The impact of problem domain on Bayesian inferences: A systematic investigation.

Sparse (and occasionally contradictory) evidence exists regarding the impact of domain on probabilistic updating, some of which suggests that Bayesian word problems with medical content may be especially challenging. The present research aims to address this gap in knowledge through three pre-registered online studies, which involved a total of 2,238 participants. Bayesian word problems were related to one of three domains: medical, daily-life, and abstract. In the first two cases, problems presented realistic content and plausible numerical information, while in the latter, problems contained explicitly imaginary elements. Problems across domains were matched in terms of all relevant statistical values and, as much as possible, wording. Studies 1 and 2 utilized the same set of problems, but different response elicitation methods (i.e., an open-ended and a multiple-choice question, respectively). Study 3 involved a larger number of participants per condition and a smaller set of problems to more thoroughly investigate the magnitude of differences between the domains. There was a generally low rate of correct responses (17.2%, 17.4%, and 14.3% in Studies 1, 2, and 3, respectively), consistent with accuracy levels commonly observed in the literature for this specific task with online samples. Nonetheless, a small but significant difference between domains was observed: participants' accuracy did not differ between medical and daily-life problems, while it was significantly higher in corresponding abstract problems. These results suggest that medical problems are not inherently more difficult to solve, but rather that performance is improved with abstract problems for which participants cannot draw from their background knowledge.

Natural frequency tree- versus conditional probability formula-based training for medical students' estimation of screening test predictive values: a randomized controlled trial.

BACKGROUND: Medical students and professionals often struggle to understand medical test results, which can lead to poor medical decisions. Natural frequency tree-based training (NF-TT) has been suggested to help people correctly estimate the predictive value of medical tests. We aimed to compare the effectiveness of NF-TT with conventional conditional probability formula-based training (CP-FT) and investigate student variables that may influence NF-TT's effectiveness. METHODS: We conducted a parallel group randomized controlled trial of NF-TT vs. CP-FT in two medical schools in South Korea (a 1:1 allocation ratio). Participants were randomly assigned to watch either NF-TT or CP-FT video at individual computer stations. NF-TT video showed how to translate relevant probabilistic information into natural frequencies using a tree structure to estimate the predictive values of screening tests. CP-FT video showed how to plug the same information into a mathematical formula to calculate predictive values. Both videos were 15 min long. The primary outcome was the accuracy in estimating the predictive value of screening tests assessed using multiple-choice questions at baseline, post-intervention (i.e., immediately after training), and one-month follow-up. The secondary outcome was the accuracy of conditional probabilistic reasoning in non-medical contexts, also assessed using multiple-choice questions, but only at follow-up as a measure of transfer of learning. 231 medical students completed their participation. RESULTS: Overall, NF-TT was not more effective than CP-FT in improving the predictive value estimation accuracy at post-intervention (NF-TT: 87.13%, CP-FT: 86.03%, p = .86) and follow-up (NF-TT: 72.39%, CP-FT: 68.10%, p = .40) and facilitating transfer of training (NF-TT: 75.54%, CP-FT: 71.43%, p = .41). However, for participants without relevant prior training, NF-TT was more effective than CP-FT in improving estimation accuracy at follow-up (NF-TT: 74.86%, CP-FT: 58.71%, p = .02) and facilitating transfer of learning (NF-TT: 82.86%, CP-FT: 66.13%, p = .04). CONCLUSIONS: Introducing NF-TT early in the medical school curriculum, before students are exposed to a pervasive conditional probability formula-based approach, would offer the greatest benefit. TRIAL REGISTRATION: Korea Disease Control and Prevention Agency Clinical Research Information Service KCT0004246 (the date of first trial registration: 27/08/2019). The full trial protocol can be accessed at https://cris.nih.go.kr/cris/search/detailSearch.do?seq=15616&search_page=L .

Natural Frequency Transmissibility for Detection of Cracks in Horizontal Axis Wind Turbine Blades.

