Modeling the Electrical Activity of the Heart via Transfer Functions and Genetic Algorithms

Although healthcare and medical technology have advanced significantly over the past few decades, heart disease continues to be a major cause of mortality globally. Electrocardiography (ECG) is one of the most widely used tools for the detection of heart diseases. This study presents a mathematical model based on transfer functions that allows for the exploration and optimization of heart dynamics in Laplace space using a genetic algorithm (GA). The transfer function parameters were fine-tuned using the GA, with clinical ECG records serving as reference signals. The proposed model, which is based on polynomials and delays, approximates a real ECG with a root-mean-square error of 4.7% and an R2 value of 0.72. The model achieves the periodic nature of an ECG signal by using a single periodic impulse input. Its simplicity makes it possible to adjust waveform parameters with a predetermined understanding of their effects, which can be used to generate both arrhythmic patterns and healthy signals. This is a notable advantage over other models that are burdened by a large number of differential equations and many parameters.

Short-term dynamic characteristics of diuresis during exogenous pressure perturbations with and without arterial baroreflex control

Although body fluid volume control by the kidneys may be classified as a long-term arterial pressure (AP) control system, it does not necessarily follow that the urine flow (UF) response to changes in AP is slow. We quantified the dynamic characteristics of the UF response to short-term AP changes by changing mean AP between 60 mmHg and 100 mmHg every 10 s according to a binary white noise sequence in anesthetized rats (n = 8 animals). In a baro-on trial (the carotid sinus baroreflex was enabled), the UF response represented the combined synergistic effects of pressure diuresis (PD) and neurally mediated antidiuresis (NMA). In a baro-fix trial (the carotid sinus pressure was fixed at 100 mmHg), the UF response mainly reflected the effect of PD. The UF step response was quantified using the sum of two exponential decay functions. The fast and slow components had time constants of 6.5 ± 3.6 s and 102 ± 85 s (means ± SD), respectively, in the baro-on trial. Although the gain of the fast component did not differ between the two trials (0.49 ± 0.21 vs. 0.66 ± 0.22 µL·min-1·kg-1·mmHg-1), the gain of the slow component was greater in the baro-on than in the baro-fix trial (0.51 ± 0.14 vs. 0.09 ± 0.39 µL·min-1·kg-1·mmHg-1, P = 0.023). The magnitude of NMA relative to PD was calculated to be 32.2 ± 29.8%. In conclusion, NMA contributed to the slow component, and its magnitude was approximately one-third of that of the effect of PD.NEW & NOTEWORTHY We quantified short-term dynamic characteristics of the urine flow (UF) response to arterial pressure (AP) changes using white noise analysis. The UF step response approximated the sum of two exponential decay functions with time constants of ∼6.5 s and 102 s. The neurally mediated antidiuretic (NMA) effect contributed to the slow component of the UF step response, with the magnitude of approximately one-third of that of the pressure diuresis (PD) effect.

Quantitative structure-property relationship modelling for predicting retention indices of essential oils based on an improved horse herd optimization algorithm

The horse herd optimization algorithm (HOA), one of the more contemporary metaheuristic algorithms, has demonstrated superior performance in a number of challenging optimization tasks. In the present work, the descriptor selection issue is resolved by classifying different essential oil retention indices using the binary form, BHOA. Based on internal and external prediction criteria, Z-shape transfer functions (ZTF) were tested to verify their efficiency in improving BHOA performance in QSPR modelling for predicting retention indices of essential oils. The evaluation criteria involved the mean-squared error of the training and testing datasets (MSE), and leave-one-out internal and external validation (Q2). The degree of convergence of the proposed Z-shaped transfer functions was compared. In addition, K-fold cross validation with k = 5 was applied. The results show that ZTF, especially ZTF1, greatly improves the performance of the original BHOA. Comparatively speaking, ZTF, especially ZTF1, exhibits the fastest convergence behaviour of the binary algorithms. It chooses the fewest descriptors and requires the fewest iterations to achieve excellent prediction performance.

Digital Prediction of the Purchase Price of Fresh Tea Leaves of Enshi Yulu Based on Near-Infrared Spectroscopy Combined with Multivariate Analysis

In this study, near-infrared spectroscopy (NIRS) combined with a variety of chemometrics methods was used to establish a fast and non-destructive prediction model for the purchase price of fresh tea leaves. Firstly, a paired t-test was conducted on the quality index (QI) of seven quality grade fresh tea samples, all of which showed statistical significance (p < 0.05). Further, there was a good linear relationship between the QI, quality grades, and purchase price of fresh tea samples, with the determination coefficient being greater than 0.99. Then, the original near-infrared spectra of fresh tea samples were obtained and preprocessed, with the combination (standard normal variable (SNV) + second derivative (SD)) as the optimal preprocessing method. Four spectral intervals closely related to fresh tea prices were screened using the synergy interval partial least squares (si-PLS), namely 4377.62 cm-1-4751.74 cm-1, 4755.63 cm-1-5129.75 cm-1, 6262.70 cm-1-6633.93 cm-1, and 7386 cm-1-7756.32 cm-1, respectively. The genetic algorithm (GA) was applied to accurately extract 70 and 33 feature spectral data points from the whole denoised spectral data (DSD) and the four characteristic spectral intervals data (FSD), respectively. Principal component analysis (PCA) was applied, respectively, on the data points selected, and the cumulative contribution rates of the first three PCs were 99.856% and 99.852%. Finally, the back propagation artificial neural (BP-ANN) model with a 3-5-1 structure was calibrated with the first three PCs. When the transfer function was logistic, the best results were obtained (Rp2 = 0.985, RMSEP = 6.732 RMB/kg) by 33 feature spectral data points. The detection effect of the best BP-ANN model by 14 external samples were R2 = 0.987 and RMSEP = 6.670 RMB/kg. The results of this study have achieved real-time, non-destructive, and accurate evaluation and digital display of purchase prices of fresh tea samples by using NIRS technology.

A machine learning-based approach for RF transfer function modeling of active implantable medical electrodes at 3T MRI

Objective.The objective of this work is to propose a machine learning-based approach to rapidly and efficiently model the radiofrequency (RF) transfer function of active implantable medical (AIM) electrodes, and to overcome the limitations and drawbacks of traditional measurement methods when applied to heterogeneous tissue environments.Approach.AIM electrodes with different geometries and proximate tissue distributions were considered, and their RF transfer functions were modeled numerically. Machine learning algorithms were developed and trained with the simulated transfer function datasets for homogeneous and heterogeneous tissue distributions. The performance of the method was analyzed statistically and validated experimentally and numerically. A comprehensive uncertainty analysis was performed and uncertainty budgets were derived.Main results.The proposed method is able to predict the RF transfer function of AIM electrodes under different tissue distributions, with mean correlation coefficientsrof 0.99 and 0.98 for homogeneous and heterogeneous environments, respectively. The results were successfully validated by experimental measurements (e.g. the uncertainty of less than 0.9 dB) and numerical simulation (e.g. transfer function uncertainty <1.6 dB and power deposition uncertainty <1.9 dB). Up to 1.3 dBin vivopower deposition underestimation was observed near generic pacemakers when using a simplified homogeneous tissue model.Significance.Provide an efficient alternative of transfer function modeling, which allows a more realistic tissue distribution and the potential underestimation ofin vivoRF-induced power deposition near the AIM electrode can be reduced.

