Measuring Physical Properties of Electrospun Nanofiber Mats for Different Biomedical Applications

Electrospun nanofiber mats are nowadays often used for biotechnological and biomedical applications, such as wound healing or tissue engineering. While most studies concentrate on their chemical and biochemical properties, the physical properties are often measured without long explanations regarding the chosen methods. Here, we give an overview of typical measurements of topological features such as porosity, pore size, fiber diameter and orientation, hydrophobic/hydrophilic properties and water uptake, mechanical and electrical properties as well as water vapor and air permeability. Besides describing typically used methods with potential modifications, we suggest some low-cost methods as alternatives in cases where special equipment is not available.

Invariant Pattern Recognition with Log-Polar Transform and Dual-Tree Complex Wavelet-Fourier Features

In this paper, we propose a novel method for 2D pattern recognition by extracting features with the log-polar transform, the dual-tree complex wavelet transform (DTCWT), and the 2D fast Fourier transform (FFT2). Our new method is invariant to translation, rotation, and scaling of the input 2D pattern images in a multiresolution way, which is very important for invariant pattern recognition. We know that very low-resolution sub-bands lose important features in the pattern images, and very high-resolution sub-bands contain significant amounts of noise. Therefore, intermediate-resolution sub-bands are good for invariant pattern recognition. Experiments on one printed Chinese character dataset and one 2D aircraft dataset show that our new method is better than two existing methods for a combination of rotation angles, scaling factors, and different noise levels in the input pattern images in most testing cases.

Timing and Frequency Synchronization Using CAZAC Sequences for OFDM Systems

Since orthogonal frequency division multiplexing (OFDM) systems are very susceptible to symbol timing offset (STO) and carrier frequency offset (CFO), which cause inter-symbol interference (ISI) and inter-carrier interference (ICI), accurate STO and CFO estimations are very important. In this study, first, a new preamble structure based on the Zadoff-Chu (ZC) sequences was designed. On this basis, we proposed a new timing synchronization algorithm, called the continuous correlation peak detection (CCPD) algorithm, and its improved algorithm: the accumulated correlation peak detection (ACPD) algorithm. Next, the correlation peaks that were obtained during the timing synchronization were used for the frequency offset estimation. For this, the quadratic interpolation algorithm was adopted as the frequency offset estimation algorithm, which was better than the fast Fourier transform (FFT) algorithm. The simulation results showed that when the correct timing probability reached 100%, under the parameters of m = 8 and N = 512, the performance of the CCPD algorithm was 4 dB higher than that of Du's algorithm, and that of the ACPD algorithm was 7 dB. Under the same parameters, the quadratic interpolation algorithm also had a great performance improvement in both small and large frequency offsets, when compared with the FFT algorithm.

Estimation of a Spectral Correlation Function Using a Time-Smoothing Cyclic Periodogram and FFT Interpolation-2N-FFT Algorithm

This article addresses the problem of estimating the spectral correlation function (SCF), which provides quantitative characterization in the frequency domain of wide-sense cyclostationary properties of random processes which are considered to be the theoretical models of observed time series or discrete-time signals. The theoretical framework behind the SCF estimation is briefly reviewed so that an important difference between the width of the resolution cell in bifrequency plane and the step between the centers of neighboring cells is highlighted. The outline of the proposed double-number fast Fourier transform algorithm (2N-FFT) is described in the paper as a sequence of steps directly leading to a digital signal processing technique. The 2N-FFT algorithm is derived from the time-smoothing approach to cyclic periodogram estimation where the spectral interpolation based on doubling the FFT base is employed. This guarantees that no cyclic frequency is left out of the coverage grid so that at least one resolution element intersects it. A numerical simulation involving two processes, a harmonic amplitude modulated by stationary noise and a binary-pulse amplitude-modulated train, demonstrated that their cyclic frequencies are estimated with a high accuracy, reaching the size of step between resolution cells. In addition, the SCF components estimated by the proposed algorithm are shown to be similar to the curves provided by the theoretical models of the observed processes. The comparison between the proposed algorithm and the well-known FFT accumulation method in terms of computational complexity and required memory size reveals the cases where the 2N-FFT algorithm offers a reasonable trade-off.

