As the important electric loss of a graphene resonator, intrinsic current loss has received increasing attention, but the existing research is limited to qualitative analysis and approximate calculation. Based on the microscopic behavior of carriers, we have accurately established the calculation model of induced current loss, which is in good agreement with the existing experimental results. Compared with the previous models, the model in this work can not only fit the inverse V-shaped Q − Vdc curve well but also be compatible with the V-shaped Q − Vdc curve, which is beyond the reach of the previous models. In addition, the calculation results show that selecting the appropriate gate voltage combination when stimulating the graphene resonator can increase the quality factor by nearly 1–2 orders of magnitude. Furthermore, we reasonably explain the importance of DC gate voltage applied in the experiment compared with the case of non-DC gate voltage. This work realizes the accurate calculation of intrinsic current loss and is of great significance for reducing the intrinsic current loss in the practical application of graphene resonators.
Stressful life events induce abnormalities in emotional and cognitive behaviour. The endogenous opioid system plays an essential role in stress adaptation and coping strategies. In particular, the µ-opioid receptor (μR), one of the major opioid receptors, strongly influences memory processing in that alterations in μR signalling are associated with various neuropsychiatric disorders. However, it remains unclear whether μR signalling contributes to memory impairments induced by acute stress. Here, we utilized pharmacological methods and cell-type-selective/non-cell-type-selective μR depletion approaches combined with behavioural tests, biochemical analyses, and in vitro electrophysiological recordings to investigate the role of hippocampal μR signalling in memory-retrieval impairment induced by acute elevated platform (EP) stress in mice. Biochemical and molecular analyses revealed that hippocampal μRs were significantly activated during acute stress. Blockage of hippocampal μRs, non-selective deletion of μRs or selective deletion of μRs on GABAergic neurons (μRGABA) reversed EP-stress-induced impairment of memory retrieval, with no effect on the elevation of serum corticosterone after stress. Electrophysiological results demonstrated that stress depressed hippocampal GABAergic synaptic transmission to CA1 pyramidal neurons, thereby leading to excitation/inhibition (E/I) imbalance in a μRGABA-dependent manner. Pharmaceutically enhancing hippocampal GABAA receptor-mediated inhibitory currents in stressed mice restored their memory retrieval, whereas inhibiting those currents in the unstressed mice mimicked the stress-induced impairment of memory retrieval. Our findings reveal a novel pathway in which endogenous opioids recruited by acute stress predominantly activate μRGABA to depress GABAergic inhibitory effects on CA1 pyramidal neurons, which subsequently alters the E/I balance in the hippocampus and results in impairment of memory retrieval.
In aviation, aerospace, and other fields, nanomechanical resonators could offer excellent sensing performance. Among these, graphene resonators, as a new sensitive unit, are expected to offer very high mass and force sensitivity due to their extremely thin thickness. However, at present, the quality factor of graphene resonators at room temperature is generally low, which limits the performance improvement and further application of graphene resonators. Enhancing the quality factor of graphene resonators has emerged as a pressing research concern. In a previous study, we have proposed a new mechanism to reduce the energy dissipation of graphene resonators by utilizing phononic crystal soft-supported structures. We verified its feasibility through theoretical analysis and simulations. This article focuses on the fabrication of a phononic crystal soft-supported graphene resonator. In order to address the issues of easy fracture, deformation, and low success rate in the fabrication of phononic crystal soft-supported graphene resonators, we have studied key processes for graphene suspension release and focused ion beam etching. Through parameter optimization, finally, we have obtained phononic crystal soft-supported graphene resonators with varying cycles and pore sizes. Finally, we designed an optical excitation and detection platform based on Fabry–Pérot interference principle and explored the impact of laser power and spot size on phononic crystal soft-supported graphene resonators.
SaaS (software as a service), the new software application pattern has got wide attraction in both industry and academia. But transaction processing is a problem that prevents SaaS from wide spreading. To solve the problem, this paper proposes A business level compensation mechanism for multitenancy SaaS application transaction processing. The mechanism supports flexible and customizable transaction process through an extended compensation model with compensation events and compensation process. The implementation of the compensation mechanism, including the coordination logic, algorithms, and a reference framework are also addressed.