Characterization of a New Silk Sericin-Based Hydrogel for Water Retention in Soil

Hydrogel-type absorbent materials are currently a technological alternative for improving water retention in the soil and reducing nutrient loss by leaching and evaporation. This study aimed to evaluate the application of a new hydrogel based on silk sericin (SS) as a water retention material in soil. The morphology of the hydrogel was characterized using Scanning Electron Microscopy (SEM), and its impact on moisture retention in sandy loam soil (SLS) under different levels of matric pressure (MP) was evaluated. Additionally, water content data were collected over time for both SLS and SLS with hydrogel (SLS + H), and the data were used to fit predictive models. The results indicate that the hydrogel had a porous morphology that promoted water retention and soil release. Under a MP of 0.3 bar, the use of the hydrogel increased water retention by 44.70% with respect to that of SLS. The predictive models developed were adequately adjusted to the behavior of the moisture data over time and evidenced the incidence of the absorbent material on the dynamics of the moisture content in the soil. Therefore, these models could be useful for facilitating subsequent simulations or for designing automatic soil moisture control systems oriented to smart farming.

Toward Improvements in Pressure Measurements for Near Free-Field Blast Experiments

This paper proposes two ways to improve pressure measurement in air-blast experimentations, mostly for close-in detonations defined by a small-scaled distance below 0.4 m.kg^-1/3. Firstly, a new kind of custom-made pressure probe sensor is presented. The transducer is a piezoelectric commercial, but the tip material has been modified. The dynamic response of this prototype is established in terms of time and frequency responses, both in a laboratory environment, on a shock tube, and in free-field experiments. The experimental results show that the modified probe can meet the measurement requirements of high-frequency pressure signals. Secondly, this paper presents the initial results of a deconvolution method, using the pencil probe transfer function determination with a shock tube. We demonstrate the method on experimental results and draw conclusions and prospects.

Hybrid Analog Computer for Modeling Nonlinear Dynamical Systems: The Complete Cookbook

This paper describes a design process for a universal development kit based on an analog computer concept that can model the dynamics of an arbitrarily complex dynamical system up to the fourth order. The constructed development kit contains digital blocks and associated analog-to-digital and digital-to-analog converters (ADCs and DAC), such that multiple-segmented piecewise-linear input-output characteristics can be used for the synthesis of the prescribed mathematical model. Polynomial input-output curves can be implemented easily by four-quadrant analog multipliers. The proposed kit was verified through several experimental scenarios, starting with simple sinusoidal oscillators and ending with generators of continuous-time robust chaotic attractors. The description of each individual part of the development kit is accompanied by links to technical documentation, allowing skilled readers in the construction of electronic systems to replicate the proposed functional example. For this purpose, the electrical scheme of the hybrid analog computer and all important source codes are available online.

Calculation of Deformation-Related Quantities in a Hot-Rolling Process

The hot deformation of metal as a nonlinear system is mathematically described by a local linear model associated with the working conditions using a transfer function (TF) in the Laplace domain. Experimental data (true stress vs. true strain curves) are obtained using the established compressive uniaxial deformation test, where experimental conditions (strain rate and temperature) define the working conditions of the local linear TF model, which is intrinsically a function of strain. Based on the TF model, three important physical quantities of the tested metal are determined exactly: the work done per unit deformation, the average flow stress, and the flow-stress derivative with respect to the strain based on a particular TF. The exactly determined quantities, determined as a function of strain, can replace the previously used approximations in some rolling force and torque calculations.

An Approach of Vibration Compensation for Atomic Gravimeter under Complex Vibration Environment

Atomic gravimeter has been more frequently applied under complex and dynamic environments, but its measurement accuracy is seriously hampered by vibration-induced noise. In this case, vibration compensation provides a way to enhance the accuracy of gravity measurements by correcting the phase noise that resulted from the vibration of a Raman reflector, and improving the fitting of an interference fringe. An accurate estimation of the transfer function of vibration between the Raman reflector and the sensor plays a significant role in optimizing the effect of vibration compensation. For this reason, a vibration compensation approach was explored based on EO (equilibrium optimizer) for estimating the transfer function simplified model of a Raman reflector, and it was used to correct the interference fringe of an atomic gravimeter. The test results revealed that this approach greatly restored the actual vibration of the Raman reflector in a complex vibration environment. With a vibration compensation algorithm, it achieved the correction and fitting of the original interference fringe. In general, it dramatically reduced the RMSE (root mean square error) at the time of fitting and significantly improved the residual error in the gravity measurement. Compared with other conventional algorithms, such as GA (genetic algorithm) and PSO (particle swarm optimization), this approach realized a faster convergence and better optimization, so as to ensure more accurate gravity measurements. The study of this vibration compensation approach could provide a reference for the application of an atomic gravimeter in a wider and more complex environment.

Transfer function approach to understanding periodic forcing of signal transduction networks

Signal transduction networks are responsible for transferring information from the extracellular to the intracellular environment. This process facilitates biochemical changes in the cell which, in turn, dictates physiological changes such as differentiation and growth. Information can be stored in a variety of physical modes, including signal frequency. Different signal frequencies impart different information onto the cell surface, driving different physiological outcomes via signal transduction networks. Frequency-dependent cell behaviour is well documented in experimental literature. Understanding this frequency dependence allows us to control cells, opening avenues into therapeutics and bridges between theory and experiment. The transfer function provides one approach to understanding this. In this tutorial, we show how to obtain the transfer function of an arbitrary signal transduction network and use it to explain how the network responds to periodic forcing. We discuss advantages and limitations to this method.

Electrochemical Impedance Spectroscopy—A Tutorial

This tutorial provides the theoretical background, the principles, and applications of Electrochemical Impedance Spectroscopy (EIS) in various research and technological sectors. The text has been organized in 17 sections starting with basic knowledge on sinusoidal signals, complex numbers, phasor notation, and transfer functions, continuing with the definition of impedance in electrical circuits, the principles of EIS, the validation of the experimental data, their simulation to equivalent electrical circuits, and ending with practical considerations and selected examples on the utility of EIS to corrosion, energy related applications, and biosensing. A user interactive excel file showing the Nyquist and Bode plots of some model circuits is provided in the Supporting Information. This tutorial aspires to provide the essential background to graduate students working on EIS, as well as to endow the knowledge of senior researchers on various fields where EIS is involved. We also believe that the content of this tutorial will be a useful educational tool for EIS instructors.

Spatial analysis of acoustic noise transfer function with a human-body phantom in a clinical MRI scanner

BACKGROUND

The acoustic noise in magnetic resonance imaging (MRI) potentially depends on the measurement position and presence of a patient inside the scanner bore.

PURPOSE

To analyze the spatial characteristics of the acoustic noise by using the gradient-pulse-to-acoustic-noise transfer function (GPAN-TF) with and without a human-body phantom on the examination table.

MATERIAL AND METHODS

Acoustic noise waveforms were acquired at 80 and 110 measurement positions with and without a phantom. The GPAN-TFs µPa/(mT/m) in the coils were calculated by deconvolution. The phantom effect on the spatial distribution of the acoustic noise was assessed using the peak sound pressure levels (SPLs), mean values, peak values, and peak frequencies of the GPAN-TFs.

RESULTS

The peak SPLs in all positions for the X-, Y-, and Z-gradient coils were increased by 11.1 dB, 1.4 dB, and 6.1 dB, respectively, compared with the peak SPL of the magnetic isocenter. The maximum peak SPLs among all positions of the X-, Y-, and Z-gradient coils with the phantom were increased by 4.9 dB, 7.4 dB, and 6.9 dB, respectively, relative to those without the phantom. However, the peak SPLs decreased at some positions with the phantom placed on the table (X-gradient coil = 4.6 dB, Y-gradient coil = 5.0 dB, Z-gradient coil = 8.4 dB). The most common peak frequencies were in the range of 2000-3000 Hz.

