Time-resolved magnetic sensing with electronic spins in diamond

Quantum probes can measure time-varying fields with high sensitivity and spatial resolution, enabling the study of biological, material, and physical phenomena at the nanometer scale. In particular, nitrogen-vacancy centers in diamond have recently emerged as promising sensors of magnetic and electric fields. Although coherent control techniques have measured the amplitude of constant or oscillating fields, these techniques are not suitable for measuring time-varying fields with unknown dynamics. Here we introduce a coherent acquisition method to accurately reconstruct the temporal profile of time-varying fields using Walsh sequences. These decoupling sequences act as digital filters that efficiently extract spectral coefficients while suppressing decoherence, thus providing improved sensitivity over existing strategies. We experimentally reconstruct the magnetic field radiated by a physical model of a neuron using a single electronic spin in diamond and discuss practical applications. These results will be useful to implement time-resolved magnetic sensing with quantum probes at the nanometer scale.Comment: 8+12 page

International Telecommunication Union-Radiocommunication Sector (ITU-R) P.837-6 and P.837-7 performance to estimate Indonesian rainfall

The cognitive radio technology can improve the efficiency of spectrum utilization byproviding dynamic spectrum access to unoccupied frequency bands. Spectrum sensing is one of the key technologies of cognitive radio networks. The spectrum sensing performance of cognitive radio networks will be greatly reduced in the low SNR environment, especially when using energy detection. Because the stochastic resonance system can improve the energy detection system output SNR .To improve the spectrum sensing performance of cognitive radio networks in the low SNR environment, the stochastic resonance of the single-mode nonlinear optical system is applied to spectrum sensing based on the energy detection method in this paper. The simulation results show that in the low SNR environment, the energy detection based on stochastic resonance of the single-mode nonlinear optical system has better performance than traditional energy detection

Spectrum Sensing Based on Monostable Stochastic Resonance in Cognitive Radio Networks

The cognitive radio technology can provide dynamic spectrum access and improve the efficiency of spectrum utilization. Spectrum sensing is one of the key technologies of cognitive radio networks. The spectrum sensing performance of cognitive radio networks will be greatly reduced in the low SNR environment, especially when using energy detection. Due to the monostable stochastic resonance system can improve the energy detection system output SNR, a monostable stochastic resonanceis applied to spectrum sensing based on the energy detection method of cognitive radio networks in this paper. The simulation results show that in the low SNR environment, when the false alarm probability is constant, the proposed spectrum sensing based on monostable stochastic resonance has better performance than traditional energy detection

Accelerated High-Resolution Photoacoustic Tomography via Compressed Sensing

Current 3D photoacoustic tomography (PAT) systems offer either high image quality or high frame rates but are not able to deliver high spatial and temporal resolution simultaneously, which limits their ability to image dynamic processes in living tissue. A particular example is the planar Fabry-Perot (FP) scanner, which yields high-resolution images but takes several minutes to sequentially map the photoacoustic field on the sensor plane, point-by-point. However, as the spatio-temporal complexity of many absorbing tissue structures is rather low, the data recorded in such a conventional, regularly sampled fashion is often highly redundant. We demonstrate that combining variational image reconstruction methods using spatial sparsity constraints with the development of novel PAT acquisition systems capable of sub-sampling the acoustic wave field can dramatically increase the acquisition speed while maintaining a good spatial resolution: First, we describe and model two general spatial sub-sampling schemes. Then, we discuss how to implement them using the FP scanner and demonstrate the potential of these novel compressed sensing PAT devices through simulated data from a realistic numerical phantom and through measured data from a dynamic experimental phantom as well as from in-vivo experiments. Our results show that images with good spatial resolution and contrast can be obtained from highly sub-sampled PAT data if variational image reconstruction methods that describe the tissues structures with suitable sparsity-constraints are used. In particular, we examine the use of total variation regularization enhanced by Bregman iterations. These novel reconstruction strategies offer new opportunities to dramatically increase the acquisition speed of PAT scanners that employ point-by-point sequential scanning as well as reducing the channel count of parallelized schemes that use detector arrays.Comment: submitted to "Physics in Medicine and Biology

