Electrical Manipulation of Topological Phases in a Quantum Anomalous Hall Insulator.

Quantum anomalous Hall phases arising from the inverted band topology in magnetically doped topological insulators have emerged as an important subject of research for quantization at zero magnetic fields. Though necessary for practical implementation, sophisticated electrical control of molecular beam epitaxy (MBE)-grown quantum anomalous Hall matter have been stymied by growth and fabrication challenges. Here, a novel procedure is demonstrated, employing a combination of thin-film deposition and 2D material stacking techniques, to create dual-gated devices of the MBE-grown quantum anomalous Hall insulator, Cr-doped (Bi,Sb)2 Te3 . In these devices, orthogonal control over the field-induced charge density and the electric displacement field is demonstrated. A thorough examination of material responses to tuning along each control axis is presented, realizing magnetic property control along the former and a novel capability to manipulate the surface exchange gap along the latter. Through electrically addressing the exchange gap, the capabilities to either strengthen the quantum anomalous Hall state or suppress it entirely and drive a topological phase transition to a trivial state are demonstrated. The experimental result is explained using first principle theoretical calculations, and establishes a practical route for in situ control of quantum anomalous Hall states and topology.

Dual gating myocardial perfusion SPECT denoising using a conditional generative adversarial network.

PURPOSE: Dual respiratory-cardiac gating reduces respiratory and cardiac motion blur in myocardial perfusion single-photon emission computed tomography (MP-SPECT). However, image noise is increased as detected counts are reduced in each dual gate (DG). We aim to develop a denoising method for dual gating MP-SPECT images using a 3D conditional generative adversarial network (cGAN). METHODS: Twenty extended cardiac-torso phantoms with various 99m Tc-sestamibi distributions, defect characteristics, and body and organ sizes were used in the simulation, modeling six respiratory and eight cardiac gates (CGs), that is, 48 DGs for ordered subset expectation maximization reconstruction. Twenty clinical 99m Tc-sestamibi SPECT/CT datasets were re-binned into 7 respiratory gates and 8 CGs, that is, 56 DGs for maximum likelihood expectation maximization reconstruction. We evaluated the use of (i) phantoms' own datasets (patient-specific denoising [PD]) or other phantoms' datasets (cross-patient denoising) for training; (ii) the CG or the static (non-gated [NG]) data as the training references for cGAN; and (iii) cGAN as compared to conventional 3D post-reconstruction filtering, cardiac gating methods, and convolutional neural network. Normalized mean squared error, noise as assessed by normalized standard deviation, spatial blurring measured as the full-width-at-half-maximum of left ventricular wall, ejection fraction, joint correlation histogram, and defect size were analyzed as metrics of image quality. RESULTS: Training using patients' own dataset is superior to conventional training based on other patients' data. Using CG image as training reference provides a better trade-off in terms of noise and image blur as compared to the use of NG. cGAN-CG-PD provides superior performance as compared to other denoising methods for all physical and diagnostic indices evaluated in both simulation and clinical studies. CONCLUSIONS: cGAN denoising is promising for dual gating MP-SPECT based on the metrics mentioned earlier.

Confining Fluorescent Probes in Nanochannels to Construct Reusable Nanosensors for Ion Current and Fluorescence Dual Gating.

Here, we confined fluorescent probes to solid nanochannels to construct nanosensors, which not only significantly improved the reusability of the molecular probes, but also achieved ion current and fluorescence dual gating for more reliable detection. The combination of optical and electrical modalities can provide comprehensive spatiotemporal information that can be used to elucidate the sensing mechanism within the nanochannel. As a proof-of-concept experiment, fluorescein isothiocyanate (FITC)−hydrazine (N2H4) was selected to modify nanochannels for the effective detection of Hg2+. Based on spirolactam opening tactics, the system synergistically alters the surface charge and fluorescence intensity in response to Hg2+, establishing a dual open state of current and fluorescence. The newly prepared nanosensor exhibited a fast response (<1 min), high sensitivity, and selectivity towards Hg2+. Importantly, the nanodevice could be recovered by simple N2H4 treatment. Such sensing behavior could be used to implement optoelectronic dual-output XOR logical gates under the management of Hg2+ and N2H4. This strategy is anticipated to find broad applications in other nanochannel-based systems for various sensing applications used for monitoring of pollutants, food additives, and biomolecules.