Defects on horizontal axis wind turbine blades are difficult to identify and monitor with conventional forms of non-destructive examination due to the blade's large size and limited accessibility during continuous operation. This article examines both strain and acceleration transmissibility as methods of continuous damage detection on wind turbine blades. A scaled 117 cm offshore wind turbine blade was first designed, 3D printed, and modelled numerically in ANSYS. Transverse cracks were deliberately introduced to the blade at 10 cm intervals along its leading edge. Subsequent changes in the transmissibility, relative to an undamaged baseline model, were measured using different variable combinations at the blade's first three natural frequencies. Experimental results indicated that strain transmissibility was able to locate a 1.0 cm defect at a range of 70-110 cm from the blade hub using the amplitudes of the first natural frequency of vibration. The numerical model was able to simulate the strain experimental results and was determined to be valid for future defect characterization. Acceleration transmissibility was unable to experimentally identify defects sized at 1.0 cm and below but was able to identify 1.0 cm sized defects numerically. It was concluded that transmissibility is viable for continuous damage detection on blades but that further research into other defect types and locations is required prior to conducting full-scale testing.

The 10 Hz dynamic response of a fluid-filled pressure monitoring system is a novel alternative to the fast flush test and indicative of unacceptable systolic pressure overshoot.

The standard method for qualitatively evaluating the dynamic response is to see if the gain of the amplitude spectrum curve approaches 1 (input signal = output signal) over the frequency band of the blood pressure waveform. In a previous report, Watanabe reported that Gardner's natural frequency and damping coefficient, which are widely used as evaluation methods, do not reflect the dynamic response of the circuit. Therefore, new parameters for evaluating the dynamic response of pressure monitoring circuits were desired. In this study, arterial pressure catheters with length of 30, 60, 150, and 210 cm were prepared, and a blood pressure wave calibrator, two pressure monitors with analog output and a personal computer were used to analyze blood pressure monitoring circuits. All data collection and analytical processes were performed using step response analysis program. The gain at 10 Hz was close to 1 and the systolic blood pressure difference was small in the short circuits (30 cm, 60 cm), and the gain at 10 Hz was 1.3-1.5 in the 150 cm circuit and over 1.7 in the 210 cm circuit. The difference in systolic blood pressure increased in proportion to the length of the circuit. It could also be inferred that the gain at 10 Hz should be less than 1.2 to meet a clinically acceptable blood pressure difference. In conclusion, the gain at 10 Hz is sufficiently useful as an indicator to determine the correct systolic blood pressure.

Experimental and Computer Simulation Studies on Badminton Racquet Strings.

This study investigates experimentally, numerically, and analytically the performance of different string materials (Kevlar, synthetic gut, natural gut, and polyester) on badminton racquets. Vibration and impact tests with a shuttlecock were performed using a racquet frame made of carbon graphite mixed with epoxy resin. Different string tensions were considered in the tests (20, 22, 24, 28, 30, and 34 lb), as well as different hitting locations on the racquet frame. The results show that, as the diameter of the strings increased, the elasticity of the string decreased from 0.529 to 0.447 for diameters ranging from 0.62 to 0.70 mm. Subsequently, a badminton racquet and shuttlecock were modeled using SolidWorks2018® software (version 26), and a maximum displacement was applied to the ball to simulate an impact on the string bed. The natural frequency, maximum deformation and maximum stress were calculated analytically, and a finite element analysis was also performed using ANSYS2022 R2® software (version 22.2). The analytical and numerical results from ANSYS® showed good agreement (within 5% accuracy). The results of the study show that the natural frequency of a racquet with Kevlar strings was significantly higher than that of racquets with synthetic gut, natural gut, or polyester string materials. Specifically, the natural frequency of a racquet made of carbon graphite and epoxy resin was 23.0%, 30.7%, and 36.2% higher than that of racquets with synthetic gut, natural gut, and polyester string material, respectively. On the basis of this finding, Kevlar was chosen as the preferred material for badminton racquets strings, and a parametric analysis was then conducted. The study showed that slightly lowering the tension of the off-centered strings had a minimal effect on the von Mises stress distribution of the ball and string bed. In addition to investigating string materials, this study also examined the effects of pull and diameter variations of racquet strings on vibrations during impact. This study contributes to the understanding of the role of racquet and strings in badminton, and it also provides new insights into the factors that can affect performance in the sport. By analyzing the performance of different string materials and examining the effects of pull and diameter variations of racquet strings, this study provides valuable information for players and manufacturers looking to optimize their equipment for maximum performance.

