal error   above and below the theoretical value. Te resulting analysis in the fgure shows that the calculation method can weaken the infuence of the calculation results under the conditions of diferent liquid fow rates and diferent fow velocities. Terefore, the vibration signal processing method based on STFT time-frequency analysis can realize the quantitative and accurate detection of liquid fow rate in gas-liquid twophase fow. Te use range of the calculation model is as follows: the condition is controlled at the fow rate v: 0.4 m/s-1.2 m/s. Te liquid fow rate is calculated in the range of 0.2-0.6 m/s.

Conclusion
In this paper, the liquid fow characteristics in gas-liquid two-phase fow are detected and analyzed by the timefrequency analysis method based on the vibration signal characteristic analysis. By analyzing the time-frequency characteristics of the vibration signals excited by the airfow impacting on the pipe wall at diferent fow velocities and the gas-liquid two-phase fow impacting on the pipe wall under diferent liquid contents, it is shown that the amplitude of the vibration signal excited by the airfow impacting on the pipe wall is the smallest and the signal is stable in the frequency band of 6.5− 15 Hz. Terefore, this frequency band is identifed as the characteristic frequency band of the vibration signals excited by the liquid particle impacting on the pipe wall. At the same time, with the increase in liquid fow rate, the signal's amplitude in the characteristic frequency band is positively correlated with it. Terefore, the validity of 6.5− 15 Hz frequency band as the characteristic frequency band of liquid fow is verifed again, and the mathematical model of the relationship between liquid holdup and vibration energy is constructed. Te research method has laid a good research foundation for the subsequent detection of each phase in complex gas-liquid-solidthreephase fow and gas-solid two-phase fow.

Data Availability
Te data used to support the fndings of this study are available from the corresponding author upon request.

Conflicts of Interest
Te authors declare that there are no conficts of interest regarding the publication of this paper.