A Computational Framework for Data Fusion in MEMS-Based Cardiac and Respiratory Gating.

Dual cardiac and respiratory gating is a well-known technique for motion compensation in nuclear medicine imaging. In this study, we present a new data fusion framework for dual cardiac and respiratory gating based on multidimensional microelectromechanical (MEMS) motion sensors. Our approach aims at robust estimation of the chest vibrations, that is, high-frequency precordial vibrations and low-frequency respiratory movements for prospective gating in positron emission tomography (PET), computed tomography (CT), and radiotherapy. Our sensing modality in the context of this paper is a single dual sensor unit, including accelerometer and gyroscope sensors to measure chest movements in three different orientations. Since accelerometer- and gyroscope-derived respiration signals represent the inclination of the chest, they are similar in morphology and have the same units. Therefore, we use principal component analysis (PCA) to combine them into a single signal. In contrast to this, the accelerometer- and gyroscope-derived cardiac signals correspond to the translational and rotational motions of the chest, and have different waveform characteristics and units. To combine these signals, we use independent component analysis (ICA) in order to obtain the underlying cardiac motion. From this cardiac motion signal, we obtain the systolic and diastolic phases of cardiac cycles by using an adaptive multi-scale peak detector and a short-time autocorrelation function. Three groups of subjects, including healthy controls (n = 7), healthy volunteers (n = 12), and patients with a history of coronary artery disease (n = 19) were studied to establish a quantitative framework for assessing the performance of the presented work in prospective imaging applications. The results of this investigation showed a fairly strong positive correlation (average r = 0.73 to 0.87) between the MEMS-derived (including corresponding PCA fusion) respiration curves and the reference optical camera and respiration belt sensors. Additionally, the mean time offset of MEMS-driven triggers from camera-driven triggers was 0.23 to 0.3 ± 0.15 to 0.17 s. For each cardiac cycle, the feature of the MEMS signals indicating a systolic time interval was identified, and its relation to the total cardiac cycle length was also reported. The findings of this study suggest that the combination of chest angular velocity and accelerations using ICA and PCA can help to develop a robust dual cardiac and respiratory gating solution using only MEMS sensors. Therefore, the methods presented in this paper should help improve predictions of the cardiac and respiratory quiescent phases, particularly with the clinical patients. This study lays the groundwork for future research into clinical PET/CT imaging based on dual inertial sensors.

Scattering matrix imaging pulse design for real-time respiration and cardiac motion monitoring.

PURPOSE: The scattering matrix (S-matrix) of a parallel transmit (pTx) coil is sensitive to physiological motion but requires additional monitoring RF pulses to be measured. In this work, we present and evaluate pTx RF pulse designs that simultaneously excite for imaging and measure the S-matrix to generate real-time motion signals without prolonging the image sequence. THEORY AND METHODS: Three pTx waveforms for measuring the S-matrix were identified and superimposed onto the imaging excitation RF pulses: (1) time division multiplexing, (2) frequency division multiplexing, and (3) code division multiplexing. These 3 methods were evaluated in healthy volunteers for scattering sensitivity and image artefacts. The S-matrix and real-time motion signals were calculated on the image calculation environment of the MR scanner. Prospective cardiac triggers were identified in early systole as a high rate of change of the cardiac motion signal. Monitoring accuracy was compared against electrocardiogram or the imaged diaphragm position. RESULTS: All 3 monitoring approaches measure the S-matrix during image excitation with quality correlated to input power. No image artefacts were observed for frequency multiplexing, and low energy artefacts were observed in the other methods. The accuracy of the achieved prospective cardiac gating was 15 ± 16 ms for breath hold and 24 ± 17 ms during free breathing. The diaphragm position prediction accuracy was 1.3 ± 0.9 mm. In all volunteers, good quality cine images were acquired for breath hold scans and dual gated CINEs were demonstrated. CONCLUSION: The S-matrix can be measured during image excitation to generate real-time cardiac and respiratory motion signals for prospective gating. No artefacts are introduced when frequency division multiplexing is used.