CONCLUSION

"Hotspot" areas with and without the phantom were associated with acoustic noise sources in the clinical MRI scanner and were enhanced by the phantom's presence.

Performance-Enhanced Static Modulated Fourier Transform Spectrometer with a Spectral Reconstruction

A static modulated Fourier transform spectrometer has been noted to be a compact and fast evaluation tool for spectroscopic inspection, and many novel structures have been reported to support its performance. However, it still suffers from poor spectral resolution due to the limited sampling data points, which marks its intrinsic drawback. In this paper, we outline the enhanced performance of a static modulated Fourier transform spectrometer with a spectral reconstruction method that can compensate for the insufficient data points. An enhanced spectrum can be reconstructed by applying a linear regression method to a measured interferogram. We obtain the transfer function of a spectrometer by analyzing what interferogram can be detected with different values of parameters such as focal length of the Fourier lens, mirror displacement, and wavenumber range, instead of direct measurement of the transfer function. Additionally, the optimal experimental conditions for the narrowest spectral width are investigated. Application of the spectral reconstruction method achieves an improved spectral resolution from 74 cm^-1 when spectral reconstruction is not applied to 8.9 cm^-1, and a narrowed spectral width from 414 cm^-1 to 371 cm^-1, which are close to the values of the spectral reference. In conclusion, the spectral reconstruction method in a compact static modulated Fourier transform spectrometer effectively enhances its performance without any additional optic in the structure.

Binary Bamboo Forest Growth Optimization Algorithm for Feature Selection Problem

Inspired by the bamboo growth process, Chu et al. proposed the Bamboo Forest Growth Optimization (BFGO) algorithm. It incorporates bamboo whip extension and bamboo shoot growth into the optimization process. It can be applied very well to classical engineering problems. However, binary values can only take 0 or 1, and for some binary optimization problems, the standard BFGO is not applicable. This paper firstly proposes a binary version of BFGO, called BBFGO. By analyzing the search space of BFGO under binary conditions, the new curve V-shaped and Taper-shaped transfer function for converting continuous values into binary BFGO is proposed for the first time. A long-mutation strategy with a new mutation approach is presented to solve the algorithmic stagnation problem. Binary BFGO and the long-mutation strategy with a new mutation are tested on 23 benchmark test functions. The experimental results show that binary BFGO achieves better results in solving the optimal values and convergence speed, and the variation strategy can significantly enhance the algorithm's performance. In terms of application, 12 data sets derived from the UCI machine learning repository are selected for feature-selection implementation and compared with the transfer functions used by BGWO-a, BPSO-TVMS and BQUATRE, which demonstrates binary BFGO algorithm's potential to explore the attribute space and choose the most significant features for classification issues.

Dynamic accentuated antagonism of heart rate control during different levels of vagal nerve stimulation intensity in rats

Accentuated antagonism refers to a phenomenon in which the vagal effect on heart rate (HR) is augmented by background sympathetic tone. The dynamic aspect of accentuated antagonism remains to be elucidated during different levels of vagal nerve stimulation (VNS) intensity. We performed VNS on anesthetized rats (n = 8) according to a binary white noise signal with a switching interval of 500 ms at three different stimulation rates (low-intensity: 0-10 Hz, moderate-intensity: 0-20 Hz, and high-intensity: 0-40 Hz). The transfer function from VNS to HR was estimated with and without concomitant tonic sympathetic nerve stimulation (SNS) at 5 Hz. The asymptotic low-frequency (LF) gain (in beats/min/Hz) of the transfer function increased with SNS regardless of the VNS rate [low-intensity: 3.93 ± 0.70 vs. 5.82 ± 0.65 (P = 0.021), moderate-intensity: 3.87 ± 0.62 vs. 5.36 ± 0.53 (P = 0.018), high-intensity: 4.77 ± 0.85 vs. 7.39 ± 1.36 (P = 0.011)]. Moreover, SNS slightly increased the ratio of high-frequency (HF) gain to the LF gain. These effects of SNS were canceled by the pretreatment of ivabradine, an inhibitor of hyperpolarization-activated cyclic nucleotide-gated channels, in another group of rats (n = 6). Although background sympathetic tone antagonizes the vagal effect on mean HR, it enables finer HR control by increasing the dynamic gain of the vagal HR transfer function regardless of VNS intensity. When interpreting the HF component of HR variability, the augmenting effect from background sympathetic tone needs to be considered.

Analysis of the Underwater Radiated Noise Generated by Hull Vibrations of the Ships

Shipping traffic is recognised as the main man-noise source of the anthropogenic noise generated in the marine environment. The underwater acoustic pollution is increased due to the increment of the human activity at seas supposing a threat for marine habitats. The ship as acoustic source must be understood and controlled to manage the maritime areas both in time and space to reduce the impact of noise in marine fauna. Shipping noise is mainly composed of flow noise, propeller noise and machinery noise. This research is focused on the analysis and estimation of the underwater radiated noise generated by the vibrations of the onboard machinery or structure-borne noise based on the calculation of the transfer function. This function relates the acceleration levels of the vibrations of the hull's panels and the radiated noise by them using the radiation efficiency. Different analytical methods to estimate the radiation efficiency are presented and compared with data collected at sea. The measurements are performed acquiring simultaneously acceleration and acoustic levels by means on accelerometers installed on the hull's panels at different positions and hydrophones deployed close to the bow, middle and stern of the ship. The analysis of the transmission of the vibrations along the ships is performed using the data from different locations of the hydrophones. The quality of the measurements is analysed using the coherence function through the spectral correlation between the measurement of vibrations and acoustic levels. On the other hand, signal-to-noise ratio is computed to verify the strength of the noise sources. The computed transfer function is used to predict the underwater radiated noise from vibrations showing differences less than 2 dB re to 1 μPa².

Modeling the Design Characteristics of Woven Textile Electrodes for long-Term ECG Monitoring

An electrocardiograph records the periodic voltage generated by the heart over time. There is growing demand to continuously monitor the ECG for proactive health care and human performance optimization. To meet this demand, new conductive textile electrodes are being developed which offer an attractive alternative to adhesive gel electrodes but they come with their own challenges. The key challenge with textile electrodes is that the relationship between the manufacturing parameters and the ECG measurement is not well understood, making design an iterative process without the ability to prospectively develop woven electrodes with optimized performance. Here we address this challenge by applying the traditional skin-electrode interface circuit model to woven electrodes by constructing a parameterized model of the ECG system. Then the unknown parameters of the system are solved for with an iterative MATLAB optimizer using measured data captured with the woven electrodes. The results of this novel analysis confirm that yarn conductivity and total conductive area reduce skin electrode impedance. The results also indicate that electrode skin pressure and moisture require further investigation. By closing this gap in development, textile electrodes can be better designed and manufactured to meet the demands of long-term ECG capture.

Middle cerebral artery dynamic cerebral autoregulation is impaired by infarctions in the anterior but not the posterior cerebral artery territory in patients with mild strokes

Objective

The aim of this study was to ascertain whether dynamic cerebral autoregulation (CA) in the middle cerebral artery (MCA) is disturbed by cerebral infarctions outside the MCA territory.

Methods

We estimated transfer function parameters gain and phase from simultaneous recordings of spontaneous oscillation in blood pressure and MCA cerebral blood flow velocity in 10 consecutive patients with isolated anterior cerebral artery (ACA) infarctions and in 22 consecutive patients with isolated posterior cerebral artery (PCA) infarctions. All ACA infarctions were in the motor, premotor, or supplementary motor cortex areas and presented with pronounced leg hemiparesis. Twenty-eight age- and sex-matched healthy subjects served as controls.