Effect of Additional Mass on Natural Frequencies of Weight-Sensing Structures.

The phenomena of variability and interference in the natural frequencies of weight-sensing structures applied in complex working conditions must solve the problem of reducing or eliminating resonance under low-frequency vibrations to maximize stability, accuracy and reliability. The influence laws of the additional mass with relevant characteristics on the natural frequencies, which include the components of mass, stiffness and center-of-mass distribution, etc. Firstly, the theoretical formulas of the mathematical model are given based on different characteristics of the weight-sensing structure, and various combinations of additional masses on the weight-sensing structures are adjusted in the X-, Y-, and Z-directions. The key factors to be specifically considered in the theoretical formulas are discussed through simulation analysis and experimental validation. Secondly, the locking strength of the fastening screws of some components was changed, and another component was placed on the experimental platform in the experiment. The results show that the mass, center-of-mass, stiffness distribution and other factors of the additional mass have different effects on the natural frequencies, which are important for the demand for high-precision, high-stability weighing measurement. The results of this research can provide an effective scientific evaluation basis for the reliable prediction of natural frequencies.

A Neural Network Approach to Estimate the Frequency of a Cantilever Beam with Random Multiple Damages.

Natural frequency is an important parameter in the structural health monitoring (SHM) system. Any changes in this parameter indicate structural alteration due to damage. This study provides a neural network (NN) solution as an alternative to the finite element (FE) method to measure the natural frequencies of a cantilever beam with random multiple damage. It is based on a statistical dataset of a free vibration test obtained from the APDL (Ansys parametric design language) simulation using a MATLAB (matrix laboratory) script. The script can generate an unlimited number of possible damage combinations for any given parameters with the help of the Monte Carlo (MC) technique. MC helps to generate a random number of damages in random locations at each simulation. Damage conditions are controlled by three parameters including damage severity and damage size (in terms of the mean and standard deviation of damage). Moreover, the method proposes a curve-fitting equation to validate the predicted natural frequency for the first three modes obtained from the neural network model. Both methods are in good agreement with each other, having minimal errors in the range of 0.2-3% for each mode. The frequency result shows that the beam frequency is 8.6486 Hz if the area reduction is 10%, whereas it comes down to 7.2338 Hz if there is a 30% area reduction. A two-level factorial test shows that damage severity is the most impactful factor compared to the damage sizes on the frequency shift event. This indicates that damage alters the composition of the beam and has an impact on its frequency change with the assumed damage parameters. Therefore, the proposed NN model can estimate the frequency shift for various damage scenarios. It can be utilized in the vibration-based damage identification process to predict the frequency changes of the damaged beam without any computational burden.

Experimental Study of Bridge Expansion Joint Damage Based on Natural Frequency.

In this paper, three studies on modal bridge expansion joints were conducted through experiments. The advantages and disadvantages of acceleration and fiber optic strain sensors in the tested modal expansion joints were compared. Secondly, the variation in the natural frequency of the modal bridge expansion joints at different concrete curing periods was investigated. Finally, the effect of damage on natural frequency in different parts (the center beam, the support bar, and concrete in the anchorage zone) of the modal bridge expansion joint was analyzed. For this purpose, three specimens were cast, each with six damage states. Manual methods damaged the specimens. An impact hammer was used to excite the corresponding parts of the different components. The results showed that the acceleration sensor is optimal for the modal bridge expansion joint test. The specimen's natural frequency increased with the curing time's growth. The natural frequency increased by 10 Hz from day 3 to day 28 of curing. With the gradual increase in damage, the natural frequencies of the center beam and support bar showed a gradual decreasing trend. The damage to the concrete in the anchorage zone caused less significant changes in the natural frequency, but the overall natural frequency still had a decreasing trend. The sensitivity of each frequency to the damage was different in different parts.

