Magnon-polaritons are hybrid light-matter quasiparticles originating from the strong coupling between magnons and photons. They have emerged as a potential candidate for implementing quantum ...transducers and memories. Owing to the dampings of both photons and magnons, the polaritons have limited lifetimes. However, stationary magnon-polariton states can be reached by a dynamical balance between pumping and losses, so the intrinsically nonequilibrium system may be described by a non-Hermitian Hamiltonian. Here we design a tunable cavity quantum electrodynamics system with a small ferromagnetic sphere in a microwave cavity and engineer the dissipations of photons and magnons to create cavity magnon-polaritons which have non-Hermitian spectral degeneracies. By tuning the magnon-photon coupling strength, we observe the polaritonic coherent perfect absorption and demonstrate the phase transition at the exceptional point. Our experiment offers a novel macroscopic quantum platform to explore the non-Hermitian physics of the cavity magnon-polaritons.
Effective hemostasis is vital to reduce the pain and mortality of patients, and the research and development of hemostatic materials are prerequisite for effective hemostasis. Chitosan (CS), with ...good biodegradability, biocompatibility and non-toxicity, has been widely applied in bio-medicine, the chemical industry, the food industry and cosmetics. The excellent hemostatic properties of CS have been extensively studied. As a result, chitosan-based composite hemostatic materials have been emerging. In this review, the hemostatic mechanism of chitosan is briefly discussed, and then the progress of research on chitosan-based composite hemostatic materials with multiple forms such as films, sponges, hydrogels, particles and fibers are introduced. Finally, future perspectives of chitosan-based composite hemostatic materials are given. The objective of this review is to provide a reference for further research and development of effective hemostatic materials.
This paper introduces a novel deep learning-based algorithm that integrates a long short-term memory (LSTM)-based auto-encoder (AE) network with support vector machine (SVM) for electrocardiogram ...(ECG) arrhythmias classification. The LSTM-based AE network (LSTM-AE) is used to learn the features from ECG arrhythmias signals, and the SVM is used to classify those signals from the learned features. The LSTM-AE consists of an encoder model, which extracts high-level feature information from ECG arrhythmias signals through LSTM network, and a decoder model which outputs reconstruct ECG arrhythmias signals from high-level features through LSTM network. Experiments show that the proposed method can learn better features than the traditional method without any prior knowledge, presenting a good potential for the ECG arrhythmias classification. In the classification of five heartbeats types, including normal, left bundle branch block (LBBB), right bundle branch block (RBBB), atrial premature complexes (APC), premature ventricular contractions (PVC), the proposed method achieved average accuracy, sensitivity, and specificity of 99.74%, 99.35%, and 99.84%, respectively, in the beat-based cross-validation approach, and 85.20%, 62.99%, and 90.75%, respectively, in the record-based cross-validation approach, in public MIT-BIH Arrhythmia Database. While based on the Advancement of Medical Instrumentation (AAMI) standards, the proposed method achieved average accuracy, sensitivity, and specificity of 99.45%, 98.63%, and 99.66%, respectively, in the beat-based cross-validation approach.
We consider the problem of channel estimation for millimeter wave (mmWave) systems, where, to minimize the hardware complexity and power consumption, an analog transmit beamforming and receive ...combining structure with only one radio frequency chain at the base station and mobile station is employed. Most existing works for mmWave channel estimation exploit sparse scattering characteristics of the channel. In addition to sparsity, mmWave channels may exhibit angular spreads over the angle of arrival, angle of departure, and elevation domains. In this paper, we show that angular spreads give rise to a useful low-rank structure that, along with the sparsity, can be simultaneously utilized to reduce the sample complexity, i.e., the number of samples needed to successfully recover the mmWave channel. Specifically, to effectively leverage the joint sparse and low-rank structure, we develop a two-stage compressed sensing method for mmWave channel estimation, where the sparse and low-rank properties are respectively utilized in two consecutive stages, namely, a matrix completion stage and a sparse recovery stage. Our theoretical analysis reveals that the proposed two-stage scheme can achieve a lower sample complexity than a conventional compressed sensing method that exploits only the sparse structure of the mmWave channel. Simulation results are provided to corroborate our theoretical results and to show the superiority of the proposed two-stage method.
We consider the problem of recovering block-sparse signals whose cluster patterns are unknown a priori. Block-sparse signals with nonzero coefficients occurring in clusters arise naturally in many ...practical scenarios. However, the knowledge of the block partition is usually unavailable in practice. In this paper, we develop a new sparse Bayesian learning method for recovery of block-sparse signals with unknown cluster patterns. A pattern-coupled hierarchical Gaussian prior is introduced to characterize the pattern dependencies among neighboring coefficients, where a set of hyperparameters are employed to control the sparsity of signal coefficients. The proposed hierarchical model is similar to that for the conventional sparse Bayesian learning. However, unlike the conventional sparse Bayesian learning framework in which each individual hyperparameter is associated independently with each coefficient, in this paper, the prior for each coefficient not only involves its own hyperparameter, but also its immediate neighbor hyperparameters. In doing this way, the sparsity patterns of neighboring coefficients are related to each other and the hierarchical model has the potential to encourage structured-sparse solutions. The hyperparameters are learned by maximizing their posterior probability. We exploit an expectation-maximization (EM) formulation to develop an iterative algorithm that treats the signal as hidden variables and iteratively maximizes a lower bound on the posterior probability. In the M-step, a simple suboptimal solution is employed to replace a gradient-based search to maximize the lower bound. Numerical results are provided to illustrate the effectiveness of the proposed algorithm.
