Long-term Blood Pressure Prediction with Deep Recurrent Neural Networks

Existing methods for arterial blood pressure (BP) estimation directly map the input physiological signals to output BP values without explicitly modeling the underlying temporal dependencies in BP dynamics. As a result, these models suffer from accuracy decay over a long time and thus require frequent calibration. In this work, we address this issue by formulating BP estimation as a sequence prediction problem in which both the input and target are temporal sequences. We propose a novel deep recurrent neural network (RNN) consisting of multilayered Long Short-Term Memory (LSTM) networks, which are incorporated with (1) a bidirectional structure to access larger-scale context information of input sequence, and (2) residual connections to allow gradients in deep RNN to propagate more effectively. The proposed deep RNN model was tested on a static BP dataset, and it achieved root mean square error (RMSE) of 3.90 and 2.66 mmHg for systolic BP (SBP) and diastolic BP (DBP) prediction respectively, surpassing the accuracy of traditional BP prediction models. On a multi-day BP dataset, the deep RNN achieved RMSE of 3.84, 5.25, 5.80 and 5.81 mmHg for the 1st day, 2nd day, 4th day and 6th month after the 1st day SBP prediction, and 1.80, 4.78, 5.0, 5.21 mmHg for corresponding DBP prediction, respectively, which outperforms all previous models with notable improvement. The experimental results suggest that modeling the temporal dependencies in BP dynamics significantly improves the long-term BP prediction accuracy.Comment: To appear in IEEE BHI 201

Determining layer number of two dimensional flakes of transition-metal dichalcogenides by the Raman intensity from substrate

Transition-metal dichalcogenide (TMD) semiconductors have been widely studied due to their distinctive electronic and optical properties. The property of TMD flakes is a function of its thickness, or layer number (N). How to determine N of ultrathin TMDs materials is of primary importance for fundamental study and practical applications. Raman mode intensity from substrates has been used to identify N of intrinsic and defective multilayer graphenes up to N=100. However, such analysis is not applicable for ultrathin TMD flakes due to the lack of a unified complex refractive index ($\tilde{n}$) from monolayer to bulk TMDs. Here, we discuss the N identification of TMD flakes on the SiO$_2$/Si substrate by the intensity ratio between the Si peak from 100-nm (or 89-nm) SiO$_2$/Si substrates underneath TMD flakes and that from bare SiO$_2$/Si substrates. We assume the real part of $\tilde{n}$ of TMD flakes as that of monolayer TMD and treat the imaginary part of $\tilde{n}$ as a fitting parameter to fit the experimental intensity ratio. An empirical $\tilde{n}$, namely, $\tilde{n}_{eff}$, of ultrathin MoS$_{2}$, WS$_{2}$ and WSe$_{2}$ flakes from monolayer to multilayer is obtained for typical laser excitations (2.54 eV, 2.34 eV, or 2.09 eV). The fitted $\tilde{n}_{eff}$ of MoS$_{2}$ has been used to identify N of MoS$_{2}$ flakes deposited on 302-nm SiO$_2$/Si substrate, which agrees well with that determined from their shear and layer-breathing modes. This technique by measuring Raman intensity from the substrate can be extended to identify N of ultrathin 2D flakes with N-dependent $\tilde{n}$ . For the application purpose, the intensity ratio excited by specific laser excitations has been provided for MoS$_{2}$, WS$_{2}$ and WSe$_{2}$ flakes and multilayer graphene flakes deposited on Si substrates covered by 80-110 nm or 280-310 nm SiO$_2$ layer.Comment: 10 pages, 4 figures. Accepted by Nanotechnolog

Power-Law Decay of Standing Waves on the Surface of Topological Insulators

We propose a general theory on the standing waves (quasiparticle interference pattern) caused by the scattering of surface states off step edges in topological insulators, in which the extremal points on the constant energy contour of surface band play the dominant role. Experimentally we image the interference patterns on both Bi$_2$Te$_3$ and Bi$_2$Se$_3$ films by measuring the local density of states using a scanning tunneling microscope. The observed decay indices of the standing waves agree excellently with the theoretical prediction: In Bi$_2$Se$_3$, only a single decay index of -3/2 exists; while in Bi$_2$Te$_3$ with strongly warped surface band, it varies from -3/2 to -1/2 and finally to -1 as the energy increases. The -1/2 decay indicates that the suppression of backscattering due to time-reversal symmetry does not necessarily lead to a spatial decay rate faster than that in the conventional two-dimensional electron system. Our formalism can also explain the characteristic scattering wave vectors of the standing wave caused by non-magnetic impurities on Bi$_2$Te$_3$.Comment: 4 pages, 3 figure

CO2Vec: Embeddings of co-ordered networks based on mutual reinforcement

National Research Foundation (NRF) Singapore under International Research Centres in Singapore Funding Initiativ

Preparation and characterization of hexadecyltrimethylammonium bromide modified nanocrystalline cellulose / graphene oxide composite thin film and its potential in sensing copper ion using surface plasmon resonance technique

In this study, the preparation of hexadecyltrimethylammonium bromide modified nanocrystalline cellulose/graphene oxide composite (CTA-NCC/GO) solution under mild condition has been described. The CTA-NCC/GO thin film then was prepared by spin coating technique. Moreover, the CTA-NCC/GO thin film was characterized by Fourier transform infrared spectroscopy (FTIR) and atomic force microscopy (AFM) for the structural properties while the optical properties were characterized by ultraviolet-visible (UV–vis). FTIR confirmed the functional group that is contained in CTA-NCC/GO thin film and the surface morphology obtained from AFM results showed that the thin film is homogenous. The UV–vis analysis also showed that CTA-NCC/GO thin film has high absorption with optical band gap of 4.00 eV. Furthermore, the CTA-NCC/GO thin film has been studied to be incorporated with surface plasmon resonance spectroscopy (SPR) to detect copper ion. The SPR results showed that copper ion can be detected as low as 0.01 ppm using this thin film