Results

Compared to controls, phase was significantly reduced in the MCA ipsilateral to the lesion site and in the contralateral MCA (unaffected hemisphere) in the very low (0.02-0.07 Hz) and low (0.07-0.15 Hz) frequency ranges in the ACA infarctions but not in the PCA infarctions. Gain was reduced only in the very low frequency range in the MCA contralateral to the ACA lesion site. Systemic factors were unrelated to phase and gain results.

Conclusion

Bilateral impairment of MCA dynamic CA in patients with a unilateral ACA infarction is frequent.

Electromechanical Reciprocity Applied to the Sensing Properties of Guided Elastic Wave Transducers

Guided elastic wave (GEW) transducers for structural health monitoring (SHM) can act as transmitters (senders) and receivers (sensors). Their performance in both cases depends on the structure to which they are coupled. Therefore, they must be characterized as system transducer- structure. The characterization of the transducer-structure as transmitter using a Scanning Laser Doppler Vibrometer (SLDV) is straightforward, whereas its characterization as receiver is non-trivial. We propose to exploit electromechanical reciprocity, which is an identity between the transfer functions of electrical-to-mechanical and mechanical-to-electrical conversions. For this purpose, the well-known electromechanical reciprocity theorem was adapted to the following situation: The two reciprocal states are "electrical excitation and detection of the surface velocity at point P" and "mechanical excitation at P and measurement of the electrical quantities". According to the derived formulas, the quantities on the mechanical and electrical sides must be chosen appropriately to ensure reciprocity as well as that the corresponding transfer functions are equal. We demonstrate the reciprocity with experimental data for correctly chosen transfer functions and show the deviation in reciprocity for a different choice. Furthermore, we propose further applications of electromechanical reciprocity.

Linear and nonlinear identification of the carotid sinus baroreflex in the very low-frequency range

Since the arterial baroreflex system is classified as an immediate control system, the focus has been on analyzing its dynamic characteristics in the frequency range between 0.01 and 1 Hz. Although the dynamic characteristics in the frequency range below 0.01 Hz are not expected to be large, actual experimental data are scant. The aim was to identify the dynamic characteristics of the carotid sinus baroreflex in the frequency range down to 0.001 Hz. The carotid sinus baroreceptor regions were isolated from the systemic circulation, and carotid sinus pressure (CSP) was changed every 10 s according to Gaussian white noise with a mean of 120 mmHg and standard deviation of 20 mmHg for 90 min in anesthetized Wistar‐Kyoto rats (n = 8). The dynamic gain of the linear transfer function relating CSP to arterial pressure (AP) at 0.001 Hz tended to be greater than that at 0.01 Hz (1.060 ± 0.197 vs. 0.625 ± 0.067, p = 0.080), suggesting that baroreflex control was largely maintained at 0.001 Hz. Regarding nonlinear analysis, a second‐order Uryson model predicted AP with a higher R² value (0.645 ± 0.053) than a linear model (R² = 0.543 ± 0.057, p = 0.025) or a second‐order Volterra model (R² = 0.589 ± 0.055, p = 0.045) in testing data. These pieces of information may be used to create baroreflex models that can add a component of autonomic control to a cardiovascular digital twin for predicting acute hemodynamic responses to treatments and tailoring individual treatment strategies.

Quantifying the Surface Strain Field Induced by Active Sources with Distributed Acoustic Sensing: Theory and Practice

Quantitative dynamic strain measurements of the ground would be useful for engineering scale problems such as monitoring for natural hazards, soil-structure interaction studies, and non-invasive site investigation using full waveform inversion (FWI). Distributed acoustic sensing (DAS), a promising technology for these purposes, needs to be better understood in terms of its directional sensitivity, spatial position, and amplitude for application to engineering-scale problems. This study investigates whether the physical measurements made using DAS are consistent with the theoretical transfer function, reception patterns, and experimental measurements of ground strain made by geophones. Results show that DAS and geophone measurements are consistent in both phase and amplitude for broadband (10 s of Hz), high amplitude (10 s of microstrain), and complex wavefields originating from different positions around the array when: (1) the DAS channels and geophone locations are properly aligned, (2) the DAS cable provides good deformation coupling to the internal optical fiber, (3) the cable is coupled to the ground through direct burial and compaction, and (4) laser frequency drift is mitigated in the DAS measurements. The transfer function of DAS arrays is presented considering the gauge length, pulse shape, and cable design. The theoretical relationship between DAS-measured and pointwise strain for vertical and horizontal active sources is introduced using 3D elastic finite-difference simulations. The implications of using DAS strain measurements are discussed including directionality and magnitude differences between the actual and DAS-measured strain fields. Estimating measurement quality based on the wavelength-to-gauge length ratio for field data is demonstrated. A method for spatially aligning the DAS channels with the geophone locations at tolerances less than the spatial resolution of a DAS system is proposed.

[Analysis of Characteristics of Eye Movement While Viewing Movies and Its Application]

In this article, we present the following: a background of visually induced motion sickness (VIMS), the goal of our study, and descriptions of three recent studies conducted by our group on the measurement and analysis of eye movement while viewing movies and the relationship of eye movement with VIMS. First, this study focuses on the relationship between eye movement and motion sickness susceptibility. We investigated the relationship between the motion sickness susceptibility and the frequency of optokinetic nystagmus (OKN) with peripheral viewing. It was revealed that susceptible participants showed a lower OKN frequency under conditions that strongly support the occurrence of OKN than insusceptible participants. Second, this study focuses on the relationship between visual information and postural variation such as visually evoked postural responses (VEPRs). In this study, both eye movement and the center of gravity while viewing a movie were measured. Additionally, we evaluated the difference in the transfer gain of the transfer function (vision as input and equilibrium function as output) due to the type of movie content or way of viewing. The gain for the three-dimensional movie with peripheral viewing exceeded that for the two-dimensional movie with central viewing. Third, this study focuses on eye movement and the application of deep-learning technology. In this study, we classified the eye movement as peripheral or central using a convolutional deep neural network with supervised learning. Then, cross validation was performed to test the classification accuracy. The use of >1-s eye movement data yielded an accuracy of >90%.

Thermal variation in gradient response: measurement and modeling

PURPOSE

Many aspects and imperfections of gradient dynamics in MRI have been successfully captured by linear time-invariant (LTI) models. Changes in gradient behavior due to heating, however, violate time invariance. The goal of this work is to study such changes at the level of transfer functions and model them by thermal extension of the LTI framework.

METHODS

To study the impact of gradient heating on transfer functions, a clinical MR system was heated using a range of high-amplitude DC and AC waveforms, each followed by measuring transfer functions in rapid succession while the system cooled down. Simultaneously, gradient temperature was monitored with an array of temperature sensors positioned according to initial infrared recordings of the gradient tube. The relation between temperatures and transfer functions is cast into local and global linear models. The models are analysed in terms of self-consistency, conditioning, and prediction performance.

RESULTS

Pronounced thermal effects are observed in the time resolved transfer functions, largely attributable to in-coil eddy currents and mechanical resonances. Thermal modeling is found to capture these effects well. The keys to good model performance are well-placed temperature sensors and suitable training data.

CONCLUSION

Heating changes gradient response, violating time invariance. The utility of LTI modeling can nevertheless be recovered by a linear thermal extension, relying on temperature sensing and adequate one-time training.