Field Measurements of Wind-Induced Responses of the Shanghai World Financial Center during Super Typhoon Lekima.

In this paper, the wind-induced responses of the Shanghai World Financial Center (SWFC) under Super Typhoon Lekima are measured using the health monitoring system. Based on the measurements, the characteristics of vibration, including probability density distribution of accelerations, power spectra, and mode shapes are studied. The curve method and the standard deviation method are used to analyze the relationship of the first- and second-order natural frequencies and damping ratios with amplitudes and the mean wind speed. The results show the following: (1) The structural wind-induced responses in the X and Y directions have high consistencies, and the vibration signals exhibit a peak state; moreover, response amplitudes and acceleration signals disperse when the floor height increases. (2) The first- and second-order natural frequencies in the X and Y directions decrease with the increasing amplitudes and are negatively correlated with mean wind speed; the maximum decrease in natural frequency is 5.794%. The first- and second-order damping ratios in the X and Y directions increase with the increasing amplitudes and are positively correlated with the mean wind speed; the maximum increase in damping ratio is 95.7%. (3) The curve method and the standard deviation method are similar in identifying dynamic characteristic parameters, but the discreteness of the natural frequencies obtained by the curve method is lesser. (4) Under excitations of various typhoons, the mode shapes of SWFC are basically the same, and the mode shapes in the X and Y directions increase with the height and have nonlinearity.

Damage Identification of Semi-Rigid Joints in Frame Structures Based on Additional Virtual Mass Method.

In civil engineering, the joints of structures are complex, and their damage is generally hard to be detected. Due to the insensitivity of structural modal information to local joint damage, this paper presents a method based on additional virtual mass for damage identification of a semi-rigid joint in a frame structure. Firstly, the modeling of a semi-rigid is described. Secondly, the frequency response of the virtual structure is constructed, and the natural frequency of the constructed virtual structure is extracted by the ERA method. By adding multiple values of virtual masses at different positions, the natural frequency information sensitive to joint damage for damage identification is effectively increased. Based on the above theory, qualitative identification of joint damage is proposed to detect the potential damage, and identification of both damage location and its extent is presented, using natural frequency. Improved Orthogonal Matching Pursuit (IOMP) algorithm is employed to improve the accuracy of the natural frequency-based method for damage identification. At last, numerical simulation of a three-story frame is performed to discuss and to verify the effectiveness of the proposed method.

Indirect Monitoring of Frequencies of a Multiple Span Bridge Using Data Collected from an Instrumented Train: A Field Case Study.

In this paper, a field study is carried out to monitor the natural frequencies of Malahide viaduct bridge which is located in the north of Dublin. The bridge includes a series of simply supported spans, two of which collapsed in 2009 and were replaced. The replaced spans are stiffer than most of the others and these differences resulted in higher natural frequencies. An indirect bridge monitoring approach is employed in which acceleration responses from an instrumented train are used to estimate the natural frequencies of each span of the viaduct showing the locations of the two replaced spans with higher stiffness. For the indirect approach, an Ensemble Empirical Mode Decomposition (EEMD)-based Hilbert Huang Transform (HHT) technique is employed to identify the natural frequency of each span. This is carried out by analysing the Instantaneous Frequencies (IFs) from the calculated intrinsic mode functions. The average of the IFs calculated using 41 runs of the instrumented train (with varying carriage mass and speed for each run) are used to estimate the natural frequencies. To assess the feasibility of the indirect approach, a bespoke set of direct measurements was taken using accelerometers attached successively on each span of the viaduct. The free and forced vibrations from each span are used to estimate the first natural frequencies. The frequencies obtained from drive-by measurements are compared to those from direct measurements which confirms the effectiveness of indirect approaches. In addition, the instantaneous amplitudes of the drive-by signals are used to indicate the location of the stiffer spans. Finally, the accuracy and robustness of the indirect approaches for monitoring of multi span bridges are discussed.