Effects of the Duration of a Resting-State EEG Recording in Healthy Aging and Mild Cognitive Impairment

INTRODUCTION

The recording of resting-state EEG may provide a means to predict early cognitive decline associated with mild cognitive impairment (MCI). Previous studies have typically used very short recording times to avoid a confound with drowsiness that may occur in longer recordings. The effects of a longer recording have not however been systematically examined.

METHODS

Eyes-closed resting-state EEG activity was recorded in 40 older adult participants (20 healthy older adults and 20 people with MCI). The recording period was a relatively long 6 minutes, divided into two equal 3-minute halves to determine if drowsiness will be more apparent as the recording progresses. The participants also completed standardized neuropsychological tasks that assessed global cognition (Montreal Cognitive Assessment) and memory (California Verbal Learning Test, Second Edition). A spectral analysis was performed on both short (2 seconds) and long (8 seconds) segments in both 3-minute halves.

RESULTS

No differences in power density for any of the EEG frequency bands were found between the 2 halves of the study for either group. There was little evidence of increased drowsiness in the second half of the study even when frequency resolution was increased with the 8-second segmentation. Theta power density was overall larger for people with MCI compared to healthy older adults. A negative correlation was also observed between theta power and global cognition in healthy older adults.

CONCLUSIONS

The present results indicate that longer resting-state EEG recording can be reliably employed without increased risk of drowsiness.

Ultrasound Assessment of Honey Using Fast Fourier Transform

Ultrasound inspection permits the characteristics of some foodstuffs to be determined easily and cheaply. This experimental study included the determination of various ultrasound parameters provided by the fast Fourier transform (FFT) which had not previously been considered in testing the physical properties of different varieties of honey. These parameters are practically independent of the criteria adopted for their calculation, unlike other ultrasound variables such as pulse velocity or attenuation whose determination can vary depending on those criteria. The study was carried out on four varieties of honey (Eucalyptus, Heather, Thyme, and Thousand Flowers) using 500-kHz transducers. A simultaneously performed honey texture analysis (Texture Profile Analysis-TPA) showed significant linear correlations between the ultrasound variables provided by FFT and the texture parameters. The FFT parameters distinguished between each of the four honey varieties studied.

FPGA Implementation of an Efficient FFT Processor for FMCW Radar Signal Processing

This paper presents the design and implementation results of an efficient fast Fourier transform (FFT) processor for frequency-modulated continuous wave (FMCW) radar signal processing. The proposed FFT processor is designed with a memory-based FFT architecture and supports variable lengths from 64 to 4096. Moreover, it is designed with a floating-point operator to prevent the performance degradation of fixed-point operators. FMCW radar signal processing requires windowing operations to increase the target detection rate by reducing clutter side lobes, magnitude calculation operations based on the FFT results to detect the target, and accumulation operations to improve the detection performance of the target. In addition, in some applications such as the measurement of vital signs, the phase of the FFT result has to be calculated. In general, only the FFT is implemented in the hardware, and the other FMCW radar signal processing is performed in the software. The proposed FFT processor implements not only the FFT, but also windowing, accumulation, and magnitude/phase calculations in the hardware. Therefore, compared with a processor implementing only the FFT, the proposed FFT processor uses 1.69 times the hardware resources but achieves an execution time 7.32 times shorter.

Predictive value of graft patency and major adverse cardiac and cerebrovascular events (MACCEs) in coronary artery bypass grafting (CABG) based on Fourier transform (FFT)

Background

Transit time flow measurement (TTFM) is widely used in coronary artery bypass grafting (CABG); however, its predictive value is unclear. We aimed to identify new factors to evaluate graft quality using fast Fourier transform (FFT).

Methods

Intraoperative and postoperative 2-year follow-up data of 114 patients undergoing CABG from January 2017 to December 2018 were collected. The TTFM waveform was transformed by FFT. Mean graft flow (MGF), pulse index, the amplitude of the main wave in FFT (H₀), the amplitude of the first harmonic (H₁), H₀/H₁, and the frequency of the first harmonic (P) were analyzed as predictors using logistic regression and receiver operating characteristic (ROC) curves.