Brain image clustering by wavelet energy and CBSSO optimization algorithm

Previously, the diagnosis of brain abnormality was significantly important in the saving of social and hospital resources. Wavelet energy is known as an effective feature detection which has great efficiency in different utilities. This paper suggests a new method based on wavelet energy to automatically classify magnetic resonance imaging (MRI) brain images into two groups (normal and abnormal), utilizing support vector machine (SVM) classification based on chaotic binary shark smell optimization (CBSSO) to optimize the SVM weights. The results of the suggested CBSSO-based KSVM are compared favorably to several other methods in terms of better sensitivity and authenticity. The proposed CAD system can additionally be utilized to categorize the images with various pathological conditions, types, and illness modes

Monitoring Keap1-Nrf2 interactions in single live cells

AbstractThe transcription factor NF-E2 p45-related factor 2 (Nrf2) and its negative regulator Kelch-like ECH associated protein 1 (Keap1) control the expression of nearly 500 genes with diverse cytoprotective functions. Keap1, a substrate adaptor protein for Cullin3/Rbx1 ubiquitin ligase, normally continuously targets Nrf2 for degradation, but loses this ability in response to electrophiles and oxidants (termed inducers). Consequently, Nrf2 accumulates and activates transcription of its downstream target genes. Many inducers are phytochemicals, and cruciferous vegetables represent one of the richest sources of inducer activity among the most commonly used edible plants. Here we summarize the discovery of the isothiocyanate sulforaphane as a potent inducer which reacts with cysteine sensors of Keap1, leading to activation of Nrf2. We then describe the development of a quantitative Förster resonance energy transfer (FRET)-based methodology combined with multiphoton fluorescence lifetime imaging microscopy (FLIM) to investigate the interactions between Keap1 and Nrf2 in single live cells, and the effect of sulforaphane, and other cysteine-reactive inducers, on the dynamics of the Keap1–Nrf2 protein complex. We present the experimental evidence for the “cyclic sequential attachment and regeneration” or “conformation cycling” model of Keap1-mediated Nrf2 degradation. Finally, we discuss the implications of this mode of regulation of Nrf2 for achieving a fine balance under normal physiological conditions, and the consequences and mechanisms of disrupting this balance for tumor biology

Detector Description and Performance for the First Coincidence Observations between LIGO and GEO

For 17 days in August and September 2002, the LIGO and GEO interferometer gravitational wave detectors were operated in coincidence to produce their first data for scientific analysis. Although the detectors were still far from their design sensitivity levels, the data can be used to place better upper limits on the flux of gravitational waves incident on the earth than previous direct measurements. This paper describes the instruments and the data in some detail, as a companion to analysis papers based on the first data.Comment: 41 pages, 9 figures 17 Sept 03: author list amended, minor editorial change

Wide-band Unambiguous Quantum Sensing via Geodesic Evolution

We present a quantum sensing technique that utilizes a sequence of $\pi$ pulses to cyclically drive the qubit dynamics along a geodesic path of adiabatic evolution. This approach effectively suppresses the effects of both decoherence noise and control errors while simultaneously removing unwanted resonance terms, such as higher harmonics and spurious responses commonly encountered in dynamical decoupling control. As a result, our technique offers robust, wide-band, unambiguous, and high-resolution quantum sensing capabilities for signal detection and individual addressing of quantum systems, including spins. To demonstrate its versatility, we showcase successful applications of our method in both low-frequency and high-frequency sensing scenarios. The significance of this quantum sensing technique extends to the detection of complex signals and the control of intricate quantum environments. By enhancing detection accuracy and enabling precise manipulation of quantum systems, our method holds considerable promise for a variety of practical applications