A palladium‐catalyzed asymmetric intramolecular allylic C−H amination controlled by a chiral phosphoramidite ligand was established for the preparation of various substituted chiral ...hydropyrimidinones, the precursors of hydropyrimidines, in high yields with high enantioselectivities. In particular, dienyl sodium N‐sulfonyl amides bearing an arylethene‐1‐sulfonyl group underwent a sequential allylic C−H amination and intramolecular Diels–Alder (IMDA) reaction to produce chiral fused tricyclic tetrahydropyrimidinone frameworks in high yields and with high levels of stereoselectivity. Significantly, this method was used as the key step in an asymmetric synthesis of letermovir.
Getting to the core of it: An asymmetric palladium‐catalyzed intramolecular allylic C−H amination controlled by a chiral phosphoramidite ligand was used to provide efficient access various substituted chiral hydropyrimidines. This methodology was successfully applied to the asymmetric synthesis of letermovir (see scheme; IMDA=intramolecular Diels–Alder reaction).
Student leadership refers to a series of related abilities that students have or need to acquire in leadership roles or non-leadership roles, which includes both self-leadership and team leadership. ...In the present-day society, student leadership education is a subject of great significance, which is related to the personal development of students and the progress of society. This study discusses the connotation, influencing factors and cultivation strategies of student leadership from the perspective of student leadership education. Through the method of literature review, this paper synthesizes a variety of leadership theories, analyzes the main factors affecting the formation and development of student leadership, including school education, personality traits, family upbringing, and age, and so on, and proposes corresponding cultivation strategies, including classroom teaching, extracurricular activities, and social practice. This article argues that student leadership is a multidimensional composite ability, including self-knowledge, self-management, self-motivation, communication and collaboration, innovative problem-solving, service to others, and so on, which are interrelated and mutually reinforcing, constituting a complete ability system. This article has shown that through an in-depth discussion of student leadership, it can contribute to improving the quality of students, cultivating future social elites and promoting social progress.
Improving the separation of photogenerated carriers and suppressing the rapid complication of electron–hole pairs are essential ways to improve photocatalytic hydrogen production activity. The high ...recombination rate of the photogenerated carriers is an issue encountered when developing CdS as a promising photocatalytic material. This work allowed to accelerate the separation of photogenerated electrons and holes by loading monoclinic β-AgVO
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on hexagonal CdS nanorods to construct a one-dimensional (1D)/1D p-n heterojunction. The introduction of monoclinic β-AgVO
3
with a narrow band gap effectively improves the light absorption of CdS, which is conducive to improving the use of visible light. The integrated electric field of the p–n heterojunction can effectively transfer electrons and holes in the direction suitable to hydrogen evolution. The photoluminescence and electrochemical characterization of the catalysts showed that the p–n heterojunction formed after loading β-AgVO
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greatly improved the separation efficiency of photocarriers. The hydrogen evolution experiments show that the composite catalyst has good photocatalytic hydrogen evolution capability and stability. The composite catalyst with the best photocatalytic performance was obtained by studying β-AgVO
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with different loadings. The composite catalyst reached 581.5 μmol of hydrogen amount within 5 h, which is 3.8 times higher than that of CdS alone and its apparent quantum efficiency reaches 8.02%. The present work provides a possible solution for the development of perovskite and the extensiveness of CdS in photocatalytic hydrogen evolution.
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Lavender and its products have excellent flavor properties. However, most studies focus on the aroma profiles of lavender essential oil (LEO). The volatiles in lavender extracts (LEs), either in ...volatile compositions or their odor characteristics, have rarely been reported. In this study, the odor characteristics of LEs and LEO were comprehensively investigated by gas chromatography-mass spectrometry (GC-MS), coupled with sensory evaluation and principal chemical analysis (PCA). In addition, the extraction conditions of lavender extracts from inflorescences of
Mill. were optimized. Under the optimal conditions of extraction, twice with 95% edible ethanol as the solvent, the LEs tended to contain the higher intensity of characteristic floral, herbal and clove-like odors as well as higher scores of overall assessment and higher amounts of linalool, linalool oxides I and II, linalyl acetate, lavandulyl acetate and total volatiles than LEO. PCA analysis showed that there were significant differences on the odor characteristics between LEO and LEs. The LEO, which was produced by steam distillation with a yield of 2.21%, had the lower intensity of floral, clove-like, medicine-like, pine-like and hay notes, a lower score of overall assessment and lower levels of linalool oxides I and II, linalyl acetate, lavandulyl acetate and total volatiles compared with LEs, whereas the relative contents of linalool and camphor in LEO were significantly higher than that in LEs. Furthermore, the earthy, green and watery odors were only found in LEO. Concerning the odor characteristics and volatile compositions, the LEs had better odor properties than LEO. These results provided a theoretical basis for the industrial preparation of lavender-related products.
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