Nonreciprocal entanglement in cavity-magnon optomechanics

Cavity optomechanics, a promising platform to investigate macroscopic quantum effects, has been widely used to study nonreciprocal entanglement with Sagnec effect. Here we propose an alternative way to realize nonreciprocal entanglemment among magnons, photons, and phonons in a hybrid cavity-magnon optomechanics, where magnon Kerr effect is used. We show that the Kerr effect gives rise to a magnon frequency shift and an additional two-magnon effect. Both of them can be tuned from positive to negative via tuning the magectic field direction, leading to nonreciprocity. By tuning system parameters such as magnon frequency detuning or the coefficient of the two-magnon effect, bipartite and tripartite entanglements can be nonreciprocally enhanced. By further studying the defined bidirectional contrast ratio, we find that nonreciprocity in our system can be switch on and off, and can be engineered by the bath temperature. Our proposal not only provides a potential path to demonstrate nonreciprocal entanglement with the magnon Kerr effect, but also opens a direction to engineer and design diverse nonreciprocal devices in hybrid cavity-magnon optomechanics with nonlinear effects.Comment: 8 pages,4 figures. Accepted by Phys. Rev.

A mosaic mutation in the CLCNKB gene causing Bartter syndrome: A case report

BackgroundType III Bartter syndrome (BS) is an autosomal recessive disease caused by mutations in the CLCNKB (chloride voltage-gated channel Kb) gene that encodes CLC-Kb. CLC-Kb is mainly located in the thick ascending limb of Henle's loop and regulates chloride efflux from tubular epithelial cells to the interstitium. Type III BS is characterized by metabolic alkalosis, renal salt wasting, hyperreninemia, and hyperaldosteronism with normal blood pressure.Case presentationWe reported the case of a 3-day-old girl whose initial symptom we diagnosed as jaundice, but we accidentally found metabolic alkalosis. She showed recurrent metabolic alkalosis, hypokalemia, and hypochloremia and also had hyperreninemia and hyperaldosteronism with normal blood pressure. Both oral potassium supplements and potassium infusion therapy were unable to entirely restore the electrolyte imbalance. She was suspected of Bartter syndrome and genetic tests were performed on her and her parents. Next-generation sequencing identified CLCNKB gene mutation including heterozygous mutation c.1257delC (p.M421Cfs*58) and a low-level mutation c.595G > T (p.E199*); both mutations were also verified in the parents.ConclusionWe reported the case of a classic Bartter syndrome in a newborn with a heterozygous frameshift mutation and a mosaic non-sense mutation in the CLCNKB gene

Cyclic Delay-Doppler Shift: A Simple Transmit Diversity Technique for Delay-Doppler Waveforms in Doubly Selective Channels

Delay-Doppler waveform design has been considered as a promising solution to achieve reliable communication under high-mobility channels for the space-air-ground-integrated networks (SAGIN). In this paper, we introduce the cyclic delay-Doppler shift (CDDS) technique for delay-Doppler waveforms to extract transmit diversity in doubly selective channels. Two simple CDDS schemes, named time-domain CDDS (TD-CDDS) and modulation-domain CDDS (MD-CDDS), are proposed in the setting of multiple-input multiple-output (MIMO). We demonstrate the applications of CDDS on two representative delay-Doppler waveforms, namely orthogonal time frequency space (OTFS) and affine frequency division multiplexing (AFDM), by deriving their corresponding CDDS matrices. Furthermore, we prove theoretically and experimentally that CDDS can provide OTFS and AFDM with full transmit diversity gain on most occasions

A Phase-Coded Time-Domain Interleaved OTFS Waveform with Improved Ambiguity Function