Ivabradine increases the high frequency gain ratio in the vagal heart rate transfer function via an interaction with muscarinic potassium channels

Muscarinic potassium channels (IK,ACh ) are thought to contribute to the high frequency (HF) dynamic heart rate (HR) response to vagal nerve stimulation (VNS) because they act faster than the pathway mediated by hyperpolarization-activated cyclic nucleotide-gated (HCN) channels. However, the interactions between the two pathways have not yet been fully elucidated. We previously demonstrated that HCN channel blockade by ivabradine (IVA) increased the HF gain ratio of the transfer function from VNS to HR. To test the hypothesis that IVA increases the HF gain ratio via an interaction with IK,ACh , we examined the dynamic HR response to VNS under conditions of control (CNT), IK,ACh blockade by tertiapin-Q (TQ, 50 nM/kg), and TQ plus IVA (2 mg/kg) (TQ + IVA) in anesthetized rats (n = 8). In each condition, the right vagal nerve was stimulated for 10 min with binary white noise signals between 0-10, 0-20, and 0-40 Hz. On multiple regression analysis, the HF gain ratio positively correlated with the VNS rate with a coefficient of 1.691 ± 0.151 (×0.01) (p < 0.001). TQ had a negative effect on the HF gain ratio with a coefficient of -1.170 ± 0.214 (×0.01) (p < 0.001). IVA did not significantly increase the HF gain ratio in the presence of TQ. The HF gain ratio remained low under the TQ + IVA condition compared to controls. These results affirm that the IVA-induced increase in the HF gain ratio is dependent on the untethering of the hyperpolarizing effect of IK,ACh .

Mapping the dynamic transfer functions of eukaryotic gene regulation

Biological information can be encoded within the dynamics of signaling components, which has been implicated in a broad range of physiological processes including stress response, oncogenesis, and stem cell differentiation. To study the complexity of information transfer across the eukaryotic promoter, we screened 119 dynamic conditions-modulating the pulse frequency, amplitude, and pulse width of light-regulating the binding of an epigenome editor to a fluorescent reporter. This system revealed tunable gene expression and filtering behaviors and provided a quantification of the limit to the amount of information that can be reliably transferred across a single promoter as ∼1.7 bits. Using a library of over 100 orthogonal chromatin regulators, we further determined that chromatin state could be used to tune mutual information and expression levels, as well as completely alter the input-output transfer function of the promoter. This system unlocks the information-rich content of eukaryotic gene regulation.

A Novel Transfer Function Based Ring-Down Suppression System for PMUTs

In this paper, a novel ring-down suppression system based on transfer function is proposed for the first time to suppress the ring-down time and decrease the blind area of PMUTs (Piezoelectric Micromachined Ultrasonic Transducers). This suppression system includes a transfer function and a simple P (proportion) controller, which can reduce the ring-down time without degrading any performances of PMUTs. The transfer function serves as a virtual PMUT device, feeding its output into the P controller; then, the P controller generates a suppression signal to the actual PMUT device. The ring-down time of a 115-kHz PMUT array is demonstrated to be reduced by up to 93% through the suppression system. In addition, the P controller has been experimentally optimized, reducing the blind area of the PMUT array by about 40%. Moreover, a low ring-down PMUTs system design guideline is established, which is practical and straightforward for industrial scenarios. Finally, the system can be easily integrated into ASIC (Application Specific Integrated Circuit).

Closed-Loop Identification of Baroreflex Properties in the Frequency Domain

The arterial baroreflex system plays a key role in maintaining the homeostasis of arterial pressure (AP). Changes in AP affect autonomic nervous activities through the baroreflex neural arc, whereas changes in the autonomic nervous activities, in turn, alter AP through the baroreflex peripheral arc. This closed-loop negative feedback operation makes it difficult to identify open-loop dynamic characteristics of the neural and peripheral arcs. Regarding sympathetic AP controls, we examined the applicability of a nonparametric frequency-domain closed-loop identification method to the carotid sinus baroreflex system in anesthetized rabbits. This article compares the results of an open-loop analysis applied to open-loop data, an open-loop analysis erroneously applied to closed-loop data, and a closed-loop analysis applied to closed-loop data. To facilitate the understanding of the analytical method, sample data files and sample analytical codes were provided. In the closed-loop identification, properties of the unknown central noise that modulated the sympathetic nerve activity and the unknown peripheral noise that fluctuated AP affected the accuracy of the estimation results. A priori knowledge about the open-loop dynamic characteristics of the arterial baroreflex system may be used to advance the assessment of baroreflex function under closed-loop conditions in the future.

A technique for the reduction of RF-induced heating of active implantable medical devices during MRI

PURPOSE

The paper presents a novel method to reduce the RF-induced heating of active implantable medical devices during MRI.

METHODS

With the addition of an energy decoying and dissipating structure, RF energy can be redirected toward the dissipating rings through the decoying conductor. Three lead groups (45 cm-50 cm) and 4 (50 cm-100 cm) were studied in 1.5 Tesla MR systems by simulation and measurement, respectively. In vivo modeling was performed using human models to estimate the RF-induced heating of an active implantable medical device for spinal cord treatment.

RESULT

In the simulation study, it was shown that the peak 1g-averaged specific absorption rate near the lead-tips can be reduced by 70% to 80% compared to those from the control leads. In the experimental measurements during a 2-min exposure test in a 1.5 Telsa MR system, the temperature rises dropped from the original 18.3℃, 25.8℃, 8.1℃, and 16.1℃ (control leads 1-4) to 5.4℃, 6.9℃, 1.6℃, and 3.3℃ (leads 1-4 with the energy decoying and dissipation structure). The in vivo calculation results show that the maximum induced temperature rise among all cases can be substantially reduced (up to 80%) when the energy decoying and dissipating structures were used.

CONCLUSION

Our studies confirm the effectiveness of the novel technique for a variety of scanning scenarios. The results also indicate that the decoying conductor length, number of rings, and ring area must be carefully chosen and validated.

Estimation of Transfer Function Coefficients for Second-Order Systems via Metaheuristic Algorithms

The present research develops the parametric estimation of a second-order transfer function in its standard form, employing metaheuristic algorithms. For the estimation, the step response with a known amplitude is used. The main contribution of this research is a general method for obtaining a second-order transfer function for any order stable systems via metaheuristic algorithms. Additionally, the Final Value Theorem is used as a restriction to improve the velocity search. The tests show three advantages in using the method proposed in this work concerning similar research and the exact estimation method. The first advantage is that using the Final Value Theorem accelerates the convergence of the metaheuristic algorithms, reducing the error by up to 10 times in the first iterations. The second advantage is that, unlike the analytical method, it is unnecessary to estimate the type of damping that the system has. Finally, the proposed method is adapted to systems of different orders, managing to calculate second-order transfer functions equivalent to higher and lower orders. Response signals to the step of systems of an electrical, mechanical and electromechanical nature were used. In addition, tests were carried out with simulated signals and real signals to observe the behavior of the proposed method. In all cases, transfer functions were obtained to estimate the behavior of the system in a precise way before changes in the input. In all tests, it was shown that the use of the Final Value Theorem presents advantages compared to the use of algorithms without restrictions. Finally, it was revealed that the Gray Wolf Algorithm has a better performance for parametric estimation compared to the Jaya algorithm with an error up to 50% lower.

Three-dimensional transfer function of optical microscopes in reflection mode

Three-dimensional (3D) transfer functions build the basis for a comprehensive characterization of optical imaging systems in the spatial frequency domain. Utilizing the projection-slice theorem, the 2D modulation transfer function of an incoherent imaging system can be derived from a 3D transfer function by integration with respect to the axial spatial frequency. For a diffraction limited microscope with homogeneous incoherent pupil illumination, the modulation transfer function equals the 2D autocorrelation function of a circular disc. However, until now to the best of our knowledge no 3D transfer function has been published, which exactly leads to the 2D modulation transfer function of a diffraction limited microscope in reflection mode. In this article, we derive a formula, which after integration with respect to the axial spatial frequency coordinate perfectly fits to the diffraction limited 2D modulation transfer function. The inverse three-dimensional Fourier transform of the 3D transfer function results in a complex-valued 3D point spread function, from which the depth of field, the lateral resolution and, in addition, the corresponding 3D point spread function of both, a conventional and an interference microscope, can be obtained.