The sculpture of Nanfeng Nuo mask originated in the Han Dynasty, developed in the Tang and Song Dynasties, and prospered in the Ming and Qing Dynasties. The carving art has been passed down to this day. The sculptures of Nanfeng Nuo masks are famous for their simple and profound, vivid shapes and delicate techniques. This article first stated that under the background of AR technology, in terms of digital protection mode, limited by ideological understanding and technology, the current digital protection of Chinese traditional culture is still at the stage of digital information collection and preservation. How to enrich and perfect the existing digital protection mode with new digital technology is an urgent problem to be solved in the new era. Taking the Nanfeng Nuo mask as an example, this research analyzes the inheritance dilemma of the Nanfeng Nuo mask wood carving and the modern and innovative protection model through the reading of historical documents, field inspections of existing wood carvings, survey visits to the protection status, and understanding of digital technology. Through the fuzzy KNN algorithm and AR compared to the database, the various databases are related to form a complete protection system; in the "live inheritance protection mode", AR technology is proposed as the basic technology, and AR image acquisition technology and AR display technology are proposed. , AR human-computer interaction technology and digital protection mode are combined, and then a digital protection platform based on AR technology is designed to achieve the realization of the live inheritance mode by the way audiences participate in the use of the digital protection platform. Experimental research results show that people in their 30s to 40s may take a long time to receive and learn when facing a new interactive operating system, but now due to the popularity of social software such as WeChat, the 30 to 40 age group 24.4% of the population can also perform basic operations, which provides a prerequisite for the use of AR technology to digitize the Nanfeng Nuo mask.
Geomagnetic field is one of the geophysical fields of the Earth and can be used to limit the error accumulation of the inertial navigation system (INS). A geomagnetic aided navigation system is proposed in the paper. Two alternate processes are designed in the system - the match and the filter. In the former part, a contour constraint based correlation method is used to eliminate the initial position error of the system, greatly reducing the computational burden of the whole system. Heading error can be effectively estimated by an iterative closest point (ICP) algorithm. In the filter part, a linear Kalman filter is designed to update INS continuously. Position measurements are given by a ldquonearest pointrdquo principle and the position error caused by this principle does not accumulate with time, which leads to a nearest point based Kalman filter (NPKF). Geomagnetic anomaly maps are used to test the proposed system, and good performance is observed.
We present an analysis on the determination of the energy gap in biased bilayer graphene using tunneling measurements, report our experimental results obtained from planar tunneling spectroscopy, and compare them with those from electrical transport measurements. Bilayer graphene flakes were prepared by exfoliating from bulk graphite onto SiO2 thermally grown on a doped Si substrate. Due to the low carrier density of bilayer graphene, the Fermi level and electronic structure are expected to be highly sensitive to tunnel bias-induced charging, which is neglected in traditional tunnel junctions. We found that the tunneling signal generally exhibited a “V”-shaped tunneling conductance background that did not shift with back gate voltage, possibly due to a two-step tunneling process. We observed a tunable suppression in the tunneling conductance that follows theoretical predictions for a band gap in biased bilayer graphene. We explore the evolution of the band gap by tuning the electric field and charge carrier density produced by the tunneling bias and back gate, and compare experimental results with numerical simulations. Finally, we compare these findings with transport measurements of top- and bottom-gated bilayer graphene field effect transistors featuring similar gate dielectrics.
Fiber-optic Fabry-Perot interference (FPI) sensors offer remarkable advantages in sensing applications, particularly in harsh environments, while errors from measurement and demodulation can deteriorate the sensing precision. To better understand the error origin, a systematic error model based on First Principles is established, including random and bias errors. An optimized cavity length demodulation (CLD) method, based on the neglected imperfect incidence spectrum, is proposed for cavity length extraction and spectrum decomposition. Demodulation experiments with a fixed cavity length were conducted on the graphene fiber-optic FPI sensor. The validity of the error model and optimized CLD method was verified. The random error mainly originates from the random wander of interference peak around the resolution of the spectrum analyzer, while the bias error mainly originates from the imperfect incidence spectrum. The graphene FPI sensor and optimized CLD method were applied to pressure sensing. The bias error was effectively eliminated and the achieved random error was 20 times lower than that of the P-P method. These findings in this paper may provide valuable insights and solutions for the FPI sensor applications.
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