Results

The overall graft patency rate was 80.3%, and the incidence of major adverse cardiac and cerebrovascular events (MACCEs) was 14.9%. The results demonstrate that compared with the graft failure group, MGF, H₀, and H₁ were higher, but H₁ and P were lower in the patent group. With univariate and multivariate logistic regression analyses, the decrease in H₀ and H₁ and the increase in P were independent risk factors for graft failure, while the decrease in MGF and the increase in H₀/H₁ were only statistically significant with a univariate analysis. In the cardiovascular events group, the increase in P was an independent risk factor. With a ROC curve analysis, MGF, H₀, H₁, H₀/H₁, and P predicted graft failure, while only P predicted cardiovascular events. None of the indicators showed predictive value for MACCEs.

Conclusions

TTFM waveforms after FFT can be used to evaluate graft quality and cardiovascular events, but have no predictive value for MACCEs.

Gimbal-Less Two-Axis Electromagnetic Microscanner with Twist Mechanism

We present an electromagnetically driven microscanner based on a gimbal-less twist mechanism. In contrast to conventional microscanners using a gimbal-less leverage mechanism, our device utilizes a gimbal-less twist mechanism to increase the scan angle in optical applications requiring a large scanning mirror. The proposed gimbal-less scanner with twist mechanism increases the scan angle by 1.55 and 1.97 times for the slow and fast axes, respectively, under the same force; 3.64 and 1.97 times for the slow and fast axes, respectively, under the same maximum stress, compared to the gimbal-less leverage mechanism. The scanner with a 3-mm-diameter mirror and a current path composed of a single-turn coil was fabricated, and it showed the maximum scan angle of 5° (quasi-static) and 22° (resonant) for the slow and fast axes, respectively. The experimentally estimated crosstalk was as small as 0.47% and 0.97% for the fast and slow axes affected by the other axes, respectively, which was determined using a newly employed methodology based on fast Fourier transform.

Motor Subtypes of Parkinson's Disease Can Be Identified by Frequency Component of Postural Stability

Parkinson’s disease (PD) can be divided into two subtypes based on clinical features—namely tremor dominant (TD) and postural instability and gait difficulty (PIGD). This categorization is important at the early stage of PD, since identifying the subtypes can help to predict the clinical progression of the disease. Accordingly, correctly diagnosing subtypes is critical in initiating appropriate early interventions and tracking the progression of the disease. However, as the disease progresses, it becomes increasingly difficult to further distinguish those attributes that are relevant to the subtypes. In this study, we investigated whether a method using the standing center of pressure (COP) time series data can separate two subtypes of PD by looking at the frequency component of COP (i.e., COP position and speed). Thirty-six participants diagnosed with PD were evaluated, with their bare feet on the force platform, and were instructed to stand upright with their arms by their sides for 20 s (with their eyes open and closed), which is consistent with the traditional COP measures. Fast Fourier transform (FFT) and wavelet transform (WT) were performed to distinguish between the motor subtypes using the COP measures. The TD group exhibited larger amplitudes at the frequency range of 3–7 Hz when compared to the PIGD group. Both the FFT and WT methods were able to differentiate the subtypes. COP time series information can be used to differentiate between the two motor subtypes of PD, using the frequency component of postural stability.

A Dual-Polymer Fiber Fizeau Interferometer for Simultaneous Measurement of Relative Humidity and Temperature

This paper presents a novel design method in which a dual-polymer fiber Fizeau interferometer (DPFFI) is proposed for simultaneously measuring relative humidity (RH) and temperature (T). Since the polymer is intrinsically highly sensitive to both RH and T, the polymer fiber Fizeau interferometer (PFFI) exhibits cross-sensitivity of RH and T. In general, it is difficult to demodulate the optical responses from both variations of RH and T using a single PFFI. If two PFFIs with different structures are combined, they will individually exhibit distinct sensitivity responses with respect to RH and T, respectively. The technical problem of analyzing multiple interferences of the optical spectra of the DPFFI and the individual sensitivity of RH and T to each PFFI is obtained using the fast Fourier transform (FFT). A mathematical method is applied to solve the simultaneous equations of the DPFFI, so that the two variables RH and T can be determined at the same time. Experimental results, indicating good sensitivity and accuracy, with small measurement errors (average errors of ~1.46 °C and ~1.48%, respectively), are shown, determining the feasibility, and verifying the effectiveness, of the proposed DPFFI sensor.