Integrated sensing and communication (ISAC) is a significant application scenario in future wireless communication networks, and sensing capability of a waveform is always evaluated by the ambiguity function. To enhance the sensing performance of the orthogonal time frequency space (OTFS) waveform, we propose a novel time-domain interleaved cyclic-shifted P4-coded OTFS (TICP4-OTFS) with improved ambiguity function. TICP4-OTFS can achieve superior autocorrelation features in both the time and frequency domains by exploiting the multicarrier-like form of OTFS after interleaved and the favorable autocorrelation attributes of the P4 code. Furthermore, we present the vectorized formulation of TICP4-OTFS modulation as well as its signal structure in each domain. Numerical simulations show that our proposed TICP4-OTFS waveform outperforms OTFS with a narrower mainlobe as well as lower and more distant sidelobes in terms of delay and Doppler-dimensional ambiguity functions, and an instance of range estimation using pulse compression is illustrated to exhibit the proposed waveform\u2019s greater resolution. Besides, TICP4-OTFS achieves better performance of bit error rate for communication in low signal-to-noise ratio (SNR) scenarios.Comment: This paper has been accepted by 2023 IEEE Globecom Workshops (GC Wkshps): Workshop on Integrated Sensing and Communications for Internet of Thing

Defect identification in adhesive structures using multi-Feature fusion convolutional neural network

The interface-debonding defects of adhesive bonding structures may cause a reduction in bonding strength, which in turn affects the bonding quality of adhesive bonding samples. Hence, defect recognition in adhesive bonding structures is particularly important. In this study, a terahertz (THz) wave was used to analyze bonded structure samples, and a multi-feature fusion convolutional neural network (CNN) was used to identify the defect waveforms. The pooling method of the squeeze-and-excitation (SE) attention mechanism was optimized, defect feature weights were adaptively assigned, and feature fusion was conducted using automatic label net-works to segment the THz waveforms in the adhesive bonding area with fine granularity waveforms as an input to the multi-channel CNN. The results revealed that the speed of the THz waveform labeling with the automatic labeling network was 10 times higher than that with traditional methods, and the defect-recognition accuracy of the defect-recognition network constructed in this study was up to 99.28%. The F1-score was 99.73%, and the lowest pre-embedded defect recognition error rate of the generalization experiment samples was 0.27%

TubeR: Tubelet Transformer for Video Action Detection

We propose TubeR: a simple solution for spatio-temporal video action detection. Different from existing methods that depend on either an off-line actor detector or hand-designed actor-positional hypotheses like proposals or anchors, we propose to directly detect an action tubelet in a video by simultaneously performing action localization and recognition from a single representation. TubeR learns a set of tubelet-queries and utilizes a tubelet-attention module to model the dynamic spatio-temporal nature of a video clip, which effectively reinforces the model capacity compared to using actor-positional hypotheses in the spatio-temporal space. For videos containing transitional states or scene changes, we propose a context aware classification head to utilize short-term and long-term context to strengthen action classification, and an action switch regression head for detecting the precise temporal action extent. TubeR directly produces action tubelets with variable lengths and even maintains good results for long video clips. TubeR outperforms the previous state-of-the-art on commonly used action detection datasets AVA, UCF101-24 and JHMDB51-21

Evaluation of an identification method for the SARS-CoV-2 Delta variant based on the amplification-refractory mutation system

The Delta variant of SARS-CoV-2 dominated the COVID-19 pandemic due to its high viral replication capacity and immune evasion, causing massive outbreaks of cases, hospitalizations, and deaths. Currently, variant identification is performed mainly by sequencing. However, the high requirements for equipment and operators as well as its high cost have limited its application in underdeveloped regions. To achieve an economical and rapid method of variant identification suitable for undeveloped areas, we applied an amplification-refractory mutation system (ARMS) based on PCR for the detection of novel coronavirus variants. The results showed that this method could be finished in 90 min and detect as few as 500 copies/mL and not react with SARS-Coronavirus, influenza A H1N1(2009), and other cross-pathogens or be influenced by fresh human blood, α- interferon, and other interfering substances. In a set of double-blind trials, tests of 262 samples obtained from patients confirmed with Delta variant infection revealed that our method was able to accurately identify the Delta variant with high sensitivity and specificity. In conclusion, the ARMS-PCR method applied in Delta variant identification is rapid, sensitive, specific, economical, and suitable for undeveloped areas. In our future study, ARMS-PCR will be further applied in the identification of other variants, such as Omicron