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233 results on '"Qian, Chunqi"'

6. Toward Ultra‐High‐Quality‐Factor Wireless Masing Magnetic Resonance Sensing.

Author

Adelabu, Isaiah, Nantogma, Shiraz, Fleischer, Simon, Abdulmojeed, Mustapha, de Maissin, Henri, Schmidt, Andreas B., Lehmkuhl, Soeren, Rosen, Matthew S., Appelt, Stephan, Theis, Thomas, Qian, Chunqi, and Chekmenev, Eduard Y.

Subjects
MAGNETIC resonance, NUCLEAR spin, QUALITY factor, STIMULATED emission, DETECTOR circuits, WIRELESS power transmission, CARDIAC radionuclide imaging
Abstract

It has recently been shown that a bolus of hyperpolarized nuclear spins can yield stimulated emission signals similar in nature to maser signals, potentially enabling new ways of sensing hyperpolarized contrast media, including most notably [1‐13C]pyruvate that is under evaluation in over 50 clinical trials for metabolic imaging of cancer. The stimulated NMR signal emissions lasting for minutes do not require radio‐frequency excitation, offering unprecedented advantages compared to conventional MR sensing. However, creating nuclear spin maser emission is challenging in practice due to stringent fundamental requirements, making practical in vivo applications hardly possible using conventional passive MR detectors. Here, we demonstrate the utility of a wireless NMR maser detector, the quality factor of which was enhanced 22‐fold (to 1,670) via parametric pumping. This active‐feedback technique breaks the intrinsic fundamental limit of NMR detector circuit quality factor. We show the use of parametric pumping to reduce the threshold requirement for inducing nuclear spin masing at 300 MHz resonance frequency in a preclinical MRI scanner. Indeed, stimulated emission from hyperpolarized protons was obtained under highly unfavorable conditions of low magnetic field homogeneity (T2* of 3 ms). Greater gains of the quality factor of the MR detector (up to 1 million) were also demonstrated. [ABSTRACT FROM AUTHOR]

Published
2024
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12. ANP-I: A 28-nm 1.5-pJ/SOP Asynchronous Spiking Neural Network Processor Enabling Sub-0.1-μ J/Sample On-Chip Learning for Edge-AI Applications

Author

Zhang, Jilin, Huo, Dexuan, Zhang, Jian, Qian, Chunqi, Liu, Qi, Pan, Liyang, Wang, Zhihua, Qiao, Ning, Tang, Kea-Tiong, and Chen, Hong

Abstract

Reducing learning energy consumption is critical to edge-artificial intelligence (AI) processors with on-chip learning since on-chip learning energy dominates energy consumption, especially for applications that require long-term learning. To achieve this goal, we optimize a neuromorphic learning algorithm and propose random target window (TW) selection, hierarchical update skip (HUS), and asynchronous time step acceleration (ATSA) to reduce the on-chip learning power consumption. Our approach results in a 28-nm 1.25-mm2 asynchronous neuromorphic processor (ANP-I) with on-chip learning energy per sample less than 15% of inference energy per sample. With all weights randomly initialized, this processor enables on-chip learning for edge-AI tasks such as gesture recognition, keyword spotting, and image classification, consuming sub- $0.1 ~\mu \text{J}$ of learning energy per sample at 0.56 V and 40-MHz frequency while maintaining >92% accuracy for all tasks.

Published
2024
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15. Ultra-Low-Cost Disposable Hand-Held Clinical-Scale Propane Gas Hyperpolarizer for Pulmonary Magnetic Resonance Imaging Sensing

Author

Ariyasingha, Nuwandi M., primary, Samoilenko, Anna, additional, Birchall, Jonathan R., additional, Chowdhury, Md Raduanul H., additional, Salnikov, Oleg G., additional, Kovtunova, Larisa M., additional, Bukhtiyarov, Valerii I., additional, Zhu, David C., additional, Qian, Chunqi, additional, Bradley, Michael, additional, Gelovani, Juri G., additional, Koptyug, Igor V., additional, Goodson, Boyd M., additional, and Chekmenev, Eduard Y., additional

Published
2023
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32. ON THE DIFFERENT VELOCITIES OF INLET BOUNDARY CONDITIONS FOR HUMAN ARM ANALYSIS OF ARTERIAL FLOW USING ONE-WAY FLUID–SOLID COUPLING

Author

Qian Chunqi, Liu Meijun, Quanyu Wu, Pan Lingjiao, and Liu Xiaojie

Subjects
geography, geography.geographical_feature_category, Fluid solid coupling, Human arm, Arterial flow, Biomedical Engineering, Biophysics, Bioengineering, Boundary value problem, Mechanics, Inlet, Geology
Abstract

Simulations for blood hydrodynamic problems have been still largely incomplete despite years of research, especially for the inlet of boundary conditions that served as an essential part in computational fluid dynamics simulations of blood flow in human arteries. In this paper, the four different velocities of inlet boundary conditions were tested and compared in the human arm arterial model developed by us previously. Based on the selected points of nine key areas in the blood model,14 we analyzed the calculation results of pressure and shear stress distributions in detail. Our results show that they are changeable in different [Formula: see text] (different peak velocities of inlet boundary). The results further show that the static pressure of the aortic tree is higher than the static pressure of the branch, while the shear stress of the aortic tree is lower than the shear stress of the branch. On the other hand, the velocities changed in different [Formula: see text], the vessel walls of max total deformation appear in the middle radial obviously, compared with the equivalent and shear stress show at the entrance and bifurcations. In all, the simulation results of the brachial arteries provide the wall deformation, pressure and shear stress characteristics in different [Formula: see text], and offer a new strategy to study the two-way coupling of hemodynamics in the arm arterial model.

Published
2021
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41. Innentitelbild: Toward Ultra‐High‐Quality‐Factor Wireless Masing Magnetic Resonance Sensing (Angew. Chem. 37/2024).

Author

Adelabu, Isaiah, Nantogma, Shiraz, Fleischer, Simon, Abdulmojeed, Mustapha, de Maissin, Henri, Schmidt, Andreas B., Lehmkuhl, Soeren, Rosen, Matthew S., Appelt, Stephan, Theis, Thomas, Qian, Chunqi, and Chekmenev, Eduard Y.

Subjects
STIMULATED emission, NUCLEAR spin, QUALITY factor, RADIATION, DETECTORS
Abstract

The article titled "Toward Ultra-High-Quality-Factor Wireless Masing Magnetic Resonance Sensing" discusses the use of radiofrequency amplification by stimulated emission of radiation (RASER) to create masing of nuclear spin Zeeman energy level transitions. The authors, Eduard Y. Chekmenev et al., demonstrate the effectiveness of an active-feedback wireless NMR masing detector in enhancing the quality factor up to 1,000,000, allowing for the creation of a RASER at 300 MHz that was previously not possible with passive NMR detectors. This active-feedback-circuit approach has the potential to enable RASER sensing in a wide range of in vivo applications. [Extracted from the article]

Published
2024
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