A single setup approach for the MRI-based measurement and validation of the transfer function of elongated medical implants

Purpose

To propose a single setup using the MRI to both measure and validate the transfer function (TF) of linear implants. Conventionally, the TF of an implant is measured in one bench setup and validated using another.

Methods

It has been shown that the TF can be measured using MRI. To validate this measurement, the implant is exposed to different incident electric fields, while the temperature increase at the tip is monitored. For a good validation, the incident electric fields that the implant is exposed to should be orthogonal. We perform a simulation study on six different methods that change the incident electric field. Afterward, a TF measurement and validation study using the best method from the simulations is performed. This is done with fiberoptic temperature probes at 1.5 T for four linear implant structures using the proposed single setup.

Results

The simulation study showed that positioning local transmit coils at different locations along the lead trajectory has a similar validation quality compared with changing the implant trajectory (ie, the conventional validation method). For the validation study that was performed, an R² ≥ 0.91 was found for the four investigated leads.

Conclusion

A single setup to both measure and validate the transfer function using local transmit coils has been shown to work. The benefits of using the proposed validation method are that there is only one setup required instead of two and the implant trajectory is not varied; therefore, the relative distance between the leap tip and the temperature probe is constant.

Ivabradine augments high-frequency dynamic gain of the heart rate response to low- and moderate-intensity vagal nerve stimulation under β-blockade

Our previous study indicated that intravenously administered ivabradine (IVA) augmented the dynamic heart rate (HR) response to moderate-intensity vagal nerve stimulation (VNS). Considering an accentuated antagonism, the results were somewhat paradoxical; i.e., the accentuated antagonism indicates that an activation of hyperpolarization-activated cyclic nucleotide-gated (HCN) channels via the accumulation of intracellular cyclic adenosine monophosphate (cAMP) augments the HR response to VNS, whereas the inhibition of HCN channels by IVA also augmented the HR response to VNS. To remove the possible influence from the accentuated antagonism, we examined the effects of IVA on the dynamic vagal control of HR under β-blockade. In anesthetized rats (n = 7), the right vagal nerve was stimulated for 10 min according to binary white noise signals between 0 and 10 Hz (V_0-10), between 0 and 20 Hz (V_0-20), and between 0 and 40 Hz (V_0-40). The transfer function from VNS to HR was estimated. Under β-blockade (propranolol, 2 mg/kg iv), IVA (2 mg/kg iv) did not augment the asymptotic low-frequency gain but increased the asymptotic high-frequency gain in V_0-10 (0.53 ± 0.10 vs. 1.74 ± 0.40 beats/min/Hz, P < 0.01) and V_0-20 (0.79 ± 0.14 vs. 2.06 ± 0.47 beats/min/Hz, P < 0.001). These changes, which were observed under a minimal influence from sympathetic background tone, may reflect an increased contribution of the acetylcholine-sensitive potassium channel (I_K,ACh) pathway after IVA, because the HR control via the I_K,ACh pathway is faster and acts in the frequency range higher than the cAMP-mediated pathway.NEW & NOTEWORTHY Since ivabradine (IVA) inhibits hyperpolarization-activated cyclic nucleotide-gated channels, interactions among the sympathetic effect, vagal effect, and IVA can occur in the control of heart rate (HR). To remove the sympathetic effect, we estimated the transfer function from vagal nerve stimulation to HR under β-blockade in anesthetized rats. IVA augmented the high-frequency dynamic gain during low- and moderate-intensity vagal nerve stimulation. Untethering the hyperpolarizing effect of acetylcholine-sensitive potassium channels after IVA may be a possible underlying mechanism.

Detecting time lag between a pair of time series using visibility graph algorithm

Estimating the time lag between a pair of time series is of significance in many practical applications. In this article, we introduce a method to quantify such lags by adapting the visibility graph algorithm, which converts time series into a mathematical graph. Currently widely used method to detect such lags is based on cross-correlations, which has certain limitations. We present simulated examples where the new method identifies the lag correctly and unambiguously while as the cross-correlation method does not. The article includes results from an extensive simulation study conducted to better understand the scenarios where the new method performed better or worse than the existing approach. We also present a likelihood based parametric modeling framework and consider frameworks for quantifying uncertainty and hypothesis testing for the new approach. We apply the current and new methods to two case studies, one from neuroscience and the other from environmental epidemiology, to illustrate the methods further.

How surface stress transforms surface profiles and adhesion of rough elastic bodies

The surface of soft solids carries a surface stress that tends to flatten surface profiles. For example, surface features on a soft solid, fabricated by moulding against a stiff-patterned substrate, tend to flatten upon removal from the mould. In this work, we derive a transfer function in an explicit form that, given any initial surface profile, shows how to compute the shape of the corresponding flattened profile. We provide analytical results for several applications including flattening of one-dimensional and two-dimensional periodic structures, qualitative changes to the surface roughness spectrum, and how that strongly influences adhesion.

Dynamic Modeling Using Artificial Neural Network of Bacillus Velezensis Broth Cross-Flow Microfiltration Enhanced by Air-Sparging and Turbulence Promoter

Cross-flow microfiltration is a broadly accepted technique for separation of microbial biomass after the cultivation process. However, membrane fouling emerges as the main problem affecting permeate flux decline and separation process efficiency. Hydrodynamic methods, such as turbulence promoters and air sparging, were tested to improve permeate flux during microfiltration. In this study, a non-recurrent feed-forward artificial neural network (ANN) with one hidden layer was examined as a tool for microfiltration modeling using Bacillus velezensis cultivation broth as the feed mixture, while the Kenics static mixer and two-phase flow, as well as their combination, were used to improve permeate flux in microfiltration experiments. The results of this study have confirmed successful application of the ANN model for prediction of permeate flux during microfiltration of Bacillus velezensis cultivation broth with a coefficient of determination of 99.23% and absolute relative error less than 20% for over 95% of the predicted data. The optimal ANN topology was 5-13-1, trained by the Levenberg-Marquardt training algorithm and with hyperbolic sigmoid transfer function between the input and the hidden layer.

Reconfigurable Filtering of Neuro-Spike Communications Using Synthetically Engineered Logic Circuits

High-frequency firing activity can be induced either naturally in a healthy brain as a result of the processing of sensory stimuli or as an uncontrolled synchronous activity characterizing epileptic seizures. As part of this work, we investigate how logic circuits that are engineered in neurons can be used to design spike filters, attenuating high-frequency activity in a neuronal network that can be used to minimize the effects of neurodegenerative disorders such as epilepsy. We propose a reconfigurable filter design built from small neuronal networks that behave as digital logic circuits. We developed a mathematical framework to obtain a transfer function derived from a linearization process of the Hodgkin-Huxley model. Our results suggest that individual gates working as the output of the logic circuits can be used as a reconfigurable filtering technique. Also, as part of the analysis, the analytical model showed similar levels of attenuation in the frequency domain when compared to computational simulations by fine-tuning the synaptic weight. The proposed approach can potentially lead to precise and tunable treatments for neurological conditions that are inspired by communication theory.

