Search

In this paper, the piezospectroscopic effect for β -Ga2O3, i.e. the spectral band shift in response to strain/stress, has been calibrated by the indentation method using spatially resolved Raman spectroscopy for quantitative stress evaluation of Ga2O3 devices, taking advantage of the crack-tip tensile stress field and the spatial probe deconvolution. A series of Vickers indentation prints were introduced on (010) and ( 2 ˉ 01) Ga2O3 single crystals, and the relationships between observed band shifts and residual stresses were clarified to determine the phonon deformation potentials of the Raman bands. Accordingly, a quantitative analysis of the residual stress field in a Ga2O3 thin film grown on (0001) sapphire by plasma-assisted pulsed laser deposition, which revealed the presence of a gradient of incompletely released stress in the depth direction of the film, is shown as an example. [ABSTRACT FROM AUTHOR]

Objective. The arrhythmia identification method based on the U-net has the potential for fast application. The RR-intervals have been proven to improve the performance of single-heartbeat identification methods. However, because both the heartbeats number and location in the input of the U-net are unfixed, the approach based on the U-net cannot use RR-intervals directly. To solve this problem, we proposed a novel method. The proposed method also can identify heartbeats of four classes, including non-ectopic (N), supraventricular ectopic beat (SVEB), ventricular ectopic beat (VEB), and fusion beat (F). Approach. Our method consists of the pre-processing and the two-stage identification framework. In the pre-processing part, we filtered input signals with a band-pass filter and created the auxiliary waveforms by RR-intervals. In the first stage of the framework, we designed a network to handle input signals and auxiliary waveforms. We proposed a masking operation to separate the input signal into two signals according to the result of the network. The first signal contains heartbeats of SVEB and VEB. The second signal includes heartbeats of N and F. The second stage consists of two networks and can further identify the heartbeats of SVEB, VEB, N, and F from these two signals. Main result. We validated our method on the MIT-BIH arrhythmia database with the inter-patient model. For classes N, SVEB, VEB, and F, our approach achieved F1 scores of 98.26, 68.61, 95.99, and 47.75, respectively. Significance. Our method not only can effectively utilize RR intervals but also can identify multiple arrhythmias. [ABSTRACT FROM AUTHOR]

In this study, microstructural variation of hydroxyapatite (HAp) ceramics upon thermal treatment in air at different temperatures was investigated by x-ray diffraction patterns, Raman and x-ray photoelectron spectroscopies. The results revealed a significant dependence of the microstructure of nonstoichiometric HAp on temperature, because of the competition between hydroxylation and different kinds of dehydroxylation at different temperatures, and a gradual increase in material hardness with annealing temperature because of structural reconstruction. In summary, a suitable thermal treatment can effectively tailor microstructure and defect contents, as well as chemical composition and mechanical hardness of HAp ceramics. [ABSTRACT FROM AUTHOR]

Objective. Muscle artifacts (MA) and electrode motion artifacts (EMA) in electrocardiogram (ECG) signals lead to a large number of false alarms from cardiac diagnostic systems. To reduce false alarms, it is necessary to improve the performance of the diagnostic algorithm in noisy environments by removing excessively noisy signals. However, existing methods focus on signal quality assessment and contain too many artificial features. Here, we present a novel method to flexibly eliminate noisy signals without any artificial features. Approach. Our method contains an improved lightweight deep neural network (DNN) to capture the signal portions damaged by EMA and MA, uses the sample entropy to quantize noisy portions, and discards those portions that exceed a defined threshold. Our method was tested in conjunction with Pan-Tompkins (PT), Filter Bank (FB), and 'UNSW' R-peak detection algorithms along with two heartbeat classification algorithms on datasets synthesized from the MIT-BIH Noise Stress Test Database, the China Physiological Signal Challenge 2018 Database and the MIT-BIH Arrhythmia Database. Main results. For PT R-peak detection algorithms, the sensitivity (Se) increased noticeably from 89.01% to 99.42% in the synthesized datasets with a signal-to-noise ratio of 6 dB. With the same datasets, the Se of the FB algorithm increased about 9.29%, and a 3.64% increase occurred in the Se of the 'UNSW' algorithm. For heartbeat classification algorithms, the overall F1-score increased about 6% in the synthesized one-heartbeat datasets. It is the first study to utilize a DNN to capture noisy segments of the ECG signal. Significance. Too many false alarms can cause alarm fatigue. Our method can be utilized as the preprocessing before signal analysis, thereby reducing false alarms from the ECG diagnostic systems. [ABSTRACT FROM AUTHOR]

Objective. Electrocardiogram (ECG) signals are easily polluted by various noises which are likely to have adverse effects on subsequent interpretations. Research on model lightweighting can promote the practical application of deep learning-based ECG denoising methods in real-time processing. Approach. Firstly, grouped convolution and conventional convolution are combined to replace the continuous conventional convolution in the model, and the depthwise convolution with stride is used to compress the feature map in the encoder modules. Secondly, additional identity connections and a local maximum and minimum enhancement module are designed, which can retain the detailed information and characteristic waveform in the ECG waveform while effectively denoising. Finally, we develop knowledge distillation in the experiments, which further improves the ECG denoising performance without increasing the model complexity. The ground-truth ECG is from The China Physiological Signal Challenge (CPSC) 2018, and the noise signal is from the MIT-BIH Noise Stress Test Database (NSTDB). We evaluate denoising performance using the signal-to-noise ratio (SNR), the root mean square error (RMSE) and the Pearson correlation coefficient (P). We use the floating point of operations (FLOPs) and parameters to calculate computational complexity. Main Results. Different data generation processes are used to conduct experiments: group 1, group 2 and group 3. The results show that the proposed model (U Lde -net) can improve SNRs by 10.30 dB, 12.16 dB and 12.61 dB; reduce RMSEs by 9.88 × 10−2, 20.63 × 10−2 and 15.25 × 10−2; and increase P s by 14.77 × 10−2, 27.74 × 10−2 and 21.32 × 10−2. Moreover, the denoising performance after knowledge distillation is further improved. The U Lde -net has parameters of 6.9 K and FLOPs of 6.6 M, which are much smaller than the compared models. Significance. We designed a lightweight model, but also retain adequate ECG denoising performance. We believe that this method can be successfully applied to practical applications under time or memory limits. [ABSTRACT FROM AUTHOR]