Beam Damage Assessment Using Natural Frequency Shift and Machine Learning.

Damage detection based on modal parameter changes has become popular in the last few decades. Nowadays, there are robust and reliable mathematical relations available to predict natural frequency changes if damage parameters are known. Using these relations, it is possible to create databases containing a large variety of damage scenarios. Damage can be thus assessed by applying an inverse method. The problem is the complexity of the database, especially for structures with more cracks. In this paper, we propose two machine learning methods, namely the random forest (RF), and the artificial neural network (ANN), as search tools. The databases we developed contain damage scenarios for a prismatic cantilever beam with one crack and ideal and non-ideal boundary conditions. The crack assessment was made in two steps. First, a coarse damage location was found from the networks trained for scenarios comprising the whole beam. Afterwards, the assessment was made involving a particular network trained for the segment of the beam on which the crack was previously found. Using the two machine learning methods, we succeeded in estimating the crack location and severity with high accuracy for both simulation and laboratory experiments. Regarding the location of the crack, which was the main goal of the practitioners, the errors were less than 0.6%. Based on these achievements, we concluded that the damage assessment we propose, in conjunction with the machine learning methods, is robust and reliable.

A Bayesian Approach to Predict Blast-Induced Damage of High Rock Slope Using Vibration and Sonic Data.

The blast-induced damage of a high rock slope is directly related to construction safety and the operation performance of the slope. Approaches currently used to measure and predict the blast-induced damage are time-consuming and costly. A Bayesian approach was proposed to predict the blast-induced damage of high rock slopes using vibration and sonic data. The relationship between the blast-induced damage and the natural frequency of the rock mass was firstly developed. Based on the developed relationship, specific procedures of the Bayesian approach were then illustrated. Finally, the proposed approach was used to predict the blast-induced damage of the rock slope at the Baihetan Hydropower Station. The results showed that the damage depth representing the blast-induced damage is proportional to the change in the natural frequency. The first step of the approach is establishing a predictive model by undertaking Bayesian linear regression, and the second step is predicting the damage depth for the next bench blasting by inputting the change rate in the natural frequency into the predictive model. Probabilities of predicted results being below corresponding observations are all above 0.85. The approach can make the best of observations and includes uncertainty in predicted results.

Vibration Monitoring of Civil Engineering Structures Using Contactless Vision-Based Low-Cost IATS Prototype.

The role and importance of geodesists in the planning and building of civil engineering constructions are well known. However, the importance and benefits of collected data during maintenance in exploitation have arisen in the last thirty years due primarily to the development of Global Positioning Systems (GPS) and Global Navigation Satellite System (GNSS) instruments, sensors and systems, which can receive signals from multiple GPS systems. In the last fifteen years, the development of Terrestrial Laser Scanners (TLS) and Image-Assisted Total Stations (IATS) has enabled much wider integration of these types of geodetic instruments with their sensors into monitoring systems for the displacement and deformation monitoring of structures, as well as for regular structure inspections. While GNSS sensors have certain limitations regarding their accuracy, their suitability in monitoring systems, and the need for a clean horizon, IATS do not have these limitations. The latest development of Total Stations (TS) called IATS is a theodolite that consists of a Robotic Total Station (RTS) with integrated image sensors. Today, IATS can be used for structural and geo-monitoring, i.e., for the determination of static and dynamic displacements and deformations, as well as for the determination of civil engineering structures' natural frequencies. In this way, IATS can provide essential information about the current condition of structures. However, like all instruments and sensors, they have their advantages and disadvantages. IATS's biggest advantage is their high level of accuracy and precision and the fact that they do not need to be set up on the structure, while their biggest disadvantage is that they are expensive. In this paper, the developed low-cost IATS prototype, which consists of an RTS Leica TPS1201 instrument and GoPro Hero5 camera, is presented. At first, the IATS prototype was tested in the laboratory where simulated dynamic displacements were determined. After the experiment, the IATS prototype was used in the field for the purpose of static and dynamic load testing of the railway bridge Klostar, after its reconstruction according to HRN ISO NORM U.M1.046-Testing of bridges by load test. In this article, the determination of bridge dynamic displacements and results of the computation of natural frequencies using FFT from the measurement data obtained by means of IATS are presented. During the load testing of the bridge, the frequencies were also determined by accelerometers, and these data were used as a reference for the assessment of IATS accuracy and suitability for dynamic testing. From the conducted measurements, we successfully determined natural bridge frequencies as they match the results gained by accelerometers.