Impaired Dynamic Cerebral Autoregulation in Cerebral Venous Thrombosis

Background: Cerebral autoregulation is crucial in traumatic brain injury, which might be used for determining the optimal intracranial pressure. Cerebral venous thrombosis (CVT) is a cerebral vascular disease with features of high intracranial pressure. However, the autoregulatory mechanism of CVT remains unknown. We aimed to investigate the capacity of cerebral autoregulation in patients with CVT. Methods: This study consecutively enrolled 23 patients with CVT and 16 controls from December 2018 to May 2019. Cerebral autoregulation was assessed by transfer function analysis (rate of recovery/phase/gain) using the spontaneous oscillations of the cerebral blood flow velocity and arterial blood pressure. Results: In total, 76 middle cerebral arteries (MCAs) were investigated, including 44 MCAs in patients with CVT and 32 normal ones. The phase shift estimated in patients with CVT was significantly different from that of the controls (37.37 ± 36.53 vs. 54.00 ± 26.78, p = 0.03). The rate of recovery and gain in patients with CVT were lower than those in controls but without statistical significance. Conclusion: To our knowledge, this is the first time that a study has indicated that patients with CVT were more likely to have impaired cerebral autoregulation. Hence, cautious blood pressure control is required in such patients to prevent hyper- or hypoperfusion.

Fluctuations in intracranial pressure can be estimated non-invasively using near-infrared spectroscopy in non-human primates

Intracranial pressure (ICP) is typically measured invasively through a sensor placed inside the brain or a needle inserted into the spinal canal, limiting the patient population on which this assessment can be performed. Currently, non-invasive methods are limited due to lack of sensitivity and thus only apply to extreme cases of increased ICP, instead of use in general clinical practice. We demonstrate a novel application for near-infrared spectroscopy (NIRS) to accurately estimate ICP changes over time. Using a non-human primate (Rhesus Macaque) model, we collected optical data while we induced ICP oscillations at multiple ICP levels obtained by manipulating the height of a fluid column connected via a catheter to the lateral ventricle. Hemodynamic responses to ICP changes were measured at the occipital pole and compared to changes detected by a conventional intraparenchymal ICP probe. We demonstrate that hemoglobin concentrations are highly correlated with induced ICP oscillations and that this response is frequency dependent. We translated the NIRS data into non-invasive ICP measurements via a fitted non-parametric transfer function, demonstrating a match in both magnitude and time alignment with an invasively measured reference. Our results demonstrate that NIRS has the potential for non-invasive ICP monitoring.

Quantitative and Predictive Genetic Parts for Plant Synthetic Biology

Plant synthetic biology aims to harness the natural abilities of plants and to turn them to new purposes. A primary goal of plant synthetic biology is to produce predictable and programmable genetic circuits from simple regulatory elements and well-characterized genetic components. The number of available DNA parts for plants is increasing, and the methods for rapid quantitative characterization are being developed, but the field of plant synthetic biology is still in its early stages. We here describe methods used to describe the quantitative properties of genetic components needed for plant synthetic biology. Once the quantitative properties and transfer function of a variety of genetic parts are known, computers can select the optimal components to assemble into functional devices, such as toggle switches and positive feedback circuits. However, while the variety of circuits and traits that can be put into plants are limitless, doing synthetic biology in plants poses unique challenges. Plants are composed of differentiated cells and tissues, each representing potentially unique regulatory or developmental contexts to introduced synthetic genetic circuits. Further, plants have evolved to be highly sensitive to environmental influences, such as light or temperature, any of which can affect the quantitative function of individual parts or whole circuits. Measuring the function of plant components within the context of a plant cell and, ideally, in a living plant, will be essential to using these components in gene circuits with predictable function. Mathematical modeling will be needed to account for the variety of contexts a genetic part will experience in different plant tissues or environments. With such understanding in hand, it may be possible to redesign plant traits to serve human and environmental needs.

Low-Power Voltage Transformer Smart Frequency Modeling and Output Prediction up to 2.5 kHz, Using Sinc-Response Approach

The instrument transformers scenario is moving towards the adoption of a new generation of low-power instrument transformers. This disruptive change also requires that the modeling, characterization, and testing of those devices must be improved. Therefore, this study focuses on a smart approach developed by the authors in a previous study to estimate the output of low-power voltage transformers (LPVT). The approach-which is based on a sort of modeling in the frequency domain (the so-called sinc-response)-allows obtaining the behavior of the LPVT at rated and distorted conditions. Experimental tests performed on off-the-shelf devices confirm the applicability and effectiveness of the proposed approach when estimating the output response of LPVTs.

MRI-based transfer function determination through the transfer matrix by jointly fitting the incident and scattered B1+ field

PURPOSE

A purely experimental method for MRI-based transfer function (TF) determination is presented. A TF characterizes the potential for radiofrequency heating of a linear implant by relating the incident tangential electric field to a scattered electric field at its tip. We utilize the previously introduced transfer matrix (TM) to determine transfer functions solely from the MR measurable quantities, that is, the B 1 + and transceive phase distributions. This technique can extend the current practice of phantom-based TF assessment with dedicated experimental setup toward MR-based methods that have the potential to assess the TF in more realistic situations.

THEORY AND METHODS

An analytical description of the B 1 + magnitude and transceive phase distribution around a wire-like implant was derived based on the TM. In this model, the background field is described using a superposition of spherical and cylindrical harmonics while the transfer matrix is parameterized using a previously introduced attenuated wave model. This analytical description can be used to estimate the transfer matrix and transfer function based on the measured B 1 + distribution.

RESULTS

The TF was successfully determined for 2 mock-up implants: a 20-cm bare copper wire and a 20-cm insulated copper wire with 10 mm of insulation stripped at both endings in respectively 4 and 3 different trajectories. The measured TFs show a strong correlation with a reference determined from simulations and between the separate experiments with correlation coefficients above 0.96 between all TFs. Compared to the simulated TF, the maximum deviation in the estimated tip field is 9.4% and 12.2% for the bare and insulated wire, respectively.

CONCLUSIONS

A method has been developed to measure the TF of medical implants using MRI experiments. Jointly fitting the incident and scattered B 1 + distributions with an analytical description based on the transfer matrix enables accurate determination of the TF of 2 test implants. The presented method no longer needs input from simulated data and can therefore, in principle, be used to measure TF's in test animals or corpses.

Coupled transfer function model for the evaluation of implanted cables safety in MRI

PURPOSE

Multiple medical-device leads implanted next to each other are often encountered in clinical practice. The aim of this work is to study a coupled transfer function model to evaluate the safety of these coupled leads submitted to the RF field of a 1.5T MRI scanner for a constant distance between both leads.

METHODS

The effect of coupling on the heating of 2 cables with different termination conditions is evaluated experimentally. The coupled and single transfer functions are determined experimentally and used to predict the relative temperature increases of both cables alone and coupled. Two different coupled models, an additive model and a global model, are proposed. The coupled transfer functions are also simulated.

RESULTS

The coupling between cables has a strong influence on the resulting heating at the electrodes. The coupled additive transfer function model is a relevant tool to evaluate the heating of coupled leads separated by a constant distance. The global model underestimates the heating in one of the coupled cases by about 30%. The measured coupled transfer functions coincide with the simulated models.

CONCLUSION

It is necessary to take into account the coupling effect between leads to evaluate the safety of implanted devices. This work shows that, in the case of 2 cables separated by a constant distance, that an experimentally determined coupled transfer function allows estimation of the heating of the 2 electrodes for a given incident field. Further work should take into account the in vivo varying distance between the 2 cables.