One of the greatest triumph of condensed matter physics in the past ten years is the classification of materials by the principle of topology. The existence of topological protected dissipationless surface state makes topological insulators great potential for applications and hotly studied. However, compared with the prosperity of strong topological insulators, theoretical predicted candidate materials and experimental confirmation of weak topological insulators (WTIs) are both extremely rare. By combining systematic first-principles calculation and angle-resolved photoemission spectroscopy measurements, we have studied the electronic structure of the dark surface of the WTI candidate Zintl Ba3Cd2Sb4 and another related material Ba3Cd2As4. The existence of two Dirac surface states on specific side surfaces predicted by theoretical calculations and the observed two band inversions in the Brillouin zone give strong evidence to prove that the Ba3Cd2Sb4 is a WTI. The spectroscopic characterization of this Zintl Ba3Cd2N4 (N = As and Sb) family materials will facilitate applications of their novel topological properties. [ABSTRACT FROM AUTHOR]

Objective. Supraventricular ectopic beats (SVEB) or ventricular ectopic beats (VEB) are common arrhythmia with uncertain occurrence and morphological diversity, so realizing their automatic localization is of great significance in clinical diagnosis. Methods. We propose a modified U-net network: U SV -net, it can simultaneously realize the automatic positioning of VEB and SVEB. The improvement consists of three parts: firstly, we reconstruct part of the convolutional layer in U-net using group convolution to reduce the expression of redundant features. Secondly, a plug-and-play multi-scale 2D deformable convolution module is designed to extract cross-channel features of different scales. Thirdly, in addition to conventional output of U-net, we also compress and output the bottom feature map of U-net, the dual-output is trained through Dice-loss to take into account the learning of high/low resolution features of the model. We used the MIT-BIH arrhythmia database for patient-specific training, and used Sensitivity, Positive prediction rate and F1-scores to evaluate the effectiveness of our method. Main Result. The F1-scores of SVEB and VEB achieve the best results compared with other studies in different testing records. It is worth noting that the F1-scores of SVEB and VEB reached 81.3 and 95.4 in the 24 testing records. Moreover, our method is also at the forefront in Sensitivity and Positive prediction rate. Significance. The method proposed in this paper has great potential in the detection of SVEB and VEB. We anticipate efficiency and accuracy of clinical detection of ectopic beats would be improved. [ABSTRACT FROM AUTHOR]

Background. An electrocardiogram (ECG) is an effective and non-invasive indicator for the detection and prevention of arrhythmia. ECG signals are susceptible to noise contamination, which can lead to errors in ECG interpretation. Therefore, ECG pretreatment is important for accurate analysis. Methods. The ECG data used are from CPSC2018, and the noise signal is from MIT-BIH Noise Stress Test Database. In the experiment, the signal-to-noise ratio (SNR), the root mean square error (RMSE), and the correlation coefficient P are used to evaluate the performance of the network. The method proposed is divided into two stages. In the first stage, a U de -net model is designed for ECG signal denoising to eliminate noise. The DR-net model in the second stage is used to reconstruct the ECG signal and to correct the waveform distortion caused by noise removal in the first stage. In this paper, the U de -net and the DR-net are constructed by the convolution method to achieve end-to-end mapping from noisy ECG signals to clean ECG signals. Result. In SNR, RMSE and P indicators, U de -net + DR-net proposed in this paper can achieve the best performance compared with the other five schemes (FCN, U-net etc). In the three data sets, SNR can be increased by 11.61 dB, 13.71 dB and 14.40 dB and RMSE can be reduced by 10.46 × 10âˆ'2, 21.55 × 10âˆ'2 and 15.98 × 10âˆ'2. Conclusions. Despite the contradictory results, the proposed two-stages method can achieve both the elimination of noise and the preservation of effective details to a large extent of the signals. The proposed method has good application prospects in clinical practice. [ABSTRACT FROM AUTHOR]

We investigate the interface between a three-dimensional Dirac semimetal Cd3As2 and a normal metal via soft-point contact spectroscopy measurement. The superconducting gap features were detected below 3.8 K and 7.1 K in the case of Cd3As2 single crystals sputter-coated with the Pt and Au films, respectively, in the differential conductance dI/dV–V plots of the point contacts. As the applied magnetic field increased, the drop in the zero-bias contact resistance shifted toward lower temperatures. The topologically non-trivial band structure of Cd3As2 is considered to play a crucial role in inducing the superconductivity. Apart from realizing superconductivity in topological materials, our creative approach can be used to investigate possible topological superconductivity and exhibits a high application potential in electronic devices. [ABSTRACT FROM AUTHOR]