Natural Frequency Response Evaluation for RC Beams Affected by Steel Corrosion Using Acceleration Sensors.

This paper presented a laboratory investigation for analyzing the natural frequency response of reinforced concrete (RC) beams affected by steel corrosion. The electrochemical acceleration technique induced the corroded RC beams until the predetermined value of the steel corrosion ratio was achieved. Then, the natural frequency responses of the corroded beams were tested utilizing piezoelectric acceleration sensors. The damage states of the corroded beams were assessed through the measurement of crack parameters and the equivalent elastic modulus of the beams, which aims to clarify the fundamental characteristics of the dynamic response for the corroded RC beam with the increased steel corrosion ratio. The results revealed that steel corrosion reduces the bending stiffness of the RC beams and, thus, reduces the modal frequency. The variation of natural frequency can identify the corrosion damage even if no surface cracking of the RC beam, and the second-order frequency should be more indicative of the damage scenario. The degradations of stiffness and the natural frequency were estimated in this study by the free vibration equation of a simply supported beam, and a prediction method for the RC beam's residual service life was established. This study supports the use of variations in natural frequency as one diagnostic indicator to evaluate the health of RC bridge structures.

Why the natural frequency and the damping coefficient do not evaluate the dynamic response of clinically used pressure monitoring circuits correctly.

PURPOSE: The dynamic response of pressure monitoring circuits must be evaluated to obtain true invasive blood pressure values. Since Gardner's recommendations in 1981, the natural frequency and the damping coefficient have become standard parameters for anesthesiologists. In 2006, we published a new dynamic response evaluation method (step response analysis) that can plot frequency spectrum curves instantly in clinical situations. We also described the possibility of the defect of the standard parameters. However, the natural frequency and the damping coefficient are considered the gold standard and are even included in a major anesthesiology textbook. Therefore, we attempted to clarify the issues of these parameters with easy-to-understand pressure waves and basic numerical formulae. METHODS: A blood pressure wave calibrator, a single two-channel pressure amplifier, and personal computer were used to analyze blood pressure monitoring circuits. All data collection and analytical processes were performed using our step response analysis program. RESULTS: We compared two different circuits with almost the same natural frequency and damping coefficients. However, their amplitude spectrum curves and input/output pressure values were significantly different. CONCLUSIONS: The natural frequency and the damping coefficient are inadequate for the dynamic response evaluation. These parameters are primarily obtained from the phase spectrum curve and not from the amplitude spectrum curve. We strongly recommend an evaluation using the amplitude spectrum curve with our step response analysis method. It is crucial to maintain an amplitude gain of 1 (input amplitude = output amplitude) in the pressure wave frequency range of 0-20 Hz.

Dynamic Response of Elastomer-Based Liquid-Filled Variable Focus Lens.