Compromised Dynamic Cerebral Autoregulation in Patients With Idiopathic Rapid Eye Movement Behavior Disorder: A Case-Control Study Using Transcranial Doppler

BACKGROUND

Patients with idiopathic rapid eye movement behavior disorder (IRBD) have been suggested to exhibit altered cerebral perfusion and abnormal cerebral blood flow, which imply a possibility of cerebral autoregulation (CA) impairment. We aimed to investigate the dynamic CA (dCA) in patients with IRBD during wakefulness and to explore the correlations between dCA parameters and clinical measurements.

METHODS

We assessed the dCA capability of 30 patients with IRBD and 36 sex- and age-matched healthy controls by using transcranial Doppler and finger plethysmography. CA function was evaluated by transfer function analysis based on spontaneous oscillation of cerebral blood flow and arterial blood pressure. Transfer function parameters (phase difference and gain) were used to quantify the CA.

RESULTS

No significant differences were observed between the right and left middle cerebral artery dCA parameters (phase difference and gain) of both groups. Patients with IRBD had significantly lower phase difference than the healthy controls, indicating their impaired CA capability. Besides, the value of gain in patients with IRBD was higher than the healthy controls, but the difference did not reach statistical level.

CONCLUSIONS

CA function is compromised in patients with IRBD during wakefulness, which might be an intermediate link between IRBD and neurological symptoms.

Rapid acquisition of the 3D MRI gradient impulse response function using a simple phantom measurement

PURPOSE

To provide a simple tool for rapid measurement of the 3D gradient modulation transfer function (GMTF) of clinical MRI systems using a phantom. Knowledge of the transfer function is useful for gradient chain characterization, system calibration, and improvement of image reconstruction results.

METHODS

Starting from the well-established thin slice method used for phantom-based measurement of the 1D GMTF, we add phase encoding to partition the thin slices into voxels that act as localized field probes. From the signal phase evolution measured at the 3D voxel positions, the GMTF can be derived for cross and higher order spatial terms represented by spherical harmonics up to 3rd order.

RESULTS

Using spherical phantoms, 16 GMTFs representing all terms up to 3rd order harmonics can be determined in a scan time of <2 min. A large voxel volume of >1 mL yields high SNR, enabling signal acquisition using the system's body coil. The method is applied for improving system calibration and for characterizing the effect of additional hardware in the bore.

CONCLUSION

The presented method seems well-suited for rapid measurement of the GMTF of a clinical system, as it delivers high-quality results in a short scan time.

Study of Transfer Characteristics of a Molecular Electronic Sensor for Borehole Surveys at High Temperatures and Pressures

The paper considers the development and experimental study of the characteristics of a high-temperature motion parameter sensor based on molecular-electronic technology (MET) operating at elevated pressures. Studies were conducted in an extended temperature range (25-125 °C) with a static external pressure of up to 10 atm. A pilot plant based on a high-pressure chamber with the ability to output an electrical signal was specially designed and commissioned. A family of amplitude-frequency characteristics of a ME sensor in an extended temperature range was obtained for the first time. A theoretical model was constructed and verified to describe the transfer function of the sensor at high temperatures and pressures. The activation energies of active carriers were calculated, and a prediction was made about the possibility of using the developed devices for the needs of the oil and gas mining industries.

Incorporating local adaptation into forecasts of species' distribution and abundance under climate change

Populations of many species are genetically adapted to local historical climate conditions. Yet most forecasts of species' distributions under climate change have ignored local adaptation (LA), which may paint a false picture of how species will respond across their geographic ranges. We review recent studies that have incorporated intraspecific variation, a potential proxy for LA, into distribution forecasts, assess their strengths and weaknesses, and make recommendations for how to improve forecasts in the face of LA. The three methods used so far (species distribution models, response functions, and mechanistic models) reflect a trade-off between data availability and the ability to rigorously demonstrate LA to climate. We identify key considerations for incorporating LA into distribution forecasts that are currently missing from many published studies, including testing the spatial scale and pattern of LA, the confounding effects of LA to nonclimatic or biotic drivers, and the need to incorporate empirically based dispersal or gene flow processes. We suggest approaches to better evaluate these aspects of LA and their effects on species-level forecasts. In particular, we highlight demographic and dynamic evolutionary models as promising approaches to better integrate LA into forecasts, and emphasize the importance of independent model validation. Finally, we urge closer examination of how LA will alter the responses of central vs. marginal populations to allow stronger generalizations about changes in distribution and abundance in the face of LA.

Compromised Dynamic Cerebral Autoregulation in Patients With Depression

Background: Patients with depression tend to have various comorbid neurological symptoms, but the mechanisms remain unclear. The purpose of this study was to analyze the characteristics of dynamic cerebral autoregulation in depressed patients. Methods: Patients (aged ≥ 18 years) who were diagnosed with depression [17-item Hamilton Depression Rating Scale (HAMD) > 17] or suspected of depression (HAMD > 7) were enrolled in this study. Medically healthy volunteers were recruited as controls. The subjects also received the 7-item HAMD. We simultaneously recorded noninvasive continuous arterial blood pressure and bilateral middle cerebral artery blood flow velocity from each subject. Cerebral autoregulation was assessed by analyzing the phase difference using transfer function analysis. Results: This study enrolled 54 patients with suspected depression, 45 patients with depression, and 48 healthy volunteers. The mean phase difference values were significantly lower in the patients with depression (F = 9.071, P < 0.001). In the multiple regression analysis, depression was negatively correlated with the phase difference values. Conclusions: Dynamic cerebral autoregulation was compromised in patients with depression and negatively correlated with the depression score. Improving dynamic cerebral autoregulation may be a potential therapeutic method for treating the neurological symptoms of depression.

Improved Detection of Lung Fluid With Standardized Acoustic Stimulation of the Chest

Accumulation of excess air and water in the lungs leads to breakdown of respiratory function and is a common cause of patient hospitalization. Compact and non-invasive methods to detect the changes in lung fluid accumulation can allow physicians to assess patients’ respiratory conditions. In this paper, an acoustic transducer and a digital stethoscope system are proposed as a targeted solution for this clinical need. Alterations in the structure of the lungs lead to measurable changes which can be used to assess lung pathology. We standardize this procedure by sending a controlled signal through the lungs of six healthy subjects and six patients with lung disease. We extract mel-frequency cepstral coefficients and spectroid audio features, commonly used in classification for music retrieval, to characterize subjects as healthy or diseased. Using the \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$K$ \end{document}-nearest neighbors algorithm, we demonstrate 91.7% accuracy in distinguishing between healthy subjects and patients with lung pathology.

Tabla: A Proof-of-Concept Auscultatory Percussion Device for Low-Cost Pneumonia Detection

Pneumonia causes the deaths of over a million people worldwide each year, with most occurring in countries with limited access to expensive but effective diagnostic methods, e.g., chest X-rays. Physical examination, the other major established method of diagnosis, suffers from several drawbacks, most notably low accuracy and high interobserver error. We sought to address this diagnostic gap by developing a proof-of-concept non-invasive device to identify the accumulation of fluid in the lungs (consolidation) characteristic of pneumonia. This device, named Tabla after the percussive instrument of the same name, utilizes the technique of auscultatory percussion; a percussive input sound is sent through the chest and recorded with a digital stethoscope for analysis. Tabla analyzes differences in sound transmission through the chest at audible frequencies as a marker for lung consolidation. This paper presents preliminary data from five pneumonia patients and eight healthy subjects. We demonstrate 92.3% accuracy in distinguishing between healthy subjects and patients with pneumonia after data analysis with a K-nearest neighbors algorithm. This prototype device is low cost and simple to implement and may offer a rapid and inexpensive method for pneumonia diagnosis appropriate for general use and in areas with limited medical infrastructure.