INCREASING THE COST-EFFECTIVENESS OF IN VITRO RESEARCH THROUGH THE USE OF TITANIUM IN THE DEVICE FOR MEASURING THE ELECTRICAL PARAMETERS OF CELLS

Currently, various methods are used to assess the biocompatibility of materials. After an in-depth and detailed review of the literature, the method used in the research was selected. As part of the experiments, a method based on the analysis of the values ​​of electrical parameters of cell cultures measured in the presence of electrodes was used. The electrode is a structure made of a thin layer of metallization. It measures the change in resistance, impedance and capacity of a mixture of cells and the substance in which they are grown. The plate containing the electrode assembly is called the measurement matrix. Currently, commercially used test matrices are made of gold or platinum. However, their high price means that large-scale research is significantly limited. In order to increase the access to the widespread use of this method, it was decided that it was necessary to use cheaper materials, reducing the necessary costs of conducting experiments. Considering this, an attempt was made to use a different conductive material to build matrices compatible with the ECIS® Z-Theta measurement system. Their use would enable in vitro research on living cells. In the presented work, titanium was used as a material that may turn out to be an alternative to the materials currently used. Its application to the production of matrices will allow to study the influence of this metal on the behavior of cells.

Simultaneous Audio Encryption and Compression Using Parallel Compressive Sensing and Modified Toeplitz Measurement Matrix

With the explosive growth of voice information interaction, there is an urgent need for safe and effective compression transmission methods. In this paper, compressive sensing is used to realize the compression and encryption of speech signals. Firstly, the scheme of linear feedback shift register combined with inner product to generate measurement matrix is proposed. Secondly, we adopt a new parallel compressive sensing technique to tremendously improve the processing efficiency. Further, the two parties in the communication adopt public key cryptosystem to safely share the key and select a different measurement matrix for each frame of the voice signal to ensure the security. This scheme greatly reduces the difficulty of generating measurement matrix in hardware and improves the processing efficiency. Compared with the existing scheme by Moreno-Alvarado et al., our scheme has reduced the execution time by approximately 8%, and the mean square error (MSE) has also been reduced by approximately 5%.

Research on Deterministic Measurement Matrix of Power Line Carrier Compressed Sensing

To verify the advantages of deterministic matrix applied to power line carrier communication (PLCC) based on compressed sensing (CS). This article analyzed the research status of commonly used deterministic measurement matrices, and made simulation comparison. It is found that different types of deterministic measurement matrices generated based on chaotic mapping had higher reconstruction accuracy and higher reconstruction efficiency than Gaussian random matrix. Then, according to simulation results and the characteristics of PLCC signal, the Chebyshev sparse circulant (CSC) measurement matrix was designed by combining eighth-order Chebyshev chaotic and the idea of sparse and circulant. Actual circuit measurement shows that when compression rate was 40% and 60%, the reconstruction loss of CSC is 0.72dB and 0.49dB higher than that of Chebyshev chaotic measurement matrix and Chebyshev circulate measurement matrix, respectively. Obviously, the CSC measurement matrix designed in this paper can effectively improve the reconstruction accuracy.

Drone SAR Image Compression Based on Block Adaptive Compressive Sensing

In this paper, an adaptive block compressive sensing (BCS) method is proposed for compression of synthetic aperture radar (SAR) images. The proposed method enhances the compression efficiency by dividing the magnitude of the entire SAR image into multiple blocks and subsampling individual blocks with different compression ratios depending on the sparsity of coefficients in the discrete wavelet transform domain. Especially, a new algorithm is devised that selects the best block measurement matrix from a predetermined codebook to reduce the side information about measurement matrices transferred from the remote sensing node to the ground station. Through some modification of the iterative thresholding algorithm, a new clustered BCS recovery method is proposed that classifies the blocks into multiple clusters according to the compression ratio and iteratively reconstructs the SAR image from the received compressed data. Since the blocks in the same cluster are concurrently reconstructed using the same measurement matrix, the proposed structure mitigates the increase in computational complexity when adopting multiple measurement matrices. Using existing SAR images and experimental data obtained by self-made drone SAR and vehicular SAR systems, it is shown that the proposed scheme provides a good tradeoff between the peak signal-to-noise ratio and the computational load compared to conventional BCS-based compression techniques.

Resting ECG measurements can identify abnormalities in children with catecholaminergic polymorphic ventricular tachycardia

Background Catecholaminergic Polymorphic Ventricular Tachycardia (CPVT) is a rare inherited disease characterized by exercise- or emotionally-triggered life-threatening ventricular arrhythmias. The resting ECG is considered to be normal and diagnosis has depended on exercise testing that is difficult acutely post-arrest or in young children. Purpose To identify resting ECG abnormalities in children with CPVT through assessment of measurement matrix parameters compared to a cohort of normal children. Methods A discovery cohort of 65 CPVT patients from the Electrophysiology program were identified. After excluding those on antiarrhythmics or in an arrhythmia at the time of their baseline ECG, 31 cases were matched 3:1 by age and sex with 93 healthy controls. Each individual had baseline ECG parameters and 180 machine-derived ECG amplitudes and durations (measurement matrix) measured. Statistical differences between ECG measures were assessed using Student's T-Test adjusted with a False Detection Rate of 1%. Significant measures were processed in a machine-learning algorithm to derive a Tree Model to differentiate individuals with and without CPVT. Results No significant differences were detected between CPVT patients who had and did not have a cardiac arrest. Comparing the CPVT and control cohorts, significant repolarization differences were seen in the amplitudes of lateral (I, negative aVR, V5, V6) and anterior leads (V2, V3, V4) at the J-point, ST midpoint, ST endpoint, and T-wave. Specifically, individuals with CPVT had significantly lower mean amplitudes in all aforementioned leads except aVR where the mean amplitudes were higher. These data were then used to create a Tree Model of the discovery cohort displayed in Figure 1 with a resulting R2 of 0.74, sensitivity of 0.81, and specificity of 0.98. Conclusions Baseline differences in repolarization are detectable in the left and anterior chest leads using machine-derived measurements of baseline ECGs in patients with CPVT, which may guide clinical suspicion when evaluating the resting ECG. These results warrant further analysis including testing of the Tree Model with a validation cohort. FUNDunding Acknowledgement Type of funding sources: Other. Main funding source(s): Scholar Award from the Ted Rogers Centre for Heart Research, Toronto, Ontario, Canada to Trainee Dr. Taraneh TofighiCanadian Institute for Health Research Figure 1. CPVT Tree Model