Variable focus lenses are capable of dynamically varying their focal lengths. The focal length is varied by adjusting the curvature of the refractive surface and the media on both sides of the lens. The dynamic response is one of the most important criteria to determine the performance of variable focus lens. In this work, we investigated critical factors that affect the dynamic response of liquid-filled variable focus lens with a large aperture size. Based on a theoretical analysis of a circular disk representative of a deformable surface, we found that the dynamic response is significantly influenced by the diameter, thickness, and stiffness of the disk because these factors determine its first natural frequency. We also studied the dynamic response of elastomer-based liquid-filled variable focus lens prototype with different aperture sizes (20 and 30 mm) by using experiments and we found that the lens with the smaller aperture size had an excellent dynamic response.

Detection of Broken Strands of Transmission Line Conductors Using Fiber Bragg Grating Sensors.

Transmission lines are affected by Aeolian vibration, which causes strands to break and eventually causes an entire line to break. In this paper, a method for monitoring strand breaking based on modal identification is proposed. First, the natural frequency variation of a conductor caused by strand breakage is analyzed, and a modal experiment of the LGJ-95/15 conductor is conducted. The measurement results show that the natural frequencies of the conductor decrease with an increasing number of broken strands. Next, a monitoring system incorporating a fiber Bragg grating (FBG)-based accelerometer is designed in detail. The FBG sensor is mounted on the conductor to measure the vibration signal. A wind speed sensor is used to measure the wind speed signal and is installed on the tower. An analyzer is also installed on the tower to calculate the natural frequencies, and the data are sent to the monitoring center via 3G. Finally, a monitoring system is tested on a 110 kV experimental transmission line, and the short-time Fourier transform (STFT) method and stochastic subspace identification (SSI) method are used to identify the natural frequencies of the conductor vibration. The experimental results show that SSI analysis provides a higher precision than does STFT and can extract the natural frequency under various wind speeds as an effective basis for discriminating between broken strands.

Influence of the marvelous™ three-way stopcock on the natural frequency and damping coefficient in blood pressure transducer kits.

Two types of Planecta™ ports are commonly used as sampling ports in blood pressure transducer kits: a flat-type port (FTP) and a port with a three-way stopcock (PTS). Recently, a new type of three-way stopcock (Marvelous™) has been released as a Planecta™ counterpart, but its effects on the frequency characteristics and reliability of blood pressure monitoring have not been investigated. We assessed the influence of the Marvelous™ stopcock on the frequency characteristics of the pressure transducer kit. The basic pressure transducer kit, DT4812J, was modified by replacing one or two of the original three-way stopcocks with Marvelous™ stopcocks. The frequency characteristics (i.e., natural frequency and damping coefficient) of each kit were determined using wave parameter analysis software, and subsequently evaluated on a Gardner chart. Replacement of the original blood pressure transducer kit stopcocks with Marvelous™ stopcocks decreased the natural frequency (48.3 Hz) to 46.3 Hz or 44.8 Hz, respectively; the damping coefficient was not significantly changed. Plotting the data on a Gardner chart revealed that the changes fell within the adequate dynamic response region, indicating they were within the allowable range. Insertion of Marvelous™ stopcocks slightly affects the natural frequency of the pressure transducer kit, similar to inserting a PTS. The results indicate that the Marvelous™ stopcock is useful for accurate monitoring of arterial blood pressure, and may be recommended when insertion of two or more closed-loop blood sampling systems is necessary.

Vibration Measurement Method of a String in Transversal Motion by Using a PSD.

A position sensitive detector (PSD) is frequently used for the measurement of a one-dimensional position along a line or a two-dimensional position on a plane, but is more often used for measuring static or quasi-static positions. Along with its quick response when measuring short time-spans in the micro-second realm, a PSD is also capable of detecting the dynamic positions of moving objects. In this paper, theoretical modeling and experiments are conducted to explore the frequency characteristics of a vibrating string while moving transversely across a one-dimensional PSD. The theoretical predictions are supported by the experiments. When the string vibrates at its natural frequency while moving transversely, the PSD will detect two frequencies near this natural frequency; one frequency is higher than the natural frequency and the other is lower. Deviations in these two frequencies, which differ from the string's natural frequency, increase while